[英]Structural pattern matching and infinity
I am computing the Lp distance functions for non-negative p 's.我正在计算非负p的Lp距离函数。 For all but p = 0 and p = ∞ a built-in
pow()
function serves well.对于除p = 0 和p = ∞ 之外的所有情况,内置的
pow()
function 都能很好地发挥作用。 Before I learned about a structural pattern matching, I had used a dictionary and exception handling:在了解结构模式匹配之前,我使用过字典和异常处理:
from math import sqrt, inf
distance_function = { 0.0: lambda x, y: int(x != 0.0) + int(y != 0.0),
1.0: lambda x, y: abs(x) + abs(y), # Likely a tad faster than 'pow()'
inf: lambda x, y: max(abs(x), abs(y))}
def lp_distance(x, y, p):
try: return distance_function[p](x, y)
except KeyError: return pow(pow(abs(x), p) + pow(abs(y), p), 1.0/p)
Some people didn't want exceptions here.有些人不想在这里有例外。 So I rewrote the snippet into the following one:
所以我将片段重写为以下片段:
def lp_distance(x, y, p):
match p:
case 0.0: return int(x != 0.0) + int(y != 0.0)
case 1.0: return abs(x) + abs(y)
# The line below triggers "SyntaxError: name capture 'inf' makes remaining patterns unreachable"
case inf: return max(abs(x), abs(y))
# But the following works:
case p if p == inf: return max(abs(x), abs(y))
case _: return pow(pow(abs(x), p) + pow(abs(y), p), 1.0/p)
Why case inf:
is not correct ( Python v3.10.2 )?为什么
case inf:
不正确 ( Python v3.10.2 )?
In a case
statement, a simple name is a pattern that captures (assigns) to that name .在
case
语句中, 简单名称是一种捕获(分配)给该名称的模式。 In contrast, a dotted name is a patterns that refers to the value of that name .相反, 带点的名称是指代该名称值的模式。
In simple terms
NAME
will always succeed and it will setNAME = <subject>
.简而言之,
NAME
将始终成功,并且它将设置NAME = <subject>
。
In simple terms
NAME1.NAME2
will succeed only if<subject> == NAME1.NAME2
简单来说,只有
<subject> == NAME1.NAME2
NAME1.NAME2
才会成功
Using just case inf:
means that the value to match is unconditionally assigned to the name inf
– it does not matter if the name was previously bound.使用 just
case inf:
意味着要匹配的值无条件地分配给名称inf
名称是否先前绑定并不重要。
What you want instead is case math.inf:
, which means to compare against this value.你想要的是
case math.inf:
,这意味着要与这个值进行比较。
import math
def lp_distance(x, y, p):
match p:
case 0.0:
return int(x != 0.0) + int(y != 0.0)
case 1.0:
return abs(x) + abs(y)
# compare against a value by using its dotted name
case math.inf:
return max(abs(x), abs(y))
case _:
return pow(pow(abs(x), p) + pow(abs(y), p), 1.0/p)
As noted by the other respondents, you can't use inf directly because that is a capture pattern.正如其他受访者所指出的,您不能直接使用inf ,因为那是一种捕获模式。 The obvious solution is to use a value pattern with a dotted lookup;
显而易见的解决方案是使用带点查找的值模式; however, that only works for positive infinity .
但是,这仅适用于正无穷大。
To handle other all special values like negative infinity and NaNs, you need guards:要处理其他所有特殊值,如负无穷大和 NaN,你需要守卫:
match x:
case 1.0: ... # Exact value (literal pattern)
case 0.0: ... # Exact value (literal pattern)
case _ if math.isfinite(x): ... # Normal cases
case _ if math.isnan(x): ... # NaNs defy equality tests
case _: ... # Negative infinity
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