nums.numpy.arange

nums.numpy.arange(start=None, stop=None, step=1, dtype=None) → nums.core.array.blockarray.BlockArray

Return evenly spaced values within a given interval.

This docstring was copied from numpy.arange.

Some inconsistencies with the NumS version may exist.

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 BlockArray 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 nums.linspace for these cases.

startnumber, optional

Start of interval. The interval includes this value. The default start value is 0.

stopnumber

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.

stepnumber, 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.

dtypedtype

The type of the output array. If dtype is not given, infer the data type from the other input arguments.

arangeBlockArray

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.

linspace : Evenly spaced numbers with careful handling of endpoints.

Only step size of 1 is currently supported.

The doctests shown below are copied from NumPy. They won’t show the correct result until you operate get().

>>> nps.arange(3).get()  
array([0, 1, 2])
>>> nps.arange(3.0).get()  
array([ 0.,  1.,  2.])
>>> nps.arange(3,7).get()  
array([3, 4, 5, 6])