#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2017-2024, Cabral, Juan
# Copyright (c) 2025, QuatroPe; Clariá, Felipe
# License: MIT
# Full Text:
# https://github.com/quatrope/feets/blob/master/LICENSE
# =============================================================================
# DOCS
# =============================================================================
"""Utilities for accessing MACHO light curves.
The files are gathered from the original FATS project tutorial:
https://github.com/isadoranun/tsfeat
"""
# =============================================================================
# IMPORTS
# =============================================================================
import os
import pathlib
import tarfile
import numpy as np
from .base import LightCurveDataset
from ..extractors.extractor import DATA_ERROR, DATA_MAGNITUDE, DATA_TIME
from ..libs import doctools
# =============================================================================
# CONSTANTS
# =============================================================================
PATH = pathlib.Path(os.path.abspath(os.path.dirname(__file__)))
DATA_PATH = PATH / "data" / "macho"
DATASET_NAME = "MACHO"
DATASET_DESCRIPTION = (
"The files are gathered from the original FATS project "
"tutorial: https://github.com/isadoranun/tsfeat"
)
MACHO_EXAMPLE_ID = "lc_1.3444.614"
# =============================================================================
# FUNCTIONS
# =============================================================================
[docs]
def available_MACHO_lc():
"""List the available MACHO light curves.
Returns
-------
list
The list of available MACHO light curves.
"""
return [fp.rsplit(".", 2)[0] for fp in os.listdir(DATA_PATH)]
[docs]
def load_MACHO_example():
"""Retrieve a light curve from the MACHO survey.
The returned light curve contains data from 2 bands: R, B.
Returns
-------
LightCurveDataset
Dataset with the retrieved light curve data vectors.
Notes
-----
The files are gathered from the original FATS project tutorial:
https://github.com/isadoranun/tsfeat
See Also
--------
available_MACHO_lc
Examples
--------
>>> ds = load_MACHO_example()
>>> ds
LightCurveDataset(
_id='lc_1.3444.614', name='MACHO', bands=('R', 'B')
)
>>> ds.bands
('R', 'B')
>>> ds.data.B
<LightCurve time[1235], magnitude[1235], error[1235]>
>>> ds.data.B.magnitude
array([-6.081, -6.041, -6.046, ..., -6.009, -5.985, -5.997], shape=(1235,))
"""
return load_MACHO(MACHO_EXAMPLE_ID)
[docs]
@doctools.doc_inherit(load_MACHO_example)
def load_MACHO(macho_id):
"""
Parameters
----------
macho_id : str
The ID of the MACHO light curve to retrieve.
Examples
--------
>>> ds = load_MACHO('lc_1.3444.614')
>>> ds
LightCurveDataset(
_id='lc_1.3444.614', name='MACHO', bands=('R', 'B')
)
>>> ds.bands
('R', 'B')
>>> ds.data.B
<LightCurve time[1235], magnitude[1235], error[1235]>
>>> ds.data.B.magnitude
array([-6.081, -6.041, -6.046, ..., -6.009, -5.985, -5.997], shape=(1235,))
"""
# Read the data
tarpath = DATA_PATH / f"{macho_id}.tar.bz2"
members = {
"R": {"path": f"{macho_id}.R.mjd"},
"B": {"path": f"{macho_id}.B.mjd"},
}
with tarfile.open(tarpath, mode="r:bz2") as tf:
for band, member in members.items():
members[band]["lc"] = np.loadtxt(tf.extractfile(member["path"]))
bands = []
data = {}
for band, member in members.items():
lc = member["lc"]
data[band] = {
DATA_TIME: lc[:, 0],
DATA_MAGNITUDE: lc[:, 1],
DATA_ERROR: lc[:, 2],
}
bands.append(band)
return LightCurveDataset(
id=macho_id,
name=DATASET_NAME,
description=DATASET_DESCRIPTION,
bands=bands,
data=data,
)
