DataWriter#
- class ctapipe.io.DataWriter(**kwargs: Any)[source]#
Bases:
Component
Serialize a sequence of events into a HDF5 file, in the correct format
Examples
inside a Tool:
with DataWriter(parent=self) as write_data: for event in source: calibrate(event) process_images(event) write_data(event)
Attributes Summary
compression level, 0=None, 9=maximum
compressor algorithm to use.
A trait whose value must be an instance of a specified class.
Additional metadata keywords and values that describe this data.
returns a list of data levels requested
A trait for unicode strings.
An int trait.
A float trait.
A trait whose value must be an instance of a specified class.
output filename
overwrite output file if it exists
A trait for unicode strings.
An int trait.
A float trait.
A boolean (True, False) trait.
A boolean (True, False) trait.
A boolean (True, False) trait.
A trait for unicode strings.
An int trait.
A float trait.
Store DL1 Images if available
Store DL1 image parameters if available
Store DL2 stereo shower parameters if available
Generate PyTables index datasets for all tables that contain an event_id or tel_id.
Store muon parameters if available
Store R0 waveforms if available
Store R1 waveforms if available
Methods Summary
__call__
(event)Write a single event to the output file.
finish
()called after all events are done
table_name
(tel_id)construct dataset table names depending on chosen split method
Write the distribution of thrown showers.
Attributes Documentation
- compression_level#
compression level, 0=None, 9=maximum
- compression_type#
compressor algorithm to use.
- contact_info#
A trait whose value must be an instance of a specified class.
The value can also be an instance of a subclass of the specified class.
Subclasses can declare default classes by overriding the klass attribute
- context_metadata#
Additional metadata keywords and values that describe this data. This should be a dictionary where the keys will be appended to the CONTEXT section of the output file’s attributes. Keys can be hierarchical by using a space between each level, e.g.
SIMULATION PRODUCTION
would make a key PRODUCTION grouped under the key SIMULATION
- datalevels#
returns a list of data levels requested
- image_dtype#
A trait for unicode strings.
- image_offset#
An int trait.
- image_scale#
A float trait.
- instrument_info#
A trait whose value must be an instance of a specified class.
The value can also be an instance of a subclass of the specified class.
Subclasses can declare default classes by overriding the klass attribute
- output_path#
output filename
- overwrite#
overwrite output file if it exists
- peak_time_dtype#
A trait for unicode strings.
- peak_time_offset#
An int trait.
- peak_time_scale#
A float trait.
- transform_image#
A boolean (True, False) trait.
- transform_peak_time#
A boolean (True, False) trait.
- transform_waveform#
A boolean (True, False) trait.
- waveform_dtype#
A trait for unicode strings.
- waveform_offset#
An int trait.
- waveform_scale#
A float trait.
- write_dl1_images#
Store DL1 Images if available
- write_dl1_parameters#
Store DL1 image parameters if available
- write_dl2#
Store DL2 stereo shower parameters if available
- write_index_tables#
Generate PyTables index datasets for all tables that contain an event_id or tel_id. These speed up in-kernel pytables operations,but add some overhead to the file. They can also be generated and attached after the file is written
- write_muon_parameters#
Store muon parameters if available
- write_r0_waveforms#
Store R0 waveforms if available
- write_r1_waveforms#
Store R1 waveforms if available
Methods Documentation
- __call__(event: ArrayEventContainer)[source]#
Write a single event to the output file.