Merge branch 'master' of https://gitlab.in2p3.fr/cosmotools/CAMEL

Conflicts:
	work/tools/python/camel.py

par/examples/hlpPS_tauprior.par

+###############################################################
+#Boltzman Engine
+engine=pico
+
+
+
+###############################################################
+#Cosmological model
+par   omega_b             cosm    0.02224     0.00027   0.017   0.027
+par   omega_cdm           cosm    0.1192      0.0026    0.09    0.15
+par   100*theta_s         cosm    1.0418      0.6E-04   1.03	1.05
+par   tau_reio            cosm    0.07	      0.13E-01  0.01	0.20
+par   log(10^10A_s)       cosm    3.07	      0.025     2.7     3.5
+par   n_s                 cosm    0.96	      0.0070    0.9     1.1
+###############################################################
+
+
+gauss1    tau_reio	0.058	0.012
+
+
+###############################################################
+#LIKELIHOODS
+
+
+#-----------------------------
+#CMB high-l (HILLIPOP)
+Hillipop=HiLLiPOP/DX11dHM_superExt_CO_TT.lik
+par   A_planck     	  nui	  1.		0.001	     0.9 	1.1
+par   c0		  nui     0.		0.001     -0.05   0.05
+par   c1		  nui     0.		0.001     -0.05   0.05
+fix   c2		  nui     0.		0.001     -0.05   0.05
+par   c3		  nui     0.		0.001     -0.05   0.05
+par   c4		  nui     0.004		0.001     -0.05   0.05
+par   c5		  nui     0.004		0.001     -0.05   0.05
+par   Aradio		  nui     1.		1E-01     0.0     2
+par   Adusty		  nui     1.		1E-01     0.0     2
+par   Asz                 nui     1.		0.1       0.0     10
+par   Acib                nui     1.		0.1       0.0     10
+par   AdustTT		  nui	  1.	        0.1	  0.0     2
+fix   AdustPP		  nui	  0.		0.1	  0.0     2
+fix   AdustTP		  nui	  0.		0.1	  0.0     2
+par   Aksz                nui     0.		1.0	  0.0     10
+par   Aszxcib             nui     0.		1.0	  0.0     10
+
+#PRIORS
+gauss1    AdustTT	1	0.2
+gauss1    Asz		1	0.2
+gauss1    Acib		1	0.2
+gauss1    Aradio	1	0.2
+gauss1    Adusty	1	0.2
+gauss1    A_planck	1	0.0025
+gauss1    c0		0	2e-3
+gauss1	  c1		0	2e-3
+gauss1	  c3		0	2e-3 
+gauss1	  c4		0.002	2e-3 
+gauss1	  c5		0.002	2e-3 
+#-----------------------------
+
+
+###############################################################
+
+
+
+
+###############################################################
+#pico neutrino setup
+# 1 degenerated massive neutrino
+fix          m_ncdm          cosm       0.06 
+fix          N_nu            cosm       3.046
+fix          YHe             cosm       0.248
+fix          Alens           cosm       1
+###############################################################
+
+
+###############################################################
+#fitter
+nitermax=50000
+set_stra=2
+set_tol=0.00001
+
+#output options
+remove_cosmo_limits=false
+doHesse=true
+###############################################################

work/tools/python/camel.py

@@ -321,6 +321,7 @@ parname = {
     'AdustTT'              : '$A_\mathrm{dust}^\mathrm{TT}$',
     'AdustTP'              : '$A_\mathrm{dust}^\mathrm{TE}$',
     'AdustPP'              : '$A_\mathrm{dust}^\mathrm{EE}$',
+    'SPT_ADust'            : '$A^\mathrm{dust}_\mathrm{SPT}$',
     'SPT_high_95_cal'      : '$c^\mathrm{SPT\ high}_{95}$',
     'SPT_high_150_cal'     : '$c^\mathrm{SPT\ high}_{150}$',
     'SPT_high_220_cal'     : '$c^\mathrm{SPT\ high}_{220}$',
@@ -980,8 +981,6 @@ def writeExtendedBestFit( dbdir,   bfwrite=False, outpath=""):
                 #print param_line
 
                 sf.close()
-                    
-
         
 
         for s in  [f1 for f1 in f if ".o" in f1]:
@@ -1316,27 +1315,29 @@ class prof:
         for idir in dirs:
             if not self.parname in idir:
                 continue
-            
+
             p,d,f = os.walk("%s/%s" % (self.dbdir,idir)).next()
 
             if writeBestfit:
                 self._writeBestFit(idir,f)
-#                for f2 in [f1 for f1 in f if ".o" in f1]:
-
+            #                for f2 in [f1 for f1 in f if ".o" in f1]:
+        
             #check there are more than nestimate bestfit in directory idir
             if sum([s.startswith("best_fit") for s in f]) >= nestimate:
                 # gets the value indicated in the subfolder's name
+                
                 keep=True
                 for ii in remove:
                     if ii == idir.replace(self.parname+'_',''):
                         keep=False
-
+                
                 if keep:
                     self._s.append( idir.replace(self.parname+'_',''))
                 # same thing but casts in double
                     self._v.append( np.double(idir.replace(self.parname+'_',''))+self._offset)
 
         if len(self._s) <= 2:
+            
             raise ValueError( "not enough profiled-value available (need at least two)")
 
         sortidx = np.argsort(self._v)
@@ -1438,13 +1439,16 @@ class prof:
         for f in np.sort(files):
             #read all parameters
             fname= "%s/%s_%s/%s" % (self.dbdir,self.parname,val,f)
+            if verbose:
+                print fname
+                print os.stat(fname).st_size
             if os.stat(fname).st_size !=0:
 		bftmp = read_bestfit( "%s/%s_%s/%s" % (self.dbdir,self.parname,val,f))
-            if verbose:
-                prtval = 'chi2' if verbose == True else verbose
-                print( f, bftmp[prtval])
-            if bftmp['chi2'] < bf['chi2']:
-                bf = bftmp
+                if verbose:
+                    prtval = 'chi2' if verbose == True else verbose
+                    print( f, bftmp[prtval])
+                if bftmp['chi2'] < bf['chi2']:
+                    bf = bftmp
 
         return( bf)
 
@@ -1628,6 +1632,7 @@ class prof:
             all plot arguments
         """
         ax = plt.gca()
+<<<<<<< HEAD
         from matplotlib import __version__
         if __version__ >= '1.5':
             colordef = next(ax._get_lines.prop_cycler)
@@ -1635,6 +1640,10 @@ class prof:
             colordef = next(ax._get_lines.color_cycle)
             
         color     = kwargs.pop( "color", colordef)
+=======
+        
+        color     = kwargs.pop( "color", next(ax._get_lines.color_cycle))
+>>>>>>> 6b166d29334f58c14911e7fc538209c24df7cc54
         linestyle = kwargs.pop( "linestyle",  '-')
         label     = kwargs.pop( "label",     None)
         marker    = kwargs.pop( "marker",    'o')