How to use the NumPy linspace function with examples | 2019

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numpy.linspace(): This function Return evenly spaced numbers over a specified interval  and num evenly spaced samples, calculated over the interval [start, stop].

Syntax: numpy.linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None, axis=0)

The endpoint of the interval can optionally be excluded.

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.

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.

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.

#Example program on numpy.linspace():

import numpy as np print(np.linspace(6,2,num=5)) print(np.linspace(4.0,5.0, num = 10)) print(np.linspace(10, 20, 5))


[ 6.  5.  4.  3.  2.]
[ 4.          4.11111111  4.22222222  4.33333333  4.44444444  4.55555556
  4.66666667  4.77777778  4.88888889  5.        ]
[ 10.   12.5  15.   17.5  20. ]




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