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Lucas Camillo
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Lucas Camillo
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Dec 12, 2023
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,152 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 4, | ||
| "id": "fb157849-5454-4a60-8548-fff633fff764", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import torch\n", | ||
| "import pandas as pd\n", | ||
| "import pyaging as pya\n", | ||
| "import os" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "49adac4a-82e5-4fae-a0e0-26dcce5661bf", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "os.system(\"curl -o coefficients.xlsx https://elifesciences.org/download/aHR0cHM6Ly9jZG4uZWxpZmVzY2llbmNlcy5vcmcvYXJ0aWNsZXMvNDA2NzUvZWxpZmUtNDA2NzUtc3VwcDMtdjIueGxzeA--/elife-40675-supp3-v2.xlsx?_hash=qzOMc4yUFACfDFG%2FlgxkFTHWt%2BSXSmP9zz1BM3oOTRM%3D\")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 8, | ||
| "id": "b9f484b1-f501-41b7-9565-82e03bfe97dc", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "df = pd.read_excel('coefficients.xlsx', sheet_name='Blood', nrows=90)\n", | ||
| "\n", | ||
| "intercept = 0.0\n", | ||
| "\n", | ||
| "df['feature'] = df['Chromosome'].astype(str) + ':' + df['Position'].astype(int).astype(str)\n", | ||
| "df['coefficient'] = df['Weight']" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 9, | ||
| "id": "a284fe99-dc47-4f0c-b2ff-274e136e7020", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "features = df['feature'].tolist()\n", | ||
| "\n", | ||
| "weights = torch.tensor(df['coefficient'].tolist()).unsqueeze(0)\n", | ||
| "intercept = torch.tensor([intercept])" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 10, | ||
| "id": "7b4c3f6b-72af-4e99-84c4-65b8ef58c91d", | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "data": { | ||
| "text/plain": [ | ||
| "LinearModel(\n", | ||
| " (linear): Linear(in_features=90, out_features=1, bias=True)\n", | ||
| ")" | ||
| ] | ||
| }, | ||
| "execution_count": 10, | ||
| "metadata": {}, | ||
| "output_type": "execute_result" | ||
| } | ||
| ], | ||
| "source": [ | ||
| "model = pya.models.LinearModel(len(features))\n", | ||
| "\n", | ||
| "model.linear.weight.data = weights\n", | ||
| "model.linear.bias.data = intercept\n", | ||
| "\n", | ||
| "model" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 40, | ||
| "id": "e32706f0-ce07-455e-bb17-1993c1c0e152", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "weights_dict = {\n", | ||
| " 'preprocessing': None, \n", | ||
| " 'preprocessing_helper': None,\n", | ||
| " 'postprocessing': \"petkovichblood\",\n", | ||
| " 'postprocessing_helper': None,\n", | ||
| " 'features': features,\n", | ||
| " 'weight_dict': model.state_dict(),\n", | ||
| "}\n", | ||
| "\n", | ||
| "metadata_dict = {\n", | ||
| " 'species': 'Mus musculus',\n", | ||
| " 'data_type': 'methylation',\n", | ||
| " 'year': 2017,\n", | ||
| " 'implementation_approved_by_author(s)': '⌛',\n", | ||
| " 'preprocessing': weights_dict['preprocessing'], \n", | ||
| " 'postprocessing': weights_dict['postprocessing'], \n", | ||
| " 'citation': \"Petkovich, Daniel A., et al. \\\"Using DNA methylation profiling to evaluate biological age and longevity interventions.\\\" Cell metabolism 25.4 (2017): 954-960.\",\n", | ||
| " 'doi': \"https://doi.org/10.1016/j.cmet.2017.03.016\",\n", | ||
| " \"notes\": None,\n", | ||
| "}" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 41, | ||
| "id": "34136f3c-92b8-4641-a103-381d3a7dd857", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "torch.save(weights_dict, '../weights/petkovichblood.pt')\n", | ||
| "torch.save(metadata_dict, '../metadata/petkovichblood.pt')" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "83334bff-17c3-447c-9e37-fcb68edef5df", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "Python 3", | ||
| "language": "python", | ||
| "name": "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": "3.9.17" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 5 | ||
| } |
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