jax.numpy.linspace#
- jax.numpy.linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None, axis=0)[source]#
Return evenly spaced numbers over a specified interval.
LAX-backend implementation of
numpy.linspace()
.Original docstring below.
Returns num evenly spaced samples, calculated over the interval [start, stop].
The endpoint of the interval can optionally be excluded.
Changed in version 1.16.0: Non-scalar start and stop are now supported.
Changed in version 1.20.0: Values are rounded towards
-inf
instead of0
when an integerdtype
is specified. The old behavior can still be obtained withnp.linspace(start, stop, num).astype(int)
- Parameters:
start (array_like) β The starting value of the sequence.
stop (array_like) β The end value of the sequence, unless endpoint is set to False. In that case, the sequence consists of all but the last of
num + 1
evenly spaced samples, so that stop is excluded. Note that the step size changes when endpoint is False.num (int, optional) β Number of samples to generate. Default is 50. Must be non-negative.
endpoint (bool, optional) β If True, stop is the last sample. Otherwise, it is not included. Default is True.
retstep (bool, optional) β If True, return (samples, step), where step is the spacing between samples.
dtype (dtype, optional) β 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) 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.
- Return type:
- Returns:
samples (ndarray) β There are num equally spaced samples in the closed interval
[start, stop]
or the half-open interval[start, stop)
(depending on whether endpoint is True or False).step (float, optional) β Only returned if retstep is True
Size of spacing between samples.