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Docs for boost.py #248

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Docs for boost.py #248

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08646a3
Remove examples from README.md
DivvyCr May 5, 2020
e346c87
Update examples.
DivvyCr May 5, 2020
0fdc233
Update README.md.
DivvyCr May 5, 2020
d3b3216
Improve documentation and readability for boost.py stat.
DivvyCr Jul 22, 2020
3a660aa
Syntax fixes + Type clarifications
DivvyCr Jul 22, 2020
aaa8052
Merge branch 'master' into documentation
DivvyCr Jul 23, 2020
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106 changes: 69 additions & 37 deletions carball/analysis/stats/boost/boost.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,50 +27,20 @@ def calculate_player_stat(self, player_stat_map: Dict[str, PlayerStats], game: G
player_name = player_map[player_key].name
player_data_frame = data_frame[player_name].copy()
player_data_frame.loc[:, 'delta'] = data_frame['game'].delta

proto_boost.boost_usage = self.get_player_boost_usage(player_data_frame)

proto_boost.wasted_usage = self.get_player_boost_usage_max_speed(player_data_frame)

proto_boost.time_full_boost = self.get_time_with_max_boost(data_frame, player_data_frame)
proto_boost.time_low_boost = self.get_time_with_low_boost(data_frame, player_data_frame)
proto_boost.time_no_boost = self.get_time_with_zero_boost(data_frame, player_data_frame)
proto_boost.average_boost_level = self.get_average_boost_level(player_data_frame)

if 'boost_collect' not in player_data_frame:
logger.warning('%s did not collect any boost', player_key)
else:
gains_index = player_data_frame['boost'].diff().clip(0)
gains_index = gains_index.loc[gains_index > 0].index.to_numpy()
collect_frames = player_data_frame.loc[player_data_frame.index[player_data_frame['boost_collect'] > 34]]
# Have to loop to fuzzy match
wasted_big = 0
for index in collect_frames.index.to_numpy():
idx = gains_index[(np.abs(gains_index - index).argmin())]
int_idx = player_data_frame.index.get_loc(idx)
wasted_big += player_data_frame['boost'].iloc[int_idx - 1] / 256 * 100

collect_frames = player_data_frame.loc[player_data_frame.index[player_data_frame['boost_collect'] <= 34]]
prior_vals = np.empty([0])
for index in collect_frames.index.to_numpy():
idx = gains_index[(np.abs(gains_index - index).argmin())]
int_idx = player_data_frame.index.get_loc(idx)
val = player_data_frame['boost'].iloc[int_idx-1]
prior_vals = np.append(prior_vals, val)
deltas = ((prior_vals + 30.6) - 255)
wasted_small = deltas[deltas > 0].sum() / 256 * 100

collection = self.get_player_boost_collection(player_data_frame)
proto_boost.wasted_collection = wasted_big + wasted_small
proto_boost.wasted_big = wasted_big
proto_boost.wasted_small = wasted_small

if 'small' in collection and collection['small'] is not None:
proto_boost.num_small_boosts = collection['small']
if 'big' in collection and collection['big'] is not None:
proto_boost.num_large_boosts = collection['big']

proto_boost.num_stolen_boosts = self.get_num_stolen_boosts(player_data_frame,
player_map[player_key].is_orange)
self.calculate_and_set_player_wasted_collection(player_data_frame, proto_boost)
self.count_and_set_pad_collection(player_data_frame, proto_boost)
self.count_and_set_stolen_boosts(player_data_frame, player_map[player_key].is_orange, proto_boost)

@staticmethod
def get_player_boost_usage(player_dataframe: pd.DataFrame) -> np.float64:
Expand All @@ -84,7 +54,7 @@ def get_average_boost_level(player_dataframe: pd.DataFrame) -> np.float64:
return player_dataframe.boost.mean(skipna=True) / 255 * 100

@classmethod
def get_num_stolen_boosts(cls, player_dataframe: pd.DataFrame, is_orange):
def count_and_set_stolen_boosts(cls, player_dataframe: pd.DataFrame, is_orange, proto_boost):
big = cls.field_constants.get_big_pads()
# Get big pads below or above 0 depending on team
# The index of y position is 1. The index of the label is 2.
Expand All @@ -94,7 +64,7 @@ def get_num_stolen_boosts(cls, player_dataframe: pd.DataFrame, is_orange):
opponent_pad_labels = big[big[:, 1] > 0][:, 2] #big[where[y] is > 0][labels]
# Count all the places where isin = True by summing
stolen = player_dataframe.boost_collect.isin(opponent_pad_labels).sum()
return stolen
proto_boost.num_stolen_boosts = stolen

@staticmethod
def get_player_boost_usage_max_speed(player_dataframe: pd.DataFrame) -> np.float64:
Expand Down Expand Up @@ -138,3 +108,65 @@ def get_player_boost_collection(player_dataframe: pd.DataFrame) -> Dict[str, int
except (AttributeError, KeyError):
return {}
return ret

# NEW (DivvyC)

@staticmethod
def get_wasted_big(gains_index: np.ndarray, player_data_frame: pd.DataFrame):
# Get all frames (by their index) where the player collected more than 34 boost.
collect_frames = player_data_frame.loc[player_data_frame.index[player_data_frame['boost_collect'] > 34]]

# Have to loop to fuzzy match
wasted_big = 0
for index in collect_frames.index.to_numpy():
idx = gains_index[(np.abs(gains_index - index).argmin())]
int_idx = player_data_frame.index.get_loc(idx)
wasted_big += player_data_frame['boost'].iloc[int_idx - 1] / 256 * 100
return wasted_big

@staticmethod
def get_wasted_small(gains_index: np.ndarray, player_data_frame: pd.DataFrame):
# Now, get all frames (by their index) where the player collected less than 34 boost.
collect_frames = player_data_frame.loc[player_data_frame.index[player_data_frame['boost_collect'] <= 34]]

prior_vals = np.empty([0])
for index in collect_frames.index.to_numpy():
idx = gains_index[(np.abs(gains_index - index).argmin())]
int_idx = player_data_frame.index.get_loc(idx)
val = player_data_frame['boost'].iloc[int_idx-1]
prior_vals = np.append(prior_vals, val)
deltas = ((prior_vals + 30.6) - 255)
wasted_small = deltas[deltas > 0].sum() / 256 * 100
return wasted_small

@staticmethod
def get_gains_index(player_data_frame: pd.DataFrame):
# Get differences in boost (on a frame-by-frame basis), and only keep entries that are >= 0.
gains_index = player_data_frame['boost'].diff().clip(0)
# Get all frame indexes with non-zero values (i.e. boost gain), as a numpy array.
gains_index = gains_index.loc[gains_index > 0].index.to_numpy()
return gains_index

@staticmethod
def calculate_and_set_player_wasted_collection(player_data_frame: pd.DataFrame, proto_boost):
# Get gains_index, which returns a numpy array of all indexes where the player gained (collected) boost.
gains_index = BoostStat.get_gains_index(player_data_frame)

# Get wasted_big, and set it to the appropriate API field.
wasted_big = BoostStat.get_wasted_big(gains_index, player_data_frame)
proto_boost.wasted_big = wasted_big

# Get wasted_small, and set it to the appropriate API field.
wasted_small = BoostStat.get_wasted_small(gains_index, player_data_frame)
proto_boost.wasted_small = wasted_small

# Add wasted_small/big to get wasted_collection, and set it to the appropriate API field.
proto_boost.wasted_collection = wasted_big + wasted_small

@staticmethod
def count_and_set_pad_collection(player_data_frame: pd.DataFrame, proto_boost):
collection = BoostStat.get_player_boost_collection(player_data_frame)
if 'small' in collection and collection['small'] is not None:
proto_boost.num_small_boosts = collection['small']
if 'big' in collection and collection['big'] is not None:
proto_boost.num_large_boosts = collection['big']