PSF Function

It might be, that you do not have an actual PSF file of the PSF you want to “observe” your synthetic image with. In this case you could convolve with a 2D function:

function(X, Y, wavelength)

To construct your own function in Python you can simply write something like this:

def my_psf(X,Y,wavelength):
    # resolution in rad/pixel
    resolution = FC_object.FOV[0] / FC_object.distance / FC_object.pixel[0]

    # telescope diameter in cm
    D_telescope = 350.

    # standard deviation in pixel
    sigma = 0.44 * wavelength / D_telescope / resolution

    Z = np.exp(-(X**2 + Y**2)/(2 * sigma**2))

    return Z

Note

You can call attributes of the FC_objects like distance, FOV, etc. For more information see FluxCompensator objects.

Now to construct the psf_object add to you script:

from fluxcompensator.psf import FunctionPSF

# create PSF from a function
psf_object = FunctionPSF(psf_function=my_psf, width=32)

width is the size in pixel of the created 2D PSF function grid . X and Y in the definition of the my_psf represent the x and y coordinates in an array centered around 0 to width/2. X and Y are passed by FunctionPSF. wavelength is passed by fluxcompensator.cube.SyntheticCube.convolve_psf() or fluxcompensator.image.SyntheticImage.convolve_psf().

For further information see:

• fluxcompensator.psf.FunctionPSF