import numpy as np

import os

import pandas as pd

################################################################
######## Analysis pipeline for concatenated recordings #########
################################################################

path = "/media/andrey/My Passport/GIN/backup_Anesthesia_CA1/calcium imaging transition state/concatenated/8235/20201103_GCaMP6f_8235_isoflurane/suite2p/plane0"


Traces = np.load(path + '/F.npy', allow_pickle=True)
Npil = np.load(path + '/Fneu.npy', allow_pickle=True)
iscell = np.load(path + '/iscell.npy', allow_pickle=True)

print(Traces.shape, type(Traces))
print(Npil.shape, type(Npil))
print(iscell.shape, type(iscell))

#path_excel_rec = str(meta_data['Folder'][recording] + meta_data['Subfolder'][recording] + 'suite2p/plane0')
if not os.path.exists('#8235_iso_minidataset'):
    os.mkdir("./#8235_iso_minidataset")

if not os.path.exists('#8235_iso_minidataset/suite2p'):
    os.mkdir("./#8235_iso_minidataset/suite2p")

if not os.path.exists('#8235_iso_minidataset/suite2p/plane0'):
    os.mkdir("./#8235_iso_minidataset/suite2p/plane0")


np.save('#8235_iso_minidataset/suite2p/plane0/F.npy',Traces[:50,:])
np.save('#8235_iso_minidataset/suite2p/plane0/Fneu.npy',Npil[:50,:])
np.save('#8235_iso_minidataset/suite2p/plane0/iscell.npy',iscell[:50,:])


meta_data = pd.read_excel("../meta_data/meta_recordings_transition_state.xlsx")

meta_data = meta_data[meta_data.Mouse_all == 8235]

meta_data.index = np.arange(meta_data.shape[0])

meta_data["Number"] = meta_data.index

print(np.arange(meta_data.shape[0]))

meta_data.Folder = "/media/andrey/My Passport/GIN/Anesthesia_CA1/data_colab/"

meta_data.Subfolder = "#8235_iso_minidataset/"

meta_data.to_excel("./#8235_iso_minidataset/meta_recordings_8235.xlsx")