SubarrayDescription#

class ctapipe.instrument.SubarrayDescription(name, tel_positions, tel_descriptions, reference_location)[source]#

Bases: object

Collects the TelescopeDescription of all telescopes along with their positions on the ground.

Attributes:
name: str

name of subarray

tel_coords: ctapipe.coordinates.GroundFrame

coordinates of all telescopes

tels:

dict of TelescopeDescription for each telescope in the subarray

Attributes Summary

COMPATIBLE_VERSIONS

Version numbers supported by SubarrayDescription.from_hdf

CURRENT_TAB_VERSION

Current version number of the format written by SubarrayDescription.to_hdf

camera_types

Tuple of unique camera types in the array

footprint

area of smallest circle containing array on ground

n_tels

number of telescopes in this subarray

optics_types

Tuple of unique optics types in the array

tel

Dictionary mapping tel_ids to TelescopeDescriptions

tel_coords

Telescope positions in GroundFrame

tel_ids

Array of telescope ids in order of telescope indices

tel_index_array

Array of telescope indices that can be indexed by telescope id

tel_indices

dictionary mapping telescope ids to telescope index

telescope_types

Tuple of unique telescope types in the array

Methods Summary

from_hdf(path[, focal_length_choice])

get_tel_ids(telescopes)

Convert a list of telescope ids and telescope descriptions to a list of unique telescope ids.

get_tel_ids_for_type(tel_type)

return tuple of tel_ids that have the given tel_type

get_tel_indices_for_type(tel_type)

return tuple of telescope indices that have the given tel_type

info([printer])

print descriptive info about subarray

multiplicity(tel_mask[, tel_type])

Compute multiplicity from a telescope mask

peek([ax])

Draw a quick matplotlib plot of the array

read(path, **kwargs)

Read subarray from path

select_subarray(tel_ids[, name])

return a new SubarrayDescription that is a sub-array of this one

tel_ids_to_indices(tel_ids)

maps a telescope id (or array of them) to flat indices

tel_ids_to_mask(tel_ids)

Convert a list of telescope ids to a boolean mask of length n_tels where the index of the telescope is set to True for each tel_id in tel_ids

tel_mask_to_tel_ids(tel_mask)

Convert a boolean mask of selected telescopes to a list of tel_ids.

to_hdf(h5file[, overwrite, mode])

write the SubarrayDescription

to_table([kind])

export SubarrayDescription information as an astropy.table.Table

Attributes Documentation

COMPATIBLE_VERSIONS = {'2.0'}#

Version numbers supported by SubarrayDescription.from_hdf

CURRENT_TAB_VERSION = '2.0'#

Current version number of the format written by SubarrayDescription.to_hdf

camera_types#

Tuple of unique camera types in the array

The entries are ordered by camera name to be deterministic but the order should not be relied on.

footprint#

area of smallest circle containing array on ground

n_tels#

number of telescopes in this subarray

optics_types#

Tuple of unique optics types in the array

The entries are ordered by optics name to be deterministic but the order should not be relied on.

tel#

Dictionary mapping tel_ids to TelescopeDescriptions

tel_coords#

Telescope positions in GroundFrame

tel_ids#

Array of telescope ids in order of telescope indices

tel_index_array#

Array of telescope indices that can be indexed by telescope id

I.e. for a given telescope, this array maps the tel_id to a flat index starting at 0 for the first telescope. tel_index = subarray.tel_index_array[tel_id]

If the tel_ids are not contiguous, gaps will be filled in by int minval. For a more compact representation use the tel_indices

tel_indices#

dictionary mapping telescope ids to telescope index

telescope_types#

Tuple of unique telescope types in the array

The entries are ordered by telescope name to be deterministic but the order should not be relied on.

Methods Documentation

classmethod from_hdf(path, focal_length_choice=FocalLengthKind.EFFECTIVE)[source]#
get_tel_ids(telescopes: Iterable[int | str | TelescopeDescription]) tuple[int][source]#

Convert a list of telescope ids and telescope descriptions to a list of unique telescope ids.

Parameters:
telescopes: List[Union[int, str, TelescopeDescription]]

List of Telescope IDs and descriptions. Supported inputs for telescope descriptions are instances of TelescopeDescription as well as their string representation.

Returns:
tel_ids: List[int]

List of unique telescope ids matching telescopes

get_tel_ids_for_type(tel_type) tuple[int][source]#

return tuple of tel_ids that have the given tel_type

Parameters:
tel_type: str or TelescopeDescription

telescope type string (e.g. ‘MST_MST_NectarCam’)

get_tel_indices_for_type(tel_type)[source]#

return tuple of telescope indices that have the given tel_type

Parameters:
tel_type: str or TelescopeDescription

telescope type string (e.g. ‘MST_MST_NectarCam’)

info(printer=<built-in function print>)[source]#

print descriptive info about subarray

multiplicity(tel_mask, tel_type=None)[source]#

Compute multiplicity from a telescope mask

Parameters:
tel_masknp.ndarray

Boolean array with last dimension of size n_telescopes

tel_typeNone, str or TelescopeDescription

If not given, compute multiplicity from all telescopes. If given, the multiplicity of the given telescope type will be computed.

Returns:
multiplicityint or np.ndarray

Number of true values for given telescope mask and telescope type

peek(ax=None)[source]#

Draw a quick matplotlib plot of the array

Parameters:
axmatplotlib.axes.Axes or None

If given, the subarray will be plotted into this ax.

static read(path, **kwargs)[source]#

Read subarray from path

This uses the EventSource mechanism, so it should be able to read a subarray from any file supported by ctapipe or an installed io plugin.

kwargs are passed to the event source

select_subarray(tel_ids, name=None) SubarrayDescription[source]#

return a new SubarrayDescription that is a sub-array of this one

Parameters:
tel_ids: list(int)

list of telescope IDs to include in the new subarray

name: str

name of new sub-selection

Returns
——-
SubarrayDescription
tel_ids_to_indices(tel_ids)[source]#

maps a telescope id (or array of them) to flat indices

Parameters:
tel_idsint or List[int]

array of tel IDs

Returns:
np.array:

array of corresponding tel indices

tel_ids_to_mask(tel_ids)[source]#

Convert a list of telescope ids to a boolean mask of length n_tels where the index of the telescope is set to True for each tel_id in tel_ids

Parameters:
tel_idsint or List[int]

array of tel IDs

Returns:
np.array[dtype=bool]:

Boolean array of length n_tels with indices of the telescopes in tel_ids set to True.

tel_mask_to_tel_ids(tel_mask)[source]#

Convert a boolean mask of selected telescopes to a list of tel_ids.

Parameters:
tel_mask: array-like

Boolean array of length n_tels with indices of the telescopes in tel_ids set to True.

Returns
——-
np.array:

Array of selected tel_ids

to_hdf(h5file, overwrite=False, mode='a')[source]#

write the SubarrayDescription

Parameters:
h5filestr, bytes, path or tables.File

Path or already opened tables.File with write permission

overwriteFalse

If the output path already contains a subarray, by default an error will be raised. Set overwrite=True to overwrite an existing subarray. This does not affect other content of the file. Use mode="w" to completely overwrite the output path.

modestr

If h5file is not an already opened file, the output file will be opened with the given mode. Must be a mode that enables writing.

to_table(kind='subarray')[source]#

export SubarrayDescription information as an astropy.table.Table

Parameters:
kind: str

which table to generate (subarray or optics)