Changeset fa79f5c in sasmodels for sasmodels/direct_model.py

Timestamp:

Nov 29, 2017 8:43:12 AM (6 years ago)

Author:

Paul Kienzle <pkienzle@…>

Branches:

master, core_shell_microgels, magnetic_model, ticket-1257-vesicle-product, ticket_1156, ticket_1265_superball, ticket_822_more_unit_tests

Children:

a839b22

Parents:

32398dc

Message:

restore working sesans example using direct model

File:

• sasmodels/direct_model.py (modified) (9 diffs)

sasmodels/direct_model.py

@@ -177 +177 @@
 
 
+def _make_sesans_transform(data):
+    from sas.sascalc.data_util.nxsunit import Converter
+
+    # Pre-compute the Hankel matrix (H)
+    SElength = Converter(data._xunit)(data.x, "A")
+
+    theta_max = Converter("radians")(data.sample.zacceptance)[0]
+    q_max = 2 * np.pi / np.max(data.source.wavelength) * np.sin(theta_max)
+    zaccept = Converter("1/A")(q_max, "1/" + data.source.wavelength_unit),
+
+    Rmax = 10000000
+    hankel = sesans.SesansTransform(data.x, SElength,
+                                    data.source.wavelength,
+                                    zaccept, Rmax)
+    return hankel
+
+
 class DataMixin(object):
     """
@@ -216 +233 @@
 
         if self.data_type == 'sesans':
-            q = sesans.make_q(data.sample.zacceptance, data.Rmax)
+            res = _make_sesans_transform(data)
             index = slice(None, None)
-            res = None
             if data.y is not None:
                 Iq, dIq = data.y, data.dy
@@ -224 +240 @@
                 Iq, dIq = None, None
             #self._theory = np.zeros_like(q)
-            q_vectors = [q]
-            q_mono = sesans.make_all_q(data)
+            q_vectors = [res.q_calc]
         elif self.data_type == 'Iqxy':
             #if not model.info.parameters.has_2d:
@@ -244 +259 @@
             #self._theory = np.zeros_like(self.Iq)
             q_vectors = res.q_calc
-            q_mono = []
         elif self.data_type == 'Iq':
             index = (data.x >= data.qmin) & (data.x <= data.qmax)
@@ -269 +283 @@
             #self._theory = np.zeros_like(self.Iq)
             q_vectors = [res.q_calc]
-            q_mono = []
         elif self.data_type == 'Iq-oriented':
             index = (data.x >= data.qmin) & (data.x <= data.qmax)
@@ -286 +299 @@
                                       qy_width=data.dxl[index])
             q_vectors = res.q_calc
-            q_mono = []
         else:
             raise ValueError("Unknown data type") # never gets here
@@ -293 +305 @@
         # so we can save/restore state
         self._kernel_inputs = q_vectors
-        self._kernel_mono_inputs = q_mono
         self._kernel = None
         self.Iq, self.dIq, self.index = Iq, dIq, index
@@ -331 +342 @@
         if self._kernel is None:
             self._kernel = self._model.make_kernel(self._kernel_inputs)
-            self._kernel_mono = (
-                self._model.make_kernel(self._kernel_mono_inputs)
-                if self._kernel_mono_inputs else None)
 
         Iq_calc = call_kernel(self._kernel, pars, cutoff=cutoff)
@@ -341 +349 @@
         # TODO: refactor so we don't store the result in the model
         self.Iq_calc = Iq_calc
-        if self.data_type == 'sesans':
-            Iq_mono = (call_kernel(self._kernel_mono, pars, mono=True)
-                       if self._kernel_mono_inputs else None)
-            result = sesans.transform(self._data,
-                                      self._kernel_inputs[0], Iq_calc,
-                                      self._kernel_mono_inputs, Iq_mono)
-        else:
-            result = self.resolution.apply(Iq_calc)
-            if hasattr(self.resolution, 'nx'):
-                self.Iq_calc = (
-                    self.resolution.qx_calc, self.resolution.qy_calc,
-                    np.reshape(Iq_calc, (self.resolution.ny, self.resolution.nx))
-                )
+        result = self.resolution.apply(Iq_calc)
+        if hasattr(self.resolution, 'nx'):
+            self.Iq_calc = (
+                self.resolution.qx_calc, self.resolution.qy_calc,
+                np.reshape(Iq_calc, (self.resolution.ny, self.resolution.nx))
+            )
         return result