Fit Functions¶
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py4syn.utils.fit.
fitGauss
(xarray, yarray)[source]¶ This function mix a Linear Model with a Gaussian Model (LMFit).
See also: Lmfit Documentation
Parameters: xarray : array
X data
yarray : array
Y data
Returns: peak value: float
peak position: float
min value: float
min position: float
fwhm: float
fwhm positon: float
center of mass: float
fit_Y: array
fit_result: ModelFit
Examples
>>> import pylab as pl >>> data = 'testdata.txt' >>> X = pl.loadtxt(data); >>> x = X[:,0]; >>> y = X[:,7]; >>> >>> pkv, pkp, minv, minp, fwhm, fwhmp, com = fitGauss(x, y) >>> print("Peak ", pkv, " at ", pkp) >>> print("Min ", minv, " at ", minp) >>> print("Fwhm ", fwhm, " at ", fwhmp) >>> print("COM = ", com) >>>
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py4syn.utils.fit.
tvDenoising1D
(data, lamb)[source]¶ This function implements a 1-D Total Variation denoising according to Condat, L. (2013) “A direct algorithm for 1-D total variation denoising.”
Parameters: data : array
Data to be fit
lamb : float
Note
lamb must be nonnegative. lamb = 0 will result in output = data.
Returns: fitData: array
Examples
>>> import pylab as pl >>> data = 'testdata.txt' >>> X = pl.loadtxt(data); >>> x = X[:,0]; >>> data = X[:,7]; >>> >>> denoised = tvDenoising1D(data, lamb=200) >>> >>> pl.plot(x, data, 'b') >>> pl.hold(True) >>> pl.plot(x, denoised, 'r--') >>> pl.show()