#!/usr/bin/python3
"""
Python Script to plot values obtained by the rmit.py script
Runs a R.I.P.L.

./plot.py
-t trials
-o option:values
"""

import argparse
import itertools
import json
import math
import numpy
import re
import statistics
import sys

import matplotlib.pyplot as plt
from matplotlib.ticker import EngFormatter

class Field:
	def __init__(self, unit, _min):
		self.unit = unit
		self.min  = _min

field_names = {
	"ns per ops"           : Field('ns'    , 0),
	"Number of processors" : Field(''      , 1),
	"Ops per procs"        : Field('Ops'   , 0),
	"Ops per threads"      : Field('Ops'   , 0),
	"ns per ops/procs"     : Field('ns'    , 0),
	"Number of threads"    : Field('thrd'  , 1),
	"Total Operations(ops)": Field('Ops'   , 0),
	"Ops/sec/procs"        : Field('Ops'   , 0),
	"Total blocks"         : Field('Blocks', 0),
	"Ops per second"       : Field('Ops'   , 0),
	"Cycle size (# thrds)" : Field('thrd'  , 1),
	"Duration (ms)"        : Field('ms'    , 0),
}

def plot(in_data, x, y, out):
	fig, ax = plt.subplots()
	colors = itertools.cycle(['#0095e3','#006cb4','#69df00','#0aa000','#fb0300','#e30002','#fd8f00','#ff7f00','#8f00d6','#4b009a','#ffff00','#b13f00'])
	series = {} # scatter data for each individual data point
	groups = {} # data points for x value
	for entry in in_data:
		name = entry[0]
		if not name in series:
			series[name] = {'x':[], 'y':[]}

		if not name in groups:
			groups[name] = {}

		if x in entry[2] and y in entry[2]:
			xval = entry[2][x]
			yval = entry[2][y]
			series[name]['x'].append(xval)
			series[name]['y'].append(yval)

			if not xval in groups[name]:
				groups[name][xval] = []

			groups[name][xval].append(yval)

	lines = {} # lines from groups with min, max, median, etc.
	for name, data in groups.items():
		if not name in lines:
			lines[name] = { 'x': [], 'min':[], 'max':[], 'med':[], 'avg':[] }

		for xkey in sorted(data):
			ys = data[xkey]
			lines[name]['x']  .append(xkey)
			lines[name]['min'].append(min(ys))
			lines[name]['max'].append(max(ys))
			lines[name]['med'].append(statistics.median(ys))
			lines[name]['avg'].append(statistics.mean(ys))

	for name, data in series.items():
		_col = next(colors)
		plt.scatter(data['x'], data['y'], color=_col, label=name, marker='x')
		plt.plot(lines[name]['x'], lines[name]['min'], '--', color=_col)
		plt.plot(lines[name]['x'], lines[name]['max'], '--', color=_col)
		plt.plot(lines[name]['x'], lines[name]['med'], '-', color=_col)

	mx = max([max(s['x']) for s in series.values()])
	my = max([max(s['y']) for s in series.values()])

	plt.ylabel(y)
	plt.xlim(field_names[x].min, mx + 0.25)
	plt.xticks(range(1, math.ceil(mx) + 1))
	plt.xlabel(x)
	plt.ylim(field_names[y].min, my*1.2)
	plt.grid(b = True)
	ax.xaxis.set_major_formatter( EngFormatter(unit=field_names[x].unit) )
	ax.yaxis.set_major_formatter( EngFormatter(unit=field_names[y].unit) )
	plt.legend(loc='upper left')
	if out:
		plt.savefig(out)
	else:
		plt.show()


if __name__ == "__main__":
	# ================================================================================
	# parse command line arguments
	parser = parser = argparse.ArgumentParser(description='Python Script to draw R.M.I.T. results')
	parser.add_argument('-f', '--file', nargs='?', type=argparse.FileType('r'), default=sys.stdin)
	parser.add_argument('-o', '--out', nargs='?', type=str, default=None)
	parser.add_argument('-y', nargs='?', type=str, default="")

	try:
		options =  parser.parse_args()
	except:
		print('ERROR: invalid arguments', file=sys.stderr)
		parser.print_help(sys.stderr)
		sys.exit(1)

	# ================================================================================
	# load data
	try :
		data = json.load(options.file)
	except :
		print('ERROR: could not read input', file=sys.stderr)
		parser.print_help(sys.stderr)
		sys.exit(1)

	# ================================================================================
	# identify the keys

	series = set()
	fields = set()

	for entry in data:
		series.add(entry[0])
		for label in entry[2].keys():
			fields.add(label)

	if not options.out :
		print(series)
		print("fields")
		for f in fields:
			print("{}".format(f))

	if options.y and options.y in field_names.keys():
		plot(data, "Number of processors", options.y, options.out)
	else:
		if options.y:
			print("Could not find key '{}', defaulting to 'ns per ops'".format(options.y))
		plot(data, "Number of processors", "ns per ops", options.out)