def test():
from silx.math.fit import fittheories
from silx.math.fit import fitmanager
from silx.math.fit import functions
from silx.gui.plot.PlotWindow import PlotWindow
import numpy
a = qt.QApplication([])
x = numpy.arange(1000)
y1 = functions.sum_gauss(x, 100, 400, 100)
fit = fitmanager.FitManager(x=x, y=y1)
fitfuns = fittheories.FitTheories()
fit.addtheory(name="Gaussian",
function=functions.sum_gauss,
parameters=("height", "peak center", "fwhm"),
estimate=fitfuns.estimate_height_position_fwhm)
fit.settheory('Gaussian')
fit.configure(
PositiveFwhmFlag=True,
PositiveHeightAreaFlag=True,
AutoFwhm=True,
)
# Fit
fit.estimate()
fit.runfit()
w = ParametersTab()
w.show()
w.fillFromFit(fit.fit_results, view='Gaussians')
y2 = functions.sum_splitgauss(x, 100, 400, 100, 40, 10, 600, 50, 500, 80,
850, 10, 50)
fit.setdata(x=x, y=y2)
# Define new theory
fit.addtheory(name="Asymetric gaussian",
function=functions.sum_splitgauss,
parameters=("height", "peak center", "left fwhm",
"right fwhm"),
estimate=fitfuns.estimate_splitgauss)
fit.settheory('Asymetric gaussian')
# Fit
fit.estimate()
fit.runfit()
w.fillFromFit(fit.fit_results, view='Asymetric gaussians')
# Plot
pw = PlotWindow(control=True)
pw.addCurve(x, y1, "Gaussians")
pw.addCurve(x, y2, "Asymetric gaussians")
pw.show()
a.exec_()
def testSplitGauss(self):
"""Compare sum_splitgauss with scipy.signals.gaussian"""
y = functions.sum_splitgauss(self.x, self.g_params["height"],
self.g_params["center"],
self.g_params["fwhm1"],
self.g_params["fwhm2"])
for i in range(11):
self.assertAlmostEqual(y[i], self.scipy_asym_gaussian[i])
def test():
from silx.math.fit import fittheories
from silx.math.fit import fitmanager
from silx.math.fit import functions
from silx.gui.plot.PlotWindow import PlotWindow
import numpy
a = qt.QApplication([])
x = numpy.arange(1000)
y1 = functions.sum_gauss(x, 100, 400, 100)
fit = fitmanager.FitManager(x=x, y=y1)
fitfuns = fittheories.FitTheories()
fit.addtheory(name="Gaussian",
function=functions.sum_gauss,
parameters=("height", "peak center", "fwhm"),
estimate=fitfuns.estimate_height_position_fwhm)
fit.settheory('Gaussian')
fit.configure(PositiveFwhmFlag=True,
PositiveHeightAreaFlag=True,
AutoFwhm=True,)
# Fit
fit.estimate()
fit.runfit()
w = ParametersTab()
w.show()
w.fillFromFit(fit.fit_results, view='Gaussians')
y2 = functions.sum_splitgauss(x,
100, 400, 100, 40,
10, 600, 50, 500,
80, 850, 10, 50)
fit.setdata(x=x, y=y2)
# Define new theory
fit.addtheory(name="Asymetric gaussian",
function=functions.sum_splitgauss,
parameters=("height", "peak center", "left fwhm", "right fwhm"),
estimate=fitfuns.estimate_splitgauss)
fit.settheory('Asymetric gaussian')
# Fit
fit.estimate()
fit.runfit()
w.fillFromFit(fit.fit_results, view='Asymetric gaussians')
# Plot
pw = PlotWindow(control=True)
pw.addCurve(x, y1, "Gaussians")
pw.addCurve(x, y2, "Asymetric gaussians")
pw.show()
a.exec_()
def testSplitGauss(self):
"""Compare sum_splitgauss with scipy.signals.gaussian"""
y = functions.sum_splitgauss(self.x,
self.g_params["height"],
self.g_params["center"],
self.g_params["fwhm1"],
self.g_params["fwhm2"])
for i in range(11):
self.assertAlmostEqual(y[i], self.scipy_asym_gaussian[i])