时间戳

首页 > 解决方案 > 使用 itertools 添加标签

list - 使用 itertools 添加标签

问题描述

我有一个脚本来计算二维矩阵的行列式。我如何编写每个计算确定的标签？我创建了一个空列表来填充标签...

那是代码：

import itertools, operator
import numpy as np
list_determinant=[]
list_label=[]
K=[1,2]

l = np.asarray([(100,1),(100,2),(200,5),(200,7)])
print(l)
grouped = itertools.groupby([(label, float(value)) for (label, value) in l], operator.itemgetter(0))

def example(g):
    value = [value for label, value in g]
    xy = np.stack((value,K),axis=1)
    determinant = np.linalg.det(xy) 
    list_determinant.append(determinant)
    return determinant

function = [(label, '%.3f' %round(example(g),3)) for (label, g) in grouped]
print(function)

print(list_determinant)

print(list_label)  #???

标签： listpython-3.6itertools

解决方案

为什么不从function列表中提取标签？你的最后几行看起来像：

⋮

list_label = [label for (label, _) in function]
print(list_label)

我会对您的代码进行其他修改，但这只是个人喜好问题：

import itertools, operator
import numpy as np

K = (1, 2)

input_values = np.asarray([(100, 1), (100, 2), (200, 5), (200, 7)])
print(input_values)

values_as_float = ((label, float(value)) for (label, value) in input_values)
values_grouped = itertools.groupby(values_as_float, operator.itemgetter(0))

def compute_determinants(values_grouped):
    for (current_label, current_group) in values_grouped:
        values = [value for _, value in current_group]
        xy = np.stack((values, K), axis=1)
        determinant = np.linalg.det(xy)
        yield (current_label, determinant)

results = list(compute_determinants(values_grouped))
results_formatted = [(label, f'{determinant:.3f}') for (label, determinant) in results]
print(results_formatted)

labels, determinants = list(zip(*results))
print(determinants)
print(labels)

推荐阅读