def read_casu_logs(config_data, experiment_folder):
list_casu_numbers = config_data['controllers']['domset']['casus']
result = {
a_casu_number: casu_log.CASU_Log(a_casu_number, experiment_folder)
for a_casu_number in list_casu_numbers
}
return result
def process_arena (output_path, config_filename, bee_visitation_writer, experiment_duration, casu_A_number, casu_B_number):
casu_numbers = [min (casu_A_number, casu_B_number), max (casu_A_number, casu_B_number)]
base_path = os.path.dirname (config_filename)
# read logs
casu_logs = {
a_casu_number : casu_log.CASU_Log (
a_casu_number,
os.path.join (base_path, 'data_infrared-test/beearena/')
)
for a_casu_number in casu_numbers
}
zero_time = numpy.mean ([
a_casu_log.led_actuator [0, 0]
for a_casu_log in casu_logs.values ()
])
# compute infrared data
build_bee_visitation_CSV_file (
bee_visitation_writer = bee_visitation_writer,
experiment_duration = experiment_duration,
casu_numbers = casu_numbers,
casu_logs = casu_logs,
zero_time = zero_time,
)
# create plot
plot_arena (
output_path = output_path,
config_filename = config_filename,
experiment_duration = experiment_duration,
casu_numbers = casu_numbers,
casu_logs = casu_logs,
zero_time = zero_time,
)
def read_casu_logs(config_data, experiment_folder):
list_casu_numbers = [
a_casu_number for an_arena in config_data['arenas']
for a_casu_number in an_arena.itervalues()
]
result = {
a_casu_number: casu_log.CASU_Log(
a_casu_number,
os.path.join(experiment_folder, 'data_infrared-test/beearena/'))
for a_casu_number in list_casu_numbers
}
return result
def __init__ (self, csv_row, same_colour_threshold, delta_frame):
config_filename = csv_row [0]
experiment_folder = os.path.dirname (config_filename)
self.graph_name = csv_row [1]
self.graph_layout = csv_row [2]
self.run_number = int (csv_row [3])
with open (config_filename, 'r') as fd:
self.config_data = yaml.safe_load (fd)
self.list_casu_numbers = [
a_casu
for an_arena in self.config_data ['arenas']
for a_casu in an_arena.itervalues ()]
self.list_casu_numbers.sort ()
self.casu_video_data_column = dict ([
(a_casu, index)
for index, a_casu in enumerate (self.list_casu_numbers)])
# self.video_data = None
# self.casu_logs = None
# def load_data (self, same_colour_threshold, delta_frame):
# initialise video data features
self.video_data = read_video_data (experiment_folder, same_colour_threshold = same_colour_threshold, delta_frame = delta_frame)
# initialise casu log
self.casu_logs = {
a_casu_number : casu_log.CASU_Log (
a_casu_number,
os.path.join (
experiment_folder,
'data_infrared-test/beearena/'
)
)
for a_casu_number in self.list_casu_numbers
}
for a_casu_log in self.casu_logs.values ():
a_casu_log.compute_activity (
start_index = 0,
end_index = 50,
offset = 500,
moving_average_length = 61,
)
def process_arena (
run_number, base_path,
core_casu_number, leaf_casu_number,
first_period_length, airflow_period_length, third_period_length,
moving_average_length,
sampling_length, sampling_delta, bee_where_about_writer):
# read logs
casu_logs = {
a_casu_number : casu_log.CASU_Log (a_casu_number, os.path.join (base_path, 'data_airflow-test/beearena/'))
for a_casu_number in [core_casu_number, leaf_casu_number]
}
casu_domset_logs = {
a_casu_number : casu_domset_log.CASU_DOMSET_Log (a_casu_number, os.path.join (base_path, 'data_airflow-test/beearena/'))
for a_casu_number in [core_casu_number, leaf_casu_number]
}
# compute activity (needed by bee where about)
for a_casu_log in casu_logs.values ():
a_casu_log.compute_activity (
start_index = 0,
end_index = 50,
offset = 500,
moving_average_length = moving_average_length
)
# create plot
plot_arena (
run_number, core_casu_number, leaf_casu_number,
first_period_length, airflow_period_length, third_period_length,
casu_logs, casu_domset_logs
)
#
compute_bee_where_about (
run_number,
casu_logs,
first_period_length,
airflow_period_length,
third_period_length,
sampling_length = sampling_length,
sampling_delta = sampling_delta,
writer = bee_where_about_writer)
def process_arena(run_number, core_casu_number, leaf_casu_number, base_path,
moving_average_length, first_period_length,
third_period_length, sampling_length, sampling_delta,
bee_where_about_writer):
# read logs
casu_logs = [
casu_log.CASU_Log(
a_casu_number,
os.path.join(base_path, 'data_airflow-test/beearena/'))
for a_casu_number in [core_casu_number, leaf_casu_number]
]
for a_casu_log in casu_logs:
a_casu_log.compute_activity(
start_index=0,
end_index=50,
offset=500,
moving_average_length=moving_average_length)
plot_arena(run_number, core_casu_number, leaf_casu_number, casu_logs)
core_casu_log, leaf_casu_log = casu_logs
compute_bee_where_about(run_number, casu_logs, core_casu_log,
first_period_length, third_period_length,
sampling_length, sampling_delta,
bee_where_about_writer)
def plot_arena (run_number, core_casu_number, leaf_casu_number, base_path):
print ('[I] Creating plot for arena with core casu {} and leaf casu'.format (core_casu_number, leaf_casu_number))
casu_numbers = [core_casu_number, leaf_casu_number]
casu_labels = ['core', 'leaf']
# read logs
casu_logs = [
casu_log.CASU_Log (a_casu_number, os.path.join (base_path, 'data_airflow-test/beearena/'))
for a_casu_number in casu_numbers
]
core_casu_log, leaf_casu_log = casu_logs
casu_domset_logs = [
casu_domset_log.CASU_DOMSET_Log (a_casu_number, os.path.join (base_path, 'data_airflow-test/beearena/'))
for a_casu_number in casu_numbers
]
all_logs = casu_logs + casu_domset_logs
number_axes = 3
# create the figure
margin_left, margin_right, margin_top, margin_bottom = 0.7, 0.1, 0.5, 0.4
inter_axes_distance = 0.2
axes_width, axes_height = 6, 1.8
figure_width = margin_left + axes_width + margin_right
figure_height = margin_top + number_axes * axes_height + (number_axes - 1) * inter_axes_distance + margin_bottom
figure = matplotlib.pyplot.figure (figsize = (figure_width, figure_height))
# create the axes
list_axes = [
figure.add_axes ([
margin_left / figure_width,
(margin_bottom + index * (axes_height + inter_axes_distance)) / figure_height,
axes_width / figure_width,
axes_height / figure_height])
for index in range (number_axes)]
axes_temperature, axes_ir_raw, axes_activity = list_axes
# setup axes
axes_temperature.set_ylim (26, 38)
axes_ir_raw.set_ylim (0, 30000)
axes_activity.set_ylim (0, 1)
min_time = min ([a_casu_log.min_time () for a_casu_log in all_logs])
max_time = min ([a_casu_log.max_time () for a_casu_log in all_logs])
axes_temperature.set_xlabel ('time (m:ss)', fontsize = 7)
axes_temperature.set_ylabel (u'temperature (℃)', fontsize = 7)
axes_ir_raw.set_ylabel ('infrared (a.u.)', fontsize = 7)
axes_activity.set_ylabel ('sensor activity (a.u.)', fontsize = 7)
for axa in list_axes:
axa.set_xlim (min_time, max_time)
ts = [t for t in range (int (min_time), int (max_time), 60)]
axa.set_xticks (ts)
axa.set_xticklabels ([datetime.datetime.fromtimestamp (t - ts [0]).strftime ('%M:%S') for t in ts])
for ata in [axa.xaxis, axa.yaxis]:
for tick in ata.get_major_ticks ():
tick.label.set_fontsize (7)
# figure properties
figure.suptitle ('airflow test 2\nrun #{} core casu {} leaf casu {}'.format (run_number, core_casu_number, leaf_casu_number))
figure.legend (
handles = [
matplotlib.lines.Line2D (
xdata = [0, 1],
ydata = [1, 0],
linestyle = 'solid',
color = c)
for c in plot_common.COLOURS
],
labels = ['{}{}'.format (l, n) for l, n in zip (casu_labels, casu_numbers)],
loc = 'upper right',
fontsize = 7
)
# plot
casu_log_axes_dict = {
casu_log.IR_RAW : [axes_ir_raw],
casu_log.TEMP : [axes_temperature],
casu_log.AIRFLOW : [axes_ir_raw, axes_temperature],
casu_log.LED : [axes_ir_raw],
}
for index, a_casu_log in enumerate (casu_logs):
a_casu_log.plot (
index,
casu_log_axes_dict,
ir_raw_avg = True,
avg_temp = False,
temp_field = [assisipy.casu.TEMP_WAX]
)
casu_domset_log_axes_dict = {
casu_domset_log.CAS : [axes_activity],
casu_domset_log.CAC : [axes_activity],
casu_domset_log.NAC : [axes_activity],
casu_domset_log.CT : [axes_temperature],
casu_domset_log.NT : [axes_temperature],
casu_domset_log.CAF : [axes_activity],
}
for index, a_casu_domset_log in enumerate (casu_domset_logs):
a_casu_domset_log.plot (
index,
casu_domset_log_axes_dict,
avg_active_sensors = True
)
# final properties
for axa in list_axes:
axa.legend (
fontsize = 5
)
# save figure
figure.savefig ('casu-log_R{}-C{}-L{}.png'.format (run_number, core_casu_number, leaf_casu_number))
matplotlib.pyplot.close (figure)