When trying to install CHAP on CentOS 7 linux (with GROMACS 2018.8, Intel Compilers 2018.3 and Intel MKL 2018.3) I had to fix a few issues and bugs for making it work correctly.
--- chap-version_0_9_1/src/trajectory-analysis/chap_trajectory_analysis.cpp.orig 2018-05-02 13:22:36.000000000 +0200
+++ chap-version_0_9_1/src/trajectory-analysis/chap_trajectory_analysis.cpp 2019-12-09 13:52:36.745685228 +0100
@@ -84,7 +84,7 @@
frameStreamData_.setMultipoint(true);
// default initial probe position and chanell direction:
- pfInitProbePos_ = {std::nan(""), std::nan(""), std::nan("")};
+ pfInitProbePos_ = {(real)std::nan(""), (real)std::nan(""), (real)std::nan("")};
pfChanDirVec_ = {0.0, 0.0, 1.0};
}
--- chap-version_0_9_1/test/geometry/ut_bspline_basis_set.cpp.orig 2018-05-02 13:22:36.000000000 +0200
+++ chap-version_0_9_1/test/geometry/ut_bspline_basis_set.cpp 2019-12-06 16:57:13.304949817 +0100
@@ -41,7 +41,7 @@
std::vector<real> uniqueKnots_ = {-4, -0.5, 0.0, 0.5, 4};
// evaluation points:
- std::vector<real> evalPoints_ = {-4.0, -2.5, 0.0, 0.5, -1.0, std::sqrt(2.0), 4.0};
+ std::vector<real> evalPoints_ = {-4.0, -2.5, 0.0, 0.5, -1.0, (real)std::sqrt(2.0), 4.0};
// true knot span index:
std::vector<size_t> knotSpanIdx_ = {0, 0, 2, 3, 0, 3, 3};
--- chap-version_0_9_1/test/statistics/ut_amise_optimal_bandwidth_estimator.cpp.orig 2018-05-02 13:22:36.000000000 +0200
+++ chap-version_0_9_1/test/statistics/ut_amise_optimal_bandwidth_estimator.cpp 2019-12-06 16:59:40.880202641 +0100
@@ -62,7 +62,7 @@
// parameters:
int numReps = 2;
- std::vector<real> mean = {-10, 0.0, std::sqrt(2.0)};
+ std::vector<real> mean = {-10, 0.0, (real)std::sqrt(2.0)};
std::vector<real> numSamples = {250, 500, 750};
std::vector<real> standardDeviation = {100.0, 1.0, 0.01};
--- chap-version_0_9_1/test/statistics/ut_histogram_density_estimator.cpp.orig 2018-05-02 13:22:36.000000000 +0200
+++ chap-version_0_9_1/test/statistics/ut_histogram_density_estimator.cpp 2019-12-06 17:07:42.104516814 +0100
@@ -82,7 +82,7 @@
HistogramDensityEstimator hde;
// some bin widths to try:
- std::vector<real> binWidth = {1.0, 0.1, 1e-5, std::sqrt(2.0)};
+ std::vector<real> binWidth = {1.0, 0.1, 1e-5, (real)std::sqrt(2.0)};
// loop over bin widths and check that breaks are correct:
for(auto it = binWidth.begin(); it != binWidth.end(); it++)
@@ -138,7 +138,7 @@
// some bin widths to try:
// NOTE: if bin width too small, spline interpolation will fail!
- std::vector<real> binWidth = {1.0, 0.1, 1e-2, 0.1*std::sqrt(2.0)};
+ std::vector<real> binWidth = {1.0, 0.1, 1e-2, (real)(0.1*std::sqrt(2.0))};
// perform tests for each bin width value:
for(auto bw : binWidth)
@@ -187,7 +187,7 @@
// some bin widths to try:
// NOTE: if bin width too small, spline interpolation will fail!
- std::vector<real> binWidth = {1.0, 0.1, 1e-2, 0.1*std::sqrt(2.0)};
+ std::vector<real> binWidth = {1.0, 0.1, 1e-2, (real)(0.1*std::sqrt(2.0))};
// perform tests for each binwidth value:
for(auto bw : binWidth)
@@ -238,8 +238,8 @@
// some bin widths to try:
// NOTE: if bin width too small, spline interpolation will fail!
- std::vector<real> binWidth = {1.0, 0.1, 1e-2, 0.1*std::sqrt(2.0)};
- binWidth = {1.0, 0.1, 0.01, 0.1*std::sqrt(2.0)};
+ std::vector<real> binWidth = {1.0, 0.1, 1e-2, (real)(0.1*std::sqrt(2.0))};
+ binWidth = {1.0, 0.1, 0.01, (real)(0.1*std::sqrt(2.0))};
// get data range:
real dataMin = *std::min_element(testData_.begin(), testData_.end());
@@ -268,7 +268,7 @@
0);
// this should always be zero:
- ASSERT_NEAR(0.0, density, std::sqrt(eps));
+ ASSERT_NEAR(0.0, density, (real)std::sqrt(eps));
}
// evaluate density below data range:
@@ -283,7 +283,7 @@
0);
// this should always be zero:
- ASSERT_NEAR(0.0, density, std::sqrt(eps));
+ ASSERT_NEAR(0.0, density, (real)std::sqrt(eps));
}
// evaluate spline within data range:
@@ -317,7 +317,7 @@
integral += d;
}
integral *= evalStep;
- ASSERT_NEAR(1.0, integral, std::sqrt(eps));
+ ASSERT_NEAR(1.0, integral, (real)std::sqrt(eps));
}
}
--- chap-version_0_9_1/test/statistics/ut_summary_statistics.cpp.orig 2018-05-02 13:22:36.000000000 +0200
+++ chap-version_0_9_1/test/statistics/ut_summary_statistics.cpp 2019-12-06 17:16:08.457527879 +0100
@@ -44,7 +44,7 @@
// constructor for creating test data:
SummaryStatisticsTest()
{
- testData_ = {0.3, 1.5, -0.9, std::sqrt(2.0), -5.1};
+ testData_ = {0.3, 1.5, -0.9, (real)std::sqrt(2.0), -5.1};
}
--- chap-version_0_9_1/test/statistics/ut_gaussian_density_derivative.cpp.orig 2018-05-02 13:22:36.000000000 +0200
+++ chap-version_0_9_1/test/statistics/ut_gaussian_density_derivative.cpp 2019-12-06 17:24:42.659436050 +0100
@@ -263,9 +263,9 @@
// check that truncation criterion is met:
real b = std::min<real>(gdd.rc_,
- 0.5*(gdd.ri_ + std::sqrt(gdd.ri_*gdd.ri_ +
+ 0.5*(gdd.ri_ + (real)std::sqrt(gdd.ri_*gdd.ri_ +
8.0*trunc*gdd.bw_*gdd.bw_)));
- real error = std::sqrt(gdd.factorial(gdd.r_))
+ real error = (real)std::sqrt(gdd.factorial(gdd.r_))
/ gdd.factorial(trunc)
* std::pow((gdd.ri_ * b / (gdd.bw_*gdd.bw_)), trunc)
* std::exp(-(std::pow(gdd.ri_ - b, 2))
--- chap-version_0_9_1/test/geometry/ut_basis_spline.cpp.orig 2018-05-02 13:22:36.000000000 +0200
+++ chap-version_0_9_1/test/geometry/ut_basis_spline.cpp 2019-12-10 18:55:53.114400365 +0100
@@ -49,7 +49,7 @@
std::vector<real> knotVector_ = {-4, -0.5, 0.0, 0.5, 4};
// evaluation points:
- std::vector<real> evalPoints_ = {-4.0, -2.5, 0.0, 0.5, -1.0, std::sqrt(2.0), 4.0};
+ std::vector<real> evalPoints_ = {-4.0, -2.5, 0.0, 0.5, -1.0, (real)std::sqrt(2.0), 4.0};
};
--- chap-version_0_9_1/src/io/analysis_data_json_frame_exporter.cpp.orig 2018-05-02 13:22:36.000000000 +0200
+++ chap-version_0_9_1/src/io/analysis_data_json_frame_exporter.cpp 2019-12-10 18:45:48.496459218 +0100
@@ -169,7 +169,7 @@
const gmx::AnalysisDataFrameHeader& /*frame*/)
{
// open output file separately for each frame:
- file_.open(fileName_.c_str(), std::fstream::app);
+ file_.open(fileName_.c_str(), std::fstream::out | std::fstream::app);
// create buffer writer string writer:
rapidjson::StringBuffer buffer;
--- chap-version_0_9_1/src/io/molecular_path_obj_exporter.cpp.orig 2018-05-02 13:22:36.000000000 +0200
+++ chap-version_0_9_1/src/io/molecular_path_obj_exporter.cpp 2019-12-10 21:33:58.590351428 +0100
@@ -1064,7 +1064,7 @@
// for sequential colour scale, shift data to positive real range and
// scale by length of data interval:
real shift = -minProp;
- real scale = 1.0/(maxProp - minProp);
+ double scale = 1.0/(maxProp - minProp);
// shift and scale the property array:
std::for_each(prop.begin(), prop.end(), [shift](real &p){p += shift;});
@@ -1075,7 +1075,7 @@
// for divergent colour scale, scale both positive and negative values
// such that data lies in [-0.5, 0.5], then shift by 0.5:
real shift = 0.5;
- real scale = 1.0/std::max(std::fabs(minProp), std::fabs(maxProp))/2.0;
+ double scale = 1.0/std::max(std::fabs(minProp), std::fabs(maxProp))/2.0;
// scale and shift:
std::for_each(prop.begin(), prop.end(), [scale](real &p){p *= scale;});
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