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R9123/RawDataAnalysis/plot_raw_traces.py
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plot_raw_traces.py
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# -*- coding: utf-8 -*-
""""""""""""""""""""" MODULE IMPORT """""""""""""""""""""
### Import external modules
import numpy as np
import matplotlib.pyplot as plt
import os
import sys
import seaborn as sn
### Import internal modules
sys.path.insert(0, os.path.realpath('../Classes'))
from LoadData import LoadData
#nice plotting style
sn.set_style("whitegrid", { 'xtick.direction': 'out', 'xtick.major.size': 6.0,
'xtick.minor.size': 3.0, 'ytick.color': '.15',
'ytick.direction': 'out', 'ytick.major.size': 6.0,
'ytick.minor.size': 3.0})
""""""""""""""""""""" FUNCTION """""""""""""""""""""
def plot_raw_traces(cell, temperature, division, nb_traces = 10):
##################### LOAD DATA ##################
if cell == 'NIH3T3':
path = "../Data/NIH3T3.ALL.2017-04-04/ALL_TRACES_INFORMATION.p"
else:
path = "../Data/U2OS-2017-03-20/ALL_TRACES_INFORMATION_march_2017.p"
dataClass=LoadData(path, nb_traces, temperature = temperature,
division = division, several_cell_cycles = False)
(ll_area, ll_signal, ll_nan_circadian_factor,
ll_obs_phi, ll_peak, ll_idx_cell_cycle_start,
T_theta, T_phi) = dataClass.load(load_annotation=True)
if division:
#keep only long traces and crop them
to_keep = [i for i, l_signal in enumerate(ll_signal)\
if len(l_signal)>100]
ll_signal = [ll_signal[i][:100] for i in to_keep]
ll_area = [ll_area[i][:100] for i in to_keep]
ll_nan_circadian_factor = \
[ll_nan_circadian_factor[i][:100] for i in to_keep]
ll_obs_phi = [ll_obs_phi[i][:100] for i in to_keep]
ll_peak = [ll_peak[i][:100] for i in to_keep]
ll_idx_cell_cycle_start = [ [j for j in ll_idx_cell_cycle_start[i] \
if j<100] for i in to_keep]
zp = zip(enumerate(ll_signal), ll_nan_circadian_factor, ll_peak,
ll_idx_cell_cycle_start)
for (idx, l_signal), l_nan_circadian_factor, l_peak, l_idx_cc in zp:
tspan = np.linspace(0,len(l_signal)/2, len(l_signal))
l_idx_peak = [idx for idx, i in enumerate(l_peak) if i>0]
l_t_nan_circadian = []
i_temp = None
for idxx, (i1, i2) in enumerate(zip(l_nan_circadian_factor[:-1],
l_nan_circadian_factor[1:] )):
if not i1 and i2:
i_temp = (idxx+1)/2
if i1 and i2:
pass
if i1 and not i2:
if i_temp == None:
print('BUG')
else:
l_t_nan_circadian.append((i_temp, idxx/2))
i_temp = None
plt.subplot(210+ idx%2+1 )
plt.plot(tspan, l_signal, '.', color = 'red')
for p in l_idx_peak:
#plt.axvline(p/2)
pass
for d in l_idx_cc:
plt.axvline(d/2, color = 'black')
for a,b in l_t_nan_circadian:
#plt.axvspan(a, b, color='lightblue', alpha=0.5, lw=0)
pass
if idx%2==1:
plt.tight_layout()
plt.savefig('../Results/RawData/RawTrace_div_'+str(idx)+'_'\
+str(temperature)+"_"+cell+'.pdf')
plt.show()
plt.close()
else:
#keep only long traces and crop them so they all have the same size
#(CAUTION, CODE FOR PEAK NOT CORRECT)
ll_signal = [l_signal[:100] for l_signal in ll_signal \
if len(l_signal)>100]
#ll_peak= [l_peak[:100] for l_signal, l_peak in zip(ll_signal, ll_peak)\
#if len(l_signal)>100]
for (idx, l_signal), l_peak, in zip(enumerate(ll_signal), ll_peak):
tspan = np.linspace(0,len(l_signal)/2, len(l_signal))
l_idx_peak = [idx for idx, i in enumerate(l_peak) if i>0]
plt.subplot(210+ idx%2+1 )
plt.plot(tspan, l_signal, '.', color = 'orange')
for p in l_idx_peak:
#plt.axvline(p/2)
pass
if idx%2==1:
plt.tight_layout()
plt.savefig('../Results/RawData/RawTrace_nodiv_'+str(idx)+'_'\
+str(temperature)+"_"+cell+'.pdf')
plt.show()
plt.close()
""""""""""""" TEST """""""""""""
if __name__ == '__main__':
plot_raw_traces(cell = "NIH3T3", temperature = 37, division = False,
nb_traces = 100)
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