求与给定R代码功能一致的Python实现：数字分解为2的幂组合

以下是与指定R代码功能完全一致的Python实现，可将给定数字分解为2的幂值的组合，并生成包含组合值、幂值组合字符串及对应二进制位的DataFrame：

import math
import pandas as pd

def to_codes(x):
    # 计算每个数字的log2向下取整值，取最大值确定需要覆盖的2的幂范围
    n_list = [math.floor(math.log2(num)) for num in x]
    max_n = max(n_list)
    # 生成从max_n到1的整数序列，对应2的幂的指数
    pow_seq = list(range(max_n, 0, -1))
    powers = [2**p for p in pow_seq]
    
    # 生成每个数字对应的二进制位矩阵
    binary_matrix = []
    for num in x:
        bits = [(num // power) % 2 for power in powers]
        binary_matrix.append(bits)
    
    # 转换为DataFrame并设置列名
    df_binary = pd.DataFrame(binary_matrix, columns=[f"code_{p}" for p in powers])
    # 筛选出至少有一个非0值的列
    valid_cols = df_binary.columns[df_binary.any(axis=0)]
    df_binary = df_binary[valid_cols]
    
    # 生成每个数字对应的幂值组合字符串
    possible_codes = []
    for idx in range(len(x)):
        row_bits = df_binary.iloc[idx].values
        # 提取当前数字用到的2的幂值
        used_powers = [int(col.split("_")[1]) for col, bit in zip(df_binary.columns, row_bits) if bit == 1]
        # 反转后用逗号连接
        possible_codes.append(",".join(map(str, reversed(used_powers))))
    
    # 构造最终结果DataFrame
    result = pd.DataFrame({
        "combinedvalue": x,
        "possiblecodes": possible_codes
    })
    result = pd.concat([result, df_binary], axis=1)
    
    return result

# 测试示例
x = [20, 50]
print(to_codes(x))

输出结果 #

combinedvalue possiblecodes  code_32  code_16  code_4  code_2
0             20         4,16        0        1       1       0
1             50      2,16,32        1        1       0       1

内容的提问来源于stack exchange，提问作者Rajesh Addunuri