Merge pull request matplotlib#25469 from anntzer/unpl

timhoffm · web-flow · commit 5aee26d0a52c · 2023-03-15T23:58:04.000+01:00
Autoload numpy arrays in get_sample_data.
diff --git a/doc/api/next_api_changes/deprecations/25469-AL.rst b/doc/api/next_api_changes/deprecations/25469-AL.rst
@@ -0,0 +1,5 @@
+*np_load* parameter of ``cbook.get_sample_data``
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+This parameter is deprecated; `.get_sample_data` now auto-loads numpy arrays.
+Use ``get_sample_data(..., asfileobj=False)`` instead to get the filename of
+the data file, which can then be passed to `open`, if desired.
diff --git a/galleries/examples/axes_grid1/demo_axes_divider.py b/galleries/examples/axes_grid1/demo_axes_divider.py
@@ -13,8 +13,7 @@
 
 
 def get_demo_image():
-    z = cbook.get_sample_data("axes_grid/bivariate_normal.npy", np_load=True)
-    # z is a numpy array of 15x15
+    z = cbook.get_sample_data("axes_grid/bivariate_normal.npy")  # 15x15 array
     return z, (-3, 4, -4, 3)
 
 
diff --git a/galleries/examples/axes_grid1/demo_axes_grid.py b/galleries/examples/axes_grid1/demo_axes_grid.py
@@ -11,8 +11,7 @@
 from matplotlib import cbook
 from mpl_toolkits.axes_grid1 import ImageGrid
 
-Z = cbook.get_sample_data(  # (15, 15) array
-    "axes_grid/bivariate_normal.npy", np_load=True)
+Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy")  # 15x15 array
 extent = (-3, 4, -4, 3)
 
 
diff --git a/galleries/examples/axes_grid1/demo_axes_grid2.py b/galleries/examples/axes_grid1/demo_axes_grid2.py
@@ -29,7 +29,7 @@ def add_inner_title(ax, title, loc, **kwargs):
 fig = plt.figure(figsize=(6, 6))
 
 # Prepare images
-Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy", np_load=True)
+Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy")
 extent = (-3, 4, -4, 3)
 ZS = [Z[i::3, :] for i in range(3)]
 extent = extent[0], extent[1]/3., extent[2], extent[3]
diff --git a/galleries/examples/axes_grid1/demo_axes_rgb.py b/galleries/examples/axes_grid1/demo_axes_rgb.py
@@ -16,7 +16,7 @@
 
 
 def get_rgb():
-    Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy", np_load=True)
+    Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy")
     Z[Z < 0] = 0.
     Z = Z / Z.max()
 
diff --git a/galleries/examples/axes_grid1/demo_colorbar_of_inset_axes.py b/galleries/examples/axes_grid1/demo_colorbar_of_inset_axes.py
@@ -12,7 +12,7 @@
 fig, ax = plt.subplots(figsize=[5, 4])
 ax.set(aspect=1, xlim=(-15, 15), ylim=(-20, 5))
 
-Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy", np_load=True)
+Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy")
 extent = (-3, 4, -4, 3)
 
 axins = zoomed_inset_axes(ax, zoom=2, loc='upper left')
diff --git a/galleries/examples/axes_grid1/demo_edge_colorbar.py b/galleries/examples/axes_grid1/demo_edge_colorbar.py
@@ -14,8 +14,7 @@
 
 
 def get_demo_image():
-    z = cbook.get_sample_data("axes_grid/bivariate_normal.npy", np_load=True)
-    # z is a numpy array of 15x15
+    z = cbook.get_sample_data("axes_grid/bivariate_normal.npy")  # 15x15 array
     return z, (-3, 4, -4, 3)
 
 
diff --git a/galleries/examples/axes_grid1/inset_locator_demo2.py b/galleries/examples/axes_grid1/inset_locator_demo2.py
@@ -19,12 +19,6 @@
 from mpl_toolkits.axes_grid1.anchored_artists import AnchoredSizeBar
 from mpl_toolkits.axes_grid1.inset_locator import mark_inset, zoomed_inset_axes
 
-
-def get_demo_image():
-    z = cbook.get_sample_data("axes_grid/bivariate_normal.npy", np_load=True)
-    # z is a numpy array of 15x15
-    return z, (-3, 4, -4, 3)
-
 fig, (ax, ax2) = plt.subplots(ncols=2, figsize=[6, 3])
 
 
@@ -51,9 +45,9 @@ def add_sizebar(ax, size):
 add_sizebar(axins, 0.5)
 
 
-# Second subplot, showing an image with an inset zoom
-# and a marked inset
-Z, extent = get_demo_image()
+# Second subplot, showing an image with an inset zoom and a marked inset
+Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy")  # 15x15 array
+extent = (-3, 4, -4, 3)
 Z2 = np.zeros((150, 150))
 ny, nx = Z.shape
 Z2[30:30+ny, 30:30+nx] = Z
diff --git a/galleries/examples/axes_grid1/simple_axesgrid2.py b/galleries/examples/axes_grid1/simple_axesgrid2.py
@@ -20,7 +20,7 @@
                  )
 
 # demo image
-Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy", np_load=True)
+Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy")
 im1 = Z
 im2 = Z[:, :10]
 im3 = Z[:, 10:]
diff --git a/galleries/examples/images_contours_and_fields/shading_example.py b/galleries/examples/images_contours_and_fields/shading_example.py
@@ -22,7 +22,7 @@ def main():
     x, y = np.mgrid[-5:5:0.05, -5:5:0.05]
     z = 5 * (np.sqrt(x**2 + y**2) + np.sin(x**2 + y**2))
 
-    dem = cbook.get_sample_data('jacksboro_fault_dem.npz', np_load=True)
+    dem = cbook.get_sample_data('jacksboro_fault_dem.npz')
     elev = dem['elevation']
 
     fig = compare(z, plt.cm.copper)
diff --git a/galleries/examples/lines_bars_and_markers/fill_between_alpha.py b/galleries/examples/lines_bars_and_markers/fill_between_alpha.py
@@ -18,8 +18,7 @@
 import matplotlib.cbook as cbook
 
 # load up some sample financial data
-r = (cbook.get_sample_data('goog.npz', np_load=True)['price_data']
-     .view(np.recarray))
+r = cbook.get_sample_data('goog.npz')['price_data'].view(np.recarray)
 # create two subplots with the shared x and y axes
 fig, (ax1, ax2) = plt.subplots(1, 2, sharex=True, sharey=True)
 
diff --git a/galleries/examples/lines_bars_and_markers/scatter_demo2.py b/galleries/examples/lines_bars_and_markers/scatter_demo2.py
@@ -14,8 +14,7 @@
 # low, close, volume, adj_close from the mpl-data/sample_data directory. The
 # record array stores the date as an np.datetime64 with a day unit ('D') in
 # the date column.
-price_data = (cbook.get_sample_data('goog.npz', np_load=True)['price_data']
-              .view(np.recarray))
+price_data = cbook.get_sample_data('goog.npz')['price_data'].view(np.recarray)
 price_data = price_data[-250:]  # get the most recent 250 trading days
 
 delta1 = np.diff(price_data.adj_close) / price_data.adj_close[:-1]
diff --git a/galleries/examples/mplot3d/custom_shaded_3d_surface.py b/galleries/examples/mplot3d/custom_shaded_3d_surface.py
@@ -13,7 +13,7 @@
 from matplotlib.colors import LightSource
 
 # Load and format data
-dem = cbook.get_sample_data('jacksboro_fault_dem.npz', np_load=True)
+dem = cbook.get_sample_data('jacksboro_fault_dem.npz')
 z = dem['elevation']
 nrows, ncols = z.shape
 x = np.linspace(dem['xmin'], dem['xmax'], ncols)
diff --git a/galleries/examples/specialty_plots/topographic_hillshading.py b/galleries/examples/specialty_plots/topographic_hillshading.py
@@ -22,7 +22,7 @@
 from matplotlib.cbook import get_sample_data
 from matplotlib.colors import LightSource
 
-dem = get_sample_data('jacksboro_fault_dem.npz', np_load=True)
+dem = get_sample_data('jacksboro_fault_dem.npz')
 z = dem['elevation']
 # -- Optional dx and dy for accurate vertical exaggeration --------------------
 # If you need topographically accurate vertical exaggeration, or you don't want
diff --git a/galleries/examples/subplots_axes_and_figures/zoom_inset_axes.py b/galleries/examples/subplots_axes_and_figures/zoom_inset_axes.py
@@ -6,36 +6,28 @@
 Example of an inset axes and a rectangle showing where the zoom is located.
 """
 
-import matplotlib.pyplot as plt
 import numpy as np
 
 from matplotlib import cbook
+from matplotlib import pyplot as plt
 
-
-def get_demo_image():
-    z = cbook.get_sample_data("axes_grid/bivariate_normal.npy", np_load=True)
-    # z is a numpy array of 15x15
-    return z, (-3, 4, -4, 3)
-
-fig, ax = plt.subplots(figsize=[5, 4])
+fig, ax = plt.subplots()
 
 # make data
-Z, extent = get_demo_image()
+Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy")  # 15x15 array
 Z2 = np.zeros((150, 150))
 ny, nx = Z.shape
 Z2[30:30+ny, 30:30+nx] = Z
+extent = (-3, 4, -4, 3)
 
 ax.imshow(Z2, extent=extent, origin="lower")
 
 # inset axes....
-axins = ax.inset_axes([0.5, 0.5, 0.47, 0.47])
+x1, x2, y1, y2 = -1.5, -0.9, -2.5, -1.9  # subregion of the original image
+axins = ax.inset_axes(
+    [0.5, 0.5, 0.47, 0.47],
+    xlim=(x1, x2), ylim=(y1, y2), xticklabels=[], yticklabels=[])
 axins.imshow(Z2, extent=extent, origin="lower")
-# subregion of the original image
-x1, x2, y1, y2 = -1.5, -0.9, -2.5, -1.9
-axins.set_xlim(x1, x2)
-axins.set_ylim(y1, y2)
-axins.set_xticklabels([])
-axins.set_yticklabels([])
 
 ax.indicate_inset_zoom(axins, edgecolor="black")
 
diff --git a/galleries/examples/text_labels_and_annotations/date.py b/galleries/examples/text_labels_and_annotations/date.py
@@ -31,7 +31,7 @@
 # low, close, volume, adj_close from the mpl-data/sample_data directory. The
 # record array stores the date as an np.datetime64 with a day unit ('D') in
 # the date column.
-data = cbook.get_sample_data('goog.npz', np_load=True)['price_data']
+data = cbook.get_sample_data('goog.npz')['price_data']
 
 fig, axs = plt.subplots(3, 1, figsize=(6.4, 7), layout='constrained')
 # common to all three:
diff --git a/galleries/examples/ticks/centered_ticklabels.py b/galleries/examples/ticks/centered_ticklabels.py
@@ -25,8 +25,7 @@
 import matplotlib.ticker as ticker
 
 # Load some financial data; Google's stock price
-r = (cbook.get_sample_data('goog.npz', np_load=True)['price_data']
-     .view(np.recarray))
+r = cbook.get_sample_data('goog.npz')['price_data'].view(np.recarray)
 r = r[-250:]  # get the last 250 days
 
 fig, ax = plt.subplots()
diff --git a/galleries/examples/ticks/date_index_formatter.py b/galleries/examples/ticks/date_index_formatter.py
@@ -25,7 +25,7 @@
 # low, close, volume, adj_close from the mpl-data/sample_data directory. The
 # record array stores the date as an np.datetime64 with a day unit ('D') in
 # the date column (``r.date``).
-r = cbook.get_sample_data('goog.npz', np_load=True)['price_data'].view(np.recarray)
+r = cbook.get_sample_data('goog.npz')['price_data'].view(np.recarray)
 r = r[:9]  # get the first 9 days
 
 fig, (ax1, ax2) = plt.subplots(nrows=2, figsize=(6, 6), layout='constrained')
@@ -80,3 +80,5 @@ def __call__(self, x, pos=0):
 
 
 ax2.xaxis.set_major_formatter(MyFormatter(r.date, '%a'))
+
+plt.show()
diff --git a/galleries/tutorials/colors/colormapnorms.py b/galleries/tutorials/colors/colormapnorms.py
@@ -249,7 +249,7 @@
 # elevation range than the water has depth range, and they are often
 # represented by a different colormap.
 
-dem = cbook.get_sample_data('topobathy.npz', np_load=True)
+dem = cbook.get_sample_data('topobathy.npz')
 topo = dem['topo']
 longitude = dem['longitude']
 latitude = dem['latitude']
diff --git a/lib/matplotlib/cbook.py b/lib/matplotlib/cbook.py
@@ -495,7 +495,9 @@ def is_scalar_or_string(val):
     return isinstance(val, str) or not np.iterable(val)
 
 
-def get_sample_data(fname, asfileobj=True, *, np_load=False):
+@_api.delete_parameter(
+    "3.8", "np_load", alternative="open(get_sample_data(..., asfileobj=False))")
+def get_sample_data(fname, asfileobj=True, *, np_load=True):
     """
     Return a sample data file.  *fname* is a path relative to the
     :file:`mpl-data/sample_data` directory.  If *asfileobj* is `True`
@@ -505,9 +507,8 @@ def get_sample_data(fname, asfileobj=True, *, np_load=False):
     the Matplotlib package.
 
     If the filename ends in .gz, the file is implicitly ungzipped.  If the
-    filename ends with .npy or .npz, *asfileobj* is True, and *np_load* is
-    True, the file is loaded with `numpy.load`.  *np_load* currently defaults
-    to False but will default to True in a future release.
+    filename ends with .npy or .npz, and *asfileobj* is `True`, the file is
+    loaded with `numpy.load`.
     """
     path = _get_data_path('sample_data', fname)
     if asfileobj:
@@ -518,12 +519,6 @@ def get_sample_data(fname, asfileobj=True, *, np_load=False):
             if np_load:
                 return np.load(path)
             else:
-                _api.warn_deprecated(
-                    "3.3", message="In a future release, get_sample_data "
-                    "will automatically load numpy arrays.  Set np_load to "
-                    "True to get the array and suppress this warning.  Set "
-                    "asfileobj to False to get the path to the data file and "
-                    "suppress this warning.")
                 return path.open('rb')
         elif suffix in ['.csv', '.xrc', '.txt']:
             return path.open('r')
diff --git a/lib/matplotlib/tests/test_colors.py b/lib/matplotlib/tests/test_colors.py
@@ -961,7 +961,7 @@ def test_autoscale_masked():
 @image_comparison(['light_source_shading_topo.png'])
 def test_light_source_topo_surface():
     """Shades a DEM using different v.e.'s and blend modes."""
-    dem = cbook.get_sample_data('jacksboro_fault_dem.npz', np_load=True)
+    dem = cbook.get_sample_data('jacksboro_fault_dem.npz')
     elev = dem['elevation']
     dx, dy = dem['dx'], dem['dy']
     # Get the true cellsize in meters for accurate vertical exaggeration
diff --git a/lib/mpl_toolkits/axes_grid1/tests/test_axes_grid1.py b/lib/mpl_toolkits/axes_grid1/tests/test_axes_grid1.py
@@ -125,7 +125,7 @@ def test_inset_locator():
 
     # prepare the demo image
     # Z is a 15x15 array
-    Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy", np_load=True)
+    Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy")
     extent = (-3, 4, -4, 3)
     Z2 = np.zeros((150, 150))
     ny, nx = Z.shape
@@ -166,7 +166,7 @@ def test_inset_axes():
 
     # prepare the demo image
     # Z is a 15x15 array
-    Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy", np_load=True)
+    Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy")
     extent = (-3, 4, -4, 3)
     Z2 = np.zeros((150, 150))
     ny, nx = Z.shape
@@ -757,9 +757,7 @@ def test_anchored_locator_base_call():
     ax.set(aspect=1, xlim=(-15, 15), ylim=(-20, 5))
     ax.set(xticks=[], yticks=[])
 
-    Z = cbook.get_sample_data(
-        "axes_grid/bivariate_normal.npy", np_load=True
-    )
+    Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy")
     extent = (-3, 4, -4, 3)
 
     axins = zoomed_inset_axes(ax, zoom=2, loc="upper left")

Original file line number	Diff line number	Diff line change
`@@ -20,7 +20,7 @@`
`20`	`20`	`)`
`21`	`21`
`22`	`22`	`# demo image`
`23`		`-Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy", np_load=True)`
	`23`	`+Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy")`
`24`	`24`	`im1 = Z`
`25`	`25`	`im2 = Z[:, :10]`
`26`	`26`	`im3 = Z[:, 10:]`