hyperspy._components.gaussian module

class hyperspy._components.gaussian.Gaussian(A=1.0, sigma=1.0, centre=0.0, module='numexpr', **kwargs)

Bases: hyperspy._components.expression.Expression

Normalized gaussian function component

f(x) = \frac{A}{\sqrt{2\pi sigma^{2}}}exp\left[-\frac{\left(x-centre\right)^{2}}{2sigma^{2}}\right]

For convenience the fwhm attribute can be used to get and set the full-with-half-maximum.

See also

hyperspy._components.gaussianhf.GaussianHF

estimate_parameters(signal, x1, x2, only_current=False)

Estimate the gaussian by calculating the momenta.

Parameters

  • signal (Signal1D instance) –

  • x1 (float) – Defines the left limit of the spectral range to use for the estimation.

  • x2 (float) – Defines the right limit of the spectral range to use for the estimation.

  • only_current (bool) – If False estimates the parameters for the full dataset.

Returns

Return type

bool

Notes

Adapted from http://www.scipy.org/Cookbook/FittingData

Examples

>>> g = hs.model.components1D.Gaussian()
>>> x = np.arange(-10, 10, 0.01)
>>> data = np.zeros((32, 32, 2000))
>>> data[:] = g.function(x).reshape((1, 1, 2000))
>>> s = hs.signals.Signal1D(data)
>>> s.axes_manager._axes[-1].offset = -10
>>> s.axes_manager._axes[-1].scale = 0.01
>>> g.estimate_parameters(s, -10, 10, False)
property fwhm
hyperspy._components.gaussian.sigma2fwhm = 2.3548200450309493
hyperspy._components.gaussian.sqrt2pi = 2.5066282746310002