Changeset 2385397 in sasview for src/sas

Timestamp:

Sep 13, 2018 6:17:46 AM (6 years ago)

Author:

wojciech

Branches:

ESS_GUI, ESS_GUI_batch_fitting, ESS_GUI_bumps_abstraction, ESS_GUI_iss1116, ESS_GUI_opencl, ESS_GUI_ordering, ESS_GUI_sync_sascalc

Children:

eeea6a3

Parents:

13da5f5 (diff), 1a15ada (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 'ESS_GUI' of ​https://github.com/SasView/sasview into ESS_GUI_Pr_fixes

Location:

src/sas

Files:

• qtgui/Perspectives/Fitting/FittingUtilities.py (modified) (1 diff)
• qtgui/Perspectives/Fitting/UnitTesting/FittingWidgetTest.py (modified) (2 diffs)
• qtgui/Perspectives/Inversion/DMaxExplorerWidget.py (modified) (5 diffs)
• qtgui/Perspectives/Inversion/InversionPerspective.py (modified) (10 diffs)
• sascalc/pr/invertor.py (modified) (6 diffs)

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

@@ -23 +23 @@
 
 poly_header_tooltips = ['Select parameter for fitting',
-                        'Enter polydispersity ratio (STD/mean). '
+                        'Enter polydispersity ratio (Std deviation/mean).\n'+
+                        'For angles this can be either std deviation or full width (for uniform distributions) in degrees',
                         'STD: standard deviation from the mean value',
                         'Enter minimum value for parameter',

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

@@ -393 +393 @@
 
         # Test tooltips
-        self.assertEqual(len(self.widget._poly_model.header_tooltips), 8)
+        self.assertEqual(len(self.widget._poly_model.header_tooltips), 9)
 
         header_tooltips = ['Select parameter for fitting',
-                             'Enter polydispersity ratio (STD/mean). '
-                             'STD: standard deviation from the mean value',
-                             'Enter minimum value for parameter',
-                             'Enter maximum value for parameter',
-                             'Enter number of points for parameter',
-                             'Enter number of sigmas parameter',
-                             'Select distribution function',
-                             'Select filename with user-definable distribution']
+                            'Enter polydispersity ratio (Std deviation/mean).\n'+
+                            'For angles this can be either std deviation or full width (for uniform distributions) in degrees',
+                            'STD: standard deviation from the mean value',
+                            'Enter minimum value for parameter',
+                            'Enter maximum value for parameter',
+                            'Enter number of points for parameter',
+                            'Enter number of sigmas parameter',
+                            'Select distribution function',
+                            'Select filename with user-definable distribution']
         for column, tooltip in enumerate(header_tooltips):
              self.assertEqual(self.widget._poly_model.headerData( column,
@@ -908 +909 @@
         self.assertFalse(self.widget.tabFitting.isTabEnabled(4))
 
-    def testReadFitPage2D(self):
+    # to be fixed after functionality is ready
+    def notestReadFitPage2D(self):
         """
         Read in the fitpage object and restore state

src/sas/qtgui/Perspectives/Inversion/DMaxExplorerWidget.py

@@ -42 +42 @@
         self.parent = parent
 
-        self.setWindowTitle("Dₐₓ Explorer")
+        self.setWindowTitle("Dmax Explorer")
 
         self.pr_state = pr_state
@@ -116 +116 @@
         bck = []
         chi2 = []
-
+        plotable_xs = [] #Introducing this to make sure size of x and y for plotting is the same.8
         try:
             dmin = float(self.model.item(W.DMIN).text())
@@ -128 +128 @@
 
         original = self.pr_state.d_max
+
         for x in xs:
             self.pr_state.d_max = x
@@ -140 +141 @@
                 bck.append(self.pr_state.background)
                 chi2.append(self.pr_state.chi2)
+                plotable_xs.append(x)
             except Exception as ex:
                 # This inversion failed, skip this D_max value
@@ -188 +190 @@
             y_unit = "a.u."
 
-        data = Data1D(xs, ys)
+        data = Data1D(plotable_xs, ys)
         if self.hasPlot:
             self.plot.removePlot(None)

src/sas/qtgui/Perspectives/Inversion/InversionPerspective.py

@@ -43 +43 @@
     estimateSignal = QtCore.pyqtSignal(tuple)
     estimateNTSignal = QtCore.pyqtSignal(tuple)
+    estimateDynamicNTSignal = QtCore.pyqtSignal(tuple)
+    estimateDynamicSignal = QtCore.pyqtSignal(tuple)
     calculateSignal = QtCore.pyqtSignal(tuple)
 
@@ -194 +196 @@
         self.model.itemChanged.connect(self.model_changed)
         self.estimateNTSignal.connect(self._estimateNTUpdate)
+        self.estimateDynamicNTSignal.connect(self._estimateDynamicNTUpdate)
+        self.estimateDynamicSignal.connect(self._estimateDynamicUpdate)
         self.estimateSignal.connect(self._estimateUpdate)
         self.calculateSignal.connect(self._calculateUpdate)
+
+        self.maxDistanceInput.textEdited.connect(self.performEstimateDynamic)
 
     def setupMapper(self):
@@ -309 +315 @@
                                             and not self.isCalculating)
         self.removeButton.setEnabled(self.logic.data_is_loaded)
-        self.explorerButton.setEnabled(self.logic.data_is_loaded
-                                       and np.all(self.logic.data.dy != 0))
+        self.explorerButton.setEnabled(self.logic.data_is_loaded)
         self.stopButton.setVisible(self.isCalculating)
         self.regConstantSuggestionButton.setEnabled(
@@ -501 +506 @@
         self.dataPlot = self._dataList[data_ref].get(DICT_KEYS[2])
         self.performEstimate()
+
+    def updateDynamicGuiValues(self):
+        pr = self._calculator
+        alpha = self._calculator.suggested_alpha
+        self.model.setItem(WIDGETS.W_MAX_DIST,
+                            QtGui.QStandardItem("{:.4g}".format(pr.get_dmax())))
+        self.regConstantSuggestionButton.setText("{:-3.2g}".format(alpha))
+        self.noOfTermsSuggestionButton.setText(
+             "{:n}".format(self.nTermsSuggested))
+
+        self.enableButtons()
 
     def updateGuiValues(self):
@@ -520 +536 @@
         self.model.setItem(WIDGETS.W_MAX_DIST,
                            QtGui.QStandardItem("{:.4g}".format(pr.get_dmax())))
-        self.regConstantSuggestionButton.setText("{:-3.2g}".format(alpha))
-        self.noOfTermsSuggestionButton.setText(
-            "{:n}".format(self.nTermsSuggested))
 
         if isinstance(pr.chi2, np.ndarray):
@@ -671 +684 @@
         self.estimationThreadNT.ready(2.5)
 
+    def performEstimateDynamicNT(self):
+        """
+        Perform parameter estimation
+        """
+        from .Thread import EstimateNT
+
+        self.updateCalculator()
+
+        # If a thread is already started, stop it
+        self.stopEstimateNTThread()
+
+        pr = self._calculator.clone()
+        # Skip the slit settings for the estimation
+        # It slows down the application and it doesn't change the estimates
+        pr.slit_height = 0.0
+        pr.slit_width = 0.0
+        nfunc = self.getNFunc()
+
+        self.estimationThreadNT = EstimateNT(pr, nfunc,
+                                             error_func=self._threadError,
+                                             completefn=self._estimateDynamicNTCompleted,
+                                             updatefn=None)
+        self.estimationThreadNT.queue()
+        self.estimationThreadNT.ready(2.5)
+
     def stopEstimateNTThread(self):
         if (self.estimationThreadNT is not None and
@@ -693 +731 @@
         self.estimationThread.ready(2.5)
 
+    def performEstimateDynamic(self):
+        """
+            Perform parameter estimation
+        """
+        from .Thread import EstimatePr
+
+        # If a thread is already started, stop it
+        self.stopEstimationThread()
+
+        self.estimationThread = EstimatePr(self._calculator.clone(),
+                                           self.getNFunc(),
+                                           error_func=self._threadError,
+                                           completefn=self._estimateDynamicCompleted,
+                                           updatefn=None)
+        self.estimationThread.queue()
+        self.estimationThread.ready(2.5)
+
     def stopEstimationThread(self):
         """ Stop the estimation thread if it exists and is running """
@@ -705 +760 @@
         ''' Send a signal to the main thread for model update'''
         self.estimateSignal.emit((alpha, message, elapsed))
+
+    def _estimateDynamicCompleted(self, alpha, message, elapsed):
+        ''' Send a signal to the main thread for model update'''
+        self.estimateDynamicSignal.emit((alpha, message, elapsed))
 
     def _estimateUpdate(self, output_tuple):
@@ -720 +779 @@
             logger.info(message)
         self.performEstimateNT()
+        self.performEstimateDynamicNT()
+
+    def _estimateDynamicUpdate(self, output_tuple):
+        """
+        Parameter estimation completed,
+        display the results to the user
+
+        :param alpha: estimated best alpha
+        :param elapsed: computation time
+        """
+        alpha, message, elapsed = output_tuple
+        self._calculator.alpha = alpha
+        self._calculator.elapsed += self._calculator.elapsed
+        if message:
+            logger.info(message)
+        self.performEstimateDynamicNT()
 
     def _estimateNTCompleted(self, nterms, alpha, message, elapsed):
         ''' Send a signal to the main thread for model update'''
         self.estimateNTSignal.emit((nterms, alpha, message, elapsed))
+
+    def _estimateDynamicNTCompleted(self, nterms, alpha, message, elapsed):
+        ''' Send a signal to the main thread for model update'''
+        self.estimateDynamicNTSignal.emit((nterms, alpha, message, elapsed))
 
     def _estimateNTUpdate(self, output_tuple):
@@ -747 +826 @@
             self.startThread()
 
+    def _estimateDynamicNTUpdate(self, output_tuple):
+        """
+        Parameter estimation completed,
+        display the results to the user
+
+        :param alpha: estimated best alpha
+        :param nterms: estimated number of terms
+        :param elapsed: computation time
+        """
+        nterms, alpha, message, elapsed = output_tuple
+        self._calculator.elapsed += elapsed
+        self._calculator.suggested_alpha = alpha
+        self.nTermsSuggested = nterms
+        # Save useful info
+        self.updateDynamicGuiValues()
+        if message:
+            logger.info(message)
+        if self.isBatch:
+            self.acceptAlpha()
+            self.acceptNoTerms()
+            self.startThread()
+
     def _calculateCompleted(self, out, cov, pr, elapsed):
         ''' Send a signal to the main thread for model update'''

src/sas/sascalc/pr/invertor.py

@@ -71 +71 @@
         A[j][i] = (Fourier transformed base function for point j)
 
-    We them choose a number of r-points, n_r, to evaluate the second
+    We then choose a number of r-points, n_r, to evaluate the second
     derivative of P(r) at. This is used as our regularization term.
     For a vector r of length n_r, the following n_r rows are set to ::
@@ -144 +144 @@
         x, y, err, d_max, q_min, q_max and alpha
         """
-        if   name == 'x':
+        if name == 'x':
             if 0.0 in value:
                 msg = "Invertor: one of your q-values is zero. "
@@ -227 +227 @@
         return None
 
+    def add_errors(self, yvalues):
+        """
+        Adds errors to data set is they are not avaialble
+        :return:
+        """
+        stats_errors = np.zeros(len(yvalues))
+        for i in range(len(yvalues)):
+            # Scale the error so that we can fit over several decades of Q
+            scale = 0.05 * np.sqrt(yvalues[i])
+            min_err = 0.01 * yvalues[i]
+            stats_errors[i] = scale * np.sqrt(np.fabs(yvalues[i])) + min_err
+        logger.warning("Simulated errors have been added to the data set\n")
+        return stats_errors
+
     def clone(self):
         """
@@ -244 +258 @@
         invertor.x = self.x
         invertor.y = self.y
-        invertor.err = self.err
+        if np.size(self.err) == 0 or np.all(self.err) == 0:
+            invertor.err = self.add_errors(self.y)
+        else:
+            invertor.err = self.err
         invertor.est_bck = self.est_bck
         invertor.background = self.background
@@ -268 +285 @@
             A[i][j] = (Fourier transformed base function for point j)
 
-        We them choose a number of r-points, n_r, to evaluate the second
+        We then choose a number of r-points, n_r, to evaluate the second
         derivative of P(r) at. This is used as our regularization term.
         For a vector r of length n_r, the following n_r rows are set to ::
@@ -289 +306 @@
         # Reset the background value before proceeding
         # self.background = 0.0
+        if np.size(self.err) == 0 or np.all(self.err) == 0:
+            self.err = self.add_errors(self.y)
         if not self.est_bck:
             self.y -= self.background