def parse_team_stats(self, homeaway='home'):
# Parse each team's stats, relative to a single game
team_stats = {}
batting = self.boxscore.find('batting', team_flag=homeaway)
pitching = self.boxscore.find('pitching', team_flag=homeaway)
team_stats['game_id'] = self.game_id
team_stats['team_id'] = try_int(self.boxscore.get(homeaway + '_id'))
team_stats['at_home'] = (homeaway == 'home')
games_back_text = self.linescore.get(homeaway + '_games_back')
games_back_wildcard_text = self.linescore.get(homeaway + '_games_back')
# If a team is 0 games back, they'll be listed as '-'. The
# games_back_wildcard is sometimes '-', sometimes missing in this case.
# If they're 0 games back, set both to 0
if games_back_text == '-':
team_stats['games_back'] = 0
team_stats['games_back_wildcard'] = 0
elif games_back_wildcard_text == '-':
team_stats['games_back_wildcard'] = 0
team_stats['games_back'] = try_float(games_back_text)
else:
team_stats['games_back'] = try_float(games_back_text)
team_stats['games_back_wildcard'] = try_float(
games_back_wildcard_text)
wins = try_int(self.boxscore.get(homeaway + '_wins', 0))
losses = try_int(self.boxscore.get(homeaway + '_loss', 0))
team_stats['wins'] = wins
team_stats['losses'] = losses
team_stats['winrate'] = 0 if (wins +
losses) == 0 else wins / (wins + losses)
team_stats['avg'] = try_float(batting.get('avg'))
team_stats['at_bats'] = try_int(batting.get('ab'))
team_stats['runs'] = try_int(batting.get('r'))
team_stats['hits'] = try_int(batting.get('h'))
team_stats['doubles'] = try_int(batting.get('d'))
team_stats['triples'] = try_int(batting.get('t'))
team_stats['home_runs'] = try_int(batting.get('hr'))
team_stats['rbis'] = try_int(batting.get('rbi'))
team_stats['walks'] = try_int(batting.get('bb'))
team_stats['putouts'] = try_int(batting.get('po'))
team_stats['da'] = try_int(batting.get('da'))
team_stats['strikeouts'] = try_int(batting.get('so'))
team_stats['left_on_base'] = try_int(batting.get('lob'))
team_stats['era'] = try_float(pitching.get('era'))
# Drop None values and add TeamStats object to the to_load list
team_stats = dict(
(k, v) for k, v in team_stats.items() if v is not None)
self.to_load.append(TeamStats(**team_stats))
def parse_team_stats(self, homeaway='home'):
# Parse each team's stats, relative to a single game
team_stats = {}
batting = self.boxscore.find('batting', team_flag=homeaway)
pitching = self.boxscore.find('pitching', team_flag=homeaway)
team_stats['game_id'] = self.game_id
team_stats['team_id'] = try_int(self.boxscore.get(homeaway + '_id'))
team_stats['at_home'] = (homeaway == 'home')
games_back_text = self.linescore.get(homeaway + '_games_back')
games_back_wildcard_text = self.linescore.get(homeaway + '_games_back')
# If a team is 0 games back, they'll be listed as '-'. The
# games_back_wildcard is sometimes '-', sometimes missing in this case.
# If they're 0 games back, set both to 0
if games_back_text == '-':
team_stats['games_back'] = 0
team_stats['games_back_wildcard'] = 0
elif games_back_wildcard_text == '-':
team_stats['games_back_wildcard'] = 0
team_stats['games_back'] = try_float(games_back_text)
else:
team_stats['games_back'] = try_float(games_back_text)
team_stats['games_back_wildcard'] = try_float(games_back_wildcard_text)
wins = try_int(self.boxscore.get(homeaway + '_wins', 0))
losses = try_int(self.boxscore.get(homeaway + '_loss', 0))
team_stats['wins'] = wins
team_stats['losses'] = losses
team_stats['winrate'] = 0 if (wins + losses) == 0 else wins / (wins + losses)
team_stats['avg'] = try_float(batting.get('avg'))
team_stats['at_bats'] = try_int(batting.get('ab'))
team_stats['runs'] = try_int(batting.get('r'))
team_stats['hits'] = try_int(batting.get('h'))
team_stats['doubles'] = try_int(batting.get('d'))
team_stats['triples'] = try_int(batting.get('t'))
team_stats['home_runs'] = try_int(batting.get('hr'))
team_stats['rbis'] = try_int(batting.get('rbi'))
team_stats['walks'] = try_int(batting.get('bb'))
team_stats['putouts'] = try_int(batting.get('po'))
team_stats['da'] = try_int(batting.get('da'))
team_stats['strikeouts'] = try_int(batting.get('so'))
team_stats['left_on_base'] = try_int(batting.get('lob'))
team_stats['era'] = try_float(pitching.get('era'))
# Drop None values and add TeamStats object to the to_load list
team_stats = dict((k, v) for k, v in team_stats.items() if v is not None)
self.to_load.append(TeamStats(**team_stats))
def parse_batters(self):
# Parses batter statistics and adds all batters to the to_load list
for batter in self.boxscore.find_all('batter'):
b = {}
b['game_id'] = self.game_id
homeaway = batter.parent.get('team_flag')
b['team_id'] = try_int(self.boxscore.get(homeaway + '_id'))
b['batter_id'] = try_int(batter.get('id'))
b['name'] = batter.get('name')
b['full_name'] = batter.get('name_display_first_last')
b['avg'] = try_float(batter.get('avg'))
b['batting_order'] = try_int(batter.get('bo'))
b['at_bats'] = try_int(batter.get('ab'))
b['strikeouts'] = try_int(batter.get('so'))
b['flyouts'] = try_int(batter.get('ao'))
b['hits'] = try_int(batter.get('h'))
b['doubles'] = try_int(batter.get('d'))
b['triples'] = try_int(batter.get('t'))
b['home_runs'] = try_int(batter.get('hr'))
b['walks'] = try_int(batter.get('bb'))
b['hit_by_pitch'] = try_int(batter.get('hbp'))
b['sac_bunts'] = try_int(batter.get('sac'))
b['sac_flys'] = try_int(batter.get('fs'))
b['rbi'] = try_int(batter.get('rbi'))
b['assists'] = try_int(batter.get('a'))
b['runs'] = try_int(batter.get('r'))
b['left_on_base'] = try_int(batter.get('lob'))
b['caught_stealing'] = try_int(batter.get('cs'))
b['stolen_bases'] = try_int(batter.get('sb'))
b['season_walks'] = try_int(batter.get('s_bb'))
b['season_hits'] = try_int(batter.get('s_h'))
b['season_home_runs'] = try_int(batter.get('s_hr'))
b['season_runs'] = try_int(batter.get('s_r'))
b['season_rbi'] = try_int(batter.get('s_rbi'))
b['season_strikeouts'] = try_int(batter.get('s_so'))
b['position'] = batter.get('pos')
b['putouts'] = try_int(batter.get('po'))
b['errors'] = try_int(batter.get('e'))
b['fielding'] = try_float(batter.get('fldg'))
# Drop None values and add to to_load list
b = dict((k, v) for k, v in b.items() if v is not None)
self.to_load.append(Batter(**b))
def parse_batters(self):
# Parses batter statistics and adds all batters to the to_load list
for batter in self.boxscore.find_all('batter'):
b = {}
b['game_id'] = self.game_id
homeaway = batter.parent.get('team_flag')
b['team_id'] = try_int(self.boxscore.get(homeaway + '_id'))
b['batter_id'] = try_int(batter.get('id'))
b['name'] = batter.get('name')
b['full_name'] = batter.get('name_display_first_last')
b['avg'] = try_float(batter.get('avg'))
b['batting_order'] = try_int(batter.get('bo'))
b['at_bats'] = try_int(batter.get('ab'))
b['strikeouts'] = try_int(batter.get('so'))
b['flyouts'] = try_int(batter.get('ao'))
b['hits'] = try_int(batter.get('h'))
b['doubles'] = try_int(batter.get('d'))
b['triples'] = try_int(batter.get('t'))
b['home_runs'] = try_int(batter.get('hr'))
b['walks'] = try_int(batter.get('bb'))
b['hit_by_pitch'] = try_int(batter.get('hbp'))
b['sac_bunts'] = try_int(batter.get('sac'))
b['sac_flys'] = try_int(batter.get('fs'))
b['rbi'] = try_int(batter.get('rbi'))
b['assists'] = try_int(batter.get('a'))
b['runs'] = try_int(batter.get('r'))
b['left_on_base'] = try_int(batter.get('lob'))
b['caught_stealing'] = try_int(batter.get('cs'))
b['stolen_bases'] = try_int(batter.get('sb'))
b['season_walks'] = try_int(batter.get('s_bb'))
b['season_hits'] = try_int(batter.get('s_h'))
b['season_home_runs'] = try_int(batter.get('s_hr'))
b['season_runs'] = try_int(batter.get('s_r'))
b['season_rbi'] = try_int(batter.get('s_rbi'))
b['season_strikeouts'] = try_int(batter.get('s_so'))
b['position'] = batter.get('pos')
b['putouts'] = try_int(batter.get('po'))
b['errors'] = try_int(batter.get('e'))
b['fielding'] = try_float(batter.get('fldg'))
# Drop None values and add to to_load list
b = dict((k, v) for k, v in b.items() if v is not None)
self.to_load.append(Batter(**b))
def _count_vocab(self, raw_documents, fixed_vocab):
"""Create sparse feature matrix, and vocabulary where fixed_vocab=False
"""
if fixed_vocab:
vocabulary = self.vocabulary_
else:
# Add a new value when a new vocabulary item is seen
vocabulary = defaultdict()
vocabulary.default_factory = vocabulary.__len__
analyze = self.build_analyzer()
j_indices = []
indptr = _make_int_array()
values = _make_float_array()
indptr.append(0)
for doc in raw_documents:
feature_counter = {}
current_num = 0
for feature in analyze(doc):
maybe_float = try_float(feature)
if maybe_float > 0 and maybe_float <= 200:
current_num = maybe_float
continue
try:
if current_num == 0:
continue
feature_idx = vocabulary[feature]
if feature_idx not in feature_counter:
feature_counter[feature_idx] = current_num / 200
current_num = 0
except KeyError:
# Ignore out-of-vocabulary items for fixed_vocab=True
continue
j_indices.extend(feature_counter.keys())
values.extend(feature_counter.values())
indptr.append(len(j_indices))
if not fixed_vocab:
# disable defaultdict behaviour
vocabulary = dict(vocabulary)
if not vocabulary:
raise ValueError("empty vocabulary; perhaps the documents only"
" contain stop words")
j_indices = np.asarray(j_indices, dtype=np.intc)
indptr = np.frombuffer(indptr, dtype=np.intc)
values = np.frombuffer(values, dtype=np.float32)
X = sp.csr_matrix((values, j_indices, indptr),
shape=(len(indptr) - 1, len(vocabulary)),
dtype=np.float32)
X.sort_indices()
return vocabulary, X
def parse_pitchers(self):
# Parses pitcher statistics and adds all pitchers to the to_load list
for pitcher in self.boxscore.find_all('pitcher'):
p = {}
p['pitcher_id'] = try_int(pitcher.get('id'))
p['game_id'] = self.game_id
homeaway = pitcher.parent.get('team_flag')
p['team_id'] = try_int(self.boxscore.get(homeaway + '_id'))
p['name'] = pitcher.get('name')
p['full_name'] = pitcher.get('name_display_first_last')
p['position'] = pitcher.get('pos')
p['outs'] = try_int(pitcher.get('out'))
p['batters_faced'] = try_int(pitcher.get('bf'))
p['home_runs'] = try_int(pitcher.get('hr'))
p['walks'] = try_int(pitcher.get('bb'))
p['strikeouts'] = try_int(pitcher.get('so'))
p['earned_runs'] = try_int(pitcher.get('er'))
p['runs'] = try_int(pitcher.get('r'))
p['hits'] = try_int(pitcher.get('h'))
p['wins'] = try_int(pitcher.get('w'))
p['losses'] = try_int(pitcher.get('l'))
p['saves'] = try_int(pitcher.get('sv'))
p['era'] = try_float(pitcher.get('era'))
p['pitches_thrown'] = try_int(pitcher.get('np'))
p['strikes'] = try_int(pitcher.get('s'))
p['blown_saves'] = try_int(pitcher.get('bs'))
p['holds'] = try_int(pitcher.get('hld'))
p['season_innings_pitched'] = try_float(pitcher.get('s_ip'))
p['season_hits'] = try_int(pitcher.get('s_h'))
p['season_runs'] = try_int(pitcher.get('s_r'))
p['season_earned_runs'] = try_int(pitcher.get('s_er'))
p['season_walks'] = try_int(pitcher.get('s_bb'))
p['season_strikeouts'] = try_int(pitcher.get('s_so'))
p['game_score'] = try_int(pitcher.get('game_score'))
p['blown_save'] = pitcher.get('blown_save')
p['save'] = pitcher.get('save')
p['loss'] = pitcher.get('loss')
p['win'] = pitcher.get('win')
# Drop None values and add to the to_load list
p = dict((k, v) for k, v in p.items() if v is not None)
self.to_load.append(Pitcher(**p))
def parse_pitchers(self):
# Parses pitcher statistics and adds all pitchers to the to_load list
for pitcher in self.boxscore.find_all('pitcher'):
p = {}
p['pitcher_id'] = try_int(pitcher.get('id'))
p['game_id'] = self.game_id
homeaway = pitcher.parent.get('team_flag')
p['team_id'] = try_int(self.boxscore.get(homeaway + '_id'))
p['name'] = pitcher.get('name')
p['full_name'] = pitcher.get('name_display_first_last')
p['position'] = pitcher.get('pos')
p['outs'] = try_int(pitcher.get('out'))
p['batters_faced'] = try_int(pitcher.get('bf'))
p['home_runs'] = try_int(pitcher.get('hr'))
p['walks'] = try_int(pitcher.get('bb'))
p['strikeouts'] = try_int(pitcher.get('so'))
p['earned_runs'] = try_int(pitcher.get('er'))
p['runs'] = try_int(pitcher.get('r'))
p['hits'] = try_int(pitcher.get('h'))
p['wins'] = try_int(pitcher.get('w'))
p['losses'] = try_int(pitcher.get('l'))
p['saves'] = try_int(pitcher.get('sv'))
p['era'] = try_float(pitcher.get('era'))
p['pitches_thrown'] = try_int(pitcher.get('np'))
p['strikes'] = try_int(pitcher.get('s'))
p['blown_saves'] = try_int(pitcher.get('bs'))
p['holds'] = try_int(pitcher.get('hld'))
p['season_innings_pitched'] = try_float(pitcher.get('s_ip'))
p['season_hits'] = try_int(pitcher.get('s_h'))
p['season_runs'] = try_int(pitcher.get('s_r'))
p['season_earned_runs'] = try_int(pitcher.get('s_er'))
p['season_walks'] = try_int(pitcher.get('s_bb'))
p['season_strikeouts'] = try_int(pitcher.get('s_so'))
p['game_score'] = try_int(pitcher.get('game_score'))
p['blown_save'] = pitcher.get('blown_save')
p['save'] = pitcher.get('save')
p['loss'] = pitcher.get('loss')
p['win'] = pitcher.get('win')
# Drop None values and add to the to_load list
p = dict((k, v) for k, v in p.items() if v is not None)
self.to_load.append(Pitcher(**p))
def _parse_ppm(page):
msg_list = [r'returned an error: (.*)$', r'(Too many residues)']
for msg in msg_list:
error = re.findall(msg, page)
if error:
with open("ppm_error.txt", "w") as fp:
fp.write(error[0])
raise Exception(error[0])
pdb_url = PPM_URL + re.findall(r'href="\./(pdb_upload/.*out\.pdb)"',
page)[0]
delta_g = re.findall(r'([-+]?[0-9]*\.?[0-9]+) kcal/mol', page)[0]
info_dict = {"delta_g": try_float(delta_g)}
return pdb_url, info_dict
def load_page(self, url):
"""
Loads URL to json
:param url:
:return:
"""
auth = None
if 'github_token' in self.state and 'github_user' in self.state:
auth = HTTPBasicAuth(self.state['github_user'], self.state['github_token'])
for attempt in range(self.attempts):
if self.terminate:
raise Exception('Terminating')
try:
res = requests.get(url, timeout=10, auth=auth)
headers = res.headers
if res.status_code == 404:
logger.warning('URL not found: %s' % url)
return None, None, None
self.rate_limit_reset = utils.try_float(headers.get('X-RateLimit-Reset')) + 10
self.rate_limit_remaining = utils.try_int(headers.get('X-RateLimit-Remaining'))
if self.rate_limit_remaining is not None and self.rate_limit_remaining <= 1:
sleep_sec = self.rate_limit_reset - time.time()
logger.info('Rate limit exceeded, sleeping till: %d, it is %d seconds, %d minutes'
% (self.rate_limit_reset, sleep_sec, sleep_sec / 60.0))
self.sleep_interruptible(self.rate_limit_reset)
raise Exception('Rate limit exceeded')
if res.status_code // 100 != 2:
res.raise_for_status()
data = res.content
if data is None:
raise Exception('Empty response')
js = json.loads(data, object_pairs_hook=OrderedDict)
return js, headers, res
except Exception as e:
logger.warning('Exception in loading page: %s, page: %s' % (e, url))
logger.warning('Skipping url: %s' % url)
return None, None, None
def load_page_local(self):
"""
Loads page stored in thread local
:return:
"""
auth = None
resource = self.local_data.resource
if resource.usr is not None:
auth = HTTPBasicAuth(resource.usr, resource.token)
job = self.local_data.job
res = requests.get(job.url, timeout=10, auth=auth)
headers = res.headers
resource.reset_time = utils.try_float(headers.get('X-RateLimit-Reset'))
resource.remaining = utils.try_int(
headers.get('X-RateLimit-Remaining'))
resource.last_used = time.time()
resource.used_cnt += 1
if res.status_code == 403 and resource.remaining is not None and resource.remaining < 10:
resource.fail_cnt += 1
raise RateLimitHit
if res.status_code == 404:
resource.fail_cnt += 1
logger.warning('URL not found: %s' % job.url)
return None, None, None
if res.status_code // 100 != 2:
resource.fail_cnt += 1
res.raise_for_status()
data = res.content
if data is None:
resource.fail_cnt += 1
raise Exception('Empty response')
js = json.loads(data, object_pairs_hook=OrderedDict)
return js, headers, res
def _parse_opm_info(page):
# check if there were no matches
no_matches = re.findall(r'<h2>Search Results for ".*"</h2>No matches',
page)
if no_matches:
return None
# check if this page only points to a representative structure
rep = re.findall(
r'Representative structure\(s\) of this protein: <br /> '
r'<a href="protein\.php\?pdbid=([0-9a-zA-Z]{4})">', page)
if rep:
return {"representative": rep[0].upper()}
opm_type = re.findall(r'<li><i>Type:</i> <a.*>(.*)</a>', page)
opm_class = re.findall(r'<li><i>Class:</i> <a.*>(.*)</a>', page)
opm_superfamily = re.findall(
r'<li><i>Superfamily:</i> <a[^<]*>([^<]*)</a>', page)
opm_family = re.findall(r'<li><i>Family:</i> <a[^<]*>([^<]*)</a>', page)
opm_species = re.findall(r'<li><i>Species:</i> <i><a.*>(.*)</a></i>', page)
opm_localization = re.findall(r'<li><i>Localization:</i> <a.*>(.*)</a>',
page)
related_ids = re.findall(r'"\?extrapdb=([0-9a-zA-Z]{4})"', page)
related_ids = [x.upper() for x in related_ids]
related_ids.sort()
delta_g = re.findall(r'([-+]?[0-9]*\.?[0-9]+) kcal/mol', page)
return {
"type": opm_type[0].split(" ", 1)[1],
"class": opm_class[0].split(" ", 1)[1],
"superfamily": opm_superfamily[0].split(" ", 1)[1],
"family": opm_family[0].split(" ", 1)[1],
"species": opm_species[0].strip(),
"localization": opm_localization[0],
"related_ids": related_ids,
"delta_g": try_float(get_index(delta_g, 0))
}
def transform(self, X):
keys = {
"1", "2", "3", "4", "5", "7", "8", "9", "a", "as", "at", "b",
"bars", "beautiful", "boots", "bottles", "bowls", "box", "boxes",
"brand", "bras", "bucks", "cans", "card", "cards", "case", "cm",
"comes", "compartments", "controllers", "cream", "credit", "crop",
"dd", "dollar", "dollars", "dolls", "dress", "dvds", "each",
"edition", "euc", "fashion", "feet", "fits", "fl", "ft", "g",
"games", "gb", "gms", "gold", "gram", "grams", "hr", "hrs", "in",
"inch", "inches", "k", "karat", "layers", "up", "meter", "mil",
"mini", "mint", "ml", "mm", "month", "mugs", "no", "not", "nwt",
"off", "onesies", "opi", "ounce", "ounces", "outfits", "oz",
"packages", "packets", "packs", "pair", "panels", "pants",
"patches", "pc", "pics", "piece", "pieces", "pokémon", "pokemon",
"pounds", "price", "protection", "random", "retro", "ring",
"rings", "rolls", "samples", "sandals", "series", "sets", "sheets",
"shirts", "shoe", "shoes", "shows", "slots", "small", "so", "some",
"stamped", "sterling", "stickers", "still", "stretch", "strips",
"summer", "t", "tags", "tiny", "tone", "tubes", "victoria",
"vinyl", "w", "waist", "waistband", "waterproof", "watt", "white",
"wireless", "x10", "x13", "x15", "x3", "x4", "x5", "x6", "x7",
"x8", "x9", "yrs", "½", "lipsticks", "bar", "apple", "access",
"wax", "monster", "spell", "spinners", "lunch", "ac", "jamberry",
"medal", "gerard"
}
regex = re.compile("(\d+)[ ]?(\w+)", re.IGNORECASE)
specifics = []
for x in X:
spec = {}
for val, key in regex.findall(str(x), re.IGNORECASE):
if key in keys:
val = try_float(val)
if val > 3000:
continue
spec[key] = val
spec['{}_{}'.format(key, val)] = 1
specifics.append(spec)
return specifics
def parse_pitches(self):
# Parse every pitch in all innings, adding them to the to_load list.
pitch_counter = count()
for pitch in self.innings.find_all('pitch'):
# Some years are missing pitch_ids. Since we're using it as a key,
# assign here and increment the counter
p = {}
p['game_id'] = self.game_id
p['pitch_id'] = int(pitch.get('id', next(pitch_counter)))
p['at_bat_number'] = try_int(pitch.parent.get('num'))
p['description'] = pitch.get('des')
p['type'] = pitch.get('type')
try:
t = dateutil.parser.parse(pitch.get('tfs_zulu', ''))
p['timestamp'] = t.astimezone(timezone('America/New_York'))
except ValueError:
logging.warning('Could not parse timestamp: Game {}; pitch {}'.format(
self.game_id, p['pitch_id']))
p['x'] = try_float(pitch.get('x'))
p['y'] = try_float(pitch.get('y'))
p['event_num'] = try_int(pitch.get('event_num'))
p['sv_id'] = pitch.get('sv_id')
p['play_guid'] = pitch.get('play_guid')
p['start_speed'] = try_float(pitch.get('start_speed'))
p['end_speed'] = try_float(pitch.get('end_speed'))
p['sz_top'] = try_float(pitch.get('sz_top'))
p['sz_bottom'] = try_float(pitch.get('sz_bot'))
p['pfx_x'] = try_float(pitch.get('pfx_x'))
p['pfx_z'] = try_float(pitch.get('pfx_z'))
p['x0'] = try_float(pitch.get('x0'))
p['y0'] = try_float(pitch.get('y0'))
p['z0'] = try_float(pitch.get('z0'))
p['vx0'] = try_float(pitch.get('vx0'))
p['vy0'] = try_float(pitch.get('vy0'))
p['vz0'] = try_float(pitch.get('vz0'))
p['ax'] = try_float(pitch.get('ax'))
p['ay'] = try_float(pitch.get('ay'))
p['az'] = try_float(pitch.get('az'))
p['break_y'] = try_float(pitch.get('break_y'))
p['break_angle'] = try_float(pitch.get('break_angle'))
p['break_length'] = try_float(pitch.get('break_length'))
p['pitch_type'] = pitch.get('pitch_type')
p['type_confidence'] = try_float(pitch.get('type_confidence'))
p['zone'] = try_int(pitch.get('zone'))
p['nasty'] = try_int(pitch.get('nasty'))
p['spin_dir'] = try_float(pitch.get('spin_dir'))
p['spin_rate'] = try_float(pitch.get('spin_rate'))
# Drop None items and add Pitch to to_load
p = dict((k, v) for k, v in p.items() if v is not None)
logging.info(p)
self.to_load.append(Pitch(**p))
def parse_pitches(self):
# Parse every pitch in all innings, adding them to the to_load list.
pitch_counter = count()
for pitch in self.innings.find_all('pitch'):
# Some years are missing pitch_ids. Since we're using it as a key,
# assign here and increment the counter
p = {}
p['game_id'] = self.game_id
p['pitch_id'] = int(pitch.get('id', next(pitch_counter)))
p['at_bat_number'] = try_int(pitch.parent.get('num'))
p['description'] = pitch.get('des')
p['type'] = pitch.get('type')
try:
t = dateutil.parser.parse(pitch.get('tfs_zulu', ''))
p['timestamp'] = t.astimezone(timezone('America/New_York'))
except ValueError:
logging.warning(
'Could not parse timestamp: Game {}; pitch {}'.format(
self.game_id, p['pitch_id']))
p['x'] = try_float(pitch.get('x'))
p['y'] = try_float(pitch.get('y'))
p['event_num'] = try_int(pitch.get('event_num'))
p['sv_id'] = pitch.get('sv_id')
p['play_guid'] = pitch.get('play_guid')
p['start_speed'] = try_float(pitch.get('start_speed'))
p['end_speed'] = try_float(pitch.get('end_speed'))
p['sz_top'] = try_float(pitch.get('sz_top'))
p['sz_bottom'] = try_float(pitch.get('sz_bot'))
p['pfx_x'] = try_float(pitch.get('pfx_x'))
p['pfx_z'] = try_float(pitch.get('pfx_z'))
p['x0'] = try_float(pitch.get('x0'))
p['y0'] = try_float(pitch.get('y0'))
p['z0'] = try_float(pitch.get('z0'))
p['vx0'] = try_float(pitch.get('vx0'))
p['vy0'] = try_float(pitch.get('vy0'))
p['vz0'] = try_float(pitch.get('vz0'))
p['ax'] = try_float(pitch.get('ax'))
p['ay'] = try_float(pitch.get('ay'))
p['az'] = try_float(pitch.get('az'))
p['break_y'] = try_float(pitch.get('break_y'))
p['break_angle'] = try_float(pitch.get('break_angle'))
p['break_length'] = try_float(pitch.get('break_length'))
p['pitch_type'] = pitch.get('pitch_type')
p['type_confidence'] = try_float(pitch.get('type_confidence'))
p['zone'] = try_int(pitch.get('zone'))
p['nasty'] = try_int(pitch.get('nasty'))
p['spin_dir'] = try_float(pitch.get('spin_dir'))
p['spin_rate'] = try_float(pitch.get('spin_rate'))
# Drop None items and add Pitch to to_load
p = dict((k, v) for k, v in p.items() if v is not None)
logging.info(p)
self.to_load.append(Pitch(**p))
def compileInstanceResults(self, sInst):
for mLog, lN in self.lResLogs: ## Select method and its name list
lNames = self.getMethodName(lN)
aDetThis = self.aDetThisInst[lNames] ## Result table line section
if sInst in mLog:
self.nReported += 1
aResultThisInst = OrderedDict({"n_Reported": 1})
aResultThisInst["n_CheckFailed"] = 0
mRes = mLog[sInst] ## The method's entry for this instance
aDetThis["chk"] = "ok"
if "SOLUTION_CHECKS_FAILED" in mRes and \
0<mRes["SOLUTION_CHECKS_FAILED"]:
aResultThisInst["n_CheckFailed"] = 1
aDetThis["chk"] = "BAD"
utils.addMapValues(self.mCmpVecVals[lNames],
aResultThisInst)
print(
"WARNING: SOLUTION CHECK(S) FAILED for the instance ",
sInst,
", method '",
lNames,
"'.",
sep='',
file=self.ioBadChecks)
continue ## TODO. Param?
aResultThisInst["n_ErrorsBackend"] = 0
aResultThisInst["n_ErrorsLogical"] = 0
aDetThis["errH"] = 0
aDetThis["errL"] = 0
mSlv = mRes["__SOLVE__"]
dObj_MZN = utils.try_float(mSlv.get("ObjVal_MZN"))
aDetThis["objMZN"] = dObj_MZN
dObj_SLV = utils.try_float(mSlv.get("ObjVal_Solver"))
aDetThis["objSLV"] = dObj_SLV
dBnd_SLV = utils.try_float(mSlv.get("DualBnd_Solver"))
aDetThis["bnd"] = dBnd_SLV
dTime_All = utils.try_float(mSlv.get("TimeReal_All"))
aDetThis["tAll"] = dTime_All
dTime_Flt = utils.try_float(mSlv.get("Time_Flt"))
aResultThisInst[
"t_Flatten"] = dTime_Flt if dTime_Flt is not None else dTime_All ##??
aDetThis["tFlt"] = dTime_Flt
dTime_Last = utils.try_float(mSlv.get("TimeReal_LastStatus"))
aDetThis["tBest"] = dTime_Last
## Compare obj vals
dObj, bObj_MZN = (dObj_MZN, True) if \
None!=dObj_MZN and abs( dObj_MZN ) < 1e45 else (mSlv.get("ObjVal_MZN"), False)
## Assuming solver value is better if different. WHY? Well it' happened both ways
dObj, bObj_SLV = (dObj_SLV, True) if \
None!=dObj_SLV and abs( dObj_SLV ) < 1e45 else (dObj, False)
if bObj_MZN and bObj_SLV:
if abs(dObj_MZN - dObj_SLV) > 1e-6 * max(
abs(dObj_MZN), abs(dObj_SLV)):
aResultThisInst["n_ErrorsLogical"] += 1
aDetThis["errL"] += 1
print(
" WARNING: DIFFERENT MZN / SOLVER OBJ VALUES for the instance ",
sInst,
", method '",
lNames,
"' : ",
dObj_MZN,
" / ",
dObj_SLV,
sep='',
file=self.ioContrObjValMZN)
## Retrieve solution status
if "Sol_Status" in mSlv:
n_SolStatus = mSlv["Sol_Status"][0]
else:
n_SolStatus = 0
## Retrieve dual bound
dBnd = None
if None != dBnd_SLV and abs(dBnd_SLV) < 1e45:
dBnd = dBnd_SLV
self.lDualBnd.append((
dBnd_SLV,
lNames)) ## Even infeas instances can have dual bound?
## Trying to deduce opt sense if not given:
if 1 == len(self.sSenses):
nSense = next(iter(self.sSenses.keys()))
else:
nSense = -2 ## ??
aDetThis["sns"] = self.mapProblemSense[nSense]
self.bOptProblem = True if 0 != nSense else False ## or (None!=dBnd or None!=dObj)
### ... here assumed it's an opt problem by default... why... need to check bounds first??
## Handle optimality / SAT completed
if 2 == n_SolStatus:
if not self.bOptProblem:
self.lSatAll.append(lNames)
aResultThisInst["n_SATALL"] = 1
aDetThis["stt"] = self.mapStatShort[4]
else: ## Assume it's an optimization problem????? TODO
self.lOpt.append(
lNames) ## Append the optimal method list
aResultThisInst["n_OPT"] = 1
aDetThis["stt"] = self.mapStatShort[2]
if None == dObj or abs(dObj) >= 1e45:
aResultThisInst["n_ErrorsLogical"] += 1
aDetThis["errL"] += 1
print(
" WARNING: OPTIMAL STATUS BUT BAD OBJ VALUE, instance ",
sInst,
", method '",
lNames,
"': '",
("" if None == dObj else str(dObj)),
"', result record: ", # mRes,
",, dObj_MZN: ",
dObj_MZN,
sep='',
file=self.ioBadObjValueStatusOpt)
else:
self.mOptVal[
dObj] = lNames ## Could have used OrderedDict
self.lOptVal.append(
(dObj,
lNames)) ## To have both a map and the order
self.lPrimBnd.append((dObj, lNames))
## Handle feasibility / SAT
elif 1 == n_SolStatus:
if not self.bOptProblem:
self.lSat.append(lNames)
aResultThisInst["n_SAT"] = 1
aDetThis["stt"] = self.mapStatShort[3]
else: ## Assume it's an optimization problem????? TODO
self.lFeas.append(
lNames) ## Append the optimal method list
aResultThisInst["n_FEAS"] = 1
aDetThis["stt"] = self.mapStatShort[1]
if None == dObj or abs(dObj) >= 1e45:
aResultThisInst["n_ErrorsLogical"] += 1
aDetThis["errL"] += 1
print(
" WARNING: feasible status but bad obj value, instance ",
sInst,
", method '",
lNames,
"' :'",
("" if None == dObj else str(dObj)),
"', result record: ", # mRes,
sep='',
file=self.ioBadObjValueStatusFeas)
else:
self.lPrimBnd.append((dObj, lNames))
## Handle infeasibility
elif -1 >= n_SolStatus and -3 <= n_SolStatus:
self.lInfeas.append(lNames)
aResultThisInst["n_INFEAS"] = 1
aDetThis["stt"] = self.mapStatShort[n_SolStatus]
self.mInfeas.setdefault(sInst, [])
self.mInfeas[sInst].append(lNames)
## Handle ERROR?
elif -4 == n_SolStatus:
aResultThisInst["n_ErrorsBackend"] = 1
aDetThis["errH"] += 1
aDetThis["stt"] = self.mapStatShort[
n_SolStatus] ## Should not happen TODO
self.mError.setdefault(sInst, []).append(lNames)
print(
"ERROR REPORTED for the instance ",
sInst,
", method '",
lNames,
"', result record: ", ## mRes,
sep='',
file=self.ioErrors)
else:
aResultThisInst["n_UNKNOWN"] = 1
aDetThis["stt"] = self.mapStatShort[0]
## Handle NOFZN
if None == dTime_Flt:
aResultThisInst["n_NOFZN"] = 1
self.mNoFZN.setdefault(sInst, []).append(lNames)
## Handle FAIL???
# LAST:
utils.addMapValues(self.mCmpVecVals[lNames], aResultThisInst)
def _post_exec(self):
if self.parallel and self.check_only:
dct = collections.defaultdict(list)
status_dct = {}
tag_dct = {}
db_records = []
for t in self.tool_list:
check_info = t.check(full=True)
cur_info = CURATED_INFO.get(t.pdb_id, {})
tag = re.split("/|\.", check_info)[0]
if tag == "mppd":
tag = "provi"
if tag != "opm":
# check if opm found two mplanes
try:
if len(t.opm.get_planes()) != 2:
tag = "mplane"
except IOError:
# print tag, check_info, t.id
pass
else:
if os.path.isfile(t.opm.outpath("ppm_error.txt")):
tag = "ppm"
# print open( t.opm.outpath( "ppm_error.txt" ) ).read()
if tag != "pdb_info" and t.pdb_info.check():
info = t.pdb_info.get_info()
if "CA ATOMS ONLY" in info.get("model_type", {}):
tag = "calpha_only"
if cur_info.get("backbone_only"):
tag = "backbone_only"
if "THEORETICAL MODEL" == info.get("experiment", ""):
tag = "theoretical_model"
res = info.get("resolution")
if res and res >= 4.0 and res != "NOT":
tag = "resolution"
if info.get("obsolete"):
tag = "obsolete"
try:
opm_info = t.opm_info.get_info()
if opm_info and opm_info.get("type") != "Transmembrane":
tag = "no_transmembrane"
except:
pass
if cur_info.get("no_pdb_entry"):
tag = "no_pdb_entry"
if cur_info.get("no_transmembrane"):
tag = "no_transmembrane"
tag_dct[t.pdb_id] = tag
dct[tag].append(t)
# representative id search
test_rep_list = flatten([
zip([x] * len(dct[x]), dct[x])
for x in ["opm", "ppm", "msms0", "msms_vdw_fin", "dowser"]
])
print test_rep_list
for tag, t in test_rep_list:
try:
opm_info = t.opm_info.get_info()
mpstruc_info = t.mpstruc_info.get_info()
except:
continue
rid_list = []
if opm_info:
rep_id = opm_info.get("representative")
if rep_id:
rid_list.append(rep_id.upper())
rid_list += opm_info.get("related_ids", [])
if mpstruc_info:
master_id = mpstruc_info.get("master")
if master_id:
rid_list.append(master_id.upper())
rid_list += mpstruc_info.get("related", [])
rep = None
for rid in rid_list:
for x in dct["Ok"]:
if x.pdb_id == rid:
rep = x
break
else:
continue
break
if rep:
dct["representative"].append(t)
else:
dct["no_representative"].append(t)
ignore_tags = [
"no_pdb_entry",
"mplane",
"representative",
"no_representative",
"no_transmembrane",
"theoretical_model",
"obsolete",
]
# status types
# included: all good
# linked: only a representative available
# pending: to be included
# obsolete: superseeded
# defect: low resolution; missing atoms
# model: theoretical model
for pdb_id, tag in tag_dct.iteritems():
if tag == "Ok":
status = "included"
elif tag == "obsolete":
status = "obsolete"
elif tag == "theoretical_model":
status = "model"
elif tag in ["calpha_only", "backbone_only"]:
status = "backbone_only"
elif tag == "resolution":
status = "low_resolution"
elif tag in ["opm", "ppm", "msms0", "msms_vdw_fin"]:
if pdb_id in dct["representative"]:
status = "linked"
else:
status = "pending"
elif tag in ignore_tags:
continue
else:
status = "unknown"
print tag
status_dct[pdb_id] = status
for tag, t_list in dct.iteritems():
if tag != "Ok":
print tag, " ".join(map(lambda x: x.id, t_list))
for tag, t_list in dct.iteritems():
print tag, len(t_list)
if self.database:
for tag, t_list in dct.iteritems():
if tag in ignore_tags:
continue
for t in t_list:
t_info = t.get_info()
if tag == "Ok":
for s in t.get_stats():
if s['source'] == 'fin' and s[
'segment'] == 'TM':
t_stats = s
break
else:
raise Exception('no stats found %s' % t.pdb_id)
else:
t_stats = {}
cur_info = CURATED_INFO.get(t.pdb_id, {})
db_records.append(
MppdDbRecord(
t_info['pdb_id'],
t_info['pdb_title'],
",".join(t_info['pdb_keywords']),
t_info['pdb_experiment'],
t_info['pdb_resolution'],
t_info['opm_superfamily'],
t_info['opm_family'],
t_info['opm_representative'],
t_info['opm_species'],
",".join(t_info['opm_related']),
t_info['mpstruc_group'],
t_info['mpstruc_subgroup'],
t_info['mpstruc_name'],
t_info['mpstruc_species'],
t_info['mpstruc_master'],
",".join(t_info['mpstruc_related']),
cur_info.get('representative', ""),
",".join(cur_info.get('related', [])),
status_dct[t.pdb_id],
t_stats.get('packdens_protein_buried'),
t_stats.get('water_count'),
t_stats.get('residue_count'),
t_stats.get('msms'),
))
db = SqliteBackend("mppd.db", MppdDbRecord)
db.write(db_records)
if self.extract:
fdir = self.extract
if not os.path.exists(fdir):
os.makedirs(fdir)
shutil.copyfile(self.outpath("mppd.db"),
os.path.join(fdir, "mppd.db"))
for t in dct.get('Ok', []):
flist = [
t.original_dry_pdb, t.final_pdb, t.opm.mplane_file,
t.hbexplore_fin.hbx_file + ".bonds",
t.voronoia_fin.vol_file + ".atmprop",
t.outpath("mppd.provi")
]
flist += t.msms_vdw_fin.component_files()
for fsrc in flist:
fdst = os.path.join(fdir, t.id, t.relpath(fsrc))
if not os.path.exists(os.path.dirname(fdst)):
os.makedirs(os.path.dirname(fdst))
shutil.copyfile(fsrc, fdst)
if self.figures:
alpha = 0.3
size = 7.0
nres = collections.defaultdict(list)
nwater = collections.defaultdict(list)
resolution = collections.defaultdict(list)
ncav = collections.defaultdict(list)
sesvol = collections.defaultdict(list)
packdens = collections.defaultdict(list)
packdens_buried = collections.defaultdict(list)
for t in dct.get('Ok', []):
stats = t.get_stats()
info = t.get_info()
for s in stats:
if s["segment"] != "TM":
continue
key = (s["source"], s["segment"])
nres[key].append(s["residue_count"])
nwater[key].append(s["water_count"])
resolution[key].append(
try_float(info["pdb_resolution"], 0.0))
ncav[key].append(s["msms"])
sesvol[key].append(s["msms_ses"])
packdens[key].append(s["packdens_protein"])
packdens_buried[key].append(
s["packdens_protein_buried"])
print nres.keys()
for key in nres.keys():
print key
x = np.array(nwater[key])
y = np.array(nres[key])
x_y = x / y
r = np.array(resolution[key])
cav = np.array(ncav[key])
cav_y = cav / y
vol = np.array(sesvol[key]) * -1
vol_y = vol / y
pd = np.array(packdens[key])
pd_buried = np.array(packdens_buried[key])
from mpl_toolkits.axes_grid.anchored_artists import (
AnchoredText)
def hist(axis, x, label, loc=1, nzero=False):
if nzero:
x = x[x != 0]
if len(x) == 0:
x = np.array([0])
axis.hist(x, normed=True, bins=25)
axis.set_xlabel(label)
summary = ("Var: %.4f\nStd: %.4f\nMean: %.4f\n"
"Median: %.4f\nMin: %.4f\nMax: %.4f\n") % (
np.var(x), x.std(), x.mean(),
np.median(x), x.min(), x.max())
at = AnchoredText(summary,
loc=loc or 1,
prop={"size": 10},
frameon=True,
pad=0.5,
borderpad=1.0)
axis.add_artist(at)
def scatter(axis, x, y, xlabel, ylabel, loc=1, nzero=True):
if nzero:
xnzero = x != 0
ynzero = y != 0
x = x[xnzero & ynzero]
y = y[xnzero & ynzero]
try:
r = pearsonr(x, y)
except Exception:
r = (np.nan, np.nan)
axis.scatter(x, y, alpha=alpha, s=size)
axis.set_xlabel(xlabel)
axis.set_ylabel(ylabel)
axis.set_ylim((0, axis.get_ylim()[1]))
summary = "r: %.4f\np: %.4f\n" % r
at = AnchoredText(summary,
loc=loc or 1,
prop={"size": 10},
frameon=True,
pad=0.5,
borderpad=1.0)
axis.add_artist(at)
fig, (ax) = plt.subplots(3, 4, figsize=[20, 12])
scatter(ax[0, 0], x, y, "#h20", "#res")
hist(ax[0, 1], x_y, "#h2o / #res")
scatter(ax[1, 0], r, x_y, "resolution [A]", "#h2o / #res")
hist(ax[1, 1], cav_y, "#cav / #res")
hist(ax[2, 0], vol_y, "ses_vol [A^3] / #res")
hist(ax[0, 2], pd, "packing density")
scatter(ax[1, 2], r, pd, "resolution [A]",
"packing density")
hist(ax[0, 3], pd_buried, "packing density buried")
scatter(ax[1, 3], r, pd_buried, "resolution [A]",
"packing density buried")
fig.savefig("_".join(key) + ".png")
def bar(ax, ydata, labels):
y = [np.array(yd).mean() for yd in ydata]
x = np.arange(len(y))
e = [np.array(yd).std() for yd in ydata]
ax.bar(x,
y,
align='center',
yerr=e,
ecolor='black',
facecolor='#777777')
ax.set_xticks(x)
ax.set_xticklabels(labels)
xlim = (x.min() - 1, x.max() + 1)
ax.set_xlim(xlim)
# ...
tm_keys = [("org", "TM"), ("fin", "TM"), ("dow", "TM")]
if all(map(lambda k: k in nres, tm_keys)):
ydata = []
labels = []
for key in tm_keys:
ydata.append(
(np.array(nwater[key]) / np.array(nres[key])) *
100)
labels.append(key[0])
fig, (ax) = plt.subplots(1, 1, figsize=[6, 4.5])
bar(ax, ydata, labels)
fig.savefig("h2o_per_100_res.png")
# ...
nwater_cutoff = collections.defaultdict(list)
cutoff_list = np.arange(1.4, 3.9, step=0.1)
for t in dct.get('Ok', []):
stats2 = t.get_stats2()
for s2 in stats2:
key = s2["segment"]
if not len(nwater_cutoff[key]):
for cutoff in cutoff_list:
nwater_cutoff[key].append([])
water_count = s2["water_count"]
# residue_count = s2["residue_count"]
count_list = s2["exp_water_cutoff_count"]
for i, cutoff in enumerate(cutoff_list):
frac = try_div(count_list[i], water_count)
nwater_cutoff[key][i].append(frac)
for key in nwater_cutoff.keys():
fig, (ax) = plt.subplots(1, 1, figsize=[8, 4])
bar(ax, nwater_cutoff[key], map(str, cutoff_list))
fig.savefig(str(key) + ".png")
