package scipy

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

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.

Imitate numpy.matrix handling of shape arguments

Down-cast index array to np.intp dtype if it is of a larger dtype.

Raise an error if the array contains a value that is too large for intp.

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)

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.

Is x a valid 2-tuple of dimensions?

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

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

Is x of coo_matrix type?

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

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

Examples -------- >>> from scipy.sparse import coo_matrix, isspmatrix_coo >>> isspmatrix_coo(coo_matrix([5])) True

>>> from scipy.sparse import coo_matrix, csr_matrix, isspmatrix_coo >>> isspmatrix_coo(csr_matrix([5])) False

None

None

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'>

Same as `upcast` but taking dtype.char as input (faster).

Issue a warning, or maybe ignore it or raise an exception.