有没有更短,更清晰的代码样式来解决此问题?
我正在尝试将一些float值分类为区域间文件夹。

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

最佳答案

具体解决方案

没有真正的通用解决方案,但是您可以使用以下表达式。

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

一般解决方案

如果您实际上需要某种概括,请注意任何非线性模式都会引起麻烦。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,从某些float rounding error来看,上述内容仍不完全安全。您可以通过手动键入intervals列表而不使用理解来增加精度。

连续间隔

如您的示例所示,如果数据中的间隔是连续的,那么它们之间就没有间隙,那么我们可以使用一些优化方法。即,我们只能在列表中存储每个间隔的上限。然后通过保持排序,我们可以使用 bisect 进行有效查找。
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'

重要说明:选择使用较高界限和bisect_right的原因是示例中排除了较高界限。如果排除了下限,那么我们将不得不使用bisect_left

另请注意,您可能希望以某些特殊方式处理[-0.95、0.95 []范围以外的数字,并注意将其留在bisect中。

关于python - Python if-else代码样式,用于减少浮点取整的代码,我们在Stack Overflow上找到一个类似的问题:https://stackoverflow.com/questions/55180829/

10-11 22:06
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