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Make get_sample_data autoload npy/npz files. · SMSinclair/matplotlib@d7d11a7 · GitHub

  1. SMSinclair
  2. matplotlib

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Make get_sample_data autoload npy/npz files.
This makes examples shorter and more to the point by simplifying the data-load part. A small (standard) backcompat-dance is needed.
1 parent 5ab1352 commit d7d11a7

24 files changed

Lines changed: 102 additions & 130 deletions

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‎doc/api/api_changes_3.3/behaviour.rst‎

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@@ -294,3 +294,10 @@ FT_LOAD_DEFAULT, etc. The old synonyms (respectively "either", "native",
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"auto", and "none") are still supported, but their use is discouraged. To get
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normalized values, use `.backend_agg.get_hinting_flag`, which returns integer
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flag values.
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`.cbook.get_sample_data` auto-loads numpy arrays
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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When `.cbook.get_sample_data` is used to load a npy or npz file and the
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keyword-only parameter ``np_load`` is True, the file is automatically loaded
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using `numpy.load`. ``np_load`` defaults to False for backwards compatibility,
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but will become True in a later release.

‎examples/axes_grid1/demo_axes_divider.py‎

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@@ -6,14 +6,13 @@
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Axes divider to calculate location of axes and
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create a divider for them using existing axes instances.
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"""
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from matplotlib import cbook
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import matplotlib.pyplot as plt
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def get_demo_image():
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import numpy as np
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from matplotlib.cbook import get_sample_data
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f = get_sample_data("axes_grid/bivariate_normal.npy", asfileobj=False)
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z = np.load(f)
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z = cbook.get_sample_data("axes_grid/bivariate_normal.npy", np_load=True)
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# z is a numpy array of 15x15
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return z, (-3, 4, -4, 3)
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‎examples/axes_grid1/demo_axes_grid.py‎

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@@ -6,6 +6,7 @@
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Grid of 2x2 images with single or own colorbar.
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"""
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from matplotlib import cbook
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import matplotlib.pyplot as plt
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from mpl_toolkits.axes_grid1 import ImageGrid
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@@ -14,10 +15,7 @@
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def get_demo_image():
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import numpy as np
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from matplotlib.cbook import get_sample_data
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f = get_sample_data("axes_grid/bivariate_normal.npy", asfileobj=False)
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z = np.load(f)
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z = cbook.get_sample_data("axes_grid/bivariate_normal.npy", np_load=True)
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# z is a numpy array of 15x15
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return z, (-3, 4, -4, 3)
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‎examples/axes_grid1/demo_axes_grid2.py‎

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@@ -7,23 +7,15 @@
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"""
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import numpy as np
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from matplotlib import cbook
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import matplotlib.colors
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import matplotlib.pyplot as plt
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from mpl_toolkits.axes_grid1 import ImageGrid
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import matplotlib.colors
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plt.rcParams["mpl_toolkits.legacy_colorbar"] = False
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def get_demo_image():
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from matplotlib.cbook import get_sample_data
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f = get_sample_data("axes_grid/bivariate_normal.npy", asfileobj=False)
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z = np.load(f)
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# z is a numpy array of 15x15
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return z, (-3, 4, -4, 3)
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def add_inner_title(ax, title, loc, **kwargs):
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from matplotlib.offsetbox import AnchoredText
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from matplotlib.patheffects import withStroke
@@ -39,7 +31,8 @@ def add_inner_title(ax, title, loc, **kwargs):
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fig = plt.figure(figsize=(6, 6))
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# Prepare images
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Z, extent = get_demo_image()
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Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy", np_load=True)
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extent = (-3, 4, -4, 3)
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ZS = [Z[i::3, :] for i in range(3)]
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extent = extent[0], extent[1]/3., extent[2], extent[3]
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‎examples/axes_grid1/demo_axes_rgb.py‎

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def get_rgb():
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f = cbook.get_sample_data("axes_grid/bivariate_normal.npy")
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Z = np.load(f) # 15x15 numpy array.
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Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy", np_load=True)
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Z[Z < 0] = 0.
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Z = Z / Z.max()
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‎examples/axes_grid1/demo_colorbar_of_inset_axes.py‎

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@@ -4,36 +4,25 @@
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===========================
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"""
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import matplotlib.pyplot as plt
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from matplotlib import cbook
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import matplotlib.pyplot as plt
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from mpl_toolkits.axes_grid1.inset_locator import inset_axes, zoomed_inset_axes
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def get_demo_image():
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from matplotlib.cbook import get_sample_data
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import numpy as np
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f = get_sample_data("axes_grid/bivariate_normal.npy", asfileobj=False)
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z = np.load(f)
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# z is a numpy array of 15x15
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return z, (-3, 4, -4, 3)
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fig, ax = plt.subplots(figsize=[5, 4])
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Z, extent = get_demo_image()
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ax.set(aspect=1,
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xlim=(-15, 15),
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ylim=(-20, 5))
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Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy", np_load=True)
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extent = (-3, 4, -4, 3)
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ax.set(aspect=1, xlim=(-15, 15), ylim=(-20, 5))
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axins = zoomed_inset_axes(ax, zoom=2, loc='upper left')
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im = axins.imshow(Z, extent=extent, origin="lower")
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plt.xticks(visible=False)
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plt.yticks(visible=False)
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# colorbar
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cax = inset_axes(axins,
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width="5%", # width = 10% of parent_bbox width
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bbox_transform=axins.transAxes,
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borderpad=0,
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)
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fig.colorbar(im, cax=cax)
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plt.show()

‎examples/axes_grid1/demo_edge_colorbar.py‎

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of an image grid.
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"""
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from matplotlib import cbook
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import matplotlib.pyplot as plt
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from mpl_toolkits.axes_grid1 import AxesGrid
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def get_demo_image():
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import numpy as np
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from matplotlib.cbook import get_sample_data
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f = get_sample_data("axes_grid/bivariate_normal.npy", asfileobj=False)
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z = np.load(f)
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z = cbook.get_sample_data("axes_grid/bivariate_normal.npy", np_load=True)
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# z is a numpy array of 15x15
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return z, (-3, 4, -4, 3)
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‎examples/axes_grid1/inset_locator_demo2.py‎

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created via `~.mark_inset`.
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"""
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from matplotlib import cbook
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import matplotlib.pyplot as plt
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from mpl_toolkits.axes_grid1.inset_locator import zoomed_inset_axes, mark_inset
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from mpl_toolkits.axes_grid1.anchored_artists import AnchoredSizeBar
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import numpy as np
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def get_demo_image():
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from matplotlib.cbook import get_sample_data
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import numpy as np
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f = get_sample_data("axes_grid/bivariate_normal.npy", asfileobj=False)
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z = np.load(f)
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z = cbook.get_sample_data("axes_grid/bivariate_normal.npy", np_load=True)
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# z is a numpy array of 15x15
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return z, (-3, 4, -4, 3)
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@@ -60,11 +57,9 @@ def add_sizebar(ax, size):
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ny, nx = Z.shape
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Z2[30:30+ny, 30:30+nx] = Z
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# extent = [-3, 4, -4, 3]
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ax2.imshow(Z2, extent=extent, origin="lower")
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axins2 = zoomed_inset_axes(ax2, 6, loc=1) # zoom = 6
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axins2 = zoomed_inset_axes(ax2, zoom=6, loc=1)
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axins2.imshow(Z2, extent=extent, origin="lower")
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# sub region of the original image

‎examples/axes_grid1/simple_axesgrid2.py‎

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Align multiple images of different sizes using
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`~mpl_toolkits.axes_grid1.axes_grid.ImageGrid`.
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"""
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from matplotlib import cbook
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import matplotlib.pyplot as plt
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from mpl_toolkits.axes_grid1 import ImageGrid
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def get_demo_image():
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import numpy as np
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from matplotlib.cbook import get_sample_data
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f = get_sample_data("axes_grid/bivariate_normal.npy", asfileobj=False)
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z = np.load(f)
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# z is a numpy array of 15x15
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return z, (-3, 4, -4, 3)
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fig = plt.figure(figsize=(5.5, 3.5))
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grid = ImageGrid(fig, 111, # similar to subplot(111)
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nrows_ncols=(1, 3),
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axes_pad=0.1,
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label_mode="L",
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)
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Z, extent = get_demo_image() # demo image
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# demo image
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Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy", np_load=True)
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im1 = Z
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im2 = Z[:, :10]
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im3 = Z[:, 10:]

‎examples/frontpage/3D.py‎

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import matplotlib.pyplot as plt
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import numpy as np
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with cbook.get_sample_data('jacksboro_fault_dem.npz') as file, \
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np.load(file) as dem:
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z = dem['elevation']
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nrows, ncols = z.shape
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x = np.linspace(dem['xmin'], dem['xmax'], ncols)
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y = np.linspace(dem['ymin'], dem['ymax'], nrows)
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x, y = np.meshgrid(x, y)
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dem = cbook.get_sample_data('jacksboro_fault_dem.npz', np_load=True)
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z = dem['elevation']
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nrows, ncols = z.shape
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x = np.linspace(dem['xmin'], dem['xmax'], ncols)
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y = np.linspace(dem['ymin'], dem['ymax'], nrows)
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x, y = np.meshgrid(x, y)
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region = np.s_[5:50, 5:50]
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x, y, z = x[region], y[region], z[region]

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