Merge pull request matplotlib#640 from jkseppan/merge-v1.1.x

Merge v1.1.x

Author: efiring

CHANGELOG

@@ -1,3 +1,5 @@
+2011-12-27 Work around an EINTR bug in some versions of subprocess. - JKS
+
 2011-10-25 added support for \operatorname to mathtext,
            including the ability to insert spaces, such as
            $\operatorname{arg\,max}$ - PI

INSTALL

@@ -45,10 +45,10 @@ progress::
     >>> import numpy
     >>> print numpy.__version__
 
-matplotlib requires numpy version 1.1 or later.  Although it is not a
-requirement to use matplotlib, we strongly encourage you to install
-`ipython <http://ipython.org>`_, which is an interactive
-shell for python that is matplotlib-aware.
+matplotlib requires numpy version |minimum_numpy_version| or later.
+Although it is not a requirement to use matplotlib, we strongly
+encourage you to install `ipython <http://ipython.org>`_, which is an
+interactive shell for python that is matplotlib-aware.
 
 Next, we need to get matplotlib installed.  We provide prebuilt
 binaries for OS X and Windows on the matplotlib `download
@@ -182,7 +182,7 @@ libraries themselves.
 :term:`python` 2.6 (or later but not python3)
     matplotlib requires python 2.6 or later (`download <http://www.python.org/download/>`__)
 
-:term:`numpy` 1.1 (or later)
+:term:`numpy` |minimum_numpy_version| (or later)
     array support for python (`download
     <http://sourceforge.net/project/showfiles.php?group_id=1369&package_id=175103>`__)
 

doc/conf.py

@@ -182,3 +182,7 @@
 # Show both class-level docstring and __init__ docstring in class
 # documentation
 autoclass_content = 'both'
+
+rst_epilog = """
+.. |minimum_numpy_version| replace:: %s
+""" % matplotlib.__version__numpy__

examples/api/radar_chart.py

@@ -1,77 +1,124 @@
+"""
+Example of creating a radar chart (a.k.a. a spider or star chart) [1]_.
+
+Although this example allows a frame of either 'circle' or 'polygon', polygon
+frames don't have proper gridlines (the lines are circles instead of polygons).
+It's possible to get a polygon grid by setting GRIDLINE_INTERPOLATION_STEPS in
+matplotlib.axis to the desired number of vertices, but the orientation of the
+polygon is not aligned with the radial axes.
+
+.. [1] http://en.wikipedia.org/wiki/Radar_chart
+"""
 import numpy as np
 
 import matplotlib.pyplot as plt
-from matplotlib.projections.polar import PolarAxes 
-from matplotlib.projections import register_projection 
-
-def radar_factory(num_vars, frame='circle'): 
-    """Create a radar chart with `num_vars` axes.""" 
-    # calculate evenly-spaced axis angles 
-    theta = 2*np.pi * np.linspace(0, 1-1./num_vars, num_vars) 
-    # rotate theta such that the first axis is at the top 
-    theta += np.pi/2 
-
-    def draw_poly_frame(self, x0, y0, r): 
-        # TODO: use transforms to convert (x, y) to (r, theta)
-        verts = [(r*np.cos(t) + x0, r*np.sin(t) + y0) for t in theta] 
-        return plt.Polygon(verts, closed=True, edgecolor='k') 
-        
-    def draw_circle_frame(self, x0, y0, r): 
-        return plt.Circle((x0, y0), r) 
-
-    frame_dict = {'polygon': draw_poly_frame, 'circle': draw_circle_frame} 
-    if frame not in frame_dict: 
-        raise ValueError, 'unknown value for `frame`: %s' % frame 
-
-    class RadarAxes(PolarAxes): 
-        """Class for creating a radar chart (a.k.a. a spider or star chart) 
-        
-        http://en.wikipedia.org/wiki/Radar_chart 
-        """ 
-        name = 'radar' 
-        # use 1 line segment to connect specified points 
-        RESOLUTION = 1 
-        # define draw_frame method 
-        draw_frame = frame_dict[frame] 
-        
-        def fill(self, *args, **kwargs): 
-            """Override fill so that line is closed by default""" 
-            closed = kwargs.pop('closed', True) 
-            return super(RadarAxes, self).fill(closed=closed, *args, **kwargs) 
-        
-        def plot(self, *args, **kwargs): 
-            """Override plot so that line is closed by default""" 
-            lines = super(RadarAxes, self).plot(*args, **kwargs) 
-            for line in lines: 
-                self._close_line(line) 
-        
-        def _close_line(self, line): 
-            x, y = line.get_data() 
-            # FIXME: markers at x[0], y[0] get doubled-up 
-            if x[0] != x[-1]: 
-                x = np.concatenate((x, [x[0]])) 
-                y = np.concatenate((y, [y[0]])) 
-                line.set_data(x, y) 
-        
-        def set_varlabels(self, labels): 
-            self.set_thetagrids(theta * 180/np.pi, labels) 
-        
-        def _gen_axes_patch(self): 
-            x0, y0 = (0.5, 0.5) 
-            r = 0.5 
-            return self.draw_frame(x0, y0, r)
-        
-    register_projection(RadarAxes) 
-    return theta 
-
-
-if __name__ == '__main__': 
-    #The following data is from the Denver Aerosol Sources and Health study. 
-    #See  doi:10.1016/j.atmosenv.2008.12.017    
+from matplotlib.path import Path
+from matplotlib.spines import Spine
+from matplotlib.projections.polar import PolarAxes
+from matplotlib.projections import register_projection
+
+
+def radar_factory(num_vars, frame='circle'):
+    """Create a radar chart with `num_vars` axes.
+
+    This function creates a RadarAxes projection and registers it.
+
+    Parameters
+    ----------
+    num_vars : int
+        Number of variables for radar chart.
+    frame : {'circle' | 'polygon'}
+        Shape of frame surrounding axes.
+
+    """
+    # calculate evenly-spaced axis angles
+    theta = 2*np.pi * np.linspace(0, 1-1./num_vars, num_vars)
+    # rotate theta such that the first axis is at the top
+    theta += np.pi/2
+
+    def draw_poly_patch(self):
+        verts = unit_poly_verts(theta)
+        return plt.Polygon(verts, closed=True, edgecolor='k')
+
+    def draw_circle_patch(self):
+        # unit circle centered on (0.5, 0.5)
+        return plt.Circle((0.5, 0.5), 0.5)
+
+    patch_dict = {'polygon': draw_poly_patch, 'circle': draw_circle_patch}
+    if frame not in patch_dict:
+        raise ValueError, 'unknown value for `frame`: %s' % frame
+
+    class RadarAxes(PolarAxes):
+
+        name = 'radar'
+        # use 1 line segment to connect specified points
+        RESOLUTION = 1
+        # define draw_frame method
+        draw_patch = patch_dict[frame]
+
+        def fill(self, *args, **kwargs):
+            """Override fill so that line is closed by default"""
+            closed = kwargs.pop('closed', True)
+            return super(RadarAxes, self).fill(closed=closed, *args, **kwargs)
+
+        def plot(self, *args, **kwargs):
+            """Override plot so that line is closed by default"""
+            lines = super(RadarAxes, self).plot(*args, **kwargs)
+            for line in lines:
+                self._close_line(line)
+
+        def _close_line(self, line):
+            x, y = line.get_data()
+            # FIXME: markers at x[0], y[0] get doubled-up
+            if x[0] != x[-1]:
+                x = np.concatenate((x, [x[0]]))
+                y = np.concatenate((y, [y[0]]))
+                line.set_data(x, y)
+
+        def set_varlabels(self, labels):
+            self.set_thetagrids(theta * 180/np.pi, labels)
+
+        def _gen_axes_patch(self):
+            return self.draw_patch()
+
+        def _gen_axes_spines(self):
+            if frame == 'circle':
+                return PolarAxes._gen_axes_spines(self)
+            # The following is a hack to get the spines (i.e. the axes frame)
+            # to draw correctly for a polygon frame.
+
+            # spine_type must be 'left', 'right', 'top', 'bottom', or `circle`.
+            spine_type = 'circle'
+            verts = unit_poly_verts(theta)
+            # close off polygon by repeating first vertex
+            verts.append(verts[0])
+            path = Path(verts)
+
+            spine = Spine(self, spine_type, path)
+            spine.set_transform(self.transAxes)
+            return {'polar': spine}
+
+    register_projection(RadarAxes)
+    return theta
+
+
+def unit_poly_verts(theta):
+    """Return vertices of polygon for subplot axes.
+
+    This polygon is circumscribed by a unit circle centered at (0.5, 0.5)
+    """
+    x0, y0, r = [0.5] * 3
+    verts = [(r*np.cos(t) + x0, r*np.sin(t) + y0) for t in theta]
+    return verts
+
+
+def example_data():
+    #The following data is from the Denver Aerosol Sources and Health study.
+    #See  doi:10.1016/j.atmosenv.2008.12.017
     #
     #The data are pollution source profile estimates for five modeled pollution
     #sources (e.g., cars, wood-burning, etc) that emit 7-9 chemical species.
-    #The radar charts are experimented with here to see if we can nicely 
+    #The radar charts are experimented with here to see if we can nicely
     #visualize how the modeled source profiles change across four scenarios:
     #  1) No gas-phase species present, just seven particulate counts on
     #     Sulfate
@@ -81,64 +128,69 @@ def _gen_axes_patch(self):
     #     Organic Carbon fraction 2 (OC2)
     #     Organic Carbon fraction 3 (OC3)
     #     Pyrolized Organic Carbon (OP)
-    #  2)Inclusion of gas-phase specie carbon monoxide (CO) 
-    #  3)Inclusion of gas-phase specie ozone (O3). 
+    #  2)Inclusion of gas-phase specie carbon monoxide (CO)
+    #  3)Inclusion of gas-phase specie ozone (O3).
     #  4)Inclusion of both gas-phase speciesis present...
+    data = {
+        'column names':
+            ['Sulfate', 'Nitrate', 'EC', 'OC1', 'OC2', 'OC3', 'OP', 'CO', 'O3'],
+        'Basecase':
+            [[0.88, 0.01, 0.03, 0.03, 0.00, 0.06, 0.01, 0.00, 0.00],
+             [0.07, 0.95, 0.04, 0.05, 0.00, 0.02, 0.01, 0.00, 0.00],
+             [0.01, 0.02, 0.85, 0.19, 0.05, 0.10, 0.00, 0.00, 0.00],
+             [0.02, 0.01, 0.07, 0.01, 0.21, 0.12, 0.98, 0.00, 0.00],
+             [0.01, 0.01, 0.02, 0.71, 0.74, 0.70, 0.00, 0.00, 0.00]],
+        'With CO':
+            [[0.88, 0.02, 0.02, 0.02, 0.00, 0.05, 0.00, 0.05, 0.00],
+             [0.08, 0.94, 0.04, 0.02, 0.00, 0.01, 0.12, 0.04, 0.00],
+             [0.01, 0.01, 0.79, 0.10, 0.00, 0.05, 0.00, 0.31, 0.00],
+             [0.00, 0.02, 0.03, 0.38, 0.31, 0.31, 0.00, 0.59, 0.00],
+             [0.02, 0.02, 0.11, 0.47, 0.69, 0.58, 0.88, 0.00, 0.00]],
+        'With O3':
+            [[0.89, 0.01, 0.07, 0.00, 0.00, 0.05, 0.00, 0.00, 0.03],
+             [0.07, 0.95, 0.05, 0.04, 0.00, 0.02, 0.12, 0.00, 0.00],
+             [0.01, 0.02, 0.86, 0.27, 0.16, 0.19, 0.00, 0.00, 0.00],
+             [0.01, 0.03, 0.00, 0.32, 0.29, 0.27, 0.00, 0.00, 0.95],
+             [0.02, 0.00, 0.03, 0.37, 0.56, 0.47, 0.87, 0.00, 0.00]],
+        'CO & O3':
+            [[0.87, 0.01, 0.08, 0.00, 0.00, 0.04, 0.00, 0.00, 0.01],
+             [0.09, 0.95, 0.02, 0.03, 0.00, 0.01, 0.13, 0.06, 0.00],
+             [0.01, 0.02, 0.71, 0.24, 0.13, 0.16, 0.00, 0.50, 0.00],
+             [0.01, 0.03, 0.00, 0.28, 0.24, 0.23, 0.00, 0.44, 0.88],
+             [0.02, 0.00, 0.18, 0.45, 0.64, 0.55, 0.86, 0.00, 0.16]]
+    }
+    return data
+
+
+if __name__ == '__main__':
     N = 9
-    theta = radar_factory(N)
-    spoke_labels = ['Sulfate', 'Nitrate', 'EC', 'OC1', 'OC2', 'OC3', 'OP', 'CO', 
-                    'O3']
-    f1_base = [0.88, 0.01, 0.03, 0.03, 0.00, 0.06, 0.01, 0.00, 0.00]
-    f1_CO =   [0.88, 0.02, 0.02, 0.02, 0.00, 0.05, 0.00, 0.05, 0.00] 
-    f1_O3 =   [0.89, 0.01, 0.07, 0.00, 0.00, 0.05, 0.00, 0.00, 0.03] 
-    f1_both = [0.87, 0.01, 0.08, 0.00, 0.00, 0.04, 0.00, 0.00, 0.01] 
-
-    f2_base = [0.07, 0.95, 0.04, 0.05, 0.00, 0.02, 0.01, 0.00, 0.00]
-    f2_CO =   [0.08, 0.94, 0.04, 0.02, 0.00, 0.01, 0.12, 0.04, 0.00] 
-    f2_O3 =   [0.07, 0.95, 0.05, 0.04, 0.00, 0.02, 0.12, 0.00, 0.00] 
-    f2_both = [0.09, 0.95, 0.02, 0.03, 0.00, 0.01, 0.13, 0.06, 0.00] 
-
-    f3_base = [0.01, 0.02, 0.85, 0.19, 0.05, 0.10, 0.00, 0.00, 0.00]
-    f3_CO =   [0.01, 0.01, 0.79, 0.10, 0.00, 0.05, 0.00, 0.31, 0.00] 
-    f3_O3 =   [0.01, 0.02, 0.86, 0.27, 0.16, 0.19, 0.00, 0.00, 0.00] 
-    f3_both = [0.01, 0.02, 0.71, 0.24, 0.13, 0.16, 0.00, 0.50, 0.00] 
-    
-    f4_base = [0.02, 0.01, 0.07, 0.01, 0.21, 0.12, 0.98, 0.00, 0.00]
-    f4_CO =   [0.00, 0.02, 0.03, 0.38, 0.31, 0.31, 0.00, 0.59, 0.00] 
-    f4_O3 =   [0.01, 0.03, 0.00, 0.32, 0.29, 0.27, 0.00, 0.00, 0.95] 
-    f4_both = [0.01, 0.03, 0.00, 0.28, 0.24, 0.23, 0.00, 0.44, 0.88] 
-
-    f5_base = [0.01, 0.01, 0.02, 0.71, 0.74, 0.70, 0.00, 0.00, 0.00]
-    f5_CO =   [0.02, 0.02, 0.11, 0.47, 0.69, 0.58, 0.88, 0.00, 0.00] 
-    f5_O3 =   [0.02, 0.00, 0.03, 0.37, 0.56, 0.47, 0.87, 0.00, 0.00] 
-    f5_both = [0.02, 0.00, 0.18, 0.45, 0.64, 0.55, 0.86, 0.00, 0.16] 
-
-    fig = plt.figure(figsize=(9,9))
-    # adjust spacing around the subplots
+    theta = radar_factory(N, frame='polygon')
+
+    data = example_data()
+    spoke_labels = data.pop('column names')
+
+    fig = plt.figure(figsize=(9, 9))
     fig.subplots_adjust(wspace=0.25, hspace=0.20, top=0.85, bottom=0.05)
-    title_list = ['Basecase', 'With CO', 'With O3', 'CO & O3']
-    data = {'Basecase': [f1_base, f2_base, f3_base, f4_base, f5_base],
-            'With CO': [f1_CO, f2_CO, f3_CO, f4_CO, f5_CO],
-            'With O3': [f1_O3, f2_O3, f3_O3, f4_O3, f5_O3], 
-            'CO & O3': [f1_both, f2_both, f3_both, f4_both, f5_both]}
+
     colors = ['b', 'r', 'g', 'm', 'y']
-    # chemicals range from 0 to 1
-    radial_grid = [0.2, 0.4, 0.6, 0.8]
-    # If you don't care about the order, you can loop over data_dict.items()
-    for n, title in enumerate(title_list):
+    # Plot the four cases from the example data on separate axes
+    for n, title in enumerate(data.keys()):
         ax = fig.add_subplot(2, 2, n+1, projection='radar')
-        plt.rgrids(radial_grid)
+        plt.rgrids([0.2, 0.4, 0.6, 0.8])
         ax.set_title(title, weight='bold', size='medium', position=(0.5, 1.1),
                      horizontalalignment='center', verticalalignment='center')
         for d, color in zip(data[title], colors):
-            ax.plot(theta, d, color=color) 
-            ax.fill(theta, d, facecolor=color, alpha=0.25)  
+            ax.plot(theta, d, color=color)
+            ax.fill(theta, d, facecolor=color, alpha=0.25)
         ax.set_varlabels(spoke_labels)
+
     # add legend relative to top-left plot
     plt.subplot(2,2,1)
     labels = ('Factor 1', 'Factor 2', 'Factor 3', 'Factor 4', 'Factor 5')
     legend = plt.legend(labels, loc=(0.9, .95), labelspacing=0.1)
     plt.setp(legend.get_texts(), fontsize='small')
-    plt.figtext(0.5, 0.965,  '5-Factor Solution Profiles Across Four Scenarios', 
-               ha='center', color='black', weight='bold', size='large')        
+
+    plt.figtext(0.5, 0.965,  '5-Factor Solution Profiles Across Four Scenarios',
+               ha='center', color='black', weight='bold', size='large')
     plt.show()
+

lib/matplotlib/__init__.py

@@ -100,6 +100,7 @@
 from __future__ import print_function
 
 __version__  = '1.2.x'
+__version__numpy__ = '1.4' # minimum required numpy version
 
 import os, re, shutil, subprocess, sys, warnings
 import distutils.sysconfig
@@ -161,11 +162,17 @@ def byte2str(b): return b
 if not _python24:
     raise ImportError('matplotlib requires Python 2.4 or later')
 
+
 import numpy
-nmajor, nminor = [int(n) for n in numpy.__version__.split('.')[:2]]
-if not (nmajor > 1 or (nmajor == 1 and nminor >= 1)):
+from distutils import version
+expected_version = version.StrictVersion(__version__numpy__)
+found_version = version.StrictVersion(numpy.__version__)
+if not found_version >= expected_version:
     raise ImportError(
-            'numpy 1.1 or later is required; you have %s' % numpy.__version__)
+        'numpy %s or later is required; you have %s' % (
+            __version__numpy__, numpy.__version__))
+del version
+
 
 def is_string_like(obj):
     if hasattr(obj, 'shape'): return 0