def previewAll(self):
if not np.shape(self.data.X):
self.errorBox('There is no data', 'No data...')
return
self.subplot.clear()
self.subplot.plot(self.data.X, self.data.current, label = 'Experimental data')
cols = self.tableWidget.columnCount()
rows = self.tableWidget.rowCount()
cumulative = np.zeros(len(self.data.X))
intensity = [float(self.tableWidget.item(row, 5).text()) for row in range(rows) if self.tableWidget.item(row, 0).checkState()&Qt.Checked]
norm = max(self.data.current)/max(intensity)
for row in range(rows):
if self.tableWidget.item(row, 0).checkState() & Qt.Checked:
error = [self.itemCheck(self.tableWidget.item(row, col), silent=True) for col in range(1, cols-1)]
if True in error:
self.errorBox("Bad parameters", "Bad values")
return
params =[float(self.tableWidget.item(row, col).text()) for col in [5, 6, 2]]
params[0] *= norm
label = self.tableWidget.item(row, 1).text()
shape = self.tableWidget.cellWidget(row, 7).currentText().strip()[0]
if shape == 'V':
params = np.append(params, 0.5)
elif shape == 'B':
params = np.append(params, 0.02)
p = FIT.Peak(FIT, self.data.X, *params, shape = shape)
cumulative += p
self.subplot.plot(self.data.X, p, label = label)
self.subplot.plot(self.data.X, cumulative, 'r--', label = "Cumulative")
self.plotAdjust()
def previewBand(self, row):
if not np.shape(self.data.X):
self.errorBox('There is no data', 'No data...')
return
cols = self.tableWidget.columnCount()
params =[self.tableWidget.item(row, col).text() for col in range(1, cols-1)]
shape = self.tableWidget.cellWidget(row, cols-1).currentText().strip()[0]
label = params[0]
params = np.asarray([params[4], params[5], params[1]]).astype(float)
if shape == 'V':
params = np.append(params, 0.5)
elif shape == 'B':
params = np.append(params, 0.02)
self.Plot(self.data.X, self.data.current, "Experimental data")
self.subplot.plot(self.data.X, FIT.Peak(FIT, self.data.X, *params, shape = shape), label = label)
self.subplot.legend()
self.canvas.draw()
