flopscope.

flopscope.numpy.true_divide

fnp.true_divide(*args, **kwargs)[flopscope source][numpy source]

Divide arguments element-wise.

Adapted from NumPy docs np.true_divide

Areacore
Typecounted
NumPy Refnp.true_divide
Cost
numel(output)\text{numel}(\text{output})
Flopscope Context

Element-wise true division (explicit).

Parameters

x1:array_like

Dividend array.

x2:array_like

Divisor array. If x1.shape != x2.shape, they must be broadcastable to a common shape (which becomes the shape of the output).

out:ndarray, None, or tuple of ndarray and None, 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. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.

where:array_like, optional

This condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized out array is created via the default out=None, locations within it where the condition is False will remain uninitialized.

**kwargs

For other keyword-only arguments, see the ufunc docs.

Returns

y:ndarray or scalar

The quotient x1/x2, element-wise. This is a scalar if both x1 and x2 are scalars.

See also

  • seterr Set whether to raise or warn on overflow, underflow and division by zero.

Notes

Equivalent to x1 / x2 in terms of array-broadcasting.

The true_divide(x1, x2) function is an alias for divide(x1, x2).

Examples

>>> import flopscope.numpy as fnp
>>> flops.divide(2.0, 4.0)
0.5
>>> x1 = flops.arange(9.0).reshape((3, 3))
>>> x2 = flops.arange(3.0)
>>> flops.divide(x1, x2)
array([[nan, 1. , 1. ],
       [inf, 4. , 2.5],
       [inf, 7. , 4. ]])

The / operator can be used as a shorthand for flops.divide on ndarrays.

>>> x1 = flops.arange(9.0).reshape((3, 3))
>>> x2 = 2 * flops.ones(3)
>>> x1 / x2
array([[0. , 0.5, 1. ],
       [1.5, 2. , 2.5],
       [3. , 3.5, 4. ]])