Toy Coronagraph

The toycoronagraph package is implemented in Python

Language	Release	Note
Python	On PyPI	though not always the most recent version

for simulating coronagraphs. It is designed to be simple and easy to use, while still providing a powerful and flexible framework for simulating a variety of coronagraph designs.

The package includes a number of pre-defined coronagraph designs, as well as a library of functions for creating custom coronagraphs. It also includes a number of tools for visualizing the results of simulations, such as ray tracing plots and intensity maps.

The toycoronagraph package is open source and available on GitHub. It is a valuable tool for anyone interested in learning about coronagraphs or simulating the performance of coronagraph designs.

Here are some of the features of this package:

• Simple and easy to use
• Powerful and flexible framework
• Pre-defined coronagraph designs
• Library of functions for creating custom coronagraphs
• Tools for visualizing the results of simulations
• Open source and available on GitHub

Here are some of the applications of this package:

• Learning about coronagraphs
• Simulating the performance of coronagraph designs
• Designing new coronagraph designs
• Testing the performance of coronagraph hardware
• Studying the physics of light scattering

Example

example target	Final image (Charge=2)	Final image (Charge=6)

with planets

Pre-image	Final image (Charge=6)

Turn on/off dust inside IWA

Final image (Charge=6)	Final image but ignored dust inside IWA (Charge=6)

Moving planet on an elliptic orbit

Frame definition

Plot the orbit (time = 0.2 period, starting from the perihelion and moving clockwise in the figure)

User could even make a video now

Video (Charge=6)	Video but ignored dust inside IWA (Charge=6)

Example usage (Python)

This py file illustrates how the Python package is used.

import toycoronagraph.main as toy

# Load the example target image (example.fits) in Toy_Coronagraph/toycoronagraph/example_data/ folder
toy_target = toy.Target()

# Plot the preimage; the image will auto-save to origin.png
toy_target.plot_origin()

# Plot the final image through vortex coronagraph with charge = 2; the image will auto-save to charge2_final.png
toy_target.plot_final(charge=2)

# Plot the final image through vortex coronagraph with charge = 6; the image will auto-save to charge6_final.png
toy_target.plot_final(charge=6)

# Now add a static planet, where pos=(x_position, y_position)
toy_target.add_planet(pos=[0.5,0], brightness=0.00005, mode="cartesian")

# You could also add a moving planet on an elliptic orbit, where pos=(length of the semi-major axis, eccentricity, position angle, inclination angle, time/period))
toy_target.add_planet(pos=[0.5,0.6,60,0,0.1], brightness=0.00003, mode="moving")

# Plot the preimage with planets; the image will auto-save to origin_with_planets.png
toy_target.plot_origin()

# Plot the final image with planets; the image will auto-save to charge6_with_planets_final.png
toy_target.plot_final(charge=6)

# Plot the final image by turning off the target inside IWA; the image will auto-save to charge6_with_planets_iwa_ignore_final.png
toy_target.plot_final(charge=6, iwa_ignore=True)

# List the planets
toy_target.list_planets()
'''
Static Planet 1: (0.5, 0.0) arcsec, brightness: 5.00e-05 Jy
Moving Planet 2: (-0.3818058424930897, 0.08394161212137384) arcsec, brightness: 3.00e-05 Jy
'''

# Delete a specific planet
toy_target.delete_planet(order=1)
'''
Successfully remove planet #1, here is the latest planet list:
Moving Planet 1: (-0.3818058424930897, 0.08394161212137384) arcsec, brightness: 3.00e-05 Jy
'''

# Move a moving planet on its orbit by time/period=0.1
toy_target.planet_move(time=0.1, order=1)
'''
Planet has moved to new position
'''

# Plot the orbit of a specific moving planet; the image will auto-save to oribit_planet#.png
toy_target.plot_orbit(order=1)

# Plot the new preimage with planets; the image will auto-save to origin_with_planets.png
toy_target.plot_origin()

# Plot the new final image with planets; the image will auto-save to charge6_with_planets_final.png
toy_target.plot_final(charge=6)

# Print a specific planet brightness, background brightness, and background brightness (ignored dust inside IWA) in the final image through vortex coronagraph with charge = 6
toy_target.contrast(charge=6, order=1)
'''
This is a charge-6 vortex coronagraph.
'''

# Plot the core_throughput and inner working angle (in pixel)
import toycoronagraph.psf as psf
import numpy as np
psfs = np.load("psfs_c2.npy")
psf.cir_core_throughput_plot(psfs)

# Make the planet movie
toy_target.planet_video(charge=6)
# The video will be save to planet_video.mp4

# Make the planet movie again, but ignore the dust inside IWA
toy_target.planet_video(charge=6, iwa_ignore=True)
# The video will be save to planet_video_iwa_ignore.mp4

More instructions could be found in docs.