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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 linspace for 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 dtype is not given, infer the data
type from the other input arguments.
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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.
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See also
- linspace
- Evenly spaced numbers with careful handling of endpoints.
- ogrid
- Arrays of evenly spaced numbers in N-dimensions.
- mgrid
- Grid-shaped arrays of evenly spaced numbers in N-dimensions.
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])