Releases: rmnldwg/lydata
0.1.2
0.1.1
0.1.0
What's New
With this release, we make the switch from rapidly evolving 0.0.X
versions to something that changes a little more slowly. However, we still consider the library experimental and breaking changes may still occur frequently.
🚀 Features
- (utils) Add often needed
enhance
function to complete sub-/superlevel involvement and infer maximum likelihood status.
🐛 Bug Fixes
- Avoid
KeyError
ininfer_superlevels
⚙️ Miscellaneous Tasks
- Add link to release 0.0.4
Change
infer_su(b|per)levels
skips inferring involvement of sub-/super LNLs that are already present- (load) Rename
skip_disk
touse_github
- (query) Rename
in_
toisin
forC
object
0.0.4
What's New
🚀 Features
- [breaking] Make several helper functions private (e.g.,
_max_likelihood()
) - (utils) Add more shortname columns, like
surgery
for("patient", "#", "neck_dissection")
- (load) Allow search for datasets at different locations on disk
- (query) Add
C
object for easierQ
creation - (query) Add
in_
toC
object - (validate) Add
transform_to_lyprox
function
🐛 Bug Fixes
- (load) Resolve circular import of
_repo
📚 Documentation
- Add intersphinx mapping to pandera
- Expand module docstrings
- Update
README.md
with library examples
🧪 Testing
- Fix failure due to changing order of items in set
Change
- (validate) Add args to renamed validation
- Import useful stuff as top-level
- Make
main()
funcs private
Remove
- (load) [breaking]
load_dataset()
not needed, one can just usenext(load_datasets())
0.0.3
What's New
🚀 Features
- Add method to infer sublevel involvement #2
- Add method to infer superlevel involvement #2
- (load) Allow loading from different repository and/or reference (tag, commit, ...) #4
🐛 Bug Fixes
- Make
align_diagnoses()
safer - Make
combine()
method work as intended - (load) Year may be equal to current year, not only smaller
📚 Documentation
- Make accessor method docstring more detailed
- Mention panda's
update()
in methods
⚙️ Miscellaneous Tasks
- Add documentation link to metadata
- Add changelog
- Remove pyright setting (where from?)
- Ignore B028 ruff rule
0.0.2
Warning
This is still very much experimental. Anything might change at any time.
What's New
🚀 Features
- Add some basic logging
- Add
percent
andinvert
to portion
📚 Documentation
- Host documentation on https://lydata.readthedocs.io
- Ensure intersphinx links work
🧪 Testing
- Add doctest to
join_datasets()
Change
- Switch to pydantic for dataset definition
- Shorten accessor name to
ly
Refac
- Make load funcs/methods clean & consistent
2023 CLB Multisite v2
This updates the previously published dataset due to an error in the diagnostic_consensus
column. The data did no actually come with this information, but we assume the diagnosis based on imaging to be negative (i.e., healthy) when no neck dissection was performed. However, due to a bug, it was also set to "healthy", when the pathology after neck dissection reported a healthy LNL. This is obviously wrong and was corrected here.
The full diff can be found here. Note that this also includes many other changes to other datasets since the first release.
0.0.1
First Version 🥳
This marks the first (highly experimental) release of a little Python package for loading, accessing, querying, and validating the datasets in this repo.
If it turns out to be useful, I'll continue to develop this into a mature set of tools that could ultimately deduplicate a lot of code in the lyprox and lyscripts repos.
2021 USZ Oropharynx v2
With this release, we update the previous one about the same dataset.
Note that the data itself remains unchanged, but we spotted a bug in the figures.ipynb
that is supposed to reproduce the plots. That bug was fixed with this release.
full diff to previous release (also includes diff to meanwhile added 2021-clb-oropharynx dataset)
2021 USZ Oropharynx
This release contains the detailed patterns of lymphatic progression of 287 patients with squamous cell carcinomas (SCCs) in the oropharynx, treated at the University Hospital Zurich (USZ) between 2013 and 2019.
The archive 2021-usz-oropharynx.zip
contains
- a
README.md
that explains how the dataset was extracted and what it contains - the data itself as
data.csv
- a citation file
CITATION.cff
that can be used to cite his dataset (one may also cite our Data in Brief article). - a jupyter notebook
figures.ipynb
for rendering figures visualizing different aspects of the data - the folder
figures
containing the already rendered figures which we also used in our publication for Radiation & Oncology