total_cost=32.5 vip=True if total_cost>50: if vip: discount=0.8 else: discount=0.9 else total_cost>30: discount=0.9 total_cost*=discount print('实际费用为:{}元'.format(total_cost))
时间: 2024-03-07 11:49:55 浏览: 27
这段代码存在错误,应该修改为:
```python
total_cost = 32.5
vip = True
if total_cost > 50:
if vip:
discount = 0.8
else:
discount = 0.9
elif total_cost > 30:
discount = 0.9
else:
discount = 1.0
total_cost *= discount
print('实际费用为:{}元'.format(total_cost))
```
修改后的代码,首先判断订单金额是否大于50元,如果是,则再判断是否是VIP客户,如果是,则打八折,否则打九折;如果订单金额不足50元,再判断是否大于30元,如果是,则打九折;如果订单金额不足30元,则没有折扣。最后计算实际费用并输出。
相关问题
n, m = map(float, input().split()) if n <= 200: call_cost = 0 else: call_cost = (n - 200) * 0.15 data_cost = 0 if m <= 10: pass elif m <= 1024: data_cost += (m - 10) / 1024 * 5 else: data_cost += (1024 - 10) / 1024 * 5 data_cost += (m - 1024) / 1024 * 3 total_cost = 29 + call_cost + data_cost print("{:.2f}".format(total_cost))
There are a few issues with this code. First, there needs to be an input statement to get the values of n and m. Second, the variables call_cost and data_cost are not being added together to get the total_cost. Third, the print statement is not using the total_cost variable.
Here is a corrected version of the code:
n, m = map(float, input().split())
if n <= 200:
call_cost = 0
else:
call_cost = (n - 200) * 0.15
if m <= 10:
data_cost = 0
elif m <= 1024:
data_cost = (m - 10) / 1024 * 5
else:
data_cost = (1024 - 10) / 1024 * 5 + (m - 1024) / 1024 * 3
total_cost = 29 + call_cost + data_cost
print("{:.2f}".format(total_cost))
% 设置模拟参数 N = 10000; mu_p = 198900; sigma_p = sqrt(4500.2); mu_f = 120050.28; sigma_f = sqrt(3900.6); mu_r =30710; sigma_r = sqrt(892.6); mu_s = -1572.5; sigma_s = sqrt(60.2); % 生成随机样本 p_cost = normrnd(mu_p, sigma_p, [N, 1]); f_cost = normrnd(mu_f, sigma_f, [N, 1]); r_cost = normrnd(mu_r, sigma_r, [N, 1]); s_cost = normrnd(mu_s, sigma_s, [N, 1]); % 计算总成本 total_cost = p_cost + f_cost + r_cost + s_cost; % 绘制总成本直方图 histogram(total_cost, 'Normalization', 'pdf'); xlabel('Total Cost (Millions of Yuan)'); ylabel('Probability Density'); % 输出统计信息 fprintf('Mean Total Cost: %.2f (Millions of Yuan)\n', mean(total_cost)); fprintf('Standard Deviation of Total Cost: %.2f (Millions of Yuan)\n', std(total_cost));帮我修改输出结果横坐标的跨度
可以使用 `xlim` 函数修改输出结果横坐标的跨度。例如,将横坐标范围设置为 $[50, 350]$,可以在代码最后添加以下语句:
```matlab
xlim([50, 350]);
```
修改后的完整代码如下:
```matlab
% 设置模拟参数
N = 10000;
mu_p = 198900;
sigma_p = sqrt(4500.2);
mu_f = 120050.28;
sigma_f = sqrt(3900.6);
mu_r = 30710;
sigma_r = sqrt(892.6);
mu_s = -1572.5;
sigma_s = sqrt(60.2);
% 生成随机样本
p_cost = normrnd(mu_p, sigma_p, [N, 1]);
f_cost = normrnd(mu_f, sigma_f, [N, 1]);
r_cost = normrnd(mu_r, sigma_r, [N, 1]);
s_cost = normrnd(mu_s, sigma_s, [N, 1]);
% 计算总成本
total_cost = p_cost + f_cost + r_cost + s_cost;
% 绘制总成本直方图
histogram(total_cost, 'Normalization', 'pdf');
xlabel('Total Cost (Millions of Yuan)');
ylabel('Probability Density');
xlim([50, 350]);
% 输出统计信息
fprintf('Mean Total Cost: %.2f (Millions of Yuan)\n', mean(total_cost));
fprintf('Standard Deviation of Total Cost: %.2f (Millions of Yuan)\n', std(total_cost));
```