def trip_duration_stats(df):
"""Displays statistics on the total and average trip duration."""
print_section("Calculating Trip Duration...")
start_time = time.time()
# display total travel time
total_travel = df["Trip Duration"].sum()
print_result("Total travel time -> ", total_travel)
# display mean travel time
mean_travel = df["Trip Duration"].mean()
print_result("Mean travel time -> ", mean_travel)
# display max travel time
max_travel = df["Trip Duration"].max()
print_result("Max travel time -> ", max_travel)
# display the total trip duration for each user type
print_section("Travel time for each user type:")
total_trip_duration = df.groupby(["User Type"]).sum()["Trip Duration"]
for index, user_trip in enumerate(total_trip_duration):
temp = " - " + total_trip_duration.index[index] + " : "
print_result(temp, user_trip)
print("\nThis took %s seconds." % (time.time() - start_time))
print('-' * 40)
def station_stats(df):
"""Displays statistics on the most popular stations and trip."""
print_section("Calculating The Most Popular Stations and Trip...")
start_time = time.time()
# display most commonly used start station
start_station = df["Start Station"].value_counts().idxmax()
# station_message =
print_result("Most commonly used start station -> ", start_station)
# display most commonly used end station
most_common_end_station = df["End Station"].value_counts().idxmax()
print_result("Most commonly used end station -> ", most_common_end_station)
# display most frequent combination of start station and end station trip
most_common_start_end_station = df[["Start Station",
"End Station"]].mode().loc[0]
print_result("Most commonly used start station is ",
most_common_start_end_station[0])
print_result("And the most commonly used end station is ",
most_common_start_end_station[1])
print("\nThis took %s seconds." % (time.time() - start_time))
print('-' * 40)
def gender_stats(df):
"""Displays statistics of analysis based on the gender of bikeshare users."""
# Display counts of gender
print_section("Counts of gender :")
gender_counts = df["Gender"].value_counts()
# print out the total of each genders
for index, gender_count in enumerate(gender_counts):
temp = " - " + gender_counts.index[index] + " : "
print_result(temp, gender_count)
def birth_stats(df):
"""Displays statistics of analysis based on the birth years of bikeshare users."""
print_section("Birthday stats :")
# Display earliest, most recent, and most common year of birth
birth_year = df["Birth Year"]
# the most common birth year
most_common_year = birth_year.value_counts().idxmax()
print_result("The most common birth year -> ", most_common_year)
# the most recent birth year
most_recent = birth_year.max()
print_result("The most recent birth year -> ", most_recent)
# the most earliest birth year
earliest_year = birth_year.min()
print_result("The most earliest birth year -> ", earliest_year)
def time_stats(df):
"""Displays statistics on the most frequent times of travel."""
print_section("Calculating The Most Frequent Times of Travel...")
start_time = time.time()
# display the most common month
common_month = df["month"].value_counts().idxmax()
print_result("Most common month -> ", common_month)
# display the most common day of week
day_of_week = df["day_of_week"].value_counts().idxmax()
print_result("Most common day of week -> ", day_of_week)
# display the most common start hour
start_hour = df["hour"].value_counts().idxmax()
print_result("Most common start hour is -> ", start_hour)
print("\nThis took %s seconds." % (time.time() - start_time))
print('-' * 40)
def user_stats(df):
"""Displays statistics on bikeshare users."""
print_section("Calculating User Stats...")
start_time = time.time()
# Display counts of user types
print_section("Counts of user types :")
value_counts = df["User Type"].value_counts()
# print out the total numbers of each user types
for index, user_count in enumerate(value_counts):
temp = " - " + value_counts.index[index] + " : "
print_result(temp, user_count)
if "Gender" in df.columns:
gender_stats(df)
if "Birth Year" in df.columns:
birth_stats(df)
print("\nThis took %s seconds." % (time.time() - start_time))
print('-' * 40)
print('-' * 40)
def create_config(**options):
config = OrderedDict()
config['arch'] = options['arch']
config['lr'] = options['lr']
config['momentum'] = options['momentum'] if 'momentum' in options else 0.0
config[
'nesterov'] = options['nesterov'] if 'nesterov' in options else False
config['weight_decay'] = options[
'weight_decay'] if 'weight_decay' in options else 0.0
config['lr_decay'] = options['lr_decay'] if 'lr_decay' in options else 1.0
if config['lr_decay'] < 0:
config['lr_decay'] = -1.0 / config['lr_decay']
config['lr_decay_step'] = options[
'lr_decay_step'] if 'lr_decay_step' in options else -1.0
if isinstance(config['lr_decay_step'], str):
lr_decay_step = config['lr_decay_step'].split(',')
if len(lr_decay_step) == 1:
lr_decay_step = int(lr_decay_step[0])
else:
if not lr_decay_step[-1]:
lr_decay_step = lr_decay_step[:-1]
lr_decay_step = [int(x) for x in lr_decay_step]
config['lr_decay_step'] = lr_decay_step
config['method'] = options['method'] if 'method' in options else 'dft'
if 'fixed' not in config['arch']:
if config['method'] == 'flr':
config['method'] = 'lru'
elif config['method'] == 'fmx':
config['method'] = 'max'
elif config['method'] == 'fsm':
config['method'] = 'sum'
config['conv_balanced_row_num'] = options['conv_balanced_row_num'] \
if 'conv_balanced_row_num' in options else 1
config['fc_balanced_row_num'] = options['fc_balanced_row_num'] \
if 'fc_balanced_row_num' in options else 1
config['conv_balanced_freq'] = options['conv_balanced_freq'] \
if 'conv_balanced_freq' in options else 1024
config['fc_balanced_freq'] = options['fc_balanced_freq'] \
if 'fc_balanced_freq' in options else 1024
config[
'rram_size'] = options['rram_size'] if 'rram_size' in options else 512
config['small_rram_size'] = options['small_rram_size'] \
if 'small_rram_size' in options else 128
config['is_small_by_pos'] = options['is_small_by_pos'] \
if 'is_small_by_pos' in options else False
config[
'input_bits'] = options['input_bits'] if 'input_bits' in options else 8
config['output_bits'] = options[
'output_bits'] if 'output_bits' in options else 8
config['weight_bits'] = options[
'weight_bits'] if 'weight_bits' in options else 8
config_str = 'Training Config:\n'
for key, val in config.items():
config_str += '{}: {}\n'.format(key, val)
print_section(config_str, up=89, down=False)
alg_id = config['arch'] + '_' + config['method'] + \
'_c_' + str(config['conv_balanced_row_num']) + \
'_t_' + str(config['fc_balanced_row_num']) + \
'_b_' + str(config['conv_balanced_freq']) + \
'_f_' + str(config['fc_balanced_freq']) + \
'_r_' + str(config['rram_size']) + \
'_p_' + str(1 if config['is_small_by_pos'] else 0) + \
'_h_' + str(config['small_rram_size']) + '_' + \
datetime.datetime.now().strftime('%m%d_%H%M')
print_section('saving to %s' % alg_id, up=False, down=89)
config['checkpoint_dir'] = os.path.join('checkpoints', alg_id)
config['log_dir'] = os.path.join('logs', alg_id)
config['experiment_id'] = alg_id
config['config_str'] = config_str
return config