diff --git a/README.md b/README.md new file mode 100644 index 0000000..a1d02e1 --- /dev/null +++ b/README.md @@ -0,0 +1,29 @@ +This is the readme for the model associated with the paper + +Esposito U, Giugliano M, van Rossum M, Vasilaki E (2014) "Measuring +symmetry, asymmetry and randomness in neural network connectivity" +*PLoS One* 9:e100805 + +The matlab code reproduces Figures 1, 2, 3A and 3C from the paper. To +run it you need to use Matlab with Symbolic Math Toolbox and +Statistics Toolbox. + +## Content and usage: + +1. Unzip Espositoetal2013_MatlabCode into an empty directory. The code + is organized in 8 .m files. +2. To obtain the graphs of Fig. 1 run Uniform_PDFs.m (for + Fig. 1A,B,C,D) and Uniform_PDFs_pruned.m (for Fig. 1E,F,G,H). + For example the figure generated for 1D looks like: + + ![screenshot](./screenshot.png) +3. To obtain the graphs of Fig. 2 run Gaussian_PDFs.m (for + Fig. 2A,B,C,D) and Gaussian_PDFs_pruned.m (for Fig. 2E,F,G,H). +4. To obtain the graphs of Fig. 3A,C run Uniform_Statistics.m (for + Fig. 3A) and Gaussian_Statistics.m (for Fig. 3C). +5. Uniform_Statistics.m calls sym_measure.m. +6. Gaussian_Statistics.m calls sym_measure.m and correl.m. + +--- + +2025-07-09: Converted README to Markdown. diff --git a/Readme.html b/Readme.html deleted file mode 100644 index b6db521..0000000 --- a/Readme.html +++ /dev/null @@ -1,25 +0,0 @@ -
-This is the readme for the model associated with the paper
-
-Esposito U, Giugliano M, van Rossum M, Vasilaki E (2014) "Measuring
-symmetry, asymmetry and randomness in neural network connectivity"
-PLoS One 9:e100805
-
-The matlab code reproduces Figures 1, 2, 3A and 3C from the paper.  To
-run it you need to use Matlab with Symbolic Math Toolbox and
-Statistics Toolbox.
-
-Content and usage:
-1. Unzip Espositoetal2013_MatlabCode into an empty directory. The code
-is organized in 8 .m files.
-2. To obtain the graphs of Fig. 1 run Uniform_PDFs.m (for
-Fig. 1A,B,C,D) and Uniform_PDFs_pruned.m (for Fig. 1E,F,G,H).
-For example the figure generated for 1D looks like:
-screenshot
-3. To obtain the graphs of Fig. 2 run Gaussian_PDFs.m (for
-Fig. 2A,B,C,D) and Gaussian_PDFs_pruned.m (for Fig. 2E,F,G,H).
-4. To obtain the graphs of Fig. 3A,C run Uniform_Statistics.m (for
-Fig. 3A) and Gaussian_Statistics.m (for Fig. 3C).
-5. Uniform_Statistics.m calls sym_measure.m.
-6. Gaussian_Statistics.m calls sym_measure.m and correl.m.
-