jax.numpy.logspace#

jax.numpy.logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None, axis=0)[source]#

Return numbers spaced evenly on a log scale.

LAX-backend implementation of numpy.logspace().

Original docstring below.

In linear space, the sequence starts at base ** start (base to the power of start) and ends with base ** stop (see endpoint below).

Changed in version 1.16.0: Non-scalar start and stop are now supported.

Changed in version 1.25.0: Non-scalar ‘base` is now supported

Parameters:

  • start (array_like) – base ** start is the starting value of the sequence.

  • stop (array_like) – base ** stop is the final value of the sequence, unless endpoint is False. In that case, num + 1 values are spaced over the interval in log-space, of which all but the last (a sequence of length num) are returned.

  • num (integer, optional) – Number of samples to generate. Default is 50.

  • endpoint (boolean, optional) – If true, stop is the last sample. Otherwise, it is not included. Default is True.

  • base (array_like, optional) – The base of the log space. The step size between the elements in ln(samples) / ln(base) (or log_base(samples)) is uniform. Default is 10.0.

  • dtype (dtype) – The type of the output array. If dtype is not given, the data type is inferred from start and stop. The inferred type will never be an integer; float is chosen even if the arguments would produce an array of integers.

  • axis (int, optional) – The axis in the result to store the samples. Relevant only if start, stop, or base are array-like. By default (0), the samples will be along a new axis inserted at the beginning. Use -1 to get an axis at the end.

Returns:

samples – num samples, equally spaced on a log scale.

Return type:

ndarray