parm_format = '{:.2e}'
# p_o2 and p_test over a range
p_arr = np.empty([0, 2])
for po2 in np.linspace(0.05, 0.12, 5):
for ptest in np.linspace(1E-7, 1E-6, 5):
p_arr = np.append(p_arr, [[po2, ptest]], axis=0)
#When T- is severely oxygen limited
parm_name = 'p_o2-p_test'
parm_name_array = ['p_o2', 'p_test']
post_path = 'Tneg-o2limited_'
cf.timeseries(pre_path=pre_path,
parm_name=parm_name,
parm_array=p_arr,
parm_format=parm_format,
plot_Tpos=False,
post_path=post_path)
df = cf.eq_values(pre_path=pre_path,
parm_name=parm_name,
parm_array=p_arr,
parm_format=parm_format,
parm_name_array=parm_name_array,
post_path=post_path)
df = cf.cell_eq_ratio(df, 'Tneg', 'Tpro')
cf.plot_2parm(df=df,
pre_path=pre_path,
parm_name=parm_name,
post_path=post_path,
pri_parm=parm_name_array[0],
sec_parm=parm_name_array[1],
for ulim in np.arange(llim + 0.1, 1, 0.2):
o2_lim_arr = np.append(o2_lim_arr, [[llim, ulim]], axis=0)
parm_format = '{:.1f}'
# T-
parm_name = 'l_lim_o2Tneg-u_lim_o2Tneg'
parm_name_array = np.array(['l_lim_o2Tneg', 'u_lim_o2Tneg'])
## OG Equation
pre_path = 'EnvEq/singlecelltype/Tneg/'
cf.mkdirs(pre_path=pre_path, parm_name=parm_name)
### celleq=1E4: rho s.t T- at equilibrium is 10^4
cf.timeseries(pre_path=pre_path,
parm_name=parm_name,
parm_array=o2_lim_arr,
parm_format=parm_format,
plot_Tpos=False,
plot_Tpro=False,
plot_test=False)
df = cf.eq_values(pre_path=pre_path,
parm_name=parm_name,
parm_array=o2_lim_arr,
parm_format=parm_format,
parm_name_array=parm_name_array)
df['l_lim_o2Tneg'] = df['l_lim_o2Tneg'].round(1)
df['u_lim_o2Tneg'] = df['u_lim_o2Tneg'].round(1)
cf.heatmap_eqvparm(df,
pre_path=pre_path,
parm_name=parm_name,
parm_name_array=parm_name_array,
plot_Tpos=False,
'timescaled_tauconst-', ### Tp:T+:T- 1:1:1 x 666 (total ~2000) with delta scaled by 10^-2, tau fixed
'timescaled_tauconst-0.8Tp-', ### Tp:T+:T- 8:1:1 x 200 (total 2000) with delta scaled by 10^-2, tau fixed
'nonT_neg-timescaled_tauconst-0.8Tp-', ### Tp:T+:T- 8:1:1 x 200 (total 2000) with delta scaled by 10^-2, tau fixed but therapy only works with T+ and Tp numbers
'cunningham-', ### Tp:T+:T- 1:1:1 x 666 (total ~2000) with doubling times from Cunningham et al for check
'0.8Tp-cunningham-', ### Tp:T+:T- 8:1:1 x 200 (total 2000) with doubling times from Cunningham et al for chec
'nonT_neg-cunningham-', ### Tp:T+:T- 1:1:1 x 666 (total ~2000) with doubling times from Cunningham et al for check but therapy only works with T+ and Tp numbers
'nonT_neg-0.8Tp-cunningham-' ### Tp:T+:T- 8:1:1 x 200 (total 2000) with doubling times from Cunningham et al for check but therapy only works with T+ and Tp numbers
])
###
for scenario in scenarios:
for p_min in p_min_arr:
post_path = scenario + 'p={:.1e}-'.format(p_min)
cf.timeseries(pre_path=pre_path,
parm_name=parm_name,
parm_array=parms_array,
parm_format=parm_format,
post_path=post_path,
plot_tot=True)
df = cf.eq_values(pre_path=pre_path,
parm_name=parm_name,
parm_array=parms_array,
parm_format=parm_format,
post_path=post_path,
ttp=True,
limit=9000)
## High o2 efficiency, High test efficiency
parm_name = 'o2-HE_test-HE'
cf.mkdirs(pre_path=pre_path, parm_name=parm_name)
scenarios = np.array([
'', ### Tp:T+:T- 1:1:1 x 666 (total ~2000)
import common_fn as cf
import seaborn as sns
import os
plt.rcParams["svg.hashsalt"]=0
# O2 efficiency
## Tp:T+:T- 1:1:1 x 666 (total ~2000)
### High test efficiency
pre_path='EnvEq/All3/'
parm_format='{}'
parm_name='o2-efficiency'
cf.mkdirs(pre_path=pre_path,parm_name=parm_name)
cases=pd.read_csv('../input/EnvEq/All3/o2-efficiency/All3_o2-eff_cases.csv')
parms_array='Case'+cases.Case
cf.timeseries(pre_path=pre_path,parm_name=parm_name,parm_array=parms_array,parm_format=parm_format)
df=cf.eq_values(pre_path=pre_path,parm_name=parm_name,parm_array=parms_array,parm_format=parm_format)
## Tp:T+:T- 1:8:1 x 200 (total 2000)
post_path='0.8Tp-'
cf.timeseries(pre_path=pre_path,parm_name=parm_name,parm_array=parms_array,parm_format=parm_format,post_path=post_path)
df=cf.eq_values(pre_path=pre_path,parm_name=parm_name,parm_array=parms_array,parm_format=parm_format,post_path=post_path)
# test efficiency
parm_name='test-efficiency'
cf.mkdirs(pre_path=pre_path,parm_name=parm_name)
## Tp:T+:T- 1:1:1 x 666 (total ~2000)
### Null o2 efficiency
cases=pd.read_csv('../input/EnvEq/All3/test-efficiency/All3_test-eff_cases.csv')