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# This file is part of MyPaint.
# Copyright (C) 2015 by Andrew Chadwick <a.t.chadwick@gmail.com>
#
# 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 2 of the License, or
# (at your option) any later version.
"""Display filter effects."""
## Imports
from __future__ import division, print_function
import numpy as np
## Constants
# sRGB coefficients: the usual sRGB / Rec. 709 ones
_LUMA_COEFFS = (0.2126, 0.7152, 0.0722)
# Conversion matrices for simulating common color vision deficiencies
#
# The coefficients come from Loren Petrich's work, formerly at
# http://homepage.mac.com/lpetrich/ColorBlindnessSim/ColorBlindnessSim.html
# and Max Novakovic's Javascript implementation, formerly at
# http://disturbmedia.com/max/colour-blindness.html
_SIM_DEUTERANOPIA_R_COEFFS = (0.43, 0.72, -0.15)
_SIM_DEUTERANOPIA_G_COEFFS = (0.34, 0.57, 0.09)
_SIM_DEUTERANOPIA_B_COEFFS = (-0.02, 0.03, 1)
_SIM_PROTANOPIA_R_COEFFS = (0.2, 0.99, -0.19)
_SIM_PROTANOPIA_G_COEFFS = (0.16, 0.79, 0.04)
_SIM_PROTANOPIA_B_COEFFS = (0.01, 0.01, 1)
_SIM_TRITANOPIA_R_COEFFS = (0.972, 0.112, -0.084)
_SIM_TRITANOPIA_G_COEFFS = (0.022, 0.818, 0.160)
_SIM_TRITANOPIA_B_COEFFS = (-0.063, 0.881, 0.182)
## Filter functions
def luma_only(dst):
"""Convert an NxNx3 array to show only luma (brightness)"""
luma = (dst[...,0:3] * _LUMA_COEFFS).sum(axis=2)
dst[..., 0:3] = luma[..., np.newaxis]
def invert_colors(dst):
"""Invert each RGB channel in an RGB array"""
dst[...,0:3] = 255 - dst[...,0:3]
def sim_deuteranopia(dst):
"""Simulate deuteranopia (insensitivity to red)"""
r = (dst[...,0:3] * _SIM_DEUTERANOPIA_R_COEFFS).sum(axis=2)
g = (dst[...,0:3] * _SIM_DEUTERANOPIA_G_COEFFS).sum(axis=2)
b = (dst[...,0:3] * _SIM_DEUTERANOPIA_B_COEFFS).sum(axis=2)
np.clip(r, 0, 255, dst[..., 0])
np.clip(g, 0, 255, dst[..., 1])
np.clip(b, 0, 255, dst[..., 2])
def sim_protanopia(dst):
"""Simulate protanopia (insensitivity to green)"""
r = (dst[...,0:3] * _SIM_PROTANOPIA_R_COEFFS).sum(axis=2)
g = (dst[...,0:3] * _SIM_PROTANOPIA_G_COEFFS).sum(axis=2)
b = (dst[...,0:3] * _SIM_PROTANOPIA_B_COEFFS).sum(axis=2)
np.clip(r, 0, 255, dst[..., 0])
np.clip(g, 0, 255, dst[..., 1])
np.clip(b, 0, 255, dst[..., 2])
def sim_tritanopia(dst):
"""Simulate tritanopia (insensitivity to green)"""
r = (dst[...,0:3] * _SIM_TRITANOPIA_R_COEFFS).sum(axis=2)
g = (dst[...,0:3] * _SIM_TRITANOPIA_G_COEFFS).sum(axis=2)
b = (dst[...,0:3] * _SIM_TRITANOPIA_B_COEFFS).sum(axis=2)
np.clip(r, 0, 255, dst[..., 0])
np.clip(g, 0, 255, dst[..., 1])
np.clip(b, 0, 255, dst[..., 2])
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