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 _ 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/py3/sklearn/datasets/_species_distributions.py
imports: import logging
  from io import BytesIO
  from os import PathLike, makedirs, remove
  from os.path import exists
  import joblib
  import numpy
  from ..utils import Bunch
  from ..utils._param_validation import validate_params
  from .None import get_data_home
  from ._base import RemoteFileMetadata, _fetch_remote, _pkl_filepath
label_desc: Use image node_id 1 for calling a global function with example usage: _load_coverage(F, header_length, dtype) and returns: M