simpunch.level0#

Generate synthetic level 0 data.

Functions#

`perform_photometric_uncalibration`(→ ndcube.NDCube)	Undo quartic fit calibration.
`add_spikes`(→ tuple[ndcube.NDCube, numpy.ndarray])	Add spikes to images.
`create_streak_matrix`(→ numpy.ndarray)	Construct the matrix that streaks an image.
`apply_streaks`(→ ndcube.NDCube)	Apply the streak matrix to the image.
`add_deficient_pixels`(→ ndcube.NDCube)	Add deficient pixels to the image.
`add_stray_light`(→ ndcube.NDCube)	Add stray light to the image.
`uncorrect_psf`(→ ndcube.NDCube)	Apply an inverse PSF to an image.
`add_transients`() → ndcube.NDCube)	Add a block of brighter transient data to simulate aurora.
`starfield_misalignment`(→ ndcube.NDCube)	Offset the pointing in an image to simulate spacecraft uncertainty.
`apply_mask`(→ ndcube.NDCube)	Apply the appropriate instrument mask to a NDCube.
`generate_l0_pmzp`(→ str)	Generate level 0 polarized synthetic data.
`generate_l0_cr`(→ str)	Generate level 0 clear synthetic data.

Module Contents#

simpunch.level0.perform_photometric_uncalibration(input_data: ndcube.NDCube, coefficient_array: numpy.ndarray) → ndcube.NDCube[source]#: Undo quartic fit calibration.

simpunch.level0.add_spikes(input_data: ndcube.NDCube) → tuple[ndcube.NDCube, numpy.ndarray][source]#: Add spikes to images.

simpunch.level0.create_streak_matrix(n: int, exposure_time: float, readout_line_time: float, reset_line_time: float) → numpy.ndarray[source]#: Construct the matrix that streaks an image.

simpunch.level0.apply_streaks(input_data: ndcube.NDCube, exposure_time: float = 49 * 1000, readout_line_time: float = 163 / 2148, reset_line_time: float = 163 / 2148) → ndcube.NDCube[source]#: Apply the streak matrix to the image.

simpunch.level0.add_deficient_pixels(input_data: ndcube.NDCube) → ndcube.NDCube[source]#: Add deficient pixels to the image.

simpunch.level0.add_stray_light(input_data: ndcube.NDCube, inst: str = 'WFI', polar: str = 'mzp') → ndcube.NDCube[source]#: Add stray light to the image.

simpunch.level0.uncorrect_psf(input_data: ndcube.NDCube, psf_model: regularizepsf.ArrayPSFTransform) → ndcube.NDCube[source]#: Apply an inverse PSF to an image.

simpunch.level0.add_transients(input_data: ndcube.NDCube, transient_area: int = 600**2, transient_probability: float = 0.03, transient_brightness_range: tuple[float, float] = (0.6, 0.8)) → ndcube.NDCube[source]#: Add a block of brighter transient data to simulate aurora.

simpunch.level0.starfield_misalignment(input_data: ndcube.NDCube, cr_offset_scale: float = 0.1, pc_offset_scale: float = 0.1) → ndcube.NDCube[source]#: Offset the pointing in an image to simulate spacecraft uncertainty.

simpunch.level0.apply_mask(input_data: ndcube.NDCube) → ndcube.NDCube[source]#: Apply the appropriate instrument mask to a NDCube.

simpunch.level0.generate_l0_pmzp(input_file: str, path_output: str, psf_model_path: str | collections.abc.Callable, wfi_quartic_coeffs_path: str | collections.abc.Callable, nfi_quartic_coeffs_path: str | collections.abc.Callable, transient_probability: float = 0.03, shift_pointing: bool = False) → str[source]#: Generate level 0 polarized synthetic data.

simpunch.level0.generate_l0_cr(input_file: str, path_output: str, psf_model_path: str | collections.abc.Callable, wfi_quartic_coeffs_path: str | collections.abc.Callable, nfi_quartic_coeffs_path: str | collections.abc.Callable, transient_probability: float = 0.03, shift_pointing: bool = False) → str[source]#: Generate level 0 clear synthetic data.