def get_distances(data,chaining_distance):
percentage_gap_dict = OrderedDict()
for days_to_increment in [7,28,90]:
dates_data = lsl.get_day_seperate_data(data,days_to_increment)
if days_to_increment not in percentage_gap_dict:
percentage_gap_dict[days_to_increment] = OrderedDict()
for day_with_gap in dates_data:
print day_with_gap
timestamps = dates_data[day_with_gap].keys()
timestamps.sort()
current_point = ''
dx = total_distance = 0.0
chaining = 0.0
chaining_distances = []
gaps = []
dx_array = []
for ts in timestamps:
start = [dates_data[day_with_gap][ts]['start_lat'],dates_data[day_with_gap][ts]['start_lng']]
end = [dates_data[day_with_gap][ts]['end_lat'],dates_data[day_with_gap][ts]['end_lng']]
next_point = start
if current_point:
dx = lsl.get_distance(current_point,next_point)
dx_array.append(dx)
if dx <= chaining_distance:
chaining+=dates_data[day_with_gap][ts]["distance_km"]/1000.0
else:
chaining_distances.append(chaining)
gaps.append(dx)
chaining = 0.0
current_point = end
if len(chaining_distances)*len(gaps)!=0:
N = len(timestamps)
if day_with_gap not in percentage_gap_dict[days_to_increment]:
percentage_gap_dict[days_to_increment][day_with_gap] = {}
#percentage_gap_dict[days_to_increment][day_with_gap]['percentage'] = lsl.get_percentage_chain(chaining_distances,gaps)
percentage_gap_dict[days_to_increment][day_with_gap]['percentage'] = lsl.get_percentage_chain_counts(gaps,N)
percentage_gap_dict[days_to_increment][day_with_gap]['gaps'] = dx_array
if days_to_increment == 7:
percentage_gap_dict[days_to_increment][day_with_gap]['number_of_trips'] = len(timestamps)
return percentage_gap_dict
def get_percentages(dates_data,timestamps,dates):
chaining_distance = 852.0
percentage_gap_dict = {}
for d_gap in [7,28,90]:
timestamp = timestamps[d_gap]
N = len(timestamp)
current_point = ''
dx = total_distance = 0.0
chaining = 0.0
chaining_distances = []
gaps = []
dx_array = []
for ts in timestamp:
ts = str(ts)
start = [dates_data[ts]['start_lat'],dates_data[ts]['start_lng']]
end = [dates_data[ts]['end_lat'],dates_data[ts]['end_lng']]
next_point = start
if current_point:
dx = lsl.get_distance(current_point,next_point)
dx_array.append(dx)
total_distance+=dates_data[ts]["distance_km"]
if dx <= chaining_distance:
chaining+=dates_data[ts]["distance_km"]
else:
chaining_distances.append(chaining)
gaps.append(dx/1000.0)
chaining = 0.0
current_point = end
if len(chaining_distances)*len(gaps)!=0:
if d_gap not in percentage_gap_dict:
percentage_gap_dict[d_gap] = {}
percentage_gap_dict[d_gap]['chaining_distance_percentage_{0}'.format(d_gap)] = lsl.get_percentage_chain(chaining_distances,gaps)
#percentage_gap_dict[d_gap]['chaining_count_percentage_{0}'.format(d_gap)] = lsl.get_percentage_chain_counts(gaps,N)
percentage_gap_dict[d_gap]['number_isolated_chains_{0}'.format(d_gap)] = len(chaining_distances)
percentage_gap_dict[d_gap]['total_trips_{0}'.format(d_gap)] = N
percentage_gap_dict[d_gap]['covered_distance_{0}'.format(d_gap)] = total_distance
percentage_gap_dict[d_gap]['number_chained_trips_{0}'.format(d_gap)] = 'N/A'
return percentage_gap_dict
