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-rw-r--r--plot_llh/calc_fr_MCMC.py76
1 files changed, 0 insertions, 76 deletions
diff --git a/plot_llh/calc_fr_MCMC.py b/plot_llh/calc_fr_MCMC.py
deleted file mode 100644
index 1bf016a..0000000
--- a/plot_llh/calc_fr_MCMC.py
+++ /dev/null
@@ -1,76 +0,0 @@
-#! /usr/bin/env python
-from __future__ import absolute_import, division
-
-import sys
-sys.path.extend(['.', '..'])
-
-import numpy as np
-import tqdm
-
-from utils import fr as fr_utils
-from utils import misc as misc_utils
-from utils.enums import MixingScenario
-
-binning = np.logspace(np.log10(6e4), np.log10(1e7), 21)
-dimension = 6
-source = [0, 1, 0]
-scenario = MixingScenario.T13
-
-def get_fr(theta, source, binning, dimension, scenario):
- sm_mixings = theta[:6]
- nuisance = theta[6:11]
- scale = np.power(10., theta[-1])
-
- index = -nuisance[-1]
-
- bin_centers = np.sqrt(binning[:-1]*binning[1:])
- bin_width = np.abs(np.diff(binning))
-
- # TODO(shivesh): test with astroNorm
- source_flux = np.array(
- [fr * np.power(bin_centers, index) for fr in source]
- ).T
-
- mass_eigenvalues = sm_mixings[-2:]
- sm_u = fr_utils.angles_to_u(sm_mixings[:-2])
-
- mf_perbin = []
- for i_sf, sf_perbin in enumerate(source_flux):
- u = fr_utils.params_to_BSMu(
- theta = [],
- dim = dimension,
- energy = bin_centers[i_sf],
- mass_eigenvalues = mass_eigenvalues,
- sm_u = sm_u,
- no_bsm = False,
- fix_mixing = scenario,
- fix_mixing_almost = False,
- fix_scale = True,
- scale = scale
- )
- fr = fr_utils.u_to_fr(sf_perbin, u)
- mf_perbin.append(fr)
- measured_flux = np.array(mf_perbin).T
- intergrated_measured_flux = np.sum(measured_flux * bin_width, axis=1)
- averaged_measured_flux = (1./(binning[-1] - binning[0])) * \
- intergrated_measured_flux
- fr = averaged_measured_flux / np.sum(averaged_measured_flux)
-
- return map(float, fr)
-
-if len(sys.argv)< 2:
- print sys.argv
- print "Usage: calc_fr_MCMC.py input_filepath."
- exit(1)
-
-infile = sys.argv[1]
-outfile = infile[:-4] + '_proc.npy'
-
-d = np.load(infile)
-
-p = []
-for x in tqdm.tqdm(d, total=len(d)):
- p.append(get_fr(x, source, binning, dimension, scenario))
-p = np.array(p)
-
-np.save(outfile, p)