def stepup(self,pars,x):
"""
A fit function.
"""
return 0.5*SpecfitFuns.upstep(pars,x)
def stepUp(self, pars, x):
"""
Error function like.
"""
return 0.5 * SpecfitFuns.upstep(pars, x)
self.connect(self.dismissButton, qt.SIGNAL("clicked()"), self.reject)
self.connect(self.okButton, qt.SIGNAL("clicked()"), self.accept)
def getParameters(self):
parametersDict = self.parametersWidget.getParameters()
return parametersDict
def setParameters(self, ddict):
return self.parametersWidget.setParameters(ddict)
if __name__ == "__main__":
app = qt.QApplication([])
if len(sys.argv) > 1:
from PyMca import specfilewrapper as specfile
sf = specfile.Specfile(sys.argv[1])
scan = sf[0]
data = scan.data()
energy = data[0, :]
spectrum = data[1, :]
w = XASNormalizationDialog(None, spectrum, energy=energy)
else:
from PyMca import SpecfitFuns
noise = numpy.random.randn(1500.)
x = 8000. + numpy.arange(1500.)
y = SpecfitFuns.upstep([100, 8500., 50], x)
w = XASNormalizationDialog(None, y + numpy.sqrt(y) * noise, energy=x)
ret = w.exec_()
if ret:
print(w.getParameters())