def behav_color(behav):
"""
return color corresponding to behavior
if color not found returns "darkgray"
see BEHAVIORS_PLOT_COLORS list in config.py
"""
if behav in all_behaviors:
return utilities.behavior_color(plot_colors, all_behaviors.index(behav))
else:
return "darkgray"
def create_events_plot(pj,
selected_observations,
parameters,
plot_colors=BEHAVIORS_PLOT_COLORS,
plot_directory="",
file_format="png"):
selected_subjects = parameters[SELECTED_SUBJECTS]
selected_behaviors = parameters[SELECTED_BEHAVIORS]
include_modifiers = parameters[INCLUDE_MODIFIERS]
interval = parameters[TIME_INTERVAL]
start_time = parameters[START_TIME]
end_time = parameters[END_TIME]
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 modifiers not to be included set modifiers to ""
if not include_modifiers:
cursor.execute("UPDATE aggregated_events SET modifiers = ''")
cursor.execute(
"SELECT distinct behavior, modifiers FROM aggregated_events")
distinct_behav_modif = [[rows["behavior"], rows["modifiers"]]
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, "-"])
distinct_behav_modif = sorted(distinct_behav_modif)
max_len = len(distinct_behav_modif)
all_behaviors = [
pj[ETHOGRAM][x][BEHAVIOR_CODE]
for x in utilities.sorted_keys(pj[ETHOGRAM])
]
par1 = 1
bar_height = 0.5
init = dt.datetime(2017, 1, 1)
for obs_id in selected_observations:
if len(selected_subjects) > 1:
fig, axs = plt.subplots(figsize=(20, 8),
nrows=len(selected_subjects),
ncols=1,
sharex=True)
else:
fig, ax = plt.subplots(figsize=(20, 8),
nrows=len(selected_subjects),
ncols=1,
sharex=True)
axs = np.ndarray(shape=(1), dtype=type(ax))
axs[0] = ax
ok, msg, db_connector = db_functions.load_aggregated_events_in_db(
pj, selected_subjects, [obs_id], selected_behaviors)
cursor = db_connector.cursor()
# if modifiers not to be included set modifiers to ""
if not include_modifiers:
cursor.execute("UPDATE aggregated_events SET modifiers = ''")
cursor = db_connector.cursor()
cursor.execute(
"SELECT distinct behavior, modifiers FROM aggregated_events")
distinct_behav_modif = [[rows["behavior"], rows["modifiers"]]
for rows in cursor.fetchall()]
# add selected behaviors that are not observed
if not parameters["exclude behaviors"]:
for behav in selected_behaviors:
if [x for x in distinct_behav_modif if x[0] == behav] == []:
distinct_behav_modif.append([behav, "-"])
distinct_behav_modif = sorted(distinct_behav_modif)
max_len = len(distinct_behav_modif)
# time
obs_length = project_functions.observation_total_length(
pj[OBSERVATIONS][obs_id])
if obs_length == -1: # media length not available
interval = TIME_EVENTS
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,
))
ylabels = [" ".join(x) for x in distinct_behav_modif]
for ax_idx, subject in enumerate(selected_subjects):
if parameters["exclude behaviors"]:
cursor.execute(
"SELECT distinct behavior, modifiers FROM aggregated_events WHERE subject = ?",
(subject, ))
distinct_behav_modif = [[rows["behavior"], rows["modifiers"]]
for rows in cursor.fetchall()]
# add selected behaviors that are not observed
if not parameters["exclude behaviors"]:
for behav in selected_behaviors:
if [x for x in distinct_behav_modif
if x[0] == behav] == []:
distinct_behav_modif.append([behav, "-"])
distinct_behav_modif = sorted(distinct_behav_modif)
max_len = len(distinct_behav_modif)
ylabels = [" ".join(x) for x in distinct_behav_modif]
if not ax_idx:
axs[ax_idx].set_title(f"Observation {obs_id}\n{subject}",
fontsize=14)
else:
axs[ax_idx].set_title(subject, fontsize=14)
bars = {}
i = 0
for behavior_modifiers in distinct_behav_modif:
behavior, modifiers = behavior_modifiers
behavior_modifiers_str = "|".join(
behavior_modifiers) if modifiers else behavior
bars[behavior_modifiers_str] = []
# total duration
cursor.execute((
"SELECT start,stop FROM aggregated_events "
"WHERE observation = ? AND subject = ? AND behavior = ? AND modifiers = ?"
), (
obs_id,
subject,
behavior,
modifiers,
))
for row in cursor.fetchall():
bars[behavior_modifiers_str].append(
(row["start"], row["stop"]))
start_date = matplotlib.dates.date2num(init + dt.timedelta(
seconds=row["start"]))
end_date = matplotlib.dates.date2num(init + dt.timedelta(
seconds=row["stop"] + POINT_EVENT_PLOT_DURATION *
(row["stop"] == row["start"])))
try:
bar_color = utilities.behavior_color(
plot_colors, all_behaviors.index(behavior))
except Exception:
bar_color = "darkgray"
bar_color = POINT_EVENT_PLOT_COLOR if row["stop"] == row[
"start"] else bar_color
# sage colors removed from matplotlib colors list
if bar_color in ["sage", "darksage", "lightsage"]:
bar_color = {
"darksage": "#598556",
"lightsage": "#bcecac",
"sage": "#87ae73"
}[bar_color]
try:
axs[ax_idx].barh((i * par1) + par1,
end_date - start_date,
left=start_date,
height=bar_height,
align="center",
edgecolor=bar_color,
color=bar_color,
alpha=1)
except Exception:
axs[ax_idx].barh((i * par1) + par1,
end_date - start_date,
left=start_date,
height=bar_height,
align="center",
edgecolor="darkgray",
color="darkgray",
alpha=1)
i += 1
axs[ax_idx].set_ylim(bottom=0, top=(max_len * par1) + par1)
pos = np.arange(par1, max_len * par1 + par1 + 1, par1)
axs[ax_idx].set_yticks(pos[:len(ylabels)])
axs[ax_idx].set_yticklabels(ylabels, fontdict={"fontsize": 10})
axs[ax_idx].set_ylabel("Behaviors" +
" (modifiers)" * include_modifiers,
fontdict={"fontsize": 10})
axs[ax_idx].set_xlim(
left=matplotlib.dates.date2num(init +
dt.timedelta(seconds=min_time)),
right=matplotlib.dates.date2num(init + dt.timedelta(
seconds=max_time + 1)))
axs[ax_idx].grid(color="g", linestyle=":")
axs[ax_idx].xaxis_date()
axs[ax_idx].xaxis.set_major_formatter(DateFormatter("%H:%M:%S"))
axs[ax_idx].set_xlabel("Time (HH:MM:SS)",
fontdict={"fontsize": 12})
axs[ax_idx].invert_yaxis()
fig.autofmt_xdate()
plt.tight_layout()
if len(selected_observations) > 1:
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 test_idx1000(self):
assert utilities.behavior_color(config.BEHAVIORS_PLOT_COLORS, 1000) == "midnightblue"
def test_idx0(self):
assert utilities.behavior_color(config.BEHAVIORS_PLOT_COLORS, 0) == "tab:blue"
def test_idx1000(self):
assert utilities.behavior_color(config.BEHAVIORS_PLOT_COLORS, 1000) == "midnightblue"
def test_idx0(self):
assert utilities.behavior_color(config.BEHAVIORS_PLOT_COLORS, 0) == "tab:blue"
def plot_time_ranges(pj, time_format, plot_colors, obs, obsId, minTime,
videoLength, excludeBehaviorsWithoutEvents, line_width):
"""
create "hlines" matplotlib plot
used by plot_event function (legacy)
"""
def on_draw(event):
# http://matplotlib.org/faq/howto_faq.html#move-the-edge-of-an-axes-to-make-room-for-tick-labels
bboxes = []
for label in labels:
bbox = label.get_window_extent()
bboxi = bbox.inverse_transformed(fig.transFigure)
bboxes.append(bboxi)
bbox = mtransforms.Bbox.union(bboxes)
if fig.subplotpars.left < bbox.width:
fig.subplots_adjust(left=1.1 * bbox.width)
fig.canvas.draw()
return False
LINE_WIDTH = line_width
all_behaviors, observedBehaviors = [], []
maxTime = 0 # max time in all events of all subjects
# all behaviors defined in project without modifiers
all_project_behaviors = [
pj[ETHOGRAM][idx]["code"]
for idx in utilities.sorted_keys(pj[ETHOGRAM])
]
all_project_subjects = [NO_FOCAL_SUBJECT] + [
pj[SUBJECTS][idx]["name"]
for idx in utilities.sorted_keys(pj[SUBJECTS])
]
for subject in obs:
for behavior_modifiers_json in obs[subject]:
behavior_modifiers = json.loads(behavior_modifiers_json)
if not excludeBehaviorsWithoutEvents:
observedBehaviors.append(behavior_modifiers_json)
else:
if obs[subject][behavior_modifiers_json]:
observedBehaviors.append(behavior_modifiers_json)
if not behavior_modifiers_json in all_behaviors:
all_behaviors.append(behavior_modifiers_json)
for t1, t2 in obs[subject][behavior_modifiers_json]:
maxTime = max(maxTime, t1, t2)
observedBehaviors.append("")
lbl = []
if excludeBehaviorsWithoutEvents:
for behav_modif_json in observedBehaviors:
if not behav_modif_json:
lbl.append("")
continue
behav_modif = json.loads(behav_modif_json)
if len(behav_modif) == 2:
lbl.append("{0} ({1})".format(behav_modif[0], behav_modif[1]))
else:
lbl.append(behav_modif[0])
else:
all_behaviors.append('[""]') # empty json list element
for behav_modif_json in all_behaviors:
behav_modif = json.loads(behav_modif_json)
if len(behav_modif) == 2:
lbl.append("{0} ({1})".format(behav_modif[0], behav_modif[1]))
else:
lbl.append(behav_modif[0])
lbl = lbl[:] * len(obs)
lbl = lbl[:-1] # remove last empty line
fig = plt.figure(figsize=(20, 10))
fig.suptitle("Time diagram of observation {}".format(obsId), fontsize=14)
ax = fig.add_subplot(111)
labels = ax.set_yticklabels(lbl)
ax.set_ylabel("Behaviors")
if time_format == HHMMSS:
fmtr = matplotlib.dates.DateFormatter("%H:%M:%S") # %H:%M:%S:%f
ax.xaxis.set_major_formatter(fmtr)
ax.set_xlabel("Time (hh:mm:ss)")
else:
ax.set_xlabel("Time (s)")
plt.ylim(len(lbl), -0.5)
if not videoLength:
videoLength = maxTime
if pj[OBSERVATIONS][obsId]["time offset"]:
t0 = round(pj[OBSERVATIONS][obsId]["time offset"] + minTime)
t1 = round(pj[OBSERVATIONS][obsId]["time offset"] + videoLength + 2)
else:
t0 = round(minTime)
t1 = round(videoLength)
subjectPosition = t0 + (t1 - t0) * 0.05
if time_format == HHMMSS:
t0d = dt.datetime(1970, 1, 1, int(t0 / 3600),
int((t0 - int(t0 / 3600) * 3600) / 60), int(t0 % 60),
round(round(t0 % 1, 3) * 1000000))
t1d = dt.datetime(1970, 1, 1, int(t1 / 3600),
int((t1 - int(t1 / 3600) * 3600) / 60), int(t1 % 60),
round(round(t1 % 1, 3) * 1000000))
subjectPositiond = dt.datetime(
1970, 1, 1, int(subjectPosition / 3600),
int((subjectPosition - int(subjectPosition / 3600) * 3600) / 60),
int(subjectPosition % 60),
round(round(subjectPosition % 1, 3) * 1000000))
if time_format == S:
t0d, t1d = t0, t1
subjectPositiond = subjectPosition
plt.xlim(t0d, t1d)
plt.yticks(range(len(lbl) + 1), np.array(lbl))
count = 0
flagFirstSubject = True
for subject in all_project_subjects:
if subject not in obs:
continue
if not flagFirstSubject:
if excludeBehaviorsWithoutEvents:
count += 1
ax.axhline(y=(count - 1), linewidth=1, color="black")
ax.hlines(np.array([count]),
np.array([0]),
np.array([0]),
lw=LINE_WIDTH,
color=col)
else:
flagFirstSubject = False
ax.text(subjectPositiond, count - 0.5, subject)
behaviors = obs[subject]
x1, x2, y, col, pointsx, pointsy, guide = [], [], [], [], [], [], []
col_count = 0
for bm_json in all_behaviors:
if bm_json in obs[subject]:
if obs[subject][bm_json]:
for t1, t2 in obs[subject][bm_json]:
if t1 == t2:
pointsx.append(t1)
pointsy.append(count)
ax.axhline(y=count,
linewidth=1,
color="lightgray",
zorder=-1)
else:
x1.append(t1)
x2.append(t2)
y.append(count)
col.append(
utilities.behavior_color(
plot_colors,
all_project_behaviors.index(
json.loads(bm_json)[0])))
ax.axhline(y=count,
linewidth=1,
color="lightgray",
zorder=-1)
count += 1
else:
x1.append(0)
x2.append(0)
y.append(count)
col.append("white")
ax.axhline(y=count,
linewidth=1,
color="lightgray",
zorder=-1)
count += 1
else:
if not excludeBehaviorsWithoutEvents:
x1.append(0)
x2.append(0)
y.append(count)
col.append("white")
ax.axhline(y=count,
linewidth=1,
color="lightgray",
zorder=-1)
count += 1
col_count += 1
if time_format == HHMMSS:
ax.hlines(np.array(y),
np.array([
dt.datetime(1970, 1, 1, int(p / 3600),
int((p - int(p / 3600) * 3600) / 60),
int(p % 60),
round(round(p % 1, 3) * 1e6)) for p in x1
]),
np.array([
dt.datetime(1970, 1, 1, int(p / 3600),
int((p - int(p / 3600) * 3600) / 60),
int(p % 60),
round(round(p % 1, 3) * 1e6)) for p in x2
]),
lw=LINE_WIDTH,
color=col)
if time_format == S:
ax.hlines(np.array(y),
np.array(x1),
np.array(x2),
lw=LINE_WIDTH,
color=col)
if time_format == HHMMSS:
ax.plot(
np.array([
dt.datetime(1970, 1, 1, int(p / 3600),
int((p - int(p / 3600) * 3600) / 60),
int(p % 60), round(round(p % 1, 3) * 1e6))
for p in pointsx
]), pointsy, "r^")
if time_format == S:
ax.plot(pointsx, pointsy, "r^")
fig.canvas.mpl_connect("draw_event", on_draw)
plt.show()
return True
def create_events_plot(pj,
selected_observations,
parameters,
plot_colors=BEHAVIORS_PLOT_COLORS,
plot_directory="",
file_format="png"):
selected_subjects = parameters["selected subjects"]
selected_behaviors = parameters["selected behaviors"]
include_modifiers = parameters["include modifiers"]
interval = parameters[TIME_INTERVAL]
start_time = parameters[START_TIME]
end_time = parameters[END_TIME]
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 modifiers not to be included set modifiers to ""
if not include_modifiers:
cursor.execute("UPDATE aggregated_events SET modifiers = ''")
cursor.execute("SELECT distinct behavior, modifiers FROM aggregated_events")
distinct_behav_modif = [[rows["behavior"], rows["modifiers"]] 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, "-"])
distinct_behav_modif = sorted(distinct_behav_modif)
max_len = len(distinct_behav_modif)
all_behaviors = [pj[ETHOGRAM][x][BEHAVIOR_CODE] for x in utilities.sorted_keys(pj[ETHOGRAM])]
par1 = 1
bar_height = 0.5
init = dt.datetime(2017, 1, 1)
for obs_id in selected_observations:
if len(selected_subjects) > 1:
fig, axs = plt.subplots(figsize=(20, 8), nrows=len(selected_subjects), ncols=1, sharex=True)
else:
fig, ax = plt.subplots(figsize=(20, 8), nrows=len(selected_subjects), ncols=1, sharex=True)
axs = np.ndarray(shape=(1), dtype=type(ax))
axs[0] = ax
ok, msg, db_connector = db_functions.load_aggregated_events_in_db(
pj,
selected_subjects,
[obs_id],
selected_behaviors)
cursor = db_connector.cursor()
# if modifiers not to be included set modifiers to ""
if not include_modifiers:
cursor.execute("UPDATE aggregated_events SET modifiers = ''")
cursor = db_connector.cursor()
cursor.execute("SELECT distinct behavior, modifiers FROM aggregated_events")
distinct_behav_modif = [[rows["behavior"], rows["modifiers"]] for rows in cursor.fetchall()]
# add selected behaviors that are not observed
if not parameters["exclude behaviors"]:
for behav in selected_behaviors:
if [x for x in distinct_behav_modif if x[0] == behav] == []:
distinct_behav_modif.append([behav, "-"])
distinct_behav_modif = sorted(distinct_behav_modif)
max_len = len(distinct_behav_modif)
# time
obs_length = project_functions.observation_total_length(pj[OBSERVATIONS][obs_id])
if obs_length == -1: # media length not available
interval = TIME_EVENTS
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, ))
ylabels = [" ".join(x) for x in distinct_behav_modif]
for ax_idx, subject in enumerate(selected_subjects):
if parameters["exclude behaviors"]:
cursor.execute("SELECT distinct behavior, modifiers FROM aggregated_events WHERE subject = ?", (subject, ))
distinct_behav_modif = [[rows["behavior"], rows["modifiers"]] for rows in cursor.fetchall()]
# add selected behaviors that are not observed
if not parameters["exclude behaviors"]:
for behav in selected_behaviors:
if [x for x in distinct_behav_modif if x[0] == behav] == []:
distinct_behav_modif.append([behav, "-"])
distinct_behav_modif = sorted(distinct_behav_modif)
max_len = len(distinct_behav_modif)
ylabels = [" ".join(x) for x in distinct_behav_modif]
if not ax_idx:
axs[ax_idx].set_title("Observation {}\n{}".format(obs_id, subject), fontsize=14)
else:
axs[ax_idx].set_title(subject, fontsize=14)
bars = {}
i = 0
for behavior_modifiers in distinct_behav_modif:
behavior, modifiers = behavior_modifiers
behavior_modifiers_str = "|".join(behavior_modifiers) if modifiers else behavior
bars[behavior_modifiers_str] = []
# total duration
cursor.execute(("SELECT start,stop FROM aggregated_events "
"WHERE observation = ? AND subject = ? AND behavior = ? AND modifiers = ?"),
(obs_id, subject, behavior, modifiers,))
for row in cursor.fetchall():
bars[behavior_modifiers_str].append((row["start"], row["stop"]))
start_date = matplotlib.dates.date2num(init + dt.timedelta(seconds=row["start"]))
end_date = matplotlib.dates.date2num(
init + dt.timedelta(seconds=row["stop"] + POINT_EVENT_PLOT_DURATION * (row["stop"] == row["start"])))
try:
bar_color = utilities.behavior_color(plot_colors, all_behaviors.index(behavior))
except Exception:
bar_color = "darkgray"
bar_color = POINT_EVENT_PLOT_COLOR if row["stop"] == row["start"] else bar_color
# sage colors removed from matplotlib colors list
if bar_color in ["sage", "darksage", "lightsage"]:
bar_color = {"darksage": "#598556", "lightsage": "#bcecac", "sage": "#87ae73"}[bar_color]
try:
axs[ax_idx].barh((i * par1) + par1, end_date - start_date, left=start_date, height=bar_height,
align="center", edgecolor=bar_color, color=bar_color, alpha=1)
except Exception:
axs[ax_idx].barh((i * par1) + par1, end_date - start_date, left=start_date, height=bar_height,
align="center", edgecolor="darkgray", color="darkgray", alpha=1)
i += 1
axs[ax_idx].set_ylim(bottom=0, top=(max_len * par1) + par1)
pos = np.arange(par1, max_len * par1 + par1 + 1, par1)
axs[ax_idx].set_yticks(pos[:len(ylabels)])
axs[ax_idx].set_yticklabels(ylabels, fontdict={"fontsize": 10})
axs[ax_idx].set_ylabel("Behaviors" + " (modifiers)" * include_modifiers, fontdict={"fontsize": 10})
axs[ax_idx].set_xlim(left=matplotlib.dates.date2num(init + dt.timedelta(seconds=min_time)),
right=matplotlib.dates.date2num(init + dt.timedelta(seconds=max_time + 1)))
axs[ax_idx].grid(color="g", linestyle=":")
axs[ax_idx].xaxis_date()
axs[ax_idx].xaxis.set_major_formatter(DateFormatter("%H:%M:%S"))
axs[ax_idx].set_xlabel("Time (HH:MM:SS)", fontdict={"fontsize": 12})
axs[ax_idx].invert_yaxis()
fig.autofmt_xdate()
plt.tight_layout()
if len(selected_observations) > 1:
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 plot_time_ranges(pj, time_format, plot_colors, obs, obsId, minTime, videoLength, excludeBehaviorsWithoutEvents, line_width):
"""
create "hlines" matplotlib plot
used by plot_event function (legacy)
"""
def on_draw(event):
# http://matplotlib.org/faq/howto_faq.html#move-the-edge-of-an-axes-to-make-room-for-tick-labels
bboxes = []
for label in labels:
bbox = label.get_window_extent()
bboxi = bbox.inverse_transformed(fig.transFigure)
bboxes.append(bboxi)
bbox = mtransforms.Bbox.union(bboxes)
if fig.subplotpars.left < bbox.width:
fig.subplots_adjust(left=1.1*bbox.width)
fig.canvas.draw()
return False
LINE_WIDTH = line_width
all_behaviors, observedBehaviors = [], []
maxTime = 0 # max time in all events of all subjects
# all behaviors defined in project without modifiers
all_project_behaviors = [pj[ETHOGRAM][idx]["code"] for idx in utilities.sorted_keys(pj[ETHOGRAM])]
all_project_subjects = [NO_FOCAL_SUBJECT] + [pj[SUBJECTS][idx]["name"] for idx in utilities.sorted_keys(pj[SUBJECTS])]
for subject in obs:
for behavior_modifiers_json in obs[subject]:
behavior_modifiers = json.loads(behavior_modifiers_json)
if not excludeBehaviorsWithoutEvents:
observedBehaviors.append(behavior_modifiers_json)
else:
if obs[subject][behavior_modifiers_json]:
observedBehaviors.append(behavior_modifiers_json)
if not behavior_modifiers_json in all_behaviors:
all_behaviors.append(behavior_modifiers_json)
for t1, t2 in obs[subject][behavior_modifiers_json]:
maxTime = max(maxTime, t1, t2)
observedBehaviors.append("")
lbl = []
if excludeBehaviorsWithoutEvents:
for behav_modif_json in observedBehaviors:
if not behav_modif_json:
lbl.append("")
continue
behav_modif = json.loads(behav_modif_json)
if len(behav_modif) == 2:
lbl.append("{0} ({1})".format(behav_modif[0], behav_modif[1]))
else:
lbl.append(behav_modif[0])
else:
all_behaviors.append('[""]') # empty json list element
for behav_modif_json in all_behaviors:
behav_modif = json.loads(behav_modif_json)
if len(behav_modif) == 2:
lbl.append("{0} ({1})".format(behav_modif[0], behav_modif[1]))
else:
lbl.append(behav_modif[0])
lbl = lbl[:] * len(obs)
lbl = lbl[:-1] # remove last empty line
fig = plt.figure(figsize=(20, 10))
fig.suptitle("Time diagram of observation {}".format(obsId), fontsize=14)
ax = fig.add_subplot(111)
labels = ax.set_yticklabels(lbl)
ax.set_ylabel("Behaviors")
if time_format == HHMMSS:
fmtr = matplotlib.dates.DateFormatter("%H:%M:%S") # %H:%M:%S:%f
ax.xaxis.set_major_formatter(fmtr)
ax.set_xlabel("Time (hh:mm:ss)")
else:
ax.set_xlabel("Time (s)")
plt.ylim(len(lbl), -0.5)
if not videoLength:
videoLength = maxTime
if pj[OBSERVATIONS][obsId]["time offset"]:
t0 = round(pj[OBSERVATIONS][obsId]["time offset"] + minTime)
t1 = round(pj[OBSERVATIONS][obsId]["time offset"] + videoLength + 2)
else:
t0 = round(minTime)
t1 = round(videoLength)
subjectPosition = t0 + (t1 - t0) * 0.05
if time_format == HHMMSS:
t0d = dt.datetime(1970, 1, 1, int(t0 / 3600), int((t0 - int(t0 / 3600) * 3600) / 60), int(t0 % 60), round(round(t0 % 1, 3) * 1000000))
t1d = dt.datetime(1970, 1, 1, int(t1 / 3600), int((t1 - int(t1 / 3600) * 3600) / 60), int(t1 % 60), round(round(t1 % 1, 3) * 1000000))
subjectPositiond = dt.datetime(1970, 1, 1, int(subjectPosition / 3600), int((subjectPosition - int(subjectPosition / 3600) * 3600) / 60), int(subjectPosition % 60), round(round(subjectPosition % 1, 3) * 1000000))
if time_format == S:
t0d, t1d = t0, t1
subjectPositiond = subjectPosition
plt.xlim(t0d, t1d)
plt.yticks(range(len(lbl) + 1), np.array(lbl))
count = 0
flagFirstSubject = True
for subject in all_project_subjects:
if subject not in obs:
continue
if not flagFirstSubject:
if excludeBehaviorsWithoutEvents:
count += 1
ax.axhline(y=(count-1), linewidth=1, color="black")
ax.hlines(np.array([count]), np.array([0]), np.array([0]), lw=LINE_WIDTH, color=col)
else:
flagFirstSubject = False
ax.text(subjectPositiond, count - 0.5, subject)
behaviors = obs[subject]
x1, x2, y, col, pointsx, pointsy, guide = [], [], [], [], [], [], []
col_count = 0
for bm_json in all_behaviors:
if bm_json in obs[subject]:
if obs[subject][bm_json]:
for t1, t2 in obs[subject][bm_json]:
if t1 == t2:
pointsx.append(t1)
pointsy.append(count)
ax.axhline(y=count, linewidth=1, color="lightgray", zorder=-1)
else:
x1.append(t1)
x2.append(t2)
y.append(count)
col.append(utilities.behavior_color(plot_colors, all_project_behaviors.index(json.loads(bm_json)[0])))
ax.axhline(y=count, linewidth=1, color="lightgray", zorder=-1)
count += 1
else:
x1.append(0)
x2.append(0)
y.append(count)
col.append("white")
ax.axhline(y=count, linewidth=1, color="lightgray", zorder=-1)
count += 1
else:
if not excludeBehaviorsWithoutEvents:
x1.append(0)
x2.append(0)
y.append(count)
col.append("white")
ax.axhline(y=count, linewidth=1, color="lightgray", zorder=-1)
count += 1
col_count += 1
if time_format == HHMMSS:
ax.hlines(np.array(y), np.array([dt.datetime(1970, 1, 1, int(p / 3600),
int((p - int(p / 3600) * 3600) / 60),
int(p % 60), round(round(p % 1, 3) * 1e6))
for p in x1]),
np.array([dt.datetime(1970, 1, 1, int(p / 3600), int((p - int(p / 3600) * 3600) / 60), int(p % 60), round(round(p % 1, 3) * 1e6)) for p in x2]),
lw=LINE_WIDTH, color=col)
if time_format == S:
ax.hlines(np.array(y), np.array(x1), np.array(x2), lw=LINE_WIDTH, color=col)
if time_format == HHMMSS:
ax.plot(
np.array([
dt.datetime(1970, 1, 1, int(p / 3600),
int((p - int(p / 3600) * 3600) / 60), int(p % 60),
round(round(p % 1, 3) * 1e6)) for p in pointsx
]), pointsy, "r^")
if time_format == S:
ax.plot(pointsx, pointsy, "r^")
fig.canvas.mpl_connect("draw_event", on_draw)
plt.show()
return True
