Remove asfileobj=False from a bunch of examples loading sample_data.

anntzer · anntzer · commit e458a4645001 · 2019-03-07T23:43:39.000+01:00
Using a file object works just fine.

There are some more examples that load bivariate_normal.npy, but they
have a bunch of duplicated code that could use some more refactor.
diff --git a/examples/frontpage/3D.py b/examples/frontpage/3D.py
@@ -4,7 +4,6 @@
 ====================
 
 This example reproduces the frontpage 3D example.
-
 """
 
 from matplotlib import cbook
@@ -13,8 +12,8 @@
 import matplotlib.pyplot as plt
 import numpy as np
 
-filename = cbook.get_sample_data('jacksboro_fault_dem.npz', asfileobj=False)
-with np.load(filename) as dem:
+with cbook.get_sample_data('jacksboro_fault_dem.npz') as file, \
+     np.load(file) as dem:
     z = dem['elevation']
     nrows, ncols = z.shape
     x = np.linspace(dem['xmin'], dem['xmax'], ncols)
diff --git a/examples/images_contours_and_fields/image_demo.py b/examples/images_contours_and_fields/image_demo.py
@@ -51,7 +51,7 @@
 
 w, h = 512, 512
 
-with cbook.get_sample_data('ct.raw.gz', asfileobj=True) as datafile:
+with cbook.get_sample_data('ct.raw.gz') as datafile:
     s = datafile.read()
 A = np.frombuffer(s, np.uint16).astype(float).reshape((w, h))
 A /= A.max()
diff --git a/examples/images_contours_and_fields/shading_example.py b/examples/images_contours_and_fields/shading_example.py
@@ -1,27 +1,28 @@
 """
 ===============
-Shading Example
+Shading example
 ===============
 
-Example showing how to make shaded relief plots
-like Mathematica
-(http://reference.wolfram.com/mathematica/ref/ReliefPlot.html)
-or Generic Mapping Tools
-(https://gmt.soest.hawaii.edu/)
+Example showing how to make shaded relief plots like Mathematica_ or
+`Generic Mapping Tools`_.
+
+.. _Mathematica: http://reference.wolfram.com/mathematica/ref/ReliefPlot.html
+.. _Generic Mapping Tools: https://gmt.soest.hawaii.edu/
 """
+
 import numpy as np
+from matplotlib import cbook
 import matplotlib.pyplot as plt
 from matplotlib.colors import LightSource
-from matplotlib.cbook import get_sample_data
 
 
 def main():
     # Test data
     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))
 
-    filename = get_sample_data('jacksboro_fault_dem.npz', asfileobj=False)
-    with np.load(filename) as dem:
+    with cbook.get_sample_data('jacksboro_fault_dem.npz') as file, \
+         np.load(file) as dem:
         elev = dem['elevation']
 
     fig = compare(z, plt.cm.copper)
diff --git a/examples/images_contours_and_fields/watermark_image.py b/examples/images_contours_and_fields/watermark_image.py
@@ -5,25 +5,21 @@
 
 Using a PNG file as a watermark.
 """
+
 import numpy as np
 import matplotlib.cbook as cbook
 import matplotlib.image as image
 import matplotlib.pyplot as plt
 
-# Fixing random state for reproducibility
-np.random.seed(19680801)
-
 
-datafile = cbook.get_sample_data('logo2.png', asfileobj=False)
-print('loading %s' % datafile)
-im = image.imread(datafile)
-im[:, :, -1] = 0.5  # set the alpha channel
+with cbook.get_sample_data('logo2.png') as file:
+    im = image.imread(file)
 
 fig, ax = plt.subplots()
 
-ax.plot(np.random.rand(20), '-o', ms=20, lw=2, alpha=0.7, mfc='orange')
+ax.plot(np.sin(10 * np.linspace(0, 1)), '-o', ms=20, alpha=0.7, mfc='orange')
 ax.grid()
-fig.figimage(im, 10, 10, zorder=3)
+fig.figimage(im, 10, 10, zorder=3, alpha=.5)
 
 plt.show()
 
diff --git a/examples/misc/load_converter.py b/examples/misc/load_converter.py
@@ -13,12 +13,10 @@
 import numpy as np
 
 
-datafile = cbook.get_sample_data('msft.csv', asfileobj=False)
-print('loading', datafile)
-
-data = np.genfromtxt(
-    datafile, delimiter=',', names=True,
-    dtype=None, converters={0: dateutil.parser.parse})
+with cbook.get_sample_data('msft.csv') as file:
+    data = np.genfromtxt(
+        file, delimiter=',', names=True,
+        dtype=None, converters={0: dateutil.parser.parse})
 
 fig, ax = plt.subplots()
 ax.plot(data['Date'], data['High'], '-')
diff --git a/examples/mplot3d/custom_shaded_3d_surface.py b/examples/mplot3d/custom_shaded_3d_surface.py
@@ -13,8 +13,8 @@
 import numpy as np
 
 # Load and format data
-filename = cbook.get_sample_data('jacksboro_fault_dem.npz', asfileobj=False)
-with np.load(filename) as dem:
+with cbook.get_sample_data('jacksboro_fault_dem.npz') as file, \
+     np.load(file) as dem:
     z = dem['elevation']
     nrows, ncols = z.shape
     x = np.linspace(dem['xmin'], dem['xmax'], ncols)
diff --git a/examples/showcase/bachelors_degrees_by_gender.py b/examples/showcase/bachelors_degrees_by_gender.py
@@ -15,9 +15,8 @@
 from matplotlib.cbook import get_sample_data
 
 
-fname = get_sample_data('percent_bachelors_degrees_women_usa.csv',
-                        asfileobj=False)
-gender_degree_data = np.genfromtxt(fname, delimiter=',', names=True)
+with get_sample_data('percent_bachelors_degrees_women_usa.csv') as file:
+    gender_degree_data = np.genfromtxt(file, delimiter=',', names=True)
 
 # You typically want your plot to be ~1.33x wider than tall. This plot
 # is a rare exception because of the number of lines being plotted on it.
diff --git a/examples/text_labels_and_annotations/demo_annotation_box.py b/examples/text_labels_and_annotations/demo_annotation_box.py
@@ -77,8 +77,8 @@
 ax.add_artist(ab)
 
 # Annotate the 2nd position with another image (a Grace Hopper portrait)
-fn = get_sample_data("grace_hopper.png", asfileobj=False)
-arr_img = plt.imread(fn, format='png')
+with get_sample_data("grace_hopper.png") as file:
+    arr_img = plt.imread(file, format='png')
 
 imagebox = OffsetImage(arr_img, zoom=0.2)
 imagebox.image.axes = ax
diff --git a/examples/ticks_and_spines/date_index_formatter2.py b/examples/ticks_and_spines/date_index_formatter2.py
@@ -18,11 +18,10 @@
 import numpy as np
 
 
-datafile = cbook.get_sample_data('msft.csv', asfileobj=False)
-print('loading %s' % datafile)
-msft_data = np.genfromtxt(
-    datafile, delimiter=',', names=True,
-    converters={0: lambda s: dates.date2num(dateutil.parser.parse(s))})
+with cbook.get_sample_data('msft.csv') as file:
+    msft_data = np.genfromtxt(
+        file, delimiter=',', names=True,
+        converters={0: lambda s: dates.date2num(dateutil.parser.parse(s))})
 
 
 class MyFormatter(Formatter):
diff --git a/lib/matplotlib/tests/test_colors.py b/lib/matplotlib/tests/test_colors.py
@@ -391,15 +391,14 @@ def test_colors_no_float():
                   extensions=['png'])
 def test_light_source_topo_surface():
     """Shades a DEM using different v.e.'s and blend modes."""
-    fname = cbook.get_sample_data('jacksboro_fault_dem.npz', asfileobj=False)
-    dem = np.load(fname)
-    elev = dem['elevation']
-    # Get the true cellsize in meters for accurate vertical exaggeration
-    #   Convert from decimal degrees to meters
-    dx, dy = dem['dx'], dem['dy']
-    dx = 111320.0 * dx * np.cos(dem['ymin'])
-    dy = 111320.0 * dy
-    dem.close()
+    with cbook.get_sample_data('jacksboro_fault_dem.npz') as file, \
+         np.load(file) as dem:
+        elev = dem['elevation']
+        dx, dy = dem['dx'], dem['dy']
+        # Get the true cellsize in meters for accurate vertical exaggeration
+        # Convert from decimal degrees to meters
+        dx = 111320.0 * dx * np.cos(dem['ymin'])
+        dy = 111320.0 * dy
 
     ls = mcolors.LightSource(315, 45)
     cmap = cm.gist_earth
