import gradio as gr
import pandas as pd
import matplotlib.font_manager as font_manager
import matplotlib.pyplot as plt
import warnings

warnings.filterwarnings(action='ignore', category=UserWarning)

font_path = './SimHei.ttf'  # 替换为实际的字体文件路径

font_manager.fontManager.addfont(font_path)
plt.rcParams['font.family'] = 'SimHei'  # 将 'custom_font' 替换为您为该字体指定的名称


plt.rcParams['axes.unicode_minus'] = False  # 设置正常显示字符

def process_file(file):
    # 读取CSV或Excel文件并创建DataFrame
    if file.name.endswith('.csv'):
        df = pd.read_csv(file.name)
    elif file.name.endswith('.xlsx') or file.name.endswith('.xls'):
        df = pd.read_excel(file.name)
    else:
        return "不支持的数据文件格式。"
    
    columns = df.columns.tolist()
    feature_columns = columns[:-1]
    last_column = [columns[-1]]
    # 返回前5行数据，更新下拉列表选项，并使其他控件可见
    return (gr.update(choices=feature_columns, visible=True), 
            gr.update(choices=last_column, value=last_column[-1], visible=True), 
            gr.update(visible=True),
            # gr.update(visible=True),
            df.head(), 
            gr.update(visible=True)
            )

def update_choice_radio(choice_feature_column):
    # 更新数轴控件的可见性
    return gr.update(label="“" + choice_feature_column + "”是否为连续值", visible=True)

def update_slider(choice):
    # 更新数轴控件的可见性
    return gr.update(visible=choice == "是")

def generate_output(file, column1, column2, choice, bins):
    # 读取CSV或Excel文件并创建DataFrame
    if file.name.endswith('.csv'):
        df = pd.read_csv(file.name)
    elif file.name.endswith('.xlsx') or file.name.endswith('.xls'):
        df = pd.read_excel(file.name)
    else:
        return "不支持的数据文件格式。"
    data_x = df[column1]
    data_y = df[column2]

    # 自动判断column1的数据类型
    if choice == "是":
        # 如果是连续值，则进行分组
        data_x = pd.qcut(data_x, q=bins, duplicates='drop')
        data_x = data_x.apply(lambda x: f'{x.left:.2f} - {x.right:.2f}')
    else:
        # 如果是离散值，则直接使用
        pass
    
    # 统计每个身高分段中不同心血管疾病类别的数量
    counts = pd.crosstab(data_x, data_y)
    # 设置画布大小
    plt.figure(figsize=(bins*2, 10))
    # 绘制分段柱形图
    counts.plot(kind='bar')
    # 设置 x 轴刻度标签横向显示
    plt.xticks(rotation=15)
    plt.xlabel(column1, fontsize=12)
    plt.ylabel(column2, fontsize=12)
    # plt.legend(['不患病', '患病'])
    plt.title(f'{column1}与{column2}的关系', fontsize=14)
    # plt.show()   

    image_path = 'output.png'
    plt.savefig(image_path)
    # plt.close()

    return df.head(), gr.update(visible=True), image_path, gr.update(visible=True)
    
with gr.Blocks() as demo:
    with gr.Row():
        with gr.Column():
            file_input = gr.File(label="上传表格文件（支持CSV、XLS、XLSX等格式", file_types=["csv", "xls", "xlsx"])
            col1_dropdown = gr.Dropdown(label="请选择特征列", visible=False)
            col2_dropdown = gr.Dropdown(label="选择标签列", visible=False)
            choice_radio = gr.Radio(["是", "否"], label="特征列是否为连续值", visible=False) # , value="否"
            slider = gr.Slider(minimum=3, maximum=7, step=1, label="选择将特征列分组的分组数", visible=False, value=4)
            submit_button = gr.Button("查看结果", visible=False)
        with gr.Column():
            df_display = gr.Dataframe(visible=False)
            output_image = gr.Image(visible=False)

    # # 文件上传后调用 process_file 函数
    # file_input.upload(process_file, inputs=file_input, outputs=[col1_dropdown, col2_dropdown, choice_radio, df_display, df_display, submit_button])
    # 文件上传后调用 process_file 函数
    file_input.upload(process_file, inputs=file_input, outputs=[col1_dropdown, col2_dropdown, df_display, df_display, submit_button])
    
    # 选择框值改变时调用 update_col2_dropdown 函数
    col1_dropdown.change(update_choice_radio, inputs=col1_dropdown, outputs=choice_radio)

    # 选择框值改变时调用 update_slide函数
    choice_radio.change(update_slider, inputs=choice_radio, outputs=slider)
    
    # 点击提交按钮时调用 generate_output 函数
    submit_button.click(generate_output, inputs=[file_input, col1_dropdown, col2_dropdown, choice_radio, slider], outputs=[df_display, df_display, output_image, output_image])

demo.launch(share=True)