# -*- coding: utf-8 -*-
"""
Created on Tue May 29 07:53:58 2018

@author: Noah Snider
"""
import pandas as pd
import matplotlib.pyplot as plt 
import numpy as np
import time
import os 
import datetime
import matplotlib.dates as mdates



###############################################################################
''' Saved Constants'''
###############################################################################

VRG1rate = 1.0115 #rate at which VRG1 samples in real time (minutes)
VRG2rate = 0.9873 #rate at which VRG2 sampels in real time (minutes)
#convert to ms in string form to be passed into datetime index
VRG1ms = str(int(VRG1rate*60*1000)) 
VRG2ms = str(int(VRG2rate*60*1000))
tenMinuteLocator = [x for x in range(60)]
thirtyMinuteLocator = [x*5 for x in range(12)]
hourLocator = [x*15 for x in range(4)]
#==============================================================================
# line 32 - added list of tuples to reformat column widths from txt file
#==============================================================================
colspecs = [(0,11),(12,19),(20,27),(28,35),(36,43),(44,50),(51,58)] #2/19/2019 

###############################################################################
''' Helper Functions for the code that parse filename, save data and plot'''
###############################################################################

#parses filename for start date/start time
def start_datetime(filename):
    dates = filename.split('_')[1]#starting date
    times = filename.split('_')[2].replace('.txt','')#starting time
    startdate = pd.to_datetime('-'.join([dates[-4:],dates[0:2],dates[2:4]])) + pd.to_timedelta(':'.join([times[:2],times[2:5],'00']))
    return startdate


#saves the names of the two .txt files from the working directory
def nameGrabber():
    file_names = []#empty list to store file names
    for names in os.listdir():
        #append file names from working directory
        if 'VRG' in names:
            file_names.append(names)
    return file_names
file_names = nameGrabber()#save globally

    
#collects data from VRG1/2, saves to dataframe
def data_collection(): 
    columns = ['Depth','Rate','Mass','Temp'] #names of columns
    #loop through file_names
    for name in file_names:
        #save VRG1 to dataframe
        if 'VRG1' in name:
#==============================================================================
#lines 64 - 65: added colspecs to the read_fwf call and adjusted which columns get picked 
#==============================================================================
            dataVRG1 = pd.read_fwf(name,header = None,colspecs=colspecs)
            dataVRG1 = dataVRG1[[1,2,4,5]]
            dataVRG1.columns = columns
            dataVRG1 = dataVRG1.set_index(pd.date_range(start_datetime(file_names[0]),freq = VRG1ms + 'L',periods = dataVRG1.shape[0]))
            #correct temp and convert to fahrenheit
            dataVRG1['Temp'] += 4
            #drop last line in case it was partially written
            dataVRG1 = dataVRG1.drop(dataVRG1.index[-1])
        #save VRG2 to dataframe    
        if 'VRG2' in name:
#==============================================================================
#lines 80-81: added colspecs to the read_fwf call and adjusted which columns get picked 
#==============================================================================
            dataVRG2 = pd.read_fwf(name,header = None,colspecs=colspecs)
            dataVRG2 = dataVRG2[[1,2,4,5]]
            dataVRG2.columns = columns
            dataVRG2 = dataVRG2.set_index(pd.date_range(start_datetime(file_names[1]),freq = VRG2ms + 'L',periods = dataVRG2.shape[0])) 
            dataVRG2['Temp'] -= 4
            #drop last line in case it was partially written
            dataVRG2 = dataVRG2.drop(dataVRG2.index[-1])
    #return dataframe
    return dataVRG1,dataVRG2
  

#plottedData(): returns the data of the current day within school hours
def plottedData(currentdate,dataVRG1,dataVRG2):
    #grab data from the current day
    plotVRG1 = dataVRG1.loc[dataVRG1.index.date == currentdate]
    plotVRG2 = dataVRG2.loc[dataVRG2.index.date == currentdate]
    #return
    return plotVRG1,plotVRG2


def plotter(currentdate,plotVRG1,plotVRG2):
    fig.suptitle('Data for ' + str(currentdate),size = 20)
    #ax1 axis
    ax1.plot(plotVRG1['Temp'],label = 'VRG1',color = 'blue',linewidth = .5)
    ax1.plot(plotVRG2['Temp'],label = 'VRG2',color = 'orange',linewidth = .5)
    ax1.set_ylabel('Temperature \n' + str(chr(176)) + 'C',fontsize = 10)
    ax1.yaxis.labelpad = 30
    ax1.legend()
    ax1.set_yticks([-20,-10,0,10])
    ax1.set_ylim(ymax = 10,ymin = -20)
    #ax2 axis
    ax2.plot(plotVRG1['DepthCorrected'],label = 'VRG1',color = 'blue',linewidth = .5)
    ax2.plot(plotVRG2['DepthCorrected'],label = 'VRG2',color = 'orange',linewidth = .5)
    ax2.set_ylabel('Accumulation of Liquid \nmm', fontsize = 10)
    ax2.yaxis.labelpad = 35
    ax2.set_yticks([0,10,20,30])
    ax2.set_ylim(ymax = 30,ymin = -10)
    #ax3 axis
    ax3.plot(plotVRG1['Rate'],label = 'VRG1',color = 'blue',linewidth = .5)
    ax3.plot(plotVRG2['Rate'],label = 'VRG2',color = 'orange',linewidth = .5)
    ax3.set_ylabel('Precipitation Rate \nmm/hr', fontsize = 10)
    ax3.yaxis.labelpad = 40
    ax3.set_yticks([0,3,6,9])
    ax3.set_ylim(ymax = 9,ymin = -3)
    #ax4 axis
    ax4.plot(plotVRG1['Mass'],label = 'VRG1',color = 'blue',linewidth = .5)
    ax4.plot(plotVRG2['Mass'],label = 'VRG2',color = 'orange',linewidth = .5)
    ax4.ticklabel_format(axis = 'y',useOffset = False)
    ax4.set_ylabel('Container Mass \ngram', fontsize = 10)
    ax4.yaxis.labelpad = 20
    ax4.set_yticks([11000,12000,13000])
    ax4.set_ylim(ymax = 13000,ymin = 10000)
    #clear xticks 
    ax1.set_xticks([])
    ax2.set_xticks([])
    ax3.set_xticks([])
    ax4.set_xticks([])
    if plotVRG1.shape[0] < 10:
        ax4.xaxis.set_major_locator(mdates.MinuteLocator(byminute = tenMinuteLocator, interval = 1))
        ax4.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M:%S'))
    if plotVRG1.shape[0] < 30:
        ax4.xaxis.set_major_locator(mdates.MinuteLocator(byminute = thirtyMinuteLocator, interval = 1))
        ax4.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M:%S'))
    if plotVRG1.shape[0] < 60: 
        ax4.xaxis.set_major_locator(mdates.MinuteLocator(byminute = hourLocator, interval = 1))
        ax4.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M:%S'))
    else:
        ax4.xaxis.set_major_locator(mdates.HourLocator(interval=1))
        ax4.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))

def main():
    while True: 
        try:
            #if size of text file gets above 5 Mb, break 
            size = os.stat(file_names[0]).st_mode
            if size > 5000000:
                break
            #else plot
            else:
                dataVRG1,dataVRG2 = data_collection() #save data globally
                currentdate = dataVRG1.index[-1].date()
                #find current day 
                plotVRG1,plotVRG2 = plottedData(currentdate,dataVRG1,dataVRG2) #only data during a school day
                #check if plotted data is empty 
                plotVRG1['DepthCorrected'] = plotVRG1['Depth'] - plotVRG1['Depth'][0]
                plotVRG2['DepthCorrected'] = plotVRG2['Depth'] - plotVRG2['Depth'][0]
                plotter(currentdate,plotVRG1,plotVRG2) #plot
                time.sleep(5) #
                plt.draw()
                plt.pause(.01)
                ax1.cla()
                ax2.cla()
                ax3.cla()
                ax4.cla()
        except pd.errors.EmptyDataError:
            text = plt.text(.5,2,'Waiting for data to write to disk...',color = 'red',
                     horizontalalignment = 'center',verticalalignment = 'center',
                     size = 20)
            plt.draw()
            plt.pause(.01)
            time.sleep(5)
            text.remove()
        except IndexError:
            print('IndexError at ' + str(datetime.datetime.now()))
            time.sleep(5)

            

#set up plotting environment
fig = plt.figure()
ax1 = fig.add_subplot(411)
ax2 = fig.add_subplot(412)
ax3 = fig.add_subplot(413)
ax4 = fig.add_subplot(414)


 

main()