def mymodel(xarr,
b0,
b1,
amp1,
xcen1,
gw1,
lw1,
amp2,
xcen2,
gw2,
lw2,
amp3,
xcen3,
gw3,
lw3,
amp4,
xcen4,
gw4,
lw4,
return_components=False,
normalized=False,
**kwargs):
""" docstring """
base = xarr * b1 + b0
v1 = voigt(xarr, amp1, xcen1, gw1, lw1, normalized=normalized)
v2 = voigt(xarr, amp2, xcen2, gw2, lw2, normalized=normalized)
v3 = voigt(xarr, amp3, xcen3, gw3, lw3, normalized=normalized)
v4 = voigt(xarr, amp4, xcen4, gw4, lw4, normalized=normalized)
if return_components:
return np.array([base, v1, v2, v3, v4])
else:
mod = base + v1 + v2 + v3 + v4
return mod
def voigt_line(x,wvl): amp = x[0] line_cen = x[1] fwhm = 0.4*abs(x[2]) ratio = abs(x[3]) Lfwhm = fwhm / (0.5346 + (0.2166 + (ratio**-2))**0.5) Gfwhm = fwhm / (0.5346*ratio + (0.2166*ratio**2.0 + 1)**0.5) line = voigt(wvl,amp,line_cen,Gfwhm,Lfwhm,normalized=False) line = amp*line/max(line) return line
try:
import scipy
scipyOK = True
except ImportError:
scipyOK = False
if scipyOK:
import numpy as np
import pyspeckit.spectrum.models.inherited_voigtfitter as IV
from pyspeckit.spectrum.units import SpectroscopicAxis
xarr = SpectroscopicAxis(np.linspace(-100,100,1000))
dx = np.diff(xarr).mean()
V1 = IV.voigt(xarr,1,0,1,1,normalized=False)
V2 = IV.voigt(xarr,1,0,1,1,normalized=True)
assert np.sqrt(2*np.pi) - 0.05 < V1.sum()*dx.value < np.sqrt(2*np.pi) + 0.05
assert 0.99 < V2.sum()*dx.value < 1.01
else:
print("Skipped Voigt test because scipy could not be imported")
try:
import scipy
scipyOK = True
except ImportError:
scipyOK = False
if scipyOK:
import numpy as np
import pyspeckit.spectrum.models.inherited_voigtfitter as IV
from pyspeckit.spectrum.units import SpectroscopicAxis
xarr = SpectroscopicAxis(np.linspace(-100, 100, 1000))
dx = np.diff(xarr).mean()
V1 = IV.voigt(xarr, 1, 0, 1, 1, normalized=False)
V2 = IV.voigt(xarr, 1, 0, 1, 1, normalized=True)
assert np.sqrt(2 * np.pi) - 0.05 < V1.sum() * dx.value < np.sqrt(
2 * np.pi) + 0.05
assert 0.99 < V2.sum() * dx.value < 1.01
else:
print("Skipped Voigt test because scipy could not be imported")