diff --git a/poetry.lock b/poetry.lock
index be36f89..34956a7 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -11,15 +11,26 @@ files = [
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 ]
 
+[[package]]
+name = "alabaster"
+version = "0.7.16"
+description = "A light, configurable Sphinx theme"
+optional = false
+python-versions = ">=3.9"
+files = [
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+]
+
 [[package]]
 name = "arviz"
-version = "0.17.0"
+version = "0.17.1"
 description = "Exploratory analysis of Bayesian models"
 optional = false
 python-versions = ">=3.9"
 files = [
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 ]
 
 [package.dependencies]
@@ -37,35 +48,115 @@ xarray-einstats = ">=0.3"
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+[[package]]
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 [package.dependencies]
@@ -83,121 +174,125 @@ d = ["aiohttp (>=3.7.4)", "aiohttp (>=3.7.4,!=3.9.0)"]
 jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"]
 uvloop = ["uvloop (>=0.15.2)"]
 
-[[package]]
-name = "cachetools"
-version = "5.3.2"
-description = "Extensible memoizing collections and decorators"
-optional = false
-python-versions = ">=3.7"
-files = [
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-]
-
 [[package]]
 name = "certifi"
-version = "2023.5.7"
+version = "2024.6.2"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
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 ]
 
 [[package]]
 name = "cfgv"
-version = "3.3.1"
+version = "3.4.0"
 description = "Validate configuration and produce human readable error messages."
 optional = false
-python-versions = ">=3.6.1"
+python-versions = ">=3.8"
 files = [
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 ]
 
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 [[package]]
@@ -227,134 +322,126 @@ files = [
 
 [[package]]
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 optional = false
 python-versions = ">=3.9"
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@@ -378,26 +465,71 @@ files = [
 docs = ["ipython", "matplotlib", "numpydoc", "sphinx"]
 tests = ["pytest", "pytest-cov", "pytest-xdist"]
 
+[[package]]
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+description = "Physics Benchmark Dataset Generator"
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+python-versions = ">=3.8,<4.0"
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+h5py = ">=3.9.0"
+matplotlib = ">=3.7.1,<4.0.0"
+numpy = ">=1.24.3,<2.0.0"
+pyyaml = ">=6.0,<7.0"
+scikit-image = ">=0.20.0,<0.21.0"
+
+[[package]]
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+version = "2.1.0"
+description = "A library to handle automated deprecations"
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+python-versions = "*"
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+[package.dependencies]
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+
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 name = "exceptiongroup"
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 description = "Backport of PEP 654 (exception groups)"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.extras]
@@ -405,18 +537,19 @@ test = ["pytest (>=6)"]
 
 [[package]]
 name = "filelock"
-version = "3.12.1"
+version = "3.14.0"
 description = "A platform independent file lock."
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+typing = ["typing-extensions (>=4.8)"]
 
 [[package]]
 name = "flake8"
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 [package.extras]
-all = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "fs (>=2.2.0,<3)", "lxml (>=4.0,<5)", "lz4 (>=1.7.4.2)", "matplotlib", "munkres", "pycairo", "scipy", "skia-pathops (>=0.5.0)", "sympy", "uharfbuzz (>=0.23.0)", "unicodedata2 (>=15.1.0)", "xattr", "zopfli (>=0.1.4)"]
+all = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "fs (>=2.2.0,<3)", "lxml (>=4.0)", "lz4 (>=1.7.4.2)", "matplotlib", "munkres", "pycairo", "scipy", "skia-pathops (>=0.5.0)", "sympy", "uharfbuzz (>=0.23.0)", "unicodedata2 (>=15.1.0)", "xattr", "zopfli (>=0.1.4)"]
 graphite = ["lz4 (>=1.7.4.2)"]
 interpolatable = ["munkres", "pycairo", "scipy"]
-lxml = ["lxml (>=4.0,<5)"]
+lxml = ["lxml (>=4.0)"]
 pathops = ["skia-pathops (>=0.5.0)"]
 plot = ["matplotlib"]
 repacker = ["uharfbuzz (>=0.23.0)"]
@@ -501,13 +634,13 @@ woff = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "zopfli (>=0.1.4)"]
 
 [[package]]
 name = "fsspec"
-version = "2023.12.2"
+version = "2024.6.0"
 description = "File-system specification"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.extras]
@@ -515,7 +648,8 @@ abfs = ["adlfs"]
 adl = ["adlfs"]
 arrow = ["pyarrow (>=1)"]
 dask = ["dask", "distributed"]
-devel = ["pytest", "pytest-cov"]
+dev = ["pre-commit", "ruff"]
+doc = ["numpydoc", "sphinx", "sphinx-design", "sphinx-rtd-theme", "yarl"]
 dropbox = ["dropbox", "dropboxdrivefs", "requests"]
 full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "dask", "distributed", "dropbox", "dropboxdrivefs", "fusepy", "gcsfs", "libarchive-c", "ocifs", "panel", "paramiko", "pyarrow (>=1)", "pygit2", "requests", "s3fs", "smbprotocol", "tqdm"]
 fuse = ["fusepy"]
@@ -525,23 +659,37 @@ github = ["requests"]
 gs = ["gcsfs"]
 gui = ["panel"]
 hdfs = ["pyarrow (>=1)"]
-http = ["aiohttp (!=4.0.0a0,!=4.0.0a1)", "requests"]
+http = ["aiohttp (!=4.0.0a0,!=4.0.0a1)"]
 libarchive = ["libarchive-c"]
 oci = ["ocifs"]
 s3 = ["s3fs"]
 sftp = ["paramiko"]
 smb = ["smbprotocol"]
 ssh = ["paramiko"]
+test = ["aiohttp (!=4.0.0a0,!=4.0.0a1)", "numpy", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "requests"]
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+test-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "cloudpickle", "dask", "distributed", "dropbox", "dropboxdrivefs", "fastparquet", "fusepy", "gcsfs", "jinja2", "kerchunk", "libarchive-c", "lz4", "notebook", "numpy", "ocifs", "pandas", "panel", "paramiko", "pyarrow", "pyarrow (>=1)", "pyftpdlib", "pygit2", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "python-snappy", "requests", "smbprotocol", "tqdm", "urllib3", "zarr", "zstandard"]
 tqdm = ["tqdm"]
 
+[[package]]
+name = "future"
+version = "1.0.0"
+description = "Clean single-source support for Python 3 and 2"
+optional = false
+python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
+files = [
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+]
+
 [[package]]
 name = "getdist"
-version = "1.4.7"
+version = "1.4.9"
 description = "GetDist Monte Carlo sample analysis, plotting and GUI"
 optional = false
 python-versions = ">=3.7.0"
 files = [
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 ]
 
 [package.dependencies]
@@ -555,112 +703,63 @@ scipy = ">=1.5"
 docs = ["sphinx", "sphinx_rtd_theme (>=1.0)", "sphinxcontrib-jquery"]
 gui = ["PySide6 (>=6.1)"]
 
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-description = "Google Authentication Library"
-optional = false
-python-versions = ">=3.7"
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-
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-pyasn1-modules = ">=0.2.1"
-rsa = ">=3.1.4,<5"
-
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-reauth = ["pyu2f (>=0.1.5)"]
-requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
-
-[[package]]
-name = "google-auth-oauthlib"
-version = "1.2.0"
-description = "Google Authentication Library"
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-python-versions = ">=3.6"
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-
-[package.extras]
-tool = ["click (>=6.0.0)"]
-
 [[package]]
 name = "grpcio"
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+    {file = "h5py-3.11.0.tar.gz", hash = "sha256:7b7e8f78072a2edec87c9836f25f34203fd492a4475709a18b417a33cfb21fa9"},
 ]
 
 [package.dependencies]
@@ -719,13 +814,13 @@ numpy = ">=1.17.3"
 
 [[package]]
 name = "identify"
-version = "2.5.24"
+version = "2.5.36"
 description = "File identification library for Python"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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+    {file = "identify-2.5.36-py2.py3-none-any.whl", hash = "sha256:37d93f380f4de590500d9dba7db359d0d3da95ffe7f9de1753faa159e71e7dfa"},
+    {file = "identify-2.5.36.tar.gz", hash = "sha256:e5e00f54165f9047fbebeb4a560f9acfb8af4c88232be60a488e9b68d122745d"},
 ]
 
 [package.extras]
@@ -733,43 +828,86 @@ license = ["ukkonen"]
 
 [[package]]
 name = "idna"
-version = "3.4"
+version = "3.7"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
 python-versions = ">=3.5"
 files = [
-    {file = "idna-3.4-py3-none-any.whl", hash = "sha256:90b77e79eaa3eba6de819a0c442c0b4ceefc341a7a2ab77d7562bf49f425c5c2"},
-    {file = "idna-3.4.tar.gz", hash = "sha256:814f528e8dead7d329833b91c5faa87d60bf71824cd12a7530b5526063d02cb4"},
+    {file = "idna-3.7-py3-none-any.whl", hash = "sha256:82fee1fc78add43492d3a1898bfa6d8a904cc97d8427f683ed8e798d07761aa0"},
+    {file = "idna-3.7.tar.gz", hash = "sha256:028ff3aadf0609c1fd278d8ea3089299412a7a8b9bd005dd08b9f8285bcb5cfc"},
+]
+
+[[package]]
+name = "imageio"
+version = "2.34.1"
+description = "Library for reading and writing a wide range of image, video, scientific, and volumetric data formats."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "imageio-2.34.1-py3-none-any.whl", hash = "sha256:408c1d4d62f72c9e8347e7d1ca9bc11d8673328af3913868db3b828e28b40a4c"},
+    {file = "imageio-2.34.1.tar.gz", hash = "sha256:f13eb76e4922f936ac4a7fec77ce8a783e63b93543d4ea3e40793a6cabd9ac7d"},
+]
+
+[package.dependencies]
+numpy = "*"
+pillow = ">=8.3.2"
+
+[package.extras]
+all-plugins = ["astropy", "av", "imageio-ffmpeg", "pillow-heif", "psutil", "tifffile"]
+all-plugins-pypy = ["av", "imageio-ffmpeg", "pillow-heif", "psutil", "tifffile"]
+build = ["wheel"]
+dev = ["black", "flake8", "fsspec[github]", "pytest", "pytest-cov"]
+docs = ["numpydoc", "pydata-sphinx-theme", "sphinx (<6)"]
+ffmpeg = ["imageio-ffmpeg", "psutil"]
+fits = ["astropy"]
+full = ["astropy", "av", "black", "flake8", "fsspec[github]", "gdal", "imageio-ffmpeg", "itk", "numpydoc", "pillow-heif", "psutil", "pydata-sphinx-theme", "pytest", "pytest-cov", "sphinx (<6)", "tifffile", "wheel"]
+gdal = ["gdal"]
+itk = ["itk"]
+linting = ["black", "flake8"]
+pillow-heif = ["pillow-heif"]
+pyav = ["av"]
+test = ["fsspec[github]", "pytest", "pytest-cov"]
+tifffile = ["tifffile"]
+
+[[package]]
+name = "imagesize"
+version = "1.4.1"
+description = "Getting image size from png/jpeg/jpeg2000/gif file"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+files = [
+    {file = "imagesize-1.4.1-py2.py3-none-any.whl", hash = "sha256:0d8d18d08f840c19d0ee7ca1fd82490fdc3729b7ac93f49870406ddde8ef8d8b"},
+    {file = "imagesize-1.4.1.tar.gz", hash = "sha256:69150444affb9cb0d5cc5a92b3676f0b2fb7cd9ae39e947a5e11a36b4497cd4a"},
 ]
 
 [[package]]
 name = "importlib-metadata"
-version = "7.0.1"
+version = "7.1.0"
 description = "Read metadata from Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "importlib_metadata-7.0.1-py3-none-any.whl", hash = "sha256:4805911c3a4ec7c3966410053e9ec6a1fecd629117df5adee56dfc9432a1081e"},
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+    {file = "importlib_metadata-7.1.0-py3-none-any.whl", hash = "sha256:30962b96c0c223483ed6cc7280e7f0199feb01a0e40cfae4d4450fc6fab1f570"},
+    {file = "importlib_metadata-7.1.0.tar.gz", hash = "sha256:b78938b926ee8d5f020fc4772d487045805a55ddbad2ecf21c6d60938dc7fcd2"},
 ]
 
 [package.dependencies]
 zipp = ">=0.5"
 
 [package.extras]
-docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"]
+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
 perf = ["ipython"]
-testing = ["flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)", "pytest-ruff"]
+testing = ["flufl.flake8", "importlib-resources (>=1.3)", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy", "pytest-perf (>=0.9.2)", "pytest-ruff (>=0.2.1)"]
 
 [[package]]
 name = "importlib-resources"
-version = "6.1.1"
+version = "6.4.0"
 description = "Read resources from Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "importlib_resources-6.1.1-py3-none-any.whl", hash = "sha256:e8bf90d8213b486f428c9c39714b920041cb02c184686a3dee24905aaa8105d6"},
-    {file = "importlib_resources-6.1.1.tar.gz", hash = "sha256:3893a00122eafde6894c59914446a512f728a0c1a45f9bb9b63721b6bacf0b4a"},
+    {file = "importlib_resources-6.4.0-py3-none-any.whl", hash = "sha256:50d10f043df931902d4194ea07ec57960f66a80449ff867bfe782b4c486ba78c"},
+    {file = "importlib_resources-6.4.0.tar.gz", hash = "sha256:cdb2b453b8046ca4e3798eb1d84f3cce1446a0e8e7b5ef4efb600f19fc398145"},
 ]
 
 [package.dependencies]
@@ -777,7 +915,7 @@ zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""}
 
 [package.extras]
 docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"]
-testing = ["pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-ruff", "zipp (>=3.17)"]
+testing = ["jaraco.test (>=5.4)", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy", "pytest-ruff (>=0.2.1)", "zipp (>=3.17)"]
 
 [[package]]
 name = "iniconfig"
@@ -790,15 +928,29 @@ files = [
     {file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"},
 ]
 
+[[package]]
+name = "intel-openmp"
+version = "2021.4.0"
+description = "Intel OpenMP* Runtime Library"
+optional = false
+python-versions = "*"
+files = [
+    {file = "intel_openmp-2021.4.0-py2.py3-none-macosx_10_15_x86_64.macosx_11_0_x86_64.whl", hash = "sha256:41c01e266a7fdb631a7609191709322da2bbf24b252ba763f125dd651bcc7675"},
+    {file = "intel_openmp-2021.4.0-py2.py3-none-manylinux1_i686.whl", hash = "sha256:3b921236a38384e2016f0f3d65af6732cf2c12918087128a9163225451e776f2"},
+    {file = "intel_openmp-2021.4.0-py2.py3-none-manylinux1_x86_64.whl", hash = "sha256:e2240ab8d01472fed04f3544a878cda5da16c26232b7ea1b59132dbfb48b186e"},
+    {file = "intel_openmp-2021.4.0-py2.py3-none-win32.whl", hash = "sha256:6e863d8fd3d7e8ef389d52cf97a50fe2afe1a19247e8c0d168ce021546f96fc9"},
+    {file = "intel_openmp-2021.4.0-py2.py3-none-win_amd64.whl", hash = "sha256:eef4c8bcc8acefd7f5cd3b9384dbf73d59e2c99fc56545712ded913f43c4a94f"},
+]
+
 [[package]]
 name = "jinja2"
-version = "3.1.2"
+version = "3.1.4"
 description = "A very fast and expressive template engine."
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "Jinja2-3.1.2-py3-none-any.whl", hash = "sha256:6088930bfe239f0e6710546ab9c19c9ef35e29792895fed6e6e31a023a182a61"},
-    {file = "Jinja2-3.1.2.tar.gz", hash = "sha256:31351a702a408a9e7595a8fc6150fc3f43bb6bf7e319770cbc0db9df9437e852"},
+    {file = "jinja2-3.1.4-py3-none-any.whl", hash = "sha256:bc5dd2abb727a5319567b7a813e6a2e7318c39f4f487cfe6c89c6f9c7d25197d"},
+    {file = "jinja2-3.1.4.tar.gz", hash = "sha256:4a3aee7acbbe7303aede8e9648d13b8bf88a429282aa6122a993f0ac800cb369"},
 ]
 
 [package.dependencies]
@@ -809,13 +961,13 @@ i18n = ["Babel (>=2.7)"]
 
 [[package]]
 name = "joblib"
-version = "1.3.2"
+version = "1.4.2"
 description = "Lightweight pipelining with Python functions"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "joblib-1.3.2-py3-none-any.whl", hash = "sha256:ef4331c65f239985f3f2220ecc87db222f08fd22097a3dd5698f693875f8cbb9"},
-    {file = "joblib-1.3.2.tar.gz", hash = "sha256:92f865e621e17784e7955080b6d042489e3b8e294949cc44c6eac304f59772b1"},
+    {file = "joblib-1.4.2-py3-none-any.whl", hash = "sha256:06d478d5674cbc267e7496a410ee875abd68e4340feff4490bcb7afb88060ae6"},
+    {file = "joblib-1.4.2.tar.gz", hash = "sha256:2382c5816b2636fbd20a09e0f4e9dad4736765fdfb7dca582943b9c1366b3f0e"},
 ]
 
 [[package]]
@@ -931,15 +1083,34 @@ files = [
     {file = "kiwisolver-1.4.5.tar.gz", hash = "sha256:e57e563a57fb22a142da34f38acc2fc1a5c864bc29ca1517a88abc963e60d6ec"},
 ]
 
+[[package]]
+name = "lazy-loader"
+version = "0.4"
+description = "Makes it easy to load subpackages and functions on demand."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "lazy_loader-0.4-py3-none-any.whl", hash = "sha256:342aa8e14d543a154047afb4ba8ef17f5563baad3fc610d7b15b213b0f119efc"},
+    {file = "lazy_loader-0.4.tar.gz", hash = "sha256:47c75182589b91a4e1a85a136c074285a5ad4d9f39c63e0d7fb76391c4574cd1"},
+]
+
+[package.dependencies]
+packaging = "*"
+
+[package.extras]
+dev = ["changelist (==0.5)"]
+lint = ["pre-commit (==3.7.0)"]
+test = ["pytest (>=7.4)", "pytest-cov (>=4.1)"]
+
 [[package]]
 name = "markdown"
-version = "3.5.2"
+version = "3.6"
 description = "Python implementation of John Gruber's Markdown."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "Markdown-3.5.2-py3-none-any.whl", hash = "sha256:d43323865d89fc0cb9b20c75fc8ad313af307cc087e84b657d9eec768eddeadd"},
-    {file = "Markdown-3.5.2.tar.gz", hash = "sha256:e1ac7b3dc550ee80e602e71c1d168002f062e49f1b11e26a36264dafd4df2ef8"},
+    {file = "Markdown-3.6-py3-none-any.whl", hash = "sha256:48f276f4d8cfb8ce6527c8f79e2ee29708508bf4d40aa410fbc3b4ee832c850f"},
+    {file = "Markdown-3.6.tar.gz", hash = "sha256:ed4f41f6daecbeeb96e576ce414c41d2d876daa9a16cb35fa8ed8c2ddfad0224"},
 ]
 
 [package.dependencies]
@@ -951,108 +1122,109 @@ testing = ["coverage", "pyyaml"]
 
 [[package]]
 name = "markupsafe"
-version = "2.1.3"
+version = "2.1.5"
 description = "Safely add untrusted strings to HTML/XML markup."
 optional = false
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 ]
 
 [package.dependencies]
@@ -1061,12 +1233,15 @@ cycler = ">=0.10"
 fonttools = ">=4.22.0"
 importlib-resources = {version = ">=3.2.0", markers = "python_version < \"3.10\""}
 kiwisolver = ">=1.3.1"
-numpy = ">=1.21,<2"
+numpy = ">=1.23"
 packaging = ">=20.0"
 pillow = ">=8"
 pyparsing = ">=2.3.1"
 python-dateutil = ">=2.7"
 
+[package.extras]
+dev = ["meson-python (>=0.13.1)", "numpy (>=1.25)", "pybind11 (>=2.6)", "setuptools (>=64)", "setuptools_scm (>=7)"]
+
 [[package]]
 name = "mccabe"
 version = "0.7.0"
@@ -1078,6 +1253,24 @@ files = [
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 ]
 
+[[package]]
+name = "mkl"
+version = "2021.4.0"
+description = "Intel® oneAPI Math Kernel Library"
+optional = false
+python-versions = "*"
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+]
+
+[package.dependencies]
+intel-openmp = "==2021.*"
+tbb = "==2021.*"
+
 [[package]]
 name = "mpmath"
 version = "1.3.0"
@@ -1143,61 +1336,50 @@ tqdm = "*"
 
 [[package]]
 name = "nodeenv"
-version = "1.8.0"
+version = "1.9.1"
 description = "Node.js virtual environment builder"
 optional = false
-python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*"
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 files = [
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 ]
 
-[package.dependencies]
-setuptools = "*"
-
 [[package]]
 name = "numpy"
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+version = "1.24.4"
 description = "Fundamental package for array computing in Python"
 optional = false
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 ]
 
 [[package]]
@@ -1311,23 +1493,24 @@ nvidia-nvjitlink-cu12 = "*"
 
 [[package]]
 name = "nvidia-nccl-cu12"
-version = "2.18.1"
+version = "2.20.5"
 description = "NVIDIA Collective Communication Library (NCCL) Runtime"
 optional = false
 python-versions = ">=3"
 files = [
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 ]
 
 [[package]]
 name = "nvidia-nvjitlink-cu12"
-version = "12.3.101"
+version = "12.5.40"
 description = "Nvidia JIT LTO Library"
 optional = false
 python-versions = ">=3"
 files = [
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 ]
 
 [[package]]
@@ -1341,22 +1524,6 @@ files = [
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 ]
 
-[[package]]
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-version = "3.2.2"
-description = "A generic, spec-compliant, thorough implementation of the OAuth request-signing logic"
-optional = false
-python-versions = ">=3.6"
-files = [
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-
-[package.extras]
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-signals = ["blinker (>=1.4.0)"]
-signedtoken = ["cryptography (>=3.0.0)", "pyjwt (>=2.0.0,<3)"]
-
 [[package]]
 name = "opt-einsum"
 version = "3.3.0"
@@ -1377,58 +1544,57 @@ tests = ["pytest", "pytest-cov", "pytest-pep8"]
 
 [[package]]
 name = "packaging"
-version = "23.1"
+version = "24.0"
 description = "Core utilities for Python packages"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [[package]]
 name = "pandas"
-version = "2.2.0"
+version = "2.2.2"
 description = "Powerful data structures for data analysis, time series, and statistics"
 optional = false
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 [package.dependencies]
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 pytz = ">=2020.1"
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 performance = ["bottleneck (>=1.3.6)", "numba (>=0.56.4)", "numexpr (>=2.8.4)"]
 plot = ["matplotlib (>=3.6.3)"]
 postgresql = ["SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "psycopg2 (>=2.9.6)"]
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 test = ["hypothesis (>=6.46.1)", "pytest (>=7.3.2)", "pytest-xdist (>=2.2.0)"]
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 numpy = ">=1.16.6,<2"
 
 [[package]]
-name = "pyasn1"
-version = "0.5.1"
-description = "Pure-Python implementation of ASN.1 types and DER/BER/CER codecs (X.208)"
+name = "pycodestyle"
+version = "2.11.1"
+description = "Python style guide checker"
 optional = false
-python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
+python-versions = ">=3.8"
 files = [
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 ]
 
 [[package]]
-name = "pyasn1-modules"
-version = "0.3.0"
-description = "A collection of ASN.1-based protocols modules"
+name = "pyerfa"
+version = "2.0.1.4"
+description = "Python bindings for ERFA"
 optional = false
-python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
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 ]
 
 [package.dependencies]
-pyasn1 = ">=0.4.6,<0.6.0"
+numpy = ">=1.19"
 
-[[package]]
-name = "pycodestyle"
-version = "2.11.1"
-description = "Python style guide checker"
-optional = false
-python-versions = ">=3.8"
-files = [
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-]
+[package.extras]
+docs = ["sphinx-astropy (>=1.3)"]
+test = ["pytest", "pytest-doctestplus (>=0.7)"]
 
 [[package]]
 name = "pyflakes"
@@ -1719,6 +1888,20 @@ files = [
     {file = "pyflakes-3.2.0.tar.gz", hash = "sha256:1c61603ff154621fb2a9172037d84dca3500def8c8b630657d1701f026f8af3f"},
 ]
 
+[[package]]
+name = "pygments"
+version = "2.18.0"
+description = "Pygments is a syntax highlighting package written in Python."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "pygments-2.18.0-py3-none-any.whl", hash = "sha256:b8e6aca0523f3ab76fee51799c488e38782ac06eafcf95e7ba832985c8e7b13a"},
+    {file = "pygments-2.18.0.tar.gz", hash = "sha256:786ff802f32e91311bff3889f6e9a86e81505fe99f2735bb6d60ae0c5004f199"},
+]
+
+[package.extras]
+windows-terminal = ["colorama (>=0.4.6)"]
+
 [[package]]
 name = "pyknos"
 version = "0.15.2"
@@ -1740,13 +1923,13 @@ tqdm = "*"
 
 [[package]]
 name = "pyparsing"
-version = "3.1.1"
+version = "3.1.2"
 description = "pyparsing module - Classes and methods to define and execute parsing grammars"
 optional = false
 python-versions = ">=3.6.8"
 files = [
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+    {file = "pyparsing-3.1.2-py3-none-any.whl", hash = "sha256:f9db75911801ed778fe61bb643079ff86601aca99fcae6345aa67292038fb742"},
+    {file = "pyparsing-3.1.2.tar.gz", hash = "sha256:a1bac0ce561155ecc3ed78ca94d3c9378656ad4c94c1270de543f621420f94ad"},
 ]
 
 [package.extras]
@@ -1769,40 +1952,40 @@ test = ["flake8", "pytest (>=5.0)"]
 
 [[package]]
 name = "pyro-ppl"
-version = "1.8.6"
+version = "1.9.1"
 description = "A Python library for probabilistic modeling and inference"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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+    {file = "pyro_ppl-1.9.1-py3-none-any.whl", hash = "sha256:91fb2c8740d9d3bd548180ac5ecfa04552ed8c471a1ab66870180663b8f09852"},
+    {file = "pyro_ppl-1.9.1.tar.gz", hash = "sha256:5e1596de276c038a3f77d2580a90d0a97126e0104900444a088eee620bb0d65e"},
 ]
 
 [package.dependencies]
 numpy = ">=1.7"
 opt-einsum = ">=2.3.2"
 pyro-api = ">=0.1.1"
-torch = ">=1.11.0"
+torch = ">=2.0"
 tqdm = ">=4.36"
 
 [package.extras]
-dev = ["black (>=21.4b0)", "graphviz (>=0.8)", "jupyter (>=1.0.0)", "lap", "matplotlib (>=1.3)", "mypy (>=0.812)", "nbformat", "nbsphinx (>=0.3.2)", "nbstripout", "nbval", "ninja", "pandas", "pillow (==8.2.0)", "pypandoc", "pytest (>=5.0)", "pytest-xdist", "ruff", "scikit-learn", "scipy (>=1.1)", "seaborn (>=0.11.0)", "sphinx", "sphinx-rtd-theme", "torchvision (>=0.12.0)", "visdom (>=0.1.4,<0.2.2)", "wget", "yapf"]
-extras = ["graphviz (>=0.8)", "jupyter (>=1.0.0)", "lap", "matplotlib (>=1.3)", "pandas", "pillow (==8.2.0)", "scikit-learn", "seaborn (>=0.11.0)", "torchvision (>=0.12.0)", "visdom (>=0.1.4,<0.2.2)", "wget"]
+dev = ["black (>=21.4b0)", "graphviz (>=0.8)", "ipywidgets", "matplotlib (>=1.3)", "mypy (>=0.812)", "nbformat", "nbsphinx (>=0.3.2)", "nbstripout", "nbval", "ninja", "notebook", "pandas", "pillow (>=8.3.1)", "pypandoc", "pytest (>=5.0)", "pytest-xdist", "ruff", "scikit-learn", "scipy (>=1.1)", "seaborn (>=0.11.0)", "sphinx", "sphinx-rtd-theme", "torchvision (>=0.15.0)", "visdom (>=0.1.4,<0.2.2)", "wget", "yapf"]
+extras = ["graphviz (>=0.8)", "ipywidgets", "matplotlib (>=1.3)", "notebook", "pandas", "pillow (>=8.3.1)", "scikit-learn", "scipy (>=1.1)", "seaborn (>=0.11.0)", "torchvision (>=0.15.0)", "visdom (>=0.1.4,<0.2.2)", "wget"]
 funsor = ["funsor[torch] (==0.4.4)"]
 horovod = ["horovod[pytorch] (>=0.19)"]
-lightning = ["pytorch-lightning"]
+lightning = ["lightning"]
 profile = ["prettytable", "pytest-benchmark", "snakeviz"]
-test = ["black (>=21.4b0)", "graphviz (>=0.8)", "jupyter (>=1.0.0)", "lap", "matplotlib (>=1.3)", "nbval", "pandas", "pillow (==8.2.0)", "pytest (>=5.0)", "pytest-cov", "pytest-xdist", "ruff", "scikit-learn", "scipy (>=1.1)", "seaborn (>=0.11.0)", "torchvision (>=0.12.0)", "visdom (>=0.1.4,<0.2.2)", "wget"]
+test = ["black (>=21.4b0)", "graphviz (>=0.8)", "ipywidgets", "matplotlib (>=1.3)", "nbval", "notebook", "pandas", "pillow (>=8.3.1)", "pytest (>=5.0)", "pytest-cov", "pytest-xdist", "ruff", "scikit-learn", "scipy (>=1.1)", "seaborn (>=0.11.0)", "torchvision (>=0.15.0)", "visdom (>=0.1.4,<0.2.2)", "wget"]
 
 [[package]]
 name = "pytest"
-version = "7.3.2"
+version = "7.4.4"
 description = "pytest: simple powerful testing with Python"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "pytest-7.3.2-py3-none-any.whl", hash = "sha256:cdcbd012c9312258922f8cd3f1b62a6580fdced17db6014896053d47cddf9295"},
-    {file = "pytest-7.3.2.tar.gz", hash = "sha256:ee990a3cc55ba808b80795a79944756f315c67c12b56abd3ac993a7b8c17030b"},
+    {file = "pytest-7.4.4-py3-none-any.whl", hash = "sha256:b090cdf5ed60bf4c45261be03239c2c1c22df034fbffe691abe93cd80cea01d8"},
+    {file = "pytest-7.4.4.tar.gz", hash = "sha256:2cf0005922c6ace4a3e2ec8b4080eb0d9753fdc93107415332f50ce9e7994280"},
 ]
 
 [package.dependencies]
@@ -1836,13 +2019,13 @@ testing = ["fields", "hunter", "process-tests", "pytest-xdist", "six", "virtuale
 
 [[package]]
 name = "python-dateutil"
-version = "2.8.2"
+version = "2.9.0.post0"
 description = "Extensions to the standard Python datetime module"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
 files = [
-    {file = "python-dateutil-2.8.2.tar.gz", hash = "sha256:0123cacc1627ae19ddf3c27a5de5bd67ee4586fbdd6440d9748f8abb483d3e86"},
-    {file = "python_dateutil-2.8.2-py2.py3-none-any.whl", hash = "sha256:961d03dc3453ebbc59dbdea9e4e11c5651520a876d0f4db161e8674aae935da9"},
+    {file = "python-dateutil-2.9.0.post0.tar.gz", hash = "sha256:37dd54208da7e1cd875388217d5e00ebd4179249f90fb72437e91a35459a0ad3"},
+    {file = "python_dateutil-2.9.0.post0-py2.py3-none-any.whl", hash = "sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427"},
 ]
 
 [package.dependencies]
@@ -1850,73 +2033,128 @@ six = ">=1.5"
 
 [[package]]
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+version = "2.32.3"
 description = "Python HTTP for Humans."
 optional = false
-python-versions = ">=3.7"
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 files = [
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 [package.dependencies]
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 use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
 [[package]]
-name = "requests-oauthlib"
-version = "1.3.1"
-description = "OAuthlib authentication support for Requests."
+name = "ruff"
+version = "0.3.7"
+description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
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-
-[package.extras]
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-
-[[package]]
-name = "rsa"
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-description = "Pure-Python RSA implementation"
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-[package.dependencies]
-pyasn1 = ">=0.1.3"
-
 [[package]]
 name = "sbi"
 version = "0.22.0"
@@ -1989,125 +2221,153 @@ tqdm = "*"
 [package.extras]
 dev = ["autoflake", "black", "deepdiff", "flake8", "isort", "jupyter", "markdown-include", "mkdocs", "mkdocs-material", "mkdocs-redirects", "mkdocstrings[python] (>=0.18)", "nbconvert", "pep517", "pre-commit", "pyright (>=1.1.300,<1.1.306)", "pytest", "pyyaml", "torchtestcase", "twine"]
 
+[[package]]
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+description = "Image processing in Python"
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+python-versions = ">=3.8"
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+
+[[package]]
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+description = "Intel® oneAPI Threading Building Blocks (oneTBB)"
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+python-versions = "*"
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 setuptools = ">=41.0.0"
 six = ">1.9"
 tensorboard-data-server = ">=0.7.0,<0.8.0"
@@ -2172,15 +2600,32 @@ files = [
 
 [[package]]
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-version = "3.2.0"
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 ]
 
+[[package]]
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+
 [[package]]
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 version = "2.0.1"
@@ -2194,37 +2639,38 @@ files = [
 
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 ]
 
 [package.dependencies]
 filelock = "*"
 fsspec = "*"
 jinja2 = "*"
+mkl = {version = ">=2021.1.1,<=2021.4.0", markers = "platform_system == \"Windows\""}
 networkx = "*"
 nvidia-cublas-cu12 = {version = "12.1.3.1", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cuda-cupti-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
@@ -2235,25 +2681,25 @@ nvidia-cufft-cu12 = {version = "11.0.2.54", markers = "platform_system == \"Linu
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 nvidia-nvtx-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 sympy = "*"
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-typing-extensions = "*"
+triton = {version = "2.3.1", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.12\""}
+typing-extensions = ">=4.8.0"
 
 [package.extras]
-dynamo = ["jinja2"]
 opt-einsum = ["opt-einsum (>=3.3)"]
+optree = ["optree (>=0.9.1)"]
 
 [[package]]
 name = "tqdm"
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 description = "Fast, Extensible Progress Meter"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -2267,97 +2713,95 @@ telegram = ["requests"]
 
 [[package]]
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-version = "2.1.0"
+version = "2.3.1"
 description = "A language and compiler for custom Deep Learning operations"
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 python-versions = "*"
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 python-versions = ">=2"
 files = [
-    {file = "tzdata-2023.4-py2.py3-none-any.whl", hash = "sha256:aa3ace4329eeacda5b7beb7ea08ece826c28d761cda36e747cfbf97996d39bf3"},
-    {file = "tzdata-2023.4.tar.gz", hash = "sha256:dd54c94f294765522c77399649b4fefd95522479a664a0cec87f41bebc6148c9"},
+    {file = "tzdata-2024.1-py2.py3-none-any.whl", hash = "sha256:9068bc196136463f5245e51efda838afa15aaeca9903f49050dfa2679db4d252"},
+    {file = "tzdata-2024.1.tar.gz", hash = "sha256:2674120f8d891909751c38abcdfd386ac0a5a1127954fbc332af6b5ceae07efd"},
 ]
 
 [[package]]
 name = "urllib3"
-version = "2.0.3"
+version = "2.2.1"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "urllib3-2.0.3-py3-none-any.whl", hash = "sha256:48e7fafa40319d358848e1bc6809b208340fafe2096f1725d05d67443d0483d1"},
-    {file = "urllib3-2.0.3.tar.gz", hash = "sha256:bee28b5e56addb8226c96f7f13ac28cb4c301dd5ea8a6ca179c0b9835e032825"},
+    {file = "urllib3-2.2.1-py3-none-any.whl", hash = "sha256:450b20ec296a467077128bff42b73080516e71b56ff59a60a02bef2232c4fa9d"},
+    {file = "urllib3-2.2.1.tar.gz", hash = "sha256:d0570876c61ab9e520d776c38acbbb5b05a776d3f9ff98a5c8fd5162a444cf19"},
 ]
 
 [package.extras]
 brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"]
-secure = ["certifi", "cryptography (>=1.9)", "idna (>=2.0.0)", "pyopenssl (>=17.1.0)", "urllib3-secure-extra"]
+h2 = ["h2 (>=4,<5)"]
 socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
 zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "virtualenv"
-version = "20.23.0"
+version = "20.26.2"
 description = "Virtual Python Environment builder"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "virtualenv-20.23.0-py3-none-any.whl", hash = "sha256:6abec7670e5802a528357fdc75b26b9f57d5d92f29c5462ba0fbe45feacc685e"},
-    {file = "virtualenv-20.23.0.tar.gz", hash = "sha256:a85caa554ced0c0afbd0d638e7e2d7b5f92d23478d05d17a76daeac8f279f924"},
+    {file = "virtualenv-20.26.2-py3-none-any.whl", hash = "sha256:a624db5e94f01ad993d476b9ee5346fdf7b9de43ccaee0e0197012dc838a0e9b"},
+    {file = "virtualenv-20.26.2.tar.gz", hash = "sha256:82bf0f4eebbb78d36ddaee0283d43fe5736b53880b8a8cdcd37390a07ac3741c"},
 ]
 
 [package.dependencies]
-distlib = ">=0.3.6,<1"
-filelock = ">=3.11,<4"
-platformdirs = ">=3.2,<4"
+distlib = ">=0.3.7,<1"
+filelock = ">=3.12.2,<4"
+platformdirs = ">=3.9.1,<5"
 
 [package.extras]
-docs = ["furo (>=2023.3.27)", "proselint (>=0.13)", "sphinx (>=6.1.3)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=22.12)"]
-test = ["covdefaults (>=2.3)", "coverage (>=7.2.3)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.3.1)", "pytest-env (>=0.8.1)", "pytest-freezegun (>=0.4.2)", "pytest-mock (>=3.10)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=67.7.1)", "time-machine (>=2.9)"]
+docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2,!=7.3)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
+test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"]
 
 [[package]]
 name = "werkzeug"
-version = "3.0.1"
+version = "3.0.3"
 description = "The comprehensive WSGI web application library."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "werkzeug-3.0.1-py3-none-any.whl", hash = "sha256:90a285dc0e42ad56b34e696398b8122ee4c681833fb35b8334a095d82c56da10"},
-    {file = "werkzeug-3.0.1.tar.gz", hash = "sha256:507e811ecea72b18a404947aded4b3390e1db8f826b494d76550ef45bb3b1dcc"},
+    {file = "werkzeug-3.0.3-py3-none-any.whl", hash = "sha256:fc9645dc43e03e4d630d23143a04a7f947a9a3b5727cd535fdfe155a17cc48c8"},
+    {file = "werkzeug-3.0.3.tar.gz", hash = "sha256:097e5bfda9f0aba8da6b8545146def481d06aa7d3266e7448e2cccf67dd8bd18"},
 ]
 
 [package.dependencies]
@@ -2368,23 +2812,24 @@ watchdog = ["watchdog (>=2.3)"]
 
 [[package]]
 name = "xarray"
-version = "2024.1.1"
+version = "2024.5.0"
 description = "N-D labeled arrays and datasets in Python"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "xarray-2024.1.1-py3-none-any.whl", hash = "sha256:0bec81303b088c8df4f075e1579c00cfd7e5069688e4434007f0b8d7df17fc1c"},
-    {file = "xarray-2024.1.1.tar.gz", hash = "sha256:a1ba2d87a74892e213c9c83f4a462dbcdf68212320a4e31b34bd789ba7a64e35"},
+    {file = "xarray-2024.5.0-py3-none-any.whl", hash = "sha256:7ddedfe2294a0ab00f02d0fbdcb9c6300ec589f3cf436a9c7b7b577a12cd9bcf"},
+    {file = "xarray-2024.5.0.tar.gz", hash = "sha256:e0eb1cb265f265126795f388ed9591f3c752f2aca491f6c0576711fd15b708f2"},
 ]
 
 [package.dependencies]
 numpy = ">=1.23"
-packaging = ">=22"
-pandas = ">=1.5"
+packaging = ">=23.1"
+pandas = ">=2.0"
 
 [package.extras]
 accel = ["bottleneck", "flox", "numbagg", "opt-einsum", "scipy"]
-complete = ["xarray[accel,io,parallel,viz]"]
+complete = ["xarray[accel,dev,io,parallel,viz]"]
+dev = ["hypothesis", "mypy", "pre-commit", "pytest", "pytest-cov", "pytest-env", "pytest-timeout", "pytest-xdist", "ruff", "xarray[complete]"]
 io = ["cftime", "fsspec", "h5netcdf", "netCDF4", "pooch", "pydap", "scipy", "zarr"]
 parallel = ["dask[complete]"]
 viz = ["matplotlib", "nc-time-axis", "seaborn"]
@@ -2413,20 +2858,20 @@ test = ["hypothesis", "packaging", "pytest", "pytest-cov"]
 
 [[package]]
 name = "zipp"
-version = "3.17.0"
+version = "3.19.2"
 description = "Backport of pathlib-compatible object wrapper for zip files"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "zipp-3.17.0-py3-none-any.whl", hash = "sha256:0e923e726174922dce09c53c59ad483ff7bbb8e572e00c7f7c46b88556409f31"},
-    {file = "zipp-3.17.0.tar.gz", hash = "sha256:84e64a1c28cf7e91ed2078bb8cc8c259cb19b76942096c8d7b84947690cabaf0"},
+    {file = "zipp-3.19.2-py3-none-any.whl", hash = "sha256:f091755f667055f2d02b32c53771a7a6c8b47e1fdbc4b72a8b9072b3eef8015c"},
+    {file = "zipp-3.19.2.tar.gz", hash = "sha256:bf1dcf6450f873a13e952a29504887c89e6de7506209e5b1bcc3460135d4de19"},
 ]
 
 [package.extras]
-docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"]
-testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
+doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
 
 [metadata]
 lock-version = "2.0"
-python-versions = "^3.9"
-content-hash = "ae2e5e776997e3e9eb45b0a4eb7c30bc4b807b8eb0006efb214fd1dd73d51550"
+python-versions = ">=3.9,<3.12"
+content-hash = "d735cee93a7f5de8ad7fdea12a7f48f627b87cb93f1aa8285132e8eb246a556e"
diff --git a/src/data/data.py b/src/data/data.py
index 38a9f9e..0dcdef1 100644
--- a/src/data/data.py
+++ b/src/data/data.py
@@ -1,6 +1,4 @@
-import importlib.util
-import sys
-import os
+from typing import Optional
 import numpy as np
 
 from utils.config import get_item
@@ -14,6 +12,7 @@ def __init__(
         simulator_kwargs: dict = None,
         prior: str = None,
         prior_kwargs: dict = None,
+        simulation_dimensions:Optional[int] = None,
     ):
         self.rng = np.random.default_rng(
             get_item("common", "random_seed", raise_exception=False)
@@ -22,6 +21,12 @@ def __init__(
         self.simulator = load_simulator(simulator_name, simulator_kwargs)
         self.prior_dist = self.load_prior(prior, prior_kwargs)
         self.n_dims = self.get_theta_true().shape[1]
+        self.simulator_dimensions = simulation_dimensions if simulation_dimensions is not None else get_item("data", "simulator_dimensions", raise_exception=False)
+
+    def get_simulator_output_shape(self): 
+        context_shape = self.true_context().shape
+        sim_out = self.simulator(theta=self.get_theta_true()[0:1, :], n_samples=context_shape[-1])
+        return sim_out.shape
 
     def _load(self, path: str):
         raise NotImplementedError
diff --git a/src/data/h5_data.py b/src/data/h5_data.py
index 56eb23e..8d6dd17 100644
--- a/src/data/h5_data.py
+++ b/src/data/h5_data.py
@@ -1,4 +1,4 @@
-from typing import Any, Callable
+from typing import Any, Callable, Optional
 import h5py
 import numpy as np
 import torch
@@ -8,8 +8,15 @@
 
 
 class H5Data(Data):
-    def __init__(self, path: str, simulator: Callable):
-        super().__init__(path, simulator)
+    def __init__(self, 
+        path: str, 
+        simulator: Callable, 
+        simulator_kwargs: dict = None,
+        prior: str = None,
+        prior_kwargs: dict = None,
+        simulation_dimensions:Optional[int] = None,
+    ):
+        super().__init__(path, simulator, simulator_kwargs, prior, prior_kwargs, simulation_dimensions)
 
     def _load(self, path):
         assert path.split(".")[-1] == "h5", "File extension must be h5"
diff --git a/src/data/pickle_data.py b/src/data/pickle_data.py
index 2dc9238..ea2fa9d 100644
--- a/src/data/pickle_data.py
+++ b/src/data/pickle_data.py
@@ -1,11 +1,18 @@
 import pickle
-from typing import Any, Callable
+from typing import Any, Callable, Optional
 from data.data import Data
 
 
 class PickleData(Data):
-    def __init__(self, path: str, simulator: Callable):
-        super().__init__(path, simulator)
+    def __init__(self, 
+        path: str, 
+        simulator: Callable, 
+        simulator_kwargs: dict = None,
+        prior: str = None,
+        prior_kwargs: dict = None,
+        simulation_dimensions:Optional[int] = None,
+    ):
+        super().__init__(path, simulator, simulator_kwargs, prior, prior_kwargs, simulation_dimensions)
 
     def _load(self, path: str):
         assert path.split(".")[-1] == "pkl", "File extension must be 'pkl'"
diff --git a/src/metrics/local_two_sample.py b/src/metrics/local_two_sample.py
index ce7c16a..8a563fb 100644
--- a/src/metrics/local_two_sample.py
+++ b/src/metrics/local_two_sample.py
@@ -37,29 +37,43 @@ def _collect_data_params(self):
         # P is the prior and x_P is generated via the simulator from the parameters P.
         self.p = self.data.sample_prior(self.number_simulations)
         self.q = np.zeros_like(self.p)
-
         context_size = self.data.true_context().shape[-1]
-        self.outcome_given_p = np.zeros(
-            (self.number_simulations, context_size)
+        remove_first_dim = False
 
-        )
+        if self.data.simulator_dimensions == 1: 
+            self.outcome_given_p = np.zeros((self.number_simulations, context_size))
+        elif self.data.simulator_dimensions == 2: 
+            sim_out_shape = self.data.get_simulator_output_shape()
+            if len(sim_out_shape) != 2: 
+                # TODO Debug log with a warning
+                sim_out_shape = (sim_out_shape[1], sim_out_shape[2])
+                remove_first_dim = True
+   
+            sim_out_shape = np.product(sim_out_shape)
+            self.outcome_given_p = np.zeros((self.number_simulations, sim_out_shape))
+        else: 
+            raise NotImplementedError("LC2ST only implemented for 1 or two dimensions.")
+        
         self.outcome_given_q = np.zeros_like(self.outcome_given_p)
-        self.evaluation_context = np.zeros_like(self.outcome_given_p)
+        self.evaluation_context = np.zeros((self.number_simulations, context_size))
 
         for index, p in enumerate(self.p): 
             context = self.data.simulator.generate_context(context_size)
-            self.outcome_given_p[index] = self.data.simulator.simulate(p, context)
-            # Q is the approximate posterior amortized in x
             q = self.model.sample_posterior(1, context).ravel()
             self.q[index] = q
-            self.outcome_given_q[index] = self.data.simulator.simulate(q, context)
+            self.evaluation_context[index] = context
+
+            p_outcome = self.data.simulator.simulate(p, context)
+            q_outcome = self.data.simulator.simulate(q, context)
+
+            if remove_first_dim: 
+                p_outcome = p_outcome[0]
+                q_outcome = q_outcome[0]
+
+            self.outcome_given_p[index] = p_outcome.ravel()
+            self.outcome_given_q[index] = q_outcome.ravel() # Q is the approximate posterior amortized in x
+
 
-        self.evaluation_context = np.array(
-            [
-                self.data.simulator.generate_context(context_size)
-                for _ in range(self.num_simulations)
-            ]
-        )
 
     def train_linear_classifier(
         self, p, q, x_p, x_q, classifier: str, classifier_kwargs: dict = {}
@@ -127,9 +141,21 @@ def _cross_eval_score(
         cv_splits = kf.split(p)
         # train classifiers over cv-folds
         probabilities = []
-        self.evaluation_data = np.zeros(
-            (n_cross_folds, len(next(cv_splits)[1]), self.evaluation_context.shape[-1])
-        )
+
+        remove_first_dim = False
+        if self.data.simulator_dimensions == 1: 
+            self.evaluation_data =  np.zeros((n_cross_folds, len(next(cv_splits)[1]), self.evaluation_context.shape[-1]))
+        
+        elif self.data.simulator_dimensions == 2: 
+            sim_out_shape = self.data.get_simulator_output_shape()
+            if len(sim_out_shape) != 2: 
+                # TODO Debug log with a warning
+                sim_out_shape = (sim_out_shape[1], sim_out_shape[2])
+                remove_first_dim = True
+
+            sim_out_shape = np.product(sim_out_shape)
+            self.evaluation_data = np.zeros((n_cross_folds, len(next(cv_splits)[1]), sim_out_shape))
+        
         self.prior_evaluation = np.zeros_like(p)
 
         kf = KFold(n_splits=n_cross_folds, shuffle=True, random_state=42)
@@ -142,10 +168,16 @@ def _cross_eval_score(
                 p_train, q_train, x_p_train, x_q_train, classifier, classifier_kwargs
             )
             p_evaluate = p[val_index]
+
             for index, p_validation in enumerate(p_evaluate):
-                self.evaluation_data[cross_trial][index] = self.data.simulator.simulate(
+                sim_output = self.data.simulator.simulate(
                     p_validation, self.evaluation_context[val_index][index]
                 )
+
+                if remove_first_dim: 
+                    sim_output = sim_output[0]
+                self.evaluation_data[cross_trial][index] = sim_output.ravel() 
+
             self.prior_evaluation[index] = p_validation
             probabilities.append(
                 self._eval_model(
diff --git a/src/plots/predictive_posterior_check.py b/src/plots/predictive_posterior_check.py
index c1fc88b..9f7c06e 100644
--- a/src/plots/predictive_posterior_check.py
+++ b/src/plots/predictive_posterior_check.py
@@ -27,9 +27,41 @@ def __init__(
     def _plot_name(self):
         return "predictive_posterior_check.png"
 
-    def get_posterior(self, n_simulator_draws):
+    def get_posterior_2d(self, n_simulator_draws): 
         context_shape = self.data.true_context().shape
-        self.posterior_predictive_samples = np.zeros((n_simulator_draws, self.samples_per_inference,context_shape[-1]))
+        sim_out_shape = self.data.get_simulator_output_shape()
+        remove_first_dim = False
+        if len(sim_out_shape) != 2: 
+            # TODO Debug log with a warning
+            sim_out_shape = (sim_out_shape[1], sim_out_shape[2])
+            remove_first_dim = True
+
+        self.posterior_predictive_samples = np.zeros((n_simulator_draws, *sim_out_shape))
+        self.posterior_true_samples = np.zeros_like(self.posterior_predictive_samples)
+
+        random_context_indices = self.data.rng.integers(0, context_shape[0], n_simulator_draws)
+        for index, sample in enumerate(random_context_indices): 
+            context_sample = self.data.true_context()[sample, :]
+            posterior_sample = self.model.sample_posterior(1, context_sample)
+
+            # get the posterior samples for that context 
+            sim_out_posterior =  self.data.simulator.simulate(
+                theta=posterior_sample, context_samples = context_sample
+            )
+            sim_out_true = self.data.simulator.simulate(
+                theta=self.data.get_theta_true()[sample, :], context_samples=context_sample
+            )
+            if remove_first_dim: 
+                sim_out_posterior = sim_out_posterior[0]
+                sim_out_true = sim_out_true[0]
+
+            self.posterior_predictive_samples[index] = sim_out_posterior
+            self.posterior_true_samples[index] = sim_out_true
+
+
+    def get_posterior_1d(self, n_simulator_draws):
+        context_shape = self.data.true_context().shape
+        self.posterior_predictive_samples = np.zeros((n_simulator_draws, self.samples_per_inference, context_shape[-1]))
         self.posterior_true_samples = np.zeros_like(self.posterior_predictive_samples)
         self.context = np.zeros((n_simulator_draws, context_shape[-1]))
 
@@ -48,20 +80,82 @@ def get_posterior(self, n_simulator_draws):
                 theta=self.data.get_theta_true()[sample, :], context_samples=context_sample
             )
 
+    def _plot_1d(self, 
+        subplots: np.ndarray, 
+        subplot_index: int,
+        n_coverage_sigma: Optional[int] = 3, 
+        theta_true_marker: Optional[str] = '^'
+    ):
+        
+        dimension_y_simulation = self.posterior_predictive_samples[subplot_index]
+        y_simulation_mean = np.mean(dimension_y_simulation, axis=0).ravel()
+        y_simulation_std = np.std(dimension_y_simulation, axis=0).ravel()
+
+        for sigma, color in zip(range(n_coverage_sigma), self.colors):
+                subplots[0, subplot_index].fill_between(
+                self.context[subplot_index].ravel(),
+                y_simulation_mean - sigma * y_simulation_std,
+                y_simulation_mean + sigma * y_simulation_std,
+                color=color,
+                alpha=0.6,
+                label=rf"Pred. with {sigma} $\sigma$",
+            )
+
+        subplots[0, subplot_index].plot(
+            self.context[subplot_index],
+            y_simulation_mean - self.true_sigma,
+            color="black",
+            linestyle="dashdot",
+            label="True Input Error"
+        )
+        subplots[0, subplot_index].plot(
+            self.context[subplot_index],
+            y_simulation_mean + self.true_sigma,
+            color="black",
+            linestyle="dashdot",
+        )
+
+        true_y = np.mean(self.posterior_true_samples[subplot_index, :, :], axis=0).ravel()
+        subplots[1, subplot_index].scatter(
+            self.context[subplot_index], 
+            true_y, 
+            marker=theta_true_marker, 
+            label='Theta True'
+        )
+
+    def _plot_2d(self, subplots, subplot_index, include_axis_ticks): 
+        subplots[1, subplot_index].imshow(self.posterior_predictive_samples[subplot_index])
+        subplots[0, subplot_index].imshow(self.posterior_true_samples[subplot_index])
+
+        if not include_axis_ticks: 
+            subplots[1, subplot_index].set_xticks([])
+            subplots[1, subplot_index].set_yticks([])
+
+            subplots[0, subplot_index].set_xticks([])
+            subplots[0, subplot_index].set_yticks([])
+
     def _plot(
             self, 
             n_coverage_sigma: Optional[int] = 3, 
             true_sigma: Optional[float] = None, 
             theta_true_marker: Optional[str] = '^', 
             n_unique_plots: Optional[int] = 3,
+            include_axis_ticks: bool = False,
             title:str="Predictive Posterior", 
             y_label:str="Simulation Output", 
             x_label:str="X"): 
         
+        if self.data.simulator_dimensions == 1: 
+            self.get_posterior_1d(n_unique_plots)
+            self.true_sigma = true_sigma if true_sigma is not None else self.data.get_sigma_true()
+            self.colors = get_hex_colors(n_coverage_sigma, self.colorway)
 
-        self.get_posterior(n_unique_plots)
-        true_sigma = true_sigma if true_sigma is not None else self.data.get_sigma_true()
+        elif self.data.simulator_dimensions == 2: 
+            self.get_posterior_2d(n_unique_plots)
 
+        else: 
+            raise NotImplementedError("Posterior Checks only implemented for 1 or two dimensions.")
+        
         figure, subplots = plt.subplots(
             2, 
             n_unique_plots, 
@@ -69,49 +163,14 @@ def _plot(
             sharex=False, 
             sharey=True
         )
-        colors = get_hex_colors(n_coverage_sigma, self.colorway)
 
         for plot_index in range(n_unique_plots): 
+            if self.data.simulator_dimensions == 1: 
+                self._plot_1d(subplots, plot_index, n_coverage_sigma, theta_true_marker)
 
-            dimension_y_simulation = self.posterior_predictive_samples[plot_index]
-
-            y_simulation_mean = np.mean(dimension_y_simulation, axis=0).ravel()
-            y_simulation_std = np.std(dimension_y_simulation, axis=0).ravel()
-
-            for sigma, color in zip(range(n_coverage_sigma), colors):
-                 subplots[0, plot_index].fill_between(
-                    self.context[plot_index].ravel(),
-                    y_simulation_mean - sigma * y_simulation_std,
-                    y_simulation_mean + sigma * y_simulation_std,
-                    color=color,
-                    alpha=0.6,
-                    label=rf"Pred. with {sigma} $\sigma$",
-                )
-
-            subplots[0, plot_index].plot(
-                self.context[plot_index],
-                y_simulation_mean - true_sigma,
-                color="black",
-                linestyle="dashdot",
-                label="True Input Error"
-            )
-            subplots[0, plot_index].plot(
-                self.context[plot_index],
-                y_simulation_mean + true_sigma,
-                color="black",
-                linestyle="dashdot",
-            )
-
-            true_y = np.mean(self.posterior_true_samples[plot_index, :, :], axis=0).ravel()
-            subplots[1, plot_index].scatter(
-                self.context[plot_index], 
-                true_y, 
-                marker=theta_true_marker, 
-                label='Theta True'
-            )
+            else: 
+                self._plot_2d(subplots, plot_index, include_axis_ticks)
 
-        subplots[1, -1].legend()
-        subplots[0, -1].legend()
 
         subplots[1, 0].set_ylabel("True Parameters")
         subplots[0, 0].set_ylabel("Predicted Parameters")
diff --git a/src/utils/defaults.py b/src/utils/defaults.py
index 3956bb2..8ef784f 100644
--- a/src/utils/defaults.py
+++ b/src/utils/defaults.py
@@ -11,6 +11,7 @@
         "prior": "normal",
         "prior_kwargs": None,
         "simulator_kwargs": None,
+        "simulator_dimensions": 1,
     },
     "plots_common": {
         "axis_spines": False,
@@ -29,7 +30,8 @@
         "TARP": {
             "coverage_sigma": 3  # How many sigma to show coverage over
         },
-        "LC2ST": {}
+        "LC2ST": {}, 
+        "PPC":{}
     },
     "metrics_common": {
         "use_progress_bar": False,
diff --git a/src/utils/register.py b/src/utils/register.py
index 5fcc8ff..60fdcfe 100644
--- a/src/utils/register.py
+++ b/src/utils/register.py
@@ -18,12 +18,14 @@ def register_simulator(simulator_name, simulator):
     if not os.path.exists(sim_paths):
         open(sim_paths, 'a').close()
 
-    with open(sim_paths, "w+") as f: 
+    with open(sim_paths, "r+") as f: 
         try: 
             existing_sims = json.load(f)
         except json.decoder.JSONDecodeError: 
             existing_sims = {}
-
+            
+    existing_sims[simulator_name] = simulator_location
+    with open(sim_paths, "w") as f: 
         existing_sims[simulator_name] = simulator_location
         json.dump(existing_sims, f)
 
diff --git a/tests/conftest.py b/tests/conftest.py
index e08ae25..33f22db 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -1,13 +1,16 @@
+import os 
+import shutil
 import pytest
 import yaml
 import numpy as np
-import os
+from deepbench.astro_object import StarObject
 
 from data import H5Data
 from data.simulator import Simulator
 from models import SBIModel
-from utils.register import register_simulator
 from utils.config import get_item
+from utils.register import register_simulator
+
 
 class MockSimulator(Simulator):
     def generate_context(self, n_samples: int) -> np.ndarray:
@@ -39,14 +42,45 @@ def simulate(self, theta: np.ndarray, context_samples: np.ndarray) -> np.ndarray
             y[:, i] = m * context_samples + b + epsilon[:, i]
         return y.T
 
+class Mock2DSimulator(Simulator): 
+    def generate_context(self, n_samples: int) -> np.ndarray: 
+        return np.linspace(0, 28, n_samples)
+
+    def simulate(self, theta, context_samples: np.ndarray): 
+        generated_stars = []
+
+        if len(theta.shape) == 1: 
+            theta = [theta]
+            
+        for sample_index, t in enumerate(theta): 
+            star = StarObject(
+                image_dimensions = (28,28),
+                noise_level = 0.3,
+                radius = t[0].item(),
+                amplitude = t[1].item()
+            )
+            generated_stars.append(
+                star.create_object(
+                    context_samples[sample_index].item(), context_samples[sample_index].item()
+                )
+            )
+        return np.array(generated_stars)
+
 @pytest.fixture(autouse=True)
 def setUp():
     register_simulator("MockSimulator", MockSimulator)
+    register_simulator("Mock2DSimulator", Mock2DSimulator)
     yield 
+    
     simulator_config_path = get_item("common", "sim_location", raise_exception=False)
     sim_paths = f"{simulator_config_path.strip('/')}/simulators.json"
     os.remove(sim_paths)
 
+    out_dir = get_item("common", "out_dir", raise_exception=False)
+    os.makedirs("resources/test_results/", exist_ok=True)
+    shutil.copytree(out_dir, "resources/test_results/",  dirs_exist_ok=True)
+    shutil.rmtree(out_dir)
+
 @pytest.fixture
 def model_path():
     return "resources/savedmodels/sbi/sbi_linear_from_data.pkl"
@@ -56,6 +90,9 @@ def model_path():
 def data_path():
     return "resources/saveddata/data_validation.h5"
 
+@pytest.fixture
+def result_output(): 
+    return "./temp_results/"
 
 @pytest.fixture
 def simulator_name():
@@ -71,15 +108,18 @@ def mock_model(model_path):
 def mock_data(data_path, simulator_name):
     return H5Data(data_path, simulator_name)
 
+@pytest.fixture
+def mock_2d_data(data_path): 
+    return H5Data(data_path, "Mock2DSimulator", simulation_dimensions=2)
 
 @pytest.fixture
-def config_factory():
+def config_factory(result_output):
     def factory(
-        out_dir=None,
         model_path=None,
         model_engine=None,
         data_path=None,
         data_engine=None,
+        plot_2d=False,
         simulator=None,
         plot_settings=None,
         metrics_settings=None,
@@ -97,8 +137,7 @@ def factory(
         }
 
         # Single settings
-        if out_dir is not None:
-            config["common"]["out_dir"] = out_dir
+        config["common"]["out_dir"] = result_output
         if model_path is not None:
             config["model"]["model_path"] = model_path
         if model_engine is not None:
@@ -109,6 +148,8 @@ def factory(
             config["data"]["data_engine"] = data_engine
         if simulator is not None:
             config["data"]["simulator"] = simulator
+        if plot_2d: 
+            config["data"]["simulator_dimensions"] = 2
 
         # Dict settings
         if plot_settings is not None:
diff --git a/tests/test_plots.py b/tests/test_plots.py
index f32e546..88b368a 100644
--- a/tests/test_plots.py
+++ b/tests/test_plots.py
@@ -17,14 +17,13 @@
 
 @pytest.fixture
 def plot_config(config_factory):
-    out_dir = "./temp_results/"
     metrics_settings = {
         "use_progress_bar": False,
         "samples_per_inference": 10,
         "percentiles": [95],
     }
-    config = config_factory(out_dir=out_dir, metrics_settings=metrics_settings)
-    Config(config)
+    config = config_factory(metrics_settings=metrics_settings)
+    return config
 
   
 def test_all_defaults(plot_config, mock_model, mock_data): 
@@ -32,40 +31,58 @@ def test_all_defaults(plot_config, mock_model, mock_data):
     Ensures each metric has a default set of parameters and is included in the defaults list
     Ensures each test can initialize, regardless of the veracity of the output
     """
+    Config(plot_config)
     for plot_name, plot_obj in Plots.items():
         assert plot_name in Defaults["plots"]
         plot_obj(mock_model, mock_data, save=True, show=False)
 
-
 def test_plot_cdf(plot_config, mock_model, mock_data):
+    Config(plot_config)
     plot = CDFRanks(mock_model, mock_data, save=True, show=False)
     plot(**get_item("plots", "CDFRanks", raise_exception=False))
     assert os.path.exists(f"{plot.out_dir}/{plot.plot_name}")
 
-
 def test_plot_ranks(plot_config, mock_model, mock_data):
+    Config(plot_config)
     plot = Ranks(mock_model, mock_data, save=True, show=False)
     plot(**get_item("plots", "Ranks", raise_exception=False))
     assert os.path.exists(f"{plot.out_dir}/{plot.plot_name}")
 
-
 def test_plot_coverage(plot_config, mock_model, mock_data):
+    Config(plot_config)
     plot = CoverageFraction(mock_model, mock_data, save=True, show=False)
     plot(**get_item("plots", "CoverageFraction", raise_exception=False))
     assert os.path.exists(f"{plot.out_dir}/{plot.plot_name}")
 
-
 def test_plot_tarp(plot_config, mock_model, mock_data):
+    Config(plot_config)
     plot = TARP(mock_model, mock_data, save=True, show=False)
     plot(**get_item("plots", "TARP", raise_exception=False))
     assert os.path.exists(f"{plot.out_dir}/{plot.plot_name}")
 
-def test_lc2st(plot_config, mock_model, mock_data):
+def test_lc2st(plot_config, mock_model, mock_data, mock_2d_data, result_output):
+    Config(plot_config)
     plot = LocalTwoSampleTest(mock_model, mock_data, save=True, show=False)
     plot(**get_item("plots", "LC2ST", raise_exception=False))
     assert os.path.exists(f"{plot.out_dir}/{plot.plot_name}")
 
-def test_ppc(plot_config, mock_model, mock_data):
+    plot = LocalTwoSampleTest(
+        mock_model, mock_2d_data, save=True, show=False, 
+        out_dir=f"{result_output.strip('/')}/mock_2d/")
+    assert type(plot.data.simulator).__name__ == "Mock2DSimulator"
+    plot(**get_item("plots", "LC2ST", raise_exception=False))
+    assert os.path.exists(f"{plot.out_dir}/{plot.plot_name}")
+
+def test_ppc(plot_config, mock_model, mock_data, mock_2d_data, result_output):
+    Config(plot_config)
     plot = PPC(mock_model, mock_data, save=True, show=False)
     plot(**get_item("plots", "PPC", raise_exception=False))
+    assert os.path.exists(f"{plot.out_dir}/{plot.plot_name}")
+
+    plot = PPC(
+        mock_model,
+        mock_2d_data, save=True, show=False, 
+        out_dir=f"{result_output.strip('/')}/mock_2d/")
+    assert type(plot.data.simulator).__name__ == "Mock2DSimulator"
+    plot(**get_item("plots", "PPC", raise_exception=False))
     assert os.path.exists(f"{plot.out_dir}/{plot.plot_name}")
\ No newline at end of file