package scipy

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package scipy
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Module Sparse.DokSource

Sourceval get_py : string -> Py.Object.t

Get an attribute of this module as a Py.Object.t. This is useful to pass a Python function to another function.

Sourcemodule IndexMixin : sig ... end
Sourcemodule Izip : sig ... end
Sourcemodule Xrange : sig ... end
Sourceval check_shape : ?current_shape:Py.Object.t -> args:Py.Object.t -> unit -> Py.Object.t

Imitate numpy.matrix handling of shape arguments

Sourceval get_index_dtype : ?arrays:Py.Object.t -> ?maxval:float -> ?check_contents:bool -> unit -> Np.Dtype.t

Based on input (integer) arrays `a`, determine a suitable index data type that can hold the data in the arrays.

Parameters ---------- arrays : tuple of array_like Input arrays whose types/contents to check maxval : float, optional Maximum value needed check_contents : bool, optional Whether to check the values in the arrays and not just their types. Default: False (check only the types)

Returns ------- dtype : dtype Suitable index data type (int32 or int64)

Sourceval getdtype : ?a:Py.Object.t -> ?default:Py.Object.t -> dtype:Py.Object.t -> unit -> Py.Object.t

Function used to simplify argument processing. If 'dtype' is not specified (is None), returns a.dtype; otherwise returns a np.dtype object created from the specified dtype argument. If 'dtype' and 'a' are both None, construct a data type out of the 'default' parameter. Furthermore, 'dtype' must be in 'allowed' set.

None

Sourceval isintlike : Py.Object.t -> Py.Object.t

Is x appropriate as an index into a sparse matrix? Returns True if it can be cast safely to a machine int.

Sourceval isscalarlike : Py.Object.t -> Py.Object.t

Is x either a scalar, an array scalar, or a 0-dim array?

Sourceval isshape : ?nonneg:Py.Object.t -> x:Py.Object.t -> unit -> Py.Object.t

Is x a valid 2-tuple of dimensions?

If nonneg, also checks that the dimensions are non-negative.

Sourceval isspmatrix : Py.Object.t -> Py.Object.t

Is x of a sparse matrix type?

Parameters ---------- x object to check for being a sparse matrix

Returns ------- bool True if x is a sparse matrix, False otherwise

Notes ----- issparse and isspmatrix are aliases for the same function.

Examples -------- >>> from scipy.sparse import csr_matrix, isspmatrix >>> isspmatrix(csr_matrix([5])) True

>>> from scipy.sparse import isspmatrix >>> isspmatrix(5) False

Sourceval isspmatrix_dok : Py.Object.t -> Py.Object.t

Is x of dok_matrix type?

Parameters ---------- x object to check for being a dok matrix

Returns ------- bool True if x is a dok matrix, False otherwise

Examples -------- >>> from scipy.sparse import dok_matrix, isspmatrix_dok >>> isspmatrix_dok(dok_matrix([5])) True

>>> from scipy.sparse import dok_matrix, csr_matrix, isspmatrix_dok >>> isspmatrix_dok(csr_matrix([5])) False

Sourceval iteritems : Py.Object.t -> Py.Object.t

Return an iterator over the (key, value) pairs of a dictionary.

Sourceval iterkeys : Py.Object.t -> Py.Object.t

Return an iterator over the keys of a dictionary.

Sourceval itervalues : Py.Object.t -> Py.Object.t

Return an iterator over the values of a dictionary.

Sourceval upcast : Py.Object.t list -> Py.Object.t

Returns the nearest supported sparse dtype for the combination of one or more types.

upcast(t0, t1, ..., tn) -> T where T is a supported dtype

Examples --------

>>> upcast('int32') <type 'numpy.int32'> >>> upcast('bool') <type 'numpy.bool_'> >>> upcast('int32','float32') <type 'numpy.float64'> >>> upcast('bool',complex,float) <type 'numpy.complex128'>

Sourceval upcast_scalar : dtype:Py.Object.t -> scalar:Py.Object.t -> unit -> Py.Object.t

Determine data type for binary operation between an array of type `dtype` and a scalar.