BMI指数测试程序

大家都知道BMI指数吧。

但是不同的人会有不同的BMI

我给大家程序。

import tkinter as tk
from tkinter import messagebox
from joblib import load
import pandas as pd
import numpy as np

# 加载BMI数据
data = pd.read_csv('bmi.csv')

# 加载分类器
clf = load('clf.pkl')

# 计算BMI
def calculate_bmi():
    height = float(entry_height.get())
    weight = float(entry_weight.get())
    bmi = weight / (height * height)
    return bmi

# 计算建议的体重
def calculate_suggested_weight():
    height = float(entry_height.get())
    desired_bmi = 24.0
    suggested_weight = desired_bmi * (height * height)
    return suggested_weight

# 预测BMI的范围
def predict_bmi_range():
    sex = variable_sex.get()
    age = int(entry_age.get())
    height = float(entry_height.get())
    weight = float(entry_weight.get())
    bmi = weight / (height * height)

    X = np.array([[sex, age, height, weight]])
    bmi_range = clf.predict(X)

    return bmi_range[0]

# 显示结果
def show_result():
    bmi = calculate_bmi()
    bmi_range = predict_bmi_range()
    suggested_weight = calculate_suggested_weight()

    if bmi < 18.5:
        if bmi_range == 'adult_man' or bmi_range == 'adult_woman':
            messagebox.showinfo("结果", "您的BMI指数为：{}，体重过轻。建议增加锻炼，增强身体素质。".format(bmi))
        elif bmi_range == 'child_man' or bmi_range == 'child_woman':
            messagebox.showinfo("结果", "您的BMI指数为：{}，体重过轻。建议增加营养，保证健康成长。".format(bmi))
    elif 18.5 <= bmi < 24.0:
        if bmi_range == 'adult_man' or bmi_range == 'adult_woman':
            messagebox.showinfo("结果", "您的BMI指数为：{}，体重正常。保持良好的生活习惯，有助于保持健康的身体。".format(bmi))
        elif bmi_range == 'child_man' or bmi_range == 'child_woman':
            messagebox.showinfo("结果", "您的BMI指数为：{}，体重正常。保持良好的生活习惯，有助于健康成长。".format(bmi))
    elif 24.0 <= bmi < 28.0:
        if bmi_range == 'adult_man' or bmi_range == 'adult_woman':
            messagebox.showinfo("结果", "您的BMI指数为：{}，体重过重。建议控制饮食，增加锻炼，以保持健康的身体。".format(bmi))
        elif bmi_range == 'child_man' or bmi_range == 'child_woman':
            messagebox.showinfo("结果", "您的BMI指数为：{}，体重过重。建议控制饮食，增加锻炼，以保持健康的身体。".format(bmi))
    else:
        if bmi_range == 'adult_man' or bmi_range == 'adult_woman':
            messagebox.showinfo("结果", "您的BMI指数为：{}，肥胖。建议控制饮食，增加锻炼，以保持健康的身体。".format(bmi))
        elif bmi_range == 'child_man' or bmi_range == 'child_woman':
            messagebox.showinfo("结果", "您的BMI指数为：{}，肥胖。建议控制饮食，增加锻炼，以保持健康的身体。".format(bmi))

# 创建主窗口
win = tk.Tk()
win.title("BMI计算与建议")

# 创建变量
variable_sex = tk.StringVar()

# 创建标签和输入框
label_height = tk.Label(win, text="请输入身高（米）：")
label_height.pack()
entry_height = tk.Entry(win)
entry_height.pack()

label_weight = tk.Label(win, text="请输入体重（千克）：")
label_weight.pack()
entry_weight = tk.Entry(win)
entry_weight.pack()

label_sex = tk.Label(win, text="请选择性别：")
label_sex.pack()
radio_man = tk.Radiobutton(win, text="男", variable=variable_sex, value="man")
radio_man.pack()
radio_woman = tk.Radiobutton(win, text="女", variable=variable_sex, value="woman")
radio_woman.pack()

label_age = tk.Label(win, text="请输入年龄：")
label_age.pack()
entry_age = tk.Entry(win)
entry_age.pack()

# 创建按钮
button_calculate = tk.Button(win, text="计算BMI", command=show_result)
button_calculate.pack()

# 运行主循环
win.mainloop()

这是python文件

还有几个附加文件

sex,age,height,weight,bmi
man,25,1.75,70,23.5
man,30,1.8,80,24.5
man,20,1.7,60,22.8
woman,25,1.65,65,22.5
woman,20,1.6,55,21.5
man,25,1.7,70,23.5
woman,30,1.7,75,23.5
man,22,1.72,65,22.9
woman,28,1.68,60,21.7
man,18,1.65,55,20.5
woman,19,1.55,45,19.5
man,15,1.5,40,17.5
woman,20,1.6,50,21.5
man,28,1.78,75,24.0
woman,24,1.62,55,21.0
man,17,1.67,58,20.0
woman,18,1.58,48,18.5

名字叫做bmi.csv

训练数据

# 导入所需库
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn.neighbors import KNeighborsClassifier
from sklearn.metrics import accuracy_score

# 加载BMI数据
data = pd.read_csv('bmi.csv')

# 划分特征和标签
X = data[['height', 'weight']]
y = data['bmi']

# 划分训练集和测试集
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

# 数据标准化
scaler = StandardScaler()
X_train = scaler.fit_transform(X_train)
X_test = scaler.transform(X_test)

# 使用KNN分类器训练模型
clf = KNeighborsClassifier(n_neighbors=3)
clf.fit(X_train, y_train)

# 预测测试集
y_pred = clf.predict(X_test)

# 计算准确率
accuracy = accuracy_score(y_test, y_pred)
print('Accuracy:', accuracy)

# 保存模型
import joblib
joblib.dump(clf, 'clf.pkl')

clf.pkl

训练分别程序

上次我的那个爬虫文章审核因为不明原因不通过所以：我没办法了，我就多加了几个gobots.txt

呜呼

csv文件为训练文件可以变为自己的训练数据。