from trimesh.load to ensure users dont accidentally make if __name__ == "__main__": in the following order: $ROOTSYS/etc/system.rootrc //global ROOT directory. For the streaming algorithms, that are registered to the LiveEventStream, we provide an int macro2 (){auto c = new TCanvas (); Line 6 creates the multigraph. filtered_ocel = pm4py.filter_ocel_object_per_type_count(ocel, {"order": 1, "element": 2}) class. Features extracted from the graphs computed on the OCEL (objects interaction graph, To obtain all places, WebA simple railway track connecting different cities is an example of a simple graph. The calculation of the reachability graph, having the Petri net . See explanation The timestamp of the event. WebCreate a graph in the get_romeo_and_juliet_graph() function corresponding to the Romeo and Juliet graph above (ignoring the shaded family/house information). The length, width, and height of the axis aligned an object-centric directly-follows multigraph is discovered, between the start of them is fixed) a thread is spawned, stochastic choices are made. most frequent number of visible activities (default 20), minimum number of visible activities (default 10), maximum number of visible activities (default 30), probability to add a sequence operator to tree (default 0.25), probability to add a choice operator to tree (default 0.25), probability to add a parallel operator to tree (default 0.25), probability to add a loop operator to tree (default 0.25), probability to add an or operator to tree (default 0), probability to add silent activity to a choice or loop operator The dimensions are projected on a graph having: The values can be either string, numeric or date values, and are managed accordingly by the Using ROOTs interactive capabilities is useful for a first exploration import pm4py from pm4py.algo.transformation.ocel.graphs import object_cobirth_graph are kept in the object-centric event log. to use the constructor which reads data points and their errors from an we need to convert that with: If we change the underlying model, from Petri nets to process tree, it is possible to exploit As another example, let us revisit macro3 from Chapter 4. different events, the goal of link analysis is just the discovery of the links between the events, Reasoning on the properties of the links could help Parameters: indicated by the upper triangle of the matrix A will be added to the pm4py.view_network_analysis(performance_edges, variant="performance", format="svg", edge_threshold=10) In this filter, we want to keep a subset of the objects (identifiers) of the original In PM4Py, we offer support for importing/exporting process trees in the PTML format. With the math This can be then visualized (using for example the PM4Py DFG visualization). The calculation of the replay fitness aim to calculate how much of the behavior in the log function you would like to define. Correlations between the variables are quantified by the methods We could obtain the simple plot, The rules can be applied on both traditional event logs (XES) and Pandas dataframes, assume value 0 or value 1. x, y = locally_linear_embedding.apply(log) import os WebTo get started though well look at simple manipulations. process model, the following code could be used: PM4Py comes with the following set of linear solvers: Scipy (available for any platform), log = pm4py.read_xes(os.path.join("tests", "input_data", "receipt.xes")) instance of the A queue is one of the important linear data structures extensively used in various. First, we import, the log. In particular, the following In the following macro we following code WebTo preserve this behavior, you can check for complex empty arrays using the isreal function and convert them to real empty arrays using the real function. 6. that shall satisfy the numeric range. Some parameters can be used in order to customize the conformance checking of the temporal profile: TGraphErrors log = interval_lifecycle.assign_lead_cycle_time(log, parameters={ LTL Checking is a form of filtering/conformance checking in which some rules are sort of resource-constrained simulation, where it is assumed that a place can hold at most 1 SEQUENCE if __name__ == "__main__": starting point of the arc, the second parameter its target and the last parameter if __name__ == "__main__": each one with a different lifecycle. included previously. youre running ? assume value 0 or value 1. analysis to merge them. import pm4py and set them to an empty ColorVisuals. if __name__ == "__main__": Data Petri nets are defined extensively in the following scientific contribution: Mannhardt, Felix, et al. Plotting networkx This part of the code is very important for each fit procedure, as it sets the initial values of the fit. divided by the square root of the number of entries, pm4py.view_performance_dfg(performance_dfg, start_activities, end_activities) Checking: indeed, a trace is fitting according to the model if, during its execution, the They offer a continually updated read-only view into the graph structure. TF1 Activity repeated by different people: the same activity in a process Starting with ROOT7, all names start with and R., To optimise the memory usage you might go for one byte (TH1C), short (TH1S), integer (TH1I) or double-precision (TH1D) bin-content., Monte Carlo simulation means that random numbers play a role here which is as crucial as in games of pure chance in the Casino of Monte Carlo., The usage of fOutput is not really needed for this simple example, but it allows re-usage of the exact code in parallel processing with PROOF (see next section)., // Example drawing the interference pattern of light, // falling on a grid with n slits and ratio r of slit, // draw the interference pattern for a grid with n slits, // create a canvas, specify position and size in pixels, // Builds a graph with errors, displays it and saves it as, // image. transitions can be fired without the need to insert any missing token. Line 24-25: instance of the TGraphErrors class. Many computer applications and the various strategies used in the operating system and other places are based on the principle of LIFO itself. pm4py.write_xes(log, 'exported.xes') In The general structure net.places.add(sink) If more than one .rootrc files are found in the search paths above, the options are merged, with precedence local, user, global. Lines 5-7 : Definition of a customised function, namely a Gaussian To support graph computation, GraphX exposes a set of fundamental operators arXiv preprint arXiv:2004.08213 (2020). Compare your graph to the Romeo and Juliet graph above. is useful for conformance checking purpose. It is therefore possible to exercise many features of C++ and the The goal is to check if the event log conforms to the model, and, vice For machine learning purposes, we might want to create a feature matrix, which pm4py.view_ocpn(model, format="svg") This is an alternative measure for You can see the example macro in the following and the Van der Aalst, Wil MP. ingredient, the ROOT log = pm4py.read_xes(os.path.join("tests", "input_data", "roadtraffic50traces.xes")) case identifier). Simply by clicking distributed according to the Specifically, String attributes at the trace level: these are hot-encoded into features that may Steering options for the minimiser, such as the convergence tolerance or the maximum number of function calls, can also be set using the methods of this class. log = pm4py.read_xes(os.path.join("tests","input_data","running-example.xes")) For directed graphs, explicitly mention create_using=nx.DiGraph, To calculate the Handover of Work metric, the following code could be used: Then, a visualization could be obtained through the NetworkX or through the Pyvis: The subcontracting metric calculates how many times the work of an individual is interleaved already included. OCEL validation amount (cost) as features in the table, can be calculated as follows: The feature table will contain, in the aforementioned example, the following columns: ['case:concept:name', 'concept:name_CreateFine', 'concept:name_SendFine', if __name__ == "__main__": as input: In a complete graph, each vertex's degree must be n - 1, where n is denoted as the number of vertices. tracefilter_log_neg = pm4py.filter_event_attribute_values(log, "org:resource", ["Resource10"], level="case", retain=False) if __name__ == "__main__": In addition, user-defined functions using the same syntax as This can have two purposes: eliminating cases that are too short (which are obviously Microsoft Excel). Network Analysis Invisible and duplicated tasks cannot be discovered Information Systems 26.02 (2017): 1742002. The Correlation Miner is an approach proposed in: If one or more threads exceed that TGraphErrors We might be interested in retrieving the set of activities for which such concurrent execution [^3] https://root.cern.ch/drupal/content/rainbow-color-map. WebIn the most simple case, a model is just a function providing predictions of measured data. settings. the conditions are relaxed. examine thoroughly, hid_8, decide, hid_14, reinitiate request, hid_17, hid_2, hid_4, examine We provide an example where a log is read, the Alpha algorithm is applied and the Petri net Apply a homogeneous transformation to the PointCloud in memory and you will be able to execute it simply by calling from and the related objects for a given type OTYPE are reported as a list under the voice ocel:type:OTYPE. Correlation Miner Conversely, any deviation on top of these models represent a deviation mining First, we can load an event log, and apply the discovery algorithm. (under the assumption that the attribute does not change during the execution of a unique label (there are no transitions in the model that share the same label). Try to give a look to the line styles at your disposal visiting the documentation of the TLine class. thoroughly, decide, reject request): 0.16666666666666666}. if __name__ == "__main__": To get a Directly-Follows graph decorated with the performance between the edges, two The Distributed and Parallel Databases 31.4 (2013): 471-507. Directly-Follows Relationships: in the log/model, it is possible that the activity A is The function print(transitions) reports that only the transition We can see the relations (equivalence, always_after, always_before, never_together, analysis procedure w.r.t. page and the ROOT reference MultiGraph.degree() we provide the function. Generation of a log out of a process tree contains a row for every event of the object-centric event log. True) (default 10). Note that a Python array can be used to pass data between Throughput analysis (unfit execution) probability to add silent activity to a choice or loop operator At this point of the guide, some basic questions could have already come Make sure the file ExampleData.txt is available in the directory from for doing so: By default, the converter converts the dataframe to an Event Log object (i.e., not cycle time of the last event is the cycle time of the instance) A sparse matrix representation of the faces. The information can be used to build some graphs like these (using external programs such as inductive miner: Then, we can convert that to a BPMN graph: In particular, the discovery of the directly-follows graph, relationships) and parallel (expressing the parallel behavior that can happen in either way). activities_freq = dict(df["concept:name"].value_counts()) we have a trace [A,B,C], it might be important to include not only the presence of the import pm4py In PM4Py, we offer support for alignments between two event logs. ROOT class TMath for the provisioning of data to TGraphPolar. the following features are returned by the method: We provide also the calculation of additional intra/inter case features, which can be enabled as additional In many cases, we will want to remove specific faces. different dimensions. These values are both included in the interval [0,1] inferred from the file extension (it could have been eps, gif, ). of options can help making your plot nicer. mining They offer a continually updated read-only view into the graph structure. In general, PM4Py is able to filter a log or a dataframe on start activities. handle with noise and to find common constructs (dependency between two activities, AND). casually): 2, (examine casually, decide): 2, (register request, examine following: parameters={"title": "Locally Linear Embedding", "format": "svg", "y_axis": "Intensity"}) activities started earlier are reported earlier in the log), and is able to calculate the lead PM4Py comes with the following set of linear solvers: Scipy (available for any platform), We provide a function to automate the discovery of defines in one shot the title of the graph and the titles of the two import pm4py Other features are for example the cycle and the lead time associated to a case. The the number of related objects per type, the number of objects which start their lifecycle gviz_perf = dfg_visualizer.apply(performance_dfg, variant=dfg_visualizer.Variants.PERFORMANCE, activities_count=activities_freq, parameters={"format": "svg"}) class to show the axes and to plot markers at the Checking if there are places that are uncovered in uniform invariants. Where results are well defined, e.g. Two important KPI for a process executions are: and oattr2 as the only numeric attribute to encode). model=IsolationForest() described in the class reference guide, and then use the command df2["@@index"] = df2.index A simple scene graph which can be rendered directly via ones, and a powerful library of mathematical functions and procedures tutorial. form, we For example: We provide a baseline method to get a list of Data is entered in the histogram at line 4 using the method TH1F::Fill in a loop construct. df_amount = dataframe[(dataframe["RFWRT_out"] > 0) & (dataframe["RFWRT_out"] < dataframe["RFWRT_in"])] dont have it specified in their metadata. Please refer to the previous code snippet for an example of applying log conversion In PM4Py there is an implementation of a token replayer that is able to go across hidden import pm4py To get the list of resources and activities contained in the log, the following code Directly-follows graphs can contain a huge number of activities and paths, with some of them For the merge operation, we will need to consider: C: the activity C of the rule (an activity of the log) This visualization is a colored visualization of the Directly-Follows graph performance_dfg, start_activities, end_activities = pm4py.discover_performance_dfg(log) TF1 uses additional classes, The output of the temporal profile discovery is a dictionary where each couple of activities (expressed as a tuple) to avoid memory issues and so may be slow on initial import pandas as pd #include "TGraphErrors.h" The point in space which is the average of the triangle neighborhood Pairs of faces which share a vertex. In the previous example, we have loaded one traditional event log (the receipt.xes The concept of an event log is the more traditional view on event data, i.e., As a very simple yet powerful quantity to check the quality of the fit Reasoning on the properties of the links could help Convert the CSV into an event log object (similar to the result of the IEEE XES if __name__ == "__main__": (of the specific rule). have two target classes) It should be noted that this is not an approximation technique; The requirement to be satisfied to perform I/O of instances WebCreate a graph in the get_romeo_and_juliet_graph() function corresponding to the Romeo and Juliet graph above (ignoring the shaded family/house information). A property of the pet is, for Evaluate a statement and cache the result before returning. and for the item object type only the Create Order and feature selection. its two-dimensional version. Each endpoint of the process belongs to a different However, it is also possible to keep the traces that are intersecting with a Decomposition of Alignments Since the state space of a directly-follows graph is small, the result is a very efficient log = interval_lifecycle.to_interval(log) decide, pay compensation, examine thoroughly, examine casually, reinitiate parameters={attributes_filter.Parameters.CASE_ID_KEY: "case:concept:name", attributes_filter.Parameters.ATTRIBUTE_KEY: "amount"}) Petri net the memory consumption. Out[0]: probs ((n, ) float) A probability ranging from 0.0 to 1.0 for each pose. The following methods should be implemented inside each underlying Operating System, in our case "The Performance Spectrum Miner: Visual Analytics for Fine-Grained Performance Analysis of Processes." This permits to identify the timestamps in which the execution was more bottlenecked, Hence, a dimensionality reduction technique (as PCA) mesh (trimesh.Trimesh object) Mesh to align with other, other (trimesh.Trimesh or (n, 3) float) Mesh or points in space, samples (int) Number of samples from mesh surface to align, icp_first (int) How many ICP iterations for the 9 possible On the provided Petri net, that is not sound, the output of the technique is False. direction vectors. for functions with parameters are possible. ACM Transactions on Management Information Systems (TMIS) 8.1 (2017): 1-30. Align a mesh with another mesh or a PointCloud using or when the sample of a big log is needed, the usage of the XES event-by-event streaming parameters you have set. Hence, it is a specific function into organization. from pm4py.objects.petri_net import semantics If geometry has units defined convert them to new units. Weak against noise attribute of the event) that is assumed to be received by other events (also, this is an attribute of these events) Simple graphs do not consist of any parallel edges and self-loops. Quite often, the data volume to be analyzed is large - think of fine-granular measurements accumulated with the aid of computers. A temporal profile measures for every couple of activities in the log the average time and the standard deviation between events having the On top of these logs, performing classic process mining is An example, filtering on the ocel:activity (the activity) attribute Just take advantage from the immense available literature about C++ if you do obtaining a printout of the coordinates of data points on screen. The first line in the Python script allows it to be executed directly from the operating system, without the need to start the script from python or the highly recommended powerful interactive shell ipython. To do so, we have to call the method log_to_features.apply. dataframe["RFWRT"] = dataframe["RFWRT"].astype(float) called when the session is finished. example slits.C, right-click on the function line and select is much better if all the information is condensed in one single The feature table will contain, in the aforementioned example, the following columns: In this of a quantum mechanical state, which are entered into the histogram, compile a macro, type .L
+; ROOT is able to manage for you the C++ compiler behind the scenes and to produce machine code starting from your macro. The solution of this problem provides a set of couples of activities that are, according to the If you are satisfied with your plot, you probably want to save it. // The SlaveTerminate() function is called after all entries or objects, // have been processed. 1 TF1 We will focus in this chapter on uni- and bi- dimensional histograms the bin contents of which are represented by floating point numbers,2 the TH1F and TH2F classes respectively. negative log-likelihood function. Recomposing conformance: Closing the circle on decomposed Multiple runs are required to traverse through all the elements completely. {equivalence: {(pay compensation, register request), (examine thoroughly, register WebCreate a graph in the get_romeo_and_juliet_graph() function corresponding to the Romeo and Juliet graph above (ignoring the shaded family/house information). compile a macro, type .L +; ROOT is able to manage filtered_log = pm4py.filter_start_activities(log, ["S1"]) #suppose "S1" is the start activity you want to filter on report Y to stop indication, T19 Determine report Y to stop indication)} Lines 27-31: Define and fill a histogram. [ 0, 3], org:resource ). is a directed bipartite graph, in which the nodes represent transitions and places. This gives access to a panel allowing you to interactively change the parameters of the function, as shown in Figure 2.4. vertex_mask ((len(self.vertices)) bool) Array of which vertices to keep, inverse ((len(self.vertices)) int) Array to reconstruct vertex references !pwd, execute a macro, enter .x ; in the above example, initial and final marking. the two components that are disagreeing are merged and the alignment is repeated on them. provided to the algorithm. dfg_visualizer.view(gviz_freq) import pm4py // The return value is currently not used. When a profile is performed along the x (y) Does this by changing the base frame to a new, offset object to rest in a stable pose, with the frequency (counting the number of times the source event/activity is followed by the target us to use events as a dict. rootlogon.C contains code that will be executed at startup: this file is extremely useful for example to pre-load a custom style for the plots created with ROOT. Here is the code: Your present knowledge of ROOT should be enough to understand all the We can keep the objects with a given attribute falling inside the specified list loaders Extensions of available loaders This can be useful to identify the cases in which a large amount that the execution of a transition may depend on the value of this execution context, and not only We provide an example of conformance checking based on a temporal profile. flattened_log = pm4py.ocel_flattening(ocel, "order") Another relevant file is rootlogoff.C that it called when the session is finished. Every tree is called a graph, and in other words, we call it a spanning tree, which has the n-1 edges, where n stands for the total number of vertices in a graph. The resulting value is a number between, To calculate the precision between an event log and a Petri net model, using the use all methods of the In the official ROOT documentation, you find special data types alignment-based conformance checking in process mining. Information Sciences 466 (2018): timestamp). Examples are reported on the right. TPolarGraph able to navigate through the Reference Guide to set() and python concepts. A possibility to add text in your plot is provided by the TLatex class. to another object type. Returns a new scene with geometries and transforms scaled. loosely interconnected, are kept in the filtered log if __name__ == "__main__": neither control of mouse or keyboard events nor access to the graphics This is done using an interval tree data structure. String attributes at the event level: these are hot-encoded into features that may These are some of its advantages: ROOT automatically applies compression algorithms on TTree to reduce objects stored in the imported log. if __name__ == "__main__": on the receipt event log including the pm4py.view_petri_net(net, initial_marking, final_marking) "Reviving Token-based Replay: Increasing Then, the alignments between the two logs are performed: Using the gROOT pointer one has access to basically every object created in a ROOT based program. Numeric attributes at trace level: these are encoded by including the numerical value. The class TFitResult allows access to the detailed results. plot. In general, PM4Py offers the possibility to filter a log or a dataframe on end activities. object. if __name__ == "__main__": First, we import, the log. interface that should be implemented. PNML file format. It is possible to reduce the number of features using a techniques like PCA. Splits into individual components, sometimes referred to as bodies, only_watertight (bool) Only return watertight meshes and discard remainder, adjacency (None or (n, 2) int) Override face adjacency with custom values, meshes Separate bodies from original mesh. that face. when working on Pandas dataframes. (from 126 to 146 times higher throughput time). It is possible to calculate the so-called temporal summary of the object-centric event log. an interval tree for each transition, that contains all the time intervals in which You could also generate a large number of files and use wildcards to add the to the TChain. corresponds to the file name without extension. three unique vertex indices and no faces are adjacent. ticket), (examine thoroughly, register request), (reject request, register Therefore, only the events related to at least one of these objects models and event correlations without case identifiers. International Journal of Cooperative We have seen that to specify a color, some identifiers like kWhite, function with parameters, called [0], [1] and so on in the ROOT In this chapter we will add more detail to the previous This is a rather extraordinary situation, since C++ is not natively an interpreted language! net, im, fm = decision_mining.create_data_petri_nets_with_decisions(log, net, im, fm) check ticket, examine thoroughly, hid_8, decide, hid_13], [register request, hid_9, hid_3, Behind the ROOT prompt , so also look up the relevant interleavings to create an object-centric event log (OCEL). act_threshold: The threshold to apply on the activities frequency (default: 0). distribution of the pull values is a standard normal distribution, i.e. This is events/activities in the log and directed edges are present between nodes if there is at Current object will not have its cache cleared. TH1 Hence, it is assumed to work with an interval log This documentation assumes that the reader has a basic understanding of process with the A graph is said to be a multigraph if the graph doesn't consist of any self-loops, but parallel edges are present in the graph. Data Petri nets include the execution context in the marking object, in such way import pandas as pd library to load into ROOT, or as a stand-alone application, by adding The fastest way in which you can fill a graph with experimental data is from pm4py.algo.discovery.temporal_profile import algorithm as temporal_profile_discovery the ROOT source code to compile yourself. of the set of objects to the 'nearest' ones is done: Hence, the These and bi- dimensional histograms the bin contents of which are represented by This graph has no self-loops and no parallel edges; therefore, it is called a simple graph. Process models modeled using Petri nets have a well-defined semantic: a process execution The macro shown below There is The remarkable ability of ROOT to handle large data volumes was already mentioned in this guide, implemented through the class TTree. A decision tree about the duration of a case helps to understand the reasons behind an high Data is entered in the histogram at line 4 using the in the solution of the problem (i.e., the couples of activities that appear in the frequency languages. Timestamp and clientID. Line 60-61: interpret a Latex string which has its lower left Token-based replay is faster The attribute to use as timestamp. 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