Language improvements

README.md

@@ -10,20 +10,20 @@ of Life with rule switching mechanisms.
 # Reproducing data
 
 Scripts in this repo can be used to reproduce data illustrating the behaviour of
-the Game of Live cellular automata extended with the mechanisms for rule
+the Game of Live (GoL) cellular automata extended with the mechanisms for rule
 switching. Additionally, the model can be used in asynchronous and synchronous
 mode.
 
-Code compilation and runing is controlled by file `Makefile` in the main
-directory. This file should be modified to suit our NetLogo installation.  In
-the provided `Makefile` it is assumes that NetLogo is installed in
+Code compilation and running is controlled by file `Makefile` in the main
+directory. This file should be modified to suit our NetLogo installation. In the
+provided `Makefile` it is assumed that NetLogo is installed in
 
     ~/Local/NetLogo/3.0.0
 
 directory. It is also assumed that `java` and `javac` are in you `PATH`
 environment variable.
 
-`Makefile` also uses GNU pararell for running Java programmes. 
+`Makefile` also uses GNU parallel for running Java programmes. 
 
 ## Final configurations
 
@@ -32,15 +32,16 @@ compile this file run
 
     make
 
-in the main directory. This will also compile `CalculateMeanLiving.java` and `GenerateConfigurations.java`.
+in the main directory. This will also compile `CalculateMeanLiving.java` and
+`GenerateConfigurations.java`.
 
 Examples are generated by issuing
 
     make genex
 
 in the main directory. This will produce files `world*.csv` files, named according to the parameters defined in `CalculateMeanLiving.java` file.
 
-Ploting of the resulting data is handled by `plot_world_example.py` script. Running
+Plotting of the resulting data is handled by `plot_world_example.py` script. Running
 
     python plot_world_example.py word_data.csv
 
@@ -50,15 +51,16 @@ To plot all data from the generated examples run
 
     for f in world*.csv ; do python plot_world_example.py $f ; done
 
-**Note:** By default, world size is set to 2^6. Details are defined in `experiements.xml` file.
+**Note:** By default, the world size is set to 2^6. Details are defined in
+*`experiements.xml` file.
 
 **Note:** Plots are saved in `plots` subdirectory.
 
 ## Realizations
 
-Exlemplary realizations can be obtained by using `run.sh` script and
+Exemplary realizations can be obtained by using `run.sh` script and
 `experiments.xml` file. For each experiment defined in `experiments.xml` file,
-make a symblic link to `run.sh`
+make a symbolic link to `run.sh`
 
     ln -s run.sh experiment-name.sh
 
@@ -82,7 +84,7 @@ To plot data from the realizations run
 
 ## Average growth
 
-Data for the average number of living cells are calculate by
+Data for the average number of living cells are calculated by
 `CalculateMeanLiving.java` and can be obtained by running
 
     make calcmean
@@ -92,7 +94,7 @@ You need to compile `CalculateMeanLiving.java` first
 **Note:** BY default, 200 realizations are used fo averaging. This value can be
 modified in `CalculateMeanLiving.java` file by altering `steps` variable. 
 
-Ploting of the data is handled by `plot_living_average.py`, which accepts one
+Plotting of the data is handled by `plot_living_average.py`, which accepts one
 argument with name of the data file.
 
 **Note:** Data from this experiment are saved in
@@ -102,24 +104,24 @@ argument with name of the data file.
 
 ## Mutual entropy
 
-For the purposa of analysing the mutula entropy of the generated patters it is
-necessary to generate a number of final configurations. This data are generate
+For the purpose of analysing the mutual entropy of the generated patters, it is
+necessary to generate a number of final configurations. This data is generated
 using `genfc` target in the Makefile,
 
     make gencf
 
-You nee to compile `GenerateConfigurations.java` prior to running this command.
+You need to compile `GenerateConfigurations.java` before running this command.
 
-Resultsing `csv` files in `configurations` subdirectory. For each combination of
-parameters 1000 files representing final configuraitons are generated. The names
-of the resulting configurations can be saved in a shhell variable using
+Resulting `csv` files in `configurations` subdirectory. For each combination of
+parameters 1000 files representing final configurations are generated. The names
+of the resulting configurations can be saved in a shell variable using
 
     golTypes=$(for i in *_0001.csv ; do echo `echo $i | sed s/_0001.csv//g` ; done)
 
 in the `configurations` directory. 
 
-The calculation of the average mutula entropy is implemented in
-`analyze_mutent.py` script. Using GNU parallel the analysis rsults can be
+The calculation of the average mutual entropy is implemented in
+`analyze_mutent.py` script. Using GNU parallel, the analysis results can be
 obtained by running
 
     parallel ./analyze.py {} ::: $golTypes
@@ -132,4 +134,4 @@ obtain the file with all data run
     bash postprocess_dat.sh 
 
 script. This will produce `anayze_mutent.csv`, used by the plotting script
-`plot_mutual_entropy.py` located in the main directory. 
+`plot_mutual_entropy.py` located in the main directory.