WTOAAM/dataAnalysisBusiness/algorithm/pitchTSRCpAnalyst.py

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


class PitchTSRCpAnalyst(Analyst):

    def typeAnalyst(self):
        return "pitch_tsr_cp"

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

    def windRoseAnalysis(self, dataFrameMerge: pd.DataFrame, outputAnalysisDir, confData: ConfBusiness):
        """
        绘制3D曲面图。

        参数:
        df: pandas.DataFrame, 必须包含confData.field_pitch_angle1, Field_TSR, 和 Field_Cp这三个字段。

        返回:
        一个Plotly图形对象。
        """
        # 检查所需列是否存在
        required_columns = {confData.field_pitch_angle1, Field_TSR, Field_Cp}
        if not required_columns.issubset(dataFrameMerge.columns):
            raise ValueError(f"DataFrame缺少必要的列。需要的列有: {required_columns}")

        # 按设备名分组数据
        grouped = dataFrameMerge.groupby(Field_NameOfTurbine)

        for name, group in grouped:
            layout = go.Layout(
                title={
                    "text": f'3D scatter plot: Cp vs. Pitch Angle vs. TSR {name}',
                    "x": 0.5
                },
                scene=dict(
                    xaxis=dict(
                        title='Pitch Angle',
                        dtick=confData.graphSets["pitchAngle"]["step"] if not self.common.isNone(
                            confData.graphSets["pitchAngle"]["step"]) else 2,  # 设置y轴刻度间隔为0.1
                        range=[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],  # 设置y轴的范围从0到1
                    ),
                    yaxis=dict(
                        title='TSR',
                        dtick=confData.graphSets["tsr"]["step"] if not self.common.isNone(
                            confData.graphSets["tsr"]["step"]) else 5,  # 设置y轴刻度间隔为0.1
                        range=[confData.graphSets["tsr"]["min"] if not self.common.isNone(
                            confData.graphSets["tsr"]["min"]) else 0, confData.graphSets["tsr"]["max"] if not self.common.isNone(confData.graphSets["tsr"]["max"]) else 20],  # 设置y轴的范围从0到1
                    ),
                    zaxis=dict(
                        title='Cp',
                        dtick=confData.graphSets["cp"]["step"] if not self.common.isNone(
                            confData.graphSets["cp"]["step"]) else 0.5,  # 设置y轴刻度间隔为0.1
                        range=[confData.graphSets["cp"]["min"] if not self.common.isNone(
                            confData.graphSets["cp"]["min"]) else 0, confData.graphSets["cp"]["max"] if not self.common.isNone(confData.graphSets["cp"]["max"]) else 2],  # 设置y轴的范围从0到1
                    )
                ),
                margin=dict(t=50, b=10)  # t为顶部（top）间距，b为底部（bottom）间距
            )

            # 创建 3D 散点图
            fig = go.Figure(data=[go.Scatter3d(
                x=group[confData.field_pitch_angle1],
                y=group[Field_TSR],
                z=group[Field_Cp],
                mode='markers',  # 设置模式为 markers，表示绘制散点图
                marker=dict(
                    size=1,  # 设置散点的大小
                    # 你还可以设置其他属性，如颜色、透明度等
                    # color='blue',
                    # opacity=0.8
                )
            )], layout=layout)  # 假设 layout 已经定义好了

            # 保存html
            outputFileHtml = os.path.join(outputAnalysisDir, f"{name}.html")
            fig.write_html(outputFileHtml)
            # 保存图表为HTML文件
            # offline.plot(fig, filename=outputFileHtml, auto_open=False)
            # 保存图像
            # output_file = os.path.join(outputAnalysisDir, f"{name}.png")
            # fig.write_image(output_file)