DX: switch to Ruff formatter

.gitpod.yml

@@ -23,7 +23,6 @@ vscode:
     - github.vscode-github-actions
     - github.vscode-pull-request-github
     - julialang.language-julia
-    - ms-python.black-formatter
     - ms-python.python
     - ms-python.vscode-pylance
     - ms-toolsai.vscode-jupyter-cell-tags

.pre-commit-config.yaml

@@ -39,7 +39,7 @@ repos:
             metadata.vscode
 
   - repo: https://github.com/ComPWA/policy
-    rev: 0.2.4
+    rev: 0.2.5
     hooks:
       - id: check-dev-files
         args:
@@ -55,6 +55,15 @@ repos:
       - id: pin-nb-requirements
       - id: set-nb-cells
 
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.2.1
+    hooks:
+      - id: ruff
+        args: [--fix]
+        types_or: [python, pyi, jupyter]
+      - id: ruff-format
+        types_or: [python, pyi, jupyter]
+
   - repo: https://github.com/pre-commit/pre-commit-hooks
     rev: v4.5.0
     hooks:
@@ -80,19 +89,6 @@ repos:
             .*\.svg
           )$
 
-  - repo: https://github.com/psf/black-pre-commit-mirror
-    rev: 24.1.1
-    hooks:
-      - id: black
-      - id: black-jupyter
-        args: [--line-length=85]
-        types_or: [jupyter]
-
-  - repo: https://github.com/asottile/blacken-docs
-    rev: 1.16.0
-    hooks:
-      - id: blacken-docs
-
   - repo: https://github.com/pre-commit/mirrors-prettier
     rev: v4.0.0-alpha.8
     hooks:
@@ -153,10 +149,3 @@ repos:
     rev: v1.1.350
     hooks:
       - id: pyright
-
-  - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.2.1
-    hooks:
-      - id: ruff
-        args: [--fix]
-        types_or: [python, pyi, jupyter]

.vscode/extensions.json

@@ -9,7 +9,6 @@
     "github.vscode-github-actions",
     "github.vscode-pull-request-github",
     "julialang.language-julia",
-    "ms-python.black-formatter",
     "ms-python.python",
     "ms-python.vscode-pylance",
     "ms-toolsai.vscode-jupyter-cell-tags",
@@ -26,6 +25,7 @@
     "bungcip.better-toml",
     "davidanson.vscode-markdownlint",
     "garaioag.garaio-vscode-unwanted-recommendations",
+    "ms-python.black-formatter",
     "ms-python.flake8",
     "ms-python.isort",
     "ms-python.mypy-type-checker",

.vscode/settings.json

@@ -16,13 +16,12 @@
     "editor.codeActionsOnSave": {
       "source.organizeImports": "explicit"
     },
-    "editor.defaultFormatter": "ms-python.black-formatter",
+    "editor.defaultFormatter": "charliermarsh.ruff",
     "editor.rulers": [88]
   },
   "[yaml]": {
     "editor.defaultFormatter": "esbenp.prettier-vscode"
   },
-  "black-formatter.importStrategy": "fromEnvironment",
   "cSpell.enabled": true,
   "diffEditor.experimental.showMoves": true,
   "editor.formatOnSave": true,

README.md

@@ -11,7 +11,6 @@
 [![pre-commit.ci status](https://results.pre-commit.ci/badge/github/ComPWA/compwa.github.io/main.svg)](https://results.pre-commit.ci/latest/github/ComPWA/compwa.github.io/main)
 [![Spelling checked](https://img.shields.io/badge/cspell-checked-brightgreen.svg)](https://github.com/streetsidesoftware/cspell/tree/master/packages/cspell)
 [![code style: prettier](https://img.shields.io/badge/code_style-prettier-ff69b4.svg?style=flat-square)](https://github.com/prettier/prettier)
-[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
 [![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/charliermarsh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
 
 This repository contains the source code for the [compwa.github.io](https://compwa.github.io) pages.

docs/adr/001/sympy.ipynb

@@ -506,9 +506,7 @@
     "\n",
     "import sympy as sp\n",
     "\n",
-    "x, A1, mu1, sigma1, A2, mu2, sigma2 = sp.symbols(\n",
-    "    \"x, A1, mu1, sigma1, A2, mu2, sigma2\"\n",
-    ")\n",
+    "x, A1, mu1, sigma1, A2, mu2, sigma2 = sp.symbols(\"x, A1, mu1, sigma1, A2, mu2, sigma2\")\n",
     "gaussian1 = (\n",
     "    A1 / (sigma1 * sp.sqrt(2.0 * math.pi)) * sp.exp(-((x - mu1) ** 2) / (2 * sigma1))\n",
     ")\n",
@@ -591,9 +589,7 @@
     }
    ],
    "source": [
-    "numpy_gauss_sum = sp.lambdify(\n",
-    "    (x, A1, mu1, sigma1, A2, mu2, sigma2), gauss_sum, \"numpy\"\n",
-    ")\n",
+    "numpy_gauss_sum = sp.lambdify((x, A1, mu1, sigma1, A2, mu2, sigma2), gauss_sum, \"numpy\")\n",
     "print(inspect.getsource(numpy_gauss_sum))"
    ]
   },
@@ -683,9 +679,7 @@
     "\n",
     "\n",
     "def native_jax_gauss_sum(x_, A1_, mu1_, sigma1_, A2_, mu2_, sigma2_):\n",
-    "    return jax_gaussian(x_, A1_, mu1_, sigma1_) + jax_gaussian(\n",
-    "        x_, A2_, mu2_, sigma2_\n",
-    "    )"
+    "    return jax_gaussian(x_, A1_, mu1_, sigma1_) + jax_gaussian(x_, A2_, mu2_, sigma2_)"
    ]
   },
   {

docs/adr/002/composition.ipynb

@@ -131,9 +131,7 @@
     "    ff02 = blatt_weisskopf(q0_squared, meson_radius, angular_momentum)\n",
     "    width = gamma0 * (mass0 / mass) * (ff2 / ff02)\n",
     "    width = width * sp.sqrt(q_squared / q0_squared)\n",
-    "    return (\n",
-    "        relativistic_breit_wigner(mass, mass0, width) * mass0 * gamma0 * sp.sqrt(ff2)\n",
-    "    )"
+    "    return relativistic_breit_wigner(mass, mass0, width) * mass0 * gamma0 * sp.sqrt(ff2)"
    ]
   },
   {

docs/adr/002/function.ipynb

@@ -151,10 +151,7 @@
     "        width = width * sp.sqrt(q_squared / q0_squared)\n",
     "        # Expression\n",
     "        return (\n",
-    "            RelativisticBreitWigner(mass, mass0, width)\n",
-    "            * mass0\n",
-    "            * gamma0\n",
-    "            * sp.sqrt(ff2)\n",
+    "            RelativisticBreitWigner(mass, mass0, width) * mass0 * gamma0 * sp.sqrt(ff2)\n",
     "        )\n",
     "\n",
     "    @classmethod\n",

docs/report/002.ipynb

@@ -837,9 +837,7 @@
     "intensity = LambdifiedFunction(sympy_model, backend=\"jax\")\n",
     "data_converter = HelicityTransformer(model.adapter)\n",
     "rng = TFUniformRealNumberGenerator(seed=0)\n",
-    "phsp_sample = generate_phsp(\n",
-    "    10_000, model.adapter.reaction_info, random_generator=rng\n",
-    ")\n",
+    "phsp_sample = generate_phsp(10_000, model.adapter.reaction_info, random_generator=rng)\n",
     "phsp_set = data_converter.transform(phsp_sample)"
    ]
   },

docs/report/003.ipynb

@@ -705,9 +705,9 @@
    "outputs": [],
    "source": [
     "s_thr = (m1 + m2) ** 2\n",
-    "integrand = (\n",
-    "    PhaseSpaceFactor(s_prime, m1, m2) * FormFactor(s_prime, m1, m2, L, q0)\n",
-    ") / ((s_prime - s_thr) * (s_prime - s - epsilon * sp.I))\n",
+    "integrand = (PhaseSpaceFactor(s_prime, m1, m2) * FormFactor(s_prime, m1, m2, L, q0)) / (\n",
+    "    (s_prime - s_thr) * (s_prime - s - epsilon * sp.I)\n",
+    ")\n",
     "integrand"
    ]
   },
@@ -857,8 +857,7 @@
    "outputs": [],
    "source": [
     "sigma = {\n",
-    "    l_val: (s_domain - s_thr_val) / np.pi * integral_values[l_val]\n",
-    "    for l_val in l_values\n",
+    "    l_val: (s_domain - s_thr_val) / np.pi * integral_values[l_val] for l_val in l_values\n",
     "}\n",
     "sigma_scaled = {l_val: 16 * np.pi * sigma[l_val] for l_val in l_values}"
    ]
@@ -1185,9 +1184,7 @@
     "s_values = np.linspace(-0.15, 1.4, num=200)\n",
     "fig, axes = plt.subplots(nrows=2, figsize=(6, 7), sharex=True)\n",
     "ax1, ax2 = axes\n",
-    "fig.suptitle(\n",
-    "    f\"Symbolic dispersion integrals for $m_1={m1_val:.2f}, m_2={m2_val:.2f}$\"\n",
-    ")\n",
+    "fig.suptitle(f\"Symbolic dispersion integrals for $m_1={m1_val:.2f}, m_2={m2_val:.2f}$\")\n",
     "for ax in axes:\n",
     "    ax.axhline(0, linewidth=0.5, c=\"black\")\n",
     "    ax.axvline(s_thr_val, **threshold_style)\n",

docs/report/005.ipynb

@@ -449,9 +449,7 @@
    ],
    "source": [
     "K_symbol = sp.IndexedBase(\"K\", shape=(n_channels, n_channels))\n",
-    "K = sp.Matrix(\n",
-    "    [[K_symbol[i, j] for j in range(n_channels)] for i in range(n_channels)]\n",
-    ")\n",
+    "K = sp.Matrix([[K_symbol[i, j] for j in range(n_channels)] for i in range(n_channels)])\n",
     "display(K_symbol[i, j], K)"
    ]
   },

docs/report/009.ipynb

@@ -911,9 +911,7 @@
     "                    c=color,\n",
     "                    rotation=+90,\n",
     "                )\n",
-    "                threshold_indicators.append(\n",
-    "                    (line_thr, line_diff, text_thr, text_diff)\n",
-    "                )\n",
+    "                threshold_indicators.append((line_thr, line_diff, text_thr, text_diff))\n",
     "        for i, (_, line_diff, _, text_diff) in enumerate(threshold_indicators):\n",
     "            m_a = kwargs[f\"m_a{i}\"]\n",
     "            m_b = kwargs[f\"m_b{i}\"]\n",

docs/report/010.ipynb

@@ -470,9 +470,9 @@
     "    m = sp.Symbol(\"m\", real=True)\n",
     "    epsilon = sp.Symbol(\"epsilon\", real=True)\n",
     "    i = sp.Symbol(\"i\", integer=True, negative=False)\n",
-    "    expr = f_vector(\n",
-    "        n_resonances, n_channels, angular_momentum=angular_momentum\n",
-    "    ).doit()[i, 0]\n",
+    "    expr = f_vector(n_resonances, n_channels, angular_momentum=angular_momentum).doit()[\n",
+    "        i, 0\n",
+    "    ]\n",
     "    expr = symplot.substitute_indexed_symbols(expr)\n",
     "    expr = expr.subs(m, m + epsilon * sp.I)\n",
     "    np_expr, sliders = symplot.prepare_sliders(expr, m)\n",

docs/report/013.ipynb

@@ -485,9 +485,7 @@
     "    intensity_func = create_function(substituted_expression, backend=\"jax\")\n",
     "    intensities_all = np.array(intensity_func(phsp).real)\n",
     "    intensities_k = compute_sub_intensities(model, \"K^*\", phsp, full_expression)\n",
-    "    intensities_delta = compute_sub_intensities(\n",
-    "        model, \"Delta^*\", phsp, full_expression\n",
-    "    )\n",
+    "    intensities_delta = compute_sub_intensities(model, \"Delta^*\", phsp, full_expression)\n",
     "    intensities_lambda = compute_sub_intensities(\n",
     "        model, \"Lambda^*\", phsp, full_expression\n",
     "    )\n",

docs/report/014.ipynb

@@ -642,8 +642,7 @@
    "source": [
     "wigner_functions = {\n",
     "    sp.Mul(*[\n",
-    "        formulate_wigner_d(transition, node_id)\n",
-    "        for node_id in transition.topology.nodes\n",
+    "        formulate_wigner_d(transition, node_id) for node_id in transition.topology.nodes\n",
     "    ])\n",
     "    for transition in reaction.transitions\n",
     "}\n",
@@ -985,10 +984,12 @@
     "def formulate_intensity_with_coefficient(reaction: ReactionInfo):\n",
     "    amplitudes = {\n",
     "        sp.Mul(\n",
-    "            C[[\n",
-    "                create_helicity_symbol(transition.topology, state_id)\n",
-    "                for state_id in transition.final_states\n",
-    "            ]],\n",
+    "            C[\n",
+    "                [\n",
+    "                    create_helicity_symbol(transition.topology, state_id)\n",
+    "                    for state_id in transition.final_states\n",
+    "                ]\n",
+    "            ],\n",
     "            *[\n",
     "                formulate_wigner_d(transition, node_id)\n",
     "                for node_id in transition.topology.nodes\n",

docs/report/015.ipynb

@@ -557,9 +557,7 @@
     "        particle_name = state.particle.latex\n",
     "        s = sp.Rational(state.particle.spin)\n",
     "        m = sp.Rational(state.spin_projection)\n",
-    "        display(\n",
-    "            Math(Rf\"|s_{i},m_{i}\\rangle=|{s},{m}\\rangle \\quad ({particle_name})\")\n",
-    "        )\n",
+    "        display(Math(Rf\"|s_{i},m_{i}\\rangle=|{s},{m}\\rangle \\quad ({particle_name})\"))\n",
     "        if functor is formulate_rotation_chain:\n",
     "            args = (transition, i)\n",
     "        else:\n",

docs/report/016.ipynb

@@ -600,9 +600,7 @@
    "outputs": [],
    "source": [
     "func = sp.lambdify([x, omega1, omega2, phi1, phi2], expr.doit())\n",
-    "fourier_func = sp.lambdify(\n",
-    "    [w, omega1, omega2, phi1, phi2, a, b], fourier_expr.doit()\n",
-    ")"
+    "fourier_func = sp.lambdify([w, omega1, omega2, phi1, phi2, a, b], fourier_expr.doit())"
    ]
   },
   {

docs/report/017.ipynb

@@ -208,9 +208,7 @@
     "@implement_doit_method\n",
     "class Kibble(UnevaluatedExpression):\n",
     "    def __new__(cls, sigma1, sigma2, sigma3, m0, m1, m2, m3, **hints) -> Kibble:\n",
-    "        return create_expression(\n",
-    "            cls, sigma1, sigma2, sigma3, m0, m1, m2, m3, **hints\n",
-    "        )\n",
+    "        return create_expression(cls, sigma1, sigma2, sigma3, m0, m1, m2, m3, **hints)\n",
     "\n",
     "    def evaluate(self) -> sp.Expr:\n",
     "        sigma1, sigma2, sigma3, m0, m1, m2, m3 = self.args\n",
@@ -609,13 +607,7 @@
     "    T2: T0 / 3 - r * sp.cos(theta + 2 * sp.pi / 3),\n",
     "    T3: T0 / 3 - r * sp.cos(theta + 4 * sp.pi / 3),\n",
     "    T0: (\n",
-    "        m0**2\n",
-    "        + m1**2\n",
-    "        + m2**2\n",
-    "        + m3**2\n",
-    "        - (m2 + m3) ** 2\n",
-    "        - (m1 + m3) ** 2\n",
-    "        - (m1 + m2) ** 2\n",
+    "        m0**2 + m1**2 + m2**2 + m3**2 - (m2 + m3) ** 2 - (m1 + m3) ** 2 - (m1 + m2) ** 2\n",
     "    ),\n",
     "}"
    ]

docs/report/018.ipynb

@@ -213,9 +213,7 @@
     "    initial_state_mass=reaction.initial_state[-1].mass,\n",
     "    final_state_masses={i: p.mass for i, p in reaction.final_state.items()},\n",
     ")\n",
-    "transformer = SympyDataTransformer.from_sympy(\n",
-    "    model.kinematic_variables, backend=\"jax\"\n",
-    ")\n",
+    "transformer = SympyDataTransformer.from_sympy(model.kinematic_variables, backend=\"jax\")\n",
     "phsp = phsp_generator.generate(1_000_000, rng)\n",
     "phsp = transformer(phsp)"
    ]
@@ -350,9 +348,7 @@
     "\n",
     "    Z_weights = griddata(np.transpose([x, y]), weights, (X, Y))\n",
     "    Z_unweighted, x_edges, y_edges = jnp.histogram2d(x, y, bins=n_bins)\n",
-    "    Z_weighted, x_edges, y_edges = jnp.histogram2d(\n",
-    "        x, y, bins=n_bins, weights=weights\n",
-    "    )\n",
+    "    Z_weighted, x_edges, y_edges = jnp.histogram2d(x, y, bins=n_bins, weights=weights)\n",
     "    # https://numpy.org/doc/stable/reference/generated/numpy.histogram2d.html\n",
     "    Z_unweighted = Z_unweighted.T\n",
     "    Z_weighted = Z_weighted.T\n",

docs/report/020.ipynb

@@ -810,9 +810,7 @@
    ],
    "source": [
     "minuit2 = Minuit2()\n",
-    "fit_result_with_caching = minuit2.optimize(\n",
-    "    estimator_with_caching, initial_parameters\n",
-    ")\n",
+    "fit_result_with_caching = minuit2.optimize(estimator_with_caching, initial_parameters)\n",
     "fit_result_with_caching"
    ]
   },
@@ -920,9 +918,9 @@
     "        # this here is rather to take full control, it is always possible\n",
     "\n",
     "        # updating the parameters of the model. This seems not very TF compatible?\n",
-    "        self.intensity.update_parameters(\n",
-    "            {p.name: float(p) for p in self.params.values()}\n",
-    "        )\n",
+    "        self.intensity.update_parameters({\n",
+    "            p.name: float(p) for p in self.params.values()\n",
+    "        })\n",
     "\n",
     "        # converting the data to a dict for tensorwaves\n",
     "        data = {ob: jnp.asarray(ar) for ob, ar in zip(self.obs, z.unstack_x(x))}\n",