<gh_stars>1-10
import plotly
import plotly.offline as offline
import plotly.graph_objs as go
import json
import sys

def plot(inputs, output):
	# collect the plots, we don't really need the data
	ceresPlots = []
	fitPlots = []

	for l in range(0, len(inputs)):
		dataFile = open(inputs[l], 'r')
		data = json.load(dataFile)

		# set up relevant data arrays
		best = []
		avg = []
		fitBest = []
		fitAvg = []
		gen = []

		for x in range(0, len(data) - 1):
			# analyze objectives [0] (should usually always be the ceres data)
			ceresObj = []

			for i in range(0, len(data[x]["objectives"])):
				ceresObj.append(data[x]["objectives"][i][0])

			best.append(min(ceresObj))
			avg.append(sum(ceresObj) / len(ceresObj))
			fitBest.append(min(data[x]["fitness"]))
			fitAvg.append(sum(data[x]["fitness"]) / len(data[x]["fitness"]))
			gen.append(x)

		# construct plots
		bestGraph = go.Bar(x=gen, y=best, name='Best Ceres Score in Population (' + inputs[l] + ')')
		avgGraph = go.Bar(x=gen, y=avg, name='Average Population Score (' + inputs[l] + ')')

		ceresPlots.append(bestGraph)
		ceresPlots.append(avgGraph)

		fitBestGraph = go.Bar(x=gen, y=fitBest, name='Best Fitness Score in Population (' + inputs[l] + ')')
		fitAvgGraph = go.Bar(x=gen, y=fitAvg, name='Average Population Fitness (' + inputs[l] + ')')

		fitPlots.append(fitBestGraph)
		fitPlots.append(fitAvgGraph)

	print "output to " + output
	offline.plot(dict(data=ceresPlots, layout=dict(title="Ceres Objective Scores")), filename=output + "_ceres.html", auto_open=False)
	offline.plot(dict(data=fitPlots, layout=dict(title="Fitness Scores")), filename=output + "_fitness.html", auto_open=False)


if __name__ == "__main__":
	plot(sys.argv[1:(len(sys.argv) - 1)], sys.argv[len(sys.argv) - 1])