private static Matrix SimulateNAPTStageTwo(Matrix FA1, Matrix SRG1, Matrix DP1, Matrix CAP, Matrix REL, Matrix UA11, int rowColSize, Matrix output, ref Matrix SRGOutput, ref Matrix EAOutput, int stage, string EAOutputFile, string outputfile, bool overwrite, bool EADyadic, bool outputDyadic, int networkid) { //int networkid = SRG1.NetworkId; // 2. Generate Allies of Enemies matrix AE2 = SRG1 x DP1 Matrix AE2 = SRG1 * DP1; // 3. Generate SRG2 Matrix SRG2 = new Matrix(rowColSize, rowColSize); for (int i = 0; i < SRG2.Rows; i++) { for (int j = 0; j < SRG2.Cols; j++) { if (FA1[i, j] > 0) SRG2[i, j] = 0; else if (SRG1[i, j] == 1 || AE2[i, j] > 0) SRG2[i, j] = 1; else SRG2[i, j] = 0; } } // 4. Generate an Allies Capabilities Matrix AC20 = DP1 * C. Sum over rows of AC20 // Method from excel sheet Matrix AC20 = new Matrix(rowColSize, rowColSize); for (int i = 0; i < rowColSize; i++) { for (int j = 0; j < rowColSize; j++) { if (i == j || FA1[i, j] == 1) AC20[i, j] = CAP[j, j]; else AC20[i, j] = 0; } } // 5. Generate an SRG Capabilities Matrix SRGC20 = SRGC * C. Sum across rows Matrix SRGC20 = new Matrix(rowColSize, rowColSize); for (int i = 0; i < rowColSize; i++) { for (int j = 0; j < rowColSize; j++) { SRGC20[i, j] = SRG2[i, j] * CAP[j, j]; } } // 6. Generate an Alliance Opportunity Cost Vector AOC20 Vector AOC20 = new Vector(rowColSize); for (int i = 0; i < rowColSize; i++) { if (AC20.GetRowSum(i) >= SRGC20.GetRowSum(i)) AOC20[i] = 0; else AOC20[i] = SRGC20.GetRowSum(i) - AC20.GetRowSum(i); } // 7. Generate a Potential Alliance Network T2 PAN2 // method from excel sheet Matrix PAN2 = new Matrix(rowColSize, rowColSize); for (int i = 0; i < rowColSize; i++) { for (int j = 0; j < rowColSize; j++) { if (i == j || FA1[i, j] > 0) PAN2[i, j] = 0; else PAN2[i, j] = 1 - SRG2[i, j]; } } // 8. Generate a Utility for Potential Ally matrix UA21 = PAN2 * UA11. Calulate the max row for UA21 /* Matrix UA21 = new Matrix(rowColSize, rowColSize); for (int i = 0; i < rowColSize; i++) { for (int j = 0; j < rowColSize; j++) { if (i != j) UA21[i, j] = PAN2[i, j] * UA11[i, j]; else UA21[i, j] = 0; } } */ Matrix UA21 = new Matrix(UA11); // 9. Calculate the Potential Ally Capabilities matrix CUA21 // method from excel sheet Matrix CUA21 = new Matrix(rowColSize, rowColSize); for (int i = 0; i < rowColSize; i++) { for (int j = 0; j < rowColSize; j++) { if (i != j && UA21[i, j] == UA21.GetMaxInRow(i)) CUA21[i, j] = CAP[j, j]; else CUA21[i, j] = 0; } } Matrix DP2 = new Matrix(rowColSize, rowColSize); Matrix FA2 = new Matrix(rowColSize, rowColSize); NAPTStageOneHelper1(CAP, SRG2, SRGC20, PAN2, UA21, CUA21, AOC20, ref DP2, ref FA2, stage, AC20); if (stage >= 10) FA2.NetworkId = int.Parse(networkid + "" + stage); else FA2.NetworkId = int.Parse(networkid + "0" + stage); for (int i = 0; i < FA1.Rows; i++) { FA2.RowLabels[i] = FA1.RowLabels[i]; FA2.ColLabels[i] = FA1.ColLabels[i]; } // write FA2 to matrix file // Set network ID and row and col labels first if (!EADyadic) MatrixWriter.WriteMatrixToMatrixFile(FA2, EAOutputFile, overwrite); else MatrixWriter.WriteMatrixToDyadicFile(FA2, EAOutputFile, overwrite); //overwrite = false; Matrix M2 = FA2 - FA1; if (M2.IsAllZero) { // done? EAOutput = FA2; for (int i = 0; i < output.Rows; i++) { output.RowLabels[i] = (int.Parse(networkid + "0" + stage)).ToString(); } if (!outputDyadic) MatrixWriter.WriteMatrixToMatrixFile(output, outputfile, overwrite); else MatrixWriter.WriteMatrixToDyadicFile(output, outputfile, overwrite); return output; // for now } else { // need to unbinarize FA2 first Matrix Temp = new Matrix(FA2); // argument needs to be UA11 and not UA12 (according to excel) Matrix new_output = NAPTStageOneHelper2(CAP, SRG2, FA2, UA11, REL, AOC20, stage, networkid); // write new_output to matrix file if (!outputDyadic) MatrixWriter.WriteMatrixToMatrixFile(new_output, outputfile, overwrite); else MatrixWriter.WriteMatrixToDyadicFile(new_output, outputfile, overwrite); // Copy the data from SRG2 to SRGOutput SRGOutput.Clear(); for (int i = 0; i < SRG2.Rows; i++) for (int j = 0; j < SRG2.Cols; j++) SRGOutput[i, j] = SRG2[i, j]; SRGOutput.NetworkId = new_output.NetworkId; FA2.Clear(); Temp.CloneTo(FA2); return SimulateNAPTStageTwo(FA2, SRG1, DP2, CAP, REL, UA11, rowColSize, new_output, ref SRGOutput, ref EAOutput, stage + 1, EAOutputFile, outputfile, overwrite, EADyadic, outputDyadic, networkid); } }
private static Matrix SimulateNAPTStageOne(Matrix CAP, Matrix SRG, Matrix CONT, Matrix MID, Matrix DEMO, Matrix JC, Matrix CS, Matrix REL, ref Matrix SRGOutput, ref Matrix EAOutput, string EAOutputFile, string outputfile, bool overwrite, bool EADyadic, bool outputDyadic, int networkid) { int stage = 1; //int networkid = SRG.NetworkId; // 1. Transpose vectors Cap, Demo, and Rel // No need to since the vectors are just the diagonals of the matrices // 2. Generate a SRG Capability matrix SRG CAP. Sum the rows of this matrix Matrix SRGC = new Matrix(SRG); double[] srgSum = new double[SRGC.Rows]; for (int i = 0; i < SRGC.Rows; i++) { double sum = 0.0; for (int j = 0; j < SRGC.Cols; j++) { SRGC[i, j] *= CAP[j, j]; sum += SRGC[i, j]; } srgSum[i] = sum; } // 3. Generate an Alliance Opportunity Cost vector Vector AOC = new Vector(SRGC.Rows); for (int i = 0; i < AOC.Size; i++) { if (CAP[i, i] >= srgSum[i]) AOC[i] = 0; else AOC[i] = srgSum[i] - CAP[i, i]; } // 4. Generate an Enemy of Enemy matrix (EE) and binarize it Matrix EE = new Matrix(MID * MID); // 5. Generate a potential alliance network matrix PAN Matrix PAN = new Matrix(SRG.Rows, SRG.Cols); for (int i = 0; i < SRG.Rows; i++) for (int j = 0; j < SRG.Cols; j++) PAN[i, j] = 1 - SRG[i, j]; // 6. Generate a joint democracy matrix (DD) Matrix DD = new Matrix(DEMO.Rows, DEMO.Cols); for (int i = 0; i < DEMO.Rows; i++) for (int j = 0; j < DEMO.Cols; j++) DD[i, j] = DEMO[i, i] * DEMO[j, j]; // 7. Generate a contiguity to SRG matrix (SRGCT) Matrix SRGCT = SRG * CONT; // 8. Binarize the EE matrix // 9. Binarize the DD matrix // 10. Binarize the SRGCT matrix EE.Binarize(); DD.Binarize(); SRGCT.Binarize(); // 11. Generate a Utility for Potential Ally matrix UA11 Matrix UA11 = new Matrix(PAN.Rows, PAN.Cols); double[] maxRowUA11 = new double[UA11.Rows]; for (int i = 0; i < PAN.Rows; i++) { double cur_max = double.MinValue; // find max value in row for (int j = 0; j < PAN.Cols; j++) { if (i == j || PAN[i, j] == 0) UA11[i, j] = 0; else if (DEMO[i, i] == 1 && PAN[i, j] == 1) UA11[i, j] = (0.2 * EE[i, j]) + (0.4 * DD[i, j]) + (0.1 * JC[i, j]) + (0.1 * CS[i, j]) + (0.2 * SRGCT[i, j]); else if (DEMO[i, i] == 0 && PAN[i, j] == 1) UA11[i, j] = (0.5 * EE[i, j]) + (0.1 * DD[i, j]) + (0.1 * JC[i, j]) + (0.1 * CS[i, j]) + (0.2 * SRGCT[i, j]); if (UA11[i, j] > cur_max) cur_max = UA11[i, j]; } maxRowUA11[i] = cur_max; } // 12. Generate a matrix CUA11 Matrix CUA11 = new Matrix(UA11.Rows, UA11.Cols); double[] maxRowCUA11 = new double[CUA11.Rows]; for (int i = 0; i < UA11.Rows; i++) { double cur_max = double.MinValue; // find max value in row for (int j = 0; j < UA11.Cols; j++) { if (UA11[i, j] != maxRowUA11[i]) CUA11[i, j] = 0; else if (UA11[i, j] == maxRowUA11[i] && PAN[i, j] > 0 && i != j) // needs PAN and i!=j conditions CUA11[i, j] = CAP[j, j]; if (CUA11[i, j] > cur_max) cur_max = CUA11[i, j]; } maxRowCUA11[i] = cur_max; } Matrix DP1 = new Matrix(UA11.Rows, UA11.Cols); Matrix FA1 = new Matrix(UA11.Rows, UA11.Cols); NAPTStageOneHelper1(CAP, SRG, SRGC, PAN, UA11, CUA11, AOC, ref DP1, ref FA1, stage, null); // write FA1 to matrix file FA1.NetworkId = int.Parse(networkid + "0" + stage); //FA1.NetworkId = SRG.NetworkId + 1; //int.Parse(editedNetworkId + "01"); for (int i = 0; i < SRG.Rows; i++) { FA1.RowLabels[i] = SRG.RowLabels[i]; FA1.ColLabels[i] = SRG.ColLabels[i]; } if (!EADyadic) MatrixWriter.WriteMatrixToMatrixFile(FA1, EAOutputFile, overwrite); else MatrixWriter.WriteMatrixToDyadicFile(FA1, EAOutputFile, overwrite); //overwrite = false; Matrix Temp = new Matrix(FA1); Matrix Output = NAPTStageOneHelper2(CAP, SRG, FA1, UA11, REL, AOC, stage, networkid); // write Output to matrix file if (!outputDyadic) MatrixWriter.WriteMatrixToMatrixFile(Output, outputfile, overwrite); else MatrixWriter.WriteMatrixToDyadicFile(Output, outputfile, overwrite); overwrite = false; FA1.Clear(); Temp.CloneTo(FA1); return SimulateNAPTStageTwo(FA1, SRG, DP1, CAP, REL, UA11, SRG.Rows, Output, ref SRGOutput, ref EAOutput, stage + 1, EAOutputFile, outputfile, overwrite, EADyadic, outputDyadic, networkid); }
private static Matrix SimulateSimplifiedRealistStageTwo(Matrix C, Matrix R, Matrix M, Matrix BEA, string outputFile, string srgOutputFile, int networkID, bool outputDyadic, bool srgDyadic, int maxIter, double br) { int stage = 2; Matrix Temp = new Matrix(C.Rows); BEA.CloneTo(Temp); //Matrix OriginalR = new Matrix(C.Rows); //R.CloneTo(OriginalR); Matrix BEA2 = UpdateSimplifiedRealistStageTwo(C, R, M, BEA, outputFile, br); BEA2.CopyLabelsFrom(C); BEA2.NetworkId = int.Parse(networkID + "02"); R.NetworkId = BEA2.NetworkId; while (!BEA2.IsSameAs(Temp) && (stage <= maxIter)) { if (!outputDyadic) MatrixWriter.WriteMatrixToMatrixFile(BEA2, outputFile, false); else MatrixWriter.WriteMatrixToDyadicFile(BEA2, outputFile, false); if (!srgDyadic) MatrixWriter.WriteMatrixToMatrixFile(R, srgOutputFile, false); else MatrixWriter.WriteMatrixToDyadicFile(R, srgOutputFile, false); //Matrix OriginR = new Matrix(C.Rows); //R.CloneTo(OriginR); BEA.CloneTo(Temp); BEA2.CloneTo(BEA); BEA2 = UpdateSimplifiedRealistStageTwo(C, R, M, BEA, outputFile, br); stage++; BEA2.NetworkId = int.Parse(networkID + "" + (stage >= 10 ? stage + "" : "0" + stage + "")); R.NetworkId = BEA2.NetworkId; BEA2.CopyLabelsFrom(C); } return BEA2; }
/// <summary> /// Simulates stage two of the realist network formation simulation. /// </summary> /// <param name="C">Capability matrix for stage two</param> /// <param name="R">Policy relevance matrix (SRG)</param> /// <param name="EAF">EAF matrix from stage one</param> /// <param name="M">MID matrix</param> /// <returns>Expected alliance matrix</returns> /// <returns>EA matrix for stage two</returns> private static Matrix UpdateSimplifiedRealistStageTwo(Matrix C, Matrix R, Matrix M, Matrix BEA, string outputFile, double br) { int n = C.Rows; Matrix AE = M * BEA; for (int i = 0; i < n; ++i) for (int j = 0; j < n; ++j) { if (R[i, j] == 1 || AE[i, j] > 0 ) R[i, j] = 1; else R[i, j] = 0; } R.ZeroDiagonal(); Matrix SRC = R * C; Vector SRGC = new Vector(n); for (int i = 0; i < n; ++i) SRGC[i] = SRC.GetRowSum(i) * br; Matrix EAC = BEA * C; Vector AOC = new Vector(n); for (int i = 0; i < n; ++i) { if (EAC.GetRowSum(i) + C[i, i] >= SRGC[i]) AOC[i] = 0; else AOC[i] = 1 - ((EAC.GetRowSum(i) + C[i, i]) / SRGC[i]); } Matrix F = Matrix.Ones(n, n); F.ZeroDiagonal(); Matrix PAN = F - R; Matrix PAC = PAN * C; Matrix EE = M * M; EE.ZeroDiagonal(); for (int i = 0; i < n; ++i) for (int j = 0; j < n; ++j) if (EE[i, j] != 0) EE[i, j] = 1; Matrix EEC = EE * C; Vector EEM = new Vector(n); for (int i = 0; i < n; ++i) EEM[i] = Algorithms.MaxValue<double>(EEC.GetRowEnumerator(i)); Matrix EA = new Matrix(n, n); for (int i = 0; i < n; ++i) for (int j = 0; j < n; ++j) if (EAC[i, j] > 0 || AOC[i] <= 0) EA[i, j] = EAC[i, j]; else if (PAN[i, j] > 0 && EEC[i, j] == EEM[i]) EA[i, j] = EEC[i, j]; else EA[i, j] = 0; //Copied from Stage 1 Vector SEA = new Vector(n); Matrix previousEA = new Matrix(n); Matrix TempEEC = new Matrix(n); EEC.CloneTo(TempEEC); do { EA.CloneTo(previousEA); for (int i = 0; i < n; ++i) SEA[i] = EA.GetRowSum(i) + C[i, i]; for (int i = 0; i < n; ++i) { if (SRGC[i] <= SEA[i]) AOC[i] = 0; else AOC[i] = 1 - SEA[i] / SRGC[i]; } for (int i = 0; i < n; ++i) for (int j = 0; j < n; ++j) if (EEC[i, j] == EEM[i]) EEC[i, j] = 0; for (int i = 0; i < n; ++i) EEM[i] = Algorithms.MaxValue<double>(EEC.GetRowEnumerator(i)); for (int i = 0; i < n; ++i) for (int j = 0; j < n; ++j) { if (AOC[i] == 0 || EA[i, j] != 0) ; else if (PAN[i, j] > 0 && EEC[i, j] == EEM[i]) EA[i, j] = EEC[i, j]; else EA[i, j] = 0; } //for (int i = 0; i < n; ++i) // for (int j = 0; j < n; ++j) // { // if (AOC[i] == 0 || EA[i, j] > 0) ; // else if (EEC[i, j] == EEM[i]) EA[i, j] = EEC[i, j]; // else EA[i, j] = 0; // } } while ((!previousEA.IsSameAs(EA)) && !EEC.IsAllZero && !AOC.IsZeroVector); if (!AOC.IsZeroVector) { //for (int i = 0; i < n; ++i) // for (int j = 0; j < n; ++j) // if (PAC[i, j] > 0 && TempEEC[i, j] != 0) PAC[i, j] = 0; //PAC.CopyLabelsFrom(C); //MatrixWriter.WriteMatrixToMatrixFile(PAC, outputFile); Vector PAM = new Vector(n); for (int i = 0; i < n; ++i) PAM[i] = Algorithms.MaxValue<double>(PAC.GetRowEnumerator(i)); for (int i = 0; i < n; ++i) for (int j = 0; j < n; ++j) if (AOC[i] != 0 && PAC[i, j] == PAM[i] && EA[i, j] == 0) EA[i, j] = PAC[i, j]; do { EA.CloneTo(previousEA); for (int i = 0; i < n; ++i) SEA[i] = EA.GetRowSum(i) + C[i, i]; for (int i = 0; i < n; ++i) { if (SRGC[i] <= SEA[i]) AOC[i] = 0; else AOC[i] = 1 - SEA[i] / SRGC[i]; } //Matrix output = new Matrix(n, n + 4); //for (int i = 0; i < n; i++) // for (int j = 0; j < n; j++) // output[i, j] = EA[i, j]; //for (int i = 0; i < n; ++i) // output[i, n] = SEA[i]; //for (int i = 0; i < n; ++i) // output[i, n + 1] = SRGC[i]; //for (int i = 0; i < n; ++i) // output[i, n + 2] = AOC[i]; //for (int i = 0; i < n; ++i) // output[i, n + 3] = 1111; //output.CopyLabelsFrom(C); //MatrixWriter.WriteMatrixToMatrixFile(output, outputFile); for (int i = 0; i < n; ++i) for (int j = 0; j < n; ++j) if (PAC[i, j] == PAM[i]) PAC[i, j] = 0; //PAC.CopyLabelsFrom(C); //MatrixWriter.WriteMatrixToMatrixFile(PAC, outputFile); for (int i = 0; i < n; ++i) PAM[i] = Algorithms.MaxValue<double>(PAC.GetRowEnumerator(i)); for (int i = 0; i < n; ++i) for (int j = 0; j < n; ++j) if (AOC[i] != 0 && PAC[i, j] == PAM[i] && EA[i, j] == 0) EA[i, j] = PAC[i, j]; } while ((!previousEA.IsSameAs(EA)) && !PAC.IsAllZero && !AOC.IsZeroVector); }//if AOC is not all zero Matrix EAT = EA.GetTranspose(); Matrix EAF = new Matrix(n); for (int i = 0; i < n; ++i) for (int j = 0; j < n; ++j) EAF[i, j] = EA[i, j] * EAT[i, j]; for (int i = 0; i < n; ++i) for (int j = 0; j < n; ++j) { if (EAF[i, j] != 0) BEA[i, j] = 1; else BEA[i, j] = 0; } return BEA; }
/// <summary> /// Simulates stage one of the SIMPLIFIED realist network formation simulation. /// </summary> /// <param name="C">Capability matrix</param> /// <param name="R">Policy relevance matrix (SRG)</param> /// <param name="M">MID matrix</param> /// <returns>Expected alliance matrix</returns> private static Matrix SimulateSimplifiedRealistStageOne(Matrix C, Matrix R, Matrix M, string outputFile, double br) { int n = C.Rows; Matrix SRC = R * C; Vector SRGC = new Vector(n); for (int i = 0; i < n; ++i) SRGC[i] = SRC.GetRowSum(i) * br; Vector AOC = new Vector(n); for (int i = 0; i < n; ++i) { if (SRGC[i] <= C[i, i]) AOC[i] = 0; else AOC[i] = 1 - C[i, i] / SRGC[i]; } Matrix F = Matrix.Ones(n, n); F.ZeroDiagonal(); Matrix PAN = F - R; Matrix PAC = PAN * C; Matrix EE = M * M; EE.ZeroDiagonal(); for (int i = 0; i < n; ++i) for (int j = 0; j < n; ++j) if (EE[i, j] != 0) EE[i, j] = 1; Matrix EEC = EE * C; Vector EEM = new Vector(n); for (int i = 0; i < n; ++i) EEM[i] = Algorithms.MaxValue<double>(EEC.GetRowEnumerator(i)); Matrix EA = new Matrix(n, n); for (int i = 0; i < n; ++i) for (int j = 0; j < n; ++j) if (EEC[i, j] == EEM[i] && PAN[i, j] == 1 && AOC[i] != 0) EA[i, j] = EEC[i, j]; else EA[i, j] = 0; Vector SEA = new Vector(n); Matrix previousEA = new Matrix(n); do { EA.CloneTo(previousEA); for (int i = 0; i < n; ++i) SEA[i] = EA.GetRowSum(i) + C[i, i]; for (int i = 0; i < n; ++i) { if (SRGC[i] <= SEA[i]) AOC[i] = 0; else AOC[i] = 1 - SEA[i] / SRGC[i]; } for (int i = 0; i < n; ++i) for (int j = 0; j < n; ++j) if (EEC[i, j] == EEM[i]) EEC[i, j] = 0; for (int i = 0; i < n; ++i) EEM[i] = Algorithms.MaxValue<double>(EEC.GetRowEnumerator(i)); for (int i = 0; i < n; ++i) for (int j = 0; j < n; ++j) { //if (AOC[i] != 0 && EEC[i, j] == EEM[i] && EA[i, j] == 0) // EA[i, j] = EEC[i, j]; if (AOC[i] == 0 || EA[i, j] != 0); else if (PAN[i, j] > 0 && EEC[i, j] == EEM[i]) EA[i, j] = EEC[i, j]; else EA[i, j] = 0; } } while ((!previousEA.IsSameAs(EA)) && !EEC.IsAllZero && !AOC.IsZeroVector); if (!AOC.IsZeroVector) { for (int i = 0; i < n; ++i) for (int j = 0; j < n; ++j) if (PAC[i, j] > 0 && EEC[i, j] != 0) PAC[i, j] = 0; Vector PAM = new Vector(n); for (int i = 0; i < n; ++i) PAM[i] = Algorithms.MaxValue<double>(PAC.GetRowEnumerator(i)); for (int i = 0; i < n; ++i) for (int j = 0; j < n; ++j) if (AOC[i] != 0 && PAC[i, j] == PAM[i] && EA[i, j] == 0) EA[i, j] = PAC[i, j]; EA.CopyLabelsFrom(C); do { EA.CloneTo(previousEA); for (int i = 0; i < n; ++i) SEA[i] = EA.GetRowSum(i) + C[i, i]; for (int i = 0; i < n; ++i) { if (SRGC[i] <= SEA[i]) AOC[i] = 0; else AOC[i] = 1 - SEA[i] / SRGC[i]; } for (int i = 0; i < n; ++i) for (int j = 0; j < n; ++j) if (PAC[i, j] == PAM[i]) PAC[i, j] = 0; for (int i = 0; i < n; ++i) PAM[i] = Algorithms.MaxValue<double>(PAC.GetRowEnumerator(i)); for (int i = 0; i < n; ++i) for (int j = 0; j < n; ++j) if (AOC[i] != 0 && PAC[i, j] == PAM[i] && EA[i, j] == 0) EA[i, j] = PAC[i, j]; EA.CopyLabelsFrom(C); } while ((!previousEA.IsSameAs(EA)) && !PAC.IsAllZero && !AOC.IsZeroVector); }//if AOC is not all zero Matrix EAT = EA.GetTranspose(); Matrix EAF = new Matrix(n); for (int i = 0; i < n; ++i) for (int j = 0; j < n; ++j) EAF[i, j] = EA[i, j] * EAT[i, j]; Matrix BEA = new Matrix(n); for (int i = 0; i < n; ++i) for (int j = 0; j < n; ++j) { if (EAF[i, j] != 0) BEA[i, j] = 1; else BEA[i, j] = 0; } return BEA; }