numpy中arange函数的用法

numpy中的arange函数用法

： >>help(numpy.arange)

Help on built-in function arange in module numpy.core.multiarray:

arange(...)
    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.（默认为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`.
        (除了步长非整数和浮点数舍入影响out长度). 

    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,
        (如果step给出,start就必须传入).

    dtype : dtype
        The type of the output array.  If `dtype` is not given, infer the data
        type from the other input arguments.
        (如果dtype并未给出,会根据输入的参数来决定）

    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])

---

之前想偷懒，想直接省略stop直接传入start和step两个参数。例如：

>>a = np.arange(12, , 2).reshape(2, 3)

结果输出语法错误。
事后觉得这样其实就算能过，但是可读性并不高。

>>a = np.arange(0, 12, 2).reshape(2, 3)

这样可读性好多了