def plot_plate_trajectories(featurefilepath,
saveDir=None,
downsample=10,
filter_trajectories=False,
mark_endpoints=False,
del_if_exists=False):
""" Tile plots and merge into a single plot for the
entire 96-well plate, correcting for camera orientation. """
file_dict = get_video_set(featurefilepath)
# define multi-panel figure
columns = 3
rows = 2
x = 25.5
y = 16
plt.ioff() if saveDir else plt.ion()
plt.close('all')
fig, axs = plt.subplots(rows,columns,figsize=[x,y])
x_offset = 1.5 / x # for bottom left image
width = 0.3137 # for all but top left image
width_tl = 0.3725 # for top left image
height = 0.5 # for all images
errlog = []
for channel, (maskedfilepath, featurefilepath) in file_dict.items():
if saveDir:
saveName = maskedfilepath.parent.stem + ('_filtered.png' if filter_trajectories else '.png')
savePath = Path(saveDir) / saveName
if savePath.exists():
if del_if_exists:
os.remove(savePath)
else:
print("Skipping file '%s' (already exists)" % savePath.name)
continue
_loc, rotate = CH2PLATE_dict[channel]
_ri, _ci = _loc
# create bbox for image layout in figure
if (_ri == 0) and (_ci == 0):
# first image (with well names), bbox slightly shifted
bbox = [0, height, width_tl, height]
else:
# other images
bbox = [x_offset + width * _ci, height * (rows - (_ri + 1)), width, height]
# get location of subplot for camera
ax = axs[_loc]
try:
# plot first frame of video + annotate wells
FOVsplitter = FOVMultiWellsSplitter(maskedfilepath)
FOVsplitter.plot_wells(is_rotate180=rotate, ax=ax, line_thickness=10)
# plot worm trajectories
plot_trajectory(featurefilepath,
downsample=downsample,
filter_trajectories=filter_trajectories,
mark_endpoints=mark_endpoints,
rotate=rotate,
img_shape=FOVsplitter.img_shape,
legend=False,
ax=ax)
except Exception as e:
print("WARNING: Could not plot video file: '%s'\n%s" % (maskedfilepath, e))
errlog.append(maskedfilepath)
# set image position in figure
ax.set_position(bbox)
if saveDir:
if savePath.exists():
print("Skipping file '%s' (already exists)" % savePath.name)
else:
Path(saveDir).mkdir(exist_ok=True, parents=True)
fig.savefig(savePath,
bbox_inches='tight',
dpi=300,
pad_inches=0,
transparent=True)
print(errlog) # TODO: Save errlog to file?
return
def plot_plate_trajectories(featurefilepath, saveDir=None, downsample=10):
""" Tile plots and merge into a single plot for the
entire 96-well plate, correcting for camera orientation. """
from tierpsy.analysis.split_fov.FOVMultiWellsSplitter import FOVMultiWellsSplitter
file_dict = get_video_set(featurefilepath)
# define multi-panel figure
columns = 3
rows = 2
h_in = 6
x_off_abs = (3600 - 3036) / 3036 * h_in
x = columns * h_in + x_off_abs
y = rows * h_in
fig, axs = plt.subplots(rows, columns, figsize=[x, y])
x_offset = x_off_abs / x # for bottom left image
width = (1 - x_offset) / columns # for all but top left image
width_tl = width + x_offset # for top left image
height = 1 / rows # for all images
for channel, ch_featfilepath in file_dict.items():
_loc, rotate = CH2PLATE_dict[channel]
_ri, _ci = _loc
# create bbox for image layout in figure
if (_ri == 0) and (_ci == 0):
# first image (with well names), bbox slightly shifted
bbox = [0, height, width_tl, height]
else:
# other images
bbox = [
x_offset + width * _ci, height * (rows - (_ri + 1)), width,
height
]
# get location of subplot for camera
ax = axs[_loc]
# plot first frame of video + annotate wells
fovsplitter = FOVMultiWellsSplitter(ch_featfilepath)
# let's check if the fovsplitter managed to get a frame automatically
if fovsplitter.img is None:
fovsplitter.img = get_frame_from_raw(feat2raw(ch_featfilepath))
fovsplitter.plot_wells(is_rotate180=rotate, ax=ax, line_thickness=10)
# plot worm trajectories
plot_trajectory(ch_featfilepath,
ax=ax,
downsample=downsample,
legend=False,
rotate=rotate,
img_shape=fovsplitter.img_shape)
# set image position in figure
ax.set_position(bbox)
plt.show()
if saveDir:
saveName = Path(featurefilepath).parent.stem + '.png'
savePath = Path(saveDir) / saveName
fig.savefig(savePath,
bbox_inches='tight',
dpi=300,
pad_inches=0,
transparent=True)
return (fig)