如何在 Python 中拉伸浮动列表?

How do I stretch a list of floats in Python?

我在 Python 工作,并且有一个一天的小时值列表。为简单起见,假设一天只有 10 个小时。

 [0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0]

我想围绕中心点将其拉伸到 150%,最终得到:

 [0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0]

请注意,这只是一个示例,我还需要按在给定小时内留下小数的数量来拉伸事物。例如拉伸到 125% 会得到:

 [0.0, 0.0, 0.5, 1.0, 1.0, 1.0, 1.0, 0.5, 0.0, 0.0]

我对处理小数额的第一个想法是使用 np.repeat 将列表乘以 10 倍,应用一些方法来拉伸中点附近的值,然后最终将列表分成块10 并取每小时的平均值。

我的主要问题是 "stretching" 部分,但如果答案也解决了第二部分,那就更好了。

我猜,你需要这样的东西:

def stretch(xs, coef):
  # compute new distibution
  oldDist = sum(hours[:len(hours)/2])
  newDist = oldDist * coef

  # generate new list
  def f(x):
    if newDist - x < 0:
      return 0.0
    return min(1.0, newDist - x)

  t = [f(x) for x in range(len(xs)/2)]
  res = list(reversed(t))
  res.extend(t)
  return res

但要注意奇数小时数。

如果我查看预期的输出,算法是这样的:

  • 以数字列表开头,值 >0.0 表示工作时间
  • 将这些时间加起来
  • 计算请求的额外小时数
  • 除以那些 通过添加或附加在序列两端的额外时间 每个 'end'
  • 的一半

所以:

hours     = [0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0]
expansion = 130
extra_hrs = float(sum(hours)) * float(expansion - 100)/100

# find indices of the first and last non-zero hours
# because of floating point can't use "==" for comparison.
hr_idx    = [idx for (idx, value) in enumerate(hours) if value>0.001]

# replace the entries before the first and after the last 
# with half the extra hours
print "Before expansion:",hours
hours[ hr_idx[0]-1 ] = hours[ hr_idx[-1]+1 ] = extra_hrs/2.0
print "After  expansion:",hours

给出输出:

Before expansion: [0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0]
After  expansion: [0.0, 0.0, 0.6, 1.0, 1.0, 1.0, 1.0, 0.6, 0.0, 0.0]

这就是我最终所做的。它有点难看,因为它需要处理小于 100% 的拉伸系数。

def stretch(xs, coef, centre):
    """Scale a list by a coefficient around a point in the list.

    Parameters
    ----------
    xs : list
        Input values.
    coef : float
        Coefficient to scale by.
    centre : int
        Position in the list to use as a centre point.

    Returns
    -------
    list

    """
    grain = 100    
    stretched_array = np.repeat(xs, grain * coef)

    if coef < 1:
        # pad start and end
        total_pad_len = grain * len(xs) - len(stretched_array)
        centre_pos = float(centre) / len(xs)
        start_pad_len = centre_pos * total_pad_len
        end_pad_len = (1 - centre_pos) * total_pad_len
        start_pad = [stretched_array[0]] * int(start_pad_len)
        end_pad = [stretched_array[-1]] * int(end_pad_len)
        stretched_array = np.array(start_pad + list(stretched_array) + end_pad)
    else:
        pivot_point = (len(xs) - centre) * grain * coef
        first = int(pivot_point - (len(xs) * grain)/2)
        last = first + len(xs) * grain
        stretched_array = stretched_array[first:last]

    return [round(chunk.mean(), 2) for chunk in chunks(stretched_array, grain)]


def chunks(iterable, n):
    """
    Yield successive n-sized chunks from iterable.
    Source: 

    """
    for i in xrange(0, len(iterable), n):
        yield iterable[i:i + n]