python-monitors
is a pure Python package to monitor formal specifications over temporal sequences. It supports several specification languages such as regular expressions and variants of temporal logic. The usage is fairly easy thanks to Python and allows fast prototyping of applications that monitor temporal sequences using these specifications.
WARNING: This repository is depreciated in favor of the project Reelay but will remain as a pure Python solution albeit limited in functionatity and speed. Reelay implements the same runtime monitors and more in C++, which are accessible from Python via bindings.
The latest release of the package can be installed via pip
such that
pip install python-monitors
This command will also install dependencies python-intervals
and antlr4-python3-runtime
. Alternatively, you can install directly from this repository by running the command
pip install git+https://github.com/doganulus/python-monitors.git
First generate a monitor from past Metric Temporal Logic (MTL) formula:
from monitors import mtl
my_mtl_monitor = mtl.monitor("always(q -> once[2,4](p))")
Then process a data sequence (over propositions) by updating the monitor and collecting the output at each step:
data = dict(
p = [False, True, False, False, False, False, False, True, False, False, False, False, False, False, False],
q = [False, False, False, False, False, True, False, False, False, False, False, False, False, False, True ]
)
for p, q in zip(data['p'], data['q']):
output = my_mtl_monitor.update(p = p, q = q)
print(my_mtl_monitor.time, output, my_mtl_monitor.states)
Any Boolean-valued Python function can be used as a predicate in MTL formulas. They are passed to monitor construction via a dictionary as follows:
def my_predicate(x):
return x < 5
# Named parameters should share the same strings in the expression
my_mtl_monitor = mtl.monitor("always[0,5](p(x))", p=my_predicate)
for n in [9, 13, 4, 1, 2, 3,1,1,1,2]:
output = my_mtl_monitor.update(x = n)
print(my_mtl_monitor.time, my_predicate(n), output, my_mtl_monitor.states)
Regular expressions over propositions and predicates are available in a similar fashion:
from monitors import regexp
def pred1(x):
return x < 5
def pred2(x):
return x > 12
# Named parameters should share the same strings in the expression
my_reg_monitor = regexp.monitor("True*; p1(x); p2(x)+; p1(x)+", p1=pred1, p2=pred2)
for n in [1, 1, 1, 1, 13, 13, 14, 1, 1, 2]:
output = my_reg_monitor.update(x = n)
print(output, my_reg_monitor.states)
For MTL monitoring algorithm, please cite Online Monitoring of Metric Temporal Logic using Sequential Networks. For RE monitoring algorithm, please cite Sequential Circuits from Regular Expressions Revisited.