trialwise = np.array(())

ctrialwise = np.array(())

strialwise = np.array(())

dfofall = np.array(())

baselineall = np.array(())

for datafile in datafiles:

frm = sio.loadmat(datafile.replace('.rois','.mat'),squeeze_me=True)['info']['frame'][()][1:]

with h5py.File(datafile,mode='r') as f:

to_add = f['corrected'][:].T

to_add[np.isnan(to_add)] = np.nanmin(to_add)

# baseline = np.percentile(to_add,blcutoff,axis=1)

baseline = sfi.percentile_filter(to_add[:,::ds],blcutoff,(1,int(blspan/ds)))

baseline = np.repeat(baseline,ds,axis=1)

for i in range(baseline.shape[0]):

baseline[i] = sfi.gaussian_filter1d(baseline[i],blspan/2)

# if baseline.shape[1]<to_add.shape[1]:

# baseline = np.hstack((baseline,np.repeat(baseline[:,-1],to_add.shape[1]-baseline.shape[1])))

if baseline.shape[1]>to_add.shape[1]:

baseline = baseline[:,:to_add.shape[1]]

c = np.zeros_like(to_add)

s = np.zeros_like(to_add)

dfof = np.zeros_like(to_add)

for i in range(c.shape[0]):

# dfof = (to_add[i]-baseline[i,np.newaxis])/baseline[i,np.newaxis]

dfof[i] = (to_add[i]-baseline[i,:])/(baseline[i,:])

#try:

c[i],s[i],_,_,_ = deconvolve(dfof[i].astype(np.float64),penalty=1,sn=5e-3)

#except:

# print("in "+datafile+" couldn't do "+str(i))

try:

trialwise = np.concatenate((trialwise,to_add),axis=0)

ctrialwise = np.concatenate((ctrialwise,c),axis=0)

strialwise = np.concatenate((strialwise,s),axis=0)

dfofall = np.concatenate((dfofall,dfof),axis=0)

baselineall = np.concatenate((baselineall,baseline),axis=0)

except:

trialwise = to_add.copy()

ctrialwise = c.copy()

strialwise = s.copy()

dfofall = dfof.copy()

baselineall = baseline.copy()

return trialwise,ctrialwise,strialwise,dfofall,baselineall