punchbowl.level1.initial_uncertainty#

Functions#

dn_to_photons(→ numpy.ndarray)

Convert an input array from DN to photon count.

compute_noise(→ numpy.ndarray)

Generate noise based on an input data array, with specified noise parameters.

compute_uncertainty(→ numpy.ndarray)

With an input data array compute a corresponding uncertainty array.

update_initial_uncertainty_task(→ ndcube.NDCube)

Prefect task to compute initial uncertainty.

Module Contents#

punchbowl.level1.initial_uncertainty.dn_to_photons(data_array: numpy.ndarray, gain: float = 4.3) → numpy.ndarray#

Convert an input array from DN to photon count.

punchbowl.level1.initial_uncertainty.compute_noise(data: numpy.ndarray, bias_level: float = 100, dark_level: float = 55.81, gain: float = 4.9, read_noise_level: float = 17, bitrate_signal: int = 16) → numpy.ndarray#

Generate noise based on an input data array, with specified noise parameters.

Parameters:

  • data – input data array (n x n)

  • bias_level – ccd bias level

  • dark_level – ccd dark level

  • gain – ccd gain

  • read_noise_level – ccd read noise level

  • bitrate_signal – desired ccd data bit level

Returns:

computed noise array corresponding to input data and ccd/noise parameters

Return type:

np.ndarray

punchbowl.level1.initial_uncertainty.compute_uncertainty(data_array: numpy.ndarray, bias_level: float = 100, dark_level: float = 55.81, gain: float = 4.9, read_noise_level: float = 17, bitrate_signal: int = 16) → numpy.ndarray#

With an input data array compute a corresponding uncertainty array.

punchbowl.level1.initial_uncertainty.update_initial_uncertainty_task(data_object: ndcube.NDCube, bias_level: float = 100, dark_level: float = 55.81, gain: float = 4.9, read_noise_level: float = 17, bitrate_signal: int = 16) → ndcube.NDCube#

Prefect task to compute initial uncertainty.