数据排序及索引

"""
对数据进行排序
并返回数据以及索引
"""
import time

from operator import itemgetter

import numpy as np


def cal_sort(new_distance):
    '''
    对间隔距离进行排序
    '''

    res = []
    for i in range(len(new_distance)):
        res.append([new_distance[i].astype(np.uint8), i])
    # res = np.asarray(res)
    res_tup = tuple(res)
    print(res_tup)
    result = sorted(res_tup, key=itemgetter(0), reverse=True)

    # 进行从大到小排序
    print(result)
    return result


def cal_gray(new_unique_gray, max_idx):
    '''
    计算灰度级之间间隔的最大距离的相邻左右灰度级
    '''
    left_gray = new_unique_gray[max_idx]
    right_gray = new_unique_gray[max_idx + 1]
    return left_gray, right_gray


update = np.array([1, 2, 4, 6, 9,14,20,30])
distance = np.array([10,6,5,3, 2, 2, 1])
dis_sorted = cal_sort(distance)

print(dis_sorted)

# flag = True
tp = np.copy(update)
# flag = True
for k in range(5):
    left_gray, right_gray = cal_gray(update, dis_sorted[k][1])
    print("left_gray, right_gray: ", left_gray, right_gray)
    res = 1 / 2 * (left_gray + right_gray)
    print("res: ", res)
    # if flag:
    #     flag = False
    print("dis_sorted[k]: ", dis_sorted[k][0])
    print("tp: ", tp)
    print("np.where(tp == 2)[0]: ", np.where(tp == 2)[0])
    tp = np.insert(tp, np.where(tp == left_gray)[0] + 1, res)
print(tp)