Tiled Image parameters update (#62)

* initial changes - wip

* image viewer added - wip

* add image viewer

* Removed unses polyfill plugin, update tiled image parameters

* Updated dependencies

* Bump TileDB Viz version to 1.0.2-alpha.12

* lint fix

* Pin capnp-ts to 0.4.0

* Remove packageManager entry since jlab v3 uses yarn v1

---------

Co-authored-by: Margriet Groenendijk <[email protected]>
Co-authored-by: SarantopoulosKon <[email protected]>

Author: 3 people

.yarnrc.yml

@@ -1,2 +1,3 @@
 enableImmutableInstalls: false
-nodeLinker: node-modules
+
+nodeLinker: node-modules

package.json

@@ -58,7 +58,7 @@
   "dependencies": {
     "@jupyter-widgets/base": "^2 || ^3 || ^4 || ^5 || ^6",
     "@jupyterlab/application": "^3 || ^4",
-    "@tiledb-inc/viz-core": "^1.0.2-alpha.2"
+    "@tiledb-inc/viz-core": "1.0.2-alpha.12"
   },
   "devDependencies": {
     "@jupyterlab/builder": "^3 || ^4",
@@ -86,6 +86,9 @@
     "webpack": "^5.88.1",
     "webpack-cli": "^5.1.4"
   },
+  "resolutions": {
+    "capnp-ts": "0.4.0"
+  },
   "jupyterlab": {
     "extension": "lib/plugin",
     "outputDir": "pybabylonjs/labextension",

pybabylonjs/args.py

@@ -15,19 +15,13 @@
     "inspector": None,
     "color_scheme": None,
     "z_scale": None,
-    "topo_offset": None,
-    "classes": {"numbers": [], "names": []},
-    "time_offset": None,
-    "point_shift": [None, None, None],
     "rgb_max": None,
     "bbox": None,
     "name_space": None,
     "group_name": None,
     "array_name": None,
     "token": None,
     "tiledb_env": None,
-    "mbtoken": None,
-    "mbstyle": None,
     "crs": None,
     "buffer_size": None,
     "streaming": None,
@@ -46,45 +40,65 @@
     "worker_pool_size": None,
 }
 
+IMAGE_ARGS_DEFAULTS = {
+    "width": None,
+    "height": None,
+    "wheel_precision": None,  # used? in base class?
+    "move_speed": None,  # used?
+    "name_space": None,
+    "array_name": None,
+    "group_name": None,
+    "geometry_array_name": None,
+    "base_group": None,
+    "token": None,
+    "tiledb_env": None,
+    "default_channels": None,
+}
 
-def check_point_cloud_args(source, mode, point_cloud_args_in):
-    if mode == "time":
-        raise ValueError("This mode will be implemented soon")
-    if mode == "classes":
-        raise ValueError("This mode will be implemented soon")
-        if not "classes" in point_cloud_args_in:
-            raise ValueError(
-                "The classes containing numbers and names is not specified"
-            )
-    elif mode == "topo":
-        raise ValueError("This mode will be implemented soon")
-        if not "mbtoken" in point_cloud_args_in:
-            raise ValueError("The Mapbox token is not specified")
-        if not "crs" in point_cloud_args_in:
-            raise ValueError(
-                "The crs (coordinate reference system) of the data is not specified"
-            )
-        if not "bbox" in point_cloud_args_in:
-            raise ValueError("The bbox is not specified")
 
+def in_pixels(h, default):
+    if h is None:
+        return default
+    if isinstance(h, str):
+        if "px" in h:
+            return h
+        return h + "px"
+    if isinstance(h, int):
+        return str(h) + "px"
+    if isinstance(h, float):
+        return str(int(h)) + "px"
+
+
+def check_image_args(image_args_in):
+    image_args = {}
+    for key in IMAGE_ARGS_DEFAULTS.keys():
+        if key in image_args_in:
+            if key is not None:
+                image_args[key] = image_args_in.pop(key)
+
+    image_args["height"] = in_pixels(image_args.get("height"), "500px")
+    image_args["width"] = in_pixels(image_args.get("width"), "700px")
+
+    if not "token" in image_args:
+        try:
+            token = os.getenv("TILEDB_REST_TOKEN")
+        except:
+            if token == None:
+                raise ValueError(
+                    "The TileDB Cloud token needed to access the array is not specified or cannot be accessed"
+                )
+        image_args = {**image_args, "token": token}
+
+    return image_args
+
+
+def check_point_cloud_args(source, streaming, point_cloud_args_in):
     point_cloud_args = {}
     for key in POINT_CLOUD_ARGS_DEFAULTS.keys():
         if key in point_cloud_args_in:
             if key is not None:
                 point_cloud_args[key] = point_cloud_args_in.pop(key)
 
-    def in_pixels(h, default):
-        if h is None:
-            return default
-        if isinstance(h, str):
-            if "px" in h:
-                return h
-            return h + "px"
-        if isinstance(h, int):
-            return str(h) + "px"
-        if isinstance(h, float):
-            return str(int(h)) + "px"
-
     point_cloud_args["height"] = in_pixels(point_cloud_args.get("height"), "500px")
     point_cloud_args["width"] = in_pixels(point_cloud_args.get("width"), "700px")
 
@@ -101,7 +115,7 @@ def in_pixels(h, default):
     return point_cloud_args
 
 
-def check_point_cloud_data_dict(mode, data):
+def check_point_cloud_data_dict(data):
     for var in ["X", "Y", "Z", "Red", "Green", "Blue"]:
         if not var in data:
             raise ValueError("Data dictionary does not contain " + var)
@@ -115,28 +129,16 @@ def check_point_cloud_data_dict(mode, data):
     ):
         raise ValueError("Attributes in data dictionary do not have the same length.")
 
-    if mode == "time":
-        if not "GpsTime" in data:
-            raise ValueError("Data dictionary does not contain 'GpsTime'")
-
-        i = np.argsort(data["GpsTime"])
-        for key in ["Red", "Green", "Blue", "GpsTime", "X", "Y", "Z"]:
-            data[key] = data[key][i]
-
-    elif mode == "classes":
-        if not "Classification" in data:
-            raise ValueError("Data dictionary does not contain 'Classification'")
-
     return data
 
 
-def check_point_cloud_data_local(mode, uri, point_cloud_args):
+def check_point_cloud_data_local(uri, point_cloud_args):
     if os.path.isdir(uri) == False:
         raise ValueError("uri: " + uri + " does not exist.")
     if not "bbox" in point_cloud_args:
         raise ValueError("The bbox for slicing data from the array is not specified")
 
-    data = create_point_cloud(mode, uri, point_cloud_args["bbox"])
+    data = create_point_cloud(uri, point_cloud_args["bbox"])
 
     return data
 

pybabylonjs/babylonjs.py

@@ -46,8 +46,8 @@ class BabylonMBRS(BabylonBase):
 
 @register
 class BabylonImage(BabylonBase):
-    """Ground surface as 2D array with BabylonJS"""
+    """Images with BabylonJS"""
 
-    _model_name = Unicode("BabylonImageModel").tag(sync=True)
-    _view_name = Unicode("BabylonImageView").tag(sync=True)
+    _model_name = Unicode("BabylonTileImageModel").tag(sync=True)
+    _view_name = Unicode("BabylonTileImageView").tag(sync=True)
     value = Dict().tag(sync=True)

pybabylonjs/data.py

@@ -2,20 +2,12 @@
 # Licensed under the MIT License.
 """Functions to format data from the arrays to be used in the visualization."""
 
-import io
-import numpy as np
 import pandas as pd
-import cv2
 import tiledb
 
 
-def create_point_cloud(mode, array_uri: str, bbox):
-    if mode == "time":
-        attrs = ["Red", "Green", "Blue", "GpsTime"]
-    elif mode == "classes":
-        attrs = ["Red", "Green", "Blue", "Classification"]
-    else:
-        attrs = ["Red", "Green", "Blue"]
+def create_point_cloud(array_uri: str, bbox):
+    attrs = ["Red", "Green", "Blue"]
 
     with tiledb.open(array_uri) as arr:
         data = arr.query(attrs=attrs, dims=["X", "Y", "Z"])[
@@ -24,75 +16,9 @@ def create_point_cloud(mode, array_uri: str, bbox):
             bbox["Z"][0] : bbox["Z"][1],
         ]
 
-    if mode == "time":
-        i = np.argsort(data["GpsTime"])
-        for key in ["Red", "Green", "Blue", "GpsTime", "X", "Y", "Z"]:
-            data[key] = data[key][i]
-
     return data
 
 
-def create_mapbox_image(data: dict, point_cloud_args):
-    """Create a Dict with an additional topographic image from mapbox
-
-    Parameters:
-    """
-    import requests
-    from rasterio.coords import BoundingBox
-    from rasterio.warp import transform_bounds
-
-    mbtoken = point_cloud_args["mbtoken"]
-    style_id = point_cloud_args["mbstyle"]
-    data_crs = point_cloud_args["crs"]
-    bbox_in = point_cloud_args["bbox"]
-
-    dst_crs = {"init": "EPSG:4326"}  # lat/lon
-
-    if bbox_in:
-        bbox = BoundingBox(
-            bbox_in["X"][0], bbox_in["Y"][0], bbox_in["X"][1], bbox_in["Y"][1]
-        )
-    else:
-        bbox = BoundingBox(
-            data["X"].min(), data["Y"].min(), data["X"].max(), data["Y"].max()
-        )
-
-    dst_bbox = transform_bounds(data_crs, dst_crs, *bbox)
-
-    w = bbox[2] - bbox[0]
-    h = bbox[3] - bbox[1]
-
-    if w > h:
-        ww = 1280
-        hh = int(h / w * 1280)
-    elif h > w:
-        hh = 1280
-        ww = int(w / h * 1280)
-
-    f = requests.get(
-        (
-            "https://api.mapbox.com/styles/v1/mapbox/"
-            + style_id
-            + "/static/["
-            + str(dst_bbox[0])
-            + ","
-            + str(dst_bbox[1])
-            + ","
-            + str(dst_bbox[2])
-            + ","
-            + str(dst_bbox[3])
-            + "]/"
-            + str(ww)
-            + "x"
-            + str(hh)
-            + "?access_token="
-            + mbtoken
-        )
-    )
-
-    return f.content
-
-
 def create_mbrs(array_uri: str):
     """Create a Dict to be passed on to BabylonMBRS to create MBRS outlines."""
     fragments_info = tiledb.array_fragments(array_uri, include_mbrs=True)
@@ -137,35 +63,3 @@ def create_mbrs(array_uri: str):
     ]
 
     return dict(extents=extents, data=data)
-
-
-def create_image(array_uri: str, **kwargs):
-    """Create a Dict to be passed on to BabylonGround containing images as blobs.
-
-    Parameters:
-    array_uri: uri of the dense array
-    attribute: the attribute to load from the array
-    xy_bbox: ranges of x and y to slice data on [x1,x2,y1,y2]
-    band: band number to slice from the array
-    scale_factor: factor to scale the values in the image
-    """
-
-    def numpy_to_binary(arr):
-        is_success, buffer = cv2.imencode(".png", arr)
-        io_buf = io.BytesIO(buffer)
-        return io_buf.read()
-
-    bbox = kwargs["xy_bbox"]
-    band = kwargs["band"]
-    image_type = kwargs["image_type"]
-    sar_scale = kwargs["sar_scale_factor"]
-
-    with tiledb.open(array_uri, "r") as arr:
-        img = arr[band, bbox[0] : bbox[1], bbox[2] : bbox[3]][kwargs["attribute"]]
-
-    if image_type == "sar":
-        img = 20 * np.log10(img * sar_scale)
-        img = ((img - np.min(img)) / (np.max(img) - np.min(img))) * 255
-    binary_image = numpy_to_binary(img)
-
-    return dict(data=binary_image)