jax.numpy.geomspace

jax.numpy.geomspace(start, stop, num=50, endpoint=True, dtype=None, axis=0)

Return numbers spaced evenly on a log scale (a geometric progression).

LAX-backend implementation of numpy.geomspace().

Original docstring below.

This is similar to logspace, but with endpoints specified directly. Each output sample is a constant multiple of the previous.

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

Parameters:

• start (array_like) – The starting value of the sequence.

• stop (array_like) – 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.

• dtype (dtype) – The type of the output array. If dtype is not given, the data type is inferred from start and stop. The inferred dtype 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 or stop 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