Performance increases by replacing "df.loc" by "df.at"

spatz/connections/__init__.py

@@ -0,0 +1 @@
+from spatz.connections.serial import *

spatz/dataset.py

@@ -199,18 +199,18 @@ class Dataset(Advanceable):
             float: Returns the requested value.
         """
         if self.__interpolation == 'linear':
-            t_min = self.__df['time'].iloc[self.__idx]
-            t_max = self.__df['time'].iloc[self.__idx + 1]
+            t_min = self.__df.at[self.__idx, 'time']
+            t_max = self.__df.at[self.__idx + 1, 'time']
 
             # Sometimes no time passes in-between two samples.
             if t_max == t_min:
-                return self.__df[name].iloc[self.__idx]
+                return self.__df.at[name, self.__idx]
             
             # Compute the weight for interpolation.
             alpha = (self.get_time() - t_min) / (t_max - t_min)
 
             # Interpolate linearly between the two data points.
-            return (1 - alpha) * self.__df[name].iloc[self.__idx] + alpha * self.__df[name].iloc[self.__idx + 1]
+            return (1 - alpha) * self.__df.at[self.__idx, name] + alpha * self.__df.at[self.__idx + 1, name]
 
     def fetch_values(self, names: List[str]) -> np.array:
         """Get specific values from the dataframe.

spatz/logger.py

@@ -49,9 +49,9 @@ class Logger(Advanceable):
         self.__idx = -1
 
     def _on_step(self, _: float):
-        self.__df = pd.concat([self.__df, pd.DataFrame()], ignore_index=True)
+        self.__df = pd.concat([pd.DataFrame(), self.__df], ignore_index=True, copy=False)
         self.__idx += 1
-        self.__df.loc[self.__idx, 'time'] = self.get_time()
+        self.__df.at[self.__idx, 'time'] = self.get_time()
 
     def _on_reset(self):
         self.__df = pd.DataFrame.from_dict({'time': [self.get_time()]}).astype(np.float64)
@@ -64,12 +64,12 @@ class Logger(Advanceable):
             value (Any): The value to log.
             domain (str, optional): The domain the value belongs to. Defaults to 'any'.
         """
-        name = domain + '/' + attrib
+        name = f'{domain}/{attrib}'
 
         if name not in self.__df.columns:
             self.__df[name] = pd.Series([pd.NA] * len(self.__df))
 
-        self.__df.loc[self.__idx, name] = value
+        self.__df.at[self.__idx, name] = value
 
     def get_dataframe(self) -> pd.DataFrame:
         return self.__df

spatz/sensors/__init__.py

@@ -3,6 +3,3 @@ from spatz.sensors.gps import GPS
 from spatz.sensors.imu import Accelerometer, Gyroscope, IMU
 from spatz.sensors.pressure import PressureSensor
 from spatz.sensors.compound import CompoundSensor
-
-
-from pandas import NA