def estimate_OU_par(cell, temperature, W=None, gamma_A=0.03, gamma_B=0.03):
"""
Estimate mean and variance of OU processes given a set of conditions,
according to which a set of traces is filtered.
Parameters
----------
cell : string
Cell type.
temperature : integer
Temperature condition.
W : list
Waveform.
gamma_A : float
Regression parameter for the amplitude.
gamma_b : float
Regression parameter for the background.
Returns
-------
The mean and standard deviations of the amplitude and the background.
"""
######### CORRECTION BECAUSE NOT ENOUGH TRACES AT 34°C AND 40°C #########
print(
'CAUTION : Parameters for None temperature selected since not enough \
traces at 34°C and 40°C')
temperature = None
##################### LOAD DATA ################
if cell == 'NIH3T3':
path = "Data/NIH3T3.ALL.2017-04-04/ALL_TRACES_INFORMATION.p"
dataClass = LoadData(path,
10000000,
temperature=temperature,
division=False)
elif cell == 'U2OS':
path = "Data/U2OS-2017-03-20/ALL_TRACES_INFORMATION_march_2017.p"
dataClass = LoadData(path,
10000000,
temperature=temperature,
division=True)
try:
(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)
except:
dataClass.path = '../' + dataClass.path
(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)
return estimate_OU_par_from_signal(ll_signal, W, gamma_A, gamma_B)
