feat: more examples and updates

examples/allen_zarr_volume.py

@@ -47,6 +47,8 @@ def make_cordinate_space(state):
         scales=[748, 748, 1, 1],
     )
     state.dimensions = co_ords
+    state.enable_adaptive_downsampling = False
+    state.wireFrame = True
 
 
 if __name__ == "__main__":

examples/logo.py

@@ -0,0 +1,37 @@
+import neuroglancer
+
+from neuroglancer_utils.create_datasets.create_mc_logo import create_mc_logo
+from neuroglancer_utils.viewer_utils import (
+    launch_nglancer,
+    open_browser,
+)
+
+from time import sleep
+
+
+def add_image_layer(state):
+    data = create_mc_logo()
+    dimensions = neuroglancer.CoordinateSpace(
+        names=["x", "y", "z"], units="nm", scales=[1, 1, 1]
+    )
+    local_volume = neuroglancer.LocalVolume(data, dimensions)
+    state.layers["image"] = neuroglancer.ImageLayer(
+        source=local_volume,
+        volume_rendering=True,
+        shader="""
+#uicontrol invlerp normalized
+void main() {
+    emitRGBA(vec4(0.0, 0.0, normalized(), normalized()));
+    }
+""",
+    )
+    state.show_axis_lines = False
+
+
+if __name__ == "__main__":
+    viewer = launch_nglancer()
+    open_browser(viewer, hang=False)
+    sleep(2)
+
+    with viewer.txn() as s:
+        add_image_layer(s)

examples/single_data_point_transfer_function.py

@@ -26,7 +26,7 @@ def colormap_version(viewer):
         },
         "colormap": {
             "controlPoints": [[0, "#000000", 0.0], [84, "#ffffff", 1.0]],
-            "window": [0, 100],
+            "window": [0, 50],
             "channel": [],
             "defaultColor": "#ff00ff",
         },
@@ -41,7 +41,7 @@ def colormap_version(viewer):
             layer=neuroglancer.ImageLayer(
                 source=neuroglancer.LocalVolume(
                     dimensions=s.dimensions,
-                    data=np.full(shape=(1, 1), dtype=np.uint32, fill_value=42),
+                    data=np.full(shape=(1, 1), dtype=np.uint64, fill_value=63),
                 ),
                 panels=[add_render_panel()],
             ),

examples/small_minimal.py

@@ -0,0 +1,39 @@
+import neuroglancer
+import numpy as np
+
+from neuroglancer_utils.viewer_utils import (
+    launch_nglancer,
+    open_browser,
+)
+
+from time import sleep
+
+
+def add_image_layer(state):
+    data = np.full(shape=(10,) * 3, fill_value=255, dtype=np.uint8)
+    dimensions = neuroglancer.CoordinateSpace(
+        names=["x", "y", "z"], units="nm", scales=[1, 1, 1]
+    )
+    local_volume = neuroglancer.LocalVolume(data, dimensions)
+    state.layers["image"] = neuroglancer.ImageLayer(
+        source=local_volume,
+        volume_rendering=True,
+        shader="""
+void main() {
+    emitRGBA(vec4(1.0, 1.0, 1.0, 0.001));
+    }
+    """,
+    )
+    state.show_axis_lines = False
+    state.projection_scale = 1e-8
+    state.position = [5, 5, 5]
+    state.layout = "3d"
+
+
+if __name__ == "__main__":
+    viewer = launch_nglancer()
+    open_browser(viewer, hang=False)
+    sleep(2)
+
+    with viewer.txn() as s:
+        add_image_layer(s)

examples/sphere.py

@@ -15,7 +15,7 @@
 from time import sleep
 
 import neuroglancer
-from neuroglancer_utils.create_datasets.create_sphere import create_sphere
+from neuroglancer_utils.create_datasets.create_sphere import create_sphere_in_cube
 from neuroglancer_utils.local_server import create_server
 
 from neuroglancer_utils.layer_utils import add_render_panel
@@ -29,9 +29,19 @@
     update_title,
 )
 
-def add_image_layer(state, **kwargs):
+
+def add_image_layer(state, data, **kwargs):
+    dimensions = neuroglancer.CoordinateSpace(
+        names=["x", "y", "z"], units="nm", scales=[40, 40, 40]
+    )
+    local_volume = neuroglancer.LocalVolume(
+        data,
+        dimensions,
+        max_downsampling=float("inf"),
+        max_downsampled_size=8,
+    )
     state.layers["image"] = neuroglancer.ImageLayer(
-        source="precomputed://http://127.0.0.1:9000/sphere",
+        source=local_volume,
         volume_rendering_mode="max",
         tool_bindings={
             "A": neuroglancer.VolumeRenderingGainTool(),
@@ -45,23 +55,20 @@ def get_shader():
     return """#uicontrol invlerp normalized(range=[0,255], clamp=true)
 void main() {
     float val = normalized();
-    emitIntensity(val);
     emitGrayscale(val);
 }
 """
 
 
 if __name__ == "__main__":
-    create_sphere()
+    data = create_sphere_in_cube(400, 0.9)
     create_server(directory="datasets")
     viewer = launch_nglancer()
     with viewer.txn() as s:
-        add_image_layer(s, shader=get_shader())
+        add_image_layer(s, data, shader=get_shader())
     threedee_view(viewer)
     remove_axis_lines(viewer)
     update_title(viewer, "Sphere example")
     set_gpu_memory(viewer, gpu_memory=2)
     update_projection(viewer, orientation=[0.25, 0.6, 0.65, 0.3])
     open_browser(viewer, hang=False)
-    sleep(4)  # TODO this is a hack to wait for viewer to open
-    update_projection(viewer, scale=1500, depth=3000)

neuroglancer_utils/create_datasets/create_mc_logo.py

@@ -0,0 +1,36 @@
+from cloudvolume import CloudVolume
+import numpy as np
+from PIL import Image
+from pathlib import Path
+
+
+HOMEPATH = Path.home()
+FILEPATH = HOMEPATH / "Documents" / "mc_logo.png"
+
+
+def create_mc_logo(output_path="file://datasets/mc_logo"):
+    img = Image.open(FILEPATH)
+    luminance = np.array(img)[:, :, -1]
+    Image.fromarray(luminance).save(HOMEPATH / "Documents" / "mc_logo_gray.png")
+    imgdata = luminance.T
+    dim_size = int((imgdata.shape[0] + imgdata.shape[1]) / 2)
+    rawdata = np.zeros(
+        shape=(imgdata.shape[0], imgdata.shape[1], dim_size),
+        dtype=np.uint8,
+    )
+    for i in range(dim_size):
+        rawdata[:, :, i] = imgdata
+
+    # CloudVolume.from_numpy(
+    #     rawdata,
+    #     vol_path=output_path,
+    #     resolution=(1, 1, 1),
+    #     layer_type="image",
+    #     progress=True,
+    #     compress=False,
+    # )
+    return rawdata
+
+
+if __name__ == "__main__":
+    create_mc_logo()