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Bugfix/TCL_true_color #161

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Oct 15, 2024
+21 −13
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Bugfix/TCL_true_color #161

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26 changes: 17 additions & 9 deletions lambdas/raster_tiler/lambda_function.py
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Original file line number Diff line number Diff line change
Expand Up @@ -99,20 +99,28 @@ def apply_annual_loss_filter(
year <= _end_year - 2000
)

red: ndarray = np.ones(intensity.shape).astype("uint8") * 228
# Construct RGBA bands with floating point values for precision
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Any chance you can describe in a comment the type of intensity.shape, and what the possible range of its values are? That would also make it clearer why float32 is the right choice for maintaining accuracy (and for instance, why you don't need to use float64).

red: np.ndarray = np.ones(intensity.shape).astype("float32") * 228
green: ndarray = (
np.ones(intensity.shape) * 102
np.ones(intensity.shape).astype("float32") * 102
+ (72 - zoom)
- (scaled_intensity * (3 / max(zoom, 1)))
).astype("uint8")
)
blue: ndarray = (
np.ones(intensity.shape) * 153 + (33 - zoom) - (intensity / max(zoom, 1))
).astype("uint8")
np.ones(intensity.shape).astype("float32") * 153
+ (33 - zoom)
- (intensity / max(zoom, 1))
)
alpha: ndarray = (
(scaled_intensity if zoom < 13 else intensity) * start_year_mask * end_year_mask
).astype("uint8")
).astype("float32")

return np.array([red, green, blue, alpha])
# Ensure GBA values are in [0, 255] range
green = np.clip(green, 0, 255).astype("uint8")
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Do you want to clip red to 255 as well? If not, can you put in a comment on why you don't need to clip it. (For instance, maybe intensity.shape is only a value between 0 and 1, so you know red is already between 0 and 228?)

blue = np.clip(blue, 0, 255).astype("uint8")
alpha = np.clip(alpha, 0, 255).astype("uint8")

return np.array([red.astype("uint8"), green, blue, alpha])


##############################
Expand Down Expand Up @@ -352,15 +360,15 @@ def read_tile_cache(dataset, version, implementation, x, y, z, **kwargs) -> ndar

arr = np.array(png)

return seperate_bands(arr)
return separat_bands(arr)


##########################
# Array functions
##########################


def seperate_bands(arr: ndarray) -> ndarray:
def separat_bands(arr: ndarray) -> ndarray:

logger.debug("Store bands in separate arrays")
# convert data from (height, width, bands) to (bands, height, width)
Expand Down
8 changes: 4 additions & 4 deletions tests/lambda/test_array_functions.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,22 +3,22 @@
from lambdas.raster_tiler.lambda_function import (
array_to_img,
combine_bands,
seperate_bands,
separat_bands,
)


def test_seperate_bands():
def test_separat_bands():
data = np.array([[[1, 2, 3]], [[1, 2, 3]], [[1, 2, 3]]])

flip = seperate_bands(data)
flip = separat_bands(data)
assert flip.shape == (3, 1, 3)
assert np.all(flip[0] == 1)
assert np.all(flip[1] == 2)
assert np.all(flip[2] == 3)

data = np.array([[[1, 2, 3, 4]], [[1, 2, 3, 4]], [[1, 2, 3, 4]]])

flip = seperate_bands(data)
flip = separat_bands(data)
assert flip.shape == (4, 1, 3)
assert np.all(flip[0] == 1)
assert np.all(flip[1] == 2)
Expand Down
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