Merge pull request matplotlib#11959 from anntzer/iterableless

cbook.iterable -> np.iterable.

Author: timhoffm

doc/api/api_changes/2018-08-17-AL-deprecations.rst renamed to doc/api/next_api_changes/2018-08-17-AL-deprecations.rst

@@ -4,4 +4,5 @@ API deprecations
 The following API elements are deprecated:
 
 - ``tk_window_focus``,
+- ``cbook.iterable``,
 - ``mlab.demean``,

examples/units/basic_units.py

@@ -11,7 +11,6 @@
 
 import matplotlib.units as units
 import matplotlib.ticker as ticker
-from matplotlib.cbook import iterable
 
 
 class ProxyDelegate(object):
@@ -345,22 +344,22 @@ def axisinfo(unit, axis):
     def convert(val, unit, axis):
         if units.ConversionInterface.is_numlike(val):
             return val
-        if iterable(val):
+        if np.iterable(val):
             return [thisval.convert_to(unit).get_value() for thisval in val]
         else:
             return val.convert_to(unit).get_value()
 
     @staticmethod
     def default_units(x, axis):
         'return the default unit for x or None'
-        if iterable(x):
+        if np.iterable(x):
             for thisx in x:
                 return thisx.unit
         return x.unit
 
 
 def cos(x):
-    if iterable(x):
+    if np.iterable(x):
         return [math.cos(val.convert_to(radians).get_value()) for val in x]
     else:
         return math.cos(x.convert_to(radians).get_value())

examples/units/evans_test.py

@@ -9,7 +9,8 @@
 to what kind of units client packages use.
 """
 
-from matplotlib.cbook import iterable
+import numpy as np
+
 import matplotlib.units as units
 import matplotlib.ticker as ticker
 import matplotlib.pyplot as plt
@@ -49,15 +50,15 @@ def convert(obj, unit, axis):
         if units.ConversionInterface.is_numlike(obj):
             return obj
 
-        if iterable(obj):
+        if np.iterable(obj):
             return [o.value(unit) for o in obj]
         else:
             return obj.value(unit)
 
     @staticmethod
     def default_units(x, axis):
         'return the default unit for x or None'
-        if iterable(x):
+        if np.iterable(x):
             for thisx in x:
                 return thisx.unit
         else:

lib/matplotlib/animation.py

@@ -1643,7 +1643,7 @@ def __init__(self, fig, func, frames=None, init_func=None, fargs=None,
             self._iter_gen = itertools.count
         elif callable(frames):
             self._iter_gen = frames
-        elif cbook.iterable(frames):
+        elif np.iterable(frames):
             self._iter_gen = lambda: iter(frames)
             if hasattr(frames, '__len__'):
                 self.save_count = len(frames)

lib/matplotlib/artist.py

@@ -1175,7 +1175,7 @@ def __init__(self, o):
         responsibility to make sure this is so.
         """
         if not isinstance(o, Artist):
-            if cbook.iterable(o):
+            if np.iterable(o):
                 o = list(o)
                 if len(o):
                     o = o[0]

lib/matplotlib/axes/_axes.py

@@ -33,7 +33,6 @@
 import matplotlib.ticker as mticker
 import matplotlib.transforms as mtransforms
 import matplotlib.tri as mtri
-from matplotlib.cbook import iterable
 from matplotlib.container import BarContainer, ErrorbarContainer, StemContainer
 from matplotlib.axes._base import _AxesBase, _process_plot_format
 
@@ -1035,11 +1034,11 @@ def hlines(self, y, xmin, xmax, colors='k', linestyles='solid',
         xmin = self.convert_xunits(xmin)
         xmax = self.convert_xunits(xmax)
 
-        if not iterable(y):
+        if not np.iterable(y):
             y = [y]
-        if not iterable(xmin):
+        if not np.iterable(xmin):
             xmin = [xmin]
-        if not iterable(xmax):
+        if not np.iterable(xmax):
             xmax = [xmax]
 
         y, xmin, xmax = cbook.delete_masked_points(y, xmin, xmax)
@@ -1113,11 +1112,11 @@ def vlines(self, x, ymin, ymax, colors='k', linestyles='solid',
         ymin = self.convert_yunits(ymin)
         ymax = self.convert_yunits(ymax)
 
-        if not iterable(x):
+        if not np.iterable(x):
             x = [x]
-        if not iterable(ymin):
+        if not np.iterable(ymin):
             ymin = [ymin]
-        if not iterable(ymax):
+        if not np.iterable(ymax):
             ymax = [ymax]
 
         x, ymin, ymax = cbook.delete_masked_points(x, ymin, ymax)
@@ -1243,9 +1242,9 @@ def eventplot(self, positions, orientation='horizontal', lineoffsets=1,
         lineoffsets = self.convert_yunits(lineoffsets)
         linelengths = self.convert_yunits(linelengths)
 
-        if not iterable(positions):
+        if not np.iterable(positions):
             positions = [positions]
-        elif any(iterable(position) for position in positions):
+        elif any(np.iterable(position) for position in positions):
             positions = [np.asanyarray(position) for position in positions]
         else:
             positions = [np.asanyarray(positions)]
@@ -1259,15 +1258,15 @@ def eventplot(self, positions, orientation='horizontal', lineoffsets=1,
         linewidths = cbook.local_over_kwdict(linewidths, kwargs, 'linewidth')
         linestyles = cbook.local_over_kwdict(linestyles, kwargs, 'linestyle')
 
-        if not iterable(lineoffsets):
+        if not np.iterable(lineoffsets):
             lineoffsets = [lineoffsets]
-        if not iterable(linelengths):
+        if not np.iterable(linelengths):
             linelengths = [linelengths]
-        if not iterable(linewidths):
+        if not np.iterable(linewidths):
             linewidths = [linewidths]
-        if not iterable(colors):
+        if not np.iterable(colors):
             colors = [colors]
-        if hasattr(linestyles, 'lower') or not iterable(linestyles):
+        if hasattr(linestyles, 'lower') or not np.iterable(linestyles):
             linestyles = [linestyles]
 
         lineoffsets = np.asarray(lineoffsets)
@@ -3065,18 +3064,18 @@ def errorbar(self, x, y, yerr=None, xerr=None,
             ecolor = base_style['color']
         # make sure all the args are iterable; use lists not arrays to
         # preserve units
-        if not iterable(x):
+        if not np.iterable(x):
             x = [x]
 
-        if not iterable(y):
+        if not np.iterable(y):
             y = [y]
 
         if xerr is not None:
-            if not iterable(xerr):
+            if not np.iterable(xerr):
                 xerr = [xerr] * len(x)
 
         if yerr is not None:
-            if not iterable(yerr):
+            if not np.iterable(yerr):
                 yerr = [yerr] * len(y)
 
         # make the style dict for the 'normal' plot line
@@ -3168,7 +3167,7 @@ def extract_err(err, data):
             except (TypeError, ValueError):
                 pass
             else:
-                if iterable(a) and iterable(b):
+                if np.iterable(a) and np.iterable(b):
                     # using list comps rather than arrays to preserve units
                     low = [thisx - thiserr for thisx, thiserr
                            in cbook.safezip(data, a)]
@@ -4437,7 +4436,7 @@ def hexbin(self, x, y, C=None, gridsize=100, bins=None,
         x, y, C = cbook.delete_masked_points(x, y, C)
 
         # Set the size of the hexagon grid
-        if iterable(gridsize):
+        if np.iterable(gridsize):
             nx, ny = gridsize
         else:
             nx = gridsize
@@ -4632,7 +4631,7 @@ def hexbin(self, x, y, C=None, gridsize=100, bins=None,
                 norm.autoscale(accum)
 
         if bins is not None:
-            if not iterable(bins):
+            if not np.iterable(bins):
                 minimum, maximum = min(accum), max(accum)
                 bins -= 1  # one less edge than bins
                 bins = minimum + (maximum - minimum) * np.arange(bins) / bins
@@ -6514,7 +6513,7 @@ def hist(self, x, bins=None, range=None, density=None, weights=None,
             bin_range = self.convert_xunits(bin_range)
 
         # Check whether bins or range are given explicitly.
-        binsgiven = (cbook.iterable(bins) or bin_range is not None)
+        binsgiven = np.iterable(bins) or bin_range is not None
 
         # We need to do to 'weights' what was done to 'x'
         if weights is not None:

lib/matplotlib/axes/_base.py

@@ -13,7 +13,7 @@
 
 from matplotlib import cbook, rcParams
 from matplotlib.cbook import (
-    _OrderedSet, _check_1d, _string_to_bool, iterable, index_of, get_label)
+    _OrderedSet, _check_1d, _string_to_bool, index_of, get_label)
 from matplotlib import docstring
 import matplotlib.colors as mcolors
 import matplotlib.lines as mlines
@@ -3005,7 +3005,7 @@ def set_xbound(self, lower=None, upper=None):
 
         .. ACCEPTS: (lower: float, upper: float)
         """
-        if upper is None and iterable(lower):
+        if upper is None and np.iterable(lower):
             lower, upper = lower
 
         old_lower, old_upper = self.get_xbound()
@@ -3124,7 +3124,7 @@ def set_xlim(self, left=None, right=None, emit=True, auto=False,
         >>> set_xlim(5000, 0)
 
         """
-        if right is None and iterable(left):
+        if right is None and np.iterable(left):
             left, right = left
         if xmin is not None:
             cbook.warn_deprecated('3.0', name='`xmin`',
@@ -3357,7 +3357,7 @@ def set_ybound(self, lower=None, upper=None):
 
         .. ACCEPTS: (lower: float, upper: float)
         """
-        if upper is None and iterable(lower):
+        if upper is None and np.iterable(lower):
             lower, upper = lower
 
         old_lower, old_upper = self.get_ybound()
@@ -3457,7 +3457,7 @@ def set_ylim(self, bottom=None, top=None, emit=True, auto=False,
 
         >>> set_ylim(5000, 0)
         """
-        if top is None and iterable(bottom):
+        if top is None and np.iterable(bottom):
             bottom, top = bottom
         if ymin is not None:
             cbook.warn_deprecated('3.0', name='`ymin`',

lib/matplotlib/cbook/__init__.py

@@ -327,6 +327,7 @@ class is even handier, and prettier to use.  Whenever you want to
     pass
 
 
+@deprecated('3.1', alternative='np.iterable')
 def iterable(obj):
     """return true if *obj* is iterable"""
     try:
@@ -415,7 +416,7 @@ def open_file_cm(path_or_file, mode="r", encoding=None):
 
 def is_scalar_or_string(val):
     """Return whether the given object is a scalar or string like."""
-    return isinstance(val, str) or not iterable(val)
+    return isinstance(val, str) or not np.iterable(val)
 
 
 def _string_to_bool(s):
@@ -1026,7 +1027,7 @@ def delete_masked_points(*args):
     margs = []
     seqlist = [False] * len(args)
     for i, x in enumerate(args):
-        if not isinstance(x, str) and iterable(x) and len(x) == nrecs:
+        if not isinstance(x, str) and np.iterable(x) and len(x) == nrecs:
             seqlist[i] = True
             if isinstance(x, np.ma.MaskedArray):
                 if x.ndim > 1:

lib/matplotlib/colorbar.py

@@ -388,7 +388,7 @@ def __init__(self, ax, cmap=None,
         self.ticklocation = ticklocation
 
         self.set_label(label)
-        if cbook.iterable(ticks):
+        if np.iterable(ticks):
             self.locator = ticker.FixedLocator(ticks, nbins=len(ticks))
         else:
             self.locator = ticks    # Handle default in _ticker()
@@ -559,7 +559,7 @@ def set_ticks(self, ticks, update_ticks=True):
             use :meth:`update_ticks` to manually update the ticks.
 
         """
-        if cbook.iterable(ticks):
+        if np.iterable(ticks):
             self.locator = ticker.FixedLocator(ticks, nbins=len(ticks))
         else:
             self.locator = ticks
@@ -707,9 +707,9 @@ def add_lines(self, levels, colors, linewidths, erase=True):
         y = self._locate(levels)
         igood = (y < 1.001) & (y > -0.001)
         y = y[igood]
-        if cbook.iterable(colors):
+        if np.iterable(colors):
             colors = np.asarray(colors)[igood]
-        if cbook.iterable(linewidths):
+        if np.iterable(linewidths):
             linewidths = np.asarray(linewidths)[igood]
         X, Y = np.meshgrid([0, 1], y)
         if self.orientation == 'vertical':
@@ -1289,7 +1289,7 @@ def make_axes(parents, location=None, orientation=None, fraction=0.15,
     anchor = kw.pop('anchor', loc_settings['anchor'])
     parent_anchor = kw.pop('panchor', loc_settings['panchor'])
 
-    parents_iterable = cbook.iterable(parents)
+    parents_iterable = np.iterable(parents)
     # turn parents into a list if it is not already. We do this w/ np
     # because `plt.subplots` can return an ndarray and is natural to
     # pass to `colorbar`.

lib/matplotlib/colors.py

@@ -484,7 +484,7 @@ def __call__(self, X, alpha=None, bytes=False):
         if not self._isinit:
             self._init()
         mask_bad = None
-        if not cbook.iterable(X):
+        if not np.iterable(X):
             vtype = 'scalar'
             xa = np.array([X])
         else:
@@ -716,7 +716,7 @@ def from_list(name, colors, N=256, gamma=1.0):
         to divide the range unevenly.
         """
 
-        if not cbook.iterable(colors):
+        if not np.iterable(colors):
             raise ValueError('colors must be iterable')
 
         if (isinstance(colors[0], Sized) and len(colors[0]) == 2
@@ -812,7 +812,7 @@ def __init__(self, colors, name='from_list', N=None):
             if isinstance(colors, str):
                 self.colors = [colors] * N
                 self.monochrome = True
-            elif cbook.iterable(colors):
+            elif np.iterable(colors):
                 if len(colors) == 1:
                     self.monochrome = True
                 self.colors = list(
@@ -907,7 +907,7 @@ def process_value(value):
         Experimental; we may want to add an option to force the
         use of float32.
         """
-        is_scalar = not cbook.iterable(value)
+        is_scalar = not np.iterable(value)
         if is_scalar:
             value = [value]
         dtype = np.min_scalar_type(value)
@@ -962,7 +962,7 @@ def inverse(self, value):
         (vmin,), _ = self.process_value(self.vmin)
         (vmax,), _ = self.process_value(self.vmax)
 
-        if cbook.iterable(value):
+        if np.iterable(value):
             val = np.ma.asarray(value)
             return vmin + val * (vmax - vmin)
         else:
@@ -1035,7 +1035,7 @@ def inverse(self, value):
             raise ValueError("Not invertible until scaled")
         vmin, vmax = self.vmin, self.vmax
 
-        if cbook.iterable(value):
+        if np.iterable(value):
             val = np.ma.asarray(value)
             return vmin * np.ma.power((vmax / vmin), val)
         else:
@@ -1222,7 +1222,7 @@ def inverse(self, value):
         gamma = self.gamma
         vmin, vmax = self.vmin, self.vmax
 
-        if cbook.iterable(value):
+        if np.iterable(value):
             val = np.ma.asarray(value)
             return np.ma.power(val, 1. / gamma) * (vmax - vmin) + vmin
         else: