dia_array#
- class scipy.sparse.dia_array(arg1, shape=None, dtype=None, copy=False, *, maxprint=None)[source]#
- Sparse array with DIAgonal storage. - This can be instantiated in several ways:
- dia_array(D)
- where D is a 2-D ndarray 
- dia_array(S)
- with another sparse array or matrix S (equivalent to S.todia()) 
- dia_array((M, N), [dtype])
- to construct an empty array with shape (M, N), dtype is optional, defaulting to dtype=’d’. 
- dia_array((data, offsets), shape=(M, N))
- where the - data[k,:]stores the diagonal entries for diagonal- offsets[k](See example below)
 
 - Notes - Sparse arrays can be used in arithmetic operations: they support addition, subtraction, multiplication, division, and matrix power. Sparse arrays with DIAgonal storage do not support slicing. - Examples - >>> import numpy as np >>> from scipy.sparse import dia_array >>> dia_array((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_array((data, offsets), shape=(4, 4)).toarray() array([[1, 0, 3, 0], [1, 2, 0, 4], [0, 2, 3, 0], [0, 0, 3, 4]]) - >>> from scipy.sparse import dia_array >>> n = 10 >>> ex = np.ones(n) >>> data = np.array([ex, 2 * ex, ex]) >>> offsets = np.array([-1, 0, 1]) >>> dia_array((data, offsets), shape=(n, n)).toarray() array([[2., 1., 0., ..., 0., 0., 0.], [1., 2., 1., ..., 0., 0., 0.], [0., 1., 2., ..., 0., 0., 0.], ..., [0., 0., 0., ..., 2., 1., 0.], [0., 0., 0., ..., 1., 2., 1.], [0., 0., 0., ..., 0., 1., 2.]]) - Attributes:
 - Methods - __len__()- arcsin()- Element-wise arcsin. - arcsinh()- Element-wise arcsinh. - arctan()- Element-wise arctan. - arctanh()- Element-wise arctanh. - asformat(format[, copy])- Return this array/matrix in the passed format. - astype(dtype[, casting, copy])- Cast the array/matrix elements to a specified type. - ceil()- Element-wise ceil. - conj([copy])- Element-wise complex conjugation. - conjugate([copy])- Element-wise complex conjugation. - copy()- Returns a copy of this array/matrix. - count_nonzero([axis])- Number of non-zero entries, equivalent to - deg2rad()- Element-wise deg2rad. - diagonal([k])- Returns the kth diagonal of the array/matrix. - dot(other)- Ordinary dot product - expm1()- Element-wise expm1. - floor()- Element-wise floor. - log1p()- Element-wise log1p. - maximum(other)- Element-wise maximum between this and another array/matrix. - mean([axis, dtype, out])- Compute the arithmetic mean along the specified axis. - minimum(other)- Element-wise minimum between this and another array/matrix. - multiply(other)- Point-wise multiplication by another array/matrix. - nonzero()- Nonzero indices of the array/matrix. - power(n[, dtype])- This function performs element-wise power. - rad2deg()- Element-wise rad2deg. - reshape(self, shape[, order, copy])- Gives a new shape to a sparse array/matrix without changing its data. - resize(*shape)- Resize the array/matrix in-place to dimensions given by - shape- rint()- Element-wise rint. - setdiag(values[, k])- Set diagonal or off-diagonal elements of the array/matrix. - sign()- Element-wise sign. - sin()- Element-wise sin. - sinh()- Element-wise sinh. - sqrt()- Element-wise sqrt. - sum([axis, dtype, out])- Sum the array/matrix elements over a given axis. - tan()- Element-wise tan. - tanh()- Element-wise tanh. - toarray([order, out])- Return a dense ndarray representation of this sparse array/matrix. - tobsr([blocksize, copy])- Convert this array/matrix to Block Sparse Row format. - tocoo([copy])- Convert this array/matrix to COOrdinate format. - tocsc([copy])- Convert this array/matrix to Compressed Sparse Column format. - tocsr([copy])- Convert this array/matrix to Compressed Sparse Row format. - todense([order, out])- Return a dense representation of this sparse array. - todia([copy])- Convert this array/matrix to sparse DIAgonal format. - todok([copy])- Convert this array/matrix to Dictionary Of Keys format. - tolil([copy])- Convert this array/matrix to List of Lists format. - trace([offset])- Returns the sum along diagonals of the sparse array/matrix. - transpose([axes, copy])- Reverses the dimensions of the sparse array/matrix. - trunc()- Element-wise trunc. - __mul__