{"id":25817313,"url":"https://github.com/landscapegeoinformatics/mcarto2023","last_synced_at":"2025-02-28T06:34:03.230Z","repository":{"id":242924961,"uuid":"622857898","full_name":"LandscapeGeoinformatics/mcarto2023","owner":"LandscapeGeoinformatics","description":"Materials for the Python lab session in the Mathematical Cartography course","archived":false,"fork":false,"pushed_at":"2023-04-04T19:16:03.000Z","size":4955,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2024-06-05T19:27:55.989Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/LandscapeGeoinformatics.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-04-03T07:54:47.000Z","updated_at":"2024-06-05T19:27:59.272Z","dependencies_parsed_at":"2024-06-12T00:30:35.595Z","dependency_job_id":null,"html_url":"https://github.com/LandscapeGeoinformatics/mcarto2023","commit_stats":null,"previous_names":["landscapegeoinformatics/mcarto2023"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LandscapeGeoinformatics%2Fmcarto2023","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LandscapeGeoinformatics%2Fmcarto2023/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LandscapeGeoinformatics%2Fmcarto2023/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LandscapeGeoinformatics%2Fmcarto2023/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/LandscapeGeoinformatics","download_url":"https://codeload.github.com/LandscapeGeoinformatics/mcarto2023/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241112451,"owners_count":19911690,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-02-28T06:34:02.610Z","updated_at":"2025-02-28T06:34:03.215Z","avatar_url":"https://github.com/LandscapeGeoinformatics.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Matemaatiline kartograafia 2023\nAntud juhendid toetavad geograafia eriala magistriõppe kursust \u003cb\u003eMatemaatiline kartograafia LOOM.02.007\u003c/b\u003e ja keskenduvad Pythoni matemaatilise kartograafia ja visualiseerimise teegi [Cartopy](https://scitools.org.uk/cartopy/docs/latest/) võimalustele.\n\nEsimene juhend annab ülevaate kaardiakna loomisest, erinevate projektsioonide kasutamisest ja lihtsamate kaardielementide (kaardivõrk, tekst) konstrueerimisest:\n* https://github.com/LandscapeGeoinformatics/mcarto2023/blob/main/Kaardiakna_juhtimine.ipynb\n\nTeine juhend keskendub täiendavate kaardielementide lisamisele, mille hulka kuuluvad nii lisadetailid (punkttähised, tekst ja legend) kui erinevad matemaatilised ja kartograafilised konstruktsioonid (ortodroom jms):\n* https://github.com/LandscapeGeoinformatics/mcarto2023/blob/main/Kaardielemendid.ipynb\n\n## Ettevalmistus\nJuhendite kasutamine eeldab [Anaconda](https://conda.io/en/main/miniconda.html) olemasolu, mis peaks olema arvutiklassi arvutites tagatud. Kes soovib seda seadistada oma arvutis, võib selleks kasutada Alex Kmochi vastavat [juhendit](https://kodu.ut.ee/~kmoch/geopython2020/L0/Installing_Miniconda_GIS.html).\n\nPärast Anaconda installimist laadi alla ja paki kuhugi kausta lahti käesolev repositoorium koos kõigi failidega.\n\n`Code -\u003e Download ZIP`\n\n![download_zip](img/download_zip.png)\n\nSeejärel leia ja ava käsurea kaudu nn Anaconda Prompt.\n\n![anaconda_prompt](img/anaconda_prompt.png)\n\nLiigu käsu `cd` abil kausta, kuhu pakkisid eelnevalt lahti GitHubist alla laaditud ZIP faili.\n\n`cd C:\\Users\\Holger\\mcarto2023-main\\mcarto2023-main`\n\nKäsu `ls` (Windowsis ka käsk `dir`) abil peaks nähtavale tulema kausta sisu, sh praktikumis kasutatavad Jupyteri töövihikud.\n\n![folder](img/folder.png)\n\nAlustuseks loome Anaconda keskkonna nimega `mcarto2023` ning installime sellesse `cartopy` ja `jupyterlab` teegid, mida kasutame praktikumi ülesannetes. Parameeter `-c conda-forge` määrab Pythoni teekide lähtekanaliks [conda-forge](https://conda-forge.org/) repositooriumi.\n\n`conda create -n mcarto2023 -c conda-forge cartopy jupyterlab`\n\n![create_env](img/create_env.png)\n\nJärgmine rida aktiveerib äsjaloodud keskkonna.\n\n`conda activate mcarto2023`\n\n![activate_env](img/activate_env.png)\n\nEnne harjutuste kallale asumist installime veel nn Jupyteri kerneli ehk anname Jupyteri töövihikutele teada, et soovime nende jooksutamisel kasutada vastloodud `mcarto2023` keskkonda.\n\n`python -m ipykernel install --user --name mcarto2023`\n\n![install_kernel](img/install_kernel.png)\n\nLõpuks aktiveeri Jupyteri keskkond.\n\n`jupyter lab`\n\nAvaneb brauser, kus klõps failil laiendiga *.ipynb* avab vastava töövihiku, mida saab brauseri aknas kasutama hakata.\n\n![browser](img/browser.png)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flandscapegeoinformatics%2Fmcarto2023","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flandscapegeoinformatics%2Fmcarto2023","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flandscapegeoinformatics%2Fmcarto2023/lists"}