Changeset f619de7 in sasmodels for sasmodels/mixture.py

Timestamp:

Apr 11, 2016 11:14:50 AM (8 years ago)

Author:

Paul Kienzle <pkienzle@…>

Branches:

master, core_shell_microgels, costrafo411, magnetic_model, release_v0.94, release_v0.95, ticket-1257-vesicle-product, ticket_1156, ticket_1265_superball, ticket_822_more_unit_tests

Children:

7ae2b7f

Parents:

9a943d0

Message:

more type hinting

File:

• sasmodels/mixture.py (modified) (8 diffs)

sasmodels/mixture.py

@@ -15 +15 @@
 
 from .modelinfo import Parameter, ParameterTable, ModelInfo
+from .kernel import KernelModel, Kernel
+
+try:
+    from typing import List
+    from .details import CallDetails
+except ImportError:
+    pass
 
 def make_mixture_info(parts):
+    # type: (List[ModelInfo]) -> ModelInfo
     """
     Create info block for product model.
@@ -22 +30 @@
     flatten = []
     for part in parts:
-        if part['composition'] and part['composition'][0] == 'mixture':
-            flatten.extend(part['compostion'][1])
+        if part.composition and part.composition[0] == 'mixture':
+            flatten.extend(part.composition[1])
         else:
             flatten.append(part)
@@ -29 +37 @@
 
     # Build new parameter list
-    pars = []
+    combined_pars = []
     for k, part in enumerate(parts):
         # Parameter prefix per model, A_, B_, ...
@@ -35 +43 @@
         # to support vector parameters
         prefix = chr(ord('A')+k) + '_'
-        pars.append(Parameter(prefix+'scale'))
-        for p in part['parameters'].kernel_pars:
+        combined_pars.append(Parameter(prefix+'scale'))
+        for p in part.parameters.kernel_parameters:
             p = copy(p)
-            p.name = prefix+p.name
-            p.id = prefix+p.id
+            p.name = prefix + p.name
+            p.id = prefix + p.id
             if p.length_control is not None:
-                p.length_control = prefix+p.length_control
-            pars.append(p)
-    partable = ParameterTable(pars)
+                p.length_control = prefix + p.length_control
+            combined_pars.append(p)
+    parameters = ParameterTable(combined_pars)
 
     model_info = ModelInfo()
-    model_info.id = '+'.join(part['id'])
-    model_info.name = ' + '.join(part['name'])
+    model_info.id = '+'.join(part.id for part in parts)
+    model_info.name = ' + '.join(part.name for part in parts)
     model_info.filename = None
     model_info.title = 'Mixture model with ' + model_info.name
@@ -53 +61 @@
     model_info.docs = model_info.title
     model_info.category = "custom"
-    model_info.parameters = partable
+    model_info.parameters = parameters
     #model_info.single = any(part['single'] for part in parts)
     model_info.structure_factor = False
@@ -64 +72 @@
 
 
-class MixtureModel(object):
+class MixtureModel(KernelModel):
     def __init__(self, model_info, parts):
+        # type: (ModelInfo, List[KernelModel]) -> None
         self.info = model_info
         self.parts = parts
 
     def __call__(self, q_vectors):
+        # type: (List[np.ndarray]) -> MixtureKernel
         # Note: may be sending the q_vectors to the n times even though they
         # are only needed once.  It would mess up modularity quite a bit to
@@ -76 +86 @@
         # in opencl; or both in opencl, but one in single precision and the
         # other in double precision).
-        kernels = [part(q_vectors) for part in self.parts]
+        kernels = [part.make_kernel(q_vectors) for part in self.parts]
         return MixtureKernel(self.info, kernels)
 
     def release(self):
+        # type: () -> None
         """
         Free resources associated with the model.
@@ -87 +98 @@
 
 
-class MixtureKernel(object):
+class MixtureKernel(Kernel):
     def __init__(self, model_info, kernels):
-        dim = '2d' if kernels[0].q_input.is_2d else '1d'
+        # type: (ModelInfo, List[Kernel]) -> None
+        self.dim = kernels[0].dim
+        self.info =  model_info
+        self.kernels = kernels
 
-        # fixed offsets starts at 2 for scale and background
-        fixed_pars, pd_pars = [], []
-        offsets = [[2, 0]]
-        #vol_index = []
-        def accumulate(fixed, pd, volume):
-            # subtract 1 from fixed since we are removing background
-            fixed_offset, pd_offset = offsets[-1]
-            #vol_index.extend(k+pd_offset for k,v in pd if v in volume)
-            offsets.append([fixed_offset + len(fixed) - 1, pd_offset + len(pd)])
-            pd_pars.append(pd)
-        if dim == '2d':
-            for p in kernels:
-                partype = p.info.partype
-                accumulate(partype['fixed-2d'], partype['pd-2d'], partype['volume'])
-        else:
-            for p in kernels:
-                partype = p.info.partype
-                accumulate(partype['fixed-1d'], partype['pd-1d'], partype['volume'])
-
-        #self.vol_index = vol_index
-        self.offsets = offsets
-        self.fixed_pars = fixed_pars
-        self.pd_pars = pd_pars
-        self.info = model_info
-        self.kernels = kernels
-        self.results = None
-
-    def __call__(self, fixed_pars, pd_pars, cutoff=1e-5):
-        scale, background = fixed_pars[0:2]
+    def __call__(self, call_details, value, weight, cutoff):
+        # type: (CallDetails, np.ndarray, np.ndarry, float) -> np.ndarray
+        scale, background = value[0:2]
         total = 0.0
-        self.results = []  # remember the parts for plotting later
-        for k in range(len(self.offsets)-1):
-            start_fixed, start_pd = self.offsets[k]
-            end_fixed, end_pd = self.offsets[k+1]
-            part_fixed = [fixed_pars[start_fixed], 0.0] + fixed_pars[start_fixed+1:end_fixed]
-            part_pd = [pd_pars[start_pd], 0.0] + pd_pars[start_pd+1:end_pd]
-            part_result = self.kernels[k](part_fixed, part_pd)
+        # remember the parts for plotting later
+        self.results = []
+        for kernel, kernel_details in zip(self.kernels, call_details.parts):
+            part_result = kernel(kernel_details, value, weight, cutoff)
             total += part_result
-            self.results.append(scale*sum+background)
+            self.results.append(part_result)
 
         return scale*total + background
 
     def release(self):
-        self.p_kernel.release()
-        self.q_kernel.release()
+        # type: () -> None
+        for k in self.kernels:
+            k.release()