import math

import matplotlib.pyplot as plot

from . import _dataset
from ._nomogram import calculate_swi as _calculate_swi
from ._nomogram import MAX_TEMPERATURE_DIFFERENCE, MAX_CONVECTIVE_CLOUD_DEPTH


def _grid(start, end, steps):
	step = (end - start) / steps
	i = start
	while i < end or math.isclose(i, end):
		yield i
		i += step


def _scaled_range(steps, maximum):
	step = maximum / steps
	for i in range(steps):
		yield i * step


def colorful(width=1000, height=1000):
	C = []
	X = list(_grid(0, MAX_TEMPERATURE_DIFFERENCE, width))
	Y = list(_grid(0, MAX_CONVECTIVE_CLOUD_DEPTH, height))
	for y in _scaled_range(height, MAX_CONVECTIVE_CLOUD_DEPTH):
		row = []
		for x in _scaled_range(width, MAX_TEMPERATURE_DIFFERENCE):
			row.append(_calculate_swi(x, y))
		C.append(row)
	plot.pcolormesh(X, Y, C, cmap='viridis', vmin=-10, vmax=10, rasterized=True)
	for _, data in _dataset.INDICES:
		plot.plot([x.x for x in data], [x.y for x in data])
	plot.show()


if __name__ == "__main__":
	colorful()