{"id":18654420,"url":"https://github.com/pycroscopy/cnms_um_2018_spima","last_synced_at":"2025-04-11T17:31:20.500Z","repository":{"id":88233423,"uuid":"140280498","full_name":"pycroscopy/CNMS_UM_2018_SPIMA","owner":"pycroscopy","description":"Introduction to Spectral and Image processing in Python","archived":false,"fork":false,"pushed_at":"2019-08-09T18:47:26.000Z","size":85817,"stargazers_count":6,"open_issues_count":0,"forks_count":3,"subscribers_count":6,"default_branch":"master","last_synced_at":"2025-03-25T16:22:54.477Z","etag":null,"topics":["notebooks"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/pycroscopy.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2018-07-09T12:13:02.000Z","updated_at":"2022-02-21T16:24:48.000Z","dependencies_parsed_at":"2023-03-13T18:28:07.376Z","dependency_job_id":null,"html_url":"https://github.com/pycroscopy/CNMS_UM_2018_SPIMA","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pycroscopy%2FCNMS_UM_2018_SPIMA","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pycroscopy%2FCNMS_UM_2018_SPIMA/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pycroscopy%2FCNMS_UM_2018_SPIMA/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pycroscopy%2FCNMS_UM_2018_SPIMA/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/pycroscopy","download_url":"https://codeload.github.com/pycroscopy/CNMS_UM_2018_SPIMA/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248449718,"owners_count":21105550,"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":["notebooks"],"created_at":"2024-11-07T07:15:19.780Z","updated_at":"2025-04-11T17:31:15.486Z","avatar_url":"https://github.com/pycroscopy.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Imaging and Spectral Data Analysis in Python\n\nWe present a set of jupyter notebooks and presentations that go over the\nbasics of:\n\n- Image and spectral data analysis in Python \n- [USID](https://pycroscopy.github.io/pyUSID/data_format.html), [pyUSID](https://pycroscopy.github.io/pyUSID/about.html), \n  and [pycroscopy](https://pycroscopy.github.io/pycroscopy/about.html) as tools for analyzing large and multidimensional imaging / spectroscopy datasets \n    \nThis material was developed as part of the [2018 CNMS User Meeting](./CNMS_UM_Workshop_schedule.md)\n\nSee our [list of tutorials](https://pycroscopy.github.io/pyUSID/external_guides.html) for more information\n  \n## Getting started\n### (Recommended) Working on your personal computer\n1. (one time only) Install necessary software:\n    1. Follow [these instructions](https://pycroscopy.github.io/pycroscopy/install.html) to install Anaconda + \n       pycroscopy on your own laptop\n    2. Also please install pyUSID via: ``pip install pyUSID`` just like how you installed pycroscopy\n2. (one time only) Download the contents of this tutorial onto your computer:\n    1. click on the green ``Clone or download`` button\n    2. Click on ``Download ZIP``\n    3. Download the zip file to your Documents / Downloads / Desktop\n    4. Unzip the zip file\n3. Start up a Jupyter Notebook:\n    1. Start a terminal:\n        1. Windows users: Click on ``Start`` \u003e\u003e ``Anaconda3`` \u003e\u003e ``Anaconda Prompt``\n        2. Mac / Linux users: Open ``Terminal``. You can find it by holding down your ``Command`` and ``Space`` key and \n           typing ``Terminal`` in the search bar that pops up.\n    2. In the ``Terminal`` or ``Anaconda Prompt``, type ``jupyter notebook`` and press the ``Enter`` or ``Return`` key.\n       If everything happened correctly, a new tab should pop up on your default browser showing familiar folders such \n       as ``Desktop``, ``Documents``, etc. \n    3. **Do not close the Terminal or Anaconda Prompt!**\n4. Finally, work on the notebooks in this tutorial:\n    1. Navigate to the folder (e.g. - ``Desktop``) where you unzipped the zip file \n       in step 2.\n    2. Click on the ``index.ipynb`` file which should present a new tab on your browser that looks [like this](./index.ipynb)\n5. Once you are done working on the jupyter notebooks:\n    1. Go back to the ``Terminal`` or ``Anaconda Prompt``. Hold down the ``Ctrl`` (control) key and press the ``C`` key \n       twice to shut down the Jupyter server.\n    2. You can now close the Jupyter browser tabs and the ``Terminal`` or ``Anaconda Prompt``\n    \n*We understand that this may seem a little tedious in the beginning but we assure you that you will get used to this very quickly*\n\n### Trying out the tutorial online\nIf you are having trouble with installing Anaconda on your personal computer (above), please try one of the following:\n\n- **Azure notebooks**\n    1. You will need to [sign up](https://signup.live.com/?wa=wsignin1.0\u0026rpsnv=13\u0026ct=1533149109\u0026rver=6.7.6643.0\u0026wp=MBI_SSL\u0026wreply=https%3a%2f%2faccount.microsoft.com%2fauth%2fcomplete-signin%3fru%3dhttps%253A%252F%252Faccount.microsoft.com%252F%253Frefd%253Daccount.microsoft.com%2526refp%253Dsignedout-index\u0026id=292666\u0026lw=1\u0026fl=easi2\u0026pcexp=true\u0026uictx=me\u0026contextid=D0A988B000A50828\u0026bk=1533149128\u0026uiflavor=web\u0026uaid=098dd33703314790a45fcfb799fd93d3\u0026mkt=EN-US\u0026lc=1033\u0026lic=1) for a Microsoft (Outlook, Hotmail, ...) account if you don't already have one.\n    2. Once you are logged in, click [here](https://notebooks.azure.com/ssomnath/libraries/cnms2018um)\n    3. Next, click on the ``Clone`` button (just above the search bar) to make your own copy of the project\n    4. Once your copy of the project has been created, click on the ``Run`` button along the same line as the ``Clone`` button\n    5. You should be directed to a familiar Jupyter notebook server page.\n        \n- **Binder**\n    - The benefit of Binder is that one does not need a Microsoft account, \n      but the drawback is that your solutions / edits will be lost if you close the browser tab(s)\n    - Click [here](https://mybinder.org/v2/gh/pycroscopy/pyUSID_Tutorial/master) to launch the jupyter notebook server.\n      This will take a while so please be patient.\n      \nFinally, for either option, click [here](./index.ipynb) to get started with the notebooks\n\n## Getting help\nPlease get in touch with us on our [Google group](https://groups.google.com/forum/#!forum/pycroscopy)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpycroscopy%2Fcnms_um_2018_spima","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpycroscopy%2Fcnms_um_2018_spima","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpycroscopy%2Fcnms_um_2018_spima/lists"}