def sph_project(
vertices, val, ax=None, vmin=None, vmax=None, cmap=None, cbar=True, tri=False, boundary=False, **basemap_args
):
"""Draw a signal on a 2D projection of the sphere.
Parameters
----------
vertices : (N,3) ndarray
unit vector points of the sphere
val: (N) ndarray
Function values.
ax : mpl axis, optional
If specified, draw onto this existing axis instead.
vmin, vmax: floats
Values to cut the z
cmap: mpl colormap
cbar: Whether to add the color-bar to the figure
triang: Whether to display the plot triangulated as a pseudo-color plot.
boundary: Whether to draw the boundary around the projection in a black line
Returns
-------
ax : axis
Matplotlib figure axis
Examples
--------
>>> from dipy.data import get_sphere
>>> verts = get_sphere('symmetric724').vertices
>>> ax = sph_project(verts.T, np.random.rand(len(verts.T))) # skip if not has_basemap
"""
if ax is None:
fig, ax = plt.subplots(1)
if cmap is None:
cmap = matplotlib.cm.hot
basemap_args.setdefault("projection", "ortho")
basemap_args.setdefault("lat_0", 0)
basemap_args.setdefault("lon_0", 0)
basemap_args.setdefault("resolution", "c")
from mpl_toolkits.basemap import Basemap
m = Basemap(**basemap_args)
if boundary:
m.drawmapboundary()
# Rotate the coordinate system so that you are looking from the north pole:
verts_rot = np.array(np.dot(np.matrix([[0, 0, -1], [0, 1, 0], [1, 0, 0]]), vertices))
# To get the orthographic projection, when the first coordinate is positive:
neg_idx = np.where(verts_rot[0] > 0)
# rotate the entire bvector around to point in the other direction:
verts_rot[:, neg_idx] *= -1
_, theta, phi = geo.cart2sphere(verts_rot[0], verts_rot[1], verts_rot[2])
lat, lon = geo.sph2latlon(theta, phi)
x, y = m(lon, lat)
my_min = np.nanmin(val)
if vmin is not None:
my_min = vmin
my_max = np.nanmax(val)
if vmax is not None:
my_max = vmax
if tri:
m.pcolor(x, y, val, vmin=my_min, vmax=my_max, tri=True, cmap=cmap)
else:
cmap_data = cmap._segmentdata
red_interp, blue_interp, green_interp = (
interp.interp1d(np.array(cmap_data[gun])[:, 0], np.array(cmap_data[gun])[:, 1])
for gun in ["red", "blue", "green"]
)
r = (val - my_min) / float(my_max - my_min)
# Enforce the maximum and minumum boundaries, if there are values
# outside those boundaries:
r[r < 0] = 0
r[r > 1] = 1
for this_x, this_y, this_r in zip(x, y, r):
red = red_interp(this_r)
blue = blue_interp(this_r)
green = green_interp(this_r)
m.plot(this_x, this_y, "o", c=[red.item(), green.item(), blue.item()])
if cbar:
mappable = matplotlib.cm.ScalarMappable(cmap=cmap)
mappable.set_array([my_min, my_max])
# setup colorbar axes instance.
pos = ax.get_position()
l, b, w, h = pos.bounds
# setup colorbar axes
cax = fig.add_axes([l + w + 0.075, b, 0.05, h], frameon=False)
fig.colorbar(mappable, cax=cax) # draw colorbar
return ax
def sph_project(vertices,
val,
ax=None,
vmin=None,
vmax=None,
cmap=None,
cbar=True,
tri=False,
boundary=False,
**basemap_args):
"""Draw a signal on a 2D projection of the sphere.
Parameters
----------
vertices : (N,3) ndarray
unit vector points of the sphere
val: (N) ndarray
Function values.
ax : mpl axis, optional
If specified, draw onto this existing axis instead.
vmin, vmax : floats
Values to cut the z
cmap : mpl colormap
cbar: Whether to add the color-bar to the figure
triang : Whether to display the plot triangulated as a pseudo-color plot.
boundary : Whether to draw the boundary around the projection
in a black line
Returns
-------
ax : axis
Matplotlib figure axis
Examples
--------
>>> from dipy.data import get_sphere
>>> verts = get_sphere('symmetric724').vertices
>>> ax = sph_project(verts.T, np.random.rand(len(verts.T))) # skip if not has_basemap
"""
if ax is None:
fig, ax = plt.subplots(1)
if cmap is None:
cmap = matplotlib.cm.hot
basemap_args.setdefault('projection', 'ortho')
basemap_args.setdefault('lat_0', 0)
basemap_args.setdefault('lon_0', 0)
basemap_args.setdefault('resolution', 'c')
from mpl_toolkits.basemap import Basemap
m = Basemap(**basemap_args)
if boundary:
m.drawmapboundary()
# Rotate the coordinate system so that you are looking from the north pole:
verts_rot = np.array(
np.dot(np.array([[0, 0, -1], [0, 1, 0], [1, 0, 0]]), vertices))
# To get the orthographic projection, when the first coordinate is
# positive:
neg_idx = np.where(verts_rot[0] > 0)
# rotate the entire bvector around to point in the other direction:
verts_rot[:, neg_idx] *= -1
_, theta, phi = geo.cart2sphere(verts_rot[0], verts_rot[1], verts_rot[2])
lat, lon = geo.sph2latlon(theta, phi)
x, y = m(lon, lat)
my_min = np.nanmin(val)
if vmin is not None:
my_min = vmin
my_max = np.nanmax(val)
if vmax is not None:
my_max = vmax
if tri:
m.pcolor(x, y, val, vmin=my_min, vmax=my_max, tri=True, cmap=cmap)
else:
cmap_data = cmap._segmentdata
red_interp, blue_interp, green_interp = (interp.interp1d(
np.array(cmap_data[gun])[:, 0],
np.array(cmap_data[gun])[:,
1]) for gun in ['red', 'blue', 'green'])
r = (val - my_min) / float(my_max - my_min)
# Enforce the maximum and minumum boundaries, if there are values
# outside those boundaries:
r[r < 0] = 0
r[r > 1] = 1
for this_x, this_y, this_r in zip(x, y, r):
red = red_interp(this_r)
blue = blue_interp(this_r)
green = green_interp(this_r)
m.plot(this_x,
this_y,
'o',
c=[red.item(), green.item(),
blue.item()])
if cbar:
mappable = matplotlib.cm.ScalarMappable(cmap=cmap)
mappable.set_array([my_min, my_max])
# setup colorbar axes instance.
pos = ax.get_position()
l, b, w, h = pos.bounds
# setup colorbar axes
cax = fig.add_axes([l + w + 0.075, b, 0.05, h], frameon=False)
fig.colorbar(mappable, cax=cax) # draw colorbar
return ax