brainpy.math.arange#

brainpy.math.arange(start: Union[int, Any], stop: Optional[Union[int, Any]] = None, step: Optional[Union[int, Any]] = None, dtype: Optional[Union[Any, str, numpy.dtype, jax._src.typing.SupportsDType]] = None) → jax._src.basearray.Array[source]#

Return evenly spaced values within a given interval.

LAX-backend implementation of numpy.arange().

Original docstring below.

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 (integer or real, optional) – Start of interval. The interval includes this value. The default start value is 0.

  • stop (integer or real) – 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 (integer or real, 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 – 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.

Return type

ndarray