help numpy.linspace

Help on function linspace in module numpy: linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None, axis=0)   Return 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. versionchanged::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 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 Number of samples to generate. Default is 50. Must be non-negative.

endpoint : bool, optional If True, stop is the last sample. Otherwise, it is not included. Default is True.

retstep : bool, optional If True, return ( samples , step ), where step is the spacing between samples.

dtype : dtype, optional The type of the output array. If dtype is not given, infer the data type from the other input arguments.

versionadded::1.9.0

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.

versionadded::1.16.0 Returns ------- samples : ndarray 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 Only returned if retstep is True Size of spacing between samples. See Also -------- arange : Similar to linspace , but uses a step size (instead of the number of samples). geomspace : Similar to linspace , but with numbers spaced evenly on a log scale (a geometric progression). logspace : Similar to geomspace , but with the end points specified as logarithms.
Examples

>>> import numpy as np
>>> np.linspace(2.0, 3.0, num=5)
array([2.  , 2.25, 2.5 , 2.75, 3.  ])
>>> np.linspace(2.0, 3.0, num=5, endpoint=False)
array([2. ,  2.2,  2.4,  2.6,  2.8])
>>> np.linspace(2.0, 3.0, num=5, retstep=True)
(array([2.  ,  2.25,  2.5 ,  2.75,  3.  ]), 0.25)

Graphical illustration:

import numpy as np
import matplotlib.pyplot as plt
N = 8
y = np.zeros(N)
x1 = np.linspace(0, 10, N, endpoint=True)
x2 = np.linspace(0, 10, N, endpoint=False)
plt.plot(x1, y, 'o')
plt.plot(x2, y + 0.5, 'o')
plt.ylim([-0.5, 1])
plt.show()