About python-monitors

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. For high-performance monitoring tasks, please see the project Reelay that targets C++ applications.

Install

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 

Use

MTL over propositions

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)

MTL over predicates (also known as STL)

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

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)

Cite

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.