Merge branch '11-add-python-packaging' into 'dev'

Resolve "camel.py"

See merge request cosmotools/CAMEL!7

work/tools/python/camel/__init__.py

+from .camel import *

work/tools/python/camel.py → work/tools/python/camel/camel.py

@@ -73,7 +73,7 @@ def mergeMC( filename, burnin=0.9, num=None, ext="txt", par=None, nelts=None):
         if nelts < len(chain):
             chain = chain[np.array(np.random.random(nelts)*len(chain),int),:]
 
-    dchain = dict( zip(par,np.transpose(chain)))
+    dchain = dict( list(zip(par,np.transpose(chain))))
 
     return(dchain)
 
@@ -222,7 +222,7 @@ def GelmanRubin( chains, gap=10000, length_min=1000, length_max=None, new=False)
         print( "Not enough samples...")
         exit()
 
-    it = range(length_min,length_max,gap)[1:-1]
+    it = list(range(length_min,length_max,gap))[1:-1]
     R = []
     for isamp in it:
         print( "%d%%" % int(it.index(isamp)*100./len(it)))
@@ -262,7 +262,7 @@ def Geweke( chains, gap=10000, length_max=None):
         print( "Not enough samples...")
         exit()
 
-    it = range(length_min,length_max,gap)[1:]
+    it = list(range(length_min,length_max,gap))[1:]
     T = []
     for isamp in it:
         print( "%d%%" % int(it.index(isamp)*100./len(it)))
@@ -402,7 +402,7 @@ to_cosmomcName = {
     'Aps143x217'           : 'Aps143x217',
     }
 
-from_cosmomcName = dict(zip(to_cosmomcName.values(),to_cosmomcName.keys()))
+from_cosmomcName = dict(list(zip(list(to_cosmomcName.values()),list(to_cosmomcName.keys()))))
 
 
 
@@ -442,7 +442,7 @@ def posterior1d( chains, params, nbin=50, smooth=1,
 
         for c in range(nchain):
             chain = chains[c]
-            if chain.has_key(par):
+            if par in chain:
                 hist1d( chain[par], smooth=smooth, color=colors[c], linestyle=linestyles[c], lw=lw[c], bins=nbin)
 
         ax.tick_params(axis='both', which='major', labelsize=16)
@@ -810,8 +810,8 @@ def plot_correlation( matC, par, **kwargs):
     covmat = np.tril( matC, k=-1)
     covmat[covmat==0] = np.NaN
     plt.imshow( covmat, vmin=vmin, vmax=vmax, **kwargs)
-    plt.yticks( range(len(covmat)), [parname.get(p,p) for p in par])
-    plt.xticks( range(len(covmat)), '')
+    plt.yticks( list(range(len(covmat))), [parname.get(p,p) for p in par])
+    plt.xticks( list(range(len(covmat))), '')
     plt.colorbar()
     for i in range( len(par[:-1])):
         #    text( i, i+0.25, parname.get(par[i+1],par[i+1]),rotation=-90)
@@ -880,7 +880,7 @@ def read_bestfit( dirname):
     newline =  f.readline()
     if  not "nan" in newline and not "inf" in newline and not "Abort" in newline:
         value = np.array( newline.split(), dtype=np.double)
-        bestfit = dict(zip(param, value))
+        bestfit = dict(list(zip(param, value)))
     else :
         bestfit = {'chi2':np.inf}
 
@@ -990,11 +990,11 @@ simple_lik_name = {
 
 def writeExtendedBestFit( dbdir,   bfwrite=False, outpath=""):
     #Extract Bestfit from logfile
-    path, dirs, files = os.walk("%s" % (dbdir)).next()
+    path, dirs, files = next(os.walk("%s" % (dbdir)))
 
     for idir in dirs:
 
-        p,d,f = os.walk("%s/%s" % (dbdir,idir)).next()
+        p,d,f = next(os.walk("%s/%s" % (dbdir,idir)))
 
         # this will find the last 'camelZZ.par' file in folder
         camelparfile=""
@@ -1161,11 +1161,11 @@ def writeExtendedBestFit( dbdir,   bfwrite=False, outpath=""):
 def writeDerivedBestFit( dbdir,   bfwrite=False, outpath=""):
 
     #Extract Bestfit from logfile
-    path, dirs, files = os.walk("%s" % (dbdir)).next()
+    path, dirs, files = next(os.walk("%s" % (dbdir)))
 
     for idir in dirs:
 
-        p,d,f = os.walk("%s/%s" % (dbdir,idir)).next()
+        p,d,f = next(os.walk("%s/%s" % (dbdir,idir)))
 
         # this will find the last 'camelZZ.par' file in folder
         camelparfile=""
@@ -1308,7 +1308,7 @@ def writeDerivedBestFit( dbdir,   bfwrite=False, outpath=""):
                         values += (chval.replace("chi2=","")).replace("\n","")
                         values += " "
                     if not gderived:
-                        print("before os.system"            )
+                        print("before os.system")
                         os.system("$CAMELROOT/Linux-x86_64/writeSpectra %s 1000 toto.fits > tmp.out" %(camelparfile) )
 
                         addin = open("tmp.out","r")
@@ -1364,7 +1364,7 @@ def writeDerivedBestFit( dbdir,   bfwrite=False, outpath=""):
                 bestfitfile = "%s/%s/best_fit%d" %(outpath,idir,count)
 
             print(bestfitfile)
-            print(goodline )
+            print(goodline)
             #            print(values,bestfitfile)
             #            if (not os.path.isfile(bestfitfile))  :
             if goodline:
@@ -1418,7 +1418,7 @@ class prof:
         self._offset = offset
         self._CL = 68
 
-        path, dirs, files = os.walk("%s" % (self.dbdir)).next()
+        path, dirs, files = next(os.walk("%s" % (self.dbdir)))
         if sum([self.parname+"_" in d for d in dirs])==0:
             raise ValueError( "Wrong directory")
 
@@ -1428,7 +1428,7 @@ class prof:
             if not self.parname in idir:
                 continue
 
-            p,d,f = os.walk("%s/%s" % (self.dbdir,idir)).next()
+            p,d,f = next(os.walk("%s/%s" % (self.dbdir,idir)))
 
             if writeBestfit:
                 self._writeBestFit(idir,f)
@@ -1527,7 +1527,7 @@ class prof:
         Get all fit chi2 at a given value from multi-Minimize runs
         """
         import os
-        path, dirs, files = os.walk("%s/%s_%s" % (self.dbdir,self.parname,val)).next()
+        path, dirs, files = next(os.walk("%s/%s_%s" % (self.dbdir,self.parname,val)))
         files = [f for f in files if f.startswith("best")]
         nmin = len(files)
 
@@ -1546,7 +1546,7 @@ class prof:
         Get minimum at a given value from multi-Minimize runs
         """
         import os
-        path, dirs, files = os.walk("%s/%s_%s" % (self.dbdir,self.parname,val)).next()
+        path, dirs, files = next(os.walk("%s/%s_%s" % (self.dbdir,self.parname,val)))
         files = [f for f in files if f.startswith("best")]
         nmin = len(files)
 
@@ -1558,7 +1558,7 @@ class prof:
                 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))
+                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])
@@ -1571,7 +1571,7 @@ class prof:
     def _params( self, val):
         #Returns list of parameters from the fit file for a given value of the parameter
         import os
-        path, dirs, files = os.walk("%s/%s_%s" % (self.dbdir,self.parname,val)).next()
+        path, dirs, files = next(os.walk("%s/%s_%s" % (self.dbdir,self.parname,val)))
         files = [f for f in files if f.startswith("best")]
 
         #read all parameters
@@ -1709,7 +1709,7 @@ class prof:
 
         if CL:
             CL2delta = {68:1,95:3.84,99:6.63}
-            if CL in CL2delta.keys():
+            if CL in list(CL2delta.keys()):
                 delta = CL2delta[CL]
             else:
                 raise ValueError('CL not in the list')