TableLoader¶

class ctapipe.io.tableloader.TableLoader(**kwargs: Any)[source]¶

Bases: ctapipe.core.component.Component

Load telescope-event or subarray-event data from ctapipe HDF5 files

This class provides high-level access to data stored in ctapipe HDF5 files, such as created by the ctapipe-process tool (ProcessorTool).

The following TableLoader methods load data from all relevant tables, depending on the options, and joins them into single tables:

TableLoader.read_subarray_events
TableLoader.read_telescope_events
TableLoader.read_telescope_events_by_type retuns a dict with a table per telescope type, which is needed for e.g. DL1 image data that might have different shapes for each of the telescope types as tables do not support variable length columns.

Attributes

subarraySubarrayDescription: The subarray as read from input_url.

Attributes Summary

`focal_length_choice`	Use a Enum class as model for the data type description.
`input_url`	A path Trait for input/output files.
`load_dl1_images`	A boolean (True, False) trait.
`load_dl1_parameters`	A boolean (True, False) trait.
`load_dl2`	A boolean (True, False) trait.
`load_instrument`	A boolean (True, False) trait.
`load_simulated`	A boolean (True, False) trait.
`load_true_images`	A boolean (True, False) trait.
`load_true_parameters`	A boolean (True, False) trait.

Methods Summary

`close`()	Close the underlying hdf5 file
`read_shower_distribution`()	Read the simulated shower distribution histograms
`read_simulation_configuration`()	Read the simulation configuration table
`read_subarray_events`([start, stop, keep_order])	Read subarray-based event information.
`read_subarray_events_chunked`(chunk_size)	Iterate over chunks of subarray events.
`read_telescope_events`([telescopes, start, stop])	Read telescope-based event information.
`read_telescope_events_by_type`([telescopes, …])	Read telescope-based event information.
`read_telescope_events_by_type_chunked`(…)	Iterate over chunks of telescope events.
`read_telescope_events_chunked`(chunk_size, …)	Iterate over chunks of telescope events.

Attributes Documentation

focal_length_choice¶

Use a Enum class as model for the data type description. Note that if no default-value is provided, the first enum-value is used as default-value.

# -- SINCE: Python 3.4 (or install backport: pip install enum34)
import enum
from traitlets import HasTraits, UseEnum

class Color(enum.Enum):
    red = 1         # -- IMPLICIT: default_value
    blue = 2
    green = 3

class MyEntity(HasTraits):
    color = UseEnum(Color, default_value=Color.blue)

entity = MyEntity(color=Color.red)
entity.color = Color.green    # USE: Enum-value (preferred)
entity.color = "green"        # USE: name (as string)
entity.color = "Color.green"  # USE: scoped-name (as string)
entity.color = 3              # USE: number (as int)
assert entity.color is Color.green

input_url¶

A path Trait for input/output files.

Attributes

exists: boolean or None: If True, path must exist, if False path must not exist
directory_ok: boolean: If False, path must not be a directory
file_ok: boolean: If False, path must not be a file

load_dl1_images¶: A boolean (True, False) trait.

load_dl1_parameters¶: A boolean (True, False) trait.

load_dl2¶: A boolean (True, False) trait.

load_instrument¶: A boolean (True, False) trait.

load_simulated¶: A boolean (True, False) trait.

load_true_images¶: A boolean (True, False) trait.

load_true_parameters¶: A boolean (True, False) trait.

Methods Documentation

close()[source]¶: Close the underlying hdf5 file

read_shower_distribution()[source]¶: Read the simulated shower distribution histograms

read_simulation_configuration()[source]¶: Read the simulation configuration table

read_subarray_events(start=None, stop=None, keep_order=True)[source]¶

Read subarray-based event information.

Returns

table: astropy.io.Table: Table with primary index columns “obs_id” and “event_id”.

read_subarray_events_chunked(chunk_size)[source]¶

Iterate over chunks of subarray events.

Parameters

chunk_size: int: Number of subarray events to load per chunk

read_telescope_events(telescopes=None, start=None, stop=None)[source]¶

Read telescope-based event information.

If the corresponding traitlets are True, also subarray event information is joined onto the table.

The start, stop parameters enable to only load parts of the file, note however, to maintain integrity of subarray events, these refer to the subarray indices in the file. E.g. start=0, stop=10 would load the telescope events corresponding to the first 10 subarray events in the input file.

Parameters

telescopes: Optional[List[Union[int, str, TelescopeDescription]]]: A list containing any combination of telescope IDs and/or telescope descriptions. If None, all available telescopes are read.
start: int: First subarray event to read
stop: int: Last subarray event (non-inclusive)

Returns

events: astropy.io.Table: Table with primary index columns “obs_id”, “event_id” and “tel_id”.

read_telescope_events_by_type(telescopes=None, start=None, stop=None) → Dict[str, astropy.table.table.Table][source]¶

Read telescope-based event information.

Parameters

telescopes: List[Union[int, str, TelescopeDescription]]: Any list containing a combination of telescope IDs or telescope_descriptions.

Returns

tables: dict(astropy.io.Table): Dictionary of tables organized by telescope types Table with primary index columns “obs_id”, “event_id” and “tel_id”.

read_telescope_events_by_type_chunked(chunk_size, **kwargs)[source]¶

Iterate over chunks of telescope events.

Parameters

chunk_size: int: Number of subarray events to load per chunk. The telescope tables might be larger or smaller than chunk_size depending on the selected telescopes.
**kwargs are passed to `read_telescope_events`

read_telescope_events_chunked(chunk_size, **kwargs)[source]¶

Iterate over chunks of telescope events.

Parameters

chunk_size: int: Number of subarray events to load per chunk. The telescope tables might be larger or smaller than chunk_size depending on the selected telescopes.
**kwargs are passed to `read_telescope_events`