def get_moves_by_day(data):
moves = []
cur_move = []
last_endtime = None
H1 = 30
H2 = 15
for record in data:
if record['duration'] > H1:
if len(cur_move) > 1:
moves.append(cur_move)
cur_move = []
last_endtime = None
else:
start_time = str2date(record['start_time'])
end_time = str2date(record['end_time'])
if last_endtime is None:
cur_move.append(record)
last_endtime = end_time
else:
delta = (start_time - last_endtime).total_seconds() / 60
if delta < H2:
cur_move.append(record)
last_endtime = end_time
else:
if len(cur_move) > 1:
moves.append(cur_move)
cur_move = []
last_endtime = None
return moves
def get_location_in_range(move, start, end):
result = []
for location in move:
cur_start = str2date(location['start_time'])
cur_end = str2date(location['end_time'])
if cur_start < end and (cur_start >= start or cur_end <= end):
result.append(location)
return result
def get_location_in_range(move, start, end):
result = []
for location in move:
cur_start = str2date(location["start_time"])
cur_end = str2date(location["end_time"])
if cur_start < end and (cur_start >= start or cur_end <= end):
result.append(location)
return result
def entropy(move, delta_t, time_range):
if len(move) <= 1:
return 0
location_time_ranges = {}
move_start = str2date(move[0]['start_time'])
move_end = str2date(move[-1]['end_time'])
if move_start > time_range[0]:
delta_t -= (move_start - time_range[0]).total_seconds() / 60.0
if move_end < time_range[1]:
delta_t -= (time_range[1] - move_end).total_seconds() / 60.0
if delta_t <= 0:
return 0
last_end_time = None
last_location = None
last_duration = None
last_start_time = None
for location in move:
cur_location = location['location']
cur_start_time = str2date(location['start_time'])
cur_end_time = str2date(location['end_time'])
cur_duration = location['duration']
location_time_ranges.setdefault(cur_location, 0)
if last_end_time:
location_time_ranges[last_location] += (
cur_start_time - last_end_time).total_seconds() / 60.0
from_ts = max(time_range[0], last_start_time)
to_ts = min(time_range[1], last_end_time)
location_time_ranges[last_location] += (
to_ts - from_ts).total_seconds() / 60.0
last_start_time = cur_start_time
last_end_time = cur_end_time
last_location = cur_location
last_duration = cur_duration
if location:
from_ts = max(time_range[0], last_start_time)
to_ts = min(time_range[1], last_end_time)
location_time_ranges[last_location] += (to_ts -
from_ts).total_seconds() / 60.0
for location in list(location_time_ranges.keys()):
location_time_ranges[location] /= delta_t
entropy = sum([
-1 * proba * math.log(proba, 2)
for proba in list(location_time_ranges.values()) if proba > 0
])
return entropy
def transient_entropy(location, move):
delta_t = 10
# set start_time
start_time = str2date(location["start_time"])
# get - t/2 and + t/2
time_range = [
start_time - datetime.timedelta(minutes=delta_t / 2),
start_time + datetime.timedelta(minutes=delta_t / 2),
]
location_in_ranges = get_location_in_range(move, time_range[0], time_range[1])
pprint.pprint(location_in_ranges)
location_time_ranges = {}
move_start = str2date(move[0]["start_time"])
move_end = str2date(move[-1]["end_time"])
if move_start > time_range[0]:
location_time_ranges["before"] = (move_start - time_range[0]).total_seconds() / 60.0
if move_end < time_range[1]:
location_time_ranges["after"] = (time_range[1] - move_end).total_seconds() / 60.0
# delta_t -= (time_range[1] - move_end).total_seconds() / 60.0
last_end_time = None
last_location = None
last_duration = None
last_start_time = None
for location in location_in_ranges:
cur_location = location["location"]
cur_start_time = str2date(location["start_time"])
cur_end_time = str2date(location["end_time"])
cur_duration = location["duration"]
location_time_ranges.setdefault(cur_location, 0)
if last_end_time:
location_time_ranges[last_location] += (cur_start_time - last_end_time).total_seconds() / 60.0
from_ts = max(time_range[0], last_start_time)
to_ts = min(time_range[1], last_end_time)
location_time_ranges[last_location] += (to_ts - from_ts).total_seconds() / 60.0
last_start_time = cur_start_time
last_end_time = cur_end_time
last_location = cur_location
last_duration = cur_duration
if location:
from_ts = max(time_range[0], last_start_time)
to_ts = min(time_range[1], last_end_time)
location_time_ranges[last_location] += (to_ts - from_ts).total_seconds() / 60.0
for location in list(location_time_ranges.keys()):
location_time_ranges[location] /= delta_t
entropy = sum([-1 * proba * math.log(proba, 2) for proba in list(location_time_ranges.values()) if proba > 0])
return entropy
def to_dist(row):
result = {}
for day in row:
date = day["date"]
result.setdefault(date, {})
for location in day["locations"]:
loc = location["location"]
result[date].setdefault(loc, 0)
st = str2date(location["start_time"])
dt = str2date(location["end_time"])
duration = (dt - st).total_seconds() / 60.0
result[date][loc] += duration
return result
def to_dist(row):
result = {}
for day in row:
date = day['date']
result.setdefault(date, {})
for location in day['locations']:
loc = location['location']
result[date].setdefault(loc, 0)
st = str2date(location['start_time'])
dt = str2date(location['end_time'])
duration = (dt - st).total_seconds() / 60.0
result[date][loc] += duration
return result
def entropy(move, delta_t, time_range):
if len(move) <= 1:
return 0
location_time_ranges = {}
move_start = str2date(move[0]["start_time"])
move_end = str2date(move[-1]["end_time"])
if move_start > time_range[0]:
delta_t -= (move_start - time_range[0]).total_seconds() / 60.0
if move_end < time_range[1]:
delta_t -= (time_range[1] - move_end).total_seconds() / 60.0
if delta_t <= 0:
return 0
last_end_time = None
last_location = None
last_duration = None
last_start_time = None
for location in move:
cur_location = location["location"]
cur_start_time = str2date(location["start_time"])
cur_end_time = str2date(location["end_time"])
cur_duration = location["duration"]
location_time_ranges.setdefault(cur_location, 0)
if last_end_time:
location_time_ranges[last_location] += (cur_start_time - last_end_time).total_seconds() / 60.0
from_ts = max(time_range[0], last_start_time)
to_ts = min(time_range[1], last_end_time)
location_time_ranges[last_location] += (to_ts - from_ts).total_seconds() / 60.0
last_start_time = cur_start_time
last_end_time = cur_end_time
last_location = cur_location
last_duration = cur_duration
if location:
from_ts = max(time_range[0], last_start_time)
to_ts = min(time_range[1], last_end_time)
location_time_ranges[last_location] += (to_ts - from_ts).total_seconds() / 60.0
for location in list(location_time_ranges.keys()):
location_time_ranges[location] /= delta_t
entropy = sum([-1 * proba * math.log(proba, 2) for proba in list(location_time_ranges.values()) if proba > 0])
return entropy
def get_speed_by_day_at_change_point(all_rows, day):
cols = ['start_time', 'location']
speeds = []
results = merge_locations_by_date([dict(list(zip(cols, row))) for row in all_rows])
points = set()
for location in results:
points.add(location['start_time'])
points.add(location['end_time'])
points = [str2date(x) for x in sorted(points)]
if len(all_rows) == 0:
return speeds
delta_t = 60
for i in range(len(points)):
start_time = points[i] - datetime.timedelta(minutes=delta_t / 2)
end_time = points[i] + datetime.timedelta(minutes=delta_t / 2)
rows = [x for x in all_rows if date2str(start_time) <= x[0] <= date2str(end_time)]
if len(rows) == 0:
speeds.append({
'time': date2str(points[i]),
'speed': 0
})
continue
rows = merge_locations_by_date([dict(list(zip(cols, row))) for row in rows])
get_delta_by_day(rows)
speed = entropy(rows, delta_t, [start_time, end_time])
speeds.append({
'time': date2str(points[i]),
'speed': speed
})
return speeds
def transient_entropy(location, move):
delta_t = 10
# set start_time
start_time = str2date(location['start_time'])
# get - t/2 and + t/2
time_range = [
start_time - datetime.timedelta(minutes=delta_t / 2),
start_time + datetime.timedelta(minutes=delta_t / 2)
]
location_in_ranges = get_location_in_range(move, time_range[0],
time_range[1])
pprint.pprint(location_in_ranges)
location_time_ranges = {}
move_start = str2date(move[0]['start_time'])
move_end = str2date(move[-1]['end_time'])
if move_start > time_range[0]:
location_time_ranges['before'] = (move_start -
time_range[0]).total_seconds() / 60.0
if move_end < time_range[1]:
location_time_ranges['after'] = (time_range[1] -
move_end).total_seconds() / 60.0
# delta_t -= (time_range[1] - move_end).total_seconds() / 60.0
last_end_time = None
last_location = None
last_duration = None
last_start_time = None
for location in location_in_ranges:
cur_location = location['location']
cur_start_time = str2date(location['start_time'])
cur_end_time = str2date(location['end_time'])
cur_duration = location['duration']
location_time_ranges.setdefault(cur_location, 0)
if last_end_time:
location_time_ranges[last_location] += (
cur_start_time - last_end_time).total_seconds() / 60.0
from_ts = max(time_range[0], last_start_time)
to_ts = min(time_range[1], last_end_time)
location_time_ranges[last_location] += (
to_ts - from_ts).total_seconds() / 60.0
last_start_time = cur_start_time
last_end_time = cur_end_time
last_location = cur_location
last_duration = cur_duration
if location:
from_ts = max(time_range[0], last_start_time)
to_ts = min(time_range[1], last_end_time)
location_time_ranges[last_location] += (to_ts -
from_ts).total_seconds() / 60.0
for location in list(location_time_ranges.keys()):
location_time_ranges[location] /= delta_t
entropy = sum([
-1 * proba * math.log(proba, 2)
for proba in list(location_time_ranges.values()) if proba > 0
])
return entropy
