log10 freq fix

models/galaxy_model/run_sampler.py

@@ -67,11 +67,10 @@ def log_prior(par):
 
 
 def log_likelihood(par):
-    
     M1 = np.linspace(9,12,25)
     q = np.linspace(0.25,1,10)
     z = np.linspace(0.,1.5,5)
-    f = frequencies
+    f = np.atleast_1d([ np.log10(fi) for fi in frequencies ])
     initpar = dict(Phi0 = par[0], 
                    PhiI = par[1], 
                    M0 = par[2], 
@@ -95,7 +94,8 @@ def log_likelihood(par):
     logL = 0.
     for i in range(numberOfFrequencyBinsToUse):
         logL += KDEs[i].logpdf(model[i])
-    return logL
+    print(model,logL)
+    return logL[0]
 
 
 
@@ -119,6 +119,11 @@ bounds=[(-3.4,-2.4),
         (0.01,0.99),
         (-2.,2.)]
 
+
+
+
+
+
 # read in the data
 numberOfFrequencyBinsToUse = 5
 frequencies, samples = readChains(numberOfFrequencyBinsToUse)
@@ -126,6 +131,11 @@ frequencies, samples = readChains(numberOfFrequencyBinsToUse)
 # make the kdes
 KDEs = makeKDEs(samples, numberOfFrequencyBinsToUse)
 
+
+#parTest = np.array([-2.78,-0.28,11.3,-1.24,-0.04,0.04,0.10,1.27,0.01,0.39,-0.2,-1.91,0.01,8.42,1.03,0.38,0.51,-0.7])
+#log_likelihood(parTest)
+#exit()
+
 # ptmcmc things
 x0 = np.array([-2.8,-0.2,11.25,-1.25,0.,0.025,0.8,0.,0.,1.,0.,-0.5,0.,8.25,1.,0.4,0.5,0.])
 ndim = len(x0)