remove SpeedDataframe and Speedmap

ecoscope/analysis/__init__.py

@@ -1,6 +1,5 @@
 __all__ = [
     "ecograph",
-    "speed",
     "UD",
     "astronomy",
     "classifier",

ecoscope/mapping/map.py

@@ -14,13 +14,11 @@
 
 try:
     import matplotlib as mpl
-    from ecoscope.analysis.speed import SpeedDataFrame
     from lonboard import Map
     from lonboard.types.layer import PathLayerKwargs, PolygonLayerKwargs, ScatterplotLayerKwargs
     from lonboard._geoarrow.ops.bbox import Bbox
     from lonboard._viewport import compute_view, bbox_to_zoom_level
     from lonboard._viz import viz_layer
-    from lonboard.colormap import apply_categorical_cmap
     from lonboard._layer import (
         BaseLayer,
         BitmapLayer,
@@ -46,42 +44,7 @@
     )
 
 
-class EcoMapMixin:
-    def add_speedmap(
-        self,
-        trajectory: gpd.GeoDataFrame,
-        classification_method: str = "equal_interval",
-        num_classes: int = 6,
-        speed_colors: List = None,
-        bins: List = None,
-        legend: bool = True,
-    ):
-
-        speed_df = SpeedDataFrame.from_trajectory(
-            trajectory=trajectory,
-            classification_method=classification_method,
-            num_classes=num_classes,
-            speed_colors=speed_colors,
-            bins=bins,
-        )
-
-        colors = speed_df["speed_colour"].to_list()
-        rgb = []
-        for i, color in enumerate(colors):
-            color = color.strip("#")
-            rgb.append(list(int(color[i : i + 2], 16) for i in (0, 2, 4)))
-
-        cmap = apply_categorical_cmap(values=speed_df.index.to_series(), cmap=rgb)
-        path_kwargs = {"get_color": cmap, "pickable": False}
-        self.add_gdf(speed_df, path_kwargs=path_kwargs)
-
-        if legend:
-            self.add_legend(labels=speed_df.label.to_list(), colors=speed_df.speed_colour.to_list())
-
-        return speed_df
-
-
-class EcoMap(EcoMapMixin, Map):
+class EcoMap(Map):
     def __init__(self, static=False, default_widgets=True, *args, **kwargs):
 
         kwargs["height"] = kwargs.get("height", 600)