/NumPy 1.17

# numpy.ma.arange

`numpy.ma.arange([start, ]stop, [step, ]dtype=None) = <numpy.ma.core._convert2ma object>`

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.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 as a position argument, `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. `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`.

`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])
```