reogranise into a python package

1 files changed, 106 insertions, 0 deletions

diff --git a/golemflavor/mn.py b/golemflavor/mn.py
new file mode 100644
index 0000000..e3a4a09
--- /dev/null
+++ b/golemflavor/mn.py
@@ -0,0 +1,106 @@
+# author : S. Mandalia
+#          s.p.mandalia@qmul.ac.uk
+#
+# date   : April 19, 2018
+
+"""
+Useful functions to use MultiNest for the BSM flavour ratio analysis
+"""
+
+from __future__ import absolute_import, division
+
+from functools import partial
+
+import numpy as np
+
+from pymultinest import analyse, run
+
+from utils import llh as llh_utils
+from utils.misc import gen_identifier, make_dir, parse_bool, solve_ratio
+
+
+def CubePrior(cube, ndim, n_params):
+    pass
+
+
+def lnProb(cube, ndim, n_params, mn_paramset, llh_paramset, asimov_paramset,
+           args):
+    if ndim != len(mn_paramset):
+        raise AssertionError(
+            'Length of MultiNest scan paramset is not the same as the input '
+            'params\ncube={0}\nmn_paramset]{1}'.format(cube, mn_paramset)
+        )
+    pranges = mn_paramset.ranges
+    for i in xrange(ndim):
+        mn_paramset[i].value = (pranges[i][1]-pranges[i][0])*cube[i] + pranges[i][0]
+    for pm in mn_paramset.names:
+        llh_paramset[pm].value = mn_paramset[pm].value
+    theta = llh_paramset.values
+    llh = llh_utils.ln_prob(
+        theta=theta,
+        args=args,
+        asimov_paramset=asimov_paramset,
+        llh_paramset=llh_paramset,
+    )
+    return llh
+
+
+def mn_argparse(parser):
+    parser.add_argument(
+        '--mn-live-points', type=int, default=3000,
+        help='Number of live points for MultiNest evaluations'
+    )
+    parser.add_argument(
+        '--mn-tolerance', type=float, default=0.01,
+        help='Tolerance for MultiNest'
+    )
+    parser.add_argument(
+        '--mn-efficiency', type=float, default=0.3,
+        help='Sampling efficiency for MultiNest'
+    )
+    parser.add_argument(
+        '--mn-output', type=str, default='./mnrun/',
+        help='Folder to store MultiNest evaluations'
+    )
+    parser.add_argument(
+        '--run-mn', type=parse_bool, default='True',
+        help='Run MultiNest'
+    )
+
+
+def mn_evidence(mn_paramset, llh_paramset, asimov_paramset, args, prefix='mn'):
+    """Run the MultiNest algorithm to calculate the evidence."""
+    n_params = len(mn_paramset)
+
+    for n in mn_paramset.names:
+        llh_paramset[n].value = mn_paramset[n].value
+
+    lnProbEval = partial(
+        lnProb,
+        mn_paramset     = mn_paramset,
+        llh_paramset    = llh_paramset,
+        asimov_paramset = asimov_paramset,
+        args            = args,
+    )
+
+    if args.run_mn:
+        make_dir(prefix)
+        print 'Running evidence calculation for {0}'.format(prefix)
+        run(
+            LogLikelihood              = lnProbEval,
+            Prior                      = CubePrior,
+            n_dims                     = n_params,
+            n_live_points              = args.mn_live_points,
+            evidence_tolerance         = args.mn_tolerance,
+            sampling_efficiency        = args.mn_efficiency,
+            outputfiles_basename       = prefix,
+            importance_nested_sampling = True,
+            # resume                     = False,
+            resume                     = True,
+            verbose                    = True
+        )
+
+    analyser = analyse.Analyzer(
+        outputfiles_basename=prefix, n_params=n_params
+    )
+    return analyser.get_stats()['global evidence']