def save_ROIs(self):
self.sbin = int(self.binSpinBox.value())
# save running parameters as defaults
ops = self.save_ops()
if len(self.save_path) > 0:
savepath = self.save_path
else:
savepath = None
print(savepath)
if len(self.ROIs) > 0:
rois = utils.roi_to_dict(self.ROIs, self.rROI)
else:
rois = None
proc = {
'Ly': self.Ly,
'Lx': self.Lx,
'sy': self.sy,
'sx': self.sx,
'LY': self.LY,
'LX': self.LX,
'sbin': ops['sbin'],
'fullSVD': ops['fullSVD'],
'rois': rois,
'save_mat': ops['save_mat'],
'save_path': ops['save_path'],
'filenames': self.filenames,
'iframes': self.iframes
}
savename = process.save(proc, savepath=savepath)
self.batchlist.append(savename)
basename, filename = os.path.split(savename)
filename, ext = os.path.splitext(filename)
self.batchname[len(self.batchlist) - 1].setText(filename)
self.processbatch.setEnabled(True)
def run(filenames, parent=None, proc=None, savepath=None):
''' uses filenames and processes fullSVD if no roi's specified '''
''' parent is from GUI '''
''' proc can be a saved ROI file from GUI '''
''' savepath is the folder in which to save _proc.npy '''
print('processing videos')
# grab files
Lys = []
Lxs = []
rois=None
if parent is not None:
filenames = parent.filenames
video = parent.video
containers = []
for fs in filenames:
cs = []
for f in fs:
cs.append(av.open(f))
cs[-1].streams.video[0].thread_type = 'AUTO'
containers.append(cs)
cumframes = parent.cumframes
nframes = parent.nframes
iframes = parent.iframes
sbin = parent.sbin
rois = utils.roi_to_dict(parent.ROIs, parent.rROI)
Ly = parent.Ly
Lx = parent.Lx
fullSVD = parent.checkBox.isChecked()
save_mat = parent.save_mat.isChecked()
sy = parent.sy
sx = parent.sx
else:
video=[]
containers = []
nframes = 0
iframes = []
cumframes = [0]
k=0
for fs in filenames:
vs = []
cs = []
for f in fs:
try:
vs.append(pims.Video(f))
except:
vs.append(pims.PyAVReaderIndexed(f))
cs.append(av.open(f))
cs[-1].streams.video[0].thread_type = 'AUTO'
video.append(vs)
containers.append(cs)
iframes.append(len(video[-1][0]))
cumframes.append(cumframes[-1] + len(video[-1][0]))
nframes += len(video[-1][0])
if k==0:
Ly = []
Lx = []
for vs in video[-1]:
fshape = vs.frame_shape
Ly.append(fshape[0])
Lx.append(fshape[1])
k+=1
iframes = np.array(iframes).astype(int)
cumframes = np.array(cumframes).astype(int)
if proc is None:
sbin = 4
fullSVD = True
save_mat = False
rois=None
else:
sbin = proc['sbin']
fullSVD = proc['fullSVD']
save_mat = proc['save_mat']
rois = proc['rois']
sy = proc['sy']
sx = proc['sx']
Lybin, Lxbin, iinds = binned_inds(Ly, Lx, sbin)
LYbin,LXbin,sybin,sxbin = utils.video_placement(Lybin, Lxbin)
nroi = 0
if rois is not None:
for r in rois:
if r['rind']==1:
r['yrange_bin'] = np.arange(np.floor(r['yrange'][0]/sbin),
np.floor(r['yrange'][-1]/sbin)).astype(int)
r['xrange_bin'] = np.arange(np.floor(r['xrange'][0]/sbin),
np.floor(r['xrange'][-1])/sbin).astype(int)
nroi+=1
isRGB = True
#if len(frame_shape) > 2:
# isRGB = True
tic = time.time()
# compute average frame and average motion across videos (binned by sbin)
avgframe, avgmotion = subsampled_mean(video, cumframes, Ly, Lx, sbin)
avgframe_reshape = utils.multivideo_reshape(np.hstack(avgframe)[:,np.newaxis],
LYbin,LXbin,sybin,sxbin,Lybin,Lxbin,iinds)
avgframe_reshape = np.squeeze(avgframe_reshape)
avgmotion_reshape = utils.multivideo_reshape(np.hstack(avgmotion)[:,np.newaxis],
LYbin,LXbin,sybin,sxbin,Lybin,Lxbin,iinds)
avgmotion_reshape = np.squeeze(avgmotion_reshape)
print('computed subsampled mean at %1.2fs'%(time.time() - tic))
ncomps = 500
if fullSVD or nroi>0:
# compute SVD from frames subsampled across videos and return spatial components
U = compute_SVD(video, cumframes, Ly, Lx, avgmotion, ncomps, sbin, rois, fullSVD)
print('computed subsampled SVD at %1.2fs'%(time.time() - tic))
U_reshape = U.copy()
if fullSVD:
U_reshape[0] = utils.multivideo_reshape(U_reshape[0], LYbin,LXbin,sybin,sxbin,Lybin,Lxbin,iinds)
if nroi>0:
k=1
for r in rois:
if r['rind']==1:
ly = r['yrange_bin'].size
lx = r['xrange_bin'].size
U_reshape[k] = np.reshape(U[k].copy(), (ly,lx,U[k].shape[-1]))
k+=1
else:
U = []
U_reshape = []
# project U onto all movie frames
# and compute pupil (if selected)
V, pups, blinks, runs = process_ROIs(containers, cumframes, Ly, Lx, avgmotion, U, sbin, tic, rois, fullSVD)
# smooth pupil and blinks and running
print('smoothing ...')
for p in pups:
if 'area' in p:
p['area_smooth'],_ = pupil.smooth(p['area'].copy())
p['com_smooth'] = p['com'].copy()
p['com_smooth'][:,0],_ = pupil.smooth(p['com_smooth'][:,0].copy())
p['com_smooth'][:,1],_ = pupil.smooth(p['com_smooth'][:,1].copy())
for b in blinks:
b,_ = pupil.smooth(b.copy())
#for r in runs:
# r[:,0],_ = pupil.smooth(r[:,0].copy())
# r[:,1],_ = pupil.smooth(r[:,1].copy())
#V_smooth = []
#for m in V:
# ms,ireplace = pupil.smooth(m[:,0].copy())#, win=50)
# ireplace[np.logical_or(ms>ms.std()*4, ms<ms.std()*-4)] = True
# print(ireplace.sum())
# inds = ireplace.nonzero()[0][:,np.newaxis] + np.arange(-50,51,1,int)[np.newaxis,:]
# inds[inds<0] = 0
# inds[inds>=m.shape[0]] = m.shape[0]-1
# m[ireplace,:] = np.nanmedian(m[inds,:], axis=1)
#V_smooth.append(m)
print('computed projection at %1.2fs'%(time.time() - tic))
proc = {
'filenames': filenames, 'save_path': savepath, 'iframes': iframes, 'Ly': Ly, 'Lx': Lx,
'sbin': sbin, 'fullSVD': fullSVD, 'save_mat': save_mat,
'Lybin': Lybin, 'Lxbin': Lxbin,
'sybin': sybin, 'sxbin': sxbin, 'LYbin': LYbin, 'LXbin': LXbin,
'avgframe': avgframe, 'avgmotion': avgmotion,
'avgframe_reshape': avgframe_reshape, 'avgmotion_reshape': avgmotion_reshape,
'motSVD': V, 'motMask': U, 'motMask_reshape': U_reshape,
'pupil': pups, 'running': runs, 'blink': blinks, 'rois': rois
}
# save processing
savename = save(proc, savepath)
return savename