code: def _setdiag(self, values, k=0):
      M, N = self.shape
  
      if values.ndim == 0:
          # broadcast
          values_n = np.inf
      else:
          values_n = len(values)
  
      if k < 0:
          n = min(M + k, N, values_n)
          min_index = 0
          max_index = n
      else:
          n = min(M, N - k, values_n)
          min_index = k
          max_index = k + n
  
      if values.ndim != 0:
          # allow also longer sequences
          values = values[:n]
  
      data_rows, data_cols = self.data.shape
      if k in self.offsets:
          if max_index > data_cols:
              data = np.zeros(
                  (data_rows, max_index), dtype=self.data.dtype
              )
              data[:, :data_cols] = self.data
              self.data = data
          self.data[self.offsets == k, min_index:max_index] = values
      else:
          self.offsets = np.append(
              self.offsets, self.offsets.dtype.type(k)
          )
          m = max(max_index, data_cols)
          data = np.zeros((data_rows + 1, m), dtype=self.data.dtype)
          data[:-1, :data_cols] = self.data
          data[-1, min_index:max_index] = values
          self.data = data
  
imports: import numpy
  from ._matrix import spmatrix
  from ._base import issparse, _formats, _spbase, sparray
  from ._data import _data_matrix
  from ._sputils import isshape, upcast_char, getdtype, get_sum_dtype, validateaxis, check_shape
  from ._sparsetools import dia_matvec
label_desc: Use image node_id 10 for calling the _dia_base obj's underlying member method code with example usage: obj._setdiag(values, k) without return types