Merge pull request #226 from pymc-devs/normalargs

Add `sd` argument to Normal

Author: jsalvatier

pymc/distributions/continuous.py

@@ -68,7 +68,7 @@ def logp(value):
     return locals()
 
 @tensordist(continuous)
-def Normal(mu=0.0, tau=1.0):
+def Normal(mu=0.0, tau=None, sd=None):
     """
     Normal log-likelihood.
 
@@ -82,13 +82,24 @@ def Normal(mu=0.0, tau=1.0):
     tau : float
         Precision of the distribution, which corresponds to
         :math:`1/\sigma^2` (tau > 0).
+    sd : float 
+        Standard deviation of the distribution. Alternative parameterization.
 
     .. note::
     - :math:`E(X) = \mu`
     - :math:`Var(X) = 1/\tau`
 
     """
 
+    if tau is None :
+        if sd is None:
+            tau = 1.
+        else: 
+            tau = sd**-2 
+    else:
+        if sd is not None: 
+            raise ValueError("Can't pass both tau and sd")
+
     def logp(value):
 
         return bound(

pymc/tuning/starting.py

@@ -23,7 +23,7 @@ def find_MAP(start = None, vars=None, fmin = optimize.fmin_bfgs, return_raw = Fa
     vars : list 
         List of variables to set to MAP point (Defaults to all continuous).
     fmin : function
-        Optimization algorithm (Defaults to `scipy.optimize.fmin_l_bfgs_b`).
+        Optimization algorithm (Defaults to `scipy.optimize.fmin_bfgs`).
     return_raw : Bool
         Whether to return extra value returned by fmin (Defaults to False)
     model : Model (optional if in `with` context)