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update glasbey license
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‎LICENSE/LICENSE_GLASBEY

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MIT License
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Copyright (c) 2022 Leland McInnes and 2014 Sergey Alexandrov
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.

‎src/cmap/data/glasbey/__init__.py

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"""glasbey vendored from https://github.com/lmcinnes/glasbey.
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(Vendored to remove dependency on matplotlib and scikit-learn, and make numba optional.)
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MIT License
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Copyright (c) 2022 Leland McInnes and 2014 Sergey Alexandrov
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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"""

‎src/cmap/data/glasbey/_glasbey.py

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# glasbey vendored from https://github.com/lmcinnes/glasbey.
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# see __init__ and LICENSE_GLASBEY
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from __future__ import annotations
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from typing import Literal

‎src/cmap/data/glasbey/_grids.py

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# MIT License
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# Leland McInnes
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# glasbey vendored from https://github.com/lmcinnes/glasbey.
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# see __init__ and LICENSE_GLASBEY
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from __future__ import annotations
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from typing import Sized

‎src/cmap/data/glasbey/_internals.py

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# MIT License
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# Leland McInnes, Sergey Alexandrov
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# glasbey vendored from https://github.com/lmcinnes/glasbey.
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# see __init__ and LICENSE_GLASBEY
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import numpy as np
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# "numbafication" is done at the bottom of the module
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def get_next_color(distances, colors, new_color):
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argmax = -1
@@ -104,42 +104,6 @@ def generate_palette_cam02ucs_and_other(
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return result
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# def generate_next_color_cam02ucs(colors, current_distances, new_palette_block):
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# for i in range(new_palette_block.shape[0]):
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# _ = get_next_color(current_distances, colors, new_palette_block[i])
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# return get_next_color(current_distances, colors, new_palette_block[0])
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# def generate_next_color_cam02ucs_and_other(
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# colors1,
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# colors2,
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# current_distances,
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# new_palette_block1,
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# new_palette_block2,
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# alpha=0.0,
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# ):
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# for i in range(new_palette_block1.shape[0]):
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# _ = two_space_get_next_color(
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# current_distances,
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# colors1,
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# colors2,
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# new_palette_block1[i],
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# new_palette_block2[i],
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# alpha=alpha,
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# )
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# result, _ = two_space_get_next_color(
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# current_distances,
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# colors1,
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# colors2,
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# new_palette_block1[0],
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# new_palette_block2[0],
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# alpha=alpha,
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# )
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# return result
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try:
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import numba
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except ImportError:
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cache=True,
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)
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# get_next_color(distances, colors, new_color)
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get_next_color = jit1(get_next_color)
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jit2 = numba.njit(
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cache=True,
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)
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# generate_palette_cam02ucs(colors, initial_palette, size)
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generate_palette_cam02ucs = jit2(generate_palette_cam02ucs)
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# jit3 = numba.njit(
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# [
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# # 'f4[::1](f4[:,::1], f4[::1], f4[:,::1])',
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# numba.types.Array(numba.float32, 1, "C", readonly=True)(
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# numba.types.Array(numba.float32, 2, "C", readonly=True),
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# numba.types.Array(numba.float32, 1, "C"),
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# numba.types.Array(numba.float32, 2, "C", readonly=True),
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# )
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# ],
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# locals={
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# "i": numba.uint16,
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# },
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# cache=True,
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# )
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# generate_next_color_cam02ucs = jit3(generate_next_color_cam02ucs)
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jit4 = numba.njit(
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[
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"UniTuple(f4[::1], 2)(f4[::1], f4[:, ::1], f4[:, ::1], f4[::1], f4[::1], f4)",
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)
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generate_palette_cam02ucs_and_other = jit5(generate_palette_cam02ucs_and_other)
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# jit6 = numba.njit(
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# [
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# numba.types.Array(numba.float32, 1, "C", readonly=True)(
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# numba.types.Array(numba.float32, 2, "C", readonly=True),
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# numba.types.Array(numba.float32, 2, "C", readonly=True),
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# numba.types.Array(numba.float32, 1, "C"),
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# numba.types.Array(numba.float32, 2, "C", readonly=True),
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# numba.types.Array(numba.float32, 2, "C", readonly=True),
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# numba.float32,
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# )
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# ],
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# locals={
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# "i": numba.uint16,
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# },
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# cache=True,
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# )
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# generate_next_color_cam02ucs_and_other = jit6(
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# generate_next_color_cam02ucs_and_other
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# )

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