IUCr CPD Quantitative Phase Analysis Dataset

This repository contains the dataset assembled by the International Union of Crystallography (IUCr) in the late 1990s to research the use of powder X-ray diffraction (PXRD) data for quantitative phase analysis.

1. Overview

This repository contains the dataset assembled by the International Union of Crystallography (IUCr) by the Commission on Powder Diffraction (CPD) for the Round Robin on Quantitative Phase Analysis. The original dataset and details about the CPD project are available directly from the project website (which is no longer actively maintained):

https://www.iucr.org/resources/commissions/powder-diffraction/projects/qarr

1.1. Dataset Contents

├── README.md            <- this file
├── RELEASE-NOTES.md     <- dataset release notes
├── DATASET-LICENSE      <- license for data components of the dataset
├── DATASET-NOTICE       <- copyright notices for third-party data included in
│                           the dataset
├── SOFTWARE-LICENSE     <- license for software components of the dataset
├── SOFTWARE-NOTICE      <- copyright notice for the software components of the
│                           dataset
├── Makefile             <- Makefile containing useful shortcuts (`make` rules).
│                           Use `make help` to show the list of available rules.
├── pyproject.toml       <- Python project metadata file
├── poetry.lock          <- Poetry lockfile
├── bin/                 <- scripts and programs for managing the dataset
├── data/                <- directory containing data for dataset
│   ├── mixtures/        <- PXRD data for mixtures
│   ├── pure-compounds/  <- PXRD data for pure compounds
│   └── VERSION          <- version of the latest official release of the dataset
├── docs/                <- dataset documentation
└── extras/              <- additional files and references that may be useful
                            for dataset maintenance

1.2. Data Format

Data files with the prn extension contain diffractogram data stored in column format (without headers): 2-theta, counts.
The pure-compounds/structures.txt file contains structure information for pure compounds (except for the pharmaceutical compounds pharm1gr and pharm2gr).
The mixtures/compositions.txt file contains weight percentages for the samples associated with the diffractograms in the mixtures directory.

1.3. License

The data contained in this dataset is covered under the Creative Commons Attribution 4.0 International Public License (included in the DATASET-LICENSE file). Licenses for third-party data included with this dataset are contained in the DATASET-NOTICE file.

The software contained in this repository is covered under the Apache License 2.0 (included in the SOFTWARE-LICENSE file). The copyright for the software is contained in the SOFTWARE-NOTICE file.

1.4. Known Issues

Structure information is unavailable for the pharmaceutical compounds (i.e., PXRD data files pharm1gr.prn and pharm2gr.prn).

2. Using the Dataset

The instructions provided below require DVC and FastDS to be installed.

2.1. Importing the Dataset

To use the dataset a "read-only" manner (i.e., without maintenance code), import the dataset after initializing DVC in the working directory.

Initialize DVC.
```
$ cd /PATH/TO/PROJECT
$ fds init
$ fds commit "Initialize DVC"
```
In the example commands above, /PATH/TO/PROJECT should be replaced by the path to the directory that where the dataset will be used.

Recommended. Enable auto staging for DVC-managed data.

$ dvc config core.autostage true
$ fds commit "Enable DVC auto staging"

Import the dataset.
```
$ dvc import https://github.com/velexi-research/IUCr-CPD-Quantitative-Phase-Analysis-Dataset.git data -o LOCAL_PATH
$ fds commit "Import 'IUCr CPD Quantitative Phase Analysis Dataset'"
```
In the example command above, the following substitutions should be made:
- LOCAL_PATH should be replaced by the local path relative to /PATH/TO/PROJECT where the dataset should be placed. Note: the parent directory of LOCAL_PATH should be created before running dvc import.
- DATASET_NAME should be replaced by the name of the imported dataset.
For example, if the dataset repository is located at

https://github.com/account/cool-dataset

and we would like to to place the dataset into a directory named data/cool-dataset, we would use the following command:
```
$ mkdir data
$ dvc import https://github.com/account/cool-dataset data -o data/cool-dataset
$ fds commit "Import cool-dataset"
```

2.2. Updating the Dataset

If a previously imported dataset has been updated, the local copy of the dataset can be updated (to the latest version on the default branch of the dataset Git repository) by using the dvc update command.

$ dvc update DATASET.dvc
$ fds commit "Update 'IUCr CPD Quantitative Phase Analysis Dataset'"

or

$ dvc update DATASET
$ fds commit "Update 'IUCr CPD Quantitative Phase Analysis Dataset'"

In the example commands above, the following substitutions should be made:

DATASET.dvc should be replaced by the .dvc file that was generated when the dataset was imported (or, equivalently, DATASET should be replaced by name of the directory that the dataset was imported into).

To specify the particular revision of the dataset to retreive, use the --rev REVISION option, where REVISION is a Git tag, branch, or commit SHA/hash.

$ dvc update DATASET.dvc --rev REVISION
$ fds commit "Update 'IUCr CPD Quantitative Phase Analysis Dataset'"

3. Maintaining the Dataset

3.1. Managing Data

3.1.1. Adding Data

Add the data files to the data directory.
Add the contents of data to the data tracked by DVC.
```
$ fds add data
```
Commit the dataset changes to the local Git repository.
```
$ fds commit "Add initial version of data"
```
Push the dataset changes to the remote Git repository and DVC remote storage.
```
$ fds push
```

3.1.2. Updating Data

Update the data files in the data directory.
Update the data tracked by DVC with the new content of the data directory.
```
$ fds add data
```
Commit the dataset changes to the local Git repository.
```
$ fds commit "Update dataset"
```
Push the dataset changes to the remote Git repository and DVC remote storage.
```
$ fds push
```

3.1.3. Removing Data

Remove the data files from the data directory.
Update the data tracked by DVC with the new content of the data directory.
```
$ fds add data
```
Commit the dataset changes to the local Git repository.
```
$ fds commit "Update dataset"
```
Push the dataset changes to the remote Git repository and DVC remote storage.
```
$ fds push
```

3.2. Releasing an Official Dataset Version

Make sure that the dataset has been updated (Section 3.1.2)
Update the README.md file.
Increment the version number in pyproject.toml.

Update data/VERSION.

$ cd data
$ poetry version -s > VERSION

Recommended. Update the release notes for the dataset to include any major changes from the previous released version of the dataset.

Create a tag for the release in git.

$ git tag `poetry version -s`
$ git push --tags

Optional. If the Git repository for the dataset is hosted on GitHub (or analogous service), create a release associated with the git tag created in Step #4.

3.3. Dataset Conventions

Data

data directory. All data files that should be imported when using the dvc import URL data -o LOCAL_PATH command should be placed in the data directory.
- Depending on the nature of the dataset, it may be useful to organize the data files into sub-directories (e.g., by type of data).
data/VERSION file. The data/VERSION file contains the version number of the latest official release of the dataset. It is generated automatically and should not be manually edited.

Documentation

README.md file. The README.md file should contain
- a high-level description of the dataset and
- instructions for software tools used to create and maintain the dataset.
docs directory. The docs directory should be used for detailed documentation for the dataset (i.e., data and supporting software tools).

Supporting Software Tools

bin directory. The bin directory should be used for supporting software tools (e.g., data capture and processing scripts) developed to help maintain the dataset.
pyproject.toml file. Python dependencies for supporting tools should be maintained in the pyproject.toml file. Most of the time, poetry utility will appropriately update pyproject.toml as dependencies are added or removed.
extras directory. The extras directory should be used for ancillary files (e.g., direnv configuration template, general reference documents for tools that are not dataset-specific).

4. References

Software Tools

DVC Documentation
FastDS
FastDS Quick Reference
Poetry Quick Reference

IUCr References

IUCr CPD Round Robin on Quantitative Phase Analysis: Standard Powder X-ray Diffraction Data Sets - Data Analysis Kit
IUCr CPD Round Robin on Quantitative Phase Analysis: Weighed and Measured Values of Distributed Samples and Data

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README.md

README.md

IUCr CPD Quantitative Phase Analysis Dataset

Contents

1. Overview

1.1. Dataset Contents

1.2. Data Format

1.3. License

1.4. Known Issues

2. Using the Dataset

2.1. Importing the Dataset

2.2. Updating the Dataset

3. Maintaining the Dataset

3.1. Managing Data

3.1.1. Adding Data

3.1.2. Updating Data

3.1.3. Removing Data

3.2. Releasing an Official Dataset Version

3.3. Dataset Conventions

Data

Documentation

Supporting Software Tools

4. References

Software Tools

IUCr References

Files

README.md

Latest commit

History

README.md

File metadata and controls

IUCr CPD Quantitative Phase Analysis Dataset

Contents

1. Overview

1.1. Dataset Contents

1.2. Data Format

1.3. License

1.4. Known Issues

2. Using the Dataset

2.1. Importing the Dataset

2.2. Updating the Dataset

3. Maintaining the Dataset

3.1. Managing Data

3.1.1. Adding Data

3.1.2. Updating Data

3.1.3. Removing Data

3.2. Releasing an Official Dataset Version

3.3. Dataset Conventions

Data

Documentation

Supporting Software Tools

4. References

Software Tools

IUCr References