#!/usr/bin/env python3

from datetime import timezone, datetime
from numberdealers import parse_numberdealers
import matplotlib.pyplot as plt
import numpy as np


def xy(messages):
	x = []
	y = []
	for msg in messages:
		# x.append(datetime.fromtimestamp(msg.create_at / 1000, timezone.utc))
		x.append(msg.create_at / 1000)
		y.append(msg.recognized_number)
	return x, y


def find(xs, condition):
	for i, x in enumerate(xs):
		if condition(x):
			return i


def abline(slope, intercept, point1_x, point2_x):
	"""Plot a line from slope and intercept"""
	axes = plt.gca()
	x_vals = np.array([point1_x, point2_x])
	y_vals = slope * x_vals + intercept
	plt.plot(x_vals, y_vals, linewidth=1, color='grey')


def main():
	import sys
	if len(sys.argv) <= 2:
		print("Usage: plot_numberdealers.py <numberdealers.json> <numberdealers-ng.json>")
		return 1
	with open(sys.argv[1], encoding="utf-8") as fh:
		numbers_og, _errors = parse_numberdealers.parse(fh)
	with open(sys.argv[2], encoding="utf-8") as fh:
		numbers_ng, _errors = parse_numberdealers.parse(fh)

	start_of_current_slope = find(numbers_og, lambda msg: msg.create_at >= numbers_ng[0].create_at)
	# a = (y2-y1) / (x2-x1)
	slope_og = (
		numbers_og[-1].recognized_number - numbers_og[start_of_current_slope].recognized_number
	) / (
		numbers_og[-1].create_at/1000 - numbers_og[start_of_current_slope].create_at/1000
	)
	# b = y - a x
	intercept_og = numbers_og[-1].recognized_number - slope_og * numbers_og[-1].create_at/1000

	slope_ng = (
		numbers_ng[-1].recognized_number - numbers_ng[0].recognized_number
	) / (
		numbers_ng[-1].create_at/1000 - numbers_ng[0].create_at/1000
	)
	intercept_ng = numbers_ng[-1].recognized_number - slope_ng * numbers_ng[-1].create_at/1000

	# a1 x + b1 = a2 x + b2
	# (a1 - a2) x = b2 - b1
	# x = (b2 - b1) / (a1 - a2)
	intercept_x = (intercept_ng - intercept_og) / (slope_og - slope_ng)
	intercept_y = slope_ng * intercept_x + intercept_ng

	fig, ax = plt.subplots(figsize=(15, 6))
	ax.plot(*xy(numbers_og))
	ax.plot(*xy(numbers_ng))
	abline(slope_og, intercept_og, numbers_og[-1].create_at/1000, intercept_x)
	abline(slope_ng, intercept_ng, numbers_ng[-1].create_at/1000, intercept_x)

	plt.margins(x=0)

	locs = np.append(
		np.linspace(numbers_og[0].create_at/1000, numbers_ng[0].create_at/1000, 6),
		[numbers_ng[-1].create_at/1000, intercept_x]
	)
	# func = lambda x: x < intercept_x
	# locs = np.append(locs[func(locs)][:-1], [intercept_x])
	labels = ["{:%Y-%m-%d}".format(datetime.fromtimestamp(x, timezone.utc)) for x in locs]
	plt.xticks(locs, labels)

	plt.grid()

	# plt.show()
	plt.savefig("plot.png")
	return 0


if __name__ == "__main__":
	import sys
	sys.exit(main())