code: def _load_coverage(F, header_length=6, dtype=np.int16):
      """Load a coverage file from an open file object.
  
      This will return a numpy array of the given dtype
      """
      header = [F.readline() for i in range(header_length)]
      make_tuple = lambda t: (t.split()[0], float(t.split()[1]))
      header = dict([make_tuple(line) for line in header])
  
      M = np.loadtxt(F, dtype=dtype)
      nodata = int(header[b"NODATA_value"])
      if nodata != -9999:
          M[nodata] = -9999
      return M
  
file_path: catboost/contrib/python/scikit-learn/py2/sklearn/datasets/species_distributions.py
imports: from io import BytesIO
  from os import makedirs
  from os.path import exists
  import numpy
  from sklearn.datasets.base import get_data_home, Bunch
  from sklearn.datasets.base import _pkl_filepath
  from sklearn.externals import joblib
label_desc: Use image node_id 1 for calling a global function with example usage: _load_coverage(F, header_length, dtype) and returns: M