nlcpy.linspace
- nlcpy.linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None, axis=0)[source]
Returns evenly spaced numbers over a specified interval.
Returns num evenly spaced samples, calculated over the interval
[start, stop]
. The endpoint of the interval can optionally be excluded.- Parameters
- startarray_like
The starting value of the sequence.
- stoparray_like
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.- numint, optional
Number of samples to generate. Default is 50. Must be non-negative.
- endpointbool, optional
If True, stop is the last sample. Otherwise, it is not included. Default is True.
- retstepbool, optional
If True, return (samples, step) where step is the spacing between samples.
- dtypedtype, optional
The type of the output array. If dtype is not given, infer the data type from the other input arguments.
- axisint, 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
- samplesndarray
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).- stepfloat, optional
Only returned if retstep is True Size of spacing between samples.
See also
arange
Returns evenly spaced values within a given interval.
Examples
>>> import nlcpy as vp >>> vp.linspace(2.0, 3.0, num=5) array([2. , 2.25, 2.5 , 2.75, 3. ]) >>> vp.linspace(2.0, 3.0, num=5, endpoint=False) array([2. , 2.2, 2.4, 2.6, 2.8]) >>> vp.linspace(2.0, 3.0, num=5, retstep=True) (array([2. , 2.25, 2.5 , 2.75, 3. ]), array([0.25]))