numpy.arange¶
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numpy.arange([start, ]stop, [step, ]dtype=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 - linspacefor these cases.- Parameters: - start : number, optional - Start of interval. The interval includes this value. The default start value is 0. - stop : number - 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. - step : number, 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, start must also be given.- dtype : dtype - The type of the output array. If - dtypeis not given, infer the data type from the other input arguments.- Returns: - arange : ndarray - 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.- See also - Examples - >>> 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])