linspace¶

linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None, axis=0, ctx=None)¶

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.

Parameters:

start : real number: The starting value of the sequence.
stop : real number: 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.

See also

arange: Similar to linspace, but uses a step size (instead of the number of samples).

Notes

This function differs from the original numpy.linspace in the following aspects:

start and stop do not support list, numpy ndarray and mxnet ndarray
axis could only be 0
There could be an additional ctx argument to specify the device, e.g. the i-th GPU.

Examples

>>> 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 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.asnumpy(), y.asnumpy(), 'o')
[<matplotlib.lines.Line2D object at 0x...>]
>>> plt.plot(x2.asnumpy(), (y + 0.5).asnumpy(), 'o')
[<matplotlib.lines.Line2D object at 0x...>]
>>> plt.ylim([-0.5, 1])
(-0.5, 1)
>>> plt.show()