More color table updates
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@ -73,4 +73,39 @@ for p in palettes:
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print(f"{prefix}->{len(all_colors)}")
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for c in all_colors:
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c.nn(all_colors)
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c.nn(all_colors)
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smallest_dist = 9999999999999
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largest_dist = 0
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for c in all_colors:
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dist = rgbdist(c, c.nearest_neighbor)
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if dist > largest_dist: largest_dist = dist
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if dist < smallest_dist: smallest_dist = dist
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#print(f"{c.prefix}:{c.name} -> {c.nearest_neighbor.prefix}:{c.nearest_neighbor.name}\t{rgbdist(c, c.nearest_neighbor):.2f}")
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# questions -
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# are there any colors where their nearest neighbor's nearest neighbor isn't them? (There should be)
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nonnear_pairs = 0
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for c in all_colors:
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neighbor = c.nearest_neighbor
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their_neighbor = neighbor.nearest_neighbor
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if c is not their_neighbor:
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#print(f"{c.prefix}:{c.name} -> {neighbor.prefix}:{neighbor.name} -> {their_neighbor.prefix}:{their_neighbor.name}")
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nonnear_pairs += 1
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print("Non-near pairs:", nonnear_pairs)
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#print(f"{c.prefix}:{c.name} -> {c.nearest_neighbor.prefix}:{c.nearest_neighbor.name}\t{rgbdist(c, c.nearest_neighbor):.2f}")
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# Are there duplicates? They should be removed from the palette that won't be used
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dupes = 0
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for c in all_colors:
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for c2 in all_colors:
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if c is c2: continue
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if c.r == c2.r and c.g == c2.g and c.b == c2.b:
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dupes += 1
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print("dupes:", dupes, "this many will need to be removed:", dupes / 2)
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# What order to put them in? Do we want large radiuses first, or some sort of "common color" table?
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# does manhattan distance change any answers over the 16.7M RGB values?
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# What's the worst case lookup? (Checking all 1200 colors to find the name?)
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