waveformtools.dataIO

Functions for handling data IO operations from waveforms class.

Functions

construct_mode_list(ell_max, spin_weight)	Construct a modes list in the form.
get_ell_max_from_file(data_dir[, var_type, ...])	Get the largest available mode number from available data in files.
get_ell_max_from_keys(all_keys)	Get ell max from a list of keys.
get_ell_max_from_tar_gz_file(file_path)	Get the ell_max from files in a tar.gz.
get_files_in_tar_gz(file_path)	Get the files in a tar.gz.
get_iteration_numbers_from_keys(keys_list)	Get the iteration number from keys.
initialize_modes_array(time_axis, modes_array)	Initialize a modes array given the time axis
load_RIT_Psi4_data_from_disk(data_file_path)	Load the Psi4 waveforms from the RIT catalogue.
load_RIT_Strain_data_from_disk([wfa, ...])	Load the RIT or strain waveforms from the RIT/ MAYA catalogue data,.
load_SpECTRE_data_from_disk([wfa, label, ...])	Load the SpECTRE or SpEC CCE waveform to modes_array, from hdf5 files from disk.
load_SpEC_data_from_disk([wfa, label, ...])	Load the SpEC waveform to modes_array,from hdf5 files from disk.
load_SpEC_non_extrap_data_from_disk([wfa, ...])	Load the SpEC waveform at finite radii.
load_gen_data_from_disk([wfa, label, ...])	Load the RIT strain waveforms from the RIT catalogue,.
read_data_from_tar_gz_subfile(...)	Extract and read the data in a subfile inside the given open.
reorder_modes_list(modes_list)	Reorder a modes list.
save_modes_data_to_gen(wfa[, ell_max, ...])	Save the waveform mode data to an hdf file.
sort_keys(modes_keys_list)	Sort the keys in a list based on its iteration number

waveformtools.dataIO.construct_mode_list(ell_max, spin_weight)

Construct a modes list in the form.

[[ell1, [emm1, emm2, …], [ell2, [emm..]],..] given the \(\ell_{max}.\)

Parameters:

spin_weight: int

The spin weight of the modes.

ell_max: int

The \(\ell_{max}\) of the modes list.

Returns:

modes_list: list

A list containg the mode indices lists.

Notes

The modes list is the form which the waveform object understands.

waveformtools.dataIO.get_ell_max_from_file(data_dir, var_type='Psi4', file_name='*.h5')

Get the largest available mode number from available data in files.

Parameters:

data_dir: string

A string containing the directory path where the mode files can be found.

var_type: string, optional

A string that denotes the variable that is being loaded. Options are Psi4 and strain. The former is the default.

file_name: string, optional

The h5 file that contains the modes data. It defaults to the only file in the directory. If there are multiple files, it throws an error.

Returns

——-

ell_max: int

The maximum available ell.

keys_list: list

A list of data access keys.

Notes

Reads in various ASCII dat files for RIT Psi4, h5 files for RIT strain and gen strain.

waveformtools.dataIO.get_ell_max_from_keys(all_keys)

Get ell max from a list of keys.

Parameters:

all_keys: list

A list of strings string containing the modes keys.

Returns

——-

ell_max: int

The maximum available ell.

waveformtools.dataIO.get_ell_max_from_tar_gz_file(file_path)

Get the ell_max from files in a tar.gz.

Parameters:

file_path: str,pathlib.Path

The full path to the tar file

Returns:

ell_max: int

The l max of the modes available

filtered_fnames: list of str

A list contaning the names of the modes files.

waveformtools.dataIO.get_files_in_tar_gz(file_path)

Get the files in a tar.gz.

Parameters:

file_path: str,pathlib.Path

The full path to the tar file

waveformtools.dataIO.get_iteration_numbers_from_keys(keys_list)

Get the iteration number from keys.

Parameters:

keys_list: list

The list of keys.

Returns:

iteration_numbers: list

The list containing the iteration numbers.

waveformtools.dataIO.initialize_modes_array(time_axis, modes_array, resam_type='finest', ell_max=8)

Initialize a modes array given the time axis

waveformtools.dataIO.load_RIT_Psi4_data_from_disk(data_file_path, wfa=None, label='RIT_rPsi4inf', ell_max=None, modes_list=None, save_as_ma=False, spin_weight=-2, resam_type='finest', interp_kind='cubic', crop=False, centre=False, output_modes_array=False)

Load the Psi4 waveforms from the RIT catalogue.

from ASCII files from disk.

Parameters:

wfa: ModesArray

An instance of the waveforms ModesArray class. Updates this instance if provided, else creates a new instance.

data_file_path: string/pathlib.Path

A string containing the directory path where the mode files can be found.

label: string, optional

The label of the modes_array object.

ell_max: int, optional

The maximum mode number to load. If not specified, then all available modes are loaded.

save_as_ma: bool, optional

Save to disk again as a modes_array h5 file?

spin_weight: int, optional

The spin weight of the object. Used for filtering modes. Defaults to -2.

resam_type: string, float, optional

The type of resampling to do. Options are finest and coarsest, and user input float.

interp_kind: string, optional

The interpolation type to use. Default is cubic.

Returns:

rit_modes_array: modes_array

A modes_array instance containing the loaded modes if output_modes_array is True

time_axis, modes_data: ndarray

Time axis and an array whose first axis is time and second is flatened modes index consistent with ModesArray

Notes

It seems like the time axis of individual modes are identical to each other. Hence, one need not worry about choosing the time domain. This may change in the future.

waveformtools.dataIO.load_RIT_Strain_data_from_disk(wfa=None, data_dir='./', file_name='*', label='RIT_strain', spin_weight=-2, ell_max='auto', resam_type='auto', interp_kind='cubic', save_as_ma=False, modes_list=None, crop=False, centre=True, r_ext_factor=1, debug=False)

Load the RIT or strain waveforms from the RIT/ MAYA catalogue data,.

from hdf5 files from disk.

Parameters:

wfa: waveforms

An instance of the waveforms class. Creates a new one if not provided.

data_dir: string

A string containing the directory path where the mode files can be found.

label: string, optional

The label of the modes_array object.

ell_max: int, optional

The maximum mode number to load. If not specified, then all available modes are loaded.

save_as_ma: bool, optional

Save to disk again as a modes_array h5 file?

spin_weight: int, optional

The spin weight of the object. Used for filtering modes. Defaults to -2.

resam_type: string, float, optional

The type of resampling to do. Options are the finest and coarsest, and user input float.

interp_kind: string, optional

The interpolation type to use. Default is cubic.

Returns:

rit_modes_array: modes_array

A modes_array instance containing the loaded modes.

Notes

It seems like the time axis of individual modes are identical to each other. Hence, one need not worry about choosing the time domain. This may change in future.

waveformtools.dataIO.load_SpECTRE_data_from_disk(wfa=None, label='SpECTRE Strain', data_dir='./', file_name='rhOverM_Extrapolated_N5_CoM_Mem.h5', r_ext=None, ell_max=12, centre=True, modes_list=None, r_ext_factor=1, save_as_ma='False', resam_type='auto', kind='cubic', compression_opts=0, spin_weight=None)

Load the SpECTRE or SpEC CCE waveform to modes_array, from hdf5 files from disk.

Parameters:

wfa: modes_array, optional

The modes array to which to store the loaded waveform to. A new modes array will be returned if not provided.

data_dir: string

A string containing the directory path where the mode files can be found.

file_name: string

The name of the file containing the waveform data.

label: string, optional

The label of the modes_array object.

ell_max: int, optional

The maximum mode number to load. If not specified, then all available modes are loaded.

save_as_ma: bool, optional

Save to disk again as a modes_array h5 file?

resam_type: string, float, optional

The type of resampling to do. Options are finest and coarsest, and user input float.

interp_kind: string, optional

The interpolation type to use. Default is cubic.

Returns:

modes_array: modes_array

A modes_array instance containing the loaded modes.

waveformtools.dataIO.load_SpEC_data_from_disk(wfa=None, label='SXS Strain', data_dir='./', file_name='rhOverM_Extrapolated_N5_CoM_Mem.h5', extrap_order=None, r_ext=None, ell_max=None, centre=True, modes_list=None, save_as_ma='False', resam_type='auto', interp_kind='cubic', compression_opts=0, r_ext_factor=1, debug=False)

Load the SpEC waveform to modes_array,from hdf5 files from disk.

Parameters:

wfa: modes_array, optional

The modes array to which to store the loaded waveform to. A new modes array will be returned if not provided.

data_dir: string

A string containing the directory path where the mode files can be found.

file_name: string

The name of the file containing the waveform data.

label: string, optional

The label of the modes_array object.

ell_max: int, optional

The maximum mode number to load. If not specified, then all available modes are loaded.

save_as_ma: bool, optional

Save to disk again as a modes_array h5 file?

resam_type: string, float, optional

The type of resampling to do. Options are finest and coarsest, and user input float.

interp_kind: string, optional

The interpolation type to use. Default is cubic.

Returns:

modes_array: modes_array

A modes_array instance containing the loaded modes.

waveformtools.dataIO.load_SpEC_non_extrap_data_from_disk(wfa=None, label='SXS Strain', data_dir='./', file_name='rh_FiniteRadii_CodeUnits.h5', r_ext=None, ell_max=None, centre=True, modes_list=None, save_as_ma='False', resam_type='auto', interp_kind='cubic', compression_opts=0, r_ext_factor=1, debug=False)

Load the SpEC waveform at finite radii.

to modes_array, from hdf5 files from disk.

Parameters:

wfa: modes_array, optional

The modes array to which to store the loaded waveform to. A new modes array will be returned if not provided.

data_dir: string

A string containing the directory path where the mode files can be found.

file_name: string

The name of the file containing the waveform data.

label: string, optional

The label of the modes_array object.

ell_max: int, optional

The maximum mode number to load. If not specified, then all available modes are loaded.

save_as_ma: bool, optional

Save to disk again as a modes_array h5 file?

resam_type: string, float, optional

The type of resampling to do. Options are finest and coarsest, and user input float.

interp_kind: string, optional

The interpolation type to use. Default is cubic.

Returns:

modes_array: modes_array

A modes_array instance containing the loaded modes.

waveformtools.dataIO.load_gen_data_from_disk(wfa=None, label='generic waveform', data_dir='./', file_name='*.h5', r_ext=None, ell_max=8, pre_key=None, modes_list=None, crop=False, centre=True, key_ex=None, r_ext_factor=1, *args, **kwargs)

Load the RIT strain waveforms from the RIT catalogue,.

from hdf5 files from disk.

Parameters:

data_dir: string

A string containing the directory path where the mode files can be found.

label: string, optional

The label of the modes_array object.

ell_max: int, optional

The maximum mode number to load. If not specified, then all available modes are loaded.

save_as_ma: bool, optional

Save to disk again as a modes_array h5 file?

spin_weight: int, optional

The spin weight of the object. Used for filtering modes. Defaults to -2.

resam_type: string, float, optional

The type of resampling to do. Options are finest and coarsest, and user input float.

interp_kind: string, optional

The interpolation type to use. Default is cubic.

Returns:

rit_modes_array: modes_array

A modes_array instance containing the loaded modes.

Notes

It seems like the time axis of individual modes are identical to each other. Hence, one need not worry about choosing the time domain. This may change in future.

waveformtools.dataIO.read_data_from_tar_gz_subfile(tar_gz_file_handle, subfile_name)

Extract and read the data in a subfile inside the given open.

tar gz file handle

waveformtools.dataIO.reorder_modes_list(modes_list)

Reorder a modes list.

waveformtools.dataIO.save_modes_data_to_gen(wfa, ell_max=None, pre_key=None, key_format=None, modes_to_save=None, out_file_name='mp_new_modes.h5', r_ext_factor=None, compression_opts=0, r_ext=None)

Save the waveform mode data to an hdf file.

Parameters:

pre_key: str, optional

A string containing the key of the group in the HDF file in which the modes` dataset exists. It defaults to None.

mode_numbers: list

The mode numbers to load from the file. Each item in the list is a list that contains two integrer numbers, one for the mode index \(\ell\) and the other for the mode index \(m\).

Returns:

waveform_obj: 3d array

Sets the three dimensional array waveform.modes that contains the required \(\ell, m\) modes.

Examples

>>> from waveformtools.modes_array import ModesArray
>>> wf = modes_array()
>>> wf.data_dir = './'
>>> wf.filename = 'data_file.h5'
>>> wf.modes_list = [[2, 2], [3, 3]]
>>> wf.load_gen_data()

waveformtools.dataIO.sort_keys(modes_keys_list)

Sort the keys in a list based on its iteration number

Parameters:

modes_keys_list: str

The list of keys.

Returns:

sorted_modes_keys_list: str

The sorted list.