# jax.numpy.arange¶

jax.numpy.arange(start, stop=None, step=None, dtype=None)[source]

Return evenly spaced values within a given interval.

LAX-backend implementation of arange(). Original docstring below.

arange([start,] stop[, step,], dtype=None)

Values are generated within the half-open interval [start, stop) (in other words, the interval including start but excluding stop). For integer arguments the function is equivalent to the Python built-in range function, but returns an ndarray rather than a list.

When using a non-integer step, such as 0.1, the results will often not be consistent. It is better to use numpy.linspace for these cases.

Parameters
• start (number, optional) – Start of interval. The interval includes this value. The default start value is 0.

• stop (number) – End of interval. The interval does not include this value, except in some cases where step is not an integer and floating point round-off affects the length of out.

• step (number, optional) – Spacing between values. For any output out, this is the distance between two adjacent values, out[i+1] - out[i]. The default step size is 1. If step is specified as a position argument, start must also be given.

• dtype (dtype) – The type of the output array. If dtype is not given, infer the data type from the other input arguments.

Returns

• arange (ndarray) – Array of evenly spaced values.

• For floating point arguments, the length of the result is

• ceil((stop - start)/step). Because of floating point overflow,

• this rule may result in the last element of out being greater

• than stop.

numpy.linspace()

Evenly spaced numbers with careful handling of endpoints.

numpy.ogrid()

Arrays of evenly spaced numbers in N-dimensions.

numpy.mgrid()

Grid-shaped arrays of evenly spaced numbers in N-dimensions.

Examples

>>> np.arange(3)
array([0, 1, 2])
>>> np.arange(3.0)
array([ 0.,  1.,  2.])
>>> np.arange(3,7)
array([3, 4, 5, 6])
>>> np.arange(3,7,2)
array([3, 5])