113 lines
3.7 KiB
Python
113 lines
3.7 KiB
Python
import sys
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import numpy as np
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from numpy.testing import assert_array_almost_equal
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import matplotlib.pyplot as plt
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from matplotlib.testing.decorators import image_comparison
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import matplotlib.transforms as mtransforms
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on_win = (sys.platform == 'win32')
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on_mac = (sys.platform == 'darwin')
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def velocity_field():
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Y, X = np.mgrid[-3:3:100j, -3:3:100j]
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U = -1 - X**2 + Y
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V = 1 + X - Y**2
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return X, Y, U, V
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def swirl_velocity_field():
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x = np.linspace(-3., 3., 100)
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y = np.linspace(-3., 3., 100)
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X, Y = np.meshgrid(x, y)
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a = 0.1
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U = np.cos(a) * (-Y) - np.sin(a) * X
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V = np.sin(a) * (-Y) + np.cos(a) * X
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return x, y, U, V
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@image_comparison(['streamplot_startpoints'], remove_text=True, style='mpl20')
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def test_startpoints():
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X, Y, U, V = velocity_field()
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start_x = np.linspace(X.min(), X.max(), 10)
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start_y = np.linspace(Y.min(), Y.max(), 10)
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start_points = np.column_stack([start_x, start_y])
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plt.streamplot(X, Y, U, V, start_points=start_points)
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plt.plot(start_x, start_y, 'ok')
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@image_comparison(['streamplot_colormap'],
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tol=.04, remove_text=True, style='mpl20')
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def test_colormap():
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X, Y, U, V = velocity_field()
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plt.streamplot(X, Y, U, V, color=U, density=0.6, linewidth=2,
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cmap=plt.cm.autumn)
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plt.colorbar()
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@image_comparison(['streamplot_linewidth'], remove_text=True, style='mpl20')
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def test_linewidth():
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X, Y, U, V = velocity_field()
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speed = np.hypot(U, V)
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lw = 5 * speed / speed.max()
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# Compatibility for old test image
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df = 25 / 30
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ax = plt.figure().subplots()
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ax.set(xlim=(-3.0, 2.9999999999999947),
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ylim=(-3.0000000000000004, 2.9999999999999947))
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ax.streamplot(X, Y, U, V, density=[0.5 * df, 1. * df], color='k',
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linewidth=lw)
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@image_comparison(['streamplot_masks_and_nans'],
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remove_text=True, style='mpl20', tol=0.04 if on_win else 0)
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def test_masks_and_nans():
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X, Y, U, V = velocity_field()
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mask = np.zeros(U.shape, dtype=bool)
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mask[40:60, 40:60] = 1
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U[:20, :20] = np.nan
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U = np.ma.array(U, mask=mask)
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# Compatibility for old test image
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ax = plt.figure().subplots()
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ax.set(xlim=(-3.0, 2.9999999999999947),
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ylim=(-3.0000000000000004, 2.9999999999999947))
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with np.errstate(invalid='ignore'):
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ax.streamplot(X, Y, U, V, color=U, cmap=plt.cm.Blues)
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@image_comparison(['streamplot_maxlength.png'],
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remove_text=True, style='mpl20',
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tol=0.002 if on_mac else 0)
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def test_maxlength():
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x, y, U, V = swirl_velocity_field()
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ax = plt.figure().subplots()
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ax.streamplot(x, y, U, V, maxlength=10., start_points=[[0., 1.5]],
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linewidth=2, density=2)
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assert ax.get_xlim()[-1] == ax.get_ylim()[-1] == 3
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# Compatibility for old test image
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ax.set(xlim=(None, 3.2555988021882305), ylim=(None, 3.078326760195413))
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@image_comparison(['streamplot_direction.png'],
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remove_text=True, style='mpl20')
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def test_direction():
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x, y, U, V = swirl_velocity_field()
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plt.streamplot(x, y, U, V, integration_direction='backward',
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maxlength=1.5, start_points=[[1.5, 0.]],
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linewidth=2, density=2)
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def test_streamplot_limits():
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ax = plt.axes()
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x = np.linspace(-5, 10, 20)
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y = np.linspace(-2, 4, 10)
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y, x = np.meshgrid(y, x)
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trans = mtransforms.Affine2D().translate(25, 32) + ax.transData
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plt.barbs(x, y, np.sin(x), np.cos(y), transform=trans)
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# The calculated bounds are approximately the bounds of the original data,
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# this is because the entire path is taken into account when updating the
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# datalim.
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assert_array_almost_equal(ax.dataLim.bounds, (20, 30, 15, 6),
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decimal=1)
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