matplotlib · jenshnielsen · Mar 19, 2016 · Mar 6, 2016 · Mar 6, 2016 · Mar 6, 2016
diff --git a/doc/api/api_changes/2016-03-13-PMH.rst b/doc/api/api_changes/2016-03-13-PMH.rst
@@ -0,0 +1,10 @@
+Changed default ``autorange`` behavior in boxplots
+``````````````````````````````````````````````````
+
+Prior to v1.5.2, the whiskers of boxplots would extend to the mininum
+and maximum values if the quartiles were all equal (i.e., Q1 = median
+= Q3). This behavior has been disabled by default to restore consistency
+with other plotting packages.
+
+To restore the old behavior, simply set ``autorange=True`` when
+calling ``plt.boxplot``.
diff --git a/lib/matplotlib/animation.py b/lib/matplotlib/animation.py
@@ -755,8 +755,8 @@ def save(self, filename, writer=None, fps=None, dpi=None, codec=None,
         # Re-use the savefig DPI for ours if none is given
         if dpi is None:
             dpi = rcParams['savefig.dpi']
-            if dpi == 'figure':
-                dpi = self._fig.dpi
+        if dpi == 'figure':
+            dpi = self._fig.dpi
 
         if codec is None:
             codec = rcParams['animation.codec']

diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
diff --git a/lib/matplotlib/backend_bases.py b/lib/matplotlib/backend_bases.py
@@ -2141,8 +2141,8 @@ def print_figure(self, filename, dpi=None, facecolor='w', edgecolor='w',
 
         if dpi is None:
             dpi = rcParams['savefig.dpi']
-            if dpi == 'figure':
-                dpi = self.figure.dpi
+        if dpi == 'figure':
+            dpi = self.figure.dpi
 
         origDPI = self.figure.dpi
         origfacecolor = self.figure.get_facecolor()

diff --git a/lib/matplotlib/backends/backend_qt5agg.py b/lib/matplotlib/backends/backend_qt5agg.py
@@ -172,6 +172,9 @@ def draw_idle(self):
             QtCore.QTimer.singleShot(0, self.__draw_idle_agg)
 
     def __draw_idle_agg(self, *args):
+        if self.height() < 0 or self.width() < 0:
+            self._agg_draw_pending = False
+            return
         try:
             FigureCanvasAgg.draw(self)
             self.update()

diff --git a/lib/matplotlib/backends/qt_compat.py b/lib/matplotlib/backends/qt_compat.py
@@ -42,7 +42,23 @@
 
 QT_API = None
 
-if (QT_API_ENV is not None):
+# check if any binding is already imported, if so silently ignore the
+# rcparams/ENV settings and use what ever is already imported.
+if 'PySide' in sys.modules:
+    # user has imported PySide before importing mpl
+    QT_API = QT_API_PYSIDE
+
+if 'PyQt4' in sys.modules:
+    # user has imported PyQt4 before importing mpl
+    # this case also handles the PyQt4v2 case as once sip is imported
+    # the API versions can not be changed so do not try
+    QT_API = QT_API_PYQT
+
+if 'PyQt5' in sys.modules:
+    # the user has imported PyQt5 before importing mpl
+    QT_API = QT_API_PYQT5
+
+if (QT_API_ENV is not None) and QT_API is None:
     try:
         QT_ENV_MAJOR_VERSION = ETS[QT_API_ENV][1]
     except KeyError:
@@ -61,15 +77,12 @@
     elif rcParams['backend'] == 'Qt4Agg':
         QT_API = rcParams['backend.qt4']
     else:
-        # A different backend was specified, but we still got here because a Qt
-        # related file was imported. This is allowed, so lets try and guess
-        # what we should be using.
-        if "PyQt4" in sys.modules or "PySide" in sys.modules:
-            # PyQt4 or PySide is actually used.
-            QT_API = rcParams['backend.qt4']
-        else:
-            # This is a fallback: PyQt5
-            QT_API = rcParams['backend.qt5']
+        # A non-Qt backend was specified, no version of the Qt
+        # bindings is imported, but we still got here because a Qt
+        # related file was imported. This is allowed, fall back to Qt5
+        # using which ever binding the rparams ask for.
+
+        QT_API = rcParams['backend.qt5']
 
 # We will define an appropriate wrapper for the differing versions
 # of file dialog.

diff --git a/lib/matplotlib/cbook.py b/lib/matplotlib/cbook.py
@@ -715,6 +715,17 @@ def is_sequence_of_strings(obj):
     return True
 
 
+def is_hashable(obj):
+    """
+    Returns true if *obj* can be hashed
+    """
+    try:
+        hash(obj)
+    except TypeError:
+        return False
+    return True
+
+
 def is_writable_file_like(obj):
     'return true if *obj* looks like a file object with a *write* method'
     return hasattr(obj, 'write') and six.callable(obj.write)
@@ -1863,39 +1874,46 @@ def delete_masked_points(*args):
     return margs
 
 
-def boxplot_stats(X, whis=1.5, bootstrap=None, labels=None):
-    '''
-    Returns list of dictionaries of staticists to be use to draw a series of
-    box and whisker plots. See the `Returns` section below to the required
-    keys of the dictionary. Users can skip this function and pass a user-
-    defined set of dictionaries to the new `axes.bxp` method instead of
-    relying on MPL to do the calcs.
+def boxplot_stats(X, whis=1.5, bootstrap=None, labels=None,
+                  autorange=False):
+    """
+    Returns list of dictionaries of statistics used to draw a series
+    of box and whisker plots. The `Returns` section enumerates the
+    required keys of the dictionary. Users can skip this function and
+    pass a user-defined set of dictionaries to the new `axes.bxp` method
+    instead of relying on MPL to do the calculations.
 
     Parameters
     ----------
     X : array-like
-        Data that will be represented in the boxplots. Should have 2 or fewer
-        dimensions.
+        Data that will be represented in the boxplots. Should have 2 or
+        fewer dimensions.
 
     whis : float, string, or sequence (default = 1.5)
-        As a float, determines the reach of the whiskers past the first and
-        third quartiles (e.g., Q3 + whis*IQR, QR = interquartile range, Q3-Q1).
-        Beyond the whiskers, data are considered outliers and are plotted as
-        individual points. Set this to an unreasonably high value to force the
-        whiskers to show the min and max data. Alternatively, set this to an
-        ascending sequence of percentile (e.g., [5, 95]) to set the whiskers
-        at specific percentiles of the data. Finally, can  `whis` be the
-        string 'range' to force the whiskers to the min and max of the data.
-        In the edge case that the 25th and 75th percentiles are equivalent,
-        `whis` will be automatically set to 'range'
-
-    bootstrap : int or None (default)
-        Number of times the confidence intervals around the median should
-        be bootstrapped (percentile method).
-
-    labels : sequence
-        Labels for each dataset. Length must be compatible with dimensions
-        of `X`
+        As a float, determines the reach of the whiskers past the first
+        and third quartiles (e.g., Q3 + whis*IQR, QR = interquartile
+        range, Q3-Q1). Beyond the whiskers, data are considered outliers
+        and are plotted as individual points. This can be set this to an
+        ascending sequence of percentile (e.g., [5, 95]) to set the
+        whiskers at specific percentiles of the data. Finally, `whis`
+        can be the string ``'range'`` to force the whiskers to the
+        minimum and maximum of the data. In the edge case that the 25th
+        and 75th percentiles are equivalent, `whis` can be automatically
+        set to ``'range'`` via the `autorange` option.
+
+    bootstrap : int, optional
+        Number of times the confidence intervals around the median
+        should be bootstrapped (percentile method).
+
+    labels : array-like, optional
+        Labels for each dataset. Length must be compatible with
+        dimensions of `X`.
+
+    autorange : bool, optional (False)
+        When `True` and the data are distributed such that the  25th and
+        75th percentiles are equal, ``whis`` is set to ``'range'`` such
+        that the whisker ends are at the minimum and maximum of the
+        data.
 
     Returns
     -------
@@ -1920,8 +1938,8 @@ def boxplot_stats(X, whis=1.5, bootstrap=None, labels=None):
 
     Notes
     -----
-    Non-bootstrapping approach to confidence interval uses Gaussian-based
-    asymptotic approximation:
+    Non-bootstrapping approach to confidence interval uses Gaussian-
+    based asymptotic approximation:
 
     .. math::
 
@@ -1931,7 +1949,7 @@ def boxplot_stats(X, whis=1.5, bootstrap=None, labels=None):
     McGill, R., Tukey, J.W., and Larsen, W.A. (1978) "Variations of
     Boxplots", The American Statistician, 32:12-16.
 
-    '''
+    """
 
     def _bootstrap_median(data, N=5000):
         # determine 95% confidence intervals of the median
@@ -2011,7 +2029,7 @@ def _compute_conf_interval(data, med, iqr, bootstrap):
 
         # interquartile range
         stats['iqr'] = q3 - q1
-        if stats['iqr'] == 0:
+        if stats['iqr'] == 0 and autorange:
             whis = 'range'
 
         # conf. interval around median

diff --git a/lib/matplotlib/collections.py b/lib/matplotlib/collections.py
@@ -151,7 +151,7 @@ def _get_value(val):
         except TypeError:
             if cbook.iterable(val) and len(val):
                 try:
-                    float(val[0])
+                    float(cbook.safe_first_element(val))
                 except (TypeError, ValueError):
                     pass  # raise below
                 else:
@@ -164,7 +164,7 @@ def _get_bool(val):
         if not cbook.iterable(val):
             val = (val,)
         try:
-            bool(val[0])
+            bool(cbook.safe_first_element(val))
         except (TypeError, IndexError):
             raise TypeError('val must be a bool or nonzero sequence of them')
         return val
@@ -532,7 +532,7 @@ def set_linestyle(self, ls):
             The line style.
         """
         try:
-            if cbook.is_string_like(ls):
+            if cbook.is_string_like(ls) and cbook.is_hashable(ls):
                 ls = cbook.ls_mapper.get(ls, ls)
                 dashes = [mlines.get_dash_pattern(ls)]
             elif cbook.iterable(ls):

diff --git a/lib/matplotlib/colors.py b/lib/matplotlib/colors.py
@@ -821,7 +821,8 @@ def __init__(self, colors, name='from_list', N=None):
         if N is None:
             N = len(self.colors)
         else:
-            if cbook.is_string_like(self.colors):
+            if (cbook.is_string_like(self.colors) and
+                    cbook.is_hashable(self.colors)):
                 self.colors = [self.colors] * N
                 self.monochrome = True
             elif cbook.iterable(self.colors):

diff --git a/lib/matplotlib/figure.py b/lib/matplotlib/figure.py
@@ -1508,8 +1508,6 @@ def savefig(self, *args, **kwargs):
         """
 
         kwargs.setdefault('dpi', rcParams['savefig.dpi'])
-        if kwargs['dpi'] == 'figure':
-            kwargs['dpi'] = self.get_dpi()
         frameon = kwargs.pop('frameon', rcParams['savefig.frameon'])
         transparent = kwargs.pop('transparent',
                                  rcParams['savefig.transparent'])

diff --git a/...matplotlib/tests/baseline_images/test_axes/boxplot_autorange_false_whiskers.png b/...matplotlib/tests/baseline_images/test_axes/boxplot_autorange_false_whiskers.png
diff --git a/.../test_axes/boxplot_autorange_whiskers.png → ..._axes/boxplot_autorange_true_whiskers.png b/.../test_axes/boxplot_autorange_whiskers.png → ..._axes/boxplot_autorange_true_whiskers.png
diff --git a/lib/matplotlib/tests/baseline_images/test_axes/boxplot_autorange_whiskers.pdf b/lib/matplotlib/tests/baseline_images/test_axes/boxplot_autorange_whiskers.pdf