# -*- coding: utf-8 -*-

"""
This python module implements visualization techniques/modes

Copyright (C) 2018  SINTEF ICT

This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with this program.  If not, see <http://www.gnu.org/licenses/>.
"""

import numpy as np


def gen_schlieren(rho):
    # Compute length of z-component of normalized gradient vector
    normal = np.gradient(rho)  # [x, y, 1]
    length = 1.0 / np.sqrt(normal[0] ** 2 + normal[1] ** 2 + 1.0)
    schlieren = np.power(length, 128)
    return schlieren


def gen_vorticity(rho, rho_u, rho_v):
    u = rho_u / rho
    v = rho_v / rho
    u = np.sqrt(u ** 2 + v ** 2)
    u_max = u.max()

    du_dy, _ = np.gradient(u)
    _, dv_dx = np.gradient(v)

    # Length of curl
    curl = dv_dx - du_dy
    return curl


def gen_colors(rho, rho_u, rho_v, cmap, vmax, vmin):
    from matplotlib.colors import Normalize
    schlieren = gen_schlieren(rho)
    curl = gen_vorticity(rho, rho_u, rho_v)

    colors = Normalize(vmin, vmax, clip=True)(curl)
    colors = cmap(colors)
    for k in range(3):
        colors[:, :, k] = colors[:, :, k] * schlieren

    return colors