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bundles / numpy 2.4.3 / numpy / linspace

_ArrayFunctionDispatcher

numpy:linspace

source: /numpy/_core/function_base.py :27

Signature

def   linspace ( start stop num = 50 endpoint = True retstep = False dtype = None axis = 0 * device = None )

Summary

Return evenly spaced numbers over a specified interval.

Extended Summary

Returns num evenly spaced samples, calculated over the interval [start, stop].

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, 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

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.

device : str, optional

The device on which to place the created array. Default: None. For Array-API interoperability only, so must be "cpu" if passed.

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.

Examples

import numpy as np
np.linspace(2.0, 3.0, num=5)
np.linspace(2.0, 3.0, num=5, endpoint=False)
np.linspace(2.0, 3.0, num=5, retstep=True)
Graphical illustration:
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()
fig-7e99eb20b3ab7b51.png

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).

how-to-partition

ref

logspace

Similar to geomspace, but with the end points specified as logarithms.

Aliases

  • numpy.linspace

Referenced by

Other packages