# Spatially structured perisomatic inhibition organized along polarized fast-spiking interneuron axons


### How to setup the python environment

It is recommended to use [Anaconda](https://www.continuum.io/downloads) to create a virtual environment with the
 necessary dependencies. With anaconda, it is a one button install. After cloning the repository and changing into the root folder, type
```
conda env create -f environment.yml
```

This creates an environment called interneuron_polarity, which can be activated via
```bash
conda activate interneuron_polarity
```

To run the scripts, you also need to make the repository folder available in the python path (requires conda--build)
```bash
conda develop .
```

### How to run the simulation

The entire process is split in three main scripts. The simulation is setup and run via
```bash
python scripts/spatial_network/perlin_map/run_simulation_perlin_map.py
```
Relevant parameters are the range of scale and seed values for the input map generation as explained in the script. 
A preliminary analysis of the simulated data is done by running 
```bash
python scripts/spatial_network/perlin_map/preliminary_analysis_perlin_map.py
```
The final analysis and figure generation is done by 
```bash
python scripts/spatial_network/perlin_map/final_analysis_and_plotting_perlin_map.py
```
Note, that running the simulation script will overwrite the saved data. 
The bulk of the runtime lies within the simulation and preliminary analysis which can be executed together via
```bash
python scripts/spatial_network/perlin_map/run_and_analyze_perlin.py
```
after which the figure script can be tweaked and executed without loss of data.

For the supplement figure, a pinwheel map is used as an alternative input map. The run, analyse and plot scripts are
 organized in the same manner but found in the folder `scripts/spatial_network/supplement_pinwheel_map`. 

### Additional Ressources

The simulation saves the generated data in a hdf5-file. Since the full parameter exploration used for the model section of the paper requires significant time to run, the generated data set can also be downloaded from the following location. When the pre-simulated dataset is used, only the figure script needs to be executed to get the results of the data analysis. Note that the save file will be overwritten when the simulation is started again.

- Full perlin data set
- Full pinwheel data set
- Pregenerated pinwheel maps