import pandas as pd
import geopandas as gpd
import movingpandas as mpd
import shapely as shp
import hvplot.pandas
import matplotlib.pyplot as plt
import folium

from geopandas import GeoDataFrame, read_file
from shapely.geometry import Point, LineString, Polygon
from datetime import datetime, timedelta
from holoviews import opts, dim

import warnings

warnings.filterwarnings("ignore")

plot_defaults = {"linewidth": 5, "capstyle": "round", "figsize": (9, 3), "legend": True}
opts.defaults(
    opts.Overlay(active_tools=["wheel_zoom"], frame_width=500, frame_height=400)
)

mpd.show_versions()

MovingPandas 0.20.0

SYSTEM INFO
-----------
python     : 3.10.15 | packaged by conda-forge | (main, Oct 16 2024, 01:15:49) [MSC v.1941 64 bit (AMD64)]
executable : c:\Users\Agarkovam\AppData\Local\miniforge3\envs\mpd-ex\python.exe
machine    : Windows-10-10.0.19045-SP0

GEOS, GDAL, PROJ INFO
---------------------
GEOS       : None
GEOS lib   : None
GDAL       : None
GDAL data dir: None
PROJ       : 9.5.0
PROJ data dir: C:\Users\Agarkovam\AppData\Local\miniforge3\envs\mpd-ex\Library\share\proj

PYTHON DEPENDENCIES
-------------------
geopandas  : 1.0.1
pandas     : 2.2.3
fiona      : None
numpy      : 1.23.1
shapely    : 2.0.6
pyproj     : 3.7.0
matplotlib : 3.9.2
mapclassify: 2.8.1
geopy      : 2.4.1
holoviews  : 1.20.0
hvplot     : 0.11.1
geoviews   : 1.13.0
stonesoup  : 1.4

gdf = read_file("../data/geolife_small.gpkg")
tc = mpd.TrajectoryCollection(gdf, "trajectory_id", t="t")

tc.hvplot(line_width=7.0, tiles="CartoLight")

tc.explore(column="trajectory_id", cmap="plasma", style_kwds={"weight": 4})

generalized = mpd.MinDistanceGeneralizer(tc).generalize(tolerance=100)

aggregator = mpd.TrajectoryCollectionAggregator(
    generalized,
    max_distance=1000,
    min_distance=100,
    min_stop_duration=timedelta(minutes=5),
)

pts = aggregator.get_significant_points_gdf()
clusters = aggregator.get_clusters_gdf()
(pts.hvplot(geo=True, tiles="CartoLight") * clusters.hvplot(geo=True, color="red"))

m = pts.explore(marker_kwds={"radius": 3}, name="Significant points")

clusters.explore(m=m, color="red", marker_kwds={"radius": 3}, name="Cluster centroids")

folium.TileLayer("CartoDB positron").add_to(m)
folium.LayerControl().add_to(m)

m

flows = aggregator.get_flows_gdf()

(
    flows.hvplot(
        geo=True,
        hover_cols=["weight"],
        line_width=dim("weight") * 7,
        color="#1f77b3",
        tiles="CartoLight",
    )
    * clusters.hvplot(geo=True, color="red", size=dim("n"))
)

m = flows.explore(
    style_kwds={"weight": 5},
    name="Flows",
)

clusters.explore(
    m=m,
    color="red",
    style_kwds={"style_function": lambda x: {"radius": x["properties"]["n"]}},
    name="Clusters",
)

folium.TileLayer("OpenStreetMap").add_to(m)
folium.LayerControl().add_to(m)

m

Aggregating trajectories¶

TrajectoryCollectionAggregator¶