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misc cleaning / eigenization
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@@ -238,8 +238,7 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveOneStep(
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/* on the first iteration, calculate the norm of the scaled x */
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/* and initialize the step bound delta. */
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wa3 = diag.cwiseProduct(x);
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xnorm = wa3.stableNorm();
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xnorm = diag.cwiseProduct(x).stableNorm();
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delta = parameters.factor * xnorm;
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if (delta == 0.)
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delta = parameters.factor;
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@@ -269,8 +268,7 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveOneStep(
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/* store the direction p and x + p. calculate the norm of p. */
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wa1 = -wa1;
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wa2 = x + wa1;
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wa3 = diag.cwiseProduct(wa1);
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pnorm = wa3.stableNorm();
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pnorm = diag.cwiseProduct(wa1).stableNorm();
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/* on the first iteration, adjust the initial step bound. */
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if (iter == 1)
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@@ -489,8 +487,7 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffOneStep(
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/* on the first iteration, calculate the norm of the scaled x */
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/* and initialize the step bound delta. */
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wa3 = diag.cwiseProduct(x);
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xnorm = wa3.stableNorm();
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xnorm = diag.cwiseProduct(x).stableNorm();
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delta = parameters.factor * xnorm;
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if (delta == 0.)
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delta = parameters.factor;
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@@ -520,8 +517,7 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffOneStep(
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/* store the direction p and x + p. calculate the norm of p. */
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wa1 = -wa1;
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wa2 = x + wa1;
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wa3 = diag.cwiseProduct(wa1);
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pnorm = wa3.stableNorm();
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pnorm = diag.cwiseProduct(wa1).stableNorm();
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/* on the first iteration, adjust the initial step bound. */
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if (iter == 1)
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