请把完成代码再发给我一下

完整代码如下：

import sympy as sp
import plotly.graph_objs as go

x, y, z = sp.symbols('x y z')
eq1 = sp.Eq((x**3)/3 - (y**2)/2-z, (x**2 + y**2 - 1)*(y**2 + z**2 - 1)*(x**2 + z**2 - 1) - 1)
sol = sp.solve(eq1, [x, y, z])
points = []
for s in sol:
    points.append([s[x], s[y], s[z]])

fig = go.Figure(data=[go.Scatter3d(x=[p[0] for p in points], y=[p[1] for p in points], z=[p[2] for p in points], mode='lines')])
fig.show()

这段代码会生成一个交互式的3D图形，显示两个曲面的交线。

相关问题

请你依照上述内容写一个c++代码发给我

当然可以！以下是一个基于上述设计思路的C++代码示例：

#include <iostream>
#include <fstream>
#include <vector>
#include <algorithm>

using namespace std;

class Employee {
public:
    int id;
    string name;
    string gender;
    int age;

    Employee(int id, string name, string gender, int age) {
        this->id = id;
        this->name = name;
        this->gender = gender;
        this->age = age;
    }
};

class Teacher : public Employee {
public:
    string department;
    string major;
    string title;

    Teacher(int id, string name, string gender, int age, string department, string major, string title) : Employee(id, name, gender, age) {
        this->department = department;
        this->major = major;
        this->title = title;
    }
};

class LabAssistant : public Employee {
public:
    string lab;
    string position;

    LabAssistant(int id, string name, string gender, int age, string lab, string position) : Employee(id, name, gender, age) {
        this->lab = lab;
        this->position = position;
    }
};

class Administrator : public Employee {
public:
    string politicalStatus;
    string title;

    Administrator(int id, string name, string gender, int age, string politicalStatus, string title) : Employee(id, name, gender, age) {
        this->politicalStatus = politicalStatus;
        this->title = title;
    }
};

vector<Employee*> employees;

void inputData() {
    int type;
    cout << "请选择员工类型（1-教师，2-实验员，3-行政人员）：";
    cin >> type;

    int id;
    string name, gender;
    int age;

    cout << "请输入员工编号：";
    cin >> id;
    cout << "请输入员工姓名：";
    cin >> name;
    cout << "请输入员工性别：";
    cin >> gender;
    cout << "请输入员工年龄：";
    cin >> age;

    if (type == 1) {
        string department, major, title;
        cout << "请输入所在系部：";
        cin >> department;
        cout << "请输入专业：";
        cin >> major;
        cout << "请输入职称：";
        cin >> title;

        employees.push_back(new Teacher(id, name, gender, age, department, major, title));
    } else if (type == 2) {
        string lab, position;
        cout << "请输入所在实验室：";
        cin >> lab;
        cout << "请输入职务：";
        cin >> position;

        employees.push_back(new LabAssistant(id, name, gender, age, lab, position));
    } else if (type == 3) {
        string politicalStatus, title;
        cout << "请输入政治面貌：";
        cin >> politicalStatus;
        cout << "请输入职称：";
        cin >> title;

        employees.push_back(new Administrator(id, name, gender, age, politicalStatus, title));
    }

    cout << "成功录入员工信息！" << endl;
}

void displayData() {
    if (employees.empty()) {
        cout << "当前系统中没有记录！" << endl;
        return;
    }

    for (const auto& employee : employees) {
        cout << "编号：" << employee->id << "，姓名：" << employee->name << "，性别：" << employee->gender
             << "，年龄：" << employee->age << endl;
    }
}

void sortDataByAge() {
    if (employees.empty()) {
        cout << "当前系统中没有记录！" << endl;
        return;
    }

    sort(employees.begin(), employees.end(), [](const Employee* a, const Employee* b) {
        return a->age < b->age;
    });

    cout << "按照年龄排序完成！" << endl;
}

void saveData() {
    if (employees.empty()) {
        cout << "当前系统中没有记录！" << endl;
        return;
    }

    ofstream file("employees.txt");
    if (file.is_open()) {
        for (const auto& employee : employees) {
            file << employee->id << "," << employee->name << "," << employee->gender << "," << employee->age << endl;
        }
        file.close();
        cout << "员工信息已保存到文件中。" << endl;
    } else {
        cout << "无法打开文件！" << endl;
    }
}

int main() {
    int choice;

    do {
        cout << "**********************" << endl;
        cout << "1. 数据录入" << endl;
        cout << "2. 显示功能" << endl;
        cout << "3. 统计功能" << endl;
        cout << "4. 保存功能" << endl;
        cout << "5. 退出系统" << endl;
        cout << "**********************" << endl;

        cout << "请选择操作：";
        cin >> choice;

        switch (choice) {
            case 1:
                inputData();
                break;
            case 2:
                displayData();
                break;
            case 3:
                sortDataByAge();
                break;
            case 4:
                saveData();
                break;
            case 5:
                cout << "退出系统。" << endl;
                break;
            default:
                cout << "无效的选择！" << endl;
                break;
        }
    } while (choice != 5);

    // 释放内存
    for (const auto& employee : employees) {
        delete employee;
    }

    return 0;
}

这是一个基本的实现，你可以根据需要进行修改和扩展。请注意，此代码示例可能不包含输入验证和错误处理。在实际应用中，你可能需要添加适当的验证和错误处理机制。

希望这可以帮助到你！如果有任何进一步的问题，请随时提问。

请在代码中加入最后绘图部分，并发给我完整代码

好的，这里是加入了绘图部分的完整代码。这段代码会对PTB心电信号进行滤波和去噪处理，并将处理后的数据绘制成图像，方便直观查看。

import numpy as np
import wfdb
import os
from scipy import signal
import matplotlib.pyplot as plt

# 设置数据集路径
data_path = 'D:/下载/ptb-xl-a-large-publicly-available-electrocardiography-dataset-1.0.3'

# 定义滤波器
def butter_bandpass(lowcut, highcut, fs, order=5):
    nyq = 0.5 * fs
    low = lowcut / nyq
    high = highcut / nyq
    b, a = signal.butter(order, [low, high], btype='band')
    return b, a

# 定义去噪函数
def remove_noise(data, fs):
    b, a = butter_bandpass(0.05, 150, fs, order=5)
    filtered = signal.filtfilt(b, a, data)
    return filtered

# 遍历所有数据文件
for subdir, dirs, files in os.walk(data_path):
    for file in files:
        if file.endswith('.mat'):
            # 读取数据
            record = wfdb.rdrecord(os.path.join(subdir, file))
            data = record.p_signal[:, 0]
            fs = record.fs
            
            # 数据预处理
            filtered_data = remove_noise(data, fs)
            
            # 绘制图像
            t = np.arange(0, len(filtered_data) / fs, 1 / fs)
            fig, ax = plt.subplots()
            ax.plot(t, filtered_data)
            ax.set(xlabel='Time (s)', ylabel='Amplitude (mV)', title=file)
            ax.grid()
            plt.show()
            
            # 保存处理后的数据
            wfdb.rdwrite(os.path.join(subdir, file), fs, filtered_data, record.signame, record.units)
            
            print(file + '处理完成')

这段代码会对PTB心电信号进行滤波和去噪处理，并将处理后的数据绘制成图像，方便直观查看。在处理完成后，程序会输出文件名，表明该文件已经处理完成。