coronalyze.core.photometry

coronalyze.core.photometry#

Convolution-based aperture photometry for coronagraphic images.

Provides differentiable aperture kernels (soft and hard) and convolution-based flux map generation for efficient photometry calculations.

Functions#

make_aperture_kernel(radius[, soft, sharpness])

Create a circular aperture kernel for convolution-based photometry.

flux_map(image, kernel)

Generate a flux map via convolution with an aperture kernel.

circular_aperture_mask(shape, center, radius)

Create a circular aperture mask.

soft_aperture_mask(shape, center, radius[, sharpness])

Create a soft (differentiable) circular aperture mask.

aperture_photometry(image, center, radius)

Perform circular aperture photometry on an image.

aperture_solid_angle(radius_pixels, pixel_scale_arcsec)

Calculate the solid angle of a circular aperture.

Module Contents#

coronalyze.core.photometry.make_aperture_kernel(radius, soft=False, sharpness=10.0)[source]#

Create a circular aperture kernel for convolution-based photometry.

This function is cached (up to 32 configurations) to avoid repeated kernel creation overhead when called with the same parameters.

Args:

radius: Aperture radius in pixels. soft: If True, use sigmoid-based soft edge for differentiability.

If False, use hard binary mask.

sharpness: Steepness of sigmoid transition (only used if soft=True).

Returns:

2D aperture kernel. Not normalized (sum of counts, not average).

Parameters:

  • radius (float)

  • soft (bool)

  • sharpness (float)

Return type:

jax.numpy.ndarray

coronalyze.core.photometry.flux_map(image, kernel)[source]#

Generate a flux map via convolution with an aperture kernel.

Each pixel in the output represents the integrated flux that would be measured if an aperture were centered at that position.

Args:

image: 2D image array. kernel: Aperture kernel from make_aperture_kernel.

Returns:

2D flux map with same shape as input image.

Parameters:

  • image (jax.numpy.ndarray)

  • kernel (jax.numpy.ndarray)

Return type:

jax.numpy.ndarray

coronalyze.core.photometry.circular_aperture_mask(shape, center, radius)[source]#

Create a circular aperture mask.

Args:

shape: Image shape (ny, nx). center: Center of aperture (y, x) in pixels. radius: Radius of aperture in pixels.

Returns:

Boolean mask array with True inside the aperture.

Parameters:

  • shape (tuple[int, int])

  • center (tuple[float, float])

  • radius (float)

Return type:

jax.numpy.ndarray

coronalyze.core.photometry.soft_aperture_mask(shape, center, radius, sharpness=10.0)[source]#

Create a soft (differentiable) circular aperture mask.

Uses a sigmoid function to create a smooth transition at the aperture edge, enabling gradient-based optimization through the mask.

Args:

shape: Image shape (ny, nx). center: Center of aperture (y, x) in pixels. radius: Radius of aperture in pixels. sharpness: Steepness of the sigmoid transition.

Returns:

Soft mask array with values in [0, 1].

Parameters:

  • shape (tuple[int, int])

  • center (tuple[float, float])

  • radius (float)

  • sharpness (float)

Return type:

jax.numpy.ndarray

coronalyze.core.photometry.aperture_photometry(image, center, radius)[source]#

Perform circular aperture photometry on an image.

Args:

image: 2D image array. center: Center of aperture (y, x) in pixels. radius: Radius of aperture in pixels.

Returns:

Total flux within the aperture.

Parameters:

  • image (jax.numpy.ndarray)

  • center (tuple[float, float])

  • radius (float)

Return type:

float

coronalyze.core.photometry.aperture_solid_angle(radius_pixels, pixel_scale_arcsec)[source]#

Calculate the solid angle of a circular aperture.

Args:

radius_pixels: Aperture radius in pixels. pixel_scale_arcsec: Pixel scale in arcseconds per pixel.

Returns:

Solid angle in arcsec^2.

Parameters:

  • radius_pixels (float)

  • pixel_scale_arcsec (float)

Return type:

float

Contents