package scipy

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package scipy
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val 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.

module IndexMixin : sig ... end
val asmatrix : ?dtype:Py.Object.t -> data:Py.Object.t -> unit -> Py.Object.t

None

val check_reshape_kwargs : Py.Object.t -> Py.Object.t

Unpack keyword arguments for reshape function.

This is useful because keyword arguments after star arguments are not allowed in Python 2, but star keyword arguments are. This function unpacks 'order' and 'copy' from the star keyword arguments (with defaults) and throws an error for any remaining.

val check_shape : ?current_shape:Py.Object.t -> args:Py.Object.t -> unit -> Py.Object.t

Imitate numpy.matrix handling of shape arguments

val 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)

val 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.

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

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

val 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.

val 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

val isspmatrix_lil : Py.Object.t -> Py.Object.t

Is x of lil_matrix type?

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

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

Examples -------- >>> from scipy.sparse import lil_matrix, isspmatrix_lil >>> isspmatrix_lil(lil_matrix([5])) True

>>> from scipy.sparse import lil_matrix, csr_matrix, isspmatrix_lil >>> isspmatrix_lil(csr_matrix([5])) False

val 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.