WTOAAM/wtoaamapi/apps/business/algorithm/generatorSpeedTorqueAnalyst.py

import os
import pandas as pd
import numpy as np
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
from .analyst import Analyst
from .utils.directoryUtil import DirectoryUtil as dir
from confBusiness import Field_NameOfTurbine,Field_GeneratorTorque, ConfBusiness


class GeneratorSpeedTorqueAnalyst(Analyst):
    """
    风电机组发电机转速-转矩分析
    """

    def typeAnalyst(self):
        return "speed_torque"

    def turbinesAnalysis(self, dataFrameMerge, outputAnalysisDir, confData: ConfBusiness):
        self.create_and_save_plots(
            dataFrameMerge, outputAnalysisDir, confData, confData.field_gen_speed, confData.field_power)

    def create_and_save_plots(self, dataFrame: pd.DataFrame, outputAnalysisDir, confData: ConfBusiness, fieldGeneratorSpeed, field_Active_Power):
        x_name = 'generator_speed'
        y_name = 'generator_torque'

        grouped = dataFrame.groupby(Field_NameOfTurbine)
        for name, group in grouped:
            groupNew=group.copy()

            if not self.common.isNone(confData.value_gen_speed_multiple):
                groupNew[fieldGeneratorSpeed]=group[fieldGeneratorSpeed]*confData.value_gen_speed_multiple 
            # sns.lmplot函数参数scatter_kws： 设置为{"s": 5}时，会出现颜色丢失问题；改为={"s": 5, "color": "b"}后，则造成图形风格不统一问题；
            g = sns.lmplot(x=fieldGeneratorSpeed, y=Field_GeneratorTorque, data=groupNew, fit_reg=False, scatter_kws={
                           "s": 5, "color": "b"}, legend=False, height=6, aspect=1.2)
            # g = sns.lmplot(x=fieldGeneratorSpeed, y=Field_GeneratorTorque, data=group, fit_reg=False, scatter_kws={
            #                "s": 5}, legend=False, height=6, aspect=1.2)
            
            for ax in g.axes.flat:
                # ax.xaxis.set_major_locator(MultipleLocator(100))
                ax.set_xlim(confData.value_gen_speed_min,
                            confData.value_gen_speed_max)
                
                # 设置x轴的刻度步长  
                # 假设您想要每100个单位一个刻度  
                if not self.common.isNone(confData.value_gen_speed_step):
                    loc = MultipleLocator(confData.value_gen_speed_step) # 创建每100个单位一个刻度的定位器  
                    ax.xaxis.set_major_locator(loc) # 将定位器应用到x轴上 

                ax.set_xlabel(x_name)
                ax.set_ylabel(y_name)


            plt.tight_layout()
            plt.title(f'{Field_NameOfTurbine}={name}')
            # 保存图片到指定路径
            output_file = os.path.join(outputAnalysisDir, f"{name}.png")
            plt.savefig(output_file, bbox_inches='tight', dpi=120)
            plt.close()