diff --git a/.copier-answers.yml b/.copier-answers.yml index 5751d20f..4003a370 100644 --- a/.copier-answers.yml +++ b/.copier-answers.yml @@ -1,16 +1,16 @@ # WARNING: Do not edit this file manually. # Any changes will be overwritten by Copier. -_commit: v0.10.0 +_commit: v0.10.1-2-gd05af4f _src_path: gh:easyscience/templates app_docs_url: https://easyscience.github.io/dynamics-app -app_doi: 10.5281/zenodo.18163581 +app_doi: 10.5281/zenodo.18877180 app_package_name: easydynamics_app app_python: '3.12' app_repo_name: dynamics-app home_page_url: https://easyscience.github.io/dynamics home_repo_name: dynamics lib_docs_url: https://easyscience.github.io/dynamics-lib -lib_doi: 10.5281/zenodo.18163581 +lib_doi: 10.5281/zenodo.18877180 lib_package_name: easydynamics lib_python_max: '3.12' lib_python_min: '3.11' diff --git a/docs/docs/assets/javascripts/extra.js b/docs/docs/assets/javascripts/extra.js index dd3fc356..9596ee07 100644 --- a/docs/docs/assets/javascripts/extra.js +++ b/docs/docs/assets/javascripts/extra.js @@ -1,6 +1,5 @@ -(function() { - - "use strict" +;(function () { + 'use strict' // Variables const header = document.getElementsByTagName('header')[0] @@ -10,20 +9,19 @@ // Hide-show header shadow function toggleHeaderShadow() { if (window.pageYOffset <= 0) { - header.classList.remove("md-header--shadow") + header.classList.remove('md-header--shadow') } else { - header.classList.add("md-header--shadow") + header.classList.add('md-header--shadow') } } // Onload - window.onload = function() { + window.onload = function () { toggleHeaderShadow() } // Onscroll - window.onscroll = function() { + window.onscroll = function () { toggleHeaderShadow() } - })() diff --git a/docs/docs/assets/javascripts/mathjax.js b/docs/docs/assets/javascripts/mathjax.js index a92ce69a..333524ec 100644 --- a/docs/docs/assets/javascripts/mathjax.js +++ b/docs/docs/assets/javascripts/mathjax.js @@ -3,21 +3,27 @@ window.MathJax = { //inlineMath: [['\\(', '\\)']], //displayMath: [['\\[', '\\]']], // Add support for $...$ and \(...\) delimiters - inlineMath: [['$', '$'], ['\\(', '\\)']], + inlineMath: [ + ['$', '$'], + ['\\(', '\\)'], + ], // Add support for $$...$$ and \[...]\ delimiters - displayMath: [['$$', '$$'], ['\\[', '\\]']], + displayMath: [ + ['$$', '$$'], + ['\\[', '\\]'], + ], processEscapes: true, - processEnvironments: true + processEnvironments: true, }, options: { //ignoreHtmlClass: ".*|", //processHtmlClass: "arithmatex" // Skip code blocks only - skipHtmlTags: ['script','noscript','style','textarea','pre','code'], + skipHtmlTags: ['script', 'noscript', 'style', 'textarea', 'pre', 'code'], // Only ignore explicit opt-out ignoreHtmlClass: 'no-mathjax|tex2jax_ignore', - } -}; + }, +} document$.subscribe(() => { MathJax.startup.output.clearCache() diff --git a/docs/docs/installation-and-setup/index.md b/docs/docs/installation-and-setup/index.md index 150ba5ab..6c928741 100644 --- a/docs/docs/installation-and-setup/index.md +++ b/docs/docs/installation-and-setup/index.md @@ -225,49 +225,32 @@ Google Colab. If you decide to run the tutorials locally, you need to download them first. This can be done individually via the :material-download: -**Download Notebook** button available on each tutorial page, or all at -once using the command line, as shown below. +**Download Notebook** button available on each tutorial page. ### Run Tutorials Locally with Pixi recommended { #running-with-pixi data-toc-label="Run Tutorials Locally with Pixi" } - Navigate to your existing Pixi project, created as described in the [Installing with Pixi](#installing-with-pixi) section. -- Add JupyterLab and the Pixi kernel for Jupyter: +- Launch the Jupyter Lab server: ```txt - pixi add --pypi jupyterlab pixi-kernel - ``` -- Download all the EasyDynamics tutorials to the `tutorials/` directory: - ```txt - pixi run easydynamics download-all-tutorials - ``` -- Start JupyterLab in the `tutorials/` directory to access the - notebooks: - ```txt - pixi run jupyter lab tutorials/ + pixi run jupyter lab ``` - Your web browser should open automatically. Click on one of the - `*.ipynb` files and select the `Python (Pixi)` kernel to get started. + `*.ipynb` files downloaded previously and select the `Python (Pixi)` + kernel to get started. ### Classical Run Tutorials Locally -- Install Jupyter Notebook and IPython kernel: - ```txt - pip install notebook ipykernel - ``` - Add the virtual environment as a Jupyter kernel: ```txt python -m ipykernel install --user --name=venv --display-name "EasyDynamics Python kernel" ``` -- Download all the EasyDynamics tutorials to the `tutorials/` directory: - ```txt - python -m easydynamics download-all-tutorials - ``` -- Launch the Jupyter Notebook server (opens browser automatically at - `http://localhost:8888/`): +- Launch the Jupyter Notebook server: ```txt - jupyter notebook tutorials/ + jupyter notebook ``` -- Open one of the `*.ipynb` files and select the +- Your web browser should open automatically. Click on one of the + `*.ipynb` files downloaded previously and select the `EasyDynamics Python kernel` to get started. ### Run Tutorials via Google Colab diff --git a/docs/docs/introduction/index.md b/docs/docs/introduction/index.md index 7b8e76a1..d749ae2a 100644 --- a/docs/docs/introduction/index.md +++ b/docs/docs/introduction/index.md @@ -45,7 +45,7 @@ Zenodo, each with a version-specific Digital Object Identifier (DOI). Citation details in various styles (e.g., APA, MLA) and formats (e.g., BibTeX, JSON) are available on the -[Zenodo archive page](https://doi.org/10.5281/zenodo.18163581). +[Zenodo archive page](https://doi.org/10.5281/zenodo.18877180). ## Contributing diff --git a/docs/docs/tutorials/analysis.ipynb b/docs/docs/tutorials/analysis.ipynb index 8403f24a..0ea7d90a 100644 --- a/docs/docs/tutorials/analysis.ipynb +++ b/docs/docs/tutorials/analysis.ipynb @@ -21,6 +21,8 @@ "outputs": [], "source": [ "# Imports\n", + "import pooch\n", + "\n", "from easydynamics.analysis.analysis import Analysis\n", "from easydynamics.experiment import Experiment\n", "from easydynamics.sample_model import BrownianTranslationalDiffusion\n", @@ -46,7 +48,12 @@ "source": [ "# Load the vanadium data\n", "vanadium_experiment = Experiment('Vanadium')\n", - "vanadium_experiment.load_hdf5(filename='vanadium_data_example.h5')" + "file_path = pooch.retrieve(\n", + " url='https://github.com/easyscience/dynamics-lib/raw/refs/heads/docs/docs/docs/tutorials/data/vanadium_data_example.h5',\n", + " known_hash='16cc1b327c303feeb88fb9dda5390dc4880b62396b1793f98c6fef0b27c7b873',\n", + ")\n", + "\n", + "vanadium_experiment.load_hdf5(filename=file_path)" ] }, { @@ -164,7 +171,12 @@ "# Now it's time to look at the data we want to fit. We first load the\n", "# data\n", "diffusion_experiment = Experiment('Diffusion')\n", - "diffusion_experiment.load_hdf5(filename='diffusion_data_example.h5')" + "\n", + "file_path = pooch.retrieve(\n", + " url='https://github.com/easyscience/dynamics-lib/raw/refs/heads/docs/docs/docs/tutorials/data/diffusion_data_example.h5',\n", + ")\n", + "\n", + "diffusion_experiment.load_hdf5(filename=file_path)" ] }, { @@ -330,9 +342,9 @@ ], "metadata": { "kernelspec": { - "display_name": "easydynamics_newbase", + "display_name": "Python (Pixi)", "language": "python", - "name": "python3" + "name": "pixi-kernel-python3" }, "language_info": { "codemirror_mode": { @@ -344,7 +356,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.12" + "version": "3.12.13" } }, "nbformat": 4, diff --git a/docs/docs/tutorials/analysis1d.ipynb b/docs/docs/tutorials/analysis1d.ipynb index 48eb8082..8230118a 100644 --- a/docs/docs/tutorials/analysis1d.ipynb +++ b/docs/docs/tutorials/analysis1d.ipynb @@ -11,11 +11,13 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "bca91d3c", "metadata": {}, "outputs": [], "source": [ + "import pooch\n", + "\n", "from easydynamics.analysis.analysis1d import Analysis1d\n", "from easydynamics.experiment import Experiment\n", "from easydynamics.sample_model import DeltaFunction\n", @@ -31,18 +33,25 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "8deca9b6", "metadata": {}, "outputs": [], "source": [ "vanadium_experiment = Experiment('Vanadium')\n", - "vanadium_experiment.load_hdf5(filename='vanadium_data_example.h5')" + "\n", + "file_path = pooch.retrieve(\n", + " url='https://github.com/easyscience/dynamics-lib/raw/refs/heads/docs/docs/docs/tutorials/data/vanadium_data_example.h5',\n", + " known_hash='16cc1b327c303feeb88fb9dda5390dc4880b62396b1793f98c6fef0b27c7b873',\n", + ")\n", + "\n", + "\n", + "vanadium_experiment.load_hdf5(filename=file_path)" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "41f842f0", "metadata": {}, "outputs": [], @@ -73,15 +82,16 @@ ")\n", "\n", "fit_result = my_analysis.fit()\n", - "fig = my_analysis.plot_data_and_model()" + "fig = my_analysis.plot_data_and_model()\n", + "fig" ] } ], "metadata": { "kernelspec": { - "display_name": "easydynamics_newbase", + "display_name": "Python (Pixi)", "language": "python", - "name": "python3" + "name": "pixi-kernel-python3" }, "language_info": { "codemirror_mode": { @@ -93,7 +103,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.12" + "version": "3.12.13" } }, "nbformat": 4, diff --git a/docs/docs/tutorials/diffusion_data_example.h5 b/docs/docs/tutorials/data/diffusion_data_example.h5 similarity index 100% rename from docs/docs/tutorials/diffusion_data_example.h5 rename to docs/docs/tutorials/data/diffusion_data_example.h5 diff --git a/docs/docs/tutorials/vanadium_data_example.h5 b/docs/docs/tutorials/data/vanadium_data_example.h5 similarity index 100% rename from docs/docs/tutorials/vanadium_data_example.h5 rename to docs/docs/tutorials/data/vanadium_data_example.h5 diff --git a/docs/docs/tutorials/experiment.ipynb b/docs/docs/tutorials/experiment.ipynb index f6e185df..0c4572f4 100644 --- a/docs/docs/tutorials/experiment.ipynb +++ b/docs/docs/tutorials/experiment.ipynb @@ -16,6 +16,8 @@ "metadata": {}, "outputs": [], "source": [ + "import pooch\n", + "\n", "from easydynamics.experiment import Experiment\n", "\n", "%matplotlib widget" @@ -29,8 +31,15 @@ "outputs": [], "source": [ "# Load and plot example vanadium data\n", + "# Load the vanadium data\n", "vanadium_experiment = Experiment('Vanadium')\n", - "vanadium_experiment.load_hdf5(filename='vanadium_data_example.h5')\n", + "\n", + "file_path = pooch.retrieve(\n", + " url='https://github.com/easyscience/dynamics-lib/raw/refs/heads/docs/docs/docs/tutorials/data/vanadium_data_example.h5',\n", + " known_hash='16cc1b327c303feeb88fb9dda5390dc4880b62396b1793f98c6fef0b27c7b873',\n", + ")\n", + "\n", + "vanadium_experiment.load_hdf5(filename=file_path)\n", "\n", "vanadium_experiment.plot_data()" ] @@ -61,9 +70,9 @@ ], "metadata": { "kernelspec": { - "display_name": "easydynamics_newbase", + "display_name": "Python (Pixi)", "language": "python", - "name": "python3" + "name": "pixi-kernel-python3" }, "language_info": { "codemirror_mode": { diff --git a/docs/docs/tutorials/index.md b/docs/docs/tutorials/index.md index 63d819a7..8c8ee61e 100644 --- a/docs/docs/tutorials/index.md +++ b/docs/docs/tutorials/index.md @@ -17,20 +17,34 @@ The tutorials are organized into the following categories: ## Getting Started -- [Component collection](component_collection.ipynb) – Learn how to - create a collectin of components for fitting. +We are working on expanding the list of tutorials to include advanced +concept such as interpolating `Parameter`s, sharing `Parameter`s at +multiple `Q` and analysing complex inelastic data. + +- [Tutorial 1: Brownian Diffusion](tutorial1_brownian.ipynb) - Learn how + to analyse QENS data with elastic incoherent background and Brownian + diffusion. + +## Classes and Methods + +Here we go into more detail with each class that is used in the +tutorials. + - [Components](components.ipynb) – Learn how to use the EasyDynamics - components. + model components, which are the basic building blocks of your model. +- [Component collection](component_collection.ipynb) – Learn how to + create a collection of components for fitting. - [Convolution](convolution.ipynb) – Learn how to calculate the convolution of your resolution function with your model. -- [Detailed balance](detailed_balance.ipynb) – Learn how to apply - detailed balancing to your model. +- [Detailed balance](detailed_balance.ipynb) – Learn about detailed + balancing. - [Diffusion model](diffusion_model.ipynb) – Learn how to create and use a model of diffusion. - [Sample model](sample_model.ipynb) – Learn how to create a model of - the scattering from your sample. + the scattering from your sample including model components and + diffusion models. - [Instrument model](instrument_model.ipynb) – Learn how to create a. - model of your instrument. + model of your instrument including resolution and background. - [Experiment](experiment.ipynb) - Learn how to load and bin your data. - [Analysis](analysis.ipynb) - Learn how to fit a model to your data. - [Analysis 1D](analysis1d.ipynb) - Learn how to fit a model to your diff --git a/docs/docs/tutorials/tutorial1_brownian.ipynb b/docs/docs/tutorials/tutorial1_brownian.ipynb new file mode 100644 index 00000000..86725cfa --- /dev/null +++ b/docs/docs/tutorials/tutorial1_brownian.ipynb @@ -0,0 +1,622 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "8643b10c", + "metadata": {}, + "source": [ + "# Brownian Diffusion\n", + "We here show how to set up an Analysis object and use it to first fit an artificial vanadium measurement to obtain the resolution. Next, we use the fitted resolution to fit an artificial measurement of a model with diffusion and some elastic scattering. \n", + "\n", + "We extract and plot the relevant parameters. Finally, we show how to fit directly to the diffusion model.\n", + "\n", + "In the near future, it will be possible to fit the width and area of the Lorentzian to the diffusion model as well." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bca91d3c", + "metadata": {}, + "outputs": [], + "source": [ + "# Imports\n", + "import pooch\n", + "\n", + "from easydynamics.analysis.analysis import Analysis\n", + "from easydynamics.experiment import Experiment\n", + "from easydynamics.sample_model import BrownianTranslationalDiffusion\n", + "from easydynamics.sample_model import ComponentCollection\n", + "from easydynamics.sample_model import DeltaFunction\n", + "from easydynamics.sample_model import Gaussian\n", + "from easydynamics.sample_model import Lorentzian\n", + "from easydynamics.sample_model import Polynomial\n", + "from easydynamics.sample_model.background_model import BackgroundModel\n", + "from easydynamics.sample_model.instrument_model import InstrumentModel\n", + "from easydynamics.sample_model.resolution_model import ResolutionModel\n", + "from easydynamics.sample_model.sample_model import SampleModel\n", + "\n", + "# Make the plots interactive\n", + "%matplotlib widget" + ] + }, + { + "cell_type": "markdown", + "id": "4c8e97b7", + "metadata": {}, + "source": [ + "We first create an `Experiment` object to contain the data. The data must either be a hdf5 file or a scipp.DataArray; in both cases it must have coordinates `Q` and `energy`. We here use Pooch to download an example vanadium data set.\n", + "\n", + "The data can be rebinned if needed, but we will show how to do that in a different tutorial." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8deca9b6", + "metadata": {}, + "outputs": [], + "source": [ + "# Load the vanadium data\n", + "vanadium_experiment = Experiment('Vanadium')\n", + "\n", + "file_path = pooch.retrieve(\n", + " url='https://github.com/easyscience/dynamics-lib/raw/refs/heads/docs/docs/docs/tutorials/data/vanadium_data_example.h5',\n", + " known_hash='16cc1b327c303feeb88fb9dda5390dc4880b62396b1793f98c6fef0b27c7b873',\n", + ")\n", + "\n", + "vanadium_experiment.load_hdf5(filename=file_path)" + ] + }, + { + "cell_type": "markdown", + "id": "7daa3f64", + "metadata": {}, + "source": [ + "We can visualize the data in multiple ways, relying on plopp: https://scipp.github.io/plopp/\n", + "\n", + "We here show two ways to look at the data: as a 2d colormap with intensity as function of `Q` and `energy`, and as a slicer with intensity as function of `energy` for various `Q`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fbd31297", + "metadata": {}, + "outputs": [], + "source": [ + "vanadium_experiment.plot_data(slicer=False)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4153ba52", + "metadata": {}, + "outputs": [], + "source": [ + "vanadium_experiment.plot_data(slicer=True)" + ] + }, + { + "cell_type": "markdown", + "id": "6c87b01c", + "metadata": {}, + "source": [ + "We now want to fit the vanadium data to determine our resolution. The scattering from vanadium is almost exclusively incoherent elastic, so we model it as a delta function. We do this by creating a `SampleModel` and adding a `DeltaFunction` component to it. The component acts as a template and gets copied to every `Q` when we attach the `SampleModel` to our `Analysis` object. Let's create the `SampleModel`.\n", + "\n", + "We do not give the `DeltaFunction` a `center` value. In this case, the center will be fixed at 0 energy transfer. We set the start value of the area to 1." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6762faba", + "metadata": {}, + "outputs": [], + "source": [ + "delta_function = DeltaFunction(display_name='DeltaFunction', area=1)\n", + "sample_model = SampleModel(components=delta_function)" + ] + }, + { + "cell_type": "markdown", + "id": "dc82774e", + "metadata": {}, + "source": [ + "We now want to define our resolution function. We will here model it as a Gaussian. We create a `ComponentCollection` and append the `Gaussian` to it. We can add as many components to our resolution as we like; sometimes you need several Gaussians and other functions to accurately describe the resolution.\n", + "\n", + "We fix the area of the resolution to have value 1. If we did not do this, we would fit both the area of the delta function and of the resolution Gaussian, and the fit would never converge.\n", + "\n", + "We finally insert the components in a `ResolutionModel`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8fdb7f19", + "metadata": {}, + "outputs": [], + "source": [ + "resolution_components = ComponentCollection()\n", + "res_gauss = Gaussian(width=0.1, area=1, display_name='Res. Gauss')\n", + "res_gauss.area.fixed = True\n", + "resolution_components.append_component(res_gauss)\n", + "resolution_model = ResolutionModel(components=resolution_components)" + ] + }, + { + "cell_type": "markdown", + "id": "088ac17d", + "metadata": {}, + "source": [ + "The background intensity was not 0, so we also create a background model. We use a `Polynomial` with a single coefficient, i.e. a flat background. We here show how to create the `BackgroundModel` and add the background in a single line. We could of course also add it like we did for the `SampleModel` or first create a `ComponentCollection` like we did for the `ResolutionModel`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1ec6836f", + "metadata": {}, + "outputs": [], + "source": [ + "background_model = BackgroundModel(components=Polynomial(coefficients=[0.001]))" + ] + }, + { + "cell_type": "markdown", + "id": "eae3d14b", + "metadata": {}, + "source": [ + "We combine the resolution abd background model into an `InstrumentModel`. This model also contains a fittable energy offset to account for instrument misalignment. All components are centered at this energy offset." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0ad79a75", + "metadata": {}, + "outputs": [], + "source": [ + "instrument_model = InstrumentModel(\n", + " resolution_model=resolution_model,\n", + " background_model=background_model,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "a99be7c1", + "metadata": {}, + "source": [ + "We are now ready to collect everything in an analysis object. We give it a display name, the experiment, the sample model and the instrument model. It will then automatically generate a model for each `Q` using the templates given in the `SampleModel`, `ResolutionModel` and `BackgroundModel`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b98d63dc", + "metadata": {}, + "outputs": [], + "source": [ + "vanadium_analysis = Analysis(\n", + " display_name='Vanadium Full Analysis',\n", + " experiment=vanadium_experiment,\n", + " sample_model=sample_model,\n", + " instrument_model=instrument_model,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "a81248a4", + "metadata": {}, + "source": [ + "Let us first fit a single Q index and plot the data and model to see how it looks. For this, we use the `independent` fit method and choose an arbitrary Q index" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "aec75b7f", + "metadata": {}, + "outputs": [], + "source": [ + "fit_result_independent_single_Q = vanadium_analysis.fit(fit_method='independent', Q_index=5)\n", + "vanadium_analysis.plot_data_and_model(Q_index=5)" + ] + }, + { + "cell_type": "markdown", + "id": "c3fe553b", + "metadata": {}, + "source": [ + "The fit looks good, so let us fit all Q indices independently and plot the results." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e98e3d65", + "metadata": {}, + "outputs": [], + "source": [ + "fit_result_independent_all_Q = vanadium_analysis.fit(fit_method='independent')\n", + "vanadium_analysis.plot_data_and_model()" + ] + }, + { + "cell_type": "markdown", + "id": "12936c9d", + "metadata": {}, + "source": [ + "It can be nice to inspect the fit parameters, and sometimes continue working with them. To do this, we can convert them to a scipp dataset.\n", + "\n", + "We can also plot the parameters as a function of `Q` using the `plot_parameters` method." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "133e682e", + "metadata": {}, + "outputs": [], + "source": [ + "# Inspect the Parameters as a scipp Dataset\n", + "vanadium_analysis.parameters_to_dataset()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dfacdf24", + "metadata": {}, + "outputs": [], + "source": [ + "# Plot some of fitted parameters as a function of Q\n", + "vanadium_analysis.plot_parameters(names=['DeltaFunction area'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b6f9f316", + "metadata": {}, + "outputs": [], + "source": [ + "vanadium_analysis.plot_parameters(names=['Res. Gauss width'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "572664a0", + "metadata": {}, + "outputs": [], + "source": [ + "vanadium_analysis.plot_parameters(names=['energy_offset'])" + ] + }, + { + "cell_type": "markdown", + "id": "ea2e5996", + "metadata": {}, + "source": [ + "We are now happy with our resolution function and can start looking at the data we want to fit. We first load and inspect the data in the same way as before. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3609e6c1", + "metadata": {}, + "outputs": [], + "source": [ + "diffusion_experiment = Experiment('Diffusion')\n", + "\n", + "file_path = pooch.retrieve(\n", + " url='https://github.com/easyscience/dynamics-lib/raw/refs/heads/docs/docs/docs/tutorials/data/diffusion_data_example.h5',\n", + ")\n", + "\n", + "diffusion_experiment.load_hdf5(filename=file_path)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ba9b14cc", + "metadata": {}, + "outputs": [], + "source": [ + "diffusion_experiment.plot_data(slicer=True)" + ] + }, + { + "cell_type": "markdown", + "id": "6da4f9e2", + "metadata": {}, + "source": [ + "The data seems to have a sharp elastic peak, a quasielastic peak and a non-zero background. We set up the corresponding `SampleModel` and `BackgroundModel` just like before." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e685909a", + "metadata": {}, + "outputs": [], + "source": [ + "delta_function = DeltaFunction(display_name='DeltaFunction', area=0.2)\n", + "lorentzian = Lorentzian(display_name='Lorentzian', area=0.5, width=0.3)\n", + "component_collection = ComponentCollection(\n", + " components=[delta_function, lorentzian],\n", + ")\n", + "\n", + "sample_model = SampleModel(\n", + " components=component_collection,\n", + ")\n", + "\n", + "background_model = BackgroundModel(components=Polynomial(coefficients=[0.001]))" + ] + }, + { + "cell_type": "markdown", + "id": "927b8fb5", + "metadata": {}, + "source": [ + "We also create a new instrument_model and attach it to our analysis. We want to use the resolutin that we determined from the vanadium data. Ideally, we'd just attach it to the instrument model like before. However, this is currently not possible due to a small issue in EasyDynamics that will be fixed asap. For now, we need to hack it a bit." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "53ecf27e", + "metadata": {}, + "outputs": [], + "source": [ + "instrument_model = InstrumentModel(\n", + " background_model=background_model,\n", + ")\n", + "\n", + "diffusion_analysis = Analysis(\n", + " display_name='Diffusion Analysis',\n", + " experiment=diffusion_experiment,\n", + " sample_model=sample_model,\n", + " instrument_model=instrument_model,\n", + ")\n", + "\n", + "# We need to hack in the resolution model from the vanadium analysis,\n", + "# since the setters and getters overwrite the model. This will be fixed\n", + "# asap.\n", + "diffusion_analysis.instrument_model._resolution_model = (\n", + " vanadium_analysis.instrument_model.resolution_model\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "b72a710b", + "metadata": {}, + "source": [ + "We don't want to fit our resolution anymore, so we fix all the parameters in it." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "18e2f0bf", + "metadata": {}, + "outputs": [], + "source": [ + "# We fix all parameters of the resolution model.\n", + "diffusion_analysis.instrument_model.resolution_model.fix_all_parameters()" + ] + }, + { + "cell_type": "markdown", + "id": "e366a05d", + "metadata": {}, + "source": [ + "Before we start fitting it is a good idea to check how good our start guesses are. We do this by plotting the data and the model using `plot_data_and_model`:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c66828eb", + "metadata": {}, + "outputs": [], + "source": [ + "diffusion_analysis.plot_data_and_model()" + ] + }, + { + "cell_type": "markdown", + "id": "2a4b7572", + "metadata": {}, + "source": [ + "The start guesses are not perfect, but they look good enough to start fitting. Let's give it a try!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9678eede", + "metadata": {}, + "outputs": [], + "source": [ + "diffusion_analysis.fit(fit_method='independent')\n", + "diffusion_analysis.plot_data_and_model()" + ] + }, + { + "cell_type": "markdown", + "id": "45daa848", + "metadata": {}, + "source": [ + "The fit looks good, so now we want to look at the most interesting fit parameters: the width and area of the Lorentzian. In later versions of EasyDynamics it will be possible to fit them to e.g. a DiffusionModel." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "df14b5c4", + "metadata": {}, + "outputs": [], + "source": [ + "# Let us look at the most interesting fit parameters\n", + "diffusion_analysis.plot_parameters(names=['Lorentzian width', 'Lorentzian area'])" + ] + }, + { + "cell_type": "markdown", + "id": "eb226c8f", + "metadata": {}, + "source": [ + "There is a clear trend: the area is more or less constant, while the width seems to increase with `Q^2`. We therefore try and fit a Brownian translational diffusion model to the data. In this model, the scattering is given by\n", + "$$\n", + "I(Q,E) = S \\frac{\\Gamma(Q)}{\\Gamma(Q)^2 + E^2},\n", + "$$\n", + "where $\\Gamma(Q) = D Q^2$ and $D$ is the diffusion coefficient. $S$ is an overall scale.\n", + "\n", + "In addition to this diffusion model, there is still the elastic incoherent scattering.\n", + "\n", + "We create a new `SampleModel` which as a `DeltaFunction` component for the elastic incoherent scattering and a `BrownianTranslationalDiffusion` diffusion model to describe the rest. We also create a new `BackgroundModel` and `InstrumentModel`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3b6bba77", + "metadata": {}, + "outputs": [], + "source": [ + "delta_function = DeltaFunction(display_name='DeltaFunction', area=0.2)\n", + "component_collection = ComponentCollection(\n", + " components=[delta_function],\n", + ")\n", + "diffusion_model = BrownianTranslationalDiffusion(\n", + " display_name='Brownian Translational Diffusion', diffusion_coefficient=2.4e-9, scale=0.5\n", + ")\n", + "\n", + "sample_model = SampleModel(\n", + " components=component_collection,\n", + " diffusion_models=diffusion_model,\n", + ")\n", + "\n", + "background_model = BackgroundModel(components=Polynomial(coefficients=[0.001]))\n", + "\n", + "instrument_model = InstrumentModel(\n", + " background_model=background_model,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "8bb4abe9", + "metadata": {}, + "source": [ + "We attach all our models to a new `Analysis` object, again being mindful that we need to hack in the resolution. I promise this will be fixed soon!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3efb9b53", + "metadata": {}, + "outputs": [], + "source": [ + "diffusion_model_analysis = Analysis(\n", + " display_name='Diffusion Full Analysis',\n", + " experiment=diffusion_experiment,\n", + " sample_model=sample_model,\n", + " instrument_model=instrument_model,\n", + ")\n", + "\n", + "# We again need to hack in the resolution model from the vanadium\n", + "# analysis, since the setters and getters overwrite the model. This will\n", + "# be fixed asap.\n", + "diffusion_model_analysis.instrument_model._resolution_model = (\n", + " vanadium_analysis.instrument_model.resolution_model\n", + ")\n", + "diffusion_model_analysis.instrument_model.resolution_model.fix_all_parameters()" + ] + }, + { + "cell_type": "markdown", + "id": "786157c0", + "metadata": {}, + "source": [ + "As always, we first check the start parameters before we fit" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "683dd27c", + "metadata": {}, + "outputs": [], + "source": [ + "diffusion_model_analysis.plot_data_and_model()" + ] + }, + { + "cell_type": "markdown", + "id": "43e2aa66", + "metadata": {}, + "source": [ + "We can now fit all the data simultaneously to our model. It looks good!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fd04d359", + "metadata": {}, + "outputs": [], + "source": [ + "diffusion_model_analysis.fit(fit_method='simultaneous')\n", + "diffusion_model_analysis.plot_data_and_model()" + ] + }, + { + "cell_type": "markdown", + "id": "bbeec088", + "metadata": {}, + "source": [ + "It does not make sense to plot the diffusion parameters, but we can display them (with uncertainties) like this." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "842c1f01", + "metadata": {}, + "outputs": [], + "source": [ + "diffusion_model.get_all_parameters()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python (Pixi)", + "language": "python", + "name": "pixi-kernel-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": "3.12.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/docs/user-guide/concept.md b/docs/docs/user-guide/concept.md new file mode 100644 index 00000000..4bb3bff4 --- /dev/null +++ b/docs/docs/user-guide/concept.md @@ -0,0 +1,56 @@ +The goal of EasyDynamics is to make it easy to fit QENS and powder INS +data. + +The fit is carried out by an `Analysis` object, which contains an +`Experiment` that contains the data, a `SampleModel` that describes the +scattering from the sample, and an `InstrumentModel` that describes the +instrument. Within the `InstrumentModel` lives the `ResolutionModel`, +which describes the instrument resolution, a `BackgroundModel`, which +describes the background scattering and an offset in energy to handle +small misalignments of the instrument. The `Analysis` object keeps track +of all of this and automatically calculates the convolution of the +resolution and the sample model. All objects are unit-aware and +automatically handle conversion, e.g. between $\mu$eV and meV. The +`Analysis` object furthermore contains methods to visualize the data, +model and fit parameters. + +The `SampleModel`, `BackgroundModel` and `InstrumentModel` each contains +a list of `ComponentCollection`s (one for each Q) describing the model +of the measured data. A `ComponentCollection` is essentially a list of +`ModelComponents`. A `ModelComponent` can be any of `Gaussian`, +`Lorentzian`, `Voigt` (the convolution of a `Gaussian` and +`Lorentzian`), `DeltaFunction`, `DampedHarmonicOscillator` and +`Polynomium`. + +Each `ModelComponent` has a number of `Parameter`s. The `Gaussian`, for +example, has `area`, `center` and `width`. Each of these `Parameter`s +has a number of properties and methods that can be accessed as needed. +The most important are, in no particular order: + +- `value`: The current value of the `Parameter` - gets updated when + fitting. +- `variance`: The variance of the `Parameter` - gets updated when + fitting. +- `error`: The square root of the `variance` - also gets updated when + fitting. +- `min`: the minimum value of the `Parameter` when fitting it. +- `max`: the maximum value of the `Parameter` when fitting it. +- `fixed`: If True, the `Parameter` is not fitted. +- `unit`: The unit of the `Parameter`. +- `convert_unit`: Change the unit of the `Parameter. + +So, for example, one can create a `Gaussian` and change its `Parameter`s +like this: + +```python +gaussian = Gaussian() +gaussian.area=2.0 +gaussian.area.fixed=True +gaussian.width.fixed=False +gaussian.width.min=0.5 +``` + +And so on. + +It is furthermore possible to make a `Parameter` depend on another +`Parameter`. We refer to the examples for this. diff --git a/docs/docs/user-guide/data_format.md b/docs/docs/user-guide/data_format.md new file mode 100644 index 00000000..e7441a0f --- /dev/null +++ b/docs/docs/user-guide/data_format.md @@ -0,0 +1,10 @@ +The data format for EasyDynamics is still under development, and input +is welcome. + +Currently, the data is stored in an `Experiment` object, and must be a +`scipp.DataArray` with coordinates `Q` and `energy`. + +If you have data that you wish to analyse with EasyDynamics, then please +do not hesitate to contact us and we will help create a loader for your +data. This will also provide us valuable information about what kind of +data formats we need to support. diff --git a/docs/docs/user-guide/first_steps.md b/docs/docs/user-guide/first_steps.md new file mode 100644 index 00000000..48fb9d82 --- /dev/null +++ b/docs/docs/user-guide/first_steps.md @@ -0,0 +1,52 @@ +# First Steps + +This section introduces the basic usage of the EasyDynamics Python API. +You'll learn how to import the package and use core classes and utility +functions, + +## Importing EasyDynamics + +### Importing the entire package + +To start using EasyDynamics, first import the package in your Python +script or Jupyter Notebook. This can be done with the following command: + +```python +import easydynamics +``` + +Alternatively, you can import it with an alias to avoid naming conflicts +and for convenience: + +```python +import easydynamics as ed +``` + +The latter syntax allows you to access all the modules and classes +within the package using the `ed` prefix. For example, you can create an +`Analysis` instance like this: + +```python +analysis = ed.Analysis() +``` + +### Importing specific parts + +Alternatively, you can import specific classes or methods from the +package. For example, you can import the `Analysis`, `SampleModel`, +`Experiment` and `Gaussian` classes like this: + +```python +from easydynamics.Analysis import Analysis +from easydynamics.Experiment import Experiment +from easydynamics.SampleModel import SampleModel, Gaussian +``` + +This enables you to use these classes and methods directly without the +package prefix. This is especially useful when you're using only a few +components and want to keep your code clean and concise. In this case, +you can create a `Analysis` instance like this: + +```python +analysis = Analysis() +``` diff --git a/docs/docs/user-guide/index.md b/docs/docs/user-guide/index.md index 849e9d01..7196d30a 100644 --- a/docs/docs/user-guide/index.md +++ b/docs/docs/user-guide/index.md @@ -4,21 +4,14 @@ icon: material/book-open-variant # :material-book-open-variant: User Guide -This section provides an overview of the **core concepts**, **key -parameters** and **workflow steps** required for using EasyDynamics -effectively. +This section provides an overview of the **core concepts** of +EasyDynamics. It will be expanded as the package matures. Here is a brief overview of the User Guide sections: -- [Glossary](#) – Defines common terms and labels used throughout the - documentation. -- [Concept](#) – Introduces the overall idea behind data analysis in - EasyDynamics. -- [Data Format](#) – Explains the data structures and file formats used - by EasyDynamics. -- [Parameters](#) – Describes how parameters are structured, named, and - accessed within the EasyDynamics. -- [First Steps](#) – Shows how to begin using EasyDynamics in Python or - Jupyter notebooks. -- [Analysis Workflow](#) – Breaks down the data analysis pipeline into - practical, sequential steps. +- [Concept](concept.md) – Introduces the overall idea behind data + analysis in EasyDynamics. +- [Data Format](data_format.md) – Explains the data structures and file + formats used by EasyDynamics. +- [First Steps](first_steps.md) – Shows how to begin using EasyDynamics + in Python or Jupyter notebooks. diff --git a/docs/mkdocs.yml b/docs/mkdocs.yml index 1939b307..bd73822e 100644 --- a/docs/mkdocs.yml +++ b/docs/mkdocs.yml @@ -176,11 +176,16 @@ nav: - Installation & Setup: installation-and-setup/index.md - User Guide: - User Guide: user-guide/index.md + - Concept: user-guide/concept.md + - Data Format: user-guide/data_format.md + - First Steps: user-guide/first_steps.md - Tutorials: - Tutorials: tutorials/index.md - Getting Started: - - Component collection: tutorials/component_collection.ipynb + - Tutorial 1. Brownian Diffusion: tutorials/tutorial1_brownian.ipynb + - Classes and Methods: - Components: tutorials/components.ipynb + - Component collection: tutorials/component_collection.ipynb - Convolution: tutorials/convolution.ipynb - Detailed balance: tutorials/detailed_balance.ipynb - Diffusion model: tutorials/diffusion_model.ipynb diff --git a/pixi.lock b/pixi.lock index 0c574543..79b0bdd0 100644 --- a/pixi.lock +++ b/pixi.lock @@ -9,38 +9,37 @@ environments: pypi-prerelease-mode: if-necessary-or-explicit packages: linux-64: - - conda: https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2 - - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-2_gnu.tar.bz2 - - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_8.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/c-ares-1.34.6-hb03c661_0.conda - 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'easyscience', # The base library of the EasyScience framework - 'pooch', # Data downloader - 'darkdetect', # Detecting dark mode (system-level) - 'pandas', # Displaying tables in Jupyter notebooks - 'plotly', # Interactive plots - 'py3Dmol', # Visualisation of crystal structures - 'ipympl', # Matplotlib Jupyter backend - 'ipywidgets', # Jupyter widgets - 'jupyterlab', # Jupyter notebooks - 'pixi-kernel', # Pixi Jupyter kernel - 'plopp', # Plotting library + 'easyscience', # The base library of the EasyScience framework + 'pooch', # Data downloader + 'darkdetect', # Detecting dark mode (system-level) + 'plopp', # Plotting library + 'jupyterlab', # Jupyter notebooks + 'pixi-kernel', # Pixi Jupyter kernel + 'ipykernel', # Jupyter kernel (required for running notebooks) + 'ipywidgets', # Widgets (needed for interactive matplotlib backends) + 'ipympl', # Matplotlib Jupyter widget backend (%matplotlib widget) + 'IPython', # Interactive Python shell + 'scipp<26.1.0', # TEMPORARY: ARM macOS fails with higher versions ] [project.optional-dependencies] @@ -70,7 +70,7 @@ dev = [ ] [project.urls] -Homepage = 'https://easyscience.github.io/dynamics' +Homepage = 'https://easyscience.github.io/dynamics-lib' Documentation = 'https://easyscience.github.io/dynamics-lib' 'Release Notes' = 'https://github.com/easyscience/dynamics-lib/releases' 'Source Code' = 'https://github.com/easyscience/dynamics-lib' diff --git a/src/easydynamics/experiment/experiment.py b/src/easydynamics/experiment/experiment.py index d0c6c912..5bd6728c 100644 --- a/src/easydynamics/experiment/experiment.py +++ b/src/easydynamics/experiment/experiment.py @@ -312,7 +312,7 @@ def plot_data(self, slicer=False, **kwargs) -> None: Args: slicer (bool): If True, use plopp's slicer instead of plot. - **kwargs: Additional keyword arguments to pass to plopp. + **kwargs (Any): Additional keyword arguments to pass to plopp. Raises: ValueError: If there is no data to plot. @@ -325,8 +325,6 @@ def plot_data(self, slicer=False, **kwargs) -> None: if not _in_notebook(): raise RuntimeError('plot_data() can only be used in a Jupyter notebook environment.') - from IPython.display import display - plot_kwargs_defaults = { 'title': self.display_name, } @@ -342,7 +340,7 @@ def plot_data(self, slicer=False, **kwargs) -> None: self._binned_data.transpose(dims=['energy', 'Q']), **plot_kwargs_defaults, ) - display(fig) + return fig ########### # private methods diff --git a/tests/unit/easydynamics/experiment/test_experiment.py b/tests/unit/easydynamics/experiment/test_experiment.py index 0e895b97..6601c16c 100644 --- a/tests/unit/easydynamics/experiment/test_experiment.py +++ b/tests/unit/easydynamics/experiment/test_experiment.py @@ -286,20 +286,19 @@ def test_plot_data_success(self, experiment): with ( patch(f'{Experiment.__module__}._in_notebook', return_value=True), patch('plopp.plot') as mock_plot, - patch('IPython.display.display') as mock_display, ): mock_fig = MagicMock() mock_plot.return_value = mock_fig # THEN - experiment.plot_data() + result = experiment.plot_data() # EXPECT mock_plot.assert_called_once() args, kwargs = mock_plot.call_args assert sc.identical(args[0], experiment._data.transpose()) assert kwargs['title'] == f'{experiment.display_name}' - mock_display.assert_called_once_with(mock_fig) + assert result == mock_fig def test_plot_data_no_data_raises(self): "Test plotting data raises ValueError when no data is present" diff --git a/tools/add_spdx.py b/tools/add_spdx.py index 295a7e0d..28febde7 100644 --- a/tools/add_spdx.py +++ b/tools/add_spdx.py @@ -1,3 +1,5 @@ +# SPDX-FileCopyrightText: 2026 EasyScience contributors +# SPDX-License-Identifier: BSD-3-Clause """Add SPDX headers to Python files. - SPDX-FileCopyrightText with the license holder name and organization diff --git a/tools/check_spdx.py b/tools/check_spdx.py index 80555ab1..c8a4df21 100644 --- a/tools/check_spdx.py +++ b/tools/check_spdx.py @@ -1,3 +1,5 @@ +# SPDX-FileCopyrightText: 2026 EasyScience contributors +# SPDX-License-Identifier: BSD-3-Clause """Check SPDX headers in Python files.""" from __future__ import annotations diff --git a/tools/remove_spdx.py b/tools/remove_spdx.py index 50e547a7..f5d09da5 100644 --- a/tools/remove_spdx.py +++ b/tools/remove_spdx.py @@ -1,3 +1,5 @@ +# SPDX-FileCopyrightText: 2026 EasyScience contributors +# SPDX-License-Identifier: BSD-3-Clause """Remove SPDX headers from Python files.""" from __future__ import annotations diff --git a/tools/test_scripts.py b/tools/test_scripts.py index 2d347579..e24b28e2 100644 --- a/tools/test_scripts.py +++ b/tools/test_scripts.py @@ -1,3 +1,5 @@ +# SPDX-FileCopyrightText: 2026 EasyScience contributors +# SPDX-License-Identifier: BSD-3-Clause """Test runner for tutorial scripts in the 'tutorials' directory. This test discovers and executes all Python scripts located under the diff --git a/tools/update_github_labels.py b/tools/update_github_labels.py index 8ec8c2d7..84de575e 100644 --- a/tools/update_github_labels.py +++ b/tools/update_github_labels.py @@ -1,3 +1,5 @@ +# SPDX-FileCopyrightText: 2026 EasyScience contributors +# SPDX-License-Identifier: BSD-3-Clause """Set/update GitHub labels for current or specified easyscience repository. @@ -17,7 +19,7 @@ import argparse import json import shlex -import subprocess +import subprocess # noqa: S404 import sys from dataclasses import dataclass