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)
for file in files:
# connect to database
connection = sqlite3.connect(file)
# create an animalPool, which basically contains your animals
animalPool = AnimalPool()
# load infos about the animals
animalPool.loadAnimals(connection)
# load all detection (positions) of all animals for the first hour
animalPool.loadDetection(start=0, end=oneHour)
eventTimeLine = EventTimeLine(connection,
"Oral-genital Contact",
idA=1,
idB=2,
minFrame=0,
maxFrame=oneHour)
print("Event list for label ", eventTimeLine.eventNameWithId)
print("for animal 1:", animalPool.getAnimalDictionnary()[1].RFID)
print("for animal 2:", animalPool.getAnimalDictionnary()[2].RFID)
print("Number of events:", len(eventTimeLine.getEventList()))
print("start frame", "end frame", "duration(in frame)")
for event in eventTimeLine.eventList:
print(event.startFrame, event.endFrame, event.duration())
detectionMoveTimeLine = EventTimeLine(connection,
"Detection",
idA=1,
minFrame=minT,
maxFrame=maxT)
eventTimeLineList.append(detectionMoveTimeLine)
eventTimeLineList.append(naiveMoveTimeLine)
eventTimeLine = EventTimeLine(connection,
"Move",
idA=1,
minFrame=minT,
maxFrame=maxT)
for event in eventTimeLine.getEventList():
print(event)
print("Total time corrected move: ",
str(eventTimeLine.getTotalLength()))
eventTimeLineList.append(eventTimeLine)
eventTimeLine.plotTimeLine()
plotMultipleTimeLine(eventTimeLineList)
for i in range(0, 100):
print("---")
print(naiveMoveTimeLine.getEventList()[i])
print(eventTimeLine.getEventList()[i])