Metadata-Version: 2.1
Name: pychronicles
Version: 0.0.3
Summary: A package for chronicle recognition
Home-page: https://gitlab.inria.fr/tguyet
Author: Thomas Guyet
Author-email: thomas.guyet@irisa.fr
License: UNKNOWN
Description: # PyChronicle package
        
        A chronicle is a specification of the complex temporal behaviors as a temporal constraint graph. It can be used to recognize complex behaviors in sequence the temporal events.
        
        A chronicle is a multiset of events and a set of temporal constraints specifying that occurrences of pairs of events must occurs within a given temporal interval.
        
        The package implements the model of chronicles and an efficient algorithm to recognize it.
        
        # Requirements
        
        Use `pip install -r requirements.txt` to install requirements
        
        * numpy
        * scipy
        * lazr.restfulclient
        * larz.uri
        
        LAZR is used to instantiate chronicles from CRS files (with simple grammar).
        
        # Usage
        
        Example of usage:
        
            from pychronicles import *
            #define a sequence of events
            seq = [3,4,'b','a','a',1,3,'coucou','b','coucou',5,'coucou',5]
            
            #define a chronicle
            c=Chronicle()
            c.add_event(0,'b')
            c.add_event(1,1)
            c.add_constraint(1,3, (3,45))
            print(c)
            
            #recognize the chronicle in the sequence
            occs=c.recognize(seq)
            print("occurrences: "+str(occs))
        
        It is possible to specify chronicles using the CRS format. The following code illustrate the syntax for specifying a chronicle in this format.
        
            chronicle C27_sub_0[]()
            {
        	    event(Event_Type1[], t006)
        	    event(Event_Type1[], t004)
        	    event(Event_Type2[], t002)
        	    event(Event_Type3[], t001)
        
        	    t004-t006 in [17,25]
        	    t006-t002 in [-16,-10]
        	    t002-t001 in [14,29]
        	    t004-t001 in [27,35]
            }
        
        
        # Authorship
        
        **Author:** Thomas Guyet
        **Institution:** AGROCAMPUS-OUEST/IRISA
        **date:10/2019**
        
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
