add CR values on the plot

3 files changed, 39 insertions, 8 deletions

diff --git a/fr.py b/fr.py
index 918f13e..f6d35de 100755
--- a/fr.py
+++ b/fr.py
@@ -157,7 +157,7 @@ def parse_args():
         help='Spectral index for spectral energy dependance'
     )
     parser.add_argument(
-        '--binning', default=[1e4, 1e7, 10], type=int, nargs=3,
+        '--binning', default=[1e4, 1e7, 10], type=float, nargs=3,
         help='Binning for spectral energy dependance'
     )
     parser.add_argument(
diff --git a/submitter/make_dag.py b/submitter/make_dag.py
index 80bd751..133819b 100644
--- a/submitter/make_dag.py
+++ b/submitter/make_dag.py
@@ -18,15 +18,15 @@ full_scan_mfr = [
 fix_sfr_mfr = [
     (1, 1, 1, 1, 0, 0),
     (1, 1, 1, 0, 1, 0),
-    # (1, 1, 1, 0, 0, 1),
+    (1, 1, 1, 0, 0, 1),
     (1, 1, 1, 1, 2, 0),
-    # (1, 1, 0, 0, 1, 0),
+    (1, 1, 0, 0, 1, 0),
     (1, 1, 0, 1, 2, 0),
-    # (1, 1, 0, 1, 0, 0),
-    # (1, 0, 0, 1, 0, 0),
+    (1, 1, 0, 1, 0, 0),
+    (1, 0, 0, 1, 0, 0),
     (0, 1, 0, 0, 1, 0),
-    # (1, 2, 0, 0, 1, 0),
-    # (1, 2, 0, 1, 2, 0)
+    (1, 2, 0, 0, 1, 0),
+    (1, 2, 0, 1, 2, 0)
 ]
 
 # MCMC
@@ -79,7 +79,10 @@ with open(outfile, 'w') as f:
         for en in energy:
             print 'energy {0:.0E}'.format(en)
 
-            outchain_head = '/data/user/smandalia/flavour_ratio/data/{0}/DIM{1}/{2:.0E}'.format(likelihood, dim, en)
+            if energy_dependance == 'mono':
+                outchain_head = '/data/user/smandalia/flavour_ratio/data/{0}/DIM{1}/{2:.0E}'.format(likelihood, dim, en)
+            elif energy_dependance == 'spectral':
+                outchain_head = '/data/user/smandalia/flavour_ratio/data/{0}/DIM{1}/SI_{2}'.format(likelihood, dim, spectral_index)
 
             for sig in sigma_ratio:
                 print 'sigma', sig
diff --git a/utils/plot.py b/utils/plot.py
index af713eb..d395342 100644
--- a/utils/plot.py
+++ b/utils/plot.py
@@ -28,11 +28,20 @@ rc('text', usetex=False)
 rc('font', **{'family':'serif', 'serif':['Computer Modern'], 'size':18})
 
 
+def centers(x):
+    return (x[:-1]+x[1:])*0.5
+
+
 def calc_nbins(x):
     n =  (np.max(x) - np.min(x)) / (2 * len(x)**(-1./3) * (np.percentile(x, 75) - np.percentile(x, 25)))
     return np.floor(n)
 
 
+def calc_bins(x):
+    nbins = calc_nbins(x)
+    return np.linspace(np.min(x), np.max(x)+2, num=nbins+1)
+
+
 def most_likely(arr):
     """Return the densest region given a 1D array of data."""
     binning = calc_bins(arr)
@@ -169,6 +178,25 @@ def chainer_plot(infile, outfile, outformat, args, mcmc_paramset):
             mpl.pyplot.figtext(0.4, 0.7, fig_text, fontsize=4)
         else:
             mpl.pyplot.figtext(0.5, 0.7, fig_text, fontsize=15)
+
+        for i_ax_1, ax_1 in enumerate(g.subplots):
+            for i_ax_2, ax_2 in enumerate(ax_1):
+                if i_ax_1 == i_ax_2:
+                    itv = interval(Tchain[:,i_ax_1], percentile=90.)
+                    for l in itv:
+                        ax_2.axvline(l, color='gray', ls='--')
+                        ax_2.set_title(r'${0:.2f}_{{-{1:.2f}}}^{{+{2:.2f}}}$'.format(
+                            itv[1], itv[0], itv[2]
+                        ), fontsize=10)
+
+        # if not args.fix_mixing:
+        #     sc_index = mcmc_paramset.from_tag(ParamTag.SCALE, index=True)
+        #     itv = interval(Tchain[:,sc_index], percentile=90.)
+        #     mpl.pyplot.figtext(
+        #         0.5, 0.3, 'Scale 90% Interval = [1E{0}, 1E{1}], Center = '
+        #         '1E{2}'.format(itv[0], itv[2], itv[1])
+        #     )
+
         for of in outformat:
             g.export(outfile+'_angles.'+of)