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Merge pull request #491 from DataverseLabs/main
Update dev to be in the same state as main before the new release
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.github/workflows/python-install-and-test-on-linux-always.yml

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jobs:
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build:
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permissions: read-all
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runs-on: ubuntu-latest
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coverage run -m pytest -v -s
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- name: Generate Coverage Report
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run: |
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coverage report -m
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coverage report -m
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name: Build tests coverage badge
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on:
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push:
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branches:
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- main
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- dev
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jobs:
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build:
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permissions:
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actions: read
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attestations: read
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checks: read
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contents: write
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deployments: read
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id-token: none
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issues: none
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discussions: none
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packages: read
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pages: read
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pull-requests: write
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security-events: read
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statuses: read
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runs-on: ubuntu-latest
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strategy:
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fail-fast: false
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matrix:
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python-version: ["3.12"]
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steps:
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- uses: actions/checkout@v4
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v4
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with:
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python-version: ${{ matrix.python-version }}
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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pip install .
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pip install --group dev
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- name: Test with pytest
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run: |
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coverage run -m pytest -v -s
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- name: Generate Coverage Report
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run: |
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coverage report -m
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- name: Coverage Badge
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uses: tj-actions/coverage-badge-py@1788babcb24544eb5bbb6e0d374df5d1e54e670f # v2
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- name: Verify Changed files
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uses: tj-actions/verify-changed-files@a1c6acee9df209257a246f2cc6ae8cb6581c1edf # v20
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id: verify-changed-files
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with:
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files: coverage.svg
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- name: Commit files
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if: steps.verify-changed-files.outputs.files_changed == 'true'
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run: |
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git config --local user.email "github-actions[bot]@users.noreply.github.com"
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git config --local user.name "github-actions[bot]"
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git add coverage.svg
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git commit -m "Updated coverage.svg"
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- name: Push changes
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if: steps.verify-changed-files.outputs.files_changed == 'true'
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uses: ad-m/github-push-action@master
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with:
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github_token: ${{ secrets.github_token }}
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branch: ${{ github.ref }}

README.md

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![status](https://joss.theoj.org/papers/3f87f562264c4e5174d9e6ed6d8812aa/status.svg) ![License](https://img.shields.io/github/license/szymon-datalions/pyinterpolate) ![Documentation Status](https://readthedocs.org/projects/pyinterpolate/badge/?version=latest) [![CodeFactor](https://www.codefactor.io/repository/github/dataverselabs/pyinterpolate/badge)](https://www.codefactor.io/repository/github/dataverselabs/pyinterpolate)
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![JOSS](https://joss.theoj.org/papers/3f87f562264c4e5174d9e6ed6d8812aa/status.svg) [![License](https://img.shields.io/badge/License-BSD_2--Clause-orange.svg)](https://opensource.org/licenses/BSD-2-Clause) ![Documentation Status](https://readthedocs.org/projects/pyinterpolate/badge/?version=latest) [![CodeFactor](https://www.codefactor.io/repository/github/dataverselabs/pyinterpolate/badge)](https://www.codefactor.io/repository/github/dataverselabs/pyinterpolate)
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[![Run Unit Test via Pytest](https://github.com/DataverseLabs/pyinterpolate/actions/workflows/python-install-and-test-on-linux-always.yml/badge.svg)](https://github.com/DataverseLabs/pyinterpolate/actions/workflows/python-install-and-test-on-linux-always.yml) [![CodeQL](https://github.com/DataverseLabs/pyinterpolate/actions/workflows/github-code-scanning/codeql/badge.svg)](https://github.com/DataverseLabs/pyinterpolate/actions/workflows/github-code-scanning/codeql) ![Tests Coverage](https://github.com/DataverseLabs/pyinterpolate/blob/main/coverage.svg)
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# Pyinterpolate
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All tests are grouped in the `test` directory. If you would like to contribute, then you won't avoid testing, but it is described step-by-step here: [CONTRIBUTION.md](https://github.com/DataverseLabs/pyinterpolate/blob/main/CONTRIBUTION.md)
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## Commercial and scientific projects where library has been used
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* Tick-Borne Disease Detector (Data Lions company) for the European Space Agency (2019-2020).
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* B2C project related to the prediction of demand for specific flu medications (2020).
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* B2G project related to the large-scale infrastructure maintenance (2020-2021).
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* E-commerce service for reporting and analysis, building spatial / temporal profiles of customers (2022+).
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* The external data augmentation for e-commerce services (2022+).
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* Regional aggregates transformation and preprocessing for location intelligence tasks (2025+).
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## Community
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Join our community in Discord: [Discord Server Pyinterpolate](https://discord.gg/3EMuRkj)
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## Use cases
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* [Lyme Disease Risk Assessment Based on the Earth Observation Data and Spatial Processing Technique. ESA Φ-week 2021](https://phiweek.esa.int/detailed-programme)
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* [Disaggregation of socio-economic data](https://ml-gis-service.com/index.php/2022/12/09/get-more-from-crime-rate-data-and-other-socio-economic-indicators-with-pyinterpolate/)
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* [Interpolation of air pollution](https://ml-gis-service.com/index.php/2021/10/31/data-science-interpolate-air-quality-measurements-with-python/)
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* [Educational - Spatial Data Science for Social Geography Course - Interpolation](https://github.com/martinfleis/sds?tab=readme-ov-file#spatial-data-science-for-social-geography)
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## Bibliography
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- Goovaerts P., Kriging and Semivariogram Deconvolution in the Presence of Irregular Geographical Units, Mathematical Geology 40(1), 101-128, 2008
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- Deutsch C.V., Correcting for Negative Weights in Ordinary Kriging, Computers & Geosciences Vol.22, No.7, pp. 765-773, 1996
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## Community
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Join our community in Discord: [Discord Server Pyinterpolate](https://discord.gg/3EMuRkj)
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## How to cite
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coverage.svg

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Use Cases
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=========
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* Tick-Borne Disease Detector for the European Space Agency (2019-2020).
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* B2C project related to the prediction of demand for specific flu medications (2020).
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* B2G project related to the large-scale infrastructure maintenance (2020-2021).
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* E-commerce service for reporting and analysis, building spatial / temporal profiles of customers (2022+).
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* The external data augmentation for e-commerce services (2022+).
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* As a module for the hotel price optimization system (2023+).
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* `Lyme Disease Risk Assessment Based on the Earth Observation Data and Spatial Processing Technique. ESA Φ-week 2021 <https://phiweek.esa.int/detailed-programme>`_
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* `Disaggregation of socio-economic data <https://ml-gis-service.com/index.php/2022/12/09/get-more-from-crime-rate-data-and-other-socio-economic-indicators-with-pyinterpolate/>`_
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* `Interpolation of air pollution <https://ml-gis-service.com/index.php/2021/10/31/data-science-interpolate-air-quality-measurements-with-python/>`_
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* `Educational - Spatial Data Science for Social Geography Course - Interpolation <https://github.com/martinfleis/sds?tab=readme-ov-file#spatial-data-science-for-social-geography>`_

docs/build/html/community/community/use_cases.html

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<section id="use-cases">
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<h1>Use Cases<a class="headerlink" href="#use-cases" title="Link to this heading">#</a></h1>
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<ul class="simple">
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<li><p>Tick-Borne Disease Detector for the European Space Agency (2019-2020).</p></li>
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<li><p>B2C project related to the prediction of demand for specific flu medications (2020).</p></li>
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<li><p>B2G project related to the large-scale infrastructure maintenance (2020-2021).</p></li>
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<li><p>E-commerce service for reporting and analysis, building spatial / temporal profiles of customers (2022+).</p></li>
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<li><p>The external data augmentation for e-commerce services (2022+).</p></li>
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<li><p>As a module for the hotel price optimization system (2023+).</p></li>
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<li><p><a class="reference external" href="https://phiweek.esa.int/detailed-programme">Lyme Disease Risk Assessment Based on the Earth Observation Data and Spatial Processing Technique. ESA Φ-week 2021</a></p></li>
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<li><p><a class="reference external" href="https://ml-gis-service.com/index.php/2022/12/09/get-more-from-crime-rate-data-and-other-socio-economic-indicators-with-pyinterpolate/">Disaggregation of socio-economic data</a></p></li>
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<li><p><a class="reference external" href="https://ml-gis-service.com/index.php/2021/10/31/data-science-interpolate-air-quality-measurements-with-python/">Interpolation of air pollution</a></p></li>
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<li><p><a class="reference external" href="https://github.com/martinfleis/sds?tab=readme-ov-file#spatial-data-science-for-social-geography">Educational - Spatial Data Science for Social Geography Course - Interpolation</a></p></li>
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</ul>
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</section>
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Use Cases
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=========
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* Tick-Borne Disease Detector for the European Space Agency (2019-2020).
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* B2C project related to the prediction of demand for specific flu medications (2020).
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* B2G project related to the large-scale infrastructure maintenance (2020-2021).
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* E-commerce service for reporting and analysis, building spatial / temporal profiles of customers (2022+).
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* The external data augmentation for e-commerce services (2022+).
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* As a module for the hotel price optimization system (2023+).
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* `Lyme Disease Risk Assessment Based on the Earth Observation Data and Spatial Processing Technique. ESA Φ-week 2021 <https://phiweek.esa.int/detailed-programme>`_
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* `Disaggregation of socio-economic data <https://ml-gis-service.com/index.php/2022/12/09/get-more-from-crime-rate-data-and-other-socio-economic-indicators-with-pyinterpolate/>`_
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* `Interpolation of air pollution <https://ml-gis-service.com/index.php/2021/10/31/data-science-interpolate-air-quality-measurements-with-python/>`_
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* `Educational - Spatial Data Science for Social Geography Course - Interpolation <https://github.com/martinfleis/sds?tab=readme-ov-file#spatial-data-science-for-social-geography>`_

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