Adding __truedic__ operator to GazePosition. Adding centroid and distances method to TimestampedGazePositions.

1 files changed, 40 insertions, 13 deletions

diff --git a/src/argaze/GazeFeatures.py b/src/argaze/GazeFeatures.py
index 286a554..32b7de7 100644
--- a/src/argaze/GazeFeatures.py
+++ b/src/argaze/GazeFeatures.py
@@ -151,6 +151,17 @@ class GazePosition(tuple, DataFeatures.TimestampedObject):
 			The returned position timestamp is the self object timestamp.
 		"""
 		return GazePosition(tuple(numpy.array(self) * factor), precision=self.__precision * factor if self.__precision is not None else None, timestamp=self.timestamp)
+	
+	def __truediv__(self, factor: int | float | tuple) -> Self:
+		"""divide position by a factor.
+
+		!!! note
+			The returned position precision is also divided by the factor.
+
+		!!! note
+			The returned position timestamp is the self object timestamp.
+		"""
+		return GazePosition(tuple(numpy.array(self) / factor), precision=self.__precision / factor if self.__precision is not None else None, timestamp=self.timestamp)
 
 	def __pow__(self, factor: int | float) -> Self:
 		"""Power position by a factor.
@@ -226,6 +237,30 @@ class TimeStampedGazePositions(DataFeatures.TimestampedObjectsList):
 			return TimeStampedGazePositions({ast.literal_eval(ts_str): json_positions[ts_str] for ts_str in json_positions})
 	'''
 
+	def centroid(self) -> numpy.array:
+		"""Calculate positions' centroid.
+
+		Returns:
+			centroid: centroid of all positions.
+		"""
+
+		positions_array = numpy.asarray(self.values())
+		centroid = numpy.mean(positions_array, axis=0)
+
+		return (centroid[0], centroid[1])
+
+	def distances(self, point: numpy.array) -> numpy.array:
+		"""Calculate all positions' distances to a point.
+
+		Returns:
+			distances: array with all distances to the point.
+		"""
+
+		positions_array = numpy.asarray(self.values())
+		distances_array = numpy.sqrt(numpy.sum((positions_array - point)**2, axis=1))
+
+		return distances_array
+
 	@classmethod
 	def from_dataframe(cls, dataframe: pandas.DataFrame, timestamp: str, x: str, y: str, precision: str = None,
 					   message: str = None) -> Self:
@@ -370,14 +405,12 @@ class GazeMovement(TimeStampedGazePositions, DataFeatures.TimestampedObject):
 		message: a string to describe why the movement is what it is.
 	"""
 
-	def __new__(cls, positions: TimeStampedGazePositions = None, finished: bool = False,
-				message: str = None, timestamp: int | float = math.nan):
+	def __new__(cls, positions: TimeStampedGazePositions = None, **kwargs):
 
 		# noinspection PyArgumentList
 		return TimeStampedGazePositions.__new__(cls, positions)
 
-	def __init__(self, positions: TimeStampedGazePositions = None, finished: bool = False,
-				 message: str = None, timestamp: int | float = math.nan):
+	def __init__(self, positions: TimeStampedGazePositions = None, finished: bool = False, message: str = None, timestamp: int | float = math.nan):
 		"""Initialize GazeMovement"""
 
 		TimeStampedGazePositions.__init__(self, positions)
@@ -476,8 +509,8 @@ class GazeMovement(TimeStampedGazePositions, DataFeatures.TimestampedObject):
 class Fixation(GazeMovement):
 	"""Define abstract fixation as gaze movement."""
 
-	def __init__(self, positions: TimeStampedGazePositions = TimeStampedGazePositions(), finished: bool = False,
-				 message: str = None, **kwargs):
+	def __init__(self, positions: TimeStampedGazePositions = TimeStampedGazePositions(), finished: bool = False, message: str = None, **kwargs):
+		
 		super().__init__(positions, finished, message, **kwargs)
 
 		self._focus = ()
@@ -487,11 +520,6 @@ class Fixation(GazeMovement):
 		"""Get representative position of the fixation."""
 		return self._focus
 
-	@focus.setter
-	def focus(self, focus: tuple):
-		"""Set representative position of the fixation."""
-		self._focus = focus
-
 	def merge(self, fixation) -> Self:
 		"""Merge another fixation into this fixation."""
 
@@ -1072,8 +1100,7 @@ class AOIScanPath(list):
 
 		size = len(self.__expected_aoi)
 		# noinspection PyAttributeOutsideInit
-		self.__transition_matrix = pandas.DataFrame(numpy.zeros((size, size)), index=self.__expected_aoi,
-													columns=self.__expected_aoi)
+		self.__transition_matrix = pandas.DataFrame(numpy.zeros((size, size)), index=self.__expected_aoi, columns=self.__expected_aoi)
 
 	def __get_aoi_letter(self, aoi):