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diff --git a/austin.py b/austin.py
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-#! /usr/bin/env python
-# author : S. Mandalia
-#          s.p.mandalia@qmul.ac.uk
-#
-# date   : February 24, 2019
-
-"""
-HESE BSM Flavour Figure 2
-"""
-
-from __future__ import absolute_import, division
-
-import argparse
-from functools import partial
-
-import numpy as np
-
-from utils import fr as fr_utils
-from utils import misc as misc_utils
-from utils import plot as plot_utils
-from utils.enums import str_enum
-from utils.enums import Likelihood, ParamTag, PriorsCateg
-from utils.param import Param, ParamSet
-
-from matplotlib import pyplot as plt
-
-# from pymultinest import Analyzer
-import json
-
-
-def define_nuisance():
-    """Define the nuisance parameters."""
-    nuisance = []
-    tag = ParamTag.NUISANCE
-    lg_prior = PriorsCateg.LIMITEDGAUSS
-    nuisance.extend([
-        Param(name='convNorm',        value=1.,  seed=[0.5, 2. ], ranges=[0.1, 10.], std=0.4, prior=lg_prior, tag=tag),
-        Param(name='promptNorm',      value=0.,  seed=[0. , 6. ], ranges=[0. , 20.], std=2.4, prior=lg_prior, tag=tag),
-        Param(name='muonNorm',        value=1.,  seed=[0.1, 2. ], ranges=[0. , 10.], std=0.1, tag=tag),
-        Param(name='astroNorm',       value=6.9, seed=[0.,  5. ], ranges=[0. , 20.], std=1.5, tag=tag),
-        Param(name='astroDeltaGamma', value=2.5, seed=[2.4, 3. ], ranges=[-5., 5. ], std=0.1, tag=tag)
-    ])
-    return ParamSet(nuisance)
-
-
-def get_paramsets(args, nuisance_paramset):
-    paramset = []
-    if args.likelihood in [Likelihood.GOLEMFIT, Likelihood.GF_FREQ]:
-        gf_nuisance = [x for x in nuisance_paramset.from_tag(ParamTag.NUISANCE)]
-        paramset.extend(gf_nuisance)
-    tag = ParamTag.BESTFIT
-    paramset.extend([
-        Param(name='astroFlavorAngle1', value=0, ranges=[0., 1.], std=0.2, tag=tag),
-        Param(name='astroFlavorAngle2', value=0, ranges=[-1., 1.], std=0.2, tag=tag),
-    ])
-    paramset = ParamSet(paramset)
-    return paramset
-
-
-def process_args(args):
-    """Process the input args."""
-    if args.likelihood is not Likelihood.GOLEMFIT \
-       and args.likelihood is not Likelihood.GF_FREQ:
-        raise AssertionError(
-            'Likelihood method {0} not supported for this '
-            'script!\nChoose either GOLEMFIT or GF_FREQ'.format(
-                str_enum(args.likelihood)
-            )
-        )
-
-def parse_args(args=None):
-    """Parse command line arguments"""
-    parser = argparse.ArgumentParser(
-        description="HESE BSM Flavour Figure 2",
-        formatter_class=misc_utils.SortingHelpFormatter,
-    )
-    parser.add_argument(
-        '--likelihood', default='golemfit',
-        type=partial(misc_utils.enum_parse, c=Likelihood),
-        choices=Likelihood, help='likelihood contour'
-    )
-    parser.add_argument(
-        '--contour-dir', type=str,
-        help='Path to directory containing MultiNest runs'
-    )
-    parser.add_argument(
-        '--outfile', type=str, default='./untitled',
-        help='Output path'
-    )
-    if args is None: return parser.parse_args()
-    else: return parser.parse_args(args.split())
-
-
-def main():
-    args = parse_args()
-    process_args(args)
-    misc_utils.print_args(args)
-
-    paramset = get_paramsets(args, define_nuisance())
-    n_params = len(paramset)
-    print n_params
-
-    # Data
-    prefix = 'austin'
-    # data_path = '/home/aschneider/programs/GOLEMSPACE/sources/GolemFit/scripts/diffuse/mcmcs/results/dpl_numu_prior_flavor_20190302-162221-a747f528-8aa6-4488-8c80-059572c099fe.json'
-    # data_path = '/home/aschneider/programs/GOLEMSPACE/sources/GolemFit/scripts/diffuse/mcmcs/results/spl_flavor_20190311-170924-5297d736-3c6e-447f-8de7-4a0653a51bb6.json'
-    data_path = '/home/aschneider/programs/GOLEMSPACE/sources/GolemFit/scripts/diffuse/mcmcs/results/spl_flavor_20190420-161513-524f1731-0bcb-49e3-a2ea-ff3c69b4e53c.json'
-    with open(data_path) as f:
-        d_json = json.load(f)
-    names = d_json['func_args']
-    chains = np.array(d_json['chain'])
-    print 'names', names
-    print 'chains.shape', chains.shape
-    flavour_angles = chains[:,4:6]
-    flavour_ratios = np.array(
-        map(fr_utils.angles_to_fr, flavour_angles)
-    )
-
-    # # Load HESE contour.
-    # prefix = 'shivesh'
-    # contour_infile = '/data/user/smandalia/flavour_ratio/data/contour/contour_REAL.npy'
-    # contour_angles = np.load(contour_infile)[:,-2:]
-    # flavour_ratios = np.array(map(fr_utils.angles_to_fr, contour_angles))
-
-    nbins = 25
-    ax_labels = [r'$f_{e}^{\oplus}$', r'$f_{\mu}^{\oplus}$', r'$f_{\tau}^{\oplus}$']
-
-    fig = plt.figure(figsize=(8, 8))
-    ax = fig.add_subplot(111)
-    tax = plot_utils.get_tax(ax, scale=nbins, ax_labels=ax_labels)
-
-    levels = [10, 20, 40, 60, 68, 80, 90, 99]
-    for l in levels:
-        plot_utils.flavour_contour(
-            frs = flavour_ratios,
-            ax = ax,
-            nbins = nbins,
-            coverage = l,
-            linewidth = 2,
-            # color = 'green'
-        )
-
-    ax.legend()
-
-    fig.savefig('contour_{0}.png'.format(prefix), bbox_inches='tight', dpi=150)
-
-    print "DONE!"
-
-
-main.__doc__ = __doc__
-
-
-if __name__ == '__main__':
-    main()