update SimpleModel

Author: igomezv

simplemc/models/SimpleModel.py

@@ -7,20 +7,18 @@
 
 class SimpleModel:
     """
-    This is a generic model
-
-    Parameters
-    ----------
-    parameters : list
-        List of Parameter objects
-    model : str
-        model or function. It should be in terms of x
-        Example: '5*np.cos(x)' or 'x**2-5*x'
+        This is a generic model
 
+        Parameters
+        ----------
+        parameters : list
+            List of Parameter objects
+        function : function
+            model or function. It should be in terms of the parameters
     """
-    def __init__(self, parameters, model):
+    def __init__(self, parameters, function):
         self.parameters = parameters
-        self.model = model
+        self.function = function
         SimpleModel.updateParams(self, [])
 
     # my free params (parameters/priors see ParamDefs.py)
@@ -38,23 +36,14 @@ def printParameters(self, params):
             l.append("{}: {} = +/- {}".format(p.name, p.value, p.error))
         return l
 
+    def updateParams(self, pars):
+        return True
 
     def genericModel(self, x):
-        # values = []
-        # for param in self.parameters:
-        #     values.append(param.value)
-        # return self.function(values, x)
+        values = []
         for param in self.parameters:
-            exec("%s = %f" % (param.name, param.value))
-        try:
-            r = eval(self.model)
-        except:
-            print("Please check your model expression: {}".format(self.model))
-            sys.exit("Your expression should be in terms of x. \\ For example: '5*np.sin(x)' or '5*x**2'")
-        return r
-
-    def updateParams(self, pars):
-        return True
+            values.append(param.value)
+        return self.function(values, x)
 
     def prior_loglike(self):
         return 0
@@ -63,7 +52,8 @@ def prior_loglike(self):
 class SimpleCosmoModel(LCDMCosmology):
     def __init__(self,  extra_params=None, RHSquared=None):
         """
-        This is a simple cosmological model based on LCDMCosmology class.
+        This is a simple cosmological model based on slightly deviations of LCDMCosmology
+        class, RHSquared must to have an analytical form.
 
         Parameters
         ----------

testModel.py

@@ -8,34 +8,28 @@
 # (bound_inf, bound_sup),  LaTeX name
 # The name of the variables must to be the same at the name of the Parameter
 m = Parameter("m", 0, 0.05, (0, 0.1), "m_0")
+# m = Parameter("m", 3, 0.5, (0,5), "m_0")
 b = Parameter("b", 3, 0.05, (0, 5), "b_0")
 
 # 2) Create a list with your parameters objects
 parameterlist = [m, b]
 
 # 3) Define a method that reads a list of parameters,
+# unzip them and return the a function of x with the
+# parameters.
+def model(parameterlist, x):
+    m, b = parameterlist
+    return m*x+b
 
-model = 'm*x+b'
 cosmo_model = 'Ocb/a**3+Omrad/a**4+NuContrib+(1.0-Om-m)'
 
 # 4) Use SimpleMC as usually, but with model = custom_model
 
-# analyzer = DriverMC(model='simple', datasets='dline', analyzername='mcmc',
-#                     custom_parameters=parameterlist, custom_function=model)
+analyzer = DriverMC(model='simple', datasets='dline', analyzername='mcmc',
+                    custom_parameters=parameterlist, custom_function=model)
 
-analyzer = DriverMC(model='simple_cosmo', datasets='SN', analyzername='mcmc',
-                    custom_parameters=parameterlist, custom_function=cosmo_model)
+# analyzer = DriverMC(model='simple_cosmo', datasets='SN', analyzername='mcmc',
+#                     custom_parameters=parameterlist, custom_function=cosmo_model)
 
 
-analyzer.executer(nsamp=1000)
-
-# import corner
-# import numpy as np
-# import matplotlib.pyplot as plt
-#
-# dir = 'simplemc/chains/'
-# text_chain = 'simple_phy_dline_mcmc_1.txt'
-# npchain = np.loadtxt(dir+text_chain)
-# chain = npchain[:,2:5]
-# figure = corner.corner(chain)
-# plt.show()
+analyzer.executer(nsamp=1000)