AirTerminalDevice/model/_base/_base_device.py

import numpy as np
import pandas as pd
import plotnine as gg

from ._base import BaseModel

class BaseDevice(BaseModel):
    
    def __init__(self) -> None:
        super().__init__()
    
    def curve(
        self,
        input_data: pd.DataFrame,
        x         : str,
        y         : str,
        color     : str = None,
        grid_x    : str = None,
        grid_y    : str = None,
    ):
        
        if x not in input_data.columns: 
            raise Exception(f'{x} is not in input_data')
        
        product = [np.linspace(input_data.loc[:,x].min(),input_data.loc[:,x].max(),100)]
        names   = [x]
        
        if color is not None:
            if color not in input_data.columns: 
                raise Exception(f'{color} is not in input_data')
            product.append(np.quantile(input_data.loc[:,color],q=[0.25,0.5,0.75]))
            names.append(color)
        if grid_x is not None:
            if grid_x not in input_data.columns: 
                raise Exception(f'{grid_x} is not in input_data')
            product.append(np.quantile(input_data.loc[:,grid_x],q=[0.25,0.5,0.75]))
            names.append(grid_x)
        if grid_y is not None:
            if grid_y not in input_data.columns: 
                raise Exception(f'{grid_y} is not in input_data')
            product.append(np.quantile(input_data.loc[:,grid_y],q=[0.25,0.5,0.75]))
            names.append(grid_y)
        
        curve_input = (
            pd.MultiIndex.from_product(
                product,
                names=names
            )
            .to_frame(index=False)
        )
        curve_input_all = curve_input.copy(deep=True)
        
        for col in input_data.columns:
            if col not in curve_input_all:
                curve_input_all.loc[:,col] = input_data.loc[:,col].median()
        pred_data  = self.predict_system(curve_input_all)
        if y not in pred_data.columns:
            raise Exception(f'{y} is not in Prediction')
        
        curve_data = pd.concat([curve_input,pred_data],axis=1)
        plot = (
            curve_data
            .round(2)
            .pipe(gg.ggplot)
            + gg.aes(x=x,y=y)
            + gg.geom_line()
        )
        if color is not None:
            plot += gg.aes(color=f'factor({color})',group=color)
            plot += gg.labs(color=color)
        
        if grid_x is not None or grid_y is not None:
            plot += gg.facet_grid(rows=grid_x,cols=grid_y,labeller='label_both')
        
        return plot