#!/usr/bin/env python
# -*- coding: utf-8 -*-
# This file is part of the
# Pyedra Project (https://github.com/milicolazo/Pyedra/).
# Copyright (c) 2020, Milagros Colazo
# License: MIT
# Full Text: https://github.com/milicolazo/Pyedra/blob/master/LICENSE
# ============================================================================
# DOCS
# ============================================================================
"""
The pyedra.datasets module includes utilities to load datasets.
It also features some artificial data generators.
"""
# ============================================================================
# IMPORTS
# ============================================================================
import os
import pathlib
import pandas as pd
# ============================================================================
# CONSTANTS
# ============================================================================
PATH = pathlib.Path(os.path.abspath(os.path.dirname(__file__)))
# ============================================================================
# FUNCTIONS
# ============================================================================
[docs]def load_carbognani2019():
"""Input for use with the phase functions.
This dataset contains the first and second columns of Table 2 of
[6]_ . These columns correspond to: phase angle
(°) and V_max (mag). V_max is the reduced magnitude of the
lightcurve maximum.
References
----------
.. [6] Carbognani, A., Cellino, A., & Caminiti, S. (2019). New
phase-magnitude curves for some main belt asteroids, fit of
different photometric systems and calibration of the
albedo-Photometry relation. Planetary and Space Science,
169, 15-34.
"""
path = PATH / "carbognani2019.csv"
return pd.read_csv(path)
[docs]def load_penttila2016():
"""Tabulated values of the base functions for H-G1-G2 system.
This dataset corresponds to Table B.4 of [7]_ .
References
----------
.. [7] A. Penttilä, V. G. Shevchenko, O. Wilkman, & K. Muinonen
(2016). H,G1, G2 photometric phase function extended to
low-accuracy data. 123:117–125.
"""
path = PATH / "penttila2016.csv"
return pd.read_csv(path)
[docs]def load_gaia():
"""Gaia observations.
The data used to obtain these quantities were downloaded from the Gaia
Archive (https://gea.esac.esa.int/archive/) [8]_ .
References
----------
.. [8] Gaia Collaboration et al., 2018, A&A, 616, A13
"""
path = PATH / "gaia.csv.bz2"
return pd.read_csv(path, na_filter=False, compression="bz2")