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Merge branch 'feature/v0.4.3' into develop
2 parents 1199e81 + f378ffa commit 6f1bf7c

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4 files changed

+5
-6
lines changed

4 files changed

+5
-6
lines changed

colour/io/luts/cinespace_csp.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -177,7 +177,7 @@ def _parse_table_section(lines):
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seek += 9
178178
size, table = _parse_table_section(lines[seek:])
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180-
attest(np.product(size) == len(table), '"LUT" table size is invalid!')
180+
attest(np.prod(size) == len(table), '"LUT" table size is invalid!')
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LUT: LUT3x1D | LUT3D | LUTSequence
183183
if (

colour/notation/munsell.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1756,7 +1756,7 @@ def xyY_from_renotation(specification: ArrayLike) -> NDArrayFloat:
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(_munsell_specifications() == specification).all(axis=-1)
17571757
)
17581758

1759-
return MUNSELL_COLOURS_ALL[int(index[0])][1]
1759+
return MUNSELL_COLOURS_ALL[as_int_scalar(index[0])][1]
17601760
except Exception as error:
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raise ValueError(
17621762
f'"{specification}" specification does not exists in '

colour/plotting/common.py

Lines changed: 2 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -64,6 +64,7 @@
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CanonicalMapping,
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Structure,
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as_float_array,
67+
as_int_scalar,
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attest,
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first_item,
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is_sibling,
@@ -1330,7 +1331,7 @@ def plot_multi_colour_swatches(
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13311332
offset_X += width + spacing
13321333

1333-
x_max = min(len(colour_swatches), int(columns))
1334+
x_max = min(len(colour_swatches), as_int_scalar(columns))
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x_max = x_max * width + x_max * spacing - spacing
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y_max = offset_Y
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colour/volume/rgb.py

Lines changed: 1 addition & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -310,9 +310,7 @@ def RGB_colourspace_volume_MonteCarlo(
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[arguments for _ in range(processes)],
311311
)
312312

313-
Lab_volume = np.product(
314-
[np.sum(np.abs(x)) for x in as_float_array(limits)]
315-
)
313+
Lab_volume = np.prod([np.sum(np.abs(x)) for x in as_float_array(limits)])
316314

317315
return Lab_volume * np.sum(results) / (process_samples * processes)
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