feat: add in progress sis example

Author: seankmartin

examples/load_sis.py

@@ -0,0 +1,125 @@
+import argparse
+import webbrowser
+import neuroglancer
+import neuroglancer.cli
+from pathlib import Path
+import dask.array as da
+import numpy as np
+
+HERE = Path(__file__).parent
+# path to the file
+FILEPATH = Path("x.sis")
+
+
+class OlympusSISFile:
+    def __init__(self, path):
+        self._path = path
+        self._file = open(path, "rb")
+        self._get_header_size()
+        self._file.seek(self.header_size)
+
+        # TEMP - hardcoded values from metadata
+        # Something is a litte wrong though as it's too big
+        self.width = 3299
+        self.height = 3289
+        self.depth = 10  # actual 1025
+        self.channels = 1  # actual 9
+
+    def read(self, size=-1):
+        return self._file.read(size)
+
+    def seek(self, offset, whence=0):
+        if whence == 0:
+            return self._file.seek(self.header_size + offset)
+        elif whence == 1:
+            return self._file.seek(offset, 1)
+        elif whence == 2:
+            return self._file.seek(offset, 2)
+
+    def tell(self):
+        return self._file.tell() - self.header_size
+
+    def close(self):
+        self._file.close()
+
+    def __enter__(self):
+        return self
+
+    def __exit__(self, exc_type, exc_val, exc_tb):
+        self.close()
+
+    def _get_header_size(self):
+        i = 0
+        while True and i < 1000000:
+            line = self._file.readline().decode("utf-8")
+            i += 1
+            if line.startswith("Header"):
+                break
+        # The format is Header = <size>
+        # 49 chars for the bit before Header = <size>
+        self.header_size = int(line.split("=")[1].strip()) + 49
+        print(f"Header size: {self.header_size}")
+
+    def write_header_to_file(self, path):
+        self._file.seek(0)
+        with open(path, "wb") as f:
+            f.write(self._file.read(self.header_size))
+        self._file.seek(self.header_size)
+
+    def to_numpy_memmap(self):
+        return np.memmap(
+            self._path,
+            offset=self.header_size,
+            dtype=np.uint16,
+            mode="r",
+            shape=(self.height, self.width, self.depth, self.channels),
+        )
+
+
+def add_image_layer(state, data, name="image"):
+    dimensions = neuroglancer.CoordinateSpace(
+        names=["x", "y", "z", "c"], units="nm", scales=[1, 1, 1, 1]
+    )
+    local_volume = neuroglancer.LocalVolume(data, dimensions)
+    state.layers.append(
+        name=name,
+        layer=neuroglancer.ImageLayer(
+            source=local_volume,
+            volume_rendering_mode="ON",
+            volume_rendering_depth_samples=400,
+        ),
+        shader="""
+#uicontrol invlerp normalized
+void main() {
+    float val = normalized();
+    emitRGBA(vec4(val, val, val, val));
+    }
+    """,
+    )
+    state.layout = "3d"
+
+
+def launch_nglancer():
+    ap = argparse.ArgumentParser()
+    neuroglancer.cli.add_server_arguments(ap)
+    args = ap.parse_args()
+    neuroglancer.cli.handle_server_arguments(args)
+    viewer = neuroglancer.Viewer()
+    return viewer
+
+
+def main():
+    chunks = (512, 512, 1, 1)
+    with OlympusSISFile(str(FILEPATH)) as f:
+        f.write_header_to_file("header.txt")
+        mmapped = f.to_numpy_memmap()
+        # TODO would need to replace with a lazy load from the mmap
+        dask_array = da.from_array(mmapped, chunks=chunks)
+    viewer = launch_nglancer()
+    with viewer.txn() as s:
+        add_image_layer(s, dask_array, "image")
+    webbrowser.open_new(viewer.get_viewer_url())
+
+
+if __name__ == "__main__":
+    main()