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69 lines (63 loc) · 1.95 KB
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[project]
name = "ps-predictions"
version = "0.1.0"
description = "Code used in my PhD to train model for PS prediction, generate predictions, and analyse data for papers."
authors = [{name = "Dominika Malinowska"}]
license = {text = "MIT"}
readme = "README.md"
requires-python = ">=3.10,<3.11"
dependencies = [
"cartopy==0.22.0",
"geocube==0.4.2",
"geopandas>=0.14",
"kornia==0.7.1",
"lightning==2.2.0.post0",
"matplotlib==3.8.2",
"numpy==1.26.3",
"osmium==3.7.0",
"osmnx==1.9.1",
"pandas==2.2.0",
"pillow==10.2.0",
"pyproj==3.6.1",
"rasterio==1.3.9",
"rasterstats==0.19.0",
"scikit-learn==1.5.0",
"seaborn==0.11",
"segmentation-models-pytorch==0.3.3",
"setuptools==68.2.2",
"statsmodels==0.14.2",
"timm==0.9.2",
"torchgeo==0.5.2",
"torch @ https://download.pytorch.org/whl/cu121/torch-2.3.1%2Bcu121-cp310-cp310-linux_x86_64.whl",
"torchvision @ https://download.pytorch.org/whl/cu121/torchvision-0.18.1%2Bcu121-cp310-cp310-linux_x86_64.whl",
"torchmetrics==1.4.1",
"utm==0.7.0",
"shapely>=2.0.5,<3.0.0",
"pygeos>=0.14,<0.15",
"openpyxl>=3.1.5,<4.0.0",
"factor-analyzer>=0.5.1,<0.6.0",
"jupytext>=1.16.4,<2.0.0",
"rpy2>=3.5.17,<4.0.0",
"pingouin>=0.5.5,<0.6.0",
"ipywidgets>=8.1.7,<9.0.0",
"ptitprince>=0.2.7,<0.3.0",
"zenodo-get>=2.0.0,<3.0.0",
"ipykernel>=6.31.0",
"fiona>=1.9.4",
]
[project.optional-dependencies]
dev = [
"ipykernel>=6.29.5,<7.0.0",
]
[tool.uv]
package = true
[tool.uv.sources]
torch = { url = "https://download.pytorch.org/whl/cu121/torch-2.3.1%2Bcu121-cp310-cp310-linux_x86_64.whl" }
torchvision = { url = "https://download.pytorch.org/whl/cu121/torchvision-0.18.1%2Bcu121-cp310-cp310-linux_x86_64.whl" }
[tool.hatch.metadata]
allow-direct-references = true
[tool.hatch.build.targets.wheel]
packages = ["src/ps_predictions", "src/utils"]
[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"