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add 1-dim probability map shader to chunkflow neuroglancer command #302

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merged 1 commit into from
Feb 24, 2024
Merged

add 1-dim probability map shader to chunkflow neuroglancer command #302

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55 changes: 43 additions & 12 deletions chunkflow/flow/neuroglancer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -278,14 +278,26 @@ def _append_segmentation_layer(self, viewer_state: ng.viewer_state.ViewerState,
)
)

def _append_probability_map_layer(self, viewer_state: ng.viewer_state.ViewerState, chunk_name: str, chunk: Chunk):
def _append_probability_map_layer(self,
viewer_state: ng.viewer_state.ViewerState,
chunk_name: str, chunk: Chunk, color=None):
if chunk.dtype == np.dtype('<f4') or chunk.dtype == np.dtype('float16'):
chunk = chunk.astype(np.float32)

voxel_size = self._get_voxel_size(chunk)
# chunk = np.ascontiguousarray(chunk)
if chunk.shape[0] == 1:
shader = """void main() {
if color is not None:
shader = """#uicontrol vec3 color color(default="%s")
#uicontrol float brightness slider(min=-1, max=1)
#uicontrol float contrast slider(min=-3, max=3, step=0.01)
void main() {
emitRGB(color *
(toNormalized(getDataValue(0)) + brightness) * exp(contrast));
}
""" % color
else:
shader = """void main() {
emitGrayscale(toNormalized(getDataValue(0)));
}
"""
Expand Down Expand Up @@ -324,6 +336,23 @@ def __call__(self, datas: dict, selected: str=None):
Parameters:
chunks: multiple chunks
"""
def parse_selected_args(varname: str) -> Tuple[str, dict]:
kws = {}
if '[' in varname:
if not varname.endswith(']'):
raise ValueError(f"Unmatched bracket in variable name: '{varname}'")
varname, opts = varname[:-1].split('[')
for arg in opts.split(','):
if '=' in arg:
k, v = arg.split('=')
kws[k] = v
else:
raise ValueError("Only keyword arguments are allowed in neuroglancer variable options")
elif ']' in varname:
raise ValueError(f"Unmatched bracket in variable name: '{varname}'")

return varname, kws

if selected is None:
selected = datas.keys()
elif isinstance(selected, str):
Expand All @@ -335,41 +364,43 @@ def __call__(self, datas: dict, selected: str=None):
viewer = ng.Viewer()
with viewer.txn() as viewer_state:
for name in selected:
name, layer_kwargs = parse_selected_args(name)
data = datas[name]
layer_args = (viewer_state, name, data)
# breakpoint()

if data is None:
continue
elif isinstance(data, PointCloud):
# points
self._append_point_annotation_layer(viewer_state, name, data)
self._append_point_annotation_layer(*layer_args, **layer_kwargs)
elif isinstance(data, Synapses):
# this could be synapses
self._append_synapse_annotation_layer(viewer_state, name, data)
self._append_synapse_annotation_layer(*layer_args, **layer_kwargs)
elif (isinstance(data, defaultdict) or isinstance(data, dict)) \
and len(data)>0:
self._append_skeleton_layer(viewer_state, name, data)
self._append_skeleton_layer(*layer_args, **layer_kwargs)
elif isinstance(data, np.ndarray) and 2 == data.ndim and 3 == data.shape[1]:
# points
self._append_point_annotation_layer(viewer_state, name, data)
self._append_point_annotation_layer(*layer_args, **layer_kwargs)
elif isinstance(data, Chunk):
if data.layer_type is None:
if data.is_image:
self._append_image_layer(viewer_state, name, data)
self._append_image_layer(*layer_args, **layer_kwargs)
elif data.is_segmentation:
self._append_segmentation_layer(viewer_state, name, data)
self._append_segmentation_layer(*layer_args, **layer_kwargs)
elif data.is_probability_map:
self._append_probability_map_layer(viewer_state, name, data)
self._append_probability_map_layer(*layer_args, **layer_kwargs)
elif data.is_affinity_map:
raise ValueError('affinity map is not working yet. To-Do.')
else:
raise ValueError('unsupported data type.')
if data.layer_type == 'segmentation':
self._append_segmentation_layer(viewer_state, name, data)
self._append_segmentation_layer(*layer_args, **layer_kwargs)
elif data.layer_type == 'probability_map':
self._append_probability_map_layer(viewer_state, name, data)
self._append_probability_map_layer(*layer_args, **layer_kwargs)
elif data.layer_type in set(['image', 'affinity_map']):
self._append_image_layer(viewer_state, name, data)
self._append_image_layer(*layer_args, **layer_kwargs)
else:
raise ValueError('only support image, affinity map, probability_map, and segmentation for now.')
else:
Expand Down
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