WTOAAM/dataAnalysisBusiness/algorithm/pitchGeneratorSpeedAnalyst.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 behavior.analyst import Analyst
from utils.directoryUtil import DirectoryUtil as dir
from algorithmContract.confBusiness import *


class PitchGeneratorSpeedAnalyst(Analyst):
    """
    风电机组变桨-发电机转速分析
    """

    def typeAnalyst(self):
        return "pitch_generator_speed"

    def turbinesAnalysis(self, dataFrameMerge, outputAnalysisDir, confData: ConfBusiness):
        self.plot_speed_pitch_angle(
            dataFrameMerge, outputAnalysisDir, confData, confData.field_pitch_angle1, confData.field_gen_speed)

    def plot_speed_pitch_angle(self, dataFrameMerge, outputAnalysisDir, confData: ConfBusiness, fieldPitchAngle, fieldGeneratorSpeed):
        x_name = 'generator_speed'
        y_name = 'pitch_angle'
        # 按设备名分组数据
        grouped = dataFrameMerge.groupby(Field_NameOfTurbine)
        sns.set_palette('deep')
        # 遍历每个设备并绘制散点图
        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；
            g = sns.lmplot(x=fieldGeneratorSpeed, y=fieldPitchAngle, data=groupNew,
                           fit_reg=False, scatter_kws={"s": 5, "color": "b"}, legend=False, height=6, aspect=1.2)
            # g = sns.lmplot(x=fieldGeneratorSpeed, y=fieldPitchAngle, data=group,
            #                fit_reg=False, scatter_kws={"s": 5}, legend=False, height=6, aspect=1.2)

            # 设置x轴和y轴的刻度
            for ax in g.axes.flat:
                ax.set_xlim(confData.graphSets["generatorSpeed"]["min"] if not self.common.isNone(
                    confData.graphSets["generatorSpeed"]["min"]) else 1000, confData.graphSets["generatorSpeed"]["max"] if not self.common.isNone(confData.graphSets["generatorSpeed"]["max"]) else 2000)
                # 设置x轴的刻度步长
                # 假设您想要每100个单位一个刻度
                loc = MultipleLocator(confData.graphSets["generatorSpeed"]["step"] if not self.common.isNone(
                    confData.graphSets["generatorSpeed"]) and not self.common.isNone(
                    confData.graphSets["generatorSpeed"]["step"]) else 200)
                ax.xaxis.set_major_locator(loc)  # 将定位器应用到x轴上

                ax.yaxis.set_major_locator(MultipleLocator(confData.graphSets["pitchAngle"]["step"] if not self.common.isNone(
                    confData.graphSets["pitchAngle"]["step"]) else 2))
                ax.set_ylim(confData.graphSets["pitchAngle"]["min"] if not self.common.isNone(
                    confData.graphSets["pitchAngle"]["min"]) else -2, confData.graphSets["pitchAngle"]["max"] if not self.common.isNone(confData.graphSets["pitchAngle"]["max"]) else 28)

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

            # 设置x轴刻度值旋转角度为45度
            plt.tick_params(axis='x', rotation=45)
            # 调整布局和设置标题
            plt.tight_layout()
            plt.title(f'{Field_NameOfTurbine}={name}')

            # 保存图像并关闭绘图窗口
            output_file = os.path.join(outputAnalysisDir, f"{name}.png")
            plt.savefig(output_file, bbox_inches='tight', dpi=120)
            plt.close()