def keep_tp(data):
drop_list = list()
for row in data.itertuples():
if row.y_pred < 1:
drop_list.append(row.Index)
data = drop_and_report(data, drop_list, 'Keep only TP')
return data
def data_correctly_predicted(data):
drop_list = list()
for row in data.itertuples():
if row.track_berthed != row.y_pred:
drop_list.append(row.Index)
data = drop_and_report(data, drop_list, 'Remove correct predictions')
return data
def drop_mmsi_zero(data):
drop_list = list()
for row in data.itertuples():
if len(str(row.mmsi)) < 9:
drop_list.append(row.Index)
data = drop_and_report(data, drop_list, 'Remove unused rows')
return data
def keep_last_row(data):
drop_list = list()
for row in data.itertuples():
if row.Index != len(data) - 1 and row.track_number == data.at[
row.Index + 1, 'track_number']:
drop_list.append(row.Index)
data = drop_and_report(data, drop_list, "Keep last row of track")
return data
def remove_little_messages_tot(data):
drop_list = list()
for row in data.itertuples():
if data.at[row.Index, 'time_in_polygon'] < 60 * 30:
drop_list.append(row.Index)
continue
data = drop_and_report(data, drop_list,
'Remove obvious non-berthing tracks')
return data
def low_high_speed_check(data):
# Initialize variables for low- and high-speed check
max_speed = 25 # m/s
min_speed = 0 # m/s
drop_list = list()
for row in data.itertuples():
if row.sog_ms > max_speed or row.sog_ms < min_speed:
drop_list.append(row.Index)
data = drop_and_report(data, drop_list, 'Speed outlier')
return data