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Break/pure parametrized function #579

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301085f
DX: support composable agent configurations
redeboer Aug 7, 2026
e6fa1a2
BREAK: replace update_parameters() with pure evaluation API
redeboer Aug 5, 2026
b818ba1
MAINT: implement updates from formatters
web-flow Aug 7, 2026
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4 changes: 2 additions & 2 deletions .gitignore
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Expand Up @@ -42,8 +42,8 @@ pyvenv*/
/.agents
/.claude/
/.codex
/AGENTS.md
/CLAUDE.md
AGENTS.md
CLAUDE.md

# Exceptions
!.cspell.json
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33 changes: 16 additions & 17 deletions docs/amplitude-analysis.ipynb
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Expand Up @@ -1395,7 +1395,7 @@
"\n",
"Let's have a look at our [first guess for the parameter values](#determine-free-parameters). Recall that a {class}`.ParametrizedFunction` object computes the intensity for a certain {obj}`.DataSample`. This can be seen nicely when we use these intensities as weights on the phase space sample and plot it together with the original data sample. Here, we look at the invariant mass distribution projection of the final states `1` and `2`, which, [as we saw before](compwa-step-2.3), is the final state particle pair $\\pi^0\\pi^0$.\n",
"\n",
"Don't forget to use {meth}`~.ParametrizedFunction.update_parameters` first!"
"Don't forget to first create a function with these initial parameter values using {meth}`~.ParametrizedFunction.with_parameters`!"
]
},
{
Expand Down Expand Up @@ -1473,8 +1473,8 @@
"outputs": [],
"source": [
"original_parameters = optimized_function.parameters\n",
"optimized_function.update_parameters(initial_parameters)\n",
"compare_model(\"m_12\", data_real, phsp_real, optimized_function)"
"initial_function = optimized_function.with_parameters(initial_parameters)\n",
"compare_model(\"m_12\", data_real, phsp_real, initial_function)"
]
},
{
Expand Down Expand Up @@ -1622,7 +1622,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"Using the same method as above, we renew the parameters of the {class}`.ParametrizedFunction` and plot it again over the phase space sample."
"Using the same method as above, we create a new {class}`.ParametrizedFunction` with the optimized parameter values and plot it again over the phase space sample."
]
},
{
Expand All @@ -1631,7 +1631,7 @@
"metadata": {},
"outputs": [],
"source": [
"optimized_function.update_parameters(fit_result.parameter_values)\n",
"optimized_function = optimized_function.with_parameters(fit_result.parameter_values)\n",
"compare_model(\"m_12\", data_real, phsp_real, optimized_function)"
]
},
Expand Down Expand Up @@ -1752,22 +1752,21 @@
" input_data: DataSample,\n",
" resonances: list[str],\n",
"):\n",
" original_parameters = dict(func.parameters)\n",
" negative_lookahead = f\"(?!{'|'.join(map(re.escape, resonances))})\"\n",
" # https://regex101.com/r/WrgGyD/1\n",
" pattern = rf\"^(\\\\mathcal{{H}}|C_)({negative_lookahead}.)*$\"\n",
" set_parameters_to_zero(func, pattern)\n",
" array = func(input_data)\n",
" func.update_parameters(original_parameters)\n",
" return array\n",
" zeroed_parameters = get_zeroed_parameters(func, pattern)\n",
" return func(input_data, zeroed_parameters)\n",
"\n",
"\n",
"def set_parameters_to_zero(func: ParametrizedFunction, name_pattern: str) -> None:\n",
" new_parameters = dict(func.parameters)\n",
" for par_name in func.parameters:\n",
" if re.match(name_pattern, par_name) is not None:\n",
" new_parameters[par_name] = 0\n",
" func.update_parameters(new_parameters)"
"def get_zeroed_parameters(\n",
" func: ParametrizedFunction, name_pattern: str\n",
") -> dict[str, complex]:\n",
" return {\n",
" par_name: 0\n",
" for par_name in func.parameters\n",
" if re.match(name_pattern, par_name) is not None\n",
" }"
]
},
{
Expand Down Expand Up @@ -1908,7 +1907,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.13.13"
"version": "3.13.14"
}
},
"nbformat": 4,
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2 changes: 2 additions & 0 deletions docs/conf.py
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Expand Up @@ -107,6 +107,8 @@ def get_tensorflow_url() -> str:
"**.ipynb_checkpoints",
"*build",
"adr*",
"AGENTS.md",
"CLAUDE.md",
"tests",
]
extensions = [
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36 changes: 24 additions & 12 deletions docs/usage.ipynb
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Expand Up @@ -144,9 +144,12 @@
"bin_values, bin_edges, _ = ax.hist(data[\"x\"], bins=50, alpha=0.7, label=\"data\")\n",
"x_values = (bin_edges[1:] + bin_edges[:-1]) / 2\n",
"y_values = bin_values\n",
"function.update_parameters(initial_parameters)\n",
"lines = ax.plot(\n",
" x_values, function({\"x\": x_values}), c=\"red\", linewidth=2, label=\"model\"\n",
" x_values,\n",
" function({\"x\": x_values}, initial_parameters),\n",
" c=\"red\",\n",
" linewidth=2,\n",
" label=\"model\",\n",
")\n",
"ax.legend(loc=\"upper right\")\n",
"plt.show()"
Expand Down Expand Up @@ -201,14 +204,15 @@
"class FitAnimation(Callback):\n",
" def __init__(self, data, function, x_values, output_file, estimated_iterations=140):\n",
" self.__function = function\n",
" self.__parameters = dict(function.parameters)\n",
" self.__fig, (self.__ax1, self.__ax2) = plt.subplots(\n",
" nrows=2, figsize=(7, 7), tight_layout=True\n",
" )\n",
" self.__ax2.set_yticks(np.arange(-30, 80, 10))\n",
" self.__ax1.hist(data[\"x\"], bins=50, alpha=0.7, label=\"data\")\n",
" self.__line = self.__ax1.plot(\n",
" x_values,\n",
" function({\"x\": x_values}),\n",
" function({\"x\": x_values}, self.__parameters),\n",
" c=\"red\",\n",
" linewidth=2,\n",
" label=\"model\",\n",
Expand All @@ -217,46 +221,54 @@
"\n",
" self.__par_lines = [\n",
" self.__ax2.plot(0, value, label=par)[0]\n",
" for par, value in function.parameters.items()\n",
" for par, value in self.__parameters.items()\n",
" ]\n",
" self.__ax2.set_xlim(0, estimated_iterations)\n",
" self.__ax2.set_title(\"Parameter values\")\n",
" self.__ax2.legend(\n",
" [f\"${sp.latex(sp.Symbol(par_name))}$\" for par_name in function.parameters],\n",
" [f\"${sp.latex(sp.Symbol(par_name))}$\" for par_name in self.__parameters],\n",
" loc=\"upper right\",\n",
" )\n",
"\n",
" self.__writer = PillowWriter(fps=15)\n",
" self.__writer.setup(self.__fig, outfile=output_file)\n",
"\n",
" def on_optimize_start(self, logs):\n",
" self._update_parameters(logs)\n",
" self._update_plot()\n",
"\n",
" def on_optimize_end(self, logs):\n",
" self._update_parameters(logs)\n",
" self._update_plot()\n",
" self.__writer.finish()\n",
"\n",
" def on_iteration_end(self, iteration, logs):\n",
" self._update_parameters(logs)\n",
" self._update_plot()\n",
" self.__writer.finish()\n",
"\n",
" def on_function_call_end(self, function_call, logs):\n",
" self._update_parameters(logs)\n",
" self._update_plot()\n",
"\n",
" def _update_parameters(self, logs):\n",
" if logs is not None:\n",
" self.__parameters.update(logs[\"parameters\"])\n",
"\n",
" def _update_plot(self):\n",
" self._update_parametrization_plot()\n",
" self._update_traceback()\n",
" self.__writer.grab_frame()\n",
"\n",
" def _update_parametrization_plot(self):\n",
" title = self._render_parameters(self.__function.parameters)\n",
" title = self._render_parameters(self.__parameters)\n",
" self.__ax1.set_title(title)\n",
" self.__line.set_ydata(self.__function({\"x\": x_values}))\n",
" self.__line.set_ydata(self.__function({\"x\": x_values}, self.__parameters))\n",
"\n",
" def _update_traceback(self):\n",
" for line in self.__par_lines:\n",
" par_name = line.get_label()\n",
" new_value = function.parameters[par_name]\n",
" new_value = self.__parameters[par_name]\n",
" x = line.get_xdata()\n",
" x = [*x, x[-1] + 1]\n",
" y = [*line.get_ydata(), new_value]\n",
Expand Down Expand Up @@ -730,13 +742,13 @@
")\n",
"def plot(dphi, k_r, k_phi, sigma):\n",
" global color_mesh, X, Y\n",
" polar_function.update_parameters({\n",
" parameters = {\n",
" R\"\\Delta\\phi\": dphi,\n",
" \"k_r\": k_r,\n",
" \"k_phi\": k_phi,\n",
" \"sigma\": sigma,\n",
" })\n",
" Z = polar_function(polar_domain)\n",
" }\n",
" Z = polar_function(polar_domain, parameters)\n",
" if color_mesh is not None:\n",
" color_mesh.remove()\n",
" color_mesh = ax_interactive.pcolormesh(X, Y, Z, cmap=\"coolwarm\")"
Expand Down Expand Up @@ -793,7 +805,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.13.12"
"version": "3.13.14"
}
},
"nbformat": 4,
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14 changes: 7 additions & 7 deletions docs/usage/basics.ipynb
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Expand Up @@ -589,7 +589,7 @@
"source": [
"For the rest, the procedure is really just the same as that sketched in {ref}`compwa-step-3`.\n",
"\n",
"We tweak the parameters a bit, then use {meth}`.ParametrizedBackendFunction.update_parameters` to change the function..."
"We tweak the parameters a bit, then use {meth}`.ParametrizedBackendFunction.with_parameters` to create a new function with these parameter values..."
]
},
{
Expand All @@ -606,7 +606,7 @@
" \"sigma_0\": 0.4,\n",
" \"sigma_1\": 0.4,\n",
"}\n",
"function_1d.update_parameters(initial_parameters)"
"function_1d = function_1d.with_parameters(initial_parameters)"
]
},
{
Expand Down Expand Up @@ -730,7 +730,7 @@
"outputs": [],
"source": [
"optimized_parameters = fit_result.parameter_values\n",
"function_1d.update_parameters(optimized_parameters)"
"function_1d = function_1d.with_parameters(optimized_parameters)"
]
},
{
Expand Down Expand Up @@ -1008,7 +1008,7 @@
" \"sigma_0\": 0.4,\n",
" \"sigma_1\": 0.4,\n",
"}\n",
"function_2d.update_parameters(initial_parameters)"
"function_2d = function_2d.with_parameters(initial_parameters)"
]
},
{
Expand Down Expand Up @@ -1148,7 +1148,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"If we update the parameters in the {class}`.ParametrizedFunction` with the optimized parameter values found by the {class}`.Optimizer`, we can compare the data distribution with the function."
"If we create a new {class}`.ParametrizedFunction` with the optimized parameter values found by the {class}`.Optimizer`, we can compare the data distribution with the function."
]
},
{
Expand All @@ -1158,7 +1158,7 @@
"outputs": [],
"source": [
"optimized_parameters = fit_result.parameter_values\n",
"function_2d.update_parameters(optimized_parameters)"
"function_2d = function_2d.with_parameters(optimized_parameters)"
]
},
{
Expand Down Expand Up @@ -1263,7 +1263,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.13.13"
"version": "3.13.14"
}
},
"nbformat": 4,
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18 changes: 13 additions & 5 deletions docs/usage/binned-fit.ipynb
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Expand Up @@ -126,11 +126,15 @@
},
"outputs": [],
"source": [
"function.update_parameters(initial_parameters)\n",
"fig, ax = plt.subplots(figsize=(8, 5))\n",
"ax.set_xlabel(\"$x$\")\n",
"ax.hist(x_distribution, bins=n_bins, label=\"Data distribution\")\n",
"ax.plot(x_values, function({\"x\": x_values}), label=\"Initial fit model\", c=\"red\")\n",
"ax.plot(\n",
" x_values,\n",
" function({\"x\": x_values}, initial_parameters),\n",
" label=\"Initial fit model\",\n",
" c=\"red\",\n",
")\n",
"ax.legend()\n",
"plt.show()"
]
Expand Down Expand Up @@ -198,11 +202,15 @@
},
"outputs": [],
"source": [
"function.update_parameters(fit_result.parameter_values)\n",
"fig, ax = plt.subplots(figsize=(8, 5))\n",
"ax.set_xlabel(\"$x$\")\n",
"ax.hist(x_distribution, bins=n_bins, label=\"Data distribution\")\n",
"ax.plot(x_values, function({\"x\": x_values}), label=\"Optimized model\", c=\"red\")\n",
"ax.plot(\n",
" x_values,\n",
" function({\"x\": x_values}, fit_result.parameter_values),\n",
" label=\"Optimized model\",\n",
" c=\"red\",\n",
")\n",
"ax.legend()\n",
"plt.show()"
]
Expand Down Expand Up @@ -270,7 +278,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.13.12"
"version": "3.13.14"
}
},
"nbformat": 4,
Expand Down
7 changes: 4 additions & 3 deletions docs/usage/chi-squared.ipynb
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Expand Up @@ -98,7 +98,7 @@
"source": [
"original_parameters = function.parameters\n",
"initial_parameters = {\"a\": -25, \"b\": 1.5, \"c\": 2.6}\n",
"function.update_parameters(initial_parameters)"
"function = function.with_parameters(initial_parameters)"
]
},
{
Expand Down Expand Up @@ -207,7 +207,8 @@
},
"outputs": [],
"source": [
"compare_model(function, x_values, observed_y)"
"optimized_function = function.with_parameters(fit_result.parameter_values)\n",
"compare_model(optimized_function, x_values, observed_y)"
]
}
],
Expand All @@ -230,7 +231,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.13.12"
"version": "3.13.14"
}
},
"nbformat": 4,
Expand Down
8 changes: 3 additions & 5 deletions docs/usage/unbinned-fit.ipynb
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Expand Up @@ -182,8 +182,7 @@
"Y = np.linspace(*ylim, bins_y)\n",
"X, Y = np.meshgrid(X, Y)\n",
"\n",
"function.update_parameters(initial_parameters)\n",
"Z = function({\"x\": X, \"y\": Y})\n",
"Z = function({\"x\": X, \"y\": Y}, initial_parameters)\n",
"\n",
"fig, (ax1, ax2) = plt.subplots(figsize=(8, 7), nrows=2, sharex=True, tight_layout=True)\n",
"ax1.set_title(\"Data distribution\")\n",
Expand Down Expand Up @@ -258,8 +257,7 @@
},
"outputs": [],
"source": [
"function.update_parameters(fit_result.parameter_values)\n",
"Z = function({\"x\": X, \"y\": Y})\n",
"Z = function({\"x\": X, \"y\": Y}, fit_result.parameter_values)\n",
"\n",
"fig, (ax1, ax2) = plt.subplots(figsize=(8, 7), nrows=2, sharex=True, tight_layout=True)\n",
"ax1.set_title(\"Data distribution\")\n",
Expand Down Expand Up @@ -292,7 +290,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.13.12"
"version": "3.13.14"
}
},
"nbformat": 4,
Expand Down
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