def test_colorscale_asymmetric_cmap_vmax():
cmap = 'jet'
values = np.arange(15)
colors = js_plotting_utils.colorscale(cmap, values, vmax=7,
symmetric_cmap=False)
assert (colors['vmin'], colors['vmax']) == (0, 7)
assert colors['cmap'].N == 256
assert (colors['norm'].vmax, colors['norm'].vmin) == (7, 0)
assert not colors['symmetric_cmap']
values = np.arange(15) + 3
colors = js_plotting_utils.colorscale(cmap, values, vmax=7,
symmetric_cmap=False)
assert (colors['vmin'], colors['vmax']) == (3, 7)
assert (colors['norm'].vmax, colors['norm'].vmin) == (7, 3)
colors = js_plotting_utils.colorscale(
cmap, values, vmax=7, symmetric_cmap=False, vmin=1)
assert (colors['vmin'], colors['vmax']) == (1, 7)
assert (colors['norm'].vmax, colors['norm'].vmin) == (7, 1)
colors = js_plotting_utils.colorscale(
cmap, values, vmax=10, symmetric_cmap=False, vmin=6, threshold=5)
assert (colors['vmin'], colors['vmax']) == (0, 10)
assert (colors['norm'].vmax, colors['norm'].vmin) == (10, 0)
colors = js_plotting_utils.colorscale(
cmap, values, vmax=10, symmetric_cmap=False, vmin=None, threshold=5)
assert (colors['vmin'], colors['vmax']) == (0, 10)
assert (colors['norm'].vmax, colors['norm'].vmin) == (10, 0)
def test_colorscale_asymmetric_cmap_vmax():
cmap = 'jet'
values = np.arange(15)
colors = js_plotting_utils.colorscale(cmap, values, vmax=7,
symmetric_cmap=False)
assert (colors['vmin'], colors['vmax']) == (0, 7)
assert colors['cmap'].N == 256
assert (colors['norm'].vmax, colors['norm'].vmin) == (7, 0)
assert not colors['symmetric_cmap']
values = np.arange(15) + 3
colors = js_plotting_utils.colorscale(cmap, values, vmax=7,
symmetric_cmap=False)
assert (colors['vmin'], colors['vmax']) == (3, 7)
assert (colors['norm'].vmax, colors['norm'].vmin) == (7, 3)
colors = js_plotting_utils.colorscale(
cmap, values, vmax=7, symmetric_cmap=False, vmin=1)
assert (colors['vmin'], colors['vmax']) == (1, 7)
assert (colors['norm'].vmax, colors['norm'].vmin) == (7, 1)
colors = js_plotting_utils.colorscale(
cmap, values, vmax=10, symmetric_cmap=False, vmin=6, threshold=5)
assert (colors['vmin'], colors['vmax']) == (0, 10)
assert (colors['norm'].vmax, colors['norm'].vmin) == (10, 0)
colors = js_plotting_utils.colorscale(
cmap, values, vmax=10, symmetric_cmap=False, vmin=None, threshold=5)
assert (colors['vmin'], colors['vmax']) == (0, 10)
assert (colors['norm'].vmax, colors['norm'].vmin) == (10, 0)
def test_colorscale_no_threshold():
cmap = 'jet'
values = np.linspace(-13, -1.5, 20)
threshold = None
colors = js_plotting_utils.colorscale(cmap, values, threshold)
check_colors(colors['colors'])
assert (colors['vmin'], colors['vmax']) == (-13, 13)
assert colors['cmap'].N == 256
assert (colors['norm'].vmax, colors['norm'].vmin) == (13, -13)
assert colors['abs_threshold'] is None
colors = js_plotting_utils.colorscale(cmap, values > 0, .5)
def test_colorscale_asymmetric_cmap():
cmap = 'jet'
values = np.arange(15)
colors = js_plotting_utils.colorscale(cmap, values, symmetric_cmap=False)
assert (colors['vmin'], colors['vmax']) == (0, 14)
assert colors['cmap'].N == 256
assert (colors['norm'].vmax, colors['norm'].vmin) == (14, 0)
assert not colors['symmetric_cmap']
values = np.arange(15) + 3
colors = js_plotting_utils.colorscale(cmap, values, symmetric_cmap=False)
assert (colors['vmin'], colors['vmax']) == (3, 17)
assert (colors['norm'].vmax, colors['norm'].vmin) == (17, 3)
def test_colorscale_asymmetric_cmap():
cmap = 'jet'
values = np.arange(15)
colors = js_plotting_utils.colorscale(cmap, values, symmetric_cmap=False)
assert (colors['vmin'], colors['vmax']) == (0, 14)
assert colors['cmap'].N == 256
assert (colors['norm'].vmax, colors['norm'].vmin) == (14, 0)
assert not colors['symmetric_cmap']
values = np.arange(15) + 3
colors = js_plotting_utils.colorscale(cmap, values, symmetric_cmap=False)
assert (colors['vmin'], colors['vmax']) == (3, 17)
assert (colors['norm'].vmax, colors['norm'].vmin) == (17, 3)
def test_colorscale_vmin_vmax():
cmap = 'jet'
values = np.arange(15)
colors = js_plotting_utils.colorscale(cmap, values, vmax=7)
assert (colors['vmin'], colors['vmax']) == (-7, 7)
assert colors['cmap'].N == 256
assert (colors['norm'].vmax, colors['norm'].vmin) == (7, -7)
assert colors['symmetric_cmap']
colors = js_plotting_utils.colorscale(cmap, values, vmax=7, vmin=-5)
assert (colors['vmin'], colors['vmax']) == (-7, 7)
assert colors['cmap'].N == 256
assert (colors['norm'].vmax, colors['norm'].vmin) == (7, -7)
assert colors['symmetric_cmap']
def test_colorscale_vmin_vmax():
cmap = 'jet'
values = np.arange(15)
colors = js_plotting_utils.colorscale(cmap, values, vmax=7)
assert (colors['vmin'], colors['vmax']) == (-7, 7)
assert colors['cmap'].N == 256
assert (colors['norm'].vmax, colors['norm'].vmin) == (7, -7)
assert colors['symmetric_cmap']
colors = js_plotting_utils.colorscale(
cmap, values, vmax=7, vmin=-5)
assert (colors['vmin'], colors['vmax']) == (-7, 7)
assert colors['cmap'].N == 256
assert (colors['norm'].vmax, colors['norm'].vmin) == (7, -7)
assert colors['symmetric_cmap']
def test_colorscale_asymmetric_cmap_negative_values():
cmap = 'jet'
values = np.linspace(-15, 4)
with pytest.warns(UserWarning):
js_plotting_utils.colorscale(cmap, values, symmetric_cmap=False)
colors = js_plotting_utils.colorscale(cmap,
values,
vmax=7,
symmetric_cmap=False)
assert (colors['vmin'], colors['vmax']) == (-7, 7)
assert colors['cmap'].N == 256
assert (colors['norm'].vmax, colors['norm'].vmin) == (7, -7)
assert colors['symmetric_cmap']
def test_colorscale_symmetric_cmap(vmin, vmax):
"""Test colorscale with symmetric cmap and positive values."""
colors = colorscale('jet', np.arange(15), vmin=vmin, vmax=vmax)
assert (colors['vmin'], colors['vmax']) == (-7, 7)
assert colors['cmap'].N == 256
assert (colors['norm'].vmax, colors['norm'].vmin) == (7, -7)
assert colors['symmetric_cmap']
def one_mesh_info(surf_map,
surf_mesh,
threshold=None,
cmap=cm.cold_hot,
black_bg=False,
bg_map=None,
symmetric_cmap=True,
vmax=None,
vmin=None):
"""Prepare info for plotting one surface map on a single mesh.
This computes the dictionary that gets inserted in the web page,
which contains the encoded mesh, colors, min and max values, and
background color.
"""
info = {}
colors = colorscale(cmap,
surf_map,
threshold,
symmetric_cmap=symmetric_cmap,
vmax=vmax,
vmin=vmin)
info['inflated_left'] = mesh_to_plotly(surf_mesh)
info['vertexcolor_left'] = _get_vertexcolor(surf_map, colors['cmap'],
colors['norm'],
colors['abs_threshold'],
bg_map)
info["cmin"], info["cmax"] = float(colors['vmin']), float(colors['vmax'])
info['black_bg'] = black_bg
info['full_brain_mesh'] = False
info['colorscale'] = colors['colors']
return info
def test_colorscale_asymmetric_cmap():
cmap = 'jet'
values = np.arange(15)
(colors, vmin, vmax, new_cmap, norm, abs_threshold
) = js_plotting_utils.colorscale(cmap, values, symmetric_cmap=False)
assert (vmin, vmax) == (0, 14)
assert new_cmap.N == 256
assert (norm.vmax, norm.vmin) == (14, 0)
def test_colorscale_vmax():
cmap = 'jet'
values = np.arange(15)
(colors, vmin, vmax, new_cmap, norm, abs_threshold
) = js_plotting_utils.colorscale(cmap, values, vmax=7)
assert (vmin, vmax) == (-7, 7)
assert new_cmap.N == 256
assert (norm.vmax, norm.vmin) == (7, -7)
def test_colorscale_asymmetric_cmap_vmax():
cmap = 'jet'
values = np.arange(15)
colors = js_plotting_utils.colorscale(cmap, values, vmax=7,
symmetric_cmap=False)
assert (colors['vmin'], colors['vmax']) == (0, 7)
assert colors['cmap'].N == 256
assert (colors['norm'].vmax, colors['norm'].vmin) == (7, 0)
assert not colors['symmetric_cmap']
def test_colorscale_no_threshold():
"""Test colorscale with no thresholding."""
values = np.linspace(-13, -1.5, 20)
colors = colorscale('jet', values, None)
check_colors(colors['colors'])
assert (colors['vmin'], colors['vmax']) == (-13, 13)
assert colors['cmap'].N == 256
assert (colors['norm'].vmax, colors['norm'].vmin) == (13, -13)
assert colors['abs_threshold'] is None
def test_colorscale_threshold(threshold, expected_abs_threshold):
"""Test colorscale with different threshold values."""
colors = colorscale('jet', np.linspace(-13, -1.5, 20), threshold=threshold)
_, cstring = check_colors(colors['colors'])
assert cstring[50] == 'rgb(127, 127, 127)'
assert (colors['vmin'], colors['vmax']) == (-13, 13)
assert colors['cmap'].N == 256
assert (colors['norm'].vmax, colors['norm'].vmin) == (13, -13)
assert np.allclose(colors['abs_threshold'], expected_abs_threshold, 2)
assert colors['symmetric_cmap']
def test_colorscale_no_threshold():
cmap = 'jet'
values = np.linspace(-13, -1.5, 20)
threshold = None
colors = js_plotting_utils.colorscale(cmap, values, threshold)
check_colors(colors['colors'])
assert (colors['vmin'], colors['vmax']) == (-13, 13)
assert colors['cmap'].N == 256
assert (colors['norm'].vmax, colors['norm'].vmin) == (13, -13)
assert colors['abs_threshold'] is None
def test_colorscale_threshold_99():
cmap = 'jet'
values = np.linspace(-13, -1.5, 20)
threshold = '99%'
colors = js_plotting_utils.colorscale(cmap, values, threshold)
check_colors(colors['colors'])
assert (colors['vmin'], colors['vmax']) == (-13, 13)
assert colors['cmap'].N == 256
assert (colors['norm'].vmax, colors['norm'].vmin) == (13, -13)
assert colors['abs_threshold'] == 13
assert colors['symmetric_cmap']
def test_colorscale_threshold_99():
cmap = 'jet'
values = np.linspace(-13, -1.5, 20)
threshold = '99%'
(colors, vmin, vmax, new_cmap, norm, abs_threshold
) = js_plotting_utils.colorscale(cmap, values, threshold)
check_colors(colors)
assert (vmin, vmax) == (-13, 13)
assert new_cmap.N == 256
assert (norm.vmax, norm.vmin) == (13, -13)
assert abs_threshold == 13
def test_colorscale_threshold_99():
cmap = 'jet'
values = np.linspace(-13, -1.5, 20)
threshold = '99%'
colors = js_plotting_utils.colorscale(cmap, values, threshold)
check_colors(colors['colors'])
assert (colors['vmin'], colors['vmax']) == (-13, 13)
assert colors['cmap'].N == 256
assert (colors['norm'].vmax, colors['norm'].vmin) == (13, -13)
assert colors['abs_threshold'] == 13
assert colors['symmetric_cmap']
def test_colorscale_threshold_50():
cmap = 'jet'
values = np.linspace(-13, -1.5, 20)
threshold = '50%'
colors = js_plotting_utils.colorscale(cmap, values, threshold)
val, cstring = check_colors(colors['colors'])
assert cstring[50] == 'rgb(127, 127, 127)'
assert (colors['vmin'], colors['vmax']) == (-13, 13)
assert colors['cmap'].N == 256
assert (colors['norm'].vmax, colors['norm'].vmin) == (13, -13)
assert np.allclose(colors['abs_threshold'], 7.55, 2)
assert colors['symmetric_cmap']
def test_colorscale_asymmetric_cmap_negative_values():
cmap = 'jet'
values = np.linspace(-15, 4)
assert_warns(UserWarning, js_plotting_utils.colorscale, cmap,
values, symmetric_cmap=False)
(colors, vmin, vmax, new_cmap, norm, abs_threshold
) = js_plotting_utils.colorscale(cmap, values, vmax=7,
symmetric_cmap=False)
assert (vmin, vmax) == (-7, 7)
assert new_cmap.N == 256
assert (norm.vmax, norm.vmin) == (7, -7)
def test_colorscale_absolute_threshold():
cmap = 'jet'
values = np.linspace(-13, -1.5, 20)
threshold = 7.25
(colors, vmin, vmax, new_cmap, norm, abs_threshold
) = js_plotting_utils.colorscale(cmap, values, threshold)
val, cstring = check_colors(colors)
assert cstring[50] == 'rgb(127, 127, 127)'
assert (vmin, vmax) == (-13, 13)
assert new_cmap.N == 256
assert (norm.vmax, norm.vmin) == (13, -13)
assert np.allclose(abs_threshold, 7.25)
def test_colorscale_asymmetric_cmap_negative_values():
cmap = 'jet'
values = np.linspace(-15, 4)
assert_warns(UserWarning, js_plotting_utils.colorscale, cmap,
values, symmetric_cmap=False)
colors = js_plotting_utils.colorscale(cmap, values, vmax=7,
symmetric_cmap=False)
assert (colors['vmin'], colors['vmax']) == (-7, 7)
assert colors['cmap'].N == 256
assert (colors['norm'].vmax, colors['norm'].vmin) == (7, -7)
assert colors['symmetric_cmap']
def test_colorscale_absolute_threshold():
cmap = 'jet'
values = np.linspace(-13, -1.5, 20)
threshold = 7.25
colors = js_plotting_utils.colorscale(cmap, values, threshold)
val, cstring = check_colors(colors['colors'])
assert cstring[50] == 'rgb(127, 127, 127)'
assert (colors['vmin'], colors['vmax']) == (-13, 13)
assert colors['cmap'].N == 256
assert (colors['norm'].vmax, colors['norm'].vmin) == (13, -13)
assert np.allclose(colors['abs_threshold'], 7.25)
assert colors['symmetric_cmap']
def test_colorscale_asymmetric_cmap(values, vmax, vmin, threshold,
expected_vmin_vmax):
"""Test colorscale with asymmetric cmap."""
colors = colorscale('jet',
values,
vmax=vmax,
vmin=vmin,
threshold=threshold,
symmetric_cmap=False)
assert (min(values) < 0) | (not colors['symmetric_cmap'])
assert colors['cmap'].N == 256
assert (int(colors['vmin']), int(colors['vmax'])) == expected_vmin_vmax
assert ((colors['norm'].vmax,
colors['norm'].vmin) == expected_vmin_vmax[::-1])
def full_brain_info(volume_img,
mesh='fsaverage5',
threshold=None,
cmap=cm.cold_hot,
black_bg=False,
symmetric_cmap=True,
vmax=None,
vmin=None,
vol_to_surf_kwargs={}):
"""
Project 3D map on cortex; prepare info to plot both hemispheres.
This computes the dictionary that gets inserted in the web page,
which contains encoded meshes, colors, min and max values, and
background color.
"""
info = {}
mesh = surface.surface._check_mesh(mesh)
surface_maps = {
h: surface.vol_to_surf(volume_img,
mesh['pial_{}'.format(h)],
inner_mesh=mesh.get('white_{}'.format(h), None),
**vol_to_surf_kwargs)
for h in ['left', 'right']
}
colors = colorscale(cmap,
np.asarray(list(surface_maps.values())).ravel(),
threshold,
symmetric_cmap=symmetric_cmap,
vmax=vmax,
vmin=vmin)
for hemi, surf_map in surface_maps.items():
bg_map = surface.load_surf_data(mesh['sulc_{}'.format(hemi)])
info['pial_{}'.format(hemi)] = mesh_to_plotly(
mesh['pial_{}'.format(hemi)])
info['inflated_{}'.format(hemi)] = mesh_to_plotly(
mesh['infl_{}'.format(hemi)])
info['vertexcolor_{}'.format(hemi)] = _get_vertexcolor(
surf_map, colors['cmap'], colors['norm'], colors['abs_threshold'],
bg_map)
info["cmin"], info["cmax"] = float(colors['vmin']), float(colors['vmax'])
info['black_bg'] = black_bg
info['full_brain_mesh'] = True
info['colorscale'] = colors['colors']
return info
def plot_surf(mesh, data, view="right", threshold="85%", output_file=None):
coords, triangles = surface.load_surf_mesh(mesh)
x, y, z = coords.T
i, j, k = triangles.T
colors = colorscale(cold_hot, data, threshold)
vertexcolor = _get_vertexcolor(
data,
colors["cmap"],
colors["norm"],
colors["abs_threshold"],
surface.load_surf_data(fsaverage["sulc_right"]),
)
mesh_3d = go.Mesh3d(x=x, y=y, z=z, i=i, j=j, k=k, vertexcolor=vertexcolor)
fig = go.Figure(data=[mesh_3d])
fig.update_layout(scene_camera=CAMERAS[view], **LAYOUT)
if output_file is not None:
fig.write_image(output_file)
return fig
def fit(self, stat_map_img, bg_img="MNI152"):
"""
Generate sprite and meta-data from a brain volume. Also optionally
incorporate a background image.
:param stat_map_img: The statistical map image. Can be either a 3D volume
or a 4D volume with exactly one time point.
:type stat_map_img: stasNiimg-like object, See
http://nilearn.github.io/manipulating_images/input_output.html
:param bg_img: The background image that the stat map will be plotted on top of.
If nothing is specified, the MNI152 template will be used.
To turn off background image, just pass "bg_img=False".
:type bg_img: Niimg-like object, optional
See http://nilearn.github.io/manipulating_images/input_output.html
"""
# Prepare the color map and thresholding
mask_img, stat_map_img, data, self.threshold = _mask_stat_map(
stat_map_img, self.threshold)
self.colors_ = colorscale(
self.cmap,
data.ravel(),
threshold=self.threshold,
symmetric_cmap=self.symmetric_cmap,
vmax=self.vmax,
vmin=self.vmin,
)
if self.black_bg:
cfont = "#FFFFFF"
cbg = "#000000"
else:
cfont = "#000000"
cbg = "#FFFFFF"
# Prepare the data for the cuts
bg_img, self.bg_min_, self.bg_max_, self.black_bg_ = _load_bg_img(
stat_map_img, bg_img, self.black_bg, self.dim)
stat_map_img, mask_img = _resample_stat_map(
stat_map_img, bg_img, mask_img, self.resampling_interpolation)
self.cut_slices_ = _get_cut_slices(stat_map_img, self.cut_coords,
self.threshold)
# Now create the viewer, and populate the sprite data
self.html_ = self._brainsprite_html(bg_img, stat_map_img, mask_img)
# Add the javascript snippet
self.javascript_ = self._brainsprite_js(
shape=stat_map_img.shape,
affine=stat_map_img.affine,
colorFont=cfont,
colorBackground=cbg,
)
# Add the brainsprite.min.js library
js_dir = os.path.join(os.path.dirname(__file__), "data", "js")
with open(os.path.join(js_dir, "brainsprite.min.js")) as f:
self.library_ = f.read()
f.close()
# Suggest a size for the viewer
# width x height, in pixels
self.width_, self.height_ = _viewer_size(stat_map_img.shape)
def _plot_surf_plotly(coords, faces, surf_map=None, bg_map=None,
hemi='left', view='lateral', cmap=None,
symmetric_cmap=True, colorbar=False,
threshold=None, vmin=None, vmax=None,
cbar_vmin=None, cbar_vmax=None,
cbar_tick_format=".1f", title=None,
title_font_size=18, output_file=None):
"""Helper function for plot_surf.
.. versionadded:: 0.8.2
This function handles surface plotting when the selected
engine is plotly.
.. note::
This function assumes that plotly and kaleido are
installed.
.. warning::
This function is new and experimental. Please report
bugs that you may encounter.
"""
try:
import plotly.graph_objects as go
from nilearn.plotting.displays import PlotlySurfaceFigure
except ImportError:
msg = "Using engine='plotly' requires that ``plotly`` is installed."
raise ImportError(msg) # noqa
x, y, z = coords.T
i, j, k = faces.T
if cmap is None:
cmap = cold_hot
bg_data = None
if bg_map is not None:
bg_data = load_surf_data(bg_map)
if bg_data.shape[0] != coords.shape[0]:
raise ValueError('The bg_map does not have the same number '
'of vertices as the mesh.')
if surf_map is not None:
_check_surf_map(surf_map, coords.shape[0])
colors = colorscale(
cmap, surf_map, threshold, vmax=vmax, vmin=vmin,
symmetric_cmap=symmetric_cmap
)
vertexcolor = _get_vertexcolor(
surf_map, colors["cmap"], colors["norm"],
colors["abs_threshold"], bg_data
)
else:
if bg_data is None:
bg_data = np.zeros(coords.shape[0])
colors = colorscale('Greys', bg_data, symmetric_cmap=False)
vertexcolor = _get_vertexcolor(
bg_data, colors["cmap"], colors["norm"],
colors["abs_threshold"]
)
mesh_3d = go.Mesh3d(x=x, y=y, z=z, i=i, j=j, k=k, vertexcolor=vertexcolor)
fig_data = [mesh_3d]
if colorbar:
dummy = _get_cbar_plotly(
colors["colors"], float(colors["vmin"]), float(colors["vmax"]),
cbar_tick_format
)
fig_data.append(dummy)
cameras_view = _set_view_plot_surf_plotly(hemi, view)
fig = go.Figure(data=fig_data)
fig.update_layout(scene_camera=CAMERAS[cameras_view],
title=_configure_title_plotly(title, title_font_size),
**LAYOUT)
if output_file is not None:
try:
import kaleido # noqa: F401
except ImportError:
msg = ("Saving figures to file with engine='plotly' requires "
"that ``kaleido`` is installed.")
raise ImportError(msg) # noqa
plotly_figure = PlotlySurfaceFigure(figure=fig, output_file=output_file)
if output_file is not None:
plotly_figure.savefig()
return plotly_figure
