private static (MatchingDictionary completeMatching, MaximumMatchings2 matches) FindAllMatches(List <Data> inputs, List <Data> allData, List <WorkflowComponent> workflowComponents)
{
var inputsHash = new HashSet <string>(inputs.Select(d => d.Id));
var outputsHash = new HashSet <string>();
// 1.0. Check for non-reversible variables that are either only input or output
var nonReversibleData = allData.Where(d => !(d is DoubleData)).ToList();
Dictionary <string, IOStatus> nonReversibleStatus = workflowComponents.GetDataStatus(nonReversibleData);
//var collisionDictionary = new Dictionary<string, char>();
//foreach (var component in workflowComponents)
//{
// foreach (var input in component.ModelDataInputs)
// {
// if (!(input is DoubleData))
// {
// string inName = input.Id;
// if (collisionDictionary.ContainsKey(inName))
// collisionDictionary[inName] = 'b';
// else
// collisionDictionary[inName] = 'i';
// }
// }
// foreach (var output in component.ModelDataOutputs)
// {
// if (!(output is DoubleData))
// {
// string outName = output.Id;
// if (collisionDictionary.ContainsKey(outName))
// collisionDictionary[outName] = 'b';
// else
// collisionDictionary[outName] = 'o';
// }
// }
//}
foreach (string data in nonReversibleStatus.Keys)
{
if (nonReversibleStatus[data] == IOStatus.Input)
{
inputsHash.Add(data);
}
else if (nonReversibleStatus[data] == IOStatus.Output)
{
outputsHash.Add(data);
}
}
var bipartite = new BipartiteGraph();
Primes.Reset();
var outputsDict = new MatchingDictionary(workflowComponents.Select(c => c.Id));
// 1.1 Add Nodes for the Variables
// Filter-out the selected inputs and outputs, as they don't belong to the bipartite graph
foreach (Data data in allData.Where(d => !inputsHash.Contains(d.Id) && !outputsHash.Contains(d.Id)))
{
bipartite.AddNode(data.Id, GraphNode.Type.Type1);
}
// 1.2 Add Nodes for the Models, and edges between Variables and Nodes
foreach (WorkflowComponent component in workflowComponents)
{
int uniqueNonReversibleOutputs = 0;
outputsDict.Add(component.Id, new HashSet <string>());
bipartite.AddNode(CS(component.Id), GraphNode.Type.Type2);
GraphNode modelNode = bipartite.GetNode(CS(component.Id));
// Filter-out the selected inputs, as they don't belong to the bipartite graph
foreach (Data data in component.ModelDataInputs.Where(d => !inputsHash.Contains(d.Id)))
{
if (outputsHash.Contains(data.Id))
{
// Shouldn't arrive here
uniqueNonReversibleOutputs++;
outputsDict[component.Id].Add(data.Id);
}
else
{
bipartite.AddDirectedEdge(data.Id, modelNode, Primes.Next(), 1);
}
}
// Filter-out the selected inputs, as they don't belong to the bipartite graph
foreach (Data data in component.ModelDataOutputs.Where(d => !inputsHash.Contains(d.Id)))
{
if (outputsHash.Contains(data.Id))
{
uniqueNonReversibleOutputs++;
outputsDict[component.Id].Add(data.Id);
}
else
{
bipartite.AddDirectedEdge(data.Id, modelNode, Primes.Next(), 0);
}
}
// How many output the model need
if (component.ModelDataOutputs.Count - uniqueNonReversibleOutputs > 1)
{
bipartite.modelAndItsOutputs.Add(CS(component.Id), component.ModelDataOutputs.Count - uniqueNonReversibleOutputs); //signle output models are not stored
}
else if (component.ModelDataOutputs.Count - uniqueNonReversibleOutputs == 0)
{
bipartite.Remove(CS(component.Id));
}
}
// 1.3 Associate matchings to each model, maping models to set of outputs
var matches = new MaximumMatchings2(bipartite, getAllMatchings: true);
return(outputsDict, matches);
}
private static MatchingDictionary MatchModelsWithVariablesGlobal(List <Data> allData, List <WorkflowComponent> components, GlobalReversalMode mode)
{
if (mode == GlobalReversalMode.NoReversedModels || mode == GlobalReversalMode.Global)
{
List <WorkflowComponent> originalComponents = components.GetAllComponents();
Dictionary <string, IOStatus> status = originalComponents.GetInputsOutputsStatus(allData, out List <Data> inputs, out List <Data> outputs);
foreach (string key in status.Keys)
{
if (status[key] == IOStatus.Conflict)
{
throw new ArgumentException($"The following varibale \"{key}\" is of non-reversible type and output of more than one model. Therefore the workflow cannot be created");
}
}
var inputsHash = new HashSet <string>(inputs.Select(d => d.Id));
var bipartite = new BipartiteGraph();
Primes.Reset();
var completeMatching = new MatchingDictionary(originalComponents.Select(c => c.Id));
// 1.1 Add Nodes for the Variables
// Filter-out the selected inputs and outputs, as they don't belong to the bipartite graph
foreach (Data data in allData.Where(d => !inputsHash.Contains(d.Id)))
{
bipartite.AddNode(data.Id, GraphNode.Type.Type1);
}
// 1.2 Add Nodes for the Models, and edges between Variables and Nodes
foreach (WorkflowComponent component in originalComponents)
{
completeMatching.Add(component.Id, new HashSet <string>());
bipartite.AddNode(CS(component.Id), GraphNode.Type.Type2);
GraphNode modelNode = bipartite.GetNode(CS(component.Id));
// Filter-out the selected inputs, as they don't belong to the bipartite graph
foreach (Data data in component.ModelDataInputs.Where(d => !inputsHash.Contains(d.Id)))
{
bipartite.AddDirectedEdge(data.Id, modelNode, Primes.Next(), 1);
}
// Filter-out the selected inputs, as they don't belong to the bipartite graph
foreach (Data data in component.ModelDataOutputs.Where(d => !inputsHash.Contains(d.Id)))
{
bipartite.AddDirectedEdge(data.Id, modelNode, Primes.Next(), 0);
}
// How many output the model need
if (component.ModelDataOutputs.Count > 1)
{
bipartite.modelAndItsOutputs.Add(CS(component.Id), component.ModelDataOutputs.Count); //signle output models are not stored
}
}
// 1.3 Associate matchings to each model, maping models to set of outputs
var matches = new MaximumMatchings2(bipartite, true);
if (matches.OverConstrainedModels.Count > 0)
{
throw new ArgumentException($"The inputs conbination is not valid as the following models are overconstraint:\r\n\t" +
matches.OverConstrainedModels.Aggregate((total, last) => total += "\r\n\t" + last) + "\r\n");
}
Matching matching = matches.OrderedFilteredMaximumMatchings.FirstOrDefault()
?? throw new NullReferenceException("NO suitable matchings were found");
completeMatching.CompleteWithMatching(matching);
return(completeMatching);
}
else
{
Dictionary <string, IOStatus> status = components.GetInputsOutputsStatus(allData, out List <Data> inputs, out List <Data> outputs);
var inputsHash = new HashSet <string>(inputs.Select(d => d.Id));
var outputsHash = new HashSet <string>();
List <WorkflowComponent> originalComponents = components.GetAllComponents();
Dictionary <string, IOStatus> originalStatus = originalComponents.GetDataStatus(allData);
var nonReversibleData = allData.Where(d => !(d is DoubleData)).ToList();
Dictionary <string, IOStatus> nonReversibleStatus = components.GetDataStatus(nonReversibleData);
foreach (string data in nonReversibleStatus.Keys)
{
if (nonReversibleStatus[data] == IOStatus.Input)
{
inputsHash.Add(data); // Should be already there
}
else if (nonReversibleStatus[data] == IOStatus.Output || nonReversibleStatus[data] == IOStatus.Both)
{
outputsHash.Add(data);
}
}
var reversedInputsHash = new HashSet <string>();
var reversedOutputsHash = new HashSet <string>();
foreach (WorkflowComponent component in components)
{
if (component is IReversableWorkflow rw)
{
foreach (Data data in rw.ReversedInputs)
{
reversedInputsHash.Add(data.Id);
}
foreach (Data data in rw.ReversedOutputs)
{
reversedOutputsHash.Add(data.Id);
}
IEnumerable <Data> NonReversableReversedInputs = rw.ReversedInputs.Where(d => !(d is DoubleData));
IEnumerable <Data> NonReversableReversedOutputs = rw.ReversedOutputs.Where(d => !(d is DoubleData));
// If the model id the upper end of a reversal throug non-reversible variables.
int difference = NonReversableReversedOutputs.Count() - NonReversableReversedInputs.Count();
while (difference > 0)
{
// Assign as many reversible variable to the inputs as reversals end in the component
IEnumerable <Data> reversableReversedInputs = rw.ReversedInputs.Where(d => d is DoubleData);
foreach (Data data in reversableReversedInputs.Take(difference))
{
inputsHash.Add(data.Id);
}
}
}
}
// Relax one input per reversal -> lowerEndOfReversal might have more elements than non-reversible reversal, but those should be already not in inputHash
IEnumerable <string> lowerEndOfReversals = reversedOutputsHash.Except(reversedInputsHash);
inputsHash.ExceptWith(lowerEndOfReversals);
var bipartite = new BipartiteGraph();
Primes.Reset();
var completeMatching = new MatchingDictionary(originalComponents.Select(c => c.Id));
// 1.1 Add Nodes for the Variables
// Filter-out the selected inputs and outputs, as they don't belong to the bipartite graph
foreach (Data data in allData.Where(d => !inputsHash.Contains(d.Id) && !outputsHash.Contains(d.Id)))
{
bipartite.AddNode(data.Id, GraphNode.Type.Type1);
}
// 1.2 Add Nodes for the Models, and edges between Variables and Nodes
foreach (WorkflowComponent component in originalComponents)
{
completeMatching.Add(component.Id, new HashSet <string>());
// if the component has all its inputs and outputs determined do not add to the graph
bool addModel = component.ModelDataOutputs.Count > component.ModelDataOutputs.Where(d => inputsHash.Count > -1 && outputsHash.Contains(d.Id)).Count();
if (addModel)
{
bipartite.AddNode(component.Id, GraphNode.Type.Type2);
}
GraphNode modelNode = bipartite.GetNode(component.Id);
int uniqueNonReversibleOutputs = 0;
// Filter-out the selected inputs, as they don't belong to the bipartite graph
foreach (Data data in component.ModelDataInputs.Where(d => !inputsHash.Contains(d.Id) && !outputsHash.Contains(d.Id)))
{
bipartite.AddDirectedEdge(data.Id, modelNode, Primes.Next(), 1);
}
// Filter-out the selected inputs, as they don't belong to the bipartite graph
foreach (Data data in component.ModelDataOutputs.Where(d => !inputsHash.Contains(d.Id)))
{
if (outputsHash.Contains(data.Id))
{
uniqueNonReversibleOutputs++;
completeMatching[component.Id].Add(data.Id);
}
else
{
bipartite.AddDirectedEdge(data.Id, modelNode, Primes.Next(), 0);
}
}
// How many output the model need
if (component.ModelDataOutputs.Count - uniqueNonReversibleOutputs > 1 && addModel)
{
bipartite.modelAndItsOutputs.Add(component.Id, component.ModelDataOutputs.Count - uniqueNonReversibleOutputs); //signle output models are not stored
}
}
// 1.3 Associate matchings to each model, maping models to set of outputs
var matches = new MaximumMatchings2(bipartite, true);
if (matches.OverConstrainedModels.Count > 0)
{
throw new ArgumentException($"The inputs conbination is not valid as the following models are overconstraint:\r\n\t" +
matches.OverConstrainedModels.Aggregate((total, last) => total += "\r\n\t" + last) + "\r\n");
}
Matching matching = matches.OrderedFilteredMaximumMatchings.FirstOrDefault()
?? throw new NullReferenceException("NO suitable matchings were found");
completeMatching.CompleteWithMatching(matching);
return(completeMatching);
}
}