Testing of the @doc-json output
tessera-viz: implement classification_to_rgba
Add color_of_hex for parsing hex color strings and classification_to_rgba
for mapping integer class predictions to colored RGBA pixels. Unknown
classes render as black. Add unit arg to resolve optional alpha parameter.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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tessera-viz/lib/viz.ml
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tessera-viz/lib/viz.ml
···
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done;
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{ data; width; height }
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let color_of_hex _s =
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failwith "TODO: color_of_hex"
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let color_of_hex s =
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let s = if String.length s > 0 && s.[0] = '#' then String.sub s 1 (String.length s - 1) else s in
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let r = int_of_string ("0x" ^ String.sub s 0 2) in
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let g = int_of_string ("0x" ^ String.sub s 2 2) in
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let b = int_of_string ("0x" ^ String.sub s 4 2) in
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{ r; g; b }
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let classification_to_rgba ?alpha:_ ~predictions:_ ~colors:_ ~width:_ ~height:_ =
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failwith "TODO: classification_to_rgba"
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let classification_to_rgba ?(alpha = 200) ~predictions ~colors ~width ~height () =
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let n_pixels = height * width in
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let data = Bigarray.Array1.create Bigarray.int8_unsigned Bigarray.c_layout (n_pixels * 4) in
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let color_tbl = Hashtbl.create (List.length colors) in
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List.iter (fun (id, c) -> Hashtbl.replace color_tbl id c) colors;
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let black = { r = 0; g = 0; b = 0 } in
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for i = 0 to n_pixels - 1 do
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let off = i * 4 in
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let c = try Hashtbl.find color_tbl predictions.(i) with Not_found -> black in
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Bigarray.Array1.set data off c.r;
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Bigarray.Array1.set data (off + 1) c.g;
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Bigarray.Array1.set data (off + 2) c.b;
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Bigarray.Array1.set data (off + 3) alpha
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done;
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{ data; width; height }
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tessera-viz/lib/viz.mli
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tessera-viz/lib/viz.mli
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tessera-viz/test/test_viz.ml
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tessera-viz/test/test_viz.ml
···
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; Alcotest.test_case "data length" `Quick test_pca_data_length
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]
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(* color_of_hex tests *)
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let test_hex_with_hash () =
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let c = Viz.color_of_hex "#ff0000" in
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Alcotest.(check int) "r" 255 c.r;
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Alcotest.(check int) "g" 0 c.g;
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Alcotest.(check int) "b" 0 c.b
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let test_hex_without_hash () =
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let c = Viz.color_of_hex "00ff00" in
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Alcotest.(check int) "r" 0 c.r;
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Alcotest.(check int) "g" 255 c.g;
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Alcotest.(check int) "b" 0 c.b
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let color_tests =
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[ Alcotest.test_case "with #" `Quick test_hex_with_hash
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; Alcotest.test_case "without #" `Quick test_hex_without_hash
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]
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(* classification_to_rgba tests *)
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let test_classification_basic () =
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(* 4 pixels, 2 classes *)
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let predictions = [| 0; 1; 0; 1 |] in
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let red : Viz.color = { r = 255; g = 0; b = 0 } in
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let blue : Viz.color = { r = 0; g = 0; b = 255 } in
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let colors = [ (0, red); (1, blue) ] in
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let img = Viz.classification_to_rgba ~predictions ~colors ~width:2 ~height:2 () in
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check_pixel "pixel 0 (class 0)" 255 0 0 200 img 0;
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check_pixel "pixel 1 (class 1)" 0 0 255 200 img 1;
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check_pixel "pixel 2 (class 0)" 255 0 0 200 img 2;
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check_pixel "pixel 3 (class 1)" 0 0 255 200 img 3
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let test_classification_unknown_class () =
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let predictions = [| 0; 99 |] in
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let red : Viz.color = { r = 255; g = 0; b = 0 } in
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let colors = [ (0, red) ] in
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let img = Viz.classification_to_rgba ~predictions ~colors ~width:2 ~height:1 () in
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check_pixel "known class" 255 0 0 200 img 0;
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check_pixel "unknown class -> black" 0 0 0 200 img 1
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let test_classification_custom_alpha () =
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let predictions = [| 0 |] in
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let red : Viz.color = { r = 255; g = 0; b = 0 } in
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let colors = [ (0, red) ] in
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let img = Viz.classification_to_rgba ~alpha:128 ~predictions ~colors ~width:1 ~height:1 () in
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check_pixel "custom alpha" 255 0 0 128 img 0
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let classification_tests =
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[ Alcotest.test_case "basic 2 classes" `Quick test_classification_basic
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; Alcotest.test_case "unknown class" `Quick test_classification_unknown_class
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; Alcotest.test_case "custom alpha" `Quick test_classification_custom_alpha
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]
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let () =
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Alcotest.run "tessera-viz"
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[ ("percentile", percentile_tests)
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; ("pca_to_rgba", pca_tests)
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; ("color_of_hex", color_tests)
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; ("classification_to_rgba", classification_tests)
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]