numpy.linspace — NumPy v2.6.dev0 Manual
numpy.linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None, axis=0, *, device=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.
Changed in version 1.20.0: Values are rounded towards -inf instead of 0 when an integer dtype is specified. The old behavior can still be obtained with np.linspace(start,stop,num).astype(np.int_)
Parameters:startarray_likeThe starting value of the sequence.
stoparray_likeThe 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.
numint, optionalNumber of samples to generate. Default is 50. Must be non-negative.
endpointbool, optionalIf True, stop is the last sample. Otherwise, it is not included. Default is True.
retstepbool, optionalIf True, return (samples, step), where step is the spacing between samples.
dtypedtype, optionalThe type of the output array. If
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.
axisint, optionalThe 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.
devicestr, optionalThe device on which to place the created array. Default: None. For Array-API interoperability only, so must be "cpu" if passed.
Added in version 2.0.0.
Returns:samplesndarrayThere 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).
stepfloat, optionalOnly returned if retstep is True
Size of spacing between samples.
Examples
>>> importnumpyasnp>>> 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:
>>> importmatplotlib.pyplotasplt>>> 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')[<matplotlib.lines.Line2D object at 0x...>]>>> plt.plot(x2,y+0.5,'o')[<matplotlib.lines.Line2D object at 0x...>]>>> plt.ylim([-0.5,1])(-0.5, 1)>>> plt.show()
