models.py

"""Module containing models representing lightcurves.

The Model layer is responsible for the 'business logic' part of the software.

The lightcurves are saved in a table (2D array) where each row corresponds to a single observation. 
Depending on the dataset (LSST or Kepler), a table can contain observations of a single or several objects, 
in a single or different bands.
"""

import pandas as pd
import numpy as np
from astropy.timeseries import LombScargle

def load_dataset(filename):
    """Load a table from CSV file.
    
    :param filename: The name of the .csv file to load.
    :raises Eror: when the file is not CSV/
                  no file was given as an inut/
                  the file or directory was not found
    :returns: pd.DataFrame with the data from the file.
    """
    return pd.read_csv(filename)


def mean_mag(data, mag_col):
    """Calculate the mean magnitude of a lightcurve
    :param data: pd.DataFrame with observed magnitudes for a single source
    :param mag_col: a string with the name of the column for calculating the min value.
    :returns: the mean for the mag_col coming from the data table
    """
    return data[mag_col].mean()


def max_mag(data, mag_col):
    """Calculate the max magnitude of a lightcurve
    :param data: pd.DataFrame with observed magnitudes for a single source
    :param: a string with the name of the column for calculating the max value.
    :returns: the max for the mag_col coming from the data table
    """
    return data[mag_col].max()


def min_mag(data, mag_col):
    """Calculate the min magnitude of a lightcurve
    :param data: pd.DataFrame with observed magnitudes for a single source.
    :param mag_col: a string with the name of the column for calculating the min value.
    :returns: The min value of the column.
    """
    return data[mag_col].min()