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Alpha.m
executable file
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Alpha.m
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(* Wolfram Language package *)(* Wolfram Language Raw Program *)
myOr[list_] :=
(hayUnos = Position[list, 1];
If[ Length[hayUnos] > 0,
Return[1],
Return[0]
];);
myNand[list_] :=
(hayCeros = Position[list, 0];
If[ Length[hayCeros] > 0,
Return[1],
Return[0]
];);
myAnd[list_] :=
(ayCeros = Position[list, 0];
If[ Length[ayCeros] === 0,
Return[1],
Return[0]
];);
myXor[list_] := (Xor @@ list /. Thread[{1 -> True, 0 -> False}] /. Thread[{True -> 1, False -> 0}]);
(* (posi0 = Position[list, 0];
posi1 = Position[list, 1];
If[ Length[posi0] === 0 || Length[posi1] === 0,
Return[0],
Return[1]
];);*)
getRow[matrix_, noRow_] :=
(Return[matrix[[noRow]]]);
getCol[matrix_, noCol_] := (Return[matrix[[All, noCol]]]);
(*Nodes that send inputs to this node*)
getIndexesOfNodesInputs[node_, cm_] :=
(Return[Sort[Flatten[Position[getRow[cm, node], 1]]]]);
(*nodes that receive inputs from this node*)
getIndexesOfNodesOutputs[node_, matrix_] := (Return[Position[getCol[matrix, node],1]]);
getListInputsByIndex[input_, indexes_] :=
(Return[Part[input, indexes]]);
allPosibleInputsReverse[noNodes_] :=
(Table[Reverse[IntegerDigits[x, 2, noNodes]], {x, 0, (2^noNodes) - 1, 1}]);
setInputsToBinPhiStyle[length_, listDecimalNumbers_] :=
(Table[Reverse[IntegerDigits[Part[listDecimalNumbers, x], 2, length]], {x, 1, Length[listDecimalNumbers], 1}]);
allPosibleInputsNormal[noNodes_] :=
(Table[IntegerDigits[x, 2, noNodes], {x, 0, (2^noNodes) - 1, 1}]);
inOutBin2Dec[binInputs_, binOutputs_] :=
Block[ {},
netInDecimalForm = Table[FromDigits[Extract[binInputs, i], 2], {i, 1,Length[binInputs], 1}];
netOutDecimalForm = Table[FromDigits[Extract[binOutputs, j], 2], {j, 1,Length[binOutputs], 1}];
<|"InDec" -> netInDecimalForm, "OutDec" -> netOutDecimalForm|>
];
inOutBin2DecReverse[binInputs_, binOutputs_] :=
Block[ {},
netInDecimalForm = Table[FromDigits[Reverse[Extract[binInputs, i]], 2], {i, 1,Length[binInputs], 1}];
netOutDecimalForm = Table[FromDigits[Reverse[Extract[binOutputs, j]], 2], {j, 1,Length[binOutputs], 1}];
<|"InDec" -> netInDecimalForm, "OutDec" -> netOutDecimalForm|>
];
countOccurencesOfEachElement[list_] :=
(ocList = List[];
For[o = 0, o < Length[list], o++;
elem = Part[list, 0];
cuantos = Count[list, elem];
AppendTo[ocList, cuantos];
];
Return[ocList];
);
assignProbOcurrences[ocurrencesList_, prob_] :=
(Return[ocurrencesList*prob]);
(*calculateProbOfOccurrVec[ocList_,prob_]:=(countingVec=\
countOccurencesOfEachElement[ocList];
Return[assigProbOcurrences[countingVec,prob]];)*)
(*transform cm to edge list
cm05 = {{0, 1, 1, 1, 1}, {1, 1, 1, 0, 0}, {1, 0, 0, 1, 0}, {1, 1, 0, 0, 0}, {0, 1, 1, 1, 0}};
connMatrix2EdgeList[cm05]
out: <|"EdgeList" -> {2 -> 1, 3 -> 1, 4 -> 1, 5 -> 1, 1 -> 2, 2 -> 2,
3 -> 2, 1 -> 3, 4 -> 3, 1 -> 4, 2 -> 4, 2 -> 5, 3 -> 5, 4 -> 5}|>
*)
connMatrix2EdgeList[cm_] :=
Block[ {},
grafo = List[];
For[o = 0, o < Length[cm], o++;
noNodo = o;
fila = Part[cm, o];
(*Print["Fila "<> ToString[noNodo]<>": "<> ToString[fila]];*)
inputIndexes = Position[fila, 1];
inputIndexes = Flatten[inputIndexes];
For[u = 0, u < Length[inputIndexes], u++;
nodo = ToExpression[ToString[Extract[inputIndexes, u]] <> "->" <> ToString[noNodo]];
AppendTo[grafo, nodo];
];
];
(*Print["Edge LIst: "<> ToString[grafo]];*)
<|"EdgeList" -> grafo|>
];
(*Build map of Basins of Attraction in dec from binary representation*)
buildGraphBADecimalFromBinaryInOut[binInputs_, binOutputs_] :=
Block[ {},
netInDecimalForm = Table[FromDigits[Part[binInputs, i], 2], {i, 1, Length[binInputs],1}];
(*Print["INPUTS in decimal form"];
Print[netInDecimalForm];*)
netOutDecimalForm = Table[FromDigits[Part[binOutputs, g], 2], {g, 1, Length[binOutputs], 1}];
(*Print["OUTPUTS in decimal form"];
Print[netOutDecimalForm];*)
edgesList = Table[ToExpression[ToString[Part[netInDecimalForm, x]] <> "->" <> ToString[Part[netOutDecimalForm, x]]], {x, 1, Length[netInDecimalForm], 1}];
<|"InDec" -> netInDecimalForm, "OutDec" -> netOutDecimalForm,"EdgesList" -> edgesList|>
];
(*
cm05 = {{0, 1, 1, 1, 1}, {1, 1, 1, 0, 0}, {1, 0, 0, 1, 0}, {1, 1, 0, 0, 0}, {0, 1, 1, 1, 0}};
dyn05 = {"AND", "AND", "OR", "AND", "OR"};
calculateOneOutptuOfNetwork[{1, 0, 1, 0, 1}, cm05, dyn05]
*)
calculateOneOutptuOfNetwork[input_,cm_,dynamic_] :=
Block[ {noNodes,oneNetOutput,n,indexesInputs,inputsToThisNode,nodeOp,resOp},
noNodes=Length[input];
oneNetOutput = List[];
For[n = 0, n < noNodes, n++;
indexesInputs = getIndexesOfNodesInputs[n, cm];
inputsToThisNode = getListInputsByIndex[input, indexesInputs];
nodeOp = Part[dynamic, n];
(* begin -----------------------------*)
(*Print["------------"];
Print["indexes of inputs: "<> ToString[indexesInputs]];
Print["inputs to this node: "<> ToString[inputsToThisNode]];
Print["Dynamica this node: "<> ToString[nodeOp]];*)
(* end -----------------------------*)
If[ nodeOp === "AND",
resOp = myAnd[inputsToThisNode],
Null
];
If[ nodeOp === "XOR",
resOp = myXor[inputsToThisNode],
Null
];
If[ nodeOp === "OR",
resOp = myOr[inputsToThisNode],
Null
];
If[ nodeOp === "NAND",
resOp = myNand[inputsToThisNode],
Null
];
AppendTo[oneNetOutput, resOp];
];
<|"Output"-> oneNetOutput |>
];
(*Run one step in a network over all repertoire of possible inputs using a specific dynamic*)
runDynamic[cm_, dynamic_] :=
Block[ {noNodes,inputs,unitaryInputUnrestrictedProbability,associationsInputOutputs},
noNodes = Length[dynamic];
inputs = allPosibleInputsReverse[noNodes];
(*inputs=allPosibleInputsNormal[noNodes];*)
unitaryInputUnrestrictedProbability = Divide[1, Length[inputs]];
associationsInputOutputs = List[];
(*Print["INPUTS "];
Print[inputs];*)
noInputs = Length[inputs];
repertoireResultsNet = List[];
ucInputVectorProbability = List[];
For[k = 0, k < noInputs, k++;
oneNetOutput = List[];
input = Part[inputs, k];
(*Print[input];*)
For[n = 0, n < noNodes, n++;
indexesInputs = getIndexesOfNodesInputs[n, cm];
inputsToThisNode = getListInputsByIndex[input, indexesInputs];
nodeOp = Part[dynamic, n];
(* beging -------------------*)
(*Print["------ Node: "<> ToString[n]];
Print["input indexes: "<> ToString[indexesInputs]];
Print["real inputs: " <> ToString[inputsToThisNode]];
Print["Operation: " <> ToString[nodeOp]];*)
(* end ------------------------ *)
If[ nodeOp === "AND",
resOp = myAnd[inputsToThisNode],
Null
];
If[ nodeOp === "OR",
resOp = myOr[inputsToThisNode],
Null
];
If[ nodeOp === "XOR",
resOp = myXor[inputsToThisNode],
Null
];
If[ nodeOp === "NAND",
resOp = myNand[inputsToThisNode],
Null
];
(* being -------------------- *)
(*Print["Result: "];
Print[resOp];*)
(* end ---------------------- *)
AppendTo[oneNetOutput, resOp];
];
(* begin --------------------*)
(*Print["********* Input: "<> ToString[input]];
Print["********* Output: "<> ToString[oneNetOutput]];*)
(* end -----------------------*)
AppendTo[repertoireResultsNet, oneNetOutput];
AppendTo[associationsInputOutputs,Association[{input-> Flatten[oneNetOutput]}]];
AppendTo[ucInputVectorProbability, N[unitaryInputUnrestrictedProbability]];
];
attAssociations = Merge[associationsInputOutputs,Identity];
attractors = DeleteDuplicates[repertoireResultsNet];
attracDec = Table[FromDigits[Part[attractors, b], 2], {b, 1, Length[attractors], 1}];
attracProb = 1/Length[attractors];
probAttractors = Table[attracProb*Count[repertoireResultsNet, Part[attractors, r]], {r, 1, Length[attractors], 1}];
completeAttractorsProb = Table[N[attracProb*Count[repertoireResultsNet,Part[repertoireResultsNet, r]]], {r, 1,Length[repertoireResultsNet], 1}];
<|"RepertoireInputs" -> inputs,
"RepertoireOutputs" -> repertoireResultsNet,
"UnitaryInputUnrestrictedProbability" -> unitaryInputUnrestrictedProbability,
"Attractors" -> attractors,
"AttractorsDec" -> attracDec,
"AttAssociations"-> attAssociations,
"OnlyAttractorsProbabilities" -> probAttractors,
"CompleteAttractorProbVector" -> completeAttractorsProb,
"UCInputVectorProbability" -> ucInputVectorProbability
|>
];
(*Run one step in a network over all repertoire of possible inputs using a specific dynamic*)
createRepertoires[cm_, dynamic_] :=
Block[ {noNodes,inputs,unitaryInputUnrestrictedProbability,associationsInputOutputs,repertoireResultsNet,
noInputs,k,n,indexesInputs,inputsToThisNode, nodeOp, input,oneNetOutput, resOp},
noNodes = Length[dynamic];
inputs = allPosibleInputsReverse[noNodes];
unitaryInputUnrestrictedProbability = Divide[1, Length[inputs]];
associationsInputOutputs = List[];
noInputs = Length[inputs];
repertoireResultsNet = List[];
For[k = 0, k < noInputs, k++;
oneNetOutput = List[];
input = Part[inputs, k];
For[n = 0, n < noNodes, n++;
indexesInputs = getIndexesOfNodesInputs[n, cm];
inputsToThisNode = getListInputsByIndex[input, indexesInputs];
nodeOp = Part[dynamic, n];
If[ nodeOp === "AND",
resOp = myAnd[inputsToThisNode],
Null
];
If[ nodeOp === "OR",
resOp = myOr[inputsToThisNode],
Null
];
If[ nodeOp === "XOR",
resOp = myXor[inputsToThisNode],
Null
];
If[ nodeOp === "NAND",
resOp = myNand[inputsToThisNode],
Null
];
AppendTo[oneNetOutput, resOp];
];
AppendTo[repertoireResultsNet, oneNetOutput];
AppendTo[associationsInputOutputs,Association[{input-> Flatten[oneNetOutput]}]];
];
<|
"RepertoireInputs" -> inputs,
"RepertoireOutputs" -> repertoireResultsNet
|>
];
(*Run one step in a network over all repertoire of possible inputs using a specific dynamic*)
runDynamicHD[cm_, dynamic_, resultsPath_] :=
Block[ {},
noNodes = Length[dynamic];
inputs = allPosibleInputsReverse[noNodes];
(*inputs=allPosibleInputsNormal[noNodes];*)
unitaryInputUnrestrictedProbability = Divide[1, Length[inputs]];
associationsInputOutputs = List[];
(*Print["INPUTS "];
Print[inputs];*)
noInputs = Length[inputs];
repertoireResultsNet = List[];
ucInputVectorProbability = List[];
For[k = 0, k < noInputs, k++;
oneNetOutput = List[];
input = Part[inputs, k];
(*Print[input];*)
For[n = 0, n < noNodes, n++;
indexesInputs = getIndexesOfNodesInputs[n, cm];
inputsToThisNode = getListInputsByIndex[input, indexesInputs];
nodeOp = Part[dynamic, n];
(*Print[indexesInputs];
Print[inputsToThisNode];
Print[nodeOp];*)
If[ nodeOp === "AND",
resOp = myAnd[inputsToThisNode],
Null
];
If[ nodeOp === "OR",
resOp = myOr[inputsToThisNode],
Null
];
If[ nodeOp === "XOR",
resOp = myXor[inputsToThisNode],
Null
];
If[ nodeOp === "NAND",
resOp = myNand[inputsToThisNode],
Null
];
(*Print[resOp];*)
AppendTo[oneNetOutput, resOp];
];
AppendTo[repertoireResultsNet, oneNetOutput];
AppendTo[associationsInputOutputs,Association[{input-> Flatten[oneNetOutput]}]];
AppendTo[ucInputVectorProbability, N[unitaryInputUnrestrictedProbability]];
];
(*attAssociations = Merge[associationsInputOutputs,Identity];*)
attractors = DeleteDuplicates[repertoireResultsNet];
attracDec = Table[FromDigits[Part[attractors, b], 2], {b, 1, Length[attractors], 1}];
attracProb = 1/Length[attractors];
probAttractors = Table[attracProb*Count[repertoireResultsNet, Part[attractors, r]], {r, 1, Length[attractors], 1}];
completeAttractorsProb = Table[N[attracProb*Count[repertoireResultsNet,Part[repertoireResultsNet, r]]], {r, 1,Length[repertoireResultsNet], 1}];
Export[resultsPath<>"/RepertoireInputs.csv", inputs, "CSV"];
Export[resultsPath<>"/RepertoireOutputs.csv", repertoireResultsNet, "CSV"];
Export[resultsPath<>"/Attractors.csv",attractors , "CSV"];
<|"RepertoireInputs" -> inputs,
"RepertoireOutputs" -> repertoireResultsNet,
"UnitaryInputUnrestrictedProbability" -> unitaryInputUnrestrictedProbability,
"Attractors" -> attractors,
"AttractorsDec" -> attracDec,
(*"AttAssociations"-> insOutsAssociations,*)
"OnlyAttractorsProbabilities" -> probAttractors,
"CompleteAttractorProbVector" -> completeAttractorsProb,
"UCInputVectorProbability" -> ucInputVectorProbability
|>
];
loadBatchOfInputs[pathFile_, begin_, end_, sizeInput_] :=
Module[ {},
str = OpenRead[pathFile];
index =
Table[pos = StreamPosition[str];
Skip[str, Record];
pos, {100000}];
format = ToExpression[Table["Record", {dd, 1, sizeInput, 1}]];
readlines[n_, m_] :=
Block[ {},
SetStreamPosition[str, index[[n]]];
Flatten[
ReadList[str, format, m, RecordSeparators -> {", ", "\n"}]]
];
data = readlines[begin, end];
<|"Lines" -> data|>
];
runDynamicInputsFromFile[cm_, dynamic_,Path_,insFileName_,outsFileName_] :=
Block[ {noNodes,inputs},
noNodes = Length[dynamic];
inputs = Import[insFilePath<>"/"<>insFileName, "CSV"];
associationsInputOutputsFile = Path<>"/AssInpOut.csv";
repertoireResultsNetFile = Path<>"/Outputs.csv";
unitaryInputUnrestrictedProbability = Divide[1, Length[inputs]];
noInputs = Length[inputs];
ucInputVectorProbability = List[];
(*--------------------------------- begin*)
(*inputs=allPosibleInputsNormal[noNodes];*)
(*Print["INPUTS "];
Print[inputs];*)
(*--------------------------------- end*)
For[k = 0, k < noInputs, k++;
oneNetOutput = List[];
input = Part[inputs, k];
(*Print[input];*)
For[n = 0, n < noNodes, n++;
indexesInputs = getIndexesOfNodesInputs[n, cm];
inputsToThisNode = getListInputsByIndex[input, indexesInputs];
nodeOp = Part[dynamic, n];
(*Print[indexesInputs];
Print[inputsToThisNode];
Print[nodeOp];*)
If[ nodeOp === "AND",
resOp = myAnd[inputsToThisNode],
Null
];
If[ nodeOp === "OR",
resOp = myOr[inputsToThisNode],
Null
];
If[ nodeOp === "XOR",
resOp = myXor[inputsToThisNode],
Null
];
If[ nodeOp === "NAND",
resOp = myNand[inputsToThisNode],
Null
];
(*Print[resOp];*)
AppendTo[oneNetOutput, resOp];
];
AppendTo[repertoireResultsNet, oneNetOutput];
PutAppend[Flatten[Reverse[IntegerDigits[ii, 2, 22]]], steam];
AppendTo[associationsInputOutputsFile,Association[{input-> Flatten[oneNetOutput]}]];
AppendTo[ucInputVectorProbability, N[unitaryInputUnrestrictedProbability]];
];
attAssociations = Merge[associationsInputOutputsFile,Identity];
attractors = DeleteDuplicates[repertoireResultsNet];
attracDec = Table[FromDigits[Part[attractors, b], 2], {b, 1, Length[attractors], 1}];
attracProb = 1/Length[attractors];
probAttractors = Table[attracProb*Count[repertoireResultsNet, Part[attractors, r]], {r, 1, Length[attractors], 1}];
completeAttractorsProb = Table[N[attracProb*Count[repertoireResultsNet,Part[repertoireResultsNet, r]]], {r, 1,Length[repertoireResultsNet], 1}];
<|"RepertoireInputs" -> inputs,
"RepertoireOutputs" -> repertoireResultsNet,
"UnitaryInputUnrestrictedProbability" -> unitaryInputUnrestrictedProbability,
"Attractors" -> attractors,
"AttractorsDec" -> attracDec,
"AttAssociations"-> attAssociations,
"OnlyAttractorsProbabilities" -> probAttractors,
"CompleteAttractorProbVector" -> completeAttractorsProb,
"UCInputVectorProbability" -> ucInputVectorProbability
|>
];
runDynamicFromFileBatches[cm_, dynamic_,pathProject_,inputsFileName_,outputsPath_] :=
Block[ {noNodes,inputs},
noNodes = Length[dynamic];
noBatches = Divide[Power[2,noNodes],256];
For[h=0,i<noBatches, i++;
inputs = Import[pathProject<>"/"+FileName, {"Data", Range[256*h, 256*(h+1)]}];
Print["Loading inputs, from: " <> ToString[256*h] <> " TO " <> ToString[256*(h+1)]];
associationsInputOutputsFile = pathProject<>"/AssInpOut.csv";
repertoireResultsNetFile = pathProject<>"/Outputs.csv";
unitaryInputUnrestrictedProbability = Divide[1, Power[2,noNodes]];
noInputs = Length[inputs];
ucInputVectorProbability = List[];
(*--------------------------------- begin*)
(*inputs=allPosibleInputsNormal[noNodes];*)
(*Print["INPUTS "];
Print[inputs];*)
(*--------------------------------- end*)
For[k = 0, k < noInputs, k++;
oneNetOutput = List[];
input = Part[inputs, k];
(*Print[input];*)
For[n = 0, n < noNodes, n++;
indexesInputs = getIndexesOfNodesInputs[n, cm];
inputsToThisNode = getListInputsByIndex[input, indexesInputs];
nodeOp = Part[dynamic, n];
(*Print[indexesInputs];
Print[inputsToThisNode];
Print[nodeOp];*)
If[ nodeOp === "AND",
resOp = myAnd[inputsToThisNode],
Null
];
If[ nodeOp === "OR",
resOp = myOr[inputsToThisNode],
Null
];
If[ nodeOp === "XOR",
resOp = myXor[inputsToThisNode],
Null
];
If[ nodeOp === "NAND",
resOp = myNand[inputsToThisNode],
Null
];
(*Print[resOp];*)
AppendTo[oneNetOutput, resOp];
];
AppendTo[repertoireResultsNet, oneNetOutput];
AppendTo[associationsInputOutputsFile,Association[{input-> Flatten[oneNetOutput]}]];
Print["Saving " <> ToString[256*(h+1)] <> " outputs"];
AppendTo[ucInputVectorProbability, N[unitaryInputUnrestrictedProbability]];
];
attAssociations = Merge[associationsInputOutputsFile,Identity];
attractors = DeleteDuplicates[repertoireResultsNet];
attracDec = Table[FromDigits[Part[attractors, b], 2], {b, 1, Length[attractors], 1}];
attracProb = 1/Length[attractors];
probAttractors = Table[attracProb*Count[repertoireResultsNet, Part[attractors, r]], {r, 1, Length[attractors], 1}];
completeAttractorsProb = Table[N[attracProb*Count[repertoireResultsNet,Part[repertoireResultsNet, r]]], {r, 1,Length[repertoireResultsNet], 1}];
];
<|"RepertoireInputs" -> inputs,
"RepertoireOutputs" -> repertoireResultsNet,
"UnitaryInputUnrestrictedProbability" -> unitaryInputUnrestrictedProbability,
"Attractors" -> attractors,
"AttractorsDec" -> attracDec,
"AttAssociations"-> attAssociations,
"OnlyAttractorsProbabilities" -> probAttractors,
"CompleteAttractorProbVector" -> completeAttractorsProb,
"UCInputVectorProbability" -> ucInputVectorProbability
|>
];
(* found if in colums there are 0s, 1s or both*)
elementsInColumn[col_] := Module[{res},
res = 0;
If[Length[Position[col, 0]] > 0 && Length[Position[col, 1]] > 0,
res = "*",
If[Length[Position[col, 0]] > 0 &&
Length[Position[col, 1]] === 0,
res = 0,
If[Length[Position[col, 0]] === 0 && Length[Position[col, 1]] > 0,
res = 1,
Null]
]
];
<|"RES" -> res|>
];
findPatternsInInputsPerAttTotal[inputsPerAtt_] := Module[{kk},
ptt = Table[
Table[elementsInColumn[Part[inputsPerAtt, kk][[All, hh]]][
"RES"], {hh, 1, Length[Part[inputsPerAtt, kk][[1]]], 1}], {kk,
1, Length[inputsPerAtt], 1}];
<|"Pattern" -> ptt|>
];
giveIndexesOfDifferences[list1_, list2_] := Module[{},
diff =
Table[If[Part[list1, bb] != Part[list2, bb], bb, Null], {bb, 1, Length[list1], 1}] /. Null -> Sequence[];
<|"Differences" -> diff|>
];
(*This function works in RAM, supposing my networks are around 22 \
nodes*)
analysisBasinsAttraction[myInputs_, myOutputs_] :=
Module[{assoInputsOutputs,attAndItsInputs,qq,FlatAtts,inputsPerAtt,assAttAndInputs,allPatterns, ff, gg,
assPattOfInputsAndAtt, ll, assInputPattersToAtts, onlyPattsPattToAtts, onlyInputsPattToAtts, mm, changesInInputs,
effectInOutputs, atts },
assoInputsOutputs =
Table[Association[Part[myInputs, qq] -> Part[myOutputs, qq]], {qq,1, Length[myInputs], 1}];
attAndItsInputs = GroupBy[assoInputsOutputs, Values];
FlatAtts = Map[Flatten[#] &, Keys[attAndItsInputs]];
atts = Keys[attAndItsInputs];
inputsPerAtt = Table[Map[Flatten[#] &, Keys[attAndItsInputs[Part[atts, ff]]]], {ff, 1, Length[atts], 1}];
assAttAndInputs = Table[Association[<|Part[FlatAtts, gg] -> Part[inputsPerAtt, gg]|>], {gg, 1, Length[FlatAtts], 1}];
SortBy[assAttAndInputs, Identity];
allPatterns = findPatternsInInputsPerAttTotal[inputsPerAtt]["Pattern"];
assPattOfInputsAndAtt = Table[Association[<|Part[allPatterns, ll] -> Part[FlatAtts, ll]|>], {ll, 1,Length[FlatAtts], 1}];
assInputPattersToAtts = KeySortBy[Merge[assPattOfInputsAndAtt, Identity], Count[#, "*"] &];
(* being -------------------------*)
(*Print[assAttAndInputs];
Print[assInputPattersToAtts];*)
(*end ----------------------------*)
onlyInputsPattToAtts = Keys[assInputPattersToAtts];
onlyPattsPattToAtts = Flatten[#] & /@ Values[assInputPattersToAtts];
changesInInputs = Table[giveIndexesOfDifferences[Part[onlyInputsPattToAtts, 1],Part[onlyInputsPattToAtts, mm]]["Differences"],
{mm, 2,Length[onlyInputsPattToAtts], 1}];
effectInOutputs = Table[giveIndexesOfDifferences[Part[onlyPattsPattToAtts, 1], Part[onlyPattsPattToAtts, mm]]["Differences"],
{mm, 2,Length[onlyPattsPattToAtts], 1}];
<|"ChangeInNodes" -> changesInInputs,
"EffectInNodes" -> effectInOutputs|>
];
getCompleteSubgraph[vertices_, cm_] :=
Block[ {},
(*Print["Vertices: "<>ToString[vertices]];*)
grafoCompleto = List[];
vertices2 = vertices;
cm2 = cm;
For[i = 0, i < Length[vertices2], i++;
nodoProbado = Part[vertices2, i];
todasEntradas = Part[cm2, nodoProbado];
entradasReales = Flatten[List @@@ Position[todasEntradas, 1]];
(*Print["Todas las entradas: "<>ToString[todasEntradas]];
Print["Entradas reales: "<>ToString[entradasReales]];*)
For[m = 0, m < Length[entradasReales], m++;
AppendTo[grafoCompleto, Part[entradasReales, m]];
AppendTo[grafoCompleto, nodoProbado];
];
];
(*Print["Grafo completo: "<>ToString[
grafoCompleto]];*)
<|"GrafoCompleto" -> grafoCompleto|>
];
vertexList2NodeList[vertexList_] :=
Block[ {},
fromVertex2NodeList = List[];
lim = Divide[Length[vertexList], 2];
multiplo = 2;
(*Print["AQUI VOY A TRABAJAR.."];
Print[vertexList];*)
For[u = 0, u < lim, u++;
ind = multiplo*u;
elem1 = Part[vertexList, ind - 1];
elem2 = Part[vertexList, ind];
axeStr = ToString[elem1] <> "->" <> ToString[elem2];
axe = ToExpression[axeStr];
AppendTo[fromVertex2NodeList, axe];
(*Print["HASTA AQUI VA..."];
Print[DeleteCases[fromVertex2NodeList,Null]];*)
];
DeleteCases[fromVertex2NodeList, Null];
<|"VertexList2NodeList" -> fromVertex2NodeList|>
];
testSubGraphOp[g_, i_, cm_, op_] :=
Block[ {},
With[ {s = EdgeList[g]},
listaEjes =
Extract[s, Position[IntegerDigits[i, 2, Length[s]], 1]];
listaVertices = VertexList[Graph[listaEjes]]
];
(*Print[listaEjes];*)
listaEjesSalida[];
(*Si se quiere que se completen los grafos*)
If[ op === 1,(*Si SI se cumple*)
graCompleto = getCompleteSubgraph[listaVertices, cm];
listaNodes = graCompleto["GrafoCompleto"];
newNodeList = vertexList2NodeList[listaNodes];
listaEjesSalida = newNodeList["VertexList2NodeList"];
grafito = Graph[listaEjesSalida];,
(*Si no se cumple*)
listaEjesSalida = listaEjes;
grafito = Graph[listaEjesSalida];
];
(*listaEjes=EdgeList[];*)
(*Print[
"SubGrafo completo: "];*)
(*Print[ToString[graCompleto[
"GrafoCompleto"]]];*)
(*listaNodes=Flatten[List@@@
listaEjes];*)
(*Print["Lista vertices generados automaticamente: "<>ToString[
listaVertices]];
Print["Lista completada de vertices:"<>ToString[listaNodes]];
Print["Lista de ejes completa: "<>ToString[newNodeList[
"VertexList2NodeList"]]];*)
opcion = -1;
If[ (ConnectedGraphQ[grafito]),
opcion = 2,
opcion = 1
];
<|"Opcion" -> opcion, "SubgrafoNodeList" -> listaEjesSalida|>
];
getEdgeListSubgraphs[
subGraphsList_] :=
(Return[Table[EdgeList[Extract[subGraphsList, u]], {u, 1, Length[subGraphsList], 1}]]);
getVertexListSubgraphs[
subGraphsList_] :=
(Return[
Table[VertexList[Graph[EdgeList[Extract[subGraphsList, u]]]], {u, 1, Length[subGraphsList], 1}]]);
getSubStatesSubgraphs[vertexSubgraphsList_,
sysCurrentState_] :=
(Return[Table[Part[sysCurrentState, vertexSubgraphsList[[u]]], {u, 1, Length[vertexSubgraphsList], 1}]]);
getStateOfNodesFromList[listOfCompleteStates_,
nodesWanted_] :=
(Return[Table[Part[listOfCompleteStates[[u]], Flatten[nodesWanted]], {u,1, Length[listOfCompleteStates], 1}]]);
(*getElementContainPattern[inputs,{1,2,3},{1,1,0}]*)
getElementContainPattern[tarjectList_, nodes_, subState_] :=
Module[ {indexesFound, elemFound, decimalRep, f },
indexesFound = List[];
elemFound = List[];
decimalRep = List[];
(*Print["------------------------------"];
Print["------------------------------"];
Print["Nodes: " <> ToString[nodes]];
Print["Substate in nodes: " <> ToString[subState]];
Print["Starting search..."];*)
For[f = 0, f < Length[tarjectList], f++;
analizedElem = Part[tarjectList, f];
(*Print["Element: " <> ToString[analizedElem]];
Print["Substate: " <> ToString[Part[analizedElem,nodes]]];*)
If[ Part[Part[tarjectList, f], nodes] === subState,
AppendTo[elemFound, Part[tarjectList, f]];
AppendTo[indexesFound, f];
AppendTo[decimalRep, FromDigits[Part[tarjectList, f], 2]],
Null
];
];
<|"Elements" -> elemFound, "Indexes" -> indexesFound,
"DecimalRep" -> decimalRep|>
];
calculateProbOfOccurrVec[list_, prob_] :=
Block[ {},
diffElements = DeleteDuplicates[list];
noDiffElem = Length[diffElements];
(*Print["-----------------------------------------"];
Print["Im going to calculate Probabilities"];
Print[list];
Print["Different Elements in list: "];
Print[diffElements];
Print["THey are:"];
Print[noDiffElem];*)
probVector = List[];
For[w = 0, w < noDiffElem, w++;
(*Print["I will calculate with: "];
Print[Part[diffElements,w]];*)
repeticiones = Count[list, Part[diffElements, w]];
AppendTo[probVector, N[repeticiones*prob]];
];
Print["-----------------------------------------"];
<|"ProbabilityVector" -> probVector|>
];
(*buildCompleteProbDistrib[{{0,0},{1,1}},{1,2},inputs, {1,3}, 0.25]
keys and values = <|{0,0}\[Rule]1,{1,1}\[Rule] 2|> this is number of \
times a patter appears
inputs = complete list to analyze. Its length = complete \
probabilities distribution length.
0.25 = unitary probability
*)
buildCompleteProbDistrib[keys_, values_, objectList_, part_, unitaryProb_] :=
Block[ {},
(*Print["----INTO buildCompleteProbDistrib PROCEDURE -----"];*)
distProb = List[];
For[hh = 0, hh < Length[objectList], hh++;
objectElement = Part[objectList, hh];
subPart = Part[objectElement, part];
assignedProb = 0;
(*begin -----------------------------------------*)
(*Print[
"ObjectList:"];
Print[objectList//MatrixForm];
Print["Part"<>ToString[part]];
Print["Calculating probability element: " <> ToString[hh]<> "**" ];
Print["Object element: "<> ToString[objectElement]];
Print["Subpart: "<> ToString[subPart]];*)
(*end -----------------------------------------*)
For[pa = 1, pa <= Length[keys], pa++,
(*begin -----------------------------------------*)
(*Print["Testing key: " <> ToString[keys[[pa]]]];*)
(*end -----------------------------------------*)
If[ subPart === keys[[pa]],
(*Print["Encontrado!!"];*)
assignedProb = values[[pa]]* unitaryProb,
Null
];
];
AppendTo[distProb, assignedProb];
];
<|"ProbabilityDistribution" -> distProb |>
];
probabilityDistributionCalculation[mechanism_, purview_, outputs_, inputs_, currentState_, causalOrEffect_] :=
Module[ {currentSubstate, elementsWithCurrentSubstate, indexesOutElementsCurrentSubstate,
possiblePastFutureStates, purviewsOfPossiblePastFutureStates, singleProbability,
pps,ppp, diffPattPurviews, keys, values, completeProbDistr },
currentSubstate := Part[currentState, mechanism];
If[ causalOrEffect === "causal",
elementsWithCurrentSubstate = getElementContainPattern[outputs, mechanism, currentSubstate],
elementsWithCurrentSubstate = getElementContainPattern[inputs, mechanism, currentSubstate]
];
indexesOutElementsCurrentSubstate = elementsWithCurrentSubstate["Indexes"];
(*begin ----------------------------------------------------*)
(*Print[" ******************* New Evaluation ***********"];
Print["**Direction: "<>ToString[causalOrEffect]];
Print["OUTPUTS: "<> ToString[outputs]];
Print["INPUTS" <> ToString[inputs]];
Print["Mechanism: "<>ToString[mechanism]<> " Substate:" <> ToString[currentSubstate]];
Print[ "Purview: "<> ToString[purview]];
Print["Indixes of elements fulfill requirement:" <> ToString[indexesOutElementsCurrentSubstate]];*)
(*end ----------------------------------------------------*)
If[Length[indexesOutElementsCurrentSubstate]>0,
If[ causalOrEffect === "causal",
possiblePastFutureStates = Table[Part[inputs, indexesOutElementsCurrentSubstate[[pps]]], {pps, 1,Length[indexesOutElementsCurrentSubstate], 1}],
possiblePastFutureStates = Table[Part[outputs,indexesOutElementsCurrentSubstate[[pps]]], {pps, 1,Length[indexesOutElementsCurrentSubstate], 1}]
];
purviewsOfPossiblePastFutureStates = Table[Part[possiblePastFutureStates[[ppp]],Flatten[purview]], {ppp, 1, Length[possiblePastFutureStates],1}];
singleProbability = N[1/Length[purviewsOfPossiblePastFutureStates]];
diffPattPurviews = Counts[purviewsOfPossiblePastFutureStates];
(*begin ----------------------------------------------------*)
(*Print["Posible Past/Future states:" <> ToString[possiblePastFutureStates]];
Print["Purviews of possible past/FutureStates:"<>ToString[purviewsOfPossiblePastFutureStates]];
Print["Patt found in purviews: "<> ToString[diffPattPurviews]];*)
(*end ----------------------------------------------------*)
keys = Keys[diffPattPurviews];
values = Values[diffPattPurviews];
If[ causalOrEffect === "causal",
completeProbDistr = buildCompleteProbDistrib[keys, values, inputs, purview, singleProbability],
completeProbDistr = buildCompleteProbDistrib[keys, values, outputs, purview,singleProbability]
];
];
(*begin ----------------------------------------------------*)
(*Print["Probability Distri:" <>ToString[completeProbDistr]];*)
(*end ----------------------------------------------------*)
<|"OutputsWithCurrentSubstate" -> elementsWithCurrentSubstate["Elements"],
"IndexesOutElementsCurrentSubstate" -> indexesOutElementsCurrentSubstate,
"PossiblePastFutureStates" -> possiblePastFutureStates,
"PurviewsOfPossiblePastFutureStates" -> purviewsOfPossiblePastFutureStates,
"SingleProbability" -> singleProbability,
"AllPatternsPurviews" -> diffPattPurviews,
"CompleteProbabilityDistribution" -> completeProbDistr["ProbabilityDistribution"]|>
];
(*
option:
0=all possible subset,
1=Only connected paths
*)
createValidMechanisms[cm_, option_] :=
Block[ {edges, subsets, v, vertex, subgrafos, connectedSubgraph,i, gg,
vertexListOfSubsets },
If[option===1,
edges = connMatrix2EdgeList[cm];
subsets = Subsets[edges["EdgeList"]];
v = Reverse[Sort[VertexList[Graph[edges["EdgeList"]]]]];
vertex = ArrayReshape[v, {Length[cm], 1}];
(* begin ---------------------*)
(*Print["this is v: "<> ToString[v]];
Print["Reshapping: "<> ToString[vertex]];*)
(* end ---------------------*)
(*1) define subgraphs, 2) test if they are connected, 3) get vertex list of connected
subgraphs*)
subgrafos = Table[Graph[Part[subsets, y]], {y, 2, Length[subsets], 1}];
connectedSubgraph = Table[If[ConnectedGraphQ[Part[subgrafos, i]],Part[subgrafos, i]],
{i, 1, Length[subgrafos], 1}] /.Null -> Sequence[];
vertexListOfSubsets = Table[Sort[VertexList[Part[connectedSubgraph, r]]], {r, 1,Length[connectedSubgraph], 1}];
(* begin ---------------------*)
(*Print["-------------Subgraphs-----------"];
Print[subgrafos];
Print["------- connected Subgraphs ------------"];
Print[connectedSubgraph];
Print["----------- vertex list of Subsets ---------------"];
Print[vetexListOfSubsets];*)
(* end ---------------------*)
For[gg = 1, gg <= Length[vertex], gg++,
PrependTo[vertexListOfSubsets, Part[vertex, gg]];
];
vertexListOfSubsets = DeleteDuplicates[vertexListOfSubsets];
(*begin ---------------------------------------*)
(*Print["Edge LIst: "<> ToString[edges]];
Print["Vertex list "<> ToString[v]];
Print["Vertex list of subsets: "<> ToString[vetexListOfSubsets]];*)
(*end------------------------------------------*)
,
(*if option = 0, all possible subsets including empty set*)
vertexListOfSubsets=Subsets[Range[Length[cm]]];
];
<|"ValidMechanisims" -> vertexListOfSubsets|>
];
createValidMechanismsUsingEdgesList[cm_] :=
Block[ {},
edges = connMatrix2EdgeList[cm];
subsets = Subsets[edges["EdgeList"]];
subsets = Delete[subsets, 1];
(*Print["Edge LIst: "<> ToString[edges]];
Print["Possible subgraphs: "];
Print[subsets];*)
subgr = Table[Graph[Part[subsets, ts], VertexLabels -> "Name",ImageSize -> Tiny, EdgeStyle -> Arrowheads[0.2]], {ts, 1, Length[subsets], 1}];
filteredSubgr = Table[If[ ConnectedGraphQ[Part[subgr, ts2]],
Part[subgr, ts2],
Null
], {ts2, 1, Length[subgr], 1}] /.Null -> Sequence[];
v = Reverse[Sort[VertexList[Graph[edges["EdgeList"]]]]];
vertex = ArrayReshape[v, {Length[cm], 1}];
(*Print["Vertex list "<> ToString[v]];*)
subgrafos = Table[Graph[Part[subsets, y] createValidMechanismsUsingEdgesList], {y, 2,Length[subsets], 1}];
(*HERE IS A CHANGE: WEAKLYCONNECTEDGRAPHQ FOR CONNECTEDGRAPHQ*)
connectedSubgraph = Table[If[ ConnectedGraphQ[Part[subgrafos, i]],
Part[subgrafos, i],
Null
], {i, 1, Length[subgrafos], 1}] /.Null -> Sequence[];
vetexListOfSubsets = Table[Sort[VertexList[Part[connectedSubgraph, r]]], {r, 1,Length[connectedSubgraph], 1}];
vetexListOfSubsets = DeleteDuplicates[vetexListOfSubsets];
For[gg = 1, gg <= Length[vertex], gg++,
PrependTo[vetexListOfSubsets, Part[vertex, gg]];
];
<|"ValidMechanisims" -> vetexListOfSubsets,
"AllSubgraphs" -> subgr,
"ConnectedSubgraphs" -> filteredSubgr|>
];
createConnectedAndWeaklyConnectedSubgraphs[cm_] :=
Block[ {},
edges = connMatrix2EdgeList[cm];
v = Reverse[Sort[VertexList[Graph[edges["EdgeList"]]]]];
vertex = ArrayReshape[v, {Length[v], 1}];
subsets = Subsets[edges["EdgeList"]];
subgrafos = Table[Graph[Part[subsets, y], VertexLabels -> "Name",ImageSize -> Tiny, EdgeStyle -> Arrowheads[0.2]], {y, 2,Length[subsets], 1}];
weaklyConnectedSubgraph = Table[If[ ConnectedGraphQ[Part[subgrafos, i]],
Part[subgrafos, i],
Null
], {i, 1, Length[subgrafos], 1}] /.Null -> Sequence[];
vetexListOfWeakyConnectedGraphs = DeleteDuplicates[Table[Sort[VertexList[Part[weaklyConnectedSubgraph, r]]], {r, 1,Length[weaklyConnectedSubgraph], 1}]];
For[gg = 1, gg <= Length[vertex], gg++,
PrependTo[vetexListOfWeakyConnectedGraphs, Part[vertex, gg]]
];
connectedSubgraph = Table[If[ ConnectedGraphQ[Part[subgrafos, i]],
Part[subgrafos, i],
Null
], {i, 1, Length[subgrafos], 1}] /.Null -> Sequence[];
vetexListOfConnectedGraphs = DeleteDuplicates[ Table[Sort[VertexList[Part[connectedSubgraph, r]]], {r, 1,Length[connectedSubgraph], 1}]];
<|"VertexListWeaklyConnectedSubgraphs" -> vetexListOfWeakyConnectedGraphs,
"VertexListConnectedSubgraphs" -> vetexListOfConnectedGraphs |>
];
calculateIntegrationInformation[partitions_, purviews_, inputs_, outputs_, currentCandidateSetState_, ucPastProbDist_,
ucFutProbDist_] :=
Block[ {},
ciArray = List[];
eiArray = List[];
ceiArray = List[];
pastPossDistribArray = List[];
futPossDistribArray = List[];
For[p = 1, p <= Length[partitions], p++,
onePartition = Sort[Part[partitions, p]];
ciByMechanism = List[];
eiByMechanism = List[];
ceiByMechanism = List[];
pastPossDistribArrayByMechanism = List[];
futPossDistribArrayByMechanism = List[];
For[pp = 1, pp <= Length[purviews], pp++,
onePurview = Sort[ Part[purviews, pp]];
(*------------- PAST ANALYSIS -------------*)
pastProbabilityDistribution = probabilityDistributionCalculation[onePartition, onePurview,outputs, inputs, currentCandidateSetState, "causal"];
currentPStates = pastProbabilityDistribution["OutputsWithCurrentSubstate"];
possiblePStates = pastProbabilityDistribution["PossiblePastFutureStates"];
indexesPStates = pastProbabilityDistribution["IndexesOutElementsCurrentSubstate"];
pastDistribution = pastProbabilityDistribution["CompleteProbabilityDistribution"];
(*begin-------------------------------------------------*)
(*Print[" ------------- an analysis start here ------------"];
Print["Current set state:"<>ToString[currentCandidateSetState]<>" Partition: "<> ToString[onePartition]<> " Purview:"<> ToString[onePurview]];
Print["Past Probabilities distribution: "];
Print[ToString[pastDistribution]];*)
(*end-------------------------------------------------*)
AppendTo[pastPossDistribArrayByMechanism, pastDistribution];
ci = EuclideanDistance[pastDistribution, ucPastProbDist];
AppendTo[ciByMechanism, ci];
(*begin-------------------------------------------------*)
(*Print["------ Past Analysis --------"];
Print["Current states : " <> ToString[Length[currentPStates]] <>" elements"];
Print[currentPStates];
Print["Possible Past States: "];
Print[possiblePStates];
Print["Indexes Possible Past States" <> ToString[Length[
indexesPStates]] <> " elements"];