def test_plot_empty_slice():
# Test that things don't crash when we give a map with nothing above
# threshold
# This is only a smoke test
data = np.zeros((20, 20, 20))
img = nibabel.Nifti1Image(data, mni_affine)
plot_img(img, display_mode='y', threshold=1)
def test_plot_with_axes_or_figure():
img = _generate_img()
figure = plt.figure()
plot_img(img, figure=figure)
ax = plt.subplot(111)
plot_img(img, axes=ax)
def test_plot_empty_slice():
# Test that things don't crash when we give a map with nothing above
# threshold
# This is only a smoke test
data = np.zeros((20, 20, 20))
img = nibabel.Nifti1Image(data, mni_affine)
plot_img(img, display_mode='y', threshold=1)
def test_plot_with_axes_or_figure():
img = _generate_img()
figure = plt.figure()
plot_img(img, figure=figure)
ax = plt.subplot(111)
plot_img(img, axes=ax)
def test_plot_img_with_auto_cut_coords():
data = np.zeros((20, 20, 20))
data[3:-3, 3:-3, 3:-3] = 1
img = nibabel.Nifti1Image(data, np.eye(4))
for display_mode in "xyz":
plot_img(img, cut_coords=None, display_mode=display_mode, black_bg=True)
def test_plot_img_with_auto_cut_coords():
import matplotlib.pyplot as plt
plt.switch_backend('template')
data = np.zeros((20, 20, 20))
data[3:-3, 3:-3, 3:-3] = 1
img = nibabel.Nifti1Image(data, np.eye(4))
for display_mode in 'xyz':
plot_img(img, cut_coords=None, display_mode=display_mode,
black_bg=True)
def test_plot_empty_slice():
# Test that things don't crash when we give a map with nothing above
# threshold
# This is only a smoke test
mp.use('template', warn=False)
import matplotlib.pyplot as plt
plt.switch_backend('template')
data = np.zeros((20, 20, 20))
img = nibabel.Nifti1Image(data, mni_affine)
plot_img(img, display_mode='y', threshold=1)
def test_plot_with_axes_or_figure():
mp.use('template', warn=False)
import matplotlib.pyplot as plt
plt.switch_backend('template')
img = _generate_img()
figure = plt.figure()
plot_img(img, figure=figure)
ax = plt.subplot(111)
plot_img(img, axes=ax)
def test_plot_empty_slice():
# Test that things don't crash when we give a map with nothing above
# threshold
# This is only a smoke test
mp.use('template', warn=False)
import matplotlib.pyplot as plt
plt.switch_backend('template')
data = np.zeros((20, 20, 20))
img = nibabel.Nifti1Image(data, mni_affine)
plot_img(img, display_mode='y', threshold=1)
def test_plot_with_axes_or_figure():
img = _generate_img()
figure = plt.figure()
plot_img(img, figure=figure)
ax = plt.subplot(111)
plot_img(img, axes=ax)
# Save execution time and memory
plt.close()
def test_plot_with_axes_or_figure():
img = _generate_img()
figure = plt.figure()
plot_img(img, figure=figure)
ax = plt.subplot(111)
plot_img(img, axes=ax)
# Save execution time and memory
plt.close()
def test_plot_img_with_auto_cut_coords():
data = np.zeros((20, 20, 20))
data[3:-3, 3:-3, 3:-3] = 1
img = nibabel.Nifti1Image(data, np.eye(4))
for display_mode in 'xyz':
plot_img(img,
cut_coords=None,
display_mode=display_mode,
black_bg=True)
def test_plot_with_axes_or_figure():
mp.use('template', warn=False)
import matplotlib.pyplot as plt
plt.switch_backend('template')
img = _generate_img()
figure = plt.figure()
plot_img(img, figure=figure)
ax = plt.subplot(111)
plot_img(img, axes=ax)
def test_plot_with_axes_or_figure(testdata_3d):
img = testdata_3d['img']
figure = plt.figure()
plot_img(img, figure=figure)
ax = plt.subplot(111)
plot_img(img, axes=ax)
# Save execution time and memory
plt.close()
def test_plot_img_with_auto_cut_coords(testdata_3d):
data = np.zeros((20, 20, 20))
data[3:-3, 3:-3, 3:-3] = 1
img = nibabel.Nifti1Image(data, np.eye(4))
for display_mode in 'xyz':
plot_img(img, cut_coords=None, display_mode=display_mode,
black_bg=True)
# Save execution time and memory
plt.close()
def test_plot_img_with_auto_cut_coords():
data = np.zeros((20, 20, 20))
data[3:-3, 3:-3, 3:-3] = 1
img = nibabel.Nifti1Image(data, np.eye(4))
for display_mode in 'xyz':
plot_img(img, cut_coords=None, display_mode=display_mode,
black_bg=True)
# Save execution time and memory
plt.close()
def test_plot_img_with_auto_cut_coords():
import matplotlib.pyplot as plt
plt.switch_backend('template')
data = np.zeros((20, 20, 20))
data[3:-3, 3:-3, 3:-3] = 1
img = nibabel.Nifti1Image(data, np.eye(4))
for display_mode in 'xyz':
plot_img(img,
cut_coords=None,
display_mode=display_mode,
black_bg=True)
def test_display_methods():
img = _generate_img()
display = plot_img(img)
display.add_overlay(img, threshold=0)
display.add_edges(img, color="c")
display.add_contours(img, contours=2, linewidth=4, colors=["limegreen", "yellow"])
def test_display_methods_with_display_mode_tiled():
img = _generate_img()
display = plot_img(img, display_mode='tiled')
display.add_overlay(img, threshold=0)
display.add_edges(img, color='c')
display.add_contours(img, contours=2, linewidth=4,
colors=['limegreen', 'yellow'])
def test_plot_img_with_resampling():
data = _generate_img().get_data()
affine = np.array([[1.0, -1.0, 0.0, 0.0], [1.0, 1.0, 0.0, 0.0], [0.0, 0.0, 1.0, 0.0], [0.0, 0.0, 0.0, 1.0]])
img = nibabel.Nifti1Image(data, affine)
display = plot_img(img)
display.add_overlay(img)
display.add_contours(img, contours=2, linewidth=4, colors=["limegreen", "yellow"])
display.add_edges(img, color="c")
def test_display_methods(testdata_3d):
img = testdata_3d['img']
display = plot_img(img)
display.add_overlay(img, threshold=0)
display.add_edges(img, color='c')
display.add_contours(img, contours=2, linewidth=4,
colors=['limegreen', 'yellow'])
def test_plot_img_with_resampling():
import matplotlib.pyplot as plt
plt.switch_backend('template')
data = _generate_img().get_data()
affine = np.array([[1., -1., 0., 0.], [1., 1., 0., 0.], [0., 0., 1., 0.],
[0., 0., 0., 1.]])
img = nibabel.Nifti1Image(data, affine)
display = plot_img(img)
display.add_overlay(img)
def test_plot_img_with_resampling():
import pylab as pl
pl.switch_backend('template')
data = MNI152TEMPLATE.get_data()[:5, :5, :5]
affine = np.array([[1., -1., 0., 0.], [1., 1., 0., 0.], [0., 0., 1., 0.],
[0., 0., 0., 1.]])
img = nibabel.Nifti1Image(data, affine)
display = plot_img(img)
display.add_overlay(img)
def test_plot_img_with_resampling():
data = _generate_img().get_data()
affine = np.array([[1., -1., 0., 0.],
[1., 1., 0., 0.],
[0., 0., 1., 0.],
[0., 0., 0., 1.]])
img = nibabel.Nifti1Image(data, affine)
display = plot_img(img)
display.add_overlay(img)
def test_plot_img_with_resampling():
import matplotlib.pyplot as plt
plt.switch_backend('template')
data = _generate_img().get_data()
affine = np.array([[1., -1., 0., 0.],
[1., 1., 0., 0.],
[0., 0., 1., 0.],
[0., 0., 0., 1.]])
img = nibabel.Nifti1Image(data, affine)
display = plot_img(img)
display.add_overlay(img)
def test_display_methods():
mp.use('template', warn=False)
import matplotlib.pyplot as plt
plt.switch_backend('template')
img = _generate_img()
display = plot_img(img)
display.add_overlay(img, threshold=0)
display.add_edges(img, color='c')
display.add_contours(img, contours=2, linewidth=4,
colors=['limegreen', 'yellow'])
def test_plot_img_with_resampling():
data = _generate_img().get_data()
affine = np.array([[1., -1., 0., 0.], [1., 1., 0., 0.], [0., 0., 1., 0.],
[0., 0., 0., 1.]])
img = nibabel.Nifti1Image(data, affine)
display = plot_img(img)
display.add_overlay(img)
display.add_contours(img,
contours=2,
linewidth=4,
colors=['limegreen', 'yellow'])
display.add_edges(img, color='c')
def test_display_methods():
mp.use('template', warn=False)
import matplotlib.pyplot as plt
plt.switch_backend('template')
img = _generate_img()
display = plot_img(img)
display.add_overlay(img, threshold=0)
display.add_edges(img, color='c')
display.add_contours(img,
contours=2,
linewidth=4,
colors=['limegreen', 'yellow'])
def test_plot_img_empty():
# Test that things don't crash when we give a map with nothing above
# threshold
# This is only a smoke test
mp.use('template', warn=False)
import pylab as pl
pl.switch_backend('template')
data = np.zeros((20, 20, 20))
img = nibabel.Nifti1Image(data, mni_affine)
plot_anat(img)
slicer = plot_img(img, display_mode='y', threshold=1)
slicer.close()
pl.close('all')
def test_plot_img_with_resampling():
data = _generate_img().get_data()
affine = np.array([[1., -1., 0., 0.],
[1., 1., 0., 0.],
[0., 0., 1., 0.],
[0., 0., 0., 1.]])
img = nibabel.Nifti1Image(data, affine)
display = plot_img(img)
display.add_overlay(img)
display.add_contours(img, contours=2, linewidth=4,
colors=['limegreen', 'yellow'])
display.add_edges(img, color='c')
# Save execution time and memory
plt.close()
def test_plot_img_with_resampling(testdata_3d):
data = get_data(testdata_3d['img'])
affine = np.array([[1., -1., 0., 0.], [1., 1., 0., 0.], [0., 0., 1., 0.],
[0., 0., 0., 1.]])
img = nibabel.Nifti1Image(data, affine)
display = plot_img(img)
display.add_overlay(img)
display.add_contours(img,
contours=2,
linewidth=4,
colors=['limegreen', 'yellow'])
display.add_edges(img, color='c')
# Save execution time and memory
plt.close()
def test_plotting_functions_with_display_mode_tiled(testdata_3d):
img = testdata_3d['img']
plot_stat_map(img, display_mode='tiled')
plot_anat(display_mode='tiled')
plot_img(img, display_mode='tiled')
plt.close()
def test_plotting_functions_with_display_mode_tiled():
img = _generate_img()
plot_stat_map(img, display_mode='tiled')
plot_anat(display_mode='tiled')
plot_img(img, display_mode='tiled')
plt.close()
