Changes in sasmodels/multiscat.py [b3703f5:2c4a190] in sasmodels

File:

• sasmodels/multiscat.py (modified) (4 diffs)

sasmodels/multiscat.py

@@ -342 +342 @@
 
     *probability* is related to the expected number of scattering
-    events in the sample $\lambda$ as $p = 1 = e^{-\lambda}$.  As a
-    hack to allow probability to be a fitted parameter, the "value"
-    can be a function that takes no parameters and returns the current
-    value of the probability.  *coverage* determines how many scattering
-    steps to consider.  The default is 0.99, which sets $n$ such that
-    $1 \ldots n$ covers 99% of the Poisson probability mass function.
+    events in the sample $\lambda$ as $p = 1 - e^{-\lambda}$.
+    *coverage* determines how many scattering steps to consider.  The
+    default is 0.99, which sets $n$ such that $1 \ldots n$ covers 99%
+    of the Poisson probability mass function.
 
     *is2d* is True then 2D scattering is used, otherwise it accepts
@@ -399 +397 @@
         self.qmin = qmin
         self.nq = nq
-        self.probability = probability
+        self.probability = 0. if probability is None else probability
         self.coverage = coverage
         self.is2d = is2d
@@ -456 +454 @@
         self.Iqxy = None # type: np.ndarray
 
+        # Label probability as a fittable parameter, and give its external name
+        # Note that the external name must be a valid python identifier, since
+        # is will be set as an experiment attribute.
+        self.fittable = {'probability': 'scattering_probability'}
+
     def apply(self, theory):
         if self.is2d:
@@ -463 +466 @@
         Iq_calc = Iq_calc.reshape(self.nq, self.nq)
 
+        # CRUFT: don't need probability as a function anymore
         probability = self.probability() if callable(self.probability) else self.probability
         coverage = self.coverage