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- import sys
- import platform
- import numpy as np
- from numpy.testing import assert_array_almost_equal
- import matplotlib.pyplot as plt
- from matplotlib.testing.decorators import image_comparison
- import matplotlib.transforms as mtransforms
- on_win = (sys.platform == 'win32')
- on_mac = (sys.platform == 'darwin')
- def velocity_field():
- Y, X = np.mgrid[-3:3:100j, -3:3:100j]
- U = -1 - X**2 + Y
- V = 1 + X - Y**2
- return X, Y, U, V
- def swirl_velocity_field():
- x = np.linspace(-3., 3., 100)
- y = np.linspace(-3., 3., 100)
- X, Y = np.meshgrid(x, y)
- a = 0.1
- U = np.cos(a) * (-Y) - np.sin(a) * X
- V = np.sin(a) * (-Y) + np.cos(a) * X
- return x, y, U, V
- @image_comparison(['streamplot_startpoints'], remove_text=True, style='mpl20')
- def test_startpoints():
- X, Y, U, V = velocity_field()
- start_x = np.linspace(X.min(), X.max(), 10)
- start_y = np.linspace(Y.min(), Y.max(), 10)
- start_points = np.column_stack([start_x, start_y])
- plt.streamplot(X, Y, U, V, start_points=start_points)
- plt.plot(start_x, start_y, 'ok')
- @image_comparison(['streamplot_colormap'],
- tol=.04, remove_text=True, style='mpl20')
- def test_colormap():
- X, Y, U, V = velocity_field()
- plt.streamplot(X, Y, U, V, color=U, density=0.6, linewidth=2,
- cmap=plt.cm.autumn)
- plt.colorbar()
- @image_comparison(['streamplot_linewidth'], remove_text=True, style='mpl20',
- tol={'aarch64': 0.02}.get(platform.machine(), 0.0))
- def test_linewidth():
- X, Y, U, V = velocity_field()
- speed = np.hypot(U, V)
- lw = 5 * speed / speed.max()
- # Compatibility for old test image
- df = 25 / 30
- ax = plt.figure().subplots()
- ax.set(xlim=(-3.0, 2.9999999999999947),
- ylim=(-3.0000000000000004, 2.9999999999999947))
- ax.streamplot(X, Y, U, V, density=[0.5 * df, 1. * df], color='k',
- linewidth=lw)
- @image_comparison(['streamplot_masks_and_nans'],
- remove_text=True, style='mpl20', tol=0.04 if on_win else 0)
- def test_masks_and_nans():
- X, Y, U, V = velocity_field()
- mask = np.zeros(U.shape, dtype=bool)
- mask[40:60, 40:60] = 1
- U[:20, :20] = np.nan
- U = np.ma.array(U, mask=mask)
- # Compatibility for old test image
- ax = plt.figure().subplots()
- ax.set(xlim=(-3.0, 2.9999999999999947),
- ylim=(-3.0000000000000004, 2.9999999999999947))
- with np.errstate(invalid='ignore'):
- ax.streamplot(X, Y, U, V, color=U, cmap=plt.cm.Blues)
- @image_comparison(['streamplot_maxlength.png'],
- remove_text=True, style='mpl20',
- tol=0.002 if on_mac else 0)
- def test_maxlength():
- x, y, U, V = swirl_velocity_field()
- ax = plt.figure().subplots()
- ax.streamplot(x, y, U, V, maxlength=10., start_points=[[0., 1.5]],
- linewidth=2, density=2)
- assert ax.get_xlim()[-1] == ax.get_ylim()[-1] == 3
- # Compatibility for old test image
- ax.set(xlim=(None, 3.2555988021882305), ylim=(None, 3.078326760195413))
- @image_comparison(['streamplot_direction.png'],
- remove_text=True, style='mpl20')
- def test_direction():
- x, y, U, V = swirl_velocity_field()
- plt.streamplot(x, y, U, V, integration_direction='backward',
- maxlength=1.5, start_points=[[1.5, 0.]],
- linewidth=2, density=2)
- def test_streamplot_limits():
- ax = plt.axes()
- x = np.linspace(-5, 10, 20)
- y = np.linspace(-2, 4, 10)
- y, x = np.meshgrid(y, x)
- trans = mtransforms.Affine2D().translate(25, 32) + ax.transData
- plt.barbs(x, y, np.sin(x), np.cos(y), transform=trans)
- # The calculated bounds are approximately the bounds of the original data,
- # this is because the entire path is taken into account when updating the
- # datalim.
- assert_array_almost_equal(ax.dataLim.bounds, (20, 30, 15, 6),
- decimal=1)
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