Baba algorithm for robustly determining status changes of objects to be tracked.
pip install -U bbalg
state_verdict(
long_tracking_history: Deque[bool],
short_tracking_history: Deque[bool]
) -> Tuple[bool, bool, bool]
Baba algorithm for robustly determining status changes of objects to be tracked.
Parameters
----------
long_tracking_history: List[bool]
History of N cases. Each element represents the past N state judgment results.
e.g. N=10, [False, False, False, True, False, True, True, True, False, True]
short_tracking_history: List[bool]
History of M cases. Each element represents the past M state judgment results.
e.g. M=4, [True, True, False, True]
Returns
----------
state_interval_judgment: bool
Whether the object's state is currently ongoing.
True as long as the condition is ongoing.
True or False
state_start_judgment: bool
Whether the object has just changed to that state.
True only if it is determined that the state has changed.
True or False
state_end_judgment: bool
Whether the state of the object has just ended or not.
It becomes true only at the moment it is over.
True or False1. State-in-Progress (whether or not the state is currently in progress, true for as long as the state lasts)
The sum of N histories is greater than or equal to N/2 and the sum of the last M histories is greater than or equal to M-1
from typing import Deque
from bbalg import state_verdict
state_interval_judgment, state_start_judgment, state_end_judgment = \
state_verdict(
long_tracking_history=\
Deque([False, True, False, True, False, True, True, True, True, False], maxlen=10),
short_tracking_history=\
Deque([True, True, True, False], maxlen=4),
)
print(f'state_interval_judgment: {state_interval_judgment}')
print(f'state_start_judgment: {state_start_judgment}')
print(f'state_end_judgment: {state_end_judgment}')state_interval_judgment: True
state_start_judgment: False
state_end_judgment: False
2. State start judgment (whether the state has now been entered or not, it becomes true only at the moment of change)
Total of N histories = N/2 and the sum of the last M histories is greater than or equal to M-1
from typing import Deque
from bbalg import state_verdict
state_interval_judgment, state_start_judgment, state_end_judgment = \
state_verdict(
long_tracking_history=\
Deque([False, False, False, True, False, True, True, True, False, True], maxlen=10),
short_tracking_history=\
Deque([True, True, False, True], maxlen=4),
)
print(f'state_interval_judgment: {state_interval_judgment}')
print(f'state_start_judgment: {state_start_judgment}')
print(f'state_end_judgment: {state_end_judgment}')state_interval_judgment: True
state_start_judgment: True
state_end_judgment: False
3. State end judgment (whether the state has just ended or not, it becomes true only at the moment it ends)
Sum of N histories = N/2 and the sum of the last M histories is less than or equal to 1
from typing import Deque
from bbalg import state_verdict
state_interval_judgment, state_start_judgment, state_end_judgment = \
state_verdict(
long_tracking_history=\
Deque([True, True, False, True, False, True, False, False, True, False], maxlen=10),
short_tracking_history=\
Deque([False, False, True, False], maxlen=4),
)
print(f'state_interval_judgment: {state_interval_judgment}')
print(f'state_start_judgment: {state_start_judgment}')
print(f'state_end_judgment: {state_end_judgment}')state_interval_judgment: False
state_start_judgment: False
state_end_judgment: True