Add optional include_archived parameter to layer_names,

image_layers, segmentation_layers, and annotation_layers.
Fixes CAVEconnectome#46.

src/nglui/parser/base.py

@@ -10,68 +10,80 @@ def _is_spelunker_state(state):
     return "dimension" in state.keys()
 
 
-def layer_names(state):
+def layer_names(state, include_archived = True):
     """Get all layer names in the state
 
     Parameters
     ----------
     state : dict
         Neuroglancer state as a JSON dict
+    include_archived : bool
+        Whether to include archived layers
 
     Returns
     -------
     names : list
         List of layer names
     """
-    return [l["name"] for l in state["layers"]]
+    return [l["name"] for l in state["layers"] if \
+        (include_archived or l.get('archived', False) == False)]
 
 
-def image_layers(state):
+def image_layers(state, include_archived = True):
     """Get all image layer names in the state
 
     Parameters
     ----------
     state : dict
         Neuroglancer state as a JSON dict
+    include_archived : bool
+        Whether to include archived layers
 
     Returns
     -------
     names : list
         List of layer names
     """
-    return [l["name"] for l in state["layers"] if l["type"] == "image"]
+    return [l["name"] for l in state["layers"] if l["type"] == "image" \
+        and (include_archived or l.get('archived', False) == False)]
 
 
-def segmentation_layers(state):
+def segmentation_layers(state, include_archived = True):
     """Get all segmentation layer names in the state
 
     Parameters
     ----------
     state : dict
         Neuroglancer state as a JSON dict
+    include_archived : bool
+        Whether to include archived layers
 
     Returns
     -------
     names : list
         List of layer names
     """
-    return [l["name"] for l in state["layers"] if l["type"] in SEGMENTATION_LAYER_TYPES]
+    return [l["name"] for l in state["layers"] if l["type"] in SEGMENTATION_LAYER_TYPES \
+            and (include_archived or l.get('archived', False) == False)]
 
 
-def annotation_layers(state):
+def annotation_layers(state, include_archived = True):
     """Get all annotation layer names in the state
 
     Parameters
     ----------
     state : dict
         Neuroglancer state as a JSON dict
+    include_archived : bool
+        Whether to include archived layers
 
     Returns
     -------
     names : list
         List of layer names
     """
-    return [l["name"] for l in state["layers"] if l["type"] == "annotation"]
+    return [l["name"] for l in state["layers"] if l["type"] == "annotation" \
+            and (include_archived or l.get('archived', False) == False)]
 
 
 def tag_dictionary(state, layer_name):

tests/test_parser.py

@@ -6,16 +6,29 @@
 
 def test_layer_names(test_state):
     layer_names = parser.layer_names(test_state)
+    assert len(layer_names) == 6
+    for name in ['imagery-old1', 'imagery', 'imagery-old2', '72c5', 'segments', 'synapses']:
+        assert name in layer_names
+
+    layer_names = parser.layer_names(test_state, False)
     assert len(layer_names) == 3
-    assert "synapses" in layer_names
-
+    for name in ['imagery', 'segments', 'synapses']:
+        assert name in layer_names
 
 def test_layers(test_state):
     img_layer = parser.image_layers(test_state)
+    assert len(img_layer) == 3
+    assert img_layer == ["imagery-old1", "imagery", "imagery-old2"]
+
+    img_layer = parser.image_layers(test_state, False)
     assert len(img_layer) == 1
     assert img_layer[0] == "imagery"
 
     seg_layers = parser.segmentation_layers(test_state)
+    assert len(seg_layers) == 2
+    assert seg_layers == ["72c5", "segments"]
+
+    seg_layers = parser.segmentation_layers(test_state, False)
     assert len(seg_layers) == 1
     assert seg_layers[0] == "segments"
 

tests/testdata/test_state.json

@@ -1,12 +1,36 @@
 {
   "layers": [
+    {
+      "source": "precomputed://gs://neuroglancer/pinky100_v0/son_of_alignment_v13_rechunked",
+      "type": "image",
+      "blend": "default",
+      "shaderControls": {},
+      "name": "imagery-old1",
+      "archived": true
+    },
     {
       "source": "precomputed://gs://neuroglancer/pinky100_v0/son_of_alignment_v15_rechunked",
       "type": "image",
       "blend": "default",
       "shaderControls": {},
       "name": "imagery"
     },
+    {
+      "source": "precomputed://gs://neuroglancer/pinky100_v0/son_of_alignment_v14_rechunked",
+      "type": "image",
+      "blend": "default",
+      "shaderControls": {},
+      "name": "imagery-old2",
+      "archived": true
+    },
+    {
+      "type": "segmentation",
+      "source": "precomputed://gs://microns_public_datasets/pinky100_v184/seg",
+      "tab": "source",
+      "segments": [],
+      "name": "72c5",
+      "archived": true
+    },
     {
       "source": "precomputed://gs://microns_public_datasets/pinky100_v185/seg",
       "type": "segmentation",