Fix CI Failures (#731)

* update envs

* fix issues in point raster

* fix dask issues

* remove left over attributes

* add comments

ci/asv.yml

@@ -15,7 +15,7 @@ dependencies:
   - pandas<2.1.0
   - pathlib
   - pre_commit
-  - pyarrow<13.0.0   # pin due to CI faliures on macOS & ubuntu
+  - pyarrow
   - pytest
   - pytest-cov
   - requests

ci/docs.yml

@@ -6,7 +6,7 @@ dependencies:
     - dask
     - netcdf4
     - numba
-    - numpy<=1.24
+    - numpy
     - pathlib
     - pre_commit
     - pytest

test/test_plot.py

@@ -90,4 +90,4 @@ def test_clabel(self):
 
         raster_no_clabel = uxds['v1'][0][0].plot.rasterize(method='point')
 
-        raster_no_clabel = uxds['v1'][0][0].plot.rasterize(method='point', clabel="Foo")
+        raster_with_clabel = uxds['v1'][0][0].plot.rasterize(method='point', clabel='Foo')

uxarray/grid/grid.py

@@ -143,8 +143,6 @@ def __init__(
         self._gdf_exclude_am = None
         self._poly_collection = None
         self._line_collection = None
-        self._centroid_points_df_proj = [None, None]
-        self._corner_points_df_proj = [None, None]
         self._raster_data_id = None
 
         # initialize cached data structures (nearest neighbor operations)

uxarray/plot/dataarray_plot.py

@@ -15,7 +15,6 @@
 
 from uxarray.plot.constants import N_FACE_THRESHOLD
 
-import pandas as pd
 
 import numpy as np
 
@@ -214,65 +213,31 @@ def _point_raster(
 
     if uxda._face_centered():
         # data mapped to face centroid coordinates
-        lon = uxda.uxgrid.face_lon.values
-        lat = uxda.uxgrid.face_lat.values
+        lon, lat = uxda.uxgrid.face_lon.values, uxda.uxgrid.face_lat.values
     elif uxda._node_centered():
         # data mapped to face corner coordinates
-        lon = uxda.uxgrid.node_lon.values
-        lat = uxda.uxgrid.node_lat.values
+        lon, lat = uxda.uxgrid.node_lon.values, uxda.uxgrid.node_lat.values
     elif uxda._edge_centered():
         # data mapped to face corner coordinates
-        lon = uxda.uxgrid.edge_lon.values
-        lat = uxda.uxgrid.edge_lat.values
+        lon, lat = uxda.uxgrid.edge_lon.values, uxda.uxgrid.edge_lat.values
     else:
         raise ValueError(
             f"The Dimension of Data Variable {uxda.name} is not Node or Face centered."
         )
 
-    # determine whether we need to recompute points, typically when a new projection is selected
-    recompute = True
-    if uxda._face_centered() == "center":
-        if (
-            uxda.uxgrid._centroid_points_df_proj[0] is not None
-            and uxda.uxgrid._centroid_points_df_proj[1] == projection
-        ):
-            recompute = False
-            points_df = uxda.uxgrid._centroid_points_df_proj[0]
-
-    else:
-        if (
-            uxda.uxgrid._corner_points_df_proj[0] is not None
-            and uxda.uxgrid._corner_points_df_proj[1] == projection
-        ):
-            recompute = False
-            points_df = uxda.uxgrid._corner_points_df_proj[0]
-
-    if recompute:
-        # need to recompute points and/or projection
-        if projection is not None:
-            lon, lat, _ = projection.transform_points(ccrs.PlateCarree(), lon, lat).T
-
-        point_dict = {"lon": lon, "lat": lat, "var": uxda.values}
-
-        # Construct Dask DataFrame
-        point_ddf = dd.from_dict(data=point_dict, npartitions=npartitions)
+    if projection is not None:
+        # apply projection to coordinates
+        lon, lat, _ = projection.transform_points(ccrs.PlateCarree(), lon, lat).T
 
-        hv.extension("bokeh")
-        points = hv.Points(point_ddf, ["lon", "lat"]).opts(size=size)
+    # this will be fixed in #733
+    hv.extension("bokeh")
 
-        # cache computed points & projection
-        if cache:
-            if uxda._face_centered() == "center":
-                uxda.uxgrid._centroid_points_df_proj[0] = point_ddf
-                uxda.uxgrid._centroid_points_df_proj[1] = projection
-            else:
-                uxda.uxgrid._corner_points_df_proj[0] = point_ddf
-                uxda.uxgrid._corner_points_df_proj[1] = projection
+    # construct a dask dataframe from coordinates and data
+    point_dict = {"lon": lon, "lat": lat, "var": uxda.data}
+    point_ddf = dd.from_dict(data=point_dict, npartitions=npartitions)
 
-    else:
-        # use existing cached points & projection
-        points_df["var"] = pd.Series(uxda.values)
-        points = hv.Points(points_df, ["lon", "lat"]).opts(size=size)
+    # construct a holoviews points oobject
+    points = hv.Points(point_ddf, ["lon", "lat"]).opts(size=size)
 
     if backend == "matplotlib":
         # use holoviews matplotlib backend