Module for reading and parsing specifications file for FRET data assimilation.
Created by Nirag Kadakia at 9:30 05-18-2018
This work is licensed under the
Creative Commons Attribution-NonCommercial-ShareAlike 4.0
International License.
To view a copy of this license,
visit http://creativecommons.org/licenses/by-nc-sa/4.0/.
"""
import scipy as sp
import os
from local_methods import def_data_dir
from utils import merge_two_dicts
data_dir = def_data_dir()
def read_specs_file(data_flag, data_dir=data_dir):
"""
Function to read a specifications file.
Module to gather information from specifications file about how a
particular run is to be performed for FRET fake data generation
and FRET data assimilation.
Specs file should have format .txt and the format is as listed here:
data_var nT 3
est_var set_param_bounds bounds_Tar_3
est_spec est_type VA
Created by Nirag Kadakia at 21:46 10-26-2017
This work is licensed under the
Creative Commons Attribution-NonCommercial-ShareAlike 4.0
International License.
To view a copy of this license,
visit http://creativecommons.org/licenses/by-nc-sa/4.0/.
"""
import scipy as sp
from local_methods import def_data_dir
from matplotlib import rc
rc('font', **{'family': 'serif', 'serif': ['Computer Modern']})
rc('text', usetex=True)
import matplotlib.pyplot as plt
DATA_DIR = def_data_dir()
def opt_kernel_pred_fig(dt, kernel_length, Tt_PW):
fig = plt.figure()
fig.set_size_inches(6, 6)
plt.subplot(311)
plt.title(r'Mean subtracted stimulus')
plt.xlabel(r'Time (s)')
plt.ylabel(r'$\mu m$')
plt.xlim(Tt_PW[0], Tt_PW[-1])
plt.subplot(312)
plt.title(r'Mean subtracted FRET prediction')
International License.
To view a copy of this license, visit
http://creativecommons.org/licenses/by-nc-sa/4.0/.
"""
import os
import sys
sys.path.append('../src')
from local_methods import def_data_dir
from load_data import load_stim_file, load_meas_file
from save_data import save_meas_plots, save_stim_plots
from single_cell_FRET import single_cell_FRET
print 'Plotting stimuli...'
stim_path = '%s/stim' % def_data_dir()
data_flags = []
for (dirpath, dirnames, filenames) in os.walk(stim_path):
for filename in filenames:
if filename.endswith('.stim'):
data_flags.append(os.path.splitext(filename)[0])
for data_flag in data_flags:
stim_Tt = load_stim_file(data_flag)
scF = single_cell_FRET()
scF.Tt = stim_Tt[:, 0]
scF.stim = stim_Tt[:, 1:]
save_stim_plots(scF, data_flag)
print 'Plotting measurements...'