diff --git a/.github/workflows/docstr-cov.yml b/.github/workflows/docstr-cov.yml
index 8a741e5267b..645d285bffd 100644
--- a/.github/workflows/docstr-cov.yml
+++ b/.github/workflows/docstr-cov.yml
@@ -31,12 +31,12 @@ jobs:
           fetch-depth: 0
 
       - name: Setup Python
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v4
         with:
           python-version: 3.x
 
       - name: Install interrogate
-        run: pip install interrogate==1.5.0 parse==1.19.0
+        run: pip install interrogate==1.5.0 parse==1.19.0 setuptools
 
       - name: Get SHAs
         run: |
diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml
index 7414b517f28..699837c9b4f 100644
--- a/.github/workflows/tests.yml
+++ b/.github/workflows/tests.yml
@@ -15,8 +15,8 @@ on:
 
 env:
   CACHE_NUMBER: 0  # increase to reset cache manually
-  PYTEST_FLAGS: --tardis-refdata=${{ github.workspace }}/tardis-refdata
-                --cov=tardis --cov-report=xml --cov-report=html
+  PYTEST_FLAGS: --tardis-refdata=${{ github.workspace }}/tardis-refdata --tardis-snapshot-data=${{ github.workspace }}/tardis-regressions
+                --cov=tardis --cov-report=xml --cov-report=html 
   CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
 
 concurrency:
@@ -86,6 +86,12 @@ jobs:
         with:
           path: tardis-refdata/.git/lfs
           key: ${{ runner.os }}-lfs-${{ hashFiles('tardis-refdata/.lfs-assets-id') }}-v1
+      
+      - name: Clone tardis-sn/tardis-regressions
+        uses: actions/checkout@v4
+        with:
+          repository: tardis-sn/tardis-regressions
+          path: tardis-regressions
 
       - name: Setup environment
         uses: conda-incubator/setup-miniconda@v2
diff --git a/.zenodo.json b/.zenodo.json
index 38bbf9ae996..6385dd3064f 100644
--- a/.zenodo.json
+++ b/.zenodo.json
@@ -116,10 +116,10 @@
       "name": "Barbosa, Talytha"
     },
     {
-      "name": "Sondhi, Dhruv"
+      "name": "O'Brien, Jack"
     },
     {
-      "name": "O'Brien, Jack"
+      "name": "Sondhi, Dhruv"
     },
     {
       "name": "Yu, Jenny"
@@ -151,19 +151,22 @@
       "name": "Singh, Shreyas"
     },
     {
-      "name": "Eweis, Youssef"
+      "name": "Reinecke, Martin"
     },
     {
-      "name": "Reinecke, Martin"
+      "name": "Eweis, Youssef"
     },
     {
       "name": "Bylund, Tomas"
     },
+    {
+      "name": "Black, William"
+    },
     {
       "name": "Bentil, Laud"
     },
     {
-      "name": "Black, William"
+      "name": "Holas, Alexander"
     },
     {
       "name": "Eguren, Jordi",
@@ -178,9 +181,6 @@
     {
       "name": "Bartnik, Matthew"
     },
-    {
-      "name": "Holas, Alexander"
-    },
     {
       "name": "Varma Buddaraju, Rohith"
     },
diff --git a/conda-linux-64.lock b/conda-linux-64.lock
index 1aaa04b654c..fd93c9a7bf8 100644
--- a/conda-linux-64.lock
+++ b/conda-linux-64.lock
@@ -1,6 +1,6 @@
 # Generated by conda-lock.
 # platform: linux-64
-# input_hash: 31d323d670a8deec16e2186403aa54ab8464102ac712829e12e62d80bc50f272
+# input_hash: c282095367763377f64134aabe34418215a97ab21d09982800cc95beb98ebaa9
 @EXPLICIT
 https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2#d7c89558ba9fa0495403155b64376d81
 https://conda.anaconda.org/conda-forge/linux-64/ca-certificates-2023.7.22-hbcca054_0.conda#a73ecd2988327ad4c8f2c331482917f2
@@ -10,15 +10,15 @@ https://conda.anaconda.org/conda-forge/noarch/font-ttf-source-code-pro-2.038-h77
 https://conda.anaconda.org/conda-forge/noarch/font-ttf-ubuntu-0.83-hab24e00_0.tar.bz2#19410c3df09dfb12d1206132a1d357c5
 https://conda.anaconda.org/conda-forge/linux-64/git-lfs-3.4.0-ha770c72_0.conda#8b8aef0a35f5b98937a65b67b7d3b536
 https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.40-h41732ed_0.conda#7aca3059a1729aa76c597603f10b0dd3
-https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-ng-13.2.0-h7e041cc_1.conda#acfb4817400db5804030a3a7ef7909a1
+https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-ng-13.2.0-h7e041cc_2.conda#9172c297304f2a20134fc56c97fbe229
 https://conda.anaconda.org/conda-forge/noarch/nomkl-1.0-h5ca1d4c_0.tar.bz2#9a66894dfd07c4510beb6b3f9672ccc0
-https://conda.anaconda.org/conda-forge/linux-64/python_abi-3.11-3_cp311.conda#c2e2630ddb68cf52eec74dc7dfab20b5
+https://conda.anaconda.org/conda-forge/linux-64/python_abi-3.11-4_cp311.conda#d786502c97404c94d7d58d258a445a65
 https://conda.anaconda.org/conda-forge/noarch/tzdata-2023c-h71feb2d_0.conda#939e3e74d8be4dac89ce83b20de2492a
 https://conda.anaconda.org/conda-forge/noarch/fonts-conda-forge-1-0.tar.bz2#f766549260d6815b0c52253f1fb1bb29
-https://conda.anaconda.org/conda-forge/linux-64/libgomp-13.2.0-h807b86a_1.conda#8bb001683321dcbde117a7337b5aace7
+https://conda.anaconda.org/conda-forge/linux-64/libgomp-13.2.0-h807b86a_2.conda#e2042154faafe61969556f28bade94b9
 https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-2_gnu.tar.bz2#73aaf86a425cc6e73fcf236a5a46396d
 https://conda.anaconda.org/conda-forge/noarch/fonts-conda-ecosystem-1-0.tar.bz2#fee5683a3f04bd15cbd8318b096a27ab
-https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-13.2.0-h807b86a_1.conda#ff8999574b465089ba0aa25a5e865bd0
+https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-13.2.0-h807b86a_2.conda#c28003b0be0494f9a7664389146716ff
 https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-h7f98852_4.tar.bz2#a1fd65c7ccbf10880423d82bca54eb54
 https://conda.anaconda.org/conda-forge/linux-64/c-ares-1.19.1-hd590300_0.conda#e8c18d865be43e2fb3f7a145b6adf1f5
 https://conda.anaconda.org/conda-forge/linux-64/fribidi-1.0.10-h36c2ea0_0.tar.bz2#ac7bc6a654f8f41b352b38f4051135f8
@@ -36,10 +36,10 @@ https://conda.anaconda.org/conda-forge/linux-64/libdeflate-1.19-hd590300_0.conda
 https://conda.anaconda.org/conda-forge/linux-64/libev-4.33-h516909a_1.tar.bz2#6f8720dff19e17ce5d48cfe7f3d2f0a3
 https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.5.0-hcb278e6_1.conda#6305a3dd2752c76335295da4e581f2fd
 https://conda.anaconda.org/conda-forge/linux-64/libffi-3.4.2-h7f98852_5.tar.bz2#d645c6d2ac96843a2bfaccd2d62b3ac3
-https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-13.2.0-ha4646dd_1.conda#a0d27fd5c6f05aa45e9602b1db49581c
+https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-13.2.0-ha4646dd_2.conda#78fdab09d9138851dde2b5fe2a11019e
 https://conda.anaconda.org/conda-forge/linux-64/libiconv-1.17-h166bdaf_0.tar.bz2#b62b52da46c39ee2bc3c162ac7f1804d
 https://conda.anaconda.org/conda-forge/linux-64/libjpeg-turbo-2.1.5.1-hd590300_1.conda#323e90742f0f48fc22bea908735f55e6
-https://conda.anaconda.org/conda-forge/linux-64/libnsl-2.0.0-h7f98852_0.tar.bz2#39b1328babf85c7c3a61636d9cd50206
+https://conda.anaconda.org/conda-forge/linux-64/libnsl-2.0.0-hd590300_1.conda#854e3e1623b39777140f199c5f9ab952
 https://conda.anaconda.org/conda-forge/linux-64/libsodium-1.0.18-h36c2ea0_1.tar.bz2#c3788462a6fbddafdb413a9f9053e58d
 https://conda.anaconda.org/conda-forge/linux-64/libtool-2.4.7-h27087fc_0.conda#f204c8ba400ec475452737094fb81d52
 https://conda.anaconda.org/conda-forge/linux-64/libuuid-2.38.1-h0b41bf4_0.conda#40b61aab5c7ba9ff276c41cfffe6b80b
@@ -48,9 +48,9 @@ https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.2.13-hd590300_5.conda#
 https://conda.anaconda.org/conda-forge/linux-64/lz4-c-1.9.4-hcb278e6_0.conda#318b08df404f9c9be5712aaa5a6f0bb0
 https://conda.anaconda.org/conda-forge/linux-64/lzo-2.10-h516909a_1000.tar.bz2#bb14fcb13341b81d5eb386423b9d2bac
 https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.4-hcb278e6_0.conda#681105bccc2a3f7f1a837d47d39c9179
-https://conda.anaconda.org/conda-forge/linux-64/openssl-3.1.2-hd590300_0.conda#e5ac5227582d6c83ccf247288c0eb095
+https://conda.anaconda.org/conda-forge/linux-64/openssl-3.1.3-hd590300_0.conda#7bb88ce04c8deb9f7d763ae04a1da72f
 https://conda.anaconda.org/conda-forge/linux-64/pcre-8.45-h9c3ff4c_0.tar.bz2#c05d1820a6d34ff07aaaab7a9b7eddaa
-https://conda.anaconda.org/conda-forge/linux-64/pixman-0.40.0-h36c2ea0_0.tar.bz2#660e72c82f2e75a6b3fe6a6e75c79f19
+https://conda.anaconda.org/conda-forge/linux-64/pixman-0.42.2-h59595ed_0.conda#700edd63ccd5fc66b70b1c028cea9a68
 https://conda.anaconda.org/conda-forge/linux-64/pthread-stubs-0.4-h36c2ea0_1001.tar.bz2#22dad4df6e8630e8dff2428f6f6a7036
 https://conda.anaconda.org/conda-forge/linux-64/snappy-1.1.10-h9fff704_0.conda#e6d228cd0bb74a51dd18f5bfce0b4115
 https://conda.anaconda.org/conda-forge/linux-64/xorg-kbproto-1.0.7-h7f98852_1002.tar.bz2#4b230e8381279d76131116660f5a241a
@@ -67,7 +67,7 @@ https://conda.anaconda.org/conda-forge/linux-64/expat-2.5.0-hcb278e6_1.conda#8b9
 https://conda.anaconda.org/conda-forge/linux-64/libbrotlidec-1.1.0-hd590300_0.conda#43017394a280a42b48d11d2a6e169901
 https://conda.anaconda.org/conda-forge/linux-64/libbrotlienc-1.1.0-hd590300_0.conda#8e3e1cb77c4b355a3776bdfb74095bed
 https://conda.anaconda.org/conda-forge/linux-64/libedit-3.1.20191231-he28a2e2_2.tar.bz2#4d331e44109e3f0e19b4cb8f9b82f3e1
-https://conda.anaconda.org/conda-forge/linux-64/libgfortran-ng-13.2.0-h69a702a_1.conda#394218a92951499aed2ab1bafb30b570
+https://conda.anaconda.org/conda-forge/linux-64/libgfortran-ng-13.2.0-h69a702a_2.conda#e75a75a6eaf6f318dae2631158c46575
 https://conda.anaconda.org/conda-forge/linux-64/libllvm14-14.0.6-hcd5def8_4.conda#73301c133ded2bf71906aa2104edae8b
 https://conda.anaconda.org/conda-forge/linux-64/libnghttp2-1.52.0-h61bc06f_0.conda#613955a50485812985c059e7b269f42e
 https://conda.anaconda.org/conda-forge/linux-64/libpng-1.6.39-h753d276_0.conda#e1c890aebdebbfbf87e2c917187b4416
@@ -78,7 +78,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libxml2-2.11.5-h232c23b_1.conda#
 https://conda.anaconda.org/conda-forge/linux-64/mpfr-4.2.0-hb012696_0.conda#14d87bdff2cbd3b1179a29fb316ed743
 https://conda.anaconda.org/conda-forge/linux-64/pcre2-10.40-hc3806b6_0.tar.bz2#69e2c796349cd9b273890bee0febfe1b
 https://conda.anaconda.org/conda-forge/linux-64/readline-8.2-h8228510_1.conda#47d31b792659ce70f470b5c82fdfb7a4
-https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.12-h27826a3_0.tar.bz2#5b8c42eb62e9fc961af70bdd6a26e168
+https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-h2797004_0.conda#513336054f884f95d9fd925748f41ef3
 https://conda.anaconda.org/conda-forge/linux-64/xorg-libsm-1.2.4-h7391055_0.conda#93ee23f12bc2e684548181256edd2cf6
 https://conda.anaconda.org/conda-forge/linux-64/zeromq-4.3.4-h9c3ff4c_1.tar.bz2#21743a8d2ea0c8cfbbf8fe489b0347df
 https://conda.anaconda.org/conda-forge/linux-64/zlib-1.2.13-hd590300_5.conda#68c34ec6149623be41a1933ab996a209
@@ -111,12 +111,13 @@ https://conda.anaconda.org/conda-forge/noarch/certifi-2023.7.22-pyhd8ed1ab_0.con
 https://conda.anaconda.org/conda-forge/noarch/charset-normalizer-3.2.0-pyhd8ed1ab_0.conda#313516e9a4b08b12dfb1e1cd390a96e3
 https://conda.anaconda.org/conda-forge/noarch/click-8.1.7-unix_pyh707e725_0.conda#f3ad426304898027fc619827ff428eca
 https://conda.anaconda.org/conda-forge/noarch/colorama-0.4.6-pyhd8ed1ab_0.tar.bz2#3faab06a954c2a04039983f2c4a50d99
+https://conda.anaconda.org/conda-forge/noarch/colored-1.4.4-pyhd8ed1ab_0.conda#46762cf2ddf6a1498eec36167d719fcc
 https://conda.anaconda.org/conda-forge/noarch/cycler-0.11.0-pyhd8ed1ab_0.tar.bz2#a50559fad0affdbb33729a68669ca1cb
 https://conda.anaconda.org/conda-forge/noarch/dataclasses-0.8-pyhc8e2a94_3.tar.bz2#a362b2124b06aad102e2ee4581acee7d
-https://conda.anaconda.org/conda-forge/linux-64/debugpy-1.8.0-py311hb755f60_0.conda#18855bb6c744389b662f6e2ba20acbb7
+https://conda.anaconda.org/conda-forge/linux-64/debugpy-1.8.0-py311hb755f60_1.conda#2c241533b8eafe8028442d46ef41eb13
 https://conda.anaconda.org/conda-forge/noarch/decorator-5.1.1-pyhd8ed1ab_0.tar.bz2#43afe5ab04e35e17ba28649471dd7364
 https://conda.anaconda.org/conda-forge/noarch/defusedxml-0.7.1-pyhd8ed1ab_0.tar.bz2#961b3a227b437d82ad7054484cfa71b2
-https://conda.anaconda.org/conda-forge/linux-64/docutils-0.17.1-py311h38be061_3.tar.bz2#3ef4abc4cfa232a15421a0ceef62801f
+https://conda.anaconda.org/conda-forge/linux-64/docutils-0.17.1-py311h38be061_4.conda#6815ab599d904e21243aad721d0b2bbb
 https://conda.anaconda.org/conda-forge/noarch/entrypoints-0.4-pyhd8ed1ab_0.tar.bz2#3cf04868fee0a029769bd41f4b2fbf2d
 https://conda.anaconda.org/conda-forge/noarch/exceptiongroup-1.1.3-pyhd8ed1ab_0.conda#e6518222753f519e911e83136d2158d9
 https://conda.anaconda.org/conda-forge/noarch/executing-1.2.0-pyhd8ed1ab_0.tar.bz2#4c1bc140e2be5c8ba6e3acab99e25c50
@@ -131,16 +132,16 @@ https://conda.anaconda.org/conda-forge/noarch/imagesize-1.4.1-pyhd8ed1ab_0.tar.b
 https://conda.anaconda.org/conda-forge/noarch/iniconfig-2.0.0-pyhd8ed1ab_0.conda#f800d2da156d08e289b14e87e43c1ae5
 https://conda.anaconda.org/conda-forge/noarch/ipython_genutils-0.2.0-py_1.tar.bz2#5071c982548b3a20caf70462f04f5287
 https://conda.anaconda.org/conda-forge/noarch/json5-0.9.14-pyhd8ed1ab_0.conda#dac1dabba2b5a9d1aee175c5fcc7b436
-https://conda.anaconda.org/conda-forge/linux-64/jsonpointer-2.4-py311h38be061_2.conda#46786941fbb695d0c1fa25af64526e7c
+https://conda.anaconda.org/conda-forge/linux-64/jsonpointer-2.4-py311h38be061_3.conda#41d52d822edf991bf0e6b08c1921a8ec
 https://conda.anaconda.org/conda-forge/noarch/jupyterlab_widgets-1.1.7-pyhd8ed1ab_0.conda#608e312cd17cb7119033fae7d7420572
-https://conda.anaconda.org/conda-forge/linux-64/kiwisolver-1.4.5-py311h9547e67_0.conda#f53903649188b99e6b44c560c69f5b23
+https://conda.anaconda.org/conda-forge/linux-64/kiwisolver-1.4.5-py311h9547e67_1.conda#2c65bdf442b0d37aad080c8a4e0d452f
 https://conda.anaconda.org/conda-forge/linux-64/lcms2-2.15-h7f713cb_2.conda#9ab79924a3760f85a799f21bc99bd655
 https://conda.anaconda.org/conda-forge/linux-64/libblas-3.9.0-18_linux64_openblas.conda#bcddbb497582ece559465b9cd11042e7
 https://conda.anaconda.org/conda-forge/linux-64/libcurl-8.3.0-hca28451_0.conda#4ab41bee09a2d2e08de5f09d6f1eef62
 https://conda.anaconda.org/conda-forge/linux-64/libwebp-1.3.2-hdffd6e0_0.conda#a8661c87c873d8c8f90479318ebf0a17
 https://conda.anaconda.org/conda-forge/linux-64/llvmlite-0.40.1-py311ha6695c7_0.conda#7a2b62d839516ba0cf56717e902229f4
-https://conda.anaconda.org/conda-forge/linux-64/lxml-4.9.3-py311h1a07684_0.conda#59a580306d62ef144c9dd592b5120f36
-https://conda.anaconda.org/conda-forge/linux-64/markupsafe-2.1.3-py311h459d7ec_0.conda#9904dc4adb5d547cb21e136f98cb24b0
+https://conda.anaconda.org/conda-forge/linux-64/lxml-4.9.3-py311h1a07684_1.conda#aab51e50d994e58efdfa5382139b0468
+https://conda.anaconda.org/conda-forge/linux-64/markupsafe-2.1.3-py311h459d7ec_1.conda#71120b5155a0c500826cf81536721a15
 https://conda.anaconda.org/conda-forge/noarch/mistune-3.0.1-pyhd8ed1ab_0.conda#1dad8397c94e4de97a70de552a7dcf49
 https://conda.anaconda.org/conda-forge/noarch/mock-5.0.2-pyhd8ed1ab_0.conda#541e4834b1e46ed786829dc63e4d4ca2
 https://conda.anaconda.org/conda-forge/noarch/mpmath-1.3.0-pyhd8ed1ab_0.conda#dbf6e2d89137da32fa6670f3bffc024e
@@ -157,14 +158,14 @@ https://conda.anaconda.org/conda-forge/noarch/pickleshare-0.7.5-py_1003.tar.bz2#
 https://conda.anaconda.org/conda-forge/noarch/pkgutil-resolve-name-1.3.10-pyhd8ed1ab_1.conda#405678b942f2481cecdb3e010f4925d9
 https://conda.anaconda.org/conda-forge/noarch/pluggy-1.3.0-pyhd8ed1ab_0.conda#2390bd10bed1f3fdc7a537fb5a447d8d
 https://conda.anaconda.org/conda-forge/noarch/prometheus_client-0.17.1-pyhd8ed1ab_0.conda#02153b6b760bbec00cfe9e4c97993d06
-https://conda.anaconda.org/conda-forge/linux-64/psutil-5.9.5-py311h2582759_0.conda#a90f8e278c1cd7064b2713e6b7db87e6
+https://conda.anaconda.org/conda-forge/linux-64/psutil-5.9.5-py311h459d7ec_1.conda#490d7fa8675afd1aa6f1b2332d156a45
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+https://conda.anaconda.org/conda-forge/linux-64/scipy-1.11.3-py311h64a7726_0.conda#756e8ac1d784f704c0b22559b4bff7b0
+https://conda.anaconda.org/conda-forge/noarch/setuptools_scm-8.0.3-hd8ed1ab_0.conda#da055c131516bfc51a5f5479b9390b2e
 https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-apidoc-0.3.0-py_1.tar.bz2#855b087883443abb10f5faf6eef40860
 https://conda.anaconda.org/conda-forge/linux-64/astropy-5.3.3-py311h1f0f07a_0.conda#e625f7df5ec7b9bd3655c63000c40b04
 https://conda.anaconda.org/conda-forge/linux-64/gtk2-2.24.33-h90689f9_2.tar.bz2#957a0255ab58aaf394a91725d73ab422
-https://conda.anaconda.org/conda-forge/noarch/jsonschema-with-format-nongpl-4.19.0-pyhd8ed1ab_1.conda#d273b30bcf4db0ef6b1195b3b61b3d68
+https://conda.anaconda.org/conda-forge/noarch/jsonschema-with-format-nongpl-4.19.1-pyhd8ed1ab_0.conda#daca0665e6fe8a376e48b9f0b5865326
 https://conda.anaconda.org/conda-forge/noarch/jupyter_client-8.3.1-pyhd8ed1ab_0.conda#b7cc0981484fcb6390e6d341e55618b3
 https://conda.anaconda.org/conda-forge/linux-64/librsvg-2.56.3-h98fae49_0.conda#620e754f4344f4c27259ff460a2b9c50
-https://conda.anaconda.org/conda-forge/linux-64/matplotlib-base-3.7.2-py311h54ef318_0.conda#2631a9e423855fb586c05f8a5ee8b177
+https://conda.anaconda.org/conda-forge/linux-64/matplotlib-base-3.8.0-py311h54ef318_1.conda#20d79e2fe53b49b399f3d36977b05abb
 https://conda.anaconda.org/conda-forge/noarch/nbformat-5.9.2-pyhd8ed1ab_0.conda#61ba076de6530d9301a0053b02f093d2
 https://conda.anaconda.org/conda-forge/noarch/prompt_toolkit-3.0.39-hd8ed1ab_0.conda#4bbbe67d5df19db30f04b8e344dc9976
 https://conda.anaconda.org/conda-forge/linux-64/pytables-3.8.0-py311h10c7f7f_3.conda#c3896f06c2850c5206ae9d684121ddee
@@ -299,8 +301,8 @@ https://conda.anaconda.org/conda-forge/noarch/nbclient-0.8.0-pyhd8ed1ab_0.conda#
 https://conda.anaconda.org/conda-forge/noarch/radioactivedecay-0.4.21-pyhd8ed1ab_0.conda#673319f48d9b160c8056783d301e090c
 https://conda.anaconda.org/conda-forge/noarch/ipykernel-6.25.2-pyh2140261_0.conda#226f2032ec491cc6e9ce66072660e4f6
 https://conda.anaconda.org/conda-forge/noarch/nbconvert-core-7.8.0-pyhd8ed1ab_0.conda#62345c9e24f898bf492979be84a6eb0a
-https://conda.anaconda.org/conda-forge/linux-64/pygraphviz-1.11-py311h72a77b7_0.conda#e8f7fad69f6806368eab99a91b594ebd
-https://conda.anaconda.org/conda-forge/noarch/jupyter_server-2.7.3-pyhd8ed1ab_0.conda#969249eb7c2f7a9b820520a355dc7d04
+https://conda.anaconda.org/conda-forge/linux-64/pygraphviz-1.11-py311h72a77b7_1.conda#7044cd923985abb6e3b976e5ac0542b8
+https://conda.anaconda.org/conda-forge/noarch/jupyter_server-2.7.3-pyhd8ed1ab_1.conda#0123f934221b023ddc7443e85cac9023
 https://conda.anaconda.org/conda-forge/noarch/nbconvert-pandoc-7.8.0-pyhd8ed1ab_0.conda#1dba1a577df2625a24667612a069e91c
 https://conda.anaconda.org/conda-forge/noarch/jupyter-lsp-2.2.0-pyhd8ed1ab_0.conda#38589f4104d11f2a59ff01a9f4e3bfb3
 https://conda.anaconda.org/conda-forge/noarch/jupyterlab_server-2.25.0-pyhd8ed1ab_0.conda#a52834fa7e3d12abc5efdf06b2097a05
@@ -308,7 +310,7 @@ https://conda.anaconda.org/conda-forge/noarch/nbconvert-7.8.0-pyhd8ed1ab_0.conda
 https://conda.anaconda.org/conda-forge/noarch/notebook-shim-0.2.3-pyhd8ed1ab_0.conda#67e0fe74c156267d9159e9133df7fd37
 https://conda.anaconda.org/conda-forge/noarch/jupyterlab-4.0.6-pyhd8ed1ab_0.conda#80bb1cc3b540790cb5afecd73c2d4d1f
 https://conda.anaconda.org/conda-forge/noarch/nbclassic-1.0.0-pyhb4ecaf3_1.conda#a0be31e9bd84d6eae87cdbf74c56b90b
-https://conda.anaconda.org/conda-forge/noarch/notebook-7.0.3-pyhd8ed1ab_0.conda#1f2d368cde97926b5e351d1a0286bb1e
+https://conda.anaconda.org/conda-forge/noarch/notebook-7.0.4-pyhd8ed1ab_0.conda#9fe0b0f2e8a6dbae64947e90079ea54c
 https://conda.anaconda.org/conda-forge/noarch/widgetsnbextension-3.6.6-pyhd8ed1ab_0.conda#fe79dfe7d51794d665ec3c2fdd4e47c3
 https://conda.anaconda.org/conda-forge/noarch/ipywidgets-7.8.0-pyhd8ed1ab_0.conda#518b05adab6cfe6ea249319932d9d4a3
 https://conda.anaconda.org/conda-forge/noarch/qgrid-1.3.1-pyhd8ed1ab_4.tar.bz2#fff68c7404813a1eb2678425f00e9917
diff --git a/conda-lock.yml b/conda-lock.yml
index 7b25a11453c..def78a5fb0e 100644
--- a/conda-lock.yml
+++ b/conda-lock.yml
@@ -9,20 +9,21 @@
 # To update a single package to the latest version compatible with the version constraints in the source:
 #     conda-lock lock  --lockfile conda-lock.yml --update PACKAGE
 # To re-solve the entire environment, e.g. after changing a version constraint in the source file:
-#     conda-lock -f tardis_env3.yml -f /Users/wkerzend/python/tardis/tardis_env3.yml --lockfile conda-lock.yml
+#     conda-lock -f tardis_env3.yml -f /Users/wkerzend/python/tardis/tardis_env3.yml -f /home/atharva/workspace/code/tardis-main/tardis/tardis_env3.yml --lockfile conda-lock.yml
 metadata:
   channels:
   - url: conda-forge
     used_env_vars: []
   content_hash:
-    linux-64: 31d323d670a8deec16e2186403aa54ab8464102ac712829e12e62d80bc50f272
-    osx-64: a32c45fe2a9272de47a9c858b1b632bb1de0c3a0cd55bffe7df61cc7ef21eecd
+    linux-64: c282095367763377f64134aabe34418215a97ab21d09982800cc95beb98ebaa9
+    osx-64: e0b8122702e46d054c30bc66450a0041530cf14a3c2f3dcc4daed538bb8c0785
   platforms:
   - linux-64
   - osx-64
   sources:
   - tardis_env3.yml
   - /Users/wkerzend/python/tardis/tardis_env3.yml
+  - /home/atharva/workspace/code/tardis-main/tardis/tardis_env3.yml
 package:
 - category: main
   dependencies: {}
@@ -115,13 +116,13 @@ package:
 - category: main
   dependencies: {}
   hash:
-    md5: acfb4817400db5804030a3a7ef7909a1
-    sha256: b4ee92e483b24dbcdbaab0928e14bf338342268e3c413111413ee36284006d56
+    md5: 9172c297304f2a20134fc56c97fbe229
+    sha256: ab22ecdc974cdbe148874ea876d9c564294d5eafa760f403ed4fd495307b4243
   manager: conda
   name: libstdcxx-ng
   optional: false
   platform: linux-64
-  url: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-ng-13.2.0-h7e041cc_1.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-ng-13.2.0-h7e041cc_2.conda
   version: 13.2.0
 - category: main
   dependencies: {}
@@ -137,13 +138,13 @@ package:
 - category: main
   dependencies: {}
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-    sha256: 2966a87dcb0b11fad28f9fe8216bfa4071115776b47ffc7547492fed176e1a1f
+    md5: d786502c97404c94d7d58d258a445a65
+    sha256: 0be3ac1bf852d64f553220c7e6457e9c047dfb7412da9d22fbaa67e60858b3cf
   manager: conda
   name: python_abi
   optional: false
   platform: linux-64
-  url: https://conda.anaconda.org/conda-forge/linux-64/python_abi-3.11-3_cp311.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/python_abi-3.11-4_cp311.conda
   version: '3.11'
 - category: main
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@@ -175,13 +176,13 @@ package:
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     _libgcc_mutex: 0.1 conda_forge
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-    sha256: cc9b25e3a0329326936164ca666861738e2833460cd1e0bb2086acb5781a7795
+    md5: e2042154faafe61969556f28bade94b9
+    sha256: e1e82348f8296abfe344162b3b5f0ddc2f504759ebeb8b337ba99beaae583b15
   manager: conda
   name: libgomp
   optional: false
   platform: linux-64
-  url: https://conda.anaconda.org/conda-forge/linux-64/libgomp-13.2.0-h807b86a_1.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/libgomp-13.2.0-h807b86a_2.conda
   version: 13.2.0
 - category: main
   dependencies:
@@ -213,13 +214,13 @@ package:
     _libgcc_mutex: 0.1 conda_forge
     _openmp_mutex: '>=4.5'
   hash:
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-    sha256: 98fef2f6d766ea98e64fb378c2c9ae57bf53220440e4ba15eea3d7cf27b69a58
+    md5: c28003b0be0494f9a7664389146716ff
+    sha256: d361d3c87c376642b99c1fc25cddec4b9905d3d9b9203c1c545b8c8c1b04539a
   manager: conda
   name: libgcc-ng
   optional: false
   platform: linux-64
-  url: https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-13.2.0-h807b86a_1.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-13.2.0-h807b86a_2.conda
   version: 13.2.0
 - category: main
   dependencies:
@@ -434,13 +435,13 @@ package:
   dependencies:
     libgcc-ng: '>=13.2.0'
   hash:
-    md5: a0d27fd5c6f05aa45e9602b1db49581c
-    sha256: 30b4194151c1d6cdede3da8c33aabb848cde4db2fc68e7f5607f2e4a38d881d7
+    md5: 78fdab09d9138851dde2b5fe2a11019e
+    sha256: 55ecf5c46c05a98b4822a041d6e1cb196a7b0606126eb96b24131b7d2c8ca561
   manager: conda
   name: libgfortran5
   optional: false
   platform: linux-64
-  url: https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-13.2.0-ha4646dd_1.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-13.2.0-ha4646dd_2.conda
   version: 13.2.0
 - category: main
   dependencies:
@@ -468,15 +469,15 @@ package:
   version: 2.1.5.1
 - category: main
   dependencies:
-    libgcc-ng: '>=9.4.0'
+    libgcc-ng: '>=12'
   hash:
-    md5: 39b1328babf85c7c3a61636d9cd50206
-    sha256: 32f4fb94d99946b0dabfbbfd442b25852baf909637f2eed1ffe3baea15d02aad
+    md5: 854e3e1623b39777140f199c5f9ab952
+    sha256: c0a0c0abc1c17983168c3239d79a62d53c424bc5dd1764dbcd0fa953d6fce5e0
   manager: conda
   name: libnsl
   optional: false
   platform: linux-64
-  url: https://conda.anaconda.org/conda-forge/linux-64/libnsl-2.0.0-h7f98852_0.tar.bz2
+  url: https://conda.anaconda.org/conda-forge/linux-64/libnsl-2.0.0-hd590300_1.conda
   version: 2.0.0
 - category: main
   dependencies:
@@ -580,14 +581,14 @@ package:
     ca-certificates: ''
     libgcc-ng: '>=12'
   hash:
-    md5: e5ac5227582d6c83ccf247288c0eb095
-    sha256: b113fbac327c90cdc29c2fac0f2a2e5cc0d1918b2a5ffa7abd49b695b9b3c6e9
+    md5: 7bb88ce04c8deb9f7d763ae04a1da72f
+    sha256: f4e35f506c7e8ab7dfdc47255b0d5aa8ce0c99028ae0affafd274333042c4f70
   manager: conda
   name: openssl
   optional: false
   platform: linux-64
-  url: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.1.2-hd590300_0.conda
-  version: 3.1.2
+  url: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.1.3-hd590300_0.conda
+  version: 3.1.3
 - category: main
   dependencies:
     libgcc-ng: '>=9.3.0'
@@ -603,16 +604,17 @@ package:
   version: '8.45'
 - category: main
   dependencies:
-    libgcc-ng: '>=7.5.0'
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
   hash:
-    md5: 660e72c82f2e75a6b3fe6a6e75c79f19
-    sha256: 6a0630fff84b5a683af6185a6c67adc8bdfa2043047fcb251add0d352ef60e79
+    md5: 700edd63ccd5fc66b70b1c028cea9a68
+    sha256: ae917851474eb3b08812b02c9e945d040808523ec53f828aa74a90b0cdf15f57
   manager: conda
   name: pixman
   optional: false
   platform: linux-64
-  url: https://conda.anaconda.org/conda-forge/linux-64/pixman-0.40.0-h36c2ea0_0.tar.bz2
-  version: 0.40.0
+  url: https://conda.anaconda.org/conda-forge/linux-64/pixman-0.42.2-h59595ed_0.conda
+  version: 0.42.2
 - category: main
   dependencies:
     libgcc-ng: '>=7.5.0'
@@ -812,15 +814,15 @@ package:
   version: 3.1.20191231
 - category: main
   dependencies:
-    libgfortran5: 13.2.0 ha4646dd_1
+    libgfortran5: 13.2.0 ha4646dd_2
   hash:
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-    sha256: 08f9cd5830b5f498cbea2f32cdf755c1cdee8d3c48dd2c48d6dda142cdb5d473
+    md5: e75a75a6eaf6f318dae2631158c46575
+    sha256: 767d71999e5386210fe2acaf1b67073e7943c2af538efa85c101e3401e94ff62
   manager: conda
   name: libgfortran-ng
   optional: false
   platform: linux-64
-  url: https://conda.anaconda.org/conda-forge/linux-64/libgfortran-ng-13.2.0-h69a702a_1.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/libgfortran-ng-13.2.0-h69a702a_2.conda
   version: 13.2.0
 - category: main
   dependencies:
@@ -966,17 +968,17 @@ package:
   version: '8.2'
 - category: main
   dependencies:
-    libgcc-ng: '>=9.4.0'
-    libzlib: '>=1.2.11,<1.3.0a0'
+    libgcc-ng: '>=12'
+    libzlib: '>=1.2.13,<1.3.0a0'
   hash:
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-    sha256: 032fd769aad9d4cad40ba261ab222675acb7ec951a8832455fce18ef33fa8df0
+    md5: 513336054f884f95d9fd925748f41ef3
+    sha256: 679e944eb93fde45d0963a22598fafacbb429bb9e7ee26009ba81c4e0c435055
   manager: conda
   name: tk
   optional: false
   platform: linux-64
-  url: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.12-h27826a3_0.tar.bz2
-  version: 8.6.12
+  url: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-h2797004_0.conda
+  version: 8.6.13
 - category: main
   dependencies:
     libgcc-ng: '>=12'
@@ -1439,6 +1441,18 @@ package:
   platform: linux-64
   url: https://conda.anaconda.org/conda-forge/noarch/colorama-0.4.6-pyhd8ed1ab_0.tar.bz2
   version: 0.4.6
+- category: main
+  dependencies:
+    python: '>=3.6'
+  hash:
+    md5: 46762cf2ddf6a1498eec36167d719fcc
+    sha256: 18a1ff961c9015b674212044d5d63f7510279e6880a5626ef2af32d0abf4cc18
+  manager: conda
+  name: colored
+  optional: false
+  platform: linux-64
+  url: https://conda.anaconda.org/conda-forge/noarch/colored-1.4.4-pyhd8ed1ab_0.conda
+  version: 1.4.4
 - category: main
   dependencies:
     python: '>=3.6'
@@ -1470,13 +1484,13 @@ package:
     python: '>=3.11,<3.12.0a0'
     python_abi: 3.11.* *_cp311
   hash:
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-    sha256: 966207d8cf7774abc190e462f8f1eaa7438c8ae9d3d2ab2c96d0a5d3fef24a53
+    md5: 2c241533b8eafe8028442d46ef41eb13
+    sha256: f18492ebfaea54bbbeaec0ae207851f711ff589f60f2cc9b8a689f88b2442171
   manager: conda
   name: debugpy
   optional: false
   platform: linux-64
-  url: https://conda.anaconda.org/conda-forge/linux-64/debugpy-1.8.0-py311hb755f60_0.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/debugpy-1.8.0-py311hb755f60_1.conda
   version: 1.8.0
 - category: main
   dependencies:
@@ -1507,13 +1521,13 @@ package:
     python: '>=3.11,<3.12.0a0'
     python_abi: 3.11.* *_cp311
   hash:
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-    sha256: 4a885aa0c53716922a0b6a1af3a690d33b9965ef2eec75a0541064affdaa757a
+    md5: 6815ab599d904e21243aad721d0b2bbb
+    sha256: f8622b7ac95654b7a3236cd3fa9e07ab6121548e39713e55ee95fc64a8f1fab6
   manager: conda
   name: docutils
   optional: false
   platform: linux-64
-  url: https://conda.anaconda.org/conda-forge/linux-64/docutils-0.17.1-py311h38be061_3.tar.bz2
+  url: https://conda.anaconda.org/conda-forge/linux-64/docutils-0.17.1-py311h38be061_4.conda
   version: 0.17.1
 - category: main
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@@ -1704,13 +1718,13 @@ package:
     python: '>=3.11,<3.12.0a0'
     python_abi: 3.11.* *_cp311
   hash:
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-    sha256: bd4f518f2e717ad5ce6a442a589b853ae4a043ce38fe3145dea0fdc3c052ec19
+    md5: 41d52d822edf991bf0e6b08c1921a8ec
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   manager: conda
   name: jsonpointer
   optional: false
   platform: linux-64
-  url: https://conda.anaconda.org/conda-forge/linux-64/jsonpointer-2.4-py311h38be061_2.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/jsonpointer-2.4-py311h38be061_3.conda
   version: '2.4'
 - category: main
   dependencies:
@@ -1731,13 +1745,13 @@ package:
     python: '>=3.11,<3.12.0a0'
     python_abi: 3.11.* *_cp311
   hash:
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-    sha256: 4ff5804105829e10da7955740f8a2f058c1c5cc19d0004b59af7070544a5a42e
+    md5: 2c65bdf442b0d37aad080c8a4e0d452f
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   manager: conda
   name: kiwisolver
   optional: false
   platform: linux-64
-  url: https://conda.anaconda.org/conda-forge/linux-64/kiwisolver-1.4.5-py311h9547e67_0.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/kiwisolver-1.4.5-py311h9547e67_1.conda
   version: 1.4.5
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@@ -1820,19 +1834,19 @@ package:
 - category: main
   dependencies:
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   name: setuptools-scm
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-  url: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-7.1.0-pyhd8ed1ab_0.conda
-  version: 7.1.0
+  url: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-8.0.3-pyhd8ed1ab_0.conda
+  version: 8.0.3
 - category: main
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@@ -7800,6 +7841,20 @@ package:
   platform: osx-64
   url: https://conda.anaconda.org/conda-forge/noarch/sympy-1.12-pypyh9d50eac_103.conda
   version: '1.12'
+- category: main
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+    colored: '>=1.3.92,<2.0.0'
+    pytest: '>=7.0.0,<8.0.0'
+    python: '>=3.8.1,<4.0'
+  hash:
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+    sha256: 0945c0b2fd39441fb0920c146a43a60f0fdef535dfba636c80a52270e79242b4
+  manager: conda
+  name: syrupy
+  optional: false
+  platform: osx-64
+  url: https://conda.anaconda.org/conda-forge/noarch/syrupy-4.5.0-pyhd8ed1ab_0.conda
+  version: 4.5.0
 - category: main
   dependencies:
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@@ -7870,14 +7925,14 @@ package:
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     rpds-py: '>=0.7.1'
   hash:
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-    sha256: 4c1f9ffa8056fc96d292d119746d5d87e2d0308cd19b063943efbde05e0accdf
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   name: jsonschema
   optional: false
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-  url: https://conda.anaconda.org/conda-forge/noarch/jsonschema-4.19.0-pyhd8ed1ab_1.conda
-  version: 4.19.0
+  url: https://conda.anaconda.org/conda-forge/noarch/jsonschema-4.19.1-pyhd8ed1ab_0.conda
+  version: 4.19.1
 - category: main
   dependencies:
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@@ -7885,14 +7940,14 @@ package:
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     traitlets: '>=5.3'
   hash:
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-    sha256: 90045f63ca46c1cd66c55e7a3fce41f9719c82ec30cedc608d368fbde67b9265
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   manager: conda
   name: jupyter_core
   optional: false
   platform: osx-64
-  url: https://conda.anaconda.org/conda-forge/osx-64/jupyter_core-5.3.1-py311h6eed73b_0.conda
-  version: 5.3.1
+  url: https://conda.anaconda.org/conda-forge/osx-64/jupyter_core-5.3.2-py311h6eed73b_0.conda
+  version: 5.3.2
 - category: main
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   hash:
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-    sha256: aaf609e65752dc195b601a76f537d84ee57b26e5202436a88b8d401dda128b66
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   name: pybtex-docutils
   optional: false
   platform: osx-64
-  url: https://conda.anaconda.org/conda-forge/osx-64/pybtex-docutils-1.0.3-py311h6eed73b_0.conda
+  url: https://conda.anaconda.org/conda-forge/osx-64/pybtex-docutils-1.0.3-py311h6eed73b_1.conda
   version: 1.0.3
 - category: main
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@@ -8002,16 +8057,16 @@ package:
   version: 1.8.2
 - category: main
   dependencies:
-    setuptools-scm: '>=7.1.0,<7.1.1.0a0'
+    setuptools-scm: '>=8.0.3,<8.0.4.0a0'
   hash:
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-    sha256: c31cbd374ce9e02d99c74a3823725030158abc50a8adfea40db11b965fbd017d
+    md5: da055c131516bfc51a5f5479b9390b2e
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   manager: conda
   name: setuptools_scm
   optional: false
   platform: osx-64
-  url: https://conda.anaconda.org/conda-forge/noarch/setuptools_scm-7.1.0-hd8ed1ab_0.conda
-  version: 7.1.0
+  url: https://conda.anaconda.org/conda-forge/noarch/setuptools_scm-8.0.3-hd8ed1ab_0.conda
+  version: 8.0.3
 - category: main
   dependencies:
     pbr: ''
@@ -8032,13 +8087,13 @@ package:
     python: '>=3.11,<3.12.0a0'
     python_abi: 3.11.* *_cp311
   hash:
-    md5: 4ee477aeedcb82edff2b3d9ab2ad98ae
-    sha256: 8659a903fada1a521d385b6af6c293e8a7724071e57d776999c8d649ac0be78c
+    md5: a8e5f688e3249e1dea90b4dd4eede1a7
+    sha256: 7a2d0dcd69098d87455268a2b46cbec46a97de7090048f7ac8cadaae3d21a60e
   manager: conda
   name: contourpy
   optional: false
   platform: osx-64
-  url: https://conda.anaconda.org/conda-forge/osx-64/contourpy-1.1.1-py311h5fe6e05_0.conda
+  url: https://conda.anaconda.org/conda-forge/osx-64/contourpy-1.1.1-py311h5fe6e05_1.conda
   version: 1.1.1
 - category: main
   dependencies:
@@ -8065,13 +8120,13 @@ package:
     python: '>=3.11,<3.12.0a0'
     python_abi: 3.11.* *_cp311
   hash:
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-    sha256: 0d0947054617078c7f325f7c4e59314d5bb15bbb91998f15cf063d45786da637
+    md5: 0b74e739ce6718d03bd830816bc1aacd
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   manager: conda
   name: h5py
   optional: false
   platform: osx-64
-  url: https://conda.anaconda.org/conda-forge/osx-64/h5py-3.9.0-nompi_py311hf255e76_102.conda
+  url: https://conda.anaconda.org/conda-forge/osx-64/h5py-3.9.0-nompi_py311hf255e76_103.conda
   version: 3.9.0
 - category: main
   dependencies:
@@ -8079,21 +8134,21 @@ package:
     idna: ''
     isoduration: ''
     jsonpointer: '>1.13'
-    jsonschema: '>=4.19.0,<4.19.1.0a0'
+    jsonschema: '>=4.19.1,<4.19.2.0a0'
     python: ''
     rfc3339-validator: ''
     rfc3986-validator: '>0.1.0'
     uri-template: ''
     webcolors: '>=1.11'
   hash:
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-    sha256: fae13283e5c4b1e639b76348e3d9441bde21685c8a8c89f6d3f364e524ed5029
+    md5: daca0665e6fe8a376e48b9f0b5865326
+    sha256: af65a8783a89c03ac8437a1d95ee5ac2e50e92d3af231cec515292fe296aff8e
   manager: conda
   name: jsonschema-with-format-nongpl
   optional: false
   platform: osx-64
-  url: https://conda.anaconda.org/conda-forge/noarch/jsonschema-with-format-nongpl-4.19.0-pyhd8ed1ab_1.conda
-  version: 4.19.0
+  url: https://conda.anaconda.org/conda-forge/noarch/jsonschema-with-format-nongpl-4.19.1-pyhd8ed1ab_0.conda
+  version: 4.19.1
 - category: main
   dependencies:
     importlib_metadata: '>=4.8.3'
@@ -8169,14 +8224,14 @@ package:
     python: '>=3.11,<3.12.0a0'
     python_abi: 3.11.* *_cp311
   hash:
-    md5: f54b3f060b554070e12e815e97c02a1c
-    sha256: a2260e1a0ad66ef6bbfc56a1dd3c202e1a6d38e6f0b8e356fae0306a548d2b87
+    md5: 2abd3d878d4e9851a3ecda9e22d320e4
+    sha256: 027c0c81314d035c5dff9201d5465016148f4bce9f843843684dd89bb8481004
   manager: conda
   name: numexpr
   optional: false
   platform: osx-64
-  url: https://conda.anaconda.org/conda-forge/osx-64/numexpr-2.8.4-py311hab14417_1.conda
-  version: 2.8.4
+  url: https://conda.anaconda.org/conda-forge/osx-64/numexpr-2.8.7-py311hab14417_0.conda
+  version: 2.8.7
 - category: main
   dependencies:
     libcxx: '>=15.0.7'
@@ -8187,14 +8242,14 @@ package:
     python_abi: 3.11.* *_cp311
     pytz: '>=2020.1'
   hash:
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-    sha256: 92456166e106f226d870e7f5509e8d31464ce4f51596170bb46cc53dd2137656
+    md5: c739684a33ac866b933093225c85a666
+    sha256: 7c0d377861272791c66146be45665a67e8a2c29e54ed56e50e4e90b30e6c45dc
   manager: conda
   name: pandas
   optional: false
   platform: osx-64
-  url: https://conda.anaconda.org/conda-forge/osx-64/pandas-2.1.0-py311hab14417_0.conda
-  version: 2.1.0
+  url: https://conda.anaconda.org/conda-forge/osx-64/pandas-2.1.1-py311hab14417_0.conda
+  version: 2.1.1
 - category: main
   dependencies:
     prompt-toolkit: '>=3.0.39,<3.0.40.0a0'
@@ -8213,13 +8268,13 @@ package:
     python: '>=3.11,<3.12.0a0'
     python_abi: 3.11.* *_cp311
   hash:
-    md5: 261df2feb11abd22de42e0c9dc276a2e
-    sha256: 0bdfa5f662643583633db420f362cb930d627348e74e9750531a6a32ae628405
+    md5: df67199d1733effdfc2f959ae4f63e8f
+    sha256: b14cee247d2bb4085ba58c30d4c37e26c2009dc7417c1db021330263bc373d6f
   manager: conda
   name: pyerfa
   optional: false
   platform: osx-64
-  url: https://conda.anaconda.org/conda-forge/osx-64/pyerfa-2.0.0.3-py311h4a70a88_0.conda
+  url: https://conda.anaconda.org/conda-forge/osx-64/pyerfa-2.0.0.3-py311h4a70a88_1.conda
   version: 2.0.0.3
 - category: main
   dependencies:
@@ -8233,14 +8288,14 @@ package:
     python: '>=3.11,<3.12.0a0'
     python_abi: 3.11.* *_cp311
   hash:
-    md5: 1a79189c98a28c9fef03ba8315bcd6b8
-    sha256: a1df4a9cff160689033915b55465411183a0422c0390102c751d2b496944e4ad
+    md5: bd195650c219e5e90f45413cd0bacfa8
+    sha256: 5069ee98c5f90187f473764aefb3347bc91a63fc3a7cefede63196d43e3626bf
   manager: conda
   name: scipy
   optional: false
   platform: osx-64
-  url: https://conda.anaconda.org/conda-forge/osx-64/scipy-1.11.2-py311h16c3c4d_1.conda
-  version: 1.11.2
+  url: https://conda.anaconda.org/conda-forge/osx-64/scipy-1.11.3-py311h16c3c4d_0.conda
+  version: 1.11.3
 - category: main
   dependencies:
     importlib-metadata: ''
@@ -8346,19 +8401,19 @@ package:
     numpy: '>=1.23.5,<2.0a0'
     packaging: '>=20.0'
     pillow: '>=6.2.0'
-    pyparsing: '>=2.3.1,<3.1'
+    pyparsing: '>=2.3.1'
     python: '>=3.11,<3.12.0a0'
     python-dateutil: '>=2.7'
     python_abi: 3.11.* *_cp311
   hash:
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-    sha256: 2264ee0dbb0bac37d9fe36867f06eb0169fdeb158696cd41d83c4b0bdc503541
+    md5: 390e0db0f04fabd7330fa626c398b16f
+    sha256: cb2711d7a9d34a5954939737a38ebcb4916279c0a49d7cd7272d2e28b2b94b97
   manager: conda
   name: matplotlib-base
   optional: false
   platform: osx-64
-  url: https://conda.anaconda.org/conda-forge/osx-64/matplotlib-base-3.7.2-py311haff9b01_0.conda
-  version: 3.7.2
+  url: https://conda.anaconda.org/conda-forge/osx-64/matplotlib-base-3.8.0-py311haff9b01_0.conda
+  version: 3.8.0
 - category: main
   dependencies:
     jupyter_client: '>=6.1.12'
@@ -8454,17 +8509,17 @@ package:
   version: 7.8.0
 - category: main
   dependencies:
-    graphviz: '>=8.0.5,<9.0a0'
+    graphviz: '>=8.1.0,<9.0a0'
     python: '>=3.11,<3.12.0a0'
     python_abi: 3.11.* *_cp311
   hash:
-    md5: fed0a15be9e09c83aba369a5049655c1
-    sha256: 131fbc18d15252389162c11718bb4fcb5091ae8ab270c283ab5f4e63afab3482
+    md5: 17602bac3f0091fc1383741385b1c1b1
+    sha256: b0e97e9a5bbd65edddaa9147bfb2410bbbc8105cf02dbd0c7a717355dc81ded3
   manager: conda
   name: pygraphviz
   optional: false
   platform: osx-64
-  url: https://conda.anaconda.org/conda-forge/osx-64/pygraphviz-1.11-py311hc6eba27_0.conda
+  url: https://conda.anaconda.org/conda-forge/osx-64/pygraphviz-1.11-py311hc6eba27_1.conda
   version: '1.11'
 - category: main
   dependencies:
@@ -8507,13 +8562,13 @@ package:
     traitlets: '>=5.6.0'
     websocket-client: ''
   hash:
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-    sha256: c90bc6f842a37dd99e32b35f0f40214040756949fe5a7abc1256a227bb8ba90e
+    md5: 0123f934221b023ddc7443e85cac9023
+    sha256: 47913d8bda9f0cd5cf2a2d27039436a55a74eec51f1ad2b374a88fbf99fd46b3
   manager: conda
   name: jupyter_server
   optional: false
   platform: osx-64
-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_server-2.7.3-pyhd8ed1ab_0.conda
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_server-2.7.3-pyhd8ed1ab_1.conda
   version: 2.7.3
 - category: main
   dependencies:
@@ -8654,14 +8709,14 @@ package:
     python: '>=3.8'
     tornado: '>=6.2.0'
   hash:
-    md5: 1f2d368cde97926b5e351d1a0286bb1e
-    sha256: b94a8838af82d0d986627439f64bbe85a4806fcc1cdd300bba685df934fbd33b
+    md5: 9fe0b0f2e8a6dbae64947e90079ea54c
+    sha256: 3ee5870402d41db9d93af61cc15ca7b8ccfccc6a024d564d764aabd4ac8ce908
   manager: conda
   name: notebook
   optional: false
   platform: osx-64
-  url: https://conda.anaconda.org/conda-forge/noarch/notebook-7.0.3-pyhd8ed1ab_0.conda
-  version: 7.0.3
+  url: https://conda.anaconda.org/conda-forge/noarch/notebook-7.0.4-pyhd8ed1ab_0.conda
+  version: 7.0.4
 - category: main
   dependencies:
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diff --git a/conda-osx-64.lock b/conda-osx-64.lock
index 00013efcb38..c911a33d163 100644
--- a/conda-osx-64.lock
+++ b/conda-osx-64.lock
@@ -1,6 +1,6 @@
 # Generated by conda-lock.
 # platform: osx-64
-# input_hash: a32c45fe2a9272de47a9c858b1b632bb1de0c3a0cd55bffe7df61cc7ef21eecd
+# input_hash: e0b8122702e46d054c30bc66450a0041530cf14a3c2f3dcc4daed538bb8c0785
 @EXPLICIT
 https://conda.anaconda.org/conda-forge/osx-64/bzip2-1.0.8-h0d85af4_4.tar.bz2#37edc4e6304ca87316e160f5ca0bd1b5
 https://conda.anaconda.org/conda-forge/osx-64/c-ares-1.19.1-h0dc2134_0.conda#b3e62631b4e1b9801477523ce1d6f355
@@ -28,9 +28,8 @@ https://conda.anaconda.org/conda-forge/osx-64/libwebp-base-1.3.2-h0dc2134_0.cond
 https://conda.anaconda.org/conda-forge/osx-64/libzlib-1.2.13-h8a1eda9_5.conda#4a3ad23f6e16f99c04e166767193d700
 https://conda.anaconda.org/conda-forge/osx-64/llvm-openmp-16.0.6-hff08bdf_0.conda#39a5227d906f75102bf8586741690128
 https://conda.anaconda.org/conda-forge/osx-64/ncurses-6.4-hf0c8a7f_0.conda#c3dbae2411164d9b02c69090a9a91857
-https://conda.anaconda.org/conda-forge/osx-64/pixman-0.40.0-hbcb3906_0.tar.bz2#09a583a6f172715be21d93aaa1b42d71
 https://conda.anaconda.org/conda-forge/osx-64/pthread-stubs-0.4-hc929b4f_1001.tar.bz2#addd19059de62181cd11ae8f4ef26084
-https://conda.anaconda.org/conda-forge/osx-64/python_abi-3.11-3_cp311.conda#5e0a069a585445333868d2c6651c3b3f
+https://conda.anaconda.org/conda-forge/osx-64/python_abi-3.11-4_cp311.conda#fef7a52f0eca6bae9e8e2e255bc86394
 https://conda.anaconda.org/conda-forge/noarch/tzdata-2023c-h71feb2d_0.conda#939e3e74d8be4dac89ce83b20de2492a
 https://conda.anaconda.org/conda-forge/osx-64/xorg-libxau-1.0.11-h0dc2134_0.conda#9566b4c29274125b0266d0177b5eb97b
 https://conda.anaconda.org/conda-forge/osx-64/xorg-libxdmcp-1.1.3-h35c211d_0.tar.bz2#86ac76d6bf1cbb9621943eb3bd9ae36e
@@ -54,13 +53,14 @@ https://conda.anaconda.org/conda-forge/osx-64/libsqlite-3.43.0-h58db7d2_0.conda#
 https://conda.anaconda.org/conda-forge/osx-64/libxcb-1.15-hb7f2c08_0.conda#5513f57e0238c87c12dffedbcc9c1a4a
 https://conda.anaconda.org/conda-forge/osx-64/libxml2-2.11.5-h3346baf_1.conda#7584dee6af7de378aed0ae49aebedb8a
 https://conda.anaconda.org/conda-forge/osx-64/lz4-c-1.9.4-hf0c8a7f_0.conda#aa04f7143228308662696ac24023f991
-https://conda.anaconda.org/conda-forge/osx-64/openssl-3.1.2-h8a1eda9_0.conda#85d5377436d19183c8ac5afbb8e713a1
+https://conda.anaconda.org/conda-forge/osx-64/openssl-3.1.3-h8a1eda9_0.conda#26f9b58f905547e658e9587f8e8cfe43
 https://conda.anaconda.org/conda-forge/osx-64/pandoc-3.1.3-h9d075a6_0.conda#e86a3d5c966a09b6129354114483f7a7
 https://conda.anaconda.org/conda-forge/osx-64/pcre-8.45-he49afe7_0.tar.bz2#0526850419e04ac003bc0b65a78dc4cc
 https://conda.anaconda.org/conda-forge/osx-64/pcre2-10.40-h1c4e4bc_0.tar.bz2#e0f80c8f3a0352a54eddfe59cd2b25b1
+https://conda.anaconda.org/conda-forge/osx-64/pixman-0.42.2-he965462_0.conda#e4180dcfd3e3621560fe1ad522997520
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@@ -222,14 +223,14 @@ https://conda.anaconda.org/conda-forge/noarch/snakeviz-2.2.0-pyhd8ed1ab_0.conda#
 https://conda.anaconda.org/conda-forge/noarch/terminado-0.17.1-pyhd1c38e8_0.conda#046120b71d8896cb7faef78bfdbfee1e
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 https://conda.anaconda.org/conda-forge/noarch/tqdm-4.66.1-pyhd8ed1ab_0.conda#03c97908b976498dcae97eb4e4f3149c
-https://conda.anaconda.org/conda-forge/noarch/typing-extensions-4.7.1-hd8ed1ab_0.conda#f96688577f1faa58096d06a45136afa2
-https://conda.anaconda.org/conda-forge/noarch/urllib3-2.0.4-pyhd8ed1ab_0.conda#18badd8fa3648d1beb1fcc7f2e0f756e
-https://conda.anaconda.org/conda-forge/osx-64/argon2-cffi-bindings-21.2.0-py311h5547dcb_3.tar.bz2#c09459e349fa61afc352f473766de109
+https://conda.anaconda.org/conda-forge/noarch/typing-extensions-4.8.0-hd8ed1ab_0.conda#384462e63262a527bda564fa2d9126c0
+https://conda.anaconda.org/conda-forge/noarch/urllib3-2.0.5-pyhd8ed1ab_0.conda#3bda70bbeb2920f44db5375af2e5fe38
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-https://conda.anaconda.org/conda-forge/osx-64/harfbuzz-8.2.0-h7666e2a_0.conda#7b263a6bd9fbebd829f10f529209ff50
+https://conda.anaconda.org/conda-forge/osx-64/harfbuzz-8.2.1-h7666e2a_0.conda#81f8f2aaf6bd4b408a0a8823edf7ce3b
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 https://conda.anaconda.org/conda-forge/noarch/jupyter_server_terminals-0.4.4-pyhd8ed1ab_1.conda#7c0965e1d4a0ee1529e8eaa03a78a5b3
@@ -238,54 +239,55 @@ https://conda.anaconda.org/conda-forge/osx-64/liblapack-3.9.0-18_osx64_openblas.
 https://conda.anaconda.org/conda-forge/noarch/pbr-5.11.1-pyhd8ed1ab_0.conda#5bde4ebca51438054099b9527c904ecb
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-https://conda.anaconda.org/conda-forge/osx-64/pyobjc-framework-cocoa-9.2-py311hf110eff_0.conda#6ba4637fa1ed0a1e829b1f278c12274a
+https://conda.anaconda.org/conda-forge/osx-64/pyobjc-framework-cocoa-10.0-py311hf110eff_1.conda#8fb67274a648901045368717d6221aed
 https://conda.anaconda.org/conda-forge/noarch/pytest-cov-4.1.0-pyhd8ed1ab_0.conda#06eb685a3a0b146347a58dda979485da
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 https://conda.anaconda.org/conda-forge/noarch/pytest-metadata-3.0.0-pyhd8ed1ab_1.conda#8bdcc0f401561213821bf67513abeeff
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-https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-7.1.0-pyhd8ed1ab_0.conda#6613dbb3b25cc648a107f33ca9f80fc1
+https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-8.0.3-pyhd8ed1ab_0.conda#23929f6e32fba28210bf0c329a8cf941
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-https://conda.anaconda.org/conda-forge/noarch/jsonschema-4.19.0-pyhd8ed1ab_1.conda#d442886dffcee45604595fea2ad3a181
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+https://conda.anaconda.org/conda-forge/noarch/jsonschema-4.19.1-pyhd8ed1ab_0.conda#78aff5d2af74e6537c1ca73017f01f4f
+https://conda.anaconda.org/conda-forge/osx-64/jupyter_core-5.3.2-py311h6eed73b_0.conda#32b2a44c7686c1dc850e4dd44f16b2d8
 https://conda.anaconda.org/conda-forge/osx-64/numpy-1.24.4-py311hc44ba51_0.conda#31c12f08652b27a8f9cceb39ea4a1d4e
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 https://conda.anaconda.org/conda-forge/noarch/prompt-toolkit-3.0.39-pyha770c72_0.conda#a4986c6bb5b0d05a38855b0880a5f425
-https://conda.anaconda.org/conda-forge/osx-64/pybtex-docutils-1.0.3-py311h6eed73b_0.conda#218f01e087a8a12f3474ff43c9879628
+https://conda.anaconda.org/conda-forge/osx-64/pybtex-docutils-1.0.3-py311h6eed73b_1.conda#36996441974a061f9e0b600741599585
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 https://conda.anaconda.org/conda-forge/noarch/send2trash-1.8.2-pyhd1c38e8_0.conda#2657c3de5371c571aef6678afb4aaadd
-https://conda.anaconda.org/conda-forge/noarch/setuptools_scm-7.1.0-hd8ed1ab_0.conda#75abb977a0ae63a8039b12fa0925eeb8
+https://conda.anaconda.org/conda-forge/noarch/setuptools_scm-8.0.3-hd8ed1ab_0.conda#da055c131516bfc51a5f5479b9390b2e
 https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-apidoc-0.3.0-py_1.tar.bz2#855b087883443abb10f5faf6eef40860
-https://conda.anaconda.org/conda-forge/osx-64/contourpy-1.1.1-py311h5fe6e05_0.conda#4ee477aeedcb82edff2b3d9ab2ad98ae
+https://conda.anaconda.org/conda-forge/osx-64/contourpy-1.1.1-py311h5fe6e05_1.conda#a8e5f688e3249e1dea90b4dd4eede1a7
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-https://conda.anaconda.org/conda-forge/osx-64/h5py-3.9.0-nompi_py311hf255e76_102.conda#8261fdb0f3ef9287449d3731ef927ed7
-https://conda.anaconda.org/conda-forge/noarch/jsonschema-with-format-nongpl-4.19.0-pyhd8ed1ab_1.conda#d273b30bcf4db0ef6b1195b3b61b3d68
+https://conda.anaconda.org/conda-forge/osx-64/h5py-3.9.0-nompi_py311hf255e76_103.conda#0b74e739ce6718d03bd830816bc1aacd
+https://conda.anaconda.org/conda-forge/noarch/jsonschema-with-format-nongpl-4.19.1-pyhd8ed1ab_0.conda#daca0665e6fe8a376e48b9f0b5865326
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-https://conda.anaconda.org/conda-forge/osx-64/numexpr-2.8.4-py311hab14417_1.conda#f54b3f060b554070e12e815e97c02a1c
-https://conda.anaconda.org/conda-forge/osx-64/pandas-2.1.0-py311hab14417_0.conda#e081bf78c37d2671a7d442a56c3a8728
+https://conda.anaconda.org/conda-forge/osx-64/numexpr-2.8.7-py311hab14417_0.conda#2abd3d878d4e9851a3ecda9e22d320e4
+https://conda.anaconda.org/conda-forge/osx-64/pandas-2.1.1-py311hab14417_0.conda#c739684a33ac866b933093225c85a666
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-https://conda.anaconda.org/conda-forge/osx-64/pyerfa-2.0.0.3-py311h4a70a88_0.conda#261df2feb11abd22de42e0c9dc276a2e
-https://conda.anaconda.org/conda-forge/osx-64/scipy-1.11.2-py311h16c3c4d_1.conda#1a79189c98a28c9fef03ba8315bcd6b8
+https://conda.anaconda.org/conda-forge/osx-64/pyerfa-2.0.0.3-py311h4a70a88_1.conda#df67199d1733effdfc2f959ae4f63e8f
+https://conda.anaconda.org/conda-forge/osx-64/scipy-1.11.3-py311h16c3c4d_0.conda#bd195650c219e5e90f45413cd0bacfa8
 https://conda.anaconda.org/conda-forge/osx-64/astropy-5.3.3-py311h4a70a88_0.conda#067a1e7c5fc33393399dc5c1969469a0
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-https://conda.anaconda.org/conda-forge/osx-64/matplotlib-base-3.7.2-py311haff9b01_0.conda#bd9520e9015e70f3de839ce48c9061ea
+https://conda.anaconda.org/conda-forge/osx-64/matplotlib-base-3.8.0-py311haff9b01_0.conda#390e0db0f04fabd7330fa626c398b16f
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 https://conda.anaconda.org/conda-forge/noarch/ipykernel-6.25.2-pyh1050b4e_0.conda#a643e6f6c33ed821664f2a69f6e4e89f
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-https://conda.anaconda.org/conda-forge/osx-64/pygraphviz-1.11-py311hc6eba27_0.conda#fed0a15be9e09c83aba369a5049655c1
+https://conda.anaconda.org/conda-forge/osx-64/pygraphviz-1.11-py311hc6eba27_1.conda#17602bac3f0091fc1383741385b1c1b1
 https://conda.anaconda.org/conda-forge/noarch/radioactivedecay-0.4.21-pyhd8ed1ab_0.conda#673319f48d9b160c8056783d301e090c
-https://conda.anaconda.org/conda-forge/noarch/jupyter_server-2.7.3-pyhd8ed1ab_0.conda#969249eb7c2f7a9b820520a355dc7d04
+https://conda.anaconda.org/conda-forge/noarch/jupyter_server-2.7.3-pyhd8ed1ab_1.conda#0123f934221b023ddc7443e85cac9023
 https://conda.anaconda.org/conda-forge/noarch/nbconvert-pandoc-7.8.0-pyhd8ed1ab_0.conda#1dba1a577df2625a24667612a069e91c
 https://conda.anaconda.org/conda-forge/noarch/jupyter-lsp-2.2.0-pyhd8ed1ab_0.conda#38589f4104d11f2a59ff01a9f4e3bfb3
 https://conda.anaconda.org/conda-forge/noarch/jupyterlab_server-2.25.0-pyhd8ed1ab_0.conda#a52834fa7e3d12abc5efdf06b2097a05
@@ -293,7 +295,7 @@ https://conda.anaconda.org/conda-forge/noarch/nbconvert-7.8.0-pyhd8ed1ab_0.conda
 https://conda.anaconda.org/conda-forge/noarch/notebook-shim-0.2.3-pyhd8ed1ab_0.conda#67e0fe74c156267d9159e9133df7fd37
 https://conda.anaconda.org/conda-forge/noarch/jupyterlab-4.0.6-pyhd8ed1ab_0.conda#80bb1cc3b540790cb5afecd73c2d4d1f
 https://conda.anaconda.org/conda-forge/noarch/nbclassic-1.0.0-pyhb4ecaf3_1.conda#a0be31e9bd84d6eae87cdbf74c56b90b
-https://conda.anaconda.org/conda-forge/noarch/notebook-7.0.3-pyhd8ed1ab_0.conda#1f2d368cde97926b5e351d1a0286bb1e
+https://conda.anaconda.org/conda-forge/noarch/notebook-7.0.4-pyhd8ed1ab_0.conda#9fe0b0f2e8a6dbae64947e90079ea54c
 https://conda.anaconda.org/conda-forge/noarch/widgetsnbextension-3.6.6-pyhd8ed1ab_0.conda#fe79dfe7d51794d665ec3c2fdd4e47c3
 https://conda.anaconda.org/conda-forge/noarch/ipywidgets-7.8.0-pyhd8ed1ab_0.conda#518b05adab6cfe6ea249319932d9d4a3
 https://conda.anaconda.org/conda-forge/noarch/qgrid-1.3.1-pyhd8ed1ab_4.tar.bz2#fff68c7404813a1eb2678425f00e9917
diff --git a/docs/contributing/development/running_tests.rst b/docs/contributing/development/running_tests.rst
index e299cb8febc..d5d1a0e4c59 100644
--- a/docs/contributing/development/running_tests.rst
+++ b/docs/contributing/development/running_tests.rst
@@ -70,6 +70,18 @@ Or, to run tests for a particular file or directory
     You can check if cache was generated by looking in the ``Restore LFS Cache`` step of the workflow run. 
     Cache can also be found under the "Management" Section under "Actions" tab.
 
+
+Running Syrupy Tests
+======================
+The tests module is currently being restructured to use `Syrupy <https://github.com/tophat/syrupy>`_. 
+These tests generate individual HDF(for Pandas) and ``.npy`` or ``.npz`` (for NumPy) files(or snapshots) for each test case.
+For other objects, the plugin serialises them and saves them as ``.ambr`` files. There is a custom extension in the 
+main local `conftest <https://github.com/tardis-sn/tardis/blob/master/tardis/conftest.py>`_ file to get this to work.
+The plugin currently only supports ``assert_allclose`` for NumPy and ``assert_series_equal`` and ``assert_frame_equal`` for 
+Pandas. Snapshots can be generated by using the same ``--generate-reference`` flag and are compared automatically.
+You however need to provide the location to your snapshot directory using the ``--tardis-snapshot-data`` flag.
+The snapshots are also saved in `tardis-sn/tardis-regressions <https://github.com/tardis-sn/tardis-regressions>`_.
+
 Generating Plasma Reference
 ===========================
 
diff --git a/docs/io/configuration/components/plasma.rst b/docs/io/configuration/components/plasma.rst
index bef23b8110c..4a27598d2fe 100644
--- a/docs/io/configuration/components/plasma.rst
+++ b/docs/io/configuration/components/plasma.rst
@@ -64,3 +64,14 @@ The NLTE configuration currently allows setting ``coronal_approximation``, which
 This is useful for debugging with :term:`chianti` for example. Furthermore, one can enable 'classical_nebular' to set all
 :math:`\beta_\textrm{Sobolev}` to 1. Both options are used for checking with other codes and should not be enabled in
 normal operations.
+
+NLTE Ionization
+^^^^^^^^^^^^^^^
+
+.. code-block:: yaml
+
+    plasma:
+        nlte_ionization_species: [H I, H II, He I, He II]
+    
+This option allows the user to specify which species should be included in the NLTE ionization treatment. Note that the
+species must be present in the continuum interaction species as well.
diff --git a/docs/physics/setup/plasma/index.rst b/docs/physics/setup/plasma/index.rst
index 6d0c26ad7ff..06c4a2203c9 100644
--- a/docs/physics/setup/plasma/index.rst
+++ b/docs/physics/setup/plasma/index.rst
@@ -73,6 +73,9 @@ The next more complex class is `LTEPlasma` which will calculate the ionization b
 
 TARDIS also allows for NLTE treatments of specified species, as well as special NLTE treatments for Helium.
 
+.. note::
+    The NLTE treatment of specified species is currently incompatible with the NLTE treatment for helium and cannot be used simulataneously.
+
 .. toctree::
     :maxdepth: 2
 
diff --git a/tardis/conftest.py b/tardis/conftest.py
index eb64d686fda..00bcb0ec413 100644
--- a/tardis/conftest.py
+++ b/tardis/conftest.py
@@ -39,7 +39,6 @@ def pytest_configure(config):
 
     """
     if ASTROPY_HEADER:
-
         config.option.astropy_header = True
 
         # Customize the following lines to add/remove entries from the list of
@@ -78,11 +77,19 @@ def pytest_configure(config):
 # Here the TARDIS testing stuff begins
 # -------------------------------------------------------------------------
 
+import re
 import pytest
 import pandas as pd
 from tardis.io.util import yaml_load_file, YAMLLoader
 from tardis.io.configuration.config_reader import Configuration
 from tardis.simulation import Simulation
+from tardis.util.syrupy_extensions import (
+    SingleFileSanitizedNames,
+    NumpySnapshotExtenstion,
+    PandasSnapshotExtenstion,
+)
+
+pytest_plugins = "syrupy"
 
 
 def pytest_addoption(parser):
@@ -101,6 +108,13 @@ def pytest_addoption(parser):
         default=False,
         help="generate reference data instead of testing",
     )
+
+    parser.addoption(
+        "--tardis-snapshot-data",
+        default=None,
+        help="Path to Tardis Snapshot Folder",
+    )
+
     parser.addoption(
         "--less-packets",
         action="store_true",
@@ -116,6 +130,8 @@ def pytest_collection_modifyitems(config, items):
         for item in items:
             if "ignore_generate" in item.keywords:
                 item.add_marker(skip_generate)
+        # automatically set update snapshots to true
+        config.option.update_snapshots = True
 
 
 # -------------------------------------------------------------------------
@@ -141,6 +157,17 @@ def tardis_ref_path(request):
         return Path(os.path.expandvars(os.path.expanduser(tardis_ref_path)))
 
 
+@pytest.fixture(scope="session")
+def tardis_snapshot_path(request):
+    tardis_snapshot_path = request.config.getoption("--tardis-snapshot-data")
+    if tardis_snapshot_path is None:
+        pytest.skip("--tardis-snapshot-data was not specified")
+    else:
+        return Path(
+            os.path.expandvars(os.path.expanduser(tardis_snapshot_path))
+        )
+
+
 from tardis.tests.fixtures.atom_data import *
 
 
@@ -211,3 +238,23 @@ def simulation_verysimple(config_verysimple, atomic_dataset):
     sim = Simulation.from_config(config_verysimple, atom_data=atomic_data)
     sim.iterate(4000)
     return sim
+
+
+# -------------------------------------------------------------------------
+# fixtures and plugins for syrupy/regression data testing
+# -------------------------------------------------------------------------
+
+
+@pytest.fixture
+def pandas_snapshot_extention():
+    return PandasSnapshotExtenstion
+
+
+@pytest.fixture
+def numpy_snapshot_extension():
+    return NumpySnapshotExtenstion
+
+
+@pytest.fixture
+def singlefilesanitized():
+    return SingleFileSanitizedNames
diff --git a/tardis/io/decay.py b/tardis/io/decay.py
index a61a54a3cb8..7005fa50e6e 100644
--- a/tardis/io/decay.py
+++ b/tardis/io/decay.py
@@ -2,10 +2,12 @@
 from radioactivedecay import Nuclide, Inventory
 from radioactivedecay.utils import Z_to_elem
 from astropy import units as u
+import logging
 
+logger = logging.getLogger(__name__)
 
-class IsotopeAbundances(pd.DataFrame):
 
+class IsotopeAbundances(pd.DataFrame):
     _metadata = ["time_0"]
 
     def __init__(self, *args, **kwargs):
@@ -92,9 +94,18 @@ def decay(self, t):
         t_second = (
             u.Quantity(t, u.day).to(u.s).value - self.time_0.to(u.s).value
         )
+        logger.info(f"Decaying abundances for {t_second} seconds")
+        if t_second < 0:
+            logger.warning(
+                f"Decay time {t_second} is negative. This could indicate a miss-specified input model."
+                f" A negative decay time can potentially lead to negative abundances."
+            )
         decayed_inventories = [item.decay(t_second) for item in inventories]
         df = IsotopeAbundances.from_inventories(decayed_inventories)
         df.sort_index(inplace=True)
+        assert (
+            df.ge(0.0).all().all()
+        ), "Negative abundances detected. Please make sure your input abundances are correct."
         return df
 
     def as_atoms(self):
diff --git a/tardis/montecarlo/montecarlo_numba/numba_interface.py b/tardis/montecarlo/montecarlo_numba/numba_interface.py
index 848ba3cfe10..50be58a6d8f 100644
--- a/tardis/montecarlo/montecarlo_numba/numba_interface.py
+++ b/tardis/montecarlo/montecarlo_numba/numba_interface.py
@@ -217,7 +217,9 @@ def opacity_state_initialize(plasma, line_interaction_type):
         ].values
 
         phot_nus = phot_nus.values
-        ff_opacity_factor = plasma.ff_cooling_factor / np.sqrt(t_electrons)
+        ff_opacity_factor = (
+            plasma.ff_cooling_factor / np.sqrt(t_electrons)
+        ).astype(np.float64)
         emissivities = plasma.fb_emission_cdf.loc[
             plasma.level2continuum_idx.index
         ].values
diff --git a/tardis/montecarlo/packet_source.py b/tardis/montecarlo/packet_source.py
index f6a069dac0e..0bd63ea1f90 100644
--- a/tardis/montecarlo/packet_source.py
+++ b/tardis/montecarlo/packet_source.py
@@ -313,7 +313,7 @@ def create_packets(self, no_of_packets):
         self.beta = ((self.radius / self.time_explosion) / const.c).to("")
         return super().create_packets(no_of_packets)
 
-    def create_packet_nus(self, no_of_packets):
+    def create_packet_mus(self, no_of_packets):
         """
         Create zero-limb-darkening packet :math:`\mu^\prime` distributed
         according to :math:`\\mu^\\prime=2 \\frac{\\mu^\\prime + \\beta}{2 \\beta + 1}`.
@@ -327,7 +327,7 @@ def create_packet_nus(self, no_of_packets):
 
         Returns
         -------
-        array of frequencies
+        Directions for packets
             numpy.ndarray
         """
         z = self.rng.random(no_of_packets)
diff --git a/tardis/montecarlo/tests/test_packet_source.py b/tardis/montecarlo/tests/test_packet_source.py
index 43338903967..a18850d4129 100644
--- a/tardis/montecarlo/tests/test_packet_source.py
+++ b/tardis/montecarlo/tests/test_packet_source.py
@@ -3,8 +3,12 @@
 import numpy as np
 import pandas as pd
 import pytest
+from numpy.testing import assert_allclose
 
-from tardis.montecarlo.packet_source import BlackBodySimpleSource
+from tardis.montecarlo.packet_source import (
+    BlackBodySimpleSource,
+    BlackBodySimpleSourceRelativistic,
+)
 from tardis.montecarlo import (
     montecarlo_configuration as montecarlo_configuration,
 )
@@ -43,6 +47,22 @@ def blackbodysimplesource(self, request):
         yield cls.bb
         montecarlo_configuration.LEGACY_MODE_ENABLED = False
 
+    @pytest.fixture(scope="class")
+    def blackbody_simplesource_relativistic(self, request):
+        """
+        Create BlackBodySimpleSourceRelativistic instance.
+
+        Yields
+        -------
+        tardis.montecarlo.packet_source.BlackBodySimpleSourceRelativistic
+        """
+        montecarlo_configuration.LEGACY_MODE_ENABLED = True
+        bb_rel = BlackBodySimpleSourceRelativistic(
+            base_seed=1963, legacy_second_seed=2508
+        )
+        yield bb_rel
+        montecarlo_configuration.LEGACY_MODE_ENABLED = False
+
     def test_bb_packet_sampling(
         self,
         request,
@@ -51,8 +71,6 @@ def test_bb_packet_sampling(
         blackbodysimplesource,
     ):
         """
-        Test generate_plot_mpl method.
-
         Parameters
         ----------
         request : _pytest.fixtures.SubRequest
@@ -75,3 +93,47 @@ def test_bb_packet_sampling(
         assert np.all(np.isclose(nus, ref_df["nus"]))
         assert np.all(np.isclose(mus, ref_df["mus"]))
         assert np.all(np.isclose(unif_energies, ref_df["energies"]))
+
+    def test_bb_packet_sampling_relativistic(
+        self,
+        tardis_ref_data,
+        blackbody_simplesource_relativistic,
+    ):
+        """
+        Parameters
+        ----------
+        tardis_ref_data : pd.HDFStore
+        blackbody_simplesource_relativistic : tardis.montecarlo.packet_source.BlackBodySimpleSourceRelativistic
+        """
+        blackbody_simplesource_relativistic.temperature = 10000
+        blackbody_simplesource_relativistic.beta = 0.25
+
+        nus = blackbody_simplesource_relativistic.create_packet_nus(100)
+        unif_energies = (
+            blackbody_simplesource_relativistic.create_packet_energies(100)
+        )
+        blackbody_simplesource_relativistic._reseed(2508)
+        mus = blackbody_simplesource_relativistic.create_packet_mus(10)
+
+        gamma = np.sqrt(1 - blackbody_simplesource_relativistic.beta**2) ** -1
+        ref_df = tardis_ref_data["/packet_unittest/blackbody"]
+        expected_nus = ref_df["nus"]
+        expected_unif_energies = ref_df["energies"] * 1.6 / gamma
+        expected_mus = np.array(
+            [
+                0.60420546,
+                0.49899691,
+                0.69583288,
+                0.96812652,
+                0.01544154,
+                0.93562304,
+                0.44306545,
+                0.77010037,
+                0.896973,
+                0.67876489,
+            ]
+        )
+
+        assert_allclose(nus, expected_nus)
+        assert_allclose(unif_energies, expected_unif_energies)
+        assert_allclose(mus, expected_mus, rtol=1e-6)
diff --git a/tardis/plasma/properties/nlte_rate_equation_solver.py b/tardis/plasma/properties/nlte_rate_equation_solver.py
index 9718efc266f..487b93ad5a3 100644
--- a/tardis/plasma/properties/nlte_rate_equation_solver.py
+++ b/tardis/plasma/properties/nlte_rate_equation_solver.py
@@ -11,7 +11,7 @@
 
 
 class NLTERateEquationSolver(ProcessingPlasmaProperty):
-    outputs = ("ion_number_density_nlte", "electron_densities_nlte")
+    outputs = ("ion_number_density", "electron_densities")
 
     def calculate(
         self,
@@ -110,6 +110,10 @@ def calculate(
                 number_density[shell],
                 initial_electron_densities[shell],
             )
+            # All first guess values have to be positive
+            assert (
+                np.greater_equal(first_guess, 0.0).all()
+            ).all(), "First guess for NLTE solver has negative values, something went wrong."
             solution = root(
                 self.population_objective_function,
                 first_guess,
@@ -591,7 +595,7 @@ def prepare_first_guess(
         """
         first_guess = pd.Series(0.0, index=rate_matrix_index)
         for atomic_number in atomic_numbers:
-            first_guess.loc[(atomic_number, 1)][0] = number_density.loc[
+            first_guess.loc[(atomic_number, 1)].iloc[0] = number_density.loc[
                 atomic_number
             ]
         # TODO: After the first iteration, the new guess can be the old solution.
diff --git a/tardis/plasma/properties/transition_probabilities.py b/tardis/plasma/properties/transition_probabilities.py
index 9def7e650df..e69d655ef6b 100644
--- a/tardis/plasma/properties/transition_probabilities.py
+++ b/tardis/plasma/properties/transition_probabilities.py
@@ -41,10 +41,16 @@ def normalize_trans_probs(p):
         all probabilites with the same source_level_idx sum to one.
         Indexed by source_level_idx, destination_level_idx.
     """
-    p_summed = p.groupby(level=0).sum()
+    # Dtype conversion is needed for pandas to return nan instead of
+    # a ZeroDivisionError in cases where the sum is zero.
+    p = p.astype(np.float64)
+    p_summed = p.groupby(level=0).sum().astype(np.float64)
     index = p.index.get_level_values("source_level_idx")
     p_norm = p / p_summed.loc[index].values
     p_norm = p_norm.fillna(0.0)
+    # Convert back to original dtypes to avoid typing problems later on
+    # in the numba code.
+    p_norm = p_norm.convert_dtypes()
     return p_norm
 
 
@@ -78,7 +84,9 @@ def series2matrix(series, idx2reduced_idx):
             idx2reduced_idx.loc[q_indices[1]].values,
         )
         max_idx = idx2reduced_idx.max() + 1
-        matrix = sp.coo_matrix((series, q_indices), shape=(max_idx, max_idx))
+        matrix = sp.coo_matrix(
+            (series.astype(np.float64), q_indices), shape=(max_idx, max_idx)
+        )
         return matrix
 
     @staticmethod
diff --git a/tardis/plasma/standard_plasmas.py b/tardis/plasma/standard_plasmas.py
index 63c6ac2324e..82bbc54a263 100644
--- a/tardis/plasma/standard_plasmas.py
+++ b/tardis/plasma/standard_plasmas.py
@@ -6,6 +6,10 @@
 import pandas as pd
 
 from tardis.io.atom_data import AtomData
+from tardis.plasma.properties.level_population import LevelNumberDensity
+from tardis.plasma.properties.nlte_rate_equation_solver import (
+    NLTERateEquationSolver,
+)
 from tardis.plasma.properties.rate_matrix_index import NLTEIndexHelper
 from tardis.util.base import species_string_to_tuple
 from tardis.plasma import BasePlasma
@@ -265,6 +269,26 @@ def assemble_plasma(config, simulation_state, atom_data=None):
             delta_treatment=config.plasma.delta_treatment
         )
 
+    if (
+        config.plasma.helium_treatment == "recomb-nlte"
+        or config.plasma.helium_treatment == "numerical-nlte"
+    ) and (
+        config.plasma.nlte_ionization_species
+        or config.plasma.nlte_excitation_species
+    ):
+        # Prevent the user from using helium NLTE treatment with
+        # NLTE ionization and excitation treatment. This is because
+        # the helium_nlte_properties could overwrite the NLTE ionization
+        # and excitation ion number and electron densities.
+        # helium_numerical_nlte_properties is also included here because
+        # it is currently in the same if else block, and thus may block
+        # the addition of the components from the else block.
+        raise PlasmaConfigError(
+            "Helium NLTE treatment is incompatible with the NLTE eonization and excitation treatment."
+        )
+
+    # TODO: Disentangle these if else block such that compatible components
+    # can be added independently.
     if config.plasma.helium_treatment == "recomb-nlte":
         plasma_modules += helium_nlte_properties
     elif config.plasma.helium_treatment == "numerical-nlte":
@@ -277,7 +301,16 @@ def assemble_plasma(config, simulation_state, atom_data=None):
                 heating_rate_data_file=config.plasma.heating_rate_data_file
             )
     else:
-        plasma_modules += helium_lte_properties
+        # If nlte ionization species are present, we don't want to add the
+        # IonNumberDensity from helium_lte_properties, since we want
+        # to use the IonNumberDensity provided by the NLTE solver.
+        if (
+            config.plasma.nlte_ionization_species
+            or config.plasma.nlte_excitation_species
+        ):
+            plasma_modules += [LevelNumberDensity]
+        else:
+            plasma_modules += helium_lte_properties
 
     if simulation_state._electron_densities is not None:
         electron_densities = pd.Series(
@@ -287,6 +320,13 @@ def assemble_plasma(config, simulation_state, atom_data=None):
             property_kwargs[IonNumberDensityHeNLTE] = dict(
                 electron_densities=electron_densities
             )
+        elif (
+            config.plasma.nlte_ionization_species
+            or config.plasma.nlte_excitation_species
+        ):
+            property_kwargs[NLTERateEquationSolver] = dict(
+                electron_densities=electron_densities
+            )
         else:
             property_kwargs[IonNumberDensity] = dict(
                 electron_densities=electron_densities
diff --git a/tardis/plasma/tests/conftest.py b/tardis/plasma/tests/conftest.py
new file mode 100644
index 00000000000..dab8927219e
--- /dev/null
+++ b/tardis/plasma/tests/conftest.py
@@ -0,0 +1,42 @@
+from pathlib import Path
+
+import pytest
+from syrupy.location import PyTestLocation
+
+SNAPSHOT_LOCATION = "plasma"
+
+
+@pytest.fixture
+def snapshot_pd(snapshot, tardis_snapshot_path, pandas_snapshot_extention):
+    refpath = tardis_snapshot_path.joinpath(SNAPSHOT_LOCATION)
+
+    class PandasSnapshotExtenstionRefdata(pandas_snapshot_extention):
+        @classmethod
+        def dirname(cls, *, test_location: "PyTestLocation") -> str:
+            return str(Path(test_location.filepath).parent.joinpath(refpath))
+
+    return snapshot.use_extension(PandasSnapshotExtenstionRefdata)
+
+
+@pytest.fixture
+def snapshot_np(snapshot, tardis_snapshot_path, numpy_snapshot_extension):
+    refpath = tardis_snapshot_path.joinpath(SNAPSHOT_LOCATION)
+
+    class NumpySnapshotExtenstionRefdata(numpy_snapshot_extension):
+        @classmethod
+        def dirname(cls, *, test_location: "PyTestLocation") -> str:
+            return str(Path(test_location.filepath).parent.joinpath(refpath))
+
+    return snapshot.use_extension(NumpySnapshotExtenstionRefdata)
+
+
+@pytest.fixture
+def snapshot(snapshot, tardis_snapshot_path, singlefilesanitized):
+    refpath = tardis_snapshot_path.joinpath(SNAPSHOT_LOCATION)
+
+    class SingleFileSanitizedRefdata(singlefilesanitized):
+        @classmethod
+        def dirname(cls, *, test_location: "PyTestLocation") -> str:
+            return str(Path(test_location.filepath).parent.joinpath(refpath))
+
+    return snapshot.use_extension(SingleFileSanitizedRefdata)
diff --git a/tardis/plasma/tests/test_complete_plasmas.py b/tardis/plasma/tests/test_complete_plasmas.py
index 4320f0d8284..6231eb11e06 100644
--- a/tardis/plasma/tests/test_complete_plasmas.py
+++ b/tardis/plasma/tests/test_complete_plasmas.py
@@ -2,11 +2,8 @@
 import warnings
 
 import pandas as pd
-import pandas.testing as pdt
 import pytest
 
-import numpy as np
-from numpy.testing import assert_almost_equal
 from tardis.io.configuration.config_reader import Configuration
 from tardis.simulation import Simulation
 
@@ -72,7 +69,6 @@ def idfn(fixture_value):
 
 
 class TestPlasma(object):
-
     general_properties = [
         "beta_rad",
         "g_electron",
@@ -157,18 +153,13 @@ def config(self, request):
         return config
 
     @pytest.fixture(scope="class")
-    def plasma(self, request, chianti_he_db_fpath, config, tardis_ref_data):
+    def plasma(self, chianti_he_db_fpath, config):
         config["atom_data"] = chianti_he_db_fpath
         sim = Simulation.from_config(config)
-        if request.config.getoption("--generate-reference"):
-            sim.plasma.to_hdf(
-                tardis_ref_data, path=config.plasma.save_path, overwrite=True
-            )
-            pytest.skip(f"Reference data saved at {tardis_ref_data}")
         return sim.plasma
 
     @pytest.mark.parametrize("attr", combined_properties)
-    def test_plasma_properties(self, plasma, tardis_ref_data, config, attr):
+    def test_plasma_properties(self, plasma, attr, snapshot_pd, snapshot_np):
         if hasattr(plasma, attr):
             actual = getattr(plasma, attr)
             if hasattr(actual, "unit"):
@@ -177,42 +168,35 @@ def test_plasma_properties(self, plasma, tardis_ref_data, config, attr):
                 actual = pd.Series(actual)
             else:
                 actual = pd.DataFrame(actual)
-            key = os.path.join(config.plasma.save_path, "plasma", attr)
-            expected = tardis_ref_data[key]
-            if type(actual) == pd.DataFrame:
-                pdt.assert_frame_equal(actual, expected)
-            elif type(actual) == pd.Series:
-                pdt.assert_series_equal(actual, expected)
+            if isinstance(actual, (pd.DataFrame, pd.Series)):
+                assert snapshot_pd == actual
             else:
-                raise TypeError(f"Unexpected type {type(actual)}")
-            # we used this before - assert_almost_equal(actual.values, expected.values)
+                assert snapshot_np == actual
         else:
             warnings.warn(f'Property "{attr}" not found')
 
-    def test_levels(self, plasma, tardis_ref_data, config):
+    def test_levels(self, plasma, snapshot_pd, snapshot_np):
         actual = pd.DataFrame(plasma.levels)
-        key = os.path.join(config.plasma.save_path, "plasma", "levels")
-        expected = tardis_ref_data[key]
-        pdt.assert_frame_equal(actual, expected)
+        if isinstance(actual, (pd.DataFrame, pd.Series)):
+            assert snapshot_pd == actual
+        else:
+            assert snapshot_np == actual
 
     @pytest.mark.parametrize("attr", scalars_properties)
-    def test_scalars_properties(self, plasma, tardis_ref_data, config, attr):
+    def test_scalars_properties(self, plasma, attr, snapshot_pd, snapshot_np):
         actual = getattr(plasma, attr)
         if hasattr(actual, "cgs"):
             actual = actual.cgs.value
-        key = os.path.join(config.plasma.save_path, "plasma", "scalars")
-        expected = tardis_ref_data[key][attr]
-        assert_almost_equal(actual, expected)
+        if isinstance(actual, (pd.DataFrame, pd.Series)):
+            assert snapshot_pd == actual
+        else:
+            assert snapshot_np == actual
 
-    def test_helium_treatment(self, plasma, tardis_ref_data, config):
+    def test_helium_treatment(self, plasma, snapshot):
         actual = plasma.helium_treatment
-        key = os.path.join(config.plasma.save_path, "plasma", "scalars")
-        expected = tardis_ref_data[key]["helium_treatment"]
-        assert actual == expected
+        assert snapshot == actual
 
-    def test_zeta_data(self, plasma, tardis_ref_data, config):
+    def test_zeta_data(self, plasma, snapshot_np):
         if hasattr(plasma, "zeta_data"):
             actual = plasma.zeta_data
-            key = os.path.join(config.plasma.save_path, "plasma", "zeta_data")
-            expected = tardis_ref_data[key]
-            assert_almost_equal(actual, expected.values)
+            assert snapshot_np == actual.values
diff --git a/tardis/plasma/tests/test_hdf_plasma.py b/tardis/plasma/tests/test_hdf_plasma.py
index 00edec980d2..01c91cb386b 100644
--- a/tardis/plasma/tests/test_hdf_plasma.py
+++ b/tardis/plasma/tests/test_hdf_plasma.py
@@ -1,21 +1,11 @@
-import os
 import pandas as pd
 import pytest
 
-from numpy.testing import assert_almost_equal
-import pandas.testing as pdt
-from tardis.plasma.properties import property_collections
-
 ###
 # saving and loading of plasma properties in the HDF file
 ###
 
 
-@pytest.fixture(scope="module", autouse=True)
-def to_hdf_buffer(hdf_file_path, simulation_verysimple):
-    simulation_verysimple.plasma.to_hdf(hdf_file_path, overwrite=True)
-
-
 plasma_properties_list = [
     "number_density",
     "beta_rad",
@@ -53,70 +43,48 @@ def to_hdf_buffer(hdf_file_path, simulation_verysimple):
 
 
 @pytest.mark.parametrize("attr", plasma_properties_list)
-def test_hdf_plasma(hdf_file_path, simulation_verysimple, attr):
+def test_hdf_plasma(simulation_verysimple, attr, snapshot_np):
     if hasattr(simulation_verysimple.plasma, attr):
         actual = getattr(simulation_verysimple.plasma, attr)
         if hasattr(actual, "cgs"):
             actual = actual.cgs.value
-        path = os.path.join("plasma", attr)
-        expected = pd.read_hdf(hdf_file_path, path)
-        assert_almost_equal(actual, expected.values)
+        assert snapshot_np == actual
 
 
-def test_hdf_levels(hdf_file_path, simulation_verysimple):
+def test_hdf_levels(simulation_verysimple, snapshot_pd):
     actual = getattr(simulation_verysimple.plasma, "levels")
     if hasattr(actual, "cgs"):
         actual = actual.cgs.value
-    path = os.path.join("plasma", "levels")
-    expected = pd.read_hdf(hdf_file_path, path)
-    pdt.assert_frame_equal(pd.DataFrame(actual), expected)
+    assert snapshot_pd == pd.DataFrame(actual)
 
 
 scalars_list = ["time_explosion", "link_t_rad_t_electron"]
 
 
 @pytest.mark.parametrize("attr", scalars_list)
-def test_hdf_scalars(hdf_file_path, simulation_verysimple, attr):
+def test_hdf_scalars(simulation_verysimple, attr, snapshot_np):
     actual = getattr(simulation_verysimple.plasma, attr)
     if hasattr(actual, "cgs"):
         actual = actual.cgs.value
-    path = os.path.join("plasma", "scalars")
-    expected = pd.read_hdf(hdf_file_path, path)[attr]
-    assert_almost_equal(actual, expected)
+    assert snapshot_np == actual
 
 
-def test_hdf_helium_treatment(hdf_file_path, simulation_verysimple):
+def test_hdf_helium_treatment(simulation_verysimple, snapshot):
     actual = getattr(simulation_verysimple.plasma, "helium_treatment")
-    path = os.path.join("plasma", "scalars")
-    expected = pd.read_hdf(hdf_file_path, path)["helium_treatment"]
-    assert actual == expected
+    assert snapshot == actual
 
 
-def test_atomic_data_uuid(hdf_file_path, simulation_verysimple):
+def test_atomic_data_uuid(simulation_verysimple, snapshot):
     actual = getattr(simulation_verysimple.plasma.atomic_data, "uuid1")
-    path = os.path.join("plasma", "scalars")
-    expected = pd.read_hdf(hdf_file_path, path)["atom_data_uuid"]
-    assert actual == expected
-
-
-@pytest.fixture(scope="module", autouse=True)
-def to_hdf_collection_buffer(hdf_file_path, simulation_verysimple):
-    simulation_verysimple.plasma.to_hdf(
-        hdf_file_path,
-        name="collection",
-        collection=property_collections.basic_inputs,
-        overwrite=True,
-    )
+    assert snapshot == actual
 
 
 collection_properties = ["t_rad", "w", "density"]
 
 
 @pytest.mark.parametrize("attr", collection_properties)
-def test_collection(hdf_file_path, simulation_verysimple, attr):
+def test_collection(simulation_verysimple, attr, snapshot_np):
     actual = getattr(simulation_verysimple.plasma, attr)
     if hasattr(actual, "cgs"):
         actual = actual.cgs.value
-    path = os.path.join("collection", attr)
-    expected = pd.read_hdf(hdf_file_path, path)
-    assert_almost_equal(actual, expected.values)
+    assert snapshot_np == actual
diff --git a/tardis/plasma/tests/test_nlte_excitation.py b/tardis/plasma/tests/test_nlte_excitation.py
index 657d49711c0..884f28af20a 100644
--- a/tardis/plasma/tests/test_nlte_excitation.py
+++ b/tardis/plasma/tests/test_nlte_excitation.py
@@ -1,18 +1,14 @@
-import pandas as pd
 import numpy as np
+import pandas as pd
 import pytest
-from numpy.testing import assert_allclose
-
 
+from tardis.plasma.properties.nlte_excitation_data import NLTEExcitationData
 from tardis.plasma.properties.nlte_rate_equation_solver import (
     NLTERateEquationSolver,
 )
-from tardis.plasma.properties.nlte_excitation_data import NLTEExcitationData
 
 
-def test_prepare_bound_bound_rate_matrix(
-    nlte_atomic_dataset,
-):
+def test_prepare_bound_bound_rate_matrix(nlte_atomic_dataset, snapshot_np):
     """
     Using a simple case of nlte_exc for HI, checks if prepare_bound_bound_rate_matrix generates the correct data.
     """
@@ -73,50 +69,10 @@ def test_prepare_bound_bound_rate_matrix(
         r_lu_matrix,
         simple_beta_sobolev,
     )
-    desired_rate_matrix = [
-        [
-            [-4.41229578e10],
-            [1.09803977e10],
-            [8.87031593e08],
-            [1.83520728e08],
-            [5.71742068e07],
-        ],
-        [
-            [3.54409576e10],
-            [-3.64473689e11],
-            [1.32571818e11],
-            [1.04228424e10],
-            [2.27047121e09],
-        ],
-        [
-            [5.71505717e09],
-            [2.97836962e11],
-            [-1.41199954e12],
-            [6.39719360e11],
-            [5.08905487e10],
-        ],
-        [
-            [2.00818482e09],
-            [4.15382182e10],
-            [1.13720607e12],
-            [-3.74593514e12],
-            [1.98120242e12],
-        ],
-        [
-            [9.58758249e08],
-            [1.41181112e10],
-            [1.41334621e11],
-            [3.09560941e12],
-            [-2.03442061e12],
-        ],
-    ]
     # if this test fails the first thing to check is if the reshape in the
     # methods made a view or a copy. If it's a copy rewrite the function.
-    assert_allclose(
-        desired_rate_matrix,
-        np.array(actual_rate_matrix),
-        rtol=1e-6,
-    )
+    # TODO: allow rtol=1e-6
+    assert snapshot_np == np.array(actual_rate_matrix)
 
 
 @pytest.mark.parametrize(
@@ -124,24 +80,17 @@ def test_prepare_bound_bound_rate_matrix(
         "coll_exc_coeff_values",
         "coll_deexc_coeff_values",
         "number_of_levels",
-        "desired_coeff_matrix",
     ],
     [
         (
             [1, -2, 3],
             [4, 9, 10],
             3,
-            [[1.0, 4.0, 9.0], [1.0, -7.0, 10.0], [-2.0, 3.0, -19.0]],
         ),
         (
             [0.21, 0.045, 0.1234],
             [0.7865, 0.987, 0.00123],
             3,
-            [
-                [-0.255, 0.7865, 0.987],
-                [0.21, -0.9099, 0.00123],
-                [0.045, 0.1234, -0.98823],
-            ],
         ),
     ],
 )
@@ -149,7 +98,7 @@ def test_coll_exc_deexc_matrix(
     coll_exc_coeff_values,
     coll_deexc_coeff_values,
     number_of_levels,
-    desired_coeff_matrix,
+    snapshot_np,
 ):
     """
     Checks the NLTERateEquationSolver.create_coll_exc_deexc_matrix for simple values of species with 3 levels.
@@ -164,4 +113,4 @@ def test_coll_exc_deexc_matrix(
     obtained_coeff_matrix = NLTERateEquationSolver.create_coll_exc_deexc_matrix(
         exc_coeff, deexc_coeff, number_of_levels
     )
-    assert_allclose(obtained_coeff_matrix, desired_coeff_matrix)
+    assert snapshot_np == obtained_coeff_matrix
diff --git a/tardis/plasma/tests/test_nlte_solver.py b/tardis/plasma/tests/test_nlte_solver.py
index fe47b496e97..fa89a9aab52 100644
--- a/tardis/plasma/tests/test_nlte_solver.py
+++ b/tardis/plasma/tests/test_nlte_solver.py
@@ -1,14 +1,9 @@
-import os
-
-import pytest
 import numpy as np
 import pandas as pd
-from copy import deepcopy
-from numpy.testing import assert_allclose, assert_almost_equal
-from tardis.io.configuration.config_reader import Configuration
-from tardis.model.base import SimulationState
+import pytest
+from numpy.testing import assert_allclose
+
 from tardis.plasma.properties import NLTERateEquationSolver
-from tardis.io.atom_data.base import AtomData
 from tardis.plasma.properties.ion_population import IonNumberDensity
 from tardis.plasma.standard_plasmas import assemble_plasma
 
@@ -144,6 +139,7 @@ def test_rate_matrix(
     simple_total_rad_recomb_coefficients,
     simple_total_col_ion_coefficients,
     simple_total_col_recomb_coefficients,
+    snapshot_np,
 ):
     """
     Using a simple case of nlte_ion for HI and HeII, checks if the calculate_rate_matrix generates the correct data.
@@ -159,18 +155,9 @@ def test_rate_matrix(
         simple_total_col_ion_coefficients,
         simple_total_col_recomb_coefficients,
     )
-    desired_rate_matrix = [
-        [-0.077601, 0.099272, 0.000000, 0.000000, 0.000000, 0.0],
-        [1.000000, 1.000000, 0.000000, 0.000000, 0.000000, 0.0],
-        [0.000000, 0.000000, -0.157263, 0.221960, 0.000000, 0.0],
-        [0.000000, 0.000000, 0.000000, -0.834623, 0.161479, 0.0],
-        [0.000000, 0.000000, 1.000000, 1.000000, 1.000000, 0.0],
-        [0.000000, 1.000000, 0.000000, 1.000000, 2.000000, -1.0],
-    ]
-
-    assert_almost_equal(
-        desired_rate_matrix, np.array(actual_rate_matrix), decimal=6
-    )
+    # TODO: decimal=6
+    # allow for assert_almost_equal
+    assert snapshot_np == np.array(actual_rate_matrix)
 
 
 def test_jacobian_matrix(
@@ -181,6 +168,7 @@ def test_jacobian_matrix(
     simple_total_rad_recomb_coefficients,
     simple_total_col_ion_coefficients,
     simple_total_col_recomb_coefficients,
+    snapshot_np,
 ):
     """
     Using a simple case of nlte_ion for HI and HeII,
@@ -217,15 +205,8 @@ def test_jacobian_matrix(
         simple_total_col_recomb_coefficients,
     )
 
-    desired_jacobian_matrix = [
-        [-0.07760098, 0.09927163, 0.0, 0.0, 0.0, 0.23467404],
-        [1.0, 1.0, 0.0, 0.0, 0.0, 0.0],
-        [0.0, 0.0, -0.15726292, 0.22196045, 0.0, 0.04022076],
-        [0.0, 0.0, 0.0, -0.8346228, 0.16147935, 0.20061248],
-        [0.0, 0.0, 1.0, 1.0, 1.0, 0.0],
-        [0.0, 1.0, 0.0, 1.0, 2.0, -1.0],
-    ]
-    assert_almost_equal(actual_jacobian_matrix, desired_jacobian_matrix)
+    # TODO: allow for assert_almost_equal
+    assert snapshot_np == actual_jacobian_matrix
 
 
 @pytest.fixture
@@ -260,7 +241,7 @@ def nlte_raw_plasma_w0(
 
 def test_critical_case_w1(nlte_raw_plasma_w1):
     """Check that the LTE and NLTE solution agree for w=1.0."""
-    ion_number_density_nlte = nlte_raw_plasma_w1.ion_number_density_nlte.values
+    ion_number_density_nlte = nlte_raw_plasma_w1.ion_number_density.values
     ion_number_density_nlte[ion_number_density_nlte < 1e-10] = 0.0
 
     ind = IonNumberDensity(nlte_raw_plasma_w1)
diff --git a/tardis/plasma/tests/test_plasma_contiuum.py b/tardis/plasma/tests/test_plasma_contiuum.py
index 083e5fd65cd..633b47a8036 100644
--- a/tardis/plasma/tests/test_plasma_contiuum.py
+++ b/tardis/plasma/tests/test_plasma_contiuum.py
@@ -1,11 +1,9 @@
-import pytest
 import numpy as np
-from numpy.testing import assert_allclose
+
 from tardis.plasma.properties import YgData
 
 
-def test_exp1_times_exp():
+def test_exp1_times_exp(snapshot_np):
     x = np.array([499.0, 501.0, 710.0])
-    desired = np.array([0.00200000797, 0.0019920397, 0.0014064725])
     actual = YgData.exp1_times_exp(x)
-    assert_allclose(actual, desired)
+    assert snapshot_np == actual
diff --git a/tardis/plasma/tests/test_plasma_vboundary.py b/tardis/plasma/tests/test_plasma_vboundary.py
index 3ea2a53f7f5..af48ac49355 100644
--- a/tardis/plasma/tests/test_plasma_vboundary.py
+++ b/tardis/plasma/tests/test_plasma_vboundary.py
@@ -1,10 +1,10 @@
-import tardis
-import pytest
 import os
+
 import astropy.units as u
+import pytest
 
+import tardis
 from tardis.io.configuration.config_reader import Configuration
-from tardis.io.atom_data.base import AtomData
 from tardis.simulation import Simulation
 
 DATA_PATH = os.path.join(tardis.__path__[0], "plasma", "tests", "data")
diff --git a/tardis/plasma/tests/test_tardis_model_density_config.py b/tardis/plasma/tests/test_tardis_model_density_config.py
index 6bb6ff6dbdf..f3d37dc35a0 100644
--- a/tardis/plasma/tests/test_tardis_model_density_config.py
+++ b/tardis/plasma/tests/test_tardis_model_density_config.py
@@ -3,7 +3,6 @@
 from tardis.io.configuration.config_reader import Configuration
 from tardis.model import SimulationState
 from tardis.plasma.standard_plasmas import assemble_plasma
-from numpy.testing import assert_almost_equal
 
 
 @pytest.fixture
@@ -25,20 +24,16 @@ def raw_plasma(tardis_model_density_config, raw_model, kurucz_atomic_data):
     )
 
 
-def test_electron_densities(raw_plasma):
-    assert_almost_equal(raw_plasma.electron_densities[8], 2.72e14)
-    assert_almost_equal(raw_plasma.electron_densities[3], 2.6e14)
+def test_electron_densities(raw_plasma, snapshot_np):
+    assert snapshot_np == raw_plasma.electron_densities[8]
+    assert snapshot_np == raw_plasma.electron_densities[3]
 
 
-def test_isotope_number_densities(raw_plasma):
-    assert_almost_equal(
-        raw_plasma.isotope_number_density.loc[(28, 56), 0], 9688803936.317898
-    )
-    assert_almost_equal(
-        raw_plasma.isotope_number_density.loc[(28, 58), 1], 13097656958.746628
-    )
+def test_isotope_number_densities(raw_plasma, snapshot_np):
+    assert snapshot_np == raw_plasma.isotope_number_density.loc[(28, 56), 0]
+    assert snapshot_np == raw_plasma.isotope_number_density.loc[(28, 58), 1]
 
 
-def test_t_rad(raw_plasma):
-    assert_almost_equal(raw_plasma.t_rad[5], 76459.592)
-    assert_almost_equal(raw_plasma.t_rad[3], 76399.042)
+def test_t_rad(raw_plasma, snapshot_np):
+    assert snapshot_np == raw_plasma.t_rad[5]
+    assert snapshot_np == raw_plasma.t_rad[3]
diff --git a/tardis/util/syrupy_extensions.py b/tardis/util/syrupy_extensions.py
new file mode 100644
index 00000000000..050fca3a1bc
--- /dev/null
+++ b/tardis/util/syrupy_extensions.py
@@ -0,0 +1,129 @@
+import re
+from typing import Any, List, Tuple
+
+import numpy as np
+import pandas as pd
+from syrupy.data import SnapshotCollection
+from syrupy.extensions.single_file import SingleFileSnapshotExtension, WriteMode
+from syrupy.location import PyTestLocation
+from syrupy.types import SerializableData, SnapshotIndex
+
+
+class SingleFileSanitizedNames(SingleFileSnapshotExtension):
+    # changing write mode to text helps avoid an error message
+    # that comes when files are serialised in syrupy in bytes
+    # either way we won't be serialising files in most cases in bytes
+    _write_mode = WriteMode.TEXT
+    _file_extension = "txt"
+
+    # would change names of all snapshots generated
+    # that use this class- making filenames compliant with python standards.
+    @classmethod
+    def get_snapshot_name(
+        cls, *, test_location: "PyTestLocation", index: "SnapshotIndex"
+    ) -> str:
+        original_name = SingleFileSnapshotExtension.get_snapshot_name(
+            test_location=test_location, index=index
+        )
+        double_under = r"[:\[\]{}]"
+        no_space = r'[,"\']'  # quotes and commas
+
+        name = re.sub(double_under, "__", original_name)
+        name = re.sub(no_space, "", name)
+
+        return f"{name}"
+
+
+class NumpySnapshotExtenstion(SingleFileSanitizedNames):
+    _file_extension = "npy"
+
+    def matches(self, *, serialized_data, snapshot_data):
+        try:
+            if (
+                np.testing.assert_allclose(
+                    np.array(snapshot_data), np.array(serialized_data)
+                )
+                is not None
+            ):
+                return False
+            else:
+                return True
+
+        except:
+            return False
+
+    def _read_snapshot_data_from_location(
+        self, *, snapshot_location: str, snapshot_name: str, session_id: str
+    ):
+        # see https://github.com/tophat/syrupy/blob/f4bc8453466af2cfa75cdda1d50d67bc8c4396c3/src/syrupy/extensions/base.py#L139
+        try:
+            return np.load(snapshot_location)
+
+        except OSError:
+            return None
+
+    @classmethod
+    def _write_snapshot_collection(
+        cls, *, snapshot_collection: SnapshotCollection
+    ) -> None:
+        # see https://github.com/tophat/syrupy/blob/f4bc8453466af2cfa75cdda1d50d67bc8c4396c3/src/syrupy/extensions/base.py#L161
+
+        filepath, data = (
+            snapshot_collection.location,
+            next(iter(snapshot_collection)).data,
+        )
+
+        np.save(filepath, data)
+
+    def serialize(self, data: SerializableData, **kwargs: Any) -> str:
+        return data
+
+
+class PandasSnapshotExtenstion(SingleFileSanitizedNames):
+    _file_extension = "h5"
+
+    def matches(self, *, serialized_data, snapshot_data):
+        try:
+            comparer = {
+                pd.Series: pd.testing.assert_series_equal,
+                pd.DataFrame: pd.testing.assert_frame_equal,
+            }
+            try:
+                comp_func = comparer[type(serialized_data)]
+            except KeyError:
+                raise ValueError(
+                    "Can only compare Series and Dataframes with PandasSnapshotExtenstion."
+                )
+
+            if comp_func(serialized_data, snapshot_data) is not None:
+                return False
+            else:
+                return True
+
+        except:
+            return False
+
+    def _read_snapshot_data_from_location(
+        self, *, snapshot_location: str, snapshot_name: str, session_id: str
+    ):
+        # see https://github.com/tophat/syrupy/blob/f4bc8453466af2cfa75cdda1d50d67bc8c4396c3/src/syrupy/extensions/base.py#L139
+        try:
+            data = pd.read_hdf(snapshot_location)
+            return data
+
+        except OSError:
+            return None
+
+    @classmethod
+    def _write_snapshot_collection(
+        cls, *, snapshot_collection: SnapshotCollection
+    ) -> None:
+        # see https://github.com/tophat/syrupy/blob/f4bc8453466af2cfa75cdda1d50d67bc8c4396c3/src/syrupy/extensions/base.py#L161
+        filepath, data = (
+            snapshot_collection.location,
+            next(iter(snapshot_collection)).data,
+        )
+        data.to_hdf(filepath, "/data")
+
+    def serialize(self, data: SerializableData, **kwargs: Any) -> str:
+        return data
diff --git a/tardis_env3.yml b/tardis_env3.yml
index efa0e7b399e..99224c10a23 100644
--- a/tardis_env3.yml
+++ b/tardis_env3.yml
@@ -68,9 +68,11 @@ dependencies:
   - pytest-html
   - python-dokuwiki
   - coverage
+  - syrupy
 
   # Code quality
   - black =22.3
 
   # Other
   - git-lfs
+