Source code for punchbowl.data.units

import astropy.constants as const
import astropy.units as u
import numpy as np
from astropy.wcs import WCS
from numpy import ndarray

MSB = u.def_unit("MSB", 2.0090000E7 * u.W / u.m ** 2 / u.sr)


[docs] def calculate_image_pixel_area(wcs: WCS, data_shape: tuple[int, int], stride: int = 1) -> u.sr: """Calculate the sky area of every pixel in an image according to its WCS.""" xx, yy = np.meshgrid(np.arange(0, data_shape[1], stride), np.arange(0, data_shape[0], stride)) coords_ctr = wcs.pixel_to_world(xx, yy) lon_ctr, lat_ctr = coords_ctr.Tx.degree, coords_ctr.Ty.degree dx = wcs.pixel_to_world(xx + stride, yy) lon_dx, lat_dx = dx.Tx.degree, dx.Ty.degree dy = wcs.pixel_to_world(xx, yy + stride) lon_dy, lat_dy = dy.Tx.degree, dy.Ty.degree dlon_dx = ((lon_dx - lon_ctr + 180) % 360 - 180) / stride dlon_dy = ((lon_dy - lon_ctr + 180) % 360 - 180) / stride dlat_dx = (lat_dx - lat_ctr) / stride dlat_dy = (lat_dy - lat_ctr) / stride # The width of a degree of HPLN/RA shrinks as we move toward the poles cos_lat = np.cos(np.radians(lat_ctr)) # Compute the Jacobian Determinant (Area) # Area = | (dlon_dx * cos_lat * dlat_dy) - (dlon_dy * cos_lat * dlat_dx) | return np.abs((dlon_dx * cos_lat * dlat_dy) - (dlon_dy * cos_lat * dlat_dx))* u.deg**2
[docs] def msb_to_dn(data: ndarray, data_wcs: WCS, gain_bottom: float = 4.9 * u.photon / u.DN, gain_top: float = 4.9 * u.photon / u.DN, wavelength: float = 530. * u.nm, exposure: float = 49 * u.s, aperture: float = 49.57 * u.mm**2, pixel_area_stride: int = 1, ) -> ndarray: """Convert mean solar brightness to DNs.""" energy_per_photon = (const.h * const.c / wavelength).to(u.J) / u.photon photon_flux = MSB / energy_per_photon pixel_scale = calculate_image_pixel_area(data_wcs, data.shape, pixel_area_stride).to(u.sr) / u.pixel photon_count = (photon_flux * exposure * aperture * pixel_scale * u.pixel).decompose() gain = split_ccd_array(data.shape, gain_bottom, gain_top) return data * photon_count / gain
[docs] def dn_to_msb(data: ndarray, data_wcs: WCS, gain_bottom: float = 4.9 * u.photon / u.DN, gain_top: float = 4.9 * u.photon / u.DN, wavelength: float = 530. * u.nm, exposure: float = 49 * u.s, aperture: float = 34 * u.mm**2, pixel_area_stride: int = 1, pixel_scale: u.Quantity = None, ) -> ndarray: """Convert DN to mean solar brightness.""" energy_per_photon = (const.h * const.c / wavelength).to(u.J) / u.photon photon_flux = MSB / energy_per_photon if pixel_scale is None: pixel_scale = calculate_image_pixel_area(data_wcs, data.shape, pixel_area_stride).to(u.sr) / u.pixel photon_count = (photon_flux * exposure * aperture * pixel_scale * u.pixel) gain = split_ccd_array(data.shape, gain_bottom, gain_top) factor = (gain / photon_count).decompose().value return data * factor
[docs] def split_ccd_array(shape:tuple, value_bottom:float, value_top:float) -> ndarray: """Generate parameters across CCD halves.""" array = np.zeros(shape) array[:,:shape[1]//2] = value_bottom array[:,shape[1]//2:] = value_top return array.T