Convert camera images to pixels on a s square grid

import astropy.units as u
import matplotlib.pyplot as plt

from ctapipe.image.toymodel import Gaussian
from ctapipe.instrument import SubarrayDescription
from ctapipe.visualization import CameraDisplay

get the subarray from an example file

subarray = SubarrayDescription.read("dataset://gamma_prod5.simtel.zst")

Geometries with square pixels

Define a camera geometry and generate a dummy image:

geom = subarray.tel[40].camera.geometry
model = Gaussian(
    x=0.05 * u.m,
    y=0.05 * u.m,
    width=0.01 * u.m,
    length=0.05 * u.m,
    psi="30d",
)
_, image, _ = model.generate_image(geom, intensity=500, nsb_level_pe=3)

CameraDisplay(geom, image)

<ctapipe.visualization.mpl_camera.CameraDisplay object at 0x79f094d37c70>

The CameraGeometry has functions to convert the 1d image arrays to 2d arrays and back to the 1d array:

image_square = geom.image_to_cartesian_representation(image)

plt.imshow(image_square)

<matplotlib.image.AxesImage object at 0x79f08bac9a80>

image_1d = geom.image_from_cartesian_representation(image_square)

CameraDisplay(geom, image_1d)

<ctapipe.visualization.mpl_camera.CameraDisplay object at 0x79f08af8a980>

Geometries with hexagonal pixels

Define a camera geometry and generate a dummy image:

geom = subarray.tel[1].camera.geometry
model = Gaussian(
    x=0.5 * u.m,
    y=0.5 * u.m,
    width=0.1 * u.m,
    length=0.2 * u.m,
    psi="30d",
)
_, image, _ = model.generate_image(geom, intensity=5000)

CameraDisplay(geom, image)

<ctapipe.visualization.mpl_camera.CameraDisplay object at 0x79f08b5d2800>

image_square = geom.image_to_cartesian_representation(image)

Conversion into square geometry

Since the resulting array has square pixels, the pixel grid has to be rotated and distorted. This is reversible (The image_from_cartesian_representation method takes care of this):

plt.imshow(image_square)

<matplotlib.image.AxesImage object at 0x79f08a954220>

image_1d = geom.image_from_cartesian_representation(image_square)

disp = CameraDisplay(geom, image_1d)