From d349cdb230ec5b8dd5a4cd11f8f5cd59fe9eed04 Mon Sep 17 00:00:00 2001 From: "t.latour" Date: Mon, 2 Feb 2026 15:50:34 +0100 Subject: [PATCH 1/3] Switch from deprecated `pymc.ComstantData` to `pymc.Data` --- peak_performance/models.py | 56 +++++++++++++++++++------------------- 1 file changed, 28 insertions(+), 28 deletions(-) diff --git a/peak_performance/models.py b/peak_performance/models.py index 9a9532f..c757510 100644 --- a/peak_performance/models.py +++ b/peak_performance/models.py @@ -192,13 +192,13 @@ def define_model_normal(time: np.ndarray, intensity: np.ndarray) -> pm.Model: """ slope_guess, intercept_guess, noise_width_guess = initial_guesses(time, intensity) with pm.Model() as pmodel: - # add observations to the pmodel as ConstantData - pm.ConstantData("time", time) - pm.ConstantData("intensity", intensity) - # add guesses to the pmodel as ConstantData - pm.ConstantData("intercept_guess", intercept_guess) - pm.ConstantData("slope_guess", slope_guess) - noise_guess = pm.ConstantData("noise_width_guess", noise_width_guess) + # add observations to the pmodel as Data + pm.Data("time", time) + pm.Data("intensity", intensity) + # add guesses to the pmodel as Data + pm.Data("intercept_guess", intercept_guess) + pm.Data("slope_guess", slope_guess) + noise_guess = pm.Data("noise_width_guess", noise_width_guess) # priors plus error handling in case of mathematically impermissible values baseline_intercept = pm.Normal( @@ -351,13 +351,13 @@ def define_model_double_normal(time: np.ndarray, intensity: np.ndarray) -> pm.Mo slope_guess, intercept_guess, noise_width_guess = initial_guesses(time, intensity) coords = {"subpeak": [0, 1]} with pm.Model(coords=coords) as pmodel: - # add observations to the pmodel as ConstantData - pm.ConstantData("time", time) - pm.ConstantData("intensity", intensity) - # add guesses to the pmodel as ConstantData - pm.ConstantData("intercept_guess", intercept_guess) - pm.ConstantData("slope_guess", slope_guess) - noise_guess = pm.ConstantData("noise_width_guess", noise_width_guess) + # add observations to the pmodel as Data + pm.Data("time", time) + pm.Data("intensity", intensity) + # add guesses to the pmodel as Data + pm.Data("intercept_guess", intercept_guess) + pm.Data("slope_guess", slope_guess) + noise_guess = pm.Data("noise_width_guess", noise_width_guess) # priors baseline_intercept = pm.Normal( @@ -559,13 +559,13 @@ def define_model_skew(time: np.ndarray, intensity: np.ndarray) -> pm.Model: """ slope_guess, intercept_guess, noise_width_guess = initial_guesses(time, intensity) with pm.Model() as pmodel: - # add observations to the pmodel as ConstantData - pm.ConstantData("time", time) - pm.ConstantData("intensity", intensity) - # add guesses to the pmodel as ConstantData - pm.ConstantData("intercept_guess", intercept_guess) - pm.ConstantData("slope_guess", slope_guess) - noise_guess = pm.ConstantData("noise_width_guess", noise_width_guess) + # add observations to the pmodel as Data + pm.Data("time", time) + pm.Data("intensity", intensity) + # add guesses to the pmodel as Data + pm.Data("intercept_guess", intercept_guess) + pm.Data("slope_guess", slope_guess) + noise_guess = pm.Data("noise_width_guess", noise_width_guess) # priors plus error handling in case of mathematically impermissible values baseline_intercept = pm.Normal( @@ -675,13 +675,13 @@ def define_model_double_skew_normal(time: np.ndarray, intensity: np.ndarray) -> slope_guess, intercept_guess, noise_width_guess = initial_guesses(time, intensity) coords = {"subpeak": [0, 1]} with pm.Model(coords=coords) as pmodel: - # add observations to the pmodel as ConstantData - pm.ConstantData("time", time) - pm.ConstantData("intensity", intensity) - # add guesses to the pmodel as ConstantData - pm.ConstantData("intercept_guess", intercept_guess) - pm.ConstantData("slope_guess", slope_guess) - noise_guess = pm.ConstantData("noise_width_guess", noise_width_guess) + # add observations to the pmodel as Data + pm.Data("time", time) + pm.Data("intensity", intensity) + # add guesses to the pmodel as Data + pm.Data("intercept_guess", intercept_guess) + pm.Data("slope_guess", slope_guess) + noise_guess = pm.Data("noise_width_guess", noise_width_guess) # priors plus error handling in case of mathematically impermissible values baseline_intercept = pm.Normal( From 36ca4b6fe5781cc0e82ddee678dd7a93df1f0e50 Mon Sep 17 00:00:00 2001 From: "t.latour" Date: Mon, 2 Feb 2026 16:21:35 +0100 Subject: [PATCH 2/3] bump pre-commit version --- .pre-commit-config.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 67918db..32a7428 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -19,7 +19,7 @@ repos: hooks: - id: black - repo: https://github.com/pre-commit/mirrors-mypy - rev: v1.4.1 + rev: v1.19.1 hooks: - id: mypy exclude: 'test_.*?\.py$' From cb92a70a42216ef2558b7e350854e04a8d95f820 Mon Sep 17 00:00:00 2001 From: "t.latour" Date: Tue, 3 Feb 2026 08:50:53 +0100 Subject: [PATCH 3/3] Bump project version --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 02c44a0..283b467 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta" [project] name = "peak_performance" -version = "0.7.2" +version = "0.7.3" authors = [ {name = "Jochen Nießer", email = "j.niesser@fz-juelich.de"}, {name = "Michael Osthege", email = "m.osthege@fz-juelich.de"},