Patch/use discrete colormap (#661)

* force discrete colormap when cmap does not have 256 values

* add more tests

CHANGES.md

@@ -1,4 +1,8 @@
 
+# 6.2.8 (2023-12-11)
+
+* apply `discrete` colormap when the provided colormap does not have 256 values
+
 # 6.2.7 (2023-11-29)
 
 * Adjusting dataset latitude for WarpedVRT parameters calculation when EPSG:4326 dataset latitudes overflows EPSG:3857 min/max latitude (https://github.com/cogeotiff/rio-tiler/pull/660)

rio_tiler/colormap.py

@@ -103,11 +103,11 @@ def apply_cmap(data: numpy.ndarray, colormap: ColorMapType) -> DataMaskType:
     if isinstance(colormap, Sequence):
         return apply_intervals_cmap(data, colormap)
 
-    # if colormap has more than 256 values OR its `max` key >= 256 we can't use
+    # if colormap has less or more than 256 values OR its `max` key >= 256 we can't use
     # rio_tiler.colormap.make_lut, because we don't want to create a `lookup table`
     # with more than 256 entries (256 x 4) array. In this case we use `apply_discrete_cmap`
     # which can work with arbitrary colormap dict.
-    if len(colormap) > 256 or max(colormap) >= 256 or min(colormap) < 0:
+    if len(colormap) != 256 or max(colormap) >= 256 or min(colormap) < 0:
         return apply_discrete_cmap(data, colormap)
 
     lookup_table = make_lut(colormap)

tests/test_cmap.py

@@ -151,6 +151,9 @@ def test_apply_discrete_cmap():
     mask[2:5, 2:5] = 255
     mask[5:, 5:] = 255
     numpy.testing.assert_array_equal(m, mask)
+    dd, mm = colormap.apply_cmap(data, cm)
+    numpy.testing.assert_array_equal(dd, d)
+    numpy.testing.assert_array_equal(mm, m)
 
     data = data.astype("uint16")
     d, m = colormap.apply_discrete_cmap(data, cm)
@@ -251,3 +254,31 @@ def test_parse_color_bad():
 
     with pytest.raises(InvalidColorFormat):
         colormap.parse_color([0, 0, 0, 0, 0])
+
+
+def test_discrete_float():
+    """test for titiler issue 738."""
+    cm = {
+        0: (0, 255, 255, 255),
+        1: (83, 151, 145, 255),
+        2: (87, 194, 23, 255),
+        3: (93, 69, 255, 255),
+        4: (98, 217, 137, 255),
+        5: (140, 255, 41, 255),
+        6: (150, 110, 255, 255),
+        7: (179, 207, 100, 255),
+        8: (214, 130, 156, 255),
+        9: (232, 170, 108, 255),
+        10: (255, 225, 128, 255),
+        11: (255, 184, 180, 255),
+        12: (255, 255, 140, 255),
+        13: (255, 180, 196, 255),
+        14: (255, 0, 0, 255),
+        15: (255, 218, 218, 255),
+    }
+
+    data = numpy.round(numpy.random.random_sample((1, 256, 256)) * 15)
+    d, m = colormap.apply_cmap(data.copy(), cm)
+    dd, mm = colormap.apply_discrete_cmap(data.copy(), cm)
+    assert d.dtype == numpy.uint8
+    assert m.dtype == numpy.uint8