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CITATION.cff

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- neural processes
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- active learning
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license: MIT
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version: 0.3.6
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date-released: '2024-02-02'
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version: 0.3.7
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date-released: '2024-07-14'

README.md

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[![release](https://img.shields.io/badge/release-v0.3.6-green?logo=github)](https://github.com/alan-turing-institute/deepsensor/releases)
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[![release](https://img.shields.io/badge/release-v0.3.7-green?logo=github)](https://github.com/alan-turing-institute/deepsensor/releases)
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[![Latest Docs](https://img.shields.io/badge/docs-latest-blue.svg)](https://alan-turing-institute.github.io/deepsensor/)
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![Tests](https://github.com/alan-turing-institute/deepsensor/actions/workflows/tests.yml/badge.svg)
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[![Coverage Status](https://coveralls.io/repos/github/alan-turing-institute/deepsensor/badge.svg?branch=main)](https://coveralls.io/github/alan-turing-institute/deepsensor?branch=main)
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# Set up task loader
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task_loader = TaskLoader(context=ds, target=ds)
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# Set up model
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# Set up ConvNP, which by default instantiates a ConvCNP with Gaussian marginals
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model = ConvNP(data_processor, task_loader)
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# Generate training tasks with up 100 grid cells as context and all grid cells

setup.cfg

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[metadata]
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name = deepsensor
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version = 0.3.6
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version = 0.3.7
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author = Tom R. Andersson
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author_email = [email protected]
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description = A Python package for modelling xarray and pandas data with neural processes.

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