Release 1.2.3

.github/workflows/tests.yml

@@ -35,7 +35,7 @@ jobs:
           python3 -m pip install .[test]
       - name: Run tests
         run: |
-          coverage run --omit=tests/*,*/_*.py -m unittest discover -v -p *_test.py .
+          coverage run --omit=tests/*,*/_*.py -m pytest
           coverage xml
       - name: Upload to codecov
         uses: codecov/codecov-action@v3

CHANGELOG.md

@@ -2,6 +2,26 @@
 
 All notable changes to this project will be documented in this file.
 
+<a name="1.2.3"></a>
+
+## [1.2.3] - 2024-07-26
+
+### Features
+
+- (**mid**) Add missing `binary` constructor to `Midline` model. Now all models have a `binary` and `trinary` constructor.
+
+### Styling
+
+- Add rules to [ruff].
+
+### Testing
+
+- Make suite testable with [pytest].
+
+### Ci
+
+- Switch to [pytest] for testing.
+
 <a name="1.2.2"></a>
 
 ## [1.2.2] - 2024-06-25
@@ -23,11 +43,11 @@ All notable changes to this project will be documented in this file.
 
 ### Styling
 
-- Use ruff to fix lint and format code.
+- Use [ruff] to fix lint and format code.
 
 ### Build
 
-- Remove upper cap in deps.
+- Remove upper cap in dependencies because of [this](https://iscinumpy.dev/post/bound-version-constraints/).
 
 ### Change
 
@@ -793,3 +813,6 @@ Almost the entire API has changed. I'd therefore recommend to have a look at the
 [#41]: https://github.com/rmnldwg/lymph/issues/41
 [#40]: https://github.com/rmnldwg/lymph/issues/40
 [#38]: https://github.com/rmnldwg/lymph/issues/38
+
+[ruff]: https://astral.sh/ruff
+[pytest]: https://docs.pytest.org/en/stable/

lymph/models/midline.py

@@ -105,7 +105,7 @@ def __init__(
         if is_symmetric["tumor_spread"]:
             raise ValueError(
                 "If you want the tumor spread to be symmetric, consider using the "
-                "Bilateral class."
+                "Bilateral class.",
             )
         self.is_symmetric = is_symmetric
 
@@ -124,7 +124,7 @@ def __init__(
         if self.use_midext_evo and use_central:
             raise ValueError(
                 "Evolution to central tumor not yet implemented. Choose to use either "
-                "the central model or the midline extension evolution."
+                "the central model or the midline extension evolution.",
                 # Actually, this shouldn't be too hard, but we still need to think
                 # about it for a bit.
             )
@@ -168,6 +168,13 @@ def __init__(
             is_modality_leaf=False,
         )
 
+    @classmethod
+    def binary(cls, *args, **kwargs) -> Midline:
+        """Create a binary model."""
+        uni_kwargs = kwargs.pop("uni_kwargs", {})
+        uni_kwargs["allowed_states"] = [0, 1]
+        return cls(*args, uni_kwargs=uni_kwargs, **kwargs)
+
     @classmethod
     def trinary(cls, *args, **kwargs) -> Midline:
         """Create a trinary model."""
@@ -242,7 +249,7 @@ def unknown(self) -> models.Bilateral:
         if self.marginalize_unknown:
             return self._unknown
         raise AttributeError(
-            "This instance does not marginalize over unknown midline extension."
+            "This instance does not marginalize over unknown midline extension.",
         )
 
     def get_tumor_spread_params(
@@ -262,15 +269,15 @@ def get_tumor_spread_params(
 
         if self.use_mixing:
             params["contra"] = self.noext.contra.get_tumor_spread_params(
-                as_flat=as_flat
+                as_flat=as_flat,
             )
             params["mixing"] = self.mixing_param
         else:
             params["noext"] = {
-                "contra": self.noext.contra.get_tumor_spread_params(as_flat=as_flat)
+                "contra": self.noext.contra.get_tumor_spread_params(as_flat=as_flat),
             }
             params["ext"] = {
-                "contra": self.ext.contra.get_tumor_spread_params(as_flat=as_flat)
+                "contra": self.ext.contra.get_tumor_spread_params(as_flat=as_flat),
             }
 
         if as_flat or not as_dict:
@@ -295,15 +302,15 @@ def get_lnl_spread_params(
         if ext_lnl_params != noext_lnl_params:
             raise ValueError(
                 "LNL spread params not synched between ext and noext models. "
-                "Returning the ext params."
+                "Returning the ext params.",
             )
 
         if self.use_central:
             central_lnl_params = self.central.get_lnl_spread_params(as_flat=False)
             if central_lnl_params != ext_lnl_params:
                 warnings.warn(
                     "LNL spread params not synched between central and ext models. "
-                    "Returning the ext params."
+                    "Returning the ext params.",
                 )
 
         if as_flat or not as_dict:
@@ -412,7 +419,8 @@ def set_tumor_spread_params(
             noext_contra_kwargs = global_kwargs.copy()
             noext_contra_kwargs.update(kwargs.get("noext", {}).get("contra", {}))
             args = self.noext.contra.set_tumor_spread_params(
-                *args, **noext_contra_kwargs
+                *args,
+                **noext_contra_kwargs,
             )
 
             ext_contra_kwargs = global_kwargs.copy()
@@ -521,7 +529,7 @@ def load_patient_data(
         elif is_unknown.sum() > 0:
             warnings.warn(
                 f"Discarding {is_unknown.sum()} patients where midline extension "
-                "is unknown."
+                "is unknown.",
             )
 
     def midext_evo(self) -> np.ndarray:
@@ -638,7 +646,9 @@ def obs_dist(
         """
         if given_state_dist is None:
             given_state_dist = self.state_dist(
-                t_stage=t_stage, mode=mode, central=central
+                t_stage=t_stage,
+                mode=mode,
+                central=central,
             )
 
         if given_state_dist.ndim == 2:
@@ -653,7 +663,9 @@ def obs_dist(
         return np.stack(obs_dist)
 
     def _hmm_likelihood(
-        self, log: bool = True, for_t_stage: str | None = None
+        self,
+        log: bool = True,
+        for_t_stage: str | None = None,
     ) -> float:
         """Compute the likelihood of the stored data under the hidden Markov model."""
         llh = 0.0 if log else 1.0
@@ -771,7 +783,9 @@ def posterior_state_dist(
         if given_state_dist is None:
             utils.safe_set_params(self, given_params)
             given_state_dist = self.state_dist(
-                t_stage=t_stage, mode=mode, central=central
+                t_stage=t_stage,
+                mode=mode,
+                central=central,
             )
 
         if given_state_dist.ndim == 2:
@@ -817,7 +831,9 @@ def marginalize(
 
         if given_state_dist is None:
             given_state_dist = self.state_dist(
-                t_stage=t_stage, mode=mode, central=central
+                t_stage=t_stage,
+                mode=mode,
+                central=central,
             )
 
         if given_state_dist.ndim == 2:
@@ -907,7 +923,7 @@ def draw_patients(
 
         if self.use_central:
             raise NotImplementedError(
-                "Drawing patients from the central model not yet supported."
+                "Drawing patients from the central model not yet supported.",
             )
 
         drawn_t_stages = rng.choice(
@@ -920,13 +936,16 @@ def draw_patients(
             [
                 distributions[t_stage].draw_diag_times(rng=rng)
                 for t_stage in drawn_t_stages
-            ]
+            ],
         )
 
         if self.use_midext_evo:
             midext_evo = self.midext_evo()
             drawn_midexts = np.array(
-                [rng.choice(a=[False, True], p=midext_evo[t]) for t in drawn_diag_times]
+                [
+                    rng.choice(a=[False, True], p=midext_evo[t])
+                    for t in drawn_diag_times
+                ],
             )
         else:
             drawn_midexts = rng.choice(
@@ -956,7 +975,8 @@ def draw_patients(
                 seed=seed,
             )
             drawn_case_diags = np.concatenate(
-                [drawn_ipsi_diags, drawn_contra_diags], axis=1
+                [drawn_ipsi_diags, drawn_contra_diags],
+                axis=1,
             )
             drawn_diags[drawn_midexts == (case == "ext")] = drawn_case_diags
 

pyproject.toml

@@ -1,21 +1,15 @@
 [build-system]
-requires = [
-    "setuptools >= 61.0.0",
-    "setuptools_scm >= 7.0.0",
-    "wheel",
-]
+requires = ["setuptools >= 61.0.0", "setuptools_scm >= 7.0.0", "wheel"]
 build-backend = "setuptools.build_meta"
 
 [project]
 name = "lymph-model"
 description = "Package for statistical modelling of lymphatic metastatic spread."
-authors = [
-    {name = "Roman Ludwig", email = "roman.ludwig@usz.ch"}
-]
+authors = [{ name = "Roman Ludwig", email = "roman.ludwig@usz.ch" }]
 readme = "README.rst"
 requires-python = ">=3.10"
 keywords = ["cancer", "metastasis", "lymphatic progression", "model"]
-license = {text = "MIT"}
+license = { text = "MIT" }
 classifiers = [
     "Development Status :: 3 - Alpha",
     "License :: OSI Approved :: MIT License",
@@ -26,24 +20,12 @@ classifiers = [
     "Operating System :: OS Independent",
     "Topic :: Scientific/Engineering",
 ]
-dependencies = [
-    "numpy",
-    "pandas",
-    "cachetools",
-]
+dependencies = ["numpy", "pandas", "cachetools"]
 dynamic = ["version"]
 
 [project.optional-dependencies]
-test = [
-    "scipy",
-    "coverage",
-    "emcee",
-]
-dev = [
-    "pre-commit",
-    "pylint",
-    "git-cliff",
-]
+test = ["pytest", "scipy", "coverage", "emcee"]
+dev = ["pre-commit"]
 docs = [
     "sphinx",
     "sphinx-book-theme",
@@ -68,7 +50,12 @@ packages = ["lymph"]
 include-package-data = true
 
 [tool.setuptools.dynamic]
-version = {attr = "lymph._version.version"}
+version = { attr = "lymph._version.version" }
+
+
+[tool.pytest.ini_options]
+testpaths = ["tests"]
+filterwarnings = ["ignore::pandas.errors.PerformanceWarning"]
 
 
 [tool.isort]
@@ -87,7 +74,24 @@ all = true
 exclude = ["tests", "docs"]
 
 [tool.ruff.lint]
-select = ["E", "F", "W", "B", "C", "R", "U", "D", "I", "S", "T", "A", "N", "NPY201"]
+select = [
+    "E",
+    "F",
+    "W",
+    "B",
+    "C",
+    "R",
+    "U",
+    "D",
+    "I",
+    "S",
+    "T",
+    "A",
+    "N",
+    "COM",
+    "FURB",
+    "NPY201",
+]
 ignore = ["B028"]
 
 
@@ -141,20 +145,20 @@ filter_unconventional = true
 split_commits = false
 # regex for preprocessing the commit messages
 commit_preprocessors = [
-  # { pattern = '\((\w+\s)?#([0-9]+)\)', replace = "([#${2}](https://github.com/orhun/git-cliff/issues/${2}))"}, # replace issue numbers
+    # { pattern = '\((\w+\s)?#([0-9]+)\)', replace = "([#${2}](https://github.com/orhun/git-cliff/issues/${2}))"}, # replace issue numbers
 ]
 # regex for parsing and grouping commits
 commit_parsers = [
-  { message = "^feat", group = "Features" },
-  { message = "^fix", group = "Bug Fixes" },
-  { message = "^docs", group = "Documentation" },
-  { message = "^perf", group = "Performance" },
-  { message = "^refactor", group = "Refactor" },
-  { message = "^style", group = "Styling" },
-  { message = "^test", group = "Testing" },
-  { message = "^chore\\(release\\): prepare for", skip = true },
-  { message = "^chore", group = "Miscellaneous Tasks" },
-  { body = ".*security", group = "Security" },
+    { message = "^feat", group = "Features" },
+    { message = "^fix", group = "Bug Fixes" },
+    { message = "^docs", group = "Documentation" },
+    { message = "^perf", group = "Performance" },
+    { message = "^refactor", group = "Refactor" },
+    { message = "^style", group = "Styling" },
+    { message = "^test", group = "Testing" },
+    { message = "^chore\\(release\\): prepare for", skip = true },
+    { message = "^chore", group = "Miscellaneous Tasks" },
+    { body = ".*security", group = "Security" },
 ]
 # protect breaking changes from being skipped due to matching a skipping commit_parser
 protect_breaking_commits = false

tests/bayesian_unilateral_test.py

@@ -1,4 +1,5 @@
 """Test the Bayesian Unilateral Model."""
+import unittest
 
 import numpy as np
 
@@ -7,7 +8,7 @@
 
 class BayesianUnilateralModelTestCase(
     fixtures.BinaryUnilateralModelMixin,
-    fixtures.IgnoreWarningsTestCase,
+    unittest.TestCase,
 ):
     """Test the Bayesian Unilateral Model."""