Changeset 3221de0 in sasmodels for sasmodels/compare.py

Timestamp:

Feb 1, 2018 9:40:30 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:

b4272a2

Parents:

b3af1c2

Message:

restructure handling of opencl flags so it works with sasview

File:

• sasmodels/compare.py (modified) (5 diffs)

sasmodels/compare.py

@@ -40 +40 @@
 from . import core
 from . import kerneldll
+from . import kernelcl
 from .data import plot_theory, empty_data1D, empty_data2D, load_data
 from .direct_model import DirectModel, get_mesh
@@ -623 +624 @@
 
 
+def time_calculation(calculator, pars, evals=1):
+    # type: (Calculator, ParameterSet, int) -> Tuple[np.ndarray, float]
+    """
+    Compute the average calculation time over N evaluations.
+
+    An additional call is generated without polydispersity in order to
+    initialize the calculation engine, and make the average more stable.
+    """
+    # initialize the code so time is more accurate
+    if evals > 1:
+        calculator(**suppress_pd(pars))
+    toc = tic()
+    # make sure there is at least one eval
+    value = calculator(**pars)
+    for _ in range(evals-1):
+        value = calculator(**pars)
+    average_time = toc()*1000. / evals
+    #print("I(q)",value)
+    return value, average_time
+
+def make_data(opts):
+    # type: (Dict[str, Any]) -> Tuple[Data, np.ndarray]
+    """
+    Generate an empty dataset, used with the model to set Q points
+    and resolution.
+
+    *opts* contains the options, with 'qmax', 'nq', 'res',
+    'accuracy', 'is2d' and 'view' parsed from the command line.
+    """
+    qmin, qmax, nq, res = opts['qmin'], opts['qmax'], opts['nq'], opts['res']
+    if opts['is2d']:
+        q = np.linspace(-qmax, qmax, nq)  # type: np.ndarray
+        data = empty_data2D(q, resolution=res)
+        data.accuracy = opts['accuracy']
+        set_beam_stop(data, qmin)
+        index = ~data.mask
+    else:
+        if opts['view'] == 'log' and not opts['zero']:
+            q = np.logspace(math.log10(qmin), math.log10(qmax), nq)
+        else:
+            q = np.linspace(qmin, qmax, nq)
+        if opts['zero']:
+            q = np.hstack((0, q))
+        data = empty_data1D(q, resolution=res)
+        index = slice(None, None)
+    return data, index
+
 DTYPE_MAP = {
     'half': '16',
@@ -643 +691 @@
     Return a model calculator using the OpenCL calculation engine.
     """
-    if not core.HAVE_OPENCL:
-        raise RuntimeError("OpenCL not available")
-    model = core.build_model(model_info, dtype=dtype, platform="ocl")
-    calculator = DirectModel(data, model, cutoff=cutoff)
-    calculator.engine = "OCL%s"%DTYPE_MAP[str(model.dtype)]
-    return calculator
 
 def eval_ctypes(model_info, data, dtype='double', cutoff=0.):
@@ -660 +702 @@
     return calculator
 
-def time_calculation(calculator, pars, evals=1):
-    # type: (Calculator, ParameterSet, int) -> Tuple[np.ndarray, float]
-    """
-    Compute the average calculation time over N evaluations.
-
-    An additional call is generated without polydispersity in order to
-    initialize the calculation engine, and make the average more stable.
-    """
-    # initialize the code so time is more accurate
-    if evals > 1:
-        calculator(**suppress_pd(pars))
-    toc = tic()
-    # make sure there is at least one eval
-    value = calculator(**pars)
-    for _ in range(evals-1):
-        value = calculator(**pars)
-    average_time = toc()*1000. / evals
-    #print("I(q)",value)
-    return value, average_time
-
-def make_data(opts):
-    # type: (Dict[str, Any]) -> Tuple[Data, np.ndarray]
-    """
-    Generate an empty dataset, used with the model to set Q points
-    and resolution.
-
-    *opts* contains the options, with 'qmax', 'nq', 'res',
-    'accuracy', 'is2d' and 'view' parsed from the command line.
-    """
-    qmin, qmax, nq, res = opts['qmin'], opts['qmax'], opts['nq'], opts['res']
-    if opts['is2d']:
-        q = np.linspace(-qmax, qmax, nq)  # type: np.ndarray
-        data = empty_data2D(q, resolution=res)
-        data.accuracy = opts['accuracy']
-        set_beam_stop(data, qmin)
-        index = ~data.mask
-    else:
-        if opts['view'] == 'log' and not opts['zero']:
-            q = np.logspace(math.log10(qmin), math.log10(qmax), nq)
-        else:
-            q = np.linspace(qmin, qmax, nq)
-        if opts['zero']:
-            q = np.hstack((0, q))
-        data = empty_data1D(q, resolution=res)
-        index = slice(None, None)
-    return data, index
-
 def make_engine(model_info, data, dtype, cutoff, ngauss=0):
     # type: (ModelInfo, Data, str, float) -> Calculator
@@ -718 +713 @@
         set_integration_size(model_info, ngauss)
 
-    if dtype is None or not dtype.endswith('!'):
-        return eval_opencl(model_info, data, dtype=dtype, cutoff=cutoff)
-    else:
-        return eval_ctypes(model_info, data, dtype=dtype[:-1], cutoff=cutoff)
+    if dtype != "default" and not dtype.endswith('!') and not kernelcl.use_opencl():
+        raise RuntimeError("OpenCL not available " + kernelcl.OPENCL_ERROR)
+
+    model = core.build_model(model_info, dtype=dtype, platform="ocl")
+    calculator = DirectModel(data, model, cutoff=cutoff)
+    engine_type = calculator._model.__class__.__name__.replace('Model','').upper()
+    bits = calculator._model.dtype.itemsize*8
+    precision = "fast" if getattr(calculator._model, 'fast', False) else str(bits)
+    calculator.engine = "%s[%s]" % (engine_type, precision)
+    return calculator
 
 def _show_invalid(data, theory):