From d22dbae97ae67bb5258628a27d122520e6a33e82 Mon Sep 17 00:00:00 2001
From: Jonas Eschle <mayou36@jonas.eschle.com>
Date: Tue, 16 Apr 2024 16:35:19 -0400
Subject: [PATCH 1/6] enh: upgrade to Python312

---
 .pre-commit-config.yaml                    |  4 +--
 environment.yml                            |  5 ++-
 setup.cfg                                  | 12 ++++---
 src/hepstats/hypotests/hypotests_object.py | 21 +++++------
 src/hepstats/hypotests/toyutils.py         | 15 ++++----
 src/hepstats/utils/fit/__init__.py         | 10 +++++-
 src/hepstats/utils/fit/diverse.py          | 16 +++++++--
 src/hepstats/utils/fit/sampling.py         | 33 +++++------------
 tests/hypotests/test_calculators.py        |  2 +-
 tests/hypotests/test_discovery.py          | 42 ++++------------------
 tests/hypotests/test_toysutils.py          |  2 +-
 11 files changed, 67 insertions(+), 95 deletions(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 18e269d1..bfffe832 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -63,10 +63,10 @@ repos:
     rev: 1.8.5
     hooks:
       - id: nbqa-isort
-        additional_dependencies: [ isort==5.6.4 ]
+        additional_dependencies: [ isort]
 
       - id: nbqa-pyupgrade
-        additional_dependencies: [ pyupgrade==2.7.4 ]
+        additional_dependencies: [ pyupgrade]
         args: [ --py38-plus ]
 
 
diff --git a/environment.yml b/environment.yml
index ea3517ba..471d88d3 100644
--- a/environment.yml
+++ b/environment.yml
@@ -6,11 +6,10 @@ dependencies:
   - numpy
   - scipy
   - iminuit
-  - tensorflow>=2.4
   - tensorflow-probability
-  #- zfit
+  #- zfit  # todo: conda-forge is 0.18.1, we need 0.20.0
   - asdf
   - matplotlib
   - pip:
     - .
-    - zfit >=0.6.4
+    - zfit >=0.20.0
diff --git a/setup.cfg b/setup.cfg
index 7d595eb8..5cd7b1b9 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -23,7 +23,6 @@ classifiers =
     Programming Language :: Python
     Programming Language :: Python :: 3
     Programming Language :: Python :: 3 :: Only
-    Programming Language :: Python :: 3.8
     Programming Language :: Python :: 3.9
     Programming Language :: Python :: 3.10
     Programming Language :: Python :: 3.11
@@ -43,7 +42,7 @@ install_requires =
     scipy
     tqdm
     uhi
-python_requires = >=3.8
+python_requires = >=3.9
 package_dir =
     = src
 
@@ -52,8 +51,9 @@ where = src
 
 [options.extras_require]
 dev =
-    black
-    zfit
+    %(docs)s
+    %(test)s
+    pre-commit
 docs =
     matplotlib
     pydata-sphinx-theme
@@ -65,7 +65,9 @@ test =
     pytest
     pytest-cov
     pytest-runner
-    zfit
+    zfit>=0.20.0
+zfit =
+    zfit>=0.20.0
 
 [tool:pytest]
 junit_family = xunit2
diff --git a/src/hepstats/hypotests/hypotests_object.py b/src/hepstats/hypotests/hypotests_object.py
index 19e6bde7..914e8720 100644
--- a/src/hepstats/hypotests/hypotests_object.py
+++ b/src/hepstats/hypotests/hypotests_object.py
@@ -3,7 +3,7 @@
 import numpy as np
 
 from .parameters import POI
-from ..utils.fit import get_nevents
+from ..utils.fit import get_nevents, set_values_once
 from ..utils.fit.api_check import is_valid_data, is_valid_pdf
 from ..utils.fit.api_check import is_valid_loss, is_valid_fitresult, is_valid_minimizer
 
@@ -117,8 +117,7 @@ def set_params_to_bestfit(self):
         """
         Set the values of the parameters in the models to the best fit values
         """
-        for param in self.parameters:
-            param.set_value(self.bestfit.params[param]["value"])
+        set_values_once(self.parameters, self.bestfit)
 
     def lossbuilder(self, model, data, weights=None, oldloss=None):
         """Method to build a new loss function.
@@ -156,7 +155,7 @@ def lossbuilder(self, model, data, weights=None, oldloss=None):
 
         if weights is not None:
             for d, w in zip(data, weights):
-                d.set_weights(w)
+                d = d.with_weights(w)
 
         if hasattr(oldloss, "create_new"):
             loss = oldloss.create_new(
@@ -193,15 +192,11 @@ def __init__(self, input, minimizer, sampler, sample):
         self._sample = sample
         self._toys_loss = {}
 
-    def sampler(self, floating_params=None):
+    def sampler(self):
         """
         Create sampler with models.
 
-        Args:
-            floating_params: floating parameters in the sampler
-
-        Example with `zfit`:
-            >>> sampler = calc.sampler(floating_params=[zfit.Parameter("mean")])
+        >>> sampler = calc.sampler()
         """
         self.set_params_to_bestfit()
         nevents = []
@@ -214,7 +209,7 @@ def sampler(self, floating_params=None):
             else:
                 nevents.append(nevents_data)
 
-        return self._sampler(self.loss.model, nevents, floating_params)
+        return self._sampler(self.loss.model, nevents)
 
     def sample(self, sampler, ntoys, poi: POI, constraints=None):
         """
@@ -229,7 +224,7 @@ def sample(self, sampler, ntoys, poi: POI, constraints=None):
 
         Example with `zfit`:
             >>> mean = zfit.Parameter("mean")
-            >>> sampler = calc.sampler(floating_params=[mean])
+            >>> sampler = calc.sampler()
             >>> sample = calc.sample(sampler, 1000, POI(mean, 1.2))
 
         Returns:
@@ -257,6 +252,6 @@ def toys_loss(self, parameter_name: str):
         """
         if parameter_name not in self._toys_loss:
             parameter = self.get_parameter(parameter_name)
-            sampler = self.sampler(floating_params=[parameter])
+            sampler = self.sampler()
             self._toys_loss[parameter.name] = self.lossbuilder(self.model, sampler)
         return self._toys_loss[parameter_name]
diff --git a/src/hepstats/hypotests/toyutils.py b/src/hepstats/hypotests/toyutils.py
index 62f56831..8c684d5a 100644
--- a/src/hepstats/hypotests/toyutils.py
+++ b/src/hepstats/hypotests/toyutils.py
@@ -7,6 +7,7 @@
 
 import asdf
 import numpy as np
+import zfit.param
 from tqdm.auto import tqdm
 
 from .exceptions import ParameterNotFound, FormatError
@@ -219,7 +220,7 @@ def ntoys(self, poigen: POI, poieval: POIarray) -> int:
         except KeyError:
             return 0
 
-    def generate_and_fit_toys(
+    def generate_and_fit_toys(  # TODO PROFILE THIS
         self,
         ntoys: int,
         poigen: POI,
@@ -265,6 +266,7 @@ def generate_and_fit_toys(
         ntrials = 0
 
         progressbar = tqdm(total=ntoys)
+        minimum = None
 
         for i in range(ntoys):
             ntrials += 1
@@ -282,13 +284,13 @@ def generate_and_fit_toys(
                     )
                     param_dict = next(samples)
 
-                with ExitStack() as stack:
-                    for param, value in param_dict.items():
-                        stack.enter_context(param.set_value(value))
+                with zfit.param.set_values(param_dict):
 
                     for _ in range(2):
                         try:
-                            minimum = minimizer.minimize(loss=toys_loss)
+                            minimum = minimizer.minimize(
+                                loss=toys_loss
+                            )  # TODO: , init=minimum use previous minimum as starting point for parameter uncertainties
                             converged = minimum.converged
                             if converged:
                                 break
@@ -303,7 +305,8 @@ def generate_and_fit_toys(
                         msg = f"{nfailures} out of {ntrials} fits failed or didn't converge."
                         warnings.warn(msg, FitFailuresWarning)
                     continue
-
+                if minimum is None:
+                    raise RuntimeError("No minimum found.")
                 bestfit[i] = minimum.params[param]["value"]
                 nll_bestfit[i] = pll(minimizer, toys_loss, POI(param, bestfit[i]))
 
diff --git a/src/hepstats/utils/fit/__init__.py b/src/hepstats/utils/fit/__init__.py
index e7a31b74..5878e45f 100644
--- a/src/hepstats/utils/fit/__init__.py
+++ b/src/hepstats/utils/fit/__init__.py
@@ -1,2 +1,10 @@
-from .diverse import get_value, eval_pdf, pll, array2dataset, get_nevents, set_values
+from .diverse import (
+    get_value,
+    eval_pdf,
+    pll,
+    array2dataset,
+    get_nevents,
+    set_values,
+    set_values_once,
+)
 from .sampling import base_sampler, base_sample
diff --git a/src/hepstats/utils/fit/diverse.py b/src/hepstats/utils/fit/diverse.py
index 891eeeb7..01648d72 100644
--- a/src/hepstats/utils/fit/diverse.py
+++ b/src/hepstats/utils/fit/diverse.py
@@ -1,4 +1,4 @@
-from contextlib import ExitStack, contextmanager
+from contextlib import ExitStack, contextmanager, suppress
 
 import numpy as np
 
@@ -12,6 +12,16 @@ def get_value(value):
     return np.array(value)
 
 
+def set_values_once(params, values):
+    with suppress(ImportError):
+        import zfit
+
+        return zfit.param.set_values(params, values)  # more efficient
+
+    for p, v in zip(params, values):
+        p.set_value(v)
+
+
 def eval_pdf(model, x, params=None, allow_extended=False):
     """Compute pdf of model at a given point x and for given parameters values"""
 
@@ -34,7 +44,7 @@ def pdf(model, x):
         return pdf(model, x)
 
 
-def pll(minimizer, loss, pois) -> float:
+def pll(minimizer, loss, pois, init=None) -> float:
     """Compute minimum profile likelihood for fixed given parameters values."""
 
     with ExitStack() as stack:
@@ -44,7 +54,7 @@ def pll(minimizer, loss, pois) -> float:
             param.floating = False
 
         if any(param_loss.floating for param_loss in loss.get_params()):
-            minimum = minimizer.minimize(loss=loss)
+            minimum = minimizer.minimize(loss=loss)  # TODO: add init?
             value = minimum.fmin
         else:
             value = get_value(loss.value())
diff --git a/src/hepstats/utils/fit/sampling.py b/src/hepstats/utils/fit/sampling.py
index 753c56c4..293c3b98 100644
--- a/src/hepstats/utils/fit/sampling.py
+++ b/src/hepstats/utils/fit/sampling.py
@@ -6,14 +6,13 @@
 from .diverse import get_value
 
 
-def base_sampler(models, nevents, floating_params=None):
+def base_sampler(models, nevents):
     """
     Creates samplers from models.
 
     Args:
         models (list(model)): models to sample
         nevents (list(int)): number of in each sampler
-        floating_params (list(parameter), optionnal): floating parameter in the samplers
 
     Returns:
         Samplers
@@ -22,24 +21,10 @@ def base_sampler(models, nevents, floating_params=None):
     assert all(is_valid_pdf(m) for m in models)
     assert len(nevents) == len(models)
 
-    if floating_params:
-        floating_params_names = [f.name for f in floating_params]
-
     samplers = []
-    fixed_params = []
-    for m in models:
-
-        def to_fix(p):
-            if floating_params:
-                return p.name in floating_params_names
-            else:
-                return False
 
-        fixed = [p for p in m.get_params() if not to_fix(p)]
-        fixed_params.append(fixed)
-
-    for i, (m, p) in enumerate(zip(models, fixed_params)):
-        sampler = m.create_sampler(n=nevents[i], fixed_params=p)
+    for i, m in enumerate(models):
+        sampler = m.create_sampler(n=nevents[i])
         samplers.append(sampler)
 
     return samplers
@@ -72,13 +57,13 @@ def base_sample(samplers, ntoys, parameter=None, value=None, constraints=None):
                 continue
 
     for i in range(ntoys):
-        if not (parameter is None or value is None):
-            with parameter.set_value(value):
-                for s in samplers:
-                    s.resample()
+        if parameter is None or value is None:
+            params = None
         else:
-            for s in samplers:
-                s.resample()
+            params = {parameter: value}
+
+        for s in samplers:
+            s.resample(params=params)
 
         if constraints is not None:
             yield {param: value[i] for param, value in sampled_constraints.items()}
diff --git a/tests/hypotests/test_calculators.py b/tests/hypotests/test_calculators.py
index b7106547..da3eb667 100644
--- a/tests/hypotests/test_calculators.py
+++ b/tests/hypotests/test_calculators.py
@@ -182,7 +182,7 @@ def test_frequentist_calculator_one_poi(constraint):
     assert calc.ntoysnull == 100
     assert calc.ntoysalt == 100
 
-    samplers = calc.sampler(floating_params=[mean])
+    samplers = calc.sampler()
     assert all(is_valid_data(s) for s in samplers)
     loss = calc.toys_loss(mean.name)
     assert is_valid_loss(loss)
diff --git a/tests/hypotests/test_discovery.py b/tests/hypotests/test_discovery.py
index 26d11319..12e75b84 100644
--- a/tests/hypotests/test_discovery.py
+++ b/tests/hypotests/test_discovery.py
@@ -1,20 +1,15 @@
 import os
-import pytest
+
 import numpy as np
-import tqdm
+import pytest
 import zfit
-from zfit.loss import ExtendedUnbinnedNLL, UnbinnedNLL
+from zfit.loss import UnbinnedNLL
 from zfit.minimize import Minuit
 
-from zfit.models.dist_tfp import WrapDistribution
-import tensorflow_probability as tfp
-from zfit.util import ztyping
-from collections import OrderedDict
-
 import hepstats
-from hepstats.hypotests.calculators.basecalculator import BaseCalculator
-from hepstats.hypotests.calculators import AsymptoticCalculator, FrequentistCalculator
 from hepstats.hypotests import Discovery
+from hepstats.hypotests.calculators import AsymptoticCalculator, FrequentistCalculator
+from hepstats.hypotests.calculators.basecalculator import BaseCalculator
 from hepstats.hypotests.parameters import POI
 
 notebooks_dir = f"{os.path.dirname(hepstats.__file__)}/../../notebooks/hypotests"
@@ -101,31 +96,6 @@ def test_with_frequentist_calculator(create_loss, nbins):
     assert significance >= 3
 
 
-class Poisson(WrapDistribution):
-    _N_OBS = 1
-
-    def __init__(
-        self,
-        lamb: ztyping.ParamTypeInput,
-        obs: ztyping.ObsTypeInput,
-        name: str = "Poisson",
-    ):
-        """
-        Temporary class
-        """
-        (lamb,) = self._check_input_params(lamb)
-        params = OrderedDict((("lamb", lamb),))
-        dist_params = lambda: dict(rate=lamb.value())
-        distribution = tfp.distributions.Poisson
-        super().__init__(
-            distribution=distribution,
-            dist_params=dist_params,
-            obs=obs,
-            params=params,
-            name=name,
-        )
-
-
 def create_loss_counting():
     n = 370
     nbkg = 340
@@ -135,7 +105,7 @@ def create_loss_counting():
     Nobs = zfit.ComposedParameter("Nobs", lambda a, b: a + b, params=[Nsig, Nbkg])
 
     obs = zfit.Space("N", limits=(0, 800))
-    model = Poisson(obs=obs, lamb=Nobs)
+    model = zfit.pdf.Poisson(obs=obs, lamb=Nobs)
 
     data = zfit.data.Data.from_numpy(obs=obs, array=np.array([n]))
 
diff --git a/tests/hypotests/test_toysutils.py b/tests/hypotests/test_toysutils.py
index 2a5fe28f..21b82140 100644
--- a/tests/hypotests/test_toysutils.py
+++ b/tests/hypotests/test_toysutils.py
@@ -127,7 +127,7 @@ def test_toymanager_attributes():
         == tmc.get_toyresult(poigen, poieval).ntoys
     )
 
-    samplers = tm.sampler(floating_params=[poigen.parameter])
+    samplers = tm.sampler()
     assert all(is_valid_data(s) for s in samplers)
     loss = tm.toys_loss(poigen.name)
     assert is_valid_loss(loss)

From 33195ca4368a18515a9f28fca4cacf69515b6cf8 Mon Sep 17 00:00:00 2001
From: Jonas Eschle <mayou36@jonas.eschle.com>
Date: Tue, 16 Apr 2024 17:25:49 -0400
Subject: [PATCH 2/6] ci: update python versions

---
 .github/workflows/main.yml | 16 +++++++---------
 1 file changed, 7 insertions(+), 9 deletions(-)

diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
index 39ddf631..af148c8c 100644
--- a/.github/workflows/main.yml
+++ b/.github/workflows/main.yml
@@ -31,19 +31,17 @@ jobs:
         os:
           - ubuntu-latest
         python-version:
-          - "3.8"
           - "3.9"
           - "3.10"
           - "3.11"
+          - "3.12"
         include:
           - os: windows-latest
-            python-version: "3.8"
-          - os: windows-latest
-            python-version: "3.11"
-          - os: macos-latest
-            python-version: "3.8"
+            python-version: "3.9"
           - os: macos-latest
-            python-version: "3.11"
+            python-version: "3.9"
+          - os: macos-14
+            python-version: "3.9"
     name: Check Python ${{ matrix.python-version }} ${{ matrix.os }}
     steps:
       - uses: actions/checkout@v4
@@ -75,7 +73,7 @@ jobs:
         run: python -m pytest --doctest-modules --cov=hepstats --cov-report=xml -n3
 
       - name: Upload coverage to Codecov
-        if: matrix.python-version == '3.11' && matrix.os == 'ubuntu-latest'
+        if: matrix.python-version == '3.12' && matrix.os == 'ubuntu-latest'
         uses: codecov/codecov-action@v4
         with:
           token: ${{ secrets.CODECOV_TOKEN }}  # technically not needed, but prevents failures: https://community.codecov.com/t/upload-issues-unable-to-locate-build-via-github-actions-api/3954
@@ -109,7 +107,7 @@ jobs:
           fetch-depth: 0
       - uses: actions/setup-python@v5
         with:
-          python-version: "3.11"
+          python-version: "3.12"
       - name: Install dependencies
         run: |
           pip install -U -q -e .[docs]

From 91e440023f4fa4f71f667a6fbebae128e0b8cc35 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 16 Apr 2024 21:42:47 +0000
Subject: [PATCH 3/6] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 src/hepstats/hypotests/hypotests_object.py | 5 ++---
 src/hepstats/hypotests/toyutils.py         | 5 ++---
 src/hepstats/utils/fit/diverse.py          | 3 +++
 src/hepstats/utils/fit/sampling.py         | 5 +----
 4 files changed, 8 insertions(+), 10 deletions(-)

diff --git a/src/hepstats/hypotests/hypotests_object.py b/src/hepstats/hypotests/hypotests_object.py
index bebd0acb..d922954c 100644
--- a/src/hepstats/hypotests/hypotests_object.py
+++ b/src/hepstats/hypotests/hypotests_object.py
@@ -4,10 +4,9 @@
 
 import numpy as np
 
-from .parameters import POI
 from ..utils.fit import get_nevents, set_values_once
-from ..utils.fit.api_check import is_valid_data, is_valid_pdf
-from ..utils.fit.api_check import is_valid_loss, is_valid_fitresult, is_valid_minimizer
+from ..utils.fit.api_check import is_valid_data, is_valid_fitresult, is_valid_loss, is_valid_minimizer, is_valid_pdf
+from .parameters import POI
 
 
 class HypotestsObject:
diff --git a/src/hepstats/hypotests/toyutils.py b/src/hepstats/hypotests/toyutils.py
index af341269..a4cad7c3 100644
--- a/src/hepstats/hypotests/toyutils.py
+++ b/src/hepstats/hypotests/toyutils.py
@@ -2,7 +2,6 @@
 
 import warnings
 from collections.abc import Callable
-from contextlib import ExitStack
 from pathlib import Path
 
 import asdf
@@ -283,7 +282,6 @@ def generate_and_fit_toys(  # TODO PROFILE THIS
                     param_dict = next(samples)
 
                 with zfit.param.set_values(param_dict):
-
                     for _ in range(2):
                         try:
                             minimum = minimizer.minimize(
@@ -304,7 +302,8 @@ def generate_and_fit_toys(  # TODO PROFILE THIS
                         warnings.warn(msg, FitFailuresWarning, stacklevel=2)
                     continue
                 if minimum is None:
-                    raise RuntimeError("No minimum found.")
+                    msg = "No minimum found."
+                    raise RuntimeError(msg)
                 bestfit[i] = minimum.params[param]["value"]
                 nll_bestfit[i] = pll(minimizer, toys_loss, POI(param, bestfit[i]))
 
diff --git a/src/hepstats/utils/fit/diverse.py b/src/hepstats/utils/fit/diverse.py
index 1f793bb7..775aa9ab 100644
--- a/src/hepstats/utils/fit/diverse.py
+++ b/src/hepstats/utils/fit/diverse.py
@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 from contextlib import ExitStack, contextmanager, suppress
 
 import numpy as np
@@ -20,6 +22,7 @@ def set_values_once(params, values):
 
     for p, v in zip(params, values):
         p.set_value(v)
+    return None
 
 
 def eval_pdf(model, x, params=None, allow_extended=False):
diff --git a/src/hepstats/utils/fit/sampling.py b/src/hepstats/utils/fit/sampling.py
index ff825400..a1cf86bd 100644
--- a/src/hepstats/utils/fit/sampling.py
+++ b/src/hepstats/utils/fit/sampling.py
@@ -57,10 +57,7 @@ def base_sample(samplers, ntoys, parameter=None, value=None, constraints=None):
                 continue
 
     for i in range(ntoys):
-        if parameter is None or value is None:
-            params = None
-        else:
-            params = {parameter: value}
+        params = None if parameter is None or value is None else {parameter: value}
 
         for s in samplers:
             s.resample(params=params)

From ce060d32940ae9aa414b2f2ce5329818c5471e0f Mon Sep 17 00:00:00 2001
From: Jonas Eschle <mayou36@jonas.eschle.com>
Date: Tue, 16 Apr 2024 17:56:34 -0400
Subject: [PATCH 4/6] ci: fix macos version

---
 .github/workflows/main.yml | 9 +++++----
 1 file changed, 5 insertions(+), 4 deletions(-)

diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
index af148c8c..daa3e465 100644
--- a/.github/workflows/main.yml
+++ b/.github/workflows/main.yml
@@ -41,7 +41,7 @@ jobs:
           - os: macos-latest
             python-version: "3.9"
           - os: macos-14
-            python-version: "3.9"
+            python-version: "3.12"  # old versions not supported
     name: Check Python ${{ matrix.python-version }} ${{ matrix.os }}
     steps:
       - uses: actions/checkout@v4
@@ -66,11 +66,12 @@ jobs:
             ${{ runner.os }}-pip-
 
       - name: Install package
-        run: python -m pip install -e .[test] pytest-xdist   # for multiprocessing
-
+        run: |
+          python -m pip install --upgrade pip
+          python -m pip install -e .[test] pytest-xdist   # for multiprocessing
 
       - name: Test package
-        run: python -m pytest --doctest-modules --cov=hepstats --cov-report=xml -n3
+        run: python -m pytest --doctest-modules --cov=hepstats --cov-report=xml -n auto
 
       - name: Upload coverage to Codecov
         if: matrix.python-version == '3.12' && matrix.os == 'ubuntu-latest'

From 18633beda98166a09a67535691a9937bfb5f4e92 Mon Sep 17 00:00:00 2001
From: Jonas Eschle <mayou36@jonas.eschle.com>
Date: Tue, 16 Apr 2024 18:36:59 -0400
Subject: [PATCH 5/6] chore: fix unused init arg

---
 src/hepstats/utils/fit/diverse.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/src/hepstats/utils/fit/diverse.py b/src/hepstats/utils/fit/diverse.py
index 775aa9ab..db2fe281 100644
--- a/src/hepstats/utils/fit/diverse.py
+++ b/src/hepstats/utils/fit/diverse.py
@@ -46,6 +46,7 @@ def pdf(model, x):
 
 def pll(minimizer, loss, pois, init=None) -> float:
     """Compute minimum profile likelihood for fixed given parameters values."""
+    del init  # unused currently
 
     with ExitStack() as stack:
         for p in pois:

From 1b5696a8657a178d38e03902957411c0cc88ec2d Mon Sep 17 00:00:00 2001
From: Jonas Eschle <mayou36@jonas.eschle.com>
Date: Tue, 16 Apr 2024 18:38:07 -0400
Subject: [PATCH 6/6] ci: downgrade python for docs

---
 .github/workflows/main.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
index daa3e465..b90fc319 100644
--- a/.github/workflows/main.yml
+++ b/.github/workflows/main.yml
@@ -108,7 +108,7 @@ jobs:
           fetch-depth: 0
       - uses: actions/setup-python@v5
         with:
-          python-version: "3.12"
+          python-version: "3.11"
       - name: Install dependencies
         run: |
           pip install -U -q -e .[docs]