A C++11 single-header Matrix Market reader (raw file here).
Build examples and tests (tools are always built)
mkdir build && cd build
cmake .. -DMM_BUILD_EXAMPLES=ON -DMM_BUILD_TESTS=ON
make && make testExample:
#include "mm/mm.hpp"
int main(int argc, char **argv)
{
if (argc < 2)
{
std::cerr << "Usage: " << argv[0] << " <file.mtx>\n";
exit(EXIT_FAILURE);
}
const std::string path = argv[1];
{
std::cout << "with Ordinal=int, Scalar=float, Offset=size_t" << std::endl;
typedef int Ordinal;
typedef float Scalar;
typedef MtxReader<Ordinal, Scalar> reader_t;
typedef typename reader_t::coo_type coo_t;
typedef typename coo_t::entry_type entry_t;
// read matrix as coo
reader_t reader(path);
coo_t coo = reader.read_coo();
// non-zeros, rows, cols
std::cout << coo.nnz() << std::endl; // size_t
std::cout << coo.num_rows() << "," << coo.num_cols() << std::endl; // int
// first entry
entry_t e = coo.entries[0];
std::cout << e.i << "," << e.j << std::endl; // int, int
std::cout << e.e << std::endl; // float
}
{
std::cout << "with Ordinal=int64_t, Scalar=std::complex<float>, Offset=int" << std::endl;
typedef MtxReader<int64_t, std::complex<float>, int> reader_t;
typedef typename reader_t::coo_type coo_t;
typedef typename coo_t::entry_type entry_t;
// read matrix as coo
reader_t reader(path);
coo_t coo = reader.read_coo();
// non-zeros, rows, cols
std::cout << coo.nnz() << std::endl; // int
std::cout << coo.num_rows() << "," << coo.num_cols() << std::endl; // complex<double>
// first entry
entry_t e = coo.entries[0];
std::cout << e.i << "," << e.j << std::endl; // int64_t
std::cout << e.e << std::endl; // complex<double>
}
return 0;
}You decide statically what your Ordinal, Scalar, and Offset types will be:
Ordinal: the type of i, jScalar: the type of the matrix entriesOffset: the type of the number of non-zeros
You provide that to your reader. Optionally, use typedefs for convenience:
typedef int64_t Ordinal;
typedef std::complex<float> Scalar;
typedef int Offset;
typedef MtxReader<Ordinal, Scalar, Offset> reader_t;
typedef typename reader_t::coo_type coo_t;
typedef typename coo_t::entry_type entry_t;
reader_t reader(/* path to mtx file */);The Scalar conversions will behave as you expect:
- Each
Scalarwill be constructed from the read value:Scalar(x). patternmatrices will yield youScalar(1)as all values- If the matrix is
complexand theScalaris not, theScalarwill be equal to the magnitude of the complex number. - If
Scalaris complex and the matrix is not, the imaginary part of theScalarwill be 0. - Any explicit zeros in the mtx file will not be included in the resulting non-zero entries.
You can then read the matrix as a COO file
coo_t coo = reader.read_coo();The COO is also templated over Ordinal, Scalar, and Offset.
So COO::nnz() is an Offset, COO::num_rows() and COO::num_cols() are Ordinal.
You can then iterate over entries:
for (entry_t e : coo.entries) {
e.i;
e.j;
e.e;
// ...
}Entries are also templated over Ordinal and Scalar.
Entry::i and Entry::j are Ordinal, Entry::e is Scalar.
The "additional" non-zeros implied by hermitian, symmetric, skew-symmetric are added to the resulting COO.
This means that coo.nnz() may not be the number of entries listed in the .mtx file.
Some tools are provided
Print some statistics about provided mtx files
Print counts of dense blocks in the provided matrix.
Convert an mtx file to a PPM file visuzalizing non-zero entries.
tools/mtx-to-ppm in.mtx out.ppm 2048- create
out.ppmwith a visualization of the non-zeros inin.mtx. THe longest image dimension will be 2048 pixels.
- create
tools/mtx-to-ppm in.mtx out.ppm 537 223- create
out.ppmwith a visualization of the non-zeros inin.mtx. The image will be 537 by 223 pixels.
- create
PPM files are large, and probably should be converted to another lossless format before distribution. A comment will be included in the PMM file with some information about the source matrix and the mapping of non-zeros to pixel values. For example:
# created by github.com/cwpearson/matrix-market/tools/mtx-to-ppm
# source matrix: 208918 x 208918 w/ 5540838 nnz
# each pixel approx 102 x 102 entries
# approx pixel's nnz count vs value
# each row is pixel value, then nnz count for val ... val+9
# 0: 482 470 459 448 437 427 417 407 397 388
# 10: 378 369 360 352 343 335 327 319 312 304
# 20: 297 290 283 276 269 263 257 251 245 239
# 30: 233 227 222 217 211 206 201 197 192 187
# 40: 183 179 174 170 166 162 158 154 151 147
# 50: 144 140 137 133 130 127 124 121 118 115
# 60: 113 110 107 105 102 100 97 95 93 91
# 70: 88 86 84 82 80 78 76 75 73 71
# 80: 69 68 66 65 63 61 60 59 57 56
# 90: 54 53 52 51 49 48 47 46 45 44
# 100: 43 42 41 40 39 38 37 36 35 34
# 110: 34 33 32 31 30 30 29 28 28 27
# 120: 26 26 25 24 24 23 23 22 22 21
# 130: 21 20 20 19 19 18 18 17 17 17
# 140: 16 16 15 15 15 14 14 14 13 13
# 150: 13 12 12 12 12 11 11 11 10 10
# 160: 10 10 10 9 9 9 9 8 8 8
# 170: 8 8 7 7 7 7 7 7 6 6
# 180: 6 6 6 6 6 5 5 5 5 5
# 190: 5 5 5 4 4 4 4 4 4 4
# 200: 4 4 4 4 3 3 3 3 3 3
# 210: 3 3 3 3 3 3 3 3 2 2
# 220: 2 2 2 2 2 2 2 2 2 2
# 230: 2 2 2 2 2 2 2 2 2 1
# 240: 1 1 1 1 1 1 1 1 1 1
# 250: 1 1 1 1 1 0
data/abb313.mtx: rectangular, coordinate pattern generaldata/08blocks.mtx: square, coordinate integer generaldata/Trefethen_20b: coordinate integer symmetricdata/mhd1280b: coordinate complex Hermitian
This code is released under the GPLv3 license (please see the LICENSE file).
The test matrix data is provided by the SuiteSparse Matrix Collection and is not covered by the license.
Alternative licensing schemes may be available upon request - please contact the maintainer.