Changeset 0ff62d4 in sasmodels for sasmodels/kernel.py

Timestamp:

Apr 15, 2016 12:31:35 PM (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:

f2f67a6

Parents:

8f6817d

Message:

refactor: move dispersion_mesh alongside build_details in kernel.py

File:

• sasmodels/kernel.py (modified) (2 diffs)

sasmodels/kernel.py

@@ -10 +10 @@
 """
 
+import numpy as np
+from .details import mono_details, poly_details
+
 try:
     from typing import List
+except ImportError:
+    pass
+else:
     from .details import CallDetails
     from .modelinfo import ModelInfo
     import numpy as np  # type: ignore
-except ImportError:
-    pass
 
 class KernelModel(object):
@@ -42 +46 @@
         # type: () -> None
         pass
+
+try:
+    np.meshgrid([])
+    meshgrid = np.meshgrid
+except ValueError:
+    # CRUFT: np.meshgrid requires multiple vectors
+    def meshgrid(*args):
+        if len(args) > 1:
+            return np.meshgrid(*args)
+        else:
+            return [np.asarray(v) for v in args]
+
+def dispersion_mesh(model_info, pars):
+    """
+    Create a mesh grid of dispersion parameters and weights.
+
+    Returns [p1,p2,...],w where pj is a vector of values for parameter j
+    and w is a vector containing the products for weights for each
+    parameter set in the vector.
+    """
+    value, weight = zip(*pars)
+    weight = [w if w else [1.] for w in weight]
+    weight = np.vstack([v.flatten() for v in meshgrid(*weight)])
+    weight = np.prod(weight, axis=0)
+    value = [v.flatten() for v in meshgrid(*value)]
+    lengths = [par.length for par in model_info.parameters.kernel_parameters
+               if par.type == 'volume']
+    if any(n > 1 for n in lengths):
+        pars = []
+        offset = 0
+        for n in lengths:
+            pars.append(np.vstack(value[offset:offset+n]) if n > 1 else value[offset])
+            offset += n
+        value = pars
+    return value, weight
+
+
+
+def build_details(kernel, pairs):
+    # type: (Kernel, Tuple[List[np.ndarray], List[np.ndarray]]) -> Tuple[CallDetails, np.ndarray, np.ndarray]
+    """
+    Construct the kernel call details object for calling the particular kernel.
+    """
+    values, weights = zip(*pairs)
+    if max([len(w) for w in weights]) > 1:
+        call_details = poly_details(kernel.info, weights)
+    else:
+        call_details = mono_details(kernel.info)
+    weights, values = [np.hstack(v) for v in (weights, values)]
+    weights = weights.astype(dtype=kernel.dtype)
+    values = values.astype(dtype=kernel.dtype)
+    return call_details, weights, values
+