From fa3c9dcffceb24682ade158a3c1fb7fdc450dde3 Mon Sep 17 00:00:00 2001
From: Gael varoquaux <gael.varoquaux@normalesup.org>
Date: Sun, 18 Dec 2011 10:47:39 +0100
Subject: [PATCH] COSMIT: prettify datasets docs
---
doc/datasets/index.rst | 16 +++++++++++++---
1 file changed, 13 insertions(+), 3 deletions(-)
diff --git a/doc/datasets/index.rst b/doc/datasets/index.rst
index 8f2a973305..cfb6538165 100644
--- a/doc/datasets/index.rst
+++ b/doc/datasets/index.rst
@@ -28,10 +28,11 @@ that comes from the 'real world'.
General dataset API
===================
+
There are three distinct kinds of dataset interfaces for different types
of datasets.
The simplest one is the interface for sample images, which is described
-below in the :ref: _Sample_images section.
+below in the :ref:`sample_images` section.
The dataset generation functions and the svmlight loader share a simplistic
interface, returning a tuple ``(X, y)`` consisting of a n_samples x n_features
@@ -71,6 +72,8 @@ These datasets are useful to quickly illustrate the behavior of the
various algorithms implemented in the scikit. They are however often too
small to be representative of real world machine learning tasks.
+.. _sample_images:
+
Sample images
=============
@@ -83,7 +86,13 @@ and pipeline on 2D data.
load_sample_images
load_sample_image
-.. note::
+.. image:: ../auto_examples/cluster/images/plot_color_quantization_1.png
+ :target: ../auto_examples/cluster/plot_color_quantization.html
+ :scale: 30
+ :align: right
+
+
+.. warning::
The default coding of images is based on the ``uint8`` dtype to
spare memory. Often machine learning algorithms work best if the
@@ -104,8 +113,9 @@ Sample generators
In addition, scikit-learn includes various random sample generators that
can be used to build artifical datasets of controled size and complexity.
-.. figure:: ../auto_examples/images/plot_random_dataset_1.png
+.. image:: ../auto_examples/images/plot_random_dataset_1.png
:target: ../auto_examples/plot_random_dataset.html
+ :scale: 50
:align: center
.. autosummary::
--
GitLab