# This source code is part of the Gecos package and is distributed
# under the 3-Clause BSD License. Please see 'LICENSE.rst' for further
# information.
__author__ = "Patrick Kunzmann"
__all__ = ["ColorSpace"]
from os.path import join, dirname, realpath
import itertools
import numpy as np
from .colors import lab_to_rgb
SPACE_FILE_NAME = join(dirname(realpath(__file__)), "space.npy")
[docs]class ColorSpace():
"""
Create a color space, that spans the complete *RGB* gamut of the *Lab*
color space.
The *Lab* components are discretized into integer values.
A color space describes the boundaries of the color scheme to be generated.
It uses the *Lab* color space.
In addition to the inherent limit to colors, that can also be displayed in
*RGB* space, further parts of the space can be removed by calling
:func:`remove()`.
Parameters
----------
file_name : str, optional
The path of a custom file to load the precalculated *RGB* convertible
space from.
Attributes
----------
shape : tuple of int
The shape of the space, i.e. the amount of *Lab* values in each
dimension.
lab : ndarray, shape=(100, 256, 256, 3), dtype=int
The complete discretized *Lab* color space in the *ab* range of
``-128`` to ``127``.
space : shape=(100, 256, 256), dtype=bool
The allowed part of the `lab` attribute, i.e. the part that is
convertible into *RGB* and was not manually removed.
"""
def __init__(self, file_name=None):
if file_name is None:
file_name = SPACE_FILE_NAME
l = np.arange(100)
a = b = np.arange(-128,128)
self._lab = np.zeros((100,256,256,3), dtype=int)
self._lab[:,:,:,0] = l[:, np.newaxis, np.newaxis]
self._lab[:,:,:,1] = a[np.newaxis, :, np.newaxis]
self._lab[:,:,:,2] = b[np.newaxis, np.newaxis, :]
with open(file_name, "rb") as file:
self._space = np.load(file)
[docs] def remove(self, mask):
"""
Remove a portion of the color space.
Parameters
----------
space : ndarray, shape=(100, 256, 256), dtype=bool
The space is removed where this mask is true.
Examples
--------
Remove space below a defined lightness:
>>> L_MIN = 50
>>> space = ColorSpace()
>>> lab = space.lab
>>> l = lab[..., 0]
>>> space.remove(l < L_MIN)
"""
self._space &= ~mask
[docs] def get_rgb_space(self):
"""
Convert the *Lab* colors of the space in *RGB* colors.
Returns
-------
rgb : ndarray, shape=(100,256,256,3), dtype=float
The *RGB* colors.
Colors that cannot be displayed in *RGB* or were manually
removed from the space are ``NaN``.
"""
rgb = lab_to_rgb(self._lab)
rgb[~self._space] = np.nan
return rgb
@property
def space(self):
return self._space.copy()
@property
def shape(self):
return (100, 256, 256)
@property
def lab(self):
return self._lab.copy()
@staticmethod
def _generate(file_name=None):
"""
Precalculate which part of the *Lab* space can be displayed in
*RGB* and save the result as boolean mask into a
*NumPy* ``.npy`` file.
"""
lab = np.zeros((100, 256, 256, 3), dtype=int)
lab[:,:,:,0] = np.arange(100 )[:, np.newaxis, np.newaxis]
lab[:,:,:,1] = np.arange(-128, 128)[np.newaxis, :, np.newaxis]
lab[:,:,:,2] = np.arange(-128, 128)[np.newaxis, np.newaxis, :]
rgb = lab_to_rgb(lab)
space = np.ones((100, 256, 256), dtype=bool)
space[np.isnan(rgb).any(axis=-1)] = False
if file_name is None:
file_name = SPACE_FILE_NAME
with open(file_name, "wb") as file:
np.save(file, space)
