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 withbase ** stop
(see endpoint below).Changed in version 1.16.0: Non-scalar start and stop are now supported.
- Parameters:
start (array_like) β
base ** start
is the starting value of the sequence.stop (array_like) β
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) β Number of samples to generate. Default is 50.
endpoint (boolean, optional) β If true, stop is the last sample. Otherwise, it is not included. Default is True.
base (array_like, optional) β The base of the log space. The step size between the elements in
ln(samples) / ln(base)
(orlog_base(samples)
) is uniform. Default is 10.0.dtype (dtype) β 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) β 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 β num samples, equally spaced on a log scale.
- Return type:
ndarray