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"""Implements a converter for regular SPADL actions to atomic actions.""" |
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from typing import cast |
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import pandas as pd |
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from pandera.typing import DataFrame |
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import socceraction.spadl.config as _spadl |
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from socceraction.spadl.base import _add_dribbles |
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from socceraction.spadl.schema import SPADLSchema |
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from . import config as _atomicspadl |
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from .schema import AtomicSPADLSchema |
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def convert_to_atomic(actions: DataFrame[SPADLSchema]) -> DataFrame[AtomicSPADLSchema]: |
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"""Convert regular SPADL actions to atomic actions. |
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Parameters |
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---------- |
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actions : pd.DataFrame |
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A SPADL dataframe. |
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Returns |
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------- |
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pd.DataFrame |
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The Atomic-SPADL dataframe. |
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""" |
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atomic_actions = cast(pd.DataFrame, actions.copy()) |
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atomic_actions = _extra_from_passes(atomic_actions) |
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atomic_actions = _add_dribbles(atomic_actions) |
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atomic_actions = _extra_from_shots(atomic_actions) |
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atomic_actions = _extra_from_fouls(atomic_actions) |
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atomic_actions = _convert_columns(atomic_actions) |
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atomic_actions = _simplify(atomic_actions) |
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return cast(DataFrame[AtomicSPADLSchema], atomic_actions) |
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def _extra_from_passes(actions: pd.DataFrame) -> pd.DataFrame: |
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next_actions = actions.shift(-1) |
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same_team = actions.team_id == next_actions.team_id |
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passlike = [ |
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"pass", |
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"cross", |
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"throw_in", |
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"freekick_short", |
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"freekick_crossed", |
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"corner_crossed", |
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"corner_short", |
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"clearance", |
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"goalkick", |
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] |
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pass_ids = [_spadl.actiontypes.index(ty) for ty in passlike] |
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interceptionlike = [ |
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"interception", |
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"tackle", |
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"keeper_punch", |
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"keeper_save", |
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"keeper_claim", |
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"keeper_pick_up", |
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] |
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interception_ids = [_spadl.actiontypes.index(ty) for ty in interceptionlike] |
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samegame = actions.game_id == next_actions.game_id |
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sameperiod = actions.period_id == next_actions.period_id |
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extra_idx = ( |
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actions.type_id.isin(pass_ids) |
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& samegame |
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& sameperiod |
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& ~next_actions.type_id.isin(interception_ids) |
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) |
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prev = actions[extra_idx] |
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nex = next_actions[extra_idx] |
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extra = pd.DataFrame() |
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extra["game_id"] = prev.game_id |
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extra["original_event_id"] = prev.original_event_id |
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extra["period_id"] = prev.period_id |
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extra["action_id"] = prev.action_id + 0.1 |
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extra["time_seconds"] = (prev.time_seconds + nex.time_seconds) / 2 |
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extra["start_x"] = prev.end_x |
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extra["start_y"] = prev.end_y |
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extra["end_x"] = prev.end_x |
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extra["end_y"] = prev.end_y |
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extra["bodypart_id"] = _atomicspadl.bodyparts.index("foot") |
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extra["result_id"] = -1 |
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offside = prev.result_id == _spadl.results.index("offside") |
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out = ((nex.type_id == _atomicspadl.actiontypes.index("goalkick")) & (~same_team)) | ( |
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nex.type_id == _atomicspadl.actiontypes.index("throw_in") |
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) |
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ar = _atomicspadl.actiontypes |
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extra["type_id"] = -1 |
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extra["type_id"] = ( |
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extra.type_id.mask(same_team, ar.index("receival")) |
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.mask(~same_team, ar.index("interception")) |
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.mask(out, ar.index("out")) |
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.mask(offside, ar.index("offside")) |
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) |
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is_interception = extra["type_id"] == ar.index("interception") |
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extra["team_id"] = prev.team_id.mask(is_interception, nex.team_id) |
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extra["player_id"] = nex.player_id.mask(out | offside, prev.player_id).astype( |
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prev.player_id.dtype |
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) |
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actions = pd.concat([actions, extra], ignore_index=True, sort=False) |
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actions = actions.sort_values(["game_id", "period_id", "action_id"]).reset_index(drop=True) |
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actions["action_id"] = range(len(actions)) |
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return actions |
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def _extra_from_shots(actions: pd.DataFrame) -> pd.DataFrame: |
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next_actions = actions.shift(-1) |
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shotlike = ["shot", "shot_freekick", "shot_penalty"] |
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shot_ids = [_spadl.actiontypes.index(ty) for ty in shotlike] |
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samegame = actions.game_id == next_actions.game_id |
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sameperiod = actions.period_id == next_actions.period_id |
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shot = actions.type_id.isin(shot_ids) |
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goal = shot & (actions.result_id == _spadl.results.index("success")) |
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owngoal = actions.result_id == _spadl.results.index("owngoal") |
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next_corner_goalkick = next_actions.type_id.isin( |
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[ |
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_atomicspadl.actiontypes.index("corner_crossed"), |
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_atomicspadl.actiontypes.index("corner_short"), |
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_atomicspadl.actiontypes.index("goalkick"), |
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] |
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) |
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out = shot & next_corner_goalkick & samegame & sameperiod |
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extra_idx = goal | owngoal | out |
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prev = actions[extra_idx] |
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extra = pd.DataFrame() |
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extra["game_id"] = prev.game_id |
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extra["original_event_id"] = prev.original_event_id |
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extra["period_id"] = prev.period_id |
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extra["action_id"] = prev.action_id + 0.1 |
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extra["time_seconds"] = prev.time_seconds |
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extra["start_x"] = prev.end_x |
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extra["start_y"] = prev.end_y |
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extra["end_x"] = prev.end_x |
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extra["end_y"] = prev.end_y |
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extra["bodypart_id"] = prev.bodypart_id |
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extra["result_id"] = -1 |
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extra["team_id"] = prev.team_id |
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extra["player_id"] = prev.player_id |
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ar = _atomicspadl.actiontypes |
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extra["type_id"] = -1 |
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extra["type_id"] = ( |
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extra.type_id.mask(out, ar.index("out")) |
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.mask(goal, ar.index("goal")) |
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.mask(owngoal, ar.index("owngoal")) |
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) |
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actions = pd.concat([actions, extra], ignore_index=True, sort=False) |
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actions = actions.sort_values(["game_id", "period_id", "action_id"]).reset_index(drop=True) |
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actions["action_id"] = range(len(actions)) |
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return actions |
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def _extra_from_fouls(actions: pd.DataFrame) -> pd.DataFrame: |
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yellow = actions.result_id == _spadl.results.index("yellow_card") |
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red = actions.result_id == _spadl.results.index("red_card") |
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prev = actions[yellow | red] |
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extra = pd.DataFrame() |
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extra["game_id"] = prev.game_id |
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extra["original_event_id"] = prev.original_event_id |
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extra["period_id"] = prev.period_id |
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extra["action_id"] = prev.action_id + 0.1 |
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extra["time_seconds"] = prev.time_seconds |
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extra["start_x"] = prev.end_x |
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extra["start_y"] = prev.end_y |
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extra["end_x"] = prev.end_x |
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extra["end_y"] = prev.end_y |
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extra["bodypart_id"] = prev.bodypart_id |
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extra["result_id"] = -1 |
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extra["team_id"] = prev.team_id |
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extra["player_id"] = prev.player_id |
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ar = _atomicspadl.actiontypes |
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extra["type_id"] = -1 |
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extra["type_id"] = extra.type_id.mask(yellow, ar.index("yellow_card")).mask( |
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red, ar.index("red_card") |
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) |
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actions = pd.concat([actions, extra], ignore_index=True, sort=False) |
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actions = actions.sort_values(["game_id", "period_id", "action_id"]).reset_index(drop=True) |
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actions["action_id"] = range(len(actions)) |
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return actions |
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def _convert_columns(actions: pd.DataFrame) -> pd.DataFrame: |
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actions["x"] = actions.start_x |
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actions["y"] = actions.start_y |
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actions["dx"] = actions.end_x - actions.start_x |
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actions["dy"] = actions.end_y - actions.start_y |
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return actions[ |
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[ |
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"game_id", |
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"original_event_id", |
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"action_id", |
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"period_id", |
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"time_seconds", |
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"team_id", |
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"player_id", |
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"x", |
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"y", |
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"dx", |
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"dy", |
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"type_id", |
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"bodypart_id", |
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] |
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] |
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def _simplify(actions: pd.DataFrame) -> pd.DataFrame: |
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a = actions |
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ar = _atomicspadl.actiontypes |
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cornerlike = ["corner_crossed", "corner_short"] |
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corner_ids = [_spadl.actiontypes.index(ty) for ty in cornerlike] |
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freekicklike = ["freekick_crossed", "freekick_short", "shot_freekick"] |
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freekick_ids = [_spadl.actiontypes.index(ty) for ty in freekicklike] |
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a["type_id"] = a.type_id.mask(a.type_id.isin(corner_ids), ar.index("corner")) |
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a["type_id"] = a.type_id.mask(a.type_id.isin(freekick_ids), ar.index("freekick")) |
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return a |
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