diff --git a/scikits/learn/datasets/README.txt b/scikits/learn/datasets/README.txt
deleted file mode 100644
index 4e8bdbafff4ecb6764fede8bbd41673b1a09c2de..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/README.txt
+++ /dev/null
@@ -1,28 +0,0 @@
-Last Change: Tue Jul 17 04:00 PM 2007 J
-
-This packages datasets defines a set of packages which contain datasets useful
-for demo, examples, etc... This can be seen as an equivalent of the R dataset
-package, but for python.
-
-Each subdir is a python package, and should define the function load, returning
-the corresponding data. For example, to access datasets data1, you should be able to do:
-
->> from datasets.data1 import load
->> d = load() # -> d contains the data of the datasets data1
-
-load can do whatever it wants: fetching data from a file (python script, csv
-file, etc...), from the internet, etc... Some special variables must be defined
-for each package, containing a python string:
-    - COPYRIGHT: copyright informations
-    - SOURCE: where the data are coming from
-    - DESCHOSRT: short description
-    - DESCLONG: long description
-    - NOTE: some notes on the datasets.
-
-For the datasets to be useful in the learn scikits, which is the project which initiated this datasets package, the data returned by load has to be a dict with the following conventions:
-    - 'data': this value should be a record array containing the actual data.
-    - 'label': this value should be a rank 1 array of integers, contains the
-      label index for each sample, that is label[i] should be the label index
-      of data[i].
-    - 'class': a record array such as class[i] is the class name. In other
-      words, this makes the correspondance label index <> label name.
diff --git a/scikits/learn/datasets/faithful/COPYING b/scikits/learn/datasets/faithful/COPYING
deleted file mode 100644
index 465e793f163956fa6218b782b8197e06677cdcdd..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/faithful/COPYING
+++ /dev/null
@@ -1,34 +0,0 @@
-# The code and descriptive text is copyrighted and offered under the terms of
-# the BSD License from the authors; see below. However, the actual dataset may
-# have a different origin and intellectual property status. See the SOURCE and
-# COPYRIGHT variables for this information.
-
-# Copyright (c) 2007 David Cournapeau <cournape@gmail.com>
-#
-# All rights reserved.
-#
-# Redistribution and use in source and binary forms, with or without
-# modification, are permitted provided that the following conditions are
-# met:
-#
-#     * Redistributions of source code must retain the above copyright
-#       notice, this list of conditions and the following disclaimer.
-#     * Redistributions in binary form must reproduce the above copyright
-#       notice, this list of conditions and the following disclaimer in
-#       the documentation and/or other materials provided with the
-#       distribution.
-#     * Neither the author nor the names of any contributors may be used
-#       to endorse or promote products derived from this software without
-#       specific prior written permission.
-#
-# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
-# TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
-# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
-# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
-# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
-# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
-# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
-# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
-# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
-# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
diff --git a/scikits/learn/datasets/faithful/README b/scikits/learn/datasets/faithful/README
deleted file mode 100644
index de148e6d6beb179a1409047ae3c00a44cf49859f..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/faithful/README
+++ /dev/null
@@ -1,6 +0,0 @@
-Each OldfaithfulC*.txt is one column of the datasets as presented in Azzalini
-and Bowman. The Oldfaithful.txt is simply a cat of all thos files: this is just
-to make checking easier. The data in the txt are *exactly* the same than the
-ones in Azzalini and Bowman: again, post processing them in python is easy
-(converting the time in seconds, etc...), and having exactly the data of the
-reference makes it easier to check.
diff --git a/scikits/learn/datasets/faithful/__init__.py b/scikits/learn/datasets/faithful/__init__.py
deleted file mode 100644
index 58177e96c0218c012b0a792406300fe1dcbc7a1a..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/faithful/__init__.py
+++ /dev/null
@@ -1,8 +0,0 @@
-#! /usr/bin/env python
-# Last Change: Fri Jun 08 12:00 PM 2007 J
-import data as _faith
-__doc__     = _faith.DESCRSHORT
-copyright   = _faith.COPYRIGHT
-source      = _faith.SOURCE
-
-load        = _faith.load
diff --git a/scikits/learn/datasets/faithful/data.py b/scikits/learn/datasets/faithful/data.py
deleted file mode 100644
index 4da277cf23362eb9c4947630e6b77f1aff96d8cf..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/faithful/data.py
+++ /dev/null
@@ -1,53 +0,0 @@
-# encoding: utf-8
-"""Old faithful dataset."""
-
-__docformat__ = 'restructuredtext'
-
-COPYRIGHT   = """See SOURCE. Pr Azzalini has explicitely given his consent for
-the use of those data in scipy."""
-TITLE       = "Old Faithful Geyser Data"
-SOURCE      = """AZZALINI A., BOWMAN A. W. (1990).  A look at some data on the
-Old Faithful Geyser.  Applied Statistics (Journal of the Royal Statistical
-Society series C), vol. 39, pp. 357-365. Data collected by the Yellowstone Park
-geologist, R. A. Hutchinson.
-
-References: 
-    - Härdle, W. (1991) Smoothing Techniques with Implementation in S.  New
-    York: Springer.
-    - Azzalini, A. and Bowman, A. W. (1990).  A look at some data on the Old
-Faithful geyser. Applied Statistics, 39, 357--365.
-
-Those data are exactly the ones from Azzalini and Bowman's article."""
-
-DESCRSHORT  = """Waiting time between eruptions and the duration of the
-eruption for the Old Faithful geyser in Yellowstone National Park, Wyoming,
-USA. Waiting times and duration time are in seconds"""
-
-DESCRLONG   = """According to Azzalini and Bowman's article, those data
-were recorded continuously from 1th August to 15th August 1985.
-
-Some of the durations times are labelled as L, M or S (Large, Small, Medium).
-According to Azzalini and Bowman's paper: 'because the unbroken sequence
-required measurements to be taken at night, some duration times are recorded as
-L (long), S (short) and M (medium). Other data sets do not contain a con-
-tinuous stream of data, making it difficult to deal with time series features'
-"""
-
-NOTE = """Eruptions time in minutes, waiting time to next eruption in
-minutes"""
-
-import numpy as np
-
-def load():
-    """load the actual data and returns them.
-    
-    :returns:
-        waiting: array
-             waiting time until next eruption, in minutes
-        duration: array
-             duration of eruption, in minutes
-    """
-    from faithful import waiting, duration
-    waiting = np.array(waiting, np.float)
-    duration = np.array(duration, np.float)
-    return waiting, duration
diff --git a/scikits/learn/datasets/faithful/faithful.py b/scikits/learn/datasets/faithful/faithful.py
deleted file mode 100644
index 317cb8cd288107e0d30abc50ff4b57131581946e..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/faithful/faithful.py
+++ /dev/null
@@ -1,42 +0,0 @@
-duration = [3.6, 1.8, 3.333, 2.283, 4.533, 2.883, 4.7,
-3.6, 1.95, 4.35, 1.833, 3.917, 4.2, 1.75, 4.7, 2.167, 1.75, 4.8, 1.6, 4.25,
-1.8, 1.75, 3.45, 3.067, 4.533, 3.6, 1.967, 4.083, 3.85, 4.433, 4.3, 4.467,
-3.367, 4.033, 3.833, 2.017, 1.867, 4.833, 1.833, 4.783, 4.35, 1.883, 4.567,
-1.75, 4.533, 3.317, 3.833, 2.1, 4.633, 2, 4.8, 4.716, 1.833, 4.833, 1.733,
-4.883, 3.717, 1.667, 4.567, 4.317, 2.233, 4.5, 1.75, 4.8, 1.817, 4.4, 4.167,
-4.7, 2.067, 4.7, 4.033, 1.967, 4.5, 4, 1.983, 5.067, 2.017, 4.567, 3.883,
-3.6, 4.133, 4.333, 4.1, 2.633, 4.067, 4.933, 3.95, 4.517, 2.167, 4, 2.2,
-4.333, 1.867, 4.817, 1.833, 4.3, 4.667, 3.75, 1.867, 4.9, 2.483, 4.367,
-2.1, 4.5, 4.05, 1.867, 4.7, 1.783, 4.85, 3.683, 4.733, 2.3, 4.9, 4.417,
-1.7, 4.633, 2.317, 4.6, 1.817, 4.417, 2.617, 4.067, 4.25, 1.967, 4.6, 3.767,
-1.917, 4.5, 2.267, 4.65, 1.867, 4.167, 2.8, 4.333, 1.833, 4.383, 1.883,
-4.933, 2.033, 3.733, 4.233, 2.233, 4.533, 4.817, 4.333, 1.983, 4.633, 2.017,
-5.1, 1.8, 5.033, 4, 2.4, 4.6, 3.567, 4, 4.5, 4.083, 1.8, 3.967, 2.2, 4.15,
-2, 3.833, 3.5, 4.583, 2.367, 5, 1.933, 4.617, 1.917, 2.083, 4.583, 3.333,
-4.167, 4.333, 4.5, 2.417, 4, 4.167, 1.883, 4.583, 4.25, 3.767, 2.033, 4.433,
-4.083, 1.833, 4.417, 2.183, 4.8, 1.833, 4.8, 4.1, 3.966, 4.233, 3.5, 4.366,
-2.25, 4.667, 2.1, 4.35, 4.133, 1.867, 4.6, 1.783, 4.367, 3.85, 1.933, 4.5,
-2.383, 4.7, 1.867, 3.833, 3.417, 4.233, 2.4, 4.8, 2, 4.15, 1.867, 4.267,
-1.75, 4.483, 4, 4.117, 4.083, 4.267, 3.917, 4.55, 4.083, 2.417, 4.183,
-2.217, 4.45, 1.883, 1.85, 4.283, 3.95, 2.333, 4.15, 2.35, 4.933, 2.9, 4.583,
-3.833, 2.083, 4.367, 2.133, 4.35, 2.2, 4.45, 3.567, 4.5, 4.15, 3.817, 3.917,
-4.45, 2, 4.283, 4.767, 4.533, 1.85, 4.25, 1.983, 2.25, 4.75, 4.117, 2.15,
-4.417, 1.817, 4.467]
-
-waiting = [79, 54, 74, 62, 85, 55, 88, 85, 51, 85,
-54, 84, 78, 47, 83, 52, 62, 84, 52, 79, 51, 47, 78, 69, 74, 83, 55, 76,
-78, 79, 73, 77, 66, 80, 74, 52, 48, 80, 59, 90, 80, 58, 84, 58, 73, 83,
-64, 53, 82, 59, 75, 90, 54, 80, 54, 83, 71, 64, 77, 81, 59, 84, 48, 82,
-60, 92, 78, 78, 65, 73, 82, 56, 79, 71, 62, 76, 60, 78, 76, 83, 75, 82,
-70, 65, 73, 88, 76, 80, 48, 86, 60, 90, 50, 78, 63, 72, 84, 75, 51, 82,
-62, 88, 49, 83, 81, 47, 84, 52, 86, 81, 75, 59, 89, 79, 59, 81, 50, 85,
-59, 87, 53, 69, 77, 56, 88, 81, 45, 82, 55, 90, 45, 83, 56, 89, 46, 82,
-51, 86, 53, 79, 81, 60, 82, 77, 76, 59, 80, 49, 96, 53, 77, 77, 65, 81,
-71, 70, 81, 93, 53, 89, 45, 86, 58, 78, 66, 76, 63, 88, 52, 93, 49, 57,
-77, 68, 81, 81, 73, 50, 85, 74, 55, 77, 83, 83, 51, 78, 84, 46, 83, 55,
-81, 57, 76, 84, 77, 81, 87, 77, 51, 78, 60, 82, 91, 53, 78, 46, 77, 84,
-49, 83, 71, 80, 49, 75, 64, 76, 53, 94, 55, 76, 50, 82, 54, 75, 78, 79,
-78, 78, 70, 79, 70, 54, 86, 50, 90, 54, 54, 77, 79, 64, 75, 47, 86, 63,
-85, 82, 57, 82, 67, 74, 54, 83, 73, 73, 88, 80, 71, 83, 56, 79, 78, 84,
-58, 83, 43, 60, 75, 81, 46, 90, 46, 74]
-
diff --git a/scikits/learn/datasets/german/__init__.py b/scikits/learn/datasets/german/__init__.py
deleted file mode 100644
index 9d8e1ff6afe947b3fd9bda94b2bab285a6dc2c3b..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/german/__init__.py
+++ /dev/null
@@ -1,10 +0,0 @@
-#! /usr/bin/env python
-# Last Change: Mon Jul 09 06:00 PM 2007 J
-import data as _german
-__doc__     = _german.DESCRSHORT
-copyright   = _german.COPYRIGHT
-source      = _german.SOURCE
-
-load        = _german.load
-
-all = ['load', 'copyright', 'source']
diff --git a/scikits/learn/datasets/german/data.py b/scikits/learn/datasets/german/data.py
deleted file mode 100644
index a697756e269078b9fb87f4e4973e23c3f2e85b52..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/german/data.py
+++ /dev/null
@@ -1,107 +0,0 @@
-#! /usr/bin/env python
-# -*- coding: utf-8 -*-
-# Last Change: Tue Jul 17 05:00 PM 2007 J
-
-# The code and descriptive text is copyrighted and offered under the terms of
-# the BSD License from the authors; see below. However, the actual dataset may
-# have a different origin and intellectual property status. See the SOURCE and
-# COPYRIGHT variables for this information.
-
-# Copyright (c) 2007 David Cournapeau <cournape@gmail.com>
-#
-# All rights reserved.
-#
-# Redistribution and use in source and binary forms, with or without
-# modification, are permitted provided that the following conditions are
-# met:
-#
-#     * Redistributions of source code must retain the above copyright
-#       notice, this list of conditions and the following disclaimer.
-#     * Redistributions in binary form must reproduce the above copyright
-#       notice, this list of conditions and the following disclaimer in
-#       the documentation and/or other materials provided with the
-#       distribution.
-#     * Neither the author nor the names of any contributors may be used
-#       to endorse or promote products derived from this software without
-#       specific prior written permission.
-#
-# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
-# TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
-# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
-# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
-# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
-# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
-# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
-# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
-# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
-# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
-"""Iris dataset."""
-
-__docformat__ = 'restructuredtext'
-
-COPYRIGHT   = """This is public domain. """
-TITLE       = "German Dataset"
-SOURCE      = """
-http://www.liacc.up.pt/ML/old/statlog/datasets.html
-
-Professor Dr. Hans Hofmann 
-Institut für Statistik und Ökonometrie Universität Hamburg 
-FB Wirtschaftswissenschaften 
-Von-Melle-Park 5 
-2000 Hamburg 13
-
-Two datasets are provided. the original dataset, in the form provided by Prof.
-Hofmann, contains categorical/symbolic attributes and is in the file
-"german.dat".  For algorithms that need numerical attributes, Strathclyde
-University produced the file "german.numer". This file has been edited and
-several indicator variables added to make it suitable for algorithms which
-cannot cope with categorical variables. Several attributes that are ordered
-categorical (such as attribute 17) have been coded as integer. This was the
-form used by StatLog. 
-
-Here (scikits), only the numeric datasets are provided.
-"""
-
-DESCRSHORT  = """"""
-
-DESCRLONG   = """"""
-
-NOTE        = """
-Number of Instances: 1000. 700 for class 0 (good credit) and 300 for class 1
-(bad credit).
-
-Number of Attributes: 24.
-
-label: 0 for good credit, +1 for bad credit
-"""
-
-def load():
-    """load the german data and returns them.
-    
-    :returns:
-        data: dict
-            Contains the following values:
-                'data' : the actual data
-                'label' : label[i] is the label index of data[i]
-                'class' : class[label[i]] is the label name of data[i]
-    """
-    import numpy
-    from german import feat, label
-    data = {}
-    # Create the data
-    descr = [('feat' + str(i), numpy.int) for i in range(1, 25)]
-    data['data'] = numpy.empty(len(feat['feat1']), dtype = descr)
-    for i in feat.keys():
-        data['data'][i] = numpy.array(numpy.round([float(j) for j in feat[i]]))
-    # Create the label
-    data['label'] = numpy.array([numpy.int(i) for i in label], numpy.int)
-    data['label'][data['label'] == -1] = 0
-    # Create the class
-    classes = ['good credit', 'bad credit']
-    data['class'] = numpy.empty(2, 'S%d' % numpy.max([len(i) for i in classes]))
-    data['class'][0] = 'good credit'
-    data['class'][1] = 'bad credit'
-    
-    return data
diff --git a/scikits/learn/datasets/german/german.py b/scikits/learn/datasets/german/german.py
deleted file mode 100644
index d41ed983d757e9f1e5018a9a9f56b8fde72f8ecc..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/german/german.py
+++ /dev/null
@@ -1,4086 +0,0 @@
-# Autogenerated by convert.py at Tue, 17 Jul 2007 08:52:29 +0000
-
-label = ['-1', '+1', '-1', '-1', '+1', '-1', '-1', '-1', '-1', '+1', '+1',
-'+1', '-1', '+1', '-1', '+1', '-1', '-1', '+1', '-1', '-1', '-1', '-1', '-1',
-'-1', '-1', '-1', '-1', '-1', '+1', '-1', '-1', '-1', '-1', '-1', '+1', '-1',
-'+1', '-1', '-1', '-1', '-1', '-1', '-1', '+1', '-1', '-1', '-1', '-1', '-1',
-'-1', '-1', '-1', '-1', '+1', '-1', '+1', '-1', '-1', '+1', '-1', '-1', '+1',
-'+1', '-1', '-1', '-1', '-1', '+1', '-1', '-1', '-1', '-1', '-1', '+1', '-1',
-'+1', '-1', '-1', '-1', '+1', '-1', '-1', '-1', '-1', '-1', '-1', '+1', '-1',
-'+1', '-1', '-1', '+1', '-1', '-1', '+1', '-1', '-1', '-1', '-1', '-1', '-1',
-'-1', '-1', '-1', '+1', '+1', '-1', '-1', '-1', '-1', '-1', '-1', '+1', '-1',
-'-1', '+1', '-1', '+1', '-1', '+1', '-1', '-1', '-1', '+1', '-1', '-1', '+1',
-'-1', '+1', '-1', '+1', '-1', '-1', '-1', '-1', '-1', '+1', '-1', '-1', '-1',
-'-1', '-1', '+1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1',
-'-1', '+1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '+1',
-'-1', '-1', '+1', '+1', '-1', '+1', '-1', '+1', '+1', '-1', '-1', '-1', '-1',
-'+1', '+1', '+1', '-1', '+1', '-1', '+1', '-1', '+1', '-1', '+1', '+1', '+1',
-'-1', '+1', '+1', '-1', '+1', '-1', '+1', '-1', '-1', '-1', '+1', '-1', '-1',
-'-1', '-1', '-1', '-1', '-1', '-1', '+1', '+1', '-1', '-1', '-1', '-1', '-1',
-'-1', '-1', '-1', '-1', '-1', '-1', '-1', '+1', '+1', '+1', '-1', '+1', '-1',
-'-1', '-1', '-1', '+1', '+1', '+1', '-1', '-1', '+1', '-1', '+1', '-1', '-1',
-'-1', '-1', '-1', '-1', '+1', '-1', '-1', '+1', '-1', '-1', '-1', '-1', '+1',
-'-1', '-1', '-1', '-1', '-1', '-1', '-1', '+1', '-1', '-1', '+1', '-1', '-1',
-'-1', '-1', '+1', '+1', '-1', '-1', '-1', '+1', '-1', '-1', '-1', '-1', '-1',
-'-1', '-1', '-1', '-1', '-1', '+1', '-1', '+1', '-1', '-1', '-1', '+1', '-1',
-'-1', '-1', '-1', '-1', '+1', '+1', '-1', '+1', '-1', '-1', '+1', '+1', '-1',
-'-1', '-1', '-1', '+1', '-1', '+1', '-1', '-1', '-1', '-1', '+1', '+1', '-1',
-'-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '+1', '+1', '+1', '+1', '+1',
-'-1', '+1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1',
-'+1', '-1', '+1', '-1', '+1', '-1', '+1', '-1', '+1', '-1', '+1', '-1', '-1',
-'-1', '-1', '+1', '-1', '-1', '-1', '+1', '-1', '-1', '-1', '-1', '-1', '+1',
-'+1', '-1', '-1', '+1', '-1', '-1', '+1', '-1', '-1', '-1', '-1', '-1', '-1',
-'-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '+1', '-1', '-1',
-'-1', '+1', '-1', '-1', '+1', '-1', '-1', '-1', '+1', '-1', '-1', '+1', '-1',
-'+1', '-1', '+1', '-1', '-1', '+1', '-1', '-1', '-1', '-1', '+1', '-1', '-1',
-'-1', '-1', '+1', '-1', '+1', '-1', '-1', '-1', '+1', '-1', '-1', '-1', '+1',
-'-1', '-1', '-1', '+1', '+1', '-1', '+1', '-1', '-1', '+1', '-1', '-1', '-1',
-'-1', '+1', '-1', '-1', '+1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1',
-'+1', '-1', '-1', '-1', '+1', '+1', '+1', '-1', '+1', '+1', '-1', '-1', '-1',
-'-1', '-1', '-1', '-1', '-1', '-1', '+1', '-1', '-1', '-1', '-1', '-1', '+1',
-'-1', '-1', '-1', '+1', '+1', '-1', '-1', '-1', '+1', '-1', '-1', '+1', '+1',
-'+1', '-1', '+1', '-1', '-1', '+1', '-1', '-1', '-1', '-1', '-1', '-1', '+1',
-'-1', '-1', '-1', '+1', '+1', '-1', '-1', '-1', '-1', '-1', '+1', '-1', '-1',
-'+1', '-1', '-1', '-1', '+1', '-1', '-1', '+1', '-1', '+1', '-1', '+1', '+1',
-'-1', '+1', '-1', '-1', '+1', '-1', '-1', '-1', '+1', '-1', '-1', '+1', '+1',
-'+1', '+1', '+1', '-1', '+1', '-1', '+1', '-1', '-1', '+1', '-1', '-1', '+1',
-'+1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '+1', '-1', '+1', '-1', '-1',
-'+1', '-1', '+1', '-1', '-1', '+1', '+1', '-1', '-1', '-1', '+1', '+1', '+1',
-'+1', '+1', '+1', '-1', '-1', '+1', '+1', '+1', '-1', '-1', '-1', '+1', '-1',
-'-1', '+1', '+1', '-1', '-1', '+1', '-1', '-1', '-1', '+1', '-1', '-1', '+1',
-'+1', '-1', '+1', '-1', '-1', '+1', '-1', '-1', '-1', '+1', '-1', '+1', '+1',
-'-1', '-1', '-1', '-1', '+1', '+1', '-1', '+1', '-1', '-1', '+1', '-1', '+1',
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-
diff --git a/scikits/learn/datasets/german/src/convert.py b/scikits/learn/datasets/german/src/convert.py
deleted file mode 100755
index 5e230c9cb1548b5e1d447e336227a9795e64a37a..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/german/src/convert.py
+++ /dev/null
@@ -1,27 +0,0 @@
-#! /usr/bin/env python
-# Last Change: Tue Jul 17 05:00 PM 2007 J
-
-# This script generates a python file from the txt data
-import time
-import csv
-from scikits.learn.datasets.misc import dumpvar
-
-dataname = 'german.numer'
-f = open(dataname, 'r')
-a = csv.reader(f, delimiter = ' ')
-el = [i for i in a]
-# Remove last value corresponding to empty line in data file
-assert len(el) == 1000
-
-label = [i[0] for i in el]
-feat = {}
-for i in range(len(el[0][1:-1])):
-    feat['feat' + str(i+1)] = [j[i+1].split(':')[1] for j in el]
-
-a = open("../german.py", "w")
-a.write('# Autogenerated by convert.py at %s\n\n' % 
-        time.strftime("%a, %d %b %Y %H:%M:%S +0000", time.gmtime()))
-
-a.writelines(dumpvar(label, 'label'))
-a.writelines(dumpvar(feat, 'feat'))
-a.close()
diff --git a/scikits/learn/datasets/german/src/german.numer b/scikits/learn/datasets/german/src/german.numer
deleted file mode 100644
index 37a084a9aba183e300108355ceac4018aac517d4..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/german/src/german.numer
+++ /dev/null
@@ -1,1000 +0,0 @@
--1 1:1.000000 2:6.000000 3:4.000000 4:12.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:67.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
-+1 1:2.000000 2:48.000000 3:2.000000 4:60.000000 5:1.000000 6:3.000000 7:2.000000 8:2.000000 9:1.000000 10:22.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:4.000000 4:21.000000 5:1.000000 6:4.000000 7:3.000000 8:3.000000 9:1.000000 10:49.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:42.000000 3:2.000000 4:79.000000 5:1.000000 6:4.000000 7:3.000000 8:4.000000 9:2.000000 10:45.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
-+1 1:1.000000 2:24.000000 3:3.000000 4:49.000000 5:1.000000 6:3.000000 7:3.000000 8:4.000000 9:4.000000 10:53.000000 11:3.000000 12:2.000000 13:2.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:36.000000 3:2.000000 4:91.000000 5:5.000000 6:3.000000 7:3.000000 8:4.000000 9:4.000000 10:35.000000 11:3.000000 12:1.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:24.000000 3:2.000000 4:28.000000 5:3.000000 6:5.000000 7:3.000000 8:4.000000 9:2.000000 10:53.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:36.000000 3:2.000000 4:69.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:3.000000 10:35.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:12.000000 3:2.000000 4:31.000000 5:4.000000 6:4.000000 7:1.000000 8:4.000000 9:1.000000 10:61.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
-+1 1:2.000000 2:30.000000 3:4.000000 4:52.000000 5:1.000000 6:1.000000 7:4.000000 8:2.000000 9:3.000000 10:28.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
-+1 1:2.000000 2:12.000000 3:2.000000 4:13.000000 5:1.000000 6:2.000000 7:2.000000 8:1.000000 9:3.000000 10:25.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
-+1 1:1.000000 2:48.000000 3:2.000000 4:43.000000 5:1.000000 6:2.000000 7:2.000000 8:4.000000 9:2.000000 10:24.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:12.000000 3:2.000000 4:16.000000 5:1.000000 6:3.000000 7:2.000000 8:1.000000 9:3.000000 10:22.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
-+1 1:1.000000 2:24.000000 3:4.000000 4:12.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:60.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:15.000000 3:2.000000 4:14.000000 5:1.000000 6:3.000000 7:2.000000 8:4.000000 9:3.000000 10:28.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
-+1 1:1.000000 2:24.000000 3:2.000000 4:13.000000 5:2.000000 6:3.000000 7:2.000000 8:2.000000 9:3.000000 10:32.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:24.000000 3:4.000000 4:24.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:2.000000 10:53.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:30.000000 3:0.000000 4:81.000000 5:5.000000 6:2.000000 7:3.000000 8:3.000000 9:3.000000 10:25.000000 11:1.000000 12:3.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:24.000000 3:2.000000 4:34.000000 5:3.000000 6:5.000000 7:3.000000 8:2.000000 9:3.000000 10:31.000000 11:3.000000 12:1.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:9.000000 3:4.000000 4:21.000000 5:1.000000 6:3.000000 7:3.000000 8:4.000000 9:3.000000 10:48.000000 11:3.000000 12:3.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:6.000000 3:2.000000 4:26.000000 5:3.000000 6:3.000000 7:3.000000 8:3.000000 9:1.000000 10:44.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:10.000000 3:4.000000 4:22.000000 5:1.000000 6:2.000000 7:3.000000 8:3.000000 9:1.000000 10:48.000000 11:3.000000 12:2.000000 13:2.000000 14:1.000000 15:2.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:12.000000 3:4.000000 4:18.000000 5:2.000000 6:2.000000 7:3.000000 8:4.000000 9:2.000000 10:44.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:10.000000 3:4.000000 4:21.000000 5:5.000000 6:3.000000 7:4.000000 8:1.000000 9:3.000000 10:26.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:2.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:6.000000 3:2.000000 4:14.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:36.000000 11:1.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:6.000000 3:0.000000 4:4.000000 5:1.000000 6:5.000000 7:4.000000 8:4.000000 9:3.000000 10:39.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:3.000000 2:12.000000 3:1.000000 4:4.000000 5:4.000000 6:3.000000 7:2.000000 8:3.000000 9:1.000000 10:42.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:7.000000 3:2.000000 4:24.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:34.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
-+1 1:1.000000 2:60.000000 3:3.000000 4:68.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:4.000000 10:63.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:18.000000 3:2.000000 4:19.000000 5:4.000000 6:2.000000 7:4.000000 8:3.000000 9:1.000000 10:36.000000 11:1.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:24.000000 3:2.000000 4:40.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:3.000000 10:27.000000 11:2.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:18.000000 3:2.000000 4:59.000000 5:2.000000 6:3.000000 7:3.000000 8:2.000000 9:3.000000 10:30.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:4.000000 4:13.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:4.000000 10:57.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:3.000000 2:12.000000 3:2.000000 4:15.000000 5:1.000000 6:2.000000 7:2.000000 8:1.000000 9:2.000000 10:33.000000 11:1.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
-+1 1:2.000000 2:45.000000 3:4.000000 4:47.000000 5:1.000000 6:2.000000 7:3.000000 8:2.000000 9:2.000000 10:25.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:48.000000 3:4.000000 4:61.000000 5:1.000000 6:3.000000 7:3.000000 8:3.000000 9:4.000000 10:31.000000 11:1.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:3.000000 2:10.000000 3:2.000000 4:12.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:3.000000 10:37.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:9.000000 3:2.000000 4:5.000000 5:1.000000 6:3.000000 7:3.000000 8:3.000000 9:1.000000 10:24.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:30.000000 3:2.000000 4:23.000000 5:3.000000 6:5.000000 7:3.000000 8:2.000000 9:3.000000 10:30.000000 11:1.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:2.000000 2:12.000000 3:2.000000 4:12.000000 5:3.000000 6:3.000000 7:1.000000 8:1.000000 9:3.000000 10:26.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:18.000000 3:3.000000 4:62.000000 5:1.000000 6:3.000000 7:3.000000 8:4.000000 9:1.000000 10:44.000000 11:3.000000 12:1.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:30.000000 3:4.000000 4:62.000000 5:2.000000 6:4.000000 7:4.000000 8:4.000000 9:3.000000 10:24.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
-+1 1:1.000000 2:48.000000 3:4.000000 4:61.000000 5:1.000000 6:5.000000 7:2.000000 8:4.000000 9:4.000000 10:58.000000 11:2.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:11.000000 3:4.000000 4:14.000000 5:1.000000 6:2.000000 7:2.000000 8:4.000000 9:3.000000 10:35.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:36.000000 3:2.000000 4:23.000000 5:3.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:39.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:6.000000 3:2.000000 4:14.000000 5:3.000000 6:1.000000 7:2.000000 8:2.000000 9:2.000000 10:23.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:1.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:11.000000 3:4.000000 4:72.000000 5:1.000000 6:3.000000 7:3.000000 8:4.000000 9:2.000000 10:39.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:12.000000 3:2.000000 4:21.000000 5:2.000000 6:3.000000 7:2.000000 8:2.000000 9:1.000000 10:28.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:1.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:24.000000 3:3.000000 4:23.000000 5:5.000000 6:2.000000 7:3.000000 8:2.000000 9:2.000000 10:29.000000 11:1.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:27.000000 3:3.000000 4:60.000000 5:1.000000 6:5.000000 7:3.000000 8:2.000000 9:3.000000 10:30.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:12.000000 3:2.000000 4:13.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:3.000000 10:25.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:18.000000 3:2.000000 4:34.000000 5:5.000000 6:3.000000 7:3.000000 8:1.000000 9:2.000000 10:31.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:6.000000 3:1.000000 4:8.000000 5:5.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:26.000000 11:2.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:36.000000 3:4.000000 4:96.000000 5:1.000000 6:3.000000 7:2.000000 8:2.000000 9:3.000000 10:31.000000 11:2.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:3.000000 2:18.000000 3:2.000000 4:20.000000 5:1.000000 6:5.000000 7:2.000000 8:2.000000 9:3.000000 10:23.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:2.000000 2:9.000000 3:2.000000 4:14.000000 5:1.000000 6:3.000000 7:4.000000 8:1.000000 9:1.000000 10:27.000000 11:1.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:15.000000 3:4.000000 4:15.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:50.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:24.000000 3:2.000000 4:32.000000 5:1.000000 6:2.000000 7:2.000000 8:4.000000 9:2.000000 10:26.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:27.000000 3:2.000000 4:52.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:2.000000 10:48.000000 11:3.000000 12:4.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:2.000000 4:22.000000 5:1.000000 6:2.000000 7:2.000000 8:2.000000 9:3.000000 10:29.000000 11:1.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:12.000000 3:2.000000 4:10.000000 5:4.000000 6:3.000000 7:4.000000 8:1.000000 9:1.000000 10:22.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:36.000000 3:2.000000 4:24.000000 5:5.000000 6:3.000000 7:2.000000 8:4.000000 9:3.000000 10:25.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:36.000000 3:2.000000 4:81.000000 5:1.000000 6:3.000000 7:2.000000 8:2.000000 9:2.000000 10:30.000000 11:1.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:7.000000 3:4.000000 4:7.000000 5:5.000000 6:5.000000 7:3.000000 8:2.000000 9:2.000000 10:46.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:8.000000 3:4.000000 4:12.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:4.000000 10:51.000000 11:1.000000 12:2.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:2.000000 2:42.000000 3:4.000000 4:60.000000 5:1.000000 6:4.000000 7:2.000000 8:1.000000 9:1.000000 10:41.000000 11:1.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:1.000000 2:12.000000 3:4.000000 4:15.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:4.000000 10:66.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:2.000000 2:11.000000 3:3.000000 4:48.000000 5:1.000000 6:4.000000 7:3.000000 8:4.000000 9:2.000000 10:51.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:54.000000 3:0.000000 4:94.000000 5:5.000000 6:3.000000 7:3.000000 8:2.000000 9:2.000000 10:39.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:30.000000 3:2.000000 4:38.000000 5:1.000000 6:2.000000 7:4.000000 8:1.000000 9:2.000000 10:22.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:15.000000 3:2.000000 4:12.000000 5:3.000000 6:5.000000 7:3.000000 8:3.000000 9:2.000000 10:47.000000 11:2.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:18.000000 3:2.000000 4:16.000000 5:2.000000 6:3.000000 7:2.000000 8:4.000000 9:2.000000 10:24.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:24.000000 3:2.000000 4:18.000000 5:1.000000 6:5.000000 7:2.000000 8:4.000000 9:1.000000 10:58.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:10.000000 3:2.000000 4:23.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:52.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:12.000000 3:4.000000 4:14.000000 5:1.000000 6:3.000000 7:2.000000 8:2.000000 9:1.000000 10:29.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:2.000000 2:18.000000 3:4.000000 4:13.000000 5:1.000000 6:2.000000 7:2.000000 8:1.000000 9:2.000000 10:27.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:1.000000 2:18.000000 3:2.000000 4:22.000000 5:2.000000 6:4.000000 7:3.000000 8:3.000000 9:3.000000 10:30.000000 11:3.000000 12:1.000000 13:2.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:4.000000 2:12.000000 3:4.000000 4:6.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:56.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:12.000000 3:4.000000 4:14.000000 5:1.000000 6:5.000000 7:3.000000 8:3.000000 9:1.000000 10:54.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:3.000000 2:24.000000 3:4.000000 4:36.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:4.000000 10:20.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:1.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:12.000000 3:2.000000 4:13.000000 5:4.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:54.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:12.000000 3:4.000000 4:20.000000 5:5.000000 6:4.000000 7:2.000000 8:2.000000 9:3.000000 10:61.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:18.000000 3:2.000000 4:26.000000 5:2.000000 6:3.000000 7:3.000000 8:4.000000 9:3.000000 10:34.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:36.000000 3:4.000000 4:23.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:36.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:20.000000 3:3.000000 4:71.000000 5:5.000000 6:4.000000 7:3.000000 8:4.000000 9:2.000000 10:36.000000 11:1.000000 12:2.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:24.000000 3:2.000000 4:15.000000 5:2.000000 6:5.000000 7:4.000000 8:4.000000 9:1.000000 10:41.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:36.000000 3:2.000000 4:23.000000 5:1.000000 6:4.000000 7:3.000000 8:4.000000 9:3.000000 10:24.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:6.000000 3:3.000000 4:9.000000 5:1.000000 6:3.000000 7:2.000000 8:2.000000 9:1.000000 10:24.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:9.000000 3:4.000000 4:19.000000 5:1.000000 6:4.000000 7:3.000000 8:3.000000 9:3.000000 10:35.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:2.000000 4:24.000000 5:5.000000 6:2.000000 7:4.000000 8:4.000000 9:3.000000 10:26.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:2.000000 2:12.000000 3:2.000000 4:61.000000 5:1.000000 6:4.000000 7:3.000000 8:2.000000 9:3.000000 10:32.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:24.000000 3:2.000000 4:77.000000 5:5.000000 6:2.000000 7:2.000000 8:2.000000 9:2.000000 10:30.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:2.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:14.000000 3:2.000000 4:14.000000 5:3.000000 6:5.000000 7:4.000000 8:2.000000 9:1.000000 10:35.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:6.000000 3:3.000000 4:14.000000 5:2.000000 6:5.000000 7:1.000000 8:2.000000 9:3.000000 10:31.000000 11:1.000000 12:2.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:3.000000 2:15.000000 3:2.000000 4:4.000000 5:1.000000 6:2.000000 7:2.000000 8:4.000000 9:2.000000 10:23.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:18.000000 3:2.000000 4:63.000000 5:1.000000 6:4.000000 7:3.000000 8:3.000000 9:1.000000 10:28.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:1.000000 2:12.000000 3:2.000000 4:17.000000 5:3.000000 6:5.000000 7:4.000000 8:1.000000 9:1.000000 10:35.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:48.000000 3:4.000000 4:36.000000 5:5.000000 6:5.000000 7:3.000000 8:1.000000 9:1.000000 10:47.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:1.000000 2:10.000000 3:4.000000 4:21.000000 5:5.000000 6:2.000000 7:2.000000 8:3.000000 9:1.000000 10:27.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:2.000000 16:0.000000 17:0.000000 18:0.000000 19:1.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:2.000000 2:12.000000 3:4.000000 4:24.000000 5:3.000000 6:4.000000 7:1.000000 8:3.000000 9:3.000000 10:36.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:4.000000 2:24.000000 3:4.000000 4:39.000000 5:1.000000 6:5.000000 7:2.000000 8:2.000000 9:3.000000 10:41.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:12.000000 3:2.000000 4:18.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:24.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:3.000000 2:10.000000 3:4.000000 4:8.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:4.000000 10:63.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:1.000000 2:12.000000 3:4.000000 4:21.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:2.000000 10:30.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:12.000000 3:2.000000 4:7.000000 5:1.000000 6:3.000000 7:4.000000 8:2.000000 9:1.000000 10:40.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:2.000000 2:12.000000 3:4.000000 4:19.000000 5:1.000000 6:1.000000 7:3.000000 8:2.000000 9:3.000000 10:34.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:2.000000 2:48.000000 3:2.000000 4:85.000000 5:5.000000 6:4.000000 7:2.000000 8:2.000000 9:3.000000 10:24.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:15.000000 3:2.000000 4:27.000000 5:1.000000 6:2.000000 7:3.000000 8:3.000000 9:2.000000 10:27.000000 11:1.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:18.000000 3:2.000000 4:20.000000 5:1.000000 6:3.000000 7:3.000000 8:4.000000 9:4.000000 10:47.000000 11:1.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:60.000000 3:2.000000 4:101.000000 5:2.000000 6:4.000000 7:2.000000 8:4.000000 9:1.000000 10:21.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:4.000000 4:12.000000 5:5.000000 6:5.000000 7:2.000000 8:2.000000 9:1.000000 10:38.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:27.000000 3:3.000000 4:86.000000 5:4.000000 6:3.000000 7:3.000000 8:2.000000 9:3.000000 10:27.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:2.000000 2:15.000000 3:4.000000 4:27.000000 5:5.000000 6:4.000000 7:3.000000 8:2.000000 9:1.000000 10:35.000000 11:1.000000 12:3.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:3.000000 2:12.000000 3:2.000000 4:19.000000 5:1.000000 6:3.000000 7:2.000000 8:2.000000 9:3.000000 10:44.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:3.000000 2:6.000000 3:2.000000 4:7.000000 5:4.000000 6:2.000000 7:4.000000 8:2.000000 9:1.000000 10:27.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:2.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:1.000000 23:0.000000 24:0.000000 
--1 1:2.000000 2:36.000000 3:2.000000 4:48.000000 5:1.000000 6:2.000000 7:2.000000 8:1.000000 9:4.000000 10:30.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:1.000000 2:27.000000 3:2.000000 4:34.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:3.000000 10:27.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:4.000000 2:21.000000 3:4.000000 4:23.000000 5:1.000000 6:2.000000 7:2.000000 8:4.000000 9:2.000000 10:23.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:48.000000 3:1.000000 4:36.000000 5:2.000000 6:4.000000 7:3.000000 8:2.000000 9:3.000000 10:30.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:6.000000 3:4.000000 4:9.000000 5:1.000000 6:5.000000 7:2.000000 8:4.000000 9:4.000000 10:39.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:4.000000 4:7.000000 5:2.000000 6:4.000000 7:2.000000 8:3.000000 9:3.000000 10:51.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:36.000000 3:4.000000 4:54.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:2.000000 10:28.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:18.000000 3:4.000000 4:16.000000 5:4.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:46.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:6.000000 3:2.000000 4:13.000000 5:2.000000 6:5.000000 7:3.000000 8:4.000000 9:4.000000 10:42.000000 11:1.000000 12:1.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:10.000000 3:2.000000 4:19.000000 5:1.000000 6:3.000000 7:3.000000 8:4.000000 9:2.000000 10:38.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:2.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:3.000000 2:36.000000 3:2.000000 4:58.000000 5:1.000000 6:3.000000 7:3.000000 8:1.000000 9:3.000000 10:24.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:24.000000 3:4.000000 4:78.000000 5:4.000000 6:5.000000 7:2.000000 8:4.000000 9:4.000000 10:29.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:24.000000 3:3.000000 4:70.000000 5:2.000000 6:4.000000 7:3.000000 8:4.000000 9:3.000000 10:36.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:1.000000 2:9.000000 3:4.000000 4:13.000000 5:2.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:48.000000 11:3.000000 12:2.000000 13:2.000000 14:1.000000 15:2.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:12.000000 3:1.000000 4:3.000000 5:1.000000 6:5.000000 7:4.000000 8:1.000000 9:3.000000 10:45.000000 11:1.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:24.000000 3:2.000000 4:35.000000 5:2.000000 6:4.000000 7:3.000000 8:3.000000 9:3.000000 10:38.000000 11:1.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:6.000000 3:4.000000 4:19.000000 5:5.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:34.000000 11:3.000000 12:2.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:24.000000 3:4.000000 4:29.000000 5:2.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:36.000000 11:3.000000 12:1.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:18.000000 3:4.000000 4:11.000000 5:1.000000 6:2.000000 7:2.000000 8:1.000000 9:2.000000 10:30.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:15.000000 3:2.000000 4:13.000000 5:3.000000 6:4.000000 7:3.000000 8:3.000000 9:2.000000 10:36.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:10.000000 3:2.000000 4:73.000000 5:1.000000 6:1.000000 7:3.000000 8:4.000000 9:4.000000 10:70.000000 11:1.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:36.000000 3:2.000000 4:9.000000 5:3.000000 6:5.000000 7:3.000000 8:4.000000 9:2.000000 10:36.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:6.000000 3:2.000000 4:30.000000 5:3.000000 6:3.000000 7:3.000000 8:2.000000 9:3.000000 10:32.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:2.000000 2:11.000000 3:2.000000 4:16.000000 5:4.000000 6:2.000000 7:2.000000 8:1.000000 9:1.000000 10:20.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:2.000000 4:40.000000 5:1.000000 6:4.000000 7:2.000000 8:4.000000 9:2.000000 10:25.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:12.000000 3:2.000000 4:8.000000 5:1.000000 6:3.000000 7:2.000000 8:1.000000 9:1.000000 10:26.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:2.000000 2:8.000000 3:2.000000 4:14.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:33.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:2.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:1.000000 2:12.000000 3:2.000000 4:26.000000 5:1.000000 6:3.000000 7:1.000000 8:1.000000 9:3.000000 10:42.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:6.000000 3:4.000000 4:3.000000 5:3.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:52.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:2.000000 4:20.000000 5:1.000000 6:4.000000 7:3.000000 8:2.000000 9:3.000000 10:31.000000 11:3.000000 12:2.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:1.000000 2:21.000000 3:4.000000 4:6.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:65.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:24.000000 3:4.000000 4:38.000000 5:4.000000 6:3.000000 7:3.000000 8:4.000000 9:1.000000 10:50.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:15.000000 3:4.000000 4:14.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:2.000000 10:31.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:2.000000 2:16.000000 3:4.000000 4:12.000000 5:1.000000 6:1.000000 7:3.000000 8:3.000000 9:3.000000 10:68.000000 11:3.000000 12:3.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:1.000000 23:0.000000 24:0.000000 
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--1 1:2.000000 2:18.000000 3:0.000000 4:32.000000 5:1.000000 6:3.000000 7:2.000000 8:4.000000 9:3.000000 10:33.000000 11:1.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:2.000000 2:24.000000 3:2.000000 4:28.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:4.000000 10:36.000000 11:1.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:9.000000 3:4.000000 4:9.000000 5:3.000000 6:5.000000 7:3.000000 8:2.000000 9:3.000000 10:52.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:12.000000 3:2.000000 4:12.000000 5:1.000000 6:3.000000 7:4.000000 8:3.000000 9:1.000000 10:27.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:27.000000 3:3.000000 4:51.000000 5:1.000000 6:4.000000 7:3.000000 8:4.000000 9:3.000000 10:26.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:12.000000 3:4.000000 4:15.000000 5:1.000000 6:5.000000 7:3.000000 8:1.000000 9:1.000000 10:38.000000 11:3.000000 12:2.000000 13:2.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:30.000000 3:4.000000 4:106.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:4.000000 10:38.000000 11:3.000000 12:3.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:12.000000 3:4.000000 4:19.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:43.000000 11:3.000000 12:3.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:12.000000 3:4.000000 4:14.000000 5:1.000000 6:4.000000 7:3.000000 8:3.000000 9:2.000000 10:26.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:24.000000 3:2.000000 4:66.000000 5:1.000000 6:3.000000 7:4.000000 8:2.000000 9:3.000000 10:21.000000 11:2.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:12.000000 3:2.000000 4:14.000000 5:4.000000 6:4.000000 7:3.000000 8:2.000000 9:2.000000 10:55.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:2.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:9.000000 3:4.000000 4:31.000000 5:5.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:33.000000 11:3.000000 12:2.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:36.000000 3:2.000000 4:38.000000 5:5.000000 6:5.000000 7:2.000000 8:4.000000 9:1.000000 10:45.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:36.000000 3:4.000000 4:33.000000 5:5.000000 6:5.000000 7:3.000000 8:2.000000 9:3.000000 10:51.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:6.000000 3:4.000000 4:9.000000 5:5.000000 6:4.000000 7:2.000000 8:3.000000 9:2.000000 10:39.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:18.000000 3:0.000000 4:31.000000 5:1.000000 6:4.000000 7:3.000000 8:1.000000 9:2.000000 10:31.000000 11:1.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:3.000000 2:36.000000 3:2.000000 4:39.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:23.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:24.000000 3:2.000000 4:30.000000 5:1.000000 6:3.000000 7:1.000000 8:2.000000 9:1.000000 10:24.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:10.000000 3:2.000000 4:14.000000 5:1.000000 6:3.000000 7:2.000000 8:4.000000 9:3.000000 10:64.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:12.000000 3:2.000000 4:6.000000 5:1.000000 6:2.000000 7:4.000000 8:1.000000 9:1.000000 10:26.000000 11:1.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:12.000000 3:2.000000 4:12.000000 5:5.000000 6:3.000000 7:2.000000 8:4.000000 9:2.000000 10:23.000000 11:1.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:2.000000 4:7.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:30.000000 11:1.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:3.000000 4:30.000000 5:5.000000 6:3.000000 7:3.000000 8:4.000000 9:1.000000 10:32.000000 11:3.000000 12:2.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:15.000000 3:2.000000 4:47.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:3.000000 10:30.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:36.000000 3:0.000000 4:26.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:3.000000 10:27.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:1.000000 2:24.000000 3:2.000000 4:31.000000 5:1.000000 6:2.000000 7:3.000000 8:1.000000 9:4.000000 10:22.000000 11:1.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:9.000000 3:2.000000 4:25.000000 5:3.000000 6:5.000000 7:3.000000 8:4.000000 9:4.000000 10:51.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:12.000000 3:2.000000 4:21.000000 5:2.000000 6:4.000000 7:3.000000 8:1.000000 9:4.000000 10:35.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:18.000000 3:2.000000 4:9.000000 5:1.000000 6:3.000000 7:4.000000 8:2.000000 9:1.000000 10:25.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:4.000000 3:4.000000 4:15.000000 5:1.000000 6:4.000000 7:3.000000 8:1.000000 9:1.000000 10:42.000000 11:3.000000 12:3.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:12.000000 3:4.000000 4:13.000000 5:1.000000 6:3.000000 7:2.000000 8:2.000000 9:2.000000 10:35.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:30.000000 3:2.000000 4:25.000000 5:1.000000 6:5.000000 7:3.000000 8:3.000000 9:2.000000 10:39.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:6.000000 3:2.000000 4:16.000000 5:1.000000 6:4.000000 7:3.000000 8:2.000000 9:2.000000 10:51.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:12.000000 3:4.000000 4:12.000000 5:1.000000 6:3.000000 7:2.000000 8:2.000000 9:1.000000 10:27.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:1.000000 4:34.000000 5:3.000000 6:3.000000 7:2.000000 8:3.000000 9:1.000000 10:35.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:24.000000 3:2.000000 4:13.000000 5:1.000000 6:4.000000 7:3.000000 8:1.000000 9:1.000000 10:25.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:4.000000 4:7.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:52.000000 11:3.000000 12:3.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:6.000000 3:0.000000 4:12.000000 5:2.000000 6:3.000000 7:3.000000 8:1.000000 9:4.000000 10:35.000000 11:1.000000 12:1.000000 13:1.000000 14:1.000000 15:2.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:3.000000 2:24.000000 3:2.000000 4:19.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:26.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:1.000000 2:6.000000 3:4.000000 4:7.000000 5:4.000000 6:4.000000 7:2.000000 8:4.000000 9:1.000000 10:39.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:3.000000 2:12.000000 3:2.000000 4:23.000000 5:1.000000 6:3.000000 7:2.000000 8:2.000000 9:3.000000 10:46.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:24.000000 3:3.000000 4:42.000000 5:2.000000 6:3.000000 7:3.000000 8:3.000000 9:2.000000 10:35.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:9.000000 3:2.000000 4:20.000000 5:5.000000 6:4.000000 7:3.000000 8:1.000000 9:3.000000 10:24.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:60.000000 3:3.000000 4:74.000000 5:5.000000 6:3.000000 7:3.000000 8:1.000000 9:1.000000 10:27.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:24.000000 3:4.000000 4:27.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:35.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:15.000000 3:2.000000 4:38.000000 5:2.000000 6:2.000000 7:2.000000 8:4.000000 9:3.000000 10:23.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:11.000000 3:4.000000 4:12.000000 5:2.000000 6:1.000000 7:2.000000 8:4.000000 9:1.000000 10:57.000000 11:3.000000 12:3.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:12.000000 3:2.000000 4:17.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:27.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:24.000000 3:2.000000 4:16.000000 5:1.000000 6:5.000000 7:2.000000 8:4.000000 9:3.000000 10:55.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:18.000000 3:4.000000 4:53.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:4.000000 10:36.000000 11:3.000000 12:3.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:12.000000 3:4.000000 4:27.000000 5:1.000000 6:5.000000 7:2.000000 8:4.000000 9:4.000000 10:57.000000 11:1.000000 12:3.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:10.000000 3:4.000000 4:12.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:32.000000 11:3.000000 12:2.000000 13:2.000000 14:1.000000 15:2.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:36.000000 3:4.000000 4:63.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:36.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:2.000000 4:15.000000 5:1.000000 6:2.000000 7:2.000000 8:3.000000 9:3.000000 10:38.000000 11:2.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:24.000000 3:2.000000 4:10.000000 5:5.000000 6:5.000000 7:3.000000 8:2.000000 9:3.000000 10:25.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:18.000000 3:2.000000 4:27.000000 5:5.000000 6:4.000000 7:3.000000 8:3.000000 9:2.000000 10:32.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:2.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:4.000000 4:14.000000 5:3.000000 6:4.000000 7:2.000000 8:4.000000 9:3.000000 10:37.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:48.000000 3:1.000000 4:122.000000 5:5.000000 6:1.000000 7:3.000000 8:4.000000 9:4.000000 10:36.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:0.000000 19:1.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:4.000000 2:9.000000 3:2.000000 4:27.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:32.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:18.000000 3:4.000000 4:24.000000 5:1.000000 6:3.000000 7:2.000000 8:2.000000 9:3.000000 10:26.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:12.000000 3:2.000000 4:13.000000 5:5.000000 6:5.000000 7:1.000000 8:4.000000 9:2.000000 10:49.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:24.000000 3:2.000000 4:19.000000 5:2.000000 6:3.000000 7:3.000000 8:4.000000 9:3.000000 10:29.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:15.000000 3:4.000000 4:34.000000 5:4.000000 6:5.000000 7:3.000000 8:4.000000 9:4.000000 10:23.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:2.000000 4:16.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:50.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:3.000000 2:18.000000 3:1.000000 4:14.000000 5:5.000000 6:4.000000 7:3.000000 8:4.000000 9:3.000000 10:49.000000 11:1.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:15.000000 3:4.000000 4:15.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:2.000000 10:63.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:24.000000 3:4.000000 4:39.000000 5:2.000000 6:2.000000 7:1.000000 8:2.000000 9:3.000000 10:37.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:47.000000 3:2.000000 4:107.000000 5:1.000000 6:2.000000 7:2.000000 8:1.000000 9:1.000000 10:35.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:48.000000 3:2.000000 4:48.000000 5:1.000000 6:4.000000 7:3.000000 8:3.000000 9:2.000000 10:26.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:48.000000 3:3.000000 4:76.000000 5:2.000000 6:1.000000 7:3.000000 8:4.000000 9:4.000000 10:31.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:2.000000 2:12.000000 3:2.000000 4:11.000000 5:1.000000 6:3.000000 7:2.000000 8:4.000000 9:1.000000 10:49.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:12.000000 3:2.000000 4:11.000000 5:1.000000 6:3.000000 7:4.000000 8:2.000000 9:1.000000 10:26.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:2.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:1.000000 2:24.000000 3:4.000000 4:64.000000 5:1.000000 6:5.000000 7:2.000000 8:4.000000 9:4.000000 10:44.000000 11:3.000000 12:2.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:3.000000 2:42.000000 3:4.000000 4:48.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:4.000000 10:56.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:48.000000 3:4.000000 4:76.000000 5:5.000000 6:5.000000 7:1.000000 8:2.000000 9:3.000000 10:46.000000 11:1.000000 12:2.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:4.000000 2:12.000000 3:2.000000 4:47.000000 5:5.000000 6:2.000000 7:2.000000 8:4.000000 9:3.000000 10:20.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:10.000000 3:2.000000 4:13.000000 5:5.000000 6:5.000000 7:3.000000 8:2.000000 9:2.000000 10:45.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:2.000000 16:1.000000 17:0.000000 18:0.000000 19:1.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:18.000000 3:2.000000 4:25.000000 5:1.000000 6:3.000000 7:3.000000 8:4.000000 9:1.000000 10:43.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:21.000000 3:4.000000 4:27.000000 5:4.000000 6:4.000000 7:3.000000 8:2.000000 9:3.000000 10:32.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:6.000000 3:2.000000 4:7.000000 5:1.000000 6:1.000000 7:2.000000 8:4.000000 9:1.000000 10:54.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:1.000000 23:0.000000 24:0.000000 
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--1 1:1.000000 2:10.000000 3:4.000000 4:10.000000 5:1.000000 6:4.000000 7:3.000000 8:3.000000 9:2.000000 10:49.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:0.000000 19:1.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:6.000000 3:2.000000 4:15.000000 5:4.000000 6:3.000000 7:1.000000 8:2.000000 9:1.000000 10:33.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:30.000000 3:2.000000 4:48.000000 5:5.000000 6:4.000000 7:2.000000 8:4.000000 9:2.000000 10:24.000000 11:2.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:2.000000 2:9.000000 3:2.000000 4:3.000000 5:1.000000 6:3.000000 7:4.000000 8:4.000000 9:1.000000 10:22.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:48.000000 3:2.000000 4:54.000000 5:5.000000 6:1.000000 7:3.000000 8:4.000000 9:4.000000 10:40.000000 11:1.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:1.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:24.000000 3:2.000000 4:55.000000 5:2.000000 6:3.000000 7:3.000000 8:1.000000 9:3.000000 10:25.000000 11:2.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:3.000000 2:24.000000 3:2.000000 4:37.000000 5:1.000000 6:2.000000 7:2.000000 8:4.000000 9:3.000000 10:26.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:3.000000 2:4.000000 3:2.000000 4:15.000000 5:5.000000 6:2.000000 7:3.000000 8:2.000000 9:1.000000 10:29.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:2.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:1.000000 2:12.000000 3:2.000000 4:7.000000 5:1.000000 6:3.000000 7:3.000000 8:3.000000 9:2.000000 10:38.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:24.000000 3:2.000000 4:44.000000 5:5.000000 6:3.000000 7:2.000000 8:4.000000 9:2.000000 10:48.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:12.000000 3:4.000000 4:7.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:3.000000 10:32.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:1.000000 2:24.000000 3:2.000000 4:29.000000 5:1.000000 6:4.000000 7:3.000000 8:1.000000 9:4.000000 10:34.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:1.000000 2:18.000000 3:2.000000 4:27.000000 5:4.000000 6:3.000000 7:3.000000 8:2.000000 9:3.000000 10:28.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:18.000000 3:4.000000 4:10.000000 5:1.000000 6:3.000000 7:2.000000 8:3.000000 9:1.000000 10:36.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:8.000000 3:4.000000 4:34.000000 5:1.000000 6:4.000000 7:3.000000 8:4.000000 9:1.000000 10:39.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:2.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:12.000000 3:4.000000 4:58.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:2.000000 10:49.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:2.000000 4:15.000000 5:4.000000 6:4.000000 7:2.000000 8:3.000000 9:3.000000 10:34.000000 11:3.000000 12:1.000000 13:2.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:3.000000 2:36.000000 3:2.000000 4:45.000000 5:1.000000 6:5.000000 7:3.000000 8:2.000000 9:3.000000 10:31.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:6.000000 3:2.000000 4:11.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:28.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:24.000000 3:4.000000 4:66.000000 5:1.000000 6:1.000000 7:3.000000 8:4.000000 9:4.000000 10:75.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:2.000000 2:13.000000 3:2.000000 4:21.000000 5:1.000000 6:2.000000 7:2.000000 8:4.000000 9:2.000000 10:23.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:1.000000 2:24.000000 3:2.000000 4:42.000000 5:1.000000 6:3.000000 7:3.000000 8:4.000000 9:2.000000 10:28.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:10.000000 3:2.000000 4:15.000000 5:1.000000 6:3.000000 7:1.000000 8:2.000000 9:3.000000 10:31.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:24.000000 3:4.000000 4:57.000000 5:1.000000 6:2.000000 7:2.000000 8:4.000000 9:4.000000 10:24.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:21.000000 3:2.000000 4:36.000000 5:1.000000 6:4.000000 7:2.000000 8:4.000000 9:3.000000 10:26.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:18.000000 3:2.000000 4:32.000000 5:3.000000 6:2.000000 7:4.000000 8:3.000000 9:1.000000 10:25.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:18.000000 3:2.000000 4:44.000000 5:1.000000 6:5.000000 7:3.000000 8:1.000000 9:1.000000 10:33.000000 11:1.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:1.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:3.000000 2:10.000000 3:2.000000 4:39.000000 5:1.000000 6:2.000000 7:3.000000 8:1.000000 9:2.000000 10:37.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:15.000000 3:4.000000 4:15.000000 5:1.000000 6:3.000000 7:2.000000 8:2.000000 9:3.000000 10:43.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:13.000000 3:4.000000 4:9.000000 5:1.000000 6:2.000000 7:3.000000 8:4.000000 9:1.000000 10:23.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:24.000000 3:2.000000 4:38.000000 5:3.000000 6:1.000000 7:2.000000 8:4.000000 9:4.000000 10:23.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:1.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:6.000000 3:3.000000 4:17.000000 5:2.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:34.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:9.000000 3:2.000000 4:12.000000 5:1.000000 6:2.000000 7:2.000000 8:4.000000 9:1.000000 10:23.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:18.000000 3:4.000000 4:32.000000 5:5.000000 6:1.000000 7:3.000000 8:4.000000 9:4.000000 10:38.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:4.000000 2:10.000000 3:2.000000 4:7.000000 5:3.000000 6:5.000000 7:3.000000 8:4.000000 9:4.000000 10:46.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:12.000000 3:4.000000 4:23.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:49.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:1.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:12.000000 3:2.000000 4:8.000000 5:1.000000 6:3.000000 7:4.000000 8:2.000000 9:1.000000 10:28.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:2.000000 2:18.000000 3:2.000000 4:12.000000 5:5.000000 6:3.000000 7:3.000000 8:4.000000 9:4.000000 10:61.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:3.000000 2:12.000000 3:2.000000 4:34.000000 5:5.000000 6:5.000000 7:3.000000 8:3.000000 9:3.000000 10:37.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:3.000000 2:12.000000 3:3.000000 4:22.000000 5:1.000000 6:3.000000 7:2.000000 8:2.000000 9:3.000000 10:36.000000 11:2.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:6.000000 3:2.000000 4:18.000000 5:1.000000 6:3.000000 7:4.000000 8:2.000000 9:2.000000 10:21.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:12.000000 3:2.000000 4:15.000000 5:1.000000 6:4.000000 7:3.000000 8:4.000000 9:3.000000 10:36.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:18.000000 3:4.000000 4:38.000000 5:1.000000 6:4.000000 7:3.000000 8:1.000000 9:3.000000 10:27.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:18.000000 3:2.000000 4:36.000000 5:1.000000 6:2.000000 7:2.000000 8:4.000000 9:3.000000 10:22.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:2.000000 2:18.000000 3:2.000000 4:30.000000 5:1.000000 6:4.000000 7:2.000000 8:4.000000 9:1.000000 10:40.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:36.000000 3:2.000000 4:31.000000 5:5.000000 6:3.000000 7:3.000000 8:4.000000 9:1.000000 10:36.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:18.000000 3:4.000000 4:61.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:33.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:10.000000 3:4.000000 4:21.000000 5:1.000000 6:2.000000 7:2.000000 8:3.000000 9:1.000000 10:23.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:60.000000 3:4.000000 4:138.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:4.000000 10:63.000000 11:1.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:4.000000 2:18.000000 3:3.000000 4:23.000000 5:1.000000 6:1.000000 7:4.000000 8:3.000000 9:1.000000 10:34.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:7.000000 3:3.000000 4:8.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:4.000000 10:36.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:6.000000 3:4.000000 4:4.000000 5:2.000000 6:3.000000 7:2.000000 8:4.000000 9:3.000000 10:52.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:20.000000 3:2.000000 4:22.000000 5:5.000000 6:4.000000 7:3.000000 8:4.000000 9:3.000000 10:39.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:22.000000 3:2.000000 4:13.000000 5:5.000000 6:4.000000 7:2.000000 8:4.000000 9:2.000000 10:25.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:3.000000 2:12.000000 3:2.000000 4:13.000000 5:1.000000 6:2.000000 7:3.000000 8:1.000000 9:1.000000 10:26.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:30.000000 3:3.000000 4:43.000000 5:2.000000 6:3.000000 7:3.000000 8:2.000000 9:2.000000 10:26.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:18.000000 3:4.000000 4:22.000000 5:1.000000 6:3.000000 7:2.000000 8:1.000000 9:3.000000 10:25.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:18.000000 3:2.000000 4:11.000000 5:5.000000 6:2.000000 7:2.000000 8:2.000000 9:1.000000 10:21.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:18.000000 3:4.000000 4:74.000000 5:1.000000 6:1.000000 7:3.000000 8:4.000000 9:2.000000 10:40.000000 11:2.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:2.000000 2:15.000000 3:4.000000 4:23.000000 5:3.000000 6:3.000000 7:3.000000 8:4.000000 9:3.000000 10:27.000000 11:1.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:9.000000 3:2.000000 4:14.000000 5:1.000000 6:4.000000 7:2.000000 8:2.000000 9:3.000000 10:27.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:18.000000 3:2.000000 4:18.000000 5:1.000000 6:3.000000 7:4.000000 8:2.000000 9:2.000000 10:30.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:2.000000 2:12.000000 3:2.000000 4:10.000000 5:4.000000 6:2.000000 7:2.000000 8:4.000000 9:1.000000 10:19.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:36.000000 3:2.000000 4:32.000000 5:1.000000 6:4.000000 7:3.000000 8:4.000000 9:4.000000 10:39.000000 11:1.000000 12:1.000000 13:2.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:1.000000 2:6.000000 3:4.000000 4:20.000000 5:1.000000 6:4.000000 7:2.000000 8:4.000000 9:3.000000 10:31.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:9.000000 3:4.000000 4:24.000000 5:1.000000 6:1.000000 7:3.000000 8:3.000000 9:3.000000 10:31.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:2.000000 2:39.000000 3:3.000000 4:118.000000 5:2.000000 6:4.000000 7:3.000000 8:3.000000 9:4.000000 10:32.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:12.000000 3:2.000000 4:26.000000 5:1.000000 6:1.000000 7:2.000000 8:4.000000 9:4.000000 10:55.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:1.000000 2:36.000000 3:4.000000 4:23.000000 5:1.000000 6:3.000000 7:4.000000 8:2.000000 9:2.000000 10:46.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:24.000000 3:4.000000 4:15.000000 5:4.000000 6:3.000000 7:2.000000 8:1.000000 9:1.000000 10:43.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:18.000000 3:2.000000 4:15.000000 5:1.000000 6:2.000000 7:4.000000 8:4.000000 9:1.000000 10:39.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:18.000000 3:4.000000 4:19.000000 5:5.000000 6:3.000000 7:4.000000 8:4.000000 9:1.000000 10:28.000000 11:1.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:14.000000 3:3.000000 4:8.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:3.000000 10:27.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:18.000000 3:3.000000 4:29.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:43.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:24.000000 3:4.000000 4:22.000000 5:5.000000 6:4.000000 7:3.000000 8:4.000000 9:3.000000 10:43.000000 11:3.000000 12:2.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:15.000000 3:2.000000 4:11.000000 5:1.000000 6:2.000000 7:4.000000 8:2.000000 9:1.000000 10:27.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:2.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:2.000000 4:32.000000 5:3.000000 6:5.000000 7:1.000000 8:2.000000 9:3.000000 10:26.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:2.000000 2:24.000000 3:2.000000 4:20.000000 5:1.000000 6:5.000000 7:2.000000 8:4.000000 9:3.000000 10:20.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:33.000000 3:4.000000 4:73.000000 5:1.000000 6:4.000000 7:3.000000 8:2.000000 9:3.000000 10:35.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:4.000000 2:10.000000 3:2.000000 4:16.000000 5:3.000000 6:3.000000 7:3.000000 8:2.000000 9:4.000000 10:40.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:2.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:36.000000 3:4.000000 4:58.000000 5:1.000000 6:5.000000 7:3.000000 8:2.000000 9:2.000000 10:35.000000 11:3.000000 12:2.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:1.000000 2:18.000000 3:3.000000 4:85.000000 5:5.000000 6:3.000000 7:2.000000 8:2.000000 9:3.000000 10:23.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:21.000000 3:2.000000 4:28.000000 5:3.000000 6:4.000000 7:2.000000 8:2.000000 9:3.000000 10:31.000000 11:1.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:4.000000 2:15.000000 3:2.000000 4:32.000000 5:4.000000 6:4.000000 7:2.000000 8:3.000000 9:3.000000 10:20.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:12.000000 3:2.000000 4:20.000000 5:5.000000 6:3.000000 7:3.000000 8:2.000000 9:3.000000 10:30.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:12.000000 3:4.000000 4:10.000000 5:1.000000 6:4.000000 7:3.000000 8:3.000000 9:1.000000 10:47.000000 11:3.000000 12:2.000000 13:2.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:21.000000 3:3.000000 4:16.000000 5:2.000000 6:4.000000 7:3.000000 8:3.000000 9:1.000000 10:34.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:2.000000 2:18.000000 3:2.000000 4:28.000000 5:1.000000 6:3.000000 7:4.000000 8:3.000000 9:3.000000 10:21.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:28.000000 3:4.000000 4:27.000000 5:1.000000 6:5.000000 7:3.000000 8:2.000000 9:3.000000 10:29.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:18.000000 3:4.000000 4:11.000000 5:4.000000 6:3.000000 7:3.000000 8:3.000000 9:1.000000 10:46.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:9.000000 3:2.000000 4:13.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:20.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:5.000000 3:2.000000 4:34.000000 5:1.000000 6:4.000000 7:3.000000 8:4.000000 9:1.000000 10:74.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:1.000000 2:6.000000 3:4.000000 4:19.000000 5:1.000000 6:1.000000 7:3.000000 8:4.000000 9:4.000000 10:36.000000 11:3.000000 12:3.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:24.000000 3:4.000000 4:21.000000 5:1.000000 6:3.000000 7:1.000000 8:2.000000 9:1.000000 10:33.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:9.000000 3:2.000000 4:21.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:25.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:6.000000 3:2.000000 4:7.000000 5:3.000000 6:4.000000 7:4.000000 8:4.000000 9:1.000000 10:23.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:24.000000 3:4.000000 4:13.000000 5:4.000000 6:5.000000 7:2.000000 8:4.000000 9:1.000000 10:37.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:42.000000 3:4.000000 4:34.000000 5:1.000000 6:1.000000 7:3.000000 8:4.000000 9:3.000000 10:65.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:1.000000 20:0.000000 21:1.000000 22:1.000000 23:0.000000 24:0.000000 
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--1 1:4.000000 2:12.000000 3:2.000000 4:19.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:39.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:1.000000 2:12.000000 3:2.000000 4:16.000000 5:1.000000 6:3.000000 7:2.000000 8:3.000000 9:2.000000 10:30.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:1.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:20.000000 3:3.000000 4:26.000000 5:1.000000 6:3.000000 7:3.000000 8:3.000000 9:3.000000 10:29.000000 11:1.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:9.000000 3:4.000000 4:12.000000 5:5.000000 6:5.000000 7:2.000000 8:4.000000 9:2.000000 10:41.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:2.000000 2:7.000000 3:2.000000 4:26.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:35.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:3.000000 2:12.000000 3:2.000000 4:14.000000 5:5.000000 6:5.000000 7:2.000000 8:4.000000 9:1.000000 10:55.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:4.000000 2:36.000000 3:4.000000 4:111.000000 5:5.000000 6:3.000000 7:3.000000 8:2.000000 9:3.000000 10:30.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:6.000000 3:2.000000 4:5.000000 5:1.000000 6:3.000000 7:2.000000 8:1.000000 9:1.000000 10:29.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:0.000000 4:28.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:2.000000 10:34.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:2.000000 4:27.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:35.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:4.000000 2:24.000000 3:2.000000 4:27.000000 5:1.000000 6:2.000000 7:2.000000 8:1.000000 9:4.000000 10:29.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:1.000000 2:11.000000 3:4.000000 4:39.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:36.000000 11:3.000000 12:2.000000 13:2.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:1.000000 2:6.000000 3:2.000000 4:3.000000 5:1.000000 6:2.000000 7:2.000000 8:1.000000 9:1.000000 10:27.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:18.000000 3:2.000000 4:46.000000 5:1.000000 6:2.000000 7:3.000000 8:2.000000 9:3.000000 10:32.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:36.000000 3:2.000000 4:36.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:2.000000 10:37.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:15.000000 3:2.000000 4:17.000000 5:1.000000 6:2.000000 7:3.000000 8:3.000000 9:1.000000 10:36.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:12.000000 3:2.000000 4:30.000000 5:1.000000 6:2.000000 7:2.000000 8:1.000000 9:1.000000 10:34.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:2.000000 2:12.000000 3:2.000000 4:8.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:2.000000 10:38.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:18.000000 3:2.000000 4:20.000000 5:1.000000 6:4.000000 7:3.000000 8:1.000000 9:3.000000 10:34.000000 11:2.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:24.000000 3:2.000000 4:29.000000 5:1.000000 6:3.000000 7:3.000000 8:4.000000 9:4.000000 10:63.000000 11:1.000000 12:1.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:48.000000 3:3.000000 4:72.000000 5:5.000000 6:5.000000 7:3.000000 8:3.000000 9:3.000000 10:32.000000 11:1.000000 12:2.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:33.000000 3:3.000000 4:28.000000 5:1.000000 6:3.000000 7:2.000000 8:2.000000 9:3.000000 10:26.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:3.000000 4:47.000000 5:1.000000 6:4.000000 7:3.000000 8:3.000000 9:3.000000 10:35.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:6.000000 3:2.000000 4:12.000000 5:5.000000 6:1.000000 7:3.000000 8:4.000000 9:2.000000 10:36.000000 11:3.000000 12:1.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:4.000000 2:39.000000 3:2.000000 4:26.000000 5:3.000000 6:3.000000 7:3.000000 8:4.000000 9:3.000000 10:24.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:3.000000 2:24.000000 3:2.000000 4:52.000000 5:1.000000 6:4.000000 7:3.000000 8:2.000000 9:3.000000 10:25.000000 11:1.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:12.000000 3:2.000000 4:10.000000 5:2.000000 6:4.000000 7:3.000000 8:4.000000 9:1.000000 10:39.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:15.000000 3:4.000000 4:15.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:44.000000 11:3.000000 12:2.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:12.000000 3:4.000000 4:36.000000 5:1.000000 6:3.000000 7:2.000000 8:1.000000 9:1.000000 10:23.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:24.000000 3:2.000000 4:12.000000 5:1.000000 6:2.000000 7:3.000000 8:1.000000 9:2.000000 10:26.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:30.000000 3:2.000000 4:36.000000 5:4.000000 6:5.000000 7:2.000000 8:4.000000 9:2.000000 10:57.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:15.000000 3:3.000000 4:10.000000 5:4.000000 6:4.000000 7:2.000000 8:2.000000 9:2.000000 10:30.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:4.000000 4:12.000000 5:3.000000 6:3.000000 7:3.000000 8:4.000000 9:1.000000 10:44.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:12.000000 3:2.000000 4:31.000000 5:1.000000 6:3.000000 7:3.000000 8:4.000000 9:3.000000 10:52.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:2.000000 4:38.000000 5:1.000000 6:5.000000 7:2.000000 8:4.000000 9:4.000000 10:62.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:0.000000 19:1.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:10.000000 3:2.000000 4:14.000000 5:2.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:35.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:2.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:6.000000 3:2.000000 4:35.000000 5:1.000000 6:3.000000 7:3.000000 8:3.000000 9:2.000000 10:26.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:0.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:4.000000 4:19.000000 5:1.000000 6:5.000000 7:3.000000 8:2.000000 9:4.000000 10:26.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:6.000000 3:4.000000 4:12.000000 5:2.000000 6:3.000000 7:2.000000 8:1.000000 9:2.000000 10:27.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:6.000000 3:2.000000 4:4.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:2.000000 10:38.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:12.000000 3:4.000000 4:21.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:39.000000 11:3.000000 12:2.000000 13:2.000000 14:1.000000 15:2.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:24.000000 3:4.000000 4:16.000000 5:1.000000 6:4.000000 7:3.000000 8:3.000000 9:2.000000 10:40.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:18.000000 3:2.000000 4:13.000000 5:1.000000 6:5.000000 7:4.000000 8:2.000000 9:1.000000 10:32.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:3.000000 2:6.000000 3:4.000000 4:13.000000 5:2.000000 6:5.000000 7:1.000000 8:4.000000 9:3.000000 10:28.000000 11:3.000000 12:2.000000 13:2.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:1.000000 2:36.000000 3:2.000000 4:55.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:4.000000 10:42.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:3.000000 2:9.000000 3:2.000000 4:11.000000 5:2.000000 6:5.000000 7:1.000000 8:4.000000 9:1.000000 10:49.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:39.000000 3:2.000000 4:86.000000 5:2.000000 6:5.000000 7:3.000000 8:2.000000 9:3.000000 10:45.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:4.000000 2:6.000000 3:4.000000 4:7.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:4.000000 10:36.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:4.000000 4:55.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:4.000000 10:44.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:24.000000 3:2.000000 4:35.000000 5:2.000000 6:4.000000 7:2.000000 8:4.000000 9:3.000000 10:23.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:18.000000 3:2.000000 4:11.000000 5:1.000000 6:3.000000 7:2.000000 8:4.000000 9:1.000000 10:26.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:26.000000 3:2.000000 4:80.000000 5:1.000000 6:2.000000 7:3.000000 8:3.000000 9:3.000000 10:30.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:15.000000 3:4.000000 4:15.000000 5:2.000000 6:3.000000 7:2.000000 8:3.000000 9:3.000000 10:31.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:2.000000 2:36.000000 3:2.000000 4:23.000000 5:1.000000 6:4.000000 7:3.000000 8:1.000000 9:3.000000 10:32.000000 11:3.000000 12:2.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:12.000000 3:3.000000 4:15.000000 5:1.000000 6:3.000000 7:4.000000 8:4.000000 9:1.000000 10:41.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:2.000000 4:13.000000 5:2.000000 6:4.000000 7:4.000000 8:3.000000 9:2.000000 10:26.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:2.000000 4:31.000000 5:5.000000 6:2.000000 7:3.000000 8:2.000000 9:3.000000 10:25.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:1.000000 2:6.000000 3:2.000000 4:14.000000 5:5.000000 6:1.000000 7:2.000000 8:3.000000 9:2.000000 10:75.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:2.000000 2:18.000000 3:4.000000 4:36.000000 5:1.000000 6:5.000000 7:2.000000 8:4.000000 9:2.000000 10:37.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:3.000000 2:18.000000 3:2.000000 4:30.000000 5:1.000000 6:2.000000 7:2.000000 8:1.000000 9:2.000000 10:45.000000 11:2.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:12.000000 3:4.000000 4:13.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:61.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:24.000000 3:4.000000 4:20.000000 5:1.000000 6:3.000000 7:2.000000 8:4.000000 9:3.000000 10:37.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:2.000000 4:16.000000 5:1.000000 6:4.000000 7:3.000000 8:1.000000 9:3.000000 10:32.000000 11:1.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:48.000000 3:4.000000 4:89.000000 5:5.000000 6:4.000000 7:3.000000 8:1.000000 9:4.000000 10:35.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:4.000000 4:10.000000 5:5.000000 6:4.000000 7:2.000000 8:4.000000 9:1.000000 10:23.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:6.000000 3:1.000000 4:18.000000 5:3.000000 6:5.000000 7:3.000000 8:4.000000 9:2.000000 10:45.000000 11:1.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:2.000000 2:12.000000 3:4.000000 4:20.000000 5:2.000000 6:2.000000 7:3.000000 8:1.000000 9:3.000000 10:27.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:9.000000 3:2.000000 4:12.000000 5:1.000000 6:4.000000 7:2.000000 8:4.000000 9:2.000000 10:67.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:1.000000 2:24.000000 3:2.000000 4:30.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:4.000000 10:49.000000 11:1.000000 12:1.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:3.000000 2:6.000000 3:3.000000 4:7.000000 5:1.000000 6:2.000000 7:2.000000 8:1.000000 9:2.000000 10:29.000000 11:1.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:2.000000 2:24.000000 3:3.000000 4:47.000000 5:5.000000 6:3.000000 7:3.000000 8:2.000000 9:2.000000 10:37.000000 11:1.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:2.000000 2:24.000000 3:3.000000 4:16.000000 5:2.000000 6:4.000000 7:2.000000 8:2.000000 9:2.000000 10:23.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:9.000000 3:2.000000 4:14.000000 5:1.000000 6:3.000000 7:2.000000 8:2.000000 9:1.000000 10:26.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:12.000000 3:2.000000 4:21.000000 5:5.000000 6:5.000000 7:2.000000 8:4.000000 9:4.000000 10:52.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:1.000000 2:12.000000 3:4.000000 4:4.000000 5:1.000000 6:4.000000 7:2.000000 8:3.000000 9:1.000000 10:58.000000 11:3.000000 12:4.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:24.000000 3:3.000000 4:20.000000 5:5.000000 6:3.000000 7:2.000000 8:4.000000 9:3.000000 10:42.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:21.000000 3:2.000000 4:16.000000 5:4.000000 6:5.000000 7:2.000000 8:4.000000 9:1.000000 10:36.000000 11:1.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:24.000000 3:3.000000 4:39.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:4.000000 10:32.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:7.000000 3:2.000000 4:23.000000 5:1.000000 6:2.000000 7:2.000000 8:1.000000 9:1.000000 10:45.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:3.000000 2:10.000000 3:2.000000 4:13.000000 5:1.000000 6:2.000000 7:2.000000 8:2.000000 9:2.000000 10:23.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:24.000000 3:1.000000 4:28.000000 5:3.000000 6:3.000000 7:3.000000 8:4.000000 9:1.000000 10:22.000000 11:2.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:4.000000 4:45.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:74.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:4.000000 2:18.000000 3:2.000000 4:21.000000 5:1.000000 6:2.000000 7:3.000000 8:1.000000 9:1.000000 10:33.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:15.000000 3:2.000000 4:13.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:4.000000 10:45.000000 11:1.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:1.000000 2:21.000000 3:2.000000 4:34.000000 5:4.000000 6:2.000000 7:2.000000 8:2.000000 9:3.000000 10:29.000000 11:1.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:24.000000 3:1.000000 4:36.000000 5:1.000000 6:3.000000 7:2.000000 8:4.000000 9:3.000000 10:22.000000 11:1.000000 12:1.000000 13:1.000000 14:1.000000 15:2.000000 16:0.000000 17:1.000000 18:0.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:2.000000 2:48.000000 3:0.000000 4:122.000000 5:5.000000 6:3.000000 7:3.000000 8:2.000000 9:3.000000 10:48.000000 11:1.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:2.000000 2:60.000000 3:3.000000 4:92.000000 5:5.000000 6:3.000000 7:3.000000 8:2.000000 9:4.000000 10:27.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:1.000000 2:6.000000 3:4.000000 4:37.000000 5:1.000000 6:3.000000 7:3.000000 8:3.000000 9:1.000000 10:37.000000 11:3.000000 12:3.000000 13:2.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:12.000000 3:2.000000 4:6.000000 5:1.000000 6:3.000000 7:1.000000 8:2.000000 9:1.000000 10:49.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:21.000000 3:4.000000 4:37.000000 5:1.000000 6:4.000000 7:3.000000 8:3.000000 9:2.000000 10:27.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:1.000000 2:12.000000 3:2.000000 4:19.000000 5:1.000000 6:2.000000 7:2.000000 8:1.000000 9:3.000000 10:22.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:15.000000 3:2.000000 4:20.000000 5:5.000000 6:5.000000 7:3.000000 8:2.000000 9:3.000000 10:35.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:3.000000 2:6.000000 3:2.000000 4:21.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:41.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:42.000000 3:4.000000 4:40.000000 5:3.000000 6:3.000000 7:3.000000 8:4.000000 9:1.000000 10:36.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:9.000000 3:2.000000 4:38.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:64.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:24.000000 3:2.000000 4:37.000000 5:1.000000 6:3.000000 7:2.000000 8:4.000000 9:3.000000 10:28.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:12.000000 3:2.000000 4:14.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:2.000000 10:47.000000 11:1.000000 12:3.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:2.000000 4:14.000000 5:3.000000 6:4.000000 7:2.000000 8:1.000000 9:3.000000 10:28.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:60.000000 3:3.000000 4:157.000000 5:1.000000 6:4.000000 7:3.000000 8:4.000000 9:3.000000 10:21.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:2.000000 4:15.000000 5:1.000000 6:2.000000 7:2.000000 8:3.000000 9:3.000000 10:34.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:2.000000 2:15.000000 3:2.000000 4:13.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:38.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:24.000000 3:4.000000 4:19.000000 5:1.000000 6:4.000000 7:4.000000 8:2.000000 9:3.000000 10:33.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:18.000000 3:4.000000 4:19.000000 5:1.000000 6:4.000000 7:4.000000 8:1.000000 9:2.000000 10:32.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:1.000000 2:30.000000 3:0.000000 4:46.000000 5:1.000000 6:3.000000 7:1.000000 8:2.000000 9:1.000000 10:32.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:1.000000 2:48.000000 3:2.000000 4:75.000000 5:1.000000 6:4.000000 7:3.000000 8:1.000000 9:4.000000 10:50.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:4.000000 2:24.000000 3:4.000000 4:23.000000 5:1.000000 6:4.000000 7:3.000000 8:3.000000 9:3.000000 10:35.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:14.000000 3:2.000000 4:40.000000 5:1.000000 6:1.000000 7:3.000000 8:4.000000 9:4.000000 10:22.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:48.000000 3:2.000000 4:102.000000 5:5.000000 6:4.000000 7:3.000000 8:3.000000 9:3.000000 10:37.000000 11:2.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:30.000000 3:0.000000 4:42.000000 5:1.000000 6:3.000000 7:2.000000 8:1.000000 9:3.000000 10:28.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:18.000000 3:4.000000 4:64.000000 5:1.000000 6:5.000000 7:3.000000 8:1.000000 9:4.000000 10:41.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:3.000000 2:12.000000 3:2.000000 4:13.000000 5:1.000000 6:3.000000 7:4.000000 8:4.000000 9:1.000000 10:23.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:21.000000 3:2.000000 4:22.000000 5:1.000000 6:5.000000 7:3.000000 8:2.000000 9:1.000000 10:50.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:6.000000 3:3.000000 4:10.000000 5:1.000000 6:1.000000 7:3.000000 8:1.000000 9:2.000000 10:35.000000 11:2.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:3.000000 2:6.000000 3:4.000000 4:10.000000 5:1.000000 6:3.000000 7:2.000000 8:4.000000 9:2.000000 10:50.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:24.000000 3:4.000000 4:63.000000 5:1.000000 6:1.000000 7:3.000000 8:2.000000 9:4.000000 10:27.000000 11:1.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:1.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:2.000000 2:30.000000 3:1.000000 4:35.000000 5:4.000000 6:3.000000 7:3.000000 8:2.000000 9:3.000000 10:34.000000 11:2.000000 12:1.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:48.000000 3:1.000000 4:36.000000 5:1.000000 6:3.000000 7:2.000000 8:1.000000 9:1.000000 10:27.000000 11:2.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:3.000000 2:30.000000 3:4.000000 4:30.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:2.000000 10:47.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:4.000000 4:41.000000 5:2.000000 6:3.000000 7:3.000000 8:3.000000 9:2.000000 10:27.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:36.000000 3:2.000000 4:57.000000 5:2.000000 6:4.000000 7:3.000000 8:2.000000 9:3.000000 10:31.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:60.000000 3:2.000000 4:104.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:2.000000 10:42.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:6.000000 3:4.000000 4:21.000000 5:3.000000 6:3.000000 7:4.000000 8:2.000000 9:3.000000 10:24.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:30.000000 3:4.000000 4:45.000000 5:1.000000 6:4.000000 7:2.000000 8:4.000000 9:3.000000 10:26.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:24.000000 3:4.000000 4:52.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:33.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:1.000000 2:24.000000 3:2.000000 4:24.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:64.000000 11:1.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:18.000000 3:2.000000 4:15.000000 5:1.000000 6:2.000000 7:2.000000 8:1.000000 9:1.000000 10:26.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:6.000000 3:2.000000 4:15.000000 5:1.000000 6:2.000000 7:2.000000 8:2.000000 9:4.000000 10:56.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:2.000000 4:23.000000 5:5.000000 6:3.000000 7:3.000000 8:4.000000 9:4.000000 10:37.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:15.000000 3:3.000000 4:15.000000 5:1.000000 6:3.000000 7:4.000000 8:3.000000 9:1.000000 10:33.000000 11:1.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:4.000000 4:51.000000 5:1.000000 6:2.000000 7:4.000000 8:3.000000 9:4.000000 10:47.000000 11:3.000000 12:3.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:36.000000 3:3.000000 4:99.000000 5:2.000000 6:4.000000 7:3.000000 8:3.000000 9:2.000000 10:31.000000 11:3.000000 12:2.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:60.000000 3:2.000000 4:65.000000 5:5.000000 6:3.000000 7:3.000000 8:4.000000 9:4.000000 10:34.000000 11:3.000000 12:1.000000 13:2.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:3.000000 2:10.000000 3:4.000000 4:13.000000 5:5.000000 6:4.000000 7:3.000000 8:2.000000 9:2.000000 10:27.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:36.000000 3:3.000000 4:29.000000 5:2.000000 6:5.000000 7:3.000000 8:3.000000 9:4.000000 10:30.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:9.000000 3:2.000000 4:28.000000 5:2.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:35.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:1.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:12.000000 3:2.000000 4:37.000000 5:4.000000 6:3.000000 7:3.000000 8:3.000000 9:2.000000 10:31.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:15.000000 3:4.000000 4:10.000000 5:1.000000 6:3.000000 7:1.000000 8:3.000000 9:2.000000 10:25.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:15.000000 3:2.000000 4:26.000000 5:2.000000 6:3.000000 7:2.000000 8:2.000000 9:1.000000 10:25.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:24.000000 3:2.000000 4:29.000000 5:2.000000 6:2.000000 7:3.000000 8:1.000000 9:3.000000 10:29.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:6.000000 3:4.000000 4:47.000000 5:5.000000 6:2.000000 7:3.000000 8:3.000000 9:1.000000 10:44.000000 11:3.000000 12:2.000000 13:2.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:24.000000 3:2.000000 4:23.000000 5:1.000000 6:4.000000 7:3.000000 8:2.000000 9:3.000000 10:28.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:6.000000 3:2.000000 4:12.000000 5:3.000000 6:3.000000 7:3.000000 8:4.000000 9:2.000000 10:50.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:12.000000 3:2.000000 4:11.000000 5:1.000000 6:4.000000 7:3.000000 8:3.000000 9:1.000000 10:29.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:2.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:4.000000 4:9.000000 5:1.000000 6:1.000000 7:2.000000 8:2.000000 9:2.000000 10:38.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:1.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:18.000000 3:4.000000 4:18.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:3.000000 10:24.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:3.000000 2:15.000000 3:2.000000 4:19.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:40.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:3.000000 2:24.000000 3:2.000000 4:14.000000 5:2.000000 6:5.000000 7:2.000000 8:2.000000 9:4.000000 10:47.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:30.000000 3:3.000000 4:25.000000 5:2.000000 6:5.000000 7:3.000000 8:2.000000 9:2.000000 10:41.000000 11:2.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:27.000000 3:2.000000 4:25.000000 5:1.000000 6:2.000000 7:2.000000 8:1.000000 9:2.000000 10:32.000000 11:3.000000 12:1.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:15.000000 3:2.000000 4:53.000000 5:3.000000 6:5.000000 7:2.000000 8:4.000000 9:4.000000 10:35.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:2.000000 2:9.000000 3:2.000000 4:12.000000 5:1.000000 6:5.000000 7:2.000000 8:4.000000 9:1.000000 10:25.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:9.000000 3:2.000000 4:21.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:37.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:18.000000 3:4.000000 4:6.000000 5:3.000000 6:5.000000 7:3.000000 8:3.000000 9:2.000000 10:32.000000 11:1.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:4.000000 2:21.000000 3:2.000000 4:25.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:46.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:1.000000 2:9.000000 3:4.000000 4:11.000000 5:1.000000 6:3.000000 7:3.000000 8:4.000000 9:1.000000 10:25.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:30.000000 3:4.000000 4:76.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:63.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:30.000000 3:4.000000 4:31.000000 5:5.000000 6:5.000000 7:3.000000 8:2.000000 9:3.000000 10:40.000000 11:3.000000 12:2.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:18.000000 3:2.000000 4:15.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:4.000000 10:32.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:3.000000 2:24.000000 3:4.000000 4:31.000000 5:5.000000 6:3.000000 7:3.000000 8:2.000000 9:3.000000 10:31.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:20.000000 3:0.000000 4:61.000000 5:2.000000 6:5.000000 7:4.000000 8:4.000000 9:3.000000 10:31.000000 11:1.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:2.000000 2:9.000000 3:2.000000 4:8.000000 5:3.000000 6:3.000000 7:2.000000 8:3.000000 9:1.000000 10:66.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:6.000000 3:4.000000 4:2.000000 5:4.000000 6:3.000000 7:2.000000 8:2.000000 9:1.000000 10:41.000000 11:1.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:15.000000 3:4.000000 4:13.000000 5:3.000000 6:3.000000 7:4.000000 8:2.000000 9:2.000000 10:47.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:3.000000 2:24.000000 3:4.000000 4:13.000000 5:4.000000 6:3.000000 7:1.000000 8:4.000000 9:1.000000 10:36.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:24.000000 3:3.000000 4:64.000000 5:1.000000 6:2.000000 7:3.000000 8:2.000000 9:3.000000 10:33.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:2.000000 2:8.000000 3:2.000000 4:8.000000 5:1.000000 6:4.000000 7:2.000000 8:2.000000 9:1.000000 10:44.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:24.000000 3:2.000000 4:26.000000 5:4.000000 6:3.000000 7:2.000000 8:4.000000 9:3.000000 10:28.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:4.000000 3:4.000000 4:34.000000 5:1.000000 6:4.000000 7:2.000000 8:1.000000 9:1.000000 10:37.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:36.000000 3:1.000000 4:40.000000 5:5.000000 6:2.000000 7:2.000000 8:2.000000 9:4.000000 10:29.000000 11:1.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:1.000000 23:0.000000 24:0.000000 
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--1 1:1.000000 2:18.000000 3:2.000000 4:44.000000 5:2.000000 6:3.000000 7:3.000000 8:4.000000 9:3.000000 10:35.000000 11:3.000000 12:1.000000 13:2.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:6.000000 3:4.000000 4:68.000000 5:1.000000 6:4.000000 7:3.000000 8:3.000000 9:4.000000 10:45.000000 11:3.000000 12:2.000000 13:2.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:1.000000 2:24.000000 3:1.000000 4:23.000000 5:2.000000 6:4.000000 7:3.000000 8:3.000000 9:3.000000 10:32.000000 11:1.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:10.000000 3:1.000000 4:10.000000 5:1.000000 6:3.000000 7:3.000000 8:4.000000 9:1.000000 10:23.000000 11:2.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:21.000000 3:2.000000 4:32.000000 5:5.000000 6:5.000000 7:3.000000 8:3.000000 9:2.000000 10:41.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:24.000000 3:1.000000 4:25.000000 5:3.000000 6:3.000000 7:3.000000 8:4.000000 9:1.000000 10:22.000000 11:2.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:39.000000 3:4.000000 4:142.000000 5:5.000000 6:4.000000 7:3.000000 8:4.000000 9:2.000000 10:30.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:1.000000 2:13.000000 3:4.000000 4:18.000000 5:1.000000 6:2.000000 7:3.000000 8:1.000000 9:2.000000 10:28.000000 11:1.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:15.000000 3:2.000000 4:25.000000 5:1.000000 6:1.000000 7:2.000000 8:4.000000 9:3.000000 10:23.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:21.000000 3:2.000000 4:52.000000 5:5.000000 6:3.000000 7:3.000000 8:3.000000 9:3.000000 10:26.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:15.000000 3:2.000000 4:30.000000 5:1.000000 6:4.000000 7:3.000000 8:2.000000 9:3.000000 10:33.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:6.000000 3:2.000000 4:4.000000 5:1.000000 6:5.000000 7:2.000000 8:1.000000 9:2.000000 10:49.000000 11:1.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:2.000000 2:12.000000 3:2.000000 4:8.000000 5:2.000000 6:4.000000 7:2.000000 8:4.000000 9:1.000000 10:23.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:30.000000 3:4.000000 4:58.000000 5:1.000000 6:4.000000 7:2.000000 8:2.000000 9:3.000000 10:25.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:3.000000 2:6.000000 3:4.000000 4:13.000000 5:1.000000 6:3.000000 7:3.000000 8:1.000000 9:1.000000 10:74.000000 11:3.000000 12:3.000000 13:2.000000 14:1.000000 15:2.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:1.000000 23:0.000000 24:0.000000 
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--1 1:4.000000 2:24.000000 3:2.000000 4:14.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:31.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:1.000000 2:12.000000 3:2.000000 4:22.000000 5:1.000000 6:3.000000 7:3.000000 8:3.000000 9:2.000000 10:24.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:24.000000 3:4.000000 4:25.000000 5:2.000000 6:4.000000 7:4.000000 8:3.000000 9:2.000000 10:27.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:12.000000 3:2.000000 4:12.000000 5:1.000000 6:5.000000 7:4.000000 8:3.000000 9:1.000000 10:40.000000 11:1.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:10.000000 3:2.000000 4:29.000000 5:5.000000 6:2.000000 7:2.000000 8:4.000000 9:1.000000 10:31.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:12.000000 3:4.000000 4:36.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:28.000000 11:3.000000 12:3.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:4.000000 4:17.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:63.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:24.000000 3:2.000000 4:28.000000 5:5.000000 6:5.000000 7:2.000000 8:4.000000 9:1.000000 10:26.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:21.000000 3:4.000000 4:33.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:36.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:24.000000 3:4.000000 4:22.000000 5:2.000000 6:5.000000 7:3.000000 8:4.000000 9:2.000000 10:52.000000 11:1.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:3.000000 2:12.000000 3:4.000000 4:15.000000 5:3.000000 6:1.000000 7:3.000000 8:4.000000 9:4.000000 10:66.000000 11:1.000000 12:3.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:1.000000 23:0.000000 24:0.000000 
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--1 1:4.000000 2:36.000000 3:4.000000 4:35.000000 5:1.000000 6:4.000000 7:3.000000 8:4.000000 9:3.000000 10:37.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:18.000000 3:2.000000 4:35.000000 5:1.000000 6:4.000000 7:2.000000 8:1.000000 9:1.000000 10:25.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:36.000000 3:4.000000 4:57.000000 5:4.000000 6:5.000000 7:3.000000 8:2.000000 9:3.000000 10:38.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:2.000000 2:18.000000 3:2.000000 4:39.000000 5:1.000000 6:1.000000 7:2.000000 8:4.000000 9:3.000000 10:67.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:24.000000 3:4.000000 4:19.000000 5:4.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:60.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:12.000000 3:0.000000 4:14.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:31.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:2.000000 2:20.000000 3:2.000000 4:65.000000 5:5.000000 6:1.000000 7:1.000000 8:4.000000 9:1.000000 10:60.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:2.000000 2:18.000000 3:2.000000 4:19.000000 5:4.000000 6:3.000000 7:3.000000 8:2.000000 9:2.000000 10:35.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:22.000000 3:2.000000 4:27.000000 5:3.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:40.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:48.000000 3:4.000000 4:28.000000 5:5.000000 6:5.000000 7:3.000000 8:3.000000 9:3.000000 10:38.000000 11:3.000000 12:2.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:24.000000 3:2.000000 4:63.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:41.000000 11:3.000000 12:1.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:6.000000 3:4.000000 4:12.000000 5:5.000000 6:3.000000 7:4.000000 8:2.000000 9:2.000000 10:27.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:3.000000 2:24.000000 3:2.000000 4:29.000000 5:1.000000 6:5.000000 7:1.000000 8:4.000000 9:4.000000 10:51.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:2.000000 4:31.000000 5:3.000000 6:5.000000 7:3.000000 8:3.000000 9:4.000000 10:32.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:9.000000 3:2.000000 4:23.000000 5:2.000000 6:2.000000 7:2.000000 8:4.000000 9:2.000000 10:22.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:12.000000 3:4.000000 4:13.000000 5:1.000000 6:2.000000 7:2.000000 8:4.000000 9:2.000000 10:22.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:24.000000 3:3.000000 4:7.000000 5:5.000000 6:5.000000 7:4.000000 8:4.000000 9:3.000000 10:54.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:9.000000 3:2.000000 4:15.000000 5:5.000000 6:2.000000 7:3.000000 8:2.000000 9:1.000000 10:35.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:1.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:24.000000 3:4.000000 4:16.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:4.000000 10:54.000000 11:3.000000 12:2.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:18.000000 3:4.000000 4:18.000000 5:1.000000 6:5.000000 7:2.000000 8:4.000000 9:1.000000 10:48.000000 11:1.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:20.000000 3:4.000000 4:43.000000 5:1.000000 6:5.000000 7:2.000000 8:4.000000 9:2.000000 10:24.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:4.000000 4:10.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:35.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:12.000000 3:2.000000 4:75.000000 5:5.000000 6:1.000000 7:2.000000 8:2.000000 9:1.000000 10:24.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:1.000000 23:0.000000 24:0.000000 
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--1 1:2.000000 2:6.000000 3:2.000000 4:6.000000 5:1.000000 6:2.000000 7:4.000000 8:3.000000 9:1.000000 10:26.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:2.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:12.000000 3:4.000000 4:9.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:65.000000 11:3.000000 12:4.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:42.000000 3:1.000000 4:93.000000 5:1.000000 6:1.000000 7:3.000000 8:2.000000 9:4.000000 10:55.000000 11:1.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:2.000000 2:8.000000 3:2.000000 4:9.000000 5:1.000000 6:2.000000 7:4.000000 8:2.000000 9:1.000000 10:26.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:6.000000 3:2.000000 4:5.000000 5:1.000000 6:4.000000 7:4.000000 8:3.000000 9:1.000000 10:28.000000 11:1.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:2.000000 2:36.000000 3:3.000000 4:74.000000 5:1.000000 6:3.000000 7:2.000000 8:2.000000 9:2.000000 10:54.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:6.000000 3:2.000000 4:13.000000 5:3.000000 6:3.000000 7:1.000000 8:4.000000 9:1.000000 10:62.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:6.000000 3:4.000000 4:16.000000 5:1.000000 6:4.000000 7:2.000000 8:2.000000 9:3.000000 10:24.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:36.000000 3:2.000000 4:159.000000 5:1.000000 6:1.000000 7:1.000000 8:3.000000 9:3.000000 10:43.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:1.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:3.000000 2:12.000000 3:2.000000 4:30.000000 5:1.000000 6:3.000000 7:4.000000 8:1.000000 9:3.000000 10:24.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:18.000000 3:4.000000 4:38.000000 5:1.000000 6:2.000000 7:1.000000 8:2.000000 9:3.000000 10:35.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:2.000000 2:48.000000 3:3.000000 4:67.000000 5:5.000000 6:3.000000 7:3.000000 8:4.000000 9:4.000000 10:38.000000 11:3.000000 12:1.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:3.000000 4:24.000000 5:3.000000 6:3.000000 7:3.000000 8:2.000000 9:3.000000 10:44.000000 11:3.000000 12:2.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:2.000000 2:24.000000 3:2.000000 4:51.000000 5:5.000000 6:5.000000 7:2.000000 8:4.000000 9:3.000000 10:42.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:12.000000 3:2.000000 4:9.000000 5:5.000000 6:3.000000 7:2.000000 8:2.000000 9:3.000000 10:21.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:4.000000 3:2.000000 4:6.000000 5:1.000000 6:2.000000 7:2.000000 8:3.000000 9:1.000000 10:23.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:24.000000 3:4.000000 4:30.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:2.000000 10:63.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:4.000000 4:26.000000 5:1.000000 6:5.000000 7:4.000000 8:3.000000 9:1.000000 10:46.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:1.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:21.000000 3:3.000000 4:30.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:28.000000 11:2.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:24.000000 3:1.000000 4:16.000000 5:1.000000 6:4.000000 7:3.000000 8:4.000000 9:3.000000 10:50.000000 11:1.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:18.000000 3:2.000000 4:34.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:2.000000 10:47.000000 11:1.000000 12:3.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:21.000000 3:2.000000 4:40.000000 5:5.000000 6:4.000000 7:3.000000 8:3.000000 9:3.000000 10:35.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:24.000000 3:2.000000 4:12.000000 5:1.000000 6:2.000000 7:4.000000 8:2.000000 9:1.000000 10:28.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:9.000000 3:2.000000 4:14.000000 5:1.000000 6:4.000000 7:3.000000 8:4.000000 9:1.000000 10:59.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:24.000000 3:4.000000 4:40.000000 5:5.000000 6:4.000000 7:3.000000 8:4.000000 9:2.000000 10:43.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:15.000000 3:4.000000 4:15.000000 5:1.000000 6:3.000000 7:3.000000 8:4.000000 9:4.000000 10:35.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:36.000000 3:3.000000 4:109.000000 5:1.000000 6:5.000000 7:3.000000 8:2.000000 9:3.000000 10:45.000000 11:3.000000 12:2.000000 13:2.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:2.000000 4:15.000000 5:2.000000 6:2.000000 7:4.000000 8:3.000000 9:1.000000 10:33.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:10.000000 3:2.000000 4:9.000000 5:5.000000 6:4.000000 7:2.000000 8:3.000000 9:2.000000 10:40.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:15.000000 3:4.000000 4:33.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:4.000000 10:28.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:9.000000 3:2.000000 4:36.000000 5:2.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:26.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:2.000000 16:1.000000 17:0.000000 18:0.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:4.000000 4:58.000000 5:4.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:27.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:27.000000 3:4.000000 4:45.000000 5:4.000000 6:2.000000 7:3.000000 8:2.000000 9:1.000000 10:32.000000 11:2.000000 12:2.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:15.000000 3:2.000000 4:22.000000 5:3.000000 6:3.000000 7:2.000000 8:4.000000 9:3.000000 10:20.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:18.000000 3:2.000000 4:24.000000 5:1.000000 6:2.000000 7:2.000000 8:1.000000 9:3.000000 10:27.000000 11:2.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:4.000000 4:33.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:2.000000 10:42.000000 11:2.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:36.000000 3:2.000000 4:74.000000 5:5.000000 6:5.000000 7:3.000000 8:2.000000 9:2.000000 10:37.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:12.000000 3:2.000000 4:7.000000 5:1.000000 6:5.000000 7:2.000000 8:4.000000 9:2.000000 10:24.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:36.000000 3:3.000000 4:77.000000 5:3.000000 6:4.000000 7:2.000000 8:4.000000 9:3.000000 10:40.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:3.000000 2:6.000000 3:4.000000 4:13.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:46.000000 11:3.000000 12:2.000000 13:2.000000 14:1.000000 15:2.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:24.000000 3:4.000000 4:14.000000 5:2.000000 6:4.000000 7:3.000000 8:1.000000 9:1.000000 10:26.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:15.000000 3:2.000000 4:9.000000 5:5.000000 6:2.000000 7:2.000000 8:1.000000 9:1.000000 10:24.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:12.000000 3:2.000000 4:36.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:2.000000 10:29.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:1.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:11.000000 3:4.000000 4:13.000000 5:4.000000 6:3.000000 7:2.000000 8:4.000000 9:3.000000 10:40.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:18.000000 3:1.000000 4:19.000000 5:1.000000 6:2.000000 7:3.000000 8:4.000000 9:4.000000 10:36.000000 11:1.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:1.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:36.000000 3:2.000000 4:36.000000 5:1.000000 6:5.000000 7:3.000000 8:2.000000 9:3.000000 10:28.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:30.000000 3:4.000000 4:67.000000 5:5.000000 6:4.000000 7:3.000000 8:3.000000 9:2.000000 10:36.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:2.000000 4:78.000000 5:1.000000 6:4.000000 7:3.000000 8:3.000000 9:3.000000 10:38.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:24.000000 3:2.000000 4:93.000000 5:5.000000 6:3.000000 7:1.000000 8:4.000000 9:4.000000 10:48.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:30.000000 3:4.000000 4:22.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:36.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:18.000000 3:4.000000 4:11.000000 5:1.000000 6:1.000000 7:2.000000 8:4.000000 9:3.000000 10:65.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:1.000000 23:0.000000 24:0.000000 
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--1 1:2.000000 2:24.000000 3:4.000000 4:28.000000 5:5.000000 6:4.000000 7:3.000000 8:3.000000 9:4.000000 10:34.000000 11:3.000000 12:2.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:36.000000 3:4.000000 4:66.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:34.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:28.000000 3:1.000000 4:78.000000 5:5.000000 6:2.000000 7:3.000000 8:4.000000 9:1.000000 10:40.000000 11:1.000000 12:2.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:0.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:27.000000 3:4.000000 4:24.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:43.000000 11:2.000000 12:4.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:15.000000 3:4.000000 4:18.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:46.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:12.000000 3:4.000000 4:22.000000 5:1.000000 6:3.000000 7:3.000000 8:4.000000 9:2.000000 10:38.000000 11:1.000000 12:2.000000 13:1.000000 14:1.000000 15:2.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:36.000000 3:4.000000 4:58.000000 5:1.000000 6:3.000000 7:3.000000 8:4.000000 9:3.000000 10:34.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:18.000000 3:4.000000 4:12.000000 5:5.000000 6:3.000000 7:3.000000 8:3.000000 9:2.000000 10:29.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:36.000000 3:3.000000 4:89.000000 5:5.000000 6:4.000000 7:3.000000 8:2.000000 9:3.000000 10:31.000000 11:2.000000 12:1.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:1.000000 2:21.000000 3:2.000000 4:26.000000 5:1.000000 6:2.000000 7:2.000000 8:4.000000 9:2.000000 10:28.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:12.000000 3:4.000000 4:16.000000 5:4.000000 6:4.000000 7:2.000000 8:2.000000 9:2.000000 10:35.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:2.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:15.000000 3:2.000000 4:22.000000 5:5.000000 6:4.000000 7:2.000000 8:4.000000 9:1.000000 10:33.000000 11:1.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:20.000000 3:4.000000 4:35.000000 5:5.000000 6:2.000000 7:1.000000 8:4.000000 9:1.000000 10:44.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:36.000000 3:4.000000 4:105.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:4.000000 10:42.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:15.000000 3:2.000000 4:14.000000 5:5.000000 6:3.000000 7:4.000000 8:2.000000 9:1.000000 10:40.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:2.000000 4:13.000000 5:1.000000 6:5.000000 7:3.000000 8:1.000000 9:1.000000 10:36.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:1.000000 2:12.000000 3:2.000000 4:11.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:20.000000 11:3.000000 12:1.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:1.000000 2:21.000000 3:2.000000 4:38.000000 5:5.000000 6:4.000000 7:3.000000 8:2.000000 9:1.000000 10:24.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:2.000000 16:1.000000 17:0.000000 18:0.000000 19:1.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:36.000000 3:2.000000 4:37.000000 5:5.000000 6:3.000000 7:4.000000 8:2.000000 9:3.000000 10:27.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:15.000000 3:3.000000 4:36.000000 5:1.000000 6:2.000000 7:2.000000 8:2.000000 9:2.000000 10:46.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:9.000000 3:2.000000 4:32.000000 5:5.000000 6:3.000000 7:2.000000 8:2.000000 9:1.000000 10:33.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:36.000000 3:3.000000 4:45.000000 5:1.000000 6:3.000000 7:2.000000 8:4.000000 9:1.000000 10:34.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:2.000000 2:30.000000 3:2.000000 4:30.000000 5:5.000000 6:5.000000 7:2.000000 8:4.000000 9:3.000000 10:25.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:11.000000 3:2.000000 4:21.000000 5:4.000000 6:5.000000 7:1.000000 8:2.000000 9:1.000000 10:28.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:10.000000 3:2.000000 4:28.000000 5:2.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:32.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:0.000000 19:1.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:18.000000 3:4.000000 4:18.000000 5:1.000000 6:3.000000 7:2.000000 8:2.000000 9:4.000000 10:28.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:48.000000 3:3.000000 4:127.000000 5:3.000000 6:4.000000 7:3.000000 8:1.000000 9:3.000000 10:37.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:2.000000 2:12.000000 3:2.000000 4:20.000000 5:1.000000 6:4.000000 7:3.000000 8:4.000000 9:2.000000 10:30.000000 11:3.000000 12:1.000000 13:2.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:1.000000 2:18.000000 3:4.000000 4:10.000000 5:1.000000 6:2.000000 7:2.000000 8:4.000000 9:2.000000 10:21.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:30.000000 3:2.000000 4:19.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:58.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:12.000000 3:3.000000 4:13.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:43.000000 11:3.000000 12:2.000000 13:2.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:24.000000 3:2.000000 4:17.000000 5:1.000000 6:2.000000 7:3.000000 8:1.000000 9:2.000000 10:24.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:2.000000 16:0.000000 17:0.000000 18:0.000000 19:1.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:9.000000 3:4.000000 4:12.000000 5:1.000000 6:3.000000 7:3.000000 8:1.000000 9:1.000000 10:30.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:4.000000 4:5.000000 5:3.000000 6:5.000000 7:3.000000 8:4.000000 9:2.000000 10:42.000000 11:3.000000 12:2.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:12.000000 3:2.000000 4:15.000000 5:1.000000 6:3.000000 7:2.000000 8:1.000000 9:3.000000 10:23.000000 11:1.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:2.000000 2:6.000000 3:2.000000 4:21.000000 5:1.000000 6:2.000000 7:4.000000 8:3.000000 9:3.000000 10:30.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:4.000000 2:24.000000 3:4.000000 4:68.000000 5:5.000000 6:3.000000 7:3.000000 8:4.000000 9:2.000000 10:46.000000 11:3.000000 12:2.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:12.000000 3:2.000000 4:35.000000 5:5.000000 6:2.000000 7:3.000000 8:3.000000 9:2.000000 10:45.000000 11:3.000000 12:1.000000 13:2.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:10.000000 3:2.000000 4:15.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:31.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:2.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:24.000000 3:2.000000 4:9.000000 5:5.000000 6:4.000000 7:3.000000 8:2.000000 9:3.000000 10:31.000000 11:2.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:4.000000 3:4.000000 4:15.000000 5:1.000000 6:4.000000 7:3.000000 8:1.000000 9:1.000000 10:42.000000 11:3.000000 12:3.000000 13:2.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:15.000000 3:2.000000 4:18.000000 5:1.000000 6:2.000000 7:2.000000 8:1.000000 9:2.000000 10:46.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:48.000000 3:0.000000 4:84.000000 5:3.000000 6:2.000000 7:2.000000 8:1.000000 9:3.000000 10:30.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:4.000000 2:12.000000 3:2.000000 4:29.000000 5:5.000000 6:1.000000 7:3.000000 8:4.000000 9:4.000000 10:38.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
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--1 1:2.000000 2:18.000000 3:4.000000 4:36.000000 5:1.000000 6:1.000000 7:4.000000 8:3.000000 9:3.000000 10:40.000000 11:3.000000 12:3.000000 13:2.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:1.000000 23:0.000000 24:0.000000 
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--1 1:1.000000 2:12.000000 3:2.000000 4:19.000000 5:1.000000 6:3.000000 7:2.000000 8:4.000000 9:2.000000 10:29.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:24.000000 3:4.000000 4:12.000000 5:4.000000 6:5.000000 7:2.000000 8:4.000000 9:2.000000 10:57.000000 11:3.000000 12:2.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:3.000000 2:30.000000 3:4.000000 4:37.000000 5:5.000000 6:5.000000 7:3.000000 8:4.000000 9:2.000000 10:49.000000 11:2.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:9.000000 3:4.000000 4:12.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:1.000000 10:37.000000 11:3.000000 12:3.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
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--1 1:4.000000 2:6.000000 3:4.000000 4:17.000000 5:1.000000 6:5.000000 7:4.000000 8:2.000000 9:1.000000 10:30.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:21.000000 3:3.000000 4:24.000000 5:1.000000 6:3.000000 7:1.000000 8:4.000000 9:2.000000 10:47.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:15.000000 3:2.000000 4:36.000000 5:5.000000 6:3.000000 7:3.000000 8:2.000000 9:4.000000 10:29.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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--1 1:2.000000 2:6.000000 3:2.000000 4:5.000000 5:1.000000 6:2.000000 7:4.000000 8:1.000000 9:2.000000 10:22.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:30.000000 3:2.000000 4:17.000000 5:5.000000 6:3.000000 7:2.000000 8:1.000000 9:3.000000 10:26.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
-+1 1:2.000000 2:27.000000 3:4.000000 4:25.000000 5:3.000000 6:3.000000 7:3.000000 8:2.000000 9:2.000000 10:23.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:15.000000 3:2.000000 4:36.000000 5:1.000000 6:5.000000 7:2.000000 8:2.000000 9:3.000000 10:54.000000 11:1.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:42.000000 3:2.000000 4:72.000000 5:5.000000 6:4.000000 7:4.000000 8:4.000000 9:2.000000 10:29.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:11.000000 3:4.000000 4:39.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:40.000000 11:3.000000 12:2.000000 13:2.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:15.000000 3:2.000000 4:15.000000 5:2.000000 6:3.000000 7:3.000000 8:2.000000 9:1.000000 10:22.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:2.000000 4:74.000000 5:1.000000 6:3.000000 7:3.000000 8:4.000000 9:2.000000 10:43.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
-+1 1:1.000000 2:24.000000 3:1.000000 4:12.000000 5:1.000000 6:1.000000 7:2.000000 8:4.000000 9:4.000000 10:29.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:1.000000 17:0.000000 18:0.000000 19:1.000000 20:1.000000 21:0.000000 22:1.000000 23:0.000000 24:0.000000 
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--1 1:4.000000 2:30.000000 3:4.000000 4:28.000000 5:1.000000 6:3.000000 7:2.000000 8:2.000000 9:3.000000 10:33.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:3.000000 2:24.000000 3:2.000000 4:13.000000 5:3.000000 6:3.000000 7:2.000000 8:3.000000 9:3.000000 10:57.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:2.000000 2:6.000000 3:2.000000 4:8.000000 5:1.000000 6:3.000000 7:2.000000 8:3.000000 9:1.000000 10:64.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:0.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:18.000000 3:3.000000 4:24.000000 5:5.000000 6:5.000000 7:3.000000 8:2.000000 9:2.000000 10:42.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
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-+1 1:2.000000 2:30.000000 3:4.000000 4:84.000000 5:1.000000 6:4.000000 7:3.000000 8:2.000000 9:2.000000 10:49.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
-+1 1:4.000000 2:48.000000 3:2.000000 4:48.000000 5:1.000000 6:1.000000 7:3.000000 8:2.000000 9:3.000000 10:33.000000 11:1.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:3.000000 2:21.000000 3:2.000000 4:29.000000 5:2.000000 6:3.000000 7:2.000000 8:1.000000 9:3.000000 10:28.000000 11:1.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
-+1 1:1.000000 2:36.000000 3:2.000000 4:82.000000 5:1.000000 6:3.000000 7:3.000000 8:2.000000 9:2.000000 10:26.000000 11:3.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:24.000000 3:4.000000 4:20.000000 5:1.000000 6:4.000000 7:3.000000 8:2.000000 9:2.000000 10:30.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:15.000000 3:4.000000 4:14.000000 5:1.000000 6:3.000000 7:2.000000 8:3.000000 9:2.000000 10:25.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:3.000000 2:42.000000 3:0.000000 4:63.000000 5:1.000000 6:2.000000 7:1.000000 8:1.000000 9:2.000000 10:33.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:13.000000 3:2.000000 4:14.000000 5:2.000000 6:1.000000 7:2.000000 8:4.000000 9:1.000000 10:64.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:1.000000 2:24.000000 3:2.000000 4:66.000000 5:1.000000 6:1.000000 7:3.000000 8:2.000000 9:4.000000 10:29.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:2.000000 2:24.000000 3:4.000000 4:17.000000 5:1.000000 6:5.000000 7:3.000000 8:2.000000 9:2.000000 10:48.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:12.000000 3:4.000000 4:36.000000 5:5.000000 6:2.000000 7:3.000000 8:1.000000 9:2.000000 10:37.000000 11:3.000000 12:2.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:4.000000 2:15.000000 3:1.000000 4:16.000000 5:2.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:34.000000 11:1.000000 12:1.000000 13:2.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:18.000000 3:2.000000 4:19.000000 5:5.000000 6:4.000000 7:4.000000 8:4.000000 9:3.000000 10:23.000000 11:3.000000 12:2.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:1.000000 21:0.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:36.000000 3:2.000000 4:40.000000 5:1.000000 6:1.000000 7:3.000000 8:3.000000 9:2.000000 10:30.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:12.000000 3:2.000000 4:24.000000 5:5.000000 6:5.000000 7:3.000000 8:3.000000 9:3.000000 10:50.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:1.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:4.000000 2:12.000000 3:2.000000 4:17.000000 5:1.000000 6:4.000000 7:2.000000 8:4.000000 9:1.000000 10:31.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:1.000000 24:0.000000 
--1 1:1.000000 2:30.000000 3:2.000000 4:39.000000 5:1.000000 6:3.000000 7:1.000000 8:4.000000 9:2.000000 10:40.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:0.000000 
--1 1:4.000000 2:12.000000 3:2.000000 4:8.000000 5:1.000000 6:5.000000 7:3.000000 8:4.000000 9:3.000000 10:38.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
-+1 1:1.000000 2:45.000000 3:2.000000 4:18.000000 5:1.000000 6:3.000000 7:3.000000 8:4.000000 9:4.000000 10:23.000000 11:3.000000 12:1.000000 13:1.000000 14:2.000000 15:1.000000 16:0.000000 17:0.000000 18:1.000000 19:0.000000 20:0.000000 21:0.000000 22:0.000000 23:0.000000 24:1.000000 
--1 1:2.000000 2:45.000000 3:4.000000 4:46.000000 5:2.000000 6:1.000000 7:3.000000 8:4.000000 9:3.000000 10:27.000000 11:3.000000 12:1.000000 13:1.000000 14:1.000000 15:1.000000 16:0.000000 17:1.000000 18:1.000000 19:0.000000 20:0.000000 21:1.000000 22:0.000000 23:0.000000 24:1.000000 
diff --git a/scikits/learn/datasets/heart/__init__.py b/scikits/learn/datasets/heart/__init__.py
deleted file mode 100644
index f6ac2051c17358d6662728a2a3c397cd5e15867e..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/heart/__init__.py
+++ /dev/null
@@ -1,10 +0,0 @@
-#! /usr/bin/env python
-# Last Change: Mon Jul 09 06:00 PM 2007 J
-import data as _heart
-__doc__     = _heart.DESCRSHORT
-copyright   = _heart.COPYRIGHT
-source      = _heart.SOURCE
-
-load        = _heart.load
-
-all = ['load', 'copyright', 'source']
diff --git a/scikits/learn/datasets/heart/data.py b/scikits/learn/datasets/heart/data.py
deleted file mode 100644
index 6fc00b199d415a4cf94c0a6a338231d6ce447c36..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/heart/data.py
+++ /dev/null
@@ -1,100 +0,0 @@
-#! /usr/bin/env python
-# -*- coding: utf-8 -*-
-# Last Change: Mon Jul 09 03:00 PM 2007 J
-
-# The code and descriptive text is copyrighted and offered under the terms of
-# the BSD License from the authors; see below. However, the actual dataset may
-# have a different origin and intellectual property status. See the SOURCE and
-# COPYRIGHT variables for this information.
-
-# Copyright (c) 2007 David Cournapeau <cournape@gmail.com>
-#
-# All rights reserved.
-#
-# Redistribution and use in source and binary forms, with or without
-# modification, are permitted provided that the following conditions are
-# met:
-#
-#     * Redistributions of source code must retain the above copyright
-#       notice, this list of conditions and the following disclaimer.
-#     * Redistributions in binary form must reproduce the above copyright
-#       notice, this list of conditions and the following disclaimer in
-#       the documentation and/or other materials provided with the
-#       distribution.
-#     * Neither the author nor the names of any contributors may be used
-#       to endorse or promote products derived from this software without
-#       specific prior written permission.
-#
-# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
-# TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
-# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
-# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
-# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
-# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
-# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
-# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
-# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
-# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
-"""Iris dataset."""
-
-__docformat__ = 'restructuredtext'
-
-COPYRIGHT   = """See SOURCE. """
-TITLE       = "Heart disease dataset"
-SOURCE      = """http://www.liacc.up.pt/ML/old/statlog/datasets.html"""
-
-DESCRSHORT  = """Heart disease of 270 patients with 13 corresponding features."""
-
-DESCRLONG   = DESCRSHORT
-
-NOTE        = """
-Number of Instances: 270 (150 for class has heart disease, 12- for no heart disease).
-
-Number of Attributes: 13.
-
-Attribute Information:
-
-    - age
-    - sex
-    - chest pain type (4 values)
-    - resting blood pressure
-    - serum cholestoral in mg/dl
-    - fasting blood sugar > 120 mg/dl
-    - resting electrocardiographic results (values 0,1,2)
-    - maximum heart rate achieved
-    - exercise induced angina
-    - oldpeak = ST depression induced by exercise relative to rest
-    - the slope of the peak exercise ST segment
-    - number of major vessels (0-3) colored by flourosopy
-    - thal: 3 = normal; 6 = fixed defect; 7 = reversable defect 
-
-Missing Attribute Values: None
-
-Attributes types:
-
-    - Real 1,4,5,8,10,12
-    - Ordered:11,
-    - Binary: 2,6,9
-    - Nominal:7,3,13
-
-Class Distribution: 33.3% for each of 3 classes.
-"""
-
-def load():
-    """load the heart data and returns them.
-    
-    :returns:
-        data: recordarray
-            a record array of the data.
-    """
-    raise NotImplementedError("This dataset is not available yet, sorry")
-    import numpy
-    descr = [('age', numpy.int), ('sex', numpy.int),
-            ('chest pain', numpy.int), ('resting blood pressure', numpy.int),
-            ('serum cholesterol', numpy.float), ('high fasting blood sugar', numpy.int),
-            ('resting ECG', numpy.int), ('maximum heart rate', numpy.float),
-            ('angina', numpy.int), ('oldpeak', numpy.float),
-            ('slope', numpy.int), ('major vessels colored', numpy.int),
-            ('thal', numpy.int)]
diff --git a/scikits/learn/datasets/heart/heart.py b/scikits/learn/datasets/heart/heart.py
deleted file mode 100644
index ebaabc55628ddb8a19167928ee2f4a0f0b0f9717..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/heart/heart.py
+++ /dev/null
@@ -1,370 +0,0 @@
-# Autogenerated by convert.py at Mon, 09 Jul 2007 05:57:46 +0000
-
-Age = ['70.0', '67.0', '57.0', '64.0', '74.0', '65.0', '56.0', '59.0', '60.0',
-'63.0', '59.0', '53.0', '44.0', '61.0', '57.0', '71.0', '46.0', '53.0', '64.0',
-'40.0', '67.0', '48.0', '43.0', '47.0', '54.0', '48.0', '46.0', '51.0', '58.0',
-'71.0', '57.0', '66.0', '37.0', '59.0', '50.0', '48.0', '61.0', '59.0', '42.0',
-'48.0', '40.0', '62.0', '44.0', '46.0', '59.0', '58.0', '49.0', '44.0', '66.0',
-'65.0', '42.0', '52.0', '65.0', '63.0', '45.0', '41.0', '61.0', '60.0', '59.0',
-'62.0', '57.0', '51.0', '44.0', '60.0', '63.0', '57.0', '51.0', '58.0', '44.0',
-'47.0', '61.0', '57.0', '70.0', '76.0', '67.0', '45.0', '45.0', '39.0', '42.0',
-'56.0', '58.0', '35.0', '58.0', '41.0', '57.0', '42.0', '62.0', '59.0', '41.0',
-'50.0', '59.0', '61.0', '54.0', '54.0', '52.0', '47.0', '66.0', '58.0', '64.0',
-'50.0', '44.0', '67.0', '49.0', '57.0', '63.0', '48.0', '51.0', '60.0', '59.0',
-'45.0', '55.0', '41.0', '60.0', '54.0', '42.0', '49.0', '46.0', '56.0', '66.0',
-'56.0', '49.0', '54.0', '57.0', '65.0', '54.0', '54.0', '62.0', '52.0', '52.0',
-'60.0', '63.0', '66.0', '42.0', '64.0', '54.0', '46.0', '67.0', '56.0', '34.0',
-'57.0', '64.0', '59.0', '50.0', '51.0', '54.0', '53.0', '52.0', '40.0', '58.0',
-'41.0', '41.0', '50.0', '54.0', '64.0', '51.0', '46.0', '55.0', '45.0', '56.0',
-'66.0', '38.0', '62.0', '55.0', '58.0', '43.0', '64.0', '50.0', '53.0', '45.0',
-'65.0', '69.0', '69.0', '67.0', '68.0', '34.0', '62.0', '51.0', '46.0', '67.0',
-'50.0', '42.0', '56.0', '41.0', '42.0', '53.0', '43.0', '56.0', '52.0', '62.0',
-'70.0', '54.0', '70.0', '54.0', '35.0', '48.0', '55.0', '58.0', '54.0', '69.0',
-'77.0', '68.0', '58.0', '60.0', '51.0', '55.0', '52.0', '60.0', '58.0', '64.0',
-'37.0', '59.0', '51.0', '43.0', '58.0', '29.0', '41.0', '63.0', '51.0', '54.0',
-'44.0', '54.0', '65.0', '57.0', '63.0', '35.0', '41.0', '62.0', '43.0', '58.0',
-'52.0', '61.0', '39.0', '45.0', '52.0', '62.0', '62.0', '53.0', '43.0', '47.0',
-'52.0', '68.0', '39.0', '53.0', '62.0', '51.0', '60.0', '65.0', '65.0', '60.0',
-'60.0', '54.0', '44.0', '44.0', '51.0', '59.0', '71.0', '61.0', '55.0', '64.0',
-'43.0', '58.0', '60.0', '58.0', '49.0', '48.0', '52.0', '44.0', '56.0', '57.0',
-'67.0']
-
-Sex = ['1.0', '0.0', '1.0', '1.0', '0.0', '1.0', '1.0', '1.0', '1.0', '0.0',
-'1.0', '1.0', '1.0', '1.0', '0.0', '0.0', '1.0', '1.0', '1.0', '1.0', '1.0',
-'1.0', '1.0', '1.0', '0.0', '0.0', '0.0', '0.0', '1.0', '0.0', '1.0', '1.0',
-'0.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '0.0', '1.0',
-'1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '0.0', '1.0', '1.0', '0.0', '0.0',
-'0.0', '0.0', '1.0', '0.0', '0.0', '1.0', '1.0', '0.0', '1.0', '0.0', '1.0',
-'1.0', '1.0', '0.0', '0.0', '1.0', '1.0', '0.0', '1.0', '0.0', '0.0', '1.0',
-'1.0', '0.0', '0.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0',
-'1.0', '0.0', '1.0', '1.0', '0.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0',
-'0.0', '0.0', '0.0', '1.0', '0.0', '1.0', '1.0', '1.0', '1.0', '0.0', '1.0',
-'0.0', '0.0', '1.0', '0.0', '0.0', '1.0', '0.0', '1.0', '0.0', '0.0', '1.0',
-'1.0', '1.0', '1.0', '0.0', '1.0', '0.0', '1.0', '0.0', '1.0', '1.0', '0.0',
-'1.0', '1.0', '1.0', '1.0', '0.0', '0.0', '1.0', '0.0', '1.0', '1.0', '1.0',
-'1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '0.0', '1.0', '0.0', '0.0',
-'0.0', '0.0', '0.0', '1.0', '1.0', '1.0', '0.0', '1.0', '0.0', '1.0', '1.0',
-'1.0', '0.0', '0.0', '1.0', '0.0', '1.0', '1.0', '1.0', '1.0', '0.0', '1.0',
-'0.0', '1.0', '1.0', '1.0', '1.0', '1.0', '0.0', '1.0', '0.0', '1.0', '1.0',
-'1.0', '1.0', '0.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '0.0', '0.0',
-'0.0', '0.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '0.0', '1.0',
-'1.0', '1.0', '1.0', '1.0', '0.0', '1.0', '1.0', '0.0', '0.0', '1.0', '1.0',
-'1.0', '1.0', '1.0', '1.0', '1.0', '0.0', '1.0', '0.0', '0.0', '0.0', '1.0',
-'0.0', '1.0', '1.0', '1.0', '1.0', '0.0', '0.0', '1.0', '1.0', '1.0', '1.0',
-'1.0', '0.0', '0.0', '0.0', '1.0', '1.0', '0.0', '1.0', '1.0', '1.0', '1.0',
-'1.0', '1.0', '1.0', '0.0', '1.0', '1.0', '1.0', '1.0', '0.0', '1.0', '1.0',
-'1.0', '1.0', '1.0', '1.0', '0.0', '1.0', '1.0']
-
-ChestPain = ['4.0', '3.0', '2.0', '4.0', '2.0', '4.0', '3.0', '4.0', '4.0',
-'4.0', '4.0', '4.0', '3.0', '1.0', '4.0', '4.0', '4.0', '4.0', '1.0', '1.0',
-'4.0', '2.0', '4.0', '4.0', '2.0', '3.0', '4.0', '3.0', '3.0', '3.0', '3.0',
-'4.0', '3.0', '4.0', '4.0', '4.0', '4.0', '1.0', '3.0', '4.0', '4.0', '4.0',
-'3.0', '2.0', '3.0', '3.0', '3.0', '4.0', '2.0', '4.0', '4.0', '2.0', '3.0',
-'2.0', '2.0', '2.0', '4.0', '3.0', '4.0', '2.0', '3.0', '4.0', '3.0', '1.0',
-'1.0', '4.0', '4.0', '2.0', '3.0', '3.0', '4.0', '4.0', '2.0', '3.0', '4.0',
-'4.0', '4.0', '3.0', '3.0', '2.0', '4.0', '4.0', '4.0', '3.0', '4.0', '1.0',
-'2.0', '1.0', '2.0', '4.0', '2.0', '4.0', '4.0', '4.0', '4.0', '4.0', '4.0',
-'4.0', '3.0', '2.0', '3.0', '4.0', '4.0', '4.0', '4.0', '4.0', '3.0', '4.0',
-'4.0', '2.0', '4.0', '2.0', '4.0', '3.0', '2.0', '2.0', '4.0', '4.0', '1.0',
-'4.0', '3.0', '4.0', '4.0', '3.0', '3.0', '3.0', '4.0', '3.0', '2.0', '4.0',
-'4.0', '4.0', '4.0', '4.0', '3.0', '3.0', '3.0', '4.0', '2.0', '4.0', '4.0',
-'4.0', '3.0', '1.0', '2.0', '4.0', '4.0', '4.0', '3.0', '3.0', '3.0', '3.0',
-'3.0', '4.0', '3.0', '2.0', '4.0', '2.0', '1.0', '4.0', '1.0', '4.0', '2.0',
-'4.0', '4.0', '4.0', '4.0', '3.0', '4.0', '1.0', '1.0', '3.0', '4.0', '3.0',
-'1.0', '4.0', '4.0', '3.0', '4.0', '3.0', '3.0', '4.0', '4.0', '4.0', '3.0',
-'3.0', '4.0', '4.0', '4.0', '3.0', '4.0', '4.0', '2.0', '4.0', '3.0', '2.0',
-'4.0', '3.0', '1.0', '4.0', '3.0', '4.0', '4.0', '4.0', '4.0', '1.0', '3.0',
-'3.0', '3.0', '3.0', '1.0', '3.0', '3.0', '4.0', '2.0', '2.0', '3.0', '3.0',
-'3.0', '2.0', '4.0', '4.0', '3.0', '4.0', '4.0', '2.0', '3.0', '4.0', '1.0',
-'1.0', '4.0', '4.0', '4.0', '4.0', '3.0', '4.0', '4.0', '4.0', '3.0', '2.0',
-'3.0', '3.0', '4.0', '4.0', '3.0', '4.0', '4.0', '3.0', '3.0', '4.0', '4.0',
-'2.0', '4.0', '3.0', '3.0', '2.0', '3.0', '4.0', '3.0', '4.0', '3.0', '4.0',
-'2.0', '2.0', '2.0', '3.0', '2.0', '2.0', '4.0', '4.0']
-
-RestingBloodPressure = ['130.0', '115.0', '124.0', '128.0', '120.0', '120.0',
-'130.0', '110.0', '140.0', '150.0', '135.0', '142.0', '140.0', '134.0',
-'128.0', '112.0', '140.0', '140.0', '110.0', '140.0', '120.0', '130.0',
-'115.0', '112.0', '132.0', '130.0', '138.0', '120.0', '112.0', '110.0',
-'128.0', '160.0', '120.0', '170.0', '144.0', '130.0', '140.0', '160.0',
-'130.0', '122.0', '152.0', '124.0', '130.0', '101.0', '126.0', '140.0',
-'118.0', '110.0', '160.0', '150.0', '136.0', '128.0', '140.0', '140.0',
-'130.0', '105.0', '138.0', '120.0', '174.0', '120.0', '150.0', '130.0',
-'120.0', '150.0', '145.0', '150.0', '140.0', '136.0', '118.0', '108.0',
-'120.0', '120.0', '156.0', '140.0', '106.0', '142.0', '104.0', '94.0', '120.0',
-'120.0', '146.0', '120.0', '150.0', '130.0', '110.0', '148.0', '128.0',
-'178.0', '126.0', '150.0', '140.0', '130.0', '124.0', '110.0', '125.0',
-'110.0', '120.0', '100.0', '140.0', '120.0', '108.0', '120.0', '130.0',
-'165.0', '130.0', '124.0', '100.0', '150.0', '140.0', '112.0', '180.0',
-'110.0', '158.0', '135.0', '120.0', '134.0', '120.0', '200.0', '150.0',
-'130.0', '120.0', '122.0', '152.0', '160.0', '125.0', '160.0', '120.0',
-'136.0', '134.0', '117.0', '108.0', '112.0', '140.0', '120.0', '150.0',
-'142.0', '152.0', '125.0', '118.0', '132.0', '145.0', '138.0', '140.0',
-'125.0', '192.0', '123.0', '112.0', '110.0', '132.0', '112.0', '112.0',
-'120.0', '108.0', '130.0', '130.0', '105.0', '140.0', '128.0', '120.0',
-'178.0', '120.0', '150.0', '130.0', '128.0', '110.0', '180.0', '110.0',
-'130.0', '138.0', '138.0', '160.0', '140.0', '100.0', '120.0', '118.0',
-'138.0', '140.0', '150.0', '125.0', '129.0', '120.0', '134.0', '110.0',
-'102.0', '130.0', '130.0', '132.0', '108.0', '140.0', '160.0', '140.0',
-'145.0', '108.0', '126.0', '124.0', '135.0', '100.0', '110.0', '140.0',
-'125.0', '118.0', '125.0', '125.0', '140.0', '160.0', '152.0', '102.0',
-'105.0', '125.0', '130.0', '170.0', '125.0', '122.0', '128.0', '130.0',
-'130.0', '135.0', '94.0', '120.0', '120.0', '110.0', '135.0', '150.0', '130.0',
-'138.0', '135.0', '130.0', '132.0', '150.0', '118.0', '145.0', '118.0',
-'115.0', '128.0', '130.0', '160.0', '138.0', '120.0', '138.0', '120.0',
-'180.0', '140.0', '130.0', '140.0', '140.0', '130.0', '110.0', '155.0',
-'140.0', '145.0', '120.0', '130.0', '112.0', '110.0', '150.0', '160.0',
-'150.0', '132.0', '140.0', '150.0', '120.0', '130.0', '120.0', '130.0',
-'110.0', '172.0', '120.0', '140.0', '140.0', '160.0']
-
-SerumCholesterol = ['322.0', '564.0', '261.0', '263.0', '269.0', '177.0',
-'256.0', '239.0', '293.0', '407.0', '234.0', '226.0', '235.0', '234.0',
-'303.0', '149.0', '311.0', '203.0', '211.0', '199.0', '229.0', '245.0',
-'303.0', '204.0', '288.0', '275.0', '243.0', '295.0', '230.0', '265.0',
-'229.0', '228.0', '215.0', '326.0', '200.0', '256.0', '207.0', '273.0',
-'180.0', '222.0', '223.0', '209.0', '233.0', '197.0', '218.0', '211.0',
-'149.0', '197.0', '246.0', '225.0', '315.0', '205.0', '417.0', '195.0',
-'234.0', '198.0', '166.0', '178.0', '249.0', '281.0', '126.0', '305.0',
-'226.0', '240.0', '233.0', '276.0', '261.0', '319.0', '242.0', '243.0',
-'260.0', '354.0', '245.0', '197.0', '223.0', '309.0', '208.0', '199.0',
-'209.0', '236.0', '218.0', '198.0', '270.0', '214.0', '201.0', '244.0',
-'208.0', '270.0', '306.0', '243.0', '221.0', '330.0', '266.0', '206.0',
-'212.0', '275.0', '302.0', '234.0', '313.0', '244.0', '141.0', '237.0',
-'269.0', '289.0', '254.0', '274.0', '222.0', '258.0', '177.0', '160.0',
-'327.0', '235.0', '305.0', '304.0', '295.0', '271.0', '249.0', '288.0',
-'226.0', '283.0', '188.0', '286.0', '274.0', '360.0', '273.0', '201.0',
-'267.0', '196.0', '201.0', '230.0', '269.0', '212.0', '226.0', '246.0',
-'232.0', '177.0', '277.0', '249.0', '210.0', '207.0', '212.0', '271.0',
-'233.0', '213.0', '283.0', '282.0', '230.0', '167.0', '224.0', '268.0',
-'250.0', '219.0', '267.0', '303.0', '256.0', '204.0', '217.0', '308.0',
-'193.0', '228.0', '231.0', '244.0', '262.0', '259.0', '211.0', '325.0',
-'254.0', '197.0', '236.0', '282.0', '234.0', '254.0', '299.0', '211.0',
-'182.0', '294.0', '298.0', '231.0', '254.0', '196.0', '240.0', '409.0',
-'172.0', '265.0', '246.0', '315.0', '184.0', '233.0', '394.0', '269.0',
-'239.0', '174.0', '309.0', '282.0', '255.0', '250.0', '248.0', '214.0',
-'239.0', '304.0', '277.0', '300.0', '258.0', '299.0', '289.0', '298.0',
-'318.0', '240.0', '309.0', '250.0', '288.0', '245.0', '213.0', '216.0',
-'204.0', '204.0', '252.0', '227.0', '258.0', '220.0', '239.0', '254.0',
-'168.0', '330.0', '183.0', '203.0', '263.0', '341.0', '283.0', '186.0',
-'307.0', '219.0', '260.0', '255.0', '231.0', '164.0', '234.0', '177.0',
-'257.0', '325.0', '274.0', '321.0', '264.0', '268.0', '308.0', '253.0',
-'248.0', '269.0', '185.0', '282.0', '188.0', '219.0', '290.0', '175.0',
-'212.0', '302.0', '243.0', '353.0', '335.0', '247.0', '340.0', '206.0',
-'284.0', '266.0', '229.0', '199.0', '263.0', '294.0', '192.0', '286.0']
-
-FastingBloodSugar = ['0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '1.0', '0.0',
-'0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '1.0', '0.0',
-'0.0', '0.0', '0.0', '0.0', '0.0', '1.0', '0.0', '0.0', '0.0', '0.0', '1.0',
-'0.0', '0.0', '0.0', '0.0', '0.0', '1.0', '0.0', '0.0', '0.0', '0.0', '0.0',
-'0.0', '0.0', '1.0', '1.0', '1.0', '0.0', '0.0', '0.0', '0.0', '0.0', '1.0',
-'1.0', '0.0', '0.0', '0.0', '0.0', '1.0', '0.0', '0.0', '1.0', '0.0', '0.0',
-'0.0', '1.0', '0.0', '0.0', '1.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0',
-'0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0',
-'0.0', '1.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0',
-'0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '1.0', '0.0', '0.0', '0.0',
-'0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '1.0', '0.0', '0.0', '0.0', '1.0',
-'0.0', '1.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0',
-'1.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '1.0', '0.0', '0.0',
-'0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0',
-'0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '1.0', '0.0', '0.0',
-'0.0', '0.0', '0.0', '0.0', '0.0', '1.0', '0.0', '1.0', '1.0', '0.0', '0.0',
-'0.0', '0.0', '1.0', '0.0', '0.0', '1.0', '0.0', '1.0', '0.0', '0.0', '0.0',
-'1.0', '0.0', '0.0', '1.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '1.0',
-'0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '1.0',
-'0.0', '0.0', '0.0', '0.0', '0.0', '1.0', '0.0', '0.0', '0.0', '0.0', '0.0',
-'0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '1.0', '0.0', '0.0', '0.0', '1.0',
-'1.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0',
-'0.0', '1.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0',
-'0.0', '0.0', '0.0', '0.0', '1.0', '0.0', '1.0', '0.0', '0.0', '0.0', '0.0',
-'0.0', '0.0', '0.0', '0.0', '1.0', '0.0', '0.0', '0.0', '0.0']
-
-RestECGResults = ['2.0', '2.0', '0.0', '0.0', '2.0', '0.0', '2.0', '2.0',
-'2.0', '2.0', '0.0', '2.0', '2.0', '0.0', '2.0', '0.0', '0.0', '2.0', '2.0',
-'0.0', '2.0', '2.0', '0.0', '0.0', '2.0', '0.0', '2.0', '2.0', '2.0', '2.0',
-'2.0', '2.0', '0.0', '2.0', '2.0', '2.0', '2.0', '2.0', '0.0', '2.0', '0.0',
-'0.0', '0.0', '0.0', '0.0', '2.0', '2.0', '2.0', '0.0', '2.0', '0.0', '0.0',
-'2.0', '0.0', '2.0', '0.0', '2.0', '0.0', '0.0', '2.0', '0.0', '0.0', '0.0',
-'0.0', '2.0', '2.0', '2.0', '2.0', '0.0', '0.0', '0.0', '0.0', '2.0', '1.0',
-'0.0', '2.0', '2.0', '0.0', '0.0', '0.0', '0.0', '0.0', '2.0', '2.0', '0.0',
-'2.0', '2.0', '2.0', '0.0', '2.0', '0.0', '2.0', '2.0', '2.0', '0.0', '2.0',
-'2.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '2.0', '2.0', '2.0', '0.0',
-'2.0', '0.0', '0.0', '1.0', '0.0', '2.0', '0.0', '0.0', '0.0', '2.0', '2.0',
-'0.0', '2.0', '0.0', '2.0', '0.0', '2.0', '2.0', '0.0', '0.0', '2.0', '0.0',
-'0.0', '0.0', '2.0', '0.0', '2.0', '2.0', '2.0', '0.0', '2.0', '0.0', '0.0',
-'2.0', '2.0', '0.0', '2.0', '2.0', '0.0', '0.0', '2.0', '2.0', '2.0', '0.0',
-'0.0', '2.0', '0.0', '2.0', '0.0', '0.0', '2.0', '2.0', '0.0', '0.0', '0.0',
-'0.0', '2.0', '0.0', '0.0', '2.0', '2.0', '2.0', '2.0', '2.0', '2.0', '2.0',
-'2.0', '2.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '2.0', '2.0', '2.0',
-'2.0', '0.0', '2.0', '0.0', '2.0', '0.0', '0.0', '0.0', '0.0', '2.0', '0.0',
-'2.0', '2.0', '0.0', '0.0', '2.0', '0.0', '2.0', '2.0', '0.0', '2.0', '0.0',
-'0.0', '2.0', '0.0', '0.0', '2.0', '2.0', '0.0', '2.0', '2.0', '2.0', '2.0',
-'0.0', '2.0', '0.0', '0.0', '2.0', '0.0', '2.0', '0.0', '0.0', '0.0', '2.0',
-'2.0', '2.0', '2.0', '0.0', '2.0', '0.0', '0.0', '2.0', '2.0', '2.0', '2.0',
-'0.0', '2.0', '2.0', '2.0', '2.0', '2.0', '0.0', '2.0', '0.0', '2.0', '2.0',
-'0.0', '2.0', '2.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0',
-'2.0', '2.0', '0.0', '0.0', '0.0', '0.0', '2.0', '0.0', '2.0']
-
-MaximumHearRate = ['109.0', '160.0', '141.0', '105.0', '121.0', '140.0',
-'142.0', '142.0', '170.0', '154.0', '161.0', '111.0', '180.0', '145.0',
-'159.0', '125.0', '120.0', '155.0', '144.0', '178.0', '129.0', '180.0',
-'181.0', '143.0', '159.0', '139.0', '152.0', '157.0', '165.0', '130.0',
-'150.0', '138.0', '170.0', '140.0', '126.0', '150.0', '138.0', '125.0',
-'150.0', '186.0', '181.0', '163.0', '179.0', '156.0', '134.0', '165.0',
-'126.0', '177.0', '120.0', '114.0', '125.0', '184.0', '157.0', '179.0',
-'175.0', '168.0', '125.0', '96.0', '143.0', '103.0', '173.0', '142.0', '169.0',
-'171.0', '150.0', '112.0', '186.0', '152.0', '149.0', '152.0', '140.0',
-'163.0', '143.0', '116.0', '142.0', '147.0', '148.0', '179.0', '173.0',
-'178.0', '105.0', '130.0', '111.0', '168.0', '126.0', '178.0', '140.0',
-'145.0', '163.0', '128.0', '164.0', '169.0', '109.0', '108.0', '168.0',
-'118.0', '151.0', '156.0', '133.0', '162.0', '175.0', '71.0', '163.0', '124.0',
-'147.0', '166.0', '143.0', '157.0', '162.0', '138.0', '117.0', '153.0',
-'161.0', '170.0', '162.0', '162.0', '144.0', '133.0', '114.0', '103.0',
-'139.0', '116.0', '88.0', '151.0', '152.0', '163.0', '99.0', '169.0', '158.0',
-'160.0', '169.0', '132.0', '178.0', '96.0', '165.0', '160.0', '172.0', '144.0',
-'192.0', '168.0', '132.0', '182.0', '163.0', '125.0', '195.0', '95.0', '160.0',
-'114.0', '173.0', '172.0', '179.0', '158.0', '167.0', '122.0', '149.0',
-'172.0', '111.0', '170.0', '162.0', '165.0', '182.0', '154.0', '155.0',
-'130.0', '161.0', '154.0', '159.0', '152.0', '152.0', '174.0', '131.0',
-'146.0', '125.0', '115.0', '174.0', '106.0', '122.0', '147.0', '163.0',
-'163.0', '194.0', '150.0', '158.0', '122.0', '173.0', '162.0', '105.0',
-'147.0', '157.0', '112.0', '160.0', '125.0', '156.0', '156.0', '175.0',
-'161.0', '122.0', '158.0', '151.0', '162.0', '151.0', '171.0', '141.0',
-'173.0', '145.0', '178.0', '160.0', '154.0', '131.0', '187.0', '159.0',
-'166.0', '165.0', '131.0', '202.0', '172.0', '172.0', '154.0', '147.0',
-'170.0', '126.0', '127.0', '174.0', '132.0', '182.0', '132.0', '97.0', '136.0',
-'162.0', '190.0', '146.0', '140.0', '185.0', '161.0', '146.0', '145.0',
-'160.0', '120.0', '156.0', '172.0', '150.0', '182.0', '143.0', '160.0',
-'142.0', '144.0', '158.0', '148.0', '155.0', '142.0', '113.0', '188.0',
-'153.0', '123.0', '157.0', '162.0', '137.0', '132.0', '158.0', '171.0',
-'172.0', '132.0', '160.0', '171.0', '168.0', '162.0', '173.0', '153.0',
-'148.0', '108.0']
-
-ExerciceInducedAngina = ['0.0', '0.0', '0.0', '1.0', '1.0', '0.0', '1.0',
-'1.0', '0.0', '0.0', '0.0', '1.0', '0.0', '0.0', '0.0', '0.0', '1.0', '1.0',
-'1.0', '1.0', '1.0', '0.0', '0.0', '0.0', '1.0', '0.0', '1.0', '0.0', '0.0',
-'0.0', '0.0', '0.0', '0.0', '1.0', '1.0', '1.0', '1.0', '0.0', '0.0', '0.0',
-'0.0', '0.0', '1.0', '0.0', '0.0', '0.0', '0.0', '0.0', '1.0', '0.0', '1.0',
-'0.0', '0.0', '0.0', '0.0', '0.0', '1.0', '0.0', '1.0', '0.0', '0.0', '1.0',
-'0.0', '0.0', '0.0', '1.0', '1.0', '0.0', '0.0', '0.0', '1.0', '1.0', '0.0',
-'0.0', '0.0', '1.0', '1.0', '0.0', '0.0', '0.0', '0.0', '1.0', '1.0', '0.0',
-'1.0', '0.0', '0.0', '0.0', '0.0', '0.0', '1.0', '0.0', '1.0', '1.0', '0.0',
-'1.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0',
-'1.0', '0.0', '1.0', '0.0', '1.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0',
-'1.0', '0.0', '1.0', '0.0', '1.0', '1.0', '0.0', '0.0', '0.0', '1.0', '0.0',
-'0.0', '1.0', '1.0', '1.0', '0.0', '1.0', '0.0', '1.0', '0.0', '1.0', '0.0',
-'1.0', '0.0', '0.0', '0.0', '1.0', '0.0', '1.0', '0.0', '1.0', '0.0', '1.0',
-'0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '1.0', '0.0', '0.0', '1.0', '1.0',
-'1.0', '0.0', '1.0', '0.0', '1.0', '0.0', '0.0', '1.0', '0.0', '0.0', '0.0',
-'1.0', '0.0', '0.0', '0.0', '1.0', '0.0', '0.0', '0.0', '0.0', '1.0', '0.0',
-'0.0', '0.0', '0.0', '1.0', '0.0', '0.0', '1.0', '0.0', '1.0', '0.0', '1.0',
-'0.0', '0.0', '0.0', '0.0', '0.0', '1.0', '0.0', '0.0', '1.0', '1.0', '1.0',
-'0.0', '0.0', '1.0', '1.0', '0.0', '0.0', '0.0', '0.0', '1.0', '0.0', '0.0',
-'0.0', '1.0', '0.0', '0.0', '1.0', '0.0', '0.0', '1.0', '0.0', '0.0', '0.0',
-'1.0', '0.0', '0.0', '1.0', '0.0', '0.0', '1.0', '0.0', '0.0', '0.0', '1.0',
-'0.0', '0.0', '1.0', '0.0', '0.0', '0.0', '0.0', '1.0', '0.0', '0.0', '0.0',
-'1.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '1.0', '1.0', '0.0', '0.0',
-'0.0', '1.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '1.0']
-
-OldPeak = ['2.4', '1.6', '0.3', '0.2', '0.2', '0.4', '0.6', '1.2', '1.2',
-'4.0', '0.5', '0.0', '0.0', '2.6', '0.0', '1.6', '1.8', '3.1', '1.8', '1.4',
-'2.6', '0.2', '1.2', '0.1', '0.0', '0.2', '0.0', '0.6', '2.5', '0.0', '0.4',
-'2.3', '0.0', '3.4', '0.9', '0.0', '1.9', '0.0', '0.0', '0.0', '0.0', '0.0',
-'0.4', '0.0', '2.2', '0.0', '0.8', '0.0', '0.0', '1.0', '1.8', '0.0', '0.8',
-'0.0', '0.6', '0.0', '3.6', '0.0', '0.0', '1.4', '0.2', '1.2', '0.0', '0.9',
-'2.3', '0.6', '0.0', '0.0', '0.3', '0.0', '3.6', '0.6', '0.0', '1.1', '0.3',
-'0.0', '3.0', '0.0', '0.0', '0.8', '2.0', '1.6', '0.8', '2.0', '1.5', '0.8',
-'0.0', '4.2', '0.0', '2.6', '0.0', '0.0', '2.2', '0.0', '1.0', '1.0', '0.4',
-'0.1', '0.2', '1.1', '0.6', '1.0', '0.0', '1.0', '1.4', '0.5', '1.2', '2.6',
-'0.0', '0.0', '3.4', '0.0', '0.0', '0.0', '0.0', '0.0', '0.8', '4.0', '2.6',
-'1.6', '2.0', '3.2', '1.2', '0.8', '0.5', '0.0', '1.8', '0.1', '0.8', '1.4',
-'1.8', '0.1', '0.0', '2.2', '1.6', '1.4', '0.0', '1.2', '0.7', '0.0', '2.0',
-'0.0', '0.6', '1.4', '0.0', '2.0', '0.0', '2.0', '3.2', '0.0', '0.0', '1.6',
-'0.0', '2.0', '0.5', '0.0', '5.6', '0.0', '1.9', '1.0', '3.8', '1.4', '0.0',
-'3.0', '0.0', '0.0', '0.0', '1.2', '0.2', '1.4', '0.1', '2.0', '0.9', '1.5',
-'0.0', '1.9', '4.2', '3.6', '0.2', '0.0', '0.8', '1.9', '0.0', '0.6', '0.0',
-'1.9', '2.1', '0.1', '1.2', '2.9', '1.2', '2.6', '0.0', '0.0', '0.0', '1.4',
-'1.0', '1.6', '1.8', '0.0', '1.0', '0.0', '2.8', '1.6', '0.8', '1.2', '0.0',
-'0.6', '1.8', '3.5', '0.2', '2.4', '0.2', '2.2', '0.0', '1.4', '0.0', '0.0',
-'0.4', '0.0', '2.8', '2.8', '1.6', '1.8', '1.4', '0.0', '1.2', '3.0', '1.0',
-'0.0', '1.0', '1.2', '0.0', '0.0', '1.8', '6.2', '0.0', '2.5', '0.0', '0.2',
-'1.6', '0.0', '0.4', '3.6', '1.5', '1.4', '0.6', '0.8', '3.0', '2.8', '1.4',
-'0.0', '0.0', '0.6', '1.6', '0.4', '1.0', '1.2', '0.0', '1.5', '0.0', '2.4',
-'1.8', '0.6', '1.0', '0.5', '0.0', '1.3', '0.4', '1.5']
-
-SlopePeak = ['2.0', '2.0', '1.0', '2.0', '1.0', '1.0', '2.0', '2.0', '2.0',
-'2.0', '2.0', '1.0', '1.0', '2.0', '1.0', '2.0', '2.0', '3.0', '2.0', '1.0',
-'2.0', '2.0', '2.0', '1.0', '1.0', '1.0', '2.0', '1.0', '2.0', '1.0', '2.0',
-'1.0', '1.0', '3.0', '2.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0',
-'1.0', '1.0', '2.0', '1.0', '1.0', '1.0', '2.0', '2.0', '2.0', '1.0', '1.0',
-'1.0', '2.0', '1.0', '2.0', '1.0', '2.0', '2.0', '1.0', '2.0', '1.0', '1.0',
-'3.0', '2.0', '1.0', '1.0', '2.0', '1.0', '2.0', '1.0', '1.0', '2.0', '1.0',
-'2.0', '2.0', '1.0', '2.0', '1.0', '2.0', '2.0', '1.0', '2.0', '2.0', '1.0',
-'1.0', '3.0', '1.0', '2.0', '1.0', '1.0', '2.0', '2.0', '1.0', '2.0', '2.0',
-'1.0', '1.0', '1.0', '2.0', '2.0', '1.0', '2.0', '2.0', '2.0', '2.0', '2.0',
-'1.0', '2.0', '2.0', '1.0', '1.0', '1.0', '1.0', '2.0', '1.0', '3.0', '3.0',
-'3.0', '2.0', '2.0', '2.0', '1.0', '3.0', '1.0', '2.0', '2.0', '1.0', '1.0',
-'2.0', '1.0', '1.0', '3.0', '1.0', '3.0', '1.0', '2.0', '1.0', '1.0', '2.0',
-'1.0', '2.0', '1.0', '1.0', '2.0', '1.0', '2.0', '1.0', '1.0', '1.0', '2.0',
-'1.0', '2.0', '1.0', '1.0', '3.0', '1.0', '2.0', '2.0', '2.0', '2.0', '1.0',
-'2.0', '1.0', '1.0', '1.0', '3.0', '2.0', '2.0', '2.0', '2.0', '2.0', '2.0',
-'1.0', '2.0', '2.0', '2.0', '2.0', '1.0', '3.0', '2.0', '1.0', '2.0', '1.0',
-'1.0', '2.0', '1.0', '2.0', '2.0', '1.0', '3.0', '1.0', '1.0', '1.0', '2.0',
-'2.0', '2.0', '1.0', '1.0', '1.0', '1.0', '2.0', '1.0', '2.0', '2.0', '1.0',
-'2.0', '2.0', '3.0', '2.0', '2.0', '2.0', '2.0', '1.0', '1.0', '1.0', '1.0',
-'2.0', '1.0', '2.0', '2.0', '1.0', '1.0', '1.0', '2.0', '2.0', '2.0', '1.0',
-'2.0', '2.0', '2.0', '1.0', '1.0', '2.0', '3.0', '1.0', '2.0', '1.0', '1.0',
-'2.0', '1.0', '2.0', '3.0', '1.0', '1.0', '1.0', '1.0', '2.0', '2.0', '2.0',
-'1.0', '1.0', '1.0', '1.0', '1.0', '2.0', '2.0', '1.0', '1.0', '1.0', '2.0',
-'2.0', '1.0', '3.0', '1.0', '1.0', '2.0', '2.0', '2.0']
-
-MajorVesselsFlourated = ['3.0', '0.0', '0.0', '1.0', '1.0', '0.0', '1.0',
-'1.0', '2.0', '3.0', '0.0', '0.0', '0.0', '2.0', '1.0', '0.0', '2.0', '0.0',
-'0.0', '0.0', '2.0', '0.0', '0.0', '0.0', '1.0', '0.0', '0.0', '0.0', '1.0',
-'1.0', '1.0', '0.0', '0.0', '0.0', '0.0', '2.0', '1.0', '0.0', '0.0', '0.0',
-'0.0', '0.0', '0.0', '0.0', '1.0', '0.0', '3.0', '1.0', '3.0', '3.0', '0.0',
-'0.0', '1.0', '2.0', '0.0', '1.0', '1.0', '0.0', '0.0', '1.0', '1.0', '0.0',
-'0.0', '0.0', '0.0', '1.0', '0.0', '2.0', '1.0', '0.0', '1.0', '0.0', '0.0',
-'0.0', '2.0', '3.0', '0.0', '0.0', '0.0', '0.0', '1.0', '0.0', '0.0', '0.0',
-'0.0', '2.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '1.0', '1.0', '2.0',
-'1.0', '0.0', '1.0', '0.0', '0.0', '0.0', '0.0', '0.0', '3.0', '1.0', '0.0',
-'0.0', '2.0', '1.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0',
-'2.0', '0.0', '0.0', '3.0', '2.0', '1.0', '0.0', '1.0', '1.0', '2.0', '0.0',
-'1.0', '2.0', '2.0', '1.0', '0.0', '1.0', '0.0', '0.0', '1.0', '1.0', '0.0',
-'0.0', '2.0', '0.0', '1.0', '1.0', '1.0', '2.0', '1.0', '0.0', '2.0', '0.0',
-'0.0', '0.0', '0.0', '2.0', '0.0', '0.0', '0.0', '0.0', '0.0', '2.0', '0.0',
-'0.0', '0.0', '2.0', '0.0', '0.0', '0.0', '0.0', '0.0', '1.0', '1.0', '3.0',
-'2.0', '0.0', '0.0', '3.0', '3.0', '0.0', '2.0', '0.0', '0.0', '2.0', '0.0',
-'0.0', '3.0', '1.0', '1.0', '3.0', '0.0', '1.0', '0.0', '0.0', '0.0', '0.0',
-'2.0', '0.0', '0.0', '0.0', '2.0', '3.0', '1.0', '2.0', '1.0', '0.0', '1.0',
-'0.0', '1.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '3.0', '0.0', '0.0',
-'0.0', '1.0', '0.0', '0.0', '1.0', '1.0', '0.0', '3.0', '0.0', '0.0', '1.0',
-'0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '1.0', '3.0', '3.0', '0.0', '0.0',
-'0.0', '0.0', '0.0', '0.0', '0.0', '2.0', '1.0', '1.0', '2.0', '0.0', '0.0',
-'2.0', '1.0', '0.0', '1.0', '0.0', '0.0', '2.0', '0.0', '1.0', '0.0', '0.0',
-'0.0', '2.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '3.0']
-
-Thal = ['3.0', '7.0', '7.0', '7.0', '3.0', '7.0', '6.0', '7.0', '7.0', '7.0',
-'7.0', '7.0', '3.0', '3.0', '3.0', '3.0', '7.0', '7.0', '3.0', '7.0', '7.0',
-'3.0', '3.0', '3.0', '3.0', '3.0', '3.0', '3.0', '7.0', '3.0', '7.0', '6.0',
-'3.0', '7.0', '7.0', '7.0', '7.0', '3.0', '3.0', '3.0', '7.0', '3.0', '3.0',
-'7.0', '6.0', '3.0', '3.0', '3.0', '6.0', '7.0', '6.0', '3.0', '3.0', '3.0',
-'3.0', '3.0', '3.0', '3.0', '3.0', '7.0', '7.0', '7.0', '3.0', '3.0', '6.0',
-'6.0', '3.0', '3.0', '3.0', '3.0', '7.0', '3.0', '3.0', '3.0', '3.0', '7.0',
-'3.0', '3.0', '3.0', '3.0', '7.0', '7.0', '7.0', '3.0', '6.0', '3.0', '3.0',
-'7.0', '3.0', '7.0', '3.0', '3.0', '7.0', '3.0', '7.0', '3.0', '3.0', '7.0',
-'7.0', '3.0', '3.0', '3.0', '3.0', '7.0', '7.0', '7.0', '3.0', '7.0', '7.0',
-'3.0', '3.0', '3.0', '3.0', '3.0', '3.0', '3.0', '7.0', '7.0', '3.0', '7.0',
-'7.0', '3.0', '7.0', '3.0', '3.0', '3.0', '7.0', '3.0', '3.0', '7.0', '3.0',
-'3.0', '3.0', '3.0', '7.0', '3.0', '3.0', '3.0', '3.0', '7.0', '6.0', '3.0',
-'7.0', '3.0', '7.0', '7.0', '3.0', '7.0', '7.0', '3.0', '3.0', '3.0', '3.0',
-'3.0', '3.0', '3.0', '7.0', '3.0', '7.0', '7.0', '7.0', '3.0', '3.0', '7.0',
-'7.0', '3.0', '3.0', '3.0', '3.0', '3.0', '3.0', '7.0', '3.0', '3.0', '3.0',
-'3.0', '7.0', '3.0', '7.0', '3.0', '7.0', '7.0', '7.0', '3.0', '3.0', '3.0',
-'6.0', '7.0', '3.0', '7.0', '3.0', '7.0', '7.0', '7.0', '3.0', '3.0', '3.0',
-'3.0', '3.0', '3.0', '7.0', '7.0', '7.0', '7.0', '7.0', '7.0', '3.0', '7.0',
-'7.0', '3.0', '7.0', '3.0', '3.0', '7.0', '3.0', '3.0', '3.0', '7.0', '7.0',
-'3.0', '7.0', '7.0', '3.0', '7.0', '3.0', '6.0', '7.0', '7.0', '3.0', '6.0',
-'7.0', '7.0', '3.0', '7.0', '7.0', '7.0', '3.0', '7.0', '3.0', '3.0', '7.0',
-'3.0', '3.0', '3.0', '3.0', '7.0', '6.0', '3.0', '3.0', '7.0', '7.0', '3.0',
-'3.0', '3.0', '3.0', '3.0', '3.0', '7.0', '3.0', '3.0', '3.0', '7.0', '3.0',
-'3.0', '7.0', '7.0', '7.0', '3.0', '6.0', '3.0']
-
diff --git a/scikits/learn/datasets/heart/src/convert.py b/scikits/learn/datasets/heart/src/convert.py
deleted file mode 100755
index a61fbfd81dd44e062e3c1b195165daf2a04f9c29..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/heart/src/convert.py
+++ /dev/null
@@ -1,52 +0,0 @@
-#! /usr/bin/env python
-# Last Change: Mon Jul 09 02:00 PM 2007 J
-
-# This script generates a python file from the txt data
-import time
-import csv
-
-dataname = 'heart'
-f = open(dataname, 'r')
-a = csv.reader(f, delimiter = ' ')
-el = [i for i in a]
-# Remove last value corresponding to empty line in data file
-assert len(el) == 270
-
-age = [i[0] for i in el]
-sex = [i[1] for i in el]
-chpain = [i[2] for i in el]
-resblpress = [i[3] for i in el]
-serhol = [i[4] for i in el]
-fasblsug = [i[5] for i in el]
-resecg = [i[6] for i in el]
-maxheartrate = [i[7] for i in el]
-exindang = [i[8] for i in el]
-oldpk = [i[9] for i in el]
-slpk = [i[10] for i in el]
-nmaj = [i[11] for i in el]
-thal = [i[12] for i in el]
-
-# Write the data in oldfaitful.py
-a = open("heart.py", "w")
-a.write('# Autogenerated by convert.py at %s\n\n' % 
-        time.strftime("%a, %d %b %Y %H:%M:%S +0000", time.gmtime()))
-
-def dump_var(var, varname):
-    import textwrap
-    strvar = varname + " = " + str(var)
-    a.writelines([i + '\n' for i in textwrap.wrap(strvar, 79)])
-    a.write("\n")
-
-dump_var(age, 'Age')
-dump_var(sex, 'Sex')
-dump_var(chpain, 'ChestPain')
-dump_var(resblpress, 'RestingBloodPressure')
-dump_var(serhol, 'SerumCholesterol')
-dump_var(fasblsug, 'FastingBloodSugar')
-dump_var(resecg, 'RestECGResults')
-dump_var(maxheartrate, 'MaximumHearRate')
-dump_var(exindang, 'ExerciceInducedAngina')
-dump_var(oldpk, 'OldPeak')
-dump_var(slpk, 'SlopePeak')
-dump_var(nmaj, 'MajorVesselsFlourated')
-dump_var(thal, 'Thal')
diff --git a/scikits/learn/datasets/heart/src/heart b/scikits/learn/datasets/heart/src/heart
deleted file mode 100644
index 5d17e1692c1eb76ce07da3588852679f6f921a43..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/heart/src/heart
+++ /dev/null
@@ -1,270 +0,0 @@
-70.0 1.0 4.0 130.0 322.0 0.0 2.0 109.0 0.0 2.4 2.0 3.0 3.0 2
-67.0 0.0 3.0 115.0 564.0 0.0 2.0 160.0 0.0 1.6 2.0 0.0 7.0 1
-57.0 1.0 2.0 124.0 261.0 0.0 0.0 141.0 0.0 0.3 1.0 0.0 7.0 2
-64.0 1.0 4.0 128.0 263.0 0.0 0.0 105.0 1.0 0.2 2.0 1.0 7.0 1
-74.0 0.0 2.0 120.0 269.0 0.0 2.0 121.0 1.0 0.2 1.0 1.0 3.0 1
-65.0 1.0 4.0 120.0 177.0 0.0 0.0 140.0 0.0 0.4 1.0 0.0 7.0 1
-56.0 1.0 3.0 130.0 256.0 1.0 2.0 142.0 1.0 0.6 2.0 1.0 6.0 2
-59.0 1.0 4.0 110.0 239.0 0.0 2.0 142.0 1.0 1.2 2.0 1.0 7.0 2
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-61.0 1.0 1.0 134.0 234.0 0.0 0.0 145.0 0.0 2.6 2.0 2.0 3.0 2
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-46.0 0.0 4.0 138.0 243.0 0.0 2.0 152.0 1.0 0.0 2.0 0.0 3.0 1
-51.0 0.0 3.0 120.0 295.0 0.0 2.0 157.0 0.0 0.6 1.0 0.0 3.0 1
-58.0 1.0 3.0 112.0 230.0 0.0 2.0 165.0 0.0 2.5 2.0 1.0 7.0 2
-71.0 0.0 3.0 110.0 265.0 1.0 2.0 130.0 0.0 0.0 1.0 1.0 3.0 1
-57.0 1.0 3.0 128.0 229.0 0.0 2.0 150.0 0.0 0.4 2.0 1.0 7.0 2
-66.0 1.0 4.0 160.0 228.0 0.0 2.0 138.0 0.0 2.3 1.0 0.0 6.0 1
-37.0 0.0 3.0 120.0 215.0 0.0 0.0 170.0 0.0 0.0 1.0 0.0 3.0 1
-59.0 1.0 4.0 170.0 326.0 0.0 2.0 140.0 1.0 3.4 3.0 0.0 7.0 2
-50.0 1.0 4.0 144.0 200.0 0.0 2.0 126.0 1.0 0.9 2.0 0.0 7.0 2
-48.0 1.0 4.0 130.0 256.0 1.0 2.0 150.0 1.0 0.0 1.0 2.0 7.0 2
-61.0 1.0 4.0 140.0 207.0 0.0 2.0 138.0 1.0 1.9 1.0 1.0 7.0 2
-59.0 1.0 1.0 160.0 273.0 0.0 2.0 125.0 0.0 0.0 1.0 0.0 3.0 2
-42.0 1.0 3.0 130.0 180.0 0.0 0.0 150.0 0.0 0.0 1.0 0.0 3.0 1
-48.0 1.0 4.0 122.0 222.0 0.0 2.0 186.0 0.0 0.0 1.0 0.0 3.0 1
-40.0 1.0 4.0 152.0 223.0 0.0 0.0 181.0 0.0 0.0 1.0 0.0 7.0 2
-62.0 0.0 4.0 124.0 209.0 0.0 0.0 163.0 0.0 0.0 1.0 0.0 3.0 1
-44.0 1.0 3.0 130.0 233.0 0.0 0.0 179.0 1.0 0.4 1.0 0.0 3.0 1
-46.0 1.0 2.0 101.0 197.0 1.0 0.0 156.0 0.0 0.0 1.0 0.0 7.0 1
-59.0 1.0 3.0 126.0 218.0 1.0 0.0 134.0 0.0 2.2 2.0 1.0 6.0 2
-58.0 1.0 3.0 140.0 211.0 1.0 2.0 165.0 0.0 0.0 1.0 0.0 3.0 1
-49.0 1.0 3.0 118.0 149.0 0.0 2.0 126.0 0.0 0.8 1.0 3.0 3.0 2
-44.0 1.0 4.0 110.0 197.0 0.0 2.0 177.0 0.0 0.0 1.0 1.0 3.0 2
-66.0 1.0 2.0 160.0 246.0 0.0 0.0 120.0 1.0 0.0 2.0 3.0 6.0 2
-65.0 0.0 4.0 150.0 225.0 0.0 2.0 114.0 0.0 1.0 2.0 3.0 7.0 2
-42.0 1.0 4.0 136.0 315.0 0.0 0.0 125.0 1.0 1.8 2.0 0.0 6.0 2
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-59.0 0.0 4.0 174.0 249.0 0.0 0.0 143.0 1.0 0.0 2.0 0.0 3.0 2
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-63.0 1.0 1.0 145.0 233.0 1.0 2.0 150.0 0.0 2.3 3.0 0.0 6.0 1
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-51.0 1.0 4.0 140.0 261.0 0.0 2.0 186.0 1.0 0.0 1.0 0.0 3.0 1
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-47.0 1.0 3.0 108.0 243.0 0.0 0.0 152.0 0.0 0.0 1.0 0.0 3.0 2
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-45.0 1.0 4.0 104.0 208.0 0.0 2.0 148.0 1.0 3.0 2.0 0.0 3.0 1
-39.0 0.0 3.0 94.0 199.0 0.0 0.0 179.0 0.0 0.0 1.0 0.0 3.0 1
-42.0 0.0 3.0 120.0 209.0 0.0 0.0 173.0 0.0 0.0 2.0 0.0 3.0 1
-56.0 1.0 2.0 120.0 236.0 0.0 0.0 178.0 0.0 0.8 1.0 0.0 3.0 1
-58.0 1.0 4.0 146.0 218.0 0.0 0.0 105.0 0.0 2.0 2.0 1.0 7.0 2
-35.0 1.0 4.0 120.0 198.0 0.0 0.0 130.0 1.0 1.6 2.0 0.0 7.0 2
-58.0 1.0 4.0 150.0 270.0 0.0 2.0 111.0 1.0 0.8 1.0 0.0 7.0 2
-41.0 1.0 3.0 130.0 214.0 0.0 2.0 168.0 0.0 2.0 2.0 0.0 3.0 1
-57.0 1.0 4.0 110.0 201.0 0.0 0.0 126.0 1.0 1.5 2.0 0.0 6.0 1
-42.0 1.0 1.0 148.0 244.0 0.0 2.0 178.0 0.0 0.8 1.0 2.0 3.0 1
-62.0 1.0 2.0 128.0 208.0 1.0 2.0 140.0 0.0 0.0 1.0 0.0 3.0 1
-59.0 1.0 1.0 178.0 270.0 0.0 2.0 145.0 0.0 4.2 3.0 0.0 7.0 1
-41.0 0.0 2.0 126.0 306.0 0.0 0.0 163.0 0.0 0.0 1.0 0.0 3.0 1
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-61.0 0.0 4.0 130.0 330.0 0.0 2.0 169.0 0.0 0.0 1.0 0.0 3.0 2
-54.0 1.0 4.0 124.0 266.0 0.0 2.0 109.0 1.0 2.2 2.0 1.0 7.0 2
-54.0 1.0 4.0 110.0 206.0 0.0 2.0 108.0 1.0 0.0 2.0 1.0 3.0 2
-52.0 1.0 4.0 125.0 212.0 0.0 0.0 168.0 0.0 1.0 1.0 2.0 7.0 2
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diff --git a/scikits/learn/datasets/heart/src/heart.descri.txt b/scikits/learn/datasets/heart/src/heart.descri.txt
deleted file mode 100644
index 623b15e2904f5864b4e85b5119a04b086e80f767..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/heart/src/heart.descri.txt
+++ /dev/null
@@ -1,37 +0,0 @@
-.. vim:syntax=rest
-
-===================
-Dataset description
-===================
-
-    * number of examples : 270
-    * number of classes : 2. Absence (1) or presence (2) of heart disease:
-        ======= =============
-        Class	Nr.Examples
-        ======= =============
-        1	    150 ( 55.56%)
-        2	    120 ( 44.44%)
-        ======= =============
-    * number of attributes: This database contains 13 attributes (which have
-      been extracted from a larger set of 75). Attribute Information:
-
-      * age       
-      * sex       
-      * chest pain type  (4 values)       
-      * resting blood pressure  
-      * serum cholestoral in mg/dl      
-      * fasting blood sugar > 120 mg/dl       
-      * resting electrocardiographic results  (values 0,1,2) 
-      * maximum heart rate achieved  
-      * exercise induced angina    
-      * oldpeak = ST depression induced by exercise relative to rest   
-      * the slope of the peak exercise ST segment     
-      * number of major vessels (0-3) colored by flourosopy        
-      * thal: 3 = normal; 6 = fixed defect; 7 = reversable defect     
-    * Attributes types:
-
-      * Real: 	1,4,5,8,10,12
-      * Ordered:11,
-      * Binary: 2,6,9
-      * Nominal:7,3,13
-    * Missing values: none
diff --git a/scikits/learn/datasets/heart/src/heart.names b/scikits/learn/datasets/heart/src/heart.names
deleted file mode 100644
index 0c51e42ac63ec6de7654f0d9ed7e831b89651ce3..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/heart/src/heart.names
+++ /dev/null
@@ -1,14 +0,0 @@
-1,2
-at1: continuous
-at2: 1,0
-at3: 1,2,3,4
-at4: continuous
-at5: continuous
-at6: 1, 0
-at7: 0, 1, 2
-at8: continuous
-at9: 0, 1
-at10: continuous
-at11: continuous
-at12: continuous
-at13: 3, 7, 6
diff --git a/scikits/learn/datasets/misc/__init__.py b/scikits/learn/datasets/misc/__init__.py
deleted file mode 100644
index 3457bb15a4dbe6b85b3e0e8fcb8e4ac29afe240f..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/misc/__init__.py
+++ /dev/null
@@ -1 +0,0 @@
-from tools import dumpvar
diff --git a/scikits/learn/datasets/misc/tools.py b/scikits/learn/datasets/misc/tools.py
deleted file mode 100644
index 8d2c9c1846879a44996c418b5f7fbf4659d6ea44..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/misc/tools.py
+++ /dev/null
@@ -1,16 +0,0 @@
-#! /usr/bin/env python
-
-"""Some basic tools for common operations in datasets."""
-
-import textwrap
-
-def dumpvar(var, varname, wrap = 79):
-    """return a list of string representing the variable var with name varname.
-
-    For example, if var is [1, 2, 3, 4] and varname is l, this will return the
-    list ["l = [1, 2, 3, 4]"]. Each item in the list is a wrapped line, using
-    the value in wrap."""
-    strvar = varname + " = " + str(var)
-    l = [i + '\n' for i in textwrap.wrap(strvar, wrap)]
-    l.append('\n')
-    return l
diff --git a/scikits/learn/datasets/narr/__init__.py b/scikits/learn/datasets/narr/__init__.py
deleted file mode 100644
index a60cd86263d50435f23fd02a220d57ec1f02b9e1..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/narr/__init__.py
+++ /dev/null
@@ -1,8 +0,0 @@
-#! /usr/bin/env python
-# Last Change: Fri Jun 08 12:00 PM 2007 J
-import data as _narr
-__doc__     = _narr.DESCRLONG
-copyright   = _narr.COPYRIGHT
-source      = _narr.SOURCE
-
-load        = _narr.load
diff --git a/scikits/learn/datasets/narr/data.py b/scikits/learn/datasets/narr/data.py
deleted file mode 100644
index 37989bb43a70a6a739fe027ecee6cf97f8023fc7..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/narr/data.py
+++ /dev/null
@@ -1,185 +0,0 @@
-"""
-XXX: currently disabled
-"""
-
-"""
-=============
-NCEP NARR data sets
-=============
-
-This module provides access to the National Center for Environment Prediction 
-(NCEP) North American Regional Reanalysis (NARR) data sets through the 
-Data Access Protocol (DAP). The documentation describing the data set
-variables is included in the doc directory. 
-
-See the `pydap home page`_ for information on the DAP client. 
-
-.. _pydap home page: http://pydap.org/
-"""
-
-__docformat__ = 'restructuredtext'
-
-TITLE       = "NCEP North American Regional Reanalysis (NARR)"
-
-COPYRIGHT   = """The information on government servers are in the public domain,
-unless specifically annotated otherwise, and may be used freely by the public so
-long as you do not 1) claim it is your own (e.g. by claiming copyright for NWS 
-information -- see below), 2) use it in a manner that implies an endorsement 
-or affiliation with NOAA/NWS, or 3) modify it in content and then present it as 
-official government material. You also cannot present information of your own 
-in a way that makes it appear to be official government information..
-
-The user assumes the entire risk related to its use of this data. NWS is 
-providing this data "as is," and NWS disclaims any and all warranties, whether
-express or implied, including (without limitation) any implied warranties of 
-merchantability or fitness for a particular purpose. In no event will NWS be 
-liable to you or to any third party for any direct, indirect, incidental, 
-consequential, special or exemplary damages or lost profit resulting from any 
-use or misuse of this data.
-
-As required by 17 U.S.C. 403, third parties producing copyrighted works 
-consisting predominantly of the material appearing in NWS Web pages must 
-provide notice with such work(s) identifying the NWS material incorporated 
-and stating that such material is not subject to copyright protection."""
-
-DISCLAIMER = """While every effort has been made to ensure that data are
-accurate and reliable within the limits of the current state of
-the art, NOAA cannot assume liability for any damages caused by
-any errors or omissions in the data, nor as a result of the
-failure of the data to function on a particular system.
-NOAA makes no warranty, expressed or implied, nor does the fact
-of distribution constitute such a warranty.
-The data used to produce these analyses and forecasts has
-undergone automated quality checks.
-"""
- 
-SOURCE      = """National Centers for Environmental Prediction (NCEP) _`North American Regional Reanalysis (NARR)` _`NOMADS web interface`.
-
-.. __North American Regional Reanalysis (NARR): http://wwwt.emc.ncep.noaa.gov/mmb/rreanl/index.html
-.. _NOMADS web interface: http://nomads.ncdc.noaa.gov/data.php#narr_datasets
-
-References: 
-    Mesinger, F., et al, 2004: NCEP North American Regional
-Reanalysis, 15th Symp. On Global Change and Climate Variations,
-Seattle, WA, 11-15 Jan 2004.
-
-    Shafran, P., J. Woollen, W. Ebisuzaki, W. Shi, Y. Fan, R. W.
-Grumbine, M. Fennessy, 2004: Observational Data Used for Assimilation in 
-the NCEP North American Regional Reanalysis, 20th Intl. Conf. On Interactive
-Information Processing Systems for Meteor. Ocean. And Hydrology. Seattle, WA, 11-15
-Jan 2004.
-
-    Ebisuzaki, W., J. Alpert, J. Wang, D. Jovic, P. Shafran, 2004: North American
-Regional Reanalysis: end user access to large data sets, 20th Intl. Conf. On
-Interactive Information Processing Systems for Meteor. Ocean. And Hydrology. Seattle,
-WA, 11-15 Jan 2004.
-
-    Mesinger, F., G. DiMego, E. Kalnay, P. Shafran, W. Ebisuzaki, Y. Fan, R. Grumbine,
-W. Higgins, Y. Lin, K. Mitchell, D. Parrish, E. Rogers, W. Shi, D. Stokes, J. Woolen,
-2003: NCEP Regional Reanalysis, Symp. on Observing and Understanding the Variability
-of Water in Weather and Climate, Long Beach, CA, Feb.9-13, 2003.
-"""
-
-DESCRSHORT  = """NCEP NARR data sets"""
-
-DESCRLONG   = """The NARR is a reanalysis of
-historical observations using a 32 km version of the NCEP 1993
-operational ETA model and ETA data assimilation system (EDAS).
-The domain of analyses includes North and Central America as
-well as small parts of the UK, Eastern Asia and South America
-and the oceans in between. The period of the reanalyses is from
-October 1978 to the present and analyses were made 8 times
-daily. Horizontal boundary conditions were derived from the
-NCEP/DOE Reanalysis.
-The "merged" dataset provides a high spatial (32 km) and
-temporal (3 hour) analyses of North America and adjacent oceans
-and land masses from October 1978 to the present. Advantages
-over the widely used NCEP/NCAR Reanalysis are its higher
-resolution and a much better treatment of the land surface
-through a better land-surface model (NOAH), through the
-assimilation of more surface data (observed precipitation and
-surface winds) and through a better representation of the
-terrain (heights, vegetation, soil type).
-This data set contains "conventional" atmospheric analyses as
-well as model-derived fields which contain estimates of
-subsurface, surface, and radiative properties.
-"""
-
-import datetime
-import numpy as np
-
-NARR_A_URL = "http://nomads.ncdc.noaa.gov:9091/dods/NCEP_NARR_DAILY"
-
-def load(year, month, day, verbose=True):
-    """
-    Load the National Center for Environment Prediction (NCEP) North American 
-    Regional Reanalysis (NARR) data at the given date. The data is available 
-    through Data Access Protocol (DAP) from a remote server. The returned 
-    object is not the entire data set, but only the metadata describing the 
-    data set content. Individual variables are properties of the object, and
-    are downloaded only on explicit request (see example below).  
-    
-    Parameters:
-        year : int
-        month : int 
-        day : int
-        
-    Note:
-    The data is available starting on 1979-01-01 and up to the the month before
-    last. Each dataset contains around 190 different variables at 3h intervals. 
-    The DAP protocol was formerly known as the Distributed Oceanographic Data 
-    Systems (DODS).
-    
-    
-    Some variables included in the set:
-        ugrd10m : Wind speed (u) at 10 m altitude [m/s].
-        vgrd10m : Wind speed (v) at 10 m altitude [m/s].
-        mslet: Mean sea level pressure (eta model) [pa].
-        tmpsfc : Surface temperature [K].
-        dswrfsfc : Surface downward shortwave radiation flux [W/m^2]. 
-        time : Days since 1-1-1  00:00:00.
-        lat : Latitude (0 to 89.625) at 0.375 degree resolution [deg].
-        lon : Longitude (-220 to -0.625) at 0.375 degree resolution [deg]. 
-    
-    Example:
-        narr = load(2005, 6, 23)
-        temp = narr.tmpsfc[:][:][:] # Slices refer to time, lat, lon.
-        time = narr.time[:]
-        lat = narr.lat[:]
-        lon = narr.lon[:]
-    
-    """
-    import dap.client
-    tail = 'narr-a_221_' 
-    dir1 = '%d%02d'%(year, month)
-    dir2 = dir1+'%02d'%day
-    tail = tail +dir2+'_0000_000'
-    url = '/'.join([NARR_A_URL, dir1, dir2, tail])
-    if verbose:
-        print 'Accessing DODS server: ', url
-    return dap.client.open(url)
-
-
-
-def convert_time(time):
-    """Return datetime objects. 
-    
-    The NARR dataset provides time in days since 1-1-1 00:00:00:0.0. This 
-    function converts the NARR time into a datetime.datetime object. 
-    
-    Note:
-    There seems to be a discrepancy between the days counting of NARR and 
-    python datetime. To achieve the fit, two days must be substracted from the
-    NARR time.
-    """
-    time = time-2
-    t0 = datetime.datetime(1,1, 1, 0,0,0)
-    hour = datetime.timedelta(hours=1)
-    day = datetime.timedelta(days=1)
-    time = np.atleast_1d(time)
-    days = time.astype(int)
-    hours =  ((time%1)*24).astype(int)
-    return t0+days*day+hours*hour
-    
-    
-# narr = load(1979, 1,1) XXX: currently disabled
diff --git a/scikits/learn/datasets/narr/doc/narr_data_documentation.pdf b/scikits/learn/datasets/narr/doc/narr_data_documentation.pdf
deleted file mode 100644
index fe5727b11e94a1d230f131a75a66c067db7da588..0000000000000000000000000000000000000000
Binary files a/scikits/learn/datasets/narr/doc/narr_data_documentation.pdf and /dev/null differ
diff --git a/scikits/learn/datasets/narr/doc/overview.pdf b/scikits/learn/datasets/narr/doc/overview.pdf
deleted file mode 100644
index aedba53e76d2743195e14ae9746846bdb5d4766a..0000000000000000000000000000000000000000
Binary files a/scikits/learn/datasets/narr/doc/overview.pdf and /dev/null differ
diff --git a/scikits/learn/datasets/nwis/COPYING b/scikits/learn/datasets/nwis/COPYING
deleted file mode 100644
index b79acb272fc3e83d3a6df4d58eed858069b71845..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/nwis/COPYING
+++ /dev/null
@@ -1,34 +0,0 @@
-# The code and descriptive text is copyrighted and offered under the terms of
-# the BSD License from the authors; see below. However, the actual dataset may
-# have a different origin and intellectual property status. See the SOURCE and
-# COPYRIGHT variables for this information.
-
-# Copyright (c) 2007 David Huard <david.huard@gmail.com>
-#
-# All rights reserved.
-#
-# Redistribution and use in source and binary forms, with or without
-# modification, are permitted provided that the following conditions are
-# met:
-#
-#     * Redistributions of source code must retain the above copyright
-#       notice, this list of conditions and the following disclaimer.
-#     * Redistributions in binary form must reproduce the above copyright
-#       notice, this list of conditions and the following disclaimer in
-#       the documentation and/or other materials provided with the
-#       distribution.
-#     * Neither the author nor the names of any contributors may be used
-#       to endorse or promote products derived from this software without
-#       specific prior written permission.
-#
-# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
-# TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
-# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
-# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
-# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
-# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
-# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
-# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
-# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
-# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
diff --git a/scikits/learn/datasets/nwis/__init__.py b/scikits/learn/datasets/nwis/__init__.py
deleted file mode 100644
index c305edefd3156b7680aa8b8c636557e17a397846..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/nwis/__init__.py
+++ /dev/null
@@ -1,10 +0,0 @@
-#! /usr/bin/env python
-# Last Change: Mon Jul 02 02:00 PM 2007 J
-import data as _nwis
-__doc__     = _nwis.DESCRSHORT
-copyright   = _nwis.COPYRIGHT
-source      = _nwis.SOURCE
-
-load        = _nwis.load
-
-all = ['load', 'copyright', 'source']
diff --git a/scikits/learn/datasets/nwis/data.py b/scikits/learn/datasets/nwis/data.py
deleted file mode 100644
index a2b0819c5df2f0855a22de50f6c6ccba60b19049..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/nwis/data.py
+++ /dev/null
@@ -1,98 +0,0 @@
-#! /usr/bin/env python
-# -*- coding: utf-8 -*-
-# Last Change: Wed Sep 19 2007
-
-# The code and descriptive text is copyrighted and offered under the terms of
-# the BSD License from the authors; see below. However, the actual dataset may
-# have a different origin and intellectual property status. See the SOURCE and
-# COPYRIGHT variables for this information.
-
-# Copyright (c) 2007 David Huard <david.huard@gmail.com>
-#
-# All rights reserved.
-#
-# Redistribution and use in source and binary forms, with or without
-# modification, are permitted provided that the following conditions are
-# met:
-#
-#     * Redistributions of source code must retain the above copyright
-#       notice, this list of conditions and the following disclaimer.
-#     * Redistributions in binary form must reproduce the above copyright
-#       notice, this list of conditions and the following disclaimer in
-#       the documentation and/or other materials provided with the
-#       distribution.
-#     * Neither the author nor the names of any contributors may be used
-#       to endorse or promote products derived from this software without
-#       specific prior written permission.
-#
-# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
-# TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
-# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
-# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
-# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
-# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
-# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
-# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
-# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
-# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
-"""USGS daily discharge at West Branch Delaware River at Walton NY."""
-
-__docformat__ = 'restructuredtext'
-
-COPYRIGHT   = """See src/01423000.dly """
-TITLE       = "Daily discharge at West Branch Delaware River at Walton, NY"
-SOURCE      = """Creator: National Water Information System, U.S. Geological Survey""" 
-
-DESCRSHORT  = """USGS daily discharge at West Branch Delaware River at Walton, NY."""
-
-DESCRLONG   = """Daily discharge (cubic feet per second) from 2006-9-18 to 2007-9-18 acquired by the 
-U.S. Geological Survey and released through the National Water Information System. The data code is included, describing the data quality: 'A' for approved and 'P' for provisional data. Missing discharges, or disharges affected by ice are indicated by the value -999.0. 
-"""
-
-NOTE        = """Discharge is computed by measuring the water level and estimating the related discharge through a rating curve. The rating curve is drawn using simultaneously measurements of water level and discharge. The rating curve typically changes over time due to erosion, presence of debris or ice. In this dataset, some discharges are missing due to the presence of ice."""
-
-def load():
-    """Return the nwis discharge data.
-    
-    :Returns:
-        d : dict
-            contains the following values:
-            - 'data' : a record array with the actual data
-    
-    Example
-    -------
-    Mask the missing data in discharge and plot the time series.
-    
-    >>> import datetime, pylab, numpy
-    >>> data = load()['data']
-    >>> discharge = numpy.ma.masked_values(data['discharge'], -999.0)
-    >>> datelist = zip(data['year'], data['month'], data['day'])
-    >>> date = [datetime.date(y,m,d) for y,m,d in datelist]
-    >>> pylab.plot_date(date, discharge, '-')
-    """
-    import numpy
-    from nwis import date, discharge, code
-    import re
-    
-    # Deal with missing data in discharge
-    discharge = numpy.array(discharge)
-    missing = (discharge == 'Ice') + (discharge == '')
-    discharge[missing] = -999.0
-    discharge = discharge.astype(numpy.float)    
-    
-    # Convert date string to ints
-    pattern = r'(\d{4})-(\d{2})-(\d{2})'
-    date = numpy.array([re.search(pattern, d).groups(1) for d in date]).astype(numpy.int)
-    year, month, day = date.transpose()
-        
-    data    = {}
-    format = [('year', numpy.int), ('month', numpy.int), ('day', numpy.int),
-              ('discharge', numpy.float), ('code', str)]
-    data['data'] = numpy.empty(len(discharge), format)
-    data['data']['year'] = year
-    data['data']['month'] = month
-    data['data']['day'] = day
-    data['data']['discharge'] = discharge   
-    return data
diff --git a/scikits/learn/datasets/nwis/nwis.py b/scikits/learn/datasets/nwis/nwis.py
deleted file mode 100644
index 103281b580e29b1e798050bd0314adc9fd939386..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/nwis/nwis.py
+++ /dev/null
@@ -1,137 +0,0 @@
-# Autogenerated by convert.py at Wed, 19 Sep 2007 15:53:31 +0000
-
-date = ['2006-09-18', '2006-09-19', '2006-09-20', '2006-09-21', '2006-09-22',
-'2006-09-23', '2006-09-24', '2006-09-25', '2006-09-26', '2006-09-27',
-'2006-09-28', '2006-09-29', '2006-09-30', '2006-10-01', '2006-10-02',
-'2006-10-03', '2006-10-04', '2006-10-05', '2006-10-06', '2006-10-07',
-'2006-10-08', '2006-10-09', '2006-10-10', '2006-10-11', '2006-10-12',
-'2006-10-13', '2006-10-14', '2006-10-15', '2006-10-16', '2006-10-17',
-'2006-10-18', '2006-10-19', '2006-10-20', '2006-10-21', '2006-10-22',
-'2006-10-23', '2006-10-24', '2006-10-25', '2006-10-26', '2006-10-27',
-'2006-10-28', '2006-10-29', '2006-10-30', '2006-10-31', '2006-11-01',
-'2006-11-02', '2006-11-03', '2006-11-04', '2006-11-05', '2006-11-06',
-'2006-11-07', '2006-11-08', '2006-11-09', '2006-11-10', '2006-11-11',
-'2006-11-12', '2006-11-13', '2006-11-14', '2006-11-15', '2006-11-16',
-'2006-11-17', '2006-11-18', '2006-11-19', '2006-11-20', '2006-11-21',
-'2006-11-22', '2006-11-23', '2006-11-24', '2006-11-25', '2006-11-26',
-'2006-11-27', '2006-11-28', '2006-11-29', '2006-11-30', '2006-12-01',
-'2006-12-02', '2006-12-03', '2006-12-04', '2006-12-05', '2006-12-06',
-'2006-12-07', '2006-12-08', '2006-12-09', '2006-12-10', '2006-12-11',
-'2006-12-12', '2006-12-13', '2006-12-14', '2006-12-15', '2006-12-16',
-'2006-12-17', '2006-12-18', '2006-12-19', '2006-12-20', '2006-12-21',
-'2006-12-22', '2006-12-23', '2006-12-24', '2006-12-25', '2006-12-26',
-'2006-12-27', '2006-12-28', '2006-12-29', '2006-12-30', '2006-12-31',
-'2007-01-01', '2007-01-02', '2007-01-03', '2007-01-04', '2007-01-05',
-'2007-01-06', '2007-01-07', '2007-01-08', '2007-01-09', '2007-01-10',
-'2007-01-11', '2007-01-12', '2007-01-13', '2007-01-14', '2007-01-15',
-'2007-01-16', '2007-01-17', '2007-01-18', '2007-01-19', '2007-01-20',
-'2007-01-21', '2007-01-22', '2007-01-23', '2007-01-24', '2007-01-25',
-'2007-01-26', '2007-01-27', '2007-01-28', '2007-01-29', '2007-01-30',
-'2007-01-31', '2007-02-01', '2007-02-02', '2007-02-03', '2007-02-04',
-'2007-02-05', '2007-02-06', '2007-02-07', '2007-02-08', '2007-02-09',
-'2007-02-10', '2007-02-11', '2007-02-12', '2007-02-13', '2007-02-14',
-'2007-02-15', '2007-02-16', '2007-02-17', '2007-02-18', '2007-02-19',
-'2007-02-20', '2007-02-21', '2007-02-22', '2007-02-23', '2007-02-24',
-'2007-02-25', '2007-02-26', '2007-02-27', '2007-02-28', '2007-03-01',
-'2007-03-02', '2007-03-03', '2007-03-04', '2007-03-05', '2007-03-06',
-'2007-03-07', '2007-03-08', '2007-03-09', '2007-03-10', '2007-03-11',
-'2007-03-12', '2007-03-13', '2007-03-14', '2007-03-15', '2007-03-16',
-'2007-03-17', '2007-03-18', '2007-03-19', '2007-03-20', '2007-03-21',
-'2007-03-22', '2007-03-23', '2007-03-24', '2007-03-25', '2007-03-26',
-'2007-03-27', '2007-03-28', '2007-03-29', '2007-03-30', '2007-03-31',
-'2007-04-01', '2007-04-02', '2007-04-03', '2007-04-04', '2007-04-05',
-'2007-04-06', '2007-04-07', '2007-04-08', '2007-04-09', '2007-04-10',
-'2007-04-11', '2007-04-12', '2007-04-13', '2007-04-14', '2007-04-15',
-'2007-04-16', '2007-04-17', '2007-04-18', '2007-04-19', '2007-04-20',
-'2007-04-21', '2007-04-22', '2007-04-23', '2007-04-24', '2007-04-25',
-'2007-04-26', '2007-04-27', '2007-04-28', '2007-04-29', '2007-04-30',
-'2007-05-01', '2007-05-02', '2007-05-03', '2007-05-04', '2007-05-05',
-'2007-05-06', '2007-05-07', '2007-05-08', '2007-05-09', '2007-05-10',
-'2007-05-11', '2007-05-12', '2007-05-13', '2007-05-14', '2007-05-15',
-'2007-05-16', '2007-05-17', '2007-05-18', '2007-05-19', '2007-05-20',
-'2007-05-21', '2007-05-22', '2007-05-23', '2007-05-24', '2007-05-25',
-'2007-05-26', '2007-05-27', '2007-05-28', '2007-05-29', '2007-05-30',
-'2007-05-31', '2007-06-01', '2007-06-02', '2007-06-03', '2007-06-04',
-'2007-06-05', '2007-06-06', '2007-06-07', '2007-06-08', '2007-06-09',
-'2007-06-10', '2007-06-11', '2007-06-12', '2007-06-13', '2007-06-14',
-'2007-06-15', '2007-06-16', '2007-06-17', '2007-06-18', '2007-06-19',
-'2007-06-20', '2007-06-21', '2007-06-22', '2007-06-23', '2007-06-24',
-'2007-06-25', '2007-06-26', '2007-06-27', '2007-06-28', '2007-06-29',
-'2007-06-30', '2007-07-01', '2007-07-02', '2007-07-03', '2007-07-04',
-'2007-07-05', '2007-07-06', '2007-07-07', '2007-07-08', '2007-07-09',
-'2007-07-10', '2007-07-11', '2007-07-12', '2007-07-13', '2007-07-14',
-'2007-07-15', '2007-07-16', '2007-07-17', '2007-07-18', '2007-07-19',
-'2007-07-20', '2007-07-21', '2007-07-22', '2007-07-23', '2007-07-24',
-'2007-07-25', '2007-07-26', '2007-07-27', '2007-07-28', '2007-07-29',
-'2007-07-30', '2007-07-31', '2007-08-01', '2007-08-02', '2007-08-03',
-'2007-08-04', '2007-08-05', '2007-08-06', '2007-08-07', '2007-08-08',
-'2007-08-09', '2007-08-10', '2007-08-11', '2007-08-12', '2007-08-13',
-'2007-08-14', '2007-08-15', '2007-08-16', '2007-08-17', '2007-08-18',
-'2007-08-19', '2007-08-20', '2007-08-21', '2007-08-22', '2007-08-23',
-'2007-08-24', '2007-08-25', '2007-08-26', '2007-08-27', '2007-08-28',
-'2007-08-29', '2007-08-30', '2007-08-31', '2007-09-01', '2007-09-02',
-'2007-09-03', '2007-09-04', '2007-09-05', '2007-09-06', '2007-09-07',
-'2007-09-08', '2007-09-09', '2007-09-10', '2007-09-11', '2007-09-12',
-'2007-09-13', '2007-09-14', '2007-09-15', '2007-09-16', '2007-09-17',
-'2007-09-18']
-
-discharge = ['468', '430', '412', '375', '331', '358', '372', '328', '291',
-'261', '258', '1230', '933', '1040', '1130', '920', '840', '822', '690', '602',
-'537', '486', '441', '405', '402', '397', '351', '319', '294', '303', '399',
-'354', '1190', '1770', '1260', '1090', '945', '898', '839', '713', '2790',
-'3960', '2460', '1880', '1510', '1480', '1340', '1030', '885', '789', '712',
-'838', '1560', '1090', '987', '930', '970', '863', '806', '1510', '3990',
-'2260', '1800', '1500', '1240', '1060', '1260', '1260', '995', '917', '848',
-'786', '721', '670', '757', '1260', '869', '808', '758', '692', '677', '617',
-'553', '533', '507', '489', '496', '503', '450', '436', '407', '387', '366',
-'346', '337', '326', '500', '503', '425', '647', '745', '634', '624', '601',
-'575', '672', '740', '630', '587', '599', '1560', '1340', '2020', '1840',
-'1520', '1280', '1140', '1270', '1320', '2100', '2780', '1970', '1600', '1460',
-'1240', '973', '913', '817', '729', '642', '464', 'Ice', 'Ice', 'Ice', 'Ice',
-'Ice', 'Ice', 'Ice', 'Ice', 'Ice', 'Ice', 'Ice', 'Ice', 'Ice', 'Ice', 'Ice',
-'Ice', 'Ice', 'Ice', 'Ice', 'Ice', 'Ice', 'Ice', 'Ice', 'Ice', 'Ice', 'Ice',
-'Ice', 'Ice', 'Ice', 'Ice', 'Ice', 'Ice', 'Ice', 'Ice', 'Ice', 'Ice', 'Ice',
-'Ice', 'Ice', 'Ice', 'Ice', 'Ice', 'Ice', 'Ice', 'Ice', 'Ice', '1680', '6580',
-'4550', '2730', '1980', '1500', '1280', '1030', '1330', '3530', '2690', '3910',
-'3250', '4330', '4090', '3080', '2310', '1850', '1550', '1480', '1270', '1300',
-'1440', '1180', '1020', '914', '808', '727', '656', '812', '1070', '839',
-'1370', '3980', '4180', '3880', '3810', '3620', '2830', '2290', '1920', '1730',
-'1500', '1620', '1220', '1140', '1050', '909', '780', '822', '704', '605',
-'547', '497', '453', '417', '387', '423', '800', '602', '463', '411', '380',
-'396', '458', '370', '344', '442', '407', '325', '287', '263', '240', '221',
-'211', '241', '215', '181', '166', '164', '203', '230', '323', '325', '255',
-'196', '170', '155', '139', '129', '123', '119', '112', '104', '100', '120',
-'104', '106', '377', '217', '205', '165', '140', '126', '116', '116', '147',
-'146', '116', '105', '97', '91', '97', '134', '156', '135', '124', '123',
-'177', '144', '150', '131', '110', '100', '97', '93', '96', '116', '316',
-'245', '159', '145', '207', '174', '139', '144', '240', '231', '164', '140',
-'125', '112', '114', '110', '95', '87', '85', '118', '121', '489', '488',
-'261', '201', '171', '150', '155', '256', '188', '163', '143', '158', '174',
-'148', '138', '141', '123', '112', '103', '95', '89', '84', '79', '74', '70',
-'67', '63', '60', '58', '68', '135', '124', '983', '1220', '542', '397', '',
-'625', '465', '392']
-
-code = ['A', 'A', 'A', 'A', 'A', 'A', 'A', 'A', 'A', 'A', 'A', 'A', 'A', 'P',
-'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P',
-'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P',
-'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P',
-'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P',
-'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P',
-'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P',
-'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P',
-'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P',
-'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P',
-'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P',
-'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P',
-'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P',
-'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P',
-'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P',
-'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P',
-'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P',
-'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P',
-'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P',
-'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P',
-'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P',
-'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P',
-'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P', '', 'P', 'P', 'P']
-
diff --git a/scikits/learn/datasets/nwis/src/01423000.dly b/scikits/learn/datasets/nwis/src/01423000.dly
deleted file mode 100644
index 04e433ed5dec7199f8c05e49e4fd5d3bfe23d705..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/nwis/src/01423000.dly
+++ /dev/null
@@ -1,394 +0,0 @@
-# ---------------------------------- WARNING ----------------------------------------
-# The data you have obtained from this automated U.S. Geological Survey database
-# have not received Director's approval and as such are provisional and subject to
-# revision.  The data are released on the condition that neither the USGS nor the
-# United States Government may be held liable for any damages resulting from its use.
-# Additional info: http://waterdata.usgs.gov/nwis/help/?provisional
-#
-# File-format description:  http://waterdata.usgs.gov/nwis/?tab_delimited_format_info
-# Automated-retrieval info: http://waterdata.usgs.gov/nwis/?automated_retrieval_info
-#
-# Contact:   gs-w_support_nwisweb@usgs.gov
-# retrieved: 2007-09-19 10:31:26 EDT
-#
-# Data for the following site(s) are contained in this file
-#    USGS 01423000 WEST BRANCH DELAWARE RIVER AT WALTON NY
-# -----------------------------------------------------------------------------------
-#
-# Data provided for site 01423000
-#    DD parameter statistic   Description
-#    01   00060     00003     Discharge, cubic feet per second (Mean)
-#
-# Data-value qualification codes included in this output: 
-#     Ice  Ice affected  
-#     A  Approved for publication -- Processing and review completed.  
-#     P  Provisional data subject to revision.  
-# 
-agency_cd	site_no	datetime	01_00060_00003	01_00060_00003_cd
-5s	15s	16s	14s	14s
-USGS	01423000	2006-09-18	468	A
-USGS	01423000	2006-09-19	430	A
-USGS	01423000	2006-09-20	412	A
-USGS	01423000	2006-09-21	375	A
-USGS	01423000	2006-09-22	331	A
-USGS	01423000	2006-09-23	358	A
-USGS	01423000	2006-09-24	372	A
-USGS	01423000	2006-09-25	328	A
-USGS	01423000	2006-09-26	291	A
-USGS	01423000	2006-09-27	261	A
-USGS	01423000	2006-09-28	258	A
-USGS	01423000	2006-09-29	1230	A
-USGS	01423000	2006-09-30	933	A
-USGS	01423000	2006-10-01	1040	P
-USGS	01423000	2006-10-02	1130	P
-USGS	01423000	2006-10-03	920	P
-USGS	01423000	2006-10-04	840	P
-USGS	01423000	2006-10-05	822	P
-USGS	01423000	2006-10-06	690	P
-USGS	01423000	2006-10-07	602	P
-USGS	01423000	2006-10-08	537	P
-USGS	01423000	2006-10-09	486	P
-USGS	01423000	2006-10-10	441	P
-USGS	01423000	2006-10-11	405	P
-USGS	01423000	2006-10-12	402	P
-USGS	01423000	2006-10-13	397	P
-USGS	01423000	2006-10-14	351	P
-USGS	01423000	2006-10-15	319	P
-USGS	01423000	2006-10-16	294	P
-USGS	01423000	2006-10-17	303	P
-USGS	01423000	2006-10-18	399	P
-USGS	01423000	2006-10-19	354	P
-USGS	01423000	2006-10-20	1190	P
-USGS	01423000	2006-10-21	1770	P
-USGS	01423000	2006-10-22	1260	P
-USGS	01423000	2006-10-23	1090	P
-USGS	01423000	2006-10-24	945	P
-USGS	01423000	2006-10-25	898	P
-USGS	01423000	2006-10-26	839	P
-USGS	01423000	2006-10-27	713	P
-USGS	01423000	2006-10-28	2790	P
-USGS	01423000	2006-10-29	3960	P
-USGS	01423000	2006-10-30	2460	P
-USGS	01423000	2006-10-31	1880	P
-USGS	01423000	2006-11-01	1510	P
-USGS	01423000	2006-11-02	1480	P
-USGS	01423000	2006-11-03	1340	P
-USGS	01423000	2006-11-04	1030	P
-USGS	01423000	2006-11-05	885	P
-USGS	01423000	2006-11-06	789	P
-USGS	01423000	2006-11-07	712	P
-USGS	01423000	2006-11-08	838	P
-USGS	01423000	2006-11-09	1560	P
-USGS	01423000	2006-11-10	1090	P
-USGS	01423000	2006-11-11	987	P
-USGS	01423000	2006-11-12	930	P
-USGS	01423000	2006-11-13	970	P
-USGS	01423000	2006-11-14	863	P
-USGS	01423000	2006-11-15	806	P
-USGS	01423000	2006-11-16	1510	P
-USGS	01423000	2006-11-17	3990	P
-USGS	01423000	2006-11-18	2260	P
-USGS	01423000	2006-11-19	1800	P
-USGS	01423000	2006-11-20	1500	P
-USGS	01423000	2006-11-21	1240	P
-USGS	01423000	2006-11-22	1060	P
-USGS	01423000	2006-11-23	1260	P
-USGS	01423000	2006-11-24	1260	P
-USGS	01423000	2006-11-25	995	P
-USGS	01423000	2006-11-26	917	P
-USGS	01423000	2006-11-27	848	P
-USGS	01423000	2006-11-28	786	P
-USGS	01423000	2006-11-29	721	P
-USGS	01423000	2006-11-30	670	P
-USGS	01423000	2006-12-01	757	P
-USGS	01423000	2006-12-02	1260	P
-USGS	01423000	2006-12-03	869	P
-USGS	01423000	2006-12-04	808	P
-USGS	01423000	2006-12-05	758	P
-USGS	01423000	2006-12-06	692	P
-USGS	01423000	2006-12-07	677	P
-USGS	01423000	2006-12-08	617	P
-USGS	01423000	2006-12-09	553	P
-USGS	01423000	2006-12-10	533	P
-USGS	01423000	2006-12-11	507	P
-USGS	01423000	2006-12-12	489	P
-USGS	01423000	2006-12-13	496	P
-USGS	01423000	2006-12-14	503	P
-USGS	01423000	2006-12-15	450	P
-USGS	01423000	2006-12-16	436	P
-USGS	01423000	2006-12-17	407	P
-USGS	01423000	2006-12-18	387	P
-USGS	01423000	2006-12-19	366	P
-USGS	01423000	2006-12-20	346	P
-USGS	01423000	2006-12-21	337	P
-USGS	01423000	2006-12-22	326	P
-USGS	01423000	2006-12-23	500	P
-USGS	01423000	2006-12-24	503	P
-USGS	01423000	2006-12-25	425	P
-USGS	01423000	2006-12-26	647	P
-USGS	01423000	2006-12-27	745	P
-USGS	01423000	2006-12-28	634	P
-USGS	01423000	2006-12-29	624	P
-USGS	01423000	2006-12-30	601	P
-USGS	01423000	2006-12-31	575	P
-USGS	01423000	2007-01-01	672	P
-USGS	01423000	2007-01-02	740	P
-USGS	01423000	2007-01-03	630	P
-USGS	01423000	2007-01-04	587	P
-USGS	01423000	2007-01-05	599	P
-USGS	01423000	2007-01-06	1560	P
-USGS	01423000	2007-01-07	1340	P
-USGS	01423000	2007-01-08	2020	P
-USGS	01423000	2007-01-09	1840	P
-USGS	01423000	2007-01-10	1520	P
-USGS	01423000	2007-01-11	1280	P
-USGS	01423000	2007-01-12	1140	P
-USGS	01423000	2007-01-13	1270	P
-USGS	01423000	2007-01-14	1320	P
-USGS	01423000	2007-01-15	2100	P
-USGS	01423000	2007-01-16	2780	P
-USGS	01423000	2007-01-17	1970	P
-USGS	01423000	2007-01-18	1600	P
-USGS	01423000	2007-01-19	1460	P
-USGS	01423000	2007-01-20	1240	P
-USGS	01423000	2007-01-21	973	P
-USGS	01423000	2007-01-22	913	P
-USGS	01423000	2007-01-23	817	P
-USGS	01423000	2007-01-24	729	P
-USGS	01423000	2007-01-25	642	P
-USGS	01423000	2007-01-26	464	P
-USGS	01423000	2007-01-27	Ice	P
-USGS	01423000	2007-01-28	Ice	P
-USGS	01423000	2007-01-29	Ice	P
-USGS	01423000	2007-01-30	Ice	P
-USGS	01423000	2007-01-31	Ice	P
-USGS	01423000	2007-02-01	Ice	P
-USGS	01423000	2007-02-02	Ice	P
-USGS	01423000	2007-02-03	Ice	P
-USGS	01423000	2007-02-04	Ice	P
-USGS	01423000	2007-02-05	Ice	P
-USGS	01423000	2007-02-06	Ice	P
-USGS	01423000	2007-02-07	Ice	P
-USGS	01423000	2007-02-08	Ice	P
-USGS	01423000	2007-02-09	Ice	P
-USGS	01423000	2007-02-10	Ice	P
-USGS	01423000	2007-02-11	Ice	P
-USGS	01423000	2007-02-12	Ice	P
-USGS	01423000	2007-02-13	Ice	P
-USGS	01423000	2007-02-14	Ice	P
-USGS	01423000	2007-02-15	Ice	P
-USGS	01423000	2007-02-16	Ice	P
-USGS	01423000	2007-02-17	Ice	P
-USGS	01423000	2007-02-18	Ice	P
-USGS	01423000	2007-02-19	Ice	P
-USGS	01423000	2007-02-20	Ice	P
-USGS	01423000	2007-02-21	Ice	P
-USGS	01423000	2007-02-22	Ice	P
-USGS	01423000	2007-02-23	Ice	P
-USGS	01423000	2007-02-24	Ice	P
-USGS	01423000	2007-02-25	Ice	P
-USGS	01423000	2007-02-26	Ice	P
-USGS	01423000	2007-02-27	Ice	P
-USGS	01423000	2007-02-28	Ice	P
-USGS	01423000	2007-03-01	Ice	P
-USGS	01423000	2007-03-02	Ice	P
-USGS	01423000	2007-03-03	Ice	P
-USGS	01423000	2007-03-04	Ice	P
-USGS	01423000	2007-03-05	Ice	P
-USGS	01423000	2007-03-06	Ice	P
-USGS	01423000	2007-03-07	Ice	P
-USGS	01423000	2007-03-08	Ice	P
-USGS	01423000	2007-03-09	Ice	P
-USGS	01423000	2007-03-10	Ice	P
-USGS	01423000	2007-03-11	Ice	P
-USGS	01423000	2007-03-12	Ice	P
-USGS	01423000	2007-03-13	Ice	P
-USGS	01423000	2007-03-14	1680	P
-USGS	01423000	2007-03-15	6580	P
-USGS	01423000	2007-03-16	4550	P
-USGS	01423000	2007-03-17	2730	P
-USGS	01423000	2007-03-18	1980	P
-USGS	01423000	2007-03-19	1500	P
-USGS	01423000	2007-03-20	1280	P
-USGS	01423000	2007-03-21	1030	P
-USGS	01423000	2007-03-22	1330	P
-USGS	01423000	2007-03-23	3530	P
-USGS	01423000	2007-03-24	2690	P
-USGS	01423000	2007-03-25	3910	P
-USGS	01423000	2007-03-26	3250	P
-USGS	01423000	2007-03-27	4330	P
-USGS	01423000	2007-03-28	4090	P
-USGS	01423000	2007-03-29	3080	P
-USGS	01423000	2007-03-30	2310	P
-USGS	01423000	2007-03-31	1850	P
-USGS	01423000	2007-04-01	1550	P
-USGS	01423000	2007-04-02	1480	P
-USGS	01423000	2007-04-03	1270	P
-USGS	01423000	2007-04-04	1300	P
-USGS	01423000	2007-04-05	1440	P
-USGS	01423000	2007-04-06	1180	P
-USGS	01423000	2007-04-07	1020	P
-USGS	01423000	2007-04-08	914	P
-USGS	01423000	2007-04-09	808	P
-USGS	01423000	2007-04-10	727	P
-USGS	01423000	2007-04-11	656	P
-USGS	01423000	2007-04-12	812	P
-USGS	01423000	2007-04-13	1070	P
-USGS	01423000	2007-04-14	839	P
-USGS	01423000	2007-04-15	1370	P
-USGS	01423000	2007-04-16	3980	P
-USGS	01423000	2007-04-17	4180	P
-USGS	01423000	2007-04-18	3880	P
-USGS	01423000	2007-04-19	3810	P
-USGS	01423000	2007-04-20	3620	P
-USGS	01423000	2007-04-21	2830	P
-USGS	01423000	2007-04-22	2290	P
-USGS	01423000	2007-04-23	1920	P
-USGS	01423000	2007-04-24	1730	P
-USGS	01423000	2007-04-25	1500	P
-USGS	01423000	2007-04-26	1620	P
-USGS	01423000	2007-04-27	1220	P
-USGS	01423000	2007-04-28	1140	P
-USGS	01423000	2007-04-29	1050	P
-USGS	01423000	2007-04-30	909	P
-USGS	01423000	2007-05-01	780	P
-USGS	01423000	2007-05-02	822	P
-USGS	01423000	2007-05-03	704	P
-USGS	01423000	2007-05-04	605	P
-USGS	01423000	2007-05-05	547	P
-USGS	01423000	2007-05-06	497	P
-USGS	01423000	2007-05-07	453	P
-USGS	01423000	2007-05-08	417	P
-USGS	01423000	2007-05-09	387	P
-USGS	01423000	2007-05-10	423	P
-USGS	01423000	2007-05-11	800	P
-USGS	01423000	2007-05-12	602	P
-USGS	01423000	2007-05-13	463	P
-USGS	01423000	2007-05-14	411	P
-USGS	01423000	2007-05-15	380	P
-USGS	01423000	2007-05-16	396	P
-USGS	01423000	2007-05-17	458	P
-USGS	01423000	2007-05-18	370	P
-USGS	01423000	2007-05-19	344	P
-USGS	01423000	2007-05-20	442	P
-USGS	01423000	2007-05-21	407	P
-USGS	01423000	2007-05-22	325	P
-USGS	01423000	2007-05-23	287	P
-USGS	01423000	2007-05-24	263	P
-USGS	01423000	2007-05-25	240	P
-USGS	01423000	2007-05-26	221	P
-USGS	01423000	2007-05-27	211	P
-USGS	01423000	2007-05-28	241	P
-USGS	01423000	2007-05-29	215	P
-USGS	01423000	2007-05-30	181	P
-USGS	01423000	2007-05-31	166	P
-USGS	01423000	2007-06-01	164	P
-USGS	01423000	2007-06-02	203	P
-USGS	01423000	2007-06-03	230	P
-USGS	01423000	2007-06-04	323	P
-USGS	01423000	2007-06-05	325	P
-USGS	01423000	2007-06-06	255	P
-USGS	01423000	2007-06-07	196	P
-USGS	01423000	2007-06-08	170	P
-USGS	01423000	2007-06-09	155	P
-USGS	01423000	2007-06-10	139	P
-USGS	01423000	2007-06-11	129	P
-USGS	01423000	2007-06-12	123	P
-USGS	01423000	2007-06-13	119	P
-USGS	01423000	2007-06-14	112	P
-USGS	01423000	2007-06-15	104	P
-USGS	01423000	2007-06-16	100	P
-USGS	01423000	2007-06-17	120	P
-USGS	01423000	2007-06-18	104	P
-USGS	01423000	2007-06-19	106	P
-USGS	01423000	2007-06-20	377	P
-USGS	01423000	2007-06-21	217	P
-USGS	01423000	2007-06-22	205	P
-USGS	01423000	2007-06-23	165	P
-USGS	01423000	2007-06-24	140	P
-USGS	01423000	2007-06-25	126	P
-USGS	01423000	2007-06-26	116	P
-USGS	01423000	2007-06-27	116	P
-USGS	01423000	2007-06-28	147	P
-USGS	01423000	2007-06-29	146	P
-USGS	01423000	2007-06-30	116	P
-USGS	01423000	2007-07-01	105	P
-USGS	01423000	2007-07-02	97	P
-USGS	01423000	2007-07-03	91	P
-USGS	01423000	2007-07-04	97	P
-USGS	01423000	2007-07-05	134	P
-USGS	01423000	2007-07-06	156	P
-USGS	01423000	2007-07-07	135	P
-USGS	01423000	2007-07-08	124	P
-USGS	01423000	2007-07-09	123	P
-USGS	01423000	2007-07-10	177	P
-USGS	01423000	2007-07-11	144	P
-USGS	01423000	2007-07-12	150	P
-USGS	01423000	2007-07-13	131	P
-USGS	01423000	2007-07-14	110	P
-USGS	01423000	2007-07-15	100	P
-USGS	01423000	2007-07-16	97	P
-USGS	01423000	2007-07-17	93	P
-USGS	01423000	2007-07-18	96	P
-USGS	01423000	2007-07-19	116	P
-USGS	01423000	2007-07-20	316	P
-USGS	01423000	2007-07-21	245	P
-USGS	01423000	2007-07-22	159	P
-USGS	01423000	2007-07-23	145	P
-USGS	01423000	2007-07-24	207	P
-USGS	01423000	2007-07-25	174	P
-USGS	01423000	2007-07-26	139	P
-USGS	01423000	2007-07-27	144	P
-USGS	01423000	2007-07-28	240	P
-USGS	01423000	2007-07-29	231	P
-USGS	01423000	2007-07-30	164	P
-USGS	01423000	2007-07-31	140	P
-USGS	01423000	2007-08-01	125	P
-USGS	01423000	2007-08-02	112	P
-USGS	01423000	2007-08-03	114	P
-USGS	01423000	2007-08-04	110	P
-USGS	01423000	2007-08-05	95	P
-USGS	01423000	2007-08-06	87	P
-USGS	01423000	2007-08-07	85	P
-USGS	01423000	2007-08-08	118	P
-USGS	01423000	2007-08-09	121	P
-USGS	01423000	2007-08-10	489	P
-USGS	01423000	2007-08-11	488	P
-USGS	01423000	2007-08-12	261	P
-USGS	01423000	2007-08-13	201	P
-USGS	01423000	2007-08-14	171	P
-USGS	01423000	2007-08-15	150	P
-USGS	01423000	2007-08-16	155	P
-USGS	01423000	2007-08-17	256	P
-USGS	01423000	2007-08-18	188	P
-USGS	01423000	2007-08-19	163	P
-USGS	01423000	2007-08-20	143	P
-USGS	01423000	2007-08-21	158	P
-USGS	01423000	2007-08-22	174	P
-USGS	01423000	2007-08-23	148	P
-USGS	01423000	2007-08-24	138	P
-USGS	01423000	2007-08-25	141	P
-USGS	01423000	2007-08-26	123	P
-USGS	01423000	2007-08-27	112	P
-USGS	01423000	2007-08-28	103	P
-USGS	01423000	2007-08-29	95	P
-USGS	01423000	2007-08-30	89	P
-USGS	01423000	2007-08-31	84	P
-USGS	01423000	2007-09-01	79	P
-USGS	01423000	2007-09-02	74	P
-USGS	01423000	2007-09-03	70	P
-USGS	01423000	2007-09-04	67	P
-USGS	01423000	2007-09-05	63	P
-USGS	01423000	2007-09-06	60	P
-USGS	01423000	2007-09-07	58	P
-USGS	01423000	2007-09-08	68	P
-USGS	01423000	2007-09-09	135	P
-USGS	01423000	2007-09-10	124	P
-USGS	01423000	2007-09-11	983	P
-USGS	01423000	2007-09-12	1220	P
-USGS	01423000	2007-09-13	542	P
-USGS	01423000	2007-09-14	397	P
-USGS	01423000	2007-09-15		
-USGS	01423000	2007-09-16	625	P
-USGS	01423000	2007-09-17	465	P
-USGS	01423000	2007-09-18	392	P
diff --git a/scikits/learn/datasets/nwis/src/convert.py b/scikits/learn/datasets/nwis/src/convert.py
deleted file mode 100644
index 3efa78cb00fdf4b18606c86997daf01961463e5d..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/nwis/src/convert.py
+++ /dev/null
@@ -1,26 +0,0 @@
-import numpy, csv, time
-from scikits.learn.datasets.misc import dumpvar
-
-
-f = open('01423000.dly', 'r')
-reader = csv.reader(f)
-reader.dialect.delimiter='\t'
-
-n_comments = 28
-for i in range(n_comments):
-	reader.next()
-
-LABELS = ['agency', 'station', 'date', 'discharge', 'code']
-
-table = numpy.array([a for a in reader])
-
-AGENCY, STATION, DATE, DISCHARGE, CODE = table.transpose()
-
-# Write the data in nwis.py
-a = open("../nwis.py", "w")
-a.write('# Autogenerated by convert.py at %s\n\n' % 
-        time.strftime("%a, %d %b %Y %H:%M:%S +0000", time.gmtime()))
-
-for i in range(2,5):
-	a.writelines(dumpvar(list(table[:,i]), LABELS[i]))
-a.close()
diff --git a/scikits/learn/datasets/oldfaithful/COPYING b/scikits/learn/datasets/oldfaithful/COPYING
deleted file mode 100644
index 465e793f163956fa6218b782b8197e06677cdcdd..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/oldfaithful/COPYING
+++ /dev/null
@@ -1,34 +0,0 @@
-# The code and descriptive text is copyrighted and offered under the terms of
-# the BSD License from the authors; see below. However, the actual dataset may
-# have a different origin and intellectual property status. See the SOURCE and
-# COPYRIGHT variables for this information.
-
-# Copyright (c) 2007 David Cournapeau <cournape@gmail.com>
-#
-# All rights reserved.
-#
-# Redistribution and use in source and binary forms, with or without
-# modification, are permitted provided that the following conditions are
-# met:
-#
-#     * Redistributions of source code must retain the above copyright
-#       notice, this list of conditions and the following disclaimer.
-#     * Redistributions in binary form must reproduce the above copyright
-#       notice, this list of conditions and the following disclaimer in
-#       the documentation and/or other materials provided with the
-#       distribution.
-#     * Neither the author nor the names of any contributors may be used
-#       to endorse or promote products derived from this software without
-#       specific prior written permission.
-#
-# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
-# TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
-# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
-# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
-# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
-# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
-# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
-# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
-# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
-# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
diff --git a/scikits/learn/datasets/oldfaithful/README b/scikits/learn/datasets/oldfaithful/README
deleted file mode 100644
index de148e6d6beb179a1409047ae3c00a44cf49859f..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/oldfaithful/README
+++ /dev/null
@@ -1,6 +0,0 @@
-Each OldfaithfulC*.txt is one column of the datasets as presented in Azzalini
-and Bowman. The Oldfaithful.txt is simply a cat of all thos files: this is just
-to make checking easier. The data in the txt are *exactly* the same than the
-ones in Azzalini and Bowman: again, post processing them in python is easy
-(converting the time in seconds, etc...), and having exactly the data of the
-reference makes it easier to check.
diff --git a/scikits/learn/datasets/oldfaithful/__init__.py b/scikits/learn/datasets/oldfaithful/__init__.py
deleted file mode 100644
index 58177e96c0218c012b0a792406300fe1dcbc7a1a..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/oldfaithful/__init__.py
+++ /dev/null
@@ -1,8 +0,0 @@
-#! /usr/bin/env python
-# Last Change: Fri Jun 08 12:00 PM 2007 J
-import data as _faith
-__doc__     = _faith.DESCRSHORT
-copyright   = _faith.COPYRIGHT
-source      = _faith.SOURCE
-
-load        = _faith.load
diff --git a/scikits/learn/datasets/oldfaithful/data.py b/scikits/learn/datasets/oldfaithful/data.py
deleted file mode 100644
index d71bbaf600934a986bce0c505e2f35c3976af26a..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/oldfaithful/data.py
+++ /dev/null
@@ -1,92 +0,0 @@
-#! /usr/bin/env python
-# -*- coding: utf-8 -*-
-
-# The code and descriptive text is copyrighted and offered under the terms of
-# the BSD License from the authors; see below. However, the actual dataset may
-# have a different origin and intellectual property status. See the SOURCE and
-# COPYRIGHT variables for this information.
-
-# Copyright (c) 2007 David Cournapeau <cournape@gmail.com>
-#
-# All rights reserved.
-#
-# Redistribution and use in source and binary forms, with or without
-# modification, are permitted provided that the following conditions are
-# met:
-#
-#     * Redistributions of source code must retain the above copyright
-#       notice, this list of conditions and the following disclaimer.
-#     * Redistributions in binary form must reproduce the above copyright
-#       notice, this list of conditions and the following disclaimer in
-#       the documentation and/or other materials provided with the
-#       distribution.
-#     * Neither the author nor the names of any contributors may be used
-#       to endorse or promote products derived from this software without
-#       specific prior written permission.
-#
-# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
-# TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
-# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
-# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
-# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
-# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
-# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
-# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
-# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
-# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
-# Last Change: Fri Jun 08 11:00 AM 2007 J
-
-"""Old faithful dataset."""
-
-__docformat__ = 'restructuredtext'
-
-COPYRIGHT   = """See SOURCE. Pr Azzalini has explicitely given his consent for
-the use of those data in scipy."""
-TITLE       = "Old Faithful Geyser Data"
-SOURCE      = """AZZALINI A., BOWMAN A. W. (1990).  A look at some data on the
-Old Faithful Geyser.  Applied Statistics (Journal of the Royal Statistical
-Society series C), vol. 39, pp. 357-365. Data collected by the Yellowstone Park
-geologist, R. A. Hutchinson.
-
-References: 
-    - Härdle, W. (1991) Smoothing Techniques with Implementation in S.  New
-    York: Springer.
-    - Azzalini, A. and Bowman, A. W. (1990).  A look at some data on the Old
-Faithful geyser. Applied Statistics, 39, 357--365.
-
-Those data are exactly the ones from Azzalini and Bowman's article."""
-
-DESCRSHORT  = """Waiting time between eruptions and the duration of the
-eruption for the Old Faithful geyser in Yellowstone National Park, Wyoming,
-USA. Waiting times and duration time are in seconds"""
-
-DESCRLONG   = """According to Azzalini and Bowman's article, those data
-were recorded continuously from 1th August to 15th August 1985.
-
-Some of the durations times are labelled as L, M or S (Large, Small, Medium).
-According to Azzalini and Bowman's paper: "because the unbroken sequence
-required measurements to be taken at night, some duration times are recorded as
-L (long), S (short) and M (medium). Other data sets do not contain a con-
-tinuous stream of data, making it difficult to deal with time series features."
-"""
-
-NOTE        = """Eruptions time in seconds, waiting time to next eruption (in
-seconds)"""
-
-def load():
-    """load the actual data and returns them.
-    
-    :returns:
-        data: recordarray
-            a record array of the data.
-    """
-    import numpy
-    from oldfaithful import waiting, duration
-    assert len(waiting) == len(duration) == 299
-    data    = numpy.empty(len(waiting), \
-            [('duration', '|S5'), ('waiting', 'int')])
-    data['waiting']    = waiting
-    data['duration']   = duration
-    return {'data': data}
diff --git a/scikits/learn/datasets/oldfaithful/oldfaithful.py b/scikits/learn/datasets/oldfaithful/oldfaithful.py
deleted file mode 100644
index d798b12e08edde641ce80585cbbda98bc1ec374a..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/oldfaithful/oldfaithful.py
+++ /dev/null
@@ -1,45 +0,0 @@
-duration = [241, 129, 'L', 'L', 'L', 'S', 263, 257, 122, 290, 110, 327, 97,
-292, 263, 106, 280, 'S', 284, 253, 114, 298, 'S', 'L', 'S', 'L', 170, 270, 244,
-223, 211, 268, 133, 293, 156, 249, 132, 286, 110, 276, 136, 248, 'S', 'L', 'S',
-'L', 113, 256, 125, 268, 133, 240, 106, 260, 131, 269, 233, 200, 224, 240, 117,
-316, 'S', 'L', 'S', 'L', 'S', 'L', 212, 130, 270, 121, 249, 252, 260, 116, 279,
-229, 242, 250, 280, 109, 'L', 'M', 'L', 'S', 267, 123, 255, 115, 280, 104, 263,
-106, 276, 112, 267, 98, 302, 109, 306, 98, 257, 'S', 'L', 'S', 272, 120, 'L',
-176, 284, 234, 117, 247, 108, 280, 110, 282, 127, 287, 109, 246, 279, 'L', 'S',
-'L', 'L', 253, 248, 236, 225, 265, 148, 250, 228, 259, 232, 281, 102, 298, 256,
-275, 'L', 'L', 'L', 'L', 119, 276, 50, 295, 104, 275, 102, 285, 110, 270, 112,
-267, 267, 240, 288, 'L', 'L', 'S', 'L', 116, 275, 120, 222, 172, 290, 207, 263,
-108, 264, 149, 271, 126, 261, 262, 107, 295, 109, 'L', 'L', 'L', 232, 111, 282,
-121, 268, 112, 250, 114, 255, 195, 253, 113, 299, 111, 240, 118, 286, 'L', 'S',
-'L', 'L', 143, 265, 253, 262, 120, 267, 105, 270, 97, 282, 154, 222, 254, 116,
-261, 'L', 'L', 'L', 253, 240, 248, 113, 268, 117, 253, 103, 267, 255, 238, 263,
-118, 267, 256, 115, 265, 'M', 'L', 'S', 'L', 197, 110, 277, 110, 277, 276, 255,
-116, 299, 118, 258, 252, 272, 264, 277, 'S', 'L', 'L', 235, 'S', 270, 108, 240,
-165, 284, 238, 117, 298, 111, 288, 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'S', 'L',
-116, 260, 100, 286, 117, 281, 116, 265, 128, 245, 124, 'L', 'L', 'S']
-
-waiting = [4800, 4260, 3420, 4800, 4500, 4620, 3600, 5160, 4620, 3360, 4860,
-3000, 5340, 3240, 5400, 4380, 3600, 4980, 3900, 4920, 5040, 3240, 5100, 3480,
-4740, 3420, 5280, 4080, 4560, 4680, 4440, 5100, 4500, 3900, 4560, 3480, 5460,
-3000, 5220, 2880, 5580, 3240, 5160, 3180, 4680, 3120, 4980, 3600, 5220, 2940,
-4800, 3600, 5520, 2580, 5340, 3600, 5040, 4140, 4440, 4260, 6480, 3000, 4620,
-3420, 4800, 3660, 4920, 2880, 4860, 4380, 3720, 4740, 3240, 4800, 4380, 4860,
-3720, 4860, 4260, 4740, 4860, 4440, 3540, 4860, 3960, 5220, 3180, 4800, 3000,
-5220, 3060, 4920, 3480, 4860, 2940, 5520, 3000, 5280, 3720, 5580, 3360, 5340,
-3060, 4740, 3480, 4920, 3120, 5280, 3120, 4680, 4140, 4500, 4620, 3180, 4800,
-3300, 5220, 3180, 5100, 3660, 5580, 3240, 4560, 4800, 4860, 3540, 5160, 4680,
-4260, 4620, 4560, 5640, 4500, 3000, 4980, 4920, 4320, 4620, 4500, 3900, 4740,
-4320, 4680, 4620, 4740, 4500, 4680, 3840, 4800, 2940, 5280, 3240, 5100, 3060,
-5760, 3000, 4800, 4680, 4860, 4320, 4500, 4680, 5220, 4140, 3300, 4980, 2940,
-4920, 3420, 5040, 3420, 5040, 4380, 4680, 3420, 4740, 3420, 5400, 3720, 5220,
-4680, 3120, 5880, 2880, 4680, 4740, 3900, 5040, 3000, 4980, 3600, 4800, 3000,
-5280, 3000, 5040, 4440, 4560, 3900, 5340, 2940, 5280, 3060, 4680, 5100, 3900,
-4500, 4620, 4140, 5520, 4080, 5220, 3660, 4860, 3300, 5580, 3180, 5040, 4200,
-4380, 5580, 3000, 5220, 4620, 4440, 4320, 4920, 4440, 4800, 2940, 5460, 3180,
-5160, 2940, 4740, 5340, 5220, 4560, 3540, 4800, 5340, 2700, 5580, 4320, 4260,
-3240, 4740, 4440, 3900, 4680, 3420, 5220, 4320, 5040, 2820, 5040, 3420, 5220,
-4080, 5160, 4500, 4380, 3180, 4920, 5580, 4620, 3240, 5760, 2880, 5340, 3780,
-5040, 4560, 3720, 4980, 3000, 5100, 4680, 4680, 4860, 4680, 4560, 4440, 4860,
-3960, 5040, 2880, 5580, 2820, 5220, 3060, 4680, 3240, 5220, 3120, 5100, 3480,
-5280, 4740]
-
diff --git a/scikits/learn/datasets/oldfaithful/src/Oldfaithful.txt b/scikits/learn/datasets/oldfaithful/src/Oldfaithful.txt
deleted file mode 100644
index ba3cadf10cc84efe5d5f660d74415f8adf9002aa..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/oldfaithful/src/Oldfaithful.txt
+++ /dev/null
@@ -1,299 +0,0 @@
-4:01,80
-2:09 ,71
-L,57
-L,80
-L,75
-S,77
-4:23,60
-4:17,86
-2:02,77
-4:50,56
-1:50,81
-5:27,50
-1:37,89
-4:52,54
-4:23,90
-1:46,73
-4:40,60
-S,83
-4:44,65
-4:13,82
-1:54,84
-4:58,54
-S,85
-L,58
-S,79
-L,57
-2:50,88
-4:30,68
-4:04,76
-3:43,78
-3:31,74
-4:28,85
-2:13,75
-4:53,65
-2:36,76
-4:09,58
-2:12 ,91
-4:46,50
-1:50,87
-4:36,48
-2:16,93
-4:08,54
-S,86
-L,53
-S,78
-L,52
-1:53,83
-4:16,60
-2:05,87
-4:28,49
-2:13,80
-4:00,60
-1:46,92
-4:20,43
-2:11,89
-4:29,60
-3:53,84
-3:20,69
-3:44,74
-4:00,71
-1:57,108
-5:16,50
-S,77
-L,57
-S,80
-L,61
-S,82
-L,48
-3:32,81
-2:10,73
-4:30,62
-2:01,79
-4:09,54
-4:12,80
-4:20,73
-1:56,81
-4:39,62
-3:49,81
-4:02,71
-4:10,79
-4:40,81
-1:49,74
-L,59
-M,81
-L,66
-S,87
-4:27,53
-2:03,80
-4:15,50
-1:55,87
-4:40,51
-1:44,82
-4:23,58
-1:46,81
-4:36,49
-1:52,92
-4:27,50
-1:38,88
-5:02,62
-1:49,93
-5:06,56
-1:38,89
-4:17,51
-S,79
-L,58
-S,82
-4:32,52
-2:00,88
-L,52
-2:56,78
-4:44,69
-3:54,75
-1:57,77
-4:07,53
-1:48,80
-4:40,55
-1:50,87
-4:42,53
-2:07,85
-4:47,61
-1:49,93
-4:06,54
-4:39,76
-L,80
-S,81
-L,59
-L,86
-4:13,78
-4:08,71
-3:56,77
-3:45,76
-4:25,94
-2:28,75
-4:10,50
-3:48,83
-4:19,82
-3:52,72
-4:41,77
-1:42,75
-4:58,65
-4:16,79
-4:35,72
-L,78
-L,77
-L,79
-L,75
-1:59,78
-4:36,64
-0:50,80
-4:55,49
-1:44,88
-4:35,54
-1:42,85
-4:45,51
-1:50,96
-4:30,50
-1:52,80
-4:27,78
-4:27,81
-4:00,72
-4:48,75
-L,78
-L,87
-S,69
-L,55
-1:56,83
-4:35,49
-2:00,82
-3:42,57
-2:52,84
-4:50,57
-3:27,84
-4:23,73
-1:48,78
-4:24,57
-2:29,79
-4:31,57
-2:06,90
-4:21,62
-4:22,87
-1:47,78
-4:55,52
-1:49,98
-L,48
-L,78
-L,79
-3:52,65
-1:51,84
-4:42,50
-2:01,83
-4:28,60
-1:52,80
-4:10,50
-1:54,88
-4:15,50
-3:15,84
-4:13,74
-1:53,76
-4:59,65
-1:51,89
-4:00,49
-1:58,88
-4:46,51
-L,78
-S,85
-L,65
-L,75
-2:23,77
-4:25,69
-4:13,92
-4:22,68
-2:00,87
-4:27,61
-1:45,81
-4:30,55
-1:37,93
-4:42,53
-2:34,84
-3:42,70
-4:14,73
-1:56,93
-4:21,50
-L,87
-L,77
-L,74
-4:13,72
-4:00,82
-4:08,74
-1:53,80
-4:28,49
-1:57,91
-4:13,53
-1:43,86
-4:27,49
-4:15,79
-3:58,89
-4:23,87
-1:58,76
-4:27,59
-4:16,80
-1:55,89
-4:25,45
-M,93
-L,72
-S,71
-L,54
-3:17,79
-1:50,74
-4:37,65
-1:50,78
-4:37,57
-4:36,87
-4:15,72
-1:56,84
-4:59,47
-1:58,84
-4:18,57
-4:12,87
-4:32,68
-4:24,86
-4:37,75
-S,73
-L,53
-L,82
-3:55,93
-S,77
-4:30,54
-1:48,96
-4:00,48
-2:45,89
-4:44,63
-3:58,84
-1:57,76
-4:58,62
-1:51,83
-4:48,50
-L,85
-L,78
-L,78
-L,81
-L,78
-L,76
-L,74
-S,81
-L,66
-1:56,84
-4:20,48
-1:40,93
-4:46,47
-1:57,87
-4:41,51
-1:56,78
-4:25,54
-2:08,87
-4:05,52
-2:04,85
-L,58
-L,88
-S,79
diff --git a/scikits/learn/datasets/oldfaithful/src/OldfaithfulC1.txt b/scikits/learn/datasets/oldfaithful/src/OldfaithfulC1.txt
deleted file mode 100644
index e4856b3bbae12abe7f923385fcecd51877637fb4..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/oldfaithful/src/OldfaithfulC1.txt
+++ /dev/null
@@ -1,50 +0,0 @@
-4:01,80
-2:09 ,71
-L,57
-L,80
-L,75
-S,77
-4:23,60
-4:17,86
-2:02,77
-4:50,56
-1:50,81
-5:27,50
-1:37,89
-4:52,54
-4:23,90
-1:46,73
-4:40,60
-S,83
-4:44,65
-4:13,82
-1:54,84
-4:58,54
-S,85
-L,58
-S,79
-L,57
-2:50,88
-4:30,68
-4:04,76
-3:43,78
-3:31,74
-4:28,85
-2:13,75
-4:53,65
-2:36,76
-4:09,58
-2:12 ,91
-4:46,50
-1:50,87
-4:36,48
-2:16,93
-4:08,54
-S,86
-L,53
-S,78
-L,52
-1:53,83
-4:16,60
-2:05,87
-4:28,49
diff --git a/scikits/learn/datasets/oldfaithful/src/OldfaithfulC2.txt b/scikits/learn/datasets/oldfaithful/src/OldfaithfulC2.txt
deleted file mode 100644
index 6561b07470bc9e891e509d07e1b509408b3cf658..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/oldfaithful/src/OldfaithfulC2.txt
+++ /dev/null
@@ -1,50 +0,0 @@
-2:13,80
-4:00,60
-1:46,92
-4:20,43
-2:11,89
-4:29,60
-3:53,84
-3:20,69
-3:44,74
-4:00,71
-1:57,108
-5:16,50
-S,77
-L,57
-S,80
-L,61
-S,82
-L,48
-3:32,81
-2:10,73
-4:30,62
-2:01,79
-4:09,54
-4:12,80
-4:20,73
-1:56,81
-4:39,62
-3:49,81
-4:02,71
-4:10,79
-4:40,81
-1:49,74
-L,59
-M,81
-L,66
-S,87
-4:27,53
-2:03,80
-4:15,50
-1:55,87
-4:40,51
-1:44,82
-4:23,58
-1:46,81
-4:36,49
-1:52,92
-4:27,50
-1:38,88
-5:02,62
-1:49,93
diff --git a/scikits/learn/datasets/oldfaithful/src/OldfaithfulC3.txt b/scikits/learn/datasets/oldfaithful/src/OldfaithfulC3.txt
deleted file mode 100644
index 32f462f23831196bc04c7b476682bce42aae12ab..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/oldfaithful/src/OldfaithfulC3.txt
+++ /dev/null
@@ -1,50 +0,0 @@
-5:06,56
-1:38,89
-4:17,51
-S,79
-L,58
-S,82
-4:32,52
-2:00,88
-L,52
-2:56,78
-4:44,69
-3:54,75
-1:57,77
-4:07,53
-1:48,80
-4:40,55
-1:50,87
-4:42,53
-2:07,85
-4:47,61
-1:49,93
-4:06,54
-4:39,76
-L,80
-S,81
-L,59
-L,86
-4:13,78
-4:08,71
-3:56,77
-3:45,76
-4:25,94
-2:28,75
-4:10,50
-3:48,83
-4:19,82
-3:52,72
-4:41,77
-1:42,75
-4:58,65
-4:16,79
-4:35,72
-L,78
-L,77
-L,79
-L,75
-1:59,78
-4:36,64
-0:50,80
-4:55,49
diff --git a/scikits/learn/datasets/oldfaithful/src/OldfaithfulC4.txt b/scikits/learn/datasets/oldfaithful/src/OldfaithfulC4.txt
deleted file mode 100644
index fa5f4f7ceb3409a761f468479bf53d95fa993aa7..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/oldfaithful/src/OldfaithfulC4.txt
+++ /dev/null
@@ -1,50 +0,0 @@
-1:44,88
-4:35,54
-1:42,85
-4:45,51
-1:50,96
-4:30,50
-1:52,80
-4:27,78
-4:27,81
-4:00,72
-4:48,75
-L,78
-L,87
-S,69
-L,55
-1:56,83
-4:35,49
-2:00,82
-3:42,57
-2:52,84
-4:50,57
-3:27,84
-4:23,73
-1:48,78
-4:24,57
-2:29,79
-4:31,57
-2:06,90
-4:21,62
-4:22,87
-1:47,78
-4:55,52
-1:49,98
-L,48
-L,78
-L,79
-3:52,65
-1:51,84
-4:42,50
-2:01,83
-4:28,60
-1:52,80
-4:10,50
-1:54,88
-4:15,50
-3:15,84
-4:13,74
-1:53,76
-4:59,65
-1:51,89
diff --git a/scikits/learn/datasets/oldfaithful/src/OldfaithfulC5.txt b/scikits/learn/datasets/oldfaithful/src/OldfaithfulC5.txt
deleted file mode 100644
index 51a381364780799d28d53ee02732ba5dd4107de6..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/oldfaithful/src/OldfaithfulC5.txt
+++ /dev/null
@@ -1,50 +0,0 @@
-4:00,49
-1:58,88
-4:46,51
-L,78
-S,85
-L,65
-L,75
-2:23,77
-4:25,69
-4:13,92
-4:22,68
-2:00,87
-4:27,61
-1:45,81
-4:30,55
-1:37,93
-4:42,53
-2:34,84
-3:42,70
-4:14,73
-1:56,93
-4:21,50
-L,87
-L,77
-L,74
-4:13,72
-4:00,82
-4:08,74
-1:53,80
-4:28,49
-1:57,91
-4:13,53
-1:43,86
-4:27,49
-4:15,79
-3:58,89
-4:23,87
-1:58,76
-4:27,59
-4:16,80
-1:55,89
-4:25,45
-M,93
-L,72
-S,71
-L,54
-3:17,79
-1:50,74
-4:37,65
-1:50,78
diff --git a/scikits/learn/datasets/oldfaithful/src/OldfaithfulC6.txt b/scikits/learn/datasets/oldfaithful/src/OldfaithfulC6.txt
deleted file mode 100644
index b9576f6b99ac8cb6b074bd59d6ec55055646c740..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/oldfaithful/src/OldfaithfulC6.txt
+++ /dev/null
@@ -1,49 +0,0 @@
-4:37,57
-4:36,87
-4:15,72
-1:56,84
-4:59,47
-1:58,84
-4:18,57
-4:12,87
-4:32,68
-4:24,86
-4:37,75
-S,73
-L,53
-L,82
-3:55,93
-S,77
-4:30,54
-1:48,96
-4:00,48
-2:45,89
-4:44,63
-3:58,84
-1:57,76
-4:58,62
-1:51,83
-4:48,50
-L,85
-L,78
-L,78
-L,81
-L,78
-L,76
-L,74
-S,81
-L,66
-1:56,84
-4:20,48
-1:40,93
-4:46,47
-1:57,87
-4:41,51
-1:56,78
-4:25,54
-2:08,87
-4:05,52
-2:04,85
-L,58
-L,88
-S,79
diff --git a/scikits/learn/datasets/oldfaithful/src/convert.py b/scikits/learn/datasets/oldfaithful/src/convert.py
deleted file mode 100755
index f31211f921bb5238ee3faaffa3a929b39ffbb9a0..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/oldfaithful/src/convert.py
+++ /dev/null
@@ -1,36 +0,0 @@
-#! /usr/bin/env python
-# Last Change: Tue Jul 17 04:00 PM 2007 J
-
-# This script generates a python file from the txt data
-import csv
-from scikits.learn.datasets.misc import dumpvar
-
-dataname = 'Oldfaithful.txt'
-f = open(dataname, 'r')
-a = csv.reader(f)
-el = [i for i in a]
-duration = [i[0] for i in el]
-waiting = [i[1] for i in el]
-
-# Convert duration and waiting times in second
-duration2 = []
-for i in range(len(duration)):
-	if duration[i] == 'L':
-		duration2.append('L')
-	elif duration[i] == 'M':
-		duration2.append('M')
-	elif duration[i] == 'S':
-		duration2.append('S')
-	else:
-		m, s = duration[i].split(':')
-		m = int(m)
-		s = int(s)
-		assert s >= 0 and s < 60
-		duration2.append(m * 60 + s)
-waiting2 = [int(i) * 60 for i in waiting]
-
-# Write the data in oldfaitful.py
-a = open("../oldfaithful.py", "w")
-
-a.writelines(dumpvar(duration2, 'duration'))
-a.writelines(dumpvar(waiting2, 'waiting'))
diff --git a/scikits/learn/datasets/pendigits/COPYING b/scikits/learn/datasets/pendigits/COPYING
deleted file mode 100644
index 465e793f163956fa6218b782b8197e06677cdcdd..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/pendigits/COPYING
+++ /dev/null
@@ -1,34 +0,0 @@
-# The code and descriptive text is copyrighted and offered under the terms of
-# the BSD License from the authors; see below. However, the actual dataset may
-# have a different origin and intellectual property status. See the SOURCE and
-# COPYRIGHT variables for this information.
-
-# Copyright (c) 2007 David Cournapeau <cournape@gmail.com>
-#
-# All rights reserved.
-#
-# Redistribution and use in source and binary forms, with or without
-# modification, are permitted provided that the following conditions are
-# met:
-#
-#     * Redistributions of source code must retain the above copyright
-#       notice, this list of conditions and the following disclaimer.
-#     * Redistributions in binary form must reproduce the above copyright
-#       notice, this list of conditions and the following disclaimer in
-#       the documentation and/or other materials provided with the
-#       distribution.
-#     * Neither the author nor the names of any contributors may be used
-#       to endorse or promote products derived from this software without
-#       specific prior written permission.
-#
-# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
-# TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
-# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
-# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
-# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
-# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
-# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
-# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
-# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
-# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
diff --git a/scikits/learn/datasets/pendigits/README b/scikits/learn/datasets/pendigits/README
deleted file mode 100644
index 8b53e8194d2ab3de79550e4b3efef4dc8b31bd28..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/pendigits/README
+++ /dev/null
@@ -1,2 +0,0 @@
-The original data are taking from the UCI Machine Learning:
-http://mlearn.ics.uci.edu/MLRepository.html
diff --git a/scikits/learn/datasets/pendigits/__init__.py b/scikits/learn/datasets/pendigits/__init__.py
deleted file mode 100644
index 043d06079de03f7d3793cf81c796f01dd8c8008d..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/pendigits/__init__.py
+++ /dev/null
@@ -1,8 +0,0 @@
-#! /usr/bin/env python
-# Last Change: Sun Jul 22 03:00 PM 2007 J
-import data as _pendigit
-__doc__     = _pendigit.DESCRSHORT
-copyright   = _pendigit.COPYRIGHT
-source      = _pendigit.SOURCE
-
-import testing, training
diff --git a/scikits/learn/datasets/pendigits/data.py b/scikits/learn/datasets/pendigits/data.py
deleted file mode 100644
index db8f51364a71438774f68d601ff4fb06f669d978..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/pendigits/data.py
+++ /dev/null
@@ -1,156 +0,0 @@
-#! /usr/bin/env python
-# -*- coding: utf-8 -*-
-# Last Change: Sun Jul 22 03:00 PM 2007 J
-
-# The code and descriptive text is copyrighted and offered under the terms of
-# the BSD License from the authors; see below. However, the actual dataset may
-# have a different origin and intellectual property status. See the SOURCE and
-# COPYRIGHT variables for this information.
-
-# Copyright (c) 2007 David Cournapeau <cournape@gmail.com>
-#
-# All rights reserved.
-#
-# Redistribution and use in source and binary forms, with or without
-# modification, are permitted provided that the following conditions are
-# met:
-#
-#     * Redistributions of source code must retain the above copyright
-#       notice, this list of conditions and the following disclaimer.
-#     * Redistributions in binary form must reproduce the above copyright
-#       notice, this list of conditions and the following disclaimer in
-#       the documentation and/or other materials provided with the
-#       distribution.
-#     * Neither the author nor the names of any contributors may be used
-#       to endorse or promote products derived from this software without
-#       specific prior written permission.
-#
-# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
-# TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
-# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
-# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
-# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
-# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
-# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
-# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
-# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
-# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
-"""Pen-based recognition of handwritten digits."""
-
-__docformat__ = 'restructuredtext'
-
-COPYRIGHT   = """See SOURCE. """
-TITLE       = """Pen-Based Recognition of Handwritten Digits Original,
-unnormalized version"""
-SOURCE      = """
-E. Alpaydin, Fevzi. Alimoglu
-Department of Computer Engineering
-Bogazici University, 80815 Istanbul Turkey
-alpaydin@boun.edu.tr
-September 1998
-
-References: 
-	F. Alimoglu (1995) Combining Multiple Classifiers for Pen-Based
-	Handwritten Digit Recognition, 
-	MSc Thesis, Institute of Graduate Studies in Science and 
-	Engineering, Bogazici University.
-	http://www.cmpe.boun.edu.tr/~alimoglu/alimoglu.ps.gz
-
-	F. Alimoglu, E. Alpaydin, "Methods of Combining Multiple Classifiers 
-	Based on Different Representations for Pen-based Handwriting
-	Recognition," Proceedings of the Fifth Turkish Artificial 
-	Intelligence and Artificial Neural Networks Symposium (TAINN 96), 
-	June 1996, Istanbul, Turkey.
-	http://www.cmpe.boun.edu.tr/~alimoglu/tainn96.ps.gz."""
-
-DESCRSHORT  = """
-We create a digit database by collecting 250 samples from 44 writers.
-The samples written by 30 writers are used for training,
-cross-validation and writer dependent testing, and the digits 
-written by the other 14 are used for writer independent testing. This
-database is available in the UNIPEN format."""
-
-DESCRLONG   = """
-We create a digit database by collecting 250 samples from 44 writers.
-The samples written by 30 writers are used for training,
-cross-validation and writer dependent testing, and the digits 
-written by the other 14 are used for writer independent testing. This
-database is available in the UNIPEN format.
-
-We use a WACOM PL-100V pressure sensitive tablet with an integrated 
-LCD display and a cordless stylus. The input and display areas are
-located in the same place. Attached to the serial port of an Intel 
-486 based PC, it allows us to collect handwriting samples. The tablet
-sends $x$ and $y$ tablet coordinates and pressure level values of the
-pen at fixed time intervals (sampling rate) of 100 miliseconds. 
-
-These writers are asked to write 250 digits in random order inside 
-boxes of 500 by 500 tablet pixel resolution.  Subject are monitored 
-only during the first entry screens. Each screen contains five boxes
-with the digits to be written displayed above. Subjects are told to
-write only inside these boxes.  If they make a mistake or are unhappy
-with their writing, they are instructed to clear the content of a box 
-by using an on-screen button. The first ten digits are ignored 
-because most writers are not familiar with this type of input devices,
-but subjects are not aware of this. 
-
-In our study, we use only ($x, y$) coordinate information. The stylus
-pressure level values are ignored. The raw data that we capture 
-from the tablet consist of integer values between 0 and 500 
-(tablet input box resolution). 
-
-In order to train and test our classifiers, we need to represent 
-digits as constant length feature vectors. A commonly used technique
-leading to good results is resampling the ( x_t, y_t) points. 
-Temporal resampling (points regularly spaced in time) or spatial
-resampling (points regularly spaced in arc length) can be used here. 
-Raw point data are already regularly spaced in time but the distance
-between them is variable. Previous research showed that spatial
-resampling to obtain a constant number of regularly spaced points 
-on the trajectory yields much better performance, because it provides 
-a better alignment between points. Our resampling algorithm uses 
-simple linear interpolation between pairs of points. The resampled
-digits are represented as a sequence of T points ( x_t, y_t )_{t=1}^T,
-regularly spaced in arc length, as opposed to the input sequence, 
-which is regularly spaced in time.
-
-So, the input vector size is 2*T, two times the number of points
-resampled. We considered spatial resampling to T=8,12,16 points in our
-experiments and found that T=8 gave the best trade-off between 
-accuracy and complexity.
-"""
-
-NOTE        = """
-Number of Instances
--------------------
-
-pendigits-orig.tra	Training	7494
-pendigits-orig.tes	Testing		3498
-
-The way we used the dataset was to use first half of training for 
-actual training, one-fourth for validation and one-fourth
-for writer-dependent testing. The test set was used for 
-writer-independent testing and is the actual quality measure.
-
-pendigits.tra divides into
-    Actual training	set	3748
-    Validation		1873
-    Writer-dependent test	1873
-
-Number of Attributes
---------------------
-
-16 (8 (x, y) coordinates)
-
-For Each Attribute:
--------------------
-
-All input attributes are integers in the range 0..100.
-
-Missing Attribute Values
-------------------------
-
-None 
-"""
diff --git a/scikits/learn/datasets/pendigits/setup.py b/scikits/learn/datasets/pendigits/setup.py
deleted file mode 100644
index bc27b247f20c9c1971b7657e60e9afe08a09f848..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/pendigits/setup.py
+++ /dev/null
@@ -1,12 +0,0 @@
-#!/usr/bin/env python
-
-def configuration(parent_package='',top_path=None):
-    from numpy.distutils.misc_util import Configuration
-    config = Configuration('pendigits',parent_package,top_path)
-    config.add_subpackage('training')
-    config.add_subpackage('testing')
-    config.make_config_py() # installs __config__.py
-    return config
-
-if __name__ == '__main__':
-    print 'This is the wrong setup.py file to run'
diff --git a/scikits/learn/datasets/pendigits/src/convert.py b/scikits/learn/datasets/pendigits/src/convert.py
deleted file mode 100755
index ba521d735663815ce992c1a218c7d65385725858..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/pendigits/src/convert.py
+++ /dev/null
@@ -1,25 +0,0 @@
-#! /usr/bin/env python
-# Last Change: Sun Jul 22 01:00 PM 2007 J
-
-# This script generates a python file from the txt data
-import csv
-from scikits.learn.datasets.misc import dumpvar
-
-dataname_tra = 'pendigits.tra'
-dataname_tes = 'pendigits.tes'
-f = open(dataname_tra, 'r')
-a = csv.reader(f)
-tra = [[int(j) for j in i] for i in a]
-
-f = open(dataname_tes, 'r')
-a = csv.reader(f)
-tes = [[int(j) for j in i] for i in a]
-
-# Write the data in pendigits.py
-ftra = open("../pendigits_tra.py", "w")
-ftes = open("../pendigits_tes.py", "w")
-
-ftra.writelines(dumpvar(tra, 'training'))
-ftra.close()
-ftes.writelines(dumpvar(tes, 'testing'))
-ftes.close()
diff --git a/scikits/learn/datasets/pendigits/src/index.txt b/scikits/learn/datasets/pendigits/src/index.txt
deleted file mode 100644
index ecd62cf01ba5a02b58c6ee98a30c40d7f82ccf8b..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/pendigits/src/index.txt
+++ /dev/null
@@ -1,6 +0,0 @@
-ftp://ftp.ics.uci.edu/pub/machine-learning-databases/pendigits/pendigits-orig.tes.Z
-ftp://ftp.ics.uci.edu/pub/machine-learning-databases/pendigits/pendigits-orig.names
-ftp://ftp.ics.uci.edu/pub/machine-learning-databases/pendigits/pendigits-orig.tra.Z
-ftp://ftp.ics.uci.edu/pub/machine-learning-databases/pendigits/pendigits.names
-ftp://ftp.ics.uci.edu/pub/machine-learning-databases/pendigits/pendigits.tes
-ftp://ftp.ics.uci.edu/pub/machine-learning-databases/pendigits/pendigits.tra
diff --git a/scikits/learn/datasets/pendigits/src/pendigits-orig.names b/scikits/learn/datasets/pendigits/src/pendigits-orig.names
deleted file mode 100644
index 7ee5178c0efe2f51727f2c21705241fa714c1299..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/pendigits/src/pendigits-orig.names
+++ /dev/null
@@ -1,95 +0,0 @@
-1. Title of Database: Pen-Based Recognition of Handwritten Digits
-		Original, unnormalized version
-2. Source:
-	E. Alpaydin, Fevzi. Alimoglu
-	Department of Computer Engineering
-	Bogazici University, 80815 Istanbul Turkey
-	alpaydin@boun.edu.tr
-	September 1998
-
-3. Past Usage:
-	F. Alimoglu (1995) Combining Multiple Classifiers for Pen-Based
-	Handwritten Digit Recognition, 
-	MSc Thesis, Institute of Graduate Studies in Science and 
-	Engineering, Bogazici University.
-	http://www.cmpe.boun.edu.tr/~alimoglu/alimoglu.ps.gz
-
-	F. Alimoglu, E. Alpaydin, "Methods of Combining Multiple Classifiers 
-	Based on Different Representations for Pen-based Handwriting
-	Recognition," Proceedings of the Fifth Turkish Artificial 
-	Intelligence and Artificial Neural Networks Symposium (TAINN 96), 
-	June 1996, Istanbul, Turkey.
-	http://www.cmpe.boun.edu.tr/~alimoglu/tainn96.ps.gz
-
-	
-4. Relevant Information:
-
-	We create a digit database by collecting 250 samples from 44 writers.
-	The samples written by 30 writers are used for training,
-	cross-validation and writer dependent testing, and the digits 
-	written by the other 14 are used for writer independent testing. This
-	database is available in the UNIPEN format.
-
-	We use a WACOM PL-100V pressure sensitive tablet with an integrated 
-	LCD display and a cordless stylus. The input and display areas are
-	located in the same place. Attached to the serial port of an Intel 
-	486 based PC, it allows us to collect handwriting samples. The tablet
-	sends $x$ and $y$ tablet coordinates and pressure level values of the
-	pen at fixed time intervals (sampling rate) of 100 miliseconds. 
-
-	These writers are asked to write 250 digits in random order inside 
-	boxes of 500 by 500 tablet pixel resolution.  Subject are monitored 
-	only during the first entry screens. Each screen contains five boxes
-	with the digits to be written displayed above. Subjects are told to
-	write only inside these boxes.  If they make a mistake or are unhappy
-	with their writing, they are instructed to clear the content of a box 
-	by using an on-screen button. The first ten digits are ignored 
-	because most writers are not familiar with this type of input devices,
-	but subjects are not aware of this. 
-
-	In our study, we use only ($x, y$) coordinate information. The stylus
-	pressure level values are ignored. The raw data that we capture 
-	from the tablet consist of integer values between 0 and 500 
-	(tablet input box resolution). 
-
-	pendigits-orig contain original, unnormalized data. pendigits is the 
-	normalized and resampled version where all inputs are of the same
-	length. Here because of speed or the digit, feature vectors may be of
-	different lengths, e.g., '1' is shorter than '8'.
-
-5. Number of Instances
-	pendigits-orig.tra	Training	7494
-	pendigits-orig.tes	Testing		3498
-	
-	The way we used the dataset was to use first half of training for 
-	actual training, one-fourth for validation and one-fourth
-	for writer-dependent testing. The test set was used for 
-	writer-independent testing and is the actual quality measure.
-
-	pendigits.tra divides into
-		Actual training	set	3748
-		Validation		1873
-		Writer-dependent test	1873
-
-6. Number of Attributes
-	Input size depends on writing speed and time and is not fixed
-	+1 class attribute
-
-7. For Each Attribute:
-	The data is in the UNIPEN format. See
-	I. Guyon UNIPEN 1.0 Format Definition, 
-	ftp://ftp.cis.upenn.edu/pub/UNIPEN-pub/definition/unipen.def
-	1994
-
-8. Missing Attribute Values
-	None
-
-9. Class Distribution
-
-          classes
-          0    1    2    3    4    5    6    7    8    9
-tra     384  390  392  370  391  375  351  375  363  357 Tot 3748 
-cv      209  201  201  163  185  163  191  196  178  186 Tot 1873 
-wdep    187  188  187  186  204  182  178  207  178  176 Tot 1873 
-windep  363  364  364  336  364  335  336  364  336  336 Tot 3498 
-
diff --git a/scikits/learn/datasets/pendigits/src/pendigits-orig.tes.Z b/scikits/learn/datasets/pendigits/src/pendigits-orig.tes.Z
deleted file mode 100644
index 8ade618c4f40f5ad5f267b94d0310c217ea4aa20..0000000000000000000000000000000000000000
Binary files a/scikits/learn/datasets/pendigits/src/pendigits-orig.tes.Z and /dev/null differ
diff --git a/scikits/learn/datasets/pendigits/src/pendigits-orig.tra.Z b/scikits/learn/datasets/pendigits/src/pendigits-orig.tra.Z
deleted file mode 100644
index d273620921a9eeb258ea7d77d620e0752dfe5ebb..0000000000000000000000000000000000000000
Binary files a/scikits/learn/datasets/pendigits/src/pendigits-orig.tra.Z and /dev/null differ
diff --git a/scikits/learn/datasets/pendigits/src/pendigits.names b/scikits/learn/datasets/pendigits/src/pendigits.names
deleted file mode 100644
index 2d8a87f7f49ac2a8fcba01e67449f1e100e4e2ac..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/pendigits/src/pendigits.names
+++ /dev/null
@@ -1,136 +0,0 @@
-1. Title of Database: Pen-Based Recognition of Handwritten Digits
-
-2. Source:
-	E. Alpaydin, Fevzi. Alimoglu
-	Department of Computer Engineering
-	Bogazici University, 80815 Istanbul Turkey
-	alpaydin@boun.edu.tr
-	July 1998
-
-3. Past Usage:
-	F. Alimoglu (1996) Combining Multiple Classifiers for Pen-Based
-	Handwritten Digit Recognition, 
-	MSc Thesis, Institute of Graduate Studies in Science and 
-	Engineering, Bogazici University.
-	http://www.cmpe.boun.edu.tr/~alimoglu/alimoglu.ps.gz
-
-	F. Alimoglu, E. Alpaydin, "Methods of Combining Multiple Classifiers 
-	Based on Different Representations for Pen-based Handwriting
-	Recognition," Proceedings of the Fifth Turkish Artificial 
-	Intelligence and Artificial Neural Networks Symposium (TAINN 96), 
-	June 1996, Istanbul, Turkey.
-	http://www.cmpe.boun.edu.tr/~alimoglu/tainn96.ps.gz
-
-	
-4. Relevant Information:
-
-	We create a digit database by collecting 250 samples from 44 writers.
-	The samples written by 30 writers are used for training,
-	cross-validation and writer dependent testing, and the digits 
-	written by the other 14 are used for writer independent testing. This
-	database is also available in the UNIPEN format.
-
-	We use a WACOM PL-100V pressure sensitive tablet with an integrated 
-	LCD display and a cordless stylus. The input and display areas are
-	located in the same place. Attached to the serial port of an Intel 
-	486 based PC, it allows us to collect handwriting samples. The tablet
-	sends $x$ and $y$ tablet coordinates and pressure level values of the
-	pen at fixed time intervals (sampling rate) of 100 miliseconds. 
-
-	These writers are asked to write 250 digits in random order inside 
-	boxes of 500 by 500 tablet pixel resolution.  Subject are monitored 
-	only during the first entry screens. Each screen contains five boxes
-	with the digits to be written displayed above. Subjects are told to
-	write only inside these boxes.  If they make a mistake or are unhappy
-	with their writing, they are instructed to clear the content of a box 
-	by using an on-screen button. The first ten digits are ignored 
-	because most writers are not familiar with this type of input devices,
-	but subjects are not aware of this. 
-
-	In our study, we use only ($x, y$) coordinate information. The stylus
-	pressure level values are ignored. First we apply normalization to 
-	make our representation invariant to translations and scale 
-	distortions. The raw data that we capture from the tablet consist of
-	integer values between 0 and 500 (tablet input box resolution). The 
-	new coordinates are such that the coordinate which has the maximum 
-	range varies between 0 and 100. Usually $x$ stays in this range, since
-	most characters are taller than they are wide.  
-
-	In order to train and test our classifiers, we need to represent 
-	digits as constant length feature vectors. A commonly used technique
-	leading to good results is resampling the ( x_t, y_t) points. 
-	Temporal resampling (points regularly spaced in time) or spatial
-	resampling (points regularly spaced in arc length) can be used here. 
-	Raw point data are already regularly spaced in time but the distance
-	between them is variable. Previous research showed that spatial
-	resampling to obtain a constant number of regularly spaced points 
-	on the trajectory yields much better performance, because it provides 
-	a better alignment between points. Our resampling algorithm uses 
-	simple linear interpolation between pairs of points. The resampled
-	digits are represented as a sequence of T points ( x_t, y_t )_{t=1}^T,
-	regularly spaced in arc length, as opposed to the input sequence, 
-	which is regularly spaced in time.
-
-	So, the input vector size is 2*T, two times the number of points
-	resampled. We considered spatial resampling to T=8,12,16 points in our
-	experiments and found that T=8 gave the best trade-off between 
-	accuracy and complexity.
-
-
-5. Number of Instances
-	pendigits.tra	Training	7494
-	pendigits.tes	Testing		3498
-	
-	The way we used the dataset was to use first half of training for 
-	actual training, one-fourth for validation and one-fourth
-	for writer-dependent testing. The test set was used for 
-	writer-independent testing and is the actual quality measure.
-
-6. Number of Attributes
-	16 input+1 class attribute
-
-7. For Each Attribute:
-	All input attributes are integers in the range 0..100.
-	The last attribute is the class code 0..9
-
-8. Missing Attribute Values
-	None
-
-9. Class Distribution
-	Class: No of examples in training set
-	0:  780
-	1:  779
-	2:  780
-	3:  719
-	4:  780
-	5:  720
-	6:  720
-	7:  778
-	8:  719
-	9:  719
-	Class: No of examples in testing set
-	0:  363
-	1:  364
-	2:  364
-	3:  336
-	4:  364
-	5:  335
-	6:  336
-	7:  364
-	8:  336
-	9:  336
-
-Accuracy on the testing set with k-nn 
-using Euclidean distance as the metric
-
- k =  1 : 97.74
- k =  2 : 97.37
- k =  3 : 97.80
- k =  4 : 97.66
- k =  5 : 97.60
- k =  6 : 97.57
- k =  7 : 97.54
- k =  8 : 97.54
- k =  9 : 97.46
- k = 10 : 97.48
- k = 11 : 97.34
diff --git a/scikits/learn/datasets/pendigits/src/pendigits.tes b/scikits/learn/datasets/pendigits/src/pendigits.tes
deleted file mode 100644
index 1328a79acff5ff5184179bd04ec82a75c39bedd3..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/pendigits/src/pendigits.tes
+++ /dev/null
@@ -1,3498 +0,0 @@
- 88, 92,  2, 99, 16, 66, 94, 37, 70,  0,  0, 24, 42, 65,100,100, 8
- 80,100, 18, 98, 60, 66,100, 29, 42,  0,  0, 23, 42, 61, 56, 98, 8
-  0, 94,  9, 57, 20, 19,  7,  0, 20, 36, 70, 68,100,100, 18, 92, 8
- 95, 82, 71,100, 27, 77, 77, 73,100, 80, 93, 42, 56, 13,  0,  0, 9
- 68,100,  6, 88, 47, 75, 87, 82, 85, 56,100, 29, 75,  6,  0,  0, 9
- 70,100,100, 97, 70, 81, 45, 65, 30, 49, 20, 33,  0, 16,  0,  0, 1
- 40,100,  0, 81, 15, 58,100, 57, 47, 87, 50, 88, 40, 42, 36,  0, 4
-  3, 71,  0, 95, 45,100,100, 99, 79, 78, 48, 53, 31, 24, 54,  0, 7
- 79, 87, 98, 81, 71,100, 72, 73,100, 66, 91, 21, 48,  0,  0, 13, 9
- 92, 95, 30,100, 34, 68, 87, 89, 84, 78,100, 35, 64,  0,  0, 19, 9
- 58, 64,100, 96, 27,100,  0, 63, 79, 65, 91, 72, 48, 36, 10,  0, 9
- 34, 89,  3, 70,  1, 25, 49,  0,100, 23,100, 67, 56, 99,  0,100, 0
-  0, 90, 46,100, 88, 92, 79, 69, 60, 48, 39, 27, 47,  6,100,  0, 2
- 20, 71,  0, 29, 31,  0, 78, 12,100, 51, 84, 93, 37,100,  8, 66, 0
-100,100, 67, 98, 41, 80, 44, 50, 78, 42, 68, 16, 35,  2,  0,  0, 5
- 91, 69, 48, 57,  9, 79, 60,100,100, 75, 95, 40, 64,  8,  0,  0, 9
- 30, 74, 55,100, 89, 87, 66, 56,100, 38, 92,  8, 41,  0,  0, 20, 3
-  5, 65,  0, 89, 37,100, 88, 97,100, 79, 71, 53, 48, 26, 59,  0, 7
- 42, 93, 19, 88,  0, 42, 24,  0, 83, 11,100, 56, 75,100, 17, 97, 0
-  4,100,  0, 72, 15, 44, 79, 50,100, 76, 90, 51, 83, 22, 85,  0, 4
-100,100, 79, 80, 54, 59, 32, 38, 21, 16, 50,  0, 79, 16,  0, 16, 6
-  0, 76, 30, 48, 53,  9, 11,  0, 47, 34, 97, 66,100,100, 38, 85, 8
-  0, 93, 40,100, 57, 61, 51, 17, 35,  0, 12, 37, 54, 48,100, 49, 7
-100,100, 73, 95, 40, 69, 14, 39,  2,  2, 39,  0, 37, 29,  0, 14, 6
- 88,100, 42, 77, 12, 50,  0, 22, 45,  0,100, 17, 73, 44, 15, 49, 6
- 33, 86,  0, 55,  1, 12, 52,  0, 90, 34,100, 76, 56,100,  6, 77, 0
- 69,100, 44, 77,  5, 50,  0, 28, 67, 23,100, 44, 95, 29, 89,  0, 4
- 27, 83,  0, 42,  9,  0, 65, 17, 96, 57,100,100, 45, 95, 10, 58, 0
- 19,100, 35, 93,  0, 63, 12, 36, 89, 37,100, 66, 94, 33, 89,  0, 4
- 27, 73, 81,100, 83, 91, 78, 52, 62, 14,  0,  0, 29,  1,100,  5, 1
- 77, 96, 38,100, 58, 77, 99, 86,100, 50, 84, 12, 43,  0,  0,  0, 9
- 41, 84, 73,100,100, 82, 62, 60, 97, 38, 91,  8, 42,  0,  0, 19, 3
- 32, 92, 24, 47, 71, 36, 38,  0,  0,  0, 21, 48, 49, 92,100,100, 5
- 53,100, 30, 95,  0, 60,100, 55, 92, 87, 77, 79, 79, 37, 79,  0, 4
-100, 95, 75,100, 42, 70,  0, 44, 42, 33, 85, 49, 83, 31, 85,  0, 4
-  0, 50, 41, 69, 76, 90,100,100, 89, 74, 78, 50, 70, 25, 68,  0, 1
-  2, 75, 37,100, 56, 99, 58, 61, 46, 25,  0,  0, 34,  5,100,  8, 1
- 10,100,  0, 60, 14, 18, 60,  0,100, 24, 96, 66, 58, 95, 19, 73, 0
- 79, 90,100, 93, 63,100, 82, 84, 99, 61, 87, 22, 44,  0,  0, 19, 9
-  0, 88, 59,100, 89, 72, 82, 40, 63,  9, 28,  0, 25, 25,100, 27, 7
-  5, 97,  9, 61, 37, 25,  0,  0,  7, 32, 56, 64,100, 96, 37,100, 8
- 59, 89, 42, 23, 29, 42, 25,100,100, 82, 75, 46, 98,  0,  0,  3, 3
- 20,100,  6, 61, 25, 28, 18,  0,  0, 27, 11, 63, 55, 75,100, 82, 5
-100,100, 49, 77, 17, 51,  2, 24, 24,  0,100, 10, 73, 35,  0, 42, 6
- 29, 80,  0, 41, 14,  0, 70, 14,100, 53,100, 96, 49,100, 19, 62, 0
- 21, 87, 33, 52, 62, 13,  5,  0,  0, 36, 74, 66,100,100,  5, 89, 8
- 13, 67, 40,100, 65, 78, 37, 42,  0, 11,  6,  4, 60,  0,100, 19, 2
-  5, 70, 56, 44, 60,  3,  0,  0, 30, 39, 84, 72,100,100, 32, 74, 8
-  0, 94, 68,100, 89, 68, 72, 33, 43,  0,  3, 21, 25, 50,100, 58, 7
-100, 93, 48,100, 27, 69, 30, 33, 16,  0,  0, 26, 41, 51,100, 58, 8
-  0, 55, 46, 58, 73, 82,100,100, 92, 75, 89, 50, 84, 25, 89,  0, 1
- 96, 66, 62,100, 32, 69, 74, 62, 89, 56,100, 10, 50,  0,  0, 10, 9
- 32, 96, 70,100, 12, 95, 32, 66, 89, 62,100, 22, 51,  0,  0, 16, 5
- 79,100, 41, 82,  0, 61, 23, 45, 77, 37, 86, 54, 86, 25,100,  0, 4
- 22, 72, 55,100, 54, 89, 53, 50, 55, 12,  0,  1, 49,  0,100,  4, 1
- 23, 70, 51,100, 74, 82, 51, 46, 20, 15,  0,  4, 50,  0,100,  2, 2
- 88,100,100, 95, 75, 79, 38, 64, 25, 47, 12, 32,  0, 16, 12,  0, 1
- 76,100, 31, 87,  1, 52,  0, 14, 61,  0,100, 27, 50, 42,  1, 21, 6
- 29, 97,  0, 57, 22, 10, 68,  0,100, 40, 83, 90, 37,100, 12, 57, 0
- 53, 67, 80, 44, 67,  7,  0,  0, 35, 36, 83, 68,100,100, 25, 80, 8
- 11, 45, 17,  6, 55,  0, 88, 25,100, 61, 79, 94, 38,100,  0, 84, 0
- 88, 90, 18,100, 17, 66, 79, 33, 49,  0,  0, 28, 41, 67,100, 98, 8
- 75,100, 42, 78, 13, 51,  0, 22, 40,  0,100, 16, 88, 43, 22, 35, 6
- 27, 82, 65,100,100, 89, 69, 62, 33, 39,  0, 15, 37,  1, 88,  0, 2
- 70, 84, 11, 76,  0, 91, 56,100, 99, 83,100, 55, 88, 28, 75,  0, 9
- 88,100, 29,100, 30, 74, 85, 83,100, 67, 97, 27, 57,  0,  0,  5, 9
- 51, 54,100, 87, 36,100, 19, 62, 44, 22,  2,  0,  0, 37, 78, 57, 8
- 15, 84,  0, 57,  5, 17, 52,  0, 95, 28,100, 67, 70,100, 20, 87, 0
-  0, 76, 29, 95, 92,100, 81, 77, 75, 56,100, 35, 85, 13, 31,  0, 3
- 38, 65, 36, 98,100,100, 99, 69, 62, 55, 96, 26, 55,  0,  0, 15, 3
- 82,100,  8, 92, 45, 60,100, 29, 52,  0,  0, 24, 21, 61, 53, 98, 8
-  0, 82, 34,100, 78, 90, 49, 62, 80, 49,100, 18, 62,  0, 18, 13, 3
- 53, 64, 73,100, 70, 83, 67, 42, 36, 11,  0,  0, 49,  4,100,  9, 1
-  0, 39, 30, 69, 48,100, 39, 69, 41, 35, 33,  5, 31,  2,100,  0, 1
- 12, 91, 48,100, 66, 77, 77, 63,100, 42, 75, 15, 34,  0,  0, 15, 3
-100, 89, 34,100,  0, 75, 76, 78, 83, 62, 90, 35, 85,  8,  5,  0, 9
- 26, 98, 24, 49, 45, 13, 17,  0,  0, 35, 26, 72, 62, 91,100,100, 5
- 61,100, 24, 88, 21, 49, 26,  9,  0,  0,  7, 37, 51, 60,100, 78, 8
- 25, 76,  0, 39, 15,  0, 68,  1, 98, 36,100, 76, 58,100,  7, 90, 0
-  0, 63, 37, 44, 42,  6,  1,  0, 25, 36, 65, 67,100,100, 46, 80, 8
- 62,100, 25, 91,  0, 49,  7,  2, 55,  0, 92, 30,100, 78, 63,100, 0
- 78, 99, 21, 85,  0, 50,  5, 14, 59,  0,100, 27,100, 65, 79,100, 0
- 76, 93, 24,100,  0, 72, 58, 73, 74, 74,100, 42, 92, 12, 37,  0, 9
-100,100, 79, 86, 62, 71, 50, 57, 33, 43, 21, 28,  8, 14,  0,  0, 1
-100, 98, 71,100, 42, 88, 35, 55, 59, 41, 61, 16, 31,  3,  0,  0, 5
- 27, 50, 56, 89, 64,100, 55, 52, 35,  9,  0,  2, 52,  2,100,  0, 1
-  0, 67, 25,100, 49, 73, 36, 33,  6,  0,  1,  6, 53,  3,100, 11, 2
- 56, 97, 15, 77,  0, 35, 23,  0, 70,  3,100, 36, 95, 78, 54,100, 0
-100, 83, 25,100, 16, 67, 58, 28, 12,  0,  0, 33, 65, 65, 89, 91, 8
- 23, 97,  0, 48, 17,  0, 58,  3, 93, 35,100, 89, 59,100, 23, 73, 0
- 95, 76, 34, 80,  0, 97, 57,100, 98, 80,100, 53, 83, 25, 59,  0, 9
-  0, 93, 41,100, 57, 65, 47, 26, 21,  0,  2, 35, 51, 38,100, 36, 7
- 17, 81, 59,100, 76, 75, 53, 48,100, 44, 89, 13, 40,  0,  0, 20, 3
- 77, 64,100, 96, 45,100, 35, 63, 34, 25,  0,  0,  0, 36, 48, 62, 8
-  9, 88, 22,100, 26, 65, 16, 31,  0,  5, 33,  1, 66,  0,100,  3, 2
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-100, 82, 29, 97, 14, 62, 60, 22,  0,  0, 27, 39, 99, 72, 77,100, 8
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-100,100, 41, 89,  8, 59,  2, 23, 46,  0, 88, 23, 43, 43,  0, 24, 6
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-100, 78, 64,100, 44, 72, 52, 35, 44,  0,  0,  2, 18, 36, 67, 56, 8
- 28, 81, 44, 54, 92, 34, 54,  1,  0,  0, 18, 45, 45, 86,100,100, 5
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-100,100, 57, 92, 24, 87,  0, 58, 33, 57, 66, 42, 48, 13,  8,  0, 5
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-100,100, 65, 89, 35, 63,  9, 34,  0,  2, 44,  0, 55, 25,  7, 19, 6
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-100, 99, 68,100, 47, 74, 52, 52, 81, 42, 63, 14, 30,  0,  0, 16, 5
-100,100, 73, 76, 37, 49,  0, 25, 51, 28, 90, 40, 85, 28, 88,  0, 4
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-100,100, 55, 93, 12, 66,  0, 29, 30,  0, 84, 15, 72, 48, 10, 46, 6
- 40, 89, 28, 61, 58, 28, 23,  0,  0, 24,  6, 63, 45, 92,100,100, 5
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-100,100, 52, 83, 16, 58,  0, 31, 16,  5, 84,  0, 66, 23,  7, 24, 6
- 30, 70, 57,100, 57, 80, 62, 45, 54, 12,  0,  2, 43,  2,100,  0, 1
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-100, 98,100,100, 71, 83, 50, 66, 36, 50, 21, 33,  0, 16,  7,  0, 1
-100, 99, 68,100, 32, 70, 10, 35, 20,  0, 76,  4, 59, 31,  0, 23, 6
- 11,100, 16, 66, 27, 32,  0,  0, 14, 28, 64, 59,100, 92, 39, 97, 8
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- 20, 85, 61,100,100, 93, 67, 69, 82, 44, 93, 18, 48,  4,  0,  0, 3
- 23, 86, 62,100, 71, 71, 41, 43,  0, 24,  7, 17, 52,  7,100,  0, 2
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-100,100, 55, 93, 20, 71,  0, 43,  4, 11, 45,  0, 68, 24, 33, 42, 6
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- 20, 87,100,100, 80, 83, 40, 66, 20, 49,  0, 33,  0, 15,100,  0, 1
-100,100,100, 92, 67, 77, 33, 62, 33, 46, 33, 30,  0, 15,  0,  0, 1
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- 80,100, 42, 78, 12, 46,  0, 10, 56,  0,100, 22, 61, 49,  8, 33, 6
- 47, 66, 50,100, 92, 98, 78, 55, 47, 18,  0,  0, 46, 19,100,  0, 2
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- 28, 94,100,100,100, 96, 22, 90, 15, 58, 86, 51, 65,  0,  0,  8, 5
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-100, 81, 67,100, 22, 81,  0, 47,  7, 13, 52,  0, 67, 30, 22, 45, 6
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-100, 66, 68, 45, 49, 71, 80,100, 95, 67, 78, 30, 45,  0,  0,  3, 9
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- 20, 80, 46, 95,100,100, 80, 76, 86, 50, 99, 23, 53,  7,  0,  0, 3
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- 63, 67, 74,100, 99, 80, 73, 39, 35,  7,  0,  3, 51,  4,100,  0, 2
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-  0, 57, 39, 75, 81, 96,100,100, 85, 74, 72, 48, 55, 23, 43,  0, 1
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- 15, 81, 54,100, 91, 81, 43, 55, 44, 49,100, 32, 66,  3,  0,  0, 3
- 40, 63, 51,100, 56, 89, 54, 51, 54, 14,  0,  0, 46,  1,100,  5, 1
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- 30, 98, 30, 76, 72, 38, 60,  0,  0, 11, 44, 48,100, 83, 49,100, 8
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-100,100, 78, 98, 34, 69,  6, 36, 15,  1, 77,  0, 68, 32,  0, 28, 6
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-100,100, 57, 84, 22, 59,  3, 28, 24,  0, 72, 11, 54, 36,  0, 28, 6
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-100,100, 55, 94, 27, 70,  6, 44,  0, 14, 29,  0, 43, 25,  2, 25, 6
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- 51, 76,  0, 73, 11, 95, 60,100, 97, 83,100, 55, 91, 27, 83,  0, 9
-100, 96, 62,100, 33, 83, 26, 45, 57, 42, 75, 19, 40,  0,  0,  1, 5
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- 31, 95, 24, 52, 49, 23, 14,  0,  0, 40, 19, 78, 56, 99,100,100, 5
-  0, 32, 33, 41, 62, 64, 85, 94,100,100, 85, 66, 70, 34, 57,  0, 1
-100, 89, 55,100, 17, 72,  0, 31, 26,  0, 67, 22, 40, 48, 13, 21, 6
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-  7, 51, 31, 90, 93,100, 99, 58, 59, 21,  0,  0, 35, 17,100,  5, 2
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-100, 88, 47,100, 23, 66, 80, 66, 91, 78, 93, 36, 62,  0,  0,  3, 9
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- 14, 71, 40,100, 49, 70, 27, 36,  0,  5, 25,  0, 66,  2,100, 19, 2
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-100,100, 59, 80, 31, 55, 16, 26, 31,  0, 82,  5, 47, 18,  0,  4, 6
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-100,100, 54, 86, 18, 59,  0, 29, 23,  1, 85,  0, 66, 18, 23, 15, 6
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-100, 74, 81,100, 33, 92,  4, 62,  0, 26, 31,  0, 61, 21, 24, 42, 6
-100, 86, 67,100, 24, 80,  0, 50,  0, 16, 41,  0, 63, 24, 18, 35, 6
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-100, 95, 49,100, 14, 71,  0, 34, 21,  0, 64, 16, 39, 45, 29, 13, 6
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- 96, 91, 37,100, 56, 59, 93, 91, 94, 71,100, 26, 56,  0,  0, 20, 9
-100,100, 62, 87, 34, 64, 13, 37,  0,  9, 29,  0, 40, 25,  1, 22, 6
- 11, 88, 57,100,100, 88, 61, 66, 67, 50, 91, 24, 55,  2,  0,  0, 3
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- 90, 82, 46,100, 38, 56, 97, 74, 92, 84,100, 35, 62,  0,  0, 19, 9
-  0, 88, 37,100, 79, 94, 92, 73, 90, 52,100, 31, 93, 10, 54,  0, 3
- 24, 91, 22, 61, 38, 25,  1,  0,  0, 39,  0, 78, 46, 95,100,100, 5
- 63, 96,  3,100, 26, 61, 54, 21,  9,  0,  0, 28, 50, 56,100, 84, 8
- 38, 85, 60,100, 58, 72, 33, 45,  0, 24, 15, 10, 58,  0,100, 10, 2
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-100,100, 60, 98, 23, 69,  0, 32, 24,  0, 77,  8, 70, 39, 17, 37, 6
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-100, 83, 62,100, 22, 73,  0, 44,  3, 13, 70,  0, 95, 22,  8, 21, 6
- 45, 96,  0, 68, 48, 62, 52, 12,  6,  0, 20, 54, 45,100,100, 99, 5
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- 25, 64, 54,100, 53, 90, 49, 45, 32,  3,  0,  0, 51,  1,100,  2, 1
-  0, 78, 57, 74, 91,100, 10, 94, 23, 74,100, 80, 86, 40, 85,  0, 9
- 37, 90, 73,100,100, 90, 64, 72, 83, 45, 83, 16, 43,  3,  0,  0, 3
-100,100, 63, 82, 35, 63, 10, 43,  0, 21, 14,  0, 63,  2, 35, 11, 6
- 44,100,  2, 69,  0, 38, 71, 39,100, 50, 60, 74, 56, 37, 58,  0, 4
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- 24, 96, 91,100,100, 95, 32, 92, 25, 62, 87, 51, 62,  0,  0,  6, 5
-100,100, 55, 85, 15, 56,  8, 21, 56,  0, 99, 24, 53, 45,  0, 26, 6
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- 29, 76, 50,100, 70, 74, 50, 42, 18, 16,  0,  0, 50,  7,100,  7, 2
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-100,100, 50, 90, 20, 61,  0, 29, 18,  0, 76,  6, 62, 31,  5, 33, 6
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- 15, 95, 69,100, 75, 66, 51, 33, 22,  0,  0,  9, 30, 29,100, 33, 7
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-100, 92, 66,100, 39, 82, 42, 57, 70, 38, 64,  9, 32,  0,  0,  8, 5
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-100,100, 57, 98, 18, 90,  0, 62, 22, 55, 57, 40, 42, 12,  4,  0, 5
-  0, 90, 41,100, 69, 86, 59, 64, 45, 43, 33, 22, 49,  3,100,  0, 2
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-  0, 91, 15, 56, 44, 22, 15,  0, 36, 34, 82, 67,100,100,  5, 95, 8
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- 13, 58, 40,100, 49, 97, 46, 45, 25,  3,  0,  1, 50,  1,100,  0, 1
- 89, 68, 81,100, 34, 80, 34, 40, 30,  0,  0,  8, 38, 42,100, 59, 8
-  0, 70, 33,100, 83, 97, 78, 59, 44, 26,  2,  0, 42,  1,100,  2, 2
-  0, 95, 56,100, 61, 80, 51, 40, 44,  0, 17, 27, 41, 39,100, 47, 7
-  0, 62, 34, 93, 81,100, 85, 61, 53, 28, 11, 17, 56, 19,100,  0, 2
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-  0, 90, 32,100, 66, 77, 45, 39, 26,  0,  1, 20, 45, 34,100, 39, 7
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- 76,100, 53, 91,  0, 71, 33, 56,100, 47, 97, 48, 47, 26, 17,  0, 4
-100,100, 65, 92, 27, 69,  0, 40,  8,  7, 58,  0, 87, 21, 41, 33, 6
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diff --git a/scikits/learn/datasets/pendigits/src/pendigits.tra b/scikits/learn/datasets/pendigits/src/pendigits.tra
deleted file mode 100644
index 15f839a0df95a622bf1ffb65aa0f654a453882c0..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/pendigits/src/pendigits.tra
+++ /dev/null
@@ -1,7494 +0,0 @@
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-100,100, 54, 85, 21, 57,  0, 27, 23,  0, 75,  7, 57, 29,  3, 23, 6
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- 29, 75, 29, 85,100,100, 85, 81, 59, 61, 38, 41, 15, 20,  0,  0, 1
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- 15, 72,  0, 39, 57, 42, 43,  0, 16, 15, 11, 62, 36, 93,100,100, 5
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- 28, 95,100,100, 51, 97,  0, 74, 16, 54, 86, 42, 71, 13,  1,  0, 5
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-100, 94, 63,100, 30, 71,  8, 39,  6,  6, 57,  0, 54, 19,  0, 10, 6
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-100, 84, 27,100,  0, 85,  0, 68, 13, 51, 20, 34, 27, 17, 60,  0, 1
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- 56, 60, 65,100,100, 83, 81, 39, 51,  0, 85, 16, 56, 50,  0, 55, 8
- 25, 79, 35,100, 78, 78, 50, 50, 68, 48,100, 21, 59,  0,  0, 11, 3
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-100,100, 55, 88, 20, 61,  0, 28, 19,  0, 66, 14, 62, 43, 17, 43, 6
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- 25, 89, 65, 55,100, 21, 20,  0,  0, 30, 55, 62, 94, 95, 22,100, 8
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-100, 97, 48,100, 12, 80,  9, 42, 51, 53, 80, 28, 49,  0,  0,  5, 5
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-100, 79, 81,100, 41, 79, 62, 59, 93, 64, 80, 27, 46,  0,  0,  0, 9
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-100, 99, 81,100, 43, 74, 13, 44,  0,  8, 44,  0, 60, 27, 13, 35, 6
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-100,100, 50, 85, 16, 58,  4, 25, 34,  0, 80, 15, 40, 27,  0,  6, 6
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- 10, 81, 37,100, 56, 62, 44, 21,  0, 13, 35, 25, 75,  0,100, 30, 2
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-100, 70, 46, 94, 32, 51, 87,  9,  0,  0, 38, 46, 80, 91, 19,100, 8
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-  0, 69, 52, 60,100, 77, 74,100, 23, 89, 47, 69, 55, 36, 51,  0, 9
- 14, 81,  0, 41, 34,  0, 87,  3,100, 56, 70,100, 20, 99,  7, 49, 0
- 13, 90, 44,100, 91, 99, 80, 71,100, 43, 92, 17, 47,  5,  0,  0, 3
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- 85, 98, 39,100,  7, 60,  0, 16, 54,  0,100, 28, 40, 38,  5,  9, 6
-100,100, 48, 89, 12, 65,  0, 38, 15, 12, 79,  0, 70, 26,  3, 23, 6
-100,100, 47, 99, 10, 70,  0, 32, 32,  0, 88,  1, 75, 32, 16, 32, 6
-  0, 24, 43, 59, 64,100, 18, 94, 67, 61,100, 23, 43,  0,  7, 29, 8
-  0, 77, 40, 64, 54, 28, 43,  0, 27, 36, 13, 72, 49, 96,100,100, 5
- 48,100, 70, 64, 94, 98, 42, 79, 96, 79,100, 40, 68,  2,  0,  0, 9
-  0, 97, 90,100, 81, 71, 52, 36, 37,  0, 16, 13,  7, 42,100, 43, 7
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- 78,100, 51, 62,  0, 32, 18, 31, 95, 29,100, 58, 73, 39, 57,  0, 4
- 12, 97,  0,100, 58, 98,100, 84, 93, 62, 71, 41, 46, 21, 32,  0, 7
- 18, 61, 37,100, 17, 65,  0, 33, 61, 39,100, 55, 66, 37, 37,  0, 4
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- 41, 94,  5, 74, 62, 66, 51,100, 56, 68,100, 34, 60,  2,  0,  0, 9
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-100,100, 60, 84, 29, 57, 11, 26, 35,  0, 83, 12, 53, 37,  0, 31, 6
- 81, 75, 62,100,  0, 86, 16, 59, 78, 74,100, 66, 92, 32, 69,  0, 9
- 36,100, 13, 75, 57, 65,100, 78, 63, 85, 41, 57, 18, 29,  0,  0, 4
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- 95, 90, 70, 95,  0,100,  0, 66, 69, 59,100, 27, 53,  0, 16, 13, 5
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-  0, 88, 55,100,100, 87, 65, 48, 39,  4, 19,  0, 22, 35, 87, 42, 7
- 85, 78, 60,100, 28, 69, 85, 68, 97, 68,100, 30, 66,  0,  0,  9, 9
- 25,100, 58, 96, 81, 69, 54, 34, 29,  0,  0, 34, 48, 44,100, 48, 7
- 20,100, 21, 84,  0, 52, 37, 42,100, 46, 97, 63, 81, 31, 71,  0, 4
- 52, 82,  3, 50,100, 72, 64,100,  0, 62, 84, 76, 86, 50, 77,  0, 9
- 70,100, 36, 70,  0, 41, 25, 31, 90, 36,100, 45, 80, 33, 62,  0, 4
-100, 65, 80, 96, 33,100, 51, 76, 94, 68, 83, 33, 48,  8,  0,  0, 9
- 57,100, 34, 80,  0, 59, 11, 40, 85, 43,100, 44, 72, 22, 57,  0, 4
-  0, 55,  6, 70, 54, 90,100,100, 76, 75, 49, 50, 24, 25,  5,  0, 1
- 31, 74, 88,100,100, 95, 98, 55, 96, 16, 25,  2,  0,  0,100,  2, 1
- 75, 61, 85,100, 22, 82, 37, 42, 55,  2,  0,  0, 31, 36,100, 60, 8
- 62,100, 39, 79,  0, 52, 13, 39, 80, 44,100, 63, 86, 32, 71,  0, 4
- 46,100,  2, 72,  0, 47, 76, 48,100, 77, 78, 64, 45, 32, 19,  0, 4
- 41, 97, 12, 58, 65, 58, 62, 14,  0,  0,  4, 54, 24, 97,100,100, 5
-  0, 48, 17, 64, 53, 84, 93,100,100, 79, 85, 53, 72, 26, 68,  0, 1
-  0, 74, 44, 86, 94,100,100, 85, 79, 64, 54, 42, 31, 21,  8,  0, 1
-100, 77, 56,100,  0, 78, 45, 57, 85, 80, 95, 40, 93,  0, 24,  7, 9
- 22, 85, 49,100, 71, 77, 45, 51, 11, 30,  0, 11, 51,  7,100,  0, 2
- 23, 88, 52,100, 51, 67, 30, 38,  0, 16, 27,  8, 64,  3,100,  0, 2
-100,100, 55, 93, 23, 59, 11, 15, 53,  0, 77, 31, 41, 62,  0, 51, 6
- 50, 50, 97, 72, 87,100, 25, 95,  0, 65, 60, 56,100, 35, 91,  0, 9
- 54, 87, 59,100, 26, 72,  0, 43, 28, 18,100, 30, 96, 30, 80,  0, 4
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- 67,100, 25, 81,  0, 49,  0, 15, 51,  0,100, 20, 63, 40,  9, 26, 6
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-100,100, 54,100, 17, 85, 15, 50, 55, 47, 85, 22, 50,  0,  0,  6, 5
-  0, 75, 61, 81,100,100, 96, 88, 87, 66, 85, 44, 85, 22, 87,  0, 1
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- 69, 94,  0, 81, 73, 55,100, 21, 32,  0, 20, 33, 58, 67, 51,100, 8
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- 29, 80, 53,100,  7, 70,  0, 49, 83, 48,100, 65, 61, 33, 29,  0, 4
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-100,100, 65, 90, 32, 67,  5, 40,  0,  8, 40,  0, 36, 27,  0, 20, 6
- 11, 81, 60,100,100, 89, 69, 55, 31, 24,  0,  0,  7, 39, 64, 43, 7
- 25, 90, 24,100, 61, 90, 31, 64, 77, 53,100, 27, 68,  4,  0,  0, 3
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- 35, 84, 71,100,100, 79, 72, 52, 35, 31,  0,  9, 39,  0, 88,  0, 2
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-  0, 85, 35,100, 77, 91, 65, 65, 68, 40,100, 19, 73,  1, 24,  0, 3
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-  0, 75, 29,100, 74, 93, 69, 60, 41, 29,  0,  3, 37,  0,100,  6, 2
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- 75,100, 44, 70, 23, 34, 47,  4,100,  6, 89, 29, 36, 26,  0,  0, 6
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- 22, 91, 24, 64, 80, 38, 67,  0,  0, 13,  4, 57, 26, 97,100,100, 5
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-100, 75, 41, 68,  0, 79, 44,100, 89, 91, 91, 61, 85, 30, 86,  0, 9
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- 85,100, 38, 76,  0, 42, 82, 41,100, 61, 78, 95, 75, 47, 71,  0, 4
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-100, 81, 65, 97, 24,100,  7, 64, 41, 57, 65, 25, 31,  0,  0,  5, 5
- 48, 84, 38, 41, 20,  0,  0, 14, 37, 51, 89, 81,100,100, 36, 84, 8
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-100,100, 55, 99, 20, 93, 23, 53, 67, 54, 80, 20, 43,  0,  0,  3, 5
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-100, 88, 79,100, 42, 74, 15, 41, 27,  8, 78,  0, 48, 17,  0, 18, 6
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-100, 86, 70,100, 45, 64, 83, 64, 98, 70, 96, 30, 62,  1,  0,  0, 9
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-100,100, 55, 81, 22, 56,  0, 25, 25,  0, 74, 12, 58, 39,  8, 40, 6
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-100,100, 56, 92, 22, 66,  0, 34,  8,  0, 56,  0, 71, 29, 25, 40, 6
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- 82, 62, 85,100, 28, 91, 48, 54, 99, 74,100, 35, 66,  0,  0,  2, 9
- 57,100,100,100, 53, 91, 22, 66, 67, 48, 91, 20, 50,  0,  0,  8, 5
- 63, 93, 69,100, 38, 67, 16, 31, 43,  4,100, 22, 48, 25,  0,  0, 6
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- 14, 87, 44, 65, 71,100,  0, 87, 44, 69, 94, 72,100, 23, 36,  0, 9
- 34, 84, 42,100, 19, 65,  0, 31, 56, 40,100, 55, 87, 38, 85,  0, 4
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- 69, 72,100,100, 35, 91,  0, 57, 59, 60,100, 61, 71, 25, 18,  0, 9
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-100, 83, 29, 71,  0, 85, 63,100,100, 79, 96, 52, 92, 26,100,  0, 9
- 14, 84, 24,100, 81, 89, 42, 65, 27, 47,100, 37, 71, 12,  0,  0, 3
-  0, 96, 21, 97, 79,100,100, 98, 67, 76, 48, 50, 33, 23, 31,  0, 7
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- 22,100,  1, 52, 63, 67, 62, 21,  0,  0,  4, 59, 28, 96,100, 97, 5
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-  0, 59, 20, 79,100,100,100, 90, 60, 67, 33, 44,  7, 22, 33,  0, 1
- 31, 94,100,100, 66, 96,  5, 79,  0, 50, 69, 37, 92, 10, 22,  0, 5
-100, 89, 58,100, 29, 72, 70, 75, 79, 49, 87,  8, 43,  0,  0,  8, 9
- 41, 75, 46,100, 87, 86, 70, 53, 38, 25,  0, 19, 53, 18,100,  0, 2
- 47, 96,100,100, 53, 93, 15, 74, 46, 58, 77, 34, 51,  9,  0,  0, 5
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- 54, 94,100,100, 60, 99, 25, 75, 41, 58, 73, 39, 44, 10,  0,  0, 5
- 90,100, 53, 73, 19, 46,  0, 16, 41,  0,100,  8, 81, 26, 20, 29, 6
- 55,100, 16, 79,  0, 39,  5,  0, 61,  1,100, 31, 67, 61,  5, 67, 0
- 84, 97, 40, 79,  0, 39,  9,  0, 62, 26,100, 67, 71,100, 15, 80, 0
- 21, 87, 49,100, 96, 87, 53, 63, 65, 48,100, 21, 55,  0,  0,  5, 3
- 60, 91,  0, 85, 19, 37, 82, 27, 31,  0,  3, 30, 40, 74,100,100, 5
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- 40, 98, 17, 76,  0, 28, 35,  0, 84, 25,100, 70, 55,100,  4, 95, 0
- 35, 93, 94,100,100, 94, 44, 82, 47, 48, 98, 31, 58,  6,  0,  0, 5
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-  8, 97, 14, 72,  0, 35, 10,  0, 69, 18,100, 53, 90, 90, 25,100, 0
-  0, 63, 63, 33, 72,  0, 20,  9, 58, 42,100, 74, 56,100,  7, 71, 8
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- 48, 86, 16, 51,  0, 11, 37,  0, 77, 29,100, 66, 81,100, 31, 92, 0
- 87, 78, 50, 94, 16, 59,  0, 19, 45,  0, 99, 24,100, 63, 67,100, 0
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-  0, 92, 35,100, 80, 99, 70, 53, 55,  0, 35, 13, 56, 31,100, 32, 7
- 26, 79,  0, 49, 14,  0, 74, 15,100, 61, 62,100,  9, 77,  1, 26, 0
- 77,100, 28, 80,  4, 52,  2, 23, 44,  0,100, 11, 51, 28,  0, 14, 6
-100, 98, 60,100, 12, 99, 28, 64, 73, 58, 78, 21, 39,  0,  0,  3, 5
- 23, 65, 37,100, 72, 83, 64, 45, 36, 12,  0,  3, 48, 10,100,  0, 2
- 46,100,  4, 75,  7, 24, 53,  0,100, 21, 89, 68, 44, 97,  0, 88, 0
-100,100, 49, 88, 20, 56,  7, 19, 46,  0, 95, 17, 51, 22,  0,  7, 6
-  4, 73, 44,100, 83, 81, 55, 43, 12, 15,  0, 22, 52, 20,100,  0, 2
- 79, 98,  0, 87, 39, 48, 95, 13, 28,  0, 46, 40,100, 77, 58,100, 8
-  0,100, 53, 99, 66, 67, 59, 33, 53,  0, 36, 18, 38, 42,100, 42, 7
-  9, 81,  5, 24, 54,  0, 99, 38,100, 94, 48,100,  8, 56,  0,  4, 0
- 58, 50, 88, 84,100,100, 84, 60, 80, 19, 40,  0,  0,  4, 64,  5, 1
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-  0, 73, 48, 91, 62,100, 56, 46, 71, 12,100, 16, 42,  6, 15,  0, 1
- 54,100,  0, 78, 47, 62, 63, 20, 13,  0, 18, 49, 40, 95,100, 95, 5
- 90,100, 39, 78,  4, 49,  0, 18, 59,  0,100, 24, 41, 39, 10, 13, 6
- 35,100, 35, 87, 14, 62,  0, 35, 35, 16, 97, 34,100, 26, 89,  0, 4
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- 13, 72, 27, 98, 93,100,100, 75, 58, 54, 85, 37, 56, 14,  0,  0, 3
- 43, 84,  0, 77, 48, 37, 28,  0,  1, 25, 68, 57,100, 97, 21,100, 8
- 23, 69, 60, 33, 48,  0,  0, 19, 48, 50,100, 81, 68,100, 17, 71, 8
- 45,100,  4, 91, 40, 77, 51, 76, 72, 49,100, 22, 69,  0,  0,  3, 9
- 56,100, 24, 73,  0, 37,  8,  2, 74,  5,100, 36, 41, 34, 27,  0, 6
-100,100, 66, 90, 26, 66,  0, 40,  4, 12, 62,  0, 80, 19, 10, 16, 6
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- 21, 80, 60, 95,100,100, 55, 87, 37, 52, 76, 28, 46,  2,  0,  0, 5
-100,100, 64, 81, 39, 55, 24, 26, 37,  0, 76, 11, 41, 24,  0, 10, 6
-  0,100, 45, 99, 83, 79, 71, 39, 66,  0,100, 23, 55, 40,  6, 48, 7
- 35, 94,  0, 66, 51, 54, 48, 13,  1,  0, 17, 47, 35, 94,100,100, 5
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- 84, 76, 80,100,  5, 88,  0, 60, 76, 63,100, 62, 83, 30, 79,  0, 9
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- 95,100, 56, 93, 18, 62,  0, 27, 37,  0,100,  8, 74, 32, 15, 16, 6
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-  0, 86, 34,100, 60, 86, 42, 60, 70, 43,100, 26, 70,  8, 29,  0, 3
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- 39,100,  6, 71,  0, 36, 61, 26,100, 47, 98, 69, 80, 35, 75,  0, 4
- 84,100, 53, 78, 18, 50,  0, 20, 39,  0,100, 14, 70, 37,  3, 34, 6
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- 12, 74, 66, 73,100,100, 39, 96,  0, 68, 62, 70, 49, 40, 27,  0, 9
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- 16,100,  0, 57, 55, 55, 44,  0, 12, 17,  6, 77, 45, 98,100,100, 6
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- 20, 98, 49,100, 51, 65, 31, 36,  0, 16, 28, 10, 64,  5,100,  0, 2
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- 26, 77, 49,100,100, 94, 76, 67, 73, 43, 94, 16, 51,  0,  0, 13, 3
- 20, 79, 30,100,100, 99, 66, 71, 45, 59, 97, 40, 70, 11,  0,  0, 3
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- 14, 73,  0, 27, 38,  0, 84, 10,100, 55, 75, 96, 31,100,  9, 60, 0
- 53,100, 33, 71,  0, 44, 14, 43, 68, 37,100, 58, 85, 33, 83,  0, 4
-  0, 69, 35,100,100, 94, 69, 49, 26,  8, 71,  0, 36, 40, 15, 83, 8
-  4, 25, 68, 64, 33, 97,  0, 36, 38,  0,100, 43, 96,100, 22, 85, 0
- 33, 95, 29, 61, 71, 39, 38,  0,  0, 15, 10, 71, 45, 98,100,100, 5
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- 14, 63,  1, 32, 34,  0, 78,  4,100, 47, 79, 92, 37,100,  0, 71, 0
-  0, 91, 10, 57, 48, 30, 20,  0,  8, 34, 12, 79, 49,100,100, 91, 5
-  0, 53, 29, 73, 67, 94, 79,100, 71, 71, 71, 41, 73, 13,100,  0, 1
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- 21,100,  7, 51, 37, 89, 39, 87, 44, 20,  0,  0, 30,  2,100,  7, 1
-100,100, 48, 80,  0, 45, 74, 36, 99, 57, 70, 86, 65, 43, 66,  0, 4
- 15, 81, 42,100, 71, 81, 54, 54, 27, 30,  0,  5, 45,  0,100,  1, 2
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- 39,100,  0, 61, 20, 14, 71,  0,100, 37, 78, 88, 29,100, 16, 49, 0
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- 83, 63, 48,100,  0, 76, 61, 40, 82,  0,  3,  9, 38, 55,100, 91, 8
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- 44, 81, 68,100, 85, 74, 69, 46, 40, 21,  0,  0, 41,  5,100,  8, 2
- 13, 81, 24,100, 89, 97,100, 75, 63, 52, 97, 22, 55,  0,  0, 12, 3
-  9, 77,  0, 28, 33,  0, 74, 16,100, 56, 77, 95, 33,100,  1, 68, 0
-100,100, 56, 80, 23, 55,  0, 26, 22,  0, 76,  4, 62, 23, 10, 13, 6
-  3, 15, 44, 51, 88, 88, 46,100, 42, 63,100, 31, 72,  0,  0, 17, 8
- 77,100, 43, 84, 18, 59,  0, 35, 48, 17, 91, 32, 82, 24,100,  0, 4
- 57, 60, 61, 61,100,100, 37, 99, 62, 78, 93, 52, 67,  2,  0,  0, 9
- 90,100, 53, 75, 16, 45,  0, 35, 52, 35,100, 44, 96, 41, 87,  0, 4
- 29, 91,100,100, 79,100,  4, 95, 21, 68, 68, 42, 68, 14,  0,  0, 5
- 51, 82, 27, 57, 99, 75, 55,100, 47, 64,100, 52, 77,  4,  0,  0, 9
- 44, 97, 13,100, 56, 87, 61, 95, 92, 58,100, 14, 53,  0,  0,  4, 9
-  0,100, 14, 81,  5, 58, 28, 39, 88, 47, 97, 44, 91, 21,100,  0, 4
-  0,100, 16, 66, 45, 34, 66,  0, 39, 28, 18, 62, 40, 94,100, 99, 5
-  0, 92, 44,100, 91, 93,100, 56, 85, 18, 61,  0, 40, 27, 86, 35, 7
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- 13, 96, 55,100,100, 74, 65, 37, 27,  0,  0, 23,  4, 51, 96, 55, 7
- 15, 52, 29, 87, 31,100, 31, 64, 29, 27,  0,  1, 40,  0,100,  1, 1
- 26, 75, 59, 41, 65,  3,  0,  0, 14, 36, 63, 66,100,100, 36, 90, 8
- 80, 80, 18, 66,  0, 84, 51,100, 78, 77, 78, 50, 78, 24,100,  0, 9
- 12, 84, 36,100,  0, 65, 46, 44,100, 57, 83, 75, 53, 38, 28,  0, 4
-100,100, 55, 96, 20, 66,  0, 32, 16,  0, 79,  2, 68, 27,  9, 13, 6
- 32, 81, 70,100, 95, 83, 69, 55, 35, 31,  0,  9, 49,  2,100,  0, 2
- 59, 55,100, 80, 66,100,  9, 89,  0, 63, 58, 55, 82, 33, 62,  0, 9
-100,100, 39, 90,  1, 59,  0, 22, 46,  0, 93, 22, 54, 46,  0, 26, 6
- 93, 71,  0, 76, 15, 92, 95,100,100, 75, 93, 50, 88, 25, 83,  0, 9
- 26, 97, 97,100, 63, 99,  0, 82, 34, 59,100, 43, 79,  9,  9,  0, 5
- 49, 72, 99, 97,100,100, 81, 60, 66, 20,  0,  0,  9,  3, 99,  8, 1
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- 27,100, 13, 66,  0, 26, 39, 31,100, 30, 93, 51, 77, 38, 77,  0, 4
- 15, 73, 41,100, 87, 93, 60, 64, 99, 43,100,  8, 50,  0,  0, 11, 3
- 56,100, 11, 85,  0, 39, 28,  0, 80,  4,100, 47, 83, 90, 32, 92, 0
- 61, 95, 20, 91,  0, 42, 25,  0, 79, 12,100, 58, 67,100, 20, 99, 0
- 73, 69,100,100,  0, 95, 39, 54, 85, 13,  7,  0, 13, 40, 89, 73, 8
-  0, 94, 30,100, 66, 78, 33, 52, 88, 46,100, 17, 52,  0,  8, 11, 3
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- 44, 82, 42, 51,100, 77, 47,100,  0, 81, 74, 69, 54, 35, 36,  0, 9
- 26,100,  0, 70, 16, 41, 69, 42,100, 70, 92, 63, 71, 31, 49,  0, 4
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-  9, 63, 66, 39, 77,  0,  0,  4, 41, 41,100, 75, 77,100,  0, 77, 8
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- 28, 68, 37,100, 96, 94, 82, 47, 66,  0,100,  6, 46, 36,  0, 70, 8
-100,100, 71, 87, 45, 65, 21, 41,  4, 16, 34,  0, 53, 16,  0, 22, 6
-100, 90, 75,100, 64, 79, 94, 96, 81, 66, 64, 37, 35, 15,  0,  0, 9
- 39, 83, 58,100,100, 90, 80, 63, 94, 37, 80,  9, 35,  0,  0, 17, 3
- 44,100,  8, 62,  0, 14, 50,  0, 99, 31,100, 78, 45, 90, 11, 49, 0
- 12, 78, 43,100,100, 97, 78, 66, 38, 40,  0, 13, 38,  0,100,  3, 2
- 28,100,  4, 63,  0, 20, 32,  0, 73, 24,100, 59, 77, 89, 30, 85, 0
- 66,100, 26, 74,  0, 49, 80, 60,100, 75, 59, 78, 37, 38,  3,  0, 4
- 40,100, 21, 89,  0, 55, 10, 18, 55,  0,100, 15, 56, 27, 26,  1, 6
-100, 84, 49, 78, 79, 39, 84,  0,  0, 13, 37, 50, 93, 85, 18,100, 8
- 32, 67, 48,100, 82, 83, 72, 48, 43, 19,  0,  0, 47, 13,100, 12, 2
- 54, 86, 84,100,100, 79, 71, 59, 56, 34, 62,  9, 22,  0,  0, 15, 3
-  0, 45, 35, 66, 74, 90,100,100, 78, 75, 52, 50, 30, 25, 24,  0, 1
- 50,100, 18, 76,  2, 48,  0, 20, 40,  0,100,  7, 68, 28,  0, 27, 6
-100,100, 55, 86, 18, 60,  0, 28, 26,  0, 79, 14, 63, 42, 10, 41, 6
- 56,100, 30, 57,  0, 34, 56, 40,100, 49, 88, 86, 62, 43, 40,  0, 4
- 10,100,  0, 76, 21, 48, 81, 52,100, 73, 88, 65, 86, 32, 88,  0, 4
-  0, 73, 30,100, 62, 86, 46, 48, 13, 22, 21, 21, 58,  4,100,  0, 2
- 26,100,  0, 71, 41, 50, 97, 52,100, 87, 81, 67, 67, 34, 59,  0, 4
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- 21,100,  9, 73,  0, 45, 39, 30, 95, 39,100, 55, 95, 28, 97,  0, 4
- 17, 85, 30, 54, 91, 46, 70,  0, 26, 14,  0, 62, 32, 93,100,100, 5
- 15, 67, 44,100, 51, 91, 44, 44, 29,  0,  0,  1, 50,  4,100,  2, 1
- 69,100, 27, 79,  3, 51,  8, 21, 51,  0,100,  3, 56, 22,  0, 28, 6
- 24, 61, 63, 80,100,100,100, 90, 79, 67, 55, 44, 26, 22,  0,  0, 1
-  0, 37, 35, 58, 70, 80,100,100, 86, 75, 70, 50, 56, 25, 49,  0, 1
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- 26,100,  7, 77,  0, 44, 43, 35, 86, 46,100, 67, 91, 33, 79,  0, 4
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-100,100, 52, 94, 22, 70,  1, 44,  0, 15, 39,  0, 70, 19, 29, 28, 6
- 28, 96,  0, 62, 12, 12, 47,  0, 82, 11,100, 58, 77,100, 42, 99, 0
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- 25, 67, 15, 26, 57,  0,100, 34, 95, 74, 42,100,  0, 67,  1, 26, 0
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- 77,100, 11, 67,100, 72, 43, 99, 36, 32,  0,  0, 84,  2, 30, 46, 8
- 11, 88, 74,100,100, 77, 69, 40, 37,  5,  6,  0,  0, 34, 72, 41, 7
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- 27, 75, 64,100,100, 99, 79, 70, 45, 44,  6, 20,  0,  0, 64,  6, 2
- 19, 91, 58,100,100, 88, 69, 60, 51, 37, 93, 17, 53,  0,  0,  1, 3
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- 19, 82, 16, 48, 45, 18, 11,  0,  0, 44, 18, 84, 58,100,100, 95, 5
- 16, 93, 35, 70,100, 86, 26,100, 46, 86, 86, 72, 52, 32,  0,  0, 9
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-100,100, 50, 81, 16, 54,  5, 25, 34,  0, 89, 14, 70, 41,  0, 49, 6
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-100, 78, 43,100,  2, 72, 51, 35, 46,  0,  0, 24, 50, 58, 76, 90, 8
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- 23, 93, 30, 64, 90, 36, 59,  0, 12, 12,  0, 54, 13, 91,100,100, 5
- 59, 77,  0, 77, 49, 38, 93,  0, 10,  6, 38, 45,100, 79, 52,100, 8
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- 22, 89,  0, 58, 44, 32, 27,  0,  1, 33,  5, 84, 48,100,100, 91, 5
-100, 87, 70,100, 50, 66, 69, 28, 35,  0,  0, 17, 44, 46, 92, 72, 8
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-  0, 90, 40,100, 66, 78, 44, 48, 10, 24,  4,  0, 52,  0,100,  2, 2
- 16, 78, 41,100, 89, 84, 38, 61, 29, 41,100, 25, 84,  2,  0,  0, 3
-100,100, 82, 90, 51, 62, 26, 32, 12,  0, 56,  6, 46, 26,  0, 12, 6
-  0, 84, 37,100, 82, 96, 85, 67, 59, 41, 31, 15, 51,  0,100,  2, 2
-  0, 86, 35, 67, 98, 33, 81,  0, 24, 22, 74, 60,100,100, 15, 99, 8
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-  0, 48, 42, 71, 64,100, 56, 56, 54, 13, 33,  0, 42,  3,100,  3, 1
-  0, 63, 23, 93, 78,100, 89, 69, 54, 41, 11, 16, 41,  4,100,  0, 2
-  0, 62, 48, 80, 89,100, 96, 78,100, 55, 96, 33, 96, 10, 85,  0, 1
- 52, 83, 74,100, 74, 63, 54, 28, 17,  0,  0, 16, 50, 22,100,  5, 2
- 26,100,  0, 75,  2, 47, 61, 41,100, 63, 93, 56, 84, 27, 75,  0, 4
- 53, 97,  0, 72, 66, 38, 95,  0, 29, 15, 71, 55,100, 98, 15,100, 8
-  8, 69, 58, 95, 62,100, 54, 61, 44, 23,  0,  0, 29,  3,100,  8, 1
-100, 91, 63,100, 42, 58, 83, 69, 97, 94, 70, 45, 37,  0,  0,  1, 9
-  2, 91, 48,100, 68, 69, 52, 34, 37,  0,  0, 24, 43, 34,100, 31, 7
- 15, 70, 20, 32, 54,  0, 96, 24,100, 66, 68,100, 16, 92,  0, 52, 0
-100,100, 66, 85, 39, 61, 16, 34, 10,  3, 45,  0, 36, 22,  0, 12, 6
-  0, 45, 53, 36, 62,  0,  7,  6, 52, 38,100, 70, 71,100, 11, 84, 8
-100,100, 53, 81, 16, 56,  0, 25, 33,  0, 89,  3, 72, 19, 19,  9, 6
-  9, 92, 56,100, 54, 58, 33, 18, 10,  0,  0, 36, 50, 38,100, 38, 7
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- 12, 99, 49,100,100, 93, 65, 62, 28, 32,  0,  0, 11, 35, 72, 39, 7
- 48,100,  0, 43, 39,  0,100, 52, 54, 87, 18, 48, 74, 78, 19, 19, 0
-100, 90, 60,100, 18, 84, 70, 88, 89, 71, 66, 44, 37, 18,  0,  0, 9
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- 68, 96, 20, 84,  0, 42, 17,  0, 74,  1,100, 40, 88, 84, 36,100, 0
-100,100, 55, 91, 21, 65,  0, 34, 17,  3, 66,  0, 69, 25, 19, 25, 6
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-100,100, 51, 81, 16, 56,  3, 27, 24,  0, 79,  3, 58, 29,  0, 38, 6
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- 26, 93,  0, 54, 16,  2, 62,  0,100, 34, 85, 86, 40,100,  6, 65, 0
-  0, 82, 24,100, 53, 84, 46, 51, 25, 23, 32,  0, 66,  1,100,  4, 2
-  0, 96, 31,100, 81, 93, 76, 48, 56,  1, 44,  0, 49, 32,100, 35, 7
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- 90, 52, 79,100,  0, 99, 19, 50, 66,  4, 16,  0, 34, 51,100, 86, 8
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- 20, 92, 10, 51, 68, 47, 45,  0,  2,  9,  0, 67, 39, 97,100,100, 5
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- 42, 66, 54,100, 81, 83, 57, 48, 24, 19,  0, 12, 50,  9,100,  0, 2
-100, 85, 58,100, 10, 97, 28, 76, 77, 73, 54, 53, 21, 28,  0,  0, 9
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- 47, 88, 72,100, 65, 44, 36,  8,  0,  0, 27, 20, 63,  5,100,  3, 2
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- 10, 81, 41, 59,100, 46, 89,  0, 31,  3,  0, 49, 10, 93, 75,100, 5
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-  0, 53, 35, 76, 78, 98,100,100, 84, 75, 68, 50, 54, 25, 54,  0, 1
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-100,100, 38, 98, 49, 62, 97, 86, 98, 77, 97, 36, 70,  2,  0,  0, 9
- 25, 90, 42,100, 15, 63,  0, 26, 42,  0,100,  3, 80, 28, 59,  6, 6
-  4, 97, 81,100,100, 67, 66, 33, 30,  0,  0,  9,  0, 36, 82, 35, 7
- 31, 71, 57, 88,100,100, 71, 80, 46, 60, 20, 41,  3, 20,  0,  0, 1
- 25, 81, 47,100, 48, 55, 27, 17,  0,  3, 32, 21, 65,  2,100,  0, 2
- 11, 82, 51,100, 93, 89, 65, 66, 73, 51,100, 32, 53, 14,  0,  0, 3
-100,100, 45, 85, 12, 55,  0, 20, 45,  0, 94, 20, 59, 45,  3, 31, 6
-  0,100, 10, 90, 56, 91,100, 92, 69, 71, 40, 48, 17, 21, 12,  0, 7
-100, 95, 87,100, 49, 76, 17, 47,  0, 14, 40,  0, 66, 25, 19, 25, 6
- 70, 89, 34, 67, 71, 37, 51,  2,  0,  0, 23, 45, 49, 88,100,100, 5
-100,100, 43, 78, 80, 39, 76,  0,  0, 10, 39, 46, 86, 82, 10, 97, 8
- 25, 98,  0, 64, 83, 72, 79, 22, 12,  0,  9, 51,  8, 95,100,100, 5
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- 67, 75, 79,100, 94, 74, 72, 42, 38, 15,  0,  0, 47,  5,100,  1, 2
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- 42, 84, 70,100,100, 87, 69, 65, 55, 43, 86, 23, 51,  5,  0,  0, 3
-100,100, 63, 81, 44, 55, 39, 28, 42,  1, 68,  0, 49, 25,  0, 27, 6
-100, 99, 60,100, 34, 78, 14, 53,  0, 27,  6,  0, 37,  9,  6, 27, 6
- 85,100, 38, 80, 13, 48, 11, 14, 58,  0,100, 22, 58, 43,  0, 42, 6
- 28, 65, 41,100, 63, 64, 55, 21, 31,  0,  0, 33, 50, 45,100, 58, 7
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- 35, 83, 69,100,100, 79, 84, 52, 47, 31,  0, 12, 14,  0, 77,  2, 2
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-100,100, 56, 88, 64, 67, 91, 96, 93, 60, 79, 24, 43,  0,  0, 11, 9
- 84,100, 72, 98, 38, 66, 18, 31, 44,  0,100, 14, 64, 39,  0, 27, 6
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- 40, 99,100, 87, 43,100, 30, 56, 73, 44, 98,  9, 38,  0,  0, 31, 5
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- 21, 91, 59,100, 62, 66, 34, 36,  0, 11, 19, 13, 59,  0,100,  9, 2
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-  0,100, 73, 94, 95, 71, 74, 36, 62,  0, 41,  5, 24, 30,100, 35, 7
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- 63, 77, 95,100, 92, 63, 64, 28, 26,  2,  0,  0, 50,  4,100,  7, 2
- 37, 81, 61,100, 91, 84, 63, 63,100, 46, 85, 14, 37,  0,  0, 16, 3
-100,100, 49, 93, 21, 62,  0, 32, 12,  0, 88,  8, 93, 34, 16, 22, 6
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- 32, 82, 69,100, 74, 70, 57, 49,100, 33, 94,  5, 47,  0,  0,  7, 3
-  0,100, 40, 97,100, 83, 92, 53, 77, 23, 59,  0, 24, 25,100, 33, 7
-100,100, 46, 80, 11, 53,  0, 23, 39,  0,100, 12, 73, 33,  7, 25, 6
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- 26, 71, 54,100, 77, 81, 52, 49, 17, 21,  0, 12, 50, 12,100,  0, 2
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- 22, 66, 47,100, 66, 68, 38, 28,  0,  1,  7,  2, 53,  2,100,  0, 2
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-  0, 96, 47,100, 71, 70, 67, 35, 58,  0,100,  1, 74, 17, 19, 18, 7
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- 13, 65, 39,100, 72, 82, 49, 44, 11, 15,  0,  0, 50,  4,100,  6, 2
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- 86, 86, 44, 64,  0, 69, 39, 95, 95,100,100, 65, 73, 31, 57,  0, 9
- 10, 97,  0, 46, 20,  0, 70, 12,100, 55, 87,100, 37, 86, 10, 43, 0
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- 38, 83,  0, 58, 41, 32, 32,  0, 13, 24, 13, 64, 35, 97,100,100, 5
- 67, 76, 87,100, 96, 74, 70, 50,100, 26, 76,  1, 34,  0,  0, 20, 3
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-  0, 83, 18, 50, 63, 16, 23,  0,  3, 35, 50, 68,100,100, 13, 95, 8
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- 25, 71, 44,100, 65, 81, 37, 52,  0, 30,  9, 18, 54, 10,100,  0, 2
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-100,100, 58, 86, 27, 66,  7, 43,  0, 18, 34,  0, 72, 14, 43, 29, 6
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- 80,100, 35, 97, 45, 76, 98, 80,100, 53, 95, 19, 53,  0,  0,  5, 9
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-100, 93, 51,100, 21, 60, 75, 61, 94, 95, 91, 46, 56,  6,  0,  0, 9
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- 32, 58, 26, 89, 73,100, 80, 56, 42, 21,  0,  0, 50,  5,100,  4, 2
- 40, 80, 60,100,100, 89, 59, 64, 60, 48,100, 27, 60,  2,  0,  0, 3
- 32, 82, 67,100,100, 85, 69, 58, 70, 36, 88, 10, 44,  0,  0,  7, 3
- 40, 74, 87, 93,100,100, 81, 73, 79, 47, 64, 20, 15,  0,  0,  6, 1
- 20, 77,  0, 44, 25,  0, 77,  9,100, 54, 76,100, 26,100,  8, 53, 0
-  0, 58,  6, 67, 53, 85,100,100, 76, 75, 52, 51, 34, 26, 40,  0, 1
-100,100, 69, 83, 36, 62, 11, 38,  0, 12, 39,  0, 70, 18, 26, 26, 6
- 28, 74, 57,100, 81, 74, 38, 47, 78, 49,100, 18, 49,  0,  0, 12, 3
- 35,100,  8, 73,  0, 39, 58, 24,100, 44,100, 67, 79, 34, 71,  0, 4
- 91,100, 56, 91, 19, 62,  0, 30, 22,  0,100,  5, 99, 33, 19, 44, 6
-  0, 93, 64,100,100, 82, 78, 51, 52, 20, 27,  0,  1, 29, 63, 32, 7
-  4, 77, 42,100, 97, 95, 77, 62, 90, 49,100, 15, 49,  0,  0, 12, 3
-  7,100,  0, 96,  1, 72,  7, 48, 38, 38, 66, 36, 70, 14,100,  0, 4
- 24, 85, 14, 63, 69, 38, 60,  0, 24, 16,  0, 55, 32, 91,100,100, 5
- 72, 72, 51,100,  4, 75, 44, 38, 52,  0,  0, 17, 41, 53,100, 81, 8
-  0, 66, 15, 99, 58,100, 64, 66, 43, 32, 11,  5, 50,  0,100,  5, 2
-  0, 95, 49,100,100, 98, 85, 63, 50, 31, 13,  0, 13, 27, 60, 29, 7
-100, 88, 77,100, 43, 80, 17, 54,  6, 24, 24,  0, 40, 22,  0, 26, 6
-  4, 70,  0, 27, 34,  0, 70,  1,100, 34, 90, 86, 55,100, 20, 83, 0
- 71, 64,100, 79, 63,100,  0, 85, 29, 61,100, 66, 94, 33, 95,  0, 9
- 98,100, 40, 87,  9, 55,  0, 21, 47,  0,100, 22, 39, 31,  7,  4, 6
- 91,100, 42, 86,  0, 11, 52,  0,100, 70, 39, 77, 76, 71, 21,  7, 0
- 30, 58, 79, 91,100,100, 88, 60, 79, 20, 16,  0,  0,  1, 86,  2, 1
-  0,100, 63,100, 79, 71, 61, 36, 47,  0, 21,  5, 36, 29,100, 31, 7
-  0, 51, 20, 66, 52, 84, 85,100,100, 86, 85, 57, 68, 29, 58,  0, 1
- 57, 89,  0,100,  1, 68, 43, 34, 30,  0,  1, 31, 41, 65,100, 86, 8
- 39, 96, 57, 59,100, 94, 34,100, 61, 66, 78, 66, 71, 15,  0,  0, 9
- 20, 77, 61,100,100, 80, 48, 46,  9,  7, 68,  0, 25, 39,  0, 82, 8
- 25, 92, 71,100, 75, 62, 57, 25, 30,  0,  0, 32, 47, 39,100, 40, 7
-  0, 58, 36, 70, 71, 86,100,100, 84, 75, 69, 51, 56, 25, 46,  0, 1
- 53, 85, 95,100,100, 97, 58, 92, 19, 72, 38, 44, 39,  9,  0,  0, 5
- 51,100, 36, 83,  3, 52,  0, 33, 67, 38,100, 53, 83, 34, 70,  0, 4
- 15,100,  0, 78,  3, 46, 66, 43,100, 58, 95, 72, 92, 36, 90,  0, 4
- 84, 90,  0, 91, 51, 56, 98, 19, 36,  0, 43, 40,100, 75, 62,100, 8
-  0, 17, 24, 44, 64, 73,100,100, 68, 84, 32, 57, 24, 28, 16,  0, 1
- 26,100,  6, 80,  0, 48, 63, 43,100, 69, 98, 60, 86, 27, 83,  0, 4
-  0, 52, 71, 71,100,100, 80, 64, 77, 26, 60,  5,  3,  3, 89,  0, 1
- 96, 98, 44,100,  5, 72,  0, 36, 38,  8,100,  6, 61, 21, 11,  0, 6
- 62,100, 20, 96,  0, 60,  9, 22, 59,  0,100, 25, 48, 35,  5,  8, 6
- 47, 85, 18, 62,  5, 20, 47,  0,100, 24, 99, 66, 59, 98,  0,100, 0
- 46, 89, 63,100, 96, 78, 59, 53,100, 47,100, 18, 50,  0,  0,  9, 3
- 35, 96,  0, 71, 35, 36, 36,  0,  3, 16,  9, 68, 45,100,100, 92, 5
-  0, 96, 41,100, 61, 68, 47, 31, 31,  0, 12, 36, 46, 48,100, 47, 7
-  0, 81, 29,100, 61, 87, 56, 49, 34, 17, 35,  0, 69,  2,100,  5, 2
-  0, 91, 47,100,100, 81, 88, 44, 60, 10, 37,  0, 24, 32, 96, 40, 7
- 22,100, 25, 63, 54, 26, 22,  0,  0, 37,  2, 82, 49, 96,100, 95, 5
- 21,100, 19, 81, 11, 50,  0, 23, 65, 30,100, 43, 65, 30, 68,  0, 4
-  0, 55, 38, 74, 83, 96,100,100, 83, 75, 71, 50, 60, 24, 43,  0, 1
-  8, 68, 25,100, 56, 74, 37, 35,  0,  6,  2,  4, 51,  0,100,  4, 2
- 75,100, 26, 84,  0, 42, 13,  0, 69,  7,100, 46, 84, 89, 33, 85, 0
-  0, 55, 41, 80, 62,100, 48, 66, 35, 32, 11,  0,  7,  4,100,  4, 1
- 81, 73, 73,100,  0, 85, 27, 60,100, 76, 99, 64, 94, 31, 86,  0, 9
- 40, 99,  0, 74,  1, 20, 44,  0, 88, 24,100, 76, 60,100, 21, 70, 0
-  1, 73, 29,100, 74, 97, 56, 63, 21, 34,  0,  4, 50,  0,100,  0, 2
- 99,100, 67, 85, 22, 58,  1, 27, 36,  0,100, 18, 77, 47,  0, 59, 6
- 37,100, 13, 73,  0, 45, 64, 40,100, 50, 75, 61, 58, 30, 43,  0, 4
- 42, 99, 55, 61, 71, 24, 18,  0,  0, 30, 64, 61,100, 94,  9,100, 8
- 90, 76, 42, 69, 40,100, 81, 90, 93, 54,100, 16, 55,  0,  0, 10, 9
- 13, 87, 11,100, 59, 95, 32, 65, 81, 56,100, 29, 56,  8,  0,  0, 3
-  4, 81, 35,100, 45, 75, 25, 56, 82, 53,100, 25, 57,  6,  0,  0, 3
- 67,100, 19, 90,  0, 47, 14,  4, 69,  0,100, 38, 91, 82, 46, 99, 0
- 41, 86, 80,100, 93, 78, 50, 58, 94, 44,100, 14, 53,  0,  0,  4, 3
- 34, 65, 42, 37, 39,  5,  0,  0,  6, 35, 27, 67, 61, 88,100,100, 5
- 90, 79, 30, 61,  4, 89, 55,100, 80, 63,100, 26, 74,  0,  0,  8, 9
- 43,100, 30, 82,  5, 53,  0, 27, 52, 39,100, 57, 83, 29, 72,  0, 4
- 15, 87, 55,100,100, 99, 84, 77, 52, 57, 63, 33, 41, 10,  0,  0, 3
- 18, 59,  9, 22, 51,  0, 96, 21,100, 63, 72,100, 22, 93,  0, 55, 0
- 20, 77, 54,100,100, 94, 81, 64, 79, 44, 94, 15, 48,  0,  0, 14, 3
- 40, 93,  0, 99, 50,100,100, 99, 82, 88, 64, 60, 55, 30, 55,  0, 7
-  0, 74, 33, 91, 92,100,100, 77, 71, 40, 52,  0, 37, 34, 69, 44, 7
- 18, 90, 11, 43, 34,  0, 87, 20,100, 67, 57,100, 10, 73,  0, 24, 0
- 34, 85, 64,100, 90, 82, 60, 56,100, 38, 92, 11, 44,  0,  0, 13, 3
-  1, 85, 48,100,100,100, 70, 76, 91, 51,100, 18, 52,  3,  0,  0, 3
- 31, 70, 47,100, 91, 75, 51, 50, 71, 48,100, 18, 51,  0,  0, 17, 3
-  0, 62, 33, 81, 70, 99,100,100, 85, 75, 67, 50, 51, 25, 37,  0, 1
-  0, 66, 35,100, 45, 92, 41, 38, 22,  1,  5,  0, 53,  3,100,  6, 1
- 46, 73, 80,100, 70, 86, 61, 46, 45,  8,  0,  0, 47,  4,100,  7, 1
- 57, 76, 47,100, 89, 95, 62, 64, 71, 49,100, 23, 57,  1,  0,  0, 3
- 93,100, 53, 77, 25, 49,  8, 19, 44,  0,100, 11, 59, 18,  0, 10, 6
- 10, 81, 61,100,100, 76, 64, 38, 35,  0, 83, 10, 51, 48,  0, 76, 8
- 42,100, 19, 75,  1, 49,  0, 23, 54, 17,100, 32, 84, 27, 86,  0, 4
- 20, 70, 29,100, 63, 82, 53, 46, 29, 14,  0,  0, 50,  3,100,  4, 2
-  0, 84, 31,100, 43, 60, 39, 16, 27,  0, 14, 27, 57, 30,100, 33, 7
- 81,100, 32, 82,  6, 55,  0, 27, 23,  0,100,  0, 97, 25, 16, 18, 6
- 23,100, 25, 91,  0, 53, 19, 42, 92, 62, 88, 62, 97, 23,100,  0, 4
-  0, 49, 40, 59, 72, 79,100,100, 85, 74, 69, 48, 53, 21, 51,  0, 1
- 41,100, 58, 66,100, 98, 34, 92, 68, 70, 75, 52, 69,  1,  0,  0, 9
- 24, 88, 59,100,100, 91, 89, 64, 61, 42, 28, 22,  0,  0, 47,  2, 2
- 93,100, 39, 81, 10, 46, 11,  7, 71,  2,100, 35, 37, 32,  0,  0, 6
- 55, 89, 85,100,100, 81, 78, 60, 69, 35, 64,  9, 33,  0,  0,  3, 3
- 85, 64, 85,100, 39, 81, 71, 56, 98, 71,100, 30, 64,  0,  0,  2, 9
- 17, 63,  6, 20, 51,  0, 95, 28,100, 72, 55,100,  0, 91,  0, 52, 0
-  0, 82,  9, 59, 56, 34, 41,  0, 10, 30,  3, 67, 42, 96,100,100, 5
- 49,100,  0, 70, 24, 56,100, 65, 86, 85, 44, 77, 21, 38,  6,  0, 4
-100, 98, 60,100, 24, 87,  3, 58, 35, 51, 58, 26, 36,  0,  0,  5, 5
- 59, 65, 91,100, 84, 96, 72, 50, 51,  8,  0,  0, 45,  1,100,  0, 1
-  0, 78, 29,100, 94, 86, 70, 48, 42, 11, 32,  0, 25, 36,100, 40, 7
diff --git a/scikits/learn/datasets/pendigits/testing/__init__.py b/scikits/learn/datasets/pendigits/testing/__init__.py
deleted file mode 100644
index 5365f9712c52f6f2b410515d2da5e3aa04e665c4..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/pendigits/testing/__init__.py
+++ /dev/null
@@ -1,8 +0,0 @@
-#! /usr/bin/env python
-# Last Change: Sun Jul 22 03:00 PM 2007 J
-import data 
-__doc__     = data.DESCRSHORT
-copyright   = data.COPYRIGHT
-source      = data.SOURCE
-
-load = data.load
diff --git a/scikits/learn/datasets/pendigits/testing/data.py b/scikits/learn/datasets/pendigits/testing/data.py
deleted file mode 100644
index d49415c4b18c21e878bf06c2ae5aa4d5687ce35e..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/pendigits/testing/data.py
+++ /dev/null
@@ -1,99 +0,0 @@
-#! /usr/bin/env python
-# -*- coding: utf-8 -*-
-# Last Change: Sun Jul 22 02:00 PM 2007 J
-
-# The code and descriptive text is copyrighted and offered under the terms of
-# the BSD License from the authors; see below. However, the actual dataset may
-# have a different origin and intellectual property status. See the SOURCE and
-# COPYRIGHT variables for this information.
-
-# Copyright (c) 2007 David Cournapeau <cournape@gmail.com>
-#
-# All rights reserved.
-#
-# Redistribution and use in source and binary forms, with or without
-# modification, are permitted provided that the following conditions are
-# met:
-#
-#     * Redistributions of source code must retain the above copyright
-#       notice, this list of conditions and the following disclaimer.
-#     * Redistributions in binary form must reproduce the above copyright
-#       notice, this list of conditions and the following disclaimer in
-#       the documentation and/or other materials provided with the
-#       distribution.
-#     * Neither the author nor the names of any contributors may be used
-#       to endorse or promote products derived from this software without
-#       specific prior written permission.
-#
-# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
-# TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
-# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
-# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
-# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
-# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
-# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
-# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
-# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
-# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
-"""Pen-based recognition of handwritten digits: testing data"""
-
-__docformat__ = 'restructuredtext'
-
-from scikits.learn.datasets.pendigits import _pendigit as PD
-
-COPYRIGHT   = PD.COPYRIGHT
-TITLE       = """Pen-Based Recognition of Handwritten Digits Original: testing data."""
-SOURCE      = PD.SOURCE
-
-DESCRSHORT  = PD.DESCRSHORT + """
-
-Those are the testing, unnormalized data."""
-
-DESCRLONG   = PD.DESCRLONG 
-NOTE        = PD.NOTE
-
-def load():
-    """load the PENDIGITS testing data.
-    
-    :returns:
-        data: dictionary.
-
-    """
-    import numpy
-    from pendigits_tes import testing
-    assert len(testing) == 3498
-
-    def raw_to_num(dt):
-        cor = numpy.empty((len(dt), 16), numpy.int)
-        digclass = numpy.empty(len(dt), dtype = numpy.int)
-        for i in range(len(cor)):
-            cor[i] = dt[i][:-1]
-            digclass[i] = dt[i][-1]
-        #xcor = coordinates[:, ::2]
-        #ycor = coordinates[:, 1::2]
-        return cor, digclass
-
-    data = {}
-
-    # Coordinates
-    cor, digclass = raw_to_num(testing)
-    dt = [('x%d' % i, numpy.int) for i in range(8)]
-    dt.extend([('y%d' % i, numpy.int) for i in range(8)])
-    data['data'] = numpy.empty(len(cor), dt)
-    for i in range(8):
-        data['data']['x%d' % i] = cor[:, 2*i]
-        data['data']['y%d' % i] = cor[:, 2*i + 1]
-
-    # label
-    data['label'] = digclass
-
-    # class names
-    cnames = ['zero', 'one', 'two', 'three', 'four', 'five', 'six', 'seven',\
-              'eight', 'nine']
-    data['class'] = numpy.empty(10, 'S%d' % numpy.max([len(i) for i in cnames]))
-    for i in range(len(cnames)):
-        data['class'][i] = cnames[i]
-
-    return data
diff --git a/scikits/learn/datasets/pendigits/testing/pendigits_tes.py b/scikits/learn/datasets/pendigits/testing/pendigits_tes.py
deleted file mode 100644
index 46476c7c92689cdc15c26d40484a3c1dffe63df6..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/pendigits/testing/pendigits_tes.py
+++ /dev/null
@@ -1,3037 +0,0 @@
-testing = [[88, 92, 2, 99, 16, 66, 94, 37, 70, 0, 0, 24, 42, 65, 100, 100, 8],
-[80, 100, 18, 98, 60, 66, 100, 29, 42, 0, 0, 23, 42, 61, 56, 98, 8], [0, 94, 9,
-57, 20, 19, 7, 0, 20, 36, 70, 68, 100, 100, 18, 92, 8], [95, 82, 71, 100, 27,
-77, 77, 73, 100, 80, 93, 42, 56, 13, 0, 0, 9], [68, 100, 6, 88, 47, 75, 87, 82,
-85, 56, 100, 29, 75, 6, 0, 0, 9], [70, 100, 100, 97, 70, 81, 45, 65, 30, 49,
-20, 33, 0, 16, 0, 0, 1], [40, 100, 0, 81, 15, 58, 100, 57, 47, 87, 50, 88, 40,
-42, 36, 0, 4], [3, 71, 0, 95, 45, 100, 100, 99, 79, 78, 48, 53, 31, 24, 54, 0,
-7], [79, 87, 98, 81, 71, 100, 72, 73, 100, 66, 91, 21, 48, 0, 0, 13, 9], [92,
-95, 30, 100, 34, 68, 87, 89, 84, 78, 100, 35, 64, 0, 0, 19, 9], [58, 64, 100,
-96, 27, 100, 0, 63, 79, 65, 91, 72, 48, 36, 10, 0, 9], [34, 89, 3, 70, 1, 25,
-49, 0, 100, 23, 100, 67, 56, 99, 0, 100, 0], [0, 90, 46, 100, 88, 92, 79, 69,
-60, 48, 39, 27, 47, 6, 100, 0, 2], [20, 71, 0, 29, 31, 0, 78, 12, 100, 51, 84,
-93, 37, 100, 8, 66, 0], [100, 100, 67, 98, 41, 80, 44, 50, 78, 42, 68, 16, 35,
-2, 0, 0, 5], [91, 69, 48, 57, 9, 79, 60, 100, 100, 75, 95, 40, 64, 8, 0, 0, 9],
-[30, 74, 55, 100, 89, 87, 66, 56, 100, 38, 92, 8, 41, 0, 0, 20, 3], [5, 65, 0,
-89, 37, 100, 88, 97, 100, 79, 71, 53, 48, 26, 59, 0, 7], [42, 93, 19, 88, 0,
-42, 24, 0, 83, 11, 100, 56, 75, 100, 17, 97, 0], [4, 100, 0, 72, 15, 44, 79,
-50, 100, 76, 90, 51, 83, 22, 85, 0, 4], [100, 100, 79, 80, 54, 59, 32, 38, 21,
-16, 50, 0, 79, 16, 0, 16, 6], [0, 76, 30, 48, 53, 9, 11, 0, 47, 34, 97, 66,
-100, 100, 38, 85, 8], [0, 93, 40, 100, 57, 61, 51, 17, 35, 0, 12, 37, 54, 48,
-100, 49, 7], [100, 100, 73, 95, 40, 69, 14, 39, 2, 2, 39, 0, 37, 29, 0, 14, 6],
-[88, 100, 42, 77, 12, 50, 0, 22, 45, 0, 100, 17, 73, 44, 15, 49, 6], [33, 86,
-0, 55, 1, 12, 52, 0, 90, 34, 100, 76, 56, 100, 6, 77, 0], [69, 100, 44, 77, 5,
-50, 0, 28, 67, 23, 100, 44, 95, 29, 89, 0, 4], [27, 83, 0, 42, 9, 0, 65, 17,
-96, 57, 100, 100, 45, 95, 10, 58, 0], [19, 100, 35, 93, 0, 63, 12, 36, 89, 37,
-100, 66, 94, 33, 89, 0, 4], [27, 73, 81, 100, 83, 91, 78, 52, 62, 14, 0, 0, 29,
-1, 100, 5, 1], [77, 96, 38, 100, 58, 77, 99, 86, 100, 50, 84, 12, 43, 0, 0, 0,
-9], [41, 84, 73, 100, 100, 82, 62, 60, 97, 38, 91, 8, 42, 0, 0, 19, 3], [32,
-92, 24, 47, 71, 36, 38, 0, 0, 0, 21, 48, 49, 92, 100, 100, 5], [53, 100, 30,
-95, 0, 60, 100, 55, 92, 87, 77, 79, 79, 37, 79, 0, 4], [100, 95, 75, 100, 42,
-70, 0, 44, 42, 33, 85, 49, 83, 31, 85, 0, 4], [0, 50, 41, 69, 76, 90, 100, 100,
-89, 74, 78, 50, 70, 25, 68, 0, 1], [2, 75, 37, 100, 56, 99, 58, 61, 46, 25, 0,
-0, 34, 5, 100, 8, 1], [10, 100, 0, 60, 14, 18, 60, 0, 100, 24, 96, 66, 58, 95,
-19, 73, 0], [79, 90, 100, 93, 63, 100, 82, 84, 99, 61, 87, 22, 44, 0, 0, 19,
-9], [0, 88, 59, 100, 89, 72, 82, 40, 63, 9, 28, 0, 25, 25, 100, 27, 7], [5, 97,
-9, 61, 37, 25, 0, 0, 7, 32, 56, 64, 100, 96, 37, 100, 8], [59, 89, 42, 23, 29,
-42, 25, 100, 100, 82, 75, 46, 98, 0, 0, 3, 3], [20, 100, 6, 61, 25, 28, 18, 0,
-0, 27, 11, 63, 55, 75, 100, 82, 5], [100, 100, 49, 77, 17, 51, 2, 24, 24, 0,
-100, 10, 73, 35, 0, 42, 6], [29, 80, 0, 41, 14, 0, 70, 14, 100, 53, 100, 96,
-49, 100, 19, 62, 0], [21, 87, 33, 52, 62, 13, 5, 0, 0, 36, 74, 66, 100, 100, 5,
-89, 8], [13, 67, 40, 100, 65, 78, 37, 42, 0, 11, 6, 4, 60, 0, 100, 19, 2], [5,
-70, 56, 44, 60, 3, 0, 0, 30, 39, 84, 72, 100, 100, 32, 74, 8], [0, 94, 68, 100,
-89, 68, 72, 33, 43, 0, 3, 21, 25, 50, 100, 58, 7], [100, 93, 48, 100, 27, 69,
-30, 33, 16, 0, 0, 26, 41, 51, 100, 58, 8], [0, 55, 46, 58, 73, 82, 100, 100,
-92, 75, 89, 50, 84, 25, 89, 0, 1], [96, 66, 62, 100, 32, 69, 74, 62, 89, 56,
-100, 10, 50, 0, 0, 10, 9], [32, 96, 70, 100, 12, 95, 32, 66, 89, 62, 100, 22,
-51, 0, 0, 16, 5], [79, 100, 41, 82, 0, 61, 23, 45, 77, 37, 86, 54, 86, 25, 100,
-0, 4], [22, 72, 55, 100, 54, 89, 53, 50, 55, 12, 0, 1, 49, 0, 100, 4, 1], [23,
-70, 51, 100, 74, 82, 51, 46, 20, 15, 0, 4, 50, 0, 100, 2, 2], [88, 100, 100,
-95, 75, 79, 38, 64, 25, 47, 12, 32, 0, 16, 12, 0, 1], [76, 100, 31, 87, 1, 52,
-0, 14, 61, 0, 100, 27, 50, 42, 1, 21, 6], [29, 97, 0, 57, 22, 10, 68, 0, 100,
-40, 83, 90, 37, 100, 12, 57, 0], [53, 67, 80, 44, 67, 7, 0, 0, 35, 36, 83, 68,
-100, 100, 25, 80, 8], [11, 45, 17, 6, 55, 0, 88, 25, 100, 61, 79, 94, 38, 100,
-0, 84, 0], [88, 90, 18, 100, 17, 66, 79, 33, 49, 0, 0, 28, 41, 67, 100, 98, 8],
-[75, 100, 42, 78, 13, 51, 0, 22, 40, 0, 100, 16, 88, 43, 22, 35, 6], [27, 82,
-65, 100, 100, 89, 69, 62, 33, 39, 0, 15, 37, 1, 88, 0, 2], [70, 84, 11, 76, 0,
-91, 56, 100, 99, 83, 100, 55, 88, 28, 75, 0, 9], [88, 100, 29, 100, 30, 74, 85,
-83, 100, 67, 97, 27, 57, 0, 0, 5, 9], [51, 54, 100, 87, 36, 100, 19, 62, 44,
-22, 2, 0, 0, 37, 78, 57, 8], [15, 84, 0, 57, 5, 17, 52, 0, 95, 28, 100, 67, 70,
-100, 20, 87, 0], [0, 76, 29, 95, 92, 100, 81, 77, 75, 56, 100, 35, 85, 13, 31,
-0, 3], [38, 65, 36, 98, 100, 100, 99, 69, 62, 55, 96, 26, 55, 0, 0, 15, 3],
-[82, 100, 8, 92, 45, 60, 100, 29, 52, 0, 0, 24, 21, 61, 53, 98, 8], [0, 82, 34,
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-43, 97, 45, 58, 48, 19, 0, 0, 42, 3, 100, 2, 1], [9, 98, 61, 100, 69, 65, 54,
-30, 33, 0, 0, 32, 19, 37, 100, 43, 7], [11, 90, 0, 41, 31, 0, 82, 0, 100, 46,
-77, 92, 30, 100, 3, 58, 0], [45, 84, 68, 100, 77, 73, 53, 45, 100, 35, 86, 11,
-37, 0, 0, 16, 3], [27, 77, 59, 100, 82, 75, 58, 43, 23, 15, 0, 0, 49, 10, 100,
-9, 2], [7, 72, 0, 57, 52, 77, 100, 100, 93, 84, 67, 56, 41, 28, 22, 0, 1], [30,
-75, 54, 100, 100, 99, 74, 72, 79, 46, 88, 18, 43, 0, 0, 12, 3], [16, 65, 29,
-100, 59, 83, 38, 41, 0, 12, 8, 16, 55, 0, 100, 7, 2], [0, 43, 32, 58, 67, 79,
-100, 100, 89, 76, 76, 51, 63, 25, 59, 0, 1], [40, 81, 77, 100, 100, 86, 78, 59,
-97, 36, 93, 10, 47, 0, 0, 10, 3], [89, 91, 34, 100, 39, 66, 74, 31, 49, 0, 0,
-19, 46, 49, 100, 76, 8], [9, 100, 7, 97, 0, 66, 100, 58, 78, 84, 46, 74, 39,
-37, 39, 0, 4], [1, 73, 49, 100, 55, 92, 51, 56, 46, 20, 0, 2, 30, 1, 100, 0,
-1], [10, 81, 44, 100, 57, 74, 32, 42, 0, 16, 16, 5, 58, 4, 100, 0, 2], [42, 86,
-24, 44, 36, 0, 82, 3, 100, 48, 86, 92, 34, 100, 0, 63, 0], [18, 84, 6, 71, 67,
-37, 38, 0, 0, 27, 51, 64, 100, 100, 17, 79, 8], [0, 88, 28, 100, 71, 96, 63,
-66, 36, 39, 23, 9, 64, 0, 100, 2, 2], [15, 65, 44, 92, 55, 100, 54, 62, 45, 25,
-0, 0, 36, 1, 100, 5, 1], [16, 86, 46, 100, 48, 64, 32, 31, 0, 3, 1, 6, 51, 5,
-100, 0, 2], [21, 76, 39, 100, 45, 67, 27, 29, 0, 0, 25, 2, 63, 1, 100, 2, 2],
-[16, 75, 0, 30, 27, 0, 71, 13, 100, 49, 96, 95, 52, 100, 24, 65, 0], [0, 91,
-40, 58, 62, 22, 22, 0, 22, 35, 69, 67, 100, 100, 18, 91, 8], [0, 86, 47, 100,
-91, 88, 56, 62, 58, 40, 100, 19, 59, 4, 8, 0, 3], [100, 96, 98, 100, 82, 83,
-68, 66, 52, 49, 32, 33, 20, 16, 0, 0, 1], [23, 90, 55, 100, 54, 66, 26, 40, 0,
-31, 32, 19, 65, 2, 100, 0, 2], [29, 100, 0, 68, 9, 23, 47, 0, 90, 10, 100, 54,
-73, 91, 30, 97, 0], [0, 82, 35, 100, 58, 85, 42, 57, 21, 29, 15, 0, 58, 2, 100,
-11, 2], [0, 52, 44, 70, 69, 100, 69, 72, 51, 41, 20, 11, 9, 1, 100, 0, 1],
-[100, 84, 42, 100, 0, 72, 39, 36, 75, 0, 32, 16, 63, 55, 69, 91, 8], [23, 66,
-31, 100, 61, 84, 48, 46, 20, 13, 0, 0, 50, 2, 100, 2, 2], [49, 76, 63, 100, 67,
-77, 34, 53, 0, 29, 8, 13, 53, 1, 100, 0, 2], [16, 59, 30, 100, 55, 87, 34, 45,
-0, 12, 2, 0, 51, 4, 100, 7, 2], [72, 100, 48, 88, 0, 69, 17, 57, 77, 46, 100,
-44, 63, 23, 32, 0, 4], [100, 100, 53, 88, 20, 61, 0, 31, 16, 1, 67, 0, 56, 27,
-3, 32, 6], [5, 75, 38, 100, 58, 76, 35, 41, 4, 11, 0, 0, 49, 7, 100, 3, 2],
-[38, 100, 24, 68, 0, 35, 71, 40, 100, 60, 96, 50, 95, 15, 100, 0, 4], [86, 100,
-46, 81, 18, 61, 0, 40, 0, 19, 32, 0, 100, 3, 46, 10, 6], [36, 96, 29, 73, 71,
-46, 47, 0, 0, 7, 15, 60, 41, 99, 100, 100, 5], [100, 98, 61, 100, 41, 90, 28,
-61, 59, 61, 57, 40, 29, 19, 0, 0, 5], [0, 58, 40, 79, 83, 100, 100, 92, 87, 69,
-73, 46, 63, 22, 80, 0, 1], [0, 93, 43, 99, 92, 100, 68, 52, 64, 0, 47, 0, 40,
-36, 100, 42, 7], [100, 100, 59, 85, 89, 80, 84, 60, 82, 36, 92, 13, 52, 1, 0,
-0, 9], [21, 95, 58, 100, 68, 68, 48, 33, 23, 0, 0, 31, 42, 41, 100, 44, 7],
-[16, 97, 76, 100, 80, 61, 56, 22, 34, 0, 0, 37, 37, 45, 100, 42, 7], [23, 96,
-79, 100, 100, 86, 74, 66, 72, 44, 88, 23, 53, 6, 0, 0, 3], [22, 83, 0, 55, 48,
-40, 45, 0, 15, 25, 15, 72, 52, 100, 100, 85, 5], [32, 82, 4, 56, 43, 25, 36, 0,
-18, 37, 0, 73, 32, 99, 100, 100, 5], [0, 98, 66, 100, 64, 66, 32, 34, 2, 0, 47,
-20, 100, 47, 28, 50, 7], [19, 70, 0, 86, 46, 100, 94, 92, 100, 68, 83, 44, 59,
-22, 41, 0, 9], [18, 96, 4, 70, 0, 99, 62, 100, 100, 97, 82, 62, 72, 25, 64, 0,
-7], [25, 76, 75, 100, 17, 68, 61, 54, 89, 90, 100, 44, 87, 10, 0, 0, 9], [24,
-100, 0, 81, 3, 55, 65, 52, 100, 72, 66, 52, 34, 27, 24, 0, 4], [43, 100, 17,
-84, 0, 62, 29, 43, 84, 47, 100, 43, 71, 22, 49, 0, 4], [0, 99, 75, 100, 83, 71,
-52, 36, 27, 0, 6, 3, 22, 30, 100, 34, 7], [63, 85, 100, 88, 61, 100, 80, 78,
-99, 58, 98, 15, 49, 0, 0, 15, 9], [36, 100, 22, 80, 0, 50, 49, 39, 100, 54, 75,
-62, 58, 31, 59, 0, 4], [0, 59, 9, 64, 57, 86, 100, 100, 72, 75, 47, 51, 21, 25,
-6, 0, 1], [86, 100, 49, 77, 28, 51, 26, 24, 51, 0, 100, 13, 63, 34, 0, 31, 6],
-[61, 80, 97, 90, 60, 100, 67, 80, 100, 58, 83, 24, 44, 4, 0, 0, 9], [86, 100,
-38, 80, 6, 51, 0, 18, 47, 0, 100, 13, 62, 30, 7, 18, 6], [17, 90, 29, 100, 62,
-82, 45, 35, 9, 0, 0, 3, 50, 4, 100, 10, 2], [0, 93, 60, 100, 99, 88, 73, 47,
-55, 5, 39, 0, 38, 34, 100, 36, 7], [0, 92, 48, 100, 76, 74, 70, 41, 57, 9, 38,
-0, 46, 20, 100, 20, 7], [0, 82, 26, 98, 59, 100, 67, 78, 55, 53, 49, 27, 65, 6,
-100, 0, 2], [0, 86, 26, 100, 55, 96, 57, 68, 45, 41, 42, 12, 68, 1, 100, 0, 2],
-[100, 100, 79, 92, 36, 73, 4, 51, 52, 49, 54, 46, 24, 24, 0, 0, 4], [32, 78,
-59, 100, 91, 88, 68, 58, 100, 41, 94, 12, 43, 0, 0, 10, 3], [86, 100, 35, 77,
-8, 51, 0, 23, 35, 0, 100, 15, 84, 42, 22, 58, 6], [92, 72, 72, 100, 34, 72, 76,
-57, 100, 71, 96, 29, 56, 0, 0, 6, 9], [0, 42, 40, 60, 74, 81, 100, 100, 90, 74,
-78, 48, 66, 23, 65, 0, 1], [5, 90, 55, 100, 78, 84, 31, 65, 71, 51, 100, 23,
-52, 5, 0, 0, 3], [15, 100, 23, 62, 66, 40, 37, 0, 0, 13, 0, 56, 45, 85, 100,
-99, 5], [24, 87, 0, 82, 30, 72, 59, 23, 4, 0, 4, 45, 36, 98, 100, 100, 5], [80,
-100, 100, 97, 48, 68, 7, 38, 0, 7, 91, 0, 98, 22, 9, 12, 6], [5, 85, 56, 100,
-82, 78, 38, 55, 52, 48, 100, 29, 63, 5, 0, 0, 3], [0, 82, 40, 100, 92, 98, 100,
-66, 83, 33, 65, 0, 35, 26, 81, 32, 7], [3, 77, 40, 100, 70, 80, 52, 45, 20, 18,
-0, 0, 50, 7, 100, 1, 2], [41, 85, 62, 100, 52, 65, 30, 36, 0, 15, 33, 7, 68, 0,
-100, 19, 2], [42, 84, 80, 85, 52, 100, 67, 81, 100, 57, 85, 22, 44, 5, 0, 0,
-9], [30, 100, 21, 71, 0, 44, 68, 41, 100, 54, 100, 55, 98, 26, 98, 0, 4], [22,
-100, 65, 96, 82, 55, 65, 14, 38, 0, 0, 29, 48, 33, 100, 33, 7], [47, 85, 100,
-100, 40, 87, 24, 59, 80, 61, 90, 34, 57, 8, 0, 0, 5], [0, 45, 42, 70, 66, 100,
-60, 62, 47, 25, 1, 5, 43, 0, 100, 4, 1], [0, 3, 29, 24, 57, 50, 83, 77, 100,
-100, 80, 69, 64, 35, 51, 0, 1], [30, 84, 61, 100, 85, 79, 67, 54, 95, 39, 100,
-14, 54, 0, 0, 10, 3], [52, 86, 60, 50, 50, 14, 0, 0, 27, 32, 73, 61, 100, 94,
-40, 100, 8], [100, 83, 65, 100, 24, 79, 0, 48, 4, 14, 46, 0, 67, 26, 24, 40,
-6], [53, 100, 5, 82, 0, 56, 81, 52, 100, 72, 66, 91, 54, 44, 44, 0, 4], [0, 85,
-39, 100, 83, 99, 87, 71, 60, 44, 32, 17, 55, 0, 100, 1, 2], [16, 95, 100, 100,
-22, 92, 2, 65, 24, 47, 96, 39, 75, 0, 0, 2, 5], [0, 87, 47, 100, 97, 87, 94,
-69, 92, 50, 100, 31, 81, 13, 22, 0, 3], [0, 64, 24, 98, 68, 100, 57, 58, 24,
-25, 7, 6, 54, 7, 100, 0, 2], [47, 100, 35, 95, 0, 66, 31, 43, 100, 48, 95, 66,
-82, 34, 79, 0, 4], [0, 84, 44, 100, 95, 94, 74, 55, 57, 16, 54, 0, 45, 40, 100,
-45, 7], [94, 93, 6, 100, 17, 69, 100, 43, 79, 0, 0, 17, 17, 63, 88, 95, 8],
-[100, 100, 78, 86, 60, 72, 44, 58, 33, 44, 18, 29, 7, 14, 0, 0, 1], [58, 65,
-71, 100, 90, 70, 63, 31, 23, 0, 0, 13, 48, 1, 100, 4, 2], [61, 100, 0, 84, 51,
-60, 100, 33, 72, 0, 16, 17, 41, 53, 87, 84, 8], [43, 75, 62, 100, 91, 87, 77,
-57, 100, 38, 87, 11, 42, 0, 0, 15, 3], [0, 73, 25, 100, 69, 95, 55, 58, 100,
-56, 90, 21, 47, 0, 2, 8, 3], [15, 99, 47, 100, 69, 70, 52, 34, 30, 0, 0, 19,
-41, 31, 100, 34, 7], [100, 77, 98, 100, 41, 83, 5, 55, 0, 23, 42, 0, 66, 24,
-11, 35, 6], [31, 68, 46, 100, 81, 88, 63, 49, 29, 16, 0, 5, 50, 0, 100, 12, 2],
-[82, 100, 2, 92, 8, 61, 75, 80, 71, 79, 100, 44, 81, 11, 0, 0, 9], [0, 63, 15,
-63, 58, 81, 100, 100, 94, 81, 67, 54, 41, 28, 16, 0, 1], [0, 69, 32, 74, 70,
-96, 100, 100, 91, 75, 81, 50, 70, 25, 64, 0, 1], [73, 83, 18, 100, 0, 67, 72,
-34, 100, 0, 6, 16, 37, 54, 70, 88, 8], [49, 89, 71, 59, 98, 23, 38, 0, 18, 33,
-60, 67, 100, 100, 0, 94, 8], [1, 83, 45, 100, 100, 93, 67, 66, 66, 50, 96, 23,
-62, 0, 0, 5, 3], [4, 88, 39, 100, 59, 78, 60, 55, 100, 42, 88, 19, 47, 6, 0, 0,
-3], [0, 88, 45, 100, 100, 99, 96, 76, 69, 54, 69, 29, 69, 5, 18, 0, 3], [100,
-72, 77, 100, 20, 74, 71, 56, 94, 81, 95, 39, 65, 0, 0, 0, 9], [10, 78, 43, 100,
-78, 86, 57, 59, 100, 46, 82, 17, 41, 0, 0, 9, 3], [0, 81, 29, 100, 59, 78, 54,
-35, 41, 0, 12, 30, 55, 41, 100, 46, 7], [0, 91, 39, 100, 75, 72, 80, 37, 79, 0,
-31, 12, 38, 29, 100, 29, 7], [0, 95, 43, 100, 77, 72, 65, 32, 47, 0, 10, 32,
-39, 52, 100, 53, 7], [44, 100, 19, 82, 0, 59, 47, 48, 100, 59, 80, 46, 54, 24,
-41, 0, 4], [26, 65, 56, 100, 58, 88, 46, 44, 15, 11, 0, 0, 50, 1, 100, 4, 1],
-[69, 100, 34, 75, 0, 44, 46, 30, 100, 44, 90, 68, 67, 35, 55, 0, 4], [25, 74,
-36, 100, 61, 78, 39, 37, 5, 4, 0, 2, 50, 0, 100, 1, 2], [99, 98, 40, 100, 39,
-68, 96, 77, 86, 83, 100, 38, 62, 6, 0, 0, 9], [86, 95, 9, 96, 27, 61, 100, 31,
-64, 0, 0, 24, 55, 61, 93, 100, 8], [10, 81, 42, 100, 48, 67, 35, 34, 7, 4, 0,
-7, 49, 0, 100, 0, 2], [0, 68, 23, 100, 35, 90, 31, 54, 20, 18, 7, 0, 53, 2,
-100, 3, 1], [63, 88, 87, 80, 71, 100, 71, 78, 100, 61, 99, 21, 52, 0, 0, 12,
-9], [0, 77, 27, 100, 54, 89, 33, 60, 11, 32, 16, 3, 58, 0, 100, 3, 2], [50, 83,
-74, 47, 90, 0, 41, 4, 59, 49, 100, 85, 47, 100, 0, 71, 8], [91, 94, 13, 83, 67,
-52, 100, 18, 16, 0, 0, 33, 36, 68, 48, 100, 8], [31, 69, 49, 100, 60, 70, 34,
-36, 0, 13, 29, 21, 65, 0, 100, 16, 2], [100, 100, 64, 90, 33, 69, 10, 45, 0,
-17, 30, 0, 50, 20, 13, 36, 6], [86, 78, 60, 100, 51, 63, 95, 77, 100, 66, 90,
-22, 47, 0, 0, 16, 9], [8, 87, 0, 83, 38, 96, 95, 100, 100, 82, 81, 50, 68, 16,
-62, 0, 7], [23, 71, 52, 100, 40, 91, 40, 57, 40, 24, 0, 0, 29, 4, 100, 4, 1],
-[100, 73, 77, 100, 31, 80, 31, 40, 29, 0, 0, 14, 35, 46, 90, 62, 8], [47, 100,
-12, 76, 0, 50, 47, 39, 100, 58, 81, 51, 59, 26, 55, 0, 4], [0, 71, 22, 100, 61,
-91, 49, 54, 21, 22, 6, 0, 53, 8, 100, 7, 2], [0, 15, 29, 40, 59, 68, 85, 97,
-100, 100, 79, 67, 60, 34, 46, 0, 1], [55, 100, 48, 93, 0, 72, 34, 58, 100, 52,
-97, 48, 58, 25, 32, 0, 4], [100, 100, 74, 97, 61, 81, 47, 65, 34, 49, 21, 33,
-5, 16, 0, 0, 1], [46, 100, 20, 73, 0, 43, 46, 30, 100, 45, 93, 58, 63, 30, 52,
-0, 4], [40, 95, 100, 100, 32, 85, 10, 58, 78, 61, 87, 29, 43, 0, 0, 6, 5], [37,
-98, 11, 60, 88, 52, 76, 8, 0, 0, 0, 46, 18, 88, 100, 100, 5], [49, 81, 50, 50,
-85, 25, 42, 0, 0, 16, 15, 58, 44, 91, 100, 100, 5], [38, 100, 19, 71, 0, 39,
-26, 22, 72, 30, 100, 51, 64, 32, 47, 0, 4], [58, 100, 0, 70, 9, 41, 97, 38,
-100, 60, 66, 78, 55, 39, 53, 0, 4], [17, 88, 3, 64, 6, 21, 60, 0, 100, 34, 100,
-76, 48, 100, 0, 78, 0], [100, 100, 69, 80, 36, 54, 17, 27, 19, 0, 83, 3, 67,
-29, 0, 40, 6], [2, 72, 33, 100, 58, 79, 34, 46, 3, 15, 0, 2, 53, 0, 100, 10,
-2], [100, 100, 77, 91, 40, 64, 15, 35, 17, 5, 80, 0, 63, 24, 0, 14, 6], [35,
-70, 75, 47, 75, 10, 0, 0, 18, 36, 68, 68, 100, 100, 23, 79, 8], [6, 83, 99, 86,
-80, 100, 0, 80, 100, 81, 91, 57, 71, 28, 54, 0, 9], [26, 100, 0, 70, 44, 54,
-100, 53, 77, 78, 46, 69, 36, 34, 28, 0, 4], [6, 86, 49, 100, 100, 76, 61, 40,
-20, 4, 41, 0, 74, 23, 0, 27, 7], [100, 100, 71, 80, 42, 59, 18, 38, 0, 14, 23,
-0, 52, 19, 22, 32, 6], [8, 67, 51, 37, 22, 0, 9, 24, 53, 58, 100, 92, 59, 100,
-0, 74, 8], [30, 84, 63, 100, 90, 86, 67, 58, 100, 39, 75, 13, 36, 0, 0, 13, 3],
-[100, 85, 57, 100, 23, 65, 82, 63, 97, 78, 96, 37, 64, 0, 0, 7, 9], [83, 89,
-36, 100, 45, 59, 92, 84, 92, 75, 100, 28, 58, 0, 0, 19, 9], [14, 99, 8, 54, 73,
-46, 44, 0, 0, 17, 1, 81, 44, 99, 100, 100, 5], [98, 100, 43, 83, 7, 51, 0, 15,
-50, 0, 100, 26, 83, 54, 19, 46, 6], [63, 100, 35, 79, 0, 55, 42, 39, 87, 48,
-85, 51, 83, 20, 100, 0, 4], [0, 65, 61, 80, 100, 100, 94, 88, 86, 65, 84, 43,
-86, 20, 92, 0, 1], [0, 100, 59, 100, 81, 88, 60, 45, 52, 0, 31, 7, 24, 32, 100,
-33, 7], [100, 81, 22, 100, 0, 67, 59, 33, 47, 0, 28, 29, 87, 64, 66, 89, 8],
-[26, 93, 63, 100, 77, 78, 56, 54, 100, 41, 98, 17, 52, 6, 0, 0, 3], [100, 70,
-49, 55, 15, 73, 53, 100, 93, 85, 80, 46, 48, 14, 0, 0, 9], [77, 81, 14, 100,
-23, 66, 79, 34, 67, 0, 0, 14, 47, 48, 100, 80, 8], [1, 63, 14, 100, 56, 87, 38,
-42, 0, 9, 2, 2, 51, 5, 100, 0, 2], [47, 87, 89, 100, 91, 75, 67, 56, 100, 39,
-80, 11, 37, 0, 0, 18, 3], [50, 100, 35, 71, 17, 42, 12, 12, 56, 0, 100, 20, 54,
-31, 0, 19, 6], [95, 100, 54, 94, 67, 54, 61, 14, 15, 0, 0, 38, 46, 58, 100, 72,
-8], [19, 94, 53, 100, 69, 67, 50, 31, 21, 0, 0, 29, 49, 34, 100, 37, 7], [0,
-66, 47, 97, 50, 100, 51, 60, 50, 20, 1, 0, 35, 4, 100, 9, 1], [0, 94, 63, 100,
-100, 96, 81, 49, 82, 0, 44, 14, 11, 44, 89, 47, 7], [13, 94, 0, 52, 16, 11, 66,
-0, 100, 32, 90, 74, 48, 100, 5, 78, 0], [49, 72, 64, 100, 100, 88, 78, 52, 43,
-22, 0, 1, 40, 6, 90, 0, 2], [56, 60, 100, 84, 44, 100, 0, 72, 66, 61, 85, 65,
-68, 32, 53, 0, 9], [81, 100, 60, 89, 22, 66, 0, 40, 42, 25, 100, 36, 94, 27,
-75, 0, 4], [61, 100, 32, 70, 0, 41, 18, 28, 77, 29, 100, 49, 95, 34, 92, 0, 4],
-[64, 100, 38, 98, 0, 75, 23, 61, 85, 46, 100, 48, 69, 24, 43, 0, 4], [1, 82,
-42, 100, 64, 79, 42, 61, 96, 49, 100, 17, 48, 0, 0, 13, 3], [41, 72, 7, 50, 0,
-7, 46, 0, 82, 34, 100, 76, 59, 100, 15, 76, 0], [11, 75, 4, 45, 21, 1, 81, 0,
-100, 43, 88, 87, 29, 100, 0, 67, 0], [100, 69, 54, 61, 13, 77, 56, 100, 96, 77,
-90, 44, 58, 14, 0, 0, 9], [100, 100, 59, 90, 22, 62, 0, 29, 22, 0, 76, 10, 51,
-37, 0, 33, 6], [0, 85, 21, 100, 66, 98, 83, 77, 90, 53, 100, 30, 75, 10, 35, 0,
-3], [0, 63, 16, 90, 100, 100, 90, 73, 53, 40, 22, 6, 11, 0, 48, 18, 7], [0, 74,
-35, 100, 100, 96, 94, 63, 52, 35, 0, 11, 5, 0, 77, 6, 2], [43, 89, 93, 100, 66,
-91, 40, 64, 82, 43, 100, 15, 52, 0, 0, 1, 5], [43, 81, 11, 69, 78, 51, 100, 17,
-27, 0, 0, 32, 14, 80, 84, 100, 5], [36, 100, 24, 70, 0, 38, 49, 33, 95, 47, 87,
-55, 96, 21, 100, 0, 4], [16, 75, 41, 100, 52, 64, 32, 27, 0, 0, 21, 9, 62, 2,
-100, 14, 2], [56, 100, 27, 79, 0, 39, 12, 0, 66, 15, 100, 51, 93, 93, 38, 93,
-0], [19, 100, 0, 61, 3, 23, 48, 0, 97, 27, 100, 66, 62, 97, 10, 81, 0], [38,
-100, 37, 81, 12, 55, 0, 28, 52, 27, 100, 42, 86, 26, 65, 0, 4]]
-
diff --git a/scikits/learn/datasets/pendigits/training/__init__.py b/scikits/learn/datasets/pendigits/training/__init__.py
deleted file mode 100644
index 5365f9712c52f6f2b410515d2da5e3aa04e665c4..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/pendigits/training/__init__.py
+++ /dev/null
@@ -1,8 +0,0 @@
-#! /usr/bin/env python
-# Last Change: Sun Jul 22 03:00 PM 2007 J
-import data 
-__doc__     = data.DESCRSHORT
-copyright   = data.COPYRIGHT
-source      = data.SOURCE
-
-load = data.load
diff --git a/scikits/learn/datasets/pendigits/training/data.py b/scikits/learn/datasets/pendigits/training/data.py
deleted file mode 100644
index 24cb84ae0c4e285d0043306114b220f7ff4594f1..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/pendigits/training/data.py
+++ /dev/null
@@ -1,97 +0,0 @@
-#! /usr/bin/env python
-# -*- coding: utf-8 -*-
-# Last Change: Sun Jul 22 03:00 PM 2007 J
-
-# The code and descriptive text is copyrighted and offered under the terms of
-# the BSD License from the authors; see below. However, the actual dataset may
-# have a different origin and intellectual property status. See the SOURCE and
-# COPYRIGHT variables for this information.
-
-# Copyright (c) 2007 David Cournapeau <cournape@gmail.com>
-#
-# All rights reserved.
-#
-# Redistribution and use in source and binary forms, with or without
-# modification, are permitted provided that the following conditions are
-# met:
-#
-#     * Redistributions of source code must retain the above copyright
-#       notice, this list of conditions and the following disclaimer.
-#     * Redistributions in binary form must reproduce the above copyright
-#       notice, this list of conditions and the following disclaimer in
-#       the documentation and/or other materials provided with the
-#       distribution.
-#     * Neither the author nor the names of any contributors may be used
-#       to endorse or promote products derived from this software without
-#       specific prior written permission.
-#
-# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
-# TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
-# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
-# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
-# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
-# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
-# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
-# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
-# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
-# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
-"""Pen-based recognition of handwritten digits: testing data"""
-
-__docformat__ = 'restructuredtext'
-
-from scikits.learn.datasets.pendigits import _pendigit as PD
-
-COPYRIGHT   = PD.COPYRIGHT
-TITLE       = """Pen-Based Recognition of Handwritten Digits Original: training data."""
-SOURCE      = PD.SOURCE
-
-DESCRSHORT  = PD.DESCRSHORT + """
-
-Those are the training, unnormalized data."""
-
-DESCRLONG   = PD.DESCRLONG 
-NOTE        = PD.NOTE
-
-def load():
-    """load the PENDIGITS training data.
-    
-    :returns:
-        data: dictionary.
-
-    """
-    import numpy
-    from pendigits_tra import training
-    assert len(training) == 7494
-
-    def raw_to_num(dt):
-        cor = numpy.empty((len(dt), 16), numpy.int)
-        digclass = numpy.empty(len(dt), dtype = numpy.int)
-        for i in range(len(cor)):
-            cor[i] = dt[i][:-1]
-            digclass[i] = dt[i][-1]
-        return cor, digclass
-
-    data = {}
-
-    # Coordinates
-    cor, digclass = raw_to_num(training)
-    dt = [('x%d' % i, numpy.int) for i in range(8)]
-    dt.extend([('y%d' % i, numpy.int) for i in range(8)])
-    data['data'] = numpy.empty(len(cor), dt)
-    for i in range(8):
-        data['data']['x%d' % i] = cor[:, 2*i]
-        data['data']['y%d' % i] = cor[:, 2*i + 1]
-
-    # label
-    data['label'] = digclass
-
-    # class names
-    cnames = ['zero', 'one', 'two', 'three', 'four', 'five', 'six', 'seven',\
-              'eight', 'nine']
-    data['class'] = numpy.empty(10, 'S%d' % numpy.max([len(i) for i in cnames]))
-    for i in range(len(cnames)):
-        data['class'][i] = cnames[i]
-
-    return data
diff --git a/scikits/learn/datasets/pendigits/training/pendigits_tra.py b/scikits/learn/datasets/pendigits/training/pendigits_tra.py
deleted file mode 100644
index 0b598c51b583c2045d38b776b633ef7221cb3ae1..0000000000000000000000000000000000000000
--- a/scikits/learn/datasets/pendigits/training/pendigits_tra.py
+++ /dev/null
@@ -1,6509 +0,0 @@
-training = [[47, 100, 27, 81, 57, 37, 26, 0, 0, 23, 56, 53, 100, 90, 40, 98,
-8], [0, 89, 27, 100, 42, 75, 29, 45, 15, 15, 37, 0, 69, 2, 100, 6, 2], [0, 57,
-31, 68, 72, 90, 100, 100, 76, 75, 50, 51, 28, 25, 16, 0, 1], [0, 100, 7, 92, 5,
-68, 19, 45, 86, 34, 100, 45, 74, 23, 67, 0, 4], [0, 67, 49, 83, 100, 100, 81,
-80, 60, 60, 40, 40, 33, 20, 47, 0, 1], [100, 100, 88, 99, 49, 74, 17, 47, 0,
-16, 37, 0, 73, 16, 20, 20, 6], [0, 100, 3, 72, 26, 35, 85, 35, 100, 71, 73, 97,
-65, 49, 66, 0, 4], [0, 39, 2, 62, 11, 5, 63, 0, 100, 43, 89, 99, 36, 100, 0,
-57, 0], [13, 89, 12, 50, 72, 38, 56, 0, 4, 17, 0, 61, 32, 94, 100, 100, 5],
-[57, 100, 22, 72, 0, 31, 25, 0, 75, 13, 100, 50, 75, 87, 26, 85, 0], [74, 87,
-31, 100, 0, 69, 62, 64, 100, 79, 100, 38, 84, 0, 18, 1, 9], [48, 96, 62, 65,
-88, 27, 21, 0, 21, 33, 79, 67, 100, 100, 0, 85, 8], [100, 100, 72, 99, 36, 78,
-34, 54, 79, 47, 64, 13, 19, 0, 0, 2, 5], [91, 74, 54, 100, 0, 87, 23, 59, 81,
-67, 100, 39, 79, 4, 21, 0, 9], [0, 85, 38, 100, 81, 88, 87, 50, 84, 12, 58, 0,
-53, 22, 100, 24, 7], [35, 76, 57, 100, 100, 92, 68, 66, 81, 38, 82, 9, 32, 0,
-0, 17, 3], [50, 84, 66, 100, 75, 75, 51, 51, 100, 42, 97, 13, 49, 0, 0, 7, 3],
-[99, 80, 63, 100, 25, 76, 79, 68, 100, 62, 97, 23, 54, 0, 0, 16, 9], [24, 66,
-43, 100, 59, 65, 34, 28, 0, 1, 16, 11, 58, 0, 100, 1, 2], [0, 73, 19, 99, 72,
-100, 70, 73, 32, 48, 5, 18, 46, 0, 100, 0, 2], [12, 77, 20, 62, 78, 40, 50, 0,
-1, 17, 0, 64, 23, 98, 100, 100, 5], [0, 46, 49, 64, 78, 87, 100, 100, 91, 75,
-85, 49, 75, 24, 89, 0, 1], [10, 86, 34, 66, 68, 34, 34, 0, 4, 26, 0, 69, 34,
-95, 100, 100, 5], [73, 62, 53, 100, 0, 72, 82, 39, 100, 0, 15, 14, 52, 57, 90,
-94, 8], [54, 100, 34, 75, 6, 43, 0, 11, 70, 0, 100, 28, 44, 46, 36, 21, 6],
-[11, 100, 0, 69, 15, 43, 87, 47, 100, 65, 74, 67, 71, 33, 66, 0, 4], [36, 92,
-7, 83, 0, 37, 26, 0, 77, 6, 100, 46, 84, 89, 36, 100, 0], [46, 100, 10, 83, 34,
-64, 100, 77, 71, 82, 49, 54, 22, 27, 0, 0, 4], [61, 59, 58, 100, 0, 84, 44, 42,
-80, 0, 8, 5, 33, 44, 100, 70, 8], [100, 84, 31, 100, 0, 88, 8, 70, 15, 53, 15,
-35, 0, 17, 0, 0, 1], [32, 59, 53, 100, 100, 95, 79, 46, 48, 0, 93, 19, 58, 55,
-0, 63, 8], [40, 99, 51, 66, 79, 26, 39, 0, 0, 27, 8, 77, 46, 100, 100, 94, 5],
-[0, 98, 36, 100, 80, 85, 68, 42, 56, 0, 25, 23, 50, 37, 100, 32, 7], [27, 76,
-1, 42, 16, 0, 70, 3, 100, 40, 92, 84, 44, 100, 0, 73, 0], [0, 0, 31, 15, 63,
-30, 88, 52, 100, 79, 82, 100, 56, 82, 79, 64, 9], [30, 86, 67, 100, 77, 77, 53,
-50, 78, 40, 100, 17, 56, 0, 0, 5, 3], [29, 91, 14, 57, 66, 39, 30, 0, 0, 19, 3,
-72, 39, 97, 100, 100, 5], [77, 97, 40, 100, 0, 59, 9, 29, 84, 33, 100, 64, 77,
-44, 48, 0, 4], [64, 93, 0, 67, 97, 67, 89, 100, 14, 70, 100, 68, 96, 36, 28, 0,
-9], [9, 93, 53, 100, 89, 80, 57, 52, 17, 30, 0, 5, 50, 2, 100, 0, 2], [0, 93,
-62, 100, 100, 78, 69, 43, 50, 5, 35, 0, 15, 35, 86, 37, 7], [30, 87, 16, 55,
-68, 41, 52, 0, 0, 16, 15, 63, 41, 100, 100, 98, 5], [60, 100, 20, 76, 0, 39,
-10, 1, 69, 0, 100, 33, 56, 40, 15, 10, 6], [0, 83, 29, 100, 88, 95, 64, 69, 73,
-43, 100, 13, 50, 1, 10, 0, 3], [5, 90, 46, 98, 89, 100, 100, 81, 77, 59, 62,
-34, 37, 14, 0, 0, 3], [100, 99, 67, 100, 24, 68, 0, 32, 27, 0, 99, 8, 77, 40,
-9, 55, 6], [47, 86, 73, 100, 89, 75, 68, 49, 100, 28, 82, 4, 38, 0, 0, 13, 3],
-[29, 72, 45, 100, 78, 78, 60, 41, 25, 12, 0, 4, 50, 6, 100, 0, 2], [1, 88, 0,
-54, 59, 31, 36, 0, 11, 28, 4, 68, 28, 97, 100, 100, 5], [63, 100, 40, 73, 70,
-63, 100, 77, 79, 74, 55, 48, 29, 23, 0, 0, 4], [11, 92, 56, 100, 83, 82, 52,
-59, 87, 39, 100, 14, 55, 0, 0, 0, 3], [51, 76, 68, 91, 100, 100, 83, 80, 59,
-60, 34, 40, 10, 20, 0, 0, 1], [56, 99, 18, 72, 0, 24, 36, 0, 85, 23, 100, 69,
-58, 100, 19, 74, 0], [0, 75, 47, 87, 100, 100, 91, 80, 72, 60, 53, 40, 35, 20,
-19, 0, 1], [17, 100, 0, 74, 6, 36, 77, 37, 100, 63, 73, 95, 71, 47, 75, 0, 4],
-[41, 96, 17, 76, 50, 37, 31, 0, 0, 34, 1, 86, 49, 98, 100, 100, 5], [20, 82,
-62, 100, 100, 81, 68, 54, 82, 50, 89, 19, 42, 0, 0, 13, 3], [12, 78, 40, 100,
-74, 77, 52, 41, 13, 14, 0, 17, 50, 8, 100, 0, 2], [18, 73, 0, 73, 10, 24, 54,
-0, 100, 22, 95, 71, 52, 100, 5, 84, 0], [97, 100, 41, 90, 4, 58, 0, 22, 52, 0,
-100, 22, 49, 38, 8, 13, 6], [57, 63, 100, 100, 0, 91, 36, 53, 95, 16, 2, 0, 5,
-36, 91, 67, 8], [30, 81, 87, 100, 100, 98, 37, 86, 46, 54, 99, 32, 59, 2, 0, 0,
-5], [12, 61, 0, 20, 44, 0, 92, 23, 100, 64, 70, 100, 15, 92, 0, 52, 0], [0, 84,
-50, 100, 72, 79, 37, 52, 51, 41, 100, 27, 62, 3, 3, 0, 3], [0, 100, 61, 100,
-100, 93, 63, 64, 36, 33, 14, 0, 9, 29, 47, 42, 7], [100, 79, 67, 100, 26, 76,
-41, 38, 47, 0, 0, 8, 38, 38, 96, 58, 8], [37, 91, 84, 100, 100, 96, 52, 87, 32,
-57, 74, 38, 41, 1, 0, 0, 5], [100, 100, 58, 83, 31, 55, 17, 24, 43, 0, 80, 19,
-50, 43, 0, 39, 6], [94, 79, 40, 100, 13, 65, 59, 30, 67, 0, 0, 17, 45, 52, 100,
-83, 8], [0, 82, 75, 56, 100, 12, 22, 0, 22, 41, 92, 73, 84, 100, 2, 80, 8],
-[80, 100, 36, 100, 58, 80, 65, 82, 82, 47, 100, 14, 53, 0, 0, 7, 9], [35, 76,
-0, 42, 11, 0, 65, 5, 100, 41, 97, 85, 49, 100, 9, 69, 0], [34, 100, 21, 76, 0,
-35, 43, 30, 91, 29, 100, 41, 74, 46, 67, 0, 4], [0, 75, 31, 72, 67, 84, 100,
-100, 94, 82, 80, 54, 68, 27, 56, 0, 1], [90, 71, 100, 100, 25, 85, 10, 50, 80,
-62, 99, 53, 64, 17, 0, 0, 9], [0, 97, 42, 100, 67, 71, 53, 35, 34, 0, 16, 23,
-40, 42, 100, 42, 7], [38, 94, 4, 63, 0, 20, 41, 0, 84, 19, 100, 60, 77, 98, 32,
-100, 0], [72, 100, 38, 88, 2, 57, 0, 19, 51, 0, 100, 20, 55, 34, 12, 7, 6],
-[26, 79, 69, 100, 92, 85, 56, 56, 90, 42, 100, 15, 51, 0, 0, 2, 3], [8, 77, 47,
-100, 100, 96, 71, 66, 100, 46, 99, 13, 46, 0, 0, 13, 3], [31, 73, 55, 100, 55,
-53, 33, 14, 0, 0, 30, 11, 65, 1, 100, 1, 2], [46, 100, 21, 85, 0, 60, 24, 42,
-68, 44, 100, 49, 76, 25, 58, 0, 4], [41, 69, 76, 100, 73, 81, 57, 39, 46, 0, 0,
-10, 50, 9, 100, 10, 1], [32, 100, 12, 76, 0, 48, 1, 21, 39, 0, 100, 9, 64, 21,
-18, 3, 6], [16, 90, 9, 61, 50, 35, 23, 0, 5, 35, 0, 81, 48, 97, 100, 100, 5],
-[21, 88, 0, 57, 88, 58, 88, 18, 15, 0, 8, 42, 12, 83, 100, 100, 5], [0, 100,
-54, 98, 91, 85, 71, 52, 62, 17, 74, 0, 100, 32, 42, 37, 7], [47, 93, 1, 67, 0,
-16, 53, 0, 100, 32, 95, 81, 42, 100, 7, 62, 0], [38, 51, 8, 66, 0, 19, 42, 0,
-87, 26, 100, 71, 61, 100, 16, 84, 0], [95, 92, 50, 100, 21, 77, 74, 87, 100,
-86, 69, 56, 37, 26, 0, 0, 9], [18, 88, 2, 54, 40, 25, 2, 0, 0, 30, 20, 70, 45,
-100, 100, 93, 5], [39, 100, 23, 82, 0, 52, 1, 21, 48, 0, 100, 16, 70, 42, 6,
-55, 6], [22, 100, 1, 66, 0, 33, 50, 32, 100, 36, 82, 63, 77, 30, 71, 0, 4], [3,
-96, 53, 100, 81, 68, 83, 28, 72, 0, 100, 34, 51, 41, 0, 43, 7], [0, 65, 38, 79,
-62, 100, 72, 86, 77, 65, 79, 43, 83, 21, 100, 0, 1], [19, 81, 0, 41, 12, 0, 54,
-1, 88, 29, 100, 71, 72, 100, 31, 91, 0], [0, 60, 38, 80, 80, 100, 100, 92, 80,
-69, 65, 46, 55, 23, 55, 0, 1], [40, 72, 16, 50, 96, 69, 70, 100, 0, 73, 65, 57,
-100, 47, 94, 0, 9], [100, 100, 63, 78, 28, 53, 0, 27, 4, 0, 60, 1, 78, 22, 24,
-21, 6], [33, 58, 19, 90, 78, 100, 91, 62, 51, 28, 0, 2, 37, 1, 100, 0, 2], [14,
-91, 9, 52, 28, 10, 74, 0, 100, 38, 86, 81, 43, 100, 0, 80, 0], [20, 85, 62,
-100, 71, 72, 45, 52, 98, 47, 100, 17, 53, 0, 0, 0, 3], [9, 100, 0, 66, 20, 25,
-61, 0, 100, 21, 93, 64, 54, 91, 9, 76, 0], [42, 83, 60, 53, 89, 11, 13, 0, 0,
-33, 77, 57, 100, 92, 18, 100, 8], [4, 63, 12, 15, 52, 0, 92, 15, 100, 63, 72,
-100, 28, 97, 0, 62, 0], [38, 94, 90, 100, 94, 79, 59, 57, 68, 33, 100, 12, 54,
-0, 0, 1, 3], [22, 55, 10, 60, 0, 18, 46, 0, 89, 28, 100, 70, 68, 100, 29, 69,
-0], [27, 100, 0, 58, 12, 5, 62, 0, 100, 39, 97, 91, 48, 97, 18, 53, 0], [43,
-94, 15, 66, 52, 38, 20, 0, 5, 35, 0, 83, 42, 100, 100, 98, 5], [0, 87, 37, 100,
-19, 70, 5, 42, 88, 49, 100, 58, 84, 28, 88, 0, 4], [73, 98, 35, 100, 0, 59, 0,
-13, 71, 8, 100, 45, 29, 41, 9, 0, 6], [15, 73, 0, 34, 30, 0, 81, 1, 100, 38,
-87, 78, 44, 100, 16, 68, 0], [85, 100, 30, 84, 5, 54, 0, 22, 48, 0, 100, 21,
-66, 47, 0, 37, 6], [0, 88, 24, 68, 76, 33, 43, 0, 29, 32, 84, 66, 100, 100, 8,
-89, 8], [50, 97, 72, 68, 100, 100, 42, 86, 93, 72, 89, 48, 70, 7, 0, 0, 9],
-[42, 100, 9, 79, 0, 46, 48, 31, 100, 46, 89, 52, 46, 30, 19, 0, 4], [7, 100, 0,
-56, 51, 37, 39, 0, 9, 15, 5, 62, 42, 92, 100, 96, 5], [100, 77, 92, 100, 49,
-76, 18, 48, 0, 15, 38, 0, 75, 23, 29, 27, 6], [44, 66, 67, 100, 80, 62, 47, 25,
-5, 0, 0, 3, 50, 4, 100, 7, 2], [37, 100, 48, 57, 74, 97, 27, 97, 80, 68, 100,
-26, 49, 0, 0, 22, 9], [100, 89, 40, 83, 63, 40, 84, 0, 0, 7, 53, 53, 80, 100,
-3, 78, 8], [45, 93, 0, 60, 75, 69, 89, 29, 19, 0, 15, 43, 26, 93, 100, 100, 5],
-[45, 100, 10, 67, 7, 16, 56, 0, 100, 31, 91, 79, 38, 95, 0, 61, 0], [13, 68,
-15, 30, 42, 0, 86, 19, 100, 56, 84, 90, 33, 100, 0, 73, 0], [49, 83, 8, 57, 0,
-17, 51, 0, 93, 28, 100, 70, 61, 100, 8, 86, 0], [16, 100, 0, 78, 5, 54, 41, 32,
-93, 39, 100, 48, 91, 24, 89, 0, 4], [22, 93, 0, 95, 50, 97, 100, 100, 67, 81,
-43, 56, 28, 28, 30, 0, 7], [52, 91, 72, 100, 87, 70, 57, 43, 100, 45, 90, 15,
-43, 0, 0, 12, 3], [96, 100, 52, 95, 48, 76, 96, 98, 100, 85, 71, 54, 39, 25, 0,
-0, 9], [29, 73, 56, 100, 68, 71, 45, 38, 11, 12, 0, 8, 50, 6, 100, 0, 2], [14,
-94, 4, 63, 43, 36, 36, 0, 10, 27, 0, 72, 47, 92, 100, 100, 5], [53, 87, 32, 47,
-98, 64, 69, 100, 58, 69, 100, 61, 71, 3, 0, 0, 9], [68, 100, 24, 83, 0, 41, 13,
-0, 60, 3, 99, 30, 100, 71, 55, 89, 0], [100, 98, 60, 100, 29, 73, 10, 41, 6, 6,
-46, 0, 46, 27, 0, 30, 6], [100, 70, 58, 100, 10, 75, 0, 24, 48, 0, 100, 19, 97,
-68, 45, 81, 0], [84, 100, 59, 99, 16, 72, 0, 42, 20, 12, 100, 0, 94, 22, 4, 27,
-6], [100, 100, 53, 81, 25, 54, 11, 25, 38, 0, 99, 8, 65, 29, 0, 25, 6], [0, 42,
-30, 56, 59, 72, 86, 94, 100, 100, 80, 68, 62, 35, 53, 0, 1], [67, 100, 30, 90,
-0, 57, 41, 40, 100, 53, 98, 67, 66, 34, 40, 0, 4], [73, 85, 31, 65, 0, 0, 52,
-9, 100, 57, 82, 100, 81, 78, 38, 25, 0], [28, 82, 0, 39, 30, 0, 80, 5, 100, 54,
-70, 99, 22, 100, 7, 50, 0], [86, 100, 48, 79, 13, 52, 0, 22, 45, 0, 100, 16,
-76, 40, 6, 35, 6], [40, 79, 61, 100, 78, 72, 46, 41, 0, 16, 1, 5, 61, 1, 100,
-0, 2], [100, 88, 69, 100, 20, 84, 70, 86, 93, 71, 70, 44, 38, 19, 0, 0, 9],
-[30, 98, 16, 60, 53, 28, 46, 0, 13, 29, 0, 68, 27, 95, 100, 100, 5], [2, 78,
-46, 99, 100, 100, 77, 76, 94, 38, 94, 0, 41, 3, 0, 28, 3], [0, 42, 34, 57, 64,
-79, 95, 100, 100, 85, 81, 57, 62, 28, 45, 0, 1], [19, 100, 4, 77, 0, 51, 46,
-36, 100, 47, 96, 49, 87, 23, 77, 0, 4], [3, 66, 16, 100, 27, 69, 14, 32, 0, 0,
-33, 5, 67, 10, 100, 11, 2], [47, 100, 40, 82, 18, 49, 0, 19, 53, 20, 92, 34,
-94, 35, 100, 0, 4], [29, 38, 61, 60, 92, 83, 100, 100, 73, 76, 49, 50, 25, 25,
-0, 0, 1], [0, 63, 41, 77, 79, 94, 100, 100, 85, 74, 75, 48, 71, 22, 82, 0, 1],
-[0, 52, 52, 83, 97, 100, 91, 55, 84, 10, 21, 0, 21, 7, 100, 7, 1], [65, 100,
-24, 84, 0, 48, 9, 10, 61, 0, 100, 24, 58, 47, 2, 46, 6], [88, 80, 12, 80, 100,
-100, 100, 91, 65, 68, 29, 46, 6, 23, 0, 0, 1], [13, 80, 53, 71, 100, 100, 23,
-99, 0, 71, 81, 74, 74, 40, 47, 0, 9], [0, 79, 51, 59, 100, 29, 51, 0, 22, 26,
-51, 60, 73, 94, 9, 100, 8], [72, 100, 38, 84, 13, 63, 0, 40, 40, 28, 88, 31,
-100, 22, 84, 0, 4], [0, 100, 67, 100, 86, 72, 56, 37, 34, 0, 6, 33, 32, 45,
-100, 46, 7], [37, 84, 69, 100, 96, 87, 55, 61, 88, 38, 100, 9, 51, 0, 0, 3, 3],
-[0, 100, 73, 97, 95, 80, 100, 64, 95, 48, 82, 31, 64, 15, 23, 0, 1], [0, 59,
-77, 74, 100, 100, 17, 93, 7, 71, 82, 68, 45, 35, 20, 0, 9], [2, 85, 31, 100,
-76, 74, 62, 37, 47, 0, 100, 8, 68, 30, 0, 41, 7], [13, 100, 0, 76, 28, 53, 94,
-56, 100, 76, 93, 66, 94, 33, 91, 0, 4], [21, 75, 40, 100, 85, 94, 67, 63, 100,
-43, 95, 11, 47, 0, 0, 13, 3], [48, 100, 15, 83, 0, 39, 23, 1, 71, 0, 100, 34,
-86, 77, 44, 98, 0], [24, 100, 100, 99, 93, 78, 64, 48, 39, 17, 19, 0, 0, 31,
-72, 38, 7], [45, 85, 93, 100, 100, 98, 48, 88, 7, 62, 48, 48, 48, 18, 0, 0, 5],
-[54, 93, 0, 88, 54, 46, 70, 0, 5, 9, 54, 52, 100, 96, 7, 100, 8], [46, 83, 87,
-100, 100, 79, 75, 54, 90, 36, 100, 13, 49, 0, 0, 12, 3], [84, 100, 46, 98, 13,
-60, 0, 19, 53, 0, 100, 32, 33, 36, 10, 4, 6], [26, 74, 19, 49, 64, 21, 20, 0,
-1, 25, 0, 64, 45, 87, 100, 100, 5], [39, 62, 78, 88, 79, 100, 57, 64, 38, 30,
-0, 0, 34, 4, 100, 0, 1], [14, 100, 1, 54, 51, 47, 36, 0, 0, 14, 6, 71, 42, 93,
-100, 97, 5], [0, 65, 43, 76, 93, 96, 100, 100, 71, 75, 48, 50, 26, 25, 5, 0,
-1], [0, 70, 53, 88, 64, 100, 62, 78, 70, 57, 83, 36, 100, 14, 98, 0, 1], [0,
-67, 16, 80, 64, 100, 85, 99, 85, 74, 89, 49, 95, 24, 100, 0, 1], [88, 99, 45,
-82, 78, 75, 90, 100, 100, 68, 93, 36, 59, 9, 0, 0, 9], [30, 100, 16, 84, 0, 51,
-28, 26, 80, 33, 100, 65, 79, 34, 68, 0, 4], [24, 100, 14, 55, 72, 52, 54, 0, 8,
-2, 0, 58, 35, 95, 100, 99, 5], [0, 78, 18, 96, 59, 95, 100, 100, 86, 82, 66,
-56, 52, 29, 47, 0, 7], [0, 91, 46, 100, 85, 80, 91, 40, 88, 0, 99, 22, 100, 52,
-50, 49, 7], [21, 92, 85, 100, 90, 67, 67, 34, 49, 0, 0, 26, 27, 43, 100, 42,
-7], [31, 95, 5, 61, 0, 23, 32, 0, 77, 18, 100, 51, 82, 85, 37, 100, 0], [19,
-73, 54, 91, 100, 100, 99, 78, 86, 52, 78, 26, 43, 8, 0, 0, 3], [98, 100, 52,
-77, 18, 52, 0, 25, 25, 0, 100, 5, 97, 29, 23, 22, 6], [79, 74, 21, 67, 15, 92,
-71, 100, 100, 75, 73, 45, 36, 18, 0, 0, 9], [100, 100, 59, 79, 26, 54, 2, 28,
-1, 0, 58, 0, 58, 21, 0, 19, 6], [19, 86, 35, 72, 95, 94, 0, 100, 60, 78, 100,
-52, 67, 26, 26, 0, 9], [16, 59, 0, 31, 31, 0, 78, 15, 100, 55, 87, 98, 40, 100,
-6, 67, 0], [83, 86, 44, 100, 0, 74, 58, 67, 100, 94, 89, 63, 77, 31, 75, 0, 9],
-[0, 97, 43, 100, 58, 62, 41, 17, 26, 0, 8, 36, 54, 34, 100, 33, 7], [0, 70, 63,
-80, 90, 100, 100, 89, 100, 67, 92, 44, 84, 22, 71, 0, 1], [30, 100, 4, 67, 0,
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-74, 91, 100, 100, 80, 75, 62, 49, 42, 25, 24, 0, 1], [2, 93, 0, 97, 50, 98,
-100, 100, 72, 78, 47, 53, 31, 26, 27, 0, 7], [69, 70, 61, 100, 2, 84, 23, 41,
-48, 0, 0, 23, 43, 59, 100, 84, 8], [36, 79, 61, 100, 72, 75, 55, 51, 100, 38,
-96, 10, 48, 0, 0, 2, 3], [70, 90, 27, 73, 1, 100, 57, 90, 84, 57, 100, 21, 66,
-0, 0, 8, 9], [9, 67, 32, 100, 58, 79, 43, 42, 17, 8, 0, 0, 49, 12, 100, 1, 2],
-[0, 92, 20, 100, 68, 94, 49, 46, 24, 0, 14, 16, 44, 48, 100, 56, 7], [19, 91,
-0, 52, 10, 10, 63, 0, 99, 32, 100, 75, 56, 100, 7, 80, 0], [33, 73, 66, 88,
-100, 100, 79, 80, 58, 60, 36, 41, 16, 20, 0, 0, 1], [45, 71, 63, 100, 20, 78,
-44, 39, 51, 0, 0, 11, 40, 40, 100, 52, 8], [49, 100, 25, 78, 0, 40, 10, 2, 76,
-0, 100, 30, 40, 39, 24, 11, 6], [0, 81, 30, 100, 78, 93, 62, 65, 28, 42, 7, 14,
-48, 1, 100, 0, 2], [59, 100, 10, 71, 99, 78, 31, 96, 0, 45, 41, 0, 100, 35, 23,
-61, 8], [52, 87, 100, 100, 92, 95, 44, 77, 71, 51, 94, 22, 47, 0, 0, 5, 5],
-[100, 100, 55, 78, 21, 52, 0, 22, 27, 0, 79, 14, 53, 27, 1, 10, 6], [100, 76,
-55, 100, 6, 70, 70, 68, 80, 82, 93, 38, 71, 0, 0, 12, 9], [0, 89, 44, 100, 92,
-93, 100, 61, 93, 29, 82, 0, 38, 18, 71, 32, 7], [14, 89, 52, 100, 64, 61, 38,
-21, 4, 0, 0, 39, 50, 46, 100, 44, 7], [51, 100, 14, 84, 0, 53, 60, 47, 100, 69,
-78, 61, 50, 31, 37, 0, 4], [55, 100, 32, 80, 0, 55, 61, 62, 100, 74, 52, 84,
-42, 41, 28, 0, 4], [7, 91, 6, 50, 71, 40, 74, 0, 12, 13, 0, 56, 16, 94, 100,
-100, 5], [56, 100, 19, 76, 0, 37, 13, 0, 66, 9, 100, 41, 94, 80, 44, 84, 0],
-[68, 82, 38, 65, 74, 27, 34, 0, 0, 33, 53, 66, 100, 100, 16, 95, 8], [0, 82,
-42, 100, 77, 82, 62, 41, 47, 0, 15, 26, 50, 36, 100, 30, 7], [0, 98, 35, 100,
-83, 99, 100, 92, 63, 75, 39, 51, 30, 24, 37, 0, 7], [23, 90, 0, 47, 16, 0, 74,
-12, 100, 57, 76, 100, 20, 79, 2, 33, 0], [35, 84, 63, 100, 92, 81, 65, 54, 32,
-30, 0, 6, 48, 1, 100, 0, 2], [31, 81, 58, 100, 100, 100, 81, 76, 65, 50, 78,
-22, 41, 7, 0, 0, 3], [0, 93, 33, 100, 74, 83, 84, 43, 79, 1, 59, 0, 51, 24,
-100, 29, 7], [100, 100, 53, 77, 18, 50, 0, 19, 42, 0, 97, 16, 68, 40, 11, 35,
-6], [9, 100, 0, 78, 1, 48, 67, 45, 100, 65, 88, 59, 90, 29, 97, 0, 4], [32, 68,
-0, 100, 38, 71, 100, 37, 75, 0, 13, 18, 35, 59, 90, 95, 8], [35, 90, 88, 100,
-81, 79, 44, 62, 94, 44, 100, 18, 54, 0, 0, 8, 3], [5, 62, 21, 83, 46, 100, 43,
-57, 43, 14, 0, 9, 50, 0, 100, 0, 1], [29, 83, 61, 100, 100, 97, 79, 75, 58, 49,
-61, 19, 38, 0, 0, 5, 3], [100, 100, 59, 90, 36, 62, 19, 33, 10, 3, 42, 0, 42,
-27, 0, 37, 6], [0, 88, 40, 100, 59, 69, 36, 36, 0, 11, 9, 13, 57, 15, 100, 0,
-2], [100, 79, 52, 100, 0, 78, 25, 50, 83, 68, 99, 77, 83, 38, 62, 0, 9], [28,
-74, 68, 100, 97, 87, 61, 57, 100, 38, 96, 8, 44, 0, 0, 13, 3], [0, 100, 63, 98,
-67, 66, 57, 32, 39, 0, 13, 19, 35, 36, 100, 36, 7], [75, 75, 38, 100, 12, 64,
-88, 31, 89, 0, 0, 20, 29, 62, 100, 96, 8], [15, 89, 34, 53, 50, 13, 4, 0, 0,
-43, 0, 87, 48, 98, 100, 100, 5], [100, 97, 69, 100, 34, 69, 13, 33, 31, 0, 90,
-4, 55, 24, 0, 10, 6], [16, 100, 1, 84, 0, 58, 29, 39, 74, 46, 100, 51, 88, 25,
-78, 0, 4], [98, 64, 52, 70, 12, 89, 68, 100, 100, 76, 86, 45, 48, 20, 0, 0, 9],
-[0, 56, 39, 72, 71, 93, 100, 100, 88, 75, 75, 50, 63, 25, 58, 0, 1], [55, 76,
-77, 100, 100, 79, 67, 52, 95, 42, 99, 12, 49, 0, 0, 14, 3], [42, 67, 16, 27,
-49, 0, 93, 19, 100, 66, 64, 98, 19, 100, 0, 59, 0], [58, 84, 91, 100, 100, 84,
-77, 60, 87, 35, 80, 10, 41, 1, 0, 0, 3], [22, 100, 0, 81, 40, 60, 100, 66, 91,
-99, 64, 67, 46, 34, 34, 0, 4], [30, 80, 66, 100, 88, 77, 48, 51, 71, 44, 100,
-18, 52, 0, 0, 5, 3], [11, 23, 44, 0, 87, 15, 100, 50, 83, 84, 41, 100, 0, 80,
-2, 46, 0], [0, 82, 33, 100, 61, 87, 49, 50, 24, 18, 24, 0, 68, 0, 100, 8, 2],
-[0, 90, 43, 100, 90, 99, 85, 58, 78, 11, 55, 0, 53, 25, 100, 32, 7], [88, 63,
-87, 100, 7, 94, 0, 59, 73, 76, 100, 77, 85, 39, 80, 0, 9], [26, 83, 18, 45, 40,
-0, 89, 6, 100, 54, 71, 94, 21, 100, 0, 57, 0], [0, 87, 40, 100, 100, 98, 89,
-60, 78, 21, 62, 0, 25, 31, 61, 45, 7], [39, 94, 47, 100, 47, 61, 26, 23, 3, 0,
-0, 39, 50, 50, 100, 63, 7], [0, 82, 44, 98, 100, 100, 93, 75, 53, 55, 78, 35,
-58, 13, 7, 0, 3], [100, 100, 65, 94, 34, 83, 27, 50, 67, 40, 76, 12, 40, 0, 0,
-7, 5], [20, 91, 25, 67, 54, 32, 19, 0, 0, 32, 0, 80, 49, 92, 100, 100, 5], [12,
-90, 67, 100, 71, 70, 26, 44, 71, 47, 100, 19, 50, 0, 0, 14, 3], [10, 100, 0,
-99, 51, 100, 95, 89, 100, 67, 91, 44, 76, 22, 69, 0, 7], [49, 90, 81, 100, 96,
-69, 74, 38, 24, 20, 0, 32, 58, 21, 100, 0, 2], [44, 86, 77, 100, 100, 85, 78,
-63, 63, 40, 70, 14, 39, 0, 0, 2, 3], [33, 63, 67, 82, 100, 100, 84, 85, 59, 64,
-37, 43, 16, 21, 0, 0, 1], [3, 94, 0, 100, 76, 100, 100, 92, 64, 70, 39, 46, 26,
-21, 33, 0, 7], [0, 83, 40, 100, 74, 78, 69, 39, 63, 0, 60, 7, 48, 34, 100, 34,
-7], [85, 96, 38, 77, 100, 40, 68, 0, 0, 20, 51, 59, 98, 100, 32, 86, 8], [55,
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-78, 1, 36, 30, 0, 82, 6, 100, 46, 80, 85, 28, 96, 0], [85, 100, 49, 87, 12, 57,
-0, 22, 45, 0, 100, 15, 78, 47, 18, 59, 6], [0, 95, 69, 100, 99, 71, 82, 35, 63,
-0, 40, 18, 26, 47, 100, 50, 7], [27, 100, 20, 79, 0, 54, 10, 31, 62, 35, 100,
-50, 81, 26, 77, 0, 4], [3, 95, 0, 47, 13, 2, 60, 0, 98, 28, 100, 74, 62, 100,
-18, 92, 0], [28, 63, 25, 25, 51, 0, 85, 27, 100, 69, 72, 99, 30, 100, 0, 71,
-0], [100, 100, 44, 99, 6, 73, 15, 48, 65, 60, 85, 26, 49, 0, 0, 12, 5], [0, 46,
-44, 72, 86, 100, 68, 93, 56, 64, 56, 34, 61, 5, 100, 0, 1], [0, 93, 49, 100,
-100, 95, 99, 60, 79, 25, 58, 0, 44, 36, 90, 40, 7], [100, 100, 42, 89, 26, 74,
-11, 59, 5, 45, 0, 29, 0, 14, 21, 0, 1], [51, 46, 46, 76, 72, 100, 62, 69, 51,
-37, 21, 7, 0, 0, 100, 6, 1], [100, 100, 64, 86, 28, 57, 3, 24, 29, 0, 80, 15,
-50, 34, 0, 18, 6], [50, 100, 17, 78, 0, 46, 5, 15, 54, 0, 100, 17, 68, 32, 26,
-10, 6], [23, 78, 51, 100, 100, 78, 70, 40, 40, 0, 78, 2, 37, 37, 0, 74, 8],
-[42, 100, 20, 71, 100, 84, 20, 97, 0, 48, 14, 0, 73, 24, 8, 58, 8], [100, 92,
-55, 100, 33, 70, 77, 69, 78, 66, 83, 21, 46, 0, 0, 9, 9], [85, 76, 67, 68, 16,
-78, 59, 100, 100, 85, 79, 53, 41, 26, 0, 0, 9], [78, 96, 9, 75, 100, 66, 82,
-100, 17, 54, 0, 0, 81, 18, 24, 61, 8], [0, 84, 50, 100, 100, 86, 70, 44, 49, 0,
-21, 8, 20, 28, 84, 30, 7], [51, 85, 83, 100, 100, 90, 81, 66, 73, 40, 73, 16,
-39, 2, 0, 0, 3], [58, 100, 21, 78, 0, 47, 39, 23, 87, 34, 100, 61, 69, 32, 54,
-0, 4], [41, 100, 1, 61, 0, 33, 67, 36, 100, 46, 85, 91, 64, 46, 43, 0, 4], [80,
-100, 52, 63, 7, 35, 0, 32, 67, 34, 100, 53, 77, 36, 53, 0, 4], [39, 84, 64,
-100, 83, 77, 71, 53, 100, 31, 80, 6, 31, 0, 0, 18, 3], [100, 89, 49, 73, 0, 65,
-41, 93, 94, 100, 78, 64, 45, 33, 23, 0, 9], [26, 80, 58, 100, 63, 61, 38, 26,
-0, 6, 22, 18, 61, 0, 100, 18, 2], [3, 100, 0, 95, 1, 61, 41, 46, 84, 53, 100,
-67, 84, 34, 88, 0, 4], [0, 79, 40, 100, 87, 89, 66, 60, 82, 46, 100, 19, 56, 0,
-4, 3, 3], [0, 23, 27, 45, 56, 68, 83, 94, 100, 100, 87, 66, 75, 33, 66, 0, 1],
-[32, 58, 26, 89, 73, 100, 80, 56, 42, 21, 0, 0, 50, 5, 100, 4, 2], [40, 80, 60,
-100, 100, 89, 59, 64, 60, 48, 100, 27, 60, 2, 0, 0, 3], [32, 82, 67, 100, 100,
-85, 69, 58, 70, 36, 88, 10, 44, 0, 0, 7, 3], [40, 74, 87, 93, 100, 100, 81, 73,
-79, 47, 64, 20, 15, 0, 0, 6, 1], [20, 77, 0, 44, 25, 0, 77, 9, 100, 54, 76,
-100, 26, 100, 8, 53, 0], [0, 58, 6, 67, 53, 85, 100, 100, 76, 75, 52, 51, 34,
-26, 40, 0, 1], [100, 100, 69, 83, 36, 62, 11, 38, 0, 12, 39, 0, 70, 18, 26, 26,
-6], [28, 74, 57, 100, 81, 74, 38, 47, 78, 49, 100, 18, 49, 0, 0, 12, 3], [35,
-100, 8, 73, 0, 39, 58, 24, 100, 44, 100, 67, 79, 34, 71, 0, 4], [91, 100, 56,
-91, 19, 62, 0, 30, 22, 0, 100, 5, 99, 33, 19, 44, 6], [0, 93, 64, 100, 100, 82,
-78, 51, 52, 20, 27, 0, 1, 29, 63, 32, 7], [4, 77, 42, 100, 97, 95, 77, 62, 90,
-49, 100, 15, 49, 0, 0, 12, 3], [7, 100, 0, 96, 1, 72, 7, 48, 38, 38, 66, 36,
-70, 14, 100, 0, 4], [24, 85, 14, 63, 69, 38, 60, 0, 24, 16, 0, 55, 32, 91, 100,
-100, 5], [72, 72, 51, 100, 4, 75, 44, 38, 52, 0, 0, 17, 41, 53, 100, 81, 8],
-[0, 66, 15, 99, 58, 100, 64, 66, 43, 32, 11, 5, 50, 0, 100, 5, 2], [0, 95, 49,
-100, 100, 98, 85, 63, 50, 31, 13, 0, 13, 27, 60, 29, 7], [100, 88, 77, 100, 43,
-80, 17, 54, 6, 24, 24, 0, 40, 22, 0, 26, 6], [4, 70, 0, 27, 34, 0, 70, 1, 100,
-34, 90, 86, 55, 100, 20, 83, 0], [71, 64, 100, 79, 63, 100, 0, 85, 29, 61, 100,
-66, 94, 33, 95, 0, 9], [98, 100, 40, 87, 9, 55, 0, 21, 47, 0, 100, 22, 39, 31,
-7, 4, 6], [91, 100, 42, 86, 0, 11, 52, 0, 100, 70, 39, 77, 76, 71, 21, 7, 0],
-[30, 58, 79, 91, 100, 100, 88, 60, 79, 20, 16, 0, 0, 1, 86, 2, 1], [0, 100, 63,
-100, 79, 71, 61, 36, 47, 0, 21, 5, 36, 29, 100, 31, 7], [0, 51, 20, 66, 52, 84,
-85, 100, 100, 86, 85, 57, 68, 29, 58, 0, 1], [57, 89, 0, 100, 1, 68, 43, 34,
-30, 0, 1, 31, 41, 65, 100, 86, 8], [39, 96, 57, 59, 100, 94, 34, 100, 61, 66,
-78, 66, 71, 15, 0, 0, 9], [20, 77, 61, 100, 100, 80, 48, 46, 9, 7, 68, 0, 25,
-39, 0, 82, 8], [25, 92, 71, 100, 75, 62, 57, 25, 30, 0, 0, 32, 47, 39, 100, 40,
-7], [0, 58, 36, 70, 71, 86, 100, 100, 84, 75, 69, 51, 56, 25, 46, 0, 1], [53,
-85, 95, 100, 100, 97, 58, 92, 19, 72, 38, 44, 39, 9, 0, 0, 5], [51, 100, 36,
-83, 3, 52, 0, 33, 67, 38, 100, 53, 83, 34, 70, 0, 4], [15, 100, 0, 78, 3, 46,
-66, 43, 100, 58, 95, 72, 92, 36, 90, 0, 4], [84, 90, 0, 91, 51, 56, 98, 19, 36,
-0, 43, 40, 100, 75, 62, 100, 8], [0, 17, 24, 44, 64, 73, 100, 100, 68, 84, 32,
-57, 24, 28, 16, 0, 1], [26, 100, 6, 80, 0, 48, 63, 43, 100, 69, 98, 60, 86, 27,
-83, 0, 4], [0, 52, 71, 71, 100, 100, 80, 64, 77, 26, 60, 5, 3, 3, 89, 0, 1],
-[96, 98, 44, 100, 5, 72, 0, 36, 38, 8, 100, 6, 61, 21, 11, 0, 6], [62, 100, 20,
-96, 0, 60, 9, 22, 59, 0, 100, 25, 48, 35, 5, 8, 6], [47, 85, 18, 62, 5, 20, 47,
-0, 100, 24, 99, 66, 59, 98, 0, 100, 0], [46, 89, 63, 100, 96, 78, 59, 53, 100,
-47, 100, 18, 50, 0, 0, 9, 3], [35, 96, 0, 71, 35, 36, 36, 0, 3, 16, 9, 68, 45,
-100, 100, 92, 5], [0, 96, 41, 100, 61, 68, 47, 31, 31, 0, 12, 36, 46, 48, 100,
-47, 7], [0, 81, 29, 100, 61, 87, 56, 49, 34, 17, 35, 0, 69, 2, 100, 5, 2], [0,
-91, 47, 100, 100, 81, 88, 44, 60, 10, 37, 0, 24, 32, 96, 40, 7], [22, 100, 25,
-63, 54, 26, 22, 0, 0, 37, 2, 82, 49, 96, 100, 95, 5], [21, 100, 19, 81, 11, 50,
-0, 23, 65, 30, 100, 43, 65, 30, 68, 0, 4], [0, 55, 38, 74, 83, 96, 100, 100,
-83, 75, 71, 50, 60, 24, 43, 0, 1], [8, 68, 25, 100, 56, 74, 37, 35, 0, 6, 2, 4,
-51, 0, 100, 4, 2], [75, 100, 26, 84, 0, 42, 13, 0, 69, 7, 100, 46, 84, 89, 33,
-85, 0], [0, 55, 41, 80, 62, 100, 48, 66, 35, 32, 11, 0, 7, 4, 100, 4, 1], [81,
-73, 73, 100, 0, 85, 27, 60, 100, 76, 99, 64, 94, 31, 86, 0, 9], [40, 99, 0, 74,
-1, 20, 44, 0, 88, 24, 100, 76, 60, 100, 21, 70, 0], [1, 73, 29, 100, 74, 97,
-56, 63, 21, 34, 0, 4, 50, 0, 100, 0, 2], [99, 100, 67, 85, 22, 58, 1, 27, 36,
-0, 100, 18, 77, 47, 0, 59, 6], [37, 100, 13, 73, 0, 45, 64, 40, 100, 50, 75,
-61, 58, 30, 43, 0, 4], [42, 99, 55, 61, 71, 24, 18, 0, 0, 30, 64, 61, 100, 94,
-9, 100, 8], [90, 76, 42, 69, 40, 100, 81, 90, 93, 54, 100, 16, 55, 0, 0, 10,
-9], [13, 87, 11, 100, 59, 95, 32, 65, 81, 56, 100, 29, 56, 8, 0, 0, 3], [4, 81,
-35, 100, 45, 75, 25, 56, 82, 53, 100, 25, 57, 6, 0, 0, 3], [67, 100, 19, 90, 0,
-47, 14, 4, 69, 0, 100, 38, 91, 82, 46, 99, 0], [41, 86, 80, 100, 93, 78, 50,
-58, 94, 44, 100, 14, 53, 0, 0, 4, 3], [34, 65, 42, 37, 39, 5, 0, 0, 6, 35, 27,
-67, 61, 88, 100, 100, 5], [90, 79, 30, 61, 4, 89, 55, 100, 80, 63, 100, 26, 74,
-0, 0, 8, 9], [43, 100, 30, 82, 5, 53, 0, 27, 52, 39, 100, 57, 83, 29, 72, 0,
-4], [15, 87, 55, 100, 100, 99, 84, 77, 52, 57, 63, 33, 41, 10, 0, 0, 3], [18,
-59, 9, 22, 51, 0, 96, 21, 100, 63, 72, 100, 22, 93, 0, 55, 0], [20, 77, 54,
-100, 100, 94, 81, 64, 79, 44, 94, 15, 48, 0, 0, 14, 3], [40, 93, 0, 99, 50,
-100, 100, 99, 82, 88, 64, 60, 55, 30, 55, 0, 7], [0, 74, 33, 91, 92, 100, 100,
-77, 71, 40, 52, 0, 37, 34, 69, 44, 7], [18, 90, 11, 43, 34, 0, 87, 20, 100, 67,
-57, 100, 10, 73, 0, 24, 0], [34, 85, 64, 100, 90, 82, 60, 56, 100, 38, 92, 11,
-44, 0, 0, 13, 3], [1, 85, 48, 100, 100, 100, 70, 76, 91, 51, 100, 18, 52, 3, 0,
-0, 3], [31, 70, 47, 100, 91, 75, 51, 50, 71, 48, 100, 18, 51, 0, 0, 17, 3], [0,
-62, 33, 81, 70, 99, 100, 100, 85, 75, 67, 50, 51, 25, 37, 0, 1], [0, 66, 35,
-100, 45, 92, 41, 38, 22, 1, 5, 0, 53, 3, 100, 6, 1], [46, 73, 80, 100, 70, 86,
-61, 46, 45, 8, 0, 0, 47, 4, 100, 7, 1], [57, 76, 47, 100, 89, 95, 62, 64, 71,
-49, 100, 23, 57, 1, 0, 0, 3], [93, 100, 53, 77, 25, 49, 8, 19, 44, 0, 100, 11,
-59, 18, 0, 10, 6], [10, 81, 61, 100, 100, 76, 64, 38, 35, 0, 83, 10, 51, 48, 0,
-76, 8], [42, 100, 19, 75, 1, 49, 0, 23, 54, 17, 100, 32, 84, 27, 86, 0, 4],
-[20, 70, 29, 100, 63, 82, 53, 46, 29, 14, 0, 0, 50, 3, 100, 4, 2], [0, 84, 31,
-100, 43, 60, 39, 16, 27, 0, 14, 27, 57, 30, 100, 33, 7], [81, 100, 32, 82, 6,
-55, 0, 27, 23, 0, 100, 0, 97, 25, 16, 18, 6], [23, 100, 25, 91, 0, 53, 19, 42,
-92, 62, 88, 62, 97, 23, 100, 0, 4], [0, 49, 40, 59, 72, 79, 100, 100, 85, 74,
-69, 48, 53, 21, 51, 0, 1], [41, 100, 58, 66, 100, 98, 34, 92, 68, 70, 75, 52,
-69, 1, 0, 0, 9], [24, 88, 59, 100, 100, 91, 89, 64, 61, 42, 28, 22, 0, 0, 47,
-2, 2], [93, 100, 39, 81, 10, 46, 11, 7, 71, 2, 100, 35, 37, 32, 0, 0, 6], [55,
-89, 85, 100, 100, 81, 78, 60, 69, 35, 64, 9, 33, 0, 0, 3, 3], [85, 64, 85, 100,
-39, 81, 71, 56, 98, 71, 100, 30, 64, 0, 0, 2, 9], [17, 63, 6, 20, 51, 0, 95,
-28, 100, 72, 55, 100, 0, 91, 0, 52, 0], [0, 82, 9, 59, 56, 34, 41, 0, 10, 30,
-3, 67, 42, 96, 100, 100, 5], [49, 100, 0, 70, 24, 56, 100, 65, 86, 85, 44, 77,
-21, 38, 6, 0, 4], [100, 98, 60, 100, 24, 87, 3, 58, 35, 51, 58, 26, 36, 0, 0,
-5, 5], [59, 65, 91, 100, 84, 96, 72, 50, 51, 8, 0, 0, 45, 1, 100, 0, 1], [0,
-78, 29, 100, 94, 86, 70, 48, 42, 11, 32, 0, 25, 36, 100, 40, 7]]
-
diff --git a/scikits/learn/datasets/setup.py b/scikits/learn/datasets/setup.py
index 2b3a6ac3d61d7afa26621c2ffb9688910dcb2a13..12cccc87cf35984aa70391d3a4383f64c9621f8a 100644
--- a/scikits/learn/datasets/setup.py
+++ b/scikits/learn/datasets/setup.py
@@ -10,6 +10,7 @@ def configuration(parent_package='',top_path=None):
     config.add_subpackage('nwis')
     config.add_subpackage('narr')
     config.add_subpackage('misc')
+	config.add_subpackage('samples_generator')
     config.add_data_dir('data')
     config.add_data_dir('descr')
     config.make_config_py() # installs __config__.py