# -*- coding: utf-8 -*-
from __future__ import print_function, division
import numpy as np
from qsrlib_qsrs.qsr_monadic_abstractclass import QSR_Monadic_2t_Abstractclass
[docs]class QSR_Moving_or_Stationary(QSR_Monadic_2t_Abstractclass):
"""Computes moving or stationary relations.
Values of the abstract properties
* **_unique_id** = "mos"
* **_all_possible_relations** = ("m", "s")
* **_dtype** = "points"
QSR specific `dynamic_args`
* **'quantisation_factor'** (*float*) = 0.0: Threshold that determines minimal Euclidean distance to be considered as moving.
Some explanation about the QSR or better link to a separate webpage explaining it. Maybe a reference if it exists.
"""
_unique_id = "mos"
"""str: Unique identifier name of the QSR."""
_all_possible_relations = ("m", "s")
"""tuple: All possible relations of the QSR."""
_dtype = "points"
"""str: On what kind of data the QSR works with."""
def __init__(self):
"""Constructor."""
super(QSR_Moving_or_Stationary, self).__init__()
self.__qsr_params_defaults = {"quantisation_factor": 0.0}
"""?"""
def _process_qsr_parameters_from_request_parameters(self, req_params, **kwargs):
"""Extract QSR specific parameters from the QSRlib request call parameters.
:param req_params: QSRlib request call parameters.
:type req_params: dict
:param kwargs: kwargs arguments.
:return: QSR specific parameter settings.
:rtype: dict
"""
qsr_params = self.__qsr_params_defaults.copy()
try:
qsr_params["quantisation_factor"] = float(req_params["dynamic_args"][self._unique_id]["quantisation_factor"])
except (KeyError, TypeError):
try:
qsr_params["quantisation_factor"] = float(req_params["dynamic_args"]["for_all_qsrs"]["quantisation_factor"])
except (TypeError, KeyError):
pass
return qsr_params
def _compute_qsr(self, data1, data2, qsr_params, **kwargs):
"""Return QSR value.
:param data1: Object data at first timestamp.
:type data1: :class:`Object_State <qsrlib_io.world_trace.Object_State>`
:param data2: Object data at second timestamp.
:type data2: :class:`Object_State <qsrlib_io.world_trace.Object_State>`
:param qsr_params: QSR specific parameters passed in `dynamic_args`.
:type qsr_params: dict
:param kwargs: kwargs arguments
:return: Computed QSR value.
:rtype: str
"""
# print(data1.x, data1.y, data2.x, data2.y, np.sqrt((data1.x-data2.x)**2 + (data1.y-data2.y**2)))
# print(np.sqrt((data1.x-data2.x)**2 + (data1.y-data2.y**2)))
return "m" if np.sqrt((data1.x-data2.x)**2 + (data1.y-data2.y)**2) > qsr_params["quantisation_factor"] else "s"