# -*- coding: utf-8 -*-
"""
Created on Mon Oct 17 13:45:38 2022

@author: Daniel Häfliger
"""

import pandas as pd
import math
import requests, json
from datetime import datetime, date, time

# Convert a date and time to to complex numbers 
# [year_real, year_imag, day_real, day_imag]
def Convert_Date(atime):
    
    y_r = math.sin(atime.timetuple().tm_yday/365*2*math.pi)
    y_i = math.cos(atime.timetuple().tm_yday/365*2*math.pi)
    d_r = math.sin((atime.hour*3600+atime.minute*60+atime.second)/((24*3600))*2*math.pi)
    d_i = math.cos((atime.hour*3600+atime.minute*60+atime.second)/((24*3600))*2*math.pi)
    return [y_r, y_i, d_r, d_i] 


# Return a list of datas of a specified measurement of an influxDB
def Get_Value(client, bucket, atime, measurement, datapoint):
    
    query_api = client.query_api()
    query = 'from(bucket:"'+bucket+'")\
    |> range(start: -'+atime+')\
    |> filter(fn:(r) => r._field == "'+datapoint+'" )\
    |> filter(fn:(r) => r._measurement == "'+measurement+'" )'
    result = query_api.query(org=client.org, query=query)
    thelist = []
    for table in result:
        for record in table.records:
            thelist.append((record.get_value()))
    return thelist


# Return the time of datas of a specified measurement of an influxDB
def Get_Time(client, bucket, atime, measurement, datapoint):
    
    query_api = client.query_api()
    query = 'from(bucket:"'+bucket+'")\
    |> range(start: -'+atime+')\
    |> filter(fn:(r) => r._field == "'+datapoint+'" )\
    |> filter(fn:(r) => r._measurement == "'+measurement+'" )'
    result = query_api.query(org=client.org, query=query)
    thelist = []
    for table in result:
        for record in table.records:
            thelist.append((record.get_time()))
            
            
    a=[]
    b=[]
    c=[]
    d=[]
    
    for i in thelist:
        x = Convert_Date(i)
        a.append(x[0])
        b.append(x[1])
        c.append(x[2])
        d.append(x[3])        
            
            
            
    return [a,b,c,d,thelist]




# Need duration in hours, interval in minutes
# Retruns array with complex time, timestamp and prediction
# Works only for max 3 days due api returns only values until then
def GetPrediction(duration, intervall, datapoint): 
    
    xfile = pd.read_xml('config.xml')

    apikey = (xfile.loc[xfile['category'] == 'influx'].weatherapitoken[0])
    place = (xfile.loc[xfile['category'] == 'influx'].place[0])
    dats = requests.get("https://api.weatherapi.com/v1/forecast.json?key="+apikey+"&q="+place+"&days=3&aqi=yes&alerts=no")
    dats=json.loads(dats.content)

    a=[]
    b=[]
    c=[]
    d=[]
    e=[]
    f=[]
    now = datetime.now()
    daycounter = 0
    lasthour=now.hour
    for i in range(0, int(duration*60/intervall)):  

      now = datetime.timestamp(now)+(intervall*60)
      now = datetime.fromtimestamp(now)

      x = Convert_Date(now)
      a.append(x[0])
      b.append(x[1])
      c.append(x[2])
      d.append(x[3])        
      e.append(now)
      bc = dats["forecast"]["forecastday"][daycounter]["hour"][now.hour][datapoint]
      
      f.append(bc)
      if lasthour>now.hour:
          daycounter+=1
      
      lasthour=now.hour
      
    return[a,b,c,d,e,f]