This repo contains the scripts to generate different network models for wakukurtosis runs.
## run_kurtosis_tests.sh
run_kurtosis_tests.sh will run kurtosis on a set of json files in a directory. It requires two arguments. First is a directory containing json files; other file types in the directory are ignored. Second is the github root/prefix of the kurtosis module you run the tests under.</br>
Running this script is somewhat complicated; so follow the following instructions to a dot. You **WILL** require the main.star provided here. The main.star reads a input json and instantiates Waku nodes accordingly. The runs are repeated for each of the input json files under the specified directory.
#### step 0)
symlink run_kurtosis_tests.sh to the root directory of your kurtosis module.</br>
#### step 1)
backup the your kurtosis module's own main.star. copy the main.star provided here to the root directory of your kurtosis module.</br>
!!! WARNING: symlinking the main.star will NOT work !!!</br>
#### step 3)
put all the json files you want to use in a directory. Call it *Foo*</br>
#### step 3)
copy the *Foo* directory to the root of your kurtosis module</br>
!!! WARNING: symlinking the directory will NOT work !!!</br>
#### step 4)
run this script in the root directory of the kurtosis module. provide the directory (*Foo*) and the github root/prefix of the kurtosis module as arguments to the script</br>
## gen_jsons.sh
gen_jsons.sh can generate given number of Waku networs and outputs them to a directory. Please make sure that the output directory exists; both relative and absolute paths work. The Wakunode parameters are generated at random; edit the MIN and MAX for finer control. The script requires bc & /dev/urandom.<br>
generate_network.py can generate networks with specified number of nodes and topics. the network types currently supported is "configuration_model" and more are on the way. Use with Python3. Comment out the `#draw(fname, H)` line to visualise the generated graph.
