Fix for SBML kinetic law formula when importing and writing SBML #89 (#…

…93)

* add priors, and custom prior

* py_inference wrapper added

* merge master

* add beta and gamma prior

* add custom prior documenting notebook

* all notebooks work

* typo bug fix

* minor update to inference notebooks

* gaussian prior fix

* bug fixes for log uniform prior and pdf computation bound checks

* add checks to rate law math ast

bioscrape/pid_interfaces.py

@@ -119,7 +119,6 @@ def exponential_prior(self, param_name, param_value):
         lambda_p = prior_dict[param_name][1]
 
         prob = lambda_p * np.exp(-lambda_p * param_value)
-
         if prob < 0:
             warnings.warn('Probability less than 0 while checking Exponential prior! Current parameter name and value: {0}:{1}.'.format(param_name, param_value))
             return np.inf
@@ -180,10 +179,8 @@ def log_uniform_prior(self, param_name, param_value):
             return np.inf
 
         prob = 1/(param_value* (np.log(upper_bound) - np.log(lower_bound)))
-
         if prob < 0:
             warnings.warn('Probability less than 0 while checking Log-Uniform prior! Current parameter name and value: {0}:{1}.'.format(param_name, param_value))
-
             return np.inf
         else:
             return np.log(prob)
@@ -204,7 +201,6 @@ def log_gaussian_prior(self, param_name, param_value):
         prob = 1/(param_value * np.sqrt(2*np.pi) * sigma) * np.exp((-0.5 * (np.log(param_value) - mu)**2)/sigma**2)
         if prob < 0:
             warnings.warn('Probability less than 0 while checking log-normal prior! Current parameter name and value: {0}:{1}.'.format(param_name, param_value))
-
             return np.inf
         else:
             return np.log(prob)

bioscrape/sbmlutil.py

@@ -92,7 +92,10 @@ def import_sbml(sbml_file, bioscrape_model = None, input_printout = False, **kwa
                 allparams[pid] = p.getValue()
         # get the formula as a string and then add
         # a leading _ to parameter names
-        kl_formula = libsbml.formulaToL3String(kl.getMath())
+        math_ast = kl.getMath()
+        if math_ast is None:
+            raise ValueError("Could not import the rate law for reaction to SBML.")
+        kl_formula = libsbml.formulaToL3String(math_ast)
         #We should no longer add underscores to parameters
         #rate_string = _add_underscore_to_parameters(kl_formula, allparams)
         rate_string = kl_formula
@@ -629,7 +632,9 @@ def add_reaction(model, inputs_list, outputs_list,
     ratestring = _remove_underscore_from_parameters(ratestring, allparams)
     # Set the ratelaw to the ratestring
     math_ast = libsbml.parseL3Formula(ratestring)
-    ratelaw.setMath(math_ast)
+    flag = ratelaw.setMath(math_ast)
+    if not flag == libsbml.LIBSBML_OPERATION_SUCCESS or math_ast is None:
+        raise ValueError("Could not write the rate law for reaction to SBML. Check the reaction definition.")
 
     #Add propensity annotation
     if propensity_annotation and propensity_type != "general":