From c46c86839e4b139b4378cbfc47250368a7e24d63 Mon Sep 17 00:00:00 2001
From: mattminder <myfiles@Mattus-MacBook-Pro.local>
Date: Tue, 28 Apr 2020 14:20:25 +0200
Subject: [PATCH] Error message when invalid input before launching CNN
---
GUI_main.py | 110 +++++++++++++++++++++++++++-------------------------
1 file changed, 58 insertions(+), 52 deletions(-)
diff --git a/GUI_main.py b/GUI_main.py
index 6423ddc..f8ebf56 100644
--- a/GUI_main.py
+++ b/GUI_main.py
@@ -65,7 +65,7 @@ import numpy as np
# Import everything for the Graphical User Interface from the PyQt5 library.
-from PyQt5.QtWidgets import QApplication, QMainWindow, QMenu, QVBoxLayout, QSizePolicy, QMessageBox, QWidget, QPushButton, QShortcut, QComboBox, QCheckBox, QLineEdit, QMenu, QAction, QStatusBar
+from PyQt5.QtWidgets import QApplication, QMainWindow, QDialog, QMenu, QVBoxLayout, QSizePolicy, QMessageBox, QWidget, QPushButton, QShortcut, QComboBox, QCheckBox, QLineEdit, QMenu, QAction, QStatusBar, QErrorMessage
from PyQt5 import QtGui
from PyQt5.QtCore import pyqtSignal, QObject, Qt
@@ -126,6 +126,11 @@ from openpyxl import load_workbook
from openpyxl import Workbook
+#def show_error(msg):
+# error_dialog = QErrorMessage()
+# error_dialog.showMessage(msg)
+# error_dialog.exec_
+
class NavigationToolbar(NavigationToolbar):
@@ -816,59 +821,60 @@ class App(QMainWindow):
dlg = lbp.CustomDialog(self)
# this if tests if the user pressed 'ok' in the dialog window
- if dlg.exec_():
+ if dlg.exec_() == QDialog.Accepted:
-# it tests if the user has entered some values
-# if not it ignores and returns.
- if dlg.entry1.text()!= '' and dlg.entry2.text() != '':
-
-# reads out the entry given by the user and converts the index
-# to integers
- time_value1 = int(dlg.entry1.text())
- time_value2 = int(dlg.entry2.text())
-
-
-# it tests if the first value is smaller or equal such that
-# time_value1 is the lower range of the time range
-# and time_value2 the upper boundary of the range.
- if time_value1 <= time_value2 :
-
-# displays that the neural network is running
- self.statusBar.showMessage('Running the neural network...')
-
-# it iterates in the list of the user-selected fields
-# of view, to return the corresponding index, the function
-# dlg.listfov.row(item) is used which gives an integer
- for item in dlg.listfov.selectedItems():
+ # it tests if the user has entered some values
+ # if not it ignores and returns.
+ if not (dlg.entry1.text()!= '' and dlg.entry2.text() != ''):
+ QMessageBox.critical(self, "Error", "No Time Specified")
+ return
-# iterates over the time indices in the range
- for t in range(time_value1, time_value2+1):
-
-# calls the neural network for time t and selected
-# fov
- if dlg.entry_threshold.text() != '':
- thr_val = float(dlg.entry_threshold.text())
- else:
- thr_val = None
- if dlg.entry_segmentation.text() != '':
- seg_val = int(dlg.entry_segmentation.text())
- else:
- seg_val = 10
-
- self.PredThreshSeg(t, dlg.listfov.row(item), thr_val, seg_val)
-
-
-# once it has iterated over all the fov, the message in
-# the status bar is cleared and the buttons are enabled.
- self.statusBar.clearMessage()
- self.EnableCNNButtons()
-
- else:
- return
- else:
- return
- else:
- return
+ # reads out the entry given by the user and converts the index
+ # to integers
+ time_value1 = int(dlg.entry1.text())
+ time_value2 = int(dlg.entry2.text())
+
+
+ # it tests if the first value is smaller or equal such that
+ # time_value1 is the lower range of the time range
+ # and time_value2 the upper boundary of the range.
+ if time_value1 > time_value2 :
+ QMessageBox.critical(self, "Error", 'Invalid Time Constraints')
+ return
+
+
+
+ # displays that the neural network is running
+ self.statusBar.showMessage('Running the neural network...')
+
+ #it iterates in the list of the user-selected fields
+ #of view, to return the corresponding index, the function
+ #dlg.listfov.row(item) is used which gives an integer
+ if len(dlg.listfov.selectedItems())==0:
+ QMessageBox.critical(self, "Error", "No FOV Selected")
+
+ for item in dlg.listfov.selectedItems():
+ #iterates over the time indices in the range
+ for t in range(time_value1, time_value2+1):
+ #calls the neural network for time t and selected
+ #fov
+ if dlg.entry_threshold.text() != '':
+ thr_val = float(dlg.entry_threshold.text())
+ else:
+ thr_val = None
+ if dlg.entry_segmentation.text() != '':
+ seg_val = int(dlg.entry_segmentation.text())
+ else:
+ seg_val = 10
+
+ self.PredThreshSeg(t, dlg.listfov.row(item), thr_val, seg_val)
+
+
+ #once it has iterated over all the fov, the message in
+ #the status bar is cleared and the buttons are enabled.
+ self.statusBar.clearMessage()
+ self.EnableCNNButtons()
+
def PredThreshSeg(self, timeindex, fovindex, thr_val, seg_val):
"""
--
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