Use shorter function names (min, max, abs, conj).

Author: anntzer

examples/api/collections_demo.py

@@ -89,9 +89,8 @@
 
 # 7-sided regular polygons
 
-col = collections.RegularPolyCollection(7,
-                                        sizes=np.fabs(xx) * 10.0, offsets=xyo,
-                                        transOffset=ax3.transData)
+col = collections.RegularPolyCollection(
+    7, sizes=np.abs(xx) * 10.0, offsets=xyo, transOffset=ax3.transData)
 trans = transforms.Affine2D().scale(fig.dpi / 72.0)
 col.set_transform(trans)  # the points to pixels transform
 ax3.add_collection(col, autolim=True)
@@ -109,7 +108,7 @@
 offs = (0.1, 0.0)
 
 yy = np.linspace(0, 2*np.pi, nverts)
-ym = np.amax(yy)
+ym = np.max(yy)
 xx = (0.2 + (ym - yy)/ym)**2 * np.cos(yy - 0.4)*0.5
 segs = []
 for i in range(ncurves):

examples/api/sankey_demo_old.py

@@ -37,11 +37,11 @@ def sankey(ax,
     import matplotlib.patches as mpatches
     from matplotlib.path import Path
 
-    outs = np.absolute(outputs)
+    outs = np.abs(outputs)
     outsigns = np.sign(outputs)
     outsigns[-1] = 0  # Last output
 
-    ins = np.absolute(inputs)
+    ins = np.abs(inputs)
     insigns = np.sign(inputs)
     insigns[0] = 0  # First input
 

examples/event_handling/poly_editor.py

@@ -70,8 +70,8 @@ def get_ind_under_point(self, event):
         xy = np.asarray(self.poly.xy)
         xyt = self.poly.get_transform().transform(xy)
         xt, yt = xyt[:, 0], xyt[:, 1]
-        d = np.sqrt((xt - event.x)**2 + (yt - event.y)**2)
-        indseq = np.nonzero(np.equal(d, np.amin(d)))[0]
+        d = np.hypot(xt - event.x, yt - event.y)
+        indseq, = np.nonzero(d == d.min())
         ind = indseq[0]
 
         if d[ind] >= self.epsilon:

examples/pylab_examples/anscombe.py

@@ -22,7 +22,7 @@ def fit(x):
     return 3 + 0.5*x
 
 
-xfit = np.array([np.amin(x), np.amax(x)])
+xfit = np.array([np.min(x), np.max(x)])
 
 plt.subplot(221)
 plt.plot(x, y1, 'ks', xfit, fit(xfit), 'r-', lw=2)
@@ -43,8 +43,7 @@ def fit(x):
 plt.setp(plt.gca(), yticks=(4, 8, 12), xticks=(0, 10, 20))
 
 plt.subplot(224)
-
-xfit = np.array([np.amin(x4), np.amax(x4)])
+xfit = np.array([np.min(x4), np.max(x4)])
 plt.plot(x4, y4, 'ks', xfit, fit(xfit), 'r-', lw=2)
 plt.axis([2, 20, 2, 14])
 plt.setp(plt.gca(), yticklabels=[], yticks=(4, 8, 12), xticks=(0, 10, 20))

examples/pylab_examples/axes_demo.py

@@ -14,7 +14,7 @@
 
 # the main axes is subplot(111) by default
 plt.plot(t, s)
-plt.axis([0, 1, 1.1*np.amin(s), 2*np.amax(s)])
+plt.axis([0, 1, 1.1 * np.min(s), 2 * np.max(s)])
 plt.xlabel('time (s)')
 plt.ylabel('current (nA)')
 plt.title('Gaussian colored noise')

examples/pylab_examples/layer_images.py

@@ -23,9 +23,7 @@ def func3(x, y):
 # for the images their apparent extent could be different due to
 # interpolation edge effects
 
-
-xmin, xmax, ymin, ymax = np.amin(x), np.amax(x), np.amin(y), np.amax(y)
-extent = xmin, xmax, ymin, ymax
+extent = np.min(x), np.max(x), np.min(y), np.max(y)
 fig = plt.figure(frameon=False)
 
 Z1 = np.add.outer(range(8), range(8)) % 2  # chessboard

examples/pylab_examples/line_collection2.py

@@ -13,8 +13,8 @@
 
 # We need to set the plot limits, they will not autoscale
 ax = plt.axes()
-ax.set_xlim((np.amin(x), np.amax(x)))
-ax.set_ylim((np.amin(np.amin(ys)), np.amax(np.amax(ys))))
+ax.set_xlim(np.min(x), np.max(x))
+ax.set_ylim(np.min(ys), np.max(ys))
 
 # colors is sequence of rgba tuples
 # linestyle is a string or dash tuple. Legal string values are

examples/pylab_examples/multi_image.py

@@ -7,8 +7,7 @@
 from matplotlib.pyplot import figure, show, axes, sci
 from matplotlib import cm, colors
 from matplotlib.font_manager import FontProperties
-from numpy import amin, amax, ravel
-from numpy.random import rand
+import numpy as np
 
 Nr = 3
 Nc = 2
@@ -37,12 +36,12 @@
             a.set_xticklabels([])
         # Make some fake data with a range that varies
         # somewhat from one plot to the next.
-        data = ((1 + i + j)/10.0)*rand(10, 20)*1e-6
-        dd = ravel(data)
+        data = ((1 + i + j) / 10) * np.random.rand(10, 20) * 1e-6
+        dd = data.ravel()
         # Manually find the min and max of all colors for
         # use in setting the color scale.
-        vmin = min(vmin, amin(dd))
-        vmax = max(vmax, amax(dd))
+        vmin = min(vmin, np.min(dd))
+        vmax = max(vmax, np.max(dd))
         images.append(a.imshow(data, cmap=cmap))
 
         ax.append(a)

examples/pylab_examples/quadmesh_demo.py

@@ -21,8 +21,7 @@
 Z = (Z - Z.min()) / (Z.max() - Z.min())
 
 # The color array can include masked values:
-Zm = ma.masked_where(np.fabs(Qz) < 0.5*np.amax(Qz), Z)
-
+Zm = ma.masked_where(np.abs(Qz) < 0.5 * np.max(Qz), Z)
 
 fig = figure()
 ax = fig.add_subplot(121)

examples/pylab_examples/vline_hline_demo.py

@@ -10,7 +10,7 @@
 def f(t):
     s1 = np.sin(2 * np.pi * t)
     e1 = np.exp(-t)
-    return np.absolute((s1 * e1)) + .05
+    return np.abs(s1 * e1) + .05
 
 t = np.arange(0.0, 5.0, 0.1)
 s = f(t)

examples/user_interfaces/embedding_in_wx3.py

@@ -74,7 +74,7 @@ def init_plot_data(self):
         z = np.sin(self.x) + np.cos(self.y)
         self.im = a.imshow(z, cmap=cm.RdBu)  # , interpolation='nearest')
 
-        zmax = np.amax(z) - ERR_TOL
+        zmax = np.max(z) - ERR_TOL
         ymax_i, xmax_i = np.nonzero(z >= zmax)
         if self.im.origin == 'upper':
             ymax_i = z.shape[0] - ymax_i
@@ -93,7 +93,7 @@ def OnWhiz(self, evt):
         z = np.sin(self.x) + np.cos(self.y)
         self.im.set_array(z)
 
-        zmax = np.amax(z) - ERR_TOL
+        zmax = np.max(z) - ERR_TOL
         ymax_i, xmax_i = np.nonzero(z >= zmax)
         if self.im.origin == 'upper':
             ymax_i = z.shape[0] - ymax_i

lib/matplotlib/axes/_axes.py

@@ -2460,7 +2460,7 @@ def stem(self, *args, **kwargs):
                            marker=linemarker, label="_nolegend_")
             stemlines.append(l)
 
-        baseline, = self.plot([np.amin(x), np.amax(x)], [bottom, bottom],
+        baseline, = self.plot([np.min(x), np.max(x)], [bottom, bottom],
                               color=basecolor, linestyle=basestyle,
                               marker=basemarker, label="_nolegend_")
 
@@ -4228,8 +4228,8 @@ def hexbin(self, x, y, C=None, gridsize=100, bins=None,
         if extent is not None:
             xmin, xmax, ymin, ymax = extent
         else:
-            xmin, xmax = (np.amin(x), np.amax(x)) if len(x) else (0, 1)
-            ymin, ymax = (np.amin(y), np.amax(y)) if len(y) else (0, 1)
+            xmin, xmax = (np.min(x), np.max(x)) if len(x) else (0, 1)
+            ymin, ymax = (np.min(y), np.max(y)) if len(y) else (0, 1)
 
             # to avoid issues with singular data, expand the min/max pairs
             xmin, xmax = mtrans.nonsingular(xmin, xmax, expander=0.1)
@@ -5470,10 +5470,10 @@ def pcolor(self, *args, **kwargs):
 
         self.add_collection(collection, autolim=False)
 
-        minx = np.amin(x)
-        maxx = np.amax(x)
-        miny = np.amin(y)
-        maxy = np.amax(y)
+        minx = np.min(x)
+        maxx = np.max(x)
+        miny = np.min(y)
+        maxy = np.max(y)
         collection.sticky_edges.x[:] = [minx, maxx]
         collection.sticky_edges.y[:] = [miny, maxy]
         corners = (minx, miny), (maxx, maxy)
@@ -5622,10 +5622,10 @@ def pcolormesh(self, *args, **kwargs):
 
         self.add_collection(collection, autolim=False)
 
-        minx = np.amin(X)
-        maxx = np.amax(X)
-        miny = np.amin(Y)
-        maxy = np.amax(Y)
+        minx = np.min(X)
+        maxx = np.max(X)
+        miny = np.min(Y)
+        maxy = np.max(Y)
         collection.sticky_edges.x[:] = [minx, maxx]
         collection.sticky_edges.y[:] = [miny, maxy]
         corners = (minx, miny), (maxx, maxy)
@@ -6386,7 +6386,7 @@ def _normalize_input(inp, ename='input'):
         else:
             labels = [six.text_type(lab) for lab in label]
 
-        for (patch, lbl) in zip_longest(patches, labels, fillvalue=None):
+        for patch, lbl in zip_longest(patches, labels, fillvalue=None):
             if patch:
                 p = patch[0]
                 p.update(kwargs)
@@ -6724,7 +6724,7 @@ def csd(self, x, y, NFFT=None, Fs=None, Fc=None, detrend=None,
         # pxy is complex
         freqs += Fc
 
-        line = self.plot(freqs, 10 * np.log10(np.absolute(pxy)), **kwargs)
+        line = self.plot(freqs, 10 * np.log10(np.abs(pxy)), **kwargs)
         self.set_xlabel('Frequency')
         self.set_ylabel('Cross Spectrum Magnitude (dB)')
         self.grid(True)
@@ -7227,7 +7227,7 @@ def specgram(self, x, NFFT=None, Fs=None, Fc=None, detrend=None,
         Z = np.flipud(Z)
 
         if xextent is None:
-            xextent = 0, np.amax(t)
+            xextent = 0, np.max(t)
         xmin, xmax = xextent
         freqs += Fc
         extent = xmin, xmax, freqs[0], freqs[-1]
@@ -7300,7 +7300,7 @@ def spy(self, Z, precision=0, marker=None, markersize=None,
             marker = 's'
         if marker is None and markersize is None:
             Z = np.asarray(Z)
-            mask = np.absolute(Z) > precision
+            mask = np.abs(Z) > precision
 
             if 'cmap' not in kwargs:
                 kwargs['cmap'] = mcolors.ListedColormap(['w', 'k'],
@@ -7316,12 +7316,12 @@ def spy(self, Z, precision=0, marker=None, markersize=None,
                     y = c.row
                     x = c.col
                 else:
-                    nonzero = np.absolute(c.data) > precision
+                    nonzero = np.abs(c.data) > precision
                     y = c.row[nonzero]
                     x = c.col[nonzero]
             else:
                 Z = np.asarray(Z)
-                nonzero = np.absolute(Z) > precision
+                nonzero = np.abs(Z) > precision
                 y, x = np.nonzero(nonzero)
             if marker is None:
                 marker = 's'

lib/matplotlib/axes/_base.py

@@ -1346,8 +1346,8 @@ def get_data_ratio(self):
         xmin, xmax = self.get_xbound()
         ymin, ymax = self.get_ybound()
 
-        xsize = max(math.fabs(xmax - xmin), 1e-30)
-        ysize = max(math.fabs(ymax - ymin), 1e-30)
+        xsize = max(abs(xmax - xmin), 1e-30)
+        ysize = max(abs(ymax - ymin), 1e-30)
 
         return ysize / xsize
 
@@ -1359,8 +1359,8 @@ def get_data_ratio_log(self):
         xmin, xmax = self.get_xbound()
         ymin, ymax = self.get_ybound()
 
-        xsize = max(math.fabs(math.log10(xmax) - math.log10(xmin)), 1e-30)
-        ysize = max(math.fabs(math.log10(ymax) - math.log10(ymin)), 1e-30)
+        xsize = max(abs(math.log10(xmax) - math.log10(xmin)), 1e-30)
+        ysize = max(abs(math.log10(ymax) - math.log10(ymin)), 1e-30)
 
         return ysize / xsize
 
@@ -1432,8 +1432,8 @@ def apply_aspect(self, position=None):
             xmin, xmax = math.log10(xmin), math.log10(xmax)
             ymin, ymax = math.log10(ymin), math.log10(ymax)
 
-        xsize = max(math.fabs(xmax - xmin), 1e-30)
-        ysize = max(math.fabs(ymax - ymin), 1e-30)
+        xsize = max(abs(xmax - xmin), 1e-30)
+        ysize = max(abs(ymax - ymin), 1e-30)
 
         l, b, w, h = position.bounds
         box_aspect = fig_aspect * (h / w)

lib/matplotlib/contour.py

@@ -226,20 +226,8 @@ def clabel(self, *args, **kwargs):
 
     def print_label(self, linecontour, labelwidth):
         "Return *False* if contours are too short for a label."
-        lcsize = len(linecontour)
-        if lcsize > 10 * labelwidth:
-            return True
-
-        xmax = np.amax(linecontour[:, 0])
-        xmin = np.amin(linecontour[:, 0])
-        ymax = np.amax(linecontour[:, 1])
-        ymin = np.amin(linecontour[:, 1])
-
-        lw = labelwidth
-        if (xmax - xmin) > 1.2 * lw or (ymax - ymin) > 1.2 * lw:
-            return True
-        else:
-            return False
+        return (len(linecontour) > 10 * labelwidth
+                or (np.ptp(linecontour, axis=0) > 1.2 * labelwidth).any())
 
     def too_close(self, x, y, lw):
         "Return *True* if a label is already near this location."
@@ -1056,8 +1044,8 @@ def _process_args(self, *args, **kwargs):
         self.levels = args[0]
         self.allsegs = args[1]
         self.allkinds = len(args) > 2 and args[2] or None
-        self.zmax = np.amax(self.levels)
-        self.zmin = np.amin(self.levels)
+        self.zmax = np.max(self.levels)
+        self.zmin = np.min(self.levels)
         self._auto = False
 
         # Check lengths of levels and allsegs.
@@ -1180,7 +1168,7 @@ def _contour_level_args(self, z, args):
         if self.filled and len(self.levels) < 2:
             raise ValueError("Filled contours require at least 2 levels.")
 
-        if len(self.levels) > 1 and np.amin(np.diff(self.levels)) <= 0.0:
+        if len(self.levels) > 1 and np.min(np.diff(self.levels)) <= 0.0:
             if hasattr(self, '_corner_mask') and self._corner_mask == 'legacy':
                 warnings.warn("Contour levels are not increasing")
             else:
@@ -1210,8 +1198,8 @@ def _process_levels(self):
         with line contours.
         """
         # following are deprecated and will be removed in 2.2
-        self._vmin = np.amin(self.levels)
-        self._vmax = np.amax(self.levels)
+        self._vmin = np.min(self.levels)
+        self._vmax = np.max(self.levels)
 
         # Make a private _levels to include extended regions; we
         # want to leave the original levels attribute unchanged.

lib/matplotlib/legend_handler.py

@@ -551,7 +551,7 @@ def create_artists(self, legend, orig_handle,
         for lm, m in zip(leg_stemlines, stemlines):
             self.update_prop(lm, m, legend)
 
-        leg_baseline = Line2D([np.amin(xdata), np.amax(xdata)],
+        leg_baseline = Line2D([np.min(xdata), np.max(xdata)],
                               [bottom, bottom])
 
         self.update_prop(leg_baseline, baseline, legend)