nlcpy.array

nlcpy.array(object, dtype=None, copy=True, order='K', subok=False, ndmin=0)[source]

Creates an array.

Parameters

objectarray_like

An array, any object exposing the array interface, an object whose __array__ method returns an array, or any (nested) sequence.

dtypedtype, optional

The desired dtype for the array. If not given, then the type will be determined as the minimum type required to hold the objects in the sequence. This argument can only be used to ‘upcast’ the array. For downcasting, use the .astype(t) method.

copybool, optional

If true (default), then the object is copied. Otherwise, a copy will only be made if __array__ returns a copy, if object is a nested sequence, or if a copy is needed to satisfy any of the other requirements (dtype, order, etc.).

order{‘K’, ‘A’, ‘C’, ‘F’}, optional

Specify the memory layout of the array. If object is not an array, the newly created array will be in C order (row major) unless ‘F’ is specified, in which case it will be in Fortran order (column major). If object is an array the following holds.

order	no copy	copy=True
‘K’	unchanged	F & C order preserved, otherwise most similar order
‘A’	unchanged	F order if input is F and not C, otherwise C order
‘C’	C order	C order
‘F’	F order	F order

When copy=False and a copy is made for other reasons, the result is the same as if copy=True, with some exceptions for A, see the Notes section. The default order is ‘K’.

subokbool, optional

If True, then sub-classes will be passed-through, otherwise, the returned array will be forced to be a base-class array (default). subok=True is Not Implemented.

ndminint, optional

Specifies the minimum number of dimensions that the resulting array should have. Ones will be prepended to the shape as needed to meet this requirement.

Returns

outndarray: An array object satisfying the specified requirements.

See also

empty_like: Returns a new array with the same shape and type as a given array.
ones_like: Returns an array of ones with the same shape and type as a given array.
zeros_like: Returns an array of zeros with the same shape and type as a given array.
full_like: Returns a full array with the same shape and type as a given array.
empty: Returns a new array of given shape and type, without initializing entries.
ones: Returns a new array of given shape and type, filled with ones.
zeros: Returns a new array of given shape and type, filled with zeros.
full: Returns a new array of given shape and type, filled with fill_value.

Restriction

object[i].shape not equals to object[j].shape for some i,j : NotImplementedError occurs.

Examples

>>> import nlcpy as vp
>>> vp.array([1, 2, 3])
array([1, 2, 3])

Upcasting:

>>> vp.array([1, 2, 3.0])
array([1., 2., 3.])

More than one dimension:

>>> vp.array([[1, 2], [3, 4]])
array([[1, 2],
       [3, 4]])

Minimum dimensions 2:

>>> vp.array([1, 2, 3], ndmin=2)
array([[1, 2, 3]])

Type provided:

>>> vp.array([1, 2, 3], dtype=complex)
array([1.+0.j, 2.+0.j, 3.+0.j])