Python if-else代码样式，用于减少舍入浮点数的代码

发布于2019-08-28 12:51 阅读(1632) 评论(0) 点赞(0) 收藏(1)

是否有更短，更清晰的代码风格来解决这个问题？我试图将一些浮点值分类到区域间文件夹中。

def classify(value):   
    if value < -0.85 and value >= -0.95:
        ts_folder = r'\-0.9'
    elif value < -0.75 and value >= -0.85:
        ts_folder = r'\-0.8'
    elif value < -0.65 and value >= -0.75:
        ts_folder = r'\-0.7'    
    elif value < -0.55 and value >= -0.65:
        ts_folder = r'\-0.6'   
    elif value < -0.45 and value >= -0.55:
        ts_folder = r'\-0.5'  
    elif value < -0.35 and value >= -0.45:
        ts_folder = r'\-0.4'
    elif value < -0.25 and value >= -0.35:
        ts_folder = r'\-0.3'
    elif value < -0.15 and value >= -0.25:
        ts_folder = r'\-0.2'
    elif value < -0.05 and value >= -0.15:
        ts_folder = r'\-0.1'
    elif value < 0.05 and value >= -0.05:
        ts_folder = r'\0.0'
    elif value < 0.15 and value >= 0.05:
        ts_folder = r'\0.1'
    elif value < 0.25 and value >= 0.15:
        ts_folder = r'\0.2'
    elif value < 0.35 and value >= 0.25:
        ts_folder = r'\0.3'
    elif value < 0.45 and value >= 0.35:
        ts_folder = r'\0.4'
    elif value < 0.55 and value >= 0.45:
        ts_folder = r'\0.5'
    elif value < 0.65 and value >= 0.55:
        ts_folder = r'\0.6'
    elif value < 0.75 and value >= 0.65:
        ts_folder = r'\0.7'  
    elif value < 0.85 and value >= 0.75:
        ts_folder = r'\0.8'
    elif value < 0.95 and value >= 0.85:
        ts_folder = r'\0.9'

    return ts_folder

解决方案

具体方案

没有真正的通用解决方案，但在您的情况下，您可以使用以下表达式。

ts_folder = r'\{:.1f}'.format(round(value, 1))

一般解决方案

如果您确实需要某种泛化，请注意任何非线性模式都会带来麻烦。虽然，有一种方法可以缩短代码。

def classify(key, intervals):
    for lo, hi, value in intervals:
        if lo <= key < hi:
            return value
    else:
        ... # return a default value or None

# A list of tuples (lo, hi, key) which associates any value in the lo to hi interval to key
intervals = [
    (value / 10 - 0.05, value / 10 + 0.05, r'\{:.1f}'.format(value / 10))
    for value in range(-9, 10)
]

value = -0.73

ts_folder = classify(value, intervals) # r'\-0.7'

请注意，上面的浮动舍入错误仍然不完全安全。您可以通过手动键入intervals列表而不是使用理解来添加精度。

连续间隔

如果数据中的间隔是连续的，那么它们之间没有间隙，如您的示例中那样，我们可以使用一些优化。也就是说，我们只能在列表中存储每个区间的上限。然后通过保持那些排序，我们可以bisect用于有效查找。

import bisect

def value_from_hi(hi):
    return r'\{:.1f}'.format(hi - 0.05)

def classify(key, boundaries):
    i = bisect.bisect_right(boundaries, key)
    if i < len(boundaries):
        return value_from_hi(boundaries[i])
    else:
        ... # return some default value

# Sorted upper bounds
boundaries = [-0.85, -0.75, -0.65, -0.55, -0.45, -0.35, -0.25, -0.15, -0.05,
              0.05, 0.15, 0.25, 0.35, 0.45, 0.55, 0.65, 0.75, 0.85, 0.95]

ts_folder = classify(-0.32, boundaries) # r'\-0.3'