WMD-group / SMACT

Python package to aid materials design and informatics
https://smact.readthedocs.io
MIT License
85 stars 21 forks source link

[WIP] Add option to use pre-supplied embeddings within SMACT for the dopant_prediction module #260

Closed AntObi closed 3 weeks ago

AntObi commented 3 weeks ago

Description

Type of change

How Has This Been Tested?

Test Configuration:

Reviewers

Checklist:

Summary by CodeRabbit

coderabbitai[bot] commented 3 weeks ago

[!WARNING]

Review failed

The pull request is closed.

Walkthrough

The Doper class in the smact library has been enhanced to include an embedding parameter and a use_probability flag, enabling more flexible and accurate dopant predictions. The get_dopants and to_table methods have been updated to reflect these changes, and a new method _calculate_species_sim_prob has been added. Additionally, the documentation configuration has been updated, and new tests have been introduced to ensure the reliability of the new features.

Changes

Files Change Summary
smact/dopant_prediction/doper.py Enhanced Doper class with embedding and use_probability parameters; updated methods accordingly
docs/conf.py Added "tabulate" module to the list of imported modules
smact/tests/test_doper.py Renamed test class, added file path handling, and introduced new test methods

Sequence Diagram(s) (Beta)

sequenceDiagram
    participant User
    participant Doper
    participant DataLoader
    participant SimilarityCalculator

    User->>Doper: Initialize with embedding and use_probability
    Doper->>DataLoader: Load embedding data
    Doper->>SimilarityCalculator: Calculate species similarity/probability
    User->>Doper: Call get_dopants
    Doper->>Doper: Check use_probability flag
    Doper->>SimilarityCalculator: Get similarity/probability scores
    Doper->>User: Return dopant predictions

Poem

In the land of code, where data's delight,
A rabbit hops with changes bright. 🐇
Embeddings and probabilities now in play,
Dopants predicted in a smarter way.
Tests and docs join the dance,
Ensuring all works at first glance.
Cheers to progress, in code we trust,
For in every byte, precision's a must!


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AntObi commented 3 weeks ago

@coderabbitai review

coderabbitai[bot] commented 3 weeks ago
Actions performed Review triggered. > Note: CodeRabbit is an incremental review system and does not re-review already reviewed commits. This command is applicable only when automatic reviews are paused.
codecov[bot] commented 3 weeks ago

Codecov Report

Attention: Patch coverage is 82.22222% with 8 lines in your changes missing coverage. Please review.

Project coverage is 74.18%. Comparing base (579e67c) to head (51bd29c).

:exclamation: Current head 51bd29c differs from pull request most recent head e58ef9b

Please upload reports for the commit e58ef9b to get more accurate results.

Files Patch % Lines
smact/dopant_prediction/doper.py 75.00% 7 Missing :warning:
smact/tests/test_doper.py 94.11% 1 Missing :warning:
Additional details and impacted files ```diff @@ Coverage Diff @@ ## develop #260 +/- ## =========================================== + Coverage 73.82% 74.18% +0.35% =========================================== Files 24 24 Lines 2048 2080 +32 =========================================== + Hits 1512 1543 +31 - Misses 536 537 +1 ```

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.

AntObi commented 3 weeks ago

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coderabbitai[bot] commented 3 weeks ago
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AntObi commented 3 weeks ago

@coderabbitai review

coderabbitai[bot] commented 3 weeks ago
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