import os
import numpy as np
import zarr
import math
import inspect
from tqdm import tqdm
try:
import matplotlib.pyplot as plt
from matplotlib.animation import ArtistAnimation
except:
not_installed = True
else:
not_installed = False
[docs]
def animation(
array,
path=None,
filename='animation',
vmin=None,
vmax=None,
title = '',
interval=250,
show=True,
verbose=0,
):
"""
Produce an animation of a 3D image.
Parameters
----------
array : numpy.array | zarr.Array
The 3D image to animate.
path : str, optional
The path to save the animation. The default is None.
filename : str, optional
The filename of the animation. The default is 'animation'.
vmin : float, optional
The minimum value for the colormap. The default is None.
vmax : float, optional
The maximum value for the colormap. The default is None.
title : str, optional
The title of the animation to be rendered on the figure.
The default is ''.
interval : int, optional
The interval between frames. The default is 250ms.
show : bool, optional
Whether to display the animation. The default is False.
verbose : int, optional
Set to 1 to show progress bars. Default is 0 (no progress bars).
"""
if not_installed:
raise ImportError(
"The plot functions are optional - please install mdreg as "
"pip install mdreg[plot] if you want to use these."
)
shape = np.shape(array)
titlesize = 10
if array.ndim == 4: ##save 3D data
# Determine the grid size for the panels
num_slices = array.shape[2]
grid_size = math.ceil(math.sqrt(num_slices))
fig_3d, axes1 = plt.subplots(grid_size, grid_size, figsize=(grid_size*2, grid_size*2))
fig_3d.subplots_adjust(wspace=0.5, hspace=0.01)
fig_3d.suptitle('{} \n \n'.format(title), fontsize=titlesize+2)
plt.tight_layout()
for i in range(grid_size * grid_size):
row = i // grid_size
col = i % grid_size
if i < num_slices:
im = np.nan_to_num(array[:, :, i, 0])
axes1[row, col].imshow(im.T, cmap='gray', animated=True, vmin=vmin, vmax=vmax)
axes1[row, col].set_title(f'Slice {i+1}', fontsize=titlesize)
else:
axes1[row, col].axis('off') # Turn off unused subplots
axes1[row, col].set_xticks([]) # Remove x-axis ticks
axes1[row, col].set_yticks([])
images = []
for j in tqdm(range(array.shape[-1]), desc='Building animation', disable=verbose==0):
ims = []
for i in range(grid_size * grid_size):
row = i // grid_size
col = i % grid_size
if i < num_slices:
im = np.nan_to_num(array[:, :, i, j])
im = axes1[row, col].imshow(im.T, cmap='gray', animated=True, vmin=vmin, vmax=vmax)
ims.append(im)
images.append(ims,)
anim = ArtistAnimation(fig_3d, images, interval=interval, repeat_delay=interval)
if path is not None:
file_3D_save = os.path.join(path, filename)
anim.save(file_3D_save + "_" + ".gif")
if show:
plt.show()
return anim
else:
plt.close()
return
else: # save 2D data
fig, ax = plt.subplots()
im = np.nan_to_num(array[:, :, 0])
im = ax.imshow(im.T, cmap='gray', animated=True, vmin=vmin, vmax=vmax)
ims = []
for i in tqdm(range(shape[-1]), desc='Building animation', disable=verbose==0):
im = np.nan_to_num(array[:, :, i])
im = ax.imshow(im.T, cmap='gray', animated=True, vmin=vmin, vmax=vmax)
ims.append([im])
anim = ArtistAnimation(fig, ims, interval=interval)
if path is not None:
file_3D_save = os.path.join(path, filename)
anim.save(file_3D_save + ".gif")
if show:
plt.show()
return anim
else:
plt.close()
return
[docs]
def series(moving, fixed, coreg, path=None, filename='animation',
vmin=None, vmax=None, interval=250, show=True):
"""
Produce an animation of the original, fitted and coregistered images.
Parameters
----------
moving : numpy.array
The moving image.
fixed : numpy.array
The fixed/fitted image.
coreg : numpy.array
The coregistered image.
path : str, optional
The path to save the animation. The default is None.
filename : str, optional
The filename of the animation. The default is 'animation'.
vmin : float, optional
The minimum value for the colormap. The default is None.
vmax : float, optional
The maximum value for the colormap. The default is None.
interval : int, optional
The interval between frames. The default is 250ms.
show : bool, optional
Whether to display the animation. The default is False.
"""
if not_installed:
raise ImportError(
"The plot functions are optional - please install mdreg as "
"pip install mdreg[plot] if you want to use these."
)
titlesize = 6
if (moving.ndim == fixed.ndim == coreg.ndim == 4):
# Determine the grid size for the panels
num_slices = moving.shape[2]
grid_size = math.ceil(math.sqrt(num_slices))
titles = ['Original Data', 'Model Fit', 'Coregistered']
anims = []
for data in (moving, fixed, coreg):
fig_3d, axes1 = plt.subplots(grid_size, grid_size, figsize=(grid_size*2, grid_size*2))
fig_3d.subplots_adjust(wspace=0.5, hspace=0.01)
data_name = titles[[np.array_equal(data, moving), np.array_equal(data, fixed), np.array_equal(data, coreg)].index(True)]
fig_3d.suptitle('Series Type: {} \n \n'.format(data_name), fontsize=titlesize+2)
plt.tight_layout()
for i in range(grid_size * grid_size):
row = i // grid_size
col = i % grid_size
if i < num_slices:
axes1[row, col].imshow(data[:, :, i, 0].T, cmap='gray', animated=True, vmin=vmin, vmax=vmax)
axes1[row, col].set_title('Slice {}'.format(i+1), fontsize=titlesize)
else:
axes1[row, col].axis('off') # Turn off unused subplots
axes1[row, col].set_xticks([]) # Remove x-axis ticks
axes1[row, col].set_yticks([])
images = []
for j in range(data.shape[-1]):
ims = []
for i in range(grid_size * grid_size):
row = i // grid_size
col = i % grid_size
if i < num_slices:
im = axes1[row, col].imshow(data[:, :, i, j].T, cmap='gray', animated=True, vmin=vmin, vmax=vmax)
ims.append(im)
images.append(ims,)
anim = ArtistAnimation(fig_3d, images, interval=interval, repeat_delay=interval)
if path is not None:
file_3D_save = os.path.join(path, filename)
data_type_name = _get_var_name(data)
anim.save(file_3D_save + "_" + data_type_name + ".gif")
if show:
plt.show()
anims.append(anim)
else:
plt.close()
if show:
return anims
else:
return
elif not (moving.ndim == fixed.ndim == coreg.ndim):
raise ValueError('Dimension mismatch in arrays provided. Please '
'ensure the three arrays have the same dimensions')
fig, ax = plt.subplots(figsize=(6, 2), ncols=3, nrows=1)
ax[0].set_title('Model fit', fontsize=titlesize+2)
ax[1].set_title('Original Data', fontsize=titlesize+2)
ax[2].set_title('Coregistered', fontsize=titlesize+2)
for i in range(3):
ax[i].set_yticklabels([])
ax[i].set_xticklabels([])
ax[0].imshow(fixed[:,:,0].T, cmap='gray', animated=True, vmin=vmin, vmax=vmax)
ax[1].imshow(moving[:,:,0].T, cmap='gray', animated=True, vmin=vmin, vmax=vmax)
ax[2].imshow(coreg[:,:,0].T, cmap='gray', animated=True, vmin=vmin, vmax=vmax)
ims = []
for i in range(fixed.shape[-1]):
im0 = ax[0].imshow(fixed[:,:,i].T, cmap='gray', animated=True, vmin=vmin, vmax=vmax)
im1 = ax[1].imshow(moving[:,:,i].T, cmap='gray', animated=True, vmin=vmin, vmax=vmax)
im2 = ax[2].imshow(coreg[:,:,i].T, cmap='gray', animated=True, vmin=vmin, vmax=vmax)
ims.append([im0, im1, im2])
anim = ArtistAnimation(fig, ims, interval=interval, repeat_delay=interval)
if path is not None:
file_3D_save = os.path.join(path, filename)
anim.save(file_3D_save + ".gif")
if show:
plt.show()
return anim
else:
plt.close()
return
[docs]
def par(array:np.ndarray, path=None, filename='image', vmin=None, vmax=None,
title='', show=True):
"""
Plot a 2D or 3D image.
Parameters
----------
array : numpy.array
The 2D or 3D image to animate.
path : str, optional
The path to save the animation. The default is None.
filename : str, optional
The filename to save the image. The default is 'image'.
vmin : float, optional
The minimum value for the colormap. The default is None.
vmax : float, optional
The maximum value for the colormap. The default is None.
title : str, optional
The title of the plot. The default is ''.
show : bool, optional
Whether to display the animation. The default is False.
"""
if not_installed:
raise ImportError(
"The plot functions are optional - please install mdreg as "
"pip install mdreg[plot] if you want to use these."
)
if array.ndim not in [2,3]:
raise ValueError("Parameter array must be 2D or 3D")
titlesize = 10
if array.ndim == 3: ##save 3D data
# Determine the grid size for the panels
num_slices = array.shape[2]
grid_size = math.ceil(math.sqrt(num_slices))
fig_3d, axes1 = plt.subplots(grid_size, grid_size, figsize=(grid_size*2, grid_size*2))
fig_3d.subplots_adjust(wspace=0.5, hspace=0.01)
fig_3d.suptitle('{} \n \n'.format(title), fontsize=titlesize+2)
plt.tight_layout()
for i in range(grid_size * grid_size):
row = i // grid_size
col = i % grid_size
if i < num_slices:
axes1[row, col].imshow(np.nan_to_num(array[:, :, i]).T, cmap='gray',
vmin=vmin, vmax=vmax)
axes1[row, col].set_title('Slice {}'.format(i+1),
fontsize=titlesize)
else:
axes1[row, col].axis('off') # Turn off unused subplots
axes1[row, col].set_xticks([]) # Remove x-axis ticks
axes1[row, col].set_yticks([])
if path is not None:
file_3D_save = os.path.join(path, filename)
fig_3d.save(file_3D_save + ".gif")
if show:
plt.show()
return fig_3d
else:
plt.close()
return
else: # save 2D data
fig, ax = plt.subplots()
im = ax.imshow(np.nan_to_num(array[:,:]).T, cmap='gray', vmin=vmin, vmax=vmax)
if path is not None:
file_3D_save = os.path.join(path, filename)
fig.save(file_3D_save + ".gif")
if show:
plt.show()
return fig
else:
plt.close()
return
def _get_var_name(var):
callers_local_vars = inspect.currentframe().f_back.f_locals.items()
for var_name, var_val in callers_local_vars:
if var_val is var:
return var_name
return None
