code: def _setdiag(self, values, k):
      if self.ndim != 2:
          raise ValueError("setting a diagonal requires two dimensions")
      M, N = self.shape
      if values.ndim and not len(values):
          return
      idx_dtype = self.row.dtype
  
      # Determine which triples to keep and where to put the new ones.
      full_keep = self.col - self.row != k
      if k < 0:
          max_index = min(M + k, N)
          if values.ndim:
              max_index = min(max_index, len(values))
          keep = np.logical_or(full_keep, self.col >= max_index)
          new_row = np.arange(-k, -k + max_index, dtype=idx_dtype)
          new_col = np.arange(max_index, dtype=idx_dtype)
      else:
          max_index = min(M, N - k)
          if values.ndim:
              max_index = min(max_index, len(values))
          keep = np.logical_or(full_keep, self.row >= max_index)
          new_row = np.arange(max_index, dtype=idx_dtype)
          new_col = np.arange(k, k + max_index, dtype=idx_dtype)
  
      # Define the array of data consisting of the entries to be added.
      if values.ndim:
          new_data = values[:max_index]
      else:
          new_data = np.empty(max_index, dtype=self.dtype)
          new_data[:] = values
  
      # Update the internal structure.
      self.indices = (
          np.concatenate((self.row[keep], new_row)),
          np.concatenate((self.col[keep], new_col)),
      )
      self.data = np.concatenate((self.data[keep], new_data))
      self.has_canonical_format = False
  
imports: import math
  from warnings import warn
  import numpy
  from ._matrix import spmatrix
  from ._sparsetools import coo_tocsr, coo_todense, coo_matvec
  from ._base import issparse, SparseEfficiencyWarning, _spbase, sparray
  from ._data import _data_matrix, _minmax_mixin
  from ._sputils import upcast, upcast_char, to_native, isshape, getdtype, getdata, downcast_intp_index, get_index_dtype, check_shape, check_reshape_kwargs
  import operator
label_desc: Use image node_id 18 for calling the _coo_base obj's underlying member method code with example usage: obj._setdiag(values, k) without return types