Use np.full{,_like} where appropriate.

anntzer · anntzer · commit 75512c55bfbd · 2018-02-22T21:59:45.000-08:00
diff --git a/examples/animation/animated_histogram.py b/examples/animation/animated_histogram.py
@@ -45,7 +45,7 @@
 #   in the ``verts`` array to keep the codes aligned with the vertices.
 nverts = nrects * (1 + 3 + 1)
 verts = np.zeros((nverts, 2))
-codes = np.ones(nverts, int) * path.Path.LINETO
+codes = np.full(nverts, path.Path.LINETO)
 codes[0::5] = path.Path.MOVETO
 codes[4::5] = path.Path.CLOSEPOLY
 verts[0::5, 0] = left
diff --git a/examples/api/donut.py b/examples/api/donut.py
@@ -32,8 +32,7 @@ def make_circle(r):
 
 inside_vertices = make_circle(0.5)
 outside_vertices = make_circle(1.0)
-codes = np.ones(
-    len(inside_vertices), dtype=mpath.Path.code_type) * mpath.Path.LINETO
+codes = np.full(len(inside_vertices), mpath.Path.LINETO)
 codes[0] = mpath.Path.MOVETO
 
 for i, (inside, outside) in enumerate(((1, 1), (1, -1), (-1, 1), (-1, -1))):
diff --git a/examples/api/filled_step.py b/examples/api/filled_step.py
@@ -63,7 +63,7 @@ def filled_hist(ax, edges, values, bottoms=None, orientation='v',
     if bottoms is None:
         bottoms = np.zeros_like(values)
     if np.isscalar(bottoms):
-        bottoms = np.ones_like(values) * bottoms
+        bottoms = np.full_like(values, bottoms)
 
     values = np.r_[values, values[-1]]
     bottoms = np.r_[bottoms, bottoms[-1]]
diff --git a/examples/mplot3d/hist3d.py b/examples/mplot3d/hist3d.py
@@ -29,8 +29,7 @@
 zpos = np.zeros_like(xpos)
 
 # Construct arrays with the dimensions for the 16 bars.
-dx = 0.5 * np.ones_like(zpos)
-dy = dx.copy()
+dx = dy = np.full_like(zpos, .5)
 dz = hist.flatten()
 
 ax.bar3d(xpos, ypos, zpos, dx, dy, dz, color='b', zsort='average')
diff --git a/examples/pyplots/boxplot_demo_pyplot.py b/examples/pyplots/boxplot_demo_pyplot.py
@@ -14,7 +14,7 @@
 
 # fake up some data
 spread = np.random.rand(50) * 100
-center = np.ones(25) * 50
+center = np.full(25, 50)
 flier_high = np.random.rand(10) * 100 + 100
 flier_low = np.random.rand(10) * -100
 data = np.concatenate((spread, center, flier_high, flier_low), 0)
@@ -61,7 +61,7 @@
 # Fake up some more data
 
 spread = np.random.rand(50) * 100
-center = np.ones(25) * 40
+center = np.full(25, 40)
 flier_high = np.random.rand(10) * 100 + 100
 flier_low = np.random.rand(10) * -100
 d2 = np.concatenate((spread, center, flier_high, flier_low), 0)
diff --git a/examples/pyplots/compound_path_demo.py b/examples/pyplots/compound_path_demo.py
@@ -29,7 +29,7 @@
 
 nverts = nrects*(1+3+1)
 verts = np.zeros((nverts, 2))
-codes = np.ones(nverts, int) * path.Path.LINETO
+codes = np.full(nverts, path.Path.LINETO)
 codes[0::5] = path.Path.MOVETO
 codes[4::5] = path.Path.CLOSEPOLY
 verts[0::5,0] = left
diff --git a/examples/specialty_plots/leftventricle_bulleye.py b/examples/specialty_plots/leftventricle_bulleye.py
@@ -78,7 +78,7 @@ def bullseye_plot(ax, data, segBold=None, cmap=None, norm=None):
         # First segment start at 60 degrees
         theta0 = theta[i * 128:i * 128 + 128] + np.deg2rad(60)
         theta0 = np.repeat(theta0[:, np.newaxis], 2, axis=1)
-        z = np.ones((128, 2)) * data[i]
+        z = np.full((128, 2), data[i])
         ax.pcolormesh(theta0, r0, z, cmap=cmap, norm=norm)
         if i + 1 in segBold:
             ax.plot(theta0, r0, '-k', lw=linewidth + 2)
@@ -92,7 +92,7 @@ def bullseye_plot(ax, data, segBold=None, cmap=None, norm=None):
         # First segment start at 60 degrees
         theta0 = theta[i * 128:i * 128 + 128] + np.deg2rad(60)
         theta0 = np.repeat(theta0[:, np.newaxis], 2, axis=1)
-        z = np.ones((128, 2)) * data[i + 6]
+        z = np.full((128, 2), data[i + 6])
         ax.pcolormesh(theta0, r0, z, cmap=cmap, norm=norm)
         if i + 7 in segBold:
             ax.plot(theta0, r0, '-k', lw=linewidth + 2)
@@ -106,7 +106,7 @@ def bullseye_plot(ax, data, segBold=None, cmap=None, norm=None):
         # First segment start at 45 degrees
         theta0 = theta[i * 192:i * 192 + 192] + np.deg2rad(45)
         theta0 = np.repeat(theta0[:, np.newaxis], 2, axis=1)
-        z = np.ones((192, 2)) * data[i + 12]
+        z = np.full((192, 2), data[i + 12])
         ax.pcolormesh(theta0, r0, z, cmap=cmap, norm=norm)
         if i + 13 in segBold:
             ax.plot(theta0, r0, '-k', lw=linewidth + 2)
@@ -118,7 +118,7 @@ def bullseye_plot(ax, data, segBold=None, cmap=None, norm=None):
         r0 = np.array([0, r[0]])
         r0 = np.repeat(r0[:, np.newaxis], theta.size, axis=1).T
         theta0 = np.repeat(theta[:, np.newaxis], 2, axis=1)
-        z = np.ones((theta.size, 2)) * data[16]
+        z = np.full((theta.size, 2), data[16])
         ax.pcolormesh(theta0, r0, z, cmap=cmap, norm=norm)
         if 17 in segBold:
             ax.plot(theta0, r0, '-k', lw=linewidth + 2)
diff --git a/examples/statistics/boxplot_demo.py b/examples/statistics/boxplot_demo.py
@@ -20,7 +20,7 @@
 
 # fake up some data
 spread = np.random.rand(50) * 100
-center = np.ones(25) * 50
+center = np.full(25, 50)
 flier_high = np.random.rand(10) * 100 + 100
 flier_low = np.random.rand(10) * -100
 data = np.concatenate((spread, center, flier_high, flier_low), 0)
@@ -56,7 +56,7 @@
 
 # fake up some more data
 spread = np.random.rand(50) * 100
-center = np.ones(25) * 40
+center = np.full(25, 40)
 flier_high = np.random.rand(10) * 100 + 100
 flier_low = np.random.rand(10) * -100
 d2 = np.concatenate((spread, center, flier_high, flier_low), 0)
diff --git a/examples/text_labels_and_annotations/legend_demo.py b/examples/text_labels_and_annotations/legend_demo.py
@@ -135,7 +135,7 @@ def create_artists(self, legend, orig_handle,
         leglines = []
         # divide the vertical space where the lines will go
         # into equal parts based on the number of lines
-        ydata = ((height) / (numlines + 1)) * np.ones(xdata.shape, float)
+        ydata = np.full_like(xdata, height / (numlines + 1))
         # for each line, create the line at the proper location
         # and set the dash pattern
         for i in range(numlines):
diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
@@ -3958,16 +3958,16 @@ def dopatch(xs, ys, **kwargs):
             datalabels.append(stats.get('label', pos))
 
             # whisker coords
-            whisker_x = np.ones(2) * pos
+            whisker_x = np.full(2, pos)
             whiskerlo_y = np.array([stats['q1'], stats['whislo']])
             whiskerhi_y = np.array([stats['q3'], stats['whishi']])
 
             # cap coords
             cap_left = pos - width * 0.25
             cap_right = pos + width * 0.25
             cap_x = np.array([cap_left, cap_right])
-            cap_lo = np.ones(2) * stats['whislo']
-            cap_hi = np.ones(2) * stats['whishi']
+            cap_lo = np.full(2, stats['whislo'])
+            cap_hi = np.full(2, stats['whishi'])
 
             # box and median coords
             box_left = pos - width * 0.5
@@ -4030,7 +4030,7 @@ def dopatch(xs, ys, **kwargs):
             # maybe draw the fliers
             if showfliers:
                 # fliers coords
-                flier_x = np.ones(len(stats['fliers'])) * pos
+                flier_x = np.full(len(stats['fliers']), pos)
                 flier_y = stats['fliers']
 
                 fliers.extend(doplot(
diff --git a/lib/matplotlib/collections.py b/lib/matplotlib/collections.py
@@ -979,8 +979,8 @@ def set_verts(self, verts, closed=True):
                     else:
                         xy = np.asarray(xy)
                         xy = np.concatenate([xy, xy[0:1]])
-                    codes = np.empty(xy.shape[0], dtype=mpath.Path.code_type)
-                    codes[:] = mpath.Path.LINETO
+                    codes = np.full(xy.shape[0], mpath.Path.LINETO,
+                                    dtype=mpath.Path.code_type)
                     codes[0] = mpath.Path.MOVETO
                     codes[-1] = mpath.Path.CLOSEPOLY
                     self._paths.append(mpath.Path(xy, codes))
diff --git a/lib/matplotlib/hatch.py b/lib/matplotlib/hatch.py
@@ -174,7 +174,7 @@ def __init__(self, hatch, density):
         self.num_rows = (hatch.count('*')) * density
         path = Path.unit_regular_star(5)
         self.shape_vertices = path.vertices
-        self.shape_codes = np.ones(len(self.shape_vertices)) * Path.LINETO
+        self.shape_codes = np.full(len(self.shape_vertices), Path.LINETO)
         self.shape_codes[0] = Path.MOVETO
         Shapes.__init__(self, hatch, density)
 
diff --git a/lib/matplotlib/legend_handler.py b/lib/matplotlib/legend_handler.py
@@ -235,7 +235,7 @@ def create_artists(self, legend, orig_handle,
         xdata, xdata_marker = self.get_xdata(legend, xdescent, ydescent,
                                              width, height, fontsize)
 
-        ydata = ((height - ydescent) / 2.) * np.ones(xdata.shape, float)
+        ydata = np.full_like(xdata, (height - ydescent) / 2)
         legline = Line2D(xdata, ydata)
 
         self.update_prop(legline, orig_handle, legend)
@@ -328,7 +328,7 @@ def create_artists(self, legend, orig_handle,
 
         xdata, xdata_marker = self.get_xdata(legend, xdescent, ydescent,
                                              width, height, fontsize)
-        ydata = ((height - ydescent) / 2.) * np.ones(xdata.shape, float)
+        ydata = np.full_like(xdata, (height - ydescent) / 2)
         legline = Line2D(xdata, ydata)
 
         self.update_prop(legline, orig_handle, legend)
@@ -470,7 +470,7 @@ def create_artists(self, legend, orig_handle,
         xdata, xdata_marker = self.get_xdata(legend, xdescent, ydescent,
                                              width, height, fontsize)
 
-        ydata = ((height - ydescent) / 2.) * np.ones(xdata.shape, float)
+        ydata = np.full_like(xdata, (height - ydescent) / 2)
         legline = Line2D(xdata, ydata)
 
         xdata_marker = np.asarray(xdata_marker)
diff --git a/lib/matplotlib/path.py b/lib/matplotlib/path.py
@@ -321,10 +321,10 @@ def make_compound_path_from_polys(cls, XY):
             raise ValueError("The third dimension of 'XY' must be 2")
         stride = numsides + 1
         nverts = numpolys * stride
-        verts = np.zeros((nverts, 2))
-        codes = np.ones(nverts, int) * cls.LINETO
+        codes = np.full(nverts, cls.LINETO)
         codes[0::stride] = cls.MOVETO
         codes[numsides::stride] = cls.CLOSEPOLY
+        verts = np.zeros((nverts, 2))
         for i in range(numsides):
             verts[i::stride] = XY[:, i]
 
@@ -572,7 +572,7 @@ def interpolated(self, steps):
         vertices = simple_linear_interpolation(self.vertices, steps)
         codes = self.codes
         if codes is not None:
-            new_codes = Path.LINETO * np.ones(((len(codes) - 1) * steps + 1, ))
+            new_codes = np.full((len(codes) - 1) * steps + 1, Path.LINETO)
             new_codes[0::steps] = codes
         else:
             new_codes = None
@@ -896,17 +896,17 @@ def arc(cls, theta1, theta2, n=None, is_wedge=False):
 
         if is_wedge:
             length = n * 3 + 4
-            vertices = np.zeros((length, 2), float)
-            codes = cls.CURVE4 * np.ones((length, ), cls.code_type)
+            vertices = np.zeros((length, 2))
+            codes = np.full(length, cls.CURVE4, cls.code_type)
             vertices[1] = [xA[0], yA[0]]
             codes[0:2] = [cls.MOVETO, cls.LINETO]
             codes[-2:] = [cls.LINETO, cls.CLOSEPOLY]
             vertex_offset = 2
             end = length - 2
         else:
             length = n * 3 + 1
-            vertices = np.empty((length, 2), float)
-            codes = cls.CURVE4 * np.ones((length, ), cls.code_type)
+            vertices = np.empty((length, 2))
+            codes = np.full(length, cls.CURVE4, cls.code_type)
             vertices[0] = [xA[0], yA[0]]
             codes[0] = cls.MOVETO
             vertex_offset = 1
diff --git a/lib/matplotlib/tests/test_axes.py b/lib/matplotlib/tests/test_axes.py
@@ -1511,7 +1511,7 @@ def test_hist_steplog():
     data += -2.0 - np.min(data)
     data_pos = data + 2.1
     data_big = data_pos + 30
-    weights = np.ones_like(data) * 1.e-5
+    weights = np.full_like(data, 1e-5)
 
     ax = plt.subplot(4, 1, 1)
     plt.hist(data, 100, histtype='stepfilled', log=True)
@@ -4931,7 +4931,7 @@ def test_violin_point_mass():
 
 
 def generate_errorbar_inputs():
-    base_xy = cycler('x', [np.arange(5)]) + cycler('y', [np.ones((5, ))])
+    base_xy = cycler('x', [np.arange(5)]) + cycler('y', [np.ones(5)])
     err_cycler = cycler('err', [1,
                                 [1, 1, 1, 1, 1],
                                 [[1, 1, 1, 1, 1],
diff --git a/lib/matplotlib/tests/test_collections.py b/lib/matplotlib/tests/test_collections.py
@@ -454,7 +454,7 @@ def test_EllipseCollection():
 
     ww = X / x[-1]
     hh = Y / y[-1]
-    aa = np.ones_like(ww) * 20  # first axis is 20 degrees CCW from x axis
+    aa = np.full_like(ww, 20)  # first axis is 20 degrees CCW from x axis
 
     ec = mcollections.EllipseCollection(ww, hh, aa,
                                         units='x',
diff --git a/lib/matplotlib/tests/test_image.py b/lib/matplotlib/tests/test_image.py
@@ -896,12 +896,9 @@ def test_imshow_deprecated_interd_warn():
 
 
 def test_full_invalid():
-    x = np.ones((10, 10))
-    x[:] = np.nan
-
+    x = np.full((10, 10), np.nan)
     f, ax = plt.subplots()
     ax.imshow(x)
-
     f.canvas.draw()
 
 
diff --git a/lib/matplotlib/tests/test_legend.py b/lib/matplotlib/tests/test_legend.py
@@ -124,7 +124,7 @@ def test_labels_first():
     fig = plt.figure()
     ax = fig.add_subplot(111)
     ax.plot(np.arange(10), '-o', label=1)
-    ax.plot(np.ones(10)*5, ':x', label="x")
+    ax.plot(np.full(10, 5), ':x', label="x")
     ax.plot(np.arange(20, 10, -1), 'd', label="diamond")
     ax.legend(loc=0, markerfirst=False)
 
diff --git a/lib/matplotlib/tests/test_lines.py b/lib/matplotlib/tests/test_lines.py
@@ -189,7 +189,7 @@ def test_lw_scaling():
     cy = cycler(matplotlib.rcParams['axes.prop_cycle'])
     for j, (ls, sty) in enumerate(zip(lins_styles, cy)):
         for lw in np.linspace(.5, 10, 10):
-            ax.plot(th, j*np.ones(50) + .1 * lw, linestyle=ls, lw=lw, **sty)
+            ax.plot(th, np.full(50, j) + .1 * lw, linestyle=ls, lw=lw, **sty)
 
 
 def test_nan_is_sorted():
diff --git a/lib/matplotlib/tests/test_path.py b/lib/matplotlib/tests/test_path.py
@@ -123,7 +123,7 @@ def test_marker_paths_pdf():
     N = 7
 
     plt.errorbar(np.arange(N),
-                 np.ones(N) + 4,
+                 np.full(N, 5),
                  np.ones(N))
     plt.xlim(-1, N)
     plt.ylim(-1, 7)
diff --git a/lib/matplotlib/tests/test_quiver.py b/lib/matplotlib/tests/test_quiver.py
@@ -158,8 +158,8 @@ def test_bad_masked_sizes():
     'Test error handling when given differing sized masked arrays'
     x = np.arange(3)
     y = np.arange(3)
-    u = np.ma.array(15. * np.ones((4,)))
-    v = np.ma.array(15. * np.ones_like(u))
+    u = np.ma.array(np.full(4, 15.))
+    v = np.ma.array(np.full(4, 15.))
     u[1] = np.ma.masked
     v[1] = np.ma.masked
     fig, ax = plt.subplots()
diff --git a/lib/matplotlib/tests/test_triangulation.py b/lib/matplotlib/tests/test_triangulation.py
@@ -645,7 +645,7 @@ def test_triinterp_colinear():
         zs_target = 1.23*xs - 4.79*ys
         for interp in (linear_interp, cubic_min_E, cubic_geom):
             zs, = interp._interpolate_multikeys(
-                xs, ys, tri_index=itri*np.ones(10, dtype=np.int32))
+                xs, ys, tri_index=np.full(10, itri, dtype=np.int32))
             assert_array_almost_equal(zs_target, zs)
 
 
diff --git a/lib/matplotlib/text.py b/lib/matplotlib/text.py
@@ -335,8 +335,7 @@ def _get_layout(self, renderer):
         # get the rotation matrix
         M = Affine2D().rotate_deg(self.get_rotation())
 
-        offsetLayout = np.zeros((len(lines), 2))
-        offsetLayout[:] = horizLayout[:, 0:2]
+        offsetLayout = horizLayout[:, 0:2].copy()
         # now offset the individual text lines within the box
         if len(lines) > 1:  # do the multiline aligment
             malign = self._get_multialignment()
diff --git a/lib/matplotlib/tri/triinterpolate.py b/lib/matplotlib/tri/triinterpolate.py
@@ -684,7 +684,7 @@ class _ReducedHCT_Element():
                           [ 4./18.,  1./18., 13./18.],
                           [13./18.,  1./18.,  4./18.],
                           [ 7./18.,  4./18.,  7./18.]], dtype=np.float64)
-    gauss_w = np.ones([9], dtype=np.float64) / 9.
+    gauss_w = np.full(9, 1 / 9)
 
     #  4) Stiffness matrix for curvature energy
     E = np.array([[1., 0., 0.], [0., 1., 0.], [0., 0., 2.]])
diff --git a/tutorials/advanced/path_tutorial.py b/tutorials/advanced/path_tutorial.py
@@ -158,7 +158,7 @@
 #
 #     nverts = nrects*(1+3+1)
 #     verts = np.zeros((nverts, 2))
-#     codes = np.ones(nverts, int) * path.Path.LINETO
+#     codes = np.full(nverts, path.Path.LINETO)
 #     codes[0::5] = path.Path.MOVETO
 #     codes[4::5] = path.Path.CLOSEPOLY
 #     verts[0::5,0] = left
@@ -201,7 +201,7 @@
 
 nverts = nrects*(1+3+1)
 verts = np.zeros((nverts, 2))
-codes = np.ones(nverts, int) * path.Path.LINETO
+codes = np.full(nverts, path.Path.LINETO)
 codes[0::5] = path.Path.MOVETO
 codes[4::5] = path.Path.CLOSEPOLY
 verts[0::5, 0] = left
