Changeset d6b8a1d in sasview for src/sas/qtgui/Plotting/LinearFit.py

Timestamp:

Nov 9, 2017 8:43:56 AM (7 years ago)

Author:

Piotr Rozyczko <rozyczko@…>

Branches:

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

Children:

53c771e

Parents:

fbfc488

git-author:

Piotr Rozyczko <rozyczko@…> (11/07/17 08:29:59)

git-committer:

Piotr Rozyczko <rozyczko@…> (11/09/17 08:43:56)

Message:

More Qt5 related fixes

File:

• src/sas/qtgui/Plotting/LinearFit.py (modified) (4 diffs)

src/sas/qtgui/Plotting/LinearFit.py

@@ -8 +8 @@
 from PyQt5 import QtWidgets
 
-from sas.qtgui.Utilities.GuiUtils import formatNumber
+from sas.qtgui.Utilities.GuiUtils import formatNumber, DoubleValidator
 
 from sas.qtgui.Plotting import Fittings
@@ -43 +43 @@
         self.y_is_log = self.yLabel == "log10(y)"
 
-        self.txtFitRangeMin.setValidator(QtGui.QDoubleValidator())
-        self.txtFitRangeMax.setValidator(QtGui.QDoubleValidator())
+        self.txtFitRangeMin.setValidator(DoubleValidator())
+        self.txtFitRangeMax.setValidator(DoubleValidator())
 
         # Default values in the line edits
@@ -158 +158 @@
         y_model = self.model.run(xmin)
         tempx.append(xminView)
-        tempy.append(numpy.power(10, y_model) if self.y_is_log else y_model)
+        tempy.append(numpy.power(10.0, y_model) if self.y_is_log else y_model)
 
         # load tempy with the maximum transformation
         y_model = self.model.run(xmax)
         tempx.append(xmaxView)
-        tempy.append(numpy.power(10, y_model) if self.y_is_log else y_model)
+        tempy.append(numpy.power(10.0, y_model) if self.y_is_log else y_model)
 
         # Set the fit parameter display when  FitDialog is opened again
@@ -247 +247 @@
             return numpy.sqrt(numpy.sqrt(x))
         elif self.xLabel == "log10(x)":
-            return numpy.power(10, x)
+            return numpy.power(10.0, x)
         elif self.xLabel == "ln(x)":
             return numpy.exp(x)
         elif self.xLabel == "log10(x^(4))":
-            return numpy.sqrt(numpy.sqrt(numpy.power(10, x)))
+            return numpy.sqrt(numpy.sqrt(numpy.power(10.0, x)))
         return x