# -*- coding: utf-8 -*-
"""
Created on Thursday, 24.05.2018 during COSPAR workshop
Lecture 6.1/9 
Generates plot of a 'Seiji' text file with several mixed columns (Text and floating point numbers)
Further analysis and plots need to be added....

@author: Chr. Monstein

"""
#--------------------------------------------------------------------------------

from matplotlib import pyplot as plt
import numpy as np
import os
#from Tkinter import Tk # Python 2.7
from tkinter import Tk
#from tkFileDialog import askopenfilename
from tkinter import filedialog

#--------------------------------------------------------------------------------

Tk().withdraw() # 

#myfile = askopenfilename(title = 'Select a *.txt-file containing Time-/Frequency coordinates of type II burst') # show an "Open" dialog box and returns path&file # Python2.7
myfile = filedialog.askopenfilename(title = 'Select a *.txt-file containing Time-/Frequency coordinates of type II burst') # show an "Open" dialog box and return file

#myfile = 'ft2.txt' # for testing only to avoid too many clicks...
fnam = os.path.basename(myfile) # extract filename only in case it contains also the path

"""
#Date      Time         Height  PA      Xpix  Ypix     X"          Y"
2013-10-05T073520.571    5.09   97.45   212   262   -4883.20    -638.40
2013-10-05T074547.663    6.17   99.39   203   259   -5891.20    -974.40
etc. or
#TIME                  Frequency
2014-01-26T08:41:44,  16.242
2014-01-26T08:42:44,  14.140
etc...
"""

MyTime = [] # reserve a list for time
Height = [] # reserve a list for Height

import csv
with open(myfile, 'r') as file:
    reader = csv.reader(file, delimiter=' ')
    next(reader, None)  # skip the headers
    for row0 in reader:
        print (row0)
        row = [x for x in row0 if x]
        dt = row[0]
        y = float(row[1])
        yy = dt[ 0: 4] # extract year
        MM = dt[ 5: 7] # extract month
        dd = dt[ 8:10] # extract day
        hh = dt[11:13] # get hours
        mm = dt[14:16] # get minutes
        ss = dt[17:19] # get seconds
        tx0 = float(hh) + float(mm)/60.0 + float(ss)/3600.0 # create decimal hour
        MyTime.append(tx0) # x-axis
        Height.append(y) # y-axis (Height or Frequency)


#--------------------------------------------------------------------------------

tmin = np.min(MyTime)
tx = (MyTime - tmin) # convert absolute into relative time

fit=np.polyfit(tx,Height,1)
speed=fit[0]*6.96e5/3600

tx2 = np.linspace(min(tx), max(tx), 100)
height2 = np.poly1d(fit)(tx2)

plt.figure(figsize=(10,7))
plt.plot(tx,Height,'o',color='red') #o,+,
plt.plot(tx2,height2,color='red')
plt.title(fnam,fontsize=16)
plt.xlabel("Relative time [hour]",size=18)
plt.ylabel("Height [Rs]",size=18)
plt.title(yy + '-' + MM + '-' + dd, size=18)
plt.grid(True) # an option
plt.tick_params(labelsize=20)
#plt.yscale('log') # this is an option to checkout
st='Speed={:5.1f} km/s'.format(speed)
plt.text(0.0,0.9*np.max(Height),st,color='blue',size=20)
plt.show()

plt.savefig('HeightTime_' + fnam + '.png')