Changeset 7ff3cf3 in sasmodels

Timestamp:

Mar 21, 2016 4:55:33 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:

5cf3c33, 3a45c2c

Parents:

e1bdc7e

Message:

getting past hello…

Location:

sasmodels

Files:

• core.py (modified) (2 diffs)
• generate.py (modified) (4 diffs)
• kernel_iq.c (modified) (2 diffs)
• kerneldll.py (modified) (2 diffs)

sasmodels/core.py

@@ -226 +226 @@
         weights = np.array([1.0])
         details = kernel.info['mono_details']
-        return kernel(pars, weights, details, cutoff)
+        return kernel(details, pars, weights, cutoff)
     else:
         pairs = [get_weights(p, values) for p in kernel.info['parameters']]
@@ -232 +232 @@
         details = generate.poly_details(kernel.info, weights, pars)
         weights, pars = [np.hstack(v) for v in (weights, pars)]
-        return kernel(pars, weights, details, cutoff)
+        return kernel(details, pars, weights, cutoff)
 
 def call_ER_VR(model_info, vol_pars):

sasmodels/generate.py

@@ -650 +650 @@
     model_info['has_2d'] = par_type['orientation'] or par_type['magnetic']
 
-def mono_details(max_pd, npars):
+def mono_details(model_info):
+    max_pd = model_info['max_pd']
+    npars = len(model_info['parameters']) - 2
     p = 5*max_pd
     c = p + 3*npars
 
-    mono = np.zeros(c + 3, 'i')
-    mono[0*max_pd:1*max_pd] = range(max_pd)       # pd_par: arbitrary order; use first
-    mono[1*max_pd:2*max_pd] = [1]*max_pd          # pd_length: only one element
-    mono[2*max_pd:3*max_pd] = range(2, max_pd+2)  # pd_offset: skip scale and background
-    mono[3*max_pd:4*max_pd] = [1]*max_pd          # pd_stride: vectors of length 1
-    mono[4*max_pd:5*max_pd] = [0]*max_pd          # pd_isvol: doens't matter if no norm
-    mono[p+0*npars:p+1*npars] = range(2, npars+2) # par_offset
-    mono[p+1*npars:p+2*npars] = [0]*npars         # no coordination
-    #mono[p+npars] = 1 # par_coord[0] is coordinated with the first par?
-    mono[p+2*npars:p+3*npars] = 0 # fast coord with 0
-    mono[c]   = 1     # fast_coord_count: one fast index
-    mono[c+1] = -1  # theta_var: None
-    mono[c+2] = 0   # fast_theta: False
-    return mono
-
-def poly_details(model_info, weights, pars, constraints=None):
+    details = np.zeros(c + 3, 'int32')
+    details[0*max_pd:1*max_pd] = range(max_pd)       # pd_par: arbitrary order; use first
+    details[1*max_pd:2*max_pd] = [1]*max_pd          # pd_length: only one element
+    details[2*max_pd:3*max_pd] = range(2, max_pd+2)  # pd_offset: skip scale and background
+    details[3*max_pd:4*max_pd] = [1]*max_pd          # pd_stride: vectors of length 1
+    details[4*max_pd:5*max_pd] = [0]*max_pd          # pd_isvol: doens't matter if no norm
+    details[p+0*npars:p+1*npars] = range(2, npars+2) # par_offset
+    details[p+1*npars:p+2*npars] = [0]*npars         # no coordination
+    #details[p+npars] = 1 # par_coord[0] is coordinated with the first par?
+    details[p+2*npars:p+3*npars] = 0 # fast coord with 0
+    details[c]   = 1     # fast_coord_count: one fast index
+    details[c+1] = -1  # theta_var: None
+    details[c+2] = 0   # fast_theta: False
+    return details
+
+def poly_details(model_info, weights, constraints=None):
     if constraints is not None:
         # Need to find the independently varying pars and sort them
@@ -676 +678 @@
         # and weights, returning par blocks
         raise ValueError("Can't handle constraints yet")
+
+    max_pd = model_info['max_pd']
+    npars = len(model_info['parameters']) - 2
+    p = 5*max_pd
+    c = p + 3*npars
+
+    # Decreasing list of polydispersity lengths
+    # Note: the reversing view, x[::-1], does not require a copy
+    idx = np.argsort([len(w) for w in weights])[::-1]
+    details = np.zeros(c + 3, 'int32')
+    details[0*max_pd:1*max_pd] = idx[:max_pd]        # pd_par: arbitrary order; use first
+    details[1*max_pd:2*max_pd] = [1]*max_pd          # pd_length: only one element
+    details[2*max_pd:3*max_pd] = range(2, max_pd+2)  # pd_offset: skip scale and background
+    details[3*max_pd:4*max_pd] = [1]*max_pd          # pd_stride: vectors of length 1
+    details[4*max_pd:5*max_pd] = [0]*max_pd          # pd_isvol: doens't matter if no norm
+    details[p+0*npars:p+1*npars] = range(2, npars+2) # par_offset
+    details[p+1*npars:p+2*npars] = [0]*npars         # no coordination
+    #details[p+npars] = 1 # par_coord[0] is coordinated with the first par?
+    details[p+2*npars:p+3*npars] = 0 # fast coord with 0
+    details[c]   = 1     # fast_coord_count: one fast index
+    details[c+1] = -1  # theta_var: None
+    details[c+2] = 0   # fast_theta: False
+    return details
+
+
 
     raise ValueError("polydispersity not supported")
@@ -768 +795 @@
         oldpars=getattr(kernel_module, 'oldpars', {}),
         tests=getattr(kernel_module, 'tests', []),
-        mono_details = mono_details(MAX_PD, len(kernel_module.parameters))
         )
     process_parameters(model_info)
@@ -775 +801 @@
     model_info.update((k, getattr(kernel_module, k, None)) for k in functions)
     create_default_functions(model_info)
+    # Precalculate the monodisperse parameters
+    # TODO: make this a lazy evaluator
+    # make_model_info is called for every model on sasview startup
+    model_info['mono_details'] = mono_details(model_info)
     return model_info
 

sasmodels/kernel_iq.c

@@ -50 +50 @@
     )
 {
-printf("aliasing\n");
   // Storage for the current parameter values.  These will be updated as we
   // walk the polydispersity cube.
@@ -56 +55 @@
   double *pvec = (double *)(&local_pars);  // Alias named parameters with a vector
 
-printf("allocating\n");
   local int offset[NPARS-2];
 
 #if 1 // defined(USE_SHORTCUT_OPTIMIZATION)
-printf("dereferencing %p as %d\n", problem, problem->pd_length[0]);
   if (problem->pd_length[0] == 1) {
     // Shouldn't need to copy!!

sasmodels/kerneldll.py

@@ -50 +50 @@
 import tempfile
 import ctypes as ct
-from ctypes import c_void_p, c_int, c_longdouble, c_double, c_float
+from ctypes import c_void_p, c_int32, c_longdouble, c_double, c_float
 
 import numpy as np
@@ -205 +205 @@
 
         # int, int, int, int*, double*, double*, double*, double*, double*, double
-        argtypes = [c_int]*3 + [c_void_p]*5 + [fp]
+        argtypes = [c_int32]*3 + [c_void_p]*5 + [fp]
         self.Iq = self.dll[generate.kernel_name(self.info, False)]
         self.Iqxy = self.dll[generate.kernel_name(self.info, True)]