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fix: 🐛 Correct typo in args_minimizer #604

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Feb 14, 2023
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fix: 🐛 Correct typo in args_minimizer #604

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166 changes: 166 additions & 0 deletions docs/examples/example9_6.ipynb
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Original file line number Diff line number Diff line change
@@ -0,0 +1,166 @@
{
"cells": [
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Global Fitting of a series of spectra"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"from spectrafit.plugins import notebook as nb"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"df = pd.read_csv(\n",
" \"https://raw.githubusercontent.com/Anselmoo/spectrafit/1cda9e0d93f9d0536380075e75fac50459555b99/Examples/data_global.csv\"\n",
")"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### This example shows how to fit a series of spectra with a common model\n",
"\n",
"To activate the _global fitting_ routine, `y_column` has to be defined to \n",
"a list of column names and not a single column name. The list of column names \n",
"will be selected for the fitting."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"spn = nb.SpectraFitNotebook(\n",
" df=df, x_column=\"energy\", y_column=[\"y_1\", \"y_2\", \"y_3\"], fname=\"example9_6\"\n",
")"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Defining the model as a function of the parameters\n",
"\n",
"The `initial model` is defined as a function of the parameters as for 2D fitting."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"## Warning: uncertainties could not be estimated:\n"
]
}
],
"source": [
"initial_model = [\n",
" {\n",
" \"pseudovoigt\": {\n",
" \"amplitude\": {\"max\": 2, \"min\": 0, \"vary\": True, \"value\": 1},\n",
" \"center\": {\"max\": 2, \"min\": -2, \"vary\": True, \"value\": 0},\n",
" \"fwhmg\": {\"max\": 0.3, \"min\": 0.02, \"vary\": True, \"value\": 0.1},\n",
" \"fwhml\": {\"max\": 0.2, \"min\": 0.01, \"vary\": True, \"value\": 0.1},\n",
" }\n",
" },\n",
" {\n",
" \"gaussian\": {\n",
" \"amplitude\": {\"max\": 2, \"min\": 0, \"vary\": True, \"value\": 0.3},\n",
" \"center\": {\"max\": 2., \"min\": 0, \"vary\": True, \"value\": 2},\n",
" \"fwhmg\": {\"max\": 0.3, \"min\": 0.02, \"vary\": True, \"value\": 0.1},\n",
" }\n",
" },\n",
" {\n",
" \"gaussian\": {\n",
" \"amplitude\": {\"max\": 2, \"min\": 0, \"vary\": True, \"value\": 0.3},\n",
" \"center\": {\"max\": 3.5, \"min\": 1.5, \"vary\": True, \"value\": 2.5},\n",
" \"fwhmg\": {\"max\": 0.4, \"min\": 0.02, \"vary\": True, \"value\": 0.2},\n",
" }\n",
" },\n",
" {\n",
" \"gaussian\": {\n",
" \"amplitude\": {\"max\": 2, \"min\": 0, \"vary\": True, \"value\": 0.3},\n",
" \"center\": {\"max\": 3.5, \"min\": 2, \"vary\": True, \"value\": 2.5},\n",
" \"fwhmg\": {\"max\": 0.4, \"min\": 0.02, \"vary\": True, \"value\": 0.3},\n",
" }\n",
" },\n",
" {\n",
" \"gaussian\": {\n",
" \"amplitude\": {\"max\": 2, \"min\": 0, \"vary\": True, \"value\": 0.3},\n",
" \"center\": {\"max\": 4.5, \"min\": 3, \"vary\": True, \"value\": 2.5},\n",
" \"fwhmg\": {\"max\": 0.4, \"min\": 0.02, \"vary\": True, \"value\": 0.3},\n",
" }\n",
" },\n",
" {\n",
" \"gaussian\": {\n",
" \"amplitude\": {\"max\": 2, \"min\": 0, \"vary\": True, \"value\": 0.3},\n",
" \"center\": {\"max\": 4.7, \"min\": 3.7, \"vary\": True, \"value\": 3.8},\n",
" \"fwhmg\": {\"max\": 0.4, \"min\": 0.02, \"vary\": True, \"value\": 0.3},\n",
" }\n",
" },\n",
"]\n",
"spn.solver_model(initial_model=initial_model, show_plot=False, show_metric=False)"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Note:\n",
"\n",
"Currently, the global fitting routine has no plot function. However, the\n",
"metric function can be used to plot the fit errors."
]
}
],
"metadata": {
"kernelspec": {
"display_name": ".venv",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.9"
},
"orig_nbformat": 4,
"vscode": {
"interpreter": {
"hash": "b199af289ce012bb6a24205fcd5edae736294423f0e29474acbaa2e2fdaf4f82"
}
}
},
"nbformat": 4,
"nbformat_minor": 2
}
2 changes: 1 addition & 1 deletion spectrafit/models.py
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Original file line number Diff line number Diff line change
Expand Up @@ -775,7 +775,7 @@ def __call__(self) -> Tuple[Minimizer, Any]:
self.solve_global_fitting,
params=self.params,
fcn_args=(self.x, self.data),
**self.args["minimizer"],
**self.args_solver["minimizer"],
)
else:
minimizer = Minimizer(
Expand Down