Merge remote-tracking branch 'origin/master' into v2.6

CHANGES/v2.5.md

@@ -193,8 +193,10 @@ For users:
 ## Version 2.5.3 (to be released)
 
 For users:
-- Fixed a bug with \ref CONVERT_TO_FES and periodic variables, see \issue{441} 
-- New patch for GROMACS 2019.4
+- Fixed a bug with \ref CONVERT_TO_FES and periodic variables, see \issue{441}
+- Fixed a bug with \ref FOURIER_TRANSFORM 
+- Updated patch for GROMACS 2019.4
+- Updated patch for GROMACS 2018.8
 - Python module:
   - Fixed building with clang-8.
   - Set `language_level` for cython to the actually used language level.

CHANGES/v2.6.md

@@ -14,10 +14,6 @@ Changes from version 2.5 which are relevant for users:
   - \ref EEFSOLV is now faster in scalar and also mpi/openmp parallel
   - New shortcuts are available for selecting protein atoms: `@sidechain-#`, `@back-#`
 
-- Python module:
-  - Added capability to read and write pandas dataset from PLUMED files (see \issue{496}).
-
-
 - New contributed modules:
   - A new Maze module by Jakub Rydzewski
      - \ref MAZE_LOSS

src/gridtools/FourierTransform.cpp

@@ -59,7 +59,7 @@ The default values of these parameters are: \f$a=1\f$ and \f$b=1\f$.
 The following example tells Plumed to compute the complex 2D 'backward' Discrete Fourier Transform by taking the data saved on a grid called 'density', and normalizing the output by \f$ \frac{1}{\sqrt{N_x\, N_y}}\f$, where \f$N_x\f$ and \f$N_y\f$ are the number of data on the grid (it can be the case that \f$N_x\neq N_y\f$):
 
 \plumedfile
-FOURIER_TRANSFORM STRIDE=1 GRID=density FT_TYPE=complex FOURIER_PARAMETERS=0,-1 
+FOURIER_TRANSFORM STRIDE=1 GRID=density FT_TYPE=complex FOURIER_PARAMETERS=0,-1
 \endplumedfile
 
 */
@@ -70,11 +70,11 @@ class FourierTransform : public ActionWithInputGrid {
 private:
   std::string output_type;
   bool real_output, store_norm;
-  std::vector<unsigned> gdirs;
   std::vector<int> fourier_params;
 public:
   static void registerKeywords( Keywords& keys );
   explicit FourierTransform(const ActionOptions&ao);
+  void clearAverage();
 #ifndef __PLUMED_HAS_FFTW
   void performOperations( const bool& from_update ) override {}
 #else
@@ -138,27 +138,20 @@ FourierTransform::FourierTransform(const ActionOptions&ao):
 
   // Create the input from the old string
   std::string vstring;
-  unsigned n=0; gdirs.resize( ingrid->getDimension() );
-  for(unsigned i=0; i<ingrid->getDimension(); ++i) {
-    gdirs[n]=i; n++;
-  }
-
-  plumed_assert( n==ingrid->getDimension() );
-
   if (real_output) {
     if (!store_norm) vstring="COMPONENTS=" + getLabel() + "_abs";
     else vstring="COMPONENTS=" + getLabel() + "_norm";
   } else vstring="COMPONENTS=" + getLabel() + "_real," + getLabel() + "_imag";
 
   // Set COORDINATES keyword
-  vstring += " COORDINATES=" + ingrid->getComponentName( gdirs[0] );
-  for(unsigned i=1; i<gdirs.size(); ++i) vstring += "," + ingrid->getComponentName( gdirs[i] );
+  vstring += " COORDINATES=" + ingrid->getComponentName( 0 );
+  for(unsigned i=1; i<ingrid->getDimension(); ++i) vstring += "," + ingrid->getComponentName( i );
 
   // Set PBC keyword
   vstring += " PBC=";
-  if( ingrid->isPeriodic(gdirs[0]) ) vstring+="T"; else vstring+="F";
-  for(unsigned i=1; i<gdirs.size(); ++i) {
-    if( ingrid->isPeriodic(gdirs[i]) ) vstring+=",T"; else vstring+=",F";
+  if( ingrid->isPeriodic(0) ) vstring+="T"; else vstring+="F";
+  for(unsigned i=1; i<ingrid->getDimension(); ++i) {
+    if( ingrid->isPeriodic(i) ) vstring+=",T"; else vstring+=",F";
   }
 
 
@@ -171,32 +164,21 @@ FourierTransform::FourierTransform(const ActionOptions&ao):
 #endif
 }
 
+void FourierTransform::clearAverage() {
+  std::vector<double> fspacing;
+  std::vector<std::string> ft_min( ingrid->getMin() ), ft_max( ingrid->getMax() );
+  for(unsigned i=0; i<ingrid->getDimension(); ++i) {
+    Tools::convert( 0.0, ft_min[i] ); Tools::convert( 2.0*pi*ingrid->getNbin()[i]/ ingrid->getGridExtent(i), ft_max[i] );
+  }
+  mygrid->setBounds( ft_min, ft_max, ingrid->getNbin(), fspacing); resizeFunctions();
+  ActionWithAveraging::clearAverage();
+}
+
 #ifdef __PLUMED_HAS_FFTW
 void FourierTransform::performOperations( const bool& from_update ) {
 
   // Spacing of the real grid
   std::vector<double> g_spacing ( ingrid->getGridSpacing() );
-  // Spacing of the k-grid
-  std::vector<double> ft_spacing;
-  // Extents of the k-grid
-  std::vector<std::string> ft_min( ingrid->getMin() ), ft_max( ingrid->getMax() );
-  // Number of bins in the k-grid (equal to the number of bins in the real grid)
-  std::vector<unsigned> ft_bins ( ingrid->getNbin() );
-
-  for (unsigned i=0; i<ingrid->getDimension(); ++i) {
-    // Check PBC in current grid dimension
-    if( !ingrid->isPeriodic(i) ) ft_bins[i]++;
-    // Compute k-grid extents
-    double dmin, dmax;
-    Tools::convert(ft_min[i],dmin); Tools::convert(ft_max[i],dmax);
-    // We want to have the min of k-grid at point (0,0)
-    dmin=0.0;
-    dmax=2.0*pi*ft_bins[i]/( ingrid->getGridExtent(i) );
-    Tools::convert(dmin,ft_min[i]); Tools::convert(dmax,ft_max[i]);
-  }
-
-  // This is the actual setup of the k-grid
-  mygrid->setBounds( ft_min, ft_max, ft_bins, ft_spacing); resizeFunctions();
 
   // *** CHECK CORRECT k-GRID BOUNDARIES ***
   //log<<"Real grid boundaries: \n"
@@ -206,11 +188,11 @@ void FourierTransform::performOperations( const bool& from_update ) {
   //    <<"  min_x: "<<ft_min[0]<<"  min_y: "<<ft_min[1]<<"\n"
   //    <<"  max_x: "<<ft_max[0]<<"  max_y: "<<ft_max[1]<<"\n";
 
-
-
   // Get the size of the input data arrays (to allocate FFT data)
+  size_t fft_dimension=static_cast<size_t>( ingrid->getNumberOfPoints() );
   std::vector<unsigned> N_input_data( ingrid->getNbin() );
-  size_t fft_dimension=1; for(unsigned i=0; i<N_input_data.size(); ++i) fft_dimension*=static_cast<size_t>( N_input_data[i] );
+  for(unsigned i=0; i<N_input_data.size(); ++i) if( !ingrid->isPeriodic(i) ) N_input_data[i]++;
+  // size_t fft_dimension=1; for(unsigned i=0; i<N_input_data.size(); ++i) fft_dimension*=static_cast<size_t>( N_input_data[i] );
 
   // FFT arrays
   std::vector<std::complex<double> > input_data(fft_dimension), fft_data(fft_dimension);

src/tools/MolDataClass.cpp

@@ -168,7 +168,7 @@ void MolDataClass::getBackboneForResidue( const std::string& type, const unsigne
       atoms.resize(5);
       atoms[0]=mypdb.getNamedAtomFromResidue("N",residuenum);
       atoms[1]=mypdb.getNamedAtomFromResidue("CA",residuenum);
-      atoms[2]=mypdb.getNamedAtomFromResidue("HA1",residuenum);
+      atoms[2]=mypdb.getNamedAtomFromResidue("HA2",residuenum);
       atoms[3]=mypdb.getNamedAtomFromResidue("C",residuenum);
       atoms[4]=mypdb.getNamedAtomFromResidue("O",residuenum);
     } else if( residuename=="ACE") {

user-doc/tutorials/others/isdb-2.txt

@@ -16,7 +16,7 @@ Once this tutorial is completed users will be able to:
 \section isdb-2-resources Resources
 
 The \tarball{isdb-2} for this project contains the following files:
-- martiniFormFactor_p2.py and martiniFormFactor_p3.py: two helpful python scripts to be used with python 2 or python 3, respectively. These are based on the martinize.py script (http://cgmartini.nl/index.php/tools2/proteins-and-bilayers/204-martinize) 
+- martiniFormFactor_p3.py: a python script to be used with python 3. This is based on the martinize.py script (http://cgmartini.nl/index.php/tools2/proteins-and-bilayers/204-martinize) 
 - start.pdb and samplextc.xtc: PDB and trajectory files on which you can perform the calculations;
 - SASDAB7.dat: a file containing SAXS intensities, downloaded from the SASDB database \cite Valentini:2015ki .
 
@@ -31,7 +31,7 @@ The Martini form factors can be exploited within a hybrid multi-resolution strat
 \section isdb-2-comp1 Computing SAXS intensities with the hybrid coarse-grained/atomistic approach
 
 Given a PDB file, PLUMED is able to compute SAXS intensities for the molecule in the PDB and to compare these intensities with the experimental ones stored in a data file. It is possible to apply the same procedure to all the conformations visited during a MD trajectory. This is achieved by using the PLUMED \ref driver utility and the \ref SAXS variable of the ISDB module.
-While computing scattering intensities with a full atomistic representation is quite easy (see the \ref SAXS keyword and later in this tutorial), in order to adopt the hybrid coarse-grained/atomistic approach a more elaborated procedure is needed, requiring the generation of few specific files to be used as input by \ref driver. To facilitate this step, it is possible to use this script (martiniFormFactor_p2.py for python 2 or martiniFormFactor_p3.py for python 3) and type in the bash shell:
+While computing scattering intensities with a full atomistic representation is quite easy (see the \ref SAXS keyword and later in this tutorial), in order to adopt the hybrid coarse-grained/atomistic approach a more elaborated procedure is needed, requiring the generation of few specific files to be used as input by \ref driver. To facilitate this step, it is possible to use this script (martiniFormFactor_p3.py for python 3) and type in the bash shell:
 
 \verbatim
 python martiniFormFactor_p3.py -f start.pdb -dat SASDAB7.dat [-unit Ang/nm -nq 15]