def default_value(ethogram, behav, param):
"""
return value for duration in case of point event
"""
default_value_ = 0
if (project_functions.event_type(behav, ethogram) == "POINT EVENT"
and param in ["duration"]):
default_value_ = "-"
return default_value_
def default_value(ethogram, behav, param):
"""
return value for duration in case of point event
"""
default_value_ = 0
if (project_functions.event_type(behav, ethogram) == "POINT EVENT"
and param in ["duration"]):
default_value_ = "-"
return default_value_
def behaviors_bar_plot(pj, selected_observations, selected_subjects,
selected_behaviors, include_modifiers, interval,
start_time, end_time, plot_directory, output_format):
"""
scatter plot
"""
parameters = [
["duration", "Total duration"],
]
ok, msg, db_connector = db_functions.load_aggregated_events_in_db(
pj, selected_subjects, selected_observations, selected_behaviors)
if not ok:
return False, msg, None
cursor = db_connector.cursor()
if include_modifiers:
cursor.execute(
"SELECT distinct behavior, modifiers FROM aggregated_events")
distinct_behav_modif = [[rows["behavior"], rows["modifiers"]]
for rows in cursor.fetchall()]
else:
cursor.execute("SELECT distinct behavior FROM aggregated_events")
distinct_behav_modif = [[rows["behavior"], ""]
for rows in cursor.fetchall()]
# add selected behaviors that are not observed
for behav in selected_behaviors:
if [x for x in distinct_behav_modif if x[0] == behav] == []:
distinct_behav_modif.append([behav, "-"])
behaviors = init_behav_modif(pj[ETHOGRAM], selected_subjects,
distinct_behav_modif, include_modifiers,
parameters)
# select time interval
for obs_id in selected_observations:
if len(selected_subjects) > 1:
fig, axs = plt.subplots(nrows=1,
ncols=len(selected_subjects),
sharey=True)
else:
fig, ax = plt.subplots(nrows=1,
ncols=len(selected_subjects),
sharey=True)
axs = np.ndarray(shape=(1), dtype=type(ax))
axs[0] = ax
# if modifiers not to be included set modifiers to ""
if not include_modifiers:
cursor.execute("UPDATE aggregated_events SET modifiers = ''")
# time
obs_length = project_functions.observation_total_length(
pj[OBSERVATIONS][obs_id])
if obs_length == -1:
obs_length = 0
if interval == TIME_FULL_OBS:
min_time = float(0)
max_time = float(obs_length)
if interval == TIME_EVENTS:
try:
min_time = float(pj[OBSERVATIONS][obs_id][EVENTS][0][0])
except Exception:
min_time = float(0)
try:
max_time = float(pj[OBSERVATIONS][obs_id][EVENTS][-1][0])
except Exception:
max_time = float(obs_length)
if interval == TIME_ARBITRARY_INTERVAL:
min_time = float(start_time)
max_time = float(end_time)
cursor.execute(
"UPDATE aggregated_events SET start = ? WHERE observation = ? AND start < ? AND stop BETWEEN ? AND ?",
(
min_time,
obs_id,
min_time,
min_time,
max_time,
))
cursor.execute(
"UPDATE aggregated_events SET stop = ? WHERE observation = ? AND stop > ? AND start BETWEEN ? AND ?",
(
max_time,
obs_id,
max_time,
min_time,
max_time,
))
cursor.execute(
"UPDATE aggregated_events SET start = ?, stop = ? WHERE observation = ? AND start < ? AND stop > ?",
(
min_time,
max_time,
obs_id,
min_time,
max_time,
))
for subject in selected_subjects:
for behavior_modifiers in distinct_behav_modif:
behavior, modifiers = behavior_modifiers
# skip if behavior defined as POINT
if POINT in project_functions.event_type(
behavior, pj[ETHOGRAM]):
continue
behavior_modifiers_str = "|".join(
behavior_modifiers) if modifiers else behavior
# total duration
cursor.execute((
"SELECT SUM(stop-start) FROM aggregated_events "
"WHERE observation = ? AND subject = ? AND behavior = ? AND modifiers = ?"
), (
obs_id,
subject,
behavior,
modifiers,
))
for row in cursor.fetchall():
behaviors[subject][behavior_modifiers_str][
"duration"] = 0 if row[0] is None else row[0]
print("behaviors")
print(behaviors)
print()
print("sorted(distinct_behav_modif)", sorted(distinct_behav_modif))
max_length = 0
behaviors_duration = {}
mb = {}
for ax_idx, subj in enumerate(selected_subjects):
behaviors_duration[subj] = {}
behavior_ticks = []
for behavior_modifiers in sorted(distinct_behav_modif):
behavior, modifiers = behavior_modifiers
# skip if behavior defined as POINT
if POINT in project_functions.event_type(
behavior, pj[ETHOGRAM]):
continue
if behavior not in behaviors_duration[subj]:
behaviors_duration[subj][behavior] = [[], []]
behavior_modifiers_str = "|".join(
behavior_modifiers) if modifiers else behavior
if behavior not in behavior_ticks:
behavior_ticks.append(behavior)
for param in parameters:
behaviors_duration[subj][behavior][0].append(
behaviors[subj][behavior_modifiers_str][param[0]])
behaviors_duration[subj][behavior][1].append(modifiers)
max_length = max(
max_length, len(behaviors_duration[subj][behavior][1]))
print()
print("behaviors_duration", behaviors_duration)
print()
print("behavior_ticks", behavior_ticks)
print()
behavior_mod_ticks = behavior_ticks[:]
for ax_idx, subj in enumerate(selected_subjects):
print("subject", subj)
md_lgd = []
b = {}
for i in range(max_length):
b[i] = []
for behavior in sorted(behaviors_duration[subj].keys()):
try:
b[i].append(behaviors_duration[subj][behavior][0][i])
if include_modifiers:
if behaviors_duration[subj][behavior][1][i]:
md_lgd.append(
behavior + " " +
behaviors_duration[subj][behavior][1][i])
else:
md_lgd.append(behavior)
except Exception:
b[i].append(0)
print()
print("behavior_mod_ticks", behavior_mod_ticks)
print()
print("b")
print(b)
print()
print("md_lgd")
print(md_lgd)
ind = np.arange(len(behavior_ticks))
width = 0.35 # the width of the bars: can also be len(x) sequence
pp = []
max_obs = 0
bottom_ = []
idx_color = 0
for i in sorted(b.keys()):
if i == 0:
pp.append(axs[ax_idx].bar(
ind,
b[i],
width,
color=BEHAVIORS_PLOT_COLORS[idx_color:idx_color +
len(b[i])]))
else:
pp.append(axs[ax_idx].bar(
ind,
b[i],
width,
color=BEHAVIORS_PLOT_COLORS[idx_color:idx_color +
len(b[i])],
bottom=bottom_))
idx_color += len(b[i])
if not bottom_:
bottom_ = b[i]
else:
bottom_ = [x + bottom_[idx] for idx, x in enumerate(b[i])]
max_obs = max(max_obs, sum(b[i]))
if ax_idx == 0:
axs[ax_idx].set_ylabel("Duration (s)")
axs[ax_idx].set_xlabel("Behaviors")
axs[ax_idx].set_title(f"{subj}")
axs[ax_idx].set_xticks(ind)
axs[ax_idx].set_xticklabels(behavior_mod_ticks, rotation=90)
axs[ax_idx].set_yticks(np.arange(0, max(bottom_), 50))
lgd_col = []
for p in pp:
for r in p:
if r.get_height():
lgd_col.append(r)
plt.legend(lgd_col, md_lgd)
if plot_directory:
output_file_name = str(
pathlib.Path(
pathlib.Path(plot_directory) /
utilities.safeFileName(obs_id)).with_suffix("." +
file_format))
plt.savefig(output_file_name)
else:
plt.show()
def create_behaviors_bar_plot(pj: dict,
selected_observations: list,
param: dict,
plot_directory: str,
output_format: str,
plot_colors:list=BEHAVIORS_PLOT_COLORS):
"""
time budget bar plot
Args:
pj (dict): project
param (dict): parameters
plot_directory (str): path of directory
output_format (str): image format
Returns:
dict:
"""
selected_subjects = param[SELECTED_SUBJECTS]
selected_behaviors = param[SELECTED_BEHAVIORS]
time_interval = param["time"]
start_time = param[START_TIME]
end_time = param[END_TIME]
parameters = ["duration", "number of occurences"]
ok, msg, db_connector = db_functions.load_aggregated_events_in_db(pj,
selected_subjects,
selected_observations,
selected_behaviors)
if not ok:
return {"error": True, "message": msg}
try:
# extract all behaviors from ethogram for colors in plot
all_behaviors = [pj[ETHOGRAM][x][BEHAVIOR_CODE] for x in utilities.sorted_keys(pj[ETHOGRAM])]
for obs_id in selected_observations:
cursor = db_connector.cursor()
# distinct behaviors
cursor.execute("SELECT distinct behavior FROM aggregated_events WHERE observation = ?",
(obs_id,))
distinct_behav = [rows["behavior"] for rows in cursor.fetchall()]
# add selected behaviors that are not observed
'''
if not param[EXCLUDE_BEHAVIORS]:
for behavior in selected_behaviors:
if [x for x in distinct_behav if x == behavior] == []:
distinct_behav.append(behavior)
'''
# distinct subjects
cursor.execute("SELECT distinct subject FROM aggregated_events WHERE observation = ?",
(obs_id,))
distinct_subjects = [rows["subject"] for rows in cursor.fetchall()]
behaviors = init_behav(pj[ETHOGRAM],
distinct_subjects,
distinct_behav,
parameters)
# plot creation
if len(distinct_subjects) > 1:
fig, axs = plt.subplots(nrows=1, ncols=len(distinct_subjects), sharey=True)
fig2, axs2 = plt.subplots(nrows=1, ncols=len(distinct_subjects), sharey=True)
else:
fig, ax = plt.subplots(nrows=1, ncols=len(distinct_subjects), sharey=True)
axs = np.ndarray(shape=(1), dtype=type(ax))
axs[0] = ax
fig2, ax2 = plt.subplots(nrows=1, ncols=len(distinct_subjects), sharey=True)
axs2 = np.ndarray(shape=(1), dtype=type(ax2))
axs2[0] = ax2
fig.suptitle("Durations of behaviors")
fig2.suptitle("Number of occurences of behaviors")
# if modifiers not to be included set modifiers to ""
cursor.execute("UPDATE aggregated_events SET modifiers = ''")
# time
obs_length = project_functions.observation_total_length(pj[OBSERVATIONS][obs_id])
if obs_length == -1:
obs_length = 0
if param["time"] == TIME_FULL_OBS:
min_time = float(0)
max_time = float(obs_length)
if param["time"] == TIME_EVENTS:
try:
min_time = float(pj[OBSERVATIONS][obs_id][EVENTS][0][0])
except Exception:
min_time = float(0)
try:
max_time = float(pj[OBSERVATIONS][obs_id][EVENTS][-1][0])
except Exception:
max_time = float(obs_length)
if param["time"] == TIME_ARBITRARY_INTERVAL:
min_time = float(start_time)
max_time = float(end_time)
cursor.execute("UPDATE aggregated_events SET start = ? WHERE observation = ? AND start < ? AND stop BETWEEN ? AND ?",
(min_time, obs_id, min_time, min_time, max_time, ))
cursor.execute("UPDATE aggregated_events SET stop = ? WHERE observation = ? AND stop > ? AND start BETWEEN ? AND ?",
(max_time, obs_id, max_time, min_time, max_time, ))
cursor.execute("UPDATE aggregated_events SET start = ?, stop = ? WHERE observation = ? AND start < ? AND stop > ?",
(min_time, max_time, obs_id, min_time, max_time, ))
for ax_idx, subject in enumerate(sorted(distinct_subjects)):
for behavior in distinct_behav:
# number of occurences
cursor.execute(("SELECT COUNT(*) AS count FROM aggregated_events "
"WHERE observation = ? AND subject = ? AND behavior = ?"),
(obs_id, subject, behavior, ))
for row in cursor.fetchall():
behaviors[subject][behavior]["number of occurences"] = 0 if row["count"] is None else row["count"]
# total duration
if STATE in project_functions.event_type(behavior, pj[ETHOGRAM]):
cursor.execute(("SELECT SUM(stop - start) AS duration FROM aggregated_events "
"WHERE observation = ? AND subject = ? AND behavior = ?"),
(obs_id, subject, behavior, ))
for row in cursor.fetchall():
behaviors[subject][behavior]["duration"] = 0 if row["duration"] is None else row["duration"]
durations, n_occurences, colors, x_labels, colors_duration, x_labels_duration = [], [], [], [], [], []
for behavior in sorted(distinct_behav):
if param[EXCLUDE_BEHAVIORS] and behaviors[subject][behavior]["number of occurences"] == 0:
continue
n_occurences.append(behaviors[subject][behavior]["number of occurences"])
x_labels.append(behavior)
try:
colors.append(utilities.behavior_color(plot_colors, all_behaviors.index(behavior)))
except Exception:
colors.append("darkgray")
if STATE in project_functions.event_type(behavior, pj[ETHOGRAM]):
durations.append(behaviors[subject][behavior]["duration"])
x_labels_duration.append(behavior)
try:
colors_duration.append(utilities.behavior_color(plot_colors, all_behaviors.index(behavior)))
except Exception:
colors_duration.append("darkgray")
#width = 0.35 # the width of the bars: can also be len(x) sequence
axs2[ax_idx].bar(np.arange(len(n_occurences)),
n_occurences,
#width,
color=colors
)
axs[ax_idx].bar(np.arange(len(durations)),
durations,
#width,
color=colors_duration
)
if ax_idx == 0:
axs[ax_idx].set_ylabel("Duration (s)")
axs[ax_idx].set_xlabel("Behaviors")
axs[ax_idx].set_title(f"{subject}")
axs[ax_idx].set_xticks(np.arange(len(durations)))
axs[ax_idx].set_xticklabels(x_labels_duration, rotation='vertical', fontsize=8)
if ax_idx == 0:
axs2[ax_idx].set_ylabel("Number of occurences")
axs2[ax_idx].set_xlabel("Behaviors")
axs2[ax_idx].set_title(f"{subject}")
axs2[ax_idx].set_xticks(np.arange(len(n_occurences)))
axs2[ax_idx].set_xticklabels(x_labels, rotation='vertical', fontsize=8)
fig.align_labels()
fig.tight_layout(rect=[0, 0.03, 1, 0.95])
fig2.align_labels()
fig2.tight_layout(rect=[0, 0.03, 1, 0.95])
if plot_directory:
# output_file_name = f"{pathlib.Path(plot_directory) / utilities.safeFileName(obs_id)}.{output_format}"
fig.savefig(f"{pathlib.Path(plot_directory) / utilities.safeFileName(obs_id)}.duration.{output_format}")
fig2.savefig(f"{pathlib.Path(plot_directory) / utilities.safeFileName(obs_id)}.number_of_occurences.{output_format}")
plt.close()
else:
fig.show()
fig2.show()
return {}
except Exception:
error_type, error_file_name, error_lineno = utilities.error_info(sys.exc_info())
logging.critical(f"Error in time budget bar plot: {error_type} {error_file_name} {error_lineno}")
return {"error": True, "exception": sys.exc_info()}
def time_budget_analysis(ethogram: dict,
cursor,
selected_observations: list,
parameters: dict,
by_category: bool = False):
"""
extract number of occurrences, total duration, mean ...
if start_time = 0 and end_time = 0 all events are extracted
Args:
ethogram (dict): project ethogram
cursor: cursor on temporary database
selected_observations (list): selected observations
parameters (dict): parameters for analysis
by_category (bool): True for grouping in category else False
Returns:
list: results
dict:
"""
categories, out = {}, []
for subject in parameters[SELECTED_SUBJECTS]:
out_cat, categories[subject] = [], {}
for behavior in parameters[SELECTED_BEHAVIORS]:
if parameters[INCLUDE_MODIFIERS]:
cursor.execute(
"SELECT DISTINCT modifiers FROM events WHERE subject = ? AND code = ?",
(subject, behavior))
distinct_modifiers = list(cursor.fetchall())
if not distinct_modifiers:
if not parameters[EXCLUDE_BEHAVIORS]:
if STATE in project_functions.event_type(
behavior, ethogram):
out.append({
"subject": subject,
"behavior": behavior,
"modifiers": "",
"duration": 0,
"duration_mean": 0,
"duration_stdev": "NA",
"number": "0",
"inter_duration_mean": "NA",
"inter_duration_stdev": "NA"
})
else: # point
out.append({
"subject": subject,
"behavior": behavior,
"modifiers": "",
"duration": 0,
"duration_mean": 0,
"duration_stdev": "NA",
"number": "0",
"inter_duration_mean": "NA",
"inter_duration_stdev": "NA"
})
continue
if POINT in project_functions.event_type(behavior, ethogram):
for modifier in distinct_modifiers:
cursor.execute(
("SELECT occurence, observation FROM events "
"WHERE subject = ? "
"AND code = ? "
"AND modifiers = ? "
"ORDER BY observation, occurence"),
(subject, behavior, modifier[0]))
rows = cursor.fetchall()
# inter events duration
all_event_interdurations = []
for idx, row in enumerate(rows):
if idx and row[1] == rows[idx - 1][1]:
all_event_interdurations.append(
float(row[0]) - float(rows[idx - 1][0]))
out_cat.append({
"subject":
subject,
"behavior":
behavior,
"modifiers":
modifier[0],
"duration":
NA,
"duration_mean":
NA,
"duration_stdev":
NA,
"number":
len(rows),
"inter_duration_mean":
round(statistics.mean(all_event_interdurations), 3)
if len(all_event_interdurations) else NA,
"inter_duration_stdev":
round(statistics.stdev(all_event_interdurations),
3)
if len(all_event_interdurations) > 1 else NA
})
if STATE in project_functions.event_type(behavior, ethogram):
for modifier in distinct_modifiers:
cursor.execute(
("SELECT occurence, observation FROM events "
"WHERE subject = ? "
"AND code = ? "
"AND modifiers = ? "
"ORDER BY observation, occurence"),
(subject, behavior, modifier[0]))
rows = list(cursor.fetchall())
if len(rows) % 2:
out.append({
"subject": subject,
"behavior": behavior,
"modifiers": modifier[0],
"duration": UNPAIRED,
"duration_mean": UNPAIRED,
"duration_stdev": UNPAIRED,
"number": UNPAIRED,
"inter_duration_mean": UNPAIRED,
"inter_duration_stdev": UNPAIRED
})
else:
all_event_durations, all_event_interdurations = [], []
for idx, row in enumerate(rows):
# event
if idx % 2 == 0:
new_init, new_end = float(row[0]), float(
rows[idx + 1][0])
all_event_durations.append(new_end -
new_init)
# inter event if same observation
if idx % 2 and idx != len(rows) - 1 and row[
1] == rows[idx + 1][1]:
if (parameters["start time"] <= row[0] <=
parameters["end time"]
and parameters["start time"] <=
rows[idx + 1][0] <=
parameters["end time"]):
all_event_interdurations.append(
float(rows[idx + 1][0]) -
float(row[0]))
out_cat.append({
"subject":
subject,
"behavior":
behavior,
"modifiers":
modifier[0],
"duration":
round(sum(all_event_durations), 3),
"duration_mean":
round(statistics.mean(all_event_durations), 3)
if len(all_event_durations) else "NA",
"duration_stdev":
round(statistics.stdev(all_event_durations), 3)
if len(all_event_durations) > 1 else "NA",
"number":
len(all_event_durations),
"inter_duration_mean":
round(
statistics.mean(all_event_interdurations),
3)
if len(all_event_interdurations) else "NA",
"inter_duration_stdev":
round(
statistics.stdev(all_event_interdurations),
3)
if len(all_event_interdurations) > 1 else "NA"
})
else: # no modifiers
if POINT in project_functions.event_type(behavior, ethogram):
cursor.execute((
"SELECT occurence,observation FROM events "
"WHERE subject = ? AND code = ? ORDER BY observation, occurence"
), (subject, behavior))
rows = list(cursor.fetchall())
if len(selected_observations) == 1:
new_rows = []
for occurence, observation in rows:
new_occurence = max(
float(parameters["start time"]), occurence)
new_occurence = min(new_occurence,
float(parameters["end time"]))
new_rows.append([new_occurence, observation])
rows = list(new_rows)
# include behaviors without events
if not len(rows):
if not parameters[EXCLUDE_BEHAVIORS]:
out.append({
"subject": subject,
"behavior": behavior,
"modifiers": "",
"duration": NA,
"duration_mean": NA,
"duration_stdev": NA,
"number": "0",
"inter_duration_mean": NA,
"inter_duration_stdev": NA
})
continue
# inter events duration
all_event_interdurations = []
for idx, row in enumerate(rows):
if idx and row[1] == rows[idx - 1][1]:
all_event_interdurations.append(
float(row[0]) - float(rows[idx - 1][0]))
out_cat.append({
"subject":
subject,
"behavior":
behavior,
"modifiers":
"",
"duration":
NA,
"duration_mean":
NA,
"duration_stdev":
NA,
"number":
len(rows),
"inter_duration_mean":
round(statistics.mean(all_event_interdurations), 3)
if len(all_event_interdurations) else NA,
"inter_duration_stdev":
round(statistics.stdev(all_event_interdurations), 3)
if len(all_event_interdurations) > 1 else NA
})
if STATE in project_functions.event_type(behavior, ethogram):
cursor.execute((
"SELECT occurence, observation FROM events "
"WHERE subject = ? AND code = ? ORDER BY observation, occurence"
), (subject, behavior))
rows = list(cursor.fetchall())
if not len(rows):
if not parameters[
EXCLUDE_BEHAVIORS]: # include behaviors without events
out.append({
"subject": subject,
"behavior": behavior,
"modifiers": "",
"duration": 0,
"duration_mean": 0,
"duration_stdev": "NA",
"number": 0,
"inter_duration_mean": "-",
"inter_duration_stdev": "-"
})
continue
if len(rows) % 2:
out.append({
"subject": subject,
"behavior": behavior,
"modifiers": "",
"duration": UNPAIRED,
"duration_mean": UNPAIRED,
"duration_stdev": UNPAIRED,
"number": UNPAIRED,
"inter_duration_mean": UNPAIRED,
"inter_duration_stdev": UNPAIRED
})
else:
all_event_durations, all_event_interdurations = [], []
for idx, row in enumerate(rows):
# event
if idx % 2 == 0:
new_init, new_end = float(row[0]), float(
rows[idx + 1][0])
all_event_durations.append(new_end - new_init)
# inter event if same observation
if idx % 2 and idx != len(rows) - 1 and row[
1] == rows[idx + 1][1]:
if (parameters["start time"] <= row[0] <=
parameters["end time"]
and parameters["start time"] <=
rows[idx + 1][0] <=
parameters["end time"]):
all_event_interdurations.append(
float(rows[idx + 1][0]) -
float(row[0]))
out_cat.append({
"subject":
subject,
"behavior":
behavior,
"modifiers":
"",
"duration":
round(sum(all_event_durations), 3),
"duration_mean":
round(statistics.mean(all_event_durations), 3)
if len(all_event_durations) else NA,
"duration_stdev":
round(statistics.stdev(all_event_durations), 3)
if len(all_event_durations) > 1 else NA,
"number":
len(all_event_durations),
"inter_duration_mean":
round(statistics.mean(all_event_interdurations), 3)
if len(all_event_interdurations) else NA,
"inter_duration_stdev":
round(statistics.stdev(all_event_interdurations),
3)
if len(all_event_interdurations) > 1 else NA
})
out += out_cat
if by_category: # and flagCategories:
for behav in out_cat:
try:
category = [
ethogram[x]["category"] for x in ethogram
if "category" in ethogram[x]
and ethogram[x]["code"] == behav['behavior']
][0]
except Exception:
category = ""
if category in categories[subject]:
if behav["duration"] not in [
"-", "NA"
] and categories[subject][category]["duration"] not in [
"-", "NA"
]:
categories[subject][category]["duration"] += behav[
"duration"]
else:
categories[subject][category]["duration"] = "-"
categories[subject][category]["number"] += behav["number"]
else:
categories[subject][category] = {
"duration": behav["duration"],
"number": behav["number"]
}
out_sorted = []
for subject in parameters[SELECTED_SUBJECTS]:
for behavior in parameters[SELECTED_BEHAVIORS]:
for row in out:
if row["subject"] == subject and row["behavior"] == behavior:
out_sorted.append(row)
# http://stackoverflow.com/questions/673867/python-arbitrary-order-by
return out_sorted, categories
def export_aggregated_events(pj, parameters, obsId):
"""
export aggregated events
Args:
pj (dict): BORIS project
parameters (dict): subjects, behaviors
obsId (str): observation id
Returns:
tablib.Dataset:
"""
data = tablib.Dataset()
observation = pj[OBSERVATIONS][obsId]
duration1 = [] # in seconds
if observation[TYPE] in [MEDIA]:
try:
for mediaFile in observation[FILE][PLAYER1]:
if "media_info" in observation:
duration1.append(
observation["media_info"]["length"][mediaFile])
except:
duration1 = []
total_length = "{0:.3f}".format(
project_functions.observation_total_length(observation))
cursor = db_functions.load_events_in_db(pj,
parameters["selected subjects"],
[obsId],
parameters["selected behaviors"])
for subject in parameters["selected subjects"]:
for behavior in parameters["selected behaviors"]:
cursor.execute(
"SELECT occurence, modifiers, comment FROM events WHERE observation = ? AND subject = ? AND code = ? ORDER by occurence",
(obsId, subject, behavior))
rows = list(cursor.fetchall())
for idx, row in enumerate(rows):
if observation[TYPE] in [MEDIA]:
if duration1:
mediaFileIdx = [
idx1 for idx1, x in enumerate(duration1)
if row["occurence"] >= sum(duration1[0:idx1])
][-1]
mediaFileString = observation[FILE][PLAYER1][
mediaFileIdx]
fpsString = observation["media_info"]["fps"][
observation[FILE][PLAYER1][mediaFileIdx]]
else:
mediaFileString = "-"
fpsString = "NA"
if observation[TYPE] in [LIVE]:
mediaFileString = "LIVE"
fpsString = "NA"
if POINT in project_functions.event_type(
behavior, pj[ETHOGRAM]):
row_data = []
row_data.extend([
obsId, observation["date"].replace("T", " "),
mediaFileString, total_length, fpsString
])
# independent variables
if INDEPENDENT_VARIABLES in pj:
for idx_var in utilities.sorted_keys(
pj[INDEPENDENT_VARIABLES]):
if pj[INDEPENDENT_VARIABLES][idx_var][
"label"] in observation[
INDEPENDENT_VARIABLES]:
row_data.append(
observation[INDEPENDENT_VARIABLES][
pj[INDEPENDENT_VARIABLES][idx_var]
["label"]])
else:
row_data.append("")
row_data.extend([
subject,
behavior,
row["modifiers"].strip(),
POINT,
"{0:.3f}".format(row["occurence"]), # start
"NA", # stop
"NA", # duration
row["comment"],
""
])
data.append(row_data)
if STATE in project_functions.event_type(
behavior, pj[ETHOGRAM]):
if idx % 2 == 0:
row_data = []
row_data.extend([
obsId, observation["date"].replace("T", " "),
mediaFileString, total_length, fpsString
])
# independent variables
if INDEPENDENT_VARIABLES in pj:
for idx_var in utilities.sorted_keys(
pj[INDEPENDENT_VARIABLES]):
if pj[INDEPENDENT_VARIABLES][idx_var][
"label"] in observation[
INDEPENDENT_VARIABLES]:
row_data.append(
observation[INDEPENDENT_VARIABLES][
pj[INDEPENDENT_VARIABLES][idx_var]
["label"]])
else:
row_data.append("")
row_data.extend([
subject, behavior, row["modifiers"].strip(), STATE,
"{0:.3f}".format(row["occurence"]),
"{0:.3f}".format(rows[idx + 1]["occurence"]),
"{0:.3f}".format(rows[idx + 1]["occurence"] -
row["occurence"]), row["comment"],
rows[idx + 1]["comment"]
])
data.append(row_data)
return data
def behaviors_bar_plot(pj, selected_observations, selected_subjects, selected_behaviors, include_modifiers,
interval, start_time, end_time,
plot_directory, output_format):
"""
scatter plot
"""
parameters = [["duration", "Total duration"],
]
ok, msg, db_connector = db_functions.load_aggregated_events_in_db(pj,
selected_subjects,
selected_observations,
selected_behaviors)
if not ok:
return False, msg, None
cursor = db_connector.cursor()
if include_modifiers:
cursor.execute("SELECT distinct behavior, modifiers FROM aggregated_events")
distinct_behav_modif = [[rows["behavior"], rows["modifiers"]] for rows in cursor.fetchall()]
else:
cursor.execute("SELECT distinct behavior FROM aggregated_events")
distinct_behav_modif = [[rows["behavior"], ""] for rows in cursor.fetchall()]
# add selected behaviors that are not observed
for behav in selected_behaviors:
if [x for x in distinct_behav_modif if x[0] == behav] == []:
distinct_behav_modif.append([behav, "-"])
behaviors = init_behav_modif(pj[ETHOGRAM],
selected_subjects,
distinct_behav_modif,
include_modifiers,
parameters)
# select time interval
for obs_id in selected_observations:
if len(selected_subjects) > 1:
fig, axs = plt.subplots(nrows=1, ncols=len(selected_subjects), sharey=True)
else:
fig, ax = plt.subplots(nrows=1, ncols=len(selected_subjects), sharey=True)
axs = np.ndarray(shape=(1), dtype=type(ax))
axs[0] = ax
# if modifiers not to be included set modifiers to ""
if not include_modifiers:
cursor.execute("UPDATE aggregated_events SET modifiers = ''")
# time
obs_length = project_functions.observation_total_length(pj[OBSERVATIONS][obs_id])
if obs_length == -1:
obs_length = 0
if interval == TIME_FULL_OBS:
min_time = float(0)
max_time = float(obs_length)
if interval == TIME_EVENTS:
try:
min_time = float(pj[OBSERVATIONS][obs_id][EVENTS][0][0])
except Exception:
min_time = float(0)
try:
max_time = float(pj[OBSERVATIONS][obs_id][EVENTS][-1][0])
except Exception:
max_time = float(obs_length)
if interval == TIME_ARBITRARY_INTERVAL:
min_time = float(start_time)
max_time = float(end_time)
cursor.execute("UPDATE aggregated_events SET start = ? WHERE observation = ? AND start < ? AND stop BETWEEN ? AND ?",
(min_time, obs_id, min_time, min_time, max_time, ))
cursor.execute("UPDATE aggregated_events SET stop = ? WHERE observation = ? AND stop > ? AND start BETWEEN ? AND ?",
(max_time, obs_id, max_time, min_time, max_time, ))
cursor.execute("UPDATE aggregated_events SET start = ?, stop = ? WHERE observation = ? AND start < ? AND stop > ?",
(min_time, max_time, obs_id, min_time, max_time, ))
for subject in selected_subjects:
for behavior_modifiers in distinct_behav_modif:
behavior, modifiers = behavior_modifiers
# skip if behavior defined as POINT
if POINT in project_functions.event_type(behavior, pj[ETHOGRAM]):
continue
behavior_modifiers_str = "|".join(behavior_modifiers) if modifiers else behavior
# total duration
cursor.execute(("SELECT SUM(stop-start) FROM aggregated_events "
"WHERE observation = ? AND subject = ? AND behavior = ? AND modifiers = ?"),
(obs_id, subject, behavior, modifiers,))
for row in cursor.fetchall():
behaviors[subject][behavior_modifiers_str]["duration"] = 0 if row[0] is None else row[0]
print("behaviors")
print(behaviors)
print()
print("sorted(distinct_behav_modif)", sorted(distinct_behav_modif))
max_length = 0
behaviors_duration = {}
mb = {}
for ax_idx, subj in enumerate(selected_subjects):
behaviors_duration[subj] = {}
behavior_ticks = []
for behavior_modifiers in sorted(distinct_behav_modif):
behavior, modifiers = behavior_modifiers
# skip if behavior defined as POINT
if POINT in project_functions.event_type(behavior, pj[ETHOGRAM]):
continue
if behavior not in behaviors_duration[subj]:
behaviors_duration[subj][behavior] = [[],[]]
behavior_modifiers_str = "|".join(behavior_modifiers) if modifiers else behavior
#print(subj, behavior, modifiers)
if behavior not in behavior_ticks:
behavior_ticks.append(behavior)
for param in parameters:
behaviors_duration[subj][behavior][0].append(behaviors[subj][behavior_modifiers_str][param[0]])
behaviors_duration[subj][behavior][1].append(modifiers)
max_length = max(max_length, len(behaviors_duration[subj][behavior][1]))
print()
print("behaviors_duration", behaviors_duration)
print()
print("behavior_ticks", behavior_ticks)
print()
#b = {}
behavior_mod_ticks = behavior_ticks[:]
for ax_idx, subj in enumerate(selected_subjects):
print("subject", subj)
md_lgd = []
b = {}
for i in range(max_length):
b[i] = []
for behavior in sorted(behaviors_duration[subj].keys()):
try:
b[i].append(behaviors_duration[subj][behavior][0][i])
if include_modifiers:
'''
if behaviors_duration[subj][behavior][1][i]:
behavior_mod_ticks[behavior_ticks.index(behavior)] = behavior_mod_ticks[behavior_ticks.index(behavior)] + "\n" + \
behaviors_duration[subj][behavior][1][i]
'''
if behaviors_duration[subj][behavior][1][i]:
md_lgd.append(behavior + " " + behaviors_duration[subj][behavior][1][i])
else:
md_lgd.append(behavior)
except:
b[i].append(0)
print()
print("behavior_mod_ticks", behavior_mod_ticks)
print()
print("b")
print(b)
print()
print("md_lgd")
print(md_lgd)
#ind = np.arange(len(behavior_ticks)) # the x locations for the groups
ind = np.arange(len(behavior_ticks))
width = 0.35 # the width of the bars: can also be len(x) sequence
pp = []
max_obs = 0
bottom_ = []
idx_color = 0
for i in sorted(b.keys()):
print(i, b[i])
if i == 0:
pp.append(axs[ax_idx].bar(ind, b[i], width, color=BEHAVIORS_PLOT_COLORS[idx_color:idx_color + len(b[i])]))
else:
pp.append(axs[ax_idx].bar(ind, b[i], width, color=BEHAVIORS_PLOT_COLORS[idx_color:idx_color + len(b[i])], bottom=bottom_))
idx_color += len(b[i])
if not bottom_:
bottom_ = b[i]
else:
bottom_ = [x + bottom_[idx] for idx,x in enumerate(b[i])]
max_obs = max(max_obs, sum(b[i]))
if ax_idx == 0:
axs[ax_idx].set_ylabel('Duration (s)')
axs[ax_idx].set_xlabel('Behaviors')
axs[ax_idx].set_title('{}'.format(subj))
axs[ax_idx].set_xticks(ind)
axs[ax_idx].set_xticklabels(behavior_mod_ticks,rotation=90)
axs[ax_idx].set_yticks(np.arange(0, max(bottom_), 50))
lgd_col = []
for p in pp:
for r in p:
if r.get_height():
lgd_col.append(r)
plt.legend(lgd_col, md_lgd)
if plot_directory:
output_file_name = str(pathlib.Path(pathlib.Path(plot_directory) / utilities.safeFileName(obs_id)).with_suffix("." + file_format))
plt.savefig(output_file_name)
else:
plt.show()
