# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. | |
# | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, | |
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
# See the License for the specific language governing permissions and | |
# limitations under the License. | |
# TODO: Address all TODOs and remove all explanatory comments | |
"""This is tracking data of the 2015-2016 NBA season""" | |
import csv | |
import json | |
import os | |
import py7zr | |
import datasets | |
import requests | |
_CITATION = """\ | |
@misc{Linou2016, | |
title = {NBA-Player-Movements}, | |
author={Kostya Linou}, | |
publisher={SportVU}, | |
year={2016} | |
""" | |
_DESCRIPTION = """\ | |
This dataset is designed to give further easy access to tracking data. | |
By merging all .7z files into one large .json file, access is easier to retrieve all information at once. | |
""" | |
_HOMEPAGE = "https://github.com/linouk23/NBA-Player-Movements/tree/master/" | |
_URL = "https://github.com/linouk23/NBA-Player-Movements/raw/master/data/2016.NBA.Raw.SportVU.Game.Logs" | |
res = requests.get(_URL) | |
items = res.json()['payload']['tree']['items'] | |
# trying subset of games | |
_URLS = {} | |
for game in items[0:20]: | |
name = game['name'][:-3] | |
_URLS[name] = _URL + "/" + name + ".7z" | |
class NbaTracking(datasets.GeneratorBasedBuilder): | |
"""Tracking data for all games of 2015-2016 season in forms of coordinates for players and ball at each moment.""" | |
_URLS = _URLS | |
def _info(self): | |
features = datasets.Features( | |
{ | |
"gameid": datasets.Value("string"), | |
"gamedate": datasets.Value("string"), | |
# question: how to indicate list of dictionaries? | |
"events": datasets.Sequence( | |
{ | |
"eventid": datasets.Value("string"), | |
# "visitor": { | |
# "name": datasets.Value("string"), | |
# "teamid": datasets.Value("int64"), | |
# "abbreviation": datasets.Value("string"), | |
# "players": datasets.Sequence({ | |
# "lastname": datasets.Value("string"), | |
# "firstname": datasets.Value("string"), | |
# "playerid": datasets.Value("int64"), | |
# "jersey": datasets.Value("string"), | |
# "position": datasets.Value("string") | |
# }) | |
# }, | |
# "home": { | |
# "name": datasets.Value("string"), | |
# "teamid": datasets.Value("int64"), | |
# "abbreviation": datasets.Value("string"), | |
# "players": datasets.Sequence({ | |
# "lastname": datasets.Value("string"), | |
# "firstname": datasets.Value("string"), | |
# "playerid": datasets.Value("int64"), | |
# "jersey": datasets.Value("string"), | |
# "position": datasets.Value("string") | |
# }) | |
# }, | |
"moments": datasets.Sequence( | |
# question, how to indicate lists of lists of different types | |
{ | |
"quarter": datasets.Value("int64"), | |
"game_clock": datasets.Value("float32"), | |
"shot_clock": datasets.Value("float32"), | |
"ball_coordinates": datasets.Sequence( | |
datasets.Value("float32"), | |
datasets.Value("float32"), | |
datasets.Value("float32") | |
), | |
"player_coordinates": datasets.Sequence( | |
{ | |
"teamid": datasets.Value("int64"), | |
"playerid": datasets.Value("int64"), | |
"x": datasets.Value("float32"), | |
"y": datasets.Value("float32"), | |
"z": datasets.Value("float32") | |
} | |
) | |
} | |
# datasets.Sequence( | |
# datasets.Value("int64"), | |
# datasets.Value("float32"), | |
# datasets.Value("float32"), | |
# datasets.Value("float32"), | |
# datasets.Value("null"), | |
# datasets.Sequence( | |
# datasets.Sequence( | |
# datasets.Value("int64"), | |
# datasets.Value("int64"), | |
# datasets.Value("float32"), | |
# datasets.Value("float32"), | |
# datasets.Value("float32") | |
# ) | |
# ) | |
# ) | |
) | |
} | |
) | |
} | |
) | |
return datasets.DatasetInfo( | |
# This is the description that will appear on the datasets page. | |
description=_DESCRIPTION, | |
# This defines the different columns of the dataset and their types | |
features=features, # Here we define them above because they are different between the two configurations | |
# If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and | |
# specify them. They'll be used if as_supervised=True in builder.as_dataset. | |
# supervised_keys=("sentence", "label"), | |
# Homepage of the dataset for documentation | |
homepage=_HOMEPAGE, | |
# Citation for the dataset | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
# TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration | |
# dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS | |
# It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files. | |
# By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive | |
# urls = _URLS[self.config.name] | |
urls = self._URLS # trying Ouwen's format | |
data_dir = dl_manager.download_and_extract(urls) | |
all_file_paths = {} | |
for key, directory_path in data_dir.items(): | |
all_file_paths[key] = os.path.join(directory_path, os.listdir(directory_path)[0]) | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
# These kwargs will be passed to _generate_examples | |
gen_kwargs={ | |
"filepaths": all_file_paths, | |
"split": "train", | |
} | |
) | |
] | |
# method parameters are unpacked from `gen_kwargs` as given in `_split_generators` | |
def _generate_examples(self, filepaths, split): | |
# TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset. | |
# The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example. | |
for game_title, link in filepaths.items(): | |
with open(link, encoding="utf-8") as fp: | |
game = json.load(fp) | |
game_id = game["gameid"] | |
game_date = game["gamedate"] | |
for event in game["events"]: | |
event_id = event["eventId"] | |
for moment in event["moments"]: | |
for element in moment: | |
quarter = element[0] | |
game_clock = element[2] | |
shot_clock = element[3] | |
ball_coords = element[5][0][2:] | |
for position in element[5][1:]: | |
team_id = position[0] | |
player_id = position[1] | |
x = position[2] | |
y = position[3] | |
z = position[4] | |
yield game_id, { | |
"gameid": game_id, | |
"gamedate": game_date, | |
"events": { | |
"eventid": event_id, | |
"moments": { | |
"quarter": quarter, | |
"game_clock": game_clock, | |
"shot_clock": shot_clock, | |
"ball_coordinates": ball_coords, | |
"player_coordinates": { | |
"teamid": team_id, | |
"playerid": player_id, | |
"x": x, | |
"y": y, | |
"z": z | |
} | |
} | |
} | |
} | |
# for key, row in enumerate(fp): | |
# data = json.load(row) | |
# # Yields examples as (key, example) tuples | |
# yield key, { | |
# } | |