# -*- coding: utf-8 -*-
"""
Created on Tue Mar 24 19:02:20 2020

@author: z5025317
"""

#creates a tide boundary time series in RMA format based on MHL tide data as provided for the RAP

#==========================================================#
#Load packages
#==========================================================#
import numpy as np
import os
import pandas as pd
import glob

os.chdir('C:/Users/z5025317/UNSW/Danial Khojasteh - HEMIP/RMA_result_explorer_code')
year = '2015'

Ocean_gauges_folder = 'J:/Project/wrl2018064 Fisheries RAP/04_Working/05_Modelling/RMA/HEMIP/Global_HEMIP_Data/MHL_Gauge_Data/20200409_Recieved/Open_ocean/'
filenames = glob.glob(Ocean_gauges_folder + '*.csv')
filenames = [filenames[0],filenames[1], filenames[3]]

timestep = 0
for tgr_csv_name in filenames:
    print (tgr_csv_name)
    tgr_csv_name = filenames[2]
    tgr_outname =  Ocean_gauges_folder + os.path.basename(tgr_csv_name)[:-4] + '_2' + year
    
    Full_df = pd.read_csv(tgr_csv_name ,header= 0, skiprows= 30, parse_dates = True) 
    Full_df.index = pd.to_datetime(Full_df.Date, format = '%d/%m/%Y') + pd.to_timedelta(Full_df.Time, unit='h') 
    Full_df = Full_df.iloc[:,[-2]]  
    Full_df.columns = ['WL[AHD]'] 
    Full_df = Full_df.loc[(Full_df.index >= year + '-01-01 00:00:00') & (Full_df.index <= str(np.int(year)+1) + '-01-01 00:00:00')]
    # str(df['2'][1500].astype(int))  
      
    # RMA2: create input file
    fq = open(
        os.path.join(Ocean_gauges_folder, tgr_outname + '.tgr'),
        'w')
    
    fq.write('TT      MHL tide for ' + os.path.basename(tgr_csv_name)+ ' ' + year +  '\n')    
    fq.write('{:<5}{:>3}{:>8}{:>8}\n'.format('CL', '', '2', year))
    #fq.write('{:<5}{:>3}{:>8}{:>8}\n'.format('CL', '', int(df['3'][0]), int(df['4'][0])))
    for i in range(1,len(Full_df),1):
    # For each new element
        fq.write('{:<5}{:>3}{:>8}{:>8}\n'.format('HD', str(np.int(Full_df.index[i-1].strftime('%j'))), str(np.round((np.float(Full_df.index[i-1].strftime('%M'))+ np.float(Full_df.index[i-1].strftime('%H'))*60) /60,2)), str(np.round(np.float(Full_df['WL[AHD]'][i-1]),3))))
    fq.write('ENDDATA')
    fq.close()