Changeset 6a455cd3 in sasview for src/sas/sasgui/perspectives/fitting

Timestamp:

Jul 24, 2017 8:27:05 AM (7 years ago)

Author:

krzywon

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, magnetic_scatt, release-4.2.2, ticket-1009, ticket-1094-headless, ticket-1242-2d-resolution, ticket-1243, ticket-1249, ticket885, unittest-saveload

Children:

146c669

Parents:

b61bd57 (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 4_1_issues

# Conflicts:
# docs/sphinx-docs/source/conf.py
# src/sas/sascalc/dataloader/readers/cansas_reader.py
# src/sas/sasgui/guiframe/documentation_window.py
# src/sas/sasgui/perspectives/fitting/models.py

Location:

src/sas/sasgui/perspectives/fitting

Files:

• basepage.py (modified) (31 diffs)
• batchfitpage.py (modified) (5 diffs)
• fitpage.py (modified) (17 diffs)
• fitting.py (modified) (45 diffs)
• media/plugin.rst (modified) (1 diff)
• model_thread.py (modified) (9 diffs)
• models.py (modified) (8 diffs)
• pagestate.py (modified) (12 diffs)
• report_dialog.py (modified) (1 diff)
• utils.py (modified) (2 diffs)
• fitpanel.py (modified) (3 diffs)

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

@@ -2 +2 @@
 Base Page for fitting
 """
+from __future__ import print_function
+
 import sys
 import os
 import wx
-import numpy
+import numpy as np
 import time
 import copy
@@ -34 +36 @@
 from sas.sasgui.guiframe.documentation_window import DocumentationWindow
 
+logger = logging.getLogger(__name__)
 
 (PageInfoEvent, EVT_PAGE_INFO) = wx.lib.newevent.NewEvent()
@@ -100 +103 @@
         self.graph_id = None
         # Q range for data set
-        self.qmin_data_set = numpy.inf
+        self.qmin_data_set = np.inf
         self.qmax_data_set = None
         self.npts_data_set = 0
@@ -251 +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):
@@ -278 +281 @@
 
         """
-        x = numpy.linspace(start=self.qmin_x, stop=self.qmax_x,
+        x = np.linspace(start=self.qmin_x, stop=self.qmax_x,
                            num=self.npts_x, endpoint=True)
         self.data = Data1D(x=x)
@@ -295 +298 @@
         """
         if self.qmin_x >= 1.e-10:
-            qmin = numpy.log10(self.qmin_x)
+            qmin = np.log10(self.qmin_x)
         else:
             qmin = -10.
 
         if self.qmax_x <= 1.e10:
-            qmax = numpy.log10(self.qmax_x)
+            qmax = np.log10(self.qmax_x)
         else:
             qmax = 10.
 
-        x = numpy.logspace(start=qmin, stop=qmax,
+        x = np.logspace(start=qmin, stop=qmax,
                            num=self.npts_x, endpoint=True, base=10.0)
         self.data = Data1D(x=x)
@@ -341 +344 @@
         qstep = self.npts_x
 
-        x = numpy.linspace(start=xmin, stop=xmax, num=qstep, endpoint=True)
-        y = numpy.linspace(start=ymin, stop=ymax, num=qstep, endpoint=True)
+        x = np.linspace(start=xmin, stop=xmax, num=qstep, endpoint=True)
+        y = np.linspace(start=ymin, stop=ymax, num=qstep, endpoint=True)
         # use data info instead
-        new_x = numpy.tile(x, (len(y), 1))
-        new_y = numpy.tile(y, (len(x), 1))
+        new_x = np.tile(x, (len(y), 1))
+        new_y = np.tile(y, (len(x), 1))
         new_y = new_y.swapaxes(0, 1)
         # all data reuire now in 1d array
         qx_data = new_x.flatten()
         qy_data = new_y.flatten()
-        q_data = numpy.sqrt(qx_data * qx_data + qy_data * qy_data)
+        q_data = np.sqrt(qx_data * qx_data + qy_data * qy_data)
         # set all True (standing for unmasked) as default
-        mask = numpy.ones(len(qx_data), dtype=bool)
+        mask = np.ones(len(qx_data), dtype=bool)
         # store x and y bin centers in q space
         x_bins = x
@@ -358 +361 @@
 
         self.data.source = Source()
-        self.data.data = numpy.ones(len(mask))
-        self.data.err_data = numpy.ones(len(mask))
+        self.data.data = np.ones(len(mask))
+        self.data.err_data = np.ones(len(mask))
         self.data.qx_data = qx_data
         self.data.qy_data = qy_data
@@ -656 +659 @@
         # It seems MAC needs wxCallAfter
         if event.GetId() == GUIFRAME_ID.COPYEX_ID:
-            print "copy excel"
+            print("copy excel")
             wx.CallAfter(self.get_copy_excel)
         elif event.GetId() == GUIFRAME_ID.COPYLAT_ID:
-            print "copy latex"
+            print("copy latex")
             wx.CallAfter(self.get_copy_latex)
         else:
@@ -782 +785 @@
                 except Exception:
                     # Skip non-data lines
-                    logging.error(traceback.format_exc())
-            return numpy.array(angles), numpy.array(weights)
+                    logger.error(traceback.format_exc())
+            return np.array(angles), np.array(weights)
         except:
             raise
@@ -1304 +1307 @@
                     [state.values, state.weights]
             except Exception:
-                logging.error(traceback.format_exc())
+                logger.error(traceback.format_exc())
             selection = self._find_polyfunc_selection(disp_model)
             for list in self.fittable_param:
@@ -1321 +1324 @@
                             list[6].Disable()
                         except Exception:
-                            logging.error(traceback.format_exc())
+                            logger.error(traceback.format_exc())
             # For array, disable all fixed params
             if selection == 1:
@@ -1330 +1333 @@
                             item[2].Disable()
                         except Exception:
-                            logging.error(traceback.format_exc())
+                            logger.error(traceback.format_exc())
 
     def _selectDlg(self):
@@ -1449 +1452 @@
                 self.state_change = True
                 self._draw_model()
-                # Time delay has been introduced to prevent _handle error
-                # on Windows
-                # This part of code is executed when model is selected and
-                # it's parameters are changed (with respect to previously
-                # selected model). There are two Iq evaluations occuring one
-                # after another and therefore there may be compilation error
-                # if model is calculated for the first time.
-                # This seems to be Windows only issue - haven't tested on Linux
-                # though.The proper solution (other than time delay) requires
-                # more fundemental code refatoring
-                # Wojtek P. Nov 7, 2016
-                if not ON_MAC:
-                    time.sleep(0.1)
                 self.Refresh()
 
-        # logging.info("is_modified flag set to %g",is_modified)
+        # logger.info("is_modified flag set to %g",is_modified)
         return is_modified
 
@@ -1569 +1559 @@
             self.save_current_state()
         except Exception:
-            logging.error(traceback.format_exc())
+            logger.error(traceback.format_exc())
 
         return flag, is_modified
@@ -2120 +2110 @@
         for data in self.data_list:
             # q value from qx and qy
-            radius = numpy.sqrt(data.qx_data * data.qx_data +
+            radius = np.sqrt(data.qx_data * data.qx_data +
                                 data.qy_data * data.qy_data)
             # get unmasked index
@@ -2126 +2116 @@
                          (radius <= float(self.qmax.GetValue()))
             index_data = (index_data) & (data.mask)
-            index_data = (index_data) & (numpy.isfinite(data.data))
+            index_data = (index_data) & (np.isfinite(data.data))
 
             if len(index_data[index_data]) < 10:
@@ -2161 +2151 @@
             index_data = (float(self.qmin.GetValue()) <= radius) & \
                          (radius <= float(self.qmax.GetValue()))
-            index_data = (index_data) & (numpy.isfinite(data.y))
+            index_data = (index_data) & (np.isfinite(data.y))
 
             if len(index_data[index_data]) < 5:
@@ -2233 +2223 @@
 
                 # Check that min is less than max
-                low = -numpy.inf if min_str == "" else float(min_str)
-                high = numpy.inf if max_str == "" else float(max_str)
+                low = -np.inf if min_str == "" else float(min_str)
+                high = np.inf if max_str == "" else float(max_str)
                 if high < low:
                     min_ctrl.SetBackgroundColour("pink")
@@ -2384 +2374 @@
                     self.model.set_dispersion(p, disp_model)
                 except Exception:
-                    logging.error(traceback.format_exc())
+                    logger.error(traceback.format_exc())
 
         # save state into
@@ -2499 +2489 @@
             self.Refresh()
         except Exception:
-            logging.error(traceback.format_exc())
+            logger.error(traceback.format_exc())
             # Error msg
             msg = "Error occurred:"
@@ -2600 +2590 @@
                 del self.state.model._persistency_dict[name.split('.')[0]]
         except Exception:
-            logging.error(traceback.format_exc())
+            logger.error(traceback.format_exc())
 
     def _lay_out(self):
@@ -2609 +2599 @@
             Layout is called after fitting.
         """
-        self._sleep4sec()
         self.Layout()
         return
-
-    def _sleep4sec(self):
-        """
-            sleep for 1 sec only applied on Mac
-            Note: This 1sec helps for Mac not to crash on self.
-            Layout after self._draw_model
-        """
-        if ON_MAC:
-            time.sleep(1)
 
     def _find_polyfunc_selection(self, disp_func=None):
@@ -2654 +2634 @@
             self.qmin_x = data_min
             self.qmax_x = math.sqrt(x * x + y * y)
-            # self.data.mask = numpy.ones(len(self.data.data),dtype=bool)
+            # self.data.mask = np.ones(len(self.data.data),dtype=bool)
             # check smearing
             if not self.disable_smearer.GetValue():
@@ -2742 +2722 @@
             except Exception:
                 # Not for control panels
-                logging.error(traceback.format_exc())
+                logger.error(traceback.format_exc())
         # Make sure the resduals plot goes to the last
         if res_item is not None:
@@ -3075 +3055 @@
                     disfunc = str(item[7].GetValue())
             except Exception:
-                logging.error(traceback.format_exc())
+                logger.error(traceback.format_exc())
 
             # 2D
@@ -3118 +3098 @@
                         disfunc += ' ' + str(weight)
             except Exception:
-                logging.error(traceback.format_exc())
+                logger.error(traceback.format_exc())
             content += name + ',' + str(check) + ',' + value + disfunc + ',' + \
                        bound_lo + ',' + bound_hi + ':'
@@ -3366 +3346 @@
 
             if value[1] == 'array':
-                pd_vals = numpy.array(value[2])
-                pd_weights = numpy.array(value[3])
+                pd_vals = np.array(value[2])
+                pd_weights = np.array(value[3])
                 if len(pd_vals) == 0 or len(pd_vals) != len(pd_weights):
                     msg = ("bad array distribution parameters for %s"
@@ -3389 +3369 @@
 
         except Exception:
-            logging.error(traceback.format_exc())
-            print "Error in BasePage._paste_poly_help: %s" % \
-                  sys.exc_info()[1]
+            logger.error(traceback.format_exc())
+            print("Error in BasePage._paste_poly_help: %s" % \
+                  sys.exc_info()[1])
 
     def _set_disp_cb(self, isarray, item):
@@ -3420 +3400 @@
             Moveit; This method doesn't belong here
         """
-        print "BasicPage.update_pinhole_smear was called: skipping"
+        print("BasicPage.update_pinhole_smear was called: skipping")
         return
 
@@ -3596 +3576 @@
         # check model type to show sizer
         if self.model is not None:
-            print "_set_model_sizer_selection: disabled."
+            print("_set_model_sizer_selection: disabled.")
             # self._set_model_sizer_selection(self.model)
 

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

@@ -200 +200 @@
 #         self.state.formfactorcombobox = self.formfactorbox.GetCurrentSelection()
 #       
-#         if self.model != None:
+#         if self.model is not None:
 #             self._set_copy_flag(True)
 #             self._set_paste_flag(True)
-#             if self.data != None:
+#             if self.data is not None:
 #                 self._set_bookmark_flag(False)
 #                 self._keep.Enable(False)
@@ -225 +225 @@
 # 
 #             
-#         if event != None:
+#         if event is not None:
 #             ## post state to fit panel
 #             new_event = PageInfoEvent(page = self)
@@ -254 +254 @@
 #         is_modified = False
 # 
-#         if self.model != None:           
+#         if self.model is not None:
 #             ##Check the values
 #             self._check_value_enter( self.fittable_param)
@@ -291 +291 @@
 #         else:
 #             #self.btFit.Enable(True)
-#             if self._is_2D() and  self.data != None:
+#             if self._is_2D() and  self.data is not None:
 #                 self.btEditMask.Enable(True)
 # 
@@ -335 +335 @@
 #             self._set_save_flag(False)
 #         else:
-#             if self.model != None:
+#             if self.model is not None:
 #                 self._set_bookmark_flag(False)
 #                 self._keep.Enable(False)

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

@@ -6 +6 @@
 import wx
 import wx.lib.newevent
-import numpy
+import numpy as np
 import copy
 import math
@@ -1115 +1115 @@
             if item.GetValue():
                 if button_list.index(item) == 0:
-                    flag = 0  # dy = numpy.ones_like(dy_data)
+                    flag = 0  # dy = np.ones_like(dy_data)
                 elif button_list.index(item) == 1:
                     flag = 1  # dy = dy_data
                 elif button_list.index(item) == 2:
-                    flag = 2  # dy = numpy.sqrt(numpy.abs(data))
+                    flag = 2  # dy = np.sqrt(np.abs(data))
                 elif button_list.index(item) == 3:
-                    flag = 3  # dy = numpy.abs(data)
+                    flag = 3  # dy = np.abs(data)
                 break
         return flag
@@ -1426 +1426 @@
         key = event.GetKeyCode()
         length = len(self.data.x)
-        indx = (numpy.abs(self.data.x - x_data)).argmin()
+        indx = (np.abs(self.data.x - x_data)).argmin()
         # return array.flat[idx]
         if key == wx.WXK_PAGEUP or key == wx.WXK_NUMPAD_PAGEUP:
@@ -1481 +1481 @@
                     self.enable2D:
                 # set mask
-                radius = numpy.sqrt(self.data.qx_data * self.data.qx_data +
+                radius = np.sqrt(self.data.qx_data * self.data.qx_data +
                                     self.data.qy_data * self.data.qy_data)
                 index_data = ((self.qmin_x <= radius) & (radius <= self.qmax_x))
                 index_data = (index_data) & (self.data.mask)
-                index_data = (index_data) & (numpy.isfinite(self.data.data))
+                index_data = (index_data) & (np.isfinite(self.data.data))
                 if len(index_data[index_data]) < 10:
                     msg = "Cannot Plot :No or too little npts in"
@@ -1602 +1602 @@
                 and data.dqx_data.any() != 0:
                 self.smear_type = "Pinhole2d"
-                self.dq_l = format_number(numpy.average(data.dqx_data))
-                self.dq_r = format_number(numpy.average(data.dqy_data))
+                self.dq_l = format_number(np.average(data.dqx_data))
+                self.dq_r = format_number(np.average(data.dqy_data))
                 return
             else:
                 return
         # check if it is pinhole smear and get min max if it is.
-        if data.dx is not None and numpy.any(data.dx):
+        if data.dx is not None and np.any(data.dx):
             self.smear_type = "Pinhole"
             self.dq_l = data.dx[0]
@@ -1616 +1616 @@
         elif data.dxl is not None or data.dxw is not None:
             self.smear_type = "Slit"
-            if data.dxl is not None and numpy.all(data.dxl, 0):
+            if data.dxl is not None and np.all(data.dxl, 0):
                 self.dq_l = data.dxl[0]
-            if data.dxw is not None and numpy.all(data.dxw, 0):
+            if data.dxw is not None and np.all(data.dxw, 0):
                 self.dq_r = data.dxw[0]
         # return self.smear_type,self.dq_l,self.dq_r
@@ -1812 +1812 @@
         if not flag:
             self.onSmear(None)
-
-    def _mac_sleep(self, sec=0.2):
-        """
-        Give sleep to MAC
-        """
-        if self.is_mac:
-            time.sleep(sec)
 
     def get_view_mode(self):
@@ -1925 +1918 @@
                 self.default_mask = copy.deepcopy(self.data.mask)
                 if self.data.err_data is not None \
-                        and numpy.any(self.data.err_data):
+                        and np.any(self.data.err_data):
                     di_flag = True
                 if self.data.dqx_data is not None \
-                        and numpy.any(self.data.dqx_data):
+                        and np.any(self.data.dqx_data):
                     dq_flag = True
             else:
                 self.slit_smearer.Enable(True)
                 self.pinhole_smearer.Enable(True)
-                if self.data.dy is not None and numpy.any(self.data.dy):
+                if self.data.dy is not None and np.any(self.data.dy):
                     di_flag = True
-                if self.data.dx is not None and numpy.any(self.data.dx):
+                if self.data.dx is not None and np.any(self.data.dx):
                     dq_flag = True
-                elif self.data.dxl is not None and numpy.any(self.data.dxl):
+                elif self.data.dxl is not None and np.any(self.data.dxl):
                     dq_flag = True
 
@@ -2071 +2064 @@
         if self.data.__class__.__name__ == "Data2D" or \
                         self.enable2D:
-            radius = numpy.sqrt(self.data.qx_data * self.data.qx_data +
+            radius = np.sqrt(self.data.qx_data * self.data.qx_data +
                                 self.data.qy_data * self.data.qy_data)
             index_data = (self.qmin_x <= radius) & (radius <= self.qmax_x)
             index_data = (index_data) & (self.data.mask)
-            index_data = (index_data) & (numpy.isfinite(self.data.data))
+            index_data = (index_data) & (np.isfinite(self.data.data))
             npts2fit = len(self.data.data[index_data])
         else:
@@ -2108 +2101 @@
         # make sure stop button to fit button all the time
         self._on_fit_complete()
-        if out is None or not numpy.isfinite(chisqr):
+        if out is None or not np.isfinite(chisqr):
             raise ValueError, "Fit error occured..."
 
@@ -2119 +2112 @@
 
         # Check if chi2 is finite
-        if chisqr is not None and numpy.isfinite(chisqr):
+        if chisqr is not None and np.isfinite(chisqr):
             # format chi2
             chi2 = format_number(chisqr, True)
@@ -2171 +2164 @@
 
                         if cov[ind] is not None:
-                            if numpy.isfinite(float(cov[ind])):
+                            if np.isfinite(float(cov[ind])):
                                 val_err = format_number(cov[ind], True)
                                 item[4].SetForegroundColour(wx.BLACK)
@@ -2192 +2185 @@
         self.save_current_state()
 
-        if not self.is_mac:
-            self.Layout()
-            self.Refresh()
-        self._mac_sleep(0.1)
         # plot model ( when drawing, do not update chisqr value again)
         self._draw_model(update_chisqr=False, source='fit')
@@ -2295 +2284 @@
             self.smear_type = 'Pinhole2d'
             len_data = len(data.data)
-            data.dqx_data = numpy.zeros(len_data)
-            data.dqy_data = numpy.zeros(len_data)
+            data.dqx_data = np.zeros(len_data)
+            data.dqy_data = np.zeros(len_data)
         else:
             self.smear_type = 'Pinhole'
             len_data = len(data.x)
-            data.dx = numpy.zeros(len_data)
+            data.dx = np.zeros(len_data)
             data.dxl = None
             data.dxw = None
@@ -2473 +2462 @@
         try:
             self.dxl = float(self.smear_slit_height.GetValue())
-            data.dxl = self.dxl * numpy.ones(data_len)
+            data.dxl = self.dxl * np.ones(data_len)
             self.smear_slit_height.SetBackgroundColour(wx.WHITE)
         except:
             self.dxl = None
-            data.dxl = numpy.zeros(data_len)
+            data.dxl = np.zeros(data_len)
             if self.smear_slit_height.GetValue().lstrip().rstrip() != "":
                 self.smear_slit_height.SetBackgroundColour("pink")
@@ -2486 +2475 @@
             self.dxw = float(self.smear_slit_width.GetValue())
             self.smear_slit_width.SetBackgroundColour(wx.WHITE)
-            data.dxw = self.dxw * numpy.ones(data_len)
+            data.dxw = self.dxw * np.ones(data_len)
         except:
             self.dxw = None
-            data.dxw = numpy.zeros(data_len)
+            data.dxw = np.zeros(data_len)
             if self.smear_slit_width.GetValue().lstrip().rstrip() != "":
                 self.smear_slit_width.SetBackgroundColour("pink")
@@ -2616 +2605 @@
             if event is None:
                 output = "-"
-            elif not numpy.isfinite(event.output):
+            elif not np.isfinite(event.output):
                 output = "-"
             else:

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

@@ -11 +11 @@
 #copyright 2009, University of Tennessee
 ################################################################################
+from __future__ import print_function
+
 import re
 import sys
@@ -16 +18 @@
 import wx
 import logging
-import numpy
+import numpy as np
 import time
 from copy import deepcopy
@@ -48 +50 @@
 
 from . import models
+
+logger = logging.getLogger(__name__)
 
 MAX_NBR_DATA = 4
@@ -119 +123 @@
         self.page_finder = {}
         # Log startup
-        logging.info("Fitting plug-in started")
+        logger.info("Fitting plug-in started")
         self.batch_capable = self.get_batch_capable()
 
@@ -300 +304 @@
         Make new model
         """
-        if self.new_model_frame != None:
+        if self.new_model_frame is not None:
             self.new_model_frame.Show(False)
             self.new_model_frame.Show(True)
@@ -346 +350 @@
                                 page.formfactorbox.SetLabel(current_val)
         except:
-            logging.error("update_custom_combo: %s", sys.exc_value)
+            logger.error("update_custom_combo: %s", sys.exc_value)
 
     def set_edit_menu(self, owner):
@@ -384 +388 @@
         help for setting list of the edit model menu labels
         """
-        if menu == None:
+        if menu is None:
             menu = self.edit_custom_model
         list_fnames = os.listdir(models.find_plugins_dir())
@@ -439 +443 @@
             wx.PostEvent(self.parent, StatusEvent(status=msg))
 
-        if page != None:
+        if page is not None:
             return set_focus_page(page)
         if caption == "Const & Simul Fit":
@@ -586 +590 @@
                 msg = "Fitting: cannot deal with the theory received"
                 evt = StatusEvent(status=msg, info="error")
-                logging.error("set_theory " + msg + "\n" + str(sys.exc_value))
+                logger.error("set_theory " + msg + "\n" + str(sys.exc_value))
                 wx.PostEvent(self.parent, evt)
 
@@ -632 +636 @@
             state = self.temp_state[self.state_index]
             #panel state should have model selection to set_state
-            if state.formfactorcombobox != None:
+            if state.formfactorcombobox is not None:
                 #set state
                 data = self.parent.create_gui_data(state.data)
@@ -875 +879 @@
                 enable1D=enable1D, enable2D=enable2D,
                 qmin=qmin, qmax=qmax, weight=weight)
-
-    def _mac_sleep(self, sec=0.2):
-        """
-        Give sleep to MAC
-        """
-        if ON_MAC:
-            time.sleep(sec)
 
     def draw_model(self, model, page_id, data=None, smearer=None,
@@ -1021 +1018 @@
                 return False
         ## If a thread is already started, stop it
-        #if self.calc_fit!= None and self.calc_fit.isrunning():
+        #if self.calc_fitis not None and self.calc_fit.isrunning():
         #    self.calc_fit.stop()
         msg = "Fitting is in progress..."
@@ -1030 +1027 @@
                                 manager=self,
                                 improvement_delta=0.1)
-        self._mac_sleep(0.2)
 
         # batch fit
@@ -1112 +1108 @@
             page = self.fit_panel.add_empty_page()
             # add data associated to the page created
-            if page != None:
+            if page is not None:
                 evt = StatusEvent(status="Page Created", info="info")
                 wx.PostEvent(self.parent, evt)
@@ -1131 +1127 @@
         page = self.fit_panel.set_data(data)
         # page could be None when loading state files
-        if page == None:
+        if page is None:
             return page
         #append Data1D to the panel containing its theory
@@ -1199 +1195 @@
         """
         # case that uid is not specified
-        if uid == None:
+        if uid is None:
             for page_id in self.page_finder.keys():
                 self.page_finder[page_id].schedule_tofit(value)
@@ -1222 +1218 @@
             for item in param:
                 ## check if constraint
-                if item[0] != None and item[1] != None:
+                if item[0] is not None and item[1] is not None:
                     listOfConstraint.append((item[0], item[1]))
         new_model = model
@@ -1237 +1233 @@
         """
         panel = self.plot_panel
-        if panel == None:
+        if panel is None:
             raise ValueError, "Fitting:_onSelect: NonType panel"
         Plugin.on_perspective(self, event=event)
@@ -1259 +1255 @@
         """
         """
-        print "update_fit result", result
+        print("update_fit result", result)
 
     def _batch_fit_complete(self, result, pars, page_id,
@@ -1270 +1266 @@
         :param elapsed: time spent at the fitting level
         """
-        self._mac_sleep(0.2)
         uid = page_id[0]
         if uid in self.fit_thread_list.keys():
@@ -1332 +1327 @@
                     new_theory = copy_data.data
                     new_theory[res.index] = res.theory
-                    new_theory[res.index == False] = numpy.nan
+                    new_theory[res.index == False] = np.nan
                     correct_result = True
                 #get all fittable parameters of the current model
@@ -1341 +1336 @@
                         param_list.remove(param)
                 if not correct_result or res.fitness is None or \
-                    not numpy.isfinite(res.fitness) or \
-                    numpy.any(res.pvec == None) or not \
-                    numpy.all(numpy.isfinite(res.pvec)):
+                    not np.isfinite(res.fitness) or \
+                        np.any(res.pvec is None) or not \
+                        np.all(np.isfinite(res.pvec)):
                     data_name = str(None)
                     if data is not None:
@@ -1352 +1347 @@
                     msg += "Data %s and Model %s did not fit.\n" % (data_name,
                                                                     model_name)
-                    ERROR = numpy.NAN
+                    ERROR = np.NAN
                     cell = BatchCell()
                     cell.label = res.fitness
@@ -1366 +1361 @@
                             batch_inputs["error on %s" % str(param)].append(ERROR)
                 else:
-                    # TODO: Why sometimes res.pvec comes with numpy.float64?
+                    # TODO: Why sometimes res.pvec comes with np.float64?
                     # probably from scipy lmfit
-                    if res.pvec.__class__ == numpy.float64:
+                    if res.pvec.__class__ == np.float64:
                         res.pvec = [res.pvec]
 
@@ -1464 +1459 @@
         cell.value = index
 
-        if theory_data != None:
+        if theory_data is not None:
             #Suucessful fit
             theory_data.id = wx.NewId()
@@ -1520 +1515 @@
             page_id = []
         ## fit more than 1 model at the same time
-        self._mac_sleep(0.2)
         try:
             index = 0
@@ -1533 +1527 @@
                 fit_msg = res.mesg
                 if res.fitness is None or \
-                    not numpy.isfinite(res.fitness) or \
-                    numpy.any(res.pvec == None) or \
-                    not numpy.all(numpy.isfinite(res.pvec)):
+                    not np.isfinite(res.fitness) or \
+                        np.any(res.pvec is None) or \
+                    not np.all(np.isfinite(res.pvec)):
                     fit_msg += "\nFitting did not converge!!!"
                     wx.CallAfter(self._update_fit_button, page_id)
                 else:
                     #set the panel when fit result are float not list
-                    if res.pvec.__class__ == numpy.float64:
+                    if res.pvec.__class__ == np.float64:
                         pvec = [res.pvec]
                     else:
                         pvec = res.pvec
-                    if res.stderr.__class__ == numpy.float64:
+                    if res.stderr.__class__ == np.float64:
                         stderr = [res.stderr]
                     else:
@@ -1552 +1546 @@
                     #(CallAfter is important to MAC)
                     try:
-                        #if res != None:
+                        #if res is not None:
                         wx.CallAfter(cpage.onsetValues, res.fitness,
                                      res.param_list,
@@ -1595 +1589 @@
         """
         event.Skip()
-        if self.menu1 == None:
+        if self.menu1 is None:
             return
         menu_item = self.menu1.FindItemById(self.id_reset_flag)
@@ -1654 +1648 @@
         caption = evt.caption
         enable_smearer = evt.enable_smearer
-        if model == None:
+        if model is None:
             return
         if uid not in self.page_finder.keys():
@@ -1692 +1686 @@
         if dy is None:
             new_plot.is_data = False
-            new_plot.dy = numpy.zeros(len(y))
+            new_plot.dy = np.zeros(len(y))
             # If this is a theory curve, pick the proper symbol to make it a curve
             new_plot.symbol = GUIFRAME_ID.CURVE_SYMBOL_NUM
@@ -1706 +1700 @@
         new_plot.title = data.name
         new_plot.group_id = data.group_id
-        if new_plot.group_id == None:
+        if new_plot.group_id is None:
             new_plot.group_id = data.group_id
         new_plot.id = data_id
@@ -1740 +1734 @@
             @param unsmeared_error: data error, rescaled to unsmeared model
         """
-        try:
-            numpy.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,
+            
+        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):
@@ -1806 +1805 @@
         Handle exception from calculator by posting it as an error.
         """
-        logging.error("".join(traceback.format_exception(etype, value, tb)))
+        logger.error("".join(traceback.format_exception(etype, value, tb)))
         msg = traceback.format_exception(etype, value, tb, limit=1)
         evt = StatusEvent(status="".join(msg), type="stop", info="error")
@@ -1825 +1824 @@
         that can be plot.
         """
-        numpy.nan_to_num(image)
+        number_finite = np.count_nonzero(np.isfinite(image)) 
+        np.nan_to_num(image)
         new_plot = Data2D(image=image, err_image=data.err_data)
         new_plot.name = model.name + '2d'
@@ -1883 +1883 @@
                 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,
@@ -2010 +2019 @@
         chisqr = None
         #to compute chisq make sure data has valid data
-        # return None if data == None
-        if not check_data_validity(data_copy) or data_copy == None:
+        # return None if data is None
+        if not check_data_validity(data_copy) or data_copy is None:
             return chisqr
 
         # Get data: data I, theory I, and data dI in order
         if data_copy.__class__.__name__ == "Data2D":
-            if index == None:
-                index = numpy.ones(len(data_copy.data), dtype=bool)
-            if weight != None:
+            if index is None:
+                index = np.ones(len(data_copy.data), dtype=bool)
+            if weight is not None:
                 data_copy.err_data = weight
             # get rid of zero error points
             index = index & (data_copy.err_data != 0)
-            index = index & (numpy.isfinite(data_copy.data))
+            index = index & (np.isfinite(data_copy.data))
             fn = data_copy.data[index]
             theory_data = self.page_finder[page_id].get_theory_data(fid=data_copy.id)
-            if theory_data == None:
+            if theory_data is None:
                 return chisqr
             gn = theory_data.data[index]
@@ -2031 +2040 @@
         else:
             # 1 d theory from model_thread is only in the range of index
-            if index == None:
-                index = numpy.ones(len(data_copy.y), dtype=bool)
-            if weight != None:
+            if index is None:
+                index = np.ones(len(data_copy.y), dtype=bool)
+            if weight is not None:
                 data_copy.dy = weight
-            if data_copy.dy == None or data_copy.dy == []:
-                dy = numpy.ones(len(data_copy.y))
+            if data_copy.dy is None or data_copy.dy == []:
+                dy = np.ones(len(data_copy.y))
             else:
                 ## Set consistently w/AbstractFitengine:
@@ -2045 +2054 @@
 
             theory_data = self.page_finder[page_id].get_theory_data(fid=data_copy.id)
-            if theory_data == None:
+            if theory_data is None:
                 return chisqr
             gn = theory_data.y
@@ -2054 +2063 @@
             res = (fn - gn) / en
         except ValueError:
-            print "Unmatch lengths %s, %s, %s" % (len(fn), len(gn), len(en))
+            print("Unmatch lengths %s, %s, %s" % (len(fn), len(gn), len(en)))
             return
 
-        residuals = res[numpy.isfinite(res)]
+        residuals = res[np.isfinite(res)]
         # get chisqr only w/finite
-        chisqr = numpy.average(residuals * residuals)
+        chisqr = np.average(residuals * residuals)
 
         self._plot_residuals(page_id=page_id, data=data_copy,
@@ -2088 +2097 @@
             theory_data = self.page_finder[page_id].get_theory_data(fid=data_copy.id)
             gn = theory_data.data
-            if weight == None:
+            if weight is None:
                 en = data_copy.err_data
             else:
@@ -2096 +2105 @@
             residuals.qy_data = data_copy.qy_data
             residuals.q_data = data_copy.q_data
-            residuals.err_data = numpy.ones(len(residuals.data))
+            residuals.err_data = np.ones(len(residuals.data))
             residuals.xmin = min(residuals.qx_data)
             residuals.xmax = max(residuals.qx_data)
@@ -2109 +2118 @@
         else:
             # 1 d theory from model_thread is only in the range of index
-            if data_copy.dy == None or data_copy.dy == []:
-                dy = numpy.ones(len(data_copy.y))
+            if data_copy.dy is None or data_copy.dy == []:
+                dy = np.ones(len(data_copy.y))
             else:
-                if weight == None:
-                    dy = numpy.ones(len(data_copy.y))
+                if weight is None:
+                    dy = np.ones(len(data_copy.y))
                 ## Set consitently w/AbstractFitengine:
                 ## But this should be corrected later.
@@ -2132 +2141 @@
                 residuals.y = (fn - gn[index]) / en
             residuals.x = data_copy.x[index]
-            residuals.dy = numpy.ones(len(residuals.y))
+            residuals.dy = np.ones(len(residuals.y))
             residuals.dx = None
             residuals.dxl = None
@@ -2150 +2159 @@
         ##group_id specify on which panel to plot this data
         group_id = self.page_finder[page_id].get_graph_id()
-        if group_id == None:
+        if group_id is None:
             group_id = data.group_id
         new_plot.group_id = "res" + str(group_id)

src/sas/sasgui/perspectives/fitting/media/plugin.rst

@@ -538 +538 @@
     sin, cos, tan, asin, acos, atan:
         Trigonometry functions and inverses, operating on radians.
-    sinh, cos, tanh, asinh, acosh, atanh:
+    sinh, cosh, tanh, asinh, acosh, atanh:
         Hyperbolic trigonometry functions.
     atan2(y,x):

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

@@ -4 +4 @@
 
 import time
-import numpy
+import numpy as np
 import math
 from sas.sascalc.data_util.calcthread import CalcThread
@@ -53 +53 @@
         self.starttime = time.time()
         # Determine appropriate q range
-        if self.qmin == None:
+        if self.qmin is None:
             self.qmin = 0
-        if self.qmax == None:
-            if self.data != None:
+        if self.qmax is None:
+            if self.data is not None:
                 newx = math.pow(max(math.fabs(self.data.xmax),
                                    math.fabs(self.data.xmin)), 2)
@@ -68 +68 @@
 
         # Define matrix where data will be plotted
-        radius = numpy.sqrt((self.data.qx_data * self.data.qx_data) + \
+        radius = np.sqrt((self.data.qx_data * self.data.qx_data) + \
                     (self.data.qy_data * self.data.qy_data))
 
@@ -75 +75 @@
         index_model = (self.qmin <= radius) & (radius <= self.qmax)
         index_model = index_model & self.data.mask
-        index_model = index_model & numpy.isfinite(self.data.data)
+        index_model = index_model & np.isfinite(self.data.data)
 
         if self.smearer is not None:
@@ -91 +91 @@
                 self.data.qy_data[index_model]
             ])
-        output = numpy.zeros(len(self.data.qx_data))
+        output = np.zeros(len(self.data.qx_data))
         # output default is None
         # This method is to distinguish between masked
@@ -163 +163 @@
         """
         self.starttime = time.time()
-        output = numpy.zeros((len(self.data.x)))
+        output = np.zeros((len(self.data.x)))
         index = (self.qmin <= self.data.x) & (self.data.x <= self.qmax)
 
@@ -175 +175 @@
                                                              self.qmax)
             mask = self.data.x[first_bin:last_bin+1]
-            unsmeared_output = numpy.zeros((len(self.data.x)))
+            unsmeared_output = np.zeros((len(self.data.x)))
             unsmeared_output[first_bin:last_bin+1] = self.model.evalDistribution(mask)
             self.smearer.model = self.model
@@ -183 +183 @@
             # Check that the arrays are compatible. If we only have a model but no data,
             # the length of data.y will be zero.
-            if isinstance(self.data.y, numpy.ndarray) and output.shape == self.data.y.shape:
-                unsmeared_data = numpy.zeros((len(self.data.x)))
-                unsmeared_error = numpy.zeros((len(self.data.x)))
+            if isinstance(self.data.y, np.ndarray) and output.shape == self.data.y.shape:
+                unsmeared_data = np.zeros((len(self.data.x)))
+                unsmeared_error = np.zeros((len(self.data.x)))
                 unsmeared_data[first_bin:last_bin+1] = self.data.y[first_bin:last_bin+1]\
                                                         * unsmeared_output[first_bin:last_bin+1]\
@@ -209 +209 @@
 
         if p_model is not None and s_model is not None:
-            sq_values = numpy.zeros((len(self.data.x)))
-            pq_values = numpy.zeros((len(self.data.x)))
+            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])

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

@@ -2 +2 @@
     Utilities to manage models
 """
+from __future__ import print_function
+
 import traceback
 import os
@@ -19 +21 @@
 from sasmodels.sasview_model import load_custom_model, load_standard_models
 from sas.sasgui.perspectives.fitting.fitpage import CUSTOM_MODEL
+
+logger = logging.getLogger(__name__)
 
 
@@ -140 +144 @@
         type, value, tb = sys.exc_info()
         if type is not None and issubclass(type, py_compile.PyCompileError):
-            print "Problem with", repr(value)
+            print("Problem with", repr(value))
             raise type, value, tb
         return 1
@@ -153 +157 @@
     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:
@@ -160 +164 @@
 
 
-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
-        logging.warning(msg)
+    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
-    logging.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)
@@ -189 +193 @@
                 msg += "\nwhile accessing model in %r" % path
                 plugin_log(msg)
-                logging.warning("Failed to load plugin %r. See %s for details"
-                                % (path, PLUGIN_LOG))
-            
+                logger.warning("Failed to load plugin %r. See %s for details"
+                               % (path, PLUGIN_LOG))
+
     return plugins
 
@@ -261 +265 @@
         temp = {}
         if self.is_changed():
-            temp =  _findModels(dir)
+            temp =  _findModels()
             self.last_time_dir_modified = time.time()
             return temp
-        logging.info("plugin model : %s" % str(temp))
+        logger.info("plugin model : %s" % str(temp))
         return temp
 
@@ -338 +342 @@
         """
         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/pagestate.py

@@ -18 +18 @@
 import copy
 import logging
-import numpy
+import numpy as np
 import traceback
 
@@ -33 +33 @@
 from sas.sascalc.dataloader.data_info import Data2D, Collimation, Detector
 from sas.sascalc.dataloader.data_info import Process, Aperture
+
+logger = logging.getLogger(__name__)
 
 # Information to read/write state as xml
@@ -395 +397 @@
                     msg = "Save state does not have enough information to load"
                     msg += " the all of the data."
-                    logging.warning(msg=msg)
+                    logger.warning(msg=msg)
             else:
                 self.formfactorcombobox = FIRST_FORM[self.categorycombobox]
@@ -410 +412 @@
         for fittable, name, value, _, uncert, lower, upper, units in params:
             if not value:
-                value = numpy.nan
+                value = np.nan
             if not uncert or uncert[1] == '' or uncert[1] == 'None':
                 uncert[0] = False
-                uncert[1] = numpy.nan
+                uncert[1] = np.nan
             if not upper or upper[1] == '' or upper[1] == 'None':
                 upper[0] = False
-                upper[1] = numpy.nan
+                upper[1] = np.nan
             if not lower or lower[1] == '' or lower[1] == 'None':
                 lower[0] = False
-                lower[1] = numpy.nan
+                lower[1] = np.nan
             if is_string:
                 p[name] = str(value)
@@ -449 +451 @@
                 lower = params.get(name + ".lower", '-inf')
                 units = params.get(name + ".units")
-                if std is not None and std is not numpy.nan:
+                if std is not None and std is not np.nan:
                     std = [True, str(std)]
                 else:
                     std = [False, '']
-                if lower is not None and lower is not numpy.nan:
+                if lower is not None and lower is not np.nan:
                     lower = [True, str(lower)]
                 else:
                     lower = [True, '-inf']
-                if upper is not None and upper is not numpy.nan:
+                if upper is not None and upper is not np.nan:
                     upper = [True, str(upper)]
                 else:
@@ -620 +622 @@
             except Exception:
                 msg = "Report string expected 'name: value' but got %r" % line
-                logging.error(msg)
+                logger.error(msg)
             if name.count("State created"):
                 repo_time = "" + value
@@ -662 +664 @@
                 except Exception:
                     msg = "While parsing 'data: ...'\n"
-                    logging.error(msg + traceback.format_exc())
+                    logger.error(msg + traceback.format_exc())
             if name == "model name ":
                 try:
@@ -678 +680 @@
                 except Exception:
                     msg = "While parsing 'Plotting Range: ...'\n"
-                    logging.error(msg + traceback.format_exc())
+                    logger.error(msg + traceback.format_exc())
         paramval = ""
         for lines in param_string.split(":"):
@@ -1037 +1039 @@
                     msg = "PageState.fromXML: Could not"
                     msg += " read timestamp\n %s" % sys.exc_value
-                    logging.error(msg)
+                    logger.error(msg)
 
             if entry is not None:
@@ -1077 +1079 @@
                             except Exception:
                                 base = "unable to load distribution %r for %s"
-                                logging.error(base % (value, parameter))
+                                logger.error(base % (value, parameter))
                                 continue
                         _disp_obj_dict = getattr(self, varname)
@@ -1099 +1101 @@
                                 msg = ("Error reading %r from %s %s\n"
                                        % (line, tagname, name))
-                                logging.error(msg + traceback.format_exc())
-                        dic[name] = numpy.array(value_list)
+                                logger.error(msg + traceback.format_exc())
+                        dic[name] = np.array(value_list)
                     setattr(self, varname, dic)
 
@@ -1207 +1209 @@
 
         except:
-            logging.info("XML document does not contain fitting information.\n"
+            logger.info("XML document does not contain fitting information.\n"
                          + traceback.format_exc())
 

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

@@ -39 +39 @@
         self.nimages = len(self.report_list[2])
 
-        if self.report_list[2] != None:
+        if self.report_list[2] is not None:
             # put image path in the report string
             if len(self.report_list[2]) == 1:

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

@@ -2 +2 @@
 Module contains functions frequently used in this package
 """
-import numpy
+import numpy as np
 
 
@@ -19 +19 @@
         data = data.y
     if flag == 0:
-        weight = numpy.ones_like(data)
+        weight = np.ones_like(data)
     elif flag == 1:
         weight = dy_data
     elif flag == 2:
-        weight = numpy.sqrt(numpy.abs(data))
+        weight = np.sqrt(np.abs(data))
     elif flag == 3:
-        weight = numpy.abs(data)
+        weight = np.abs(data)
     return weight

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

@@ -92 +92 @@
             # state must be cloned
             state = page.get_state().clone()
-            if data is not None or page.model is not None:
+            # data_list only populated with real data
+            # Fake object in data from page.get_data() if model is selected
+            if len(page.data_list) is not 0 and page.model is not None:
                 new_doc = self._manager.state_reader.write_toXML(data,
                                                                  state,
                                                                  batch_state)
+                # Fit #2 through #n are append to first fit
                 if doc is not None and hasattr(doc, "firstChild"):
-                    child = new_doc.firstChild.firstChild
-                    doc.firstChild.appendChild(child)
+                    # Only append if properly formed new_doc
+                    if new_doc is not None and hasattr(new_doc, "firstChild"):
+                        child = new_doc.firstChild.firstChild
+                        doc.firstChild.appendChild(child)
+                # First fit defines the main document
                 else:
                     doc = new_doc
@@ -395 +401 @@
                 temp_data = page.get_data()
                 if temp_data is not None and temp_data.id in data:
-                    self.SetSelection(pos)
-                    self.on_close_page(event=None)
-                    temp = self.GetSelection()
-                    self.DeletePage(temp)
+                    self.close_page_with_data(temp_data)
             if self.sim_page is not None:
                 if len(self.sim_page.model_list) == 0:
@@ -405 +408 @@
                     self.on_close_page(event=None)
                     temp = self.GetSelection()
-                    self.DeletePage(temp)
+                    self.DeletePage(pos)
                     self.sim_page = None
                     self.batch_on = False