diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 94c8b3e..47a403b 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -10,7 +10,7 @@ repos:
         # pre-commit's default_language_version, see
         # https://pre-commit.com/#top_level-default_language_version
         language_version: python3.11
-
+        files: ^(src|test)/.*\.py$
 
   - repo: https://github.com/pycqa/isort
     rev: 5.13.2
@@ -18,3 +18,4 @@ repos:
       - id: isort
         args: ["--profile", "black"]
         name: isort (python)
+        files: ^(src|test)/.*\.py$
diff --git a/docs/examples/new_sample.py b/docs/examples/new_sample.py
index ebf7144..6f7b2c9 100644
--- a/docs/examples/new_sample.py
+++ b/docs/examples/new_sample.py
@@ -3,14 +3,15 @@
 See official documentation at https://scikit-image.org/docs/0.7.0/api/skimage.transform.html#probabilistic-hough
 
 The procedure to follow is, in short:
-- import everything from the samples module
+- import everything from the analyses module
 - import the types that you might be using from the typing module
 - import any necessary libraries that you will need for your analysis
-- Create one or more subclasses of the Analysis abstract class of samples. Within each class:
+- Create one or more subclasses of the Analysis abstract class of analyses. Within each class:
     - define your input requirements
     - define a 'run' method that will implement the logic of your analysis
     - if desired, define a 'plot' method returning a plot showing the results of the analysis
 """
+
 from math import atan2
 
 # import the types that you may be using
@@ -25,7 +26,7 @@
 from skimage.transform import probabilistic_hough_line
 
 # import the sample functionality
-from microscopemetrics.samples import *
+from microscopemetrics.analyses import *
 
 
 class DetectLinesAnalysis(
diff --git a/docs/notebooks/microscope-metrics_tutorial.ipynb b/docs/notebooks/microscope-metrics_tutorial.ipynb
index d18f017..49e4967 100644
--- a/docs/notebooks/microscope-metrics_tutorial.ipynb
+++ b/docs/notebooks/microscope-metrics_tutorial.ipynb
@@ -805,4 +805,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 1
-}
\ No newline at end of file
+}
diff --git a/poetry.lock b/poetry.lock
index 8cf6df6..8191f62 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
 
 [[package]]
 name = "annotated-types"
@@ -11,6 +11,147 @@ files = [
     {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
 ]
 
+[[package]]
+name = "anyio"
+version = "4.6.2.post1"
+description = "High level compatibility layer for multiple asynchronous event loop implementations"
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "anyio-4.6.2.post1-py3-none-any.whl", hash = "sha256:6d170c36fba3bdd840c73d3868c1e777e33676a69c3a72cf0a0d5d6d8009b61d"},
+    {file = "anyio-4.6.2.post1.tar.gz", hash = "sha256:4c8bc31ccdb51c7f7bd251f51c609e038d63e34219b44aa86e47576389880b4c"},
+]
+
+[package.dependencies]
+exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
+idna = ">=2.8"
+sniffio = ">=1.1"
+typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
+
+[package.extras]
+doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21.0b1)"]
+trio = ["trio (>=0.26.1)"]
+
+[[package]]
+name = "appnope"
+version = "0.1.4"
+description = "Disable App Nap on macOS >= 10.9"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "appnope-0.1.4-py2.py3-none-any.whl", hash = "sha256:502575ee11cd7a28c0205f379b525beefebab9d161b7c964670864014ed7213c"},
+    {file = "appnope-0.1.4.tar.gz", hash = "sha256:1de3860566df9caf38f01f86f65e0e13e379af54f9e4bee1e66b48f2efffd1ee"},
+]
+
+[[package]]
+name = "argon2-cffi"
+version = "23.1.0"
+description = "Argon2 for Python"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "argon2_cffi-23.1.0-py3-none-any.whl", hash = "sha256:c670642b78ba29641818ab2e68bd4e6a78ba53b7eff7b4c3815ae16abf91c7ea"},
+    {file = "argon2_cffi-23.1.0.tar.gz", hash = "sha256:879c3e79a2729ce768ebb7d36d4609e3a78a4ca2ec3a9f12286ca057e3d0db08"},
+]
+
+[package.dependencies]
+argon2-cffi-bindings = "*"
+
+[package.extras]
+dev = ["argon2-cffi[tests,typing]", "tox (>4)"]
+docs = ["furo", "myst-parser", "sphinx", "sphinx-copybutton", "sphinx-notfound-page"]
+tests = ["hypothesis", "pytest"]
+typing = ["mypy"]
+
+[[package]]
+name = "argon2-cffi-bindings"
+version = "21.2.0"
+description = "Low-level CFFI bindings for Argon2"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "argon2-cffi-bindings-21.2.0.tar.gz", hash = "sha256:bb89ceffa6c791807d1305ceb77dbfacc5aa499891d2c55661c6459651fc39e3"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-macosx_10_9_x86_64.whl", hash = "sha256:ccb949252cb2ab3a08c02024acb77cfb179492d5701c7cbdbfd776124d4d2367"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9524464572e12979364b7d600abf96181d3541da11e23ddf565a32e70bd4dc0d"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b746dba803a79238e925d9046a63aa26bf86ab2a2fe74ce6b009a1c3f5c8f2ae"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:58ed19212051f49a523abb1dbe954337dc82d947fb6e5a0da60f7c8471a8476c"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:bd46088725ef7f58b5a1ef7ca06647ebaf0eb4baff7d1d0d177c6cc8744abd86"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-musllinux_1_1_i686.whl", hash = "sha256:8cd69c07dd875537a824deec19f978e0f2078fdda07fd5c42ac29668dda5f40f"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:f1152ac548bd5b8bcecfb0b0371f082037e47128653df2e8ba6e914d384f3c3e"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-win32.whl", hash = "sha256:603ca0aba86b1349b147cab91ae970c63118a0f30444d4bc80355937c950c082"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-win_amd64.whl", hash = "sha256:b2ef1c30440dbbcba7a5dc3e319408b59676e2e039e2ae11a8775ecf482b192f"},
+    {file = "argon2_cffi_bindings-21.2.0-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:e415e3f62c8d124ee16018e491a009937f8cf7ebf5eb430ffc5de21b900dad93"},
+    {file = "argon2_cffi_bindings-21.2.0-pp37-pypy37_pp73-macosx_10_9_x86_64.whl", hash = "sha256:3e385d1c39c520c08b53d63300c3ecc28622f076f4c2b0e6d7e796e9f6502194"},
+    {file = "argon2_cffi_bindings-21.2.0-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2c3e3cc67fdb7d82c4718f19b4e7a87123caf8a93fde7e23cf66ac0337d3cb3f"},
+    {file = "argon2_cffi_bindings-21.2.0-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6a22ad9800121b71099d0fb0a65323810a15f2e292f2ba450810a7316e128ee5"},
+    {file = "argon2_cffi_bindings-21.2.0-pp37-pypy37_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f9f8b450ed0547e3d473fdc8612083fd08dd2120d6ac8f73828df9b7d45bb351"},
+    {file = "argon2_cffi_bindings-21.2.0-pp37-pypy37_pp73-win_amd64.whl", hash = "sha256:93f9bf70084f97245ba10ee36575f0c3f1e7d7724d67d8e5b08e61787c320ed7"},
+    {file = "argon2_cffi_bindings-21.2.0-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:3b9ef65804859d335dc6b31582cad2c5166f0c3e7975f324d9ffaa34ee7e6583"},
+    {file = "argon2_cffi_bindings-21.2.0-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d4966ef5848d820776f5f562a7d45fdd70c2f330c961d0d745b784034bd9f48d"},
+    {file = "argon2_cffi_bindings-21.2.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:20ef543a89dee4db46a1a6e206cd015360e5a75822f76df533845c3cbaf72670"},
+    {file = "argon2_cffi_bindings-21.2.0-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ed2937d286e2ad0cc79a7087d3c272832865f779430e0cc2b4f3718d3159b0cb"},
+    {file = "argon2_cffi_bindings-21.2.0-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:5e00316dabdaea0b2dd82d141cc66889ced0cdcbfa599e8b471cf22c620c329a"},
+]
+
+[package.dependencies]
+cffi = ">=1.0.1"
+
+[package.extras]
+dev = ["cogapp", "pre-commit", "pytest", "wheel"]
+tests = ["pytest"]
+
+[[package]]
+name = "arrow"
+version = "1.3.0"
+description = "Better dates & times for Python"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "arrow-1.3.0-py3-none-any.whl", hash = "sha256:c728b120ebc00eb84e01882a6f5e7927a53960aa990ce7dd2b10f39005a67f80"},
+    {file = "arrow-1.3.0.tar.gz", hash = "sha256:d4540617648cb5f895730f1ad8c82a65f2dad0166f57b75f3ca54759c4d67a85"},
+]
+
+[package.dependencies]
+python-dateutil = ">=2.7.0"
+types-python-dateutil = ">=2.8.10"
+
+[package.extras]
+doc = ["doc8", "sphinx (>=7.0.0)", "sphinx-autobuild", "sphinx-autodoc-typehints", "sphinx_rtd_theme (>=1.3.0)"]
+test = ["dateparser (==1.*)", "pre-commit", "pytest", "pytest-cov", "pytest-mock", "pytz (==2021.1)", "simplejson (==3.*)"]
+
+[[package]]
+name = "asttokens"
+version = "2.4.1"
+description = "Annotate AST trees with source code positions"
+optional = false
+python-versions = "*"
+files = [
+    {file = "asttokens-2.4.1-py2.py3-none-any.whl", hash = "sha256:051ed49c3dcae8913ea7cd08e46a606dba30b79993209636c4875bc1d637bc24"},
+    {file = "asttokens-2.4.1.tar.gz", hash = "sha256:b03869718ba9a6eb027e134bfdf69f38a236d681c83c160d510768af11254ba0"},
+]
+
+[package.dependencies]
+six = ">=1.12.0"
+
+[package.extras]
+astroid = ["astroid (>=1,<2)", "astroid (>=2,<4)"]
+test = ["astroid (>=1,<2)", "astroid (>=2,<4)", "pytest"]
+
+[[package]]
+name = "async-lru"
+version = "2.0.4"
+description = "Simple LRU cache for asyncio"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "async-lru-2.0.4.tar.gz", hash = "sha256:b8a59a5df60805ff63220b2a0c5b5393da5521b113cd5465a44eb037d81a5627"},
+    {file = "async_lru-2.0.4-py3-none-any.whl", hash = "sha256:ff02944ce3c288c5be660c42dbcca0742b32c3b279d6dceda655190240b99224"},
+]
+
+[package.dependencies]
+typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.11\""}
+
 [[package]]
 name = "attrs"
 version = "24.2.0"
@@ -30,6 +171,41 @@ docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphi
 tests = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
 tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"]
 
+[[package]]
+name = "babel"
+version = "2.16.0"
+description = "Internationalization utilities"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "babel-2.16.0-py3-none-any.whl", hash = "sha256:368b5b98b37c06b7daf6696391c3240c938b37767d4584413e8438c5c435fa8b"},
+    {file = "babel-2.16.0.tar.gz", hash = "sha256:d1f3554ca26605fe173f3de0c65f750f5a42f924499bf134de6423582298e316"},
+]
+
+[package.extras]
+dev = ["freezegun (>=1.0,<2.0)", "pytest (>=6.0)", "pytest-cov"]
+
+[[package]]
+name = "beautifulsoup4"
+version = "4.12.3"
+description = "Screen-scraping library"
+optional = false
+python-versions = ">=3.6.0"
+files = [
+    {file = "beautifulsoup4-4.12.3-py3-none-any.whl", hash = "sha256:b80878c9f40111313e55da8ba20bdba06d8fa3969fc68304167741bbf9e082ed"},
+    {file = "beautifulsoup4-4.12.3.tar.gz", hash = "sha256:74e3d1928edc070d21748185c46e3fb33490f22f52a3addee9aee0f4f7781051"},
+]
+
+[package.dependencies]
+soupsieve = ">1.2"
+
+[package.extras]
+cchardet = ["cchardet"]
+chardet = ["chardet"]
+charset-normalizer = ["charset-normalizer"]
+html5lib = ["html5lib"]
+lxml = ["lxml"]
+
 [[package]]
 name = "black"
 version = "23.12.1"
@@ -76,6 +252,24 @@ 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 = "bleach"
+version = "6.1.0"
+description = "An easy safelist-based HTML-sanitizing tool."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "bleach-6.1.0-py3-none-any.whl", hash = "sha256:3225f354cfc436b9789c66c4ee030194bee0568fbf9cbdad3bc8b5c26c5f12b6"},
+    {file = "bleach-6.1.0.tar.gz", hash = "sha256:0a31f1837963c41d46bbf1331b8778e1308ea0791db03cc4e7357b97cf42a8fe"},
+]
+
+[package.dependencies]
+six = ">=1.9.0"
+webencodings = "*"
+
+[package.extras]
+css = ["tinycss2 (>=1.1.0,<1.3)"]
+
 [[package]]
 name = "build"
 version = "1.2.2.post1"
@@ -89,6 +283,7 @@ files = [
 
 [package.dependencies]
 colorama = {version = "*", markers = "os_name == \"nt\""}
+importlib-metadata = {version = ">=4.6", markers = "python_full_version < \"3.10.2\""}
 packaging = ">=19.1"
 pyproject_hooks = "*"
 tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
@@ -376,6 +571,107 @@ files = [
     {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
 ]
 
+[[package]]
+name = "comm"
+version = "0.2.2"
+description = "Jupyter Python Comm implementation, for usage in ipykernel, xeus-python etc."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "comm-0.2.2-py3-none-any.whl", hash = "sha256:e6fb86cb70ff661ee8c9c14e7d36d6de3b4066f1441be4063df9c5009f0a64d3"},
+    {file = "comm-0.2.2.tar.gz", hash = "sha256:3fd7a84065306e07bea1773df6eb8282de51ba82f77c72f9c85716ab11fe980e"},
+]
+
+[package.dependencies]
+traitlets = ">=4"
+
+[package.extras]
+test = ["pytest"]
+
+[[package]]
+name = "contourpy"
+version = "1.3.0"
+description = "Python library for calculating contours of 2D quadrilateral grids"
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "contourpy-1.3.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:880ea32e5c774634f9fcd46504bf9f080a41ad855f4fef54f5380f5133d343c7"},
+    {file = "contourpy-1.3.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:76c905ef940a4474a6289c71d53122a4f77766eef23c03cd57016ce19d0f7b42"},
+    {file = "contourpy-1.3.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:92f8557cbb07415a4d6fa191f20fd9d2d9eb9c0b61d1b2f52a8926e43c6e9af7"},
+    {file = "contourpy-1.3.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:36f965570cff02b874773c49bfe85562b47030805d7d8360748f3eca570f4cab"},
+    {file = "contourpy-1.3.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:cacd81e2d4b6f89c9f8a5b69b86490152ff39afc58a95af002a398273e5ce589"},
+    {file = "contourpy-1.3.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:69375194457ad0fad3a839b9e29aa0b0ed53bb54db1bfb6c3ae43d111c31ce41"},
+    {file = "contourpy-1.3.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:7a52040312b1a858b5e31ef28c2e865376a386c60c0e248370bbea2d3f3b760d"},
+    {file = "contourpy-1.3.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:3faeb2998e4fcb256542e8a926d08da08977f7f5e62cf733f3c211c2a5586223"},
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+    {file = "contourpy-1.3.0-cp310-cp310-win_amd64.whl", hash = "sha256:87ddffef1dbe5e669b5c2440b643d3fdd8622a348fe1983fad7a0f0ccb1cd67b"},
+    {file = "contourpy-1.3.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:0fa4c02abe6c446ba70d96ece336e621efa4aecae43eaa9b030ae5fb92b309ad"},
+    {file = "contourpy-1.3.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:834e0cfe17ba12f79963861e0f908556b2cedd52e1f75e6578801febcc6a9f49"},
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 version = "7.6.3"
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 rdflib = ["rdflib"]
 tests = ["coverage", "pytest"]
 
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+
 [[package]]
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 version = "2.20.0"
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 typing = ["typing-extensions (>=4.12.2)"]
 
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+plot = ["matplotlib"]
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+symfont = ["sympy"]
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+woff = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "zopfli (>=0.1.4)"]
+
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+optional = false
+python-versions = ">=2.7, !=3.0, !=3.1, !=3.2, !=3.3, !=3.4, <4"
+files = [
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+]
+
+[[package]]
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+description = "A pure-Python, bring-your-own-I/O implementation of HTTP/1.1"
+optional = false
+python-versions = ">=3.7"
+files = [
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+]
+
 [[package]]
 name = "hbreader"
 version = "0.9.1"
@@ -704,6 +1179,52 @@ files = [
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 ]
 
+[[package]]
+name = "httpcore"
+version = "1.0.6"
+description = "A minimal low-level HTTP client."
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "httpcore-1.0.6.tar.gz", hash = "sha256:73f6dbd6eb8c21bbf7ef8efad555481853f5f6acdeaff1edb0694289269ee17f"},
+]
+
+[package.dependencies]
+certifi = "*"
+h11 = ">=0.13,<0.15"
+
+[package.extras]
+asyncio = ["anyio (>=4.0,<5.0)"]
+http2 = ["h2 (>=3,<5)"]
+socks = ["socksio (==1.*)"]
+trio = ["trio (>=0.22.0,<1.0)"]
+
+[[package]]
+name = "httpx"
+version = "0.27.2"
+description = "The next generation HTTP client."
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "httpx-0.27.2.tar.gz", hash = "sha256:f7c2be1d2f3c3c3160d441802406b206c2b76f5947b11115e6df10c6c65e66c2"},
+]
+
+[package.dependencies]
+anyio = "*"
+certifi = "*"
+httpcore = "==1.*"
+idna = "*"
+sniffio = "*"
+
+[package.extras]
+brotli = ["brotli", "brotlicffi"]
+cli = ["click (==8.*)", "pygments (==2.*)", "rich (>=10,<14)"]
+http2 = ["h2 (>=3,<5)"]
+socks = ["socksio (==1.*)"]
+zstd = ["zstandard (>=0.18.0)"]
+
 [[package]]
 name = "hypothesis"
 version = "6.115.2"
@@ -821,6 +1342,28 @@ perf = ["ipython"]
 test = ["flufl.flake8", "importlib-resources (>=1.3)", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6,!=8.1.*)", "pytest-perf (>=0.9.2)"]
 type = ["pytest-mypy"]
 
+[[package]]
+name = "importlib-resources"
+version = "6.4.5"
+description = "Read resources from Python packages"
+optional = false
+python-versions = ">=3.8"
+files = [
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+]
+
+[package.dependencies]
+zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""}
+
+[package.extras]
+check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"]
+cover = ["pytest-cov"]
+doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+enabler = ["pytest-enabler (>=2.2)"]
+test = ["jaraco.test (>=5.4)", "pytest (>=6,!=8.1.*)", "zipp (>=3.17)"]
+type = ["pytest-mypy"]
+
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
@@ -843,6 +1386,97 @@ files = [
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 ]
 
+[[package]]
+name = "ipykernel"
+version = "6.29.5"
+description = "IPython Kernel for Jupyter"
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "ipykernel-6.29.5.tar.gz", hash = "sha256:f093a22c4a40f8828f8e330a9c297cb93dcab13bd9678ded6de8e5cf81c56215"},
+]
+
+[package.dependencies]
+appnope = {version = "*", markers = "platform_system == \"Darwin\""}
+comm = ">=0.1.1"
+debugpy = ">=1.6.5"
+ipython = ">=7.23.1"
+jupyter-client = ">=6.1.12"
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
+matplotlib-inline = ">=0.1"
+nest-asyncio = "*"
+packaging = "*"
+psutil = "*"
+pyzmq = ">=24"
+tornado = ">=6.1"
+traitlets = ">=5.4.0"
+
+[package.extras]
+cov = ["coverage[toml]", "curio", "matplotlib", "pytest-cov", "trio"]
+docs = ["myst-parser", "pydata-sphinx-theme", "sphinx", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "trio"]
+pyqt5 = ["pyqt5"]
+pyside6 = ["pyside6"]
+test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (>=0.23.5)", "pytest-cov", "pytest-timeout"]
+
+[[package]]
+name = "ipython"
+version = "8.18.1"
+description = "IPython: Productive Interactive Computing"
+optional = false
+python-versions = ">=3.9"
+files = [
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+    {file = "ipython-8.18.1.tar.gz", hash = "sha256:ca6f079bb33457c66e233e4580ebfc4128855b4cf6370dddd73842a9563e8a27"},
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+traitlets = ">=5"
+typing-extensions = {version = "*", markers = "python_version < \"3.10\""}
+
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+all = ["black", "curio", "docrepr", "exceptiongroup", "ipykernel", "ipyparallel", "ipywidgets", "matplotlib", "matplotlib (!=3.2.0)", "nbconvert", "nbformat", "notebook", "numpy (>=1.22)", "pandas", "pickleshare", "pytest (<7)", "pytest (<7.1)", "pytest-asyncio (<0.22)", "qtconsole", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "trio", "typing-extensions"]
+black = ["black"]
+doc = ["docrepr", "exceptiongroup", "ipykernel", "matplotlib", "pickleshare", "pytest (<7)", "pytest (<7.1)", "pytest-asyncio (<0.22)", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "typing-extensions"]
+kernel = ["ipykernel"]
+nbconvert = ["nbconvert"]
+nbformat = ["nbformat"]
+notebook = ["ipywidgets", "notebook"]
+parallel = ["ipyparallel"]
+qtconsole = ["qtconsole"]
+test = ["pickleshare", "pytest (<7.1)", "pytest-asyncio (<0.22)", "testpath"]
+test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.22)", "pandas", "pickleshare", "pytest (<7.1)", "pytest-asyncio (<0.22)", "testpath", "trio"]
+
+[[package]]
+name = "ipywidgets"
+version = "8.1.5"
+description = "Jupyter interactive widgets"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "ipywidgets-8.1.5-py3-none-any.whl", hash = "sha256:3290f526f87ae6e77655555baba4f36681c555b8bdbbff430b70e52c34c86245"},
+    {file = "ipywidgets-8.1.5.tar.gz", hash = "sha256:870e43b1a35656a80c18c9503bbf2d16802db1cb487eec6fab27d683381dde17"},
+]
+
+[package.dependencies]
+comm = ">=0.1.3"
+ipython = ">=6.1.0"
+jupyterlab-widgets = ">=3.0.12,<3.1.0"
+traitlets = ">=4.3.1"
+widgetsnbextension = ">=4.0.12,<4.1.0"
+
+[package.extras]
+test = ["ipykernel", "jsonschema", "pytest (>=3.6.0)", "pytest-cov", "pytz"]
+
 [[package]]
 name = "isodate"
 version = "0.6.1"
@@ -857,6 +1491,20 @@ files = [
 [package.dependencies]
 six = "*"
 
+[[package]]
+name = "isoduration"
+version = "20.11.0"
+description = "Operations with ISO 8601 durations"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "isoduration-20.11.0-py3-none-any.whl", hash = "sha256:b2904c2a4228c3d44f409c8ae8e2370eb21a26f7ac2ec5446df141dde3452042"},
+    {file = "isoduration-20.11.0.tar.gz", hash = "sha256:ac2f9015137935279eac671f94f89eb00584f940f5dc49462a0c4ee692ba1bd9"},
+]
+
+[package.dependencies]
+arrow = ">=0.15.0"
+
 [[package]]
 name = "isort"
 version = "5.13.2"
@@ -889,6 +1537,25 @@ more-itertools = "*"
 docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
 testing = ["pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
 
+[[package]]
+name = "jedi"
+version = "0.19.1"
+description = "An autocompletion tool for Python that can be used for text editors."
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "jedi-0.19.1-py2.py3-none-any.whl", hash = "sha256:e983c654fe5c02867aef4cdfce5a2fbb4a50adc0af145f70504238f18ef5e7e0"},
+    {file = "jedi-0.19.1.tar.gz", hash = "sha256:cf0496f3651bc65d7174ac1b7d043eff454892c708a87d1b683e57b569927ffd"},
+]
+
+[package.dependencies]
+parso = ">=0.8.3,<0.9.0"
+
+[package.extras]
+docs = ["Jinja2 (==2.11.3)", "MarkupSafe (==1.1.1)", "Pygments (==2.8.1)", "alabaster (==0.7.12)", "babel (==2.9.1)", "chardet (==4.0.0)", "commonmark (==0.8.1)", "docutils (==0.17.1)", "future (==0.18.2)", "idna (==2.10)", "imagesize (==1.2.0)", "mock (==1.0.1)", "packaging (==20.9)", "pyparsing (==2.4.7)", "pytz (==2021.1)", "readthedocs-sphinx-ext (==2.1.4)", "recommonmark (==0.5.0)", "requests (==2.25.1)", "six (==1.15.0)", "snowballstemmer (==2.1.0)", "sphinx (==1.8.5)", "sphinx-rtd-theme (==0.4.3)", "sphinxcontrib-serializinghtml (==1.1.4)", "sphinxcontrib-websupport (==1.2.4)", "urllib3 (==1.26.4)"]
+qa = ["flake8 (==5.0.4)", "mypy (==0.971)", "types-setuptools (==67.2.0.1)"]
+testing = ["Django", "attrs", "colorama", "docopt", "pytest (<7.0.0)"]
+
 [[package]]
 name = "jeepney"
 version = "0.8.0"
@@ -904,6 +1571,23 @@ files = [
 test = ["async-timeout", "pytest", "pytest-asyncio (>=0.17)", "pytest-trio", "testpath", "trio"]
 trio = ["async_generator", "trio"]
 
+[[package]]
+name = "jinja2"
+version = "3.1.4"
+description = "A very fast and expressive template engine."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "jinja2-3.1.4-py3-none-any.whl", hash = "sha256:bc5dd2abb727a5319567b7a813e6a2e7318c39f4f487cfe6c89c6f9c7d25197d"},
+    {file = "jinja2-3.1.4.tar.gz", hash = "sha256:4a3aee7acbbe7303aede8e9648d13b8bf88a429282aa6122a993f0ac800cb369"},
+]
+
+[package.dependencies]
+MarkupSafe = ">=2.0"
+
+[package.extras]
+i18n = ["Babel (>=2.7)"]
+
 [[package]]
 name = "json-flattener"
 version = "0.1.9"
@@ -919,6 +1603,17 @@ files = [
 click = "*"
 pyyaml = "*"
 
+[[package]]
+name = "json5"
+version = "0.9.25"
+description = "A Python implementation of the JSON5 data format."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "json5-0.9.25-py3-none-any.whl", hash = "sha256:34ed7d834b1341a86987ed52f3f76cd8ee184394906b6e22a1e0deb9ab294e8f"},
+    {file = "json5-0.9.25.tar.gz", hash = "sha256:548e41b9be043f9426776f05df8635a00fe06104ea51ed24b67f908856e151ae"},
+]
+
 [[package]]
 name = "jsonasobj2"
 version = "1.0.4"
@@ -933,6 +1628,17 @@ files = [
 [package.dependencies]
 hbreader = "*"
 
+[[package]]
+name = "jsonpointer"
+version = "3.0.0"
+description = "Identify specific nodes in a JSON document (RFC 6901)"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "jsonpointer-3.0.0-py2.py3-none-any.whl", hash = "sha256:13e088adc14fca8b6aa8177c044e12701e6ad4b28ff10e65f2267a90109c9942"},
+    {file = "jsonpointer-3.0.0.tar.gz", hash = "sha256:2b2d729f2091522d61c3b31f82e11870f60b68f43fbc705cb76bf4b832af59ef"},
+]
+
 [[package]]
 name = "jsonschema"
 version = "4.23.0"
@@ -946,9 +1652,17 @@ files = [
 
 [package.dependencies]
 attrs = ">=22.2.0"
+fqdn = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
+idna = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
+isoduration = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
+jsonpointer = {version = ">1.13", optional = true, markers = "extra == \"format-nongpl\""}
 jsonschema-specifications = ">=2023.03.6"
 referencing = ">=0.28.4"
+rfc3339-validator = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
+rfc3986-validator = {version = ">0.1.0", optional = true, markers = "extra == \"format-nongpl\""}
 rpds-py = ">=0.7.1"
+uri-template = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
+webcolors = {version = ">=24.6.0", optional = true, markers = "extra == \"format-nongpl\""}
 
 [package.extras]
 format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"]
@@ -968,6 +1682,270 @@ files = [
 [package.dependencies]
 referencing = ">=0.31.0"
 
+[[package]]
+name = "jupyter"
+version = "1.1.1"
+description = "Jupyter metapackage. Install all the Jupyter components in one go."
+optional = false
+python-versions = "*"
+files = [
+    {file = "jupyter-1.1.1-py2.py3-none-any.whl", hash = "sha256:7a59533c22af65439b24bbe60373a4e95af8f16ac65a6c00820ad378e3f7cc83"},
+    {file = "jupyter-1.1.1.tar.gz", hash = "sha256:d55467bceabdea49d7e3624af7e33d59c37fff53ed3a350e1ac957bed731de7a"},
+]
+
+[package.dependencies]
+ipykernel = "*"
+ipywidgets = "*"
+jupyter-console = "*"
+jupyterlab = "*"
+nbconvert = "*"
+notebook = "*"
+
+[[package]]
+name = "jupyter-client"
+version = "8.6.3"
+description = "Jupyter protocol implementation and client libraries"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "jupyter_client-8.6.3-py3-none-any.whl", hash = "sha256:e8a19cc986cc45905ac3362915f410f3af85424b4c0905e94fa5f2cb08e8f23f"},
+    {file = "jupyter_client-8.6.3.tar.gz", hash = "sha256:35b3a0947c4a6e9d589eb97d7d4cd5e90f910ee73101611f01283732bd6d9419"},
+]
+
+[package.dependencies]
+importlib-metadata = {version = ">=4.8.3", markers = "python_version < \"3.10\""}
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
+python-dateutil = ">=2.8.2"
+pyzmq = ">=23.0"
+tornado = ">=6.2"
+traitlets = ">=5.3"
+
+[package.extras]
+docs = ["ipykernel", "myst-parser", "pydata-sphinx-theme", "sphinx (>=4)", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"]
+test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pytest (<8.2.0)", "pytest-cov", "pytest-jupyter[client] (>=0.4.1)", "pytest-timeout"]
+
+[[package]]
+name = "jupyter-console"
+version = "6.6.3"
+description = "Jupyter terminal console"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "jupyter_console-6.6.3-py3-none-any.whl", hash = "sha256:309d33409fcc92ffdad25f0bcdf9a4a9daa61b6f341177570fdac03de5352485"},
+    {file = "jupyter_console-6.6.3.tar.gz", hash = "sha256:566a4bf31c87adbfadf22cdf846e3069b59a71ed5da71d6ba4d8aaad14a53539"},
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+ipykernel = ">=6.14"
+ipython = "*"
+jupyter-client = ">=7.0.0"
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
+prompt-toolkit = ">=3.0.30"
+pygments = "*"
+pyzmq = ">=17"
+traitlets = ">=5.4"
+
+[package.extras]
+test = ["flaky", "pexpect", "pytest"]
+
+[[package]]
+name = "jupyter-core"
+version = "5.7.2"
+description = "Jupyter core package. A base package on which Jupyter projects rely."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "jupyter_core-5.7.2-py3-none-any.whl", hash = "sha256:4f7315d2f6b4bcf2e3e7cb6e46772eba760ae459cd1f59d29eb57b0a01bd7409"},
+    {file = "jupyter_core-5.7.2.tar.gz", hash = "sha256:aa5f8d32bbf6b431ac830496da7392035d6f61b4f54872f15c4bd2a9c3f536d9"},
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+platformdirs = ">=2.5"
+pywin32 = {version = ">=300", markers = "sys_platform == \"win32\" and platform_python_implementation != \"PyPy\""}
+traitlets = ">=5.3"
+
+[package.extras]
+docs = ["myst-parser", "pydata-sphinx-theme", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "traitlets"]
+test = ["ipykernel", "pre-commit", "pytest (<8)", "pytest-cov", "pytest-timeout"]
+
+[[package]]
+name = "jupyter-events"
+version = "0.10.0"
+description = "Jupyter Event System library"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "jupyter_events-0.10.0-py3-none-any.whl", hash = "sha256:4b72130875e59d57716d327ea70d3ebc3af1944d3717e5a498b8a06c6c159960"},
+    {file = "jupyter_events-0.10.0.tar.gz", hash = "sha256:670b8229d3cc882ec782144ed22e0d29e1c2d639263f92ca8383e66682845e22"},
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+python-json-logger = ">=2.0.4"
+pyyaml = ">=5.3"
+referencing = "*"
+rfc3339-validator = "*"
+rfc3986-validator = ">=0.1.1"
+traitlets = ">=5.3"
+
+[package.extras]
+cli = ["click", "rich"]
+docs = ["jupyterlite-sphinx", "myst-parser", "pydata-sphinx-theme", "sphinxcontrib-spelling"]
+test = ["click", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (>=0.19.0)", "pytest-console-scripts", "rich"]
+
+[[package]]
+name = "jupyter-lsp"
+version = "2.2.5"
+description = "Multi-Language Server WebSocket proxy for Jupyter Notebook/Lab server"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "jupyter-lsp-2.2.5.tar.gz", hash = "sha256:793147a05ad446f809fd53ef1cd19a9f5256fd0a2d6b7ce943a982cb4f545001"},
+    {file = "jupyter_lsp-2.2.5-py3-none-any.whl", hash = "sha256:45fbddbd505f3fbfb0b6cb2f1bc5e15e83ab7c79cd6e89416b248cb3c00c11da"},
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+[package.dependencies]
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+jupyter-server = ">=1.1.2"
+
+[[package]]
+name = "jupyter-server"
+version = "2.14.2"
+description = "The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "jupyter_server-2.14.2-py3-none-any.whl", hash = "sha256:47ff506127c2f7851a17bf4713434208fc490955d0e8632e95014a9a9afbeefd"},
+    {file = "jupyter_server-2.14.2.tar.gz", hash = "sha256:66095021aa9638ced276c248b1d81862e4c50f292d575920bbe960de1c56b12b"},
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+jupyter-server-terminals = ">=0.4.4"
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+packaging = ">=22.0"
+prometheus-client = ">=0.9"
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+pyzmq = ">=24"
+send2trash = ">=1.8.2"
+terminado = ">=0.8.3"
+tornado = ">=6.2.0"
+traitlets = ">=5.6.0"
+websocket-client = ">=1.7"
+
+[package.extras]
+docs = ["ipykernel", "jinja2", "jupyter-client", "myst-parser", "nbformat", "prometheus-client", "pydata-sphinx-theme", "send2trash", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-openapi (>=0.8.0)", "sphinxcontrib-spelling", "sphinxemoji", "tornado", "typing-extensions"]
+test = ["flaky", "ipykernel", "pre-commit", "pytest (>=7.0,<9)", "pytest-console-scripts", "pytest-jupyter[server] (>=0.7)", "pytest-timeout", "requests"]
+
+[[package]]
+name = "jupyter-server-terminals"
+version = "0.5.3"
+description = "A Jupyter Server Extension Providing Terminals."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "jupyter_server_terminals-0.5.3-py3-none-any.whl", hash = "sha256:41ee0d7dc0ebf2809c668e0fc726dfaf258fcd3e769568996ca731b6194ae9aa"},
+    {file = "jupyter_server_terminals-0.5.3.tar.gz", hash = "sha256:5ae0295167220e9ace0edcfdb212afd2b01ee8d179fe6f23c899590e9b8a5269"},
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+terminado = ">=0.8.3"
+
+[package.extras]
+docs = ["jinja2", "jupyter-server", "mistune (<4.0)", "myst-parser", "nbformat", "packaging", "pydata-sphinx-theme", "sphinxcontrib-github-alt", "sphinxcontrib-openapi", "sphinxcontrib-spelling", "sphinxemoji", "tornado"]
+test = ["jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-jupyter[server] (>=0.5.3)", "pytest-timeout"]
+
+[[package]]
+name = "jupyterlab"
+version = "4.2.5"
+description = "JupyterLab computational environment"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "jupyterlab-4.2.5-py3-none-any.whl", hash = "sha256:73b6e0775d41a9fee7ee756c80f58a6bed4040869ccc21411dc559818874d321"},
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+notebook-shim = ">=0.2"
+packaging = "*"
+setuptools = ">=40.1.0"
+tomli = {version = ">=1.2.2", markers = "python_version < \"3.11\""}
+tornado = ">=6.2.0"
+traitlets = "*"
+
+[package.extras]
+dev = ["build", "bump2version", "coverage", "hatch", "pre-commit", "pytest-cov", "ruff (==0.3.5)"]
+docs = ["jsx-lexer", "myst-parser", "pydata-sphinx-theme (>=0.13.0)", "pytest", "pytest-check-links", "pytest-jupyter", "sphinx (>=1.8,<7.3.0)", "sphinx-copybutton"]
+docs-screenshots = ["altair (==5.3.0)", "ipython (==8.16.1)", "ipywidgets (==8.1.2)", "jupyterlab-geojson (==3.4.0)", "jupyterlab-language-pack-zh-cn (==4.1.post2)", "matplotlib (==3.8.3)", "nbconvert (>=7.0.0)", "pandas (==2.2.1)", "scipy (==1.12.0)", "vega-datasets (==0.9.0)"]
+test = ["coverage", "pytest (>=7.0)", "pytest-check-links (>=0.7)", "pytest-console-scripts", "pytest-cov", "pytest-jupyter (>=0.5.3)", "pytest-timeout", "pytest-tornasync", "requests", "requests-cache", "virtualenv"]
+upgrade-extension = ["copier (>=9,<10)", "jinja2-time (<0.3)", "pydantic (<3.0)", "pyyaml-include (<3.0)", "tomli-w (<2.0)"]
+
+[[package]]
+name = "jupyterlab-pygments"
+version = "0.3.0"
+description = "Pygments theme using JupyterLab CSS variables"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "jupyterlab_pygments-0.3.0-py3-none-any.whl", hash = "sha256:841a89020971da1d8693f1a99997aefc5dc424bb1b251fd6322462a1b8842780"},
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+
+[[package]]
+name = "jupyterlab-server"
+version = "2.27.3"
+description = "A set of server components for JupyterLab and JupyterLab like applications."
+optional = false
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 requests = "*"
 
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 ]
 
+[[package]]
+name = "notebook"
+version = "7.2.2"
+description = "Jupyter Notebook - A web-based notebook environment for interactive computing"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "notebook-7.2.2-py3-none-any.whl", hash = "sha256:c89264081f671bc02eec0ed470a627ed791b9156cad9285226b31611d3e9fe1c"},
+    {file = "notebook-7.2.2.tar.gz", hash = "sha256:2ef07d4220421623ad3fe88118d687bc0450055570cdd160814a59cf3a1c516e"},
+]
+
+[package.dependencies]
+jupyter-server = ">=2.4.0,<3"
+jupyterlab = ">=4.2.0,<4.3"
+jupyterlab-server = ">=2.27.1,<3"
+notebook-shim = ">=0.2,<0.3"
+tornado = ">=6.2.0"
+
+[package.extras]
+dev = ["hatch", "pre-commit"]
+docs = ["myst-parser", "nbsphinx", "pydata-sphinx-theme", "sphinx (>=1.3.6)", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"]
+test = ["importlib-resources (>=5.0)", "ipykernel", "jupyter-server[test] (>=2.4.0,<3)", "jupyterlab-server[test] (>=2.27.1,<3)", "nbval", "pytest (>=7.0)", "pytest-console-scripts", "pytest-timeout", "pytest-tornasync", "requests"]
+
+[[package]]
+name = "notebook-shim"
+version = "0.2.4"
+description = "A shim layer for notebook traits and config"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "notebook_shim-0.2.4-py3-none-any.whl", hash = "sha256:411a5be4e9dc882a074ccbcae671eda64cceb068767e9a3419096986560e1cef"},
+    {file = "notebook_shim-0.2.4.tar.gz", hash = "sha256:b4b2cfa1b65d98307ca24361f5b30fe785b53c3fd07b7a47e89acb5e6ac638cb"},
+]
+
+[package.dependencies]
+jupyter-server = ">=1.8,<3"
+
+[package.extras]
+test = ["pytest", "pytest-console-scripts", "pytest-jupyter", "pytest-tornasync"]
+
 [[package]]
 name = "numpy"
 version = "1.26.4"
@@ -1227,6 +2618,17 @@ files = [
     {file = "numpy-1.26.4.tar.gz", hash = "sha256:2a02aba9ed12e4ac4eb3ea9421c420301a0c6460d9830d74a9df87efa4912010"},
 ]
 
+[[package]]
+name = "overrides"
+version = "7.7.0"
+description = "A decorator to automatically detect mismatch when overriding a method."
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "overrides-7.7.0-py3-none-any.whl", hash = "sha256:c7ed9d062f78b8e4c1a7b70bd8796b35ead4d9f510227ef9c5dc7626c60d7e49"},
+    {file = "overrides-7.7.0.tar.gz", hash = "sha256:55158fa3d93b98cc75299b1e67078ad9003ca27945c76162c1c0766d6f91820a"},
+]
+
 [[package]]
 name = "packaging"
 version = "24.1"
@@ -1276,6 +2678,7 @@ files = [
 
 [package.dependencies]
 numpy = [
+    {version = ">=1.20.3", markers = "python_version < \"3.10\""},
     {version = ">=1.23.2", markers = "python_version >= \"3.11\""},
     {version = ">=1.21.0", markers = "python_version >= \"3.10\" and python_version < \"3.11\""},
 ]
@@ -1285,6 +2688,32 @@ pytz = ">=2020.1"
 [package.extras]
 test = ["hypothesis (>=5.5.3)", "pytest (>=6.0)", "pytest-xdist (>=1.31)"]
 
+[[package]]
+name = "pandocfilters"
+version = "1.5.1"
+description = "Utilities for writing pandoc filters in python"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+files = [
+    {file = "pandocfilters-1.5.1-py2.py3-none-any.whl", hash = "sha256:93be382804a9cdb0a7267585f157e5d1731bbe5545a85b268d6f5fe6232de2bc"},
+    {file = "pandocfilters-1.5.1.tar.gz", hash = "sha256:002b4a555ee4ebc03f8b66307e287fa492e4a77b4ea14d3f934328297bb4939e"},
+]
+
+[[package]]
+name = "parso"
+version = "0.8.4"
+description = "A Python Parser"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "parso-0.8.4-py2.py3-none-any.whl", hash = "sha256:a418670a20291dacd2dddc80c377c5c3791378ee1e8d12bffc35420643d43f18"},
+    {file = "parso-0.8.4.tar.gz", hash = "sha256:eb3a7b58240fb99099a345571deecc0f9540ea5f4dd2fe14c2a99d6b281ab92d"},
+]
+
+[package.extras]
+qa = ["flake8 (==5.0.4)", "mypy (==0.971)", "types-setuptools (==67.2.0.1)"]
+testing = ["docopt", "pytest"]
+
 [[package]]
 name = "pathspec"
 version = "0.12.1"
@@ -1465,6 +2894,7 @@ cleo = ">=2.1.0,<3.0.0"
 crashtest = ">=0.4.1,<0.5.0"
 dulwich = ">=0.21.2,<0.22.0"
 fastjsonschema = ">=2.18.0,<3.0.0"
+importlib-metadata = {version = ">=4.4", markers = "python_version < \"3.10\""}
 installer = ">=0.7.0,<0.8.0"
 keyring = ">=24.0.0,<25.0.0"
 packaging = ">=23.1"
@@ -1559,6 +2989,63 @@ files = [
 curies = ">=0.5.3"
 pyyaml = ">=5.3.1"
 
+[[package]]
+name = "prometheus-client"
+version = "0.21.0"
+description = "Python client for the Prometheus monitoring system."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "prometheus_client-0.21.0-py3-none-any.whl", hash = "sha256:4fa6b4dd0ac16d58bb587c04b1caae65b8c5043e85f778f42f5f632f6af2e166"},
+    {file = "prometheus_client-0.21.0.tar.gz", hash = "sha256:96c83c606b71ff2b0a433c98889d275f51ffec6c5e267de37c7a2b5c9aa9233e"},
+]
+
+[package.extras]
+twisted = ["twisted"]
+
+[[package]]
+name = "prompt-toolkit"
+version = "3.0.48"
+description = "Library for building powerful interactive command lines in Python"
+optional = false
+python-versions = ">=3.7.0"
+files = [
+    {file = "prompt_toolkit-3.0.48-py3-none-any.whl", hash = "sha256:f49a827f90062e411f1ce1f854f2aedb3c23353244f8108b89283587397ac10e"},
+    {file = "prompt_toolkit-3.0.48.tar.gz", hash = "sha256:d6623ab0477a80df74e646bdbc93621143f5caf104206aa29294d53de1a03d90"},
+]
+
+[package.dependencies]
+wcwidth = "*"
+
+[[package]]
+name = "psutil"
+version = "6.0.0"
+description = "Cross-platform lib for process and system monitoring in Python."
+optional = false
+python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
+files = [
+    {file = "psutil-6.0.0-cp27-cp27m-macosx_10_9_x86_64.whl", hash = "sha256:a021da3e881cd935e64a3d0a20983bda0bb4cf80e4f74fa9bfcb1bc5785360c6"},
+    {file = "psutil-6.0.0-cp27-cp27m-manylinux2010_i686.whl", hash = "sha256:1287c2b95f1c0a364d23bc6f2ea2365a8d4d9b726a3be7294296ff7ba97c17f0"},
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+    {file = "psutil-6.0.0-cp27-cp27mu-manylinux2010_i686.whl", hash = "sha256:6ec7588fb3ddaec7344a825afe298db83fe01bfaaab39155fa84cf1c0d6b13c3"},
+    {file = "psutil-6.0.0-cp27-cp27mu-manylinux2010_x86_64.whl", hash = "sha256:1e7c870afcb7d91fdea2b37c24aeb08f98b6d67257a5cb0a8bc3ac68d0f1a68c"},
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+    {file = "psutil-6.0.0-cp36-abi3-macosx_10_9_x86_64.whl", hash = "sha256:c588a7e9b1173b6e866756dde596fd4cad94f9399daf99ad8c3258b3cb2b47a0"},
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+    {file = "psutil-6.0.0-cp36-abi3-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5fd9a97c8e94059b0ef54a7d4baf13b405011176c3b6ff257c247cae0d560ecd"},
+    {file = "psutil-6.0.0-cp36-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e2e8d0054fc88153ca0544f5c4d554d42e33df2e009c4ff42284ac9ebdef4132"},
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+    {file = "psutil-6.0.0-cp36-cp36m-win_amd64.whl", hash = "sha256:34859b8d8f423b86e4385ff3665d3f4d94be3cdf48221fbe476e883514fdb71c"},
+    {file = "psutil-6.0.0-cp37-abi3-win32.whl", hash = "sha256:a495580d6bae27291324fe60cea0b5a7c23fa36a7cd35035a16d93bdcf076b9d"},
+    {file = "psutil-6.0.0-cp37-abi3-win_amd64.whl", hash = "sha256:33ea5e1c975250a720b3a6609c490db40dae5d83a4eb315170c4fe0d8b1f34b3"},
+    {file = "psutil-6.0.0-cp38-abi3-macosx_11_0_arm64.whl", hash = "sha256:ffe7fc9b6b36beadc8c322f84e1caff51e8703b88eee1da46d1e3a6ae11b4fd0"},
+    {file = "psutil-6.0.0.tar.gz", hash = "sha256:8faae4f310b6d969fa26ca0545338b21f73c6b15db7c4a8d934a5482faa818f2"},
+]
+
+[package.extras]
+test = ["enum34", "ipaddress", "mock", "pywin32", "wmi"]
+
 [[package]]
 name = "ptyprocess"
 version = "0.7.0"
@@ -1570,6 +3057,20 @@ files = [
     {file = "ptyprocess-0.7.0.tar.gz", hash = "sha256:5c5d0a3b48ceee0b48485e0c26037c0acd7d29765ca3fbb5cb3831d347423220"},
 ]
 
+[[package]]
+name = "pure-eval"
+version = "0.2.3"
+description = "Safely evaluate AST nodes without side effects"
+optional = false
+python-versions = "*"
+files = [
+    {file = "pure_eval-0.2.3-py3-none-any.whl", hash = "sha256:1db8e35b67b3d218d818ae653e27f06c3aa420901fa7b081ca98cbedc874e0d0"},
+    {file = "pure_eval-0.2.3.tar.gz", hash = "sha256:5f4e983f40564c576c7c8635ae88db5956bb2229d7e9237d03b3c0b0190eaf42"},
+]
+
+[package.extras]
+tests = ["pytest"]
+
 [[package]]
 name = "py"
 version = "1.11.0"
@@ -1713,6 +3214,20 @@ files = [
 [package.dependencies]
 typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
 
+[[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 = "pyparsing"
 version = "3.2.0"
@@ -1802,6 +3317,17 @@ files = [
 [package.dependencies]
 six = ">=1.5"
 
+[[package]]
+name = "python-json-logger"
+version = "2.0.7"
+description = "A python library adding a json log formatter"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "python-json-logger-2.0.7.tar.gz", hash = "sha256:23e7ec02d34237c5aa1e29a070193a4ea87583bb4e7f8fd06d3de8264c4b2e1c"},
+    {file = "python_json_logger-2.0.7-py3-none-any.whl", hash = "sha256:f380b826a991ebbe3de4d897aeec42760035ac760345e57b812938dc8b35e2bd"},
+]
+
 [[package]]
 name = "pytrie"
 version = "0.4.0"
@@ -1826,6 +3352,33 @@ files = [
     {file = "pytz-2024.2.tar.gz", hash = "sha256:2aa355083c50a0f93fa581709deac0c9ad65cca8a9e9beac660adcbd493c798a"},
 ]
 
+[[package]]
+name = "pywin32"
+version = "308"
+description = "Python for Window Extensions"
+optional = false
+python-versions = "*"
+files = [
+    {file = "pywin32-308-cp310-cp310-win32.whl", hash = "sha256:796ff4426437896550d2981b9c2ac0ffd75238ad9ea2d3bfa67a1abd546d262e"},
+    {file = "pywin32-308-cp310-cp310-win_amd64.whl", hash = "sha256:4fc888c59b3c0bef905ce7eb7e2106a07712015ea1c8234b703a088d46110e8e"},
+    {file = "pywin32-308-cp310-cp310-win_arm64.whl", hash = "sha256:a5ab5381813b40f264fa3495b98af850098f814a25a63589a8e9eb12560f450c"},
+    {file = "pywin32-308-cp311-cp311-win32.whl", hash = "sha256:5d8c8015b24a7d6855b1550d8e660d8daa09983c80e5daf89a273e5c6fb5095a"},
+    {file = "pywin32-308-cp311-cp311-win_amd64.whl", hash = "sha256:575621b90f0dc2695fec346b2d6302faebd4f0f45c05ea29404cefe35d89442b"},
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+    {file = "pywin32-308-cp313-cp313-win_arm64.whl", hash = "sha256:ef313c46d4c18dfb82a2431e3051ac8f112ccee1a34f29c263c583c568db63cd"},
+    {file = "pywin32-308-cp37-cp37m-win32.whl", hash = "sha256:1f696ab352a2ddd63bd07430080dd598e6369152ea13a25ebcdd2f503a38f1ff"},
+    {file = "pywin32-308-cp37-cp37m-win_amd64.whl", hash = "sha256:13dcb914ed4347019fbec6697a01a0aec61019c1046c2b905410d197856326a6"},
+    {file = "pywin32-308-cp38-cp38-win32.whl", hash = "sha256:5794e764ebcabf4ff08c555b31bd348c9025929371763b2183172ff4708152f0"},
+    {file = "pywin32-308-cp38-cp38-win_amd64.whl", hash = "sha256:3b92622e29d651c6b783e368ba7d6722b1634b8e70bd376fd7610fe1992e19de"},
+    {file = "pywin32-308-cp39-cp39-win32.whl", hash = "sha256:7873ca4dc60ab3287919881a7d4f88baee4a6e639aa6962de25a98ba6b193341"},
+    {file = "pywin32-308-cp39-cp39-win_amd64.whl", hash = "sha256:71b3322d949b4cc20776436a9c9ba0eeedcbc9c650daa536df63f0ff111bb920"},
+]
+
 [[package]]
 name = "pywin32-ctypes"
 version = "0.2.3"
@@ -1837,6 +3390,21 @@ files = [
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 ]
 
+[[package]]
+name = "pywinpty"
+version = "2.0.13"
+description = "Pseudo terminal support for Windows from Python."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "pywinpty-2.0.13-cp310-none-win_amd64.whl", hash = "sha256:697bff211fb5a6508fee2dc6ff174ce03f34a9a233df9d8b5fe9c8ce4d5eaf56"},
+    {file = "pywinpty-2.0.13-cp311-none-win_amd64.whl", hash = "sha256:b96fb14698db1284db84ca38c79f15b4cfdc3172065b5137383910567591fa99"},
+    {file = "pywinpty-2.0.13-cp312-none-win_amd64.whl", hash = "sha256:2fd876b82ca750bb1333236ce98488c1be96b08f4f7647cfdf4129dfad83c2d4"},
+    {file = "pywinpty-2.0.13-cp38-none-win_amd64.whl", hash = "sha256:61d420c2116c0212808d31625611b51caf621fe67f8a6377e2e8b617ea1c1f7d"},
+    {file = "pywinpty-2.0.13-cp39-none-win_amd64.whl", hash = "sha256:71cb613a9ee24174730ac7ae439fd179ca34ccb8c5349e8d7b72ab5dea2c6f4b"},
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+]
+
 [[package]]
 name = "pyyaml"
 version = "6.0.2"
@@ -1899,6 +3467,127 @@ files = [
     {file = "pyyaml-6.0.2.tar.gz", hash = "sha256:d584d9ec91ad65861cc08d42e834324ef890a082e591037abe114850ff7bbc3e"},
 ]
 
+[[package]]
+name = "pyzmq"
+version = "26.2.0"
+description = "Python bindings for 0MQ"
+optional = false
+python-versions = ">=3.7"
+files = [
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+core = ["importlib-metadata (>=6)", "importlib-resources (>=5.10.2)", "jaraco.collections", "jaraco.functools", "jaraco.text (>=3.7)", "more-itertools", "more-itertools (>=8.8)", "packaging", "packaging (>=24)", "platformdirs (>=2.6.2)", "tomli (>=2.0.1)", "wheel (>=0.43.0)"]
+cover = ["pytest-cov"]
+doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "pyproject-hooks (!=1.1)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier", "towncrier (<24.7)"]
+enabler = ["pytest-enabler (>=2.2)"]
+test = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "jaraco.test", "packaging (>=23.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.*)", "pytest-home (>=0.5)", "pytest-perf", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel (>=0.44.0)"]
+type = ["importlib-metadata (>=7.0.2)", "jaraco.develop (>=7.21)", "mypy (==1.11.*)", "pytest-mypy"]
+
 [[package]]
 name = "shellingham"
 version = "1.5.4"
@@ -2317,6 +4059,17 @@ files = [
     {file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
 ]
 
+[[package]]
+name = "sniffio"
+version = "1.3.1"
+description = "Sniff out which async library your code is running under"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "sniffio-1.3.1-py3-none-any.whl", hash = "sha256:2f6da418d1f1e0fddd844478f41680e794e6051915791a034ff65e5f100525a2"},
+    {file = "sniffio-1.3.1.tar.gz", hash = "sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc"},
+]
+
 [[package]]
 name = "sortedcontainers"
 version = "2.4.0"
@@ -2328,6 +4081,36 @@ files = [
     {file = "sortedcontainers-2.4.0.tar.gz", hash = "sha256:25caa5a06cc30b6b83d11423433f65d1f9d76c4c6a0c90e3379eaa43b9bfdb88"},
 ]
 
+[[package]]
+name = "soupsieve"
+version = "2.6"
+description = "A modern CSS selector implementation for Beautiful Soup."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "soupsieve-2.6-py3-none-any.whl", hash = "sha256:e72c4ff06e4fb6e4b5a9f0f55fe6e81514581fca1515028625d0f299c602ccc9"},
+    {file = "soupsieve-2.6.tar.gz", hash = "sha256:e2e68417777af359ec65daac1057404a3c8a5455bb8abc36f1a9866ab1a51abb"},
+]
+
+[[package]]
+name = "stack-data"
+version = "0.6.3"
+description = "Extract data from python stack frames and tracebacks for informative displays"
+optional = false
+python-versions = "*"
+files = [
+    {file = "stack_data-0.6.3-py3-none-any.whl", hash = "sha256:d5558e0c25a4cb0853cddad3d77da9891a08cb85dd9f9f91b9f8cd66e511e695"},
+    {file = "stack_data-0.6.3.tar.gz", hash = "sha256:836a778de4fec4dcd1dcd89ed8abff8a221f58308462e1c4aa2a3cf30148f0b9"},
+]
+
+[package.dependencies]
+asttokens = ">=2.1.0"
+executing = ">=1.2.0"
+pure-eval = "*"
+
+[package.extras]
+tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]
+
 [[package]]
 name = "tblib"
 version = "3.0.0"
@@ -2339,15 +4122,36 @@ files = [
     {file = "tblib-3.0.0.tar.gz", hash = "sha256:93622790a0a29e04f0346458face1e144dc4d32f493714c6c3dff82a4adb77e6"},
 ]
 
+[[package]]
+name = "terminado"
+version = "0.18.1"
+description = "Tornado websocket backend for the Xterm.js Javascript terminal emulator library."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "terminado-0.18.1-py3-none-any.whl", hash = "sha256:a4468e1b37bb318f8a86514f65814e1afc977cf29b3992a4500d9dd305dcceb0"},
+    {file = "terminado-0.18.1.tar.gz", hash = "sha256:de09f2c4b85de4765f7714688fff57d3e75bad1f909b589fde880460c753fd2e"},
+]
+
+[package.dependencies]
+ptyprocess = {version = "*", markers = "os_name != \"nt\""}
+pywinpty = {version = ">=1.1.0", markers = "os_name == \"nt\""}
+tornado = ">=6.1.0"
+
+[package.extras]
+docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
+test = ["pre-commit", "pytest (>=7.0)", "pytest-timeout"]
+typing = ["mypy (>=1.6,<2.0)", "traitlets (>=5.11.1)"]
+
 [[package]]
 name = "tifffile"
-version = "2024.9.20"
+version = "2024.8.30"
 description = "Read and write TIFF files"
 optional = false
-python-versions = ">=3.10"
+python-versions = ">=3.9"
 files = [
-    {file = "tifffile-2024.9.20-py3-none-any.whl", hash = "sha256:c54dc85bc1065d972cb8a6ffb3181389d597876aa80177933459733e4ed243dd"},
-    {file = "tifffile-2024.9.20.tar.gz", hash = "sha256:3fbf3be2f995a7051a8ae05a4be70c96fc0789f22ed6f1c4104c973cf68a640b"},
+    {file = "tifffile-2024.8.30-py3-none-any.whl", hash = "sha256:8bc59a8f02a2665cd50a910ec64961c5373bee0b8850ec89d3b7b485bf7be7ad"},
+    {file = "tifffile-2024.8.30.tar.gz", hash = "sha256:2c9508fe768962e30f87def61819183fb07692c258cb175b3c114828368485a4"},
 ]
 
 [package.dependencies]
@@ -2361,6 +4165,24 @@ test = ["cmapfile", "czifile", "dask", "defusedxml", "fsspec", "imagecodecs", "l
 xml = ["defusedxml", "lxml"]
 zarr = ["fsspec", "zarr"]
 
+[[package]]
+name = "tinycss2"
+version = "1.3.0"
+description = "A tiny CSS parser"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "tinycss2-1.3.0-py3-none-any.whl", hash = "sha256:54a8dbdffb334d536851be0226030e9505965bb2f30f21a4a82c55fb2a80fae7"},
+    {file = "tinycss2-1.3.0.tar.gz", hash = "sha256:152f9acabd296a8375fbca5b84c961ff95971fcfc32e79550c8df8e29118c54d"},
+]
+
+[package.dependencies]
+webencodings = ">=0.4"
+
+[package.extras]
+doc = ["sphinx", "sphinx_rtd_theme"]
+test = ["pytest", "ruff"]
+
 [[package]]
 name = "tomli"
 version = "2.0.2"
@@ -2383,6 +4205,26 @@ files = [
     {file = "tomlkit-0.13.2.tar.gz", hash = "sha256:fff5fe59a87295b278abd31bec92c15d9bc4a06885ab12bcea52c71119392e79"},
 ]
 
+[[package]]
+name = "tornado"
+version = "6.4.1"
+description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "tornado-6.4.1-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:163b0aafc8e23d8cdc3c9dfb24c5368af84a81e3364745ccb4427669bf84aec8"},
+    {file = "tornado-6.4.1-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:6d5ce3437e18a2b66fbadb183c1d3364fb03f2be71299e7d10dbeeb69f4b2a14"},
+    {file = "tornado-6.4.1-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e2e20b9113cd7293f164dc46fffb13535266e713cdb87bd2d15ddb336e96cfc4"},
+    {file = "tornado-6.4.1-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8ae50a504a740365267b2a8d1a90c9fbc86b780a39170feca9bcc1787ff80842"},
+    {file = "tornado-6.4.1-cp38-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:613bf4ddf5c7a95509218b149b555621497a6cc0d46ac341b30bd9ec19eac7f3"},
+    {file = "tornado-6.4.1-cp38-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:25486eb223babe3eed4b8aecbac33b37e3dd6d776bc730ca14e1bf93888b979f"},
+    {file = "tornado-6.4.1-cp38-abi3-musllinux_1_2_i686.whl", hash = "sha256:454db8a7ecfcf2ff6042dde58404164d969b6f5d58b926da15e6b23817950fc4"},
+    {file = "tornado-6.4.1-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:a02a08cc7a9314b006f653ce40483b9b3c12cda222d6a46d4ac63bb6c9057698"},
+    {file = "tornado-6.4.1-cp38-abi3-win32.whl", hash = "sha256:d9a566c40b89757c9aa8e6f032bcdb8ca8795d7c1a9762910c722b1635c9de4d"},
+    {file = "tornado-6.4.1-cp38-abi3-win_amd64.whl", hash = "sha256:b24b8982ed444378d7f21d563f4180a2de31ced9d8d84443907a0a64da2072e7"},
+    {file = "tornado-6.4.1.tar.gz", hash = "sha256:92d3ab53183d8c50f8204a51e6f91d18a15d5ef261e84d452800d4ff6fc504e9"},
+]
+
 [[package]]
 name = "tox"
 version = "3.28.0"
@@ -2408,6 +4250,21 @@ virtualenv = ">=16.0.0,<20.0.0 || >20.0.0,<20.0.1 || >20.0.1,<20.0.2 || >20.0.2,
 docs = ["pygments-github-lexers (>=0.0.5)", "sphinx (>=2.0.0)", "sphinxcontrib-autoprogram (>=0.1.5)", "towncrier (>=18.5.0)"]
 testing = ["flaky (>=3.4.0)", "freezegun (>=0.3.11)", "pathlib2 (>=2.3.3)", "psutil (>=5.6.1)", "pytest (>=4.0.0)", "pytest-cov (>=2.5.1)", "pytest-mock (>=1.10.0)", "pytest-randomly (>=1.0.0)"]
 
+[[package]]
+name = "traitlets"
+version = "5.14.3"
+description = "Traitlets Python configuration system"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "traitlets-5.14.3-py3-none-any.whl", hash = "sha256:b74e89e397b1ed28cc831db7aea759ba6640cb3de13090ca145426688ff1ac4f"},
+    {file = "traitlets-5.14.3.tar.gz", hash = "sha256:9ed0579d3502c94b4b3732ac120375cda96f923114522847de4b3bb98b96b6b7"},
+]
+
+[package.extras]
+docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
+test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,<8.2)", "pytest-mock", "pytest-mypy-testing"]
+
 [[package]]
 name = "trove-classifiers"
 version = "2024.10.13"
@@ -2419,6 +4276,17 @@ files = [
     {file = "trove_classifiers-2024.10.13.tar.gz", hash = "sha256:b820fc6f9544543afa15e5d9cfc426cde3b20fc2246dff6f019b835731508cef"},
 ]
 
+[[package]]
+name = "types-python-dateutil"
+version = "2.9.0.20241003"
+description = "Typing stubs for python-dateutil"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "types-python-dateutil-2.9.0.20241003.tar.gz", hash = "sha256:58cb85449b2a56d6684e41aeefb4c4280631246a0da1a719bdbe6f3fb0317446"},
+    {file = "types_python_dateutil-2.9.0.20241003-py3-none-any.whl", hash = "sha256:250e1d8e80e7bbc3a6c99b907762711d1a1cdd00e978ad39cb5940f6f0a87f3d"},
+]
+
 [[package]]
 name = "typing-extensions"
 version = "4.12.2"
@@ -2430,6 +4298,20 @@ files = [
     {file = "typing_extensions-4.12.2.tar.gz", hash = "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8"},
 ]
 
+[[package]]
+name = "uri-template"
+version = "1.3.0"
+description = "RFC 6570 URI Template Processor"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "uri-template-1.3.0.tar.gz", hash = "sha256:0e00f8eb65e18c7de20d595a14336e9f337ead580c70934141624b6d1ffdacc7"},
+    {file = "uri_template-1.3.0-py3-none-any.whl", hash = "sha256:a44a133ea12d44a0c0f06d7d42a52d71282e77e2f937d8abd5655b8d56fc1363"},
+]
+
+[package.extras]
+dev = ["flake8", "flake8-annotations", "flake8-bandit", "flake8-bugbear", "flake8-commas", "flake8-comprehensions", "flake8-continuation", "flake8-datetimez", "flake8-docstrings", "flake8-import-order", "flake8-literal", "flake8-modern-annotations", "flake8-noqa", "flake8-pyproject", "flake8-requirements", "flake8-typechecking-import", "flake8-use-fstring", "mypy", "pep8-naming", "types-PyYAML"]
+
 [[package]]
 name = "urllib3"
 version = "2.2.3"
@@ -2467,6 +4349,70 @@ platformdirs = ">=3.9.1,<5"
 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 = "wcwidth"
+version = "0.2.13"
+description = "Measures the displayed width of unicode strings in a terminal"
+optional = false
+python-versions = "*"
+files = [
+    {file = "wcwidth-0.2.13-py2.py3-none-any.whl", hash = "sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859"},
+    {file = "wcwidth-0.2.13.tar.gz", hash = "sha256:72ea0c06399eb286d978fdedb6923a9eb47e1c486ce63e9b4e64fc18303972b5"},
+]
+
+[[package]]
+name = "webcolors"
+version = "24.8.0"
+description = "A library for working with the color formats defined by HTML and CSS."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "webcolors-24.8.0-py3-none-any.whl", hash = "sha256:fc4c3b59358ada164552084a8ebee637c221e4059267d0f8325b3b560f6c7f0a"},
+    {file = "webcolors-24.8.0.tar.gz", hash = "sha256:08b07af286a01bcd30d583a7acadf629583d1f79bfef27dd2c2c5c263817277d"},
+]
+
+[package.extras]
+docs = ["furo", "sphinx", "sphinx-copybutton", "sphinx-inline-tabs", "sphinx-notfound-page", "sphinxext-opengraph"]
+tests = ["coverage[toml]"]
+
+[[package]]
+name = "webencodings"
+version = "0.5.1"
+description = "Character encoding aliases for legacy web content"
+optional = false
+python-versions = "*"
+files = [
+    {file = "webencodings-0.5.1-py2.py3-none-any.whl", hash = "sha256:a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78"},
+    {file = "webencodings-0.5.1.tar.gz", hash = "sha256:b36a1c245f2d304965eb4e0a82848379241dc04b865afcc4aab16748587e1923"},
+]
+
+[[package]]
+name = "websocket-client"
+version = "1.8.0"
+description = "WebSocket client for Python with low level API options"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "websocket_client-1.8.0-py3-none-any.whl", hash = "sha256:17b44cc997f5c498e809b22cdf2d9c7a9e71c02c8cc2b6c56e7c2d1239bfa526"},
+    {file = "websocket_client-1.8.0.tar.gz", hash = "sha256:3239df9f44da632f96012472805d40a23281a991027ce11d2f45a6f24ac4c3da"},
+]
+
+[package.extras]
+docs = ["Sphinx (>=6.0)", "myst-parser (>=2.0.0)", "sphinx-rtd-theme (>=1.1.0)"]
+optional = ["python-socks", "wsaccel"]
+test = ["websockets"]
+
+[[package]]
+name = "widgetsnbextension"
+version = "4.0.13"
+description = "Jupyter interactive widgets for Jupyter Notebook"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "widgetsnbextension-4.0.13-py3-none-any.whl", hash = "sha256:74b2692e8500525cc38c2b877236ba51d34541e6385eeed5aec15a70f88a6c71"},
+    {file = "widgetsnbextension-4.0.13.tar.gz", hash = "sha256:ffcb67bc9febd10234a362795f643927f4e0c05d9342c727b65d2384f8feacb6"},
+]
+
 [[package]]
 name = "wrapt"
 version = "1.16.0"
@@ -2640,5 +4586,5 @@ type = ["pytest-mypy"]
 
 [metadata]
 lock-version = "2.0"
-python-versions = ">=3.10.12 <3.12"
-content-hash = "2bf8c80a808841bc3b35049546502caf15bc227e646ef1cdff02768d81bcc575"
+python-versions = ">=3.9.18 <3.12"
+content-hash = "bc485ecf1a3aa6a180f8a8beb1b1abbd118297e43203cb48b72af7434ec35b5c"
diff --git a/pyproject.toml b/pyproject.toml
index ca494c0..d46e61b 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -14,7 +14,7 @@ documentation = "https://github.com/MontpellierRessourcesImagerie/microscope-met
 keywords = ["microscopy", "metrology"]
 
 [tool.pytest.ini_options]
-addopts = "--hypothesis-show-statistics --hypothesis-profile=dev --workers=auto"
+addopts = "--hypothesis-show-statistics --hypothesis-profile=dev" # --workers=auto"
 testpaths = [
     "tests"
 ]
@@ -30,13 +30,17 @@ filterwarnings = [
     "ignore:.*urllib3 v2 only supports OpenSSL.*:Warning",
 ]
 
+[tool.isort]
+profile = "black"
+
 [tool.poetry.dependencies]
-python = ">=3.10.12 <3.12"
+python = ">=3.9.18 <3.12"
 numpy = "^1"
 scikit-image = "^0"
 scipy = "^1"
 pandas = "^1"
-microscopemetrics-schema = {git = "https://github.com/juliomateoslangerak/microscopemetrics-schema.git"}
+matplotlib = "^3"
+microscopemetrics-schema = {git = "https://github.com/juliomateoslangerak/microscopemetrics-schema.git", branch = "dev"}
 
 [tool.poetry.group.test.dependencies]
 pytest = "^7"
@@ -48,6 +52,7 @@ pytest-parallel = "^0.1.1"
 [tool.poetry.group.dev.dependencies]
 black = "^23"
 poetry = "^1"
+jupyter = "^1"
 isort = "^5"
 pre-commit = "^3"
 
diff --git a/src/microscopemetrics/samples/__init__.py b/src/microscopemetrics/analyses/__init__.py
similarity index 63%
rename from src/microscopemetrics/samples/__init__.py
rename to src/microscopemetrics/analyses/__init__.py
index c204c02..828d547 100644
--- a/src/microscopemetrics/samples/__init__.py
+++ b/src/microscopemetrics/analyses/__init__.py
@@ -1,4 +1,4 @@
-# Main samples module defining the sample superclass
+# Main analyses module defining the sample superclass
 import logging
 from abc import ABC, abstractmethod
 from datetime import datetime
@@ -8,51 +8,8 @@
 import numpy as np
 import pandas as pd
 
-# We are defining some global dictionaries to register the different analysis types
-IMAGE_ANALYSIS_REGISTRY = {}
-DATASET_ANALYSIS_REGISTRY = {}
-PROGRESSION_ANALYSIS_REGISTRY = {}
-
-
-# Decorators to register exposed analysis functions
-def register_image_analysis(cls):
-    IMAGE_ANALYSIS_REGISTRY[cls.__name__] = cls
-    return cls
-
-
-def register_dataset_analysis(cls):
-    DATASET_ANALYSIS_REGISTRY[cls.__name__] = cls
-    return cls
-
-
-def register_progression_analysis(cls):
-    PROGRESSION_ANALYSIS_REGISTRY[cls.__name__] = cls
-    return cls
-
-
 # Create a logging service
 logger = logging.getLogger(__name__)
-# TODO: work on the loggers
-
-
-# def get_references(
-#     objects: Union[mm_schema.MetricsObject, list[mm_schema.MetricsObject]]
-# ) -> List[mm_schema.DataReference]:
-#     """Get the references of a metrics object or a list of metrics objects"""
-#     if isinstance(objects, mm_schema.MetricsObject):
-#         return mm_schema.DataReference(
-#             data_uri=objects.data_uri,
-#             # HACK: This is a temporary fix to get the first element of the tuple
-#             omero_host=objects.omero_host[0],
-#             omero_port=objects.omero_port[0],
-#             omero_object_type=objects.omero_object_type[0],
-#             omero_object_id=objects.omero_object_id,
-#         )
-#
-#     elif isinstance(objects, list):
-#         return [get_references(obj) for obj in objects]
-#     else:
-#         raise ValueError("Input should be a metrics object or a list of metrics objects")
 
 
 def get_object_id(
@@ -152,72 +109,6 @@ def numpy_to_mm_image(
     )
 
 
-# def numpy_to_mask_inlined(
-#     array: np.ndarray,
-#     name: str = None,
-#     description: str = None,
-#     image_url: str = None,
-#     source_image_url: Union[str, List[str]] = None,
-# ) -> mm_schema.ImageMask:
-#     """Converts a bool numpy array with dimensions order yx to an inlined mask"""
-#     if array.ndim != 2:
-#         raise ValueError("Input array should be 2D")
-#     if array.dtype != bool and array.dtype == np.uint8:
-#         try:
-#             array = array.astype(bool)
-#         except ValueError:
-#             raise ValueError("Input array could not be casted to type bool")
-#     if array.dtype != bool:
-#         raise ValueError("Input array should be of type bool")
-#
-#     return mm_schema.ImageMask(
-#         name=name,
-#         description=description,
-#         image_url=image_url,
-#         source_image_url=source_image_url,
-#         data=array.flatten().tolist(),
-#         shape_y=array.shape[0],
-#         shape_x=array.shape[1],
-#     )
-#
-#
-# def numpy_to_image_inlined(
-#     array: np.ndarray,
-#     name: str = None,
-#     description: str = None,
-#     image_url: str = None,
-#     source_image_url: Union[str, List[str]] = None,
-# ) -> mm_schema.ImageInline:
-#     """Converts a numpy array with dimensions order tzyxc or yx to an inlined image"""
-#     if array.ndim == 5:
-#         return mm_schema.Image5D(
-#             name=name,
-#             description=description,
-#             image_url=image_url,
-#             source_image_url=source_image_url,
-#             data=array.flatten().tolist(),
-#             shape_t=array.shape[0],
-#             shape_z=array.shape[1],
-#             shape_y=array.shape[2],
-#             shape_x=array.shape[3],
-#             shape_c=array.shape[4],
-#         )
-#     elif array.ndim == 2:
-#         return mm_schema.Image2D(
-#             name=name,
-#             description=description,
-#             image_url=image_url,
-#             source_image_url=source_image_url,
-#             data=array.flatten().tolist(),
-#             shape_y=array.shape[0],
-#             shape_x=array.shape[1],
-#         )
-#     else:
-#         raise NotImplementedError(
-#             f"Array of dimension {array.ndim} is not supported by this function"
-#         )
-
-
 def _create_table(
     data: Union[dict[str, list], pd.DataFrame],
     name: str,
diff --git a/src/microscopemetrics/samples/argolight.py b/src/microscopemetrics/analyses/argolight.py
similarity index 89%
rename from src/microscopemetrics/samples/argolight.py
rename to src/microscopemetrics/analyses/argolight.py
index 7104884..d5ad191 100644
--- a/src/microscopemetrics/samples/argolight.py
+++ b/src/microscopemetrics/analyses/argolight.py
@@ -1,24 +1,25 @@
 from datetime import datetime
 from itertools import product
-from typing import Any, Dict, List, Tuple, Union
+from typing import Dict, List, Tuple
 
 import microscopemetrics_schema.datamodel as mm_schema
 import numpy as np
 import pandas as pd
 from numpy import float64, int64, ndarray
 from pandas import DataFrame
-from scipy.interpolate import griddata
 from scipy.optimize import curve_fit
 from scipy.signal import find_peaks
 from skimage.transform import hough_line  # hough_line_peaks, probabilistic_hough_line
 
-from microscopemetrics.analysis.tools import (
+from microscopemetrics.analyses import logger, numpy_to_mm_image, validate_requirements
+from microscopemetrics.analyses.tools import (
+    airy_fun,
     compute_distances_matrix,
     compute_spots_properties,
+    is_saturated,
+    multi_airy_fun,
     segment_image,
 )
-from microscopemetrics.samples import logger, numpy_to_mm_image, validate_requirements
-from microscopemetrics.utilities.utilities import airy_fun, is_saturated, multi_airy_fun
 
 
 def _profile_to_columns(profile: ndarray, channel: int) -> List[Dict[str, Dict[str, List[float]]]]:
@@ -223,12 +224,12 @@ def _compute_resolution(
     )
 
 
-def analise_argolight_b(dataset: mm_schema.ArgolightBDataset) -> bool:
+def analyse_argolight_b(dataset: mm_schema.ArgolightBDataset) -> bool:
     validate_requirements()
 
     # Check image shape
     logger.info("Checking image shape...")
-    image = dataset.input.argolight_b_image.data
+    image = dataset.input_data.argolight_b_image.data
     if len(image.shape) != 5:
         logger.error("Image must be 5D")
         return False
@@ -239,8 +240,8 @@ def analise_argolight_b(dataset: mm_schema.ArgolightBDataset) -> bool:
     for c in range(image.shape[-1]):
         if is_saturated(
             channel=image[:, :, :, :, c],
-            threshold=dataset.input.saturation_threshold,
-            detector_bit_depth=dataset.input.bit_depth,
+            threshold=dataset.input_parameters.saturation_threshold,
+            detector_bit_depth=dataset.input_parameters.bit_depth,
         ):
             logger.error(f"Channel {c} is saturated")
             saturated_channels.append(c)
@@ -249,32 +250,36 @@ def analise_argolight_b(dataset: mm_schema.ArgolightBDataset) -> bool:
         return False
 
     # Calculating the distance between spots in pixels with a security margin
-    min_distance = round(dataset.input.spots_distance * 0.3)
+    min_distance = round(dataset.input_parameters.spots_distance * 0.3)
 
     # Calculating the maximum tolerated distance in microns for the same spot in a different channels
-    max_distance = dataset.input.spots_distance * 0.4
+    max_distance = dataset.input_parameters.spots_distance * 0.4
 
     labels = segment_image(
         image=image,
         min_distance=min_distance,
-        sigma=(dataset.input.sigma_z, dataset.input.sigma_y, dataset.input.sigma_x),
+        sigma=(
+            dataset.input_parameters.sigma_z,
+            dataset.input_parameters.sigma_y,
+            dataset.input_parameters.sigma_x,
+        ),
         method="local_max",
-        low_corr_factors=dataset.input.lower_threshold_correction_factors,
-        high_corr_factors=dataset.input.upper_threshold_correction_factors,
+        low_corr_factors=dataset.input_parameters.lower_threshold_correction_factors,
+        high_corr_factors=dataset.input_parameters.upper_threshold_correction_factors,
     )
 
     dataset.output.spots_labels_image = numpy_to_mm_image(  # TODO: this should be a mask
         array=labels,
-        name=f"{dataset.input.argolight_b_image.name}_spots_labels",
-        description=f"Spots labels of {dataset.input.argolight_b_image.image_url}",
-        image_url=dataset.input.argolight_b_image.image_url,
-        source_image_url=dataset.input.argolight_b_image.image_url,
+        name=f"{dataset.input_data.argolight_b_image.name}_spots_labels",
+        description=f"Spots labels of {dataset.input_data.argolight_b_image.image_url}",
+        image_url=dataset.input_data.argolight_b_image.image_url,
+        source_image_url=dataset.input_data.argolight_b_image.image_url,
     )
 
     spots_properties, spots_positions = compute_spots_properties(
         image=image,
         labels=labels,
-        remove_center_cross=dataset.input.remove_center_cross,
+        remove_center_cross=dataset.input_parameters.remove_center_cross,
     )
 
     distances_df = compute_distances_matrix(
@@ -338,7 +343,7 @@ def analise_argolight_b(dataset: mm_schema.ArgolightBDataset) -> bool:
         spots_centroids.append(
             mm_schema.Roi(
                 label=f"Centroids_ch{ch:02}",
-                image=dataset.input.argolight_b_image.image_url,
+                image=dataset.input_data.argolight_b_image.image_url,
                 shapes=channel_shapes,
             )
         )
@@ -398,7 +403,7 @@ def analise_argolight_b(dataset: mm_schema.ArgolightBDataset) -> bool:
     return True
 
 
-def analise_argolight_e(dataset: mm_schema.ArgolightEDataset) -> bool:
+def analyse_argolight_e(dataset: mm_schema.ArgolightEDataset) -> bool:
     validate_requirements()
 
     # Check image shape
@@ -410,11 +415,11 @@ def analise_argolight_e(dataset: mm_schema.ArgolightEDataset) -> bool:
     # Check for axis value
     pass  # TODO: implement
 
-    image = dataset.input.argolight_e_image.data
+    image = dataset.input_data.argolight_e_image.data
     image = image[0]  # if there is a time dimension, take the first one
-    axis = dataset.input.orientation_axis
-    pixel_size = dataset.input.argolight_e_image.voxel_size_x_micron
-    measured_band = dataset.input.measured_band
+    axis = dataset.input_parameters.orientation_axis
+    pixel_size = dataset.input_data.argolight_e_image.voxel_size_x_micron
+    measured_band = dataset.input_parameters.measured_band
 
     (
         profiles,
@@ -428,7 +433,7 @@ def analise_argolight_e(dataset: mm_schema.ArgolightEDataset) -> bool:
         image=image,
         axis=axis,
         measured_band=measured_band,
-        prominence=dataset.input.prominence_threshold,
+        prominence=dataset.input_parameters.prominence_threshold,
         do_angle_refinement=False,  # TODO: implement angle refinement
     )
     key_values = {
@@ -498,7 +503,7 @@ def analise_argolight_e(dataset: mm_schema.ArgolightEDataset) -> bool:
         rois.append(
             mm_schema.Roi(
                 label=f"ch{ch:02}_peaks",
-                image=dataset.input.argolight_e_image.image_url,
+                image=dataset.input_data.argolight_e_image.image_url,
                 shapes=shapes,
             )
         )
diff --git a/src/microscopemetrics/samples/field_illumination.py b/src/microscopemetrics/analyses/field_illumination.py
similarity index 95%
rename from src/microscopemetrics/samples/field_illumination.py
rename to src/microscopemetrics/analyses/field_illumination.py
index 53fe44c..5f7f373 100644
--- a/src/microscopemetrics/samples/field_illumination.py
+++ b/src/microscopemetrics/analyses/field_illumination.py
@@ -11,14 +11,14 @@
 from skimage.measure import regionprops
 
 from microscopemetrics import SaturationError
-from microscopemetrics.samples import (
+from microscopemetrics.analyses import (
     dict_to_table,
     get_object_id,
     logger,
     numpy_to_mm_image,
     validate_requirements,
 )
-from microscopemetrics.utilities.utilities import fit_gaussian, is_saturated
+from microscopemetrics.analyses.tools import fit_gaussian, is_saturated
 
 
 def _get_center_region_mask(channel: np.ndarray, fraction: float = 0.1) -> np.ndarray:
@@ -341,11 +341,11 @@ def _image_properties(images: list[mm_schema.Image], corner_fraction: float, sig
     return properties
 
 
-def analise_field_illumination(dataset: mm_schema.FieldIlluminationDataset) -> bool:
+def analyse_field_illumination(dataset: mm_schema.FieldIlluminationDataset) -> bool:
     validate_requirements()
 
     channel_names = []
-    for image in dataset.input.field_illumination_image:
+    for image in dataset.input_data.field_illumination_image:
         # We want to verify that the input images all have different channel names
         # As it does not make sense to average file illumination between images from the same channel
         if image.channel_series is not None:
@@ -375,8 +375,8 @@ def analise_field_illumination(dataset: mm_schema.FieldIlluminationDataset) -> b
         for c in range(image.array_data.shape[-1]):
             if is_saturated(
                 channel=image.array_data[..., c],
-                threshold=dataset.input.saturation_threshold,
-                detector_bit_depth=dataset.input.bit_depth,
+                threshold=dataset.input_parameters.saturation_threshold,
+                detector_bit_depth=dataset.input_parameters.bit_depth,
             ):
                 logger.error(f"Channel {c} is saturated")
                 saturated_channels.append(c)
@@ -385,9 +385,9 @@ def analise_field_illumination(dataset: mm_schema.FieldIlluminationDataset) -> b
             raise SaturationError(f"Channels {saturated_channels} are saturated")
 
     key_measurements = _image_properties(
-        images=dataset.input.field_illumination_image,
-        corner_fraction=dataset.input.corner_fraction,
-        sigma=dataset.input.sigma,
+        images=dataset.input_data.field_illumination_image,
+        corner_fraction=dataset.input_parameters.corner_fraction,
+        sigma=dataset.input_parameters.sigma,
     )
 
     key_measurements = mm_schema.FieldIlluminationKeyMeasurements(
@@ -403,7 +403,7 @@ def analise_field_illumination(dataset: mm_schema.FieldIlluminationDataset) -> b
             name=f"{image.name}_intensity_profiles",
             description=f"Intensity profiles of {image.name}",
         )
-        for image in dataset.input.field_illumination_image
+        for image in dataset.input_data.field_illumination_image
     ]
 
     roi_profiles = [
@@ -413,7 +413,7 @@ def analise_field_illumination(dataset: mm_schema.FieldIlluminationDataset) -> b
             linked_references=image.data_reference,
             lines=_line_profile_shapes(image.array_data),
         )
-        for image in dataset.input.field_illumination_image
+        for image in dataset.input_data.field_illumination_image
     ]
 
     roi_corners = mm_schema.Roi(
@@ -421,10 +421,10 @@ def analise_field_illumination(dataset: mm_schema.FieldIlluminationDataset) -> b
         description="ROIs used to compute the corner intensities",
         linked_references=[
             i.data_reference
-            for i in dataset.input.field_illumination_image
+            for i in dataset.input_data.field_illumination_image
             if i.data_reference is not None
         ],
-        rectangles=_corner_shapes(image.array_data, dataset.input.corner_fraction),
+        rectangles=_corner_shapes(image.array_data, dataset.input_parameters.corner_fraction),
     )
 
     roi_centers_of_mass = [
@@ -449,7 +449,7 @@ def analise_field_illumination(dataset: mm_schema.FieldIlluminationDataset) -> b
                 for c in range(image.array_data.shape[-1])
             ],
         )
-        for image in dataset.input.field_illumination_image
+        for image in dataset.input_data.field_illumination_image
     ]
 
     roi_centers_geometric = [
@@ -474,7 +474,7 @@ def analise_field_illumination(dataset: mm_schema.FieldIlluminationDataset) -> b
                 for c in range(image.array_data.shape[-1])
             ],
         )
-        for image in dataset.input.field_illumination_image
+        for image in dataset.input_data.field_illumination_image
     ]
 
     roi_centers_fitted = [
@@ -499,7 +499,7 @@ def analise_field_illumination(dataset: mm_schema.FieldIlluminationDataset) -> b
                 for c in range(image.array_data.shape[-1])
             ],
         )
-        for image in dataset.input.field_illumination_image
+        for image in dataset.input_data.field_illumination_image
     ]
 
     roi_centers_max_intensity = [
@@ -524,7 +524,7 @@ def analise_field_illumination(dataset: mm_schema.FieldIlluminationDataset) -> b
                 for c in range(image.array_data.shape[-1])
             ],
         )
-        for image in dataset.input.field_illumination_image
+        for image in dataset.input_data.field_illumination_image
     ]
 
     roi_center_region = [
@@ -546,7 +546,7 @@ def analise_field_illumination(dataset: mm_schema.FieldIlluminationDataset) -> b
                 for c in range(image.array_data.shape[-1])
             ],
         )
-        for image in dataset.input.field_illumination_image
+        for image in dataset.input_data.field_illumination_image
     ]
 
     dataset.output = mm_schema.FieldIlluminationOutput(
diff --git a/src/microscopemetrics/analyses/mappings.py b/src/microscopemetrics/analyses/mappings.py
new file mode 100644
index 0000000..e93b26d
--- /dev/null
+++ b/src/microscopemetrics/analyses/mappings.py
@@ -0,0 +1,47 @@
+"""
+This module maps the sample classes to the analysis functions and the dataset classes.
+"""
+
+from collections import namedtuple
+
+from microscopemetrics_schema import datamodel as mm_schema
+
+from microscopemetrics.analyses import field_illumination, psf_beads
+
+Mapping = namedtuple("Mapping", ["sample_class", "analysis_function", "dataset_class"])
+
+MAPPINGS = [
+    Mapping(
+        mm_schema.FluorescentHomogeneousThinField,
+        field_illumination.analyse_field_illumination,
+        mm_schema.FieldIlluminationDataset,
+    ),
+    Mapping(
+        mm_schema.FluorescentHomogeneousThickField,
+        field_illumination.analyse_field_illumination,
+        mm_schema.FieldIlluminationDataset,
+    ),
+    Mapping(mm_schema.PSFBeads, psf_beads.analyse_psf_beads, mm_schema.PSFBeadsDataset),
+]
+
+# TEST = {
+#     mm_schema.FieldIlluminationDataset: {
+#         "sample_class": [
+#             mm_schema.FluorescentHomogeneousThinField,
+#             mm_schema.FluorescentHomogeneousThickField,
+#         ],
+#         "analysis_function": [
+#             field_illumination.analyse_field_illumination,
+#             field_illumination.analyse_field_illumination,
+#         ],
+#     },
+#     mm_schema.PSFBeadsDataset: {
+#         "sample_class": [
+#             mm_schema.PSFBeads,
+#         ],
+#         "analysis_function": [
+#             psf_beads.analyse_psf_beads,
+#         ],
+#     },
+# }
+#
diff --git a/src/microscopemetrics/samples/psf_beads.py b/src/microscopemetrics/analyses/psf_beads.py
similarity index 96%
rename from src/microscopemetrics/samples/psf_beads.py
rename to src/microscopemetrics/analyses/psf_beads.py
index 0bd13da..da5d585 100644
--- a/src/microscopemetrics/samples/psf_beads.py
+++ b/src/microscopemetrics/analyses/psf_beads.py
@@ -8,14 +8,14 @@
 from skimage.filters import gaussian
 
 from microscopemetrics import FittingError, SaturationError
-from microscopemetrics.samples import (
+from microscopemetrics.analyses import (
     df_to_table,
     get_object_id,
     logger,
     numpy_to_mm_image,
     validate_requirements,
 )
-from microscopemetrics.utilities.utilities import fit_airy, fit_gaussian, is_saturated
+from microscopemetrics.analyses.tools import fit_airy, fit_gaussian, is_saturated
 
 
 def _add_column_name_level(df: pd.DataFrame, level_name: str, level_value: str):
@@ -203,7 +203,7 @@ def _generate_key_measurements(bead_properties, average_bead_properties):
     # We aggregate counts for each channel on beads according to their status
     channel_counts = (
         reindex_bead_properties_df[count_aggregation_columns]
-        .groupby(["channel_name", "channel_nr"])
+        .groupby(["channel_nr", "channel_name"])
         .agg(["sum"])
     )
     channel_counts.columns = [
@@ -216,7 +216,7 @@ def _generate_key_measurements(bead_properties, average_bead_properties):
     ]
     channel_measurements = (
         valid_bead_properties_df[measurement_aggregation_columns]
-        .groupby(["channel_name", "channel_nr"])
+        .groupby(["channel_nr", "channel_name"])
         .agg(["mean", "median", "std"])
     )
     channel_measurements.columns = [
@@ -511,7 +511,7 @@ def _process_image(
 
 def _estimate_min_bead_distance(dataset: mm_schema.PSFBeadsDataset) -> float:
     # TODO: get the resolution somewhere or pass it as a metadata
-    return dataset.input.min_lateral_distance_factor
+    return dataset.input_parameters.min_lateral_distance_factor
 
 
 def _generate_center_roi(
@@ -523,7 +523,7 @@ def _generate_center_roi(
 ):
     rois = []
 
-    for image in dataset.input.psf_beads_images:
+    for image in dataset.input_data.psf_beads_images:
         image_id = get_object_id(image) or image.name
         if positions.empty or image_id not in positions.index.get_level_values("image_id"):
             continue
@@ -566,7 +566,7 @@ def _extract_profiles(bead_properties, axis: str) -> pd.DataFrame:
     profiles = {}
     for index, row in bead_properties.iterrows():
         if isinstance(index, (list, tuple)):
-            index = {index[bead_properties.index.names.index(col_i)] for col_i in column_indexes}
+            index = [index[bead_properties.index.names.index(col_i)] for col_i in column_indexes]
 
             index_str = "_".join([str(i) for i in index])
         else:
@@ -587,15 +587,15 @@ def analyse_psf_beads(dataset: mm_schema.PSFBeadsDataset) -> bool:
     images = {}
     voxel_sizes_micron = {}
     min_bead_distance = _estimate_min_bead_distance(dataset)
-    snr_threshold = dataset.input.snr_threshold
-    fitting_r2_threshold = dataset.input.fitting_r2_threshold
+    snr_threshold = dataset.input_parameters.snr_threshold
+    fitting_r2_threshold = dataset.input_parameters.fitting_r2_threshold
 
     # Containers for output data
     saturated_channels = {}
     bead_properties = []
 
     # First loop to prepare data
-    for image in dataset.input.psf_beads_images:
+    for image in dataset.input_data.psf_beads_images:
         image_id = get_object_id(image) or image.name
         images[image_id] = image.array_data[0, ...]
 
@@ -616,8 +616,8 @@ def analyse_psf_beads(dataset: mm_schema.PSFBeadsDataset) -> bool:
         for c in range(image.array_data.shape[-1]):
             if is_saturated(
                 channel=image.array_data[..., c],
-                threshold=dataset.input.saturation_threshold,
-                detector_bit_depth=dataset.input.bit_depth,
+                threshold=dataset.input_parameters.saturation_threshold,
+                detector_bit_depth=dataset.input_parameters.bit_depth,
             ):
                 logger.error(f"Image {image_id}: channel {c} is saturated")
                 saturated_channels[image_id].append(c)
@@ -627,7 +627,7 @@ def analyse_psf_beads(dataset: mm_schema.PSFBeadsDataset) -> bool:
         raise SaturationError(f"Channels {saturated_channels} are saturated")
 
     # Second loop main image analysis
-    for image in dataset.input.psf_beads_images:
+    for image in dataset.input_data.psf_beads_images:
         image_id = get_object_id(image) or image.name
         logger.info(f"Processing image {image_id}...")
         voxel_sizes_micron[image_id] = (
@@ -638,11 +638,15 @@ def analyse_psf_beads(dataset: mm_schema.PSFBeadsDataset) -> bool:
 
         image_bead_properties = _process_image(
             image=image,
-            sigma=(dataset.input.sigma_z, dataset.input.sigma_y, dataset.input.sigma_x),
+            sigma=(
+                dataset.input_parameters.sigma_z,
+                dataset.input_parameters.sigma_y,
+                dataset.input_parameters.sigma_x,
+            ),
             min_bead_distance=min_bead_distance,
             snr_threshold=snr_threshold,
             fitting_r2_threshold=fitting_r2_threshold,
-            intensity_robust_z_score_threshold=dataset.input.intensity_robust_z_score_threshold,
+            intensity_robust_z_score_threshold=dataset.input_parameters.intensity_robust_z_score_threshold,
         )
 
         logger.info(
@@ -664,7 +668,7 @@ def analyse_psf_beads(dataset: mm_schema.PSFBeadsDataset) -> bool:
 
     # Before averaging any bead we need to verify that all voxel sizes are equal
     if len(set(voxel_sizes_micron.values())) == 1:
-        average_beads_properties = bead_properties.groupby(["channel_name", "channel_nr"]).apply(
+        average_beads_properties = bead_properties.groupby(["channel_nr", "channel_name"]).apply(
             _average_beads
         )
         average_beads_properties = average_beads_properties.join(
@@ -701,7 +705,7 @@ def analyse_psf_beads(dataset: mm_schema.PSFBeadsDataset) -> bool:
             ),
             name="average_bead",
             description="Average bead image extracted from all the beads considered valid in the dataset.",
-            source_images=dataset.input.psf_beads_images,
+            source_images=dataset.input_data.psf_beads_images,
             channel_names=[
                 i[average_beads_properties.index.names.index("channel_name")]
                 for i in average_beads_properties.index
diff --git a/src/microscopemetrics/analysis/tools.py b/src/microscopemetrics/analyses/tools.py
similarity index 53%
rename from src/microscopemetrics/analysis/tools.py
rename to src/microscopemetrics/analyses/tools.py
index e75d290..1794767 100644
--- a/src/microscopemetrics/analysis/tools.py
+++ b/src/microscopemetrics/analyses/tools.py
@@ -1,11 +1,13 @@
 """These are some possibly useful code snippets"""
+
 import logging
 from itertools import permutations
-from typing import List
+from typing import List, Optional
 
 import numpy as np
 import pandas as pd
-from scipy import ndimage
+from scipy import ndimage, special
+from scipy.optimize import curve_fit, fsolve
 from scipy.spatial.distance import cdist
 from skimage.feature import peak_local_max
 from skimage.filters import apply_hysteresis_threshold, gaussian, threshold_otsu
@@ -16,6 +18,156 @@
 # Creating logging services
 logger = logging.getLogger(__name__)
 
+INT_DETECTOR_BIT_DEPTHS = [8, 10, 11, 12, 15, 16, 32]
+FLOAT_DETECTOR_BIT_DEPTHS = [32, 64]
+
+
+def airy_fun(
+    x: np.ndarray, centre: np.float64, amp: np.float64
+) -> np.ndarray:  # , exp):  # , amp, bg):
+    with np.errstate(divide="ignore", invalid="ignore"):
+        return np.where(
+            (x - centre) == 0,
+            amp * 0.5**2,
+            amp * (special.j1(x - centre) / (x - centre)) ** 2,
+        )
+
+
+def gaussian_fun(x, background, amplitude, center, sd):
+    gauss = np.exp(-np.power(x - center, 2.0) / (2 * np.power(sd, 2.0)))
+    return background + (amplitude - background) * gauss
+
+
+def fit_gaussian(profile, guess=None):
+    if guess is None:
+        guess = [profile.min(), profile.max(), profile.argmax(), 0.8]
+    x = np.linspace(0, profile.shape[0], profile.shape[0], endpoint=False)
+    popt, pcov, infodict, mesg, ier = curve_fit(
+        f=gaussian_fun, xdata=x, ydata=profile, p0=guess, maxfev=5000, full_output=True
+    )
+
+    if ier not in [1, 2, 3, 4]:
+        logger.warning(f"No gaussian fit found. Reason: {mesg}")
+
+    fitted_profile = gaussian_fun(x, popt[0], popt[1], popt[2], popt[3])
+    fwhm = popt[3] * 2.35482
+
+    # Calculate the fit quality using the coefficient of determination (R^2)
+    y_mean = np.mean(profile)
+    sst = np.sum((profile - y_mean) ** 2)
+    ssr = np.sum((profile - fitted_profile) ** 2)
+    cd_r2 = 1 - (ssr / sst)
+
+    return fitted_profile, cd_r2, fwhm, popt
+
+
+def fit_airy(profile, guess=None):
+    profile = (profile - profile.min()) / (profile.max() - profile.min())
+    if guess is None:
+        guess = [profile.argmax(), 4 * profile.max()]
+    x = np.linspace(0, profile.shape[0], profile.shape[0], endpoint=False)
+    popt, pcov, infodict, mesg, ier = curve_fit(
+        f=airy_fun, xdata=x, ydata=profile, p0=guess, full_output=True
+    )
+
+    if ier not in [1, 2, 3, 4]:
+        logger.warning(f"No airy fit found. Reason: {mesg}")
+
+    fitted_profile = airy_fun(x, popt[0], popt[1])
+
+    # Calculate the FWHM
+    def _f(d):
+        return airy_fun(d, popt[0], popt[1]) - (fitted_profile.max() - fitted_profile.min()) / 2
+
+    guess = np.array([fitted_profile.argmax() - 1, fitted_profile.argmax() + 1])
+    v = fsolve(_f, guess)
+    fwhm = abs(v[1] - v[0])
+
+    # Calculate the fit quality using the coefficient of determination (R^2)
+    y_mean = np.mean(profile)
+    sst = np.sum((profile - y_mean) ** 2)
+    ssr = np.sum((profile - fitted_profile) ** 2)
+    cd_r2 = 1 - (ssr / sst)
+
+    return fitted_profile, cd_r2, fwhm, popt
+
+
+def multi_airy_fun(x: np.ndarray, *params) -> np.ndarray:
+    y = np.zeros_like(x)
+    for i in range(0, len(params), 2):
+        y = y + airy_fun(x, params[i], params[i + 1])
+    return y
+
+
+def is_saturated(
+    channel: np.ndarray, threshold: float = 0.0, detector_bit_depth: Optional[int] = None
+) -> bool:
+    """
+    Checks if the channel is saturated.
+    A warning if it suspects that the detector bit depth does not match the datatype.
+    thresh: float
+        Threshold for the ratio of saturated pixels to total pixels
+    detector_bit_depth: int
+        Bit depth of the detector. Sometimes, detectors bit depth are not matching the datatype of the measureemnts.
+        Here it can be specified the bit depth of the detector if known. The function is going to raise
+        If None, it will be inferred from the channel dtype.
+    """
+    if detector_bit_depth is not None:
+        if (
+            detector_bit_depth not in INT_DETECTOR_BIT_DEPTHS
+            and detector_bit_depth not in FLOAT_DETECTOR_BIT_DEPTHS
+        ):
+            raise ValueError(
+                f"The detector bit depth provided ({detector_bit_depth}) is not supported. Supported values are {INT_DETECTOR_BIT_DEPTHS} for integer detectors and {FLOAT_DETECTOR_BIT_DEPTHS} for floating point detectors."
+            )
+        if (
+            np.issubdtype(channel.dtype, np.integer)
+            and detector_bit_depth not in INT_DETECTOR_BIT_DEPTHS
+        ):
+            raise ValueError(
+                f"The channel datatype {channel.dtype} does not match the detector bit depth {detector_bit_depth}. The channel might be saturated."
+            )
+        elif (
+            np.issubdtype(channel.dtype, np.floating)
+            and detector_bit_depth not in FLOAT_DETECTOR_BIT_DEPTHS
+        ):
+            raise ValueError(
+                f"The channel datatype {channel.dtype} does not match the detector bit depth {detector_bit_depth}. The channel might be saturated."
+            )
+        else:
+            if np.issubdtype(channel.dtype, np.integer):
+                if detector_bit_depth > np.iinfo(channel.dtype).bits:
+                    raise ValueError(
+                        f"The channel datatype {channel.dtype} does not support the detector bit depth {detector_bit_depth}. The channel might be saturated."
+                    )
+                else:
+                    max_limit = pow(2, detector_bit_depth) - 1
+            elif np.issubdtype(channel.dtype, np.floating):
+                if detector_bit_depth != np.finfo(channel.dtype).bits:
+                    raise ValueError(
+                        f"The channel datatype {channel.dtype} does not support the detector bit depth {detector_bit_depth}. The channel might be saturated."
+                    )
+                else:
+                    max_limit = np.finfo(channel.dtype).max
+
+    else:
+        if np.issubdtype(channel.dtype, np.integer):
+            max_limit = np.iinfo(channel.dtype).max
+        elif np.issubdtype(channel.dtype, np.floating):
+            max_limit = np.finfo(channel.dtype).max
+        else:
+            raise ValueError("The channel provided is not a valid numpy dtype.")
+
+    if channel.max() > max_limit:
+        raise ValueError(
+            "The channel provided has values larger than the bit depth of the detector."
+        )
+
+    saturation_matrix = channel == max_limit
+    saturation_ratio = np.count_nonzero(saturation_matrix) / channel.size
+
+    return saturation_ratio > threshold
+
 
 def _segment_channel(
     channel,
@@ -257,3 +409,52 @@ def fft_3d(image):
         fft[..., c, :, :] = _channel_fft_3d(image[..., c, :, :])
 
     return fft
+
+
+def wavelength_to_rgb(wavelength, gamma=0.8):
+    """
+    Copied from https://www.noah.org/wiki/Wavelength_to_RGB_in_Python
+    This converts a given wavelength of light to an
+    approximate RGB color value. The wavelength must be given
+    in nanometers in the range from 380 nm through 750 nm
+    (789 THz through 400 THz).
+
+    Based on code by Dan Bruton
+    http://www.physics.sfasu.edu/astro/color/spectra.html
+    """
+
+    wavelength = float(wavelength)
+    if 380 < wavelength <= 440:
+        attenuation = 0.3 + 0.7 * (wavelength - 380) / (440 - 380)
+        r = ((-(wavelength - 440) / (440 - 380)) * attenuation) ** gamma
+        g = 0.0
+        b = (1.0 * attenuation) ** gamma
+    elif 440 < wavelength <= 490:
+        r = 0.0
+        g = ((wavelength - 440) / (490 - 440)) ** gamma
+        b = 1.0
+    elif 490 < wavelength <= 510:
+        r = 0.0
+        g = 1.0
+        b = (-(wavelength - 510) / (510 - 490)) ** gamma
+    elif 510 < wavelength <= 580:
+        r = ((wavelength - 510) / (580 - 510)) ** gamma
+        g = 1.0
+        b = 0.0
+    elif 580 < wavelength <= 645:
+        r = 1.0
+        g = (-(wavelength - 645) / (645 - 580)) ** gamma
+        b = 0.0
+    elif 645 < wavelength <= 750:
+        attenuation = 0.3 + 0.7 * (750 - wavelength) / (750 - 645)
+        r = (1.0 * attenuation) ** gamma
+        g = 0.0
+        b = 0.0
+    else:
+        r = 0.0
+        g = 0.0
+        b = 0.0
+    r *= int(r * 255)
+    g *= int(g * 255)
+    g *= int(g * 255)
+    return r, g, b
diff --git a/src/microscopemetrics/analysis/__init__.py b/src/microscopemetrics/analysis/__init__.py
deleted file mode 100644
index ce620fa..0000000
--- a/src/microscopemetrics/analysis/__init__.py
+++ /dev/null
@@ -1,402 +0,0 @@
-import logging
-from datetime import datetime
-from itertools import product
-
-import numpy as np
-
-from microscopemetrics.devices import devices
-
-# import inspect
-# from os import path
-# import importlib
-# importlib.resources.contents('metrics.samples')
-# importlib.import_module('.argolight', package='metrics.samples')
-
-# import dataset analysis
-# from microscopemetrics.samples.dataset import DatasetConfigurator
-
-
-# import samples
-# from microscopemetrics.samples.argolight import ArgolightConfigurator
-# from microscopemetrics.samples.psf_beads import PSFBeadsConfigurator
-
-# SAMPLE_CONFIGURATORS = [ArgolightConfigurator,
-#                         PSFBeadsConfigurator]
-# noinspection PyUnresolvedReferences
-# SAMPLE_HANDLERS = [c.SAMPLE_CLASS for c in SAMPLE_CONFIGURATORS]
-# SAMPLE_SECTIONS = [c.CONFIG_SECTION for c in SAMPLE_CONFIGURATORS]
-# SAMPLE_ANALYSES = [c.ANALYSES for c in SAMPLE_CONFIGURATORS]
-
-# Creating logging services
-module_logger = logging.getLogger("metrics.analysis")
-
-# Namespace constants
-NAMESPACE_PREFIX = "metrics"
-NAMESPACE_ANALYZED = "analyzed"
-NAMESPACE_VALIDATED = "validated"
-# TODO: Add a special case editable
-
-
-def get_image_data(image, device):
-    image_name = image.getName()
-    image_id = image.getId()
-    raw_img = interface.get_intensities(image)
-    # Images from Interface come in zctyx dimensions and locally as zcxy.
-    # The easiest for the moment is to remove t
-    if raw_img.shape[2] == 1:
-        raw_img = np.squeeze(raw_img, 2)  # TODO: Fix this time dimension.
-    else:
-        raise Exception("Image has a time dimension. Time is not yet implemented for this analysis")
-    pixel_size = interface.get_pixel_size(image)
-    pixel_size_units = interface.get_pixel_size_units(image)
-
-    device_settings = device.get_all_settings(image=image)
-
-    image_settings = {
-        "image_data": raw_img,
-        "image_name": image_name,
-        "image_id": image_id,
-        "pixel_size": pixel_size,
-        "pixel_size_units": pixel_size_units,
-    }
-    image_settings.update(device_settings)
-
-    return image_settings
-
-
-def save_data_table(
-    conn, table_name, col_names, col_descriptions, col_data, interface_obj, namespace
-):
-    table_ann = interface.create_annotation_table(
-        connection=conn,
-        table_name=table_name,
-        column_names=col_names,
-        column_descriptions=col_descriptions,
-        values=col_data,
-        namespace=namespace,
-    )
-
-    interface_obj.linkAnnotation(table_ann)
-
-
-def save_data_key_values(conn, key_values, interface_obj, namespace, editable=False):
-    map_ann = interface.create_annotation_map(
-        connection=conn, annotation=key_values, namespace=namespace
-    )
-    interface_obj.linkAnnotation(map_ann)
-
-
-def create_roi(conn, shapes, image, name, description):
-    type_to_func = {
-        "point": interface.create_shape_point,
-        "line": interface.create_shape_line,
-        "rectangle": interface.create_shape_rectangle,
-        "ellipse": interface.create_shape_ellipse,
-        "polygon": interface.create_shape_polygon,
-        "mask": interface.create_shape_mask,
-    }
-
-    new_shapes = [type_to_func[shape["type"]](**shape["args"]) for shape in shapes]
-    interface.create_roi(
-        connection=conn,
-        image=image,
-        shapes=new_shapes,
-        name=name,
-        description=description,
-    )
-
-
-def create_image(
-    conn,
-    image_intensities,
-    image_name,
-    description,
-    dataset,
-    source_image_id=None,
-    metrics_generated_tag_id=None,
-):
-    zct_list = list(
-        product(
-            range(image_intensities.shape[0]),
-            range(image_intensities.shape[1]),
-            range(image_intensities.shape[2]),
-        )
-    )
-    zct_generator = (image_intensities[z, c, t, :, :] for z, c, t in zct_list)
-
-    new_image = conn.createImageFromNumpySeq(
-        zctPlanes=zct_generator,
-        imageName=image_name,
-        sizeZ=image_intensities.shape[0],
-        sizeC=image_intensities.shape[1],
-        sizeT=image_intensities.shape[2],
-        description=description,
-        dataset=dataset,
-        sourceImageId=source_image_id,
-    )
-
-    # TODO: see with ome why description is not applied
-    img_wrapper = conn.getObject("Image", new_image.getId())
-    img_wrapper.setDescription(description)
-    img_wrapper.save()
-
-    if metrics_generated_tag_id is not None:
-        tag = conn.getObject("Annotation", metrics_generated_tag_id)
-        if tag is None:
-            module_logger.warning(
-                "Metrics tag is not found. New images will not be tagged. Verify metrics tag existence and id."
-            )
-        else:
-            new_image.linkAnnotation(tag)
-
-    return new_image
-
-
-def analyze_dataset(connection, script_params, dataset, analysis_config, device_config):
-    # TODO: must note in mapann the analyses that were done
-
-    # TODO: do something to automate selection of microscope type
-    device = devices.WideFieldMicroscope(device_config)
-
-    module_logger.info(f"Analyzing data from Dataset: {dataset.getId()}")
-    module_logger.info(f"Date and time: {datetime.now()}")
-
-    # This dictionary keeps track if the hard or soft limits are passed or not for the whole dataset
-    dataset_limits_passed = {
-        "uhl_passed": True,
-        "lhl_passed": True,
-        "usl_passed": True,
-        "lsl_passed": True,
-        "limits": list(),
-        "sources": list(),
-    }
-
-    for section, analyses, handler in zip(SAMPLE_SECTIONS, SAMPLE_ANALYSES, SAMPLE_HANDLERS):
-        if analysis_config.has_section(section):
-            module_logger.info(f"Running analysis on {section.capitalize()} sample(s)")
-            section_conf = analysis_config[section]
-            handler_instance = handler(config=section_conf)
-            for analysis in analyses:
-                if section_conf.getboolean(f"analyze_{analysis}"):
-                    namespace = (
-                        f"{NAMESPACE_PREFIX}/"
-                        f"{NAMESPACE_ANALYZED}/"
-                        f"{handler.get_module()}/"
-                        f"{analysis}/"
-                        f'{analysis_config["MAIN"]["metrics_version"]}'
-                    )
-                    images = interface.get_tagged_images_in_dataset(
-                        dataset, section_conf.getint(f"{analysis}_image_tag_id")
-                    )
-                    for image in images:
-                        image_data = get_image_data(image=image, device=device)
-                        (
-                            out_images,
-                            out_rois,
-                            out_tags,
-                            out_dicts,
-                            out_tables,
-                            image_limits_passed,
-                        ) = handler_instance.analyze_image(
-                            image=image_data, analyses=analysis, config=section_conf
-                        )
-
-                        for out_image in out_images:
-                            create_image(
-                                conn=connection,
-                                image_intensities=out_image["image_data"],
-                                image_name=out_image["image_name"],
-                                description=f'Source Image Id:{image.getId()}\n{out_image["image_desc"]}',
-                                dataset=dataset,
-                                source_image_id=image.getId(),
-                                metrics_generated_tag_id=analysis_config["MAIN"].getint(
-                                    "metrics_generated_tag_id"
-                                ),
-                            )
-
-                        for out_roi in out_rois:
-                            create_roi(
-                                conn=connection,
-                                shapes=out_roi["shapes"],
-                                image=image,
-                                name=out_roi["name"],
-                                description=out_roi["desc"],
-                            )
-
-                        for out_tag in out_tags:
-                            pass  # TODO implement interface to save tags
-
-                        for out_table_name, out_table in out_tables.items():
-                            save_data_table(
-                                conn=connection,
-                                table_name=out_table_name,
-                                col_names=[p["name"] for p in out_table],
-                                col_descriptions=[p["desc"] for p in out_table],
-                                col_data=[p["data"] for p in out_table],
-                                interface_obj=image,
-                                namespace=namespace,
-                            )
-
-                        for out_dict in out_dicts:
-                            labeled_out_dict = {
-                                "analysis_date_time": f"{datetime.now()}",
-                                "sample_type": f"{handler.get_module()}",
-                                "analysis_type": f"{analysis}",
-                            }
-                            labeled_out_dict.update(out_dict)
-
-                            save_data_key_values(
-                                conn=connection,
-                                key_values=labeled_out_dict,
-                                interface_obj=image,
-                                namespace=namespace,
-                            )
-
-                        for ilp in image_limits_passed:
-                            for k, v in ilp.items():
-                                if v is False:
-                                    dataset_limits_passed[k] = False
-                                elif type(v) is list:
-                                    dataset_limits_passed[k].extend(v)
-
-    dataset_section = DatasetConfigurator.CONFIG_SECTION
-    dataset_analyses = DatasetConfigurator.ANALYSES
-    dataset_handler = DatasetConfigurator.SAMPLE_CLASS
-
-    if analysis_config.has_section(dataset_section):
-        module_logger.info(f"Running analysis on dataset")
-        ds_conf = analysis_config[dataset_section]
-        ds_handler_instance = dataset_handler(config=ds_conf)
-        for dataset_analysis in dataset_analyses:
-            if ds_conf.getboolean(f"analyze_{dataset_analysis}"):
-                namespace = (
-                    f"{NAMESPACE_PREFIX}/"
-                    f"{NAMESPACE_ANALYZED}/"
-                    f"{dataset_handler.get_module()}/"
-                    f"{dataset_analysis}/"
-                    f'{analysis_config["MAIN"]["metrics_version"]}'
-                )
-                (
-                    out_images,
-                    out_tags,
-                    out_dicts,
-                    out_editables,
-                    out_tables,
-                    image_limits_passed,
-                ) = ds_handler_instance.analyze_dataset(
-                    dataset=dataset, analyses=dataset_analysis, config=ds_conf
-                )
-                for out_image in out_images:
-                    create_image(
-                        conn=connection,
-                        image_intensities=out_image["image_data"],
-                        image_name=out_image["image_name"],
-                        description=out_image["image_desc"],
-                        dataset=dataset,
-                        metrics_generated_tag_id=analysis_config["MAIN"].getint(
-                            "metrics_generated_tag_id"
-                        ),
-                    )
-
-                for out_tag in out_tags:
-                    pass  # TODO implement interface to save tags
-
-                for out_table_name, out_table in out_tables.items():
-                    save_data_table(
-                        conn=connection,
-                        table_name=out_table_name,
-                        col_names=[p["name"] for p in out_table],
-                        col_descriptions=[p["desc"] for p in out_table],
-                        col_data=[p["data"] for p in out_table],
-                        interface_obj=dataset,
-                        namespace=namespace,
-                    )
-
-                for out_dict, out_editable in zip(out_dicts, out_editables):
-                    if out_editable:
-                        tmp_namespace = None
-                    else:
-                        tmp_namespace = namespace
-                    save_data_key_values(
-                        conn=connection,
-                        key_values=out_dict,
-                        interface_obj=dataset,
-                        namespace=tmp_namespace,
-                    )
-
-                for ilp in image_limits_passed:
-                    for k, v in ilp.items():
-                        if v is False:
-                            dataset_limits_passed[k] = False
-                        elif type(v) is list:
-                            dataset_limits_passed[k].extend(v)
-
-    # Save final dataset limits passed tests and corresponding tags
-    namespace = (
-        f"{NAMESPACE_PREFIX}/"
-        f"{NAMESPACE_ANALYZED}/"
-        "dataset/"
-        "limits_verification/"
-        f'{analysis_config["MAIN"]["metrics_version"]}'
-    )
-
-    # dataset_limits_passed['limits'] = list(dict.fromkeys(dataset_limits_passed['limits']))  # Remove duplicates
-
-    if (
-        dataset_limits_passed["uhl_passed"] and dataset_limits_passed["lhl_passed"]
-    ):  # Hard limits passed
-        interface.link_annotation_tag(
-            connection,
-            dataset,
-            analysis_config["MAIN"].getint("passed_hard_limits_tag_id"),
-        )
-    else:
-        interface.link_annotation_tag(
-            connection,
-            dataset,
-            analysis_config["MAIN"].getint("not_passed_hard_limits_tag_id"),
-        )
-
-    if (
-        dataset_limits_passed["usl_passed"] and dataset_limits_passed["lsl_passed"]
-    ):  # Soft limits passed
-        interface.link_annotation_tag(
-            connection,
-            dataset,
-            analysis_config["MAIN"].getint("passed_soft_limits_tag_id"),
-        )
-    else:
-        interface.link_annotation_tag(
-            connection,
-            dataset,
-            analysis_config["MAIN"].getint("not_passed_soft_limits_tag_id"),
-        )
-
-    save_data_key_values(
-        conn=connection,
-        key_values=dataset_limits_passed,
-        interface_obj=dataset,
-        namespace=namespace,
-    )
-
-    try:
-        if "Comment" in script_params.keys() and script_params["Comment"] != "":
-            module_logger.info("Adding comment to Dataset.")
-            namespace = (
-                f"{NAMESPACE_PREFIX}/"
-                f"{NAMESPACE_ANALYZED}/"
-                "comment/"
-                "comment/"
-                f'{analysis_config["MAIN"]["config_version"]}'
-            )
-
-            comment_annotation = interface.create_annotation_comment(
-                connection=connection,
-                comment_string=script_params["Comment"],
-                namespace=namespace,
-            )
-            interface.link_annotation(dataset, comment_annotation)
-    except KeyError:
-        module_logger.info("No comments added")
-
-    module_logger.info(f"Sample finished for dataset: {dataset.getId()}")
diff --git a/src/microscopemetrics/devices/devices.py b/src/microscopemetrics/devices/devices.py
index 272ee0a..07d9dc0 100644
--- a/src/microscopemetrics/devices/devices.py
+++ b/src/microscopemetrics/devices/devices.py
@@ -533,9 +533,7 @@ def get_theoretical_res_rayleigh(self, **kwargs):
                 )
                 theoretical_res["resolution_theoretical_rayleigh_lateral"].append(None)
             try:
-                theoretical_res["resolution_theoretical_rayleigh_axial"].append(
-                    2 * em * ri / na**2
-                )
+                theoretical_res["resolution_theoretical_rayleigh_axial"].append(2 * em * ri / na**2)
             except TypeError as e:
                 module_logger.warning(
                     "Rayleigh theoretical axial resolution could not be calculated. Verify configuration files."
diff --git a/src/microscopemetrics/samples/dataset.py b/src/microscopemetrics/samples/dataset.py
deleted file mode 100644
index a737d17..0000000
--- a/src/microscopemetrics/samples/dataset.py
+++ /dev/null
@@ -1,74 +0,0 @@
-import logging
-from datetime import datetime
-
-from microscopemetrics.samples.samples import Analysis, Configurator
-
-module_logger = logging.getLogger("metrics.samples.dataset")
-
-
-class DatasetConfigurator(Configurator):
-    """This class handles the configuration properties of the excitation_power sample
-    - Defines configuration properties
-    - Helps in the generation of analysis_config files"""
-
-    CONFIG_SECTION = "DATASET"
-    ANALYSES = ["laser_power_measurement"]
-
-    def __init__(self, config):
-        super().__init__(config)
-
-
-@DatasetConfigurator.register_sample_analysis
-class DatasetAnalysis(Analysis):
-    """This class handles the Excitation_power sample:
-    - Defines the logic of the associated analyses
-    - Defines the creation of reports"""
-
-    def __init__(self, config=None):
-        dataset_analysis_to_func = {
-            "laser_power_measurement": self.analyze_laser_power_measurement,
-        }
-        self.configurator = DatasetConfigurator(config)
-        super().__init__(config=config, dataset_analysis_to_func=dataset_analysis_to_func)
-
-    @staticmethod
-    def analyze_laser_power_measurement(dataset, config):
-        """Opens a Map annotation where the user can enter the power measurements of the Excitation lasers. Those shoudl
-        be blocked upon validation
-
-        :param dataset: dataset instance
-        :param config: MetricsConfig instance defining analysis configuration.
-                       Must contain the analysis parameters defined by the configurator
-
-        :returns a list of images
-                 a list of rois
-                 a list of tags
-                 a list of dicts
-                 a dict containing table_names and tables
-        """
-        module_logger.info(f"Generating light sources annotation...")
-
-        wavelengths = config.getlistint("laser_power_measurement_wavelengths", None)
-        power_units = config.get("laser_power_measurement_units")
-        measurement_method = config.get("laser_power_measurement_method")
-
-        if wavelengths is None:
-            module_logger.error(
-                "Config defined to do excitation power measurements but No wavelengths were provided"
-            )
-            wavelengths = list()
-
-        key_values = {"analysis_date": datetime.now().strftime("%Y-%m-%d")}
-        for wave in wavelengths:
-            key_values.update({str(wave): ""})
-        key_values["power_units"] = power_units
-        key_values["measurement_method"] = measurement_method
-
-        out_images = []
-        out_rois = []
-        out_tags = []
-        out_dicts = [key_values]
-        out_editables = [True]
-        out_tables = []
-
-        return out_images, out_rois, out_tags, out_dicts, out_editables, out_tables
diff --git a/src/microscopemetrics/strategies/strategies.py b/src/microscopemetrics/strategies/strategies.py
index 74fefc5..951982a 100644
--- a/src/microscopemetrics/strategies/strategies.py
+++ b/src/microscopemetrics/strategies/strategies.py
@@ -11,15 +11,12 @@
     raise ImportError(
         "In order to run the strategies you need to install the test extras. Run `pip install microscopemetrics[test]`."
     )
-from microscopemetrics_schema import datamodel as mm_schema
 from microscopemetrics_schema import strategies as st_mm_schema
 from skimage.exposure import rescale_intensity as skimage_rescale_intensity
 from skimage.filters import gaussian as skimage_gaussian
 from skimage.util import random_noise as skimage_random_noise
 
-from microscopemetrics import samples as mm_samples
-from microscopemetrics.samples import (
-    argolight,
+from microscopemetrics.analyses import (  # argolight,
     field_illumination,
     numpy_to_mm_image,
     psf_beads,
@@ -208,7 +205,7 @@ def st_field_illumination_dataset(
     test_data = draw(test_data)
     field_illumination_unprocessed_dataset = draw(unprocessed_dataset)
 
-    field_illumination_unprocessed_dataset.input.field_illumination_image = [
+    field_illumination_unprocessed_dataset.input_data.field_illumination_image = [
         numpy_to_mm_image(
             array=image,
             name=f"FI_image_{i}",
@@ -220,17 +217,21 @@ def st_field_illumination_dataset(
     # Setting the bit depth to the data type of the image
     image_dtype = {
         a.array_data.dtype
-        for a in field_illumination_unprocessed_dataset.input.field_illumination_image
+        for a in field_illumination_unprocessed_dataset.input_data.field_illumination_image
     }
     if len(image_dtype) != 1:
         raise ValueError("All images should have the same data type")
     image_dtype = image_dtype.pop()
     if np.issubdtype(image_dtype, np.integer):
-        field_illumination_unprocessed_dataset.input.bit_depth = np.iinfo(image_dtype).bits
+        field_illumination_unprocessed_dataset.input_parameters.bit_depth = np.iinfo(
+            image_dtype
+        ).bits
     elif np.issubdtype(image_dtype, np.floating):
-        field_illumination_unprocessed_dataset.input.bit_depth = np.finfo(image_dtype).bits
+        field_illumination_unprocessed_dataset.input_parameters.bit_depth = np.finfo(
+            image_dtype
+        ).bits
     else:
-        field_illumination_unprocessed_dataset.input.bit_depth = None
+        field_illumination_unprocessed_dataset.input_parameters.bit_depth = None
 
     return {
         "unprocessed_dataset": field_illumination_unprocessed_dataset,
@@ -254,9 +255,7 @@ def st_field_illumination_table(
         dataset = draw(st_field_illumination_dataset())["unprocessed_dataset"]
         dataset.run()
         if dataset.processed:
-            key_values = {}
-            for col in columns:
-                key_values[col] = getattr(dataset.output.key_values, col)
+            key_values = {col: getattr(dataset.output.key_values, col) for col in columns}
         else:
             continue
         table.append(key_values)
@@ -336,14 +335,14 @@ def _gen_psf_beads_image(
         z_pos = z_image_shape // 2
         y_pos = random.choice(
             [
-                random.randint(5, int(min_distance_y / 2) - 2),
-                random.randint(y_image_shape - int(min_distance_y / 2) + 2, y_image_shape - 5),
+                random.randint(5, min_distance_y // 2 - 2),
+                random.randint(y_image_shape - min_distance_y // 2 + 2, y_image_shape - 5),
             ]
         )
         x_pos = random.choice(
             [
-                random.randint(5, int(min_distance_x / 2) - 2),
-                random.randint(x_image_shape - int(min_distance_x / 2) + 2, x_image_shape - 5),
+                random.randint(5, min_distance_x // 2 - 2),
+                random.randint(x_image_shape - min_distance_x // 2 + 2, x_image_shape - 5),
             ]
         )
         if not edge_bead_positions:
@@ -480,7 +479,7 @@ def st_psf_beads_test_data(
     min_distance_y = draw(min_distance)
     min_distance_x = draw(min_distance)
 
-    for image_nr in range(draw(nr_images)):
+    for _ in range(draw(nr_images)):
         _nr_valid_beads = draw(nr_valid_beads)
         _nr_edge_beads = draw(nr_edge_beads)
         _nr_out_of_focus_beads = draw(nr_out_of_focus_beads)
@@ -557,7 +556,7 @@ def st_psf_beads_dataset(
     test_data = draw(test_data)
     psf_beads_unprocessed_dataset = draw(unprocessed_dataset)
 
-    psf_beads_unprocessed_dataset.input.psf_beads_images = [
+    psf_beads_unprocessed_dataset.input_data.psf_beads_images = [
         numpy_to_mm_image(
             array=image,
             name=f"PSF_image_{i}",
@@ -567,16 +566,18 @@ def st_psf_beads_dataset(
     ]
 
     # Setting the bit depth to the data type of the image
-    image_dtype = {a.array_data.dtype for a in psf_beads_unprocessed_dataset.input.psf_beads_images}
+    image_dtype = {
+        a.array_data.dtype for a in psf_beads_unprocessed_dataset.input_data.psf_beads_images
+    }
     if len(image_dtype) != 1:
         raise ValueError("All images should have the same data type")
     image_dtype = image_dtype.pop()
     if np.issubdtype(image_dtype, np.integer):
-        psf_beads_unprocessed_dataset.input.bit_depth = np.iinfo(image_dtype).bits
+        psf_beads_unprocessed_dataset.input_parameters.bit_depth = np.iinfo(image_dtype).bits
     elif np.issubdtype(image_dtype, np.floating):
-        psf_beads_unprocessed_dataset.input.bit_depth = np.finfo(image_dtype).bits
+        psf_beads_unprocessed_dataset.input_parameters.bit_depth = np.finfo(image_dtype).bits
     else:
-        psf_beads_unprocessed_dataset.input.bit_depth = None
+        psf_beads_unprocessed_dataset.input_parameters.bit_depth = None
 
     return {
         "unprocessed_dataset": psf_beads_unprocessed_dataset,
diff --git a/src/microscopemetrics/utilities/__init__.py b/src/microscopemetrics/utilities/__init__.py
deleted file mode 100644
index e69de29..0000000
diff --git a/src/microscopemetrics/utilities/utilities.py b/src/microscopemetrics/utilities/utilities.py
deleted file mode 100644
index fb0cf44..0000000
--- a/src/microscopemetrics/utilities/utilities.py
+++ /dev/null
@@ -1,284 +0,0 @@
-# This is a place to hold mere utilities for metrics
-
-import json
-import warnings
-from configparser import ConfigParser
-from typing import Optional
-
-import numpy as np
-from numpy import float64, ndarray
-from scipy import special
-from scipy.optimize import curve_fit, fsolve
-
-INT_DETECTOR_BIT_DEPTHS = [8, 10, 11, 12, 15, 16, 32]
-FLOAT_DETECTOR_BIT_DEPTHS = [32, 64]
-
-
-## Some useful functions
-def convert_SI(val, unit_in, unit_out):
-    si = {
-        "nanometer": 0.000000001,
-        "micrometer": 0.000001,
-        "millimeter": 0.001,
-        "meter": 1.0,
-    }
-    return val * si[unit_in.lower()] / si[unit_out.lower()]
-
-
-# def airy_fun(x, centre, a, exp):  # , amp, bg):
-#     if (x - centre) == 0:
-#         return a * .5 ** exp
-#     else:
-#         return a * (special.j1(x - centre) / (x - centre)) ** exp
-#
-#
-# def multi_airy_fun(x, *params):
-#     y = np.zeros_like(x)
-#     for i in range(0, len(params), 3):
-#         y = y + airy_fun(x, params[i], params[i+1], params[i+2])
-#     return y
-def airy_fun(x: ndarray, centre: float64, amp: float64) -> ndarray:  # , exp):  # , amp, bg):
-    with np.errstate(divide="ignore", invalid="ignore"):
-        return np.where(
-            (x - centre) == 0,
-            amp * 0.5**2,
-            amp * (special.j1(x - centre) / (x - centre)) ** 2,
-        )
-
-
-def gaussian_fun(x, background, amplitude, center, sd):
-    gauss = np.exp(-np.power(x - center, 2.0) / (2 * np.power(sd, 2.0)))
-    return background + (amplitude - background) * gauss
-
-
-def fit_gaussian(profile, guess=None):
-    if guess is None:
-        guess = [profile.min(), profile.max(), profile.argmax(), 0.8]
-    x = np.linspace(0, profile.shape[0], profile.shape[0], endpoint=False)
-    popt, pcov, infodict, mesg, ier = curve_fit(
-        f=gaussian_fun, xdata=x, ydata=profile, p0=guess, maxfev=5000, full_output=True
-    )
-
-    if ier not in [1, 2, 3, 4]:
-        warnings.warn(f"No gaussian fit found. Reason: {mesg}")
-
-    fitted_profile = gaussian_fun(x, popt[0], popt[1], popt[2], popt[3])
-    fwhm = popt[3] * 2.35482
-
-    # Calculate the fit quality using the coefficient of determination (R^2)
-    y_mean = np.mean(profile)
-    sst = np.sum((profile - y_mean) ** 2)
-    ssr = np.sum((profile - fitted_profile) ** 2)
-    cd_r2 = 1 - (ssr / sst)
-
-    return fitted_profile, cd_r2, fwhm, popt
-
-
-def fit_airy(profile, guess=None):
-    profile = (profile - profile.min()) / (profile.max() - profile.min())
-    if guess is None:
-        guess = [profile.argmax(), 4 * profile.max()]
-    x = np.linspace(0, profile.shape[0], profile.shape[0], endpoint=False)
-    popt, pcov, infodict, mesg, ier = curve_fit(
-        f=airy_fun, xdata=x, ydata=profile, p0=guess, full_output=True
-    )
-
-    if ier not in [1, 2, 3, 4]:
-        warnings.warn(f"No airy fit found. Reason: {mesg}")
-
-    fitted_profile = airy_fun(x, popt[0], popt[1])
-
-    # Calculate the FWHM
-    def _f(d):
-        return airy_fun(d, popt[0], popt[1]) - (fitted_profile.max() - fitted_profile.min()) / 2
-
-    guess = np.array([fitted_profile.argmax() - 1, fitted_profile.argmax() + 1])
-    v = fsolve(_f, guess)
-    fwhm = abs(v[1] - v[0])
-
-    # Calculate the fit quality using the coefficient of determination (R^2)
-    y_mean = np.mean(profile)
-    sst = np.sum((profile - y_mean) ** 2)
-    ssr = np.sum((profile - fitted_profile) ** 2)
-    cd_r2 = 1 - (ssr / sst)
-
-    return fitted_profile, cd_r2, fwhm, popt
-
-
-def multi_airy_fun(x: ndarray, *params) -> ndarray:
-    y = np.zeros_like(x)
-    for i in range(0, len(params), 2):
-        y = y + airy_fun(x, params[i], params[i + 1])
-    return y
-
-
-def robust_z_score(data):
-    median = np.median(data)
-    mad = np.median(np.abs(data - median))
-    return 0.6745 * (data - median) / mad
-
-
-def z_score(data):
-    mean = np.mean(data)
-    std_dev = np.std(data)
-    return (data - mean) / std_dev
-
-
-def wavelength_to_rgb(wavelength, gamma=0.8):
-    """
-    Copied from https://www.noah.org/wiki/Wavelength_to_RGB_in_Python
-    This converts a given wavelength of light to an
-    approximate RGB color value. The wavelength must be given
-    in nanometers in the range from 380 nm through 750 nm
-    (789 THz through 400 THz).
-
-    Based on code by Dan Bruton
-    http://www.physics.sfasu.edu/astro/color/spectra.html
-    """
-
-    wavelength = float(wavelength)
-    if 380 < wavelength <= 440:
-        attenuation = 0.3 + 0.7 * (wavelength - 380) / (440 - 380)
-        r = ((-(wavelength - 440) / (440 - 380)) * attenuation) ** gamma
-        g = 0.0
-        b = (1.0 * attenuation) ** gamma
-    elif 440 < wavelength <= 490:
-        r = 0.0
-        g = ((wavelength - 440) / (490 - 440)) ** gamma
-        b = 1.0
-    elif 490 < wavelength <= 510:
-        r = 0.0
-        g = 1.0
-        b = (-(wavelength - 510) / (510 - 490)) ** gamma
-    elif 510 < wavelength <= 580:
-        r = ((wavelength - 510) / (580 - 510)) ** gamma
-        g = 1.0
-        b = 0.0
-    elif 580 < wavelength <= 645:
-        r = 1.0
-        g = (-(wavelength - 645) / (645 - 580)) ** gamma
-        b = 0.0
-    elif 645 < wavelength <= 750:
-        attenuation = 0.3 + 0.7 * (750 - wavelength) / (750 - 645)
-        r = (1.0 * attenuation) ** gamma
-        g = 0.0
-        b = 0.0
-    else:
-        r = 0.0
-        g = 0.0
-        b = 0.0
-    r *= int(r * 255)
-    g *= int(g * 255)
-    g *= int(g * 255)
-    return r, g, b
-
-
-# This class is not used after introduction of pydantic.
-class MetricsConfig(ConfigParser):
-    def getjson(self, section, option, **kwargs):
-        value = self.get(section, option, **kwargs)
-        try:
-            output = json.loads(value)
-        except json.JSONDecodeError as e:
-            raise e
-        return output
-
-    def getlist(self, section, option, **kwargs):
-        output = self.getjson(section, option, **kwargs)
-
-        if type(output) is list:
-            return output
-        else:
-            raise Exception(
-                f'The config option "{option}" in section "{section}" is not formatted as a list'
-            )
-
-    def getlistint(self, section, option, **kwargs):
-        try:
-            output = [int(x) for x in self.getlist(section, option, **kwargs)]
-            return output
-        except Exception as e:
-            print(
-                f'Some element in config option "{option}" in section "{section}" cannot be coerced into a integer'
-            )
-            raise e
-
-    def getlistfloat(self, section, option, **kwargs):
-        try:
-            output = [float(x) for x in self.getlist(section, option, **kwargs)]
-            return output
-        except Exception as e:
-            print(
-                f'Some element in config option "{option}" in section "{section}" cannot be coerced into a float'
-            )
-            raise e
-
-
-def is_saturated(
-    channel: ndarray, threshold: float = 0.0, detector_bit_depth: Optional[int] = None
-) -> bool:
-    """
-    Checks if the channel is saturated.
-    A warning if it suspects that the detector bit depth does not match the datatype.
-    thresh: float
-        Threshold for the ratio of saturated pixels to total pixels
-    detector_bit_depth: int
-        Bit depth of the detector. Sometimes, detectors bit depth are not matching the datatype of the measureemnts.
-        Here it can be specified the bit depth of the detector if known. The function is going to raise
-        If None, it will be inferred from the channel dtype.
-    """
-    if detector_bit_depth is not None:
-        if (
-            detector_bit_depth not in INT_DETECTOR_BIT_DEPTHS
-            and detector_bit_depth not in FLOAT_DETECTOR_BIT_DEPTHS
-        ):
-            raise ValueError(
-                f"The detector bit depth provided ({detector_bit_depth}) is not supported. Supported values are {INT_DETECTOR_BIT_DEPTHS} for integer detectors and {FLOAT_DETECTOR_BIT_DEPTHS} for floating point detectors."
-            )
-        if (
-            np.issubdtype(channel.dtype, np.integer)
-            and detector_bit_depth not in INT_DETECTOR_BIT_DEPTHS
-        ):
-            raise ValueError(
-                f"The channel datatype {channel.dtype} does not match the detector bit depth {detector_bit_depth}. The channel might be saturated."
-            )
-        elif (
-            np.issubdtype(channel.dtype, np.floating)
-            and detector_bit_depth not in FLOAT_DETECTOR_BIT_DEPTHS
-        ):
-            raise ValueError(
-                f"The channel datatype {channel.dtype} does not match the detector bit depth {detector_bit_depth}. The channel might be saturated."
-            )
-        else:
-            if np.issubdtype(channel.dtype, np.integer):
-                if detector_bit_depth > np.iinfo(channel.dtype).bits:
-                    raise ValueError(
-                        f"The channel datatype {channel.dtype} does not support the detector bit depth {detector_bit_depth}. The channel might be saturated."
-                    )
-                else:
-                    max_limit = pow(2, detector_bit_depth) - 1
-            elif np.issubdtype(channel.dtype, np.floating):
-                if detector_bit_depth != np.finfo(channel.dtype).bits:
-                    raise ValueError(
-                        f"The channel datatype {channel.dtype} does not support the detector bit depth {detector_bit_depth}. The channel might be saturated."
-                    )
-                else:
-                    max_limit = np.finfo(channel.dtype).max
-
-    else:
-        if np.issubdtype(channel.dtype, np.integer):
-            max_limit = np.iinfo(channel.dtype).max
-        elif np.issubdtype(channel.dtype, np.floating):
-            max_limit = np.finfo(channel.dtype).max
-        else:
-            raise ValueError("The channel provided is not a valid numpy dtype.")
-
-    if channel.max() > max_limit:
-        raise ValueError(
-            "The channel provided has values larger than the bit depth of the detector."
-        )
-
-    saturation_matrix = channel == max_limit
-    saturation_ratio = np.count_nonzero(saturation_matrix) / channel.size
-
-    return saturation_ratio > threshold
diff --git a/tests/unit/samples/test_argolight.py b/tests/unit/analyses/test_argolight.py
similarity index 97%
rename from tests/unit/samples/test_argolight.py
rename to tests/unit/analyses/test_argolight.py
index 6bf66bc..eaa2ea4 100644
--- a/tests/unit/samples/test_argolight.py
+++ b/tests/unit/analyses/test_argolight.py
@@ -1,7 +1,7 @@
 import numpy as np
 import pytest
 
-from microscopemetrics.samples import argolight, numpy_to_mm_image
+# from microscopemetrics.analyses import argolight, numpy_to_mm_image
 from tests.test_utilities import get_file
 
 
diff --git a/tests/unit/samples/test_field_illumination.py b/tests/unit/analyses/test_field_illumination.py
similarity index 83%
rename from tests/unit/samples/test_field_illumination.py
rename to tests/unit/analyses/test_field_illumination.py
index ed2786a..d300021 100644
--- a/tests/unit/samples/test_field_illumination.py
+++ b/tests/unit/analyses/test_field_illumination.py
@@ -4,7 +4,7 @@
 from microscopemetrics_schema import datamodel as mm_schema
 
 from microscopemetrics import SaturationError
-from microscopemetrics.samples import field_illumination
+from microscopemetrics.analyses import field_illumination
 from microscopemetrics.strategies import strategies as st_mm
 
 
@@ -16,7 +16,7 @@ def test_field_illumination_analysis_instantiation(dataset):
     assert dataset.name
     assert dataset.description
     assert dataset.microscope
-    assert dataset.input
+    assert dataset.input_parameters
 
 
 @given(st_mm.st_field_illumination_dataset())
@@ -24,7 +24,7 @@ def test_field_illumination_analysis_instantiation(dataset):
 def test_field_illumination_analysis_run(dataset):
     dataset = dataset["unprocessed_dataset"]
     assert not dataset.processed
-    assert field_illumination.analise_field_illumination(dataset)
+    assert field_illumination.analyse_field_illumination(dataset)
     assert dataset.processed
 
 
@@ -39,7 +39,7 @@ def test_field_illumination_analysis_run(dataset):
 def test_field_illumination_analysis_centers_geometric(dataset):
     field_illumination_dataset = dataset["unprocessed_dataset"]
     expected_output = dataset["expected_output"]
-    field_illumination.analise_field_illumination(field_illumination_dataset)
+    field_illumination.analyse_field_illumination(field_illumination_dataset)
 
     measured_centers = list(
         zip(
@@ -56,9 +56,9 @@ def test_field_illumination_analysis_centers_geometric(dataset):
     note(f"Expected output: {expected_output}")
     note(
         f"Input params: "
-        f"bit_depth: {field_illumination_dataset.input.bit_depth}"
-        f"saturation_threshold: {field_illumination_dataset.input.saturation_threshold}"
-        f"sigma: {field_illumination_dataset.input.sigma}"
+        f"bit_depth: {field_illumination_dataset.input_parameters.bit_depth}"
+        f"saturation_threshold: {field_illumination_dataset.input_parameters.saturation_threshold}"
+        f"sigma: {field_illumination_dataset.input_parameters.sigma}"
     )
 
     for measured_c, expected_c in zip(measured_centers, expected_centers):
@@ -77,7 +77,7 @@ def test_field_illumination_analysis_centers_geometric(dataset):
 def test_field_illumination_analysis_centers_of_mass(dataset):
     field_illumination_dataset = dataset["unprocessed_dataset"]
     expected_output = dataset["expected_output"]
-    field_illumination.analise_field_illumination(field_illumination_dataset)
+    field_illumination.analyse_field_illumination(field_illumination_dataset)
 
     measured_centers_weighted = list(
         zip(
@@ -94,9 +94,9 @@ def test_field_illumination_analysis_centers_of_mass(dataset):
     note(f"Expected output: {expected_output}")
     note(
         f"Input params: "
-        f"bit_depth: {field_illumination_dataset.input.bit_depth}"
-        f"saturation_threshold: {field_illumination_dataset.input.saturation_threshold}"
-        f"sigma: {field_illumination_dataset.input.sigma}"
+        f"bit_depth: {field_illumination_dataset.input_parameters.bit_depth}"
+        f"saturation_threshold: {field_illumination_dataset.input_parameters.saturation_threshold}"
+        f"sigma: {field_illumination_dataset.input_parameters.sigma}"
     )
 
     for measured_c_w, expected_c in zip(measured_centers_weighted, expected_centers):
@@ -108,7 +108,7 @@ def test_field_illumination_analysis_centers_of_mass(dataset):
 def test_field_illumination_analysis_max_intensity_positions(dataset):
     field_illumination_dataset = dataset["unprocessed_dataset"]
     expected_output = dataset["expected_output"]
-    field_illumination.analise_field_illumination(field_illumination_dataset)
+    field_illumination.analyse_field_illumination(field_illumination_dataset)
 
     measured_max_intensity_positions = list(
         zip(
@@ -125,9 +125,9 @@ def test_field_illumination_analysis_max_intensity_positions(dataset):
     note(f"Expected output: {expected_output}")
     note(
         f"Input params: "
-        f"bit_depth: {field_illumination_dataset.input.bit_depth}"
-        f"saturation_threshold: {field_illumination_dataset.input.saturation_threshold}"
-        f"sigma: {field_illumination_dataset.input.sigma}"
+        f"bit_depth: {field_illumination_dataset.input_parameters.bit_depth}"
+        f"saturation_threshold: {field_illumination_dataset.input_parameters.saturation_threshold}"
+        f"sigma: {field_illumination_dataset.input_parameters.sigma}"
     )
 
     for measured_m_i, expected_c in zip(measured_max_intensity_positions, expected_centers):
@@ -139,7 +139,7 @@ def test_field_illumination_analysis_max_intensity_positions(dataset):
 def test_field_illumination_analysis_centers_fitted(dataset):
     field_illumination_dataset = dataset["unprocessed_dataset"]
     expected_output = dataset["expected_output"]
-    field_illumination.analise_field_illumination(field_illumination_dataset)
+    field_illumination.analyse_field_illumination(field_illumination_dataset)
 
     measured_centers_fitted = list(
         zip(
@@ -156,9 +156,9 @@ def test_field_illumination_analysis_centers_fitted(dataset):
     note(f"Expected output: {expected_output}")
     note(
         f"Input params: "
-        f"bit_depth: {field_illumination_dataset.input.bit_depth}"
-        f"saturation_threshold: {field_illumination_dataset.input.saturation_threshold}"
-        f"sigma: {field_illumination_dataset.input.sigma}"
+        f"bit_depth: {field_illumination_dataset.input_parameters.bit_depth}"
+        f"saturation_threshold: {field_illumination_dataset.input_parameters.saturation_threshold}"
+        f"sigma: {field_illumination_dataset.input_parameters.sigma}"
     )
 
     for measured_m_i, expected_c in zip(measured_centers_fitted, expected_centers):
@@ -176,4 +176,4 @@ def test_field_illumination_analysis_centers_fitted(dataset):
 def test_field_illumination_analysis_raises_saturation_error(dataset):
     with pytest.raises(SaturationError):
         dataset = dataset["unprocessed_dataset"]
-        field_illumination.analise_field_illumination(dataset)
+        field_illumination.analyse_field_illumination(dataset)
diff --git a/tests/unit/samples/test_psf_beads.py b/tests/unit/analyses/test_psf_beads.py
similarity index 94%
rename from tests/unit/samples/test_psf_beads.py
rename to tests/unit/analyses/test_psf_beads.py
index 706ae75..968ab6d 100644
--- a/tests/unit/samples/test_psf_beads.py
+++ b/tests/unit/analyses/test_psf_beads.py
@@ -9,9 +9,9 @@
 from skimage.filters import gaussian
 from skimage.util import random_noise as skimage_random_noise
 
-from microscopemetrics.samples import psf_beads
+from microscopemetrics.analyses import psf_beads
 from microscopemetrics.strategies import strategies as st_mm
-from microscopemetrics.utilities.utilities import fit_gaussian
+from microscopemetrics.analyses.tools import fit_gaussian
 
 
 @given(
@@ -79,7 +79,7 @@ def test_psf_beads_analysis_instantiation(dataset):
     assert dataset.name
     assert dataset.description
     assert dataset.microscope
-    assert dataset.input
+    assert dataset.input_parameters
 
 
 @given(st_mm.st_psf_beads_dataset())
@@ -106,7 +106,7 @@ def test_psf_beads_analysis_run(dataset):
         ),
         unprocessed_dataset=st_mm_schema.st_mm_psf_beads_unprocessed_dataset(
             dataset=st_mm_schema.st_mm_dataset(
-                input=st_mm_schema.st_mm_psf_beads_input(
+                input_parameters=st_mm_schema.st_mm_psf_beads_input_parameters(
                     fitting_r2_threshold=st.just(0.8),  # TODO: Remove this?
                     intensity_robust_z_score_threshold=st.just(4.0),
                 )
@@ -117,7 +117,9 @@ def test_psf_beads_analysis_run(dataset):
 def test_psf_beads_analysis_nr_valid_beads(dataset):
     psf_beads_dataset = dataset["unprocessed_dataset"]
     expected_output = dataset["expected_output"]
-    psf_beads_dataset.input.min_lateral_distance_factor = expected_output["min_distance_y"][0]
+    psf_beads_dataset.input_parameters.min_lateral_distance_factor = expected_output[
+        "min_distance_y"
+    ][0]
 
     psf_beads.analyse_psf_beads(psf_beads_dataset)
 
@@ -145,7 +147,9 @@ def test_psf_beads_analysis_nr_lateral_edge_beads(dataset):
     psf_beads_dataset = dataset["unprocessed_dataset"]
     expected_output = dataset["expected_output"]
     psf_beads.analyse_psf_beads(psf_beads_dataset)
-    psf_beads_dataset.input.min_lateral_distance_factor = expected_output["min_distance_y"][0]
+    psf_beads_dataset.input_parameters.min_lateral_distance_factor = expected_output[
+        "min_distance_y"
+    ][0]
 
     expected = sum(len(im_ebp) for im_ebp in expected_output["edge_bead_positions"])
 
diff --git a/tests/unit/test_util_functions.py b/tests/unit/test_analysis_tools.py
similarity index 69%
rename from tests/unit/test_util_functions.py
rename to tests/unit/test_analysis_tools.py
index 32e723d..a78698a 100644
--- a/tests/unit/test_util_functions.py
+++ b/tests/unit/test_analysis_tools.py
@@ -2,7 +2,7 @@
 from hypothesis import given
 from hypothesis import strategies as st
 
-from microscopemetrics.utilities import utilities
+from microscopemetrics.analyses.tools import is_saturated
 
 
 @given(st.sampled_from([np.uint8, np.uint16, np.float32]))
@@ -17,7 +17,7 @@ def test_is_saturated(data_type):
     unsaturated_data[0:5, ...] = max_value / 2  # 50% of the image is saturated
     saturated_data = np.zeros((10, 10), data_type)
     saturated_data[0:5, ...] = max_value  # 50% of the image is saturated
-    assert not utilities.is_saturated(unsaturated_data)
-    assert not utilities.is_saturated(unsaturated_data, threshold=0.4)
-    assert utilities.is_saturated(saturated_data)
-    assert not utilities.is_saturated(saturated_data, threshold=0.6)
+    assert not is_saturated(unsaturated_data)
+    assert not is_saturated(unsaturated_data, threshold=0.4)
+    assert is_saturated(saturated_data)
+    assert not is_saturated(saturated_data, threshold=0.6)
diff --git a/tox.ini b/tox.ini
index 14d5dfb..8c7f544 100644
--- a/tox.ini
+++ b/tox.ini
@@ -12,4 +12,4 @@ skip_install = true
 
 commands =
   poetry install
-  pytest
+  pytest --hypothesis-profile=dev