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# numpy.ma.arange

`numpy.ma.``arange`([start], stop[, step], dtype=None) = <numpy.ma.core._convert2ma instance at 0x2820bd8>

  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.
  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

  `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])