def plot_chain(folder, name_tag):
files = glob.glob(folder + "*__*.txt")
params = glob.glob(folder + "*_.paramnames")
datalist = []
for f in files:
datalist.append(loadMCMC(f, params[0]))
data = astropy.table.vstack(datalist)
data_sim = data[:]
weights_act = data['acceptance'][:]
for col in [
'likelihood', 'acceptance', 'omega_b', 'omega_cdm', '100theta_s',
'tau_reio'
]:
data.remove_column(col)
if 'A_planck' in data.colnames:
data.remove_column('A_planck')
nparr_act = np.array(data.as_array().tolist()[:])
return MCSamples(samples=nparr_act,
names=data.colnames,
labels=data.colnames,
name_tag=name_tag)
import numpy as np
import matplotlib.pyplot as plt
import astropy
from loadMontePython import load as loadMCMC
import glob
basedir = '../chains/nonzero_model/'
#"/home/zequnl/Projects/isocurvature_2017/analysis/plot_triangle/nonzero/"
## F
folder = basedir + 'fF/'
files = glob.glob(folder + "*__*.txt")
params = glob.glob(folder + "*_.paramnames")
datalist = []
for f in files:
datalist.append(loadMCMC(f, params[0]))
data = astropy.table.vstack(datalist)
data_sim = data[:]
weights_act = data['acceptance'][:]
for col in [
'likelihood', 'acceptance', 'omega_b', 'omega_cdm', '100theta_s',
'tau_reio'
]:
data.remove_column(col)
nparr_act = np.array(data.as_array().tolist()[:])
pixie_s4 = MCSamples(samples=nparr_act,
names=data.colnames,
labels=data.colnames,
name_tag='PIXIE low_l + S4')
## G
import matplotlib
from getdist import plots, MCSamples
import getdist
import numpy as np
import matplotlib.pyplot as plt
import astropy
from loadMontePython import load as loadMCMC
import glob
basedir = '../chains/nonzero_model/'
#"/home/zequnl/Projects/isocurvature_2017/analysis/plot_triangle/nonzero/"
burnin = 1000
data1 = loadMCMC('../chains/planckdata/r1.txt', '../chains/planckdata/param')
data2 = loadMCMC('../chains/planckdata/r2.txt', '../chains/planckdata/param')
data = astropy.table.vstack([data1[burnin:], data2[burnin:]])
data_planck = data[:]
weights_planck = data['acceptance'][:]
for col in [
'likelihood', 'acceptance', 'omega_b', 'omega_cdm', '100theta_s',
'tau_reio'
]:
data.remove_column(col)
nparr_planck = np.array(data.as_array().tolist()[:])
planck = MCSamples(samples=nparr_planck,
names=data.colnames,
labels=data.colnames,
name_tag='Planck')