Changeset e61a9b1 in sasview for src/sas/sasgui/perspectives/fitting

Timestamp:

Aug 17, 2017 10:01:11 AM (7 years ago)

Author:

Paul Kienzle <pkienzle@…>

Branches:

master, ESS_GUI, ESS_GUI_Docs, ESS_GUI_batch_fitting, ESS_GUI_bumps_abstraction, ESS_GUI_iss1116, ESS_GUI_iss879, ESS_GUI_iss959, ESS_GUI_opencl, ESS_GUI_ordering, ESS_GUI_sync_sascalc, costrafo411, magnetic_scatt, release-4.2.2, ticket-1009, ticket-1094-headless, ticket-1242-2d-resolution, ticket-1243, ticket-1249, ticket885, unittest-saveload

Children:

d24e41d

Parents:

fc6651c (diff), bc04647 (diff)
Note: this is a merge changeset, the changes displayed below correspond to the merge itself.
Use the (diff) links above to see all the changes relative to each parent.

Message:

Merge branch 'master' into FixingTicket741

Location:

src/sas/sasgui/perspectives/fitting

Files:

• basepage.py (modified) (1 diff)
• fitting.py (modified) (4 diffs)
• models.py (modified) (5 diffs)
• model_thread.py (modified) (3 diffs)

src/sas/sasgui/perspectives/fitting/basepage.py

@@ -254 +254 @@
         if not hasattr(self, "model_view"):
             return
-        toggle_mode_on = self.model_view.IsEnabled()
+        toggle_mode_on = self.model_view.IsEnabled() or self.data is None
         if toggle_mode_on:
             if self.enable2D and not check_data_validity(self.data):

src/sas/sasgui/perspectives/fitting/fitting.py

@@ -383 +383 @@
           '(Re)Load all models present in user plugin_models folder')
         wx.EVT_MENU(owner, wx_id, self.load_plugin_models)
-   
+
     def set_edit_menu_helper(self, owner=None, menu=None):
         """
@@ -1734 +1734 @@
             @param unsmeared_error: data error, rescaled to unsmeared model
         """
-        try:
-            np.nan_to_num(y)
-            new_plot = self.create_theory_1D(x, y, page_id, model, data, state,
-                                             data_description=model.name,
-                                             data_id=str(page_id) + " " + data.name)
-            if unsmeared_model is not None:
-                self.create_theory_1D(x, unsmeared_model, page_id, model, data, state,
-                                      data_description=model.name + " unsmeared",
-                                      data_id=str(page_id) + " " + data.name + " unsmeared")
-
-                if unsmeared_data is not None and unsmeared_error is not None:
-                    self.create_theory_1D(x, unsmeared_data, page_id, model, data, state,
-                                          data_description="Data unsmeared",
-                                          data_id="Data  " + data.name + " unsmeared",
-                                          dy=unsmeared_error)
-            if sq_model is not None and pq_model is not None:
-                self.create_theory_1D(x, sq_model, page_id, model, data, state,
-                                      data_description=model.name + " S(q)",
-                                      data_id=str(page_id) + " " + data.name + " S(q)")
-                self.create_theory_1D(x, pq_model, page_id, model, data, state,
-                                      data_description=model.name + " P(q)",
-                                      data_id=str(page_id) + " " + data.name + " P(q)")
-
-            current_pg = self.fit_panel.get_page_by_id(page_id)
-            title = new_plot.title
-            batch_on = self.fit_panel.get_page_by_id(page_id).batch_on
-            if not batch_on:
-                wx.PostEvent(self.parent, NewPlotEvent(plot=new_plot,
-                                            title=str(title)))
-            elif plot_result:
-                top_data_id = self.fit_panel.get_page_by_id(page_id).data.id
-                if data.id == top_data_id:
-                    wx.PostEvent(self.parent, NewPlotEvent(plot=new_plot,
-                                            title=str(title)))
-            caption = current_pg.window_caption
-            self.page_finder[page_id].set_fit_tab_caption(caption=caption)
-
-            self.page_finder[page_id].set_theory_data(data=new_plot,
+        number_finite = np.count_nonzero(np.isfinite(y))
+        np.nan_to_num(y)
+        new_plot = self.create_theory_1D(x, y, page_id, model, data, state,
+                                         data_description=model.name,
+                                         data_id=str(page_id) + " " + data.name)
+        if unsmeared_model is not None:
+            self.create_theory_1D(x, unsmeared_model, page_id, model, data, state,
+                                  data_description=model.name + " unsmeared",
+                                  data_id=str(page_id) + " " + data.name + " unsmeared")
+
+            if unsmeared_data is not None and unsmeared_error is not None:
+                self.create_theory_1D(x, unsmeared_data, page_id, model, data, state,
+                                      data_description="Data unsmeared",
+                                      data_id="Data  " + data.name + " unsmeared",
+                                      dy=unsmeared_error)
+        # Comment this out until we can get P*S models with correctly populated parameters
+        if sq_model is not None and pq_model is not None:
+            self.create_theory_1D(x, sq_model, page_id, model, data, state,
+                                  data_description=model.name + " S(q)",
+                                  data_id=str(page_id) + " " + data.name + " S(q)")
+            self.create_theory_1D(x, pq_model, page_id, model, data, state,
+                                  data_description=model.name + " P(q)",
+                                  data_id=str(page_id) + " " + data.name + " P(q)")
+
+        current_pg = self.fit_panel.get_page_by_id(page_id)
+        title = new_plot.title
+        batch_on = self.fit_panel.get_page_by_id(page_id).batch_on
+        if not batch_on:
+            wx.PostEvent(self.parent, NewPlotEvent(plot=new_plot, title=str(title)))
+        elif plot_result:
+            top_data_id = self.fit_panel.get_page_by_id(page_id).data.id
+            if data.id == top_data_id:
+                wx.PostEvent(self.parent, NewPlotEvent(plot=new_plot, title=str(title)))
+        caption = current_pg.window_caption
+        self.page_finder[page_id].set_fit_tab_caption(caption=caption)
+
+        self.page_finder[page_id].set_theory_data(data=new_plot,
                                                       fid=data.id)
-            if toggle_mode_on:
-                wx.PostEvent(self.parent,
-                             NewPlotEvent(group_id=str(page_id) + " Model2D",
+        if toggle_mode_on:
+            wx.PostEvent(self.parent,
+                         NewPlotEvent(group_id=str(page_id) + " Model2D",
                                           action="Hide"))
-            else:
-                if update_chisqr:
-                    wx.PostEvent(current_pg,
-                                 Chi2UpdateEvent(output=self._cal_chisqr(
+        else:
+            if update_chisqr:
+                wx.PostEvent(current_pg,
+                             Chi2UpdateEvent(output=self._cal_chisqr(
                                                                 data=data,
                                                                 fid=fid,
                                                                 weight=weight,
-                                                            page_id=page_id,
-                                                            index=index)))
-                else:
-                    self._plot_residuals(page_id=page_id, data=data, fid=fid,
-                                         index=index, weight=weight)
-
+                                                                page_id=page_id,
+                                                                index=index)))
+            else:
+                self._plot_residuals(page_id=page_id, data=data, fid=fid,
+                                     index=index, weight=weight)
+
+        if not number_finite:
+            logger.error("Using the present parameters the model does not return any finite value. ")
+            msg = "Computing Error: Model did not return any finite value."
+            wx.PostEvent(self.parent, StatusEvent(status = msg, info="error"))
+        else:
             msg = "Computation  completed!"
+            if number_finite != y.size:
+                msg += ' PROBLEM: For some Q values the model returns non finite intensities!'
+                logger.error("For some Q values the model returns non finite intensities.")
             wx.PostEvent(self.parent, StatusEvent(status=msg, type="stop"))
-        except:
-            raise
 
     def _calc_exception(self, etype, value, tb):
@@ -1818 +1823 @@
         that can be plot.
         """
+        number_finite = np.count_nonzero(np.isfinite(image))
         np.nan_to_num(image)
         new_plot = Data2D(image=image, err_image=data.err_data)
@@ -1876 +1882 @@
                 self._plot_residuals(page_id=page_id, data=data, fid=fid,
                                       index=index, weight=weight)
-        msg = "Computation  completed!"
-        wx.PostEvent(self.parent, StatusEvent(status=msg, type="stop"))
+
+        if not number_finite:
+            logger.error("Using the present parameters the model does not return any finite value. ")
+            msg = "Computing Error: Model did not return any finite value."
+            wx.PostEvent(self.parent, StatusEvent(status = msg, info="error"))
+        else:
+            msg = "Computation  completed!"
+            if number_finite != image.size:
+                msg += ' PROBLEM: For some Qx,Qy values the model returns non finite intensities!'
+                logger.error("For some Qx,Qy values the model returns non finite intensities.")
+            wx.PostEvent(self.parent, StatusEvent(status=msg, type="stop"))
 
     def _draw_model2D(self, model, page_id, qmin,

src/sas/sasgui/perspectives/fitting/models.py

@@ -156 +156 @@
     try:
         import compileall
-        compileall.compile_dir(dir=dir, ddir=dir, force=1,
+        compileall.compile_dir(dir=dir, ddir=dir, force=0,
                                quiet=report_problem)
     except:
@@ -163 +163 @@
 
 
-def _findModels(dir):
+def _find_models():
     """
     Find custom models
     """
     # List of plugin objects
-    dir = find_plugins_dir()
+    directory = find_plugins_dir()
     # Go through files in plug-in directory
-    if not os.path.isdir(dir):
-        msg = "SasView couldn't locate Model plugin folder %r." % dir
+    if not os.path.isdir(directory):
+        msg = "SasView couldn't locate Model plugin folder %r." % directory
         logger.warning(msg)
         return {}
 
-    plugin_log("looking for models in: %s" % str(dir))
-    #compile_file(dir)  #always recompile the folder plugin
-    logger.info("plugin model dir: %s" % str(dir))
+    plugin_log("looking for models in: %s" % str(directory))
+    # compile_file(directory)  #always recompile the folder plugin
+    logger.info("plugin model dir: %s" % str(directory))
 
     plugins = {}
-    for filename in os.listdir(dir):
+    for filename in os.listdir(directory):
         name, ext = os.path.splitext(filename)
         if ext == '.py' and not name == '__init__':
-            path = os.path.abspath(os.path.join(dir, filename))
+            path = os.path.abspath(os.path.join(directory, filename))
             try:
                 model = load_custom_model(path)
@@ -193 +193 @@
                 plugin_log(msg)
                 logger.warning("Failed to load plugin %r. See %s for details"
-                                % (path, PLUGIN_LOG))
-            
+                               % (path, PLUGIN_LOG))
+
     return plugins
 
@@ -264 +264 @@
         temp = {}
         if self.is_changed():
-            return  _findModels(dir)
+            return  _find_models()
         logger.info("plugin model : %s" % str(temp))
         return temp
@@ -339 +339 @@
         """
         self.plugins = []
-        new_plugins = _findModels(dir)
+        new_plugins = _find_models()
         for name, plug in  new_plugins.iteritems():
             for stored_name, stored_plug in self.stored_plugins.iteritems():

src/sas/sasgui/perspectives/fitting/model_thread.py

@@ -71 +71 @@
                     (self.data.qy_data * self.data.qy_data))
 
-        # For theory, qmax is based on 1d qmax 
+        # For theory, qmax is based on 1d qmax
         # so that must be mulitified by sqrt(2) to get actual max for 2d
         index_model = (self.qmin <= radius) & (radius <= self.qmax)
@@ -91 +91 @@
                 self.data.qy_data[index_model]
             ])
-        output = np.zeros(len(self.data.qx_data))
+        # Initialize output to NaN so masked elements do not get plotted.
+        output = np.empty_like(self.data.qx_data)
         # output default is None
         # This method is to distinguish between masked
         #point(nan) and data point = 0.
-        output = output / output
+        output[:] = np.NaN
         # set value for self.mask==True, else still None to Plottools
         output[index_model] = value
@@ -198 +199 @@
             output[index] = self.model.evalDistribution(self.data.x[index])
 
+        x=self.data.x[index]
+        y=output[index]
         sq_values = None
         pq_values = None
-        s_model = None
-        p_model = None
         if isinstance(self.model, MultiplicationModel):
             s_model = self.model.s_model
             p_model = self.model.p_model
-        elif hasattr(self.model, "get_composition_models"):
-            p_model, s_model = self.model.get_composition_models()
-
-        if p_model is not None and s_model is not None:
-            sq_values = np.zeros((len(self.data.x)))
-            pq_values = np.zeros((len(self.data.x)))
-            sq_values[index] = s_model.evalDistribution(self.data.x[index])
-            pq_values[index] = p_model.evalDistribution(self.data.x[index])
+            sq_values = s_model.evalDistribution(x)
+            pq_values = p_model.evalDistribution(x)
+        elif hasattr(self.model, "calc_composition_models"):
+            results = self.model.calc_composition_models(x)
+            if results is not None:
+                sq_values = results[0]
+                pq_values = results[1]
+
 
         elapsed = time.time() - self.starttime
 
-        self.complete(x=self.data.x[index], y=output[index],
+        self.complete(x=x, y=y,
                       page_id=self.page_id,
                       state=self.state,