ScienceData#

class stixpy.product.sources.ScienceData(*, meta, control, data, energies, idb_versions=None)[source]#

Bases: L1Product

Basic science data class

Attributes Summary

`detectors`	A `stixpy.science.DetectorMasks` object representing the detectors contained in the data.
`duration`	An `astropy.units.Quantiy` array giving the duration or integration time
`energies`	A `astropy.table.Table` object representing the energies contained in the data.
`level`
`pixels`	A `stixpy.science.PixelMasks` object representing the pixels contained in the data
`service_subtype`	Service subtype
`service_type`	Service type
`ssid`	Science Structure ID for product
`time_range`	A `sunpy.time.TimeRange` for the data.
`times`	An `astropy.time.Time` array representing the center of the observed time bins.

Methods Summary

`concatenate`(others)	Concatenate two or more science products.
`get_data`([time_indices, energy_indices, ...])	Return the counts, errors, times, durations and energies for selected data.

Attributes Documentation

detectors#: A stixpy.science.DetectorMasks object representing the detectors contained in the data.

duration#: An astropy.units.Quantiy array giving the duration or integration time

energies#: A astropy.table.Table object representing the energies contained in the data.

pixels#: A stixpy.science.PixelMasks object representing the pixels contained in the data

times#: An astropy.time.Time array representing the center of the observed time bins.

Methods Documentation

concatenate(others)[source]#

Concatenate two or more science products.

Parameters:: others (list [stixpy.science.ScienceData]) – The other/s science products to concatenate
Returns:: stixpy.science.ScienceData – The concatenated science products

get_data(time_indices=None, energy_indices=None, detector_indices=None, pixel_indices=None, sum_all_times=False)[source]#

Return the counts, errors, times, durations and energies for selected data.

Optionally summing in time and or energy.

Parameters:

time_indices (list or numpy.ndarray) – If an 1xN array will be treated as mask if 2XN array will sum data between given indices. For example time_indices=[0, 2, 5] would return only the first, third and sixth times while time_indices=[[0, 2],[3, 5]] would sum the data between.
energy_indices (list or numpy.ndarray) – If an 1xN array will be treated as mask if 2XN array will sum data between given indices. For example energy_indices=[0, 2, 5] would return only the first, third and sixth times while energy_indices=[[0, 2],[3, 5]] would sum the data between.
detector_indices (list or numpy.ndarray) – If an 1xN array will be treated as mask if 2XN array will sum data between given indices. For example detector_indices=[0, 2, 5] would return only the first, third and sixth detectors while detector_indices=[[0, 2],[3, 5]] would sum the data between.
pixel_indices (list or numpy.ndarray) – If an 1xN array will be treated as mask if 2XN array will sum data between given indices. For example pixel_indices=[0, 2, 5] would return only the first, third and sixth pixels while pixel_indices=[[0, 2],[3, 5]] would sum the data between.
sum_all_times (bool) – Flag to sum all give time intervals into one

Returns:

tuple – Counts, errors, times, deltatimes, energies