%matplotlib inline
%reload_ext autoreload
%autoreload 2
import os
import galsim
import astropy.io.fits as pyfits

ngrid = 64
nx = 100
ny = nx
ud = 1
scale = 0.168

variance = 0.01
ud = galsim.UniformDeviate(1)

# setup the galaxy image and the noise image
noi_image = galsim.ImageF(nx * ngrid, ny * ngrid, scale=scale)
noi_image.setOrigin(0, 0)
corNoise = galsim.getCOSMOSNoise(
    file_name="./data/correlation.fits",
    rng=ud,
    cosmos_scale=scale,
    variance=variance,
)
corNoise.applyTo(noi_image)

galsim.Image(bounds=galsim.BoundsI(xmin=0, xmax=6399, ymin=0, ymax=6399), array=
array([[-0.06387837, -0.11317293, -0.09092055, ...,  0.12231466,
        -0.0595307 , -0.16100994],
       [ 0.04106306, -0.09442233, -0.14250383, ..., -0.06676477,
         0.01649002,  0.12679401],
       [ 0.00905336,  0.03324465, -0.13445288, ...,  0.00234344,
        -0.01069246,  0.03849047],
       ...,
       [-0.1181237 , -0.14214994,  0.02201384, ...,  0.00943333,
        -0.05264562, -0.01232291],
       [ 0.08748364, -0.04552655, -0.10468618, ...,  0.14591035,
        -0.03094922, -0.06359212],
       [ 0.01262801, -0.22272049, -0.27546167, ...,  0.15163177,
         0.0438892 , -0.1618046 ]], dtype=float32), wcs=galsim.OffsetWCS(0.168, galsim.PositionI(x=-1, y=-1), galsim.PositionD(x=0.0, y=0.0)))