code: def todia(self, copy=False):
      if self.ndim != 2:
          raise ValueError(
              "Cannot convert a 1d sparse array to dia format"
          )
      self.sum_duplicates()
      ks = self.col - self.row  # the diagonal for each nonzero
      diags, diag_idx = np.unique(ks, return_inverse=True)
  
      if len(diags) > 100:
          # probably undesired, should todia() have a maxdiags parameter?
          warn(
              "Constructing a DIA matrix with %d diagonals "
              "is inefficient" % len(diags),
              SparseEfficiencyWarning,
              stacklevel=2,
          )
  
      # initialize and fill in data array
      if self.data.size == 0:
          data = np.zeros((0, 0), dtype=self.dtype)
      else:
          data = np.zeros(
              (len(diags), self.col.max() + 1), dtype=self.dtype
          )
          data[diag_idx, self.col] = self.data
  
      return self._dia_container((data, diags), shape=self.shape)
  
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 15 for calling the _coo_base obj's underlying member method code with example usage: obj.todia(copy) and returns: self