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 target parameter associated with the given id.
  
  Parameters
  ----------
  id: integer
      LINEAR id of the desired object
  param: string
      parameter name of the desired object (see below)
  
  Returns
  -------
  val: scalar
      value of the requested target parameter
  
  Notes
  -----
  Target parameters are one of the following:
  
  ['objectID', 'raLIN', 'decLIN', 'raSDSS', 'decSDSS', 'r',
   'ug', 'gr', 'ri', 'iz', 'JK', '<mL>', 'std', 'rms',
   'Lchi2', 'LP1', 'phi1', 'S', 'prior']
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code: def get_target_parameter(self, id, param):
      """Get a target parameter associated with the given id.
  
      Parameters
      ----------
      id: integer
          LINEAR id of the desired object
      param: string
          parameter name of the desired object (see below)
  
      Returns
      -------
      val: scalar
          value of the requested target parameter
  
      Notes
      -----
      Target parameters are one of the following:
  
      ['objectID', 'raLIN', 'decLIN', 'raSDSS', 'decSDSS', 'r',
       'ug', 'gr', 'ri', 'iz', 'JK', '<mL>', 'std', 'rms',
       'Lchi2', 'LP1', 'phi1', 'S', 'prior']
      """
      i = np.where(self.targets["objectID"] == id)[0]
      try:
          val = self.targets[param][i[0]]
      except BaseException:
          raise KeyError(id)
  
      return val
  
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 5 for calling the LINEARdata obj's underlying member method code with example usage: obj.get_target_parameter(id, param) and returns: val