"""
Functions for plotting ants images
"""
__all__ = [
"plot_grid"
]
import fnmatch
import math
import os
import warnings
from matplotlib import gridspec
import matplotlib.pyplot as plt
import matplotlib.patheffects as path_effects
import matplotlib.lines as mlines
import matplotlib.patches as patches
import matplotlib.mlab as mlab
import matplotlib.animation as animation
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
import numpy as np
[docs]
def plot_grid(
images,
slices=None,
axes=2,
# general figure arguments
figsize=1.0,
rpad=0,
cpad=0,
vmin=None,
vmax=None,
colorbar=True,
cmap="Greys_r",
# title arguments
title=None,
tfontsize=20,
title_dx=0,
title_dy=0,
# row arguments
rlabels=None,
rfontsize=14,
rfontcolor="white",
rfacecolor="black",
# column arguments
clabels=None,
cfontsize=14,
cfontcolor="white",
cfacecolor="black",
# save arguments
filename=None,
dpi=400,
transparent=True,
# other args
**kwargs
):
"""
Plot a collection of images in an arbitrarily-defined grid
Matplotlib named colors: https://matplotlib.org/examples/color/named_colors.html
Arguments
---------
images : list of ANTsImage types
image(s) to plot.
if one image, this image will be used for all grid locations.
if multiple images, they should be arrange in a list the same
shape as the `gridsize` argument.
slices : integer or list of integers
slice indices to plot
if one integer, this slice index will be used for all images
if multiple integers, they should be arranged in a list the same
shape as the `gridsize` argument
axes : integer or list of integers
axis or axes along which to plot image slices
if one integer, this axis will be used for all images
if multiple integers, they should be arranged in a list the same
shape as the `gridsize` argument
Example
-------
>>> import ants
>>> import numpy as np
>>> mni1 = ants.image_read(ants.get_data('mni'))
>>> mni2 = mni1.smooth_image(1.)
>>> mni3 = mni1.smooth_image(2.)
>>> mni4 = mni1.smooth_image(3.)
>>> images = np.asarray([[mni1, mni2],
... [mni3, mni4]])
>>> slices = np.asarray([[100, 100],
... [100, 100]])
>>> ants.plot_grid(images=images, slices=slices, title='2x2 Grid')
>>> images2d = np.asarray([[mni1.slice_image(2,100), mni2.slice_image(2,100)],
... [mni3.slice_image(2,100), mni4.slice_image(2,100)]])
>>> ants.plot_grid(images=images2d, title='2x2 Grid Pre-Sliced')
>>> ants.plot_grid(images.reshape(1,4), slices.reshape(1,4), title='1x4 Grid')
>>> ants.plot_grid(images.reshape(4,1), slices.reshape(4,1), title='4x1 Grid')
>>> # Padding between rows and/or columns
>>> ants.plot_grid(images, slices, cpad=0.02, title='Col Padding')
>>> ants.plot_grid(images, slices, rpad=0.02, title='Row Padding')
>>> ants.plot_grid(images, slices, rpad=0.02, cpad=0.02, title='Row and Col Padding')
>>> # Adding plain row and/or column labels
>>> ants.plot_grid(images, slices, title='Adding Row Labels', rlabels=['Row #1', 'Row #2'])
>>> ants.plot_grid(images, slices, title='Adding Col Labels', clabels=['Col #1', 'Col #2'])
>>> ants.plot_grid(images, slices, title='Row and Col Labels',
rlabels=['Row 1', 'Row 2'], clabels=['Col 1', 'Col 2'])
>>> # Making a publication-quality image
>>> images = np.asarray([[mni1, mni2, mni2],
... [mni3, mni4, mni4]])
>>> slices = np.asarray([[100, 100, 100],
... [100, 100, 100]])
>>> axes = np.asarray([[0, 1, 2],
[0, 1, 2]])
>>> ants.plot_grid(images, slices, axes, title='Publication Figures with ANTsPy',
tfontsize=20, title_dy=0.03, title_dx=-0.04,
rlabels=['Row 1', 'Row 2'],
clabels=['Col 1', 'Col 2', 'Col 3'],
rfontsize=16, cfontsize=16)
"""
def mirror_matrix(x):
return x[::-1, :]
def rotate270_matrix(x):
return mirror_matrix(x.T)
def rotate180_matrix(x):
return x[::-1, ::-1]
def rotate90_matrix(x):
return mirror_matrix(x).T
def flip_matrix(x):
return mirror_matrix(rotate180_matrix(x))
def reorient_slice(x, axis):
if axis != 1:
x = rotate90_matrix(x)
if axis == 1:
x = rotate90_matrix(x)
x = mirror_matrix(x)
return x
def slice_image(img, axis, idx):
if axis == 0:
return img[idx, :, :].numpy()
elif axis == 1:
return img[:, idx, :].numpy()
elif axis == 2:
return img[:, :, idx].numpy()
elif axis == -1:
return img[:, :, idx].numpy()
elif axis == -2:
return img[:, idx, :].numpy()
elif axis == -3:
return img[idx, :, :].numpy()
else:
raise ValueError("axis %i not valid" % axis)
if isinstance(images, np.ndarray):
images = images.tolist()
if not isinstance(images, list):
raise ValueError("images argument must be of type list")
if not isinstance(images[0], list):
images = [images]
if slices is None:
one_slice = True
if isinstance(slices, int):
one_slice = True
if isinstance(slices, np.ndarray):
slices = slices.tolist()
if isinstance(slices, list):
one_slice = False
if not isinstance(slices[0], list):
slices = [slices]
nslicerow = len(slices)
nslicecol = len(slices[0])
nrow = len(images)
ncol = len(images[0])
if rlabels is None:
rlabels = [None] * nrow
if clabels is None:
clabels = [None] * ncol
if not one_slice:
if (nrow != nslicerow) or (ncol != nslicecol):
raise ValueError(
"`images` arg shape (%i,%i) must equal `slices` arg shape (%i,%i)!"
% (nrow, ncol, nslicerow, nslicecol)
)
fig = plt.figure(figsize=((ncol + 1) * 2.5 * figsize, (nrow + 1) * 2.5 * figsize))
if title is not None:
basex = 0.5
basey = 0.9 if clabels[0] is None else 0.95
fig.suptitle(title, fontsize=tfontsize, x=basex + title_dx, y=basey + title_dy)
if (cpad > 0) and (rpad > 0):
bothgridpad = max(cpad, rpad)
cpad = 0
rpad = 0
else:
bothgridpad = 0.0
gs = gridspec.GridSpec(
nrow,
ncol,
wspace=bothgridpad,
hspace=0.0,
top=1.0 - 0.5 / (nrow + 1),
bottom=0.5 / (nrow + 1) + cpad,
left=0.5 / (ncol + 1) + rpad,
right=1 - 0.5 / (ncol + 1),
)
if isinstance(vmin, (int, float)):
vmins = [vmin] * nrow
elif vmin is None:
vmins = [None] * nrow
else:
vmins = vmin
if isinstance(vmax, (int, float)):
vmaxs = [vmax] * nrow
elif vmax is None:
vmaxs = [None] * nrow
else:
vmaxs = vmax
if isinstance(cmap, str):
cmaps = [cmap] * nrow
elif cmap is None:
cmaps = [None] * nrow
else:
cmaps = cmap
for rowidx, rvmin, rvmax, rcmap in zip(range(nrow), vmins, vmaxs, cmaps):
for colidx in range(ncol):
ax = plt.subplot(gs[rowidx, colidx])
if colidx == 0:
if rlabels[rowidx] is not None:
bottom, height = 0.25, 0.5
top = bottom + height
# add label text
ax.text(
-0.07,
0.5 * (bottom + top),
rlabels[rowidx],
horizontalalignment="right",
verticalalignment="center",
rotation="vertical",
transform=ax.transAxes,
color=rfontcolor,
fontsize=rfontsize,
)
# add label background
extra = 0.3 if rowidx == 0 else 0.0
rect = patches.Rectangle(
(-0.3, 0),
0.3,
1.0 + extra,
facecolor=rfacecolor,
alpha=1.0,
transform=ax.transAxes,
clip_on=False,
)
ax.add_patch(rect)
if rowidx == 0:
if clabels[colidx] is not None:
bottom, height = 0.25, 0.5
left, width = 0.25, 0.5
right = left + width
top = bottom + height
ax.text(
0.5 * (left + right),
0.09 + top + bottom,
clabels[colidx],
horizontalalignment="center",
verticalalignment="center",
rotation="horizontal",
transform=ax.transAxes,
color=cfontcolor,
fontsize=cfontsize,
)
# add label background
rect = patches.Rectangle(
(0, 1.0),
1.0,
0.3,
facecolor=cfacecolor,
alpha=1.0,
transform=ax.transAxes,
clip_on=False,
)
ax.add_patch(rect)
tmpimg = images[rowidx][colidx]
if isinstance(axes, int):
tmpaxis = axes
else:
tmpaxis = axes[rowidx][colidx]
if tmpimg.dimension == 2:
tmpslice = tmpimg.numpy()
tmpslice = reorient_slice(tmpslice, tmpaxis)
else:
sliceidx = slices[rowidx][colidx] if not one_slice else slices
if sliceidx is None:
sliceidx = math.ceil(tmpimg.shape[tmpaxis] / 2)
tmpslice = slice_image(tmpimg, tmpaxis, sliceidx)
tmpslice = reorient_slice(tmpslice, tmpaxis)
im = ax.imshow(tmpslice, cmap=rcmap, aspect="auto", vmin=rvmin, vmax=rvmax)
ax.axis("off")
# A colorbar solution with make_axes_locatable will not allow y-scaling of the colorbar.
# from mpl_toolkits.axes_grid1 import make_axes_locatable
# divider = make_axes_locatable(ax)
# cax = divider.append_axes('right', size='5%', pad=0.05)
if colorbar:
axins = inset_axes(ax,
width="5%", # width = 5% of parent_bbox width
height="90%", # height : 50%
loc='center left',
bbox_to_anchor=(1.03, 0., 1, 1),
bbox_transform=ax.transAxes,
borderpad=0,
)
fig.colorbar(im, cax=axins, orientation='vertical')
if filename is not None:
filename = os.path.expanduser(filename)
plt.savefig(filename, dpi=dpi, transparent=transparent, bbox_inches="tight")
plt.close(fig)
else:
plt.show()