Create conda environment documentation

Author: Daniel Incicau

README.md

@@ -1,5 +1,10 @@
 Spiking Neural Network for the Visual Cortex (V1) Layer 5
 ============================
+This is a spike neural network model of the V1, layer 5 includes Cortico-Cortical (CC), Cortico-Subcortical (CS), PV and SST neurons. 
+
+Individual simulation metrics for neuron groups are computed such as firing rates, inter-spike intervals, burst detection.
+
+Additionally, orientation and direction selectivity are aggregated for population of cells.
 
 ### Project content
 
@@ -18,3 +23,15 @@ Spiking Neural Network for the Visual Cortex (V1) Layer 5
     ├── plotting.py                                 # Helper methods for plotting
     ├── run_amplitude_hypertuing.py                 # Script for running multiple simulations for amplitude hypertuning for different neurons
     └── run_complete_simulation.py                  # Complete simulation run entrypoint
+
+### Requirements
+Use `conda env create -n network -f requirements.txt` to unpack the conda environment. Or download with `conda install <module>` the requirements manually. 
+
+After that, activate the environment with `conda activate network`
+
+### Hints
+- There is only one best parameter set which I aggregated in `parameters.py`. If you want to try different combinations of parameters, you can change them here.
+- To run main simulation `python3 run_complete_simulation.py`
+- The project includes a script for hypertuning different input amplitudes for neuron groups. Can be run by `python3 run_amplitude_hypertuning.py`
+- All simulation outputs are persisted in the `output` folder. I recommend deleting the content between successive runs to avoid confusion.
+- Parallelization of simulations is missing. This would be a much needed improvement for the future.

helpers.py

@@ -6,16 +6,6 @@
 from scipy.signal import argrelextrema
 
 
-# TODO see how to reference this from equations
-@check_units(x=volt, result=1)
-def sigmoid(x):
-    ### Sigmoid function params
-    E_d = -38 * mV  # position control of threshold
-    D_d = 6 * mV  # sharpness control of threshold
-
-    return 1/(1+exp(-(-x-E_d)/D_d))
-
-
 def bin(spiketime, dt):
     if len(spiketime) == 0:
         return []

requirements.txt

@@ -0,0 +1,105 @@
+# This file may be used to create an environment using:
+# $ conda create --name <env> --file <this file>
+# platform: osx-arm64
+appdirs=1.4.4=pyh9f0ad1d_0
+bottleneck=1.3.5=py310hf1a086a_1
+brian2=2.5.1=py310h629746b_2
+brotli=1.0.9=h1a8c8d9_8
+brotli-bin=1.0.9=h1a8c8d9_8
+brotlipy=0.7.0=py310h8e9501a_1005
+bzip2=1.0.8=h3422bc3_4
+ca-certificates=2022.12.7=h4653dfc_0
+cctools_osx-arm64=973.0.1=hef52d2f_11
+certifi=2022.12.7=pyhd8ed1ab_0
+cffi=1.15.1=py310h2399d43_3
+charset-normalizer=2.1.1=pyhd8ed1ab_0
+clang=14.0.6=hce30654_0
+clang-14=14.0.6=default_h81a5282_0
+clang_osx-arm64=14.0.6=h15773ab_4
+clangxx=14.0.6=default_hb7ecf47_0
+clangxx_osx-arm64=14.0.6=he29aa18_4
+compiler-rt=14.0.6=h30b49de_0
+compiler-rt_osx-arm64=14.0.6=h4fb70ea_0
+contourpy=1.0.6=py310h2887b22_0
+cryptography=39.0.0=py310hfc83b78_0
+cycler=0.11.0=pyhd8ed1ab_0
+cython=0.29.33=py310h0f1eb42_0
+fonttools=4.38.0=py310h8e9501a_1
+freetype=2.12.1=hd633e50_1
+gmp=6.2.1=h9f76cd9_0
+gmpy2=2.1.2=py310h2e6cad2_1
+gsl=2.7=h6e638da_0
+idna=3.4=pyhd8ed1ab_0
+jinja2=3.1.2=pyhd8ed1ab_1
+jpeg=9e=he4db4b2_2
+kiwisolver=1.4.4=py310h2887b22_1
+lcms2=2.14=h481adae_1
+ld64_osx-arm64=609=h7167370_11
+lerc=4.0.0=h9a09cb3_0
+libblas=3.9.0=16_osxarm64_openblas
+libbrotlicommon=1.0.9=h1a8c8d9_8
+libbrotlidec=1.0.9=h1a8c8d9_8
+libbrotlienc=1.0.9=h1a8c8d9_8
+libcblas=3.9.0=16_osxarm64_openblas
+libclang-cpp14=14.0.6=default_h81a5282_0
+libcxx=14.0.6=h2692d47_0
+libdeflate=1.14=h1a8c8d9_0
+libffi=3.4.2=h3422bc3_5
+libgfortran=5.0.0=11_3_0_hd922786_27
+libgfortran5=11.3.0=hdaf2cc0_27
+libjpeg-turbo=2.1.4=h1a8c8d9_0
+liblapack=3.9.0=16_osxarm64_openblas
+libllvm14=14.0.6=hf6e71e7_1
+libopenblas=0.3.21=openmp_hc731615_3
+libpng=1.6.39=h76d750c_0
+libsqlite=3.40.0=h76d750c_0
+libtiff=4.5.0=heb92581_0
+libwebp-base=1.2.4=h57fd34a_0
+libxcb=1.13=h9b22ae9_1004
+libzlib=1.2.13=h03a7124_4
+llvm-openmp=15.0.6=h7cfbb63_0
+llvm-tools=14.0.6=hf6e71e7_1
+markupsafe=2.1.1=py310h8e9501a_2
+matplotlib=3.6.2=py310hb6292c7_0
+matplotlib-base=3.6.2=py310h78c5c2f_0
+mpc=1.2.1=h309154c_0
+mpfr=4.1.0=h6d7a090_1
+mpmath=1.2.1=pyhd8ed1ab_0
+munkres=1.1.4=pyh9f0ad1d_0
+ncurses=6.3=h07bb92c_1
+numexpr=2.8.3=py310h2b830bf_1
+numpy=1.23.5=py310h5d7c261_0
+openjpeg=2.5.0=hbc2ba62_2
+openssl=3.0.7=h03a7124_1
+packaging=23.0=pyhd8ed1ab_0
+pandas=1.4.4=py310hc377ac9_0
+pillow=9.4.0=py310h5f2e7f5_0
+pip=22.3.1=pyhd8ed1ab_0
+pooch=1.6.0=pyhd8ed1ab_0
+pthread-stubs=0.4=h27ca646_1001
+pycparser=2.21=pyhd8ed1ab_0
+pyopenssl=23.0.0=pyhd8ed1ab_0
+pyparsing=3.0.9=pyhd8ed1ab_0
+pysocks=1.7.1=pyha2e5f31_6
+python=3.10.8=h3ba56d0_0_cpython
+python-dateutil=2.8.2=pyhd8ed1ab_0
+python_abi=3.10=3_cp310
+pytz=2022.7=pyhd8ed1ab_0
+readline=8.1.2=h46ed386_0
+requests=2.28.1=pyhd8ed1ab_1
+scipy=1.10.0=py310ha0d8a01_0
+setuptools=65.6.3=pyhd8ed1ab_0
+sigtool=0.1.3=h44b9a77_0
+six=1.16.0=pyh6c4a22f_0
+sympy=1.11.1=py310hbe9552e_2
+tapi=1100.0.11=he4954df_0
+tk=8.6.12=he1e0b03_0
+tornado=6.2=py310h8e9501a_1
+tzdata=2022g=h191b570_0
+unicodedata2=15.0.0=py310h8e9501a_0
+urllib3=1.26.14=pyhd8ed1ab_0
+wheel=0.38.4=pyhd8ed1ab_0
+xorg-libxau=1.0.9=h27ca646_0
+xorg-libxdmcp=1.1.3=h27ca646_0
+xz=5.2.6=h57fd34a_0
+zstd=1.5.2=h8128057_4