- Author:
- Weiwei Ai <wai484@aucklanduni.ac.nz>
- Date:
- 2024-05-27 16:40:34+12:00
- Desc:
- Fixed typos
- Permanent Source URI:
- http://models.cellml.org/workspace/b65/rawfile/54428a600e2c560005a2d9d0a5608082f90a7c0c/src/mergeData_SGLT1.py
import os
import pandas as pd
current_dir = os.path.dirname(os.path.abspath(__file__))
csv_files = []
model_name = 'SGLT1_BG'
path_=os.path.join(current_dir, '../Electrogenic cotransporter/CellMLV2/sim_results/')
model_ids_=['_fig10_50mV','_fig10_150mV','_fig10_50mV_sugar','_fig10_150mV_sugar']
for model_id in model_ids_:
sed_model_id = model_name+model_id
csv_file=path_+'report_task_'+f'{sed_model_id}'+'.csv'
new_csv_file = path_+'report_task_'+f'{sed_model_id}'+'_post.csv'
if os.path.exists(new_csv_file):
os.remove(new_csv_file)
# remove the lines from line 2 to line 12001 and write to a new file
with open(csv_file, 'r') as f:
lines = f.readlines()
with open(new_csv_file, 'w') as f:
f.writelines(lines[:1])
f.writelines(lines[1201:])
# read the new file to pd dataframe and add a new column 'tms', which is the time in ms; and save to a new file
# tms = (t-1.2)*1000
df = pd.read_csv(new_csv_file)
df['tms'] = (df['t']-1.2)*1000
df.to_csv(new_csv_file, index=False)
csv_files = []
csv_files_sugar = []
model_name = 'SGLT1_BG'
model_ids_=['_fig5_m150mV','_fig5_m120mV','_fig5_m80mV','_fig5_m50mV','_fig5_m30mV','_fig5_0mV','_fig5_40mV','_fig5_50mV','_fig5_80mV',
'_fig5_m150mV_sugar','_fig5_m120mV_sugar','_fig5_m80mV_sugar','_fig5_m50mV_sugar','_fig5_m30mV_sugar','_fig5_0mV_sugar',
'_fig5_40mV_sugar','_fig5_50mV_sugar','_fig5_80mV_sugar',]
new_csv_file=path_+'fig5_BG_ss.csv'
new_csv_file_sugar=path_+'fig5_BG_ss_sugar.csv'
if os.path.exists(new_csv_file):
os.remove(new_csv_file)
if os.path.exists(new_csv_file_sugar):
os.remove(new_csv_file_sugar)
for model_id in model_ids_:
sed_model_id = model_name+model_id
csv_file=path_+'report_task_'+f'{sed_model_id}'+'.csv'
if 'sugar' not in model_id:
csv_files.append(csv_file)
else:
csv_files_sugar.append(csv_file)
# keep the first line of the first file, and remove the first line of the second and subsequent files
# add line 29845 of all files to the new file
line_num = 2984
for csv_file in csv_files:
with open(csv_file, 'r') as f:
lines = f.readlines()
with open(new_csv_file, 'a') as file:
if csv_file == csv_files[0]:
file.writelines(lines[:1])
file.writelines(lines[line_num:line_num+1])
else:
file.writelines(lines[line_num:line_num+1])
for csv_file in csv_files_sugar:
with open(csv_file, 'r') as f:
lines = f.readlines()
with open(new_csv_file_sugar, 'a') as file:
if csv_file == csv_files_sugar[0]:
file.writelines(lines[:1])
file.writelines(lines[line_num:line_num+1])
else:
file.writelines(lines[line_num:line_num+1])
# read the new file to pd dataframe;
# Ii in new_csv_file_sugar is A and in new_csv_file is B, the new value is A-B
# Save the new value to a new file;
# Save the V_E value to the new file as well
# Create a new pd dataframe with the new values
df_new = pd.DataFrame()
df = pd.read_csv(new_csv_file)
df_sugar = pd.read_csv(new_csv_file_sugar)
df_new['Ii'] = df_sugar['Ii']-df['Ii']
df_new['V_E'] = df['V_E']
df_new.to_csv(path_+'fig5_BG.csv', index=False)
# fast binding version
csv_files = []
csv_files_sugar = []
model_name = 'SGLT1_BG_step_ss_fast'
model_ids_=['m150mV','m120mV','m80mV','m50mV','m30mV','0mV','40mV','50mV','80mV',
'sugar_m150mV','sugar_m120mV','sugar_m80mV','sugar_m50mV','sugar_m30mV','sugar_0mV','sugar_40mV','sugar_50mV','sugar_80mV',]
new_csv_file=path_+'fig5_BG_ss_fast.csv'
new_csv_file_sugar=path_+'fig5_BG_ss_sugar_fast.csv'
if os.path.exists(new_csv_file):
os.remove(new_csv_file)
if os.path.exists(new_csv_file_sugar):
os.remove(new_csv_file_sugar)
for model_id in model_ids_:
sed_model_id = model_name+'_Data_'+model_id
csv_file=path_+f'{sed_model_id}'+'.csv'
if 'sugar' not in model_id:
csv_files.append(csv_file)
else:
csv_files_sugar.append(csv_file)
# keep the first line of the first file, and remove the first line of the second and subsequent files
# add line 12752 of all files to the new file
line_num = 298450
for csv_file in csv_files:
with open(csv_file, 'r') as f:
lines = f.readlines()
with open(new_csv_file, 'a') as file:
if csv_file == csv_files[0]:
file.writelines(lines[:1])
file.writelines(lines[line_num:line_num+1])
else:
file.writelines(lines[line_num:line_num+1])
for csv_file in csv_files_sugar:
with open(csv_file, 'r') as f:
lines = f.readlines()
with open(new_csv_file_sugar, 'a') as file:
if csv_file == csv_files_sugar[0]:
file.writelines(lines[:1])
file.writelines(lines[line_num:line_num+1])
else:
file.writelines(lines[line_num:line_num+1])
df_new = pd.DataFrame()
df = pd.read_csv(new_csv_file)
df_sugar = pd.read_csv(new_csv_file_sugar)
df_new['Ii'] = df_sugar['SGLT1_BG | Ii (fA)']*-1e-6-df['SGLT1_BG | Ii (fA)']*-1e-6
df_new['V_E'] = df['SGLT1_BG | V0_Vm (volt)']*1e3
df_new.to_csv(path_+'fig5_BG_fast.csv', index=False)
model_name='SGLT1_ss'
model_ids_=['_fig5','_fig5_sugar']
sed_model_id = model_name+model_ids_[0]
ss_csv_file=path_+'report_task_'+f'{sed_model_id}'+'.csv'
ss_csv_file_sugar=path_+'report_task_'+f'{model_name+model_ids_[1]}'+'.csv'
df_ss = pd.read_csv(ss_csv_file)
df_ss_sugar = pd.read_csv(ss_csv_file_sugar)
df_ss_new = pd.DataFrame()
df_ss_new['Ii'] = df_ss_sugar['Ii']-df_ss['Ii']
df_ss_new['Ii_1'] = df_ss_sugar['Ii_1']-df_ss['Ii_1']
df_ss_new['V0_Vm'] = df_ss['V0_Vm']
df_ss_new.to_csv(path_+'fig5_ss.csv', index=False)
model_name='SGLT1_ss_fast'
model_ids_=['_fig5','_fig5_sugar']
sed_model_id = model_name+model_ids_[0]
ss_csv_file=path_+'report_task_'+f'{sed_model_id}'+'.csv'
ss_csv_file_sugar=path_+'report_task_'+f'{model_name+model_ids_[1]}'+'.csv'
df_ss = pd.read_csv(ss_csv_file)
df_ss_sugar = pd.read_csv(ss_csv_file_sugar)
df_ss_new = pd.DataFrame()
df_ss_new['Ii'] = df_ss_sugar['Ii']-df_ss['Ii']
df_ss_new['Ii_1'] = df_ss_sugar['Ii_1']-df_ss['Ii_1']
df_ss_new['V0_Vm'] = df_ss['V0_Vm']
df_ss_new.to_csv(path_+'fig5_ss_fast.csv', index=False)
