def test_smooth_trapezoid_good(simulated_spectra, stddev):
"""
Test Trapezoid1DKernel smoothing with correct parmaeters.
Standard deviation values need to be a number greater than 0.
"""
# Create the spectrum
spec1 = simulated_spectra.s1_um_mJy_e1
flux_original = spec1.flux
# Create the flux_smoothed which is what we want to compare to
trapezoid_kernel = convolution.Trapezoid1DKernel(stddev)
flux_smoothed_astropy = convolution.convolve(flux_original,
trapezoid_kernel)
# Test trapezoid smoothing
spec1_smoothed = trapezoid_smooth(spec1, stddev)
compare_flux(spec1_smoothed.flux.value, flux_smoothed_astropy,
flux_original.value)
# Check the input and output units
assert spec1.wavelength.unit == spec1_smoothed.wavelength.unit
assert spec1.flux.unit == spec1_smoothed.flux.unit
assert len(spec1.meta) == len(spec1_smoothed.meta)
def trapezoid_smooth(spectrum, width):
"""
Smoothing based on a `astropy.convolution.Trapezoid1DKernel` kernel.
Parameters
----------
spectrum : `~specutils.Spectrum1D`
The `~specutils.Spectrum1D` object to which the smoothing will be applied.
width : number
The width of the kernel, in pixels, as defined in `astropy.convolution.Trapezoid1DKernel`
Returns
-------
spectrum : `~specutils.Spectrum1D`
Output `~specutils.Spectrum1D` which is copy of the one passed in with the updated flux.
Raises
------
ValueError
In the case that ``width`` is not the correct type or value.
"""
# Parameter checks
if not isinstance(width, (int, float)) or width <= 0:
raise ValueError('The stddev parameter, {}, must be a number greater than 0'.format(
width))
# Create the gaussian kernel
trapezoid_kernel = convolution.Trapezoid1DKernel(width)
# Call and return the convolution smoothing.
return convolution_smooth(spectrum, trapezoid_kernel)