Avoid setting dtypes as strings...

anntzer · anntzer · commit 3debddb5c8cc · 2019-12-20T18:13:38.000+01:00
... in cases where a builtin works just fine.

`dtype="d"` is the same as float, which is the default anyways.
diff --git a/examples/axes_grid1/demo_axes_rgb.py b/examples/axes_grid1/demo_axes_rgb.py
@@ -34,7 +34,7 @@ def get_rgb():
 
 def make_cube(r, g, b):
     ny, nx = r.shape
-    R = np.zeros([ny, nx, 3], dtype="d")
+    R = np.zeros((ny, nx, 3))
     R[:, :, 0] = r
     G = np.zeros_like(R)
     G[:, :, 1] = g
diff --git a/examples/axes_grid1/inset_locator_demo2.py b/examples/axes_grid1/inset_locator_demo2.py
@@ -56,9 +56,9 @@ def add_sizebar(ax, size):
 # Second subplot, showing an image with an inset zoom
 # and a marked inset
 Z, extent = get_demo_image()
-Z2 = np.zeros([150, 150], dtype="d")
+Z2 = np.zeros((150, 150))
 ny, nx = Z.shape
-Z2[30:30 + ny, 30:30 + nx] = Z
+Z2[30:30+ny, 30:30+nx] = Z
 
 # extent = [-3, 4, -4, 3]
 ax2.imshow(Z2, extent=extent, origin="lower")
diff --git a/examples/subplots_axes_and_figures/zoom_inset_axes.py b/examples/subplots_axes_and_figures/zoom_inset_axes.py
@@ -23,9 +23,9 @@ def get_demo_image():
 
 # make data
 Z, extent = get_demo_image()
-Z2 = np.zeros([150, 150], dtype="d")
+Z2 = np.zeros((150, 150))
 ny, nx = Z.shape
-Z2[30:30 + ny, 30:30 + nx] = Z
+Z2[30:30+ny, 30:30+nx] = Z
 
 ax.imshow(Z2, extent=extent, origin="lower")
 
diff --git a/lib/matplotlib/tests/test_cbook.py b/lib/matplotlib/tests/test_cbook.py
@@ -369,9 +369,9 @@ def test_to_prestep():
 
     xs, y1s, y2s = cbook.pts_to_prestep(x, y1, y2)
 
-    x_target = np.asarray([0, 0, 1, 1, 2, 2, 3], dtype='float')
-    y1_target = np.asarray([0, 1, 1, 2, 2, 3, 3], dtype='float')
-    y2_target = np.asarray([3, 2, 2, 1, 1, 0, 0], dtype='float')
+    x_target = np.asarray([0, 0, 1, 1, 2, 2, 3], dtype=float)
+    y1_target = np.asarray([0, 1, 1, 2, 2, 3, 3], dtype=float)
+    y2_target = np.asarray([3, 2, 2, 1, 1, 0, 0], dtype=float)
 
     assert_array_equal(x_target, xs)
     assert_array_equal(y1_target, y1s)
@@ -394,9 +394,9 @@ def test_to_poststep():
 
     xs, y1s, y2s = cbook.pts_to_poststep(x, y1, y2)
 
-    x_target = np.asarray([0, 1, 1, 2, 2, 3, 3], dtype='float')
-    y1_target = np.asarray([0, 0, 1, 1, 2, 2, 3], dtype='float')
-    y2_target = np.asarray([3, 3, 2, 2, 1, 1, 0], dtype='float')
+    x_target = np.asarray([0, 1, 1, 2, 2, 3, 3], dtype=float)
+    y1_target = np.asarray([0, 0, 1, 1, 2, 2, 3], dtype=float)
+    y2_target = np.asarray([3, 3, 2, 2, 1, 1, 0], dtype=float)
 
     assert_array_equal(x_target, xs)
     assert_array_equal(y1_target, y1s)
@@ -419,9 +419,9 @@ def test_to_midstep():
 
     xs, y1s, y2s = cbook.pts_to_midstep(x, y1, y2)
 
-    x_target = np.asarray([0, .5, .5, 1.5, 1.5, 2.5, 2.5, 3], dtype='float')
-    y1_target = np.asarray([0, 0, 1, 1, 2, 2, 3, 3], dtype='float')
-    y2_target = np.asarray([3, 3, 2, 2, 1, 1, 0, 0], dtype='float')
+    x_target = np.asarray([0, .5, .5, 1.5, 1.5, 2.5, 2.5, 3], dtype=float)
+    y1_target = np.asarray([0, 0, 1, 1, 2, 2, 3, 3], dtype=float)
+    y2_target = np.asarray([3, 3, 2, 2, 1, 1, 0, 0], dtype=float)
 
     assert_array_equal(x_target, xs)
     assert_array_equal(y1_target, y1s)
diff --git a/lib/matplotlib/tests/test_image.py b/lib/matplotlib/tests/test_image.py
@@ -955,7 +955,7 @@ def test_imshow_masked_interpolation():
     N = 20
     n = colors.Normalize(vmin=0, vmax=N*N-1)
 
-    data = np.arange(N*N, dtype='float').reshape(N, N)
+    data = np.arange(N*N, dtype=float).reshape(N, N)
 
     data[5, 5] = -1
     # This will cause crazy ringing for the higher-order
diff --git a/lib/matplotlib/tests/test_ticker.py b/lib/matplotlib/tests/test_ticker.py
@@ -575,7 +575,7 @@ class TestLogFormatterExponent:
         # formatted.
         (False, 10, np.array([0.1, 0.00001, np.pi, 0.2, -0.2, -0.00001]),
          range(6), ['0.1', '1e-05', '3.14', '0.2', '-0.2', '-1e-05']),
-        (False, 50, np.array([3, 5, 12, 42], dtype='float'), range(6),
+        (False, 50, np.array([3, 5, 12, 42], dtype=float), range(6),
          ['3', '5', '12', '42']),
     ]
 
diff --git a/lib/matplotlib/tests/test_units.py b/lib/matplotlib/tests/test_units.py
@@ -158,10 +158,8 @@ def test_empty_arrays():
 
 
 def test_scatter_element0_masked():
-
     times = np.arange('2005-02', '2005-03', dtype='datetime64[D]')
-
-    y = np.arange(len(times), dtype='float')
+    y = np.arange(len(times), dtype=float)
     y[0] = np.nan
     fig, ax = plt.subplots()
     ax.scatter(times, y)
diff --git a/lib/mpl_toolkits/axes_grid1/axes_divider.py b/lib/mpl_toolkits/axes_grid1/axes_divider.py
@@ -597,8 +597,8 @@ def _determine_karray(equivalent_sizes, appended_sizes,
                           total_appended_size):
 
         n = len(equivalent_sizes)
-        A = np.mat(np.zeros((n+1, n+1), dtype="d"))
-        B = np.zeros((n+1), dtype="d")
+        A = np.mat(np.zeros((n + 1, n + 1)))
+        B = np.zeros(n + 1)
         # AxK = B
 
         # populated A
diff --git a/lib/mpl_toolkits/axes_grid1/axes_rgb.py b/lib/mpl_toolkits/axes_grid1/axes_rgb.py
@@ -57,7 +57,7 @@ def make_rgb_axes(ax, pad=0.01, axes_class=None, add_all=True):
 
 def imshow_rgb(ax, r, g, b, **kwargs):
     ny, nx = r.shape
-    R = np.zeros([ny, nx, 3], dtype="d")
+    R = np.zeros((ny, nx, 3))
     R[:, :, 0] = r
     G = np.zeros_like(R)
     G[:, :, 1] = g
diff --git a/lib/mpl_toolkits/tests/test_axes_grid1.py b/lib/mpl_toolkits/tests/test_axes_grid1.py
@@ -126,9 +126,9 @@ def test_inset_locator():
     # Z is a 15x15 array
     Z = np.load(cbook.get_sample_data("axes_grid/bivariate_normal.npy"))
     extent = (-3, 4, -4, 3)
-    Z2 = np.zeros([150, 150], dtype="d")
+    Z2 = np.zeros((150, 150))
     ny, nx = Z.shape
-    Z2[30:30 + ny, 30:30 + nx] = Z
+    Z2[30:30+ny, 30:30+nx] = Z
 
     # extent = [-3, 4, -4, 3]
     ax.imshow(Z2, extent=extent, interpolation="nearest",
@@ -168,9 +168,9 @@ def test_inset_axes():
     # Z is a 15x15 array
     Z = np.load(cbook.get_sample_data("axes_grid/bivariate_normal.npy"))
     extent = (-3, 4, -4, 3)
-    Z2 = np.zeros([150, 150], dtype="d")
+    Z2 = np.zeros((150, 150))
     ny, nx = Z.shape
-    Z2[30:30 + ny, 30:30 + nx] = Z
+    Z2[30:30+ny, 30:30+nx] = Z
 
     # extent = [-3, 4, -4, 3]
     ax.imshow(Z2, extent=extent, interpolation="nearest",

Original file line number	Diff line number	Diff line change
`@@ -575,7 +575,7 @@ class TestLogFormatterExponent:`
`575`	`575`	`# formatted.`
`576`	`576`	`(False, 10, np.array([0.1, 0.00001, np.pi, 0.2, -0.2, -0.00001]),`
`577`	`577`	`range(6), ['0.1', '1e-05', '3.14', '0.2', '-0.2', '-1e-05']),`
`578`		`- (False, 50, np.array([3, 5, 12, 42], dtype='float'), range(6),`
	`578`	`+ (False, 50, np.array([3, 5, 12, 42], dtype=float), range(6),`
`579`	`579`	`['3', '5', '12', '42']),`
`580`	`580`	`]`
`581`	`581`