class_docstr: A container class for the linear dataset.
  
  Because the dataset is often not needed all at once, this class
  offers tools to access just the needed components
  
  Example
  -------
  >>> data = fetch_LINEAR_sample()  # doctest: +IGNORE_OUTPUT +REMOTE_DATA
  >>> lightcurve = data[data.ids[0]]  # doctest: +REMOTE_DATA
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docstr: Get a light curve with the given id.
  
  Parameters
  ----------
  id: integer
      LINEAR id of the desired object
  
  Returns
  -------
  lightcurve: ndarray
      a size (n_observations, 3) light-curve.
      columns are [MJD, flux, flux_err]
docstr_tok: ["Get","a","light","curve","with","the","given","id",".","Parameters","--","--","--","--","--","id",":","integer","LINEAR","id","of","the","desired","object","Returns","--","--","--","-","lightcurve",":","ndarray","a","size","(","n_observations",",","3",")","light-curve",".","columns","are","[","MJD",",","flux",",","flux_err","]"]
code: def get_light_curve(self, id):
      """Get a light curve with the given id.
  
      Parameters
      ----------
      id: integer
          LINEAR id of the desired object
  
      Returns
      -------
      lightcurve: ndarray
          a size (n_observations, 3) light-curve.
          columns are [MJD, flux, flux_err]
      """
      return self[id]
  
file_path: astroML/astroML/datasets/LINEAR_sample.py
imports: import os
  import tarfile
  import numpy
  from astropy.table import Table
  from .None import get_data_home
  from .tools import download_with_progress_bar
label_desc: Use image node_id 4 for calling the LINEARdata obj's underlying member method code with example usage: obj.get_light_curve(id) and returns: self