import seabreeze.spectrometers as sb
import datetime
import matplotlib.pyplot as plt
import numpy as np
import time
import thread
import json
import sys

startTime=datetime.datetime.now()

## Generating the filename
TIMESTAMP=startTime.strftime('%Y-%m-%d_%H%M%S')
FILENAME="spectro_"+TIMESTAMP+".json"

## Constant for total running time
RUNNINGTIME=datetime.timedelta(seconds=30)

## List for exporting to JSON
measurements=[];

print "Program started at"+str(startTime)

## Function responsible for exporting data to a JSON file
def exportData():
    while True:
        measurements.append(filteredData)
        with open(FILENAME, 'w') as outfile:
            json.dump(measurements, outfile)
        print "Exported JSON at: "+str(datetime.datetime.now())
        time.sleep(30)

## List of connected spectrometers
devices = sb.list_devices()
spec = sb.Spectrometer(devices[0])
spec.integration_time_micros(12000)
print "Connected device: "+str(spec)

## First reading and combination to a single list
x = np.array(spec.wavelengths())
y = np.array(spec.intensities())
data = zip(x,y)

## Filtering to get PAR with a margin of 50 nanometers
filteredData = [s for s in data if s[0]>=350 and s[0]<=750]

## Making a plot
plt.ion()
fig = plt.figure()
ax = fig.add_subplot(111)
line1, = ax.plot([i[0] for i in filteredData], [i[1] for i in filteredData], 'r-') # Returns a tuple of line objects, thus the comma
plt.ylim([80,4000])

## Creating a thread managing periodical data export
thread.start_new_thread(exportData, ())

## A loop making readings and updating the plot in real time
while datetime.datetime.now()<startTime+RUNNINGTIME:
    x = np.array(spec.wavelengths())
    y = np.array(spec.intensities())

    data = zip(x,y)

    filteredData = [s for s in data if s[0]>=350 and s[0]<=750]

    line1. set_xdata([i[0] for i in filteredData])
    line1.set_ydata([i[1] for i in filteredData])
    fig.canvas.draw()

print "Program finished at "+str(datetime.datetime.now())