# -*- coding: utf-8 -*-
"""
Created on Fri Dec  2 07:46:09 2022

@author: Daniel Häfliger
"""
import pandas as pd
import Influxclient as I
import influxdb_client


# Returns values of an influxDB as they where specified in the config.xml 
# as a Pandas Dataframe
def Get_Df():


    xfile = pd.read_xml('config.xml')
    org = (xfile.loc[xfile['category'] == 'influx'].organisation[0])
    token = (xfile.loc[xfile['category'] == 'influx'].influxtoken[0])
    url = (xfile.loc[xfile['category'] == 'influx'].url[0])

    client = influxdb_client.InfluxDBClient(
        url=url,
        token=token,
        org=org
    )

    bucket = (xfile.loc[xfile['category'] == 'influx'].bucket[0])
    measurement = (xfile.loc[xfile['category'] == 'influx'].measurement[0])

    interval = (xfile.loc[xfile['category'] == 'influx'].interval[0])
    valuessince = (xfile.loc[xfile['category'] == 'influx'].time[0])

    Input = xfile.loc[xfile['category'] == 'feature'].f[1]
    #numberofFeature=(xfile.loc[xfile['category']=='feature'].features[1])

    feature = Input.split()
    pred = xfile.loc[xfile['category'] == 'pred'].p1[2]
   

    data = {

        "y_r": I.Get_Time(client, bucket, valuessince, measurement, feature[0])[0],
        "y_i": I.Get_Time(client, bucket, valuessince, measurement, feature[0])[1],
        "d_r": I.Get_Time(client, bucket, valuessince, measurement, feature[0])[2],
        "d_i": I.Get_Time(client, bucket, valuessince, measurement, feature[0])[3],

    }

    for i in range(len(feature)):
        newd = {(feature[i]): I.Get_Value(client, bucket,
                                          valuessince, measurement, feature[i])}
        data.update(newd)

    newd = {(pred): I.Get_Value(client, bucket,
                                      valuessince, measurement, pred)}
    data.update(newd)
        
    return pd.DataFrame(data)



# Shifts the target variable and adds [shift_number] colums with the shiftet
# values, then return the new Dataframe
def ShiftTarget(df, shift_number, targetvariable):
    dfziel = df[[targetvariable]].copy()
    df = df.rename(columns={targetvariable:(targetvariable+str(0))})
    dfziel = dfziel.rename(columns={targetvariable:(targetvariable+str(0))})

    
    
    for i in range(shift_number):
        dfziel = dfziel.rename(columns={(targetvariable+str(i)):targetvariable+str(i+1)})
        dfziel = dfziel.shift(1)
        df = pd.concat([df, dfziel], axis=1)
 
    return df