heat.rounding

Rounding functions for DNDarrays

Module Contents

abs(x: heat.core.dndarray.DNDarray, out: heat.core.dndarray.DNDarray | None = None, dtype: Type[heat.core.types.datatype] | None = None) → heat.core.dndarray.DNDarray

Returns DNDarray containing the elementwise abolute values of the input array x.

Parameters:

  • x (DNDarray) – The array for which the compute the absolute value.

  • out (DNDarray, optional) – A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned.

  • dtype (datatype, optional) – Determines the data type of the output array. The values are cast to this type with potential loss of precision.

Raises:

TypeError – If dtype is not a heat type.

absolute(x: heat.core.dndarray.DNDarray, out: heat.core.dndarray.DNDarray | None = None, dtype: Type[heat.core.types.datatype] | None = None) → heat.core.dndarray.DNDarray

Calculate the absolute value element-wise. abs() is a shorthand for this function.

Parameters:

  • x (DNDarray) – The array for which the compute the absolute value.

  • out (DNDarray, optional) – A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned.

  • dtype (datatype, optional) – Determines the data type of the output array. The values are cast to this type with potential loss of precision.

ceil(x: heat.core.dndarray.DNDarray, out: heat.core.dndarray.DNDarray | None = None) → heat.core.dndarray.DNDarray

Return the ceil of the input, element-wise. Result is a DNDarray of the same shape as x. The ceil of the scalar x is the smallest integer i, such that i>=x. It is often denoted as \(\lceil x \rceil\).

Parameters:

  • x (DNDarray) – The value for which to compute the ceiled values.

  • out (DNDarray, optional) – A location in which to store the results. If provided, it must have a broadcastable shape. If not provided or set to None, a fresh array is allocated.

Examples

>>> import heat as ht
>>> ht.ceil(ht.arange(-2.0, 2.0, 0.4))
DNDarray([-2., -1., -1., -0., -0.,  0.,  1.,  1.,  2.,  2.], dtype=ht.float32, device=cpu:0, split=None)
clip(x: heat.core.dndarray.DNDarray, min, max, out: heat.core.dndarray.DNDarray | None = None) → heat.core.dndarray.DNDarray

Returns a DNDarray with the elements of this array, but where values <a_min are replaced with a_min, and those >a_max with a_max.

Parameters:

  • x (DNDarray) – Array containing elements to clip.

  • min (scalar or None) – Minimum value. If None, clipping is not performed on lower interval edge. Not more than one of a_min and a_max may be None.

  • max (scalar or None) – Maximum value. If None, clipping is not performed on upper interval edge. Not more than one of a_min and a_max may be None.

  • out (DNDarray, optional) – The results will be placed in this array. It may be the input array for in-place clipping. out must be of the right shape to hold the output. Its type is preserved.

Raises:

ValueError – if either min or max is not set

fabs(x: heat.core.dndarray.DNDarray, out: heat.core.dndarray.DNDarray | None = None) → heat.core.dndarray.DNDarray

Calculate the absolute value element-wise and return floating-point class:~heat.core.dndarray.DNDarray. This function exists besides abs==absolute since it will be needed in case complex numbers will be introduced in the future.

Parameters:

  • x (DNDarray) – The array for which the compute the absolute value.

  • out (DNDarray, optional) – A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned.

floor(x: heat.core.dndarray.DNDarray, out: heat.core.dndarray.DNDarray | None = None) → heat.core.dndarray.DNDarray

Return the floor of the input, element-wise. The floor of the scalar x is the largest integer i, such that i<=x. It is often denoted as \(\lfloor x \rfloor\).

Parameters:

  • x (DNDarray) – The array for which to compute the floored values.

  • out (DNDarray, optional) – A location in which to store the results. If provided, it must have a broadcastable shape. If not provided or set to None, a fresh DNDarray is allocated.

Examples

>>> import heat as ht
>>> ht.floor(ht.arange(-2.0, 2.0, 0.4))
DNDarray([-2., -2., -2., -1., -1.,  0.,  0.,  0.,  1.,  1.], dtype=ht.float32, device=cpu:0, split=None)
modf(x: heat.core.dndarray.DNDarray, out: Tuple[heat.core.dndarray.DNDarray, heat.core.dndarray.DNDarray] | None = None) → Tuple[heat.core.dndarray.DNDarray, heat.core.dndarray.DNDarray]

Return the fractional and integral parts of a DNDarray, element-wise. The fractional and integral parts are negative if the given number is negative.

Parameters:

  • x (DNDarray) – Input array

  • out (Tuple[DNDarray, DNDarray], optional) – A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned.

Raises:

  • TypeError – if x is not a DNDarray

  • TypeError – if out is not None or a tuple of DNDarray

  • ValueError – if out is a tuple of length unqual 2

Examples

>>> import heat as ht
>>> ht.modf(ht.arange(-2.0, 2.0, 0.4))
(DNDarray([ 0.0000, -0.6000, -0.2000, -0.8000, -0.4000,  0.0000,  0.4000,  0.8000,  0.2000,  0.6000], dtype=ht.float32, device=cpu:0, split=None), DNDarray([-2., -1., -1., -0., -0.,  0.,  0.,  0.,  1.,  1.], dtype=ht.float32, device=cpu:0, split=None))
round(x: heat.core.dndarray.DNDarray, decimals: int = 0, out: heat.core.dndarray.DNDarray | None = None, dtype: Type[heat.core.types.datatype] | None = None) → heat.core.dndarray.DNDarray

Calculate the rounded value element-wise.

Parameters:

  • x (DNDarray) – The array for which the compute the rounded value.

  • decimals (int, optional) – Number of decimal places to round to. If decimals is negative, it specifies the number of positions to the left of the decimal point.

  • out (DNDarray, optional) – A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned.

  • dtype (datatype, optional) – Determines the data type of the output array. The values are cast to this type with potential loss of precision.

Raises:

TypeError – if dtype is not a heat data type

Examples

>>> import heat as ht
>>> ht.round(ht.arange(-2.0, 2.0, 0.4))
DNDarray([-2., -2., -1., -1., -0.,  0.,  0.,  1.,  1.,  2.], dtype=ht.float32, device=cpu:0, split=None)
sgn(x: heat.core.dndarray.DNDarray, out: heat.core.dndarray.DNDarray | None = None) → heat.core.dndarray.DNDarray

Returns an indication of the sign of a number, element-wise. The definition for complex values is equivalent to \(x / |x|\).

Parameters:

  • x (DNDarray) – Input array

  • out (DNDarray, optional) – A location in which to store the results.

See also

sign()

Equivalent function on non-complex arrays. The definition for complex values is equivalent to \(x / \sqrt{x \cdot x}\)

Examples

>>> a = ht.array([-1, -0.5, 0, 0.5, 1])
>>> ht.sign(a)
DNDarray([-1., -1.,  0.,  1.,  1.], dtype=ht.float32, device=cpu:0, split=None)
>>> ht.sgn(ht.array([5-2j, 3+4j]))
DNDarray([(0.9284766912460327-0.3713906705379486j),  (0.6000000238418579+0.800000011920929j)], dtype=ht.complex64, device=cpu:0, split=None)
sign(x: heat.core.dndarray.DNDarray, out: heat.core.dndarray.DNDarray | None = None) → heat.core.dndarray.DNDarray

Returns an indication of the sign of a number, element-wise. The definition for complex values is equivalent to \(x / \sqrt{x \cdot x}\).

Parameters:

  • x (DNDarray) – Input array

  • out (DNDarray, optional) – A location in which to store the results.

See also

sgn()

Equivalent function on non-complex arrays. The definition for complex values is equivalent to \(x / |x|\).

Examples

>>> a = ht.array([-1, -0.5, 0, 0.5, 1])
>>> ht.sign(a)
DNDarray([-1., -1.,  0.,  1.,  1.], dtype=ht.float32, device=cpu:0, split=None)
>>> ht.sign(ht.array([5-2j, 3+4j]))
DNDarray([(1+0j), (1+0j)], dtype=ht.complex64, device=cpu:0, split=None)
trunc(x: heat.core.dndarray.DNDarray, out: heat.core.dndarray.DNDarray | None = None) → heat.core.dndarray.DNDarray

Return the trunc of the input, element-wise. The truncated value of the scalar x is the nearest integer i which is closer to zero than x is. In short, the fractional part of the signed number x is discarded.

Parameters:

  • x (DNDarray) – The array for which to compute the trunced values.

  • out (DNDarray, optional) – A location in which to store the results. If provided, it must have a broadcastable shape. If not provided or set to None, a fresh array is allocated.

Examples

>>> import heat as ht
>>> ht.trunc(ht.arange(-2.0, 2.0, 0.4))
DNDarray([-2., -1., -1., -0., -0.,  0.,  0.,  0.,  1.,  1.], dtype=ht.float32, device=cpu:0, split=None)