/
game_report.py
executable file
·198 lines (166 loc) · 6.47 KB
/
game_report.py
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#!/usr/bin/env python
import sys
import json
import numpy
import statistics
import matplotlib.pyplot
from itertools import islice, chain
from collections import defaultdict
def main():
raw = [json.loads(v) for v in sys.stdin]
constants = raw[0]
tick_time = 1.0 / constants['TICKS_PER_SECOND']
records = [fill(v, raw[1]) for v in islice(raw, 1, len(raw))]
row(
'',
*sorted('%s-%s' % (records[0]['names'][v['player_index']], v['id']) for v in records[0]['robots']),
*sorted(records[0]['names']),
'ratio',
)
report_speeds(records)
report_distances(records, tick_time)
report_radius(records)
report_hits(records)
report_rounds(records)
matplotlib.pyplot.show()
def report_speeds(records):
speeds = split_by_keys(dict(get_speeds(v)) for v in records if v['reset_ticks'] is None)
fig, ax = matplotlib.pyplot.subplots()
ax.set_title('speeds distribution')
bins = numpy.arange(0, max(max(v) for v in speeds.values()) + 1, 0.1)
for k, v in speeds.items():
ax.hist(v, bins=bins, label=k, histtype='step', linewidth=2)
ax.grid(True)
ax.legend()
ax.set_xticks(numpy.arange(0, max(max(v) for v in speeds.values()) + 1, 1.0))
names = sorted(records[0]['names'])
speeds_by_players = [statistics.mean(chain(*[w for k, w in speeds.items() if v in k])) for v in names]
row(
'mean speed',
*[statistics.mean(v) for _, v in sorted(speeds.items())],
*speeds_by_players,
speeds_by_players[0] / speeds_by_players[1]
)
def report_distances(records, tick_time):
distances = split_by_keys(get_distances(records, tick_time))
fig, ax = matplotlib.pyplot.subplots()
ax.set_title('distances')
for k, v in distances.items():
ax.plot(numpy.arange(0, len(v), 1), v, label=k, linewidth=2)
ax.set_xticks(numpy.arange(0, len(v) + 1, 1000))
for goal, player in get_goals(records):
ax.axvline(goal, color='green' if player else 'red')
ax.grid(True)
ax.legend()
names = sorted(records[0]['names'])
distances_by_players = [sum([w[-1] for k, w in distances.items() if v in k]) for v in names]
row(
'distance',
*[v[-1] for _, v in sorted(distances.items())],
*distances_by_players,
distances_by_players[0] / distances_by_players[1]
)
def report_radius(records):
radius = split_by_keys(dict(get_radius(v)) for v in records if v['reset_ticks'] is None)
fig, ax = matplotlib.pyplot.subplots()
ax.set_title('radius distribution')
for k, v in radius.items():
ax.hist(v, label=k, linewidth=2)
ax.grid(True)
ax.legend()
names = sorted(records[0]['names'])
radius_by_players = [statistics.mean(chain(*[w for k, w in radius.items() if v in k])) for v in names]
row(
'mean radius',
*[statistics.mean(v) for _, v in sorted(radius.items())],
*radius_by_players,
radius_by_players[0] / radius_by_players[1]
)
row(
'median radius',
*[statistics.mean(v) for _, v in sorted(radius.items())],
*radius_by_players,
radius_by_players[0] / radius_by_players[1]
)
def report_hits(records):
hits = split_by_keys(get_hits(records))
fig, ax = matplotlib.pyplot.subplots()
ax.set_title('hits')
for k, v in hits.items():
ax.plot(numpy.arange(0, len(v), 1), v, label=k, linewidth=2)
ax.set_xticks(numpy.arange(0, len(v) + 1, 1000))
ax.grid(True)
ax.legend()
names = sorted(records[0]['names'])
hits_by_players = [sum([w[-1] for k, w in hits.items() if v in k]) for v in names]
row(
'hits',
*['-' for _ in records[0]['robots']],
*hits_by_players,
hits_by_players[0] / hits_by_players[1]
)
def report_rounds(records):
first = True
score_0 = 0
row('initial ball.y', 'ticks', 'winner')
for record in records:
if first:
start = record
first = False
elif record['reset_ticks'] == 119:
first = True
player = record['names'][0] if score_0 < record['scores'][0] else record['names'][1]
score_0 = record['scores'][0]
row(start['ball']['position']['y'], record['current_tick'] - start['current_tick'], player)
def fill(record, first):
record['names'] = first['names']
return record
def row(*args):
print(('{:>20}' * len(args)).format(*args))
def get_goals(records):
score_0 = 0
for record in records:
if record['reset_ticks'] == 119:
yield (record['current_tick'], score_0 < record['scores'][0])
score_0 = record['scores'][0]
def get_speeds(record):
for robot in record['robots']:
velocity = numpy.array([robot['velocity']['x'], robot['velocity']['y'], robot['velocity']['z']])
speed = numpy.linalg.norm(velocity)
yield '%s-%s' % (record['names'][robot['player_index']], robot['id']), speed
def get_distances(records, tick_time):
total = defaultdict(float)
for i in range(1, len(records)):
out = dict()
prev = records[i - 1]
current = records[i]
prev_robots = sorted((v for v in prev['robots']), key=lambda v: v['id'])
current_robots = sorted((v for v in current['robots']), key=lambda v: v['id'])
for p, c in zip(prev_robots, current_robots):
key = '%s-%s' % (prev['names'][p['player_index']], p['id'])
if prev['reset_ticks'] is None and current['reset_ticks'] is None:
prev_position = numpy.array([p['position']['x'], p['position']['y'], p['position']['z']])
current_position = numpy.array([c['position']['x'], c['position']['y'], c['position']['z']])
distance = numpy.linalg.norm(current_position - prev_position) * tick_time
total[key] += distance
out[key] = total[key]
yield out
def get_radius(record):
for robot in record['robots']:
yield '%s-%s' % (record['names'][robot['player_index']], robot['id']), robot['radius']
def get_hits(records):
hits = {v: 0 for v in records[0]['names']}
for record in records:
hits = {k: v for k, v in hits.items()}
for hit in record['hits']:
if hit['player_index'] is not None:
hits[record['names'][hit['player_index']]] += 1
yield hits
def split_by_keys(values):
result = defaultdict(list)
for value in values:
for k, v in value.items():
result[k].append(v)
return result
if __name__ == '__main__':
main()