Constraints that specify lambda functions

Selecting ranges in the events DataFrame is possible. We provide support for lambda functions in order to empower the user to specify arbitrary conditions. In the example below we’re going to use a simple condition but, evidently, it can be as complex as needed.

Say we want to select all events that occurred between frames 327 and 1327. We can do it like this:

import numpy as np
import pandas as pd
import xarray as xr
import xarray_events

ds = xr.Dataset(
    data_vars={
        'ball_trajectory': (
            ['frame', 'cartesian_coords'],
            np.exp(np.linspace((-6, -8), (3, 2), 2450))
        )
    },
    coords={
        'frame': np.arange(1, 2451),
        'cartesian_coords': ['x', 'y'],
        'player_id': [2, 3, 7, 19, 20, 21, 22, 28, 34, 79]
    },
    attrs={'match_id': 12, 'resolution_fps': 25}
)

events = pd.DataFrame(
    {
        'event_type':
            ['pass', 'goal', 'pass', 'pass', 'pass',
             'penalty', 'goal', 'pass', 'pass', 'penalty'],
        'start_frame': [1, 425, 600, 945, 1100, 1280, 1890, 2020, 2300, 2390],
        'end_frame': [424, 599, 944, 1099, 1279, 1889, 2019, 2299, 2389, 2450],
        'player_id': [79, 79, 19, 2, 3, 2, 3, 79, 2, 79]
    }
)

(
    ds
    .events.load(events, {'frame': ('start_frame', 'end_frame')})
    .events.sel(
        {
            'start_frame': lambda frame: frame > 327,
            'end_frame': lambda frame: frame < 1327
        }
    )
    .events.df
)

	event_type	start_frame	end_frame	player_id
1	goal	425	599	79
2	pass	600	944	19
3	pass	945	1099	2
4	pass	1100	1279	3

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