def load_probs(fn_probs,
interval_min,
interval_max,
weekdays,
pickup,
n_keep=-1):
probs = dict()
probs[DS] = list()
probs[PR] = list()
dd = defaultdict(float)
with io.open(fn_probs, "rb") as fin:
reader = csv.DictReader(fin)
for i, row in enumerate(reader):
if i == 0:
continue
row = common.clean_dict(row)
int_within = interval_min <= row["tau"] <= interval_max
wd_eq = row["day"] == weekdays
pickup_eq = row["pickup"] == pickup
if int_within and wd_eq and pickup_eq:
dd[row["dropoff"]] += row["probability"]
if n_keep > len(dd.values()):
n_keep = len(dd.values())
probs[DS] = map(int, dd.keys())[:n_keep]
probs[PR] = dd.values()[:n_keep]
return probs
def _make_listitem(self, label, label2='', iconImage='', thumbnail='',
path='', **options):
li = xbmcgui.ListItem(label, label2=label2, iconImage=iconImage, thumbnailImage=thumbnail, path=path)
cleaned_info = clean_dict(options.get('info'))
if cleaned_info:
li.setInfo('video', cleaned_info)
if options.get('is_playable'):
li.setProperty('IsPlayable', 'true')
if options.get('context_menu'):
li.addContextMenuItems(options['context_menu'])
#endpoint = options['context_menu'].get('add_to_playlist')
#if endpoint:
#keys = ['label', 'label2', 'icon', 'thumbnail', 'path', 'info']
# need the url for calling add_to_playlist this is thwat gets added to the context menu
# need the current url for the item, it will be encoded in teh url for calling add_to_playlist
# also other info in [keys] will be added to teh add_to_playlist url's qs so we can recreate the listitem
# perhaps try pickling the listitem?
#current_url = options.get('url')
#context_menu_url = self.url_for(endpoint, url=options.get('url'), label=label, label2=label2, iconImage=iconImage, thumbnail=thumbnail)
#li.addContextMenuItems([('Add to Playlist', 'XBMC.RunPlugin(%s)' % context_menu_url)])
#return li
return options['url'], li, options.get('is_folder', True)
def load_cumulative_probs(fn_probs, interval_min, interval_max, weekdays):
dropoff_probs = defaultdict(float)
pickup_probs = defaultdict(float)
with io.open(fn_probs, "rb") as fin:
reader = csv.DictReader(fin)
next(reader)
for row in reader:
row = common.clean_dict(row)
int_within = interval_min <= row["tau"] <= interval_max
wd_eq = row["day"] in weekdays
if int_within and wd_eq:
dropoff_probs[row["dropoff"]] += row["probability"]
pickup_probs[row["pickup"]] += row["probability"]
return pickup_probs, dropoff_probs
def load_cumulative_probs(fn_probs, interval_min, interval_max, weekdays):
dropoff_probs = defaultdict(float)
pickup_probs = defaultdict(float)
with io.open(fn_probs, "rb") as fin:
reader = csv.DictReader(fin)
next(reader)
for row in reader:
row = common.clean_dict(row)
int_within = interval_min <= row["tau"] <= interval_max
wd_eq = row["day"] in weekdays
if int_within and wd_eq:
dropoff_probs[row["dropoff"]] += row["probability"]
pickup_probs[row["pickup"]] += row["probability"]
return pickup_probs, dropoff_probs
def create_demands_file(stations, fn_raw, fn_demands, kd, fl):
pbar = ProgressBar(
widgets=["Creating Demands File: ", Bar(),
Percentage(), "|", ETA()],
maxval=fl + 1).start()
cur_date = (0, 0, 0)
fout = None
writer = None
counter = 0
rows = list()
with io.open(fn_raw, "rb") as fin:
reader = csv.DictReader(fin)
for i, row in enumerate(reader):
if i == 0:
continue
nrow = [None] * len(fn_demands_fields)
row = common.clean_dict(row)
str_time = row["pickup_datetime"]
t = time.strptime(str_time, common.date_format)
cdate = (t.tm_wday + 1, t.tm_yday // 7, t.tm_year)
if cdate != cur_date:
cur_date = cdate
fname = day_dem_template.format(*cur_date)
fout = io.open(fname, "wb")
writer = csv.writer(fout, delimiter=" ")
writer.writerow(fn_demands_fields)
writer.writerow([counter])
writer.writerows(rows)
rows = list()
fout.close()
counter = 0
p_l = [row["pickup_longitude"], row["pickup_latitude"]]
d_l = [row["dropoff_longitude"], row["dropoff_latitude"]]
_, sts = kd.query(np.array([p_l, d_l]))
nrow[0] = epoch_seconds(row["pickup_datetime"])
nrow[1] = sts[0]
nrow[2] = epoch_seconds(row["dropoff_datetime"])
nrow[3] = row["dropoff_longitude"]
nrow[4] = row["dropoff_latitude"]
nrow[5] = sts[1]
nrow[6] = row["pickup_longitude"]
nrow[7] = row["pickup_latitude"]
rows.append(nrow)
counter += 1
pbar.update(i)
pbar.finish()
def load_probs(fn_probs, interval_min, interval_max, weekdays, pickup,
n_keep=-1):
probs = dict()
probs[DS] = list()
probs[PR] = list()
dd = defaultdict(float)
with io.open(fn_probs, "rb") as fin:
reader = csv.DictReader(fin)
for i, row in enumerate(reader):
if i == 0:
continue
row = common.clean_dict(row)
int_within = interval_min <= row["tau"] <= interval_max
wd_eq = row["day"] == weekdays
pickup_eq = row["pickup"] == pickup
if int_within and wd_eq and pickup_eq:
dd[row["dropoff"]] += row["probability"]
if n_keep > len(dd.values()):
n_keep = len(dd.values())
probs[DS] = map(int, dd.keys())[:n_keep]
probs[PR] = dd.values()[:n_keep]
return probs
def extract_frequencies(fn_raw, stations, kd, fl):
num_pd = OrderedDict()
num_ti = OrderedDict()
num_tau = defaultdict(int)
num_tau_occ = defaultdict(set)
counter = 0
pbar = ProgressBar(
widgets=["Extracting Frequencies: ", Bar(), Percentage(), "|", ETA()],
maxval=fl + 1).start()
with io.open(fn_raw, "rb") as fin:
reader = csv.DictReader(fin)
for i, row in enumerate(reader):
if i == 0:
continue
try:
row = common.clean_dict(row)
p_time, p_day = percent_time(row["pickup_datetime"])
p_l = [row["pickup_longitude"], row["pickup_latitude"]]
d_l = [row["dropoff_longitude"], row["dropoff_latitude"]]
_, sts = kd.query(np.array([p_l, d_l]))
tau = int(4 * 24 * p_time)
ti = (tau, p_day)
if not ti in num_pd.keys():
num_pd[ti] = dict()
if not ti in num_ti:
num_ti[ti] = 0
if not (sts[0], sts[1]) in num_pd[ti]:
num_pd[ti][(sts[0], sts[1])] = 0
counter += 1
num_pd[ti][(sts[0], sts[1])] += row["passenger_count"]
num_ti[ti] += row["passenger_count"]
num_tau[tau] += row["passenger_count"]
num_tau_occ[tau].add(p_day)
except ValueError:
pass
pbar.update(i + 1)
pbar.finish()
return num_pd, num_ti, num_tau, num_tau_occ, counter
def _make_listitem(self,
label,
label2='',
iconImage='',
thumbnail='',
path='',
**options):
li = xbmcgui.ListItem(label,
label2=label2,
iconImage=iconImage,
thumbnailImage=thumbnail,
path=path)
cleaned_info = clean_dict(options.get('info'))
if cleaned_info:
li.setInfo('video', cleaned_info)
if options.get('is_playable'):
li.setProperty('IsPlayable', 'true')
if options.get('context_menu'):
li.addContextMenuItems(options['context_menu'])
#endpoint = options['context_menu'].get('add_to_playlist')
#if endpoint:
#keys = ['label', 'label2', 'icon', 'thumbnail', 'path', 'info']
# need the url for calling add_to_playlist this is thwat gets added to the context menu
# need the current url for the item, it will be encoded in teh url for calling add_to_playlist
# also other info in [keys] will be added to teh add_to_playlist url's qs so we can recreate the listitem
# perhaps try pickling the listitem?
#current_url = options.get('url')
#context_menu_url = self.url_for(endpoint, url=options.get('url'), label=label, label2=label2, iconImage=iconImage, thumbnail=thumbnail)
#li.addContextMenuItems([('Add to Playlist', 'XBMC.RunPlugin(%s)' % context_menu_url)])
#return li
return options['url'], li, options.get('is_folder', True)
def filter_data_for_day(fn_huge, fn_filtered, wds, max_wds):
print "Filtering file based on weekday..."
current_day = None
day_count = defaultdict(int)
with io.open(fn_huge, "rb") as fin:
with io.open(fn_filtered, "wb") as fout:
reader = csv.DictReader(fin)
writer = csv.DictWriter(fout, fieldnames=common.fn_raw_fields)
writer.writeheader()
for i, row in enumerate(reader):
if i == 0:
continue
row = common.clean_dict(row)
str_time = row["pickup_datetime"]
t = time.strptime(str_time, common.date_format)
if t.tm_wday in wds:
if current_day != t.tm_yday:
current_day = t.tm_yday
if day_count[t.tm_wday] <= max_wds:
day_count[t.tm_wday] += 1
if sum(day_count.values()) > len(wds) * max_wds:
return
if day_count[t.tm_yday] <= max_wds:
writer.writerow(row)
