Examples

Gaussian

The following code scatters a Gaussian source.

First, we generate our source model as a 2D numpy array.

import matplotlib.pyplot as plt
import numpy as np

# construct gaussian source
nx,ny = 220,256
yy,xx = np.meshgrid(np.arange(ny)-ny/2,np.arange(nx)-nx/2,indexing='ij')
isrc = np.exp(-0.5*(xx**2 + yy**2) / (0.07*np.min([nx,ny]))**2)

Next we generate the screen which will be written to the file gaussian_screen.bin. This permits us to run many simulations using the same screen.

# generate screen
generate_screen(screenfile='gaussian_screen.bin')

# scatter source
iss = run_slimscat(isrc,1.,screenfile='gaussian_screen.bin')

Our gaussian source appears to have been scrambled by our simulated screen.

Gargantua

In this example we will have a bit of fun and use an image rendered to look like the supermassive black hole from the movie Interstellar.

Image by BlackRainbow

We’ll generate the screen for observations at a slightly smaller wavelength and higher resolution.

# generate scattering file
generate_screen(wavelength=0.87e-6,dx=0.2,ips=4,screenfile='gargantua_screen.bin')

And we’ll run the simulation over each RGB channel disregarding the important dependence on wavelength.

# load RGB image with rough scale appropriate for Sgr A*
model = misc.imread('gargantua.jpg')
dx = 50./350    # photon ring diameter is about 50 microarcseconds
nx,ny,nchan = model.shape

# scatter each rgb channel separately (using same screen)
r = run_slimscat(model[:,:,0],dx,screenfile='gargantua_screen.bin')
g = run_slimscat(model[:,:,1],dx,screenfile='gargantua_screen.bin')
b = run_slimscat(model[:,:,1],dx,screenfile='gargantua_screen.bin')

And Gargantua appears scattered: