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Xenonpy embeddings #141

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merged 10 commits into from
Jun 3, 2024
Merged

Xenonpy embeddings #141

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5af8e0f
Add xenonpy descriptors
AntObi May 30, 2024
dd01d9f
Add description of xenonpy descriptors to README.md
AntObi May 30, 2024
7f74d11
Add xenonpy and crystallm to docstring in core.py
AntObi May 30, 2024
ea58e83
Add xenonpy citation
AntObi May 30, 2024
cfa197a
Update composition.ipynb
AntObi May 30, 2024
98bfcce
Update baseline images
AntObi May 30, 2024
636e33c
Disable skipspecies plot tests mpl
AntObi May 30, 2024
d4b416d
Run pre-commit
AntObi May 30, 2024
6f8e755
Add publications and links for XenonPy
AntObi Jun 3, 2024
f5a0be9
Add typing-extensions to setup.py requirements
AntObi Jun 3, 2024
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93 changes: 83 additions & 10 deletions examples/composition.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,12 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"ExecuteTime": {
"end_time": "2024-04-10T13:43:50.159344600Z",
"start_time": "2024-04-10T13:43:19.758896800Z"
}
},
"outputs": [],
"source": [
"import pandas as pd\n",
Expand Down Expand Up @@ -31,7 +36,12 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"ExecuteTime": {
"end_time": "2024-04-10T13:43:50.215488400Z",
"start_time": "2024-04-10T13:43:50.156342800Z"
}
},
"outputs": [],
"source": [
"CsPbI3_magpie = CompositionalEmbedding(formula=\"CsPbI3\", embedding=\"magpie\")"
Expand All @@ -51,7 +61,12 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"ExecuteTime": {
"end_time": "2024-04-10T13:43:50.296525Z",
"start_time": "2024-04-10T13:43:50.202493200Z"
}
},
"outputs": [],
"source": [
"# Print the individual element feature vectors\n",
Expand All @@ -69,7 +84,12 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"ExecuteTime": {
"end_time": "2024-04-10T13:43:50.299527900Z",
"start_time": "2024-04-10T13:43:50.231493Z"
}
},
"outputs": [],
"source": [
"# Print the composition and the fractional composition\n",
Expand All @@ -88,7 +108,12 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"ExecuteTime": {
"end_time": "2024-04-10T13:43:50.318038500Z",
"start_time": "2024-04-10T13:43:50.248490700Z"
}
},
"outputs": [],
"source": [
"# Print the list of elements\n",
Expand Down Expand Up @@ -134,17 +159,42 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"ExecuteTime": {
"end_time": "2024-04-10T13:43:50.321038700Z",
"start_time": "2024-04-10T13:43:50.259499Z"
}
},
"outputs": [],
"source": [
"# Print the mean feature vector\n",
"print(CsPbI3_magpie.feature_vector(stats=\"mean\"))"
]
},
{
"cell_type": "code",
"outputs": [],
"source": [
"print(CompositionalEmbedding(formula=\"NaCl\", embedding=\"magpie\").feature_vector())"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2024-04-10T14:00:36.864604100Z",
"start_time": "2024-04-10T14:00:36.792600400Z"
}
},
"execution_count": null
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"ExecuteTime": {
"end_time": "2024-04-10T13:43:50.484568800Z",
"start_time": "2024-04-10T13:43:50.273490Z"
}
},
"outputs": [],
"source": [
"# Print the feature vector for the mean, variance, minpool, maxpool, and sum\n",
Expand All @@ -171,7 +221,12 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"ExecuteTime": {
"end_time": "2024-04-10T13:43:50.511108300Z",
"start_time": "2024-04-10T13:43:50.292507700Z"
}
},
"outputs": [],
"source": [
"formulas = [\"CsPbI3\", \"Fe2O3\", \"NaCl\"]\n",
Expand All @@ -182,7 +237,12 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"ExecuteTime": {
"end_time": "2024-04-10T13:43:50.640635200Z",
"start_time": "2024-04-10T13:43:50.336039400Z"
}
},
"outputs": [],
"source": [
"df = pd.DataFrame({\"formula\": formulas})\n",
Expand All @@ -196,10 +256,23 @@
"We can also calculate the \"distance\" between two compositions using their feature vectors. This can be used to determine which compositions are more similar to each other."
]
},
{
"cell_type": "code",
"outputs": [],
"source": [],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"ExecuteTime": {
"end_time": "2024-04-10T13:43:50.642632100Z",
"start_time": "2024-04-10T13:43:50.429571500Z"
}
},
"outputs": [],
"source": [
"print(\n",
Expand Down
2 changes: 2 additions & 0 deletions src/elementembeddings/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -58,6 +58,8 @@ def load_data(embedding_name: Optional[str] = None):
| Random (200 dimensions) | random_200 |
| SkipAtom | skipatom |
| Atomic Number | atomic |
| Crystallm | crystallm |
| XenonPy | xenonpy |


Args:
Expand Down
4 changes: 4 additions & 0 deletions src/elementembeddings/data/element_representations/README.md
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Expand Up @@ -164,3 +164,7 @@ The following paper describes the details:
### CrystaLLM

The following paper describes the details behind the crystal structure generation model which uses large language modelling: [Crystal Structure Generation with Autoregressive Large Language Modeling](https://arxiv.org/abs/2307.04340)

### XenonPy

The XenonPy embedding uses the 58 features which are commonly used in publications that use the [XenonPy package](.
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Add a complete URL for the XenonPy package to enhance the documentation.

- The XenonPy embedding uses the 58 features which are commonly used in publications that use the [XenonPy package](.
+ The XenonPy embedding uses the 58 features which are commonly used in publications that use the [XenonPy package](https://example.com/xenonpy).
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Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation.

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### XenonPy
The XenonPy embedding uses the 58 features which are commonly used in publications that use the [XenonPy package](.
### XenonPy
The XenonPy embedding uses the 58 features which are commonly used in publications that use the [XenonPy package](https://example.com/xenonpy).

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Ensure the file ends with a newline character for consistency and to adhere to POSIX standards.

+
Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation.

Suggested change
The XenonPy embedding uses the 58 features which are commonly used in publications that use the [XenonPy package](.
The XenonPy embedding uses the 58 features which are commonly used in publications that use the [XenonPy package](.

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