def getSingleEventTable(self, event_name):
"""
Returns pandas table containing all found events for given event name'
* Primary mouse' meta data
* Event start time
* Event end time
* Event duration
Args:
event_name (str): Event name e. g. Rearing
Returns:
DataFrame
"""
data = defaultdict(list)
for animal in self.getAnimalList():
with mute_prints():
eventTimeLine = EventTimeLine(self.conn,
event_name,
idA=animal.baseId,
minFrame=self.detectionStartFrame,
maxFrame=self.detectionEndFrame)
for e in eventTimeLine.getEventList():
data["RFID"] .append(f"{animal.name}_{animal.RFID}")
data["name"] .append(f"{animal.name}")
data["genotype"] .append(f"{animal.genotype}")
data["event_name"] .append(event_name)
data["start_sec"] .append(e.startFrame / oneSecond)
data["end_sec"] .append(e.endFrame / oneSecond)
data["duration"] .append(e.duration() / oneSecond)
df = pd.DataFrame(data)
df.insert(2, "time", pd.to_timedelta(df["start_sec"], unit="s"))
return df.sort_values("time").reset_index(drop=True)
def getDyadicGenotypeGroupedEventTable(self, event_list):
"""
Returns pandas table containing all found events for given event name
and the involved mice' genotype
* Primary / secondary mice genotype
* Event start time
* Event end time
* Event duration
Args:computeEventFeatures
event_name (str): Event name e. g. Rearing
Returns:
DataFrame
"""
data = defaultdict(list)
animal_list = self.getAnimalList()
for a in animal_list:
if a.genotype is None:
print("Genotype for all mice needs to be set... (aborting)")
for event_name in tqdm(event_list, desc="Event..."):
for A in animal_list:
for B in animal_list:
if A.baseId == B.baseId:
continue
with mute_prints():
eventTimeLine = EventTimeLine(
self.conn,
event_name,
idA=A.baseId,
idB=B.baseId,
minFrame=self.detectionStartFrame,
maxFrame=self.detectionEndFrame,
)
event_list = eventTimeLine.getEventList()
for e in event_list:
data["genotype_primary"].append(f"{A.genotype}")
data["genotype_secondary"].append(f"{B.genotype}")
data["event_name"].append(event_name)
data["start_sec"].append(e.startFrame / oneSecond)
data["end_sec"].append(e.endFrame / oneSecond)
data["duration"].append(e.duration() / oneSecond)
df = pd.DataFrame(data)
if len(df) == 0:
return df
df.insert(2, "time", pd.to_timedelta(df["start_sec"], unit="s"))
return df.sort_values("time").reset_index(drop=True)
def getAllEventsTable(self):
"""
Returns pandas table containing all found events for all found event types'
* Primary mouse' meta data
* Events' start time
* Events' end time
* Events' duration
Returns:
DataFrame
"""
with mute_prints():
all_event_names = getAllEvents(connection=self.conn)
event_table = pd.concat([self.getSingleEventTable(event_name)
for event_name in all_event_names]
, axis=0)
return event_table.sort_values("time").reset_index(drop=True)
def set_genotype(files):
if files is None:
print("No files selected (aborting)")
return
for file in files:
print("\n\nFile: ", file)
print("-" * 80)
if not os.path.exists(file):
print(" ! File does not exist... (skipping)")
continue
with mute_prints():
connection = sqlite3.connect(file)
pool = AnimalPool()
pool.loadAnimals(connection)
print(
f"Setting genotype of {len(pool.getAnimalList())} mice, press [Enter] to keep existing one):"
)
for animal in sorted(pool.getAnimalList(), key=lambda a: a.name):
genotype = input(
f" * {animal.name}_{animal.RFID} [{animal.genotype}]: ")
genotype = genotype.strip()
if len(genotype) > 0:
print(
f" - setting {animal.name}_{animal.RFID} to '{genotype}'"
)
animal.setGenotype(genotype)
else:
print(f" - keeping genotype {animal.genotype}")
print("Genotype saved in database.")
print("-" * 120)