WTOAAM/dataAnalysisBusiness/algorithm/windSpeedAnalyst.py

import os
import pandas as pd
import numpy as np
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import plotly.express as px  
from behavior.analyst import Analyst
from utils.directoryUtil import DirectoryUtil as dir
from algorithmContract.confBusiness import *

class WindSpeedAnalyst(Analyst):

    def typeAnalyst(self):
        return "wind_speed"

    def turbinesAnalysis(self, dataFrameMerge, outputAnalysisDir, confData: ConfBusiness):
        self.drawWindSpeedAnalysis(dataFrameMerge, outputAnalysisDir, confData)

    def drawWindSpeedAnalysis(self, dataFrameMerge: pd.DataFrame, outputAnalysisDir, confData: ConfBusiness):
        # 检查所需列是否存在
        required_columns = {Field_NameOfTurbine,confData.field_wind_speed}
        if not required_columns.issubset(dataFrameMerge.columns):
            raise ValueError(f"DataFrame缺少必要的列。需要的列有: {required_columns}")
        
        # 确保'风速'列是数值类型  
        dataFrameMerge[confData.field_wind_speed] = pd.to_numeric(dataFrameMerge[confData.field_wind_speed], errors='coerce')  
        
        # 计算每个turbine_name的平均风速  
        average_wind_speed = dataFrameMerge.groupby(Field_NameOfTurbine)[confData.field_wind_speed].mean().reset_index()  
        
        # 使用plotly绘制柱状图  
        fig = px.bar(average_wind_speed, x=Field_NameOfTurbine, y=confData.field_wind_speed, title='Turbine Average Wind Speed')  
        
        # 更新x轴和y轴的标签  
        fig.update_xaxes(title_text='Turbine Name', tickangle=-45)  
        fig.update_yaxes(title_text='Average Wind Speed (m/s)')  
        # 如果需要进一步调整标题样式或位置（尽管默认情况下标题是居中的）  
        # 可以使用 update_layout 来设置标题的 x 坐标（xanchor）为 'center' 来确保居中  
        fig.update_layout(title_x=0.5)  # 设置标题的x位置为图的中心  
        
        # 保存图像
        output_file = os.path.join(outputAnalysisDir, f"WindSpeedAvg_Turbines.png")
        fig.write_image(output_file)