gwadama.ioo#

Input & Output Operations

Everything related to input data retrieval and output files.

class gwadama.ioo.CoReManager(db_path)[source]#

Bases: object

Manage easily usual tasks of Watpy’s CoRe_db instances.

Ad-hoc manager to automate and make easier usual tasks in Watpy, including metadata and strain downloads, and spatial projection.

Attributes:

cdbwatpy.coredb.coredb.CoRe_db

Instance of CoRe_db from which everything is managed.

db_pathPath

Folder where is or will be stored CoRe database. Refer to ‘watpy.coredb.coredb.CoRe_db’ for more details.

eosset

All EOS found available.

metadataDataFrame

Metadata from all simulations in ‘cdb’ collected in a single DF.

downloadeddict

3-Level dictionary containing the path to existing strains (saved as TXT files), their eccentricity and radius of extraction. Tree-format:

txt_files[simkey][run] = {
‘file’: ‘path/to/file.txt’, ‘eccentricity’: ecc, ‘r_extraction’: rext

}

NOTE: ONLY KEEPS 1 RUN PER SIMULATION FOR NOW

Methods

`cast_to_float`(string)	Cast a string to float, considering '' also a NaN.
`count_runs`([filters])	Count total number of runs in the database.
`download_mode22`(simkeys[, keep_h5, ...])	Download ONLY the optimum strains Rh_22.
`gen_strain`(skey, distance, inclination, phi)	Build strain from time-domain mode 22 in mass rescaled, geom.
`get_runkey_lowest_eccentricity`(skey)	Find the run with the lowest eccentricity for a given simulation.
`load_sim`(skey)	Load a previously downloaded gw simulation.
`sw_Y22`(i, phi)	Spin-weighted spherical harmonic mode lm = 22.

filter_by
filter_multiple
show

__init__(db_path)[source]#

Initialize the manager.

Parameters:

db_pathstr: Folder where is or will be stored CoRe database. Refer to ‘watpy.coredb.coredb.CoRe_db’ for more details.

static cast_to_float(string)[source]#: Cast a string to float, considering ‘’ also a NaN.

count_runs(filters=[])[source]#

Count total number of runs in the database.

Parameters:

filterslist of lists: Format: [[key0, value0], [key1, value1], …]

download_mode22(simkeys, keep_h5=False, overwrite=False, prot='https', lfs=False, verbose=True)[source]#

Download ONLY the optimum strains Rh_22.

Downloads each simulation, keeps the strains with the lowest eccentricity and highest extraction point ‘r’ in a TXT file, updates the database ‘self.downloaded’, and (optional) removes the original HDF5 file from CoRe to free up space.

Parameters:

simkeyslist: List of simulation keys (‘db_keys’ in watpy) to download.
keep_h5bool: If False (default) removes the HDF5 file downloaded by watpy.
overwritebool: If False (default) and a certain simulation in ‘simkeys’ is already present in ‘self.downloaded’, skip it. Otherwise downloads everything again.
verbosebool: If True (default), print which simulations are downloaded and which are skipped.
prot, lfs: Refer to ‘watpy.coredb.coredb.CoRe_db.sync’.

fields_float = ['id_mass', 'id_rest_mass', 'id_mass_ratio', 'id_ADM_mass', 'id_ADM_angularmomentum', 'id_gw_frequency_Hz', 'id_gw_frequency_Momega22', 'id_kappa2T', 'id_Lambda', 'id_eccentricity', 'id_mass_starA', 'id_rest_mass_starA', 'id_mass_starB', 'id_rest_mass_starB']#

filter_by(key, value)[source]#

filter_multiple(filters)[source]#

gen_strain(skey, distance, inclination, phi)[source]#: Build strain from time-domain mode 22 in mass rescaled, geom. units.

get_runkey_lowest_eccentricity(skey)[source]#

Find the run with the lowest eccentricity for a given simulation.

Return the key of the run and the value of its eccentricity for which this parameter is the lowest among all runs of the ‘skey’ simulation.

If a simulation has multiple runs with the same eccentricity (typically all values set to 0 or NAN) it will pick the first run in the list.

If there are one or more runs with eccentricity = NAN, the first one will be returned.

Parameters:

skeystr: Key (database_key) of the simulation.

Returns:

run_keystr: Key of the run.
eccfloat: Eccentricity of the run.

header_gw_txt = 'u/M:0 Reh/M:1 Imh/M:2 Redh/M:3 Imdh/M:4 Momega:5 A/M:6 phi:7 t:8'#

load_sim(skey)[source]#: Load a previously downloaded gw simulation.

show(key, to_float=False, to_file=None)[source]#

static sw_Y22(i, phi)[source]#

Spin-weighted spherical harmonic mode lm = 22.

Ref: Ajith et al., 2011

gwadama.ioo.write_nested_dict_to_hdf5(file: str, *, data: dict, metadata: dict) → None[source]#

Save nested dictionary of NumPy arrays to HDF5 file with metadata.

Parameters:

file: str: Path to the HDF5 file.
data: dict: Nested dictionary containing NumPy arrays.
metadata: dict: Nested dictionary containing metadata for arrays.