- numpy.arange([start, ]stop, [step, ]dtype=None, *, like=None)¶
Return evenly spaced values within a given interval.
Values are generated within the half-open interval
[start, stop)(in other words, the interval including start but excluding stop). For integer arguments the function is equivalent to the Python built-in range function, but returns an ndarray rather than a list.
When using a non-integer step, such as 0.1, the results will often not be consistent. It is better to use
numpy.linspacefor these cases.
- startinteger or real, optional
Start of interval. The interval includes this value. The default start value is 0.
- stopinteger or real
End of interval. The interval does not include this value, except in some cases where step is not an integer and floating point round-off affects the length of out.
- stepinteger or real, optional
Spacing between values. For any output out, this is the distance between two adjacent values,
out[i+1] - out[i]. The default step size is 1. If step is specified as a position argument, start must also be given.
The type of the output array. If
dtypeis not given, infer the data type from the other input arguments.
Reference object to allow the creation of arrays which are not NumPy arrays. If an array-like passed in as
__array_function__protocol, the result will be defined by it. In this case, it ensures the creation of an array object compatible with that passed in via this argument.
New in version 1.20.0.
Array of evenly spaced values.
For floating point arguments, the length of the result is
ceil((stop - start)/step). Because of floating point overflow, this rule may result in the last element of out being greater than stop.
Evenly spaced numbers with careful handling of endpoints.
Arrays of evenly spaced numbers in N-dimensions.
Grid-shaped arrays of evenly spaced numbers in N-dimensions.
>>> np.arange(3) array([0, 1, 2]) >>> np.arange(3.0) array([ 0., 1., 2.]) >>> np.arange(3,7) array([3, 4, 5, 6]) >>> np.arange(3,7,2) array([3, 5])