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Run more examples
Update transient absorption case study From ported examples Update examples and integrations tests This commit adds a (failing) integration test
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Diff for: ‎.github/workflows/integration-tests.yml

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import os
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from pathlib import Path
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example_names=["fluorescence"]
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example_names=["fluorescence", "transient_absorption", "transient_absorption_two_datasets", "spectral_constraints", "spectral_guidance"]
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gh_output = Path(os.getenv("GITHUB_OUTPUT", ""))
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with gh_output.open("a", encoding="utf8") as f:
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f.writelines([f"example-list={json.dumps(example_names)}"])
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pip install git+https://github.com/glotaran/pyglotaran-extras.git@staging_support
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- name: ${{ matrix.example_name }}
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id: example-run
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uses: glotaran/pyglotaran-examples@main
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uses: s-weigand/pyglotaran-examples@main
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with:
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example_name: ${{ matrix.example_name }}
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examples_branch: staging_rewrite
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examples_branch: port-examples
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- name: Installed packages
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if: always()
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run: |

Diff for: ‎.gitignore

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docs/source/notebooks/quickstart/quickstart_project/data
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docs/source/notebooks/quickstart/quickstart_project/results
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docs/source/notebooks/quickstart/quickstart_project/project.gta
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# Auto generated autocompletions files
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examples/case_studies/*/schema*.json

Diff for: ‎examples/case_studies/02-transient_absorption/analysis-1d-co_tol.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Example Case Study 02A\n",
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"\n",
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"## Transient absorption case study\n",
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"\n",
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"This notebook details the (global) target analysis of a tim-resolved transient absorption spectroscope measurement on a so called `co` compound dissolved in toluene and excited at 530 nm.\n",
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"\n",
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"For more details see the references in [README.md](README.md) or have a look at the [inspect_data.ipynb](data/inspect_data.ipynb) notebook.\n",
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"\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Requirements\n",
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"\n",
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"Be sure to have installed [pyglotaran](https://pypi.org/project/pyglotaran/) version 0.8 or greater, as well as [pyglotaran-extras](https://pypi.org/project/pyglotaran-extras/).\n",
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"\n",
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"```shell\n",
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"pip install pyglotaran>0.8 pyglotaran-extras\n",
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"```"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Imports\n",
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"\n",
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"Imports needed for the whole notebook"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Primary imports\n",
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"# For plotting\n",
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"from pyglotaran_extras import plot_data_overview, plot_overview\n",
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"\n",
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"# For backwards compatibility (with v0.7)\n",
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"from pyglotaran_extras.compat import convert\n",
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"\n",
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"from glotaran.io import load_dataset, load_parameters, load_scheme\n",
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"\n",
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"# Optional import for schema generation\n",
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"from glotaran.utils.json_schema import create_model_scheme_json_schema"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Load data"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"data_path1 = \"data/demo_data_Hippius_etal_JPCC2007_111_13988_Figs5_9.ascii\"\n",
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"dataset1 = load_dataset(data_path1)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"plot_data_overview(dataset1, linlog=True)\n",
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"dataset1.data.coords.keys()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Global Analysis\n",
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"\n",
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"TODO"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Target Analysis\n",
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"\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Load analysis scheme and parameters"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"parameters = load_parameters(\"parameters.yml\")\n",
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"create_model_scheme_json_schema(\"schema.json\", parameters)\n",
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"# this generates a json schema file which helps to provide autocompletion support\n",
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"# in editors for the scheme file\n",
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"\n",
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"scheme = load_scheme(\"scheme.yml\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Load data into scheme"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"scheme.load_data({\"dataset1\": dataset1})"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Optimization (fitting)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"result = scheme.optimize(parameters=parameters)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Visualize results (plotting)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# We use `convert` for backwards compatibility (with v0.7 plotting functions)\n",
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"result_plot, _ = plot_overview(convert(result.data[\"dataset1\"]), linlog=True)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Save result\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import tempfile\n",
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"from pathlib import Path\n",
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"\n",
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"folder_name = Path().resolve().name\n",
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"temp_folder = Path(tempfile.gettempdir())\n",
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"result_path = temp_folder / folder_name\n",
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"result_path"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"result.save(result_path / \"result\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Further exploration\n",
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"\n",
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"Some ideas for further exploration of the data/analysis.\n",
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"\n",
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"- Compare global to target analysis\n",
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"- Pre-processing of data (baseline subtraction)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "pyglotaran310",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

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