Add NetCDF data file write/read

[drroe]

Version 6.16.3.

Adds a new data file type based on NetCDF. This is something I've wanted to do for a while to take advantage of all the features of NetCDF. The main benefits of using the NetCDF data format are:

1. Data is stored more or less exactly how it is allocated in CPPTRAJ itself. This means no precision is lost for anything as it is with ASCII data files. Matrices and eigenmodes in particular should benefit from this. It also means that data set metadata (things like data set name and aspect) are not lost.
2. All data sets can be written to a single file, regardless of set type - no other file format in CPPTRAJ supports this. So e.g. you can store a distance, a matrix, a grid, and a cluster pairwise matrix all in the same file.

Note that there was already a NetCDF format type specific to cluster pairwise matrices (.nccmatrix). This is still supported, but probably won't be developed further.

Adds tests for most data set types and updates the manual.

Below shows an example of a NetCDF file header after several matrices/eigenmodes are written to a single NetCDF file with the following CPPTRAJ input:

parm ../tz2.parm7
trajin ../tz2.nc
matrix name CA covar @CA out matrix.nc
matrix name N.CA mwcovar @N @CA out matrix.nc
matrix name heavyAtom !@H= mwcovar out matrix.nc
2drms RMS2D @CA out matrix.nc
diagmatrix CA out matrix.nc name MyEvecs
diagmatrix heavyAtom out matrix.nc name heavyEvecs
run
writedata ca.matrix.dat.save CA nosquare2d prec 12.4
writedata n.ca.matrix.dat.save N.CA nosquare2d prec 12.4
writedata heavyAtom.matrix.dat.save heavyAtom nosquare2d prec 12.4
writedata ca.rms2d.dat.save RMS2D nosquare2d prec 12.4
writedata MyEvecs.dat.save MyEvecs
writedata heavyEvecs.dat.save heavyEvecs

Disk usage of NetCDF vs disk usage of individual ASCII matrix/modes files:

$ du matrix.nc 
1508	matrix.nc
$ du ca.matrix.dat.save n.ca.matrix.dat.save heavyAtom.matrix.dat.save ca.rms2d.dat.save MyEvecs.dat.save heavyEvecs.dat.save 
44	ca.matrix.dat.save
44	n.ca.matrix.dat.save
3852	heavyAtom.matrix.dat.save
320	ca.rms2d.dat.save
16	MyEvecs.dat.save
1356	heavyEvecs.dat.save

netcdf matrix {
dimensions:
	size.0 = 666 ;
	vectsize.1 = 36 ;
	size.2 = 1404 ;
	vectsize.3 = 75 ;
	nmass.4 = 13 ;
	size.5 = 61776 ;
	vectsize.6 = 351 ;
	nmass.7 = 117 ;
	size.8 = 5050 ;
	nmodes.9 = 36 ;
	nevecelts.10 = 1296 ;
	ncoords.11 = 36 ;
	nmodes.12 = 351 ;
	nevecelts.13 = 123201 ;
	ncoords.14 = 351 ;
	nmass.15 = 117 ;
variables:
	double CA.matrix(size.0) ;
		CA.matrix:name = "CA" ;
		CA.matrix:legend = "CA" ;
		CA.matrix:scalartype = "covariance" ;
		CA.matrix:scalarmode = "matrix" ;
		CA.matrix:nindexvar = 2 ;
		CA.matrix:min0 = 1. ;
		CA.matrix:step0 = 1. ;
		CA.matrix:label0 = "Atom" ;
		CA.matrix:min1 = 1. ;
		CA.matrix:step1 = 1. ;
		CA.matrix:description = "double matrix" ;
		CA.matrix:ncols = 36 ;
		CA.matrix:nrows = 36 ;
		CA.matrix:matrixkind = "half" ;
		CA.matrix:nsnapshots = 101 ;
		CA.matrix:vectid = 1 ;
	double CA.vect(vectsize.1) ;
	double N.CA.matrix(size.2) ;
		N.CA.matrix:name = "N.CA" ;
		N.CA.matrix:legend = "N.CA" ;
		N.CA.matrix:scalartype = "mass-weighted covariance" ;
		N.CA.matrix:scalarmode = "matrix" ;
		N.CA.matrix:nindexvar = 2 ;
		N.CA.matrix:min0 = 1. ;
		N.CA.matrix:step0 = 1. ;
		N.CA.matrix:label0 = "Atom" ;
		N.CA.matrix:min1 = 1. ;
		N.CA.matrix:step1 = 1. ;
		N.CA.matrix:description = "double matrix" ;
		N.CA.matrix:ncols = 39 ;
		N.CA.matrix:nrows = 36 ;
		N.CA.matrix:matrixkind = "full" ;
		N.CA.matrix:nsnapshots = 101 ;
		N.CA.matrix:vectid = 3 ;
		N.CA.matrix:massid = 4 ;
	double N.CA.vect(vectsize.3) ;
	double N.CA.mass(nmass.4) ;
	double heavyAtom.matrix(size.5) ;
		heavyAtom.matrix:name = "heavyAtom" ;
		heavyAtom.matrix:legend = "heavyAtom" ;
		heavyAtom.matrix:scalartype = "mass-weighted covariance" ;
		heavyAtom.matrix:scalarmode = "matrix" ;
		heavyAtom.matrix:nindexvar = 2 ;
		heavyAtom.matrix:min0 = 1. ;
		heavyAtom.matrix:step0 = 1. ;
		heavyAtom.matrix:label0 = "Atom" ;
		heavyAtom.matrix:min1 = 1. ;
		heavyAtom.matrix:step1 = 1. ;
		heavyAtom.matrix:description = "double matrix" ;
		heavyAtom.matrix:ncols = 351 ;
		heavyAtom.matrix:nrows = 351 ;
		heavyAtom.matrix:matrixkind = "half" ;
		heavyAtom.matrix:nsnapshots = 101 ;
		heavyAtom.matrix:vectid = 6 ;
		heavyAtom.matrix:massid = 7 ;
	double heavyAtom.vect(vectsize.6) ;
	double heavyAtom.mass(nmass.7) ;
	float RMS2D.matrix(size.8) ;
		RMS2D.matrix:name = "RMS2D" ;
		RMS2D.matrix:legend = "RMS2D" ;
		RMS2D.matrix:nindexvar = 2 ;
		RMS2D.matrix:min0 = 1. ;
		RMS2D.matrix:step0 = 1. ;
		RMS2D.matrix:min1 = 1. ;
		RMS2D.matrix:step1 = 1. ;
		RMS2D.matrix:description = "float matrix" ;
		RMS2D.matrix:ncols = 101 ;
		RMS2D.matrix:nrows = 101 ;
		RMS2D.matrix:matrixkind = "tri" ;
	double MyEvecs.eigenvalues(nmodes.9) ;
		MyEvecs.eigenvalues:name = "MyEvecs" ;
		MyEvecs.eigenvalues:legend = "MyEvecs" ;
		MyEvecs.eigenvalues:scalartype = "covariance" ;
		MyEvecs.eigenvalues:nindexvar = 0 ;
		MyEvecs.eigenvalues:description = "eigenmodes" ;
		MyEvecs.eigenvalues:eigenvectorsid = 10 ;
		MyEvecs.eigenvalues:avgcoordsid = 11 ;
	double MyEvecs.eigenvectors(nevecelts.10) ;
	double MyEvecs.avgcoords(ncoords.11) ;
	double heavyEvecs.eigenvalues(nmodes.12) ;
		heavyEvecs.eigenvalues:name = "heavyEvecs" ;
		heavyEvecs.eigenvalues:legend = "heavyEvecs" ;
		heavyEvecs.eigenvalues:scalartype = "mass-weighted covariance" ;
		heavyEvecs.eigenvalues:nindexvar = 0 ;
		heavyEvecs.eigenvalues:description = "eigenmodes" ;
		heavyEvecs.eigenvalues:eigenvectorsid = 13 ;
		heavyEvecs.eigenvalues:avgcoordsid = 14 ;
		heavyEvecs.eigenvalues:massid = 15 ;
	double heavyEvecs.eigenvectors(nevecelts.13) ;
	double heavyEvecs.avgcoords(ncoords.14) ;
	double heavyEvecs.mass(nmass.15) ;

// global attributes:
		:program = "cpptraj" ;
		:programVersion = "V6.16.3" ;
		:Conventions = "CPPTRAJ_DATA" ;
		:ConventionVersion = "1.0" ;
}

[lgtm-com]

This pull request introduces 4 alerts when merging b4eac12 into b87be3c - view on LGTM.com

new alerts:

• 2 for 'new[]' array freed with 'delete'
• 1 for Multiplication result converted to larger type
• 1 for Too few arguments to formatting function

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[lgtm-com]

This pull request introduces 2 alerts when merging 204634f into b87be3c - view on LGTM.com

new alerts:

• 1 for Wrong type of arguments to formatting function
• 1 for Too few arguments to formatting function

---

Heads-up: LGTM.com's PR analysis will be disabled on the 5th of December, and LGTM.com will be shut down ⏻ completely on the 16th of December 2022. It looks like GitHub code scanning with CodeQL is already set up for this repo, so no further action is needed 🚀. For more information, please check out our post on the GitHub blog.