sys.path.append(os.path.expanduser('~/git/across-projects'))
from plot_types import cdf
fontsize = 20
#
#def boot_strap(x):
# x.dropna(inplace=True)
# median_values = np.zeros(1000)
# for i in xrange(1000):
# x = x.dropna()
# new_x = np.random.choice(x, len(x), replace=True)
# median_values[i] = np.median(new_x)
# return np.std(median_values)
#
#
R = rates()
#
gc = R.gc[R.gc['growth mode']=='batch']
#gc = R.gc
remove = R.gc['comments'].dropna()
gc = gc.drop(remove.index)
#rcatn = R.rcatn
#y = rcatn.median()
#
#fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12.5,6))
#
fig = plt.figure()
ax = plt.axes()
cm = plt.cm.get_cmap('Blues')
#conds = ['Chemostat u=0.11', 'Chemostat u=0.20', 'Chemostat u=0.31', 'Chemostat u=0.51']
#i = 0
from catalytic_rates import rates
from concentration_dependant_effects import MM_kinetics
from figure_correlation import generate_figure
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
from figure_correlation import generate_figure
from scipy import stats
from uncertainties import ufloat_fromstr
fontsize = 30
R = rates()
#reactions = ['CYTK1','DAPE','DHORTS_reverse','G3PD2_reverse',
# 'GLUDy_reverse','GLUR_reverse','HSST','MDH','PGI',
# 'PRAGSr','PTPATi','SERAT']
index = R.kcat.index & R.kmax.index
reactions = [R.rxns[x] for x in index]
kcat = R.kcat['kcat per active site [s-1]'][index]
kmax = R.kmax['kmax per active site [s-1]'][index]
saturation = pd.DataFrame(index=index, columns=['glc', 'ac', 'glyc'])
backwrdflx = pd.DataFrame(index=index, columns=['glc', 'ac', 'glyc'])
for c in ['glc', 'ac', 'glyc']:
f = pd.DataFrame.from_csv('../res/conc_dependant_effects_on_%s.csv' % c,
sep='\t')
saturation[c] = (f['under saturation'][index])
backwrdflx[c] = (f['backward flux'][index])
s = pd.Series(index=index)