pyarrow.Tensor#

classpyarrow.Tensor#

Bases:_Weakrefable

A n-dimensional array a.k.a Tensor.

Examples

>>>importpyarrowaspa>>>importnumpyasnp>>>x=np.array([[2,2,4],[4,5,100]],np.int32)>>>pa.Tensor.from_numpy(x,dim_names=["dim1","dim2"])<pyarrow.Tensor>type: int32shape: (2, 3)strides: (12, 4)

__init__(*args,**kwargs)#

Methods

__init__(*args, **kwargs)
dim_name(self, i)	Returns the name of the i-th tensor dimension.
equals(self, Tensor other)	Return true if the tensors contains exactly equal data.
from_numpy(obj[, dim_names])	Create a Tensor from a numpy array.
to_numpy(self)	Convert arrow::Tensor to numpy.ndarray with zero copy

Attributes

dim_names	Names of this tensor dimensions.
is_contiguous	Is this tensor contiguous in memory.
is_mutable	Is this tensor mutable or immutable.
ndim	The dimension (n) of this tensor.
shape	The shape of this tensor.
size	The size of this tensor.
strides	Strides of this tensor.
type

dim_name(self,i)#

Returns the name of the i-th tensor dimension.

Parameters:

iint

The physical index of the tensor dimension.

Examples

>>>importpyarrowaspa>>>importnumpyasnp>>>x=np.array([[2,2,4],[4,5,100]],np.int32)>>>tensor=pa.Tensor.from_numpy(x,dim_names=["dim1","dim2"])>>>tensor.dim_name(0)'dim1'>>>tensor.dim_name(1)'dim2'

dim_names#

Names of this tensor dimensions.

Examples

>>>importpyarrowaspa>>>importnumpyasnp>>>x=np.array([[2,2,4],[4,5,100]],np.int32)>>>tensor=pa.Tensor.from_numpy(x,dim_names=["dim1","dim2"])>>>tensor.dim_names['dim1', 'dim2']

equals(self,Tensorother)#

Return true if the tensors contains exactly equal data.

Parameters:

otherTensor

The other tensor to compare for equality.

Examples

>>>importpyarrowaspa>>>importnumpyasnp>>>x=np.array([[2,2,4],[4,5,100]],np.int32)>>>tensor=pa.Tensor.from_numpy(x,dim_names=["dim1","dim2"])>>>y=np.array([[2,2,4],[4,5,10]],np.int32)>>>tensor2=pa.Tensor.from_numpy(y,dim_names=["a","b"])>>>tensor.equals(tensor)True>>>tensor.equals(tensor2)False

staticfrom_numpy(obj,dim_names=None)#

Create a Tensor from a numpy array.

Parameters:

objnumpy.ndarray

The source numpy array

dim_nameslist, optional

Names of each dimension of the Tensor.

Examples

>>>importpyarrowaspa>>>importnumpyasnp>>>x=np.array([[2,2,4],[4,5,100]],np.int32)>>>pa.Tensor.from_numpy(x,dim_names=["dim1","dim2"])<pyarrow.Tensor>type: int32shape: (2, 3)strides: (12, 4)

is_contiguous#

Is this tensor contiguous in memory.

Examples

>>>importpyarrowaspa>>>importnumpyasnp>>>x=np.array([[2,2,4],[4,5,100]],np.int32)>>>tensor=pa.Tensor.from_numpy(x,dim_names=["dim1","dim2"])>>>tensor.is_contiguousTrue

is_mutable#

Is this tensor mutable or immutable.

Examples

>>>importpyarrowaspa>>>importnumpyasnp>>>x=np.array([[2,2,4],[4,5,100]],np.int32)>>>tensor=pa.Tensor.from_numpy(x,dim_names=["dim1","dim2"])>>>tensor.is_mutableTrue

ndim#

The dimension (n) of this tensor.

Examples

>>>importpyarrowaspa>>>importnumpyasnp>>>x=np.array([[2,2,4],[4,5,100]],np.int32)>>>tensor=pa.Tensor.from_numpy(x,dim_names=["dim1","dim2"])>>>tensor.ndim2

shape#

The shape of this tensor.

Examples

>>>importpyarrowaspa>>>importnumpyasnp>>>x=np.array([[2,2,4],[4,5,100]],np.int32)>>>tensor=pa.Tensor.from_numpy(x,dim_names=["dim1","dim2"])>>>tensor.shape(2, 3)

size#

The size of this tensor.

Examples

>>>importpyarrowaspa>>>importnumpyasnp>>>x=np.array([[2,2,4],[4,5,100]],np.int32)>>>tensor=pa.Tensor.from_numpy(x,dim_names=["dim1","dim2"])>>>tensor.size6

strides#

Strides of this tensor.

Examples

>>>importpyarrowaspa>>>importnumpyasnp>>>x=np.array([[2,2,4],[4,5,100]],np.int32)>>>tensor=pa.Tensor.from_numpy(x,dim_names=["dim1","dim2"])>>>tensor.strides(12, 4)

to_numpy(self)#

Convert arrow::Tensor to numpy.ndarray with zero copy

Examples

>>>importpyarrowaspa>>>importnumpyasnp>>>x=np.array([[2,2,4],[4,5,100]],np.int32)>>>tensor=pa.Tensor.from_numpy(x,dim_names=["dim1","dim2"])>>>tensor.to_numpy()array([[  2,   2,   4],       [  4,   5, 100]], dtype=int32)

type#