diff options
Diffstat (limited to 'README.md')
| -rw-r--r-- | README.md | 27 |
1 files changed, 15 insertions, 12 deletions
@@ -1,6 +1,6 @@ # Ripser -Copyright © 2015–2018 [Ulrich Bauer]. +Copyright © 2015–2019 [Ulrich Bauer]. ### Description @@ -24,6 +24,8 @@ Input formats currently supported by Ripser: - comma-separated values upper triangular distance matrix (MATLAB output from the function `pdist`) - comma-separated values full distance matrix - [DIPHA] distance matrix data + - sparse distance matrix in Sparse Triplet format + - binary lower triangular distance matrix - point cloud data Ripser's efficiency is based on a few important concepts and principles, building on key previous and concurrent developments by other researchers in computational topology: @@ -37,7 +39,7 @@ Ripser's efficiency is based on a few important concepts and principles, buildin ### Version -[Latest release][latest-release]: 1.0.1 (September 2016) +[Latest release][latest-release]: 1.1 (July 2019) ### Building @@ -56,16 +58,14 @@ make Ripser supports several compile-time options. They are switched on by defining the C preprocessor macros listed below, either using `#define` in the code or by passing an argument to the compiler. The following options are supported: - - `ASSEMBLE_REDUCTION_MATRIX`: store the reduction matrix; may affect computation time but also memory usage; recommended for large and difficult problem instances - - `USE_COEFFICIENTS`: enable support for coefficients in a prime field - `INDICATE_PROGRESS`: indicate the current progress in the console - `PRINT_PERSISTENCE_PAIRS`: output the computed persistence pairs (enabled by default in the code; comment out to disable) - `USE_GOOGLE_HASHMAP`: enable support for Google's [sparsehash] data structure; may further reduce memory footprint -For example, to build Ripser with support for coefficients: +For example, to build Ripser with support for Google's hashmap: ```sh -$ c++ -std=c++11 ripser.cpp -o ripser -Ofast -D NDEBUG -D USE_COEFFICIENTS +$ c++ -std=c++11 ripser.cpp -o ripser -Ofast -D NDEBUG -D USE_GOOGLE_HASHMAP ``` A Makefile is provided with some variants of the above options. Use `make all` to build them. The default `make` builds a binary with the default options. @@ -78,19 +78,22 @@ The input is given either in a file whose name is passed as an argument, or thro - `distance`: full distance matrix; similar to the above, but for all entries of the distance matrix. One line per row of the matrix; only the part below the diagonal is actually read. - `dipha`: DIPHA distance matrix as described on the [DIPHA] website. - `point-cloud`: point cloud; a comma (or whitespace, or other non-numerical character) separated list of coordinates of the points in some Euclidean space, one point per line. + - `sparse`: sparse distance matrix in Sparse Triplet format + - `binary`: lower distance matrix in binary file format; a sequence of the distance matrix entries below the diagonal in 64 bit double format (IEEE 754, little endian). - `--dim k`: compute persistent homology up to dimension *k*. - `--threshold t`: compute Rips complexes up to diameter *t*. - - `--modulus p`: compute homology with coefficients in the prime field Z/*p*Z (only available when built with the option `USE_COEFFICIENTS`). + - `--modulus p`: compute homology with coefficients in the prime field Z/*p*Z. + - `--ratio <r>`: only show persistence pairs with death/birth ratio > *r*. +### Experimental features -### Planned features +The following experimental features are currently available in separate branches: -The following features are currently planned for future versions: - - - computation of representative cycles for persistent homology (currenly only *co*cycles are computed) - - support for sparse distance matrices +- `representative-cocycles`: output of representative cocycles for persistent cohomology. +- `representative-cycles`: computation and output of representative cycles for persistent homology (in the standard version, only *co*cycles are computed). +- `simple`: a simplified version of Ripser, without support for sparse distance matrices and coefficients. This might be a good starting point for exploring the code. Prototype implementations are already avaliable; please contact the author if one of these features might be relevant for your research. |