code: def select_next(X, gains, current_values, max_values, idxs):
      for i in prange(idxs.shape[0]):
          idx = idxs[i]
          gains[i] = numpy.minimum(
              current_values + X[idx], max_values
          ).sum()
  
file_path: apricot/apricot/functions/saturatedCoverage.py
imports: import numpy
  from .base import BaseGraphSelection
  from tqdm import tqdm
  from numba import njit
  from numba import prange
  from scipy.sparse import csr_matrix
label_desc: Use image node_id 1 for calling a global function with example usage: select_next(X, gains, current_values, max_values, idxs) without return types