def after_align(self): #这个用来在对齐后平均。
print('Generationg averaged graphs...')
self.aligned_tif_name = []
global_aligned_tif_name = []
for i in range(len(
self.aligned_frame_folder)): #把每个run里的tif_name存到各自文件夹里
self.aligned_tif_name.append(
pp.tif_name(self.aligned_frame_folder[i]))
global_aligned_tif_name.extend(self.aligned_tif_name[i])
temp_aligned_tif_name = self.save_folder[
i] + r'\\aligned_tif_name.pkl'
pp.save_variable(self.aligned_tif_name[i], temp_aligned_tif_name)
run_average = self.frame_average(self.aligned_tif_name[i])
pp.save_variable(run_average,
self.save_folder[i] + r'\\Run_Average_graph.pkl')
self.save_graph('After_Align_Run' + self.run_lists[i], run_average,
self.save_folder[i])
#接下来保存全局平均，也存在每个文件里
global_average_graph = self.frame_average(global_aligned_tif_name)
for i in range(len(self.save_folder)):
self.save_graph('After_Align_Global', global_average_graph,
self.save_folder[i])
pp.save_variable(
global_average_graph,
self.save_folder[i] + r'\\Global_Average_graph.pkl')
def path_cycle(self): #遍历目录，把来组不同run的数据都
self.run_tif_name = []
self.global_tif_name = [] #这个是全局的tif，把所有的都放到了一起之后的。
self.save_folder = []
self.aligned_frame_folder = []
for i in range(len(self.data_folder)):
self.run_tif_name.append(pp.tif_name(
self.data_folder[i])) #这里是append，注意保留了不同folder的结构
self.global_tif_name.extend(pp.tif_name(
self.data_folder[i])) #这个是extend，放到一起了
print('There are ', len(self.run_tif_name[i]), 'tifs in condition',
self.run_lists[i])
temp_result, temp_frame = self.folder_generation(
self.data_folder[i])
self.save_folder.append(temp_result)
self.aligned_frame_folder.append(temp_frame)
self.pool.join()
print('Calculation Done, Plotting...\n')
self.plot_initialize()
self.pool_set()
self.pool.map(self.plot_spike_train, range(0, self.cell_Num))
self.pool.close()
self.pool.join()
#%%
if __name__ == '__main__':
save_folder = r'E:\ZR\Data_Temp\191026_L69_LM\1-010\results'
start_time = time.time()
print('Spike_Train Calculating...\n')
cell_group = pp.read_variable(save_folder +
r'\\Cell_Groups_Morphology.pkl') #画细胞的来源
aligned_frame_name = pp.tif_name(save_folder + r'\\Aligned_Frames')
graph_after_align = pp.read_variable(
save_folder + r'\Run_Average_graph.pkl') #注意这个是df/f的基准帧
cell_find_type = 'Morphology'
st = Spike_Train(cell_group, aligned_frame_name, graph_after_align,
save_folder, 5, cell_find_type)
st.main()
spike_train = st.spike_train
pp.save_variable(spike_train,
save_folder + r'\spike_train_' + cell_find_type + '.pkl')
print('Calculation Done!\n')
finish_time = time.time()
print('Task Time Cost:' + str(finish_time - start_time) + 's')