Changeset de0c4ba in sasmodels

Timestamp:

Mar 3, 2015 4:14:06 PM (10 years ago)

Author:

Doucet, Mathieu <doucetm@…>

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:

6c8db9e

Parents:

e930946

Message:

pylint fixes

File:

• sasmodels/sasview_model.py (modified) (18 diffs)

sasmodels/sasview_model.py

@@ -26 +26 @@
 try:
     from .kernelcl import load_model
-except ImportError,exc:
+except ImportError, exc:
     warnings.warn(str(exc))
     warnings.warn("using ctypes instead")
@@ -41 +41 @@
     will produce a class with a name compatible with SasView
     """
-    model =  load_model(kernel_module, dtype=dtype)
+    model = load_model(kernel_module, dtype=dtype)
     def __init__(self, multfactor=1):
         SasviewModel.__init__(self, model)
     attrs = dict(__init__=__init__)
-    ConstructedModel = type(model.info[namestyle],  (SasviewModel,), attrs)
+    ConstructedModel = type(model.info[namestyle], (SasviewModel,), attrs)
     return ConstructedModel
 
@@ -69 +69 @@
         self.dispersion = dict()
         partype = model.info['partype']
-        for name,units,default,limits,ptype,description in model.info['parameters']:
+        for name, units, default, limits, ptype, description in model.info['parameters']:
             self.params[name] = default
-            self.details[name] = [units]+limits
+            self.details[name] = [units] + limits
 
         for name in partype['pd-2d']:
@@ -83 +83 @@
         self.orientation_params = (
             partype['orientation']
-            + [n+'.width' for n in partype['orientation']]
+            + [n + '.width' for n in partype['orientation']]
             + partype['magnetic'])
         self.magnetic_params = partype['magnetic']
-        self.fixed = [n+'.width' for n in partype['pd-2d']]
+        self.fixed = [n + '.width' for n in partype['pd-2d']]
         self.non_fittable = []
 
         ## independent parameter name and unit [string]
-        self.input_name = model.info.get("input_name","Q")
-        self.input_unit = model.info.get("input_unit","A^{-1}")
-        self.output_name = model.info.get("output_name","Intensity")
-        self.output_unit = model.info.get("output_unit","cm^{-1}")
+        self.input_name = model.info.get("input_name", "Q")
+        self.input_unit = model.info.get("input_unit", "A^{-1}")
+        self.output_name = model.info.get("output_name", "Intensity")
+        self.output_unit = model.info.get("output_unit", "cm^{-1}")
 
         ## _persistency_dict is used by sas.perspectives.fitting.basepage
@@ -139 +139 @@
         # Look for dispersion parameters
         toks = name.split('.')
-        if len(toks)==2:
+        if len(toks) == 2:
             for item in self.dispersion.keys():
-                if item.lower()==toks[0].lower():
+                if item.lower() == toks[0].lower():
                     for par in self.dispersion[item]:
                         if par.lower() == toks[1].lower():
@@ -149 +149 @@
             # Look for standard parameter
             for item in self.params.keys():
-                if item.lower()==name.lower():
+                if item.lower() == name.lower():
                     self.params[item] = value
                     return
@@ -164 +164 @@
         # Look for dispersion parameters
         toks = name.split('.')
-        if len(toks)==2:
+        if len(toks) == 2:
             for item in self.dispersion.keys():
-                if item.lower()==toks[0].lower():
+                if item.lower() == toks[0].lower():
                     for par in self.dispersion[item]:
                         if par.lower() == toks[1].lower():
@@ -173 +173 @@
             # Look for standard parameter
             for item in self.params.keys():
-                if item.lower()==name.lower():
+                if item.lower() == name.lower():
                     return self.params[item]
 
@@ -182 +182 @@
         Return a list of all available parameters for the model
         """
-        list = self.params.keys()
+        param_list = self.params.keys()
         # WARNING: Extending the list with the dispersion parameters
-        list.extend(self.getDispParamList())
-        return list
+        param_list.extend(self.getDispParamList())
+        return param_list
 
     def getDispParamList(self):
@@ -192 +192 @@
         """
         # TODO: fix test so that parameter order doesn't matter
-        ret = ['%s.%s'%(d.lower(), p)
+        ret = ['%s.%s' % (d.lower(), p)
                for d in self._model.info['partype']['pd-2d']
                for p in ('npts', 'nsigmas', 'width')]
@@ -212 +212 @@
         **DEPRECATED**: use calculate_Iq instead
         """
-        if isinstance(x, (list,tuple)):
+        if isinstance(x, (list, tuple)):
             q, phi = x
             return self.calculate_Iq([q * math.cos(phi)],
@@ -230 +230 @@
         **DEPRECATED**: use calculate_Iq instead
         """
-        if isinstance(x, (list,tuple)):
-            return self.calculate_Iq([float(x[0])],[float(x[1])])[0]
+        if isinstance(x, (list, tuple)):
+            return self.calculate_Iq([float(x[0])], [float(x[1])])[0]
         else:
             return self.calculate_Iq([float(x)])[0]
@@ -265 +265 @@
         :param qdist: ndarray of scalar q-values or list [qx,qy] where qx,qy are 1D ndarrays
         """
-        if isinstance(qdist, (list,tuple)):
+        if isinstance(qdist, (list, tuple)):
             # Check whether we have a list of ndarrays [qx,qy]
             qx, qy = qdist
             partype = self._model.info['partype']
             if not partype['orientation'] and not partype['magnetic']:
-                return self.calculate_Iq(np.sqrt(qx**2+qy**2))
+                return self.calculate_Iq(np.sqrt(qx ** 2 + qy ** 2))
             else:
                 return self.calculate_Iq(qx, qy)
@@ -279 +279 @@
 
         else:
-            raise TypeError("evalDistribution expects q or [qx, qy], not %r"%type(qdist))
+            raise TypeError("evalDistribution expects q or [qx, qy], not %r" % type(qdist))
 
     def calculate_Iq(self, *args):
@@ -313 +313 @@
             fv = ER(*values)
             #print values[0].shape, weights.shape, fv.shape
-            return np.sum(weights*fv) / np.sum(weights)
+            return np.sum(weights * fv) / np.sum(weights)
 
     def calculate_VR(self):
@@ -327 +327 @@
             vol_pars = self._model.info['partype']['volume']
             values, weights = self._dispersion_mesh(vol_pars)
-            whole,part = VR(*values)
-            return np.sum(weights*part)/np.sum(weights*whole)
+            whole, part = VR(*values)
+            return np.sum(weights * part) / np.sum(weights * whole)
 
     def set_dispersion(self, parameter, dispersion):
@@ -373 +373 @@
 
     def _get_weights(self, par):
+        """
+            Return dispersion weights
+            :param par parameter name
+        """
         from . import weights
 
@@ -378 +382 @@
         limits = self._model.info['limits']
         dis = self.dispersion[par]
-        v,w = weights.get_weights(
+        v, w = weights.get_weights(
             dis['type'], dis['npts'], dis['width'], dis['nsigmas'],
             self.params[par], limits[par], par in relative)
-        return v,w/w.max()
-
+        return v, w / w.max()
+