diff --git a/Dockerfile b/Dockerfile
new file mode 100644
index 0000000000000000000000000000000000000000..8da070136d6cd91e9343801e25bc73b464d0a0e4
--- /dev/null
+++ b/Dockerfile
@@ -0,0 +1,20 @@
+# Start with a base image that includes conda
+FROM continuumio/miniconda3
+
+# Set environment variables
+ENV CONDA_DEFAULT_ENV=fenicsx-env
+ENV PATH /opt/conda/envs/${CONDA_DEFAULT_ENV}/bin:$PATH
+ENV HOME /root
+
+# Create the environment and install packages
+RUN conda create --name ${CONDA_DEFAULT_ENV} python=3.12.3 -y && \
+ conda install -n ${CONDA_DEFAULT_ENV} -c conda-forge fenics-dolfinx=0.8.0 mpich=4.2.1 pyvista=0.43.10 matplotlib=3.8.4 numpy=1.26.4 scipy=1.14.0 gcc=12.4.0 sphinx=7.3.7 myst-parser=4.0.0 sphinx-copybutton=0.5.2 sphinx-rtd-theme=3.0.1 pytest==8.3.3 -y
+
+# Activate environment
+SHELL ["conda", "run", "-n", "fenicsx-env", "/bin/bash", "-c"]
+
+WORKDIR /root
+
+# Set the default environment on container start
+# ENTRYPOINT ["conda", "run", "-n", "fenicsx-env", "/bin/bash", "-c"]
+CMD ["bash"]
diff --git a/README.md b/README.md
index 6db1fc4627ba6ba7d924f202f7f94a108c22a384..0067dace29cb3ac2028e1c91a5ced5e4d531a620 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,6 @@
# Reproducibility Repository for Numerical Treatment of a Thermodynamically Consistent Electrolyte Model (B.Sc. Thesis - Jan Habscheid)
-[](https://git.rwth-aachen.de/Jan.Habscheid/bsc-electrolytemodels/pipelines)
+[](https://git.rwth-aachen.de/Jan.Habscheid/bsc-electrolytemodels/pipelines)
[](https://janhab.pages.rwth-aachen.de/bsc-electrolytemodels/)
[](https://doi.org/10.5281/zenodo.13645296)
[](https://git.rwth-aachen.de/jan.habscheid/bsc-electrolytemodels/-/tags)
@@ -9,9 +9,7 @@
## Thesis
This repository contains the code to reproduce the results presented in the bachelor thesis: Numerical Treatment of a Thermodynamically Consistent Electrolyte Model
-Find the thesis at:
-
-- Insert link to thesis (not published yet)
+Find the thesis at [https://doi.org/10.18154/RWTH-2024-09837](https://doi.org/10.18154/RWTH-2024-09837)
### Abstract
@@ -29,7 +27,7 @@ All the calculations were performed on a Linux machine. According to the documen
```
conda create --name fenicsx-env python=3.12.3 -y
conda activate fenicsx-env
-conda install -c conda-forge fenics-dolfinx=0.8.0 mpich=4.2.1 pyvista=0.43.10 matplotlib=3.8.4 numpy=1.26.4 scipy=1.14.0 -y
+conda install -c conda-forge fenics-dolfinx=0.8.0 mpich=4.2.1 pyvista=0.43.10 matplotlib=3.8.4 numpy=1.26.4 scipy=1.14.0 pytest==8.3.3 -y
```
### Alternative installation
@@ -40,9 +38,26 @@ Use the "environment.yml" file to install all necessary environments
conda env create -f environment.yml
```
+### macOS installation using Docker
+
+```
+docker compose build
+docker compose run solver
+```
+
+### Testing
+
+Use pytest with
+```
+python -m pytest
+```
+
+to verify that everything was installed correctly.
+
+
## Usage
-Find the visualizations from the thesis and some extra calculations in the "examples" folder.
+Find the visualizations from the thesis and some extra calculations in the "examples" folder.
In the subfolder "ReproducableCode" is the code, to execute the calculations with some first visualizations.
The subfolder "Data" stores the data for all the simulations in a *.npz file, which can be read with numpy `np.load(file.npz)`.
"Visualizations" creates the necessary figures from the thesis and stores them in *.svg format in "Figures".
@@ -66,4 +81,4 @@ In "src" there are the generic FEniCSx implementations, that were used to calcul
- Prof. Dr. Manuel Torrilhon
- ACoM - Applied and Computational Mathematics
- RWTH Aachen University
-- mt@acom.rwth-aachen.de
\ No newline at end of file
+- mt@acom.rwth-aachen.de
diff --git a/docker-compose.yml b/docker-compose.yml
new file mode 100644
index 0000000000000000000000000000000000000000..e8645b3b682fb26c27d4f1145a4a5fa3b5386ba1
--- /dev/null
+++ b/docker-compose.yml
@@ -0,0 +1,10 @@
+services:
+ solver:
+ build:
+ context: .
+ dockerfile: Dockerfile
+ volumes:
+ - .:/root/solver
+ stdin_open: true # Equivalent to -i for interactive mode
+ tty: true # Equivalent to -t for a terminal interface
+ command: ["/bin/bash"]
diff --git a/docs/source/index.rst b/docs/source/index.rst
index 625d16901e7500c63e220495cae67fd74ddea4b5..5d893ca7b702ec28be27183eb711949a60d1188b 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -13,9 +13,7 @@ Reproducibility Repository for Numerical Treatment of a Thermodynamically Consis
Thesis
======
| This repository contains the code to reproduce the results presented in the bachelor thesis: Numerical Treatment of a Thermodynamically Consistent Electrolyte Model
-| Find the thesis at:
-
-- Insert link to thesis (not published yet)
+| Find the thesis at: https://doi.org/10.18154/RWTH-2024-09837
Abstract
========
diff --git a/environment.yml b/environment.yml
index 4c54a3639c4b9d7a7ec0829c6ec66d6eb1ffced1..c5ec78808a6c5a0ade6b7d19e74f92688e4b3da8 100644
--- a/environment.yml
+++ b/environment.yml
@@ -1,320 +1,85 @@
-name: fenicsx
-channels:
- - conda-forge
- - defaults
-dependencies:
- - _libgcc_mutex=0.1=conda_forge
- - _openmp_mutex=4.5=2_gnu
- - aiohttp=3.9.5=py312h98912ed_0
- - aiosignal=1.3.1=pyhd8ed1ab_0
- - alsa-lib=1.2.12=h4ab18f5_0
- - aom=3.9.1=hac33072_0
- - asttokens=2.4.1=pyhd8ed1ab_0
- - attr=2.5.1=h166bdaf_1
- - attrs=23.2.0=pyh71513ae_0
- - binutils_impl_linux-64=2.40=ha1999f0_7
- - binutils_linux-64=2.40=hb3c18ed_9
- - blosc=1.21.5=hc2324a3_1
- - brotli=1.1.0=hd590300_1
- - brotli-bin=1.1.0=hd590300_1
- - brotli-python=1.1.0=py312h30efb56_1
- - bzip2=1.0.8=hd590300_5
- - c-ares=1.28.1=hd590300_0
- - c-blosc2=2.14.4=hb4ffafa_1
- - ca-certificates=2024.6.2=hbcca054_0
- - cairo=1.18.0=h3faef2a_0
- - certifi=2024.6.2=pyhd8ed1ab_0
- - cffi=1.16.0=py312hf06ca03_0
- - charset-normalizer=3.3.2=pyhd8ed1ab_0
- - comm=0.2.2=pyhd8ed1ab_0
- - contourpy=1.2.1=py312h8572e83_0
- - cycler=0.12.1=pyhd8ed1ab_0
- - dav1d=1.2.1=hd590300_0
- - dbus=1.13.6=h5008d03_3
- - debugpy=1.8.1=py312h30efb56_0
- - decorator=5.1.1=pyhd8ed1ab_0
- - double-conversion=3.3.0=h59595ed_0
- - eigen=3.4.0=h00ab1b0_0
- - exceptiongroup=1.2.0=pyhd8ed1ab_2
- - executing=2.0.1=pyhd8ed1ab_0
- - expat=2.6.2=h59595ed_0
- - fenics-basix=0.8.0=py312h2492b07_1
- - fenics-dolfinx=0.8.0=py312hb4760eb_103
- - fenics-ffcx=0.8.0=pyh4af843d_0
- - fenics-libbasix=0.8.0=h9187eef_1
- - fenics-libdolfinx=0.8.0=h714c792_103
- - fenics-ufcx=0.8.0=h22f594c_0
- - fenics-ufl=2024.1.0=pyhd8ed1ab_0
- - ffmpeg=6.1.1=gpl_he44c6f3_112
- - fftw=3.3.10=mpi_mpich_hbcf76dd_10
- - font-ttf-dejavu-sans-mono=2.37=hab24e00_0
- - font-ttf-inconsolata=3.000=h77eed37_0
- - font-ttf-source-code-pro=2.038=h77eed37_0
- - font-ttf-ubuntu=0.83=h77eed37_2
- - fontconfig=2.14.2=h14ed4e7_0
- - fonts-conda-ecosystem=1=0
- - fonts-conda-forge=1=0
- - fonttools=4.53.0=py312h9a8786e_0
- - freetype=2.12.1=h267a509_2
- - fribidi=1.0.10=h36c2ea0_0
- - frozenlist=1.4.1=py312h98912ed_0
- - gcc_impl_linux-64=12.3.0=h58ffeeb_11
- - gcc_linux-64=12.3.0=h9528a6a_9
- - gettext=0.22.5=h59595ed_2
- - gettext-tools=0.22.5=h59595ed_2
- - gl2ps=1.4.2=h0708190_0
- - glew=2.1.0=h9c3ff4c_2
- - glib=2.80.2=hf974151_0
- - glib-tools=2.80.2=hb6ce0ca_0
- - gmp=6.3.0=hac33072_2
- - gnutls=3.7.9=hb077bed_0
- - graphite2=1.3.13=h59595ed_1003
- - gst-plugins-base=1.24.4=h9ad1361_0
- - gstreamer=1.24.4=haf2f30d_0
- - gxx_impl_linux-64=12.3.0=h2a574ab_11
- - gxx_linux-64=12.3.0=ha28b414_9
- - harfbuzz=8.5.0=hfac3d4d_0
- - hdf4=4.2.15=h2a13503_7
- - hdf5=1.14.3=mpi_mpich_h0f54ddc_5
- - hypre=2.31.0=mpi_mpich_hd1da18f_1
- - icu=73.2=h59595ed_0
- - idna=3.7=pyhd8ed1ab_0
- - importlib-metadata=7.2.0=pyha770c72_0
- - importlib_metadata=7.2.0=hd8ed1ab_0
- - ipykernel=6.29.4=pyh3099207_0
- - ipython=8.25.0=pyh707e725_0
- - jedi=0.19.1=pyhd8ed1ab_0
- - jsoncpp=1.9.5=h4bd325d_1
- - jupyter_client=8.6.2=pyhd8ed1ab_0
- - jupyter_core=5.7.2=py312h7900ff3_0
- - kahip=3.16=h6a42626_3
- - kahip-python=3.16=py312had6fb94_3
- - kernel-headers_linux-64=2.6.32=he073ed8_17
- - keyutils=1.6.1=h166bdaf_0
- - kiwisolver=1.4.5=py312h8572e83_1
- - krb5=1.21.2=h659d440_0
- - lame=3.100=h166bdaf_1003
- - lcms2=2.16=hb7c19ff_0
- - ld_impl_linux-64=2.40=hf3520f5_7
- - lerc=4.0.0=h27087fc_0
- - libabseil=20240116.2=cxx17_h59595ed_0
- - libadios2=2.10.0=mpi_mpich_h3e60829_3
- - libaec=1.1.3=h59595ed_0
- - libasprintf=0.22.5=h661eb56_2
- - libasprintf-devel=0.22.5=h661eb56_2
- - libass=0.17.1=h8fe9dca_1
- - libblas=3.9.0=22_linux64_openblas
- - libboost=1.84.0=hba137d9_3
- - libboost-devel=1.84.0=h00ab1b0_3
- - libboost-headers=1.84.0=ha770c72_3
- - libbrotlicommon=1.1.0=hd590300_1
- - libbrotlidec=1.1.0=hd590300_1
- - libbrotlienc=1.1.0=hd590300_1
- - libcap=2.69=h0f662aa_0
- - libcblas=3.9.0=22_linux64_openblas
- - libclang-cpp18.1=18.1.7=default_h9bb3924_0
- - libclang13=18.1.7=default_h087397f_0
- - libcups=2.3.3=h4637d8d_4
- - libcurl=8.8.0=hca28451_0
- - libdeflate=1.20=hd590300_0
- - libdrm=2.4.121=h4ab18f5_0
- - libedit=3.1.20191231=he28a2e2_2
- - libev=4.33=hd590300_2
- - libexpat=2.6.2=h59595ed_0
- - libffi=3.4.2=h7f98852_5
- - libflac=1.4.3=h59595ed_0
- - libgcc-devel_linux-64=12.3.0=h6b66f73_111
- - libgcc-ng=13.2.0=h77fa898_11
- - libgcrypt=1.10.3=hd590300_0
- - libgettextpo=0.22.5=h59595ed_2
- - libgettextpo-devel=0.22.5=h59595ed_2
- - libgfortran-ng=13.2.0=h69a702a_11
- - libgfortran5=13.2.0=h3d2ce59_11
- - libglib=2.80.2=hf974151_0
- - libglu=9.0.0=hac7e632_1003
- - libgomp=13.2.0=h77fa898_11
- - libgpg-error=1.49=h4f305b6_0
- - libhwloc=2.10.0=default_h5622ce7_1001
- - libiconv=1.17=hd590300_2
- - libidn2=2.3.7=hd590300_0
- - libjpeg-turbo=3.0.0=hd590300_1
- - liblapack=3.9.0=22_linux64_openblas
- - libllvm18=18.1.7=hb77312f_0
- - libnetcdf=4.9.2=nompi_h135f659_114
- - libnghttp2=1.58.0=h47da74e_1
- - libnsl=2.0.1=hd590300_0
- - libogg=1.3.4=h7f98852_1
- - libopenblas=0.3.27=pthreads_h413a1c8_0
- - libopenvino=2024.1.0=h2da1b83_7
- - libopenvino-auto-batch-plugin=2024.1.0=hb045406_7
- - libopenvino-auto-plugin=2024.1.0=hb045406_7
- - libopenvino-hetero-plugin=2024.1.0=h5c03a75_7
- - libopenvino-intel-cpu-plugin=2024.1.0=h2da1b83_7
- - libopenvino-intel-gpu-plugin=2024.1.0=h2da1b83_7
- - libopenvino-intel-npu-plugin=2024.1.0=he02047a_7
- - libopenvino-ir-frontend=2024.1.0=h5c03a75_7
- - libopenvino-onnx-frontend=2024.1.0=h07e8aee_7
- - libopenvino-paddle-frontend=2024.1.0=h07e8aee_7
- - libopenvino-pytorch-frontend=2024.1.0=he02047a_7
- - libopenvino-tensorflow-frontend=2024.1.0=h39126c6_7
- - libopenvino-tensorflow-lite-frontend=2024.1.0=he02047a_7
- - libopus=1.3.1=h7f98852_1
- - libpciaccess=0.18=hd590300_0
- - libpng=1.6.43=h2797004_0
- - libpq=16.3=ha72fbe1_0
- - libprotobuf=4.25.3=h08a7969_0
- - libptscotch=7.0.4=h2376d02_5
- - libsanitizer=12.3.0=hb8811af_11
- - libscotch=7.0.4=h3055ed5_5
- - libsndfile=1.2.2=hc60ed4a_1
- - libsodium=1.0.18=h36c2ea0_1
- - libsqlite=3.46.0=hde9e2c9_0
- - libssh2=1.11.0=h0841786_0
- - libstdcxx-devel_linux-64=12.3.0=h6b66f73_111
- - libstdcxx-ng=13.2.0=hc0a3c3a_11
- - libsystemd0=255=h3516f8a_1
- - libtasn1=4.19.0=h166bdaf_0
- - libtheora=1.1.1=h7f98852_1005
- - libtiff=4.6.0=h1dd3fc0_3
- - libunistring=0.9.10=h7f98852_0
- - libuuid=2.38.1=h0b41bf4_0
- - libva=2.21.0=h4ab18f5_2
- - libvorbis=1.3.7=h9c3ff4c_0
- - libvpx=1.14.1=hac33072_0
- - libwebp-base=1.4.0=hd590300_0
- - libxcb=1.15=h0b41bf4_0
- - libxcrypt=4.4.36=hd590300_1
- - libxkbcommon=1.7.0=h662e7e4_0
- - libxml2=2.12.7=hc051c1a_1
- - libzip=1.10.1=h2629f0a_3
- - libzlib=1.2.13=h4ab18f5_6
- - loguru=0.7.2=py312h7900ff3_1
- - lz4-c=1.9.4=hcb278e6_0
- - matplotlib-base=3.8.4=py312h20ab3a6_2
- - matplotlib-inline=0.1.7=pyhd8ed1ab_0
- - metis=5.1.0=h59595ed_1007
- - mpfr=4.2.1=h9458935_1
- - mpg123=1.32.6=h59595ed_0
- - mpi=1.0=mpich
- - mpi4py=3.1.6=py312h60e9011_1
- - mpich=4.2.1=h63d650b_101
- - msgpack-python=1.0.8=py312h2492b07_0
- - multidict=6.0.5=py312h98912ed_0
- - mumps-include=5.7.2=ha770c72_0
- - mumps-mpi=5.7.2=h09c71e5_0
- - munkres=1.1.4=pyh9f0ad1d_0
- - mysql-common=8.3.0=hf1915f5_4
- - mysql-libs=8.3.0=hca2cd23_4
- - ncurses=6.5=h59595ed_0
- - nest-asyncio=1.6.0=pyhd8ed1ab_0
- - nettle=3.9.1=h7ab15ed_0
- - nlohmann_json=3.11.3=h59595ed_0
- - numpy=1.26.4=py312heda63a1_0
- - ocl-icd=2.3.2=hd590300_1
- - openh264=2.4.1=h59595ed_0
- - openjpeg=2.5.2=h488ebb8_0
- - openssl=3.3.1=h4ab18f5_0
- - p11-kit=0.24.1=hc5aa10d_0
- - packaging=24.1=pyhd8ed1ab_0
- - parmetis=4.0.3=h583469f_1006
- - parso=0.8.4=pyhd8ed1ab_0
- - pcre2=10.43=hcad00b1_0
- - petsc=3.21.2=real_h7906ff3_102
- - petsc4py=3.21.2=py312hf1b966b_1
- - pexpect=4.9.0=pyhd8ed1ab_0
- - pickleshare=0.7.5=py_1003
- - pillow=10.3.0=py312hdcec9eb_0
- - pip=24.0=pyhd8ed1ab_0
- - pixman=0.43.2=h59595ed_0
- - pkg-config=0.29.2=h36c2ea0_1008
- - platformdirs=4.2.2=pyhd8ed1ab_0
- - pooch=1.8.2=pyhd8ed1ab_0
- - proj=9.3.1=h1d62c97_0
- - prompt-toolkit=3.0.47=pyha770c72_0
- - psutil=5.9.8=py312h98912ed_0
- - pthread-stubs=0.4=h36c2ea0_1001
- - ptscotch=7.0.4=h23d43cc_5
- - ptyprocess=0.7.0=pyhd3deb0d_0
- - pugixml=1.14=h59595ed_0
- - pulseaudio-client=17.0=hb77b528_0
- - pure_eval=0.2.2=pyhd8ed1ab_0
- - pycparser=2.22=pyhd8ed1ab_0
- - pygments=2.18.0=pyhd8ed1ab_0
- - pyparsing=3.1.2=pyhd8ed1ab_0
- - pysocks=1.7.1=pyha2e5f31_6
- - python=3.12.3=hab00c5b_0_cpython
- - python-dateutil=2.9.0=pyhd8ed1ab_0
- - python_abi=3.12=4_cp312
- - pyvista=0.43.10=pyhd8ed1ab_0
- - pyzmq=26.0.3=py312h8fd38d8_0
- - qt6-main=6.7.1=h2471661_2
- - readline=8.2=h8228510_1
- - requests=2.32.3=pyhd8ed1ab_0
- - scalapack=2.2.0=h417d24c_2
- - scooby=0.10.0=pyhd8ed1ab_0
- - scotch=7.0.4=h23d43cc_5
- - setuptools=70.1.0=pyhd8ed1ab_0
- - six=1.16.0=pyh6c4a22f_0
- - slepc=3.21.1=real_h97ad6bc_302
- - slepc4py=3.21.1=py312h68801f8_102
- - snappy=1.2.0=hdb0a2a9_1
- - sqlite=3.46.0=h6d4b2fc_0
- - stack_data=0.6.2=pyhd8ed1ab_0
- - suitesparse=7.7.0=hf4753ba_1
- - superlu=5.2.2=h00795ac_0
- - superlu_dist=9.0.0=h3feb4ed_1
- - svt-av1=2.1.0=hac33072_0
- - sysroot_linux-64=2.12=he073ed8_17
- - tbb=2021.12.0=h297d8ca_1
- - tbb-devel=2021.12.0=h7c56ddd_1
- - tk=8.6.13=noxft_h4845f30_101
- - tornado=6.4.1=py312h9a8786e_0
- - traitlets=5.14.3=pyhd8ed1ab_0
- - typing_extensions=4.12.2=pyha770c72_0
- - urllib3=2.2.2=pyhd8ed1ab_0
- - utfcpp=4.0.5=ha770c72_0
- - vtk=9.3.0=qt_py312h1234567_200
- - vtk-base=9.3.0=qt_py312h1234567_200
- - vtk-io-ffmpeg=9.3.0=qt_py312h1234567_200
- - wayland=1.23.0=h5291e77_0
- - wcwidth=0.2.13=pyhd8ed1ab_0
- - wheel=0.43.0=pyhd8ed1ab_1
- - wslink=2.1.1=pyhd8ed1ab_0
- - x264=1!164.3095=h166bdaf_2
- - x265=3.5=h924138e_3
- - xcb-util=0.4.0=hd590300_1
- - xcb-util-cursor=0.1.4=hd590300_1
- - xcb-util-image=0.4.0=h8ee46fc_1
- - xcb-util-keysyms=0.4.0=h8ee46fc_1
- - xcb-util-renderutil=0.3.9=hd590300_1
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diff --git a/tests/test_ElectrolyticDiode.py b/tests/test_ElectrolyticDiode.py
new file mode 100644
index 0000000000000000000000000000000000000000..b6aedddf45dcf5bfd3ee0d01a285ee9c33421304
--- /dev/null
+++ b/tests/test_ElectrolyticDiode.py
@@ -0,0 +1,94 @@
+'''
+Tests the ElectrolyticDiode implementation in src.ElectrolyticDiode.py
+'''
+
+
+from src.ElectrolyticDiode import ElectrolyticDiode
+import numpy as np
+
+# Define parameter to use in the test
+phi_bias = 10
+g_phi = 350
+y_fixed = 0.01
+z_A = -1.0
+z_C = 1.0
+K = 'incompressible'
+Lambda2 = 8.553e-6
+a2 = 7.5412e-4
+number_cells = [20, 128]
+Lx = 0.02
+Ly = 0.1
+x0 = np.array([0, 0])
+x1 = np.array([Lx, Ly])
+refinement_style = 'uniform'
+solvation = 5
+PoissonBoltzmann = False
+rtol = 1e-3
+relax_param = 0.15 # 0.1
+max_iter = 15_000
+
+
+data_comparison = np.load('tests/TestData/ElectrolyticDiode.npz')
+
+def test_ForwardBias():
+ y_A_ForwardBias, y_C_ForwardBias, phi_ForwardBias, p_ForwardBias, x_ForwardBias = ElectrolyticDiode('ForwardBias', phi_bias, g_phi, z_A, z_C, y_fixed, y_fixed, K, Lambda2, a2, number_cells, solvation, PoissonBoltzmann, relax_param, Lx, Ly, rtol, max_iter, return_type='Vector')
+
+ # test grid generation with no refinement
+ assert np.allclose(data_comparison['x_ForwardBias'], x_ForwardBias,\
+ rtol=1e-15, atol=1e-15),\
+ 'ForwardBias grid not generated correctly'
+ # test solution vector
+ assert np.allclose(data_comparison['y_A_ForwardBias'], y_A_ForwardBias,\
+ rtol=1e-15, atol=1e-15),\
+ 'y_A_ForwardBias not calculated correctly'
+ assert np.allclose(data_comparison['y_C_ForwardBias'], y_C_ForwardBias,\
+ rtol=1e-15, atol=1e-15),\
+ 'y_C_ForwardBias not calculated correctly'
+ assert np.allclose(data_comparison['phi_ForwardBias'], phi_ForwardBias,\
+ rtol=1e-15, atol=1e-15),\
+ 'phi_ForwardBias not calculated correctly'
+ assert np.allclose(data_comparison['p_ForwardBias'], p_ForwardBias,\
+ rtol=1e-15, atol=1e-15),\
+ 'p_ForwardBias not calculated correctly'
+
+def test_NoBias():
+ y_A_NoBias, y_C_NoBias, phi_NoBias, p_NoBias, x_NoBias = ElectrolyticDiode('NoBias', phi_bias, g_phi, z_A, z_C, y_fixed, y_fixed, K, Lambda2, a2, number_cells, solvation, PoissonBoltzmann, relax_param, Lx, Ly, rtol, max_iter, return_type='Vector')
+
+ # test grid generation with no refinement
+ assert np.allclose(data_comparison['x_NoBias'], x_NoBias,\
+ rtol=1e-15, atol=1e-15),\
+ 'NoBias grid not generated correctly'
+ # test solution vector
+ assert np.allclose(data_comparison['y_A_NoBias'], y_A_NoBias,\
+ rtol=1e-15, atol=1e-15),\
+ 'y_A_NoBias not calculated correctly'
+ assert np.allclose(data_comparison['y_C_NoBias'], y_C_NoBias,\
+ rtol=1e-15, atol=1e-15),\
+ 'y_C_NoBias not calculated correctly'
+ assert np.allclose(data_comparison['phi_NoBias'], phi_NoBias,\
+ rtol=1e-15, atol=1e-15),\
+ 'phi_NoBias not calculated correctly'
+ assert np.allclose(data_comparison['p_NoBias'], p_NoBias,\
+ rtol=1e-15, atol=1e-15),\
+ 'p_NoBias not calculated correctly'
+
+def test_BackwardBias():
+ y_A_BackwardBias, y_C_BackwardBias, phi_BackwardBias, p_BackwardBias, x_BackwardBias = ElectrolyticDiode('BackwardBias', phi_bias, g_phi, z_A, z_C, y_fixed, y_fixed, K, Lambda2, a2, number_cells, solvation, PoissonBoltzmann, relax_param, Lx, Ly, rtol, max_iter, return_type='Vector')
+
+ # test grid generation with no refinement
+ assert np.allclose(data_comparison['x_BackwardBias'], x_BackwardBias,\
+ rtol=1e-15, atol=1e-15),\
+ 'BackwardBias grid not generated correctly'
+ # test solution vector
+ assert np.allclose(data_comparison['y_A_BackwardBias'], y_A_BackwardBias,\
+ rtol=1e-15, atol=1e-15),\
+ 'y_A_BackwardBias not calculated correctly'
+ assert np.allclose(data_comparison['y_C_BackwardBias'], y_C_BackwardBias,\
+ rtol=1e-15, atol=1e-15),\
+ 'y_C_BackwardBias not calculated correctly'
+ assert np.allclose(data_comparison['phi_BackwardBias'], phi_BackwardBias,\
+ rtol=1e-15, atol=1e-15),\
+ 'phi_BackwardBias not calculated correctly'
+ assert np.allclose(data_comparison['p_BackwardBias'], p_BackwardBias,\
+ rtol=1e-15, atol=1e-15),\
+ 'p_BackwardBias not calculated correctly'
\ No newline at end of file
diff --git a/tests/test_Eq02.py b/tests/test_Eq02.py
new file mode 100644
index 0000000000000000000000000000000000000000..6356f24d54da28be63be14f3f5af6ab7e70c69f2
--- /dev/null
+++ b/tests/test_Eq02.py
@@ -0,0 +1,94 @@
+'''
+Tests the Eq02 implementation in src.Eq02.py
+'''
+
+
+from src.Eq02 import solve_System_2eq
+import numpy as np
+
+# Define parameter to use in the test
+phi_left = 10.0
+phi_right = 0.0
+p_right = 0.0
+y_A_R = 0.01
+y_C_R = 0.01
+z_A = -1.0
+z_C = 1.0
+K = 'incompressible'
+Lambda2 = 8.553e-6
+a2 = 7.5412e-4
+solvation = 0
+number_cells = 128
+relax_param = .1
+rtol = 1e-4
+max_iter = 500
+
+data_comparison = np.load('tests/TestData/Eq02.npz')
+
+def test_standard():
+ y_A, y_C, phi, p, x = solve_System_2eq(phi_left, phi_right, p_right, z_A, z_C, y_A_R, y_C_R, K, Lambda2, a2, number_cells, solvation=solvation, relax_param=relax_param, x0=0, x1=1, refinement_style='uniform', return_type='Vector', max_iter=max_iter, rtol=rtol)
+
+ # test grid generation with no refinement
+ assert np.allclose(data_comparison['x'], x,\
+ rtol=1e-15, atol=1e-15),\
+ 'Uniform grid not generated correctly'
+ # test solution vector
+ assert np.allclose(data_comparison['y_A'], y_A,\
+ rtol=1e-15, atol=1e-15),\
+ 'y_A not calculated correctly'
+ assert np.allclose(data_comparison['y_C'], y_C,\
+ rtol=1e-15, atol=1e-15),\
+ 'y_C not calculated correctly'
+ assert np.allclose(data_comparison['phi'], phi,\
+ rtol=1e-15, atol=1e-15),\
+ 'phi not calculated correctly'
+ assert np.allclose(data_comparison['p'], p,\
+ rtol=1e-15, atol=1e-15),\
+ 'p not calculated correctly'
+
+
+def test_solvation():
+ solvation = 5
+ y_A_solvation, y_C_solvation, phi_solvation, p_solvation, x_solvation = solve_System_2eq(phi_left, phi_right, p_right, z_A, z_C, y_A_R, y_C_R, K, Lambda2, a2, number_cells, solvation=solvation, relax_param=relax_param, x0=0, x1=1, refinement_style='log', return_type='Vector', max_iter=max_iter, rtol=rtol)
+
+ # test grid generation with logarithmic refinement
+ assert np.allclose(data_comparison['x_solvation'], x_solvation,\
+ rtol=1e-15, atol=1e-15),\
+ 'log grid not generated correctly'
+ # test solution vector
+ assert np.allclose(data_comparison['y_A_solvation'], y_A_solvation,\
+ rtol=1e-15, atol=1e-15),\
+ 'y_A with solvation not calculated correctly'
+ assert np.allclose(data_comparison['y_C_solvation'], y_C_solvation,\
+ rtol=1e-15, atol=1e-15),\
+ 'y_C with solvation not calculated correctly'
+ assert np.allclose(data_comparison['phi_solvation'], phi_solvation,\
+ rtol=1e-15, atol=1e-15),\
+ 'phi with solvation not calculated correctly'
+ assert np.allclose(data_comparison['p_solvation'], p_solvation,\
+ rtol=1e-15, atol=1e-15),\
+ 'p with solvation not calculated correctly'
+
+def test_compressibility():
+ solvation = 0
+ K = 5_000
+ y_A_compressible, y_C_compressible, phi_compressible, p_compressible, x_compressible = solve_System_2eq(phi_left, phi_right, p_right, z_A, z_C, y_A_R, y_C_R, K, Lambda2, a2, number_cells, solvation=solvation, relax_param=relax_param, x0=0, x1=1, refinement_style='hard_log', return_type='Vector', max_iter=max_iter, rtol=rtol)
+
+ # test grid generation with hard-logarithmic refinement
+ assert np.allclose(data_comparison['x_compressible'], x_compressible,\
+ rtol=1e-15, atol=1e-15),\
+ 'hard-log grid not generated correctly'
+ # test solution vector
+ assert np.allclose(data_comparison['y_A_compressible'], y_A_compressible,\
+ rtol=1e-15, atol=1e-15),\
+ 'y_A with compressible not calculated correctly'
+ assert np.allclose(data_comparison['y_C_compressible'], y_C_compressible,\
+ rtol=1e-15, atol=1e-15),\
+ 'y_C with compressible not calculated correctly'
+ assert np.allclose(data_comparison['phi_compressible'], phi_compressible,\
+ rtol=1e-15, atol=1e-15),\
+ 'phi with compressible not calculated correctly'
+ assert np.allclose(data_comparison['p_compressible'], p_compressible,\
+ rtol=1e-15, atol=1e-15),\
+ 'p with compressible not calculated correctly'
+
\ No newline at end of file
diff --git a/tests/test_Eq04.py b/tests/test_Eq04.py
new file mode 100644
index 0000000000000000000000000000000000000000..0d2652e8c8313f206af14c0540b47ca5c469f1b4
--- /dev/null
+++ b/tests/test_Eq04.py
@@ -0,0 +1,93 @@
+'''
+Tests the Eq04 implementation in src.Eq04.py
+'''
+
+from src.Eq04 import solve_System_4eq
+import numpy as np
+
+# Define parameter to use in the test
+phi_left = 10.0
+phi_right = 0.0
+p_right = 0.0
+y_A_R = 0.01
+y_C_R = 0.01
+z_A = -1.0
+z_C = 1.0
+K = 'incompressible'
+Lambda2 = 8.553e-6
+a2 = 7.5412e-4
+solvation = 0
+number_cells = 128
+relax_param = .1
+rtol = 1e-4
+max_iter = 500
+
+data_comparison = np.load('tests/TestData/Eq04.npz')
+
+def test_standard():
+ y_A, y_C, phi, p, x = solve_System_4eq(phi_left, phi_right, p_right, z_A, z_C, y_A_R, y_C_R, K, Lambda2, a2, number_cells, solvation=solvation, relax_param=relax_param, x0=0, x1=1, refinement_style='uniform', return_type='Vector', max_iter=max_iter, rtol=rtol)
+
+ # test grid generation with no refinement
+ assert np.allclose(data_comparison['x'], x,\
+ rtol=1e-15, atol=1e-15),\
+ 'Uniform grid not generated correctly'
+ # test solution vector
+ assert np.allclose(data_comparison['y_A'], y_A,\
+ rtol=1e-15, atol=1e-15),\
+ 'y_A not calculated correctly'
+ assert np.allclose(data_comparison['y_C'], y_C,\
+ rtol=1e-15, atol=1e-15),\
+ 'y_C not calculated correctly'
+ assert np.allclose(data_comparison['phi'], phi,\
+ rtol=1e-15, atol=1e-15),\
+ 'phi not calculated correctly'
+ assert np.allclose(data_comparison['p'], p,\
+ rtol=1e-15, atol=1e-15),\
+ 'p not calculated correctly'
+
+
+def test_solvation():
+ solvation = 5
+ y_A_solvation, y_C_solvation, phi_solvation, p_solvation, x_solvation = solve_System_4eq(phi_left, phi_right, p_right, z_A, z_C, y_A_R, y_C_R, K, Lambda2, a2, number_cells, solvation=solvation, relax_param=relax_param, x0=0, x1=1, refinement_style='log', return_type='Vector', max_iter=max_iter, rtol=rtol)
+
+ # test grid generation with logarithmic refinement
+ assert np.allclose(data_comparison['x_solvation'], x_solvation,\
+ rtol=1e-15, atol=1e-15),\
+ 'log grid not generated correctly'
+ # test solution vector
+ assert np.allclose(data_comparison['y_A_solvation'], y_A_solvation,\
+ rtol=1e-15, atol=1e-15),\
+ 'y_A with solvation not calculated correctly'
+ assert np.allclose(data_comparison['y_C_solvation'], y_C_solvation,\
+ rtol=1e-15, atol=1e-15),\
+ 'y_C with solvation not calculated correctly'
+ assert np.allclose(data_comparison['phi_solvation'], phi_solvation,\
+ rtol=1e-15, atol=1e-15),\
+ 'phi with solvation not calculated correctly'
+ assert np.allclose(data_comparison['p_solvation'], p_solvation,\
+ rtol=1e-15, atol=1e-15),\
+ 'p with solvation not calculated correctly'
+
+def test_compressibility():
+ solvation = 0
+ K = 5_000
+ y_A_compressible, y_C_compressible, phi_compressible, p_compressible, x_compressible = solve_System_4eq(phi_left, phi_right, p_right, z_A, z_C, y_A_R, y_C_R, K, Lambda2, a2, number_cells, solvation=solvation, relax_param=relax_param, x0=0, x1=1, refinement_style='hard_log', return_type='Vector', max_iter=max_iter, rtol=rtol)
+
+ # test grid generation with hard-logarithmic refinement
+ assert np.allclose(data_comparison['x_compressible'], x_compressible,\
+ rtol=1e-15, atol=1e-15),\
+ 'hard-log grid not generated correctly'
+ # test solution vector
+ assert np.allclose(data_comparison['y_A_compressible'], y_A_compressible,\
+ rtol=1e-15, atol=1e-15),\
+ 'y_A with compressible not calculated correctly'
+ assert np.allclose(data_comparison['y_C_compressible'], y_C_compressible,\
+ rtol=1e-15, atol=1e-15),\
+ 'y_C with compressible not calculated correctly'
+ assert np.allclose(data_comparison['phi_compressible'], phi_compressible,\
+ rtol=1e-15, atol=1e-15),\
+ 'phi with compressible not calculated correctly'
+ assert np.allclose(data_comparison['p_compressible'], p_compressible,\
+ rtol=1e-15, atol=1e-15),\
+ 'p with compressible not calculated correctly'
+
\ No newline at end of file
diff --git a/tests/test_EqN.py b/tests/test_EqN.py
new file mode 100644
index 0000000000000000000000000000000000000000..bc68dfb8aa2a79026540993821494d150ae21dfe
--- /dev/null
+++ b/tests/test_EqN.py
@@ -0,0 +1,66 @@
+'''
+Tests the EqN implementation in src.EqN.py
+'''
+
+
+from src.EqN import solve_System_Neq
+import numpy as np
+
+# Define parameter to use in the test
+phi_left = 10.0
+phi_right = 0.0
+p_right = 0.0
+y_R = [3/6, 1/6, 1/6]
+z_alpha = [-1.0, 1.0, 2.0]
+K = 'incompressible'
+Lambda2 = 8.553e-6
+a2 = 7.5412e-4
+solvation = 0
+number_cells = 128
+relax_param = .1
+rtol = 1e-4
+max_iter = 500
+
+data_comparison = np.load('tests/TestData/EqN.npz')
+
+def test_1():
+ y_alpha, phi, p, x = solve_System_Neq(phi_left, phi_right, p_right, z_alpha, y_R, K, Lambda2, a2, number_cells, solvation=solvation, relax_param=relax_param, x0=0, x1=1, refinement_style='uniform', return_type='Vector', max_iter=max_iter, rtol=rtol)
+
+ # test grid generation with no refinement
+ assert np.allclose(data_comparison['x'], x,\
+ rtol=1e-15, atol=1e-15),\
+ 'Uniform grid not generated correctly'
+ # test solution vector
+ assert np.allclose(data_comparison['y_alpha'], y_alpha,\
+ rtol=1e-15, atol=1e-15),\
+ 'y_alpha not calculated correctly'
+ assert np.allclose(data_comparison['phi'], phi,\
+ rtol=1e-15, atol=1e-15),\
+ 'phi not calculated correctly'
+ assert np.allclose(data_comparison['p'], p,\
+ rtol=1e-15, atol=1e-15),\
+ 'p not calculated correctly'
+
+def test_2():
+ y_R = [1/23, 1/23, 1/23, 1/23, 10/23]
+ z_alpha = [-4.0, -3.0, -2.0, -1.0, 1.0]
+ relax_param = 0.01
+ max_iter = 10_000
+
+ y_alpha_2, phi_2, p_2, x_2 = solve_System_Neq(phi_left, phi_right, p_right, z_alpha, y_R, K, Lambda2, a2, number_cells, solvation=solvation, relax_param=relax_param, x0=0, x1=1, refinement_style='log', return_type='Vector', max_iter=max_iter, rtol=rtol)
+
+ # test grid generation with no refinement
+ assert np.allclose(data_comparison['x_2'], x_2,\
+ rtol=1e-15, atol=1e-15),\
+ 'Log grid not generated correctly'
+ # test solution vector
+ assert np.allclose(data_comparison['y_alpha_2'], y_alpha_2,\
+ rtol=1e-15, atol=1e-15),\
+ 'y_alpha_2 not calculated correctly'
+ assert np.allclose(data_comparison['phi_2'], phi_2,\
+ rtol=1e-15, atol=1e-15),\
+ 'phi_2 not calculated correctly'
+ assert np.allclose(data_comparison['p_2'], p_2,\
+ rtol=1e-15, atol=1e-15),\
+ 'p_2 not calculated correctly'
+
\ No newline at end of file
diff --git a/tests/test_Helper_DoubleLayerCapacity.py b/tests/test_Helper_DoubleLayerCapacity.py
new file mode 100644
index 0000000000000000000000000000000000000000..0f16e3ee275608c36cd1a18266d9538d15d8055c
--- /dev/null
+++ b/tests/test_Helper_DoubleLayerCapacity.py
@@ -0,0 +1,195 @@
+'''
+Tests the Helpfer functions implemented in src.Helper_DoubleLayerCapacity.py
+'''
+
+
+from src.Helper_DoubleLayerCapacity import Phi_pot_center, dx, C_dl, n, Q_num_, Q_num_dim, Q_DL_dimless_ana, Q_DL_dim_ana, C_DL_dimless_ana, C_DL_dim_ana
+from src.Eq04 import solve_System_4eq
+from src.Eq02 import solve_System_2eq
+import numpy as np
+
+# Define Parameter
+e0 = 1.602e-19 # [As]
+k = 1.381e-23 # [J/K]
+T = 293.75 # [K]
+epsilon0 = 8.85e-12 #[F/m]
+F = 9.65e+4 # [As/mol]
+NA = 6.022e+23 # [1/mol] - Avogadro constant
+nR_mol = 55
+nR_m = nR_mol * NA * 1/(1e-3)# [1/m^3]
+pR = 1.01325 * 1e+5 # [Pa]
+LR = 20e-9
+chi = 80 # [-]
+
+# Parameter and bcs for the electrolyte
+Lambda2 = (k*T*epsilon0*(1+chi))/(e0**2 * nR_m * (LR)**2)
+a2 = (pR)/(nR_m * k * T)
+K_incompresible = 'incompressible'
+K_compressible = 20_000
+kappa = 0
+Molarity = 0.01
+y_R = Molarity / nR_mol
+z_A, z_C = -1.0, 1.0
+phi_right = 0.0
+p_right = 0
+
+# Solver settings
+number_cells = 128
+relax_param = 0.03
+p_right = 0
+rtol = 1e-4 # ! Change back to 1e-8
+
+
+# phi^L domain
+Vol_start = 0.05 # ! Change back to 0
+Volt_end = 0.75
+n_Volts = 10#0
+
+phi_left_dim = np.linspace(Vol_start, Volt_end, n_Volts)
+phi_left = phi_left_dim * e0/(k*T)
+
+data_comparison = np.load('tests/TestData/DLKap.npz')
+
+
+
+# Incompressible tests
+def test_incompressible():
+ # Calculate the numerical solution
+ y_A_num, y_C_num, y_S_num, phi_num, p_num, x_num = [], [], [], [], [], []
+ for i, phi_bcs in enumerate(phi_left):
+ y_A_, y_C_, phi_, p_, x_ = solve_System_4eq(phi_bcs, phi_right, p_right, z_A, z_C, y_R, y_R, K_incompresible, Lambda2, a2, number_cells, solvation=kappa, refinement_style='hard_log', rtol=rtol, max_iter=2500, return_type='Vector', relax_param=relax_param)
+ y_S_ = 1 - y_A_ - y_C_
+ y_A_num.append(y_A_)
+ y_C_num.append(y_C_)
+ y_S_num.append(y_S_)
+ phi_num.append(phi_)
+ p_num.append(p_)
+ x_num.append(x_)
+
+ # Calculate the numerical charge and capacity with finite differences and numerical integration
+ Q_num = []
+ Q_num_dim_ = []
+ for j in range(len(phi_left)):
+ Q_num.append(Q_num_(y_A_num[j], y_C_num[j], n(p_num[j], K_incompresible), x_num[j]))
+ Q_num_dim_.append(Q_num_dim(y_A_num[j], y_C_num[j], n(p_num[j], K_incompresible), x_num[j], z_A, z_C, nR_m, e0, LR))
+ Q_num = np.array(Q_num)
+ Q_num_dim_ = np.array(Q_num_dim_)
+
+ dx_ = phi_left[1] - phi_left[0] # [1/V], Assumption: phi^L is uniformly distributed
+ C_dl_num = C_dl(Q_num, phi_left)
+
+ dx_dim = phi_left_dim[1] - phi_left_dim[0]
+ C_dl_num_dim_ = C_dl(Q_num_dim_, phi_left_dim)
+
+
+ # Calculate the analytical charge and capacity
+ Q_ana = Q_DL_dimless_ana(y_R, y_R, 1-2*y_R, z_A, z_C, phi_left, phi_right, p_right, K_incompresible, Lambda2, a2, kappa)
+ Q_ana_dim_ = Q_DL_dim_ana(y_R, y_R, 1-2*y_R, z_A, z_C, phi_left, phi_right, p_right, K_incompresible, Lambda2, a2, nR_m, e0, LR, kappa)
+ C_dl_ana = C_DL_dimless_ana(y_R, y_R, 1-2*y_R, z_A, z_C, Phi_pot_center(phi_left), phi_right, p_right, K_incompresible, Lambda2, a2, kappa)
+ C_dl_ana_dim = C_DL_dim_ana(y_R, y_R, 1-2*y_R, z_A, z_C, Phi_pot_center(phi_left), phi_right, p_right, K_incompresible, Lambda2, a2, nR_m, e0, LR, k, T, kappa)
+
+ # Test the numerical charge and capacity
+ assert np.allclose(data_comparison['Q_num'], Q_num,\
+ rtol=1e-15, atol=1e-15),\
+ 'Incompressible: Numerical charge not calculated correctly for dimensions'
+ assert np.allclose(data_comparison['Q_num_dim_'], Q_num_dim_,\
+ rtol=1e-15, atol=1e-15),\
+ 'Incompressible: Numerical charge not calculated correctly for dimensionless'
+ assert np.allclose(data_comparison['C_dl_num'], C_dl_num,\
+ rtol=1e-15, atol=1e-15),\
+ 'Incompressible: Numerical capacity not calculated correctly for dimensions'
+ assert np.allclose(data_comparison['C_dl_num_dim_'], C_dl_num_dim_,\
+ rtol=1e-15, atol=1e-15),\
+ 'Incompressible: Numerical capacity not calculated correctly for dimensionless'
+
+ # Test the analytical charge and capacity
+ assert np.allclose(data_comparison['Q_ana'], Q_ana,\
+ rtol=1e-15, atol=1e-15),\
+ 'Incompressible: Analytical charge not calculated correctly for dimensions'
+ assert np.allclose(data_comparison['Q_ana_dim_'], Q_ana_dim_,\
+ rtol=1e-15, atol=1e-15),\
+ 'Incompressible: Analytical charge not calculated correctly for dimensionless'
+ assert np.allclose(data_comparison['C_dl_ana'], C_dl_ana,\
+ rtol=1e-15, atol=1e-15),\
+ 'Incompressible: Analytical capacity not calculated correctly for dimensions'
+ assert np.allclose(data_comparison['C_dl_ana_dim'], C_dl_ana_dim,\
+ rtol=1e-15, atol=1e-15),\
+ 'Incompressible: Analytical capacity not calculated correctly for dimensionless'
+
+# Compressible tests
+def test_compressible():
+ # Calculate the numerical solution
+ y_A_num_compressible, y_C_num_compressible, y_S_num_compressible, phi_num_compressible, p_num_compressible, x_num_compressible = [], [], [], [], [], []
+ for i, phi_bcs in enumerate(phi_left):
+ y_A_, y_C_, phi_, p_, x_ = solve_System_4eq(phi_bcs, phi_right, p_right, z_A, z_C, y_R, y_R, K_compressible, Lambda2, a2, number_cells, solvation=kappa, refinement_style='hard_log', rtol=1e-4, max_iter=2500, return_type='Vector', relax_param=relax_param)
+ y_S_ = 1 - y_A_ - y_C_
+ y_A_num_compressible.append(y_A_)
+ y_C_num_compressible.append(y_C_)
+ y_S_num_compressible.append(y_S_)
+ phi_num_compressible.append(phi_)
+ p_num_compressible.append(p_)
+ x_num_compressible.append(x_)
+
+ # Calculate the numerical charge and capacity with finite differences and numerical integration
+ Q_num_compressible = []
+ Q_num_dim_compressible = []
+ for j in range(len(phi_left)):
+ Q_num_compressible.append(Q_num_(y_A_num_compressible[j], y_C_num_compressible[j], n(p_num_compressible[j], K_compressible), x_num_compressible[j]))
+ Q_num_dim_compressible.append(Q_num_dim(y_A_num_compressible[j], y_C_num_compressible[j], n(p_num_compressible[j], K_compressible), x_num_compressible[j], z_A, z_C, nR_m, e0, LR))
+ Q_num_compressible = np.array(Q_num_compressible)
+ Q_num_dim_compressible = np.array(Q_num_dim_compressible)
+
+ dx__compressible = phi_left[1] - phi_left[0] # [1/V], Assumption: phi^L is uniformly distributed
+ C_dl_num_compressible = C_dl(Q_num_compressible, phi_left)
+
+ dx_dim_compressible = phi_left_dim[1] - phi_left_dim[0]
+ C_dl_num_dim_compressible = C_dl(Q_num_dim_compressible, phi_left_dim)
+
+ # Calculate the analytical charge and capacity
+ Q_ana_compressible = Q_DL_dimless_ana(y_R, y_R, 1-2*y_R, z_A, z_C, phi_left, phi_right, p_right, K_compressible, Lambda2, a2, kappa)
+ Q_ana_dim__compressible = Q_DL_dim_ana(y_R, y_R, 1-2*y_R, z_A, z_C, phi_left, phi_right, p_right, K_compressible, Lambda2, a2, nR_m, e0, LR, kappa)
+ C_dl_ana_compressible = C_DL_dimless_ana(y_R, y_R, 1-2*y_R, z_A, z_C, Phi_pot_center(phi_left), phi_right, p_right, K_compressible, Lambda2, a2, kappa)
+ C_dl_ana_dim_compressible = C_DL_dim_ana(y_R, y_R, 1-2*y_R, z_A, z_C, Phi_pot_center(phi_left), phi_right, p_right, K_compressible, Lambda2, a2, nR_m, e0, LR, k, T, kappa)
+
+ # Test the numerical charge and capacity
+ assert np.allclose(data_comparison['Q_num_compressible'], Q_num_compressible,\
+ rtol=1e-15, atol=1e-15),\
+ 'Compressible: Numerical charge not calculated correctly for dimensions'
+ assert np.allclose(data_comparison['Q_num_dim_compressible'], Q_num_dim_compressible,\
+ rtol=1e-15, atol=1e-15),\
+ 'Compressible: Numerical charge not calculated correctly for dimensionless'
+ assert np.allclose(data_comparison['C_dl_num_compressible'], C_dl_num_compressible,\
+ rtol=1e-15, atol=1e-15),\
+ 'Compressible: Numerical capacity not calculated correctly for dimensions'
+ assert np.allclose(data_comparison['C_dl_num_dim_compressible'], C_dl_num_dim_compressible,\
+ rtol=1e-15, atol=1e-15),\
+ 'Compressible: Numerical capacity not calculated correctly for dimensionless'
+
+ # Test the analytical charge and capacity
+ assert np.allclose(data_comparison['Q_ana_compressible'], Q_ana_compressible,\
+ rtol=1e-15, atol=1e-15),\
+ 'Compressible: Analytical charge not calculated correctly for dimensions'
+ assert np.allclose(data_comparison['Q_ana_dim__compressible'], Q_ana_dim__compressible,\
+ rtol=1e-15, atol=1e-15),\
+ 'Compressible: Analytical charge not calculated correctly for dimensionless'
+ assert np.allclose(data_comparison['C_dl_ana_compressible'], C_dl_ana_compressible,\
+ rtol=1e-15, atol=1e-15),\
+ 'Compressible: Analytical capacity not calculated correctly for dimensions'
+ assert np.allclose(data_comparison['C_dl_ana_dim_compressible'], C_dl_ana_dim_compressible,\
+ rtol=1e-15, atol=1e-15),\
+ 'Compressible: Analytical capacity not calculated correctly for dimensionless'
+
+# Test the functions
+def test_Phi_pot_center():
+ assert np.allclose(Phi_pot_center(phi_left), data_comparison['Phi_pot_center'],\
+ rtol=1e-15, atol=1e-15),\
+ 'Phi_pot_center not calculated correctly'
+
+def test_dx():
+ assert np.allclose(dx(phi_left), data_comparison['dx'],\
+ rtol=1e-15, atol=1e-15),\
+ 'dx not calculated correctly'
+def test_n():
+ assert np.allclose(n(data_comparison['p_num_compressible'][0], K_compressible), data_comparison['n'], rtol=1e-15, atol=1e-15),\
+ 'n not calculated correctly'
+
\ No newline at end of file