xvec support

[ahuang11]

Closes holoviz/geoviews#737

Not entirely sure what the level of support should be implemented for xvec; should this be in geoviews or just hvplot?

In attempt 2 (current), I convert the xarray dataset into geopandas dataframe, "flattening" extra geometries, i.e. converting them into integer indices which is done through drop_vars, and then gathering all the xarray dims as groupby; that way, it still shows up as slider widgets

Screen.Recording.2024-08-29.at.5.08.31.PM.mov

However, the integers aren't meaningful so I was wondering if there are extra geometries, should I overlay centroid points of the other geometries? If so, how do I even do that in hvplot?

In attempt 1, I try to keep it in its xarray data structure, but requires much more change in hvplot to plot geometries nested in xarray.

cc: @hoxbro

---

import geopandas as gpd
import pandas as pd
import hvplot.pandas

import xarray as xr

uri = "gs://gcp-public-data-arco-era5/ar/1959-2022-full_37-6h-0p25deg-chunk-1.zarr-v2"
era5_ds_sub = (
    # Open the dataset
    xr.open_zarr(uri, chunks={"time": 48}, consolidated=True)
    # Select the near-surface level
    .isel(level=0, drop=True)
    # subset in time
    .sel(time=slice("2017-01", "2018-01"))
    # reduce to two arrays
    [["2m_temperature", "u_component_of_wind"]]
)
era5_ds_sub


cities_df = pd.read_json(
    "hf://datasets/jamescalam/world-cities-geo/train.jsonl", lines=True
)
cities_eur = cities_df.loc[cities_df["continent"] == "Europe"]
cities_eur = gpd.GeoDataFrame(
    cities_eur,
    geometry=gpd.points_from_xy(cities_eur.longitude, cities_eur.latitude),
    crs="EPSG:4326",
).drop(["latitude", "longitude", "x", "y", "z"], axis=1)
import xvec

era5_europe_cities = era5_ds_sub.xvec.extract_points(
    cities_eur.geometry, x_coords="longitude", y_coords="latitude"
).drop_vars("index")

era5_europe_cities["2m_temperature"].isel(time=slice(0, 2)).hvplot()

import geopandas as gpd
import numpy as np
import pandas as pd
import xarray as xr
import xvec
import hvplot.xarray

from geodatasets import get_path
chicago = gpd.read_file(get_path("geoda.chicago health"))

origin = destination = chicago.geometry.array
mode = ["car", "bike", "foot"]
date = pd.date_range("2023-01-01", periods=100)
hours = range(24)
rng = np.random.default_rng(1)
data = rng.integers(1, 100, size=(3, 100, 24, len(chicago), len(chicago)))
traffic_counts = xr.DataArray(
    data,
    coords=(mode, date, hours, origin, destination),
    dims=["mode", "date", "time", "origin", "destination"],
    name="traffic_counts",
).xvec.set_geom_indexes(["origin", "destination"], crs=chicago.crs)
traffic_counts.sel(date="2023-02-28", time=12, mode="bike").hvplot("traffic_counts", hover_cols=["date", "time"])

[codecov]

Codecov Report

Attention: Patch coverage is 26.66667% with 11 lines in your changes missing coverage. Please review.

Project coverage is 88.68%. Comparing base (6c96c7e) to head (3243cbb).
Report is 19 commits behind head on main.

Files with missing lines	Patch %	Lines
hvplot/converter.py	10.00%	9 Missing ⚠️
hvplot/util.py	60.00%	2 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1405      +/-   ##
==========================================
+ Coverage   87.39%   88.68%   +1.28%     
==========================================
  Files          50       51       +1     
  Lines        7490     7509      +19     
==========================================
+ Hits         6546     6659     +113     
+ Misses        944      850      -94     

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