Changeset 319ab14 in sasmodels for sasmodels/compare_many.py

Timestamp:

Nov 25, 2015 11:12:06 AM (9 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:

0fa687d

Parents:

38d8774

Message:

allow comparison between double/quad precision and sasview

File:

• sasmodels/compare_many.py (modified) (10 diffs)

sasmodels/compare_many.py

@@ -11 +11 @@
                       columnize, constrain_pars)
 
-def get_stats(target, value, index):
+def calc_stats(target, value, index):
     resid = abs(value-target)[index]
     relerr = resid/target[index]
@@ -34 +34 @@
     print(','.join('"%s"'%c for c in columns))
 
-def compare_instance(name, data, index, N=1, mono=True, cutoff=1e-5):
+def compare_instance(name, data, index, N=1, mono=True, cutoff=1e-5,
+                     precision='double'):
     model_definition = core.load_model_definition(name)
     pars = get_demo_pars(model_definition)
@@ -41 +42 @@
     print(header)
 
-    def trymodel(fn, *args, **kw):
+    # Some not very clean macros for evaluating the models and checking the
+    # results.  They freely use variables from the current scope, even some
+    # which have not been defined yet, complete with abuse of mutable lists
+    # to allow them to update values in the current scope since nonlocal
+    # declarations are not available in python 2.7.
+    def try_model(fn, *args, **kw):
         try:
             result, _ = fn(model_definition, pars_i, data, *args, **kw)
@@ -54 +60 @@
                 result = np.NaN*data.x
         return result
+    def check_model(label, target, value, acceptable):
+        stats = calc_stats(target, value, index)
+        columns.extend(stats)
+        labels.append('GPU single')
+        max_diff[0] = max(max_diff[0], stats[0])
+        good[0] = good[0] and (stats[0] < acceptable)
 
     num_good = 0
     first = True
-    max_diff = 0
+    max_diff = [0]
     for k in range(N):
         print >>sys.stderr, name, k
@@ -64 +76 @@
         if mono: suppress_pd(pars_i)
 
-        good = True
+        good = [True]
         labels = []
         columns = []
-        if 1:
-            sasview_value = trymodel(eval_sasview)
+        #target = try_model(eval_sasview)
+        target = try_model(eval_opencl, dtype='longdouble', cutoff=cutoff)
+        if precision == 'single':
+            value = try_model(eval_opencl, dtype='single', cutoff=cutoff)
+            check_model('GPU single', target, value, 5e-5)
+            single_value = value  # remember for single/double comparison
+        elif precision == 'double':
+            if environment().has_double:
+                label = 'GPU double'
+                value = try_model(eval_opencl, dtype='double', cutoff=cutoff)
+            else:
+                label = 'CPU double'
+                value = try_model(eval_ctypes, dtype='double', cutoff=cutoff)
+            check_model(label, target, value, 5e-14)
+            double_value = value  # remember for single/double comparison
+        elif precision == 'quad':
+            value = try_model(eval_opencl, dtype='longdouble', cutoff=cutoff)
+            check_model('CPU quad', target, value, 5e-14)
         if 0:
-            gpu_single_value = trymodel(eval_opencl, dtype='single', cutoff=cutoff)
-            stats = get_stats(sasview_value, gpu_single_value, index)
-            columns.extend(stats)
-            labels.append('GPU single')
-            max_diff = max(max_diff, stats[0])
-            good = good and (stats[0] < 5e-5)
-        if 0 and environment().has_double:
-            gpu_double_value = trymodel(eval_opencl, dtype='double', cutoff=cutoff)
-            stats = get_stats(sasview_value, gpu_double_value, index)
-            columns.extend(stats)
-            labels.append('GPU double')
-            max_diff = max(max_diff, stats[0])
-            good = good and (stats[0] < 1e-12)
-        if 1:
-            cpu_double_value = trymodel(eval_ctypes, dtype='double', cutoff=cutoff)
-            stats = get_stats(sasview_value, cpu_double_value, index)
-            columns.extend(stats)
-            labels.append('CPU double')
-            max_diff = max(max_diff, stats[0])
-            good = good and (stats[0] < 1e-12)
-        if 0:
-            stats = get_stats(cpu_double_value, gpu_single_value, index)
-            columns.extend(stats)
-            labels.append('single/double')
-            max_diff = max(max_diff, stats[0])
-            good = good and (stats[0] < 5e-5)
+            check_model('single/double', double_value, single_value, 5e-5)
 
         columns += [v for _,v in sorted(pars_i.items())]
@@ -101 +104 @@
             print_column_headers(pars_i, labels)
             first = False
-        if good:
+        if good[0]:
             num_good += 1
         else:
             print(("%d,"%seed)+','.join("%g"%v for v in columns))
-    print '"good","%d/%d","max diff",%g'%(num_good, N, max_diff)
+    print '"good","%d/%d","max diff",%g'%(num_good, N, max_diff[0])
 
 
 def print_usage():
-    print "usage: compare_many.py MODEL COUNT (1dNQ|2dNQ) (CUTOFF|mono)"
+    print "usage: compare_many.py MODEL COUNT (1dNQ|2dNQ) (CUTOFF|mono) (single|double|quad)"
 
 
@@ -138 +141 @@
 is set in compare.py defaults for each model.
 
+PRECISION is the floating point precision to use for comparisons.
+
 Available models:
 """)
@@ -143 +148 @@
 
 def main():
-    if len(sys.argv) == 1:
+    if len(sys.argv) != 6:
         print_help()
         sys.exit(1)
@@ -159 +164 @@
         mono = sys.argv[4] == 'mono'
         cutoff = float(sys.argv[4]) if not mono else 0
+        precision = sys.argv[5]
     except:
+        traceback.print_exc()
         print_usage()
         sys.exit(1)
@@ -166 +173 @@
     model_list = [model] if model != "all" else MODELS
     for model in model_list:
-        compare_instance(model, data, index, N=count, mono=mono, cutoff=cutoff)
+        compare_instance(model, data, index, N=count, mono=mono,
+                         cutoff=cutoff, precision=precision)
 
 if __name__ == "__main__":