def main():
#what size images are we working with??
width = 256
height = width
frame_ref=400
f_rate=30.
f_low=[.1,.3]
f_high=[1.,3.]
#define the base dirs for the data and analysis
#note that these should become network locations
base_dir_data='/media/cornelis/DataCDH/Raw-data/Test Data'
base_dir_analysis='/media/cornelis/DataCDH/data/Test Data Output'
to_analyze=jf.check_dirs(base_dir_data,base_dir_analysis)
print(to_analyze)
#start a loop on the folders to analyze and do some things.
#we need to make a local copy for speed of loading and saving
base_dir_tmp='/home/cornelis/PycharmProjects/BrainImageAnalyzer/data'
for f in to_analyze:
#Check if the tmp dir exists or not, copy over the dirs in the date folder
if os.path.isdir(base_dir_tmp):
print('tmp found, deleting')
shutil.rmtree(base_dir_tmp)
shutil.copytree(base_dir_data+f,base_dir_tmp)
else:
shutil.copytree(base_dir_data+f,base_dir_tmp)
print('tmp not found, just copying')
#figure out which cages are present
#print('These are the cages '+str(jf.check_cages(base_dir_tmp))+' in'+f)
the_cages=jf.check_cages(base_dir_tmp)
#continue doing stuff
#step one is to read in all the raw data and save all the green videos
if len(the_cages)>0:
for c in the_cages:
#setup the dir for reading the raw data
data_dir=base_dir_tmp+str(c)+'/Videos/'
#which mice are in the cage?
the_mice=jf.check_mice(data_dir)
#print(data_dir)
os.chdir(data_dir)
raw_list=glob.glob('*.raw')
green_dir=base_dir_tmp+c+'/Green/'
os.makedirs(green_dir)
for rf in raw_list:
frames=fj.get_frames(data_dir+rf,width,height)
out_green_fn=rf[:-4]+'.g'
fj.save_to_file(green_dir,out_green_fn,frames,np.uint8)
print('waiting...')
#copy the resulting folder to the analysis location
green_dir_to_copy=base_dir_analysis+f+'/'+c
#print(green_dir_to_copy)
if os.path.isdir(green_dir_to_copy+'/Green/'):
shutil.rmtree(green_dir_to_copy+'/Green/')
shutil.copytree(green_dir,green_dir_to_copy+'/Green/')
else:
shutil.copytree(green_dir,green_dir_to_copy+'/Green/')
#Do alignments!!
print "Doing alignments..."
aligned_dir=base_dir_tmp+c+'/Aligned/'
os.makedirs(aligned_dir)
for m in the_mice:
lof, lofilenames=dj.get_file_list(green_dir, m)
print(lof)
lp=dj.get_distance_var(lof,width,height,frame_ref)
for i in range(len(lp)):
print('Working on this file: ')+str(lof[i])
#tmp_lof=[]
#tmp_lof.append(lof[i])
#print('creating 1 element list')
#print(type(tmp_lof))
frames=dj.get_green_frames(str(lof[i]),width,height)
frames=dj.shift_frames(frames,lp[i])
#save it!
out_aligned_fn=str(lofilenames[i])
out_aligned_fn=out_aligned_fn[:-4]+'_aligned.g'
fj.save_to_file(aligned_dir,out_aligned_fn,frames,np.uint8)
#copy the resulting folder to the analysis location
aligned_dir_to_copy=base_dir_analysis+f+'/'+c
if os.path.isdir(aligned_dir_to_copy+'/Aligned/'):
shutil.rmtree(aligned_dir_to_copy+'/Aligned/')
shutil.copytree(aligned_dir,aligned_dir_to_copy+'/Aligned/')
else:
shutil.copytree(aligned_dir,aligned_dir_to_copy+'/Aligned/')
#Do temporal filters, apply and calculate dff
#each filter band
for i in range(len(f_low)):
#set up a folder for this band
band_dir=base_dir_tmp+c+'/DFF_Freq_Band_'+str(f_low[i])+'-'+str(f_high[i])+'Hz/'
#and for GSR version
gsrband_dir=base_dir_tmp+c+'/GSR_DFF_Freq_Band_'+str(f_low[i])+'-'+str(f_high[i])+'Hz/'
os.makedirs(band_dir)
os.makedirs(gsrband_dir)
#go to the aligned tmp dir
os.chdir(aligned_dir)
aligned_list=glob.glob('*.g')
for af in aligned_list:
frames=dj.get_green_frames(aligned_dir+af,width,height)
avg_frames=fj.calculate_avg(frames)
frames=fj.cheby_filter(frames, f_low[i], f_high[i], f_rate)
frames+=avg_frames
frames=fj.calculate_df_f0(frames)
#save this
out_dff_fn=af[:-4]+'_DFF_'+str(f_low[i])+'-'+str(f_high[i])+'Hz.raw'
fj.save_to_file(band_dir,out_dff_fn,frames,np.float32)
#do gsr
frames=fj.gsr(frames,width,height)
#save this
out_gsr_fn=af[:-4]+'_GSR_DFF_'+str(f_low[i])+'-'+str(f_high[i])+'Hz.raw'
fj.save_to_file(gsrband_dir,out_gsr_fn,frames,np.float32)
#copy the resulting folder to the analysis location
dff_dir_to_copy=base_dir_analysis+f+'/'+c
if os.path.isdir(dff_dir_to_copy+'/DFF_Freq_Band_'+str(f_low[i])+'-'+str(f_high[i])+'Hz/'):
shutil.rmtree(dff_dir_to_copy+'/DFF_Freq_Band_'+str(f_low[i])+'-'+str(f_high[i])+'Hz/')
shutil.copytree(band_dir,dff_dir_to_copy+'/DFF_Freq_Band_'+str(f_low[i])+'-'+str(f_high[i])+'Hz/')
else:
shutil.copytree(band_dir,dff_dir_to_copy+'/DFF_Freq_Band_'+str(f_low[i])+'-'+str(f_high[i])+'Hz/')
gsr_dir_to_copy=base_dir_analysis+f+'/'+c
if os.path.isdir(gsr_dir_to_copy+'/GSR_DFF_Freq_Band_'+str(f_low[i])+'-'+str(f_high[i])+'Hz/'):
shutil.rmtree(gsr_dir_to_copy+'/GSR_DFF_Freq_Band_'+str(f_low[i])+'-'+str(f_high[i])+'Hz/')
shutil.copytree(gsrband_dir,gsr_dir_to_copy+'/GSR_DFF_Freq_Band_'+str(f_low[i])+'-'+str(f_high[i])+'Hz/')
else:
shutil.copytree(gsrband_dir,gsr_dir_to_copy+'/GSR_DFF_Freq_Band_'+str(f_low[i])+'-'+str(f_high[i])+'Hz/')
else:
print('No cages present, sry :(')
#at end of loop make sure to clean up tmp folder
shutil.rmtree(base_dir_tmp)
def getImage(self,params):
import pandas as pd
print("getImage entered")
choose_map = params['choose_map']
preprocessed_frames_dict = {}
if choose_map == 'spc_map':
# Retrieve list of all x,y values for what was ticked
tups=[(k,v) for (k,v) in params.items() if k[2:] in params['regions_check']]
coords={}
for x_tup in tups:
for y_tup in tups:
# print(str(x_tup) + " and " + str(y_tup) + "?")
if x_tup[0][0] == 'x' and y_tup[0][0] == 'y' and x_tup[0][2:] == y_tup[0][2:]:
# print(str(x_tup) + " and " + str(y_tup))
coords[x_tup[0][2:]] = (x_tup[1],y_tup[1])
# 5,6,3,2,1,4
images = {}
for coord in coords.items():
if coord[1][0]!='' and coord[1][1]!='':
print("Entered the loop")
region = coord[0]
x = float(coord[1][0])
y = float(coord[1][1])
f_low = float(params['f_low'])
f_high = float(params['f_high'])
frame_ref = float(params['frame_ref'])
raw_file_folder = params['raw_file_folder']
raw_filename_to_align = params['raw_file_to_align']
if 'preprocessed_frames' not in globals():
# The first file added to lof is raw_file_to_align
lof=[]
for root, dirs, files in os.walk(raw_file_folder):
for file in files:
if(raw_filename_to_align.lower() in file.title().lower()):
lof.append((os.path.join(root, file)))
for root, dirs, files in os.walk(raw_file_folder):
for file in files:
if ((file.endswith(".raw") or file.endswith(".g")) and (os.path.join(root, file)) not in lof):
lof.append((os.path.join(root, file)))
# Uncomment to check result immdediately after import
# frames=dj.get_green_frames(str(lof[1]),width,height)
# return(frames[0])
# CorrelationMapDisplayer = fj.CorrelationMapDisplayer(frames)
# image = CorrelationMapDisplayer.get_correlation_map(x, y, frames)
#return(frames[0])
#print("Well F**k")
# First element in aligned_frames_list is all frames aligned to user selected raw
if len(lof) > 1:
print("Doing alignments...")
aligned_frames_list = []
lp=dj.get_distance_var(lof,width,height,frame_ref)
if 'all_aligns' in params['all_alignments_check']:
for i in range(len(lp)):
print('Working on this file: ')+str(lof[i])
frames=fj.get_frames(str(lof[i]),width,height)
frames_aligned=dj.shift_frames(frames,lp[i])
aligned_frames_list.append(frames_aligned)
else:
print('Working on this file: ')+str(lof[0])
frames=dj.get_frames(str(lof[0]),width,height)
frames_aligned=dj.shift_frames(frames,lp[0])
aligned_frames_list.append(frames_aligned)
else:
aligned_frames_list=[dj.get_frames(str(lof[0]),width,height)]
frames = aligned_frames_list[0]
# Uncomment to check result immdediately after alignment
#print('MADE IT')
#return(aligned_frames_list[0][0])
# CorrelationMapDisplayer = fj.CorrelationMapDisplayer(aligned_frames_list[0])
# image = CorrelationMapDisplayer.get_correlation_map(x, y, aligned_frames_list[0])
# return(image)
#print("Well F**k")
# Do temporal filters, apply and calculate dff
# each filter band
# Again, the first element in preprocessed_frames_list is cheby filter applied to all frames aligned to user selected
# raw and then df/f0 computed and then gsr applied if option was selected
preprocessed_frames_list = []
for f in aligned_frames_list:
avg_frames=fj.calculate_avg(frames)
frames=fj.cheby_filter(frames, f_low, f_high, frame_rate)
#return(np.gradient(frames[0]))[0]
frames+=avg_frames
frames=fj.calculate_df_f0(frames)
preprocessed_frames_list.append(frames)
#do gsr
# if 'gsr' in params['gsr_check']:
# frames=fj.gsr(frames,width,height)
# preprocessed_frames_list.append(frames)
# else:
# preprocessed_frames_list.append(frames)
preprocessed_frames = preprocessed_frames_list[0]
global preprocessed_frames
#do gsr
if 'gsr' in params['gsr_check']:
#gsr_memory = True
#global gsr_memory
print('gsr commence')
preprocessed_frames=fj.gsr(preprocessed_frames,width,height)
#pickle.dump( favorite_color, open( "save.p", "wb" ) )
seed_indicator = 0.5
# output selected map
if choose_map == 'spc_map':
print('x = '+str(x))
print('y = '+ str(y))
CorrelationMapDisplayer = fj.CorrelationMapDisplayer(preprocessed_frames)
image = CorrelationMapDisplayer.get_correlation_map(y, x, preprocessed_frames)
preprocessed_frames_dict[region] = preprocessed_frames
# Make pixels around the seed equal to the maximum value 1 for the red dot to show
image[y,x]=seed_indicator
image[y+1,x]=seed_indicator
image[y,x+1]=seed_indicator
image[y+1,x+1]=seed_indicator
image[y-1,x]=seed_indicator
image[y,x-1]=seed_indicator
image[y-1,x-1]=seed_indicator
image[y-1,x+1]=seed_indicator
image[y+1,x-1]=seed_indicator
images[region] = image
else:
image = fj.standard_deviation(preprocessed_frames)
# Make pixels around the seed equal to the maximum value 1 for the red dot to show
image[y,x]=seed_indicator
image[y+1,x]=seed_indicator
image[y,x+1]=seed_indicator
image[y+1,x+1]=seed_indicator
image[y-1,x]=seed_indicator
image[y,x-1]=seed_indicator
image[y-1,x-1]=seed_indicator
image[y-1,x+1]=seed_indicator
image[y+1,x-1]=seed_indicator
images[region] = image
# You have a dictionary of all the images. Concatenate them vertically in a logical order
global preprocessed_frames_dict
images_list = []
for region in params['regions_check']:
for image_and_key in images.items():
if image_and_key[0] == region:
print(image_and_key[0])
images_list = images_list + [image_and_key[1]]
combined_image = np.vstack(images_list)
return combined_image