Question

例如，我希望在20到46之间生成22个数字，平均值为27.我希望这些数字能够尽可能地覆盖范围。

编辑：这些数字不需要是随机的。

Answer 1

警告：这不是最佳解决方案，但它对输入参数的运行速度非常快：

import random


def gen_avg(expected_avg=27, n=22, a=20, b=46):
    while True:
        l = [random.randint(a, b) for i in range(n)]
        avg = reduce(lambda x, y: x + y, l) / len(l)

        if avg == expected_avg:
            return l

for i in range(100):
    print gen_avg()

在我的笔记本电脑中，将在~2.5s内提供100个随机序列：

[21, 20, 20, 23, 25, 24, 29, 22, 42, 23, 31, 26, 30, 25, 29, 38, 20, 31, 46, 28, 41, 20]
[20, 30, 39, 26, 24, 31, 35, 36, 22, 22, 20, 32, 23, 21, 42, 32, 23, 24, 26, 28, 29, 25]
[23, 43, 21, 31, 44, 24, 24, 20, 27, 31, 28, 22, 26, 33, 25, 30, 21, 26, 33, 20, 31, 25]
[36, 28, 24, 29, 32, 21, 36, 28, 24, 27, 24, 22, 28, 28, 33, 21, 20, 32, 23, 30, 35, 21]
[21, 34, 25, 32, 20, 37, 31, 20, 46, 25, 21, 25, 35, 36, 21, 26, 21, 35, 24, 21, 30, 28]
[28, 23, 43, 22, 20, 23, 30, 41, 25, 32, 20, 21, 21, 30, 26, 22, 46, 40, 27, 26, 26, 21]
[21, 26, 38, 27, 42, 36, 43, 21, 29, 32, 22, 29, 26, 20, 23, 22, 21, 38, 23, 21, 21, 23]
[28, 21, 27, 34, 38, 21, 25, 37, 27, 22, 36, 38, 27, 20, 32, 35, 20, 24, 31, 22, 24, 24]
[28, 31, 23, 26, 36, 23, 30, 36, 32, 23, 20, 25, 23, 25, 25, 40, 21, 27, 21, 25, 28, 38]
[30, 24, 24, 25, 38, 27, 35, 31, 21, 31, 27, 22, 25, 25, 39, 31, 22, 23, 30, 29, 20, 23]
[25, 21, 42, 24, 24, 31, 22, 34, 32, 21, 23, 27, 20, 35, 31, 23, 26, 33, 20, 23, 22, 43]
[23, 23, 20, 40, 27, 22, 22, 41, 20, 21, 45, 26, 22, 28, 29, 39, 24, 23, 26, 34, 20, 38]
[22, 44, 27, 36, 29, 22, 24, 35, 30, 20, 20, 31, 38, 23, 20, 31, 25, 29, 30, 21, 24, 28]
[27, 30, 21, 28, 39, 30, 33, 33, 25, 21, 26, 33, 33, 24, 31, 20, 24, 25, 22, 27, 28, 20]
[23, 28, 24, 20, 35, 29, 33, 22, 23, 21, 31, 39, 32, 22, 24, 39, 22, 21, 29, 32, 34, 25]
[38, 25, 20, 22, 21, 44, 32, 20, 26, 20, 21, 29, 25, 20, 37, 27, 33, 23, 20, 39, 28, 27]
[29, 22, 30, 20, 31, 23, 23, 24, 28, 28, 46, 27, 24, 23, 21, 35, 20, 21, 45, 29, 27, 34]
[21, 29, 21, 33, 38, 44, 21, 20, 41, 30, 26, 23, 23, 29, 21, 32, 20, 29, 32, 29, 21, 26]
[21, 20, 24, 40, 30, 30, 31, 27, 20, 34, 28, 37, 31, 20, 38, 43, 25, 25, 21, 20, 27, 22]
[27, 35, 30, 21, 36, 37, 41, 21, 23, 24, 23, 32, 23, 25, 20, 23, 36, 40, 30, 24, 20, 24]
[39, 30, 30, 21, 26, 23, 20, 25, 36, 22, 23, 29, 23, 42, 20, 23, 32, 20, 30, 36, 25, 31]
[24, 24, 25, 41, 20, 27, 35, 31, 21, 24, 31, 36, 20, 25, 22, 32, 31, 30, 21, 22, 33, 25]
[22, 34, 33, 20, 29, 24, 34, 27, 27, 31, 20, 24, 22, 33, 36, 22, 21, 31, 21, 38, 21, 44]
[20, 43, 29, 23, 22, 32, 20, 21, 26, 23, 26, 33, 34, 22, 26, 20, 38, 21, 29, 32, 24, 33]
[23, 38, 39, 35, 21, 33, 25, 39, 33, 28, 23, 20, 22, 22, 25, 30, 20, 26, 28, 31, 24, 30]
[21, 36, 32, 42, 25, 25, 20, 46, 24, 22, 22, 22, 33, 32, 22, 29, 24, 26, 30, 23, 22, 21]
[25, 34, 20, 23, 44, 21, 40, 21, 25, 20, 26, 25, 44, 20, 24, 32, 21, 23, 31, 21, 43, 22]
[34, 31, 23, 20, 25, 30, 22, 23, 30, 22, 31, 21, 41, 42, 21, 22, 36, 20, 26, 24, 31, 32]
[27, 27, 35, 34, 31, 36, 21, 21, 24, 39, 22, 29, 29, 20, 20, 46, 23, 30, 27, 24, 28, 21]
[28, 37, 30, 31, 38, 23, 21, 20, 21, 32, 29, 24, 32, 20, 20, 21, 28, 20, 32, 41, 25, 40]
[27, 25, 24, 46, 23, 24, 26, 28, 30, 23, 23, 27, 38, 20, 44, 21, 27, 25, 20, 23, 26, 28]
[20, 28, 24, 33, 25, 22, 28, 27, 22, 27, 42, 25, 43, 27, 20, 26, 29, 33, 29, 24, 36, 23]
[39, 31, 27, 20, 23, 25, 22, 22, 24, 26, 25, 42, 21, 22, 21, 21, 28, 24, 44, 31, 35, 34]
[20, 20, 31, 30, 41, 30, 40, 20, 28, 20, 21, 25, 23, 30, 28, 25, 29, 21, 28, 28, 38, 24]
[35, 37, 30, 20, 24, 25, 36, 21, 23, 29, 25, 23, 21, 27, 22, 44, 41, 24, 33, 30, 22, 20]
[22, 22, 25, 20, 22, 29, 25, 25, 21, 33, 23, 20, 21, 42, 39, 32, 33, 30, 46, 34, 21, 22]
[26, 25, 27, 35, 30, 39, 20, 26, 43, 20, 29, 33, 23, 27, 35, 21, 20, 36, 24, 27, 21, 28]
[20, 30, 24, 31, 36, 23, 24, 46, 30, 28, 24, 25, 24, 22, 20, 33, 20, 21, 24, 23, 39, 27]
[20, 22, 33, 22, 33, 22, 38, 24, 29, 36, 23, 31, 26, 24, 28, 28, 26, 28, 43, 24, 25, 20]
[36, 26, 24, 24, 24, 33, 21, 28, 27, 29, 31, 31, 21, 27, 25, 24, 34, 20, 33, 37, 23, 30]
[25, 33, 24, 27, 30, 35, 25, 30, 23, 23, 20, 20, 28, 30, 29, 38, 25, 25, 32, 21, 25, 33]
[30, 21, 27, 33, 21, 43, 23, 23, 25, 29, 23, 38, 28, 24, 21, 44, 22, 31, 32, 21, 20, 27]
[21, 33, 26, 26, 33, 27, 26, 32, 41, 31, 25, 29, 33, 22, 26, 38, 24, 22, 21, 28, 21, 21]
[26, 28, 31, 20, 38, 20, 26, 23, 24, 24, 30, 21, 21, 33, 26, 33, 38, 28, 40, 24, 21, 26]
[21, 27, 30, 22, 24, 28, 38, 27, 20, 23, 41, 20, 26, 41, 26, 24, 29, 22, 20, 43, 21, 42]
[22, 28, 21, 25, 25, 46, 29, 27, 24, 34, 24, 27, 23, 23, 34, 21, 37, 26, 20, 44, 28, 24]
[32, 27, 21, 35, 28, 37, 21, 32, 23, 20, 21, 20, 31, 21, 32, 24, 35, 26, 42, 35, 22, 24]
[22, 36, 41, 35, 27, 20, 25, 21, 28, 32, 31, 30, 23, 26, 23, 26, 28, 33, 23, 35, 20, 23]
[28, 24, 27, 39, 37, 25, 21, 29, 36, 27, 24, 24, 26, 27, 37, 27, 28, 23, 27, 21, 22, 26]
[32, 33, 24, 31, 22, 35, 39, 20, 39, 39, 22, 21, 23, 28, 34, 23, 20, 21, 35, 24, 23, 22]
[25, 20, 20, 25, 28, 23, 37, 30, 34, 27, 22, 20, 41, 22, 22, 23, 42, 27, 39, 25, 22, 24]
[20, 36, 22, 21, 21, 38, 20, 45, 36, 28, 23, 23, 35, 26, 20, 30, 31, 28, 33, 22, 25, 31]
[30, 23, 21, 45, 20, 31, 35, 21, 22, 24, 29, 32, 34, 30, 23, 31, 20, 20, 31, 35, 29, 20]
[22, 21, 22, 32, 42, 24, 35, 22, 26, 21, 28, 23, 24, 21, 31, 20, 27, 39, 42, 21, 37, 33]
[26, 28, 24, 20, 42, 23, 22, 20, 22, 33, 24, 25, 24, 28, 38, 26, 44, 28, 31, 20, 28, 25]
[25, 42, 32, 20, 25, 20, 27, 22, 21, 20, 31, 28, 21, 31, 25, 25, 46, 28, 30, 41, 25, 20]
[20, 27, 28, 26, 34, 23, 20, 22, 34, 20, 36, 30, 21, 23, 26, 23, 31, 37, 23, 34, 40, 29]
[28, 30, 22, 21, 20, 35, 20, 24, 23, 24, 34, 33, 37, 34, 24, 21, 24, 21, 41, 32, 22, 30]
[21, 20, 21, 28, 24, 42, 36, 26, 29, 33, 26, 22, 33, 28, 26, 31, 20, 22, 29, 32, 27, 28]
[23, 41, 24, 39, 22, 23, 25, 21, 24, 35, 20, 27, 31, 43, 34, 29, 24, 22, 23, 21, 37, 21]
[20, 29, 32, 21, 27, 25, 32, 36, 24, 34, 33, 31, 25, 21, 29, 26, 21, 32, 23, 33, 20, 29]
[21, 32, 22, 26, 40, 40, 23, 28, 26, 25, 31, 21, 20, 37, 30, 30, 25, 35, 27, 24, 24, 21]
[25, 25, 27, 21, 27, 23, 20, 39, 20, 43, 29, 21, 38, 27, 30, 23, 24, 29, 20, 24, 36, 30]
[26, 20, 22, 25, 28, 22, 21, 29, 30, 37, 23, 39, 20, 34, 33, 23, 25, 30, 27, 41, 27, 26]
[29, 20, 32, 22, 26, 27, 21, 20, 27, 26, 22, 42, 28, 24, 26, 23, 40, 24, 27, 42, 23, 44]
[21, 38, 25, 26, 35, 28, 21, 40, 37, 28, 25, 23, 26, 22, 22, 21, 46, 29, 23, 23, 21, 32]
[39, 23, 20, 37, 26, 22, 30, 21, 25, 25, 32, 20, 39, 20, 33, 23, 24, 32, 38, 22, 33, 27]
[21, 21, 21, 20, 34, 20, 27, 36, 25, 20, 20, 26, 34, 40, 32, 32, 30, 22, 28, 29, 36, 35]
[37, 30, 23, 20, 21, 38, 26, 21, 41, 34, 33, 26, 36, 26, 25, 34, 34, 20, 24, 21, 20, 25]
[28, 24, 25, 29, 41, 24, 24, 29, 34, 37, 20, 29, 21, 30, 21, 28, 33, 20, 22, 43, 27, 20]
[35, 36, 20, 29, 26, 30, 26, 26, 34, 22, 24, 25, 21, 35, 34, 34, 25, 21, 23, 31, 24, 20]
[24, 25, 22, 22, 31, 28, 38, 42, 33, 24, 37, 27, 21, 42, 22, 28, 25, 20, 21, 25, 22, 29]
[26, 38, 33, 40, 22, 22, 21, 26, 29, 26, 23, 25, 35, 21, 27, 23, 35, 21, 43, 29, 20, 29]
[26, 31, 25, 20, 20, 21, 25, 25, 24, 28, 22, 30, 22, 22, 40, 37, 29, 46, 20, 38, 22, 24]
[24, 26, 23, 22, 34, 26, 30, 20, 24, 21, 32, 24, 24, 31, 31, 27, 28, 31, 32, 45, 25, 33]
[30, 32, 24, 27, 24, 21, 25, 22, 23, 39, 39, 22, 27, 23, 37, 23, 32, 23, 38, 21, 36, 22]
[27, 23, 22, 24, 28, 42, 26, 33, 28, 20, 20, 35, 22, 20, 31, 27, 34, 23, 32, 36, 23, 38]
[31, 35, 23, 28, 21, 28, 37, 20, 38, 34, 27, 20, 24, 27, 22, 26, 20, 29, 35, 31, 28, 21]
[28, 21, 33, 31, 24, 29, 20, 23, 25, 22, 28, 27, 30, 25, 29, 28, 26, 22, 38, 39, 30, 33]
[23, 36, 41, 26, 23, 29, 29, 45, 20, 23, 34, 21, 22, 39, 35, 24, 20, 24, 24, 25, 23, 28]
[25, 25, 21, 32, 44, 24, 32, 28, 33, 21, 22, 38, 32, 22, 25, 29, 22, 27, 29, 26, 26, 32]
[35, 28, 35, 24, 27, 34, 25, 30, 25, 42, 29, 26, 20, 36, 25, 25, 20, 20, 23, 21, 31, 34]
[44, 23, 20, 25, 24, 28, 20, 23, 38, 21, 24, 28, 35, 30, 20, 45, 23, 28, 39, 26, 23, 25]
[22, 25, 22, 45, 21, 22, 31, 37, 42, 28, 21, 24, 26, 25, 30, 25, 20, 36, 23, 25, 23, 29]
[32, 21, 28, 20, 20, 41, 25, 20, 46, 21, 38, 31, 25, 26, 21, 30, 20, 31, 39, 24, 22, 24]
[34, 24, 23, 26, 33, 20, 26, 26, 24, 20, 24, 25, 21, 29, 31, 30, 39, 34, 28, 27, 25, 41]
[26, 36, 20, 27, 23, 23, 20, 27, 32, 23, 24, 36, 34, 23, 24, 43, 25, 25, 33, 24, 31, 31]
[23, 21, 28, 20, 33, 46, 20, 43, 21, 24, 28, 21, 22, 34, 38, 25, 20, 20, 20, 25, 44, 32]
[30, 35, 26, 21, 28, 20, 21, 22, 24, 35, 23, 22, 21, 26, 24, 31, 41, 37, 27, 20, 43, 25]
[34, 42, 21, 20, 26, 21, 40, 20, 41, 21, 21, 23, 29, 22, 21, 26, 30, 25, 32, 29, 39, 27]
[31, 44, 40, 27, 22, 21, 44, 21, 30, 26, 20, 34, 22, 20, 20, 20, 29, 36, 22, 21, 22, 38]
[21, 43, 46, 28, 32, 22, 23, 21, 24, 21, 28, 21, 20, 33, 21, 24, 36, 22, 23, 28, 45, 32]
[21, 22, 24, 39, 21, 25, 25, 20, 23, 20, 22, 26, 40, 39, 22, 28, 41, 38, 20, 20, 33, 33]
[34, 22, 26, 23, 28, 20, 32, 25, 24, 20, 39, 28, 41, 24, 29, 32, 24, 33, 23, 34, 24, 23]
[22, 39, 36, 22, 24, 20, 28, 23, 30, 39, 23, 33, 37, 25, 27, 20, 23, 27, 34, 31, 25, 20]
[34, 20, 20, 22, 26, 21, 26, 40, 23, 20, 42, 23, 31, 25, 46, 31, 27, 28, 22, 31, 34, 23]
[24, 29, 39, 24, 39, 26, 25, 25, 29, 23, 27, 20, 46, 21, 27, 25, 20, 41, 24, 31, 25, 22]
[42, 25, 23, 30, 22, 23, 37, 20, 29, 32, 28, 22, 35, 36, 22, 20, 27, 39, 21, 20, 22, 32]
[24, 26, 37, 44, 26, 23, 21, 23, 34, 33, 36, 22, 22, 22, 21, 27, 35, 24, 22, 44, 21, 20]
[24, 27, 22, 30, 20, 27, 21, 24, 31, 22, 30, 33, 35, 24, 23, 20, 32, 28, 30, 44, 26, 29]

Answer 2

你可以用纯粹的数学方法来制作它。

随意选择所需范围内的数字（称之为n）
下一个号码是avg + abs（n-avg）
重复此操作，直到您填写所需的数字

如果所需数量的数量不均匀 - 只需选择其中一个数字作为平均数，然后你需要生成k-1个数字（这是偶数）

** 编辑 **
您可以使用此代码来操作初始列表以满足平均值的要求，因此生成的列表不对称。（优于生成列表，直到你找到正确的列表）

import random


def generate_numbers(wanted_avg, numbers_to_generate, start, end):
    rng = [i for i in range(start, end)]
    initial_selection = [random.choice(rng) for _ in range(numbers_to_generate)]
    initial_avg = reduce(lambda x, y: x+y, initial_selection) / float(numbers_to_generate)
    print "initial selection is: " + str(initial_selection)
    print "initial avg is: " + str(initial_avg)
    if initial_avg == wanted_avg:
        return initial_selection
    off = abs(initial_avg - wanted_avg)
    manipulation = off * numbers_to_generate

    sign = -1 if initial_avg > wanted_avg else 1

    manipulation_action = dict()
    acceptable_indices = range(numbers_to_generate)
    while manipulation > 0:
        random_index = random.choice(acceptable_indices)
        factor = manipulation_action[random_index] if random_index in manipulation_action else 0
        after_manipulation = initial_selection[random_index] + factor + sign * 1
        if start <= after_manipulation <= end:
            if random_index in manipulation_action:
                manipulation_action[random_index] += sign * 1
                manipulation -= 1
            else:
                manipulation_action[random_index] = sign * 1
                manipulation -= 1
        else:
            acceptable_indices.remove(random_index)

    for key in manipulation_action:
        initial_selection[key] += manipulation_action[key]

    print "after manipulation selection is: " + str(initial_selection)
    print "after manipulation avg is: " + str(reduce(lambda x, y: x+y, initial_selection) / float(numbers_to_generate))
    return initial_selection

Answer 3

所以我也使用了随机数发生器。另外，为了满足规范以尽可能地覆盖范围，我还计算了标准偏差，这是一个很好的传播衡量标准。因此，每当样本集满足平均值27的标准时，我将其与之前的匹配进行比较，并不断选择具有最高标准差的样本（平均值总是= 27）。因此，在我的脚本中，我进行了5次试验，您可以看到最终答案与具有最高std dev的samples_list匹配的输出。请注意，使用统计模块需要Python 3.4或更高版本。如果你使用的是Python 2，那么你可以用你自己的stdev函数替换它（你可以在Google或Stackoverflow上轻松找到它）

import random as rd
import statistics as st
min_val = 20
max_val = 46
sample_count = 22
expected_mean = 27
num_of_trials = 5

def get_samples_list(min_v, max_v, s_count, exp_mean):
    target_sum = sample_count * expected_mean
    samples_list = []
    curr_stdev_max = 0
    for trials in range(num_of_trials):
        samples = [0] * sample_count
        while sum(samples) != target_sum:
            samples = [rd.randint(min_v, max_v) for trial in range(s_count)]
        print ("Mean: ", st.mean(samples), "Std Dev: ", st.stdev(samples), )
        print (samples, "\n")
        if st.stdev(samples) > curr_stdev_max:
            curr_stdev_max = st.stdev(samples)
            samples_best = samples[:]
    return samples_best

samples_list = get_samples_list(min_val, max_val, sample_count, expected_mean)
print ("\nFinal list: ",samples_list)
samples_list.sort()
print ("\nSorted Final list: ",samples_list)

这是输出：

Mean:  27 Std Dev:  6.90755280213519
[34, 30, 39, 21, 23, 32, 22, 23, 22, 20, 27, 30, 29, 20, 32, 24, 42, 20, 39, 24, 20, 21] 

Mean:  27 Std Dev:  6.07100838882165
[21, 21, 34, 27, 35, 22, 29, 34, 24, 21, 20, 22, 20, 23, 26, 29, 28, 31, 30, 41, 21, 35] 

Mean:  27 Std Dev:  6.2105900340811875
[26, 27, 26, 26, 25, 42, 32, 23, 21, 34, 23, 20, 25, 25, 21, 27, 40, 21, 26, 26, 37, 21] 

Mean:  27 Std Dev:  8.366600265340756
[27, 22, 22, 44, 41, 21, 28, 36, 21, 23, 21, 25, 20, 20, 39, 46, 23, 25, 21, 23, 20, 26] 

Mean:  27 Std Dev:  6.347102826149446
[21, 30, 20, 41, 25, 23, 39, 26, 27, 20, 28, 23, 29, 24, 20, 40, 27, 27, 22, 25, 34, 23] 


Final list:  [27, 22, 22, 44, 41, 21, 28, 36, 21, 23, 21, 25, 20, 20, 39,
 46, 23, 25, 21, 23, 20, 26]

Sorted Final list:  [20, 20, 20, 21, 21, 21, 21, 22, 22, 23, 23, 23, 25, 25,
 26, 27, 28, 36, 39, 41, 44, 46]
>>>

Answer 4

尽可能覆盖范围并不是最佳，但您可以尝试：

def GenerateArr(count,minimum,maximum,average):
    arr = []
    diff = 1
    while len(arr) < count-1:
        if minimum <= average-diff and average+diff <= maximum:
            arr.append(average-diff)
            arr.append(average+diff)
            diff += 1
        else:
            arr.append(average)
            diff = 1
    if len(arr) < count:
        arr.append(average)
    return arr

print GenerateArr(22,20,46,27)

Answer 5

这是此问题的Python解决方案。这具有以下优点：

它不使用拒绝采样。
它从符合要求的所有组合中随机选择。

它基于John McClane的算法，他将其发布为answer to another question。我describe the algorithm的另一个答案。

import random # Or secrets

def permTable(nc, sum, mn, mx):
  t=[[0 for i in range(sum+1)] \
    for j in range(nc+1)]
  t[0][0]=1
  for i in range(1,nc+1):
    for j in range(0,sum+1):
      jm=max(j-(mx-mn), 0)
      v=0
      for k in range(jm, j+1): v+=t[i-1][k]
      t[i][j]=v
  return t

def getSol(nc, sum, mn, mx, table):
  s=sum-nc*mn
  ret=[0 for i in range(nc)]
  for ib in range(nc):
    i=nc-1-ib
    # Or 'secrets.randint(table[i+1][s])'
    v=random.randint(0, table[i+1][s]-1)
    r=mn
    v-=table[i][s]
    while v>=0:
      v-=table[i][s-1]
      s-=1
      r+=1
    ret[i]=r
  return ret

def genAverage(numSamples, valuesPerSample, mn, mx, avg):
   sum = avg * valuesPerSample
   pt = permTable(valuesPerSample, sum, mn, mx)
   return [getSol(valuesPerSample, sum, mn, mx, pt) \
      for i in range(numSamples)]

# Print one sample
print(genAverage(1, 22, 20, 46, 27))
# Print 100 samples
print(genAverage(100, 22, 20, 46, 27))

Answer 6

我使用了一种迭代方法，在生成数字的同时连续跟踪当前平均和目标平均。每一步都旨在在使用RNG /

的同时将cur_avg带向目标

import random

def gen_target_avg(num, min, max, avg):
    numbers = []
    sum = 0
    cur_avg = max
    print "Current avg is %f: %r" % (cur_avg, numbers)
    for n in range(0, num):
        if avg < cur_avg:
            n = random.randint(min, cur_avg)
            sum  += n
            numbers.append(n)
        elif avg > cur_avg:
            n = random.randint(cur_avg, max)
            sum += n
            numbers.append(n)
        cur_avg = sum/len(numbers)
    print "Final avg is %f: %r" % (cur_avg, numbers)

>>> gen_target_avg(100, 3, 150, 25)
Current avg is 150.000000: []
Final avg is 25.000000: [81, 47, 56, 58, 23, 27, 24, 3, 7, 11, 19, 15, 19, 11, 18, 14, 24, 20, 17, 3, 121, 16, 7, 24, 6, 14, 13]
>>> gen_target_avg(100, 3, 150, 25)  
Current avg is 150.000000: []
Final avg is 25.000000: [56, 3, 14, 139, 10, 10, 11, 34, 22, 26, 31, 24, 16,   19, 11, 28, 28, 6, 25, 19, 25, 17, 21]
>>> gen_target_avg(100, 3, 150, 30)
Current avg is 150.000000: []
Final avg is 30.000000: [143, 131, 38, 54, 34, 75, 31, 11, 63, 42, 38, 4, 22, 46, 27, 13, 6, 17, 14, 6, 21, 15, 3, 30, 15, 29, 28, 4, 32, 9, 17, 22, 10, 28, 11, 26]

如何使用Python生成具有特定平均值的范围内的数字？

6 个答案: