How to use the rampy.gaussian function in rampy

To help you get started, we’ve selected a few rampy examples, based on popular ways it is used in public projects.

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github charlesll / rampy / rampy / baseline.py View on Github external
print('ERROR: Install gcvspline to use this mode (needs a working FORTRAN compiler).')

        # optional parameters
        splinesmooth = kwargs.get('s',2.0)

        # Spline baseline with mode 1 of gcvspl.f, see gcvspline documentation
        c, wk, ier = gcvspline(yafit[:,0],yafit[:,1],np.sqrt(np.abs(yafit[:,1])),splinesmooth,splmode = 1) # gcvspl with mode 1 and smooth factor

        baseline_fitted = splderivative(x,yafit[:,0],c)

    elif method == 'gaussian':
        ### Baseline is of the type y = a*exp(-log(2)*((x-b)/c)**2)
        # optional parameters
        p0_gauss = kwargs.get('p0_gaussian',[1.,1.,1.])
        ## fit of the baseline
        coeffs, pcov = curve_fit(rampy.gaussian,yafit[:,0],yafit[:,1],p0 = p0_gauss)

        baseline_fitted = rampy.gaussian(x,coeffs[0],coeffs[1],coeffs[2])

    elif method == 'exp':
        ### Baseline is of the type y = a*exp(b*(x-xo))
        # optional parameters
        p0_exp = kwargs.get('p0_exp',[1.,1.,1.])
        ## fit of the baseline
        coeffs, pcov = curve_fit(rampy.funexp,yafit[:,0],yafit[:,1],p0 = p0_exp)

        baseline_fitted = rampy.funexp(x,coeffs[0],coeffs[1],coeffs[2])

    elif method == 'log':
        ### Baseline is of the type y = a*exp(b*(x-xo))
        # optional parameters
        p0_log = kwargs.get('p0_log',[1.,1.,1.,1.])
github charlesll / rampy / rampy / baseline.py View on Github external
# optional parameters
        splinesmooth = kwargs.get('s',2.0)

        # Spline baseline with mode 1 of gcvspl.f, see gcvspline documentation
        c, wk, ier = gcvspline(yafit[:,0],yafit[:,1],np.sqrt(np.abs(yafit[:,1])),splinesmooth,splmode = 1) # gcvspl with mode 1 and smooth factor

        baseline_fitted = splderivative(x,yafit[:,0],c)

    elif method == 'gaussian':
        ### Baseline is of the type y = a*exp(-log(2)*((x-b)/c)**2)
        # optional parameters
        p0_gauss = kwargs.get('p0_gaussian',[1.,1.,1.])
        ## fit of the baseline
        coeffs, pcov = curve_fit(rampy.gaussian,yafit[:,0],yafit[:,1],p0 = p0_gauss)

        baseline_fitted = rampy.gaussian(x,coeffs[0],coeffs[1],coeffs[2])

    elif method == 'exp':
        ### Baseline is of the type y = a*exp(b*(x-xo))
        # optional parameters
        p0_exp = kwargs.get('p0_exp',[1.,1.,1.])
        ## fit of the baseline
        coeffs, pcov = curve_fit(rampy.funexp,yafit[:,0],yafit[:,1],p0 = p0_exp)

        baseline_fitted = rampy.funexp(x,coeffs[0],coeffs[1],coeffs[2])

    elif method == 'log':
        ### Baseline is of the type y = a*exp(b*(x-xo))
        # optional parameters
        p0_log = kwargs.get('p0_log',[1.,1.,1.,1.])
        ## fit of the baseline
        coeffs, pcov = curve_fit(rampy.funlog,yafit[:,0],yafit[:,1],p0 = p0_log)

rampy

A Python module containing functions to treat spectroscopic (XANES, Raman, IR...) data

GPL-2.0
Latest version published 2 months ago

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