From fe41a8bb0204c901cff776386de2ae1dc17a9d2e Mon Sep 17 00:00:00 2001
From: Andreas Mueller <t3kcit@gmail.com>
Date: Mon, 19 Dec 2016 11:41:27 -0500
Subject: [PATCH 01/97] add plotting module and "plot_heatmap" function

---
 sklearn/plot/__init__.py           |  3 ++
 sklearn/plot/_heatmap.py           | 73 ++++++++++++++++++++++++++++++
 sklearn/plot/tests/__init__.py     |  0
 sklearn/plot/tests/test_heatmap.py | 24 ++++++++++
 sklearn/setup.py                   |  2 +
 5 files changed, 102 insertions(+)
 create mode 100644 sklearn/plot/__init__.py
 create mode 100644 sklearn/plot/_heatmap.py
 create mode 100644 sklearn/plot/tests/__init__.py
 create mode 100644 sklearn/plot/tests/test_heatmap.py

diff --git a/sklearn/plot/__init__.py b/sklearn/plot/__init__.py
new file mode 100644
index 0000000000000..7cff0ad0ee943
--- /dev/null
+++ b/sklearn/plot/__init__.py
@@ -0,0 +1,3 @@
+from ._heatmap import plot_heatmap
+
+__all__ = ["plot_heatmap"]
diff --git a/sklearn/plot/_heatmap.py b/sklearn/plot/_heatmap.py
new file mode 100644
index 0000000000000..92a38d3bc8104
--- /dev/null
+++ b/sklearn/plot/_heatmap.py
@@ -0,0 +1,73 @@
+import numpy as np
+
+
+def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
+                 yticklabels=None, cmap=None, vmin=None, vmax=None, ax=None,
+                 fmt="{:.2f}"):
+    """Plot a matrix as heatmap with explicit numbers.
+
+    Parameters
+    ----------
+    values : ndarray
+        Two-dimensional array to visualize.
+
+    xlabel : string, default=""
+        Label for the x-axis.
+
+    ylabel : string, default=""
+        Label for the y-axis.
+
+    xticklabels : list of string or None, default=None
+        Tick labels for the x-axis.
+
+    yticklabels : list of string or None, default=None
+        Tick labels for the y-axis
+
+    cmap : string or colormap
+        Matpotlib colormap to use.
+
+    vmin : int, float or None
+        Minimum clipping value.
+
+    vmax : int, float or None
+        Maximum clipping value.
+
+    ax : axes object or None
+        Matplotlib axes object to plot into. If None, the current axes are
+        used.
+
+    fmt : string, default="{:.2f}"
+        Format string to convert value to text.
+    """
+    import matplotlib.pyplot as plt
+    if ax is None:
+        ax = plt.gca()
+    img = ax.pcolor(values, cmap=cmap, vmin=None, vmax=None)
+    # this will allow us to access the pixel values:
+    img.update_scalarmappable()
+    ax.set_xlabel(xlabel)
+    ax.set_ylabel(ylabel)
+    if xticklabels is None:
+        xticklabels = [""] * values.shape[1]
+    if yticklabels is None:
+        yticklabels = [""] * values.shape[0]
+
+    ax.xaxis.set_ticks_position('bottom')
+
+    # +.5 makes the ticks centered on the pixels
+    ax.set_xticks(np.arange(values.shape[1]) + .5)
+    ax.set_xticklabels(xticklabels, ha="center")
+    ax.set_yticks(np.arange(values.shape[0]) + .5)
+    ax.set_yticklabels(yticklabels, va="center")
+    ax.set_aspect(1)
+
+    for p, color, value in zip(img.get_paths(), img.get_facecolors(),
+                               img.get_array()):
+        x, y = p.vertices[:-2, :].mean(0)
+        if np.mean(color[:3]) > 0.5:
+            # pixel bright: use black for number
+            c = 'k'
+        else:
+            c = 'w'
+        ax.text(x, y, fmt.format(value), color=c, ha="center", va="center")
+    return ax
diff --git a/sklearn/plot/tests/__init__.py b/sklearn/plot/tests/__init__.py
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/sklearn/plot/tests/test_heatmap.py b/sklearn/plot/tests/test_heatmap.py
new file mode 100644
index 0000000000000..fb27bdf0ae9be
--- /dev/null
+++ b/sklearn/plot/tests/test_heatmap.py
@@ -0,0 +1,24 @@
+from sklearn.plot import plot_heatmap
+from sklearn.utils.testing import SkipTest
+import numpy as np
+
+
+def test_heatmap():
+    try:
+        import matplotlib
+    except ImportError:
+        raise SkipTest("Not testing plot_heatmap, matplotlib not installed.")
+
+    import matplotlib.pyplot as plt
+
+    with matplotlib.rc_context(rc={'backend': 'Agg', 'interactive': False}):
+        plt.figure()
+        rng = np.random.RandomState(0)
+        X = rng.normal(size=(10, 5))
+        # use mixture of default values and keyword args
+        plot_heatmap(X, ylabel="y-axis",
+                     xticklabels=["a", "b", "c", "d", "efgh"],
+                     cmap="Paired", ax=plt.gca())
+
+        plt.draw()
+        plt.close()
diff --git a/sklearn/setup.py b/sklearn/setup.py
index 8adbbd9d49132..5bae68530cedc 100644
--- a/sklearn/setup.py
+++ b/sklearn/setup.py
@@ -36,6 +36,8 @@ def configuration(parent_package='', top_path=None):
     config.add_subpackage('model_selection/tests')
     config.add_subpackage('neural_network')
     config.add_subpackage('neural_network/tests')
+    config.add_subpackage('plot')
+    config.add_subpackage('plot/tests')
     config.add_subpackage('preprocessing')
     config.add_subpackage('preprocessing/tests')
     config.add_subpackage('semi_supervised')

From 62da4fb5a465a3be276e2e2b92b75291163b5d9a Mon Sep 17 00:00:00 2001
From: Andreas Mueller <t3kcit@gmail.com>
Date: Mon, 19 Dec 2016 11:43:56 -0500
Subject: [PATCH 02/97] add plotting module to the API docs

---
 doc/modules/classes.rst | 19 +++++++++++++++++++
 1 file changed, 19 insertions(+)

diff --git a/doc/modules/classes.rst b/doc/modules/classes.rst
index 3aee8f258b9d1..a23a3de01ee42 100644
--- a/doc/modules/classes.rst
+++ b/doc/modules/classes.rst
@@ -1357,6 +1357,25 @@ Low-level methods
    utils.shuffle
 
 
+:mod:`sklearn.plot`: Plotting functions
+=======================================
+
+.. automodule:: sklearn.plot
+   :no-members:
+   :no-inherited-members:
+
+This module is experimental. Use at your own risk.
+Use of this module requires the matplotlib library.
+
+.. currentmodule:: sklearn.plot
+
+.. autosummary::
+   :toctree: generated/
+   :template: function.rst
+
+   plot_heatmap
+
+
 Recently deprecated
 ===================
 

From 23d86710ecd7ed1846e14c684352291958160d37 Mon Sep 17 00:00:00 2001
From: Andreas Mueller <t3kcit@gmail.com>
Date: Mon, 19 Dec 2016 11:50:21 -0500
Subject: [PATCH 03/97] simplify plot_confusion_matrix example

---
 .../model_selection/plot_confusion_matrix.py  | 28 ++++---------------
 1 file changed, 6 insertions(+), 22 deletions(-)

diff --git a/examples/model_selection/plot_confusion_matrix.py b/examples/model_selection/plot_confusion_matrix.py
index 4b7c360988071..5625fa6d4b59f 100644
--- a/examples/model_selection/plot_confusion_matrix.py
+++ b/examples/model_selection/plot_confusion_matrix.py
@@ -24,15 +24,13 @@
 
 """
 
-print(__doc__)
-
-import itertools
 import numpy as np
 import matplotlib.pyplot as plt
 
 from sklearn import svm, datasets
 from sklearn.model_selection import train_test_split
 from sklearn.metrics import confusion_matrix
+from sklearn.plot import plot_heatmap
 
 # import some data to play with
 iris = datasets.load_iris()
@@ -59,29 +57,15 @@ def plot_confusion_matrix(cm, classes,
     """
     if normalize:
         cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]
-        print("Normalized confusion matrix")
-    else:
-        print('Confusion matrix, without normalization')
 
+    print(title)
     print(cm)
 
-    plt.imshow(cm, interpolation='nearest', cmap=cmap)
+    fmt = '{:.2f}' if normalize else '{:d}'
+    plot_heatmap(cm, xticklabels=classes, yticklabels=classes, cmap=cmap,
+                 xlabel="Predicted label", ylabel="True label", fmt=fmt)
+
     plt.title(title)
-    plt.colorbar()
-    tick_marks = np.arange(len(classes))
-    plt.xticks(tick_marks, classes, rotation=45)
-    plt.yticks(tick_marks, classes)
-
-    fmt = '.2f' if normalize else 'd'
-    thresh = cm.max() / 2.
-    for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):
-        plt.text(j, i, format(cm[i, j], fmt),
-                 horizontalalignment="center",
-                 color="white" if cm[i, j] > thresh else "black")
-
-    plt.tight_layout()
-    plt.ylabel('True label')
-    plt.xlabel('Predicted label')
 
 # Compute confusion matrix
 cnf_matrix = confusion_matrix(y_test, y_pred)

From 67308d4c05641df118abdc31df17640b5d9ae370 Mon Sep 17 00:00:00 2001
From: Andreas Mueller <t3kcit@gmail.com>
Date: Mon, 19 Dec 2016 12:18:08 -0500
Subject: [PATCH 04/97] add normalizer support to heatmap, use heatmap when
 plotting gridsearch results

---
 examples/svm/plot_rbf_parameters.py | 26 ++++++++++++--------------
 sklearn/plot/_heatmap.py            | 18 +++++++++++++-----
 2 files changed, 25 insertions(+), 19 deletions(-)

diff --git a/examples/svm/plot_rbf_parameters.py b/examples/svm/plot_rbf_parameters.py
index acec9896169b8..89eefc2e1d33e 100644
--- a/examples/svm/plot_rbf_parameters.py
+++ b/examples/svm/plot_rbf_parameters.py
@@ -51,11 +51,11 @@
 
 Finally one can also observe that for some intermediate values of ``gamma`` we
 get equally performing models when ``C`` becomes very large: it is not
-necessary to regularize by limiting the number of support vectors. The radius of
-the RBF kernel alone acts as a good structural regularizer. In practice though
-it might still be interesting to limit the number of support vectors with a
-lower value of ``C`` so as to favor models that use less memory and that are
-faster to predict.
+necessary to regularize by limiting the number of support vectors. The radius
+of the RBF kernel alone acts as a good structural regularizer. In practice
+though it might still be interesting to limit the number of support vectors
+with a lower value of ``C`` so as to favor models that use less memory and that
+are faster to predict.
 
 We should also note that small differences in scores results from the random
 splits of the cross-validation procedure. Those spurious variations can be
@@ -65,7 +65,6 @@
 map.
 
 '''
-print(__doc__)
 
 import numpy as np
 import matplotlib.pyplot as plt
@@ -76,6 +75,9 @@
 from sklearn.datasets import load_iris
 from sklearn.model_selection import StratifiedShuffleSplit
 from sklearn.model_selection import GridSearchCV
+from sklearn.plot import plot_heatmap
+
+print(__doc__)
 
 
 # Utility function to move the midpoint of a colormap to be around
@@ -183,14 +185,10 @@ def __call__(self, value, clip=None):
 # interesting range while not brutally collapsing all the low score values to
 # the same color.
 
-plt.figure(figsize=(8, 6))
+plt.figure(figsize=(10, 10))
 plt.subplots_adjust(left=.2, right=0.95, bottom=0.15, top=0.95)
-plt.imshow(scores, interpolation='nearest', cmap=plt.cm.hot,
-           norm=MidpointNormalize(vmin=0.2, midpoint=0.92))
-plt.xlabel('gamma')
-plt.ylabel('C')
-plt.colorbar()
-plt.xticks(np.arange(len(gamma_range)), gamma_range, rotation=45)
-plt.yticks(np.arange(len(C_range)), C_range)
+plot_heatmap(scores, cmap=plt.cm.hot, xlabel="gamma", ylabel="C",
+             xticklabels=gamma_range, yticklabels=C_range,
+             norm=MidpointNormalize(vmin=0.2, midpoint=0.92))
 plt.title('Validation accuracy')
 plt.show()
diff --git a/sklearn/plot/_heatmap.py b/sklearn/plot/_heatmap.py
index 92a38d3bc8104..74aabfd82bb97 100644
--- a/sklearn/plot/_heatmap.py
+++ b/sklearn/plot/_heatmap.py
@@ -3,7 +3,7 @@
 
 def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
                  yticklabels=None, cmap=None, vmin=None, vmax=None, ax=None,
-                 fmt="{:.2f}"):
+                 fmt="{:.2f}", xtickrotation=45, norm=None):
     """Plot a matrix as heatmap with explicit numbers.
 
     Parameters
@@ -38,25 +38,33 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
 
     fmt : string, default="{:.2f}"
         Format string to convert value to text.
+
+    xtickrotation : float, default=45
+        Rotation of the xticklabels.
+
+    norm : matplotlib normalizer
+        Normalizer passed to pcolor
     """
     import matplotlib.pyplot as plt
     if ax is None:
         ax = plt.gca()
-    img = ax.pcolor(values, cmap=cmap, vmin=None, vmax=None)
+    img = ax.pcolor(values, cmap=cmap, vmin=None, vmax=None, norm=norm)
     # this will allow us to access the pixel values:
     img.update_scalarmappable()
     ax.set_xlabel(xlabel)
     ax.set_ylabel(ylabel)
+
+    ax.set_xlim(0, values.shape[1])
+    ax.set_ylim(0, values.shape[0])
+
     if xticklabels is None:
         xticklabels = [""] * values.shape[1]
     if yticklabels is None:
         yticklabels = [""] * values.shape[0]
 
-    ax.xaxis.set_ticks_position('bottom')
-
     # +.5 makes the ticks centered on the pixels
     ax.set_xticks(np.arange(values.shape[1]) + .5)
-    ax.set_xticklabels(xticklabels, ha="center")
+    ax.set_xticklabels(xticklabels, ha="center", rotation=xtickrotation)
     ax.set_yticks(np.arange(values.shape[0]) + .5)
     ax.set_yticklabels(yticklabels, va="center")
     ax.set_aspect(1)

From 40078c676538273183087843d7f827e913cbe6eb Mon Sep 17 00:00:00 2001
From: Andreas Mueller <t3kcit@gmail.com>
Date: Mon, 19 Dec 2016 14:37:42 -0500
Subject: [PATCH 05/97] add plot to __all__

---
 sklearn/__init__.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/sklearn/__init__.py b/sklearn/__init__.py
index 26c4fff59dcf3..5847865b1a0c7 100644
--- a/sklearn/__init__.py
+++ b/sklearn/__init__.py
@@ -66,7 +66,7 @@
                'mixture', 'model_selection', 'multiclass', 'multioutput',
                'naive_bayes', 'neighbors', 'neural_network', 'pipeline',
                'preprocessing', 'random_projection', 'semi_supervised',
-               'svm', 'tree', 'discriminant_analysis',
+               'svm', 'tree', 'discriminant_analysis', 'plot',
                # Non-modules:
                'clone']
 

From 5d4384380a924258d6fe3334aa351e3e82ca9a08 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Sun, 11 Jun 2017 16:34:13 -0400
Subject: [PATCH 06/97] using pcolormesh + alignment fix

---
 sklearn/plot/_heatmap.py | 8 +++++++-
 1 file changed, 7 insertions(+), 1 deletion(-)

diff --git a/sklearn/plot/_heatmap.py b/sklearn/plot/_heatmap.py
index 74aabfd82bb97..c6e11b92060e7 100644
--- a/sklearn/plot/_heatmap.py
+++ b/sklearn/plot/_heatmap.py
@@ -45,10 +45,11 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
     norm : matplotlib normalizer
         Normalizer passed to pcolor
     """
+
     import matplotlib.pyplot as plt
     if ax is None:
         ax = plt.gca()
-    img = ax.pcolor(values, cmap=cmap, vmin=None, vmax=None, norm=norm)
+    img = ax.pcolormesh(values, cmap=cmap, vmin=None, vmax=None, norm=norm)
     # this will allow us to access the pixel values:
     img.update_scalarmappable()
     ax.set_xlabel(xlabel)
@@ -72,6 +73,11 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
     for p, color, value in zip(img.get_paths(), img.get_facecolors(),
                                img.get_array()):
         x, y = p.vertices[:-2, :].mean(0)
+
+        # adjusting x and y for alignment:
+        x = x - 1./6
+        y = y + 1./6
+
         if np.mean(color[:3]) > 0.5:
             # pixel bright: use black for number
             c = 'k'

From 221d7483871edd8c4003d462d3e73def8003fda7 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 20 Jun 2017 00:19:16 -0400
Subject: [PATCH 07/97] added confusion_matrix plot file

---
 sklearn/plot/_confusion_matrix.py | 68 +++++++++++++++++++++++++++++++
 1 file changed, 68 insertions(+)
 create mode 100644 sklearn/plot/_confusion_matrix.py

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
new file mode 100644
index 0000000000000..1e77bbdc883fc
--- /dev/null
+++ b/sklearn/plot/_confusion_matrix.py
@@ -0,0 +1,68 @@
+import numpy as np
+from sklearn.plot import plot_heatmap
+
+
+def plot_confusion_matrix(values, classes, normalize=True,
+                          xlabel="Predicted Label", ylabel="True Label",
+                          title='Confusion matrix', cmap=None, vmin=None,
+                          vmax=None, ax=None, fmt="{:.2f}",
+                          xtickrotation=45, norm=None):
+    """Print and plot the confusion matrix. Normalization can be applied by
+    setting `normalize=True`.
+
+    Parameters
+    ----------
+    values : ndarray
+        Two-dimensional array to visualize.
+
+    classes : list of strings
+        The list of classes represented in the two-dimensional input array.
+
+    normalize : boolean, default=True
+        If True, the confusion matrix will be normalized by row.
+
+    xlabel : string, default=""
+        Label for the x-axis.
+
+    ylabel : string, default=""
+        Label for the y-axis.
+
+    cmap : string or colormap
+        Matpotlib colormap to use.
+
+    vmin : int, float or None
+        Minimum clipping value.
+
+    vmax : int, float or None
+        Maximum clipping value.
+
+    ax : axes object or None
+        Matplotlib axes object to plot into. If None, the current axes are
+        used.
+
+    fmt : string, default="{:.2f}"
+        Format string to convert value to text. This will be ignored if
+        normalize argument is False.
+
+    xtickrotation : float, default=45
+        Rotation of the xticklabels.
+
+    norm : matplotlib normalizer
+        Normalizer passed to pcolor
+    """
+
+    import matplotlib.pyplot as plt
+
+    if normalize:
+        values = values.astype('float') / values.sum(axis=1)[:, np.newaxis]
+
+    print(title)
+    print(values)
+
+    fmt = fmt if normalize else '{:d}'
+
+    plot_heatmap(values, xticklabels=classes, yticklabels=classes, cmap=cmap,
+                 xlabel=xlabel, ylabel=ylabel, vmin=vmin, vmax=vmax, ax=ax,
+                 fmt=fmt, xtickrotation=xtickrotation, norm=norm)
+
+    plt.title(title)

From 74143d5aa154c02ede8e69bb5b4c66dd9505f428 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 20 Jun 2017 00:19:48 -0400
Subject: [PATCH 08/97] made vmin and vmax pass through in heatplot plot
 function

---
 sklearn/plot/_heatmap.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/sklearn/plot/_heatmap.py b/sklearn/plot/_heatmap.py
index c6e11b92060e7..fb92a981ba14c 100644
--- a/sklearn/plot/_heatmap.py
+++ b/sklearn/plot/_heatmap.py
@@ -49,7 +49,7 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
     import matplotlib.pyplot as plt
     if ax is None:
         ax = plt.gca()
-    img = ax.pcolormesh(values, cmap=cmap, vmin=None, vmax=None, norm=norm)
+    img = ax.pcolormesh(values, cmap=cmap, vmin=vmin, vmax=vmax, norm=norm)
     # this will allow us to access the pixel values:
     img.update_scalarmappable()
     ax.set_xlabel(xlabel)

From 0b377e9780d1c0c8c8366e3d394404a11e952669 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 20 Jun 2017 00:40:59 -0400
Subject: [PATCH 09/97] modified documentation plot_confusion_matrix

---
 sklearn/plot/_confusion_matrix.py | 21 ++++++++++++---------
 1 file changed, 12 insertions(+), 9 deletions(-)

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index 1e77bbdc883fc..a2ae4b7a630e1 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -2,13 +2,13 @@
 from sklearn.plot import plot_heatmap
 
 
-def plot_confusion_matrix(values, classes, normalize=True,
+def plot_confusion_matrix(values, classes, normalize=False,
                           xlabel="Predicted Label", ylabel="True Label",
                           title='Confusion matrix', cmap=None, vmin=None,
                           vmax=None, ax=None, fmt="{:.2f}",
                           xtickrotation=45, norm=None):
-    """Print and plot the confusion matrix. Normalization can be applied by
-    setting `normalize=True`.
+    """Print and plot the confusion matrix as a heatmap. Normalization can be
+    applied by setting `normalize=True`.
 
     Parameters
     ----------
@@ -18,23 +18,25 @@ def plot_confusion_matrix(values, classes, normalize=True,
     classes : list of strings
         The list of classes represented in the two-dimensional input array.
 
-    normalize : boolean, default=True
+    normalize : boolean, default=False
         If True, the confusion matrix will be normalized by row.
 
-    xlabel : string, default=""
+    xlabel : string, default="Predicted Label"
         Label for the x-axis.
 
-    ylabel : string, default=""
+    ylabel : string, default="True Label"
         Label for the y-axis.
 
     cmap : string or colormap
         Matpotlib colormap to use.
 
     vmin : int, float or None
-        Minimum clipping value.
+        Minimum clipping value. This argument will be passed on to the
+        pcolormesh function from matplotlib used to generate the heatmap.
 
     vmax : int, float or None
-        Maximum clipping value.
+        Maximum clipping value. This argument will be passed on to the
+        pcolormesh function from matplotlib used to generate the heatmap.
 
     ax : axes object or None
         Matplotlib axes object to plot into. If None, the current axes are
@@ -48,7 +50,8 @@ def plot_confusion_matrix(values, classes, normalize=True,
         Rotation of the xticklabels.
 
     norm : matplotlib normalizer
-        Normalizer passed to pcolor
+        Normalizer passed to pcolormesh function from matplotlib used to
+        generate the heatmap.
     """
 
     import matplotlib.pyplot as plt

From e875d0d755e744d95accbda927ef2a2784ea53b5 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 20 Jun 2017 00:42:13 -0400
Subject: [PATCH 10/97] updated __init__.py file to include confusion matrix
 plot

---
 sklearn/plot/__init__.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/sklearn/plot/__init__.py b/sklearn/plot/__init__.py
index 7cff0ad0ee943..fec45fff52116 100644
--- a/sklearn/plot/__init__.py
+++ b/sklearn/plot/__init__.py
@@ -1,3 +1,4 @@
 from ._heatmap import plot_heatmap
+from ._confusion_matrix import plot_confusion_matrix
 
-__all__ = ["plot_heatmap"]
+__all__ = ["plot_heatmap", "plot_confusion_matrix"]

From 74bf78636808ba6250a934a5a1818f79b36588a6 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 20 Jun 2017 00:43:08 -0400
Subject: [PATCH 11/97] plot confusion matrix example updated to use new
 function

---
 .../model_selection/plot_confusion_matrix.py  | 29 ++++---------------
 1 file changed, 5 insertions(+), 24 deletions(-)

diff --git a/examples/model_selection/plot_confusion_matrix.py b/examples/model_selection/plot_confusion_matrix.py
index 5625fa6d4b59f..95df220d242a3 100644
--- a/examples/model_selection/plot_confusion_matrix.py
+++ b/examples/model_selection/plot_confusion_matrix.py
@@ -30,7 +30,7 @@
 from sklearn import svm, datasets
 from sklearn.model_selection import train_test_split
 from sklearn.metrics import confusion_matrix
-from sklearn.plot import plot_heatmap
+from sklearn.plot import plot_confusion_matrix
 
 # import some data to play with
 iris = datasets.load_iris()
@@ -46,27 +46,6 @@
 classifier = svm.SVC(kernel='linear', C=0.01)
 y_pred = classifier.fit(X_train, y_train).predict(X_test)
 
-
-def plot_confusion_matrix(cm, classes,
-                          normalize=False,
-                          title='Confusion matrix',
-                          cmap=plt.cm.Blues):
-    """
-    This function prints and plots the confusion matrix.
-    Normalization can be applied by setting `normalize=True`.
-    """
-    if normalize:
-        cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]
-
-    print(title)
-    print(cm)
-
-    fmt = '{:.2f}' if normalize else '{:d}'
-    plot_heatmap(cm, xticklabels=classes, yticklabels=classes, cmap=cmap,
-                 xlabel="Predicted label", ylabel="True label", fmt=fmt)
-
-    plt.title(title)
-
 # Compute confusion matrix
 cnf_matrix = confusion_matrix(y_test, y_pred)
 np.set_printoptions(precision=2)
@@ -74,11 +53,13 @@ def plot_confusion_matrix(cm, classes,
 # Plot non-normalized confusion matrix
 plt.figure()
 plot_confusion_matrix(cnf_matrix, classes=class_names,
-                      title='Confusion matrix, without normalization')
+                      title='Confusion matrix, without normalization',
+                      cmap=plt.cm.Blues)
 
 # Plot normalized confusion matrix
 plt.figure()
 plot_confusion_matrix(cnf_matrix, classes=class_names, normalize=True,
-                      title='Normalized confusion matrix')
+                      title='Normalized confusion matrix',
+                      cmap=plt.cm.Blues)
 
 plt.show()

From 8a1b8616470aaeed669eb423dff2fdbfdd5b59af Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 20 Jun 2017 01:49:42 -0400
Subject: [PATCH 12/97] make matrix diagonal

---
 sklearn/plot/_heatmap.py | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/sklearn/plot/_heatmap.py b/sklearn/plot/_heatmap.py
index fb92a981ba14c..cfa0645c86e18 100644
--- a/sklearn/plot/_heatmap.py
+++ b/sklearn/plot/_heatmap.py
@@ -50,6 +50,7 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
     if ax is None:
         ax = plt.gca()
     img = ax.pcolormesh(values, cmap=cmap, vmin=vmin, vmax=vmax, norm=norm)
+
     # this will allow us to access the pixel values:
     img.update_scalarmappable()
     ax.set_xlabel(xlabel)
@@ -84,4 +85,9 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
         else:
             c = 'w'
         ax.text(x, y, fmt.format(value), color=c, ha="center", va="center")
+
+    # Invert the y-axis so that the matrix looks like a diagonal matrix and
+    # not anti-diagonal matrix
+    ax.invert_yaxis()
+
     return ax

From abaaccbb5249c0094b4a6ec844a0396d72246472 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 20 Jun 2017 02:42:55 -0400
Subject: [PATCH 13/97] modify documentation

---
 sklearn/plot/_confusion_matrix.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index a2ae4b7a630e1..36579f68a1ab5 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -27,6 +27,9 @@ def plot_confusion_matrix(values, classes, normalize=False,
     ylabel : string, default="True Label"
         Label for the y-axis.
 
+    title : string, default="Confusion matrix"
+        Title for the heatmap.
+
     cmap : string or colormap
         Matpotlib colormap to use.
 

From badf3877f5114255777fe0a20d5dc481fb1584e3 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 20 Jun 2017 02:43:45 -0400
Subject: [PATCH 14/97] adding grid search results plotting function.

---
 sklearn/plot/__init__.py            |  3 +-
 sklearn/plot/_gridsearch_results.py | 79 +++++++++++++++++++++++++++++
 2 files changed, 81 insertions(+), 1 deletion(-)
 create mode 100644 sklearn/plot/_gridsearch_results.py

diff --git a/sklearn/plot/__init__.py b/sklearn/plot/__init__.py
index fec45fff52116..c63653af62156 100644
--- a/sklearn/plot/__init__.py
+++ b/sklearn/plot/__init__.py
@@ -1,4 +1,5 @@
 from ._heatmap import plot_heatmap
 from ._confusion_matrix import plot_confusion_matrix
+from ._gridsearch_results import plot_gridsearch_results
 
-__all__ = ["plot_heatmap", "plot_confusion_matrix"]
+__all__ = ["plot_heatmap", "plot_confusion_matrix", "plot_gridsearch_results"]
diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
new file mode 100644
index 0000000000000..7f671e8932977
--- /dev/null
+++ b/sklearn/plot/_gridsearch_results.py
@@ -0,0 +1,79 @@
+import numpy as np
+from sklearn.plot import plot_heatmap
+
+
+def plot_gridsearch_results(cv_results, param_grid, metric='mean_test_score',
+                            xlabel=None, ylabel=None,
+                            title='Grid Search Results', cmap=None,
+                            vmin=None, vmax=None, ax=None, fmt="{:.2f}",
+                            xtickrotation=45, norm=None):
+    """Print and plot the confusion matrix as a heatmap. Normalization can be
+    applied by setting `normalize=True`.
+
+    Parameters
+    ----------
+    cv_results : dict of numpy (masked) ndarrays
+        The cv_results_ attribute of the GridSearchCV object.
+
+    param_grid : dict
+        A dictionary with keys as the two parameters searched and values
+        as a list of their respective values searched.
+
+    xlabel : string, default=None
+        Label for the x-axis. If None, the first key of the param_grid will
+        be used as the xlabel.
+
+    ylabel : string, default=None
+        Label for the y-axis. If None, the second key of the param_grid will
+        be used as the ylabel.
+
+    metric : string, default="mean_test_score"
+        The metric from the GridSearchCV results to display.
+
+    title : string, default="Grid Search Results"
+        Title for the heatmap.
+
+    cmap : string or colormap
+        Matpotlib colormap to use.
+
+    vmin : int, float or None
+        Minimum clipping value. This argument will be passed on to the
+        pcolormesh function from matplotlib used to generate the heatmap.
+
+    vmax : int, float or None
+        Maximum clipping value. This argument will be passed on to the
+        pcolormesh function from matplotlib used to generate the heatmap.
+
+    ax : axes object or None
+        Matplotlib axes object to plot into. If None, the current axes are
+        used.
+
+    fmt : string, default="{:.2f}"
+        Format string to convert value to text.
+
+    xtickrotation : float, default=45
+        Rotation of the xticklabels.
+
+    norm : matplotlib normalizer
+        Normalizer passed to pcolormesh function from matplotlib used to
+        generate the heatmap.
+    """
+
+    import matplotlib.pyplot as plt
+
+    parameter1, parameter2 = param_grid.keys()
+    parameter1_values = param_grid[parameter1]
+    parameter2_values = param_grid[parameter2]
+
+    scores = cv_results[metric].reshape(len(parameter1_values),
+                                        len(parameter2_values))
+
+    xlabel = parameter1 if xlabel is None else xlabel
+    ylabel = parameter2 if ylabel is None else ylabel
+
+    plot_heatmap(scores, cmap=plt.cm.hot, xlabel=xlabel, ylabel=ylabel,
+                 xticklabels=parameter1_values, yticklabels=parameter2_values,
+                 ax=ax, norm=norm)
+
+    plt.title(title)
+    plt.show()

From 46c42532e48360fc6639b9f1ff0c12fdf3f51d47 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 20 Jun 2017 02:44:33 -0400
Subject: [PATCH 15/97] modified examples/svm/plot_rbf_parameters.py with new
 function

---
 examples/svm/plot_rbf_parameters.py | 12 ++++--------
 1 file changed, 4 insertions(+), 8 deletions(-)

diff --git a/examples/svm/plot_rbf_parameters.py b/examples/svm/plot_rbf_parameters.py
index 89eefc2e1d33e..e2768af7a036a 100644
--- a/examples/svm/plot_rbf_parameters.py
+++ b/examples/svm/plot_rbf_parameters.py
@@ -75,7 +75,7 @@
 from sklearn.datasets import load_iris
 from sklearn.model_selection import StratifiedShuffleSplit
 from sklearn.model_selection import GridSearchCV
-from sklearn.plot import plot_heatmap
+from sklearn.plot import plot_gridsearch_results
 
 print(__doc__)
 
@@ -173,9 +173,6 @@ def __call__(self, value, clip=None):
     plt.yticks(())
     plt.axis('tight')
 
-scores = grid.cv_results_['mean_test_score'].reshape(len(C_range),
-                                                     len(gamma_range))
-
 # Draw heatmap of the validation accuracy as a function of gamma and C
 #
 # The score are encoded as colors with the hot colormap which varies from dark
@@ -187,8 +184,7 @@ def __call__(self, value, clip=None):
 
 plt.figure(figsize=(10, 10))
 plt.subplots_adjust(left=.2, right=0.95, bottom=0.15, top=0.95)
-plot_heatmap(scores, cmap=plt.cm.hot, xlabel="gamma", ylabel="C",
-             xticklabels=gamma_range, yticklabels=C_range,
-             norm=MidpointNormalize(vmin=0.2, midpoint=0.92))
-plt.title('Validation accuracy')
+plot_gridsearch_results(grid.cv_results_, param_grid=param_grid,
+                        title="Validation accuracy", cmap=plt.cm.hot,
+                        norm=MidpointNormalize(vmin=0.2, midpoint=0.92))
 plt.show()

From 8f4e5f144460172cd500fbc4088801dfb4b95a79 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 20 Jun 2017 17:50:21 -0400
Subject: [PATCH 16/97] removed printing confusion matrix

---
 sklearn/plot/_confusion_matrix.py | 5 +----
 1 file changed, 1 insertion(+), 4 deletions(-)

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index 36579f68a1ab5..183fe0a45b033 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -7,7 +7,7 @@ def plot_confusion_matrix(values, classes, normalize=False,
                           title='Confusion matrix', cmap=None, vmin=None,
                           vmax=None, ax=None, fmt="{:.2f}",
                           xtickrotation=45, norm=None):
-    """Print and plot the confusion matrix as a heatmap. Normalization can be
+    """Plot the confusion matrix as a heatmap. Normalization can be
     applied by setting `normalize=True`.
 
     Parameters
@@ -62,9 +62,6 @@ def plot_confusion_matrix(values, classes, normalize=False,
     if normalize:
         values = values.astype('float') / values.sum(axis=1)[:, np.newaxis]
 
-    print(title)
-    print(values)
-
     fmt = fmt if normalize else '{:d}'
 
     plot_heatmap(values, xticklabels=classes, yticklabels=classes, cmap=cmap,

From d6940f51aa67c46963b28ce94668c81d5c92991e Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 20 Jun 2017 18:01:50 -0400
Subject: [PATCH 17/97] remove param_grid argument

---
 sklearn/plot/_gridsearch_results.py | 39 ++++++++++++++++-------------
 1 file changed, 22 insertions(+), 17 deletions(-)

diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index 7f671e8932977..fd3919436eaa4 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -2,7 +2,7 @@
 from sklearn.plot import plot_heatmap
 
 
-def plot_gridsearch_results(cv_results, param_grid, metric='mean_test_score',
+def plot_gridsearch_results(cv_results, metric='mean_test_score',
                             xlabel=None, ylabel=None,
                             title='Grid Search Results', cmap=None,
                             vmin=None, vmax=None, ax=None, fmt="{:.2f}",
@@ -15,10 +15,6 @@ def plot_gridsearch_results(cv_results, param_grid, metric='mean_test_score',
     cv_results : dict of numpy (masked) ndarrays
         The cv_results_ attribute of the GridSearchCV object.
 
-    param_grid : dict
-        A dictionary with keys as the two parameters searched and values
-        as a list of their respective values searched.
-
     xlabel : string, default=None
         Label for the x-axis. If None, the first key of the param_grid will
         be used as the xlabel.
@@ -61,19 +57,28 @@ def plot_gridsearch_results(cv_results, param_grid, metric='mean_test_score',
 
     import matplotlib.pyplot as plt
 
-    parameter1, parameter2 = param_grid.keys()
-    parameter1_values = param_grid[parameter1]
-    parameter2_values = param_grid[parameter2]
+    params = sorted(cv_results['params'][0].keys())
+
+    if len(params) == 1:
+        # plot a line chart
+        pass
+    elif len(params) == 2:
+        parameter1_values = np.unique(cv_results['param_%s' % params[0]])
+        parameter2_values = np.unique(cv_results['param_%s' % params[1]])
 
-    scores = cv_results[metric].reshape(len(parameter1_values),
-                                        len(parameter2_values))
+        scores = cv_results[metric].reshape(len(parameter1_values),
+                                            len(parameter2_values))
 
-    xlabel = parameter1 if xlabel is None else xlabel
-    ylabel = parameter2 if ylabel is None else ylabel
+        xlabel = params[0] if xlabel is None else xlabel
+        ylabel = params[1] if ylabel is None else ylabel
 
-    plot_heatmap(scores, cmap=plt.cm.hot, xlabel=xlabel, ylabel=ylabel,
-                 xticklabels=parameter1_values, yticklabels=parameter2_values,
-                 ax=ax, norm=norm)
+        plot_heatmap(scores, cmap=plt.cm.hot, xlabel=xlabel, ylabel=ylabel,
+                     xticklabels=parameter1_values,
+                     yticklabels=parameter2_values,
+                     ax=ax, norm=norm)
 
-    plt.title(title)
-    plt.show()
+        plt.title(title)
+        plt.show()
+    else:
+        # print error statement
+        pass

From 18ac9c71ee9c6fc454f0bb3de0d795ed89cf4948 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Wed, 21 Jun 2017 11:12:36 -0400
Subject: [PATCH 18/97] adding cases for nparams 1,2, more

---
 sklearn/plot/_gridsearch_results.py | 42 ++++++++++++++++++++++++-----
 1 file changed, 36 insertions(+), 6 deletions(-)

diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index fd3919436eaa4..68ca542a67728 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -24,7 +24,8 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
         be used as the ylabel.
 
     metric : string, default="mean_test_score"
-        The metric from the GridSearchCV results to display.
+        The metric from the GridSearchCV results to display. This is ignored
+        if only 1 parameter is used in grid search.
 
     title : string, default="Grid Search Results"
         Title for the heatmap.
@@ -58,11 +59,38 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
     import matplotlib.pyplot as plt
 
     params = sorted(cv_results['params'][0].keys())
+    nparams = len(params)
+
+    if nparams == 1:
+        param = params[0]
+        param_range = sorted(cv_results['param_%s' % param])
+        train_scores_mean = cv_results['mean_train_score']
+        train_scores_std = cv_results['mean_train_std']
+        test_scores_mean = cv_results['mean_test_score']
+        test_scores_std = cv_results['mean_test_std']
+
+        lw = 2
+        plt.semilogx(param_range, train_scores_mean,
+                     label="Training score",
+                     color="darkorange", lw=lw)
+        plt.fill_between(param_range, train_scores_mean - train_scores_std,
+                         train_scores_mean + train_scores_std, alpha=0.2,
+                         color="darkorange", lw=lw)
+
+        plt.semilogx(param_range, test_scores_mean,
+                     label="Cross-validation score",
+                     color="navy", lw=lw)
+        plt.fill_between(param_range, test_scores_mean - test_scores_std,
+                         test_scores_mean + test_scores_std, alpha=0.2,
+                         color="navy", lw=lw)
 
-    if len(params) == 1:
-        # plot a line chart
-        pass
-    elif len(params) == 2:
+        plt.title(title)
+        plt.xlabel(param)
+        ylabel = "Score" if ylabel is None else ylabel
+        plt.ylabel(ylabel)
+        plt.show()
+
+    elif nparams == 2:
         parameter1_values = np.unique(cv_results['param_%s' % params[0]])
         parameter2_values = np.unique(cv_results['param_%s' % params[1]])
 
@@ -79,6 +107,8 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
 
         plt.title(title)
         plt.show()
+
     else:
-        # print error statement
+        raise ValueError('Plot functions supports upto 2 parameters in grid'
+                         'search, got {0}.'.format(nparams))
         pass

From 343db9d0815a6175f15670ff450ea00fba48976a Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Wed, 21 Jun 2017 12:00:56 -0400
Subject: [PATCH 19/97] minor fixes

---
 sklearn/plot/_gridsearch_results.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index 68ca542a67728..2719e38c3a52b 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -65,9 +65,9 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
         param = params[0]
         param_range = sorted(cv_results['param_%s' % param])
         train_scores_mean = cv_results['mean_train_score']
-        train_scores_std = cv_results['mean_train_std']
+        train_scores_std = cv_results['std_train_score']
         test_scores_mean = cv_results['mean_test_score']
-        test_scores_std = cv_results['mean_test_std']
+        test_scores_std = cv_results['std_test_score']
 
         lw = 2
         plt.semilogx(param_range, train_scores_mean,
@@ -86,6 +86,7 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
 
         plt.title(title)
         plt.xlabel(param)
+        plt.legend()
         ylabel = "Score" if ylabel is None else ylabel
         plt.ylabel(ylabel)
         plt.show()

From d82c4c26f5b2a1e7bfcaf00c7133d94dc0579954 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Wed, 21 Jun 2017 15:38:04 -0400
Subject: [PATCH 20/97] fixed typo

---
 sklearn/plot/_gridsearch_results.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index 2719e38c3a52b..55ce25bd2f425 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -110,6 +110,6 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
         plt.show()
 
     else:
-        raise ValueError('Plot functions supports upto 2 parameters in grid'
+        raise ValueError('Plot function supports upto 2 parameters in grid'
                          'search, got {0}.'.format(nparams))
         pass

From a3ccae9e0fac5e9599715fe186e69b7804f7bff5 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Wed, 21 Jun 2017 15:38:38 -0400
Subject: [PATCH 21/97] adding tests for confusion matrix and grid search plots

---
 sklearn/plot/tests/test_heatmap.py | 85 ++++++++++++++++++++++++++++++
 1 file changed, 85 insertions(+)

diff --git a/sklearn/plot/tests/test_heatmap.py b/sklearn/plot/tests/test_heatmap.py
index fb27bdf0ae9be..668f82b2b138f 100644
--- a/sklearn/plot/tests/test_heatmap.py
+++ b/sklearn/plot/tests/test_heatmap.py
@@ -1,5 +1,11 @@
 from sklearn.plot import plot_heatmap
+from sklearn.plot import plot_confusion_matrix
+from sklearn.plot import plot_gridsearch_results
+from sklearn.datasets import load_iris
+from sklearn.model_selection import GridSearchCV
+from sklearn.svm import SVC
 from sklearn.utils.testing import SkipTest
+from sklearn.utils.testing import assert_raises
 import numpy as np
 
 
@@ -22,3 +28,82 @@ def test_heatmap():
 
         plt.draw()
         plt.close()
+
+
+def test_confusion_matrix():
+    try:
+        import matplotlib
+    except ImportError:
+        raise SkipTest("Not testing plot_heatmap, matplotlib not installed.")
+
+    import matplotlib.pyplot as plt
+
+    with matplotlib.rc_context(rc={'backend': 'Agg', 'interactive': False}):
+        plt.figure()
+        cnf_matrix = np.random.randomint(1, 10, size=(2, 2))
+
+        # use mixture of default values and keyword args
+        plot_confusion_matrix(cnf_matrix, classes=["dummay1", "dummy2"],
+                              cmap="Paired", ax=plt.gca())
+
+        plt.draw()
+        plt.close()
+
+
+def test_gridsearch_results():
+    try:
+        import matplotlib
+    except ImportError:
+        raise SkipTest("Not testing plot_heatmap, matplotlib not installed.")
+
+    import matplotlib.pyplot as plt
+
+    iris = load_iris()
+    X = iris.data
+    y = iris.target
+
+    # We only keep the first two features in X and sub-sample the dataset to
+    # keep only 2 classes and make it a binary classification problem.
+
+    X_2d = X[:, :2]
+    X_2d = X_2d[y > 0]
+    y_2d = y[y > 0]
+    y_2d -= 1
+
+    # Define parameters:
+    C_range = np.logspace(-2, 10, 2)
+    gamma_range = np.logspace(-9, 3, 2)
+    tol_range = [1e-3, 1e-4]
+
+    # Test 1D case:
+    param_grid = dict(gamma=gamma_range)
+    grid = GridSearchCV(SVC(), param_grid=param_grid, cv=3)
+    grid.fit(X, y)
+
+    with matplotlib.rc_context(rc={'backend': 'Agg', 'interactive': False}):
+        plt.figure()
+        plot_gridsearch_results(grid.cv_results_)
+        plt.draw()
+        plt.close()
+
+    # Test 2D case:
+    param_grid = dict(gamma=gamma_range, C=C_range)
+    grid = GridSearchCV(SVC(), param_grid=param_grid, cv=3)
+    grid.fit(X, y)
+
+    with matplotlib.rc_context(rc={'backend': 'Agg', 'interactive': False}):
+        plt.figure()
+        plot_gridsearch_results(grid.cv_results_)
+        plt.draw()
+        plt.close()
+
+    # Test 3D case:
+    param_grid = dict(gamma=gamma_range, C=C_range, tol=tol_range)
+    grid = GridSearchCV(SVC(), param_grid=param_grid, cv=3)
+    grid.fit(X, y)
+
+    with matplotlib.rc_context(rc={'backend': 'Agg', 'interactive': False}):
+        plt.figure()
+        assert_raises(ValueError, plot_gridsearch_results, grid.cv_results_)
+        plt.draw()
+        plt.close()

From d27c8592975c8b3fd443a651642b416b394b0989 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Wed, 21 Jun 2017 17:26:01 -0400
Subject: [PATCH 22/97] adding test case for normalized

---
 sklearn/plot/tests/test_heatmap.py | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

diff --git a/sklearn/plot/tests/test_heatmap.py b/sklearn/plot/tests/test_heatmap.py
index 668f82b2b138f..5a199e23e24d7 100644
--- a/sklearn/plot/tests/test_heatmap.py
+++ b/sklearn/plot/tests/test_heatmap.py
@@ -42,10 +42,15 @@ def test_confusion_matrix():
         plt.figure()
         cnf_matrix = np.random.randomint(1, 10, size=(2, 2))
 
-        # use mixture of default values and keyword args
+        # plot un-normalized matrix
         plot_confusion_matrix(cnf_matrix, classes=["dummay1", "dummy2"],
                               cmap="Paired", ax=plt.gca())
 
+        # plot normalized matrix
+        plot_confusion_matrix(cnf_matrix, normalize=True,
+                              classes=["dummay1", "dummy2"],
+                              cmap="Paired", ax=plt.gca())
+
         plt.draw()
         plt.close()
 

From b5e582315dde2c51dbb9d5e31dff0a72f8ce7b8b Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Wed, 21 Jun 2017 17:28:41 -0400
Subject: [PATCH 23/97] updated doc files

---
 doc/modules/classes.rst | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/doc/modules/classes.rst b/doc/modules/classes.rst
index a23a3de01ee42..cc05404a1e280 100644
--- a/doc/modules/classes.rst
+++ b/doc/modules/classes.rst
@@ -1365,7 +1365,8 @@ Low-level methods
    :no-inherited-members:
 
 This module is experimental. Use at your own risk.
-Use of this module requires the matplotlib library.
+Use of this module requires the matplotlib library,
+version 1.5 or later (preferably 2.0).
 
 .. currentmodule:: sklearn.plot
 
@@ -1374,6 +1375,8 @@ Use of this module requires the matplotlib library.
    :template: function.rst
 
    plot_heatmap
+   plot_confusion_matrix
+   plot_gridsearch_results
 
 
 Recently deprecated

From d5c64c5376d1b2efb66d4ff78679a420c6db8877 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Thu, 29 Jun 2017 14:30:46 -0400
Subject: [PATCH 24/97] modifying doc

---
 doc/modules/classes.rst | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/doc/modules/classes.rst b/doc/modules/classes.rst
index 9aab9300a78fe..72a4f9d01d2a5 100644
--- a/doc/modules/classes.rst
+++ b/doc/modules/classes.rst
@@ -1396,7 +1396,7 @@ Low-level methods
 
 This module is experimental. Use at your own risk.
 Use of this module requires the matplotlib library,
-version 1.5 or later (preferably 2.0).
+version 1.5 or later.
 
 .. currentmodule:: sklearn.plot
 

From 35d60fada9546517c1e35434b307bb9c89bcfc00 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 4 Jul 2017 11:36:32 -0400
Subject: [PATCH 25/97] doc fix

---
 sklearn/plot/_gridsearch_results.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index 55ce25bd2f425..587ff2ae81106 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -7,8 +7,9 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
                             title='Grid Search Results', cmap=None,
                             vmin=None, vmax=None, ax=None, fmt="{:.2f}",
                             xtickrotation=45, norm=None):
-    """Print and plot the confusion matrix as a heatmap. Normalization can be
-    applied by setting `normalize=True`.
+    """Plot the grid search results as a line chart for 1D search and heatmap
+    for a 2D search. This function will not work if grid-search has more than
+    2 parameters in the search space.
 
     Parameters
     ----------

From 808c9e2af561eef6b10b91c9282a153dc3b3d51b Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 4 Jul 2017 11:37:35 -0400
Subject: [PATCH 26/97] spell fix, make_blobs instead of iris, split checks
 into 3 functions

---
 sklearn/plot/tests/test_heatmap.py | 60 ++++++++++++++++++++----------
 1 file changed, 41 insertions(+), 19 deletions(-)

diff --git a/sklearn/plot/tests/test_heatmap.py b/sklearn/plot/tests/test_heatmap.py
index 5a199e23e24d7..7ff7b85ca827c 100644
--- a/sklearn/plot/tests/test_heatmap.py
+++ b/sklearn/plot/tests/test_heatmap.py
@@ -1,7 +1,7 @@
 from sklearn.plot import plot_heatmap
 from sklearn.plot import plot_confusion_matrix
 from sklearn.plot import plot_gridsearch_results
-from sklearn.datasets import load_iris
+from sklearn.datasets import make_blobs
 from sklearn.model_selection import GridSearchCV
 from sklearn.svm import SVC
 from sklearn.utils.testing import SkipTest
@@ -43,7 +43,7 @@ def test_confusion_matrix():
         cnf_matrix = np.random.randomint(1, 10, size=(2, 2))
 
         # plot un-normalized matrix
-        plot_confusion_matrix(cnf_matrix, classes=["dummay1", "dummy2"],
+        plot_confusion_matrix(cnf_matrix, classes=["dummy1", "dummy2"],
                               cmap="Paired", ax=plt.gca())
 
         # plot normalized matrix
@@ -55,7 +55,7 @@ def test_confusion_matrix():
         plt.close()
 
 
-def test_gridsearch_results():
+def test_gridsearch_results_1d():
     try:
         import matplotlib
     except ImportError:
@@ -63,25 +63,14 @@ def test_gridsearch_results():
 
     import matplotlib.pyplot as plt
 
-    iris = load_iris()
-    X = iris.data
-    y = iris.target
-
-    # We only keep the first two features in X and sub-sample the dataset to
-    # keep only 2 classes and make it a binary classification problem.
-
-    X_2d = X[:, :2]
-    X_2d = X_2d[y > 0]
-    y_2d = y[y > 0]
-    y_2d -= 1
+    X, y = make_blobs(n_samples=20, centers=2, n_features=3,
+                      random_state=0)
 
     # Define parameters:
     C_range = np.logspace(-2, 10, 2)
-    gamma_range = np.logspace(-9, 3, 2)
-    tol_range = [1e-3, 1e-4]
 
     # Test 1D case:
-    param_grid = dict(gamma=gamma_range)
+    param_grid = dict(C=C_range)
     grid = GridSearchCV(SVC(), param_grid=param_grid, cv=3)
     grid.fit(X, y)
 
@@ -91,7 +80,23 @@ def test_gridsearch_results():
         plt.draw()
         plt.close()
 
-    # Test 2D case:
+
+def test_gridsearch_results_2d():
+    try:
+        import matplotlib
+    except ImportError:
+        raise SkipTest("Not testing plot_heatmap, matplotlib not installed.")
+
+    import matplotlib.pyplot as plt
+
+    X, y = make_blobs(n_samples=20, centers=2, n_features=3,
+                      random_state=0)
+
+    # Define parameters:
+    C_range = np.logspace(-2, 10, 2)
+    gamma_range = np.logspace(-9, 3, 2)
+
+    # Test 1D case:
     param_grid = dict(gamma=gamma_range, C=C_range)
     grid = GridSearchCV(SVC(), param_grid=param_grid, cv=3)
     grid.fit(X, y)
@@ -102,7 +107,24 @@ def test_gridsearch_results():
         plt.draw()
         plt.close()
 
-    # Test 3D case:
+
+def test_gridsearch_results_3d():
+    try:
+        import matplotlib
+    except ImportError:
+        raise SkipTest("Not testing plot_heatmap, matplotlib not installed.")
+
+    import matplotlib.pyplot as plt
+
+    X, y = make_blobs(n_samples=20, centers=2, n_features=3,
+                      random_state=0)
+
+    # Define parameters:
+    C_range = np.logspace(-2, 10, 2)
+    gamma_range = np.logspace(-9, 3, 2)
+    tol_range = [1e-3, 1e-4]
+
+    # Test 1D case:
     param_grid = dict(gamma=gamma_range, C=C_range, tol=tol_range)
     grid = GridSearchCV(SVC(), param_grid=param_grid, cv=3)
     grid.fit(X, y)

From 346cb2444147d15ad9a64b85100b3ad32b2b2019 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 4 Jul 2017 13:43:08 -0400
Subject: [PATCH 27/97] fixed parameter in examples

---
 examples/svm/plot_rbf_parameters.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/examples/svm/plot_rbf_parameters.py b/examples/svm/plot_rbf_parameters.py
index 2760c2259a112..b5e923b7ee937 100644
--- a/examples/svm/plot_rbf_parameters.py
+++ b/examples/svm/plot_rbf_parameters.py
@@ -185,7 +185,7 @@ def __call__(self, value, clip=None):
 
 plt.figure(figsize=(10, 10))
 plt.subplots_adjust(left=.2, right=0.95, bottom=0.15, top=0.95)
-plot_gridsearch_results(grid.cv_results_, param_grid=param_grid,
-                        title="Validation accuracy", cmap=plt.cm.hot,
+plot_gridsearch_results(grid.cv_results_, title="Validation accuracy",
+                        cmap=plt.cm.hot,
                         norm=MidpointNormalize(vmin=0.2, midpoint=0.92))
 plt.show()

From 3bda05ae8fceb5308de6a288ab7e22bde1f04ece Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 4 Jul 2017 16:36:36 -0400
Subject: [PATCH 28/97] modified travis files

---
 .travis.yml                   | 4 ++--
 build_tools/travis/install.sh | 2 ++
 2 files changed, 4 insertions(+), 2 deletions(-)

diff --git a/.travis.yml b/.travis.yml
index 6892cdbd53e51..71b414bd31b64 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -39,12 +39,12 @@ matrix:
     # It also runs tests requiring Pandas.
     - env: DISTRIB="conda" PYTHON_VERSION="3.6.1" INSTALL_MKL="true"
            NUMPY_VERSION="1.12.1" SCIPY_VERSION="0.19.0" PANDAS_VERSION="0.20.1"
-           CYTHON_VERSION="0.25.2" COVERAGE=true
+           CYTHON_VERSION="0.25.2" MATPLOTLIB_VERSION="2.0.2" COVERAGE=true
     # This environment use pytest to run the tests. It uses the newest
     # supported Anaconda release (4.4.0). It also runs tests requiring Pandas.
     - env: USE_PYTEST="true" DISTRIB="conda" PYTHON_VERSION="3.6.1"
            INSTALL_MKL="true" NUMPY_VERSION="1.12.1" SCIPY_VERSION="0.19.0"
-           PANDAS_VERSION="0.20.1" CYTHON_VERSION="0.25.2"
+           PANDAS_VERSION="0.20.1" CYTHON_VERSION="0.25.2"  MATPLOTLIB_VERSION="2.0.2"
     # flake8 linting on diff wrt common ancestor with upstream/master
     - env: RUN_FLAKE8="true" SKIP_TESTS="true"
            DISTRIB="conda" PYTHON_VERSION="3.5" INSTALL_MKL="true"
diff --git a/build_tools/travis/install.sh b/build_tools/travis/install.sh
index 257cfb17f3938..ab0bd356be3b1 100755
--- a/build_tools/travis/install.sh
+++ b/build_tools/travis/install.sh
@@ -42,12 +42,14 @@ if [[ "$DISTRIB" == "conda" ]]; then
     if [[ "$INSTALL_MKL" == "true" ]]; then
         conda create -n testenv --yes python=$PYTHON_VERSION pip nose pytest \
             numpy=$NUMPY_VERSION scipy=$SCIPY_VERSION \
+            matplotlib=$MATPLOTLIB_VERSION \
             mkl cython=$CYTHON_VERSION \
             ${PANDAS_VERSION+pandas=$PANDAS_VERSION}
             
     else
         conda create -n testenv --yes python=$PYTHON_VERSION pip nose pytest \
             numpy=$NUMPY_VERSION scipy=$SCIPY_VERSION \
+            matplotlib=$MATPLOTLIB_VERSION \
             nomkl cython=$CYTHON_VERSION \
             ${PANDAS_VERSION+pandas=$PANDAS_VERSION}
     fi

From b9e5800f4b264e867ba32a87dec02db5194234e6 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 4 Jul 2017 18:02:38 -0400
Subject: [PATCH 29/97] explicitly imported random module functions

---
 sklearn/plot/tests/test_heatmap.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/sklearn/plot/tests/test_heatmap.py b/sklearn/plot/tests/test_heatmap.py
index 7ff7b85ca827c..b110375adfc1b 100644
--- a/sklearn/plot/tests/test_heatmap.py
+++ b/sklearn/plot/tests/test_heatmap.py
@@ -7,6 +7,8 @@
 from sklearn.utils.testing import SkipTest
 from sklearn.utils.testing import assert_raises
 import numpy as np
+from numpy.random import (RandomState,
+                          randomint)
 
 
 def test_heatmap():
@@ -19,7 +21,7 @@ def test_heatmap():
 
     with matplotlib.rc_context(rc={'backend': 'Agg', 'interactive': False}):
         plt.figure()
-        rng = np.random.RandomState(0)
+        rng = RandomState(0)
         X = rng.normal(size=(10, 5))
         # use mixture of default values and keyword args
         plot_heatmap(X, ylabel="y-axis",
@@ -40,7 +42,7 @@ def test_confusion_matrix():
 
     with matplotlib.rc_context(rc={'backend': 'Agg', 'interactive': False}):
         plt.figure()
-        cnf_matrix = np.random.randomint(1, 10, size=(2, 2))
+        cnf_matrix = randomint(1, 10, size=(2, 2))
 
         # plot un-normalized matrix
         plot_confusion_matrix(cnf_matrix, classes=["dummy1", "dummy2"],

From 7e1475f60b66d645549f0390504cb45503b57dd5 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 4 Jul 2017 18:03:35 -0400
Subject: [PATCH 30/97] install matplotlib only if secret variable specified in
 build matrix

---
 build_tools/travis/install.sh | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/build_tools/travis/install.sh b/build_tools/travis/install.sh
index ab0bd356be3b1..e7ec4dc42d8d8 100755
--- a/build_tools/travis/install.sh
+++ b/build_tools/travis/install.sh
@@ -42,14 +42,13 @@ if [[ "$DISTRIB" == "conda" ]]; then
     if [[ "$INSTALL_MKL" == "true" ]]; then
         conda create -n testenv --yes python=$PYTHON_VERSION pip nose pytest \
             numpy=$NUMPY_VERSION scipy=$SCIPY_VERSION \
-            matplotlib=$MATPLOTLIB_VERSION \
             mkl cython=$CYTHON_VERSION \
-            ${PANDAS_VERSION+pandas=$PANDAS_VERSION}
+            ${PANDAS_VERSION+pandas=$PANDAS_VERSION} \
+            ${MATPLOTLIB_VERSION+matplotlib=$MATPLOTLIB_VERSION}
             
     else
         conda create -n testenv --yes python=$PYTHON_VERSION pip nose pytest \
             numpy=$NUMPY_VERSION scipy=$SCIPY_VERSION \
-            matplotlib=$MATPLOTLIB_VERSION \
             nomkl cython=$CYTHON_VERSION \
             ${PANDAS_VERSION+pandas=$PANDAS_VERSION}
     fi

From 343cbc72240864a33ff88d6dda749524046d62f1 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Wed, 5 Jul 2017 09:20:15 -0400
Subject: [PATCH 31/97] randint correction

---
 sklearn/plot/tests/test_heatmap.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/sklearn/plot/tests/test_heatmap.py b/sklearn/plot/tests/test_heatmap.py
index b110375adfc1b..8ea3d97ef99aa 100644
--- a/sklearn/plot/tests/test_heatmap.py
+++ b/sklearn/plot/tests/test_heatmap.py
@@ -8,7 +8,7 @@
 from sklearn.utils.testing import assert_raises
 import numpy as np
 from numpy.random import (RandomState,
-                          randomint)
+                          randint)
 
 
 def test_heatmap():
@@ -42,7 +42,7 @@ def test_confusion_matrix():
 
     with matplotlib.rc_context(rc={'backend': 'Agg', 'interactive': False}):
         plt.figure()
-        cnf_matrix = randomint(1, 10, size=(2, 2))
+        cnf_matrix = randint(1, 10, size=(2, 2))
 
         # plot un-normalized matrix
         plot_confusion_matrix(cnf_matrix, classes=["dummy1", "dummy2"],

From 2d1261d9f5da85001f3e891a871de8aa046fe5c1 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Wed, 5 Jul 2017 19:56:44 -0400
Subject: [PATCH 32/97] y_pred and y_true as input in place of matrix

---
 sklearn/plot/_confusion_matrix.py  | 21 ++++++++++++++++-----
 sklearn/plot/tests/test_heatmap.py |  7 ++++---
 2 files changed, 20 insertions(+), 8 deletions(-)

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index 183fe0a45b033..648fad9ce82e2 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -1,23 +1,32 @@
 import numpy as np
+from sklearn.metrics import confusion_matrix
 from sklearn.plot import plot_heatmap
 
 
-def plot_confusion_matrix(values, classes, normalize=False,
+def plot_confusion_matrix(y_true, y_pred, classes, sample_weights=None,
+                          normalize=False,
                           xlabel="Predicted Label", ylabel="True Label",
                           title='Confusion matrix', cmap=None, vmin=None,
                           vmax=None, ax=None, fmt="{:.2f}",
                           xtickrotation=45, norm=None):
-    """Plot the confusion matrix as a heatmap. Normalization can be
-    applied by setting `normalize=True`.
+    """Plot the confusion matrix as a heatmap. A confusion matrix is computed
+    using `y_true`, `y_pred` and `sample_weights` arguments. Normalization
+    can be applied by setting `normalize=True`.
 
     Parameters
     ----------
-    values : ndarray
-        Two-dimensional array to visualize.
+    y_true : array, shape = [n_samples]
+        Ground truth (correct) target values.
+
+    y_pred : array, shape = [n_samples]
+        Estimated targets as returned by a classifier.
 
     classes : list of strings
         The list of classes represented in the two-dimensional input array.
 
+    sample_weight : array-like of shape = [n_samples], optional
+        Sample weights used to calculate the confusion matrix
+
     normalize : boolean, default=False
         If True, the confusion matrix will be normalized by row.
 
@@ -59,6 +68,8 @@ def plot_confusion_matrix(values, classes, normalize=False,
 
     import matplotlib.pyplot as plt
 
+    values = confusion_matrix(y_true, y_pred, sample_weights=sample_weights)
+
     if normalize:
         values = values.astype('float') / values.sum(axis=1)[:, np.newaxis]
 
diff --git a/sklearn/plot/tests/test_heatmap.py b/sklearn/plot/tests/test_heatmap.py
index 8ea3d97ef99aa..51bf5a4873353 100644
--- a/sklearn/plot/tests/test_heatmap.py
+++ b/sklearn/plot/tests/test_heatmap.py
@@ -42,14 +42,15 @@ def test_confusion_matrix():
 
     with matplotlib.rc_context(rc={'backend': 'Agg', 'interactive': False}):
         plt.figure()
-        cnf_matrix = randint(1, 10, size=(2, 2))
+        array1 = randint(1, 3, size=20)
+        array2 = randint(1, 3, size=20)
 
         # plot un-normalized matrix
-        plot_confusion_matrix(cnf_matrix, classes=["dummy1", "dummy2"],
+        plot_confusion_matrix(array1, array2, classes=["dummy1", "dummy2"],
                               cmap="Paired", ax=plt.gca())
 
         # plot normalized matrix
-        plot_confusion_matrix(cnf_matrix, normalize=True,
+        plot_confusion_matrix(array1, array2, normalize=True,
                               classes=["dummay1", "dummy2"],
                               cmap="Paired", ax=plt.gca())
 

From 473f131ec282c7b173d7c73c2e67a2cf638222a7 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Thu, 6 Jul 2017 12:08:19 -0400
Subject: [PATCH 33/97] fixed typo

---
 sklearn/plot/_confusion_matrix.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index 648fad9ce82e2..803ebbdfdc1d5 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -3,7 +3,7 @@
 from sklearn.plot import plot_heatmap
 
 
-def plot_confusion_matrix(y_true, y_pred, classes, sample_weights=None,
+def plot_confusion_matrix(y_true, y_pred, classes, sample_weight=None,
                           normalize=False,
                           xlabel="Predicted Label", ylabel="True Label",
                           title='Confusion matrix', cmap=None, vmin=None,
@@ -68,7 +68,7 @@ def plot_confusion_matrix(y_true, y_pred, classes, sample_weights=None,
 
     import matplotlib.pyplot as plt
 
-    values = confusion_matrix(y_true, y_pred, sample_weights=sample_weights)
+    values = confusion_matrix(y_true, y_pred, sample_weight=sample_weight)
 
     if normalize:
         values = values.astype('float') / values.sum(axis=1)[:, np.newaxis]

From c86580a34432afa17913e266110ffa69aa035469 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Fri, 7 Jul 2017 13:13:55 -0400
Subject: [PATCH 34/97] fixed example

---
 examples/model_selection/plot_confusion_matrix.py | 7 ++-----
 1 file changed, 2 insertions(+), 5 deletions(-)

diff --git a/examples/model_selection/plot_confusion_matrix.py b/examples/model_selection/plot_confusion_matrix.py
index 95df220d242a3..29853b9412681 100644
--- a/examples/model_selection/plot_confusion_matrix.py
+++ b/examples/model_selection/plot_confusion_matrix.py
@@ -29,7 +29,6 @@
 
 from sklearn import svm, datasets
 from sklearn.model_selection import train_test_split
-from sklearn.metrics import confusion_matrix
 from sklearn.plot import plot_confusion_matrix
 
 # import some data to play with
@@ -46,19 +45,17 @@
 classifier = svm.SVC(kernel='linear', C=0.01)
 y_pred = classifier.fit(X_train, y_train).predict(X_test)
 
-# Compute confusion matrix
-cnf_matrix = confusion_matrix(y_test, y_pred)
 np.set_printoptions(precision=2)
 
 # Plot non-normalized confusion matrix
 plt.figure()
-plot_confusion_matrix(cnf_matrix, classes=class_names,
+plot_confusion_matrix(y_test, y_pred, classes=class_names,
                       title='Confusion matrix, without normalization',
                       cmap=plt.cm.Blues)
 
 # Plot normalized confusion matrix
 plt.figure()
-plot_confusion_matrix(cnf_matrix, classes=class_names, normalize=True,
+plot_confusion_matrix(y_test, y_pred, classes=class_names, normalize=True,
                       title='Normalized confusion matrix',
                       cmap=plt.cm.Blues)
 

From 2c10e41197afd0b7473147f40b0ec8e6bb87b385 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 25 Jul 2017 19:20:48 -0400
Subject: [PATCH 35/97] making classes optional

---
 sklearn/plot/_confusion_matrix.py  | 17 +++++++++++++++--
 sklearn/plot/tests/test_heatmap.py | 12 ++++++++++++
 2 files changed, 27 insertions(+), 2 deletions(-)

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index 803ebbdfdc1d5..e06af3c9c0d43 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -1,9 +1,10 @@
 import numpy as np
 from sklearn.metrics import confusion_matrix
 from sklearn.plot import plot_heatmap
+from sklearn.utils.multiclass import unique_labels
 
 
-def plot_confusion_matrix(y_true, y_pred, classes, sample_weight=None,
+def plot_confusion_matrix(y_true, y_pred, classes=None, sample_weight=None,
                           normalize=False,
                           xlabel="Predicted Label", ylabel="True Label",
                           title='Confusion matrix', cmap=None, vmin=None,
@@ -21,8 +22,10 @@ def plot_confusion_matrix(y_true, y_pred, classes, sample_weight=None,
     y_pred : array, shape = [n_samples]
         Estimated targets as returned by a classifier.
 
-    classes : list of strings
+    classes : list of strings, optional (default=None)
         The list of classes represented in the two-dimensional input array.
+        If not passed in function call, the classes will be infered from
+        y_true and y_pred
 
     sample_weight : array-like of shape = [n_samples], optional
         Sample weights used to calculate the confusion matrix
@@ -68,6 +71,16 @@ def plot_confusion_matrix(y_true, y_pred, classes, sample_weight=None,
 
     import matplotlib.pyplot as plt
 
+    unique_y = unique_labels(y_true, y_pred)
+
+    if classes is None:
+        classes = unique_y
+    else:
+        if not set(classes).issuperset(set(unique_y)):
+            raise ValueError("`classes=%s` are not a superset of the unique",
+                             "values of y_true and y_pred which are %s" %
+                             (classes, unique_y))
+
     values = confusion_matrix(y_true, y_pred, sample_weight=sample_weight)
 
     if normalize:
diff --git a/sklearn/plot/tests/test_heatmap.py b/sklearn/plot/tests/test_heatmap.py
index 51bf5a4873353..870263f421085 100644
--- a/sklearn/plot/tests/test_heatmap.py
+++ b/sklearn/plot/tests/test_heatmap.py
@@ -6,6 +6,7 @@
 from sklearn.svm import SVC
 from sklearn.utils.testing import SkipTest
 from sklearn.utils.testing import assert_raises
+from sklearn.utils.testing import assert_raise_message
 import numpy as np
 from numpy.random import (RandomState,
                           randint)
@@ -54,6 +55,17 @@ def test_confusion_matrix():
                               classes=["dummay1", "dummy2"],
                               cmap="Paired", ax=plt.gca())
 
+        # plot without passing classes explicitly
+        plot_confusion_matrix(array1, array2,
+                              cmap="Paired", ax=plt.gca())
+
+        # y having different value than classes should raise error
+        expected_msg = ("`classes=[1,2]` are not a superset of the unique",
+                        "values of y_true and y_pred which are [1,2,3]")
+        assert_raise_message(ValueError, expected_msg,
+                             plot_confusion_matrix, array1, array2,
+                             classes=[1, 2], ax=plt.gca())
+
         plt.draw()
         plt.close()
 

From f26a1a519f5880527174f7a4e7fae24cc7868847 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Thu, 27 Jul 2017 12:38:42 -0400
Subject: [PATCH 36/97] some fixes

---
 sklearn/plot/_confusion_matrix.py   |  24 +++---
 sklearn/plot/_gridsearch_results.py | 109 ++++++++++++++++------------
 sklearn/plot/_heatmap.py            |   2 +-
 sklearn/plot/tests/test_heatmap.py  |   5 +-
 4 files changed, 79 insertions(+), 61 deletions(-)

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index e06af3c9c0d43..42fcf7f789172 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -23,9 +23,9 @@ def plot_confusion_matrix(y_true, y_pred, classes=None, sample_weight=None,
         Estimated targets as returned by a classifier.
 
     classes : list of strings, optional (default=None)
-        The list of classes represented in the two-dimensional input array.
-        If not passed in function call, the classes will be infered from
-        y_true and y_pred
+        The list of names of classes represented in the two-dimensional input
+        array. If not passed in function call, the classes will be infered
+        from y_true and y_pred
 
     sample_weight : array-like of shape = [n_samples], optional
         Sample weights used to calculate the confusion matrix
@@ -76,10 +76,11 @@ def plot_confusion_matrix(y_true, y_pred, classes=None, sample_weight=None,
     if classes is None:
         classes = unique_y
     else:
-        if not set(classes).issuperset(set(unique_y)):
-            raise ValueError("`classes=%s` are not a superset of the unique",
-                             "values of y_true and y_pred which are %s" %
-                             (classes, unique_y))
+        if len(classes) != len(unique_y):
+            raise ValueError("y_true and y_pred contain %d unique classes,"
+                             "which is not the same as %d"
+                             "classes found in `classes=%s` paramter" %
+                             (len(classes), len(unique_y), unique_y))
 
     values = confusion_matrix(y_true, y_pred, sample_weight=sample_weight)
 
@@ -88,8 +89,11 @@ def plot_confusion_matrix(y_true, y_pred, classes=None, sample_weight=None,
 
     fmt = fmt if normalize else '{:d}'
 
-    plot_heatmap(values, xticklabels=classes, yticklabels=classes, cmap=cmap,
-                 xlabel=xlabel, ylabel=ylabel, vmin=vmin, vmax=vmax, ax=ax,
-                 fmt=fmt, xtickrotation=xtickrotation, norm=norm)
+    img = plot_heatmap(values, xticklabels=classes, yticklabels=classes,
+                       cmap=cmap, xlabel=xlabel, ylabel=ylabel, vmin=vmin,
+                       vmax=vmax, ax=ax, fmt=fmt, xtickrotation=xtickrotation,
+                       norm=norm)
 
     plt.title(title)
+
+    return img
diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index 587ff2ae81106..56cf657f0f1cf 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -2,6 +2,58 @@
 from sklearn.plot import plot_heatmap
 
 
+def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title):
+    import matplotlib.pyplot as plt
+
+    param = params[0]
+    param_range = sorted(cv_results['param_%s' % param])
+    train_scores_mean = cv_results['mean_train_score']
+    train_scores_std = cv_results['std_train_score']
+    test_scores_mean = cv_results['mean_test_score']
+    test_scores_std = cv_results['std_test_score']
+
+    lw = 2
+    plt.semilogx(param_range, train_scores_mean,
+                 label="Training score",
+                 color="darkorange", lw=lw)
+    plt.fill_between(param_range, train_scores_mean - train_scores_std,
+                     train_scores_mean + train_scores_std, alpha=0.2,
+                     color="darkorange", lw=lw)
+
+    img = plt.semilogx(param_range, test_scores_mean,
+                       label="Cross-validation score",
+                       color="navy", lw=lw)
+    plt.fill_between(param_range, test_scores_mean - test_scores_std,
+                     test_scores_mean + test_scores_std, alpha=0.2,
+                     color="navy", lw=lw)
+
+    plt.xlabel(param)
+    plt.legend()
+    ylabel = "Score" if ylabel is None else ylabel
+    plt.ylabel(ylabel)
+    plt.title(title)
+    plt.show()
+    return img
+
+
+def _plot_2D_results(cv_results, params, metric, ax, xlabel, ylabel,
+                     title, norm):
+    import matplotlib.pyplot as plt
+
+    parameter1_values = np.unique(cv_results['param_%s' % params[0]])
+    parameter2_values = np.unique(cv_results['param_%s' % params[1]])
+
+    scores = cv_results[metric].reshape(len(parameter1_values),
+                                        len(parameter2_values))
+
+    img = plot_heatmap(scores, cmap=plt.cm.hot, xlabel=xlabel,
+                       ylabel=ylabel, xticklabels=parameter1_values,
+                       yticklabels=parameter2_values, ax=ax, norm=norm)
+    plt.title(title)
+    plt.show()
+    return img
+
+
 def plot_gridsearch_results(cv_results, metric='mean_test_score',
                             xlabel=None, ylabel=None,
                             title='Grid Search Results', cmap=None,
@@ -54,63 +106,24 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
 
     norm : matplotlib normalizer
         Normalizer passed to pcolormesh function from matplotlib used to
-        generate the heatmap.
+        generate the heatmap. This is ignored if only 1 parameter is used in
+        grid search.
     """
 
-    import matplotlib.pyplot as plt
-
     params = sorted(cv_results['params'][0].keys())
     nparams = len(params)
+    xlabel = params[0] if xlabel is None else xlabel
+    ylabel = params[1] if ylabel is None else ylabel
 
     if nparams == 1:
-        param = params[0]
-        param_range = sorted(cv_results['param_%s' % param])
-        train_scores_mean = cv_results['mean_train_score']
-        train_scores_std = cv_results['std_train_score']
-        test_scores_mean = cv_results['mean_test_score']
-        test_scores_std = cv_results['std_test_score']
-
-        lw = 2
-        plt.semilogx(param_range, train_scores_mean,
-                     label="Training score",
-                     color="darkorange", lw=lw)
-        plt.fill_between(param_range, train_scores_mean - train_scores_std,
-                         train_scores_mean + train_scores_std, alpha=0.2,
-                         color="darkorange", lw=lw)
-
-        plt.semilogx(param_range, test_scores_mean,
-                     label="Cross-validation score",
-                     color="navy", lw=lw)
-        plt.fill_between(param_range, test_scores_mean - test_scores_std,
-                         test_scores_mean + test_scores_std, alpha=0.2,
-                         color="navy", lw=lw)
-
-        plt.title(title)
-        plt.xlabel(param)
-        plt.legend()
-        ylabel = "Score" if ylabel is None else ylabel
-        plt.ylabel(ylabel)
-        plt.show()
+        img = _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title)
 
     elif nparams == 2:
-        parameter1_values = np.unique(cv_results['param_%s' % params[0]])
-        parameter2_values = np.unique(cv_results['param_%s' % params[1]])
-
-        scores = cv_results[metric].reshape(len(parameter1_values),
-                                            len(parameter2_values))
-
-        xlabel = params[0] if xlabel is None else xlabel
-        ylabel = params[1] if ylabel is None else ylabel
-
-        plot_heatmap(scores, cmap=plt.cm.hot, xlabel=xlabel, ylabel=ylabel,
-                     xticklabels=parameter1_values,
-                     yticklabels=parameter2_values,
-                     ax=ax, norm=norm)
-
-        plt.title(title)
-        plt.show()
+        img = _plot_2D_results(cv_results, params, metric, ax, xlabel,
+                               ylabel, title, norm)
 
     else:
         raise ValueError('Plot function supports upto 2 parameters in grid'
                          'search, got {0}.'.format(nparams))
-        pass
+
+    return img
diff --git a/sklearn/plot/_heatmap.py b/sklearn/plot/_heatmap.py
index cfa0645c86e18..8b0c51d2cf5b9 100644
--- a/sklearn/plot/_heatmap.py
+++ b/sklearn/plot/_heatmap.py
@@ -90,4 +90,4 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
     # not anti-diagonal matrix
     ax.invert_yaxis()
 
-    return ax
+    return img
diff --git a/sklearn/plot/tests/test_heatmap.py b/sklearn/plot/tests/test_heatmap.py
index 870263f421085..d135591f285d6 100644
--- a/sklearn/plot/tests/test_heatmap.py
+++ b/sklearn/plot/tests/test_heatmap.py
@@ -60,8 +60,9 @@ def test_confusion_matrix():
                               cmap="Paired", ax=plt.gca())
 
         # y having different value than classes should raise error
-        expected_msg = ("`classes=[1,2]` are not a superset of the unique",
-                        "values of y_true and y_pred which are [1,2,3]")
+        expected_msg = ("y_true and y_pred contain 3 unique classes, which is"
+                        "not the same as 2 classes found in `classes=[1,2]`"
+                        "paramter")
         assert_raise_message(ValueError, expected_msg,
                              plot_confusion_matrix, array1, array2,
                              classes=[1, 2], ax=plt.gca())

From 7d202ad578df56c20df33e3e08b6f18e25b47338 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Thu, 27 Jul 2017 13:31:50 -0400
Subject: [PATCH 37/97] fixed 1d case of grid_search_results

---
 sklearn/plot/_confusion_matrix.py   | 26 +++++-----
 sklearn/plot/_gridsearch_results.py | 74 +++++++++++++++++------------
 sklearn/plot/tests/test_heatmap.py  |  6 ++-
 3 files changed, 60 insertions(+), 46 deletions(-)

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index 42fcf7f789172..60df2fec50dc0 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -27,44 +27,44 @@ def plot_confusion_matrix(y_true, y_pred, classes=None, sample_weight=None,
         array. If not passed in function call, the classes will be infered
         from y_true and y_pred
 
-    sample_weight : array-like of shape = [n_samples], optional
+    sample_weight : array-like of shape = [n_samples], optional (default=None)
         Sample weights used to calculate the confusion matrix
 
-    normalize : boolean, default=False
+    normalize : boolean, optional (default=False)
         If True, the confusion matrix will be normalized by row.
 
-    xlabel : string, default="Predicted Label"
+    xlabel : string, optional (default="Predicted Label")
         Label for the x-axis.
 
-    ylabel : string, default="True Label"
+    ylabel : string, optional (default="True Label")
         Label for the y-axis.
 
-    title : string, default="Confusion matrix"
+    title : string, optional (default="Confusion matrix")
         Title for the heatmap.
 
-    cmap : string or colormap
-        Matpotlib colormap to use.
+    cmap : string or colormap, optional (default=None)
+        Matpotlib colormap to use. If None, plt.cm.hot will be used.
 
-    vmin : int, float or None
+    vmin : int, float or None, optional (default=None)
         Minimum clipping value. This argument will be passed on to the
         pcolormesh function from matplotlib used to generate the heatmap.
 
-    vmax : int, float or None
+    vmax : int, float or None, optional (default=None)
         Maximum clipping value. This argument will be passed on to the
         pcolormesh function from matplotlib used to generate the heatmap.
 
-    ax : axes object or None
+    ax : axes object or None, optional (default=None)
         Matplotlib axes object to plot into. If None, the current axes are
         used.
 
-    fmt : string, default="{:.2f}"
+    fmt : string, optional (default="{:.2f}")
         Format string to convert value to text. This will be ignored if
         normalize argument is False.
 
-    xtickrotation : float, default=45
+    xtickrotation : float, optional (default=45)
         Rotation of the xticklabels.
 
-    norm : matplotlib normalizer
+    norm : matplotlib normalizer, optional (default=None)
         Normalizer passed to pcolormesh function from matplotlib used to
         generate the heatmap.
     """
diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index 56cf657f0f1cf..f27c0d53d1925 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -2,7 +2,8 @@
 from sklearn.plot import plot_heatmap
 
 
-def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title):
+def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title,
+                     fmt, xtickrotation):
     import matplotlib.pyplot as plt
 
     param = params[0]
@@ -13,20 +14,23 @@ def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title):
     test_scores_std = cv_results['std_test_score']
 
     lw = 2
-    plt.semilogx(param_range, train_scores_mean,
-                 label="Training score",
-                 color="darkorange", lw=lw)
-    plt.fill_between(param_range, train_scores_mean - train_scores_std,
+    x_vales = range(len(param_range))
+    plt.plot(x_vales, train_scores_mean,
+             label="Training score",
+             color="darkorange", lw=lw)
+    plt.fill_between(x_vales, train_scores_mean - train_scores_std,
                      train_scores_mean + train_scores_std, alpha=0.2,
                      color="darkorange", lw=lw)
 
-    img = plt.semilogx(param_range, test_scores_mean,
-                       label="Cross-validation score",
-                       color="navy", lw=lw)
-    plt.fill_between(param_range, test_scores_mean - test_scores_std,
+    img = plt.plot(x_vales, test_scores_mean,
+                   label="Cross-validation score",
+                   color="navy", lw=lw)
+    plt.fill_between(x_vales, test_scores_mean - test_scores_std,
                      test_scores_mean + test_scores_std, alpha=0.2,
                      color="navy", lw=lw)
-
+    plt.xticks(x_vales, [fmt.format(x) for x in param_range],
+               rotation=xtickrotation)
+    xlabel = params[0] if xlabel is None else xlabel
     plt.xlabel(param)
     plt.legend()
     ylabel = "Score" if ylabel is None else ylabel
@@ -36,8 +40,9 @@ def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title):
     return img
 
 
-def _plot_2D_results(cv_results, params, metric, ax, xlabel, ylabel,
-                     title, norm):
+def _plot_2D_results(cv_results, params, metric, ax, xlabel,
+                     ylabel, title, cmap, vmin, vmax, fmt,
+                     xtickrotation, norm):
     import matplotlib.pyplot as plt
 
     parameter1_values = np.unique(cv_results['param_%s' % params[0]])
@@ -46,9 +51,16 @@ def _plot_2D_results(cv_results, params, metric, ax, xlabel, ylabel,
     scores = cv_results[metric].reshape(len(parameter1_values),
                                         len(parameter2_values))
 
-    img = plot_heatmap(scores, cmap=plt.cm.hot, xlabel=xlabel,
-                       ylabel=ylabel, xticklabels=parameter1_values,
-                       yticklabels=parameter2_values, ax=ax, norm=norm)
+    xlabel = params[0] if xlabel is None else xlabel
+    ylabel = params[1] if ylabel is None else ylabel
+
+    cmap = cmap if cmap is not None else plt.cm.hot
+
+    img = plot_heatmap(scores, xlabel=xlabel, ylabel=ylabel,
+                       xticklabels=parameter1_values,
+                       yticklabels=parameter2_values, cmap=cmap,
+                       vmin=vmin, vmax=vmax, fmt=fmt, ax=ax,
+                       xtickrotation=xtickrotation, norm=norm)
     plt.title(title)
     plt.show()
     return img
@@ -68,43 +80,43 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
     cv_results : dict of numpy (masked) ndarrays
         The cv_results_ attribute of the GridSearchCV object.
 
-    xlabel : string, default=None
+    xlabel : string, optional (default=None)
         Label for the x-axis. If None, the first key of the param_grid will
         be used as the xlabel.
 
-    ylabel : string, default=None
+    ylabel : string, optional (default=None)
         Label for the y-axis. If None, the second key of the param_grid will
         be used as the ylabel.
 
-    metric : string, default="mean_test_score"
+    metric : string, optional (default="mean_test_score")
         The metric from the GridSearchCV results to display. This is ignored
         if only 1 parameter is used in grid search.
 
-    title : string, default="Grid Search Results"
+    title : string, optional (default="Grid Search Results")
         Title for the heatmap.
 
-    cmap : string or colormap
-        Matpotlib colormap to use.
+    cmap : string or colormap, optional (default=None)
+        Matpotlib colormap to use. If None, plt.cm.hot will be used.
 
-    vmin : int, float or None
+    vmin : int, float or None, optional (default=None)
         Minimum clipping value. This argument will be passed on to the
         pcolormesh function from matplotlib used to generate the heatmap.
 
-    vmax : int, float or None
+    vmax : int, float or None, optional (default=None)
         Maximum clipping value. This argument will be passed on to the
         pcolormesh function from matplotlib used to generate the heatmap.
 
-    ax : axes object or None
+    ax : axes object or None, optional (default=None)
         Matplotlib axes object to plot into. If None, the current axes are
         used.
 
-    fmt : string, default="{:.2f}"
+    fmt : string, optional (default="{:.2f}")
         Format string to convert value to text.
 
-    xtickrotation : float, default=45
+    xtickrotation : float, optional (default=45)
         Rotation of the xticklabels.
 
-    norm : matplotlib normalizer
+    norm : matplotlib normalizer, optional (default=None)
         Normalizer passed to pcolormesh function from matplotlib used to
         generate the heatmap. This is ignored if only 1 parameter is used in
         grid search.
@@ -112,15 +124,15 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
 
     params = sorted(cv_results['params'][0].keys())
     nparams = len(params)
-    xlabel = params[0] if xlabel is None else xlabel
-    ylabel = params[1] if ylabel is None else ylabel
 
     if nparams == 1:
-        img = _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title)
+        img = _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title,
+                               fmt, xtickrotation)
 
     elif nparams == 2:
         img = _plot_2D_results(cv_results, params, metric, ax, xlabel,
-                               ylabel, title, norm)
+                               ylabel, title, cmap, vmin, vmax, fmt,
+                               xtickrotation, norm)
 
     else:
         raise ValueError('Plot function supports upto 2 parameters in grid'
diff --git a/sklearn/plot/tests/test_heatmap.py b/sklearn/plot/tests/test_heatmap.py
index d135591f285d6..1a89536c17202 100644
--- a/sklearn/plot/tests/test_heatmap.py
+++ b/sklearn/plot/tests/test_heatmap.py
@@ -5,7 +5,6 @@
 from sklearn.model_selection import GridSearchCV
 from sklearn.svm import SVC
 from sklearn.utils.testing import SkipTest
-from sklearn.utils.testing import assert_raises
 from sklearn.utils.testing import assert_raise_message
 import numpy as np
 from numpy.random import (RandomState,
@@ -147,6 +146,9 @@ def test_gridsearch_results_3d():
 
     with matplotlib.rc_context(rc={'backend': 'Agg', 'interactive': False}):
         plt.figure()
-        assert_raises(ValueError, plot_gridsearch_results, grid.cv_results_)
+        expected_msg = ('Plot function supports upto 2 parameters in grid'
+                        'search, got 3.')
+        assert_raise_message(ValueError, expected_msg,
+                             plot_gridsearch_results, grid.cv_results_)
         plt.draw()
         plt.close()

From a5602d470623ae0a84516bd18748fe3365fb84b9 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Thu, 27 Jul 2017 14:27:21 -0400
Subject: [PATCH 38/97] fixed confusion matrix test

---
 sklearn/plot/_confusion_matrix.py   | 8 ++++----
 sklearn/plot/_gridsearch_results.py | 2 +-
 sklearn/plot/tests/test_heatmap.py  | 8 ++++----
 3 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index 60df2fec50dc0..af0ffeda548b8 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -77,10 +77,10 @@ def plot_confusion_matrix(y_true, y_pred, classes=None, sample_weight=None,
         classes = unique_y
     else:
         if len(classes) != len(unique_y):
-            raise ValueError("y_true and y_pred contain %d unique classes,"
-                             "which is not the same as %d"
-                             "classes found in `classes=%s` paramter" %
-                             (len(classes), len(unique_y), unique_y))
+            raise ValueError("y_true and y_pred contain %d unique classes, "
+                             "which is not the same as %d "
+                             "classes found in `classes=%s` parameter" %
+                             (len(unique_y), len(classes), classes))
 
     values = confusion_matrix(y_true, y_pred, sample_weight=sample_weight)
 
diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index f27c0d53d1925..1c65ae49d8404 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -136,6 +136,6 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
 
     else:
         raise ValueError('Plot function supports upto 2 parameters in grid'
-                         'search, got {0}.'.format(nparams))
+                         'search, got %d.' % nparams)
 
     return img
diff --git a/sklearn/plot/tests/test_heatmap.py b/sklearn/plot/tests/test_heatmap.py
index 1a89536c17202..a50c20f384113 100644
--- a/sklearn/plot/tests/test_heatmap.py
+++ b/sklearn/plot/tests/test_heatmap.py
@@ -59,12 +59,12 @@ def test_confusion_matrix():
                               cmap="Paired", ax=plt.gca())
 
         # y having different value than classes should raise error
-        expected_msg = ("y_true and y_pred contain 3 unique classes, which is"
-                        "not the same as 2 classes found in `classes=[1,2]`"
-                        "paramter")
+        expected_msg = ("y_true and y_pred contain 2 unique classes, which is"
+                        " not the same as 3 classes found in "
+                        "`classes=[1, 2, 3]` parameter")
         assert_raise_message(ValueError, expected_msg,
                              plot_confusion_matrix, array1, array2,
-                             classes=[1, 2], ax=plt.gca())
+                             classes=[1, 2, 3], ax=plt.gca())
 
         plt.draw()
         plt.close()

From 3192dfdde185f71e09a49b33298ecd1d296e874d Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Thu, 27 Jul 2017 14:54:53 -0400
Subject: [PATCH 39/97] working on axes not plt

---
 sklearn/plot/_gridsearch_results.py | 42 ++++++++++++++++-------------
 1 file changed, 23 insertions(+), 19 deletions(-)

diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index 1c65ae49d8404..e98bed94e2e23 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -5,6 +5,8 @@
 def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title,
                      fmt, xtickrotation):
     import matplotlib.pyplot as plt
+    if ax is None:
+        ax = plt.gca()
 
     param = params[0]
     param_range = sorted(cv_results['param_%s' % param])
@@ -15,27 +17,29 @@ def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title,
 
     lw = 2
     x_vales = range(len(param_range))
-    plt.plot(x_vales, train_scores_mean,
-             label="Training score",
-             color="darkorange", lw=lw)
-    plt.fill_between(x_vales, train_scores_mean - train_scores_std,
-                     train_scores_mean + train_scores_std, alpha=0.2,
-                     color="darkorange", lw=lw)
-
-    img = plt.plot(x_vales, test_scores_mean,
-                   label="Cross-validation score",
-                   color="navy", lw=lw)
-    plt.fill_between(x_vales, test_scores_mean - test_scores_std,
-                     test_scores_mean + test_scores_std, alpha=0.2,
-                     color="navy", lw=lw)
-    plt.xticks(x_vales, [fmt.format(x) for x in param_range],
-               rotation=xtickrotation)
+    ax.plot(x_vales, train_scores_mean,
+            label="Training score",
+            color="darkorange", lw=lw)
+    ax.fill_between(x_vales, train_scores_mean - train_scores_std,
+                    train_scores_mean + train_scores_std, alpha=0.2,
+                    color="darkorange", lw=lw)
+
+    img = ax.plot(x_vales, test_scores_mean,
+                  label="Cross-validation score",
+                  color="navy", lw=lw)
+    ax.fill_between(x_vales, test_scores_mean - test_scores_std,
+                    test_scores_mean + test_scores_std, alpha=0.2,
+                    color="navy", lw=lw)
+    ax.set_xticks(x_vales)
+    ax.set_xticklabels([fmt.format(x) for x in param_range],
+                       rotation=xtickrotation)
+
     xlabel = params[0] if xlabel is None else xlabel
-    plt.xlabel(param)
-    plt.legend()
+    ax.set_xlabel(param)
+    ax.legend()
     ylabel = "Score" if ylabel is None else ylabel
-    plt.ylabel(ylabel)
-    plt.title(title)
+    ax.set_ylabel(ylabel)
+    ax.set_title(title)
     plt.show()
     return img
 

From 37c96306eb632674082f2ea1108904f7a2eebbcf Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Fri, 28 Jul 2017 15:15:29 -0400
Subject: [PATCH 40/97] adding title to plot_heatmap, removing plt.show from
 within API

---
 examples/model_selection/plot_confusion_matrix.py |  2 +-
 sklearn/plot/_confusion_matrix.py                 | 10 +++-------
 sklearn/plot/_gridsearch_results.py               |  6 ++----
 sklearn/plot/_heatmap.py                          | 12 ++++++++++--
 4 files changed, 16 insertions(+), 14 deletions(-)

diff --git a/examples/model_selection/plot_confusion_matrix.py b/examples/model_selection/plot_confusion_matrix.py
index 29853b9412681..804d4ba6d9354 100644
--- a/examples/model_selection/plot_confusion_matrix.py
+++ b/examples/model_selection/plot_confusion_matrix.py
@@ -56,7 +56,7 @@
 # Plot normalized confusion matrix
 plt.figure()
 plot_confusion_matrix(y_test, y_pred, classes=class_names, normalize=True,
-                      title='Normalized confusion matrix',
+                      title='Confusion matrix, with normalization',
                       cmap=plt.cm.Blues)
 
 plt.show()
diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index af0ffeda548b8..1c2c8f9a22bd6 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -69,8 +69,6 @@ def plot_confusion_matrix(y_true, y_pred, classes=None, sample_weight=None,
         generate the heatmap.
     """
 
-    import matplotlib.pyplot as plt
-
     unique_y = unique_labels(y_true, y_pred)
 
     if classes is None:
@@ -90,10 +88,8 @@ def plot_confusion_matrix(y_true, y_pred, classes=None, sample_weight=None,
     fmt = fmt if normalize else '{:d}'
 
     img = plot_heatmap(values, xticklabels=classes, yticklabels=classes,
-                       cmap=cmap, xlabel=xlabel, ylabel=ylabel, vmin=vmin,
-                       vmax=vmax, ax=ax, fmt=fmt, xtickrotation=xtickrotation,
-                       norm=norm)
-
-    plt.title(title)
+                       cmap=cmap, xlabel=xlabel, ylabel=ylabel, title=title,
+                       vmin=vmin, vmax=vmax, ax=ax, fmt=fmt,
+                       xtickrotation=xtickrotation, norm=norm)
 
     return img
diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index e98bed94e2e23..0d3952cac1999 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -40,7 +40,6 @@ def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title,
     ylabel = "Score" if ylabel is None else ylabel
     ax.set_ylabel(ylabel)
     ax.set_title(title)
-    plt.show()
     return img
 
 
@@ -62,11 +61,10 @@ def _plot_2D_results(cv_results, params, metric, ax, xlabel,
 
     img = plot_heatmap(scores, xlabel=xlabel, ylabel=ylabel,
                        xticklabels=parameter1_values,
-                       yticklabels=parameter2_values, cmap=cmap,
+                       yticklabels=parameter2_values,
+                       title=title, cmap=cmap,
                        vmin=vmin, vmax=vmax, fmt=fmt, ax=ax,
                        xtickrotation=xtickrotation, norm=norm)
-    plt.title(title)
-    plt.show()
     return img
 
 
diff --git a/sklearn/plot/_heatmap.py b/sklearn/plot/_heatmap.py
index 8b0c51d2cf5b9..989c170cacd53 100644
--- a/sklearn/plot/_heatmap.py
+++ b/sklearn/plot/_heatmap.py
@@ -2,8 +2,9 @@
 
 
 def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
-                 yticklabels=None, cmap=None, vmin=None, vmax=None, ax=None,
-                 fmt="{:.2f}", xtickrotation=45, norm=None):
+                 yticklabels=None, title=None, cmap=None, vmin=None,
+                 vmax=None, ax=None, fmt="{:.2f}", xtickrotation=45,
+                 norm=None):
     """Plot a matrix as heatmap with explicit numbers.
 
     Parameters
@@ -23,6 +24,9 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
     yticklabels : list of string or None, default=None
         Tick labels for the y-axis
 
+    title : string or None, default=None
+        Title of the chart
+
     cmap : string or colormap
         Matpotlib colormap to use.
 
@@ -90,4 +94,8 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
     # not anti-diagonal matrix
     ax.invert_yaxis()
 
+    # set title if not none:
+    if title is not None:
+        ax.set_title(title)
+
     return img

From d2a91fc50518e7a0c3fc9c49bf70101ea4e371b2 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Fri, 28 Jul 2017 15:25:21 -0400
Subject: [PATCH 41/97] added section to validation curve example

---
 .../model_selection/plot_validation_curve.py  | 28 +++++++++++++++++++
 1 file changed, 28 insertions(+)

diff --git a/examples/model_selection/plot_validation_curve.py b/examples/model_selection/plot_validation_curve.py
index ed74a41ff100b..ae335b3cf89a9 100644
--- a/examples/model_selection/plot_validation_curve.py
+++ b/examples/model_selection/plot_validation_curve.py
@@ -49,3 +49,31 @@
                  color="navy", lw=lw)
 plt.legend(loc="best")
 plt.show()
+
+#####################################################################
+"""
+The same plot can also be generated using a combination of GridSearchCV and
+ plotting module of scikit-learn.
+"""
+
+print(__doc__)
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+from sklearn.datasets import load_digits
+from sklearn.svm import SVC
+from sklearn.model_selection import GridSearchCV
+from sklearn.plot import plot_gridsearch_results
+
+digits = load_digits()
+X, y = digits.data, digits.target
+
+param_grid = {'gamma': np.logspace(-6, -1, 5)}
+gs = GridSearchCV(SVC(),
+                  param_grid=param_grid,
+                  cv=10, scoring="accuracy")
+
+gs.fit(X, y)
+plot_gridsearch_results(gs.cv_results_)
+plt.show()

From f87f6430970a03f1026fa56640d7e048b07b7c24 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Fri, 28 Jul 2017 17:08:24 -0400
Subject: [PATCH 42/97] sphinx syntax fix

---
 examples/model_selection/plot_validation_curve.py | 6 ++----
 1 file changed, 2 insertions(+), 4 deletions(-)

diff --git a/examples/model_selection/plot_validation_curve.py b/examples/model_selection/plot_validation_curve.py
index ae335b3cf89a9..c345b77cd3176 100644
--- a/examples/model_selection/plot_validation_curve.py
+++ b/examples/model_selection/plot_validation_curve.py
@@ -51,10 +51,8 @@
 plt.show()
 
 #####################################################################
-"""
-The same plot can also be generated using a combination of GridSearchCV and
- plotting module of scikit-learn.
-"""
+# The same plot can also be generated using a combination of GridSearchCV and
+# plotting module of scikit-learn.
 
 print(__doc__)
 

From ba49b5c857f2a91aa4ea4b14f7f70a141e6b39f0 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 1 Aug 2017 11:02:24 -0400
Subject: [PATCH 43/97] matplotlib new figure creation modified

---
 sklearn/plot/_gridsearch_results.py | 4 +++-
 sklearn/plot/_heatmap.py            | 5 ++++-
 2 files changed, 7 insertions(+), 2 deletions(-)

diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index 0d3952cac1999..6d51402455bc2 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -6,7 +6,8 @@ def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title,
                      fmt, xtickrotation):
     import matplotlib.pyplot as plt
     if ax is None:
-        ax = plt.gca()
+        fig = plt.figure()
+        ax = fig.add_subplot(111)
 
     param = params[0]
     param_range = sorted(cv_results['param_%s' % param])
@@ -40,6 +41,7 @@ def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title,
     ylabel = "Score" if ylabel is None else ylabel
     ax.set_ylabel(ylabel)
     ax.set_title(title)
+    plt.draw()
     return img
 
 
diff --git a/sklearn/plot/_heatmap.py b/sklearn/plot/_heatmap.py
index 989c170cacd53..020e1394c1f6f 100644
--- a/sklearn/plot/_heatmap.py
+++ b/sklearn/plot/_heatmap.py
@@ -52,7 +52,8 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
 
     import matplotlib.pyplot as plt
     if ax is None:
-        ax = plt.gca()
+        fig = plt.figure()
+        ax = fig.add_subplot(111)
     img = ax.pcolormesh(values, cmap=cmap, vmin=vmin, vmax=vmax, norm=norm)
 
     # this will allow us to access the pixel values:
@@ -98,4 +99,6 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
     if title is not None:
         ax.set_title(title)
 
+    plt.draw()
+
     return img

From 3c74c7fbc338c0f91fe8d33116c7ea821e3e992d Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 1 Aug 2017 12:51:23 -0400
Subject: [PATCH 44/97] define axis closer to public layer

---
 sklearn/plot/_confusion_matrix.py   | 5 +++++
 sklearn/plot/_gridsearch_results.py | 8 +++++---
 2 files changed, 10 insertions(+), 3 deletions(-)

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index 1c2c8f9a22bd6..2ca9e10ac44b4 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -68,6 +68,7 @@ def plot_confusion_matrix(y_true, y_pred, classes=None, sample_weight=None,
         Normalizer passed to pcolormesh function from matplotlib used to
         generate the heatmap.
     """
+    import matplotlib.pyplot as plt
 
     unique_y = unique_labels(y_true, y_pred)
 
@@ -87,6 +88,10 @@ def plot_confusion_matrix(y_true, y_pred, classes=None, sample_weight=None,
 
     fmt = fmt if normalize else '{:d}'
 
+    if ax is None:
+        fig = plt.figure()
+        ax = fig.add_subplot(111)
+
     img = plot_heatmap(values, xticklabels=classes, yticklabels=classes,
                        cmap=cmap, xlabel=xlabel, ylabel=ylabel, title=title,
                        vmin=vmin, vmax=vmax, ax=ax, fmt=fmt,
diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index 6d51402455bc2..c1d1f01031b53 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -5,9 +5,6 @@
 def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title,
                      fmt, xtickrotation):
     import matplotlib.pyplot as plt
-    if ax is None:
-        fig = plt.figure()
-        ax = fig.add_subplot(111)
 
     param = params[0]
     param_range = sorted(cv_results['param_%s' % param])
@@ -125,10 +122,15 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
         generate the heatmap. This is ignored if only 1 parameter is used in
         grid search.
     """
+    import matplotlib.pyplot as plt
 
     params = sorted(cv_results['params'][0].keys())
     nparams = len(params)
 
+    if ax is None:
+        fig = plt.figure()
+        ax = fig.add_subplot(111)
+
     if nparams == 1:
         img = _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title,
                                fmt, xtickrotation)

From d7c0a305ef298dacc6cf289862c9eea6b7e64115 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Thu, 3 Aug 2017 11:19:00 -0400
Subject: [PATCH 45/97] removed plt.draw()

---
 sklearn/plot/_gridsearch_results.py | 3 ---
 sklearn/plot/_heatmap.py            | 2 --
 2 files changed, 5 deletions(-)

diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index c1d1f01031b53..f5d74c834143f 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -4,8 +4,6 @@
 
 def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title,
                      fmt, xtickrotation):
-    import matplotlib.pyplot as plt
-
     param = params[0]
     param_range = sorted(cv_results['param_%s' % param])
     train_scores_mean = cv_results['mean_train_score']
@@ -38,7 +36,6 @@ def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title,
     ylabel = "Score" if ylabel is None else ylabel
     ax.set_ylabel(ylabel)
     ax.set_title(title)
-    plt.draw()
     return img
 
 
diff --git a/sklearn/plot/_heatmap.py b/sklearn/plot/_heatmap.py
index 020e1394c1f6f..d098bd82cc927 100644
--- a/sklearn/plot/_heatmap.py
+++ b/sklearn/plot/_heatmap.py
@@ -99,6 +99,4 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
     if title is not None:
         ax.set_title(title)
 
-    plt.draw()
-
     return img

From 432a524bab90f28d677b8a94ae522c788b660948 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Sat, 12 Aug 2017 19:03:04 -0400
Subject: [PATCH 46/97] docstring split lines

---
 sklearn/plot/_confusion_matrix.py   | 8 +++++---
 sklearn/plot/_gridsearch_results.py | 4 +++-
 2 files changed, 8 insertions(+), 4 deletions(-)

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index 2ca9e10ac44b4..aa205db564706 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -10,9 +10,11 @@ def plot_confusion_matrix(y_true, y_pred, classes=None, sample_weight=None,
                           title='Confusion matrix', cmap=None, vmin=None,
                           vmax=None, ax=None, fmt="{:.2f}",
                           xtickrotation=45, norm=None):
-    """Plot the confusion matrix as a heatmap. A confusion matrix is computed
-    using `y_true`, `y_pred` and `sample_weights` arguments. Normalization
-    can be applied by setting `normalize=True`.
+    """Plot confusion matrix as a heatmap.
+
+    A confusion matrix is computed using `y_true`, `y_pred` and
+    `sample_weights` arguments. Normalization can be applied by setting
+    `normalize=True`.
 
     Parameters
     ----------
diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index f5d74c834143f..7a902903a6ec0 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -69,7 +69,9 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
                             title='Grid Search Results', cmap=None,
                             vmin=None, vmax=None, ax=None, fmt="{:.2f}",
                             xtickrotation=45, norm=None):
-    """Plot the grid search results as a line chart for 1D search and heatmap
+    """Plot grid search results.
+
+    The results are plotted as a line chart for 1D search and as a heatmap
     for a 2D search. This function will not work if grid-search has more than
     2 parameters in the search space.
 

From 226690d4dbbf8c477c6a7b5cd2c12aa5ec74d3fb Mon Sep 17 00:00:00 2001
From: Andreas Mueller <t3kcit@gmail.com>
Date: Mon, 19 Dec 2016 11:41:27 -0500
Subject: [PATCH 47/97] add plotting module and "plot_heatmap" function

---
 sklearn/plot/__init__.py           |  3 ++
 sklearn/plot/_heatmap.py           | 73 ++++++++++++++++++++++++++++++
 sklearn/plot/tests/__init__.py     |  0
 sklearn/plot/tests/test_heatmap.py | 24 ++++++++++
 sklearn/setup.py                   |  2 +
 5 files changed, 102 insertions(+)
 create mode 100644 sklearn/plot/__init__.py
 create mode 100644 sklearn/plot/_heatmap.py
 create mode 100644 sklearn/plot/tests/__init__.py
 create mode 100644 sklearn/plot/tests/test_heatmap.py

diff --git a/sklearn/plot/__init__.py b/sklearn/plot/__init__.py
new file mode 100644
index 0000000000000..7cff0ad0ee943
--- /dev/null
+++ b/sklearn/plot/__init__.py
@@ -0,0 +1,3 @@
+from ._heatmap import plot_heatmap
+
+__all__ = ["plot_heatmap"]
diff --git a/sklearn/plot/_heatmap.py b/sklearn/plot/_heatmap.py
new file mode 100644
index 0000000000000..92a38d3bc8104
--- /dev/null
+++ b/sklearn/plot/_heatmap.py
@@ -0,0 +1,73 @@
+import numpy as np
+
+
+def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
+                 yticklabels=None, cmap=None, vmin=None, vmax=None, ax=None,
+                 fmt="{:.2f}"):
+    """Plot a matrix as heatmap with explicit numbers.
+
+    Parameters
+    ----------
+    values : ndarray
+        Two-dimensional array to visualize.
+
+    xlabel : string, default=""
+        Label for the x-axis.
+
+    ylabel : string, default=""
+        Label for the y-axis.
+
+    xticklabels : list of string or None, default=None
+        Tick labels for the x-axis.
+
+    yticklabels : list of string or None, default=None
+        Tick labels for the y-axis
+
+    cmap : string or colormap
+        Matpotlib colormap to use.
+
+    vmin : int, float or None
+        Minimum clipping value.
+
+    vmax : int, float or None
+        Maximum clipping value.
+
+    ax : axes object or None
+        Matplotlib axes object to plot into. If None, the current axes are
+        used.
+
+    fmt : string, default="{:.2f}"
+        Format string to convert value to text.
+    """
+    import matplotlib.pyplot as plt
+    if ax is None:
+        ax = plt.gca()
+    img = ax.pcolor(values, cmap=cmap, vmin=None, vmax=None)
+    # this will allow us to access the pixel values:
+    img.update_scalarmappable()
+    ax.set_xlabel(xlabel)
+    ax.set_ylabel(ylabel)
+    if xticklabels is None:
+        xticklabels = [""] * values.shape[1]
+    if yticklabels is None:
+        yticklabels = [""] * values.shape[0]
+
+    ax.xaxis.set_ticks_position('bottom')
+
+    # +.5 makes the ticks centered on the pixels
+    ax.set_xticks(np.arange(values.shape[1]) + .5)
+    ax.set_xticklabels(xticklabels, ha="center")
+    ax.set_yticks(np.arange(values.shape[0]) + .5)
+    ax.set_yticklabels(yticklabels, va="center")
+    ax.set_aspect(1)
+
+    for p, color, value in zip(img.get_paths(), img.get_facecolors(),
+                               img.get_array()):
+        x, y = p.vertices[:-2, :].mean(0)
+        if np.mean(color[:3]) > 0.5:
+            # pixel bright: use black for number
+            c = 'k'
+        else:
+            c = 'w'
+        ax.text(x, y, fmt.format(value), color=c, ha="center", va="center")
+    return ax
diff --git a/sklearn/plot/tests/__init__.py b/sklearn/plot/tests/__init__.py
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/sklearn/plot/tests/test_heatmap.py b/sklearn/plot/tests/test_heatmap.py
new file mode 100644
index 0000000000000..fb27bdf0ae9be
--- /dev/null
+++ b/sklearn/plot/tests/test_heatmap.py
@@ -0,0 +1,24 @@
+from sklearn.plot import plot_heatmap
+from sklearn.utils.testing import SkipTest
+import numpy as np
+
+
+def test_heatmap():
+    try:
+        import matplotlib
+    except ImportError:
+        raise SkipTest("Not testing plot_heatmap, matplotlib not installed.")
+
+    import matplotlib.pyplot as plt
+
+    with matplotlib.rc_context(rc={'backend': 'Agg', 'interactive': False}):
+        plt.figure()
+        rng = np.random.RandomState(0)
+        X = rng.normal(size=(10, 5))
+        # use mixture of default values and keyword args
+        plot_heatmap(X, ylabel="y-axis",
+                     xticklabels=["a", "b", "c", "d", "efgh"],
+                     cmap="Paired", ax=plt.gca())
+
+        plt.draw()
+        plt.close()
diff --git a/sklearn/setup.py b/sklearn/setup.py
index 8adbbd9d49132..5bae68530cedc 100644
--- a/sklearn/setup.py
+++ b/sklearn/setup.py
@@ -36,6 +36,8 @@ def configuration(parent_package='', top_path=None):
     config.add_subpackage('model_selection/tests')
     config.add_subpackage('neural_network')
     config.add_subpackage('neural_network/tests')
+    config.add_subpackage('plot')
+    config.add_subpackage('plot/tests')
     config.add_subpackage('preprocessing')
     config.add_subpackage('preprocessing/tests')
     config.add_subpackage('semi_supervised')

From b03874ca44255a98d118bb029ba421c6db35b9d6 Mon Sep 17 00:00:00 2001
From: Andreas Mueller <t3kcit@gmail.com>
Date: Mon, 19 Dec 2016 11:43:56 -0500
Subject: [PATCH 48/97] add plotting module to the API docs

---
 doc/modules/classes.rst | 19 +++++++++++++++++++
 1 file changed, 19 insertions(+)

diff --git a/doc/modules/classes.rst b/doc/modules/classes.rst
index 5977e2f01a9b3..583c63a37343b 100644
--- a/doc/modules/classes.rst
+++ b/doc/modules/classes.rst
@@ -1395,6 +1395,25 @@ Low-level methods
    utils.validation.column_or_1d
    utils.validation.has_fit_parameter
 
+:mod:`sklearn.plot`: Plotting functions
+=======================================
+
+.. automodule:: sklearn.plot
+   :no-members:
+   :no-inherited-members:
+
+This module is experimental. Use at your own risk.
+Use of this module requires the matplotlib library.
+
+.. currentmodule:: sklearn.plot
+
+.. autosummary::
+   :toctree: generated/
+   :template: function.rst
+
+   plot_heatmap
+
+
 Recently deprecated
 ===================
 

From c6919612bc667f1820200f2fae365638391817c0 Mon Sep 17 00:00:00 2001
From: Andreas Mueller <t3kcit@gmail.com>
Date: Mon, 19 Dec 2016 11:50:21 -0500
Subject: [PATCH 49/97] simplify plot_confusion_matrix example

---
 .../model_selection/plot_confusion_matrix.py  | 28 ++++---------------
 1 file changed, 6 insertions(+), 22 deletions(-)

diff --git a/examples/model_selection/plot_confusion_matrix.py b/examples/model_selection/plot_confusion_matrix.py
index 4b7c360988071..5625fa6d4b59f 100644
--- a/examples/model_selection/plot_confusion_matrix.py
+++ b/examples/model_selection/plot_confusion_matrix.py
@@ -24,15 +24,13 @@
 
 """
 
-print(__doc__)
-
-import itertools
 import numpy as np
 import matplotlib.pyplot as plt
 
 from sklearn import svm, datasets
 from sklearn.model_selection import train_test_split
 from sklearn.metrics import confusion_matrix
+from sklearn.plot import plot_heatmap
 
 # import some data to play with
 iris = datasets.load_iris()
@@ -59,29 +57,15 @@ def plot_confusion_matrix(cm, classes,
     """
     if normalize:
         cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]
-        print("Normalized confusion matrix")
-    else:
-        print('Confusion matrix, without normalization')
 
+    print(title)
     print(cm)
 
-    plt.imshow(cm, interpolation='nearest', cmap=cmap)
+    fmt = '{:.2f}' if normalize else '{:d}'
+    plot_heatmap(cm, xticklabels=classes, yticklabels=classes, cmap=cmap,
+                 xlabel="Predicted label", ylabel="True label", fmt=fmt)
+
     plt.title(title)
-    plt.colorbar()
-    tick_marks = np.arange(len(classes))
-    plt.xticks(tick_marks, classes, rotation=45)
-    plt.yticks(tick_marks, classes)
-
-    fmt = '.2f' if normalize else 'd'
-    thresh = cm.max() / 2.
-    for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):
-        plt.text(j, i, format(cm[i, j], fmt),
-                 horizontalalignment="center",
-                 color="white" if cm[i, j] > thresh else "black")
-
-    plt.tight_layout()
-    plt.ylabel('True label')
-    plt.xlabel('Predicted label')
 
 # Compute confusion matrix
 cnf_matrix = confusion_matrix(y_test, y_pred)

From f760d6689e662c77b69d3ef1baaecaad7cf87f6f Mon Sep 17 00:00:00 2001
From: Andreas Mueller <t3kcit@gmail.com>
Date: Mon, 19 Dec 2016 12:18:08 -0500
Subject: [PATCH 50/97] add normalizer support to heatmap, use heatmap when
 plotting gridsearch results

---
 examples/svm/plot_rbf_parameters.py | 26 ++++++++++++--------------
 sklearn/plot/_heatmap.py            | 18 +++++++++++++-----
 2 files changed, 25 insertions(+), 19 deletions(-)

diff --git a/examples/svm/plot_rbf_parameters.py b/examples/svm/plot_rbf_parameters.py
index 3a909b2b422bf..789589d54bcec 100644
--- a/examples/svm/plot_rbf_parameters.py
+++ b/examples/svm/plot_rbf_parameters.py
@@ -51,11 +51,11 @@
 
 Finally one can also observe that for some intermediate values of ``gamma`` we
 get equally performing models when ``C`` becomes very large: it is not
-necessary to regularize by limiting the number of support vectors. The radius of
-the RBF kernel alone acts as a good structural regularizer. In practice though
-it might still be interesting to limit the number of support vectors with a
-lower value of ``C`` so as to favor models that use less memory and that are
-faster to predict.
+necessary to regularize by limiting the number of support vectors. The radius
+of the RBF kernel alone acts as a good structural regularizer. In practice
+though it might still be interesting to limit the number of support vectors
+with a lower value of ``C`` so as to favor models that use less memory and that
+are faster to predict.
 
 We should also note that small differences in scores results from the random
 splits of the cross-validation procedure. Those spurious variations can be
@@ -65,7 +65,6 @@
 map.
 
 '''
-print(__doc__)
 
 import numpy as np
 import matplotlib.pyplot as plt
@@ -76,6 +75,9 @@
 from sklearn.datasets import load_iris
 from sklearn.model_selection import StratifiedShuffleSplit
 from sklearn.model_selection import GridSearchCV
+from sklearn.plot import plot_heatmap
+
+print(__doc__)
 
 
 # Utility function to move the midpoint of a colormap to be around
@@ -184,14 +186,10 @@ def __call__(self, value, clip=None):
 # interesting range while not brutally collapsing all the low score values to
 # the same color.
 
-plt.figure(figsize=(8, 6))
+plt.figure(figsize=(10, 10))
 plt.subplots_adjust(left=.2, right=0.95, bottom=0.15, top=0.95)
-plt.imshow(scores, interpolation='nearest', cmap=plt.cm.hot,
-           norm=MidpointNormalize(vmin=0.2, midpoint=0.92))
-plt.xlabel('gamma')
-plt.ylabel('C')
-plt.colorbar()
-plt.xticks(np.arange(len(gamma_range)), gamma_range, rotation=45)
-plt.yticks(np.arange(len(C_range)), C_range)
+plot_heatmap(scores, cmap=plt.cm.hot, xlabel="gamma", ylabel="C",
+             xticklabels=gamma_range, yticklabels=C_range,
+             norm=MidpointNormalize(vmin=0.2, midpoint=0.92))
 plt.title('Validation accuracy')
 plt.show()
diff --git a/sklearn/plot/_heatmap.py b/sklearn/plot/_heatmap.py
index 92a38d3bc8104..74aabfd82bb97 100644
--- a/sklearn/plot/_heatmap.py
+++ b/sklearn/plot/_heatmap.py
@@ -3,7 +3,7 @@
 
 def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
                  yticklabels=None, cmap=None, vmin=None, vmax=None, ax=None,
-                 fmt="{:.2f}"):
+                 fmt="{:.2f}", xtickrotation=45, norm=None):
     """Plot a matrix as heatmap with explicit numbers.
 
     Parameters
@@ -38,25 +38,33 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
 
     fmt : string, default="{:.2f}"
         Format string to convert value to text.
+
+    xtickrotation : float, default=45
+        Rotation of the xticklabels.
+
+    norm : matplotlib normalizer
+        Normalizer passed to pcolor
     """
     import matplotlib.pyplot as plt
     if ax is None:
         ax = plt.gca()
-    img = ax.pcolor(values, cmap=cmap, vmin=None, vmax=None)
+    img = ax.pcolor(values, cmap=cmap, vmin=None, vmax=None, norm=norm)
     # this will allow us to access the pixel values:
     img.update_scalarmappable()
     ax.set_xlabel(xlabel)
     ax.set_ylabel(ylabel)
+
+    ax.set_xlim(0, values.shape[1])
+    ax.set_ylim(0, values.shape[0])
+
     if xticklabels is None:
         xticklabels = [""] * values.shape[1]
     if yticklabels is None:
         yticklabels = [""] * values.shape[0]
 
-    ax.xaxis.set_ticks_position('bottom')
-
     # +.5 makes the ticks centered on the pixels
     ax.set_xticks(np.arange(values.shape[1]) + .5)
-    ax.set_xticklabels(xticklabels, ha="center")
+    ax.set_xticklabels(xticklabels, ha="center", rotation=xtickrotation)
     ax.set_yticks(np.arange(values.shape[0]) + .5)
     ax.set_yticklabels(yticklabels, va="center")
     ax.set_aspect(1)

From f04c07992eca066899f7adce5efc00224e9d20a8 Mon Sep 17 00:00:00 2001
From: Andreas Mueller <t3kcit@gmail.com>
Date: Mon, 19 Dec 2016 14:37:42 -0500
Subject: [PATCH 51/97] add plot to __all__

---
 sklearn/__init__.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/sklearn/__init__.py b/sklearn/__init__.py
index 5f2278d1c8c37..b5e24514248a1 100644
--- a/sklearn/__init__.py
+++ b/sklearn/__init__.py
@@ -143,7 +143,7 @@ def config_context(**new_config):
                'mixture', 'model_selection', 'multiclass', 'multioutput',
                'naive_bayes', 'neighbors', 'neural_network', 'pipeline',
                'preprocessing', 'random_projection', 'semi_supervised',
-               'svm', 'tree', 'discriminant_analysis',
+               'svm', 'tree', 'discriminant_analysis', 'plot',
                # Non-modules:
                'clone']
 

From 661a1ff33eccdce0d2b8b2adc485857e010e8c45 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Sun, 11 Jun 2017 16:34:13 -0400
Subject: [PATCH 52/97] using pcolormesh + alignment fix

---
 sklearn/plot/_heatmap.py | 8 +++++++-
 1 file changed, 7 insertions(+), 1 deletion(-)

diff --git a/sklearn/plot/_heatmap.py b/sklearn/plot/_heatmap.py
index 74aabfd82bb97..c6e11b92060e7 100644
--- a/sklearn/plot/_heatmap.py
+++ b/sklearn/plot/_heatmap.py
@@ -45,10 +45,11 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
     norm : matplotlib normalizer
         Normalizer passed to pcolor
     """
+
     import matplotlib.pyplot as plt
     if ax is None:
         ax = plt.gca()
-    img = ax.pcolor(values, cmap=cmap, vmin=None, vmax=None, norm=norm)
+    img = ax.pcolormesh(values, cmap=cmap, vmin=None, vmax=None, norm=norm)
     # this will allow us to access the pixel values:
     img.update_scalarmappable()
     ax.set_xlabel(xlabel)
@@ -72,6 +73,11 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
     for p, color, value in zip(img.get_paths(), img.get_facecolors(),
                                img.get_array()):
         x, y = p.vertices[:-2, :].mean(0)
+
+        # adjusting x and y for alignment:
+        x = x - 1./6
+        y = y + 1./6
+
         if np.mean(color[:3]) > 0.5:
             # pixel bright: use black for number
             c = 'k'

From d28400b67f5b33b78f2505368b4525165f73ee7b Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 20 Jun 2017 00:19:16 -0400
Subject: [PATCH 53/97] added confusion_matrix plot file

---
 sklearn/plot/_confusion_matrix.py | 68 +++++++++++++++++++++++++++++++
 1 file changed, 68 insertions(+)
 create mode 100644 sklearn/plot/_confusion_matrix.py

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
new file mode 100644
index 0000000000000..1e77bbdc883fc
--- /dev/null
+++ b/sklearn/plot/_confusion_matrix.py
@@ -0,0 +1,68 @@
+import numpy as np
+from sklearn.plot import plot_heatmap
+
+
+def plot_confusion_matrix(values, classes, normalize=True,
+                          xlabel="Predicted Label", ylabel="True Label",
+                          title='Confusion matrix', cmap=None, vmin=None,
+                          vmax=None, ax=None, fmt="{:.2f}",
+                          xtickrotation=45, norm=None):
+    """Print and plot the confusion matrix. Normalization can be applied by
+    setting `normalize=True`.
+
+    Parameters
+    ----------
+    values : ndarray
+        Two-dimensional array to visualize.
+
+    classes : list of strings
+        The list of classes represented in the two-dimensional input array.
+
+    normalize : boolean, default=True
+        If True, the confusion matrix will be normalized by row.
+
+    xlabel : string, default=""
+        Label for the x-axis.
+
+    ylabel : string, default=""
+        Label for the y-axis.
+
+    cmap : string or colormap
+        Matpotlib colormap to use.
+
+    vmin : int, float or None
+        Minimum clipping value.
+
+    vmax : int, float or None
+        Maximum clipping value.
+
+    ax : axes object or None
+        Matplotlib axes object to plot into. If None, the current axes are
+        used.
+
+    fmt : string, default="{:.2f}"
+        Format string to convert value to text. This will be ignored if
+        normalize argument is False.
+
+    xtickrotation : float, default=45
+        Rotation of the xticklabels.
+
+    norm : matplotlib normalizer
+        Normalizer passed to pcolor
+    """
+
+    import matplotlib.pyplot as plt
+
+    if normalize:
+        values = values.astype('float') / values.sum(axis=1)[:, np.newaxis]
+
+    print(title)
+    print(values)
+
+    fmt = fmt if normalize else '{:d}'
+
+    plot_heatmap(values, xticklabels=classes, yticklabels=classes, cmap=cmap,
+                 xlabel=xlabel, ylabel=ylabel, vmin=vmin, vmax=vmax, ax=ax,
+                 fmt=fmt, xtickrotation=xtickrotation, norm=norm)
+
+    plt.title(title)

From 434e9ec423ec8cebaaee4f9f8d13d75519dac2a8 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 20 Jun 2017 00:19:48 -0400
Subject: [PATCH 54/97] made vmin and vmax pass through in heatplot plot
 function

---
 sklearn/plot/_heatmap.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/sklearn/plot/_heatmap.py b/sklearn/plot/_heatmap.py
index c6e11b92060e7..fb92a981ba14c 100644
--- a/sklearn/plot/_heatmap.py
+++ b/sklearn/plot/_heatmap.py
@@ -49,7 +49,7 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
     import matplotlib.pyplot as plt
     if ax is None:
         ax = plt.gca()
-    img = ax.pcolormesh(values, cmap=cmap, vmin=None, vmax=None, norm=norm)
+    img = ax.pcolormesh(values, cmap=cmap, vmin=vmin, vmax=vmax, norm=norm)
     # this will allow us to access the pixel values:
     img.update_scalarmappable()
     ax.set_xlabel(xlabel)

From 46c58b20992a863e28f98ec899c23f86cba21759 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 20 Jun 2017 00:40:59 -0400
Subject: [PATCH 55/97] modified documentation plot_confusion_matrix

---
 sklearn/plot/_confusion_matrix.py | 21 ++++++++++++---------
 1 file changed, 12 insertions(+), 9 deletions(-)

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index 1e77bbdc883fc..a2ae4b7a630e1 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -2,13 +2,13 @@
 from sklearn.plot import plot_heatmap
 
 
-def plot_confusion_matrix(values, classes, normalize=True,
+def plot_confusion_matrix(values, classes, normalize=False,
                           xlabel="Predicted Label", ylabel="True Label",
                           title='Confusion matrix', cmap=None, vmin=None,
                           vmax=None, ax=None, fmt="{:.2f}",
                           xtickrotation=45, norm=None):
-    """Print and plot the confusion matrix. Normalization can be applied by
-    setting `normalize=True`.
+    """Print and plot the confusion matrix as a heatmap. Normalization can be
+    applied by setting `normalize=True`.
 
     Parameters
     ----------
@@ -18,23 +18,25 @@ def plot_confusion_matrix(values, classes, normalize=True,
     classes : list of strings
         The list of classes represented in the two-dimensional input array.
 
-    normalize : boolean, default=True
+    normalize : boolean, default=False
         If True, the confusion matrix will be normalized by row.
 
-    xlabel : string, default=""
+    xlabel : string, default="Predicted Label"
         Label for the x-axis.
 
-    ylabel : string, default=""
+    ylabel : string, default="True Label"
         Label for the y-axis.
 
     cmap : string or colormap
         Matpotlib colormap to use.
 
     vmin : int, float or None
-        Minimum clipping value.
+        Minimum clipping value. This argument will be passed on to the
+        pcolormesh function from matplotlib used to generate the heatmap.
 
     vmax : int, float or None
-        Maximum clipping value.
+        Maximum clipping value. This argument will be passed on to the
+        pcolormesh function from matplotlib used to generate the heatmap.
 
     ax : axes object or None
         Matplotlib axes object to plot into. If None, the current axes are
@@ -48,7 +50,8 @@ def plot_confusion_matrix(values, classes, normalize=True,
         Rotation of the xticklabels.
 
     norm : matplotlib normalizer
-        Normalizer passed to pcolor
+        Normalizer passed to pcolormesh function from matplotlib used to
+        generate the heatmap.
     """
 
     import matplotlib.pyplot as plt

From d815fd33ad4fe7b4fbeac4f6f33972ff206a3010 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 20 Jun 2017 00:42:13 -0400
Subject: [PATCH 56/97] updated __init__.py file to include confusion matrix
 plot

---
 sklearn/plot/__init__.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/sklearn/plot/__init__.py b/sklearn/plot/__init__.py
index 7cff0ad0ee943..fec45fff52116 100644
--- a/sklearn/plot/__init__.py
+++ b/sklearn/plot/__init__.py
@@ -1,3 +1,4 @@
 from ._heatmap import plot_heatmap
+from ._confusion_matrix import plot_confusion_matrix
 
-__all__ = ["plot_heatmap"]
+__all__ = ["plot_heatmap", "plot_confusion_matrix"]

From c4828e245987f25d77fdf5e789dc116ddea909d2 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 20 Jun 2017 00:43:08 -0400
Subject: [PATCH 57/97] plot confusion matrix example updated to use new
 function

---
 .../model_selection/plot_confusion_matrix.py  | 29 ++++---------------
 1 file changed, 5 insertions(+), 24 deletions(-)

diff --git a/examples/model_selection/plot_confusion_matrix.py b/examples/model_selection/plot_confusion_matrix.py
index 5625fa6d4b59f..95df220d242a3 100644
--- a/examples/model_selection/plot_confusion_matrix.py
+++ b/examples/model_selection/plot_confusion_matrix.py
@@ -30,7 +30,7 @@
 from sklearn import svm, datasets
 from sklearn.model_selection import train_test_split
 from sklearn.metrics import confusion_matrix
-from sklearn.plot import plot_heatmap
+from sklearn.plot import plot_confusion_matrix
 
 # import some data to play with
 iris = datasets.load_iris()
@@ -46,27 +46,6 @@
 classifier = svm.SVC(kernel='linear', C=0.01)
 y_pred = classifier.fit(X_train, y_train).predict(X_test)
 
-
-def plot_confusion_matrix(cm, classes,
-                          normalize=False,
-                          title='Confusion matrix',
-                          cmap=plt.cm.Blues):
-    """
-    This function prints and plots the confusion matrix.
-    Normalization can be applied by setting `normalize=True`.
-    """
-    if normalize:
-        cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]
-
-    print(title)
-    print(cm)
-
-    fmt = '{:.2f}' if normalize else '{:d}'
-    plot_heatmap(cm, xticklabels=classes, yticklabels=classes, cmap=cmap,
-                 xlabel="Predicted label", ylabel="True label", fmt=fmt)
-
-    plt.title(title)
-
 # Compute confusion matrix
 cnf_matrix = confusion_matrix(y_test, y_pred)
 np.set_printoptions(precision=2)
@@ -74,11 +53,13 @@ def plot_confusion_matrix(cm, classes,
 # Plot non-normalized confusion matrix
 plt.figure()
 plot_confusion_matrix(cnf_matrix, classes=class_names,
-                      title='Confusion matrix, without normalization')
+                      title='Confusion matrix, without normalization',
+                      cmap=plt.cm.Blues)
 
 # Plot normalized confusion matrix
 plt.figure()
 plot_confusion_matrix(cnf_matrix, classes=class_names, normalize=True,
-                      title='Normalized confusion matrix')
+                      title='Normalized confusion matrix',
+                      cmap=plt.cm.Blues)
 
 plt.show()

From aa28778c0b053143bbdf5daee0c548d332c002f2 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 20 Jun 2017 01:49:42 -0400
Subject: [PATCH 58/97] make matrix diagonal

---
 sklearn/plot/_heatmap.py | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/sklearn/plot/_heatmap.py b/sklearn/plot/_heatmap.py
index fb92a981ba14c..cfa0645c86e18 100644
--- a/sklearn/plot/_heatmap.py
+++ b/sklearn/plot/_heatmap.py
@@ -50,6 +50,7 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
     if ax is None:
         ax = plt.gca()
     img = ax.pcolormesh(values, cmap=cmap, vmin=vmin, vmax=vmax, norm=norm)
+
     # this will allow us to access the pixel values:
     img.update_scalarmappable()
     ax.set_xlabel(xlabel)
@@ -84,4 +85,9 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
         else:
             c = 'w'
         ax.text(x, y, fmt.format(value), color=c, ha="center", va="center")
+
+    # Invert the y-axis so that the matrix looks like a diagonal matrix and
+    # not anti-diagonal matrix
+    ax.invert_yaxis()
+
     return ax

From 1f36c0f372e068b15aa812edf2f677ccc63509d3 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 20 Jun 2017 02:42:55 -0400
Subject: [PATCH 59/97] modify documentation

---
 sklearn/plot/_confusion_matrix.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index a2ae4b7a630e1..36579f68a1ab5 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -27,6 +27,9 @@ def plot_confusion_matrix(values, classes, normalize=False,
     ylabel : string, default="True Label"
         Label for the y-axis.
 
+    title : string, default="Confusion matrix"
+        Title for the heatmap.
+
     cmap : string or colormap
         Matpotlib colormap to use.
 

From 2e5f141e7ea041e4fa03b4959e78b8df48495b57 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 20 Jun 2017 02:43:45 -0400
Subject: [PATCH 60/97] adding grid search results plotting function.

---
 sklearn/plot/__init__.py            |  3 +-
 sklearn/plot/_gridsearch_results.py | 79 +++++++++++++++++++++++++++++
 2 files changed, 81 insertions(+), 1 deletion(-)
 create mode 100644 sklearn/plot/_gridsearch_results.py

diff --git a/sklearn/plot/__init__.py b/sklearn/plot/__init__.py
index fec45fff52116..c63653af62156 100644
--- a/sklearn/plot/__init__.py
+++ b/sklearn/plot/__init__.py
@@ -1,4 +1,5 @@
 from ._heatmap import plot_heatmap
 from ._confusion_matrix import plot_confusion_matrix
+from ._gridsearch_results import plot_gridsearch_results
 
-__all__ = ["plot_heatmap", "plot_confusion_matrix"]
+__all__ = ["plot_heatmap", "plot_confusion_matrix", "plot_gridsearch_results"]
diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
new file mode 100644
index 0000000000000..7f671e8932977
--- /dev/null
+++ b/sklearn/plot/_gridsearch_results.py
@@ -0,0 +1,79 @@
+import numpy as np
+from sklearn.plot import plot_heatmap
+
+
+def plot_gridsearch_results(cv_results, param_grid, metric='mean_test_score',
+                            xlabel=None, ylabel=None,
+                            title='Grid Search Results', cmap=None,
+                            vmin=None, vmax=None, ax=None, fmt="{:.2f}",
+                            xtickrotation=45, norm=None):
+    """Print and plot the confusion matrix as a heatmap. Normalization can be
+    applied by setting `normalize=True`.
+
+    Parameters
+    ----------
+    cv_results : dict of numpy (masked) ndarrays
+        The cv_results_ attribute of the GridSearchCV object.
+
+    param_grid : dict
+        A dictionary with keys as the two parameters searched and values
+        as a list of their respective values searched.
+
+    xlabel : string, default=None
+        Label for the x-axis. If None, the first key of the param_grid will
+        be used as the xlabel.
+
+    ylabel : string, default=None
+        Label for the y-axis. If None, the second key of the param_grid will
+        be used as the ylabel.
+
+    metric : string, default="mean_test_score"
+        The metric from the GridSearchCV results to display.
+
+    title : string, default="Grid Search Results"
+        Title for the heatmap.
+
+    cmap : string or colormap
+        Matpotlib colormap to use.
+
+    vmin : int, float or None
+        Minimum clipping value. This argument will be passed on to the
+        pcolormesh function from matplotlib used to generate the heatmap.
+
+    vmax : int, float or None
+        Maximum clipping value. This argument will be passed on to the
+        pcolormesh function from matplotlib used to generate the heatmap.
+
+    ax : axes object or None
+        Matplotlib axes object to plot into. If None, the current axes are
+        used.
+
+    fmt : string, default="{:.2f}"
+        Format string to convert value to text.
+
+    xtickrotation : float, default=45
+        Rotation of the xticklabels.
+
+    norm : matplotlib normalizer
+        Normalizer passed to pcolormesh function from matplotlib used to
+        generate the heatmap.
+    """
+
+    import matplotlib.pyplot as plt
+
+    parameter1, parameter2 = param_grid.keys()
+    parameter1_values = param_grid[parameter1]
+    parameter2_values = param_grid[parameter2]
+
+    scores = cv_results[metric].reshape(len(parameter1_values),
+                                        len(parameter2_values))
+
+    xlabel = parameter1 if xlabel is None else xlabel
+    ylabel = parameter2 if ylabel is None else ylabel
+
+    plot_heatmap(scores, cmap=plt.cm.hot, xlabel=xlabel, ylabel=ylabel,
+                 xticklabels=parameter1_values, yticklabels=parameter2_values,
+                 ax=ax, norm=norm)
+
+    plt.title(title)
+    plt.show()

From 1cf525d880888e45186be073f9e3a1303367b222 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 20 Jun 2017 02:44:33 -0400
Subject: [PATCH 61/97] modified examples/svm/plot_rbf_parameters.py with new
 function

---
 examples/svm/plot_rbf_parameters.py | 12 ++++--------
 1 file changed, 4 insertions(+), 8 deletions(-)

diff --git a/examples/svm/plot_rbf_parameters.py b/examples/svm/plot_rbf_parameters.py
index 789589d54bcec..2760c2259a112 100644
--- a/examples/svm/plot_rbf_parameters.py
+++ b/examples/svm/plot_rbf_parameters.py
@@ -75,7 +75,7 @@
 from sklearn.datasets import load_iris
 from sklearn.model_selection import StratifiedShuffleSplit
 from sklearn.model_selection import GridSearchCV
-from sklearn.plot import plot_heatmap
+from sklearn.plot import plot_gridsearch_results
 
 print(__doc__)
 
@@ -174,9 +174,6 @@ def __call__(self, value, clip=None):
     plt.yticks(())
     plt.axis('tight')
 
-scores = grid.cv_results_['mean_test_score'].reshape(len(C_range),
-                                                     len(gamma_range))
-
 # Draw heatmap of the validation accuracy as a function of gamma and C
 #
 # The score are encoded as colors with the hot colormap which varies from dark
@@ -188,8 +185,7 @@ def __call__(self, value, clip=None):
 
 plt.figure(figsize=(10, 10))
 plt.subplots_adjust(left=.2, right=0.95, bottom=0.15, top=0.95)
-plot_heatmap(scores, cmap=plt.cm.hot, xlabel="gamma", ylabel="C",
-             xticklabels=gamma_range, yticklabels=C_range,
-             norm=MidpointNormalize(vmin=0.2, midpoint=0.92))
-plt.title('Validation accuracy')
+plot_gridsearch_results(grid.cv_results_, param_grid=param_grid,
+                        title="Validation accuracy", cmap=plt.cm.hot,
+                        norm=MidpointNormalize(vmin=0.2, midpoint=0.92))
 plt.show()

From 6279ff904112027a7e52ce94e52335976b0f410a Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 20 Jun 2017 17:50:21 -0400
Subject: [PATCH 62/97] removed printing confusion matrix

---
 sklearn/plot/_confusion_matrix.py | 5 +----
 1 file changed, 1 insertion(+), 4 deletions(-)

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index 36579f68a1ab5..183fe0a45b033 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -7,7 +7,7 @@ def plot_confusion_matrix(values, classes, normalize=False,
                           title='Confusion matrix', cmap=None, vmin=None,
                           vmax=None, ax=None, fmt="{:.2f}",
                           xtickrotation=45, norm=None):
-    """Print and plot the confusion matrix as a heatmap. Normalization can be
+    """Plot the confusion matrix as a heatmap. Normalization can be
     applied by setting `normalize=True`.
 
     Parameters
@@ -62,9 +62,6 @@ def plot_confusion_matrix(values, classes, normalize=False,
     if normalize:
         values = values.astype('float') / values.sum(axis=1)[:, np.newaxis]
 
-    print(title)
-    print(values)
-
     fmt = fmt if normalize else '{:d}'
 
     plot_heatmap(values, xticklabels=classes, yticklabels=classes, cmap=cmap,

From e450fe52897df3c931ee5b862f309f2df8c10ec7 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 20 Jun 2017 18:01:50 -0400
Subject: [PATCH 63/97] remove param_grid argument

---
 sklearn/plot/_gridsearch_results.py | 39 ++++++++++++++++-------------
 1 file changed, 22 insertions(+), 17 deletions(-)

diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index 7f671e8932977..fd3919436eaa4 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -2,7 +2,7 @@
 from sklearn.plot import plot_heatmap
 
 
-def plot_gridsearch_results(cv_results, param_grid, metric='mean_test_score',
+def plot_gridsearch_results(cv_results, metric='mean_test_score',
                             xlabel=None, ylabel=None,
                             title='Grid Search Results', cmap=None,
                             vmin=None, vmax=None, ax=None, fmt="{:.2f}",
@@ -15,10 +15,6 @@ def plot_gridsearch_results(cv_results, param_grid, metric='mean_test_score',
     cv_results : dict of numpy (masked) ndarrays
         The cv_results_ attribute of the GridSearchCV object.
 
-    param_grid : dict
-        A dictionary with keys as the two parameters searched and values
-        as a list of their respective values searched.
-
     xlabel : string, default=None
         Label for the x-axis. If None, the first key of the param_grid will
         be used as the xlabel.
@@ -61,19 +57,28 @@ def plot_gridsearch_results(cv_results, param_grid, metric='mean_test_score',
 
     import matplotlib.pyplot as plt
 
-    parameter1, parameter2 = param_grid.keys()
-    parameter1_values = param_grid[parameter1]
-    parameter2_values = param_grid[parameter2]
+    params = sorted(cv_results['params'][0].keys())
+
+    if len(params) == 1:
+        # plot a line chart
+        pass
+    elif len(params) == 2:
+        parameter1_values = np.unique(cv_results['param_%s' % params[0]])
+        parameter2_values = np.unique(cv_results['param_%s' % params[1]])
 
-    scores = cv_results[metric].reshape(len(parameter1_values),
-                                        len(parameter2_values))
+        scores = cv_results[metric].reshape(len(parameter1_values),
+                                            len(parameter2_values))
 
-    xlabel = parameter1 if xlabel is None else xlabel
-    ylabel = parameter2 if ylabel is None else ylabel
+        xlabel = params[0] if xlabel is None else xlabel
+        ylabel = params[1] if ylabel is None else ylabel
 
-    plot_heatmap(scores, cmap=plt.cm.hot, xlabel=xlabel, ylabel=ylabel,
-                 xticklabels=parameter1_values, yticklabels=parameter2_values,
-                 ax=ax, norm=norm)
+        plot_heatmap(scores, cmap=plt.cm.hot, xlabel=xlabel, ylabel=ylabel,
+                     xticklabels=parameter1_values,
+                     yticklabels=parameter2_values,
+                     ax=ax, norm=norm)
 
-    plt.title(title)
-    plt.show()
+        plt.title(title)
+        plt.show()
+    else:
+        # print error statement
+        pass

From cf789febe13debf66e7c8bd37df1ae09d46117ef Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Wed, 21 Jun 2017 11:12:36 -0400
Subject: [PATCH 64/97] adding cases for nparams 1,2, more

---
 sklearn/plot/_gridsearch_results.py | 42 ++++++++++++++++++++++++-----
 1 file changed, 36 insertions(+), 6 deletions(-)

diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index fd3919436eaa4..68ca542a67728 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -24,7 +24,8 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
         be used as the ylabel.
 
     metric : string, default="mean_test_score"
-        The metric from the GridSearchCV results to display.
+        The metric from the GridSearchCV results to display. This is ignored
+        if only 1 parameter is used in grid search.
 
     title : string, default="Grid Search Results"
         Title for the heatmap.
@@ -58,11 +59,38 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
     import matplotlib.pyplot as plt
 
     params = sorted(cv_results['params'][0].keys())
+    nparams = len(params)
+
+    if nparams == 1:
+        param = params[0]
+        param_range = sorted(cv_results['param_%s' % param])
+        train_scores_mean = cv_results['mean_train_score']
+        train_scores_std = cv_results['mean_train_std']
+        test_scores_mean = cv_results['mean_test_score']
+        test_scores_std = cv_results['mean_test_std']
+
+        lw = 2
+        plt.semilogx(param_range, train_scores_mean,
+                     label="Training score",
+                     color="darkorange", lw=lw)
+        plt.fill_between(param_range, train_scores_mean - train_scores_std,
+                         train_scores_mean + train_scores_std, alpha=0.2,
+                         color="darkorange", lw=lw)
+
+        plt.semilogx(param_range, test_scores_mean,
+                     label="Cross-validation score",
+                     color="navy", lw=lw)
+        plt.fill_between(param_range, test_scores_mean - test_scores_std,
+                         test_scores_mean + test_scores_std, alpha=0.2,
+                         color="navy", lw=lw)
 
-    if len(params) == 1:
-        # plot a line chart
-        pass
-    elif len(params) == 2:
+        plt.title(title)
+        plt.xlabel(param)
+        ylabel = "Score" if ylabel is None else ylabel
+        plt.ylabel(ylabel)
+        plt.show()
+
+    elif nparams == 2:
         parameter1_values = np.unique(cv_results['param_%s' % params[0]])
         parameter2_values = np.unique(cv_results['param_%s' % params[1]])
 
@@ -79,6 +107,8 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
 
         plt.title(title)
         plt.show()
+
     else:
-        # print error statement
+        raise ValueError('Plot functions supports upto 2 parameters in grid'
+                         'search, got {0}.'.format(nparams))
         pass

From f6bdc2b9919ad15669a4e714a6b80eabef2c0a02 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Wed, 21 Jun 2017 12:00:56 -0400
Subject: [PATCH 65/97] minor fixes

---
 sklearn/plot/_gridsearch_results.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index 68ca542a67728..2719e38c3a52b 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -65,9 +65,9 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
         param = params[0]
         param_range = sorted(cv_results['param_%s' % param])
         train_scores_mean = cv_results['mean_train_score']
-        train_scores_std = cv_results['mean_train_std']
+        train_scores_std = cv_results['std_train_score']
         test_scores_mean = cv_results['mean_test_score']
-        test_scores_std = cv_results['mean_test_std']
+        test_scores_std = cv_results['std_test_score']
 
         lw = 2
         plt.semilogx(param_range, train_scores_mean,
@@ -86,6 +86,7 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
 
         plt.title(title)
         plt.xlabel(param)
+        plt.legend()
         ylabel = "Score" if ylabel is None else ylabel
         plt.ylabel(ylabel)
         plt.show()

From 96622fafc0ddc10647a485102cc8eaefcb1636e3 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Wed, 21 Jun 2017 15:38:04 -0400
Subject: [PATCH 66/97] fixed typo

---
 sklearn/plot/_gridsearch_results.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index 2719e38c3a52b..55ce25bd2f425 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -110,6 +110,6 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
         plt.show()
 
     else:
-        raise ValueError('Plot functions supports upto 2 parameters in grid'
+        raise ValueError('Plot function supports upto 2 parameters in grid'
                          'search, got {0}.'.format(nparams))
         pass

From 5adcafe22fd768f66013452bb0aafe575daf8c3f Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Wed, 21 Jun 2017 15:38:38 -0400
Subject: [PATCH 67/97] adding tests for confusion matrix and grid search plots

---
 sklearn/plot/tests/test_heatmap.py | 85 ++++++++++++++++++++++++++++++
 1 file changed, 85 insertions(+)

diff --git a/sklearn/plot/tests/test_heatmap.py b/sklearn/plot/tests/test_heatmap.py
index fb27bdf0ae9be..668f82b2b138f 100644
--- a/sklearn/plot/tests/test_heatmap.py
+++ b/sklearn/plot/tests/test_heatmap.py
@@ -1,5 +1,11 @@
 from sklearn.plot import plot_heatmap
+from sklearn.plot import plot_confusion_matrix
+from sklearn.plot import plot_gridsearch_results
+from sklearn.datasets import load_iris
+from sklearn.model_selection import GridSearchCV
+from sklearn.svm import SVC
 from sklearn.utils.testing import SkipTest
+from sklearn.utils.testing import assert_raises
 import numpy as np
 
 
@@ -22,3 +28,82 @@ def test_heatmap():
 
         plt.draw()
         plt.close()
+
+
+def test_confusion_matrix():
+    try:
+        import matplotlib
+    except ImportError:
+        raise SkipTest("Not testing plot_heatmap, matplotlib not installed.")
+
+    import matplotlib.pyplot as plt
+
+    with matplotlib.rc_context(rc={'backend': 'Agg', 'interactive': False}):
+        plt.figure()
+        cnf_matrix = np.random.randomint(1, 10, size=(2, 2))
+
+        # use mixture of default values and keyword args
+        plot_confusion_matrix(cnf_matrix, classes=["dummay1", "dummy2"],
+                              cmap="Paired", ax=plt.gca())
+
+        plt.draw()
+        plt.close()
+
+
+def test_gridsearch_results():
+    try:
+        import matplotlib
+    except ImportError:
+        raise SkipTest("Not testing plot_heatmap, matplotlib not installed.")
+
+    import matplotlib.pyplot as plt
+
+    iris = load_iris()
+    X = iris.data
+    y = iris.target
+
+    # We only keep the first two features in X and sub-sample the dataset to
+    # keep only 2 classes and make it a binary classification problem.
+
+    X_2d = X[:, :2]
+    X_2d = X_2d[y > 0]
+    y_2d = y[y > 0]
+    y_2d -= 1
+
+    # Define parameters:
+    C_range = np.logspace(-2, 10, 2)
+    gamma_range = np.logspace(-9, 3, 2)
+    tol_range = [1e-3, 1e-4]
+
+    # Test 1D case:
+    param_grid = dict(gamma=gamma_range)
+    grid = GridSearchCV(SVC(), param_grid=param_grid, cv=3)
+    grid.fit(X, y)
+
+    with matplotlib.rc_context(rc={'backend': 'Agg', 'interactive': False}):
+        plt.figure()
+        plot_gridsearch_results(grid.cv_results_)
+        plt.draw()
+        plt.close()
+
+    # Test 2D case:
+    param_grid = dict(gamma=gamma_range, C=C_range)
+    grid = GridSearchCV(SVC(), param_grid=param_grid, cv=3)
+    grid.fit(X, y)
+
+    with matplotlib.rc_context(rc={'backend': 'Agg', 'interactive': False}):
+        plt.figure()
+        plot_gridsearch_results(grid.cv_results_)
+        plt.draw()
+        plt.close()
+
+    # Test 3D case:
+    param_grid = dict(gamma=gamma_range, C=C_range, tol=tol_range)
+    grid = GridSearchCV(SVC(), param_grid=param_grid, cv=3)
+    grid.fit(X, y)
+
+    with matplotlib.rc_context(rc={'backend': 'Agg', 'interactive': False}):
+        plt.figure()
+        assert_raises(ValueError, plot_gridsearch_results, grid.cv_results_)
+        plt.draw()
+        plt.close()

From f4675d725c65dd502b8816bd0d505142c37852eb Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Wed, 21 Jun 2017 17:26:01 -0400
Subject: [PATCH 68/97] adding test case for normalized

---
 sklearn/plot/tests/test_heatmap.py | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

diff --git a/sklearn/plot/tests/test_heatmap.py b/sklearn/plot/tests/test_heatmap.py
index 668f82b2b138f..5a199e23e24d7 100644
--- a/sklearn/plot/tests/test_heatmap.py
+++ b/sklearn/plot/tests/test_heatmap.py
@@ -42,10 +42,15 @@ def test_confusion_matrix():
         plt.figure()
         cnf_matrix = np.random.randomint(1, 10, size=(2, 2))
 
-        # use mixture of default values and keyword args
+        # plot un-normalized matrix
         plot_confusion_matrix(cnf_matrix, classes=["dummay1", "dummy2"],
                               cmap="Paired", ax=plt.gca())
 
+        # plot normalized matrix
+        plot_confusion_matrix(cnf_matrix, normalize=True,
+                              classes=["dummay1", "dummy2"],
+                              cmap="Paired", ax=plt.gca())
+
         plt.draw()
         plt.close()
 

From bf76105182afb0bd84a1324d44c345bcce8b7bb5 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Wed, 21 Jun 2017 17:28:41 -0400
Subject: [PATCH 69/97] updated doc files

---
 doc/modules/classes.rst | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/doc/modules/classes.rst b/doc/modules/classes.rst
index 583c63a37343b..967f6d0b4cf02 100644
--- a/doc/modules/classes.rst
+++ b/doc/modules/classes.rst
@@ -1403,7 +1403,8 @@ Low-level methods
    :no-inherited-members:
 
 This module is experimental. Use at your own risk.
-Use of this module requires the matplotlib library.
+Use of this module requires the matplotlib library,
+version 1.5 or later (preferably 2.0).
 
 .. currentmodule:: sklearn.plot
 
@@ -1412,6 +1413,8 @@ Use of this module requires the matplotlib library.
    :template: function.rst
 
    plot_heatmap
+   plot_confusion_matrix
+   plot_gridsearch_results
 
 
 Recently deprecated

From 11c4006abcac76b4796d35a0edc1a272cb999fac Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Thu, 29 Jun 2017 14:30:46 -0400
Subject: [PATCH 70/97] modifying doc

---
 doc/modules/classes.rst | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/doc/modules/classes.rst b/doc/modules/classes.rst
index 967f6d0b4cf02..d359249ec38e9 100644
--- a/doc/modules/classes.rst
+++ b/doc/modules/classes.rst
@@ -1404,7 +1404,7 @@ Low-level methods
 
 This module is experimental. Use at your own risk.
 Use of this module requires the matplotlib library,
-version 1.5 or later (preferably 2.0).
+version 1.5 or later.
 
 .. currentmodule:: sklearn.plot
 

From b48617ccb70d83928d513653375d5872f09dad14 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 4 Jul 2017 11:36:32 -0400
Subject: [PATCH 71/97] doc fix

---
 sklearn/plot/_gridsearch_results.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index 55ce25bd2f425..587ff2ae81106 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -7,8 +7,9 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
                             title='Grid Search Results', cmap=None,
                             vmin=None, vmax=None, ax=None, fmt="{:.2f}",
                             xtickrotation=45, norm=None):
-    """Print and plot the confusion matrix as a heatmap. Normalization can be
-    applied by setting `normalize=True`.
+    """Plot the grid search results as a line chart for 1D search and heatmap
+    for a 2D search. This function will not work if grid-search has more than
+    2 parameters in the search space.
 
     Parameters
     ----------

From 05e86a8102eacf9fa8f632ee433672c942d37bfd Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 4 Jul 2017 11:37:35 -0400
Subject: [PATCH 72/97] spell fix, make_blobs instead of iris, split checks
 into 3 functions

---
 sklearn/plot/tests/test_heatmap.py | 60 ++++++++++++++++++++----------
 1 file changed, 41 insertions(+), 19 deletions(-)

diff --git a/sklearn/plot/tests/test_heatmap.py b/sklearn/plot/tests/test_heatmap.py
index 5a199e23e24d7..7ff7b85ca827c 100644
--- a/sklearn/plot/tests/test_heatmap.py
+++ b/sklearn/plot/tests/test_heatmap.py
@@ -1,7 +1,7 @@
 from sklearn.plot import plot_heatmap
 from sklearn.plot import plot_confusion_matrix
 from sklearn.plot import plot_gridsearch_results
-from sklearn.datasets import load_iris
+from sklearn.datasets import make_blobs
 from sklearn.model_selection import GridSearchCV
 from sklearn.svm import SVC
 from sklearn.utils.testing import SkipTest
@@ -43,7 +43,7 @@ def test_confusion_matrix():
         cnf_matrix = np.random.randomint(1, 10, size=(2, 2))
 
         # plot un-normalized matrix
-        plot_confusion_matrix(cnf_matrix, classes=["dummay1", "dummy2"],
+        plot_confusion_matrix(cnf_matrix, classes=["dummy1", "dummy2"],
                               cmap="Paired", ax=plt.gca())
 
         # plot normalized matrix
@@ -55,7 +55,7 @@ def test_confusion_matrix():
         plt.close()
 
 
-def test_gridsearch_results():
+def test_gridsearch_results_1d():
     try:
         import matplotlib
     except ImportError:
@@ -63,25 +63,14 @@ def test_gridsearch_results():
 
     import matplotlib.pyplot as plt
 
-    iris = load_iris()
-    X = iris.data
-    y = iris.target
-
-    # We only keep the first two features in X and sub-sample the dataset to
-    # keep only 2 classes and make it a binary classification problem.
-
-    X_2d = X[:, :2]
-    X_2d = X_2d[y > 0]
-    y_2d = y[y > 0]
-    y_2d -= 1
+    X, y = make_blobs(n_samples=20, centers=2, n_features=3,
+                      random_state=0)
 
     # Define parameters:
     C_range = np.logspace(-2, 10, 2)
-    gamma_range = np.logspace(-9, 3, 2)
-    tol_range = [1e-3, 1e-4]
 
     # Test 1D case:
-    param_grid = dict(gamma=gamma_range)
+    param_grid = dict(C=C_range)
     grid = GridSearchCV(SVC(), param_grid=param_grid, cv=3)
     grid.fit(X, y)
 
@@ -91,7 +80,23 @@ def test_gridsearch_results():
         plt.draw()
         plt.close()
 
-    # Test 2D case:
+
+def test_gridsearch_results_2d():
+    try:
+        import matplotlib
+    except ImportError:
+        raise SkipTest("Not testing plot_heatmap, matplotlib not installed.")
+
+    import matplotlib.pyplot as plt
+
+    X, y = make_blobs(n_samples=20, centers=2, n_features=3,
+                      random_state=0)
+
+    # Define parameters:
+    C_range = np.logspace(-2, 10, 2)
+    gamma_range = np.logspace(-9, 3, 2)
+
+    # Test 1D case:
     param_grid = dict(gamma=gamma_range, C=C_range)
     grid = GridSearchCV(SVC(), param_grid=param_grid, cv=3)
     grid.fit(X, y)
@@ -102,7 +107,24 @@ def test_gridsearch_results():
         plt.draw()
         plt.close()
 
-    # Test 3D case:
+
+def test_gridsearch_results_3d():
+    try:
+        import matplotlib
+    except ImportError:
+        raise SkipTest("Not testing plot_heatmap, matplotlib not installed.")
+
+    import matplotlib.pyplot as plt
+
+    X, y = make_blobs(n_samples=20, centers=2, n_features=3,
+                      random_state=0)
+
+    # Define parameters:
+    C_range = np.logspace(-2, 10, 2)
+    gamma_range = np.logspace(-9, 3, 2)
+    tol_range = [1e-3, 1e-4]
+
+    # Test 1D case:
     param_grid = dict(gamma=gamma_range, C=C_range, tol=tol_range)
     grid = GridSearchCV(SVC(), param_grid=param_grid, cv=3)
     grid.fit(X, y)

From 1f17578b46b354f57ea1b85e98433ee6d70a1039 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 4 Jul 2017 13:43:08 -0400
Subject: [PATCH 73/97] fixed parameter in examples

---
 examples/svm/plot_rbf_parameters.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/examples/svm/plot_rbf_parameters.py b/examples/svm/plot_rbf_parameters.py
index 2760c2259a112..b5e923b7ee937 100644
--- a/examples/svm/plot_rbf_parameters.py
+++ b/examples/svm/plot_rbf_parameters.py
@@ -185,7 +185,7 @@ def __call__(self, value, clip=None):
 
 plt.figure(figsize=(10, 10))
 plt.subplots_adjust(left=.2, right=0.95, bottom=0.15, top=0.95)
-plot_gridsearch_results(grid.cv_results_, param_grid=param_grid,
-                        title="Validation accuracy", cmap=plt.cm.hot,
+plot_gridsearch_results(grid.cv_results_, title="Validation accuracy",
+                        cmap=plt.cm.hot,
                         norm=MidpointNormalize(vmin=0.2, midpoint=0.92))
 plt.show()

From 4aa485b5cbbc9fe738b168c084d480623c6fb3fa Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 4 Jul 2017 16:36:36 -0400
Subject: [PATCH 74/97] modified travis files

---
 .travis.yml                   | 14 ++++++++++++--
 build_tools/travis/install.sh | 12 ++++++++++++
 2 files changed, 24 insertions(+), 2 deletions(-)

diff --git a/.travis.yml b/.travis.yml
index 4022f78aa0928..413c78f250fbb 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -43,8 +43,18 @@ matrix:
     - env: DISTRIB="conda" PYTHON_VERSION="3.6.2" INSTALL_MKL="true"
            NUMPY_VERSION="1.13.1" SCIPY_VERSION="0.19.1" PANDAS_VERSION="0.20.3"
            CYTHON_VERSION="0.26.1" PYAMG_VERSION="3.3.2" COVERAGE=true
-           CHECK_PYTEST_SOFT_DEPENDENCY="true"
-      if: type != cron
+           CHECK_PYTEST_SOFT_DEPENDENCY="true" MATPLOTLIB_VERSION="2.0.2"
+    # This environment use pytest to run the tests. It uses the newest
+    # supported Anaconda release (4.4.0). It also runs tests requiring Pandas.
+    - env: USE_PYTEST="true" DISTRIB="conda" PYTHON_VERSION="3.6.1"
+           INSTALL_MKL="true" NUMPY_VERSION="1.12.1" SCIPY_VERSION="0.19.0"
+           PANDAS_VERSION="0.20.1" CYTHON_VERSION="0.25.2"
+           MATPLOTLIB_VERSION="2.0.2"
+    # This environment tests the newest supported Anaconda release (4.4.0)
+    # It also runs tests requiring Pandas.
+    - env: DISTRIB="conda" PYTHON_VERSION="3.6.1" INSTALL_MKL="true"
+           NUMPY_VERSION="1.12.1" SCIPY_VERSION="0.19.0" PANDAS_VERSION="0.20.1"
+           CYTHON_VERSION="0.25.2" MATPLOTLIB_VERSION="2.0.2" COVERAGE=true
     # flake8 linting on diff wrt common ancestor with upstream/master
     - env: RUN_FLAKE8="true" SKIP_TESTS="true"
            DISTRIB="conda" PYTHON_VERSION="3.5" INSTALL_MKL="true"
diff --git a/build_tools/travis/install.sh b/build_tools/travis/install.sh
index 76cd3221cb009..d2a6aa9da4fbe 100755
--- a/build_tools/travis/install.sh
+++ b/build_tools/travis/install.sh
@@ -43,8 +43,20 @@ if [[ "$DISTRIB" == "conda" ]]; then
 
     if [[ "$INSTALL_MKL" == "true" ]]; then
         TO_INSTALL="$TO_INSTALL mkl"
+        conda create -n testenv --yes python=$PYTHON_VERSION pip nose pytest \
+            numpy=$NUMPY_VERSION scipy=$SCIPY_VERSION \
+            matplotlib=$MATPLOTLIB_VERSION \
+            mkl cython=$CYTHON_VERSION \
+            ${PANDAS_VERSION+pandas=$PANDAS_VERSION}
+            
     else
         TO_INSTALL="$TO_INSTALL nomkl"
+        conda create -n testenv --yes python=$PYTHON_VERSION pip nose pytest \
+            numpy=$NUMPY_VERSION scipy=$SCIPY_VERSION \
+            matplotlib=$MATPLOTLIB_VERSION \
+            nomkl cython=$CYTHON_VERSION \
+            ${PANDAS_VERSION+pandas=$PANDAS_VERSION}
+
     fi
 
     if [[ -n "$PANDAS_VERSION" ]]; then

From 9b9bca6141dc4fa765ba2bba271026dab52c788f Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 4 Jul 2017 18:02:38 -0400
Subject: [PATCH 75/97] explicitly imported random module functions

---
 sklearn/plot/tests/test_heatmap.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/sklearn/plot/tests/test_heatmap.py b/sklearn/plot/tests/test_heatmap.py
index 7ff7b85ca827c..b110375adfc1b 100644
--- a/sklearn/plot/tests/test_heatmap.py
+++ b/sklearn/plot/tests/test_heatmap.py
@@ -7,6 +7,8 @@
 from sklearn.utils.testing import SkipTest
 from sklearn.utils.testing import assert_raises
 import numpy as np
+from numpy.random import (RandomState,
+                          randomint)
 
 
 def test_heatmap():
@@ -19,7 +21,7 @@ def test_heatmap():
 
     with matplotlib.rc_context(rc={'backend': 'Agg', 'interactive': False}):
         plt.figure()
-        rng = np.random.RandomState(0)
+        rng = RandomState(0)
         X = rng.normal(size=(10, 5))
         # use mixture of default values and keyword args
         plot_heatmap(X, ylabel="y-axis",
@@ -40,7 +42,7 @@ def test_confusion_matrix():
 
     with matplotlib.rc_context(rc={'backend': 'Agg', 'interactive': False}):
         plt.figure()
-        cnf_matrix = np.random.randomint(1, 10, size=(2, 2))
+        cnf_matrix = randomint(1, 10, size=(2, 2))
 
         # plot un-normalized matrix
         plot_confusion_matrix(cnf_matrix, classes=["dummy1", "dummy2"],

From 129ff24570b439e7e3f8b8b8271d45f5bd1303c5 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 4 Jul 2017 18:03:35 -0400
Subject: [PATCH 76/97] install matplotlib only if secret variable specified in
 build matrix

---
 build_tools/travis/install.sh | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/build_tools/travis/install.sh b/build_tools/travis/install.sh
index d2a6aa9da4fbe..64fc28740c5fc 100755
--- a/build_tools/travis/install.sh
+++ b/build_tools/travis/install.sh
@@ -45,15 +45,14 @@ if [[ "$DISTRIB" == "conda" ]]; then
         TO_INSTALL="$TO_INSTALL mkl"
         conda create -n testenv --yes python=$PYTHON_VERSION pip nose pytest \
             numpy=$NUMPY_VERSION scipy=$SCIPY_VERSION \
-            matplotlib=$MATPLOTLIB_VERSION \
             mkl cython=$CYTHON_VERSION \
-            ${PANDAS_VERSION+pandas=$PANDAS_VERSION}
+            ${PANDAS_VERSION+pandas=$PANDAS_VERSION} \
+            ${MATPLOTLIB_VERSION+matplotlib=$MATPLOTLIB_VERSION}
             
     else
         TO_INSTALL="$TO_INSTALL nomkl"
         conda create -n testenv --yes python=$PYTHON_VERSION pip nose pytest \
             numpy=$NUMPY_VERSION scipy=$SCIPY_VERSION \
-            matplotlib=$MATPLOTLIB_VERSION \
             nomkl cython=$CYTHON_VERSION \
             ${PANDAS_VERSION+pandas=$PANDAS_VERSION}
 

From bc736433cabf410f8f7d8a88462d1ee9e9e3f3e8 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Wed, 5 Jul 2017 09:20:15 -0400
Subject: [PATCH 77/97] randint correction

---
 sklearn/plot/tests/test_heatmap.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/sklearn/plot/tests/test_heatmap.py b/sklearn/plot/tests/test_heatmap.py
index b110375adfc1b..8ea3d97ef99aa 100644
--- a/sklearn/plot/tests/test_heatmap.py
+++ b/sklearn/plot/tests/test_heatmap.py
@@ -8,7 +8,7 @@
 from sklearn.utils.testing import assert_raises
 import numpy as np
 from numpy.random import (RandomState,
-                          randomint)
+                          randint)
 
 
 def test_heatmap():
@@ -42,7 +42,7 @@ def test_confusion_matrix():
 
     with matplotlib.rc_context(rc={'backend': 'Agg', 'interactive': False}):
         plt.figure()
-        cnf_matrix = randomint(1, 10, size=(2, 2))
+        cnf_matrix = randint(1, 10, size=(2, 2))
 
         # plot un-normalized matrix
         plot_confusion_matrix(cnf_matrix, classes=["dummy1", "dummy2"],

From caebd38453fa6d45457d5c367d6c0b9f6f9f1dfa Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Wed, 5 Jul 2017 19:56:44 -0400
Subject: [PATCH 78/97] y_pred and y_true as input in place of matrix

---
 sklearn/plot/_confusion_matrix.py  | 21 ++++++++++++++++-----
 sklearn/plot/tests/test_heatmap.py |  7 ++++---
 2 files changed, 20 insertions(+), 8 deletions(-)

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index 183fe0a45b033..648fad9ce82e2 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -1,23 +1,32 @@
 import numpy as np
+from sklearn.metrics import confusion_matrix
 from sklearn.plot import plot_heatmap
 
 
-def plot_confusion_matrix(values, classes, normalize=False,
+def plot_confusion_matrix(y_true, y_pred, classes, sample_weights=None,
+                          normalize=False,
                           xlabel="Predicted Label", ylabel="True Label",
                           title='Confusion matrix', cmap=None, vmin=None,
                           vmax=None, ax=None, fmt="{:.2f}",
                           xtickrotation=45, norm=None):
-    """Plot the confusion matrix as a heatmap. Normalization can be
-    applied by setting `normalize=True`.
+    """Plot the confusion matrix as a heatmap. A confusion matrix is computed
+    using `y_true`, `y_pred` and `sample_weights` arguments. Normalization
+    can be applied by setting `normalize=True`.
 
     Parameters
     ----------
-    values : ndarray
-        Two-dimensional array to visualize.
+    y_true : array, shape = [n_samples]
+        Ground truth (correct) target values.
+
+    y_pred : array, shape = [n_samples]
+        Estimated targets as returned by a classifier.
 
     classes : list of strings
         The list of classes represented in the two-dimensional input array.
 
+    sample_weight : array-like of shape = [n_samples], optional
+        Sample weights used to calculate the confusion matrix
+
     normalize : boolean, default=False
         If True, the confusion matrix will be normalized by row.
 
@@ -59,6 +68,8 @@ def plot_confusion_matrix(values, classes, normalize=False,
 
     import matplotlib.pyplot as plt
 
+    values = confusion_matrix(y_true, y_pred, sample_weights=sample_weights)
+
     if normalize:
         values = values.astype('float') / values.sum(axis=1)[:, np.newaxis]
 
diff --git a/sklearn/plot/tests/test_heatmap.py b/sklearn/plot/tests/test_heatmap.py
index 8ea3d97ef99aa..51bf5a4873353 100644
--- a/sklearn/plot/tests/test_heatmap.py
+++ b/sklearn/plot/tests/test_heatmap.py
@@ -42,14 +42,15 @@ def test_confusion_matrix():
 
     with matplotlib.rc_context(rc={'backend': 'Agg', 'interactive': False}):
         plt.figure()
-        cnf_matrix = randint(1, 10, size=(2, 2))
+        array1 = randint(1, 3, size=20)
+        array2 = randint(1, 3, size=20)
 
         # plot un-normalized matrix
-        plot_confusion_matrix(cnf_matrix, classes=["dummy1", "dummy2"],
+        plot_confusion_matrix(array1, array2, classes=["dummy1", "dummy2"],
                               cmap="Paired", ax=plt.gca())
 
         # plot normalized matrix
-        plot_confusion_matrix(cnf_matrix, normalize=True,
+        plot_confusion_matrix(array1, array2, normalize=True,
                               classes=["dummay1", "dummy2"],
                               cmap="Paired", ax=plt.gca())
 

From 0f124f155452f1e4abd5d39dddf579dd50df8b33 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Thu, 6 Jul 2017 12:08:19 -0400
Subject: [PATCH 79/97] fixed typo

---
 sklearn/plot/_confusion_matrix.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index 648fad9ce82e2..803ebbdfdc1d5 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -3,7 +3,7 @@
 from sklearn.plot import plot_heatmap
 
 
-def plot_confusion_matrix(y_true, y_pred, classes, sample_weights=None,
+def plot_confusion_matrix(y_true, y_pred, classes, sample_weight=None,
                           normalize=False,
                           xlabel="Predicted Label", ylabel="True Label",
                           title='Confusion matrix', cmap=None, vmin=None,
@@ -68,7 +68,7 @@ def plot_confusion_matrix(y_true, y_pred, classes, sample_weights=None,
 
     import matplotlib.pyplot as plt
 
-    values = confusion_matrix(y_true, y_pred, sample_weights=sample_weights)
+    values = confusion_matrix(y_true, y_pred, sample_weight=sample_weight)
 
     if normalize:
         values = values.astype('float') / values.sum(axis=1)[:, np.newaxis]

From 5e5f741e45f65b61e6e0859bdf1d767faa108229 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Fri, 7 Jul 2017 13:13:55 -0400
Subject: [PATCH 80/97] fixed example

---
 examples/model_selection/plot_confusion_matrix.py | 7 ++-----
 1 file changed, 2 insertions(+), 5 deletions(-)

diff --git a/examples/model_selection/plot_confusion_matrix.py b/examples/model_selection/plot_confusion_matrix.py
index 95df220d242a3..29853b9412681 100644
--- a/examples/model_selection/plot_confusion_matrix.py
+++ b/examples/model_selection/plot_confusion_matrix.py
@@ -29,7 +29,6 @@
 
 from sklearn import svm, datasets
 from sklearn.model_selection import train_test_split
-from sklearn.metrics import confusion_matrix
 from sklearn.plot import plot_confusion_matrix
 
 # import some data to play with
@@ -46,19 +45,17 @@
 classifier = svm.SVC(kernel='linear', C=0.01)
 y_pred = classifier.fit(X_train, y_train).predict(X_test)
 
-# Compute confusion matrix
-cnf_matrix = confusion_matrix(y_test, y_pred)
 np.set_printoptions(precision=2)
 
 # Plot non-normalized confusion matrix
 plt.figure()
-plot_confusion_matrix(cnf_matrix, classes=class_names,
+plot_confusion_matrix(y_test, y_pred, classes=class_names,
                       title='Confusion matrix, without normalization',
                       cmap=plt.cm.Blues)
 
 # Plot normalized confusion matrix
 plt.figure()
-plot_confusion_matrix(cnf_matrix, classes=class_names, normalize=True,
+plot_confusion_matrix(y_test, y_pred, classes=class_names, normalize=True,
                       title='Normalized confusion matrix',
                       cmap=plt.cm.Blues)
 

From 2e3eec98203d6ded04e13ce341062d949c459e3a Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 25 Jul 2017 19:20:48 -0400
Subject: [PATCH 81/97] making classes optional

---
 sklearn/plot/_confusion_matrix.py  | 17 +++++++++++++++--
 sklearn/plot/tests/test_heatmap.py | 12 ++++++++++++
 2 files changed, 27 insertions(+), 2 deletions(-)

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index 803ebbdfdc1d5..e06af3c9c0d43 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -1,9 +1,10 @@
 import numpy as np
 from sklearn.metrics import confusion_matrix
 from sklearn.plot import plot_heatmap
+from sklearn.utils.multiclass import unique_labels
 
 
-def plot_confusion_matrix(y_true, y_pred, classes, sample_weight=None,
+def plot_confusion_matrix(y_true, y_pred, classes=None, sample_weight=None,
                           normalize=False,
                           xlabel="Predicted Label", ylabel="True Label",
                           title='Confusion matrix', cmap=None, vmin=None,
@@ -21,8 +22,10 @@ def plot_confusion_matrix(y_true, y_pred, classes, sample_weight=None,
     y_pred : array, shape = [n_samples]
         Estimated targets as returned by a classifier.
 
-    classes : list of strings
+    classes : list of strings, optional (default=None)
         The list of classes represented in the two-dimensional input array.
+        If not passed in function call, the classes will be infered from
+        y_true and y_pred
 
     sample_weight : array-like of shape = [n_samples], optional
         Sample weights used to calculate the confusion matrix
@@ -68,6 +71,16 @@ def plot_confusion_matrix(y_true, y_pred, classes, sample_weight=None,
 
     import matplotlib.pyplot as plt
 
+    unique_y = unique_labels(y_true, y_pred)
+
+    if classes is None:
+        classes = unique_y
+    else:
+        if not set(classes).issuperset(set(unique_y)):
+            raise ValueError("`classes=%s` are not a superset of the unique",
+                             "values of y_true and y_pred which are %s" %
+                             (classes, unique_y))
+
     values = confusion_matrix(y_true, y_pred, sample_weight=sample_weight)
 
     if normalize:
diff --git a/sklearn/plot/tests/test_heatmap.py b/sklearn/plot/tests/test_heatmap.py
index 51bf5a4873353..870263f421085 100644
--- a/sklearn/plot/tests/test_heatmap.py
+++ b/sklearn/plot/tests/test_heatmap.py
@@ -6,6 +6,7 @@
 from sklearn.svm import SVC
 from sklearn.utils.testing import SkipTest
 from sklearn.utils.testing import assert_raises
+from sklearn.utils.testing import assert_raise_message
 import numpy as np
 from numpy.random import (RandomState,
                           randint)
@@ -54,6 +55,17 @@ def test_confusion_matrix():
                               classes=["dummay1", "dummy2"],
                               cmap="Paired", ax=plt.gca())
 
+        # plot without passing classes explicitly
+        plot_confusion_matrix(array1, array2,
+                              cmap="Paired", ax=plt.gca())
+
+        # y having different value than classes should raise error
+        expected_msg = ("`classes=[1,2]` are not a superset of the unique",
+                        "values of y_true and y_pred which are [1,2,3]")
+        assert_raise_message(ValueError, expected_msg,
+                             plot_confusion_matrix, array1, array2,
+                             classes=[1, 2], ax=plt.gca())
+
         plt.draw()
         plt.close()
 

From 7f3336fd4be0bebd49e7727c53b8aa7b09cd554d Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Thu, 27 Jul 2017 12:38:42 -0400
Subject: [PATCH 82/97] some fixes

---
 sklearn/plot/_confusion_matrix.py   |  24 +++---
 sklearn/plot/_gridsearch_results.py | 109 ++++++++++++++++------------
 sklearn/plot/_heatmap.py            |   2 +-
 sklearn/plot/tests/test_heatmap.py  |   5 +-
 4 files changed, 79 insertions(+), 61 deletions(-)

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index e06af3c9c0d43..42fcf7f789172 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -23,9 +23,9 @@ def plot_confusion_matrix(y_true, y_pred, classes=None, sample_weight=None,
         Estimated targets as returned by a classifier.
 
     classes : list of strings, optional (default=None)
-        The list of classes represented in the two-dimensional input array.
-        If not passed in function call, the classes will be infered from
-        y_true and y_pred
+        The list of names of classes represented in the two-dimensional input
+        array. If not passed in function call, the classes will be infered
+        from y_true and y_pred
 
     sample_weight : array-like of shape = [n_samples], optional
         Sample weights used to calculate the confusion matrix
@@ -76,10 +76,11 @@ def plot_confusion_matrix(y_true, y_pred, classes=None, sample_weight=None,
     if classes is None:
         classes = unique_y
     else:
-        if not set(classes).issuperset(set(unique_y)):
-            raise ValueError("`classes=%s` are not a superset of the unique",
-                             "values of y_true and y_pred which are %s" %
-                             (classes, unique_y))
+        if len(classes) != len(unique_y):
+            raise ValueError("y_true and y_pred contain %d unique classes,"
+                             "which is not the same as %d"
+                             "classes found in `classes=%s` paramter" %
+                             (len(classes), len(unique_y), unique_y))
 
     values = confusion_matrix(y_true, y_pred, sample_weight=sample_weight)
 
@@ -88,8 +89,11 @@ def plot_confusion_matrix(y_true, y_pred, classes=None, sample_weight=None,
 
     fmt = fmt if normalize else '{:d}'
 
-    plot_heatmap(values, xticklabels=classes, yticklabels=classes, cmap=cmap,
-                 xlabel=xlabel, ylabel=ylabel, vmin=vmin, vmax=vmax, ax=ax,
-                 fmt=fmt, xtickrotation=xtickrotation, norm=norm)
+    img = plot_heatmap(values, xticklabels=classes, yticklabels=classes,
+                       cmap=cmap, xlabel=xlabel, ylabel=ylabel, vmin=vmin,
+                       vmax=vmax, ax=ax, fmt=fmt, xtickrotation=xtickrotation,
+                       norm=norm)
 
     plt.title(title)
+
+    return img
diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index 587ff2ae81106..56cf657f0f1cf 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -2,6 +2,58 @@
 from sklearn.plot import plot_heatmap
 
 
+def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title):
+    import matplotlib.pyplot as plt
+
+    param = params[0]
+    param_range = sorted(cv_results['param_%s' % param])
+    train_scores_mean = cv_results['mean_train_score']
+    train_scores_std = cv_results['std_train_score']
+    test_scores_mean = cv_results['mean_test_score']
+    test_scores_std = cv_results['std_test_score']
+
+    lw = 2
+    plt.semilogx(param_range, train_scores_mean,
+                 label="Training score",
+                 color="darkorange", lw=lw)
+    plt.fill_between(param_range, train_scores_mean - train_scores_std,
+                     train_scores_mean + train_scores_std, alpha=0.2,
+                     color="darkorange", lw=lw)
+
+    img = plt.semilogx(param_range, test_scores_mean,
+                       label="Cross-validation score",
+                       color="navy", lw=lw)
+    plt.fill_between(param_range, test_scores_mean - test_scores_std,
+                     test_scores_mean + test_scores_std, alpha=0.2,
+                     color="navy", lw=lw)
+
+    plt.xlabel(param)
+    plt.legend()
+    ylabel = "Score" if ylabel is None else ylabel
+    plt.ylabel(ylabel)
+    plt.title(title)
+    plt.show()
+    return img
+
+
+def _plot_2D_results(cv_results, params, metric, ax, xlabel, ylabel,
+                     title, norm):
+    import matplotlib.pyplot as plt
+
+    parameter1_values = np.unique(cv_results['param_%s' % params[0]])
+    parameter2_values = np.unique(cv_results['param_%s' % params[1]])
+
+    scores = cv_results[metric].reshape(len(parameter1_values),
+                                        len(parameter2_values))
+
+    img = plot_heatmap(scores, cmap=plt.cm.hot, xlabel=xlabel,
+                       ylabel=ylabel, xticklabels=parameter1_values,
+                       yticklabels=parameter2_values, ax=ax, norm=norm)
+    plt.title(title)
+    plt.show()
+    return img
+
+
 def plot_gridsearch_results(cv_results, metric='mean_test_score',
                             xlabel=None, ylabel=None,
                             title='Grid Search Results', cmap=None,
@@ -54,63 +106,24 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
 
     norm : matplotlib normalizer
         Normalizer passed to pcolormesh function from matplotlib used to
-        generate the heatmap.
+        generate the heatmap. This is ignored if only 1 parameter is used in
+        grid search.
     """
 
-    import matplotlib.pyplot as plt
-
     params = sorted(cv_results['params'][0].keys())
     nparams = len(params)
+    xlabel = params[0] if xlabel is None else xlabel
+    ylabel = params[1] if ylabel is None else ylabel
 
     if nparams == 1:
-        param = params[0]
-        param_range = sorted(cv_results['param_%s' % param])
-        train_scores_mean = cv_results['mean_train_score']
-        train_scores_std = cv_results['std_train_score']
-        test_scores_mean = cv_results['mean_test_score']
-        test_scores_std = cv_results['std_test_score']
-
-        lw = 2
-        plt.semilogx(param_range, train_scores_mean,
-                     label="Training score",
-                     color="darkorange", lw=lw)
-        plt.fill_between(param_range, train_scores_mean - train_scores_std,
-                         train_scores_mean + train_scores_std, alpha=0.2,
-                         color="darkorange", lw=lw)
-
-        plt.semilogx(param_range, test_scores_mean,
-                     label="Cross-validation score",
-                     color="navy", lw=lw)
-        plt.fill_between(param_range, test_scores_mean - test_scores_std,
-                         test_scores_mean + test_scores_std, alpha=0.2,
-                         color="navy", lw=lw)
-
-        plt.title(title)
-        plt.xlabel(param)
-        plt.legend()
-        ylabel = "Score" if ylabel is None else ylabel
-        plt.ylabel(ylabel)
-        plt.show()
+        img = _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title)
 
     elif nparams == 2:
-        parameter1_values = np.unique(cv_results['param_%s' % params[0]])
-        parameter2_values = np.unique(cv_results['param_%s' % params[1]])
-
-        scores = cv_results[metric].reshape(len(parameter1_values),
-                                            len(parameter2_values))
-
-        xlabel = params[0] if xlabel is None else xlabel
-        ylabel = params[1] if ylabel is None else ylabel
-
-        plot_heatmap(scores, cmap=plt.cm.hot, xlabel=xlabel, ylabel=ylabel,
-                     xticklabels=parameter1_values,
-                     yticklabels=parameter2_values,
-                     ax=ax, norm=norm)
-
-        plt.title(title)
-        plt.show()
+        img = _plot_2D_results(cv_results, params, metric, ax, xlabel,
+                               ylabel, title, norm)
 
     else:
         raise ValueError('Plot function supports upto 2 parameters in grid'
                          'search, got {0}.'.format(nparams))
-        pass
+
+    return img
diff --git a/sklearn/plot/_heatmap.py b/sklearn/plot/_heatmap.py
index cfa0645c86e18..8b0c51d2cf5b9 100644
--- a/sklearn/plot/_heatmap.py
+++ b/sklearn/plot/_heatmap.py
@@ -90,4 +90,4 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
     # not anti-diagonal matrix
     ax.invert_yaxis()
 
-    return ax
+    return img
diff --git a/sklearn/plot/tests/test_heatmap.py b/sklearn/plot/tests/test_heatmap.py
index 870263f421085..d135591f285d6 100644
--- a/sklearn/plot/tests/test_heatmap.py
+++ b/sklearn/plot/tests/test_heatmap.py
@@ -60,8 +60,9 @@ def test_confusion_matrix():
                               cmap="Paired", ax=plt.gca())
 
         # y having different value than classes should raise error
-        expected_msg = ("`classes=[1,2]` are not a superset of the unique",
-                        "values of y_true and y_pred which are [1,2,3]")
+        expected_msg = ("y_true and y_pred contain 3 unique classes, which is"
+                        "not the same as 2 classes found in `classes=[1,2]`"
+                        "paramter")
         assert_raise_message(ValueError, expected_msg,
                              plot_confusion_matrix, array1, array2,
                              classes=[1, 2], ax=plt.gca())

From 6be2a92895ac53c02f3f45794d9e22a67064b896 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Thu, 27 Jul 2017 13:31:50 -0400
Subject: [PATCH 83/97] fixed 1d case of grid_search_results

---
 sklearn/plot/_confusion_matrix.py   | 26 +++++-----
 sklearn/plot/_gridsearch_results.py | 74 +++++++++++++++++------------
 sklearn/plot/tests/test_heatmap.py  |  6 ++-
 3 files changed, 60 insertions(+), 46 deletions(-)

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index 42fcf7f789172..60df2fec50dc0 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -27,44 +27,44 @@ def plot_confusion_matrix(y_true, y_pred, classes=None, sample_weight=None,
         array. If not passed in function call, the classes will be infered
         from y_true and y_pred
 
-    sample_weight : array-like of shape = [n_samples], optional
+    sample_weight : array-like of shape = [n_samples], optional (default=None)
         Sample weights used to calculate the confusion matrix
 
-    normalize : boolean, default=False
+    normalize : boolean, optional (default=False)
         If True, the confusion matrix will be normalized by row.
 
-    xlabel : string, default="Predicted Label"
+    xlabel : string, optional (default="Predicted Label")
         Label for the x-axis.
 
-    ylabel : string, default="True Label"
+    ylabel : string, optional (default="True Label")
         Label for the y-axis.
 
-    title : string, default="Confusion matrix"
+    title : string, optional (default="Confusion matrix")
         Title for the heatmap.
 
-    cmap : string or colormap
-        Matpotlib colormap to use.
+    cmap : string or colormap, optional (default=None)
+        Matpotlib colormap to use. If None, plt.cm.hot will be used.
 
-    vmin : int, float or None
+    vmin : int, float or None, optional (default=None)
         Minimum clipping value. This argument will be passed on to the
         pcolormesh function from matplotlib used to generate the heatmap.
 
-    vmax : int, float or None
+    vmax : int, float or None, optional (default=None)
         Maximum clipping value. This argument will be passed on to the
         pcolormesh function from matplotlib used to generate the heatmap.
 
-    ax : axes object or None
+    ax : axes object or None, optional (default=None)
         Matplotlib axes object to plot into. If None, the current axes are
         used.
 
-    fmt : string, default="{:.2f}"
+    fmt : string, optional (default="{:.2f}")
         Format string to convert value to text. This will be ignored if
         normalize argument is False.
 
-    xtickrotation : float, default=45
+    xtickrotation : float, optional (default=45)
         Rotation of the xticklabels.
 
-    norm : matplotlib normalizer
+    norm : matplotlib normalizer, optional (default=None)
         Normalizer passed to pcolormesh function from matplotlib used to
         generate the heatmap.
     """
diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index 56cf657f0f1cf..f27c0d53d1925 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -2,7 +2,8 @@
 from sklearn.plot import plot_heatmap
 
 
-def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title):
+def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title,
+                     fmt, xtickrotation):
     import matplotlib.pyplot as plt
 
     param = params[0]
@@ -13,20 +14,23 @@ def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title):
     test_scores_std = cv_results['std_test_score']
 
     lw = 2
-    plt.semilogx(param_range, train_scores_mean,
-                 label="Training score",
-                 color="darkorange", lw=lw)
-    plt.fill_between(param_range, train_scores_mean - train_scores_std,
+    x_vales = range(len(param_range))
+    plt.plot(x_vales, train_scores_mean,
+             label="Training score",
+             color="darkorange", lw=lw)
+    plt.fill_between(x_vales, train_scores_mean - train_scores_std,
                      train_scores_mean + train_scores_std, alpha=0.2,
                      color="darkorange", lw=lw)
 
-    img = plt.semilogx(param_range, test_scores_mean,
-                       label="Cross-validation score",
-                       color="navy", lw=lw)
-    plt.fill_between(param_range, test_scores_mean - test_scores_std,
+    img = plt.plot(x_vales, test_scores_mean,
+                   label="Cross-validation score",
+                   color="navy", lw=lw)
+    plt.fill_between(x_vales, test_scores_mean - test_scores_std,
                      test_scores_mean + test_scores_std, alpha=0.2,
                      color="navy", lw=lw)
-
+    plt.xticks(x_vales, [fmt.format(x) for x in param_range],
+               rotation=xtickrotation)
+    xlabel = params[0] if xlabel is None else xlabel
     plt.xlabel(param)
     plt.legend()
     ylabel = "Score" if ylabel is None else ylabel
@@ -36,8 +40,9 @@ def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title):
     return img
 
 
-def _plot_2D_results(cv_results, params, metric, ax, xlabel, ylabel,
-                     title, norm):
+def _plot_2D_results(cv_results, params, metric, ax, xlabel,
+                     ylabel, title, cmap, vmin, vmax, fmt,
+                     xtickrotation, norm):
     import matplotlib.pyplot as plt
 
     parameter1_values = np.unique(cv_results['param_%s' % params[0]])
@@ -46,9 +51,16 @@ def _plot_2D_results(cv_results, params, metric, ax, xlabel, ylabel,
     scores = cv_results[metric].reshape(len(parameter1_values),
                                         len(parameter2_values))
 
-    img = plot_heatmap(scores, cmap=plt.cm.hot, xlabel=xlabel,
-                       ylabel=ylabel, xticklabels=parameter1_values,
-                       yticklabels=parameter2_values, ax=ax, norm=norm)
+    xlabel = params[0] if xlabel is None else xlabel
+    ylabel = params[1] if ylabel is None else ylabel
+
+    cmap = cmap if cmap is not None else plt.cm.hot
+
+    img = plot_heatmap(scores, xlabel=xlabel, ylabel=ylabel,
+                       xticklabels=parameter1_values,
+                       yticklabels=parameter2_values, cmap=cmap,
+                       vmin=vmin, vmax=vmax, fmt=fmt, ax=ax,
+                       xtickrotation=xtickrotation, norm=norm)
     plt.title(title)
     plt.show()
     return img
@@ -68,43 +80,43 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
     cv_results : dict of numpy (masked) ndarrays
         The cv_results_ attribute of the GridSearchCV object.
 
-    xlabel : string, default=None
+    xlabel : string, optional (default=None)
         Label for the x-axis. If None, the first key of the param_grid will
         be used as the xlabel.
 
-    ylabel : string, default=None
+    ylabel : string, optional (default=None)
         Label for the y-axis. If None, the second key of the param_grid will
         be used as the ylabel.
 
-    metric : string, default="mean_test_score"
+    metric : string, optional (default="mean_test_score")
         The metric from the GridSearchCV results to display. This is ignored
         if only 1 parameter is used in grid search.
 
-    title : string, default="Grid Search Results"
+    title : string, optional (default="Grid Search Results")
         Title for the heatmap.
 
-    cmap : string or colormap
-        Matpotlib colormap to use.
+    cmap : string or colormap, optional (default=None)
+        Matpotlib colormap to use. If None, plt.cm.hot will be used.
 
-    vmin : int, float or None
+    vmin : int, float or None, optional (default=None)
         Minimum clipping value. This argument will be passed on to the
         pcolormesh function from matplotlib used to generate the heatmap.
 
-    vmax : int, float or None
+    vmax : int, float or None, optional (default=None)
         Maximum clipping value. This argument will be passed on to the
         pcolormesh function from matplotlib used to generate the heatmap.
 
-    ax : axes object or None
+    ax : axes object or None, optional (default=None)
         Matplotlib axes object to plot into. If None, the current axes are
         used.
 
-    fmt : string, default="{:.2f}"
+    fmt : string, optional (default="{:.2f}")
         Format string to convert value to text.
 
-    xtickrotation : float, default=45
+    xtickrotation : float, optional (default=45)
         Rotation of the xticklabels.
 
-    norm : matplotlib normalizer
+    norm : matplotlib normalizer, optional (default=None)
         Normalizer passed to pcolormesh function from matplotlib used to
         generate the heatmap. This is ignored if only 1 parameter is used in
         grid search.
@@ -112,15 +124,15 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
 
     params = sorted(cv_results['params'][0].keys())
     nparams = len(params)
-    xlabel = params[0] if xlabel is None else xlabel
-    ylabel = params[1] if ylabel is None else ylabel
 
     if nparams == 1:
-        img = _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title)
+        img = _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title,
+                               fmt, xtickrotation)
 
     elif nparams == 2:
         img = _plot_2D_results(cv_results, params, metric, ax, xlabel,
-                               ylabel, title, norm)
+                               ylabel, title, cmap, vmin, vmax, fmt,
+                               xtickrotation, norm)
 
     else:
         raise ValueError('Plot function supports upto 2 parameters in grid'
diff --git a/sklearn/plot/tests/test_heatmap.py b/sklearn/plot/tests/test_heatmap.py
index d135591f285d6..1a89536c17202 100644
--- a/sklearn/plot/tests/test_heatmap.py
+++ b/sklearn/plot/tests/test_heatmap.py
@@ -5,7 +5,6 @@
 from sklearn.model_selection import GridSearchCV
 from sklearn.svm import SVC
 from sklearn.utils.testing import SkipTest
-from sklearn.utils.testing import assert_raises
 from sklearn.utils.testing import assert_raise_message
 import numpy as np
 from numpy.random import (RandomState,
@@ -147,6 +146,9 @@ def test_gridsearch_results_3d():
 
     with matplotlib.rc_context(rc={'backend': 'Agg', 'interactive': False}):
         plt.figure()
-        assert_raises(ValueError, plot_gridsearch_results, grid.cv_results_)
+        expected_msg = ('Plot function supports upto 2 parameters in grid'
+                        'search, got 3.')
+        assert_raise_message(ValueError, expected_msg,
+                             plot_gridsearch_results, grid.cv_results_)
         plt.draw()
         plt.close()

From 1c8db681b4a043d8fd6e23c9de8f20957482249a Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Thu, 27 Jul 2017 14:27:21 -0400
Subject: [PATCH 84/97] fixed confusion matrix test

---
 sklearn/plot/_confusion_matrix.py   | 8 ++++----
 sklearn/plot/_gridsearch_results.py | 2 +-
 sklearn/plot/tests/test_heatmap.py  | 8 ++++----
 3 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index 60df2fec50dc0..af0ffeda548b8 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -77,10 +77,10 @@ def plot_confusion_matrix(y_true, y_pred, classes=None, sample_weight=None,
         classes = unique_y
     else:
         if len(classes) != len(unique_y):
-            raise ValueError("y_true and y_pred contain %d unique classes,"
-                             "which is not the same as %d"
-                             "classes found in `classes=%s` paramter" %
-                             (len(classes), len(unique_y), unique_y))
+            raise ValueError("y_true and y_pred contain %d unique classes, "
+                             "which is not the same as %d "
+                             "classes found in `classes=%s` parameter" %
+                             (len(unique_y), len(classes), classes))
 
     values = confusion_matrix(y_true, y_pred, sample_weight=sample_weight)
 
diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index f27c0d53d1925..1c65ae49d8404 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -136,6 +136,6 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
 
     else:
         raise ValueError('Plot function supports upto 2 parameters in grid'
-                         'search, got {0}.'.format(nparams))
+                         'search, got %d.' % nparams)
 
     return img
diff --git a/sklearn/plot/tests/test_heatmap.py b/sklearn/plot/tests/test_heatmap.py
index 1a89536c17202..a50c20f384113 100644
--- a/sklearn/plot/tests/test_heatmap.py
+++ b/sklearn/plot/tests/test_heatmap.py
@@ -59,12 +59,12 @@ def test_confusion_matrix():
                               cmap="Paired", ax=plt.gca())
 
         # y having different value than classes should raise error
-        expected_msg = ("y_true and y_pred contain 3 unique classes, which is"
-                        "not the same as 2 classes found in `classes=[1,2]`"
-                        "paramter")
+        expected_msg = ("y_true and y_pred contain 2 unique classes, which is"
+                        " not the same as 3 classes found in "
+                        "`classes=[1, 2, 3]` parameter")
         assert_raise_message(ValueError, expected_msg,
                              plot_confusion_matrix, array1, array2,
-                             classes=[1, 2], ax=plt.gca())
+                             classes=[1, 2, 3], ax=plt.gca())
 
         plt.draw()
         plt.close()

From f737c01164fec77e91f3b43ae19378c25d3c0295 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Thu, 27 Jul 2017 14:54:53 -0400
Subject: [PATCH 85/97] working on axes not plt

---
 sklearn/plot/_gridsearch_results.py | 42 ++++++++++++++++-------------
 1 file changed, 23 insertions(+), 19 deletions(-)

diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index 1c65ae49d8404..e98bed94e2e23 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -5,6 +5,8 @@
 def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title,
                      fmt, xtickrotation):
     import matplotlib.pyplot as plt
+    if ax is None:
+        ax = plt.gca()
 
     param = params[0]
     param_range = sorted(cv_results['param_%s' % param])
@@ -15,27 +17,29 @@ def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title,
 
     lw = 2
     x_vales = range(len(param_range))
-    plt.plot(x_vales, train_scores_mean,
-             label="Training score",
-             color="darkorange", lw=lw)
-    plt.fill_between(x_vales, train_scores_mean - train_scores_std,
-                     train_scores_mean + train_scores_std, alpha=0.2,
-                     color="darkorange", lw=lw)
-
-    img = plt.plot(x_vales, test_scores_mean,
-                   label="Cross-validation score",
-                   color="navy", lw=lw)
-    plt.fill_between(x_vales, test_scores_mean - test_scores_std,
-                     test_scores_mean + test_scores_std, alpha=0.2,
-                     color="navy", lw=lw)
-    plt.xticks(x_vales, [fmt.format(x) for x in param_range],
-               rotation=xtickrotation)
+    ax.plot(x_vales, train_scores_mean,
+            label="Training score",
+            color="darkorange", lw=lw)
+    ax.fill_between(x_vales, train_scores_mean - train_scores_std,
+                    train_scores_mean + train_scores_std, alpha=0.2,
+                    color="darkorange", lw=lw)
+
+    img = ax.plot(x_vales, test_scores_mean,
+                  label="Cross-validation score",
+                  color="navy", lw=lw)
+    ax.fill_between(x_vales, test_scores_mean - test_scores_std,
+                    test_scores_mean + test_scores_std, alpha=0.2,
+                    color="navy", lw=lw)
+    ax.set_xticks(x_vales)
+    ax.set_xticklabels([fmt.format(x) for x in param_range],
+                       rotation=xtickrotation)
+
     xlabel = params[0] if xlabel is None else xlabel
-    plt.xlabel(param)
-    plt.legend()
+    ax.set_xlabel(param)
+    ax.legend()
     ylabel = "Score" if ylabel is None else ylabel
-    plt.ylabel(ylabel)
-    plt.title(title)
+    ax.set_ylabel(ylabel)
+    ax.set_title(title)
     plt.show()
     return img
 

From 170471d1b755fb745748cbf3dbd81be76615ee54 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Fri, 28 Jul 2017 15:15:29 -0400
Subject: [PATCH 86/97] adding title to plot_heatmap, removing plt.show from
 within API

---
 examples/model_selection/plot_confusion_matrix.py |  2 +-
 sklearn/plot/_confusion_matrix.py                 | 10 +++-------
 sklearn/plot/_gridsearch_results.py               |  6 ++----
 sklearn/plot/_heatmap.py                          | 12 ++++++++++--
 4 files changed, 16 insertions(+), 14 deletions(-)

diff --git a/examples/model_selection/plot_confusion_matrix.py b/examples/model_selection/plot_confusion_matrix.py
index 29853b9412681..804d4ba6d9354 100644
--- a/examples/model_selection/plot_confusion_matrix.py
+++ b/examples/model_selection/plot_confusion_matrix.py
@@ -56,7 +56,7 @@
 # Plot normalized confusion matrix
 plt.figure()
 plot_confusion_matrix(y_test, y_pred, classes=class_names, normalize=True,
-                      title='Normalized confusion matrix',
+                      title='Confusion matrix, with normalization',
                       cmap=plt.cm.Blues)
 
 plt.show()
diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index af0ffeda548b8..1c2c8f9a22bd6 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -69,8 +69,6 @@ def plot_confusion_matrix(y_true, y_pred, classes=None, sample_weight=None,
         generate the heatmap.
     """
 
-    import matplotlib.pyplot as plt
-
     unique_y = unique_labels(y_true, y_pred)
 
     if classes is None:
@@ -90,10 +88,8 @@ def plot_confusion_matrix(y_true, y_pred, classes=None, sample_weight=None,
     fmt = fmt if normalize else '{:d}'
 
     img = plot_heatmap(values, xticklabels=classes, yticklabels=classes,
-                       cmap=cmap, xlabel=xlabel, ylabel=ylabel, vmin=vmin,
-                       vmax=vmax, ax=ax, fmt=fmt, xtickrotation=xtickrotation,
-                       norm=norm)
-
-    plt.title(title)
+                       cmap=cmap, xlabel=xlabel, ylabel=ylabel, title=title,
+                       vmin=vmin, vmax=vmax, ax=ax, fmt=fmt,
+                       xtickrotation=xtickrotation, norm=norm)
 
     return img
diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index e98bed94e2e23..0d3952cac1999 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -40,7 +40,6 @@ def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title,
     ylabel = "Score" if ylabel is None else ylabel
     ax.set_ylabel(ylabel)
     ax.set_title(title)
-    plt.show()
     return img
 
 
@@ -62,11 +61,10 @@ def _plot_2D_results(cv_results, params, metric, ax, xlabel,
 
     img = plot_heatmap(scores, xlabel=xlabel, ylabel=ylabel,
                        xticklabels=parameter1_values,
-                       yticklabels=parameter2_values, cmap=cmap,
+                       yticklabels=parameter2_values,
+                       title=title, cmap=cmap,
                        vmin=vmin, vmax=vmax, fmt=fmt, ax=ax,
                        xtickrotation=xtickrotation, norm=norm)
-    plt.title(title)
-    plt.show()
     return img
 
 
diff --git a/sklearn/plot/_heatmap.py b/sklearn/plot/_heatmap.py
index 8b0c51d2cf5b9..989c170cacd53 100644
--- a/sklearn/plot/_heatmap.py
+++ b/sklearn/plot/_heatmap.py
@@ -2,8 +2,9 @@
 
 
 def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
-                 yticklabels=None, cmap=None, vmin=None, vmax=None, ax=None,
-                 fmt="{:.2f}", xtickrotation=45, norm=None):
+                 yticklabels=None, title=None, cmap=None, vmin=None,
+                 vmax=None, ax=None, fmt="{:.2f}", xtickrotation=45,
+                 norm=None):
     """Plot a matrix as heatmap with explicit numbers.
 
     Parameters
@@ -23,6 +24,9 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
     yticklabels : list of string or None, default=None
         Tick labels for the y-axis
 
+    title : string or None, default=None
+        Title of the chart
+
     cmap : string or colormap
         Matpotlib colormap to use.
 
@@ -90,4 +94,8 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
     # not anti-diagonal matrix
     ax.invert_yaxis()
 
+    # set title if not none:
+    if title is not None:
+        ax.set_title(title)
+
     return img

From df031bf3038bceb4d9da70c78efcbe0c8deef278 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Fri, 28 Jul 2017 15:25:21 -0400
Subject: [PATCH 87/97] added section to validation curve example

---
 .../model_selection/plot_validation_curve.py  | 28 +++++++++++++++++++
 1 file changed, 28 insertions(+)

diff --git a/examples/model_selection/plot_validation_curve.py b/examples/model_selection/plot_validation_curve.py
index ed74a41ff100b..ae335b3cf89a9 100644
--- a/examples/model_selection/plot_validation_curve.py
+++ b/examples/model_selection/plot_validation_curve.py
@@ -49,3 +49,31 @@
                  color="navy", lw=lw)
 plt.legend(loc="best")
 plt.show()
+
+#####################################################################
+"""
+The same plot can also be generated using a combination of GridSearchCV and
+ plotting module of scikit-learn.
+"""
+
+print(__doc__)
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+from sklearn.datasets import load_digits
+from sklearn.svm import SVC
+from sklearn.model_selection import GridSearchCV
+from sklearn.plot import plot_gridsearch_results
+
+digits = load_digits()
+X, y = digits.data, digits.target
+
+param_grid = {'gamma': np.logspace(-6, -1, 5)}
+gs = GridSearchCV(SVC(),
+                  param_grid=param_grid,
+                  cv=10, scoring="accuracy")
+
+gs.fit(X, y)
+plot_gridsearch_results(gs.cv_results_)
+plt.show()

From d676be39d59d6fd553783ec5cc88bd04a4a08e83 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Fri, 28 Jul 2017 17:08:24 -0400
Subject: [PATCH 88/97] sphinx syntax fix

---
 examples/model_selection/plot_validation_curve.py | 6 ++----
 1 file changed, 2 insertions(+), 4 deletions(-)

diff --git a/examples/model_selection/plot_validation_curve.py b/examples/model_selection/plot_validation_curve.py
index ae335b3cf89a9..c345b77cd3176 100644
--- a/examples/model_selection/plot_validation_curve.py
+++ b/examples/model_selection/plot_validation_curve.py
@@ -51,10 +51,8 @@
 plt.show()
 
 #####################################################################
-"""
-The same plot can also be generated using a combination of GridSearchCV and
- plotting module of scikit-learn.
-"""
+# The same plot can also be generated using a combination of GridSearchCV and
+# plotting module of scikit-learn.
 
 print(__doc__)
 

From f4d8a64abbf121d5ae90e11378bc870e5e9a12e3 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 1 Aug 2017 11:02:24 -0400
Subject: [PATCH 89/97] matplotlib new figure creation modified

---
 sklearn/plot/_gridsearch_results.py | 4 +++-
 sklearn/plot/_heatmap.py            | 5 ++++-
 2 files changed, 7 insertions(+), 2 deletions(-)

diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index 0d3952cac1999..6d51402455bc2 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -6,7 +6,8 @@ def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title,
                      fmt, xtickrotation):
     import matplotlib.pyplot as plt
     if ax is None:
-        ax = plt.gca()
+        fig = plt.figure()
+        ax = fig.add_subplot(111)
 
     param = params[0]
     param_range = sorted(cv_results['param_%s' % param])
@@ -40,6 +41,7 @@ def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title,
     ylabel = "Score" if ylabel is None else ylabel
     ax.set_ylabel(ylabel)
     ax.set_title(title)
+    plt.draw()
     return img
 
 
diff --git a/sklearn/plot/_heatmap.py b/sklearn/plot/_heatmap.py
index 989c170cacd53..020e1394c1f6f 100644
--- a/sklearn/plot/_heatmap.py
+++ b/sklearn/plot/_heatmap.py
@@ -52,7 +52,8 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
 
     import matplotlib.pyplot as plt
     if ax is None:
-        ax = plt.gca()
+        fig = plt.figure()
+        ax = fig.add_subplot(111)
     img = ax.pcolormesh(values, cmap=cmap, vmin=vmin, vmax=vmax, norm=norm)
 
     # this will allow us to access the pixel values:
@@ -98,4 +99,6 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
     if title is not None:
         ax.set_title(title)
 
+    plt.draw()
+
     return img

From a90c0d2ac424eb826eab7901dc969bcbc32fafd9 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Tue, 1 Aug 2017 12:51:23 -0400
Subject: [PATCH 90/97] define axis closer to public layer

---
 sklearn/plot/_confusion_matrix.py   | 5 +++++
 sklearn/plot/_gridsearch_results.py | 8 +++++---
 2 files changed, 10 insertions(+), 3 deletions(-)

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index 1c2c8f9a22bd6..2ca9e10ac44b4 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -68,6 +68,7 @@ def plot_confusion_matrix(y_true, y_pred, classes=None, sample_weight=None,
         Normalizer passed to pcolormesh function from matplotlib used to
         generate the heatmap.
     """
+    import matplotlib.pyplot as plt
 
     unique_y = unique_labels(y_true, y_pred)
 
@@ -87,6 +88,10 @@ def plot_confusion_matrix(y_true, y_pred, classes=None, sample_weight=None,
 
     fmt = fmt if normalize else '{:d}'
 
+    if ax is None:
+        fig = plt.figure()
+        ax = fig.add_subplot(111)
+
     img = plot_heatmap(values, xticklabels=classes, yticklabels=classes,
                        cmap=cmap, xlabel=xlabel, ylabel=ylabel, title=title,
                        vmin=vmin, vmax=vmax, ax=ax, fmt=fmt,
diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index 6d51402455bc2..c1d1f01031b53 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -5,9 +5,6 @@
 def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title,
                      fmt, xtickrotation):
     import matplotlib.pyplot as plt
-    if ax is None:
-        fig = plt.figure()
-        ax = fig.add_subplot(111)
 
     param = params[0]
     param_range = sorted(cv_results['param_%s' % param])
@@ -125,10 +122,15 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
         generate the heatmap. This is ignored if only 1 parameter is used in
         grid search.
     """
+    import matplotlib.pyplot as plt
 
     params = sorted(cv_results['params'][0].keys())
     nparams = len(params)
 
+    if ax is None:
+        fig = plt.figure()
+        ax = fig.add_subplot(111)
+
     if nparams == 1:
         img = _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title,
                                fmt, xtickrotation)

From fa2dec7bd475354224fd801e1413d467d3c32d85 Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Thu, 3 Aug 2017 11:19:00 -0400
Subject: [PATCH 91/97] removed plt.draw()

---
 sklearn/plot/_gridsearch_results.py | 3 ---
 sklearn/plot/_heatmap.py            | 2 --
 2 files changed, 5 deletions(-)

diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index c1d1f01031b53..f5d74c834143f 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -4,8 +4,6 @@
 
 def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title,
                      fmt, xtickrotation):
-    import matplotlib.pyplot as plt
-
     param = params[0]
     param_range = sorted(cv_results['param_%s' % param])
     train_scores_mean = cv_results['mean_train_score']
@@ -38,7 +36,6 @@ def _plot_1D_results(cv_results, params, ax, xlabel, ylabel, title,
     ylabel = "Score" if ylabel is None else ylabel
     ax.set_ylabel(ylabel)
     ax.set_title(title)
-    plt.draw()
     return img
 
 
diff --git a/sklearn/plot/_heatmap.py b/sklearn/plot/_heatmap.py
index 020e1394c1f6f..d098bd82cc927 100644
--- a/sklearn/plot/_heatmap.py
+++ b/sklearn/plot/_heatmap.py
@@ -99,6 +99,4 @@ def plot_heatmap(values, xlabel="", ylabel="", xticklabels=None,
     if title is not None:
         ax.set_title(title)
 
-    plt.draw()
-
     return img

From 876d854720d5d543361c3b5b8a8480e59572a8de Mon Sep 17 00:00:00 2001
From: aarshayj <aarshay.jain@gmail.com>
Date: Sat, 12 Aug 2017 19:03:04 -0400
Subject: [PATCH 92/97] docstring split lines

---
 sklearn/plot/_confusion_matrix.py   | 8 +++++---
 sklearn/plot/_gridsearch_results.py | 4 +++-
 2 files changed, 8 insertions(+), 4 deletions(-)

diff --git a/sklearn/plot/_confusion_matrix.py b/sklearn/plot/_confusion_matrix.py
index 2ca9e10ac44b4..aa205db564706 100644
--- a/sklearn/plot/_confusion_matrix.py
+++ b/sklearn/plot/_confusion_matrix.py
@@ -10,9 +10,11 @@ def plot_confusion_matrix(y_true, y_pred, classes=None, sample_weight=None,
                           title='Confusion matrix', cmap=None, vmin=None,
                           vmax=None, ax=None, fmt="{:.2f}",
                           xtickrotation=45, norm=None):
-    """Plot the confusion matrix as a heatmap. A confusion matrix is computed
-    using `y_true`, `y_pred` and `sample_weights` arguments. Normalization
-    can be applied by setting `normalize=True`.
+    """Plot confusion matrix as a heatmap.
+
+    A confusion matrix is computed using `y_true`, `y_pred` and
+    `sample_weights` arguments. Normalization can be applied by setting
+    `normalize=True`.
 
     Parameters
     ----------
diff --git a/sklearn/plot/_gridsearch_results.py b/sklearn/plot/_gridsearch_results.py
index f5d74c834143f..7a902903a6ec0 100644
--- a/sklearn/plot/_gridsearch_results.py
+++ b/sklearn/plot/_gridsearch_results.py
@@ -69,7 +69,9 @@ def plot_gridsearch_results(cv_results, metric='mean_test_score',
                             title='Grid Search Results', cmap=None,
                             vmin=None, vmax=None, ax=None, fmt="{:.2f}",
                             xtickrotation=45, norm=None):
-    """Plot the grid search results as a line chart for 1D search and heatmap
+    """Plot grid search results.
+
+    The results are plotted as a line chart for 1D search and as a heatmap
     for a 2D search. This function will not work if grid-search has more than
     2 parameters in the search space.
 

From fb16ab0ba482c87cfddafc406f04632331099275 Mon Sep 17 00:00:00 2001
From: aj2713 <aarshay.jain@columbia.edu>
Date: Fri, 12 Jan 2018 18:03:24 +0530
Subject: [PATCH 93/97] add tight_layout to plot confusion matrix examples

---
 examples/model_selection/plot_confusion_matrix.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/examples/model_selection/plot_confusion_matrix.py b/examples/model_selection/plot_confusion_matrix.py
index 804d4ba6d9354..b2d9f1306fb52 100644
--- a/examples/model_selection/plot_confusion_matrix.py
+++ b/examples/model_selection/plot_confusion_matrix.py
@@ -52,11 +52,13 @@
 plot_confusion_matrix(y_test, y_pred, classes=class_names,
                       title='Confusion matrix, without normalization',
                       cmap=plt.cm.Blues)
+plt.tight_layout()
 
 # Plot normalized confusion matrix
 plt.figure()
 plot_confusion_matrix(y_test, y_pred, classes=class_names, normalize=True,
                       title='Confusion matrix, with normalization',
                       cmap=plt.cm.Blues)
+plt.tight_layout()
 
 plt.show()

From 8cc94f17d9cd475412114176d2227e6881599955 Mon Sep 17 00:00:00 2001
From: aj2713 <aarshay.jain@columbia.edu>
Date: Fri, 12 Jan 2018 18:04:44 +0530
Subject: [PATCH 94/97] remove second print doc statement

---
 examples/model_selection/plot_validation_curve.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/examples/model_selection/plot_validation_curve.py b/examples/model_selection/plot_validation_curve.py
index c345b77cd3176..f2fb8dff64fe7 100644
--- a/examples/model_selection/plot_validation_curve.py
+++ b/examples/model_selection/plot_validation_curve.py
@@ -54,8 +54,6 @@
 # The same plot can also be generated using a combination of GridSearchCV and
 # plotting module of scikit-learn.
 
-print(__doc__)
-
 import matplotlib.pyplot as plt
 import numpy as np
 

From c48b61a2e2bbbd4bbcf47a6ed621748970af2b11 Mon Sep 17 00:00:00 2001
From: aj2713 <aarshay.jain@columbia.edu>
Date: Sat, 13 Jan 2018 05:17:18 +0530
Subject: [PATCH 95/97] adding axis format and tight layout

---
 examples/model_selection/plot_validation_curve.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/examples/model_selection/plot_validation_curve.py b/examples/model_selection/plot_validation_curve.py
index f2fb8dff64fe7..a5ec866a6f76a 100644
--- a/examples/model_selection/plot_validation_curve.py
+++ b/examples/model_selection/plot_validation_curve.py
@@ -71,5 +71,6 @@
                   cv=10, scoring="accuracy")
 
 gs.fit(X, y)
-plot_gridsearch_results(gs.cv_results_)
+plot_gridsearch_results(gs.cv_results_, fmt='{:.1e}')
+plt.tight_layout()
 plt.show()

From 2d1e6cfd6f3931c26aa90d60f4c6a181d0499e88 Mon Sep 17 00:00:00 2001
From: aj2713 <aarshay.jain@columbia.edu>
Date: Sat, 13 Jan 2018 05:20:51 +0530
Subject: [PATCH 96/97] adding tight_layout

---
 examples/svm/plot_rbf_parameters.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/examples/svm/plot_rbf_parameters.py b/examples/svm/plot_rbf_parameters.py
index b5e923b7ee937..f1b803d42a0c2 100644
--- a/examples/svm/plot_rbf_parameters.py
+++ b/examples/svm/plot_rbf_parameters.py
@@ -188,4 +188,5 @@ def __call__(self, value, clip=None):
 plot_gridsearch_results(grid.cv_results_, title="Validation accuracy",
                         cmap=plt.cm.hot,
                         norm=MidpointNormalize(vmin=0.2, midpoint=0.92))
+plt.tight_layout()
 plt.show()

From 01a63a7a5ad870a7693491d71377550575890893 Mon Sep 17 00:00:00 2001
From: aj2713 <aarshay.jain@columbia.edu>
Date: Sat, 13 Jan 2018 05:24:42 +0530
Subject: [PATCH 97/97] taking .travis.yml from master and adding matplotlib

---
 .travis.yml | 13 +------------
 1 file changed, 1 insertion(+), 12 deletions(-)

diff --git a/.travis.yml b/.travis.yml
index 1b0a7f5d50fa1..784339699f3e2 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -36,7 +36,7 @@ matrix:
     # Python 3.4 build
     - env: DISTRIB="conda" PYTHON_VERSION="3.4" INSTALL_MKL="false"
            NUMPY_VERSION="1.10.4" SCIPY_VERSION="0.16.1" CYTHON_VERSION="0.25.2"
-           COVERAGE=true
+           COVERAGE=true MATPLOTLIB_VERSION="2.0.2"
       if: type != cron
     # This environment tests the newest supported Anaconda release (5.0.0)
     # It also runs tests requiring Pandas and PyAMG
@@ -44,17 +44,6 @@ matrix:
            NUMPY_VERSION="1.13.1" SCIPY_VERSION="0.19.1" PANDAS_VERSION="0.20.3"
            CYTHON_VERSION="0.26.1" PYAMG_VERSION="3.3.2" COVERAGE=true
            CHECK_PYTEST_SOFT_DEPENDENCY="true" MATPLOTLIB_VERSION="2.0.2"
-    # This environment use pytest to run the tests. It uses the newest
-    # supported Anaconda release (4.4.0). It also runs tests requiring Pandas.
-    - env: USE_PYTEST="true" DISTRIB="conda" PYTHON_VERSION="3.6.1"
-           INSTALL_MKL="true" NUMPY_VERSION="1.12.1" SCIPY_VERSION="0.19.0"
-           PANDAS_VERSION="0.20.1" CYTHON_VERSION="0.25.2"
-           TEST_DOCSTRINGS="true" MATPLOTLIB_VERSION="2.0.2"
-    # This environment tests the newest supported Anaconda release (4.4.0)
-    # It also runs tests requiring Pandas.
-    - env: DISTRIB="conda" PYTHON_VERSION="3.6.1" INSTALL_MKL="true"
-           NUMPY_VERSION="1.12.1" SCIPY_VERSION="0.19.0" PANDAS_VERSION="0.20.1"
-           CYTHON_VERSION="0.25.2" MATPLOTLIB_VERSION="2.0.2" COVERAGE=true
       if: type != cron
     # flake8 linting on diff wrt common ancestor with upstream/master
     - env: RUN_FLAKE8="true" SKIP_TESTS="true"