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# scipy.sparse.dia_matrix

class `scipy.sparse.``dia_matrix`(arg1, shape=None, dtype=None, copy=False)

  Sparse matrix with DIAgonal storage

  This can be instantiated in several ways:
    dia_matrix(D)
      with a dense matrix
    dia_matrix(S)
      with another sparse matrix S (equivalent to S.todia())
    dia_matrix((M, N), [dtype])
      to construct an empty matrix with shape (M, N), dtype is optional, defaulting to dtype=’d’.
    dia_matrix((data, offsets), shape=(M, N))
      where the `data[k,:]` stores the diagonal entries for diagonal `offsets[k]` (See example below)

  Notes

  Sparse matrices can be used in arithmetic operations: they support addition, subtraction, multiplication, division, and matrix power.

  Examples

      >>> import numpy as np
      >>> from scipy.sparse import dia_matrix
      >>> dia_matrix((3, 4), dtype=np.int8).toarray()
      array([[0, 0, 0, 0],
             [0, 0, 0, 0],
             [0, 0, 0, 0]], dtype=int8)

      >>> data = np.array([[1, 2, 3, 4]]).repeat(3, axis=0)
      >>> offsets = np.array([0, -1, 2])
      >>> dia_matrix((data, offsets), shape=(4, 4)).toarray()
      array([[1, 0, 3, 0],
             [1, 2, 0, 4],
             [0, 2, 3, 0],
             [0, 0, 3, 4]])

  Attributes

  `nnz` | number of nonzero values

  dtype | (dtype) Data type of the matrix
  shape | (2-tuple) Shape of the matrix
  ndim | (int) Number of dimensions (this is always 2)
  data | DIA format data array of the matrix
  offsets | DIA format offset array of the matrix

  Methods

  `arcsin`() | Element-wise arcsin.
  `arcsinh`() | Element-wise arcsinh.
  `arctan`() | Element-wise arctan.
  `arctanh`() | Element-wise arctanh.
  `asformat`(format) | Return this matrix in a given sparse format
  `asfptype`() | Upcast matrix to a floating point format (if necessary)
  `astype`(t) |
  `ceil`() | Element-wise ceil.
  `conj`() |
  `conjugate`() |
  `copy`() |
  `deg2rad`() | Element-wise deg2rad.
  `diagonal`() | Returns the main diagonal of the matrix
  `dot`(other) | Ordinary dot product
  `expm1`() | Element-wise expm1.
  `floor`() | Element-wise floor.
  `getH`() |
  `get_shape`() |
  `getcol`(j) | Returns a copy of column j of the matrix, as an (m x 1) sparse matrix (column vector).
  `getformat`() |
  `getmaxprint`() |
  `getnnz`() | number of nonzero values
  `getrow`(i) | Returns a copy of row i of the matrix, as a (1 x n) sparse matrix (row vector).
  `log1p`() | Element-wise log1p.
  `maximum`(other) |
  `mean`([axis]) | Average the matrix over the given axis.
  `minimum`(other) |
  `multiply`(other) | Point-wise multiplication by another matrix
  `nonzero`() | nonzero indices
  `power`(n[, dtype]) | This function performs element-wise power.
  `rad2deg`() | Element-wise rad2deg.
  `reshape`(shape) |
  `rint`() | Element-wise rint.
  `set_shape`(shape) |
  `setdiag`(values[, k]) | Set diagonal or off-diagonal elements of the array.
  `sign`() | Element-wise sign.
  `sin`() | Element-wise sin.
  `sinh`() | Element-wise sinh.
  `sqrt`() | Element-wise sqrt.
  `sum`([axis]) | Sum the matrix over the given axis.
  `tan`() | Element-wise tan.
  `tanh`() | Element-wise tanh.
  `toarray`([order, out]) | Return a dense ndarray representation of this matrix.
  `tobsr`([blocksize]) |
  `tocoo`() |
  `tocsc`() |
  `tocsr`() |
  `todense`([order, out]) | Return a dense matrix representation of this matrix.
  `todia`([copy]) |
  `todok`() |
  `tolil`() |
  `transpose`() |
  `trunc`() | Element-wise trunc.