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protect calls to min and max with parentheses to make Eigen compatible with default windows.h
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@@ -45,7 +45,7 @@ static void sparse_product_impl2(const Lhs& lhs, const Rhs& rhs, ResultType& res
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// estimate the number of non zero entries
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float ratioLhs = float(lhs.nonZeros())/(float(lhs.rows())*float(lhs.cols()));
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float avgNnzPerRhsColumn = float(rhs.nonZeros())/float(cols);
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float ratioRes = std::min(ratioLhs * avgNnzPerRhsColumn, 1.f);
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float ratioRes = (std::min)(ratioLhs * avgNnzPerRhsColumn, 1.f);
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// int t200 = rows/(log2(200)*1.39);
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// int t = (rows*100)/139;
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@@ -131,7 +131,7 @@ static void sparse_product_impl(const Lhs& lhs, const Rhs& rhs, ResultType& res)
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// estimate the number of non zero entries
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float ratioLhs = float(lhs.nonZeros())/(float(lhs.rows())*float(lhs.cols()));
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float avgNnzPerRhsColumn = float(rhs.nonZeros())/float(cols);
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float ratioRes = std::min(ratioLhs * avgNnzPerRhsColumn, 1.f);
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float ratioRes = (std::min)(ratioLhs * avgNnzPerRhsColumn, 1.f);
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// mimics a resizeByInnerOuter:
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if(ResultType::IsRowMajor)
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@@ -143,7 +143,7 @@ static void sparse_product_impl(const Lhs& lhs, const Rhs& rhs, ResultType& res)
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for (Index j=0; j<cols; ++j)
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{
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// let's do a more accurate determination of the nnz ratio for the current column j of res
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//float ratioColRes = std::min(ratioLhs * rhs.innerNonZeros(j), 1.f);
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//float ratioColRes = (std::min)(ratioLhs * rhs.innerNonZeros(j), 1.f);
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// FIXME find a nice way to get the number of nonzeros of a sub matrix (here an inner vector)
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float ratioColRes = ratioRes;
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tempVector.init(ratioColRes);
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