Changes in / [ecfe6b6:4e255d1] in sasview

Location:

src/sas/qtgui

Files:

• MainWindow/DataExplorer.py (modified) (3 diffs)
• Perspectives/Fitting/FittingLogic.py (modified) (4 diffs)
• Perspectives/Fitting/FittingWidget.py (modified) (2 diffs)
• Perspectives/Fitting/ModelThread.py (modified) (2 diffs)
• Perspectives/Fitting/UnitTesting/FittingLogicTest.py (modified) (1 diff)

src/sas/qtgui/MainWindow/DataExplorer.py

@@ -4 +4 @@
 import time
 import logging
-import re
 
 from PyQt5 import QtCore
@@ -37 +36 @@
     # The controller which is responsible for managing signal slots connections
     # for the gui and providing an interface to the data model.
-
-    # This matches the ID of a plot created using FittingLogic._create1DPlot, e.g.
-    # "5 [P(Q)] modelname"
-    # or
-    # "4 modelname".
-    # Useful for determining whether the plot in question is for an intermediate result, such as P(Q) or S(Q) in the
-    # case of a product model; the identifier for this is held in square brackets, as in the example above.
-    theory_plot_ID_pattern = re.compile(r"^([0-9]+)\s+(\[(.*)\]\s+)?(.*)$")
 
     def __init__(self, parent=None, guimanager=None, manager=None):
@@ -534 +525 @@
                 self.active_plots[plot_id].replacePlot(plot_id, plot)
             else:
-                # Don't plot intermediate results, e.g. P(Q), S(Q)
-                match = self.theory_plot_ID_pattern.match(plot_id)
-                # 2nd match group contains the identifier for the intermediate result, if present (e.g. "[P(Q)]")
-                if match and match.groups()[1] != None:
-                    continue
                 # 'sophisticated' test to generate standalone plot for residuals
                 if 'esiduals' in plot.title:

src/sas/qtgui/Perspectives/Fitting/FittingLogic.py

@@ -132 +132 @@
         self._data.ymax = ymax
 
-    def _create1DPlot(self, tab_id, x, y, model, data, component=None):
-        """
-        For internal use: create a new 1D data instance based on fitting results.
-        'component' is a string indicating the model component, e.g. "P(Q)"
-        """
+    def new1DPlot(self, return_data, tab_id):
+        """
+        Create a new 1D data instance based on fitting results
+        """
+        # Unpack return data from Calc1D
+        x, y, page_id, state, weight,\
+        fid, toggle_mode_on, \
+        elapsed, index, model,\
+        data, update_chisqr, source = return_data
+
         # Create the new plot
         new_plot = Data1D(x=x, y=y)
@@ -145 +150 @@
 
         new_plot.group_id = data.group_id
-        new_plot.id = str(tab_id) + " " + ("[" + component + "] " if component else "") + model.id
-
-        # use data.filename for data, use model.id for theory
-        id_str = data.filename if data.filename else model.id
-        new_plot.name = model.name + ((" " + component) if component else "") + " [" + id_str + "]"
+        new_plot.id = str(tab_id) + " " + model.id
+
+        if data.filename:
+            new_plot.name = model.name + " [" + data.filename + "]" # data file
+        else:
+            new_plot.name = model.name + " [" + model.id + "]"  # theory
 
         new_plot.title = new_plot.name
@@ -156 +162 @@
 
         return new_plot
-
-    def new1DPlot(self, return_data, tab_id):
-        """
-        Create a new 1D data instance based on fitting results
-        """
-        # Unpack return data from Calc1D
-        x, y, page_id, state, weight,\
-        fid, toggle_mode_on, \
-        elapsed, index, model, \
-        data, update_chisqr, source, \
-        unsmeared_output, unsmeared_data, unsmeared_error, \
-        pq_values, sq_values = return_data
-
-        return self._create1DPlot(tab_id, x, y, model, data)
 
     def new2DPlot(self, return_data):
@@ -213 +205 @@
         return new_plot
 
-    def new1DProductPlots(self, return_data, tab_id):
-        """
-        If return_data contains separated P(Q) and/or S(Q) data, create 1D plots for each and return as the tuple
-        (pq_plot, sq_plot). If either are unavailable, the corresponding plot is None.
-        """
-        # Unpack return data from Calc1D
-        x, y, page_id, state, weight, \
-        fid, toggle_mode_on, \
-        elapsed, index, model, \
-        data, update_chisqr, source, \
-        unsmeared_output, unsmeared_data, unsmeared_error, \
-        pq_values, sq_values = return_data
-
-        pq_plot = None
-        sq_plot = None
-
-        if pq_values is not None:
-            pq_plot = self._create1DPlot(tab_id, x, pq_values, model, data, component="P(Q)")
-        if sq_values is not None:
-            sq_plot = self._create1DPlot(tab_id, x, sq_values, model, data, component="S(Q)")
-
-        return pq_plot, sq_plot
-
     def computeDataRange(self):
         """

src/sas/qtgui/Perspectives/Fitting/FittingWidget.py

@@ -2113 +2113 @@
             self.updateModelIndex(fitted_data)
         else:
-            if not fitted_data.name:
-                name = self.nameForFittedData(self.kernel_module.id)
-            else:
-                name = fitted_data.name
+            name = self.nameForFittedData(self.kernel_module.id)
             fitted_data.title = name
+            fitted_data.name = name
             fitted_data.filename = name
             fitted_data.symbol = "Line"
@@ -2231 +2229 @@
         self.model_data = fitted_data
 
-        # Create plots for intermediate product data
-        pq_data, sq_data = self.logic.new1DProductPlots(return_data, self.tab_id)
-        if pq_data is not None:
-            pq_data.symbol = "Line"
-            self.createNewIndex(pq_data)
-        if sq_data is not None:
-            sq_data.symbol = "Line"
-            self.createNewIndex(sq_data)
-
     def complete2D(self, return_data):
         """

src/sas/qtgui/Perspectives/Fitting/ModelThread.py

@@ -222 +222 @@
             s_model = self.model.s_model
             p_model = self.model.p_model
-        elif hasattr(self.model, "calc_composition_models"):
-            results = self.model.calc_composition_models(self.data.x[index])
-            if results is not None:
-                pq_values, sq_values = results
-
-        if pq_values is None or sq_values is None:
-            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[index] = s_model.evalDistribution(self.data.x[index])
-                pq_values[index] = p_model.evalDistribution(self.data.x[index])
+        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 = numpy.zeros((len(self.data.x)))
+            pq_values = numpy.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])
 
         elapsed = time.time() - self.starttime
@@ -246 +243 @@
                     self.data,
                     self.update_chisqr,
-                    self.source,
-                    unsmeared_output, unsmeared_data, unsmeared_error,
-                    pq_values, sq_values)
+                    self.source)
         else:
             self.complete(x=self.data.x[index], y=output[index],

src/sas/qtgui/Perspectives/Fitting/UnitTesting/FittingLogicTest.py

@@ -100 +100 @@
         data.id = "poop"
         return_data = (data.x,data.y, 7, None, None,
-                       0, True, 0.0, 1, data,
-                       data, False, None,
-                       None, None, None,
-                       None, None)
+                        0, True, 0.0, 1, data,
+                        data, False, None)
 
         new_plot = self.logic.new1DPlot(return_data=return_data, tab_id=0)