How to use the NumPy linspace function with examples | 2019
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.
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.
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.
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.
#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))
Output:
[ 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. ]
