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Merge pull request #321 from Exabyte-io/docs/SOF-7580
SOF-7580: video tutorial on using jupyter notebook for data analysis
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| { | ||
| "descriptionLinks": [ | ||
| "Using Jupyter notebooks for data analysis: https://docs.mat3ra.com/jupyterlite/accessing-jupyterlite/" | ||
| ], | ||
| "description": "We present how we can use Jupyter notebooks in Mat3ra platform for data analysis.", | ||
| "tags": [ | ||
| { | ||
| "...": "../metadata/general.json#/tags" | ||
| }, | ||
| "Jupyter", | ||
| "Python" | ||
| ], | ||
| "title": "Mat3ra Tutorial: Using Jupyter notebooks for data analysis", | ||
| "youTubeCaptions": [ | ||
| { | ||
| "text": "Hi, <break time='0.5'/> in this short tutorial, we are going to present how we can use jupyter notebooks in matera platform for data analysis.", | ||
| "startTime": "00:00:00.500", | ||
| "endTime": "00:00:08.000" | ||
| }, | ||
| { | ||
| "text": "It's a great option for those who are familiar with Python.", | ||
| "startTime": "00:00:08.500", | ||
| "endTime": "00:00:12.000" | ||
| }, | ||
| { | ||
| "text": "Here we will specifically focus on how it can help us simplify the process of analyzing data obtained from DFT simulation..", | ||
| "startTime": "00:00:13.000", | ||
| "endTime": "00:00:22.000" | ||
| }, | ||
| { | ||
| "text": "Let's head over to our platform. Use a web browser and visit platform dot matera dot com.", | ||
| "startTime": "00:00:23.000", | ||
| "endTime": "00:00:29.000" | ||
| }, | ||
| { | ||
| "text": "We are going to create a DFT workflow to calculate bandstructure of silicon using quantum espresso.", | ||
| "startTime": "00:00:30.000", | ||
| "endTime": "00:00:36.000" | ||
| }, | ||
| { | ||
| "text": "This calculation has three steps, <break time='1.0'/> first we perform self consistent field calculation.", | ||
| "startTime": "00:00:37.000", | ||
| "endTime": "00:00:43.000" | ||
| }, | ||
| { | ||
| "text": "Then we add a unit for bands calculation.", | ||
| "startTime": "00:00:44.000", | ||
| "endTime": "00:00:47.000" | ||
| }, | ||
| { | ||
| "text": "Finally, we add unit for postprocessing of bands using bands dot X.", | ||
| "startTime": "00:00:52.000", | ||
| "endTime": "00:00:55.000" | ||
| }, | ||
| { | ||
| "text": "Save and exit workflow. <break time='0.5'/> Create a job with the workflow we have just created.", | ||
| "startTime": "00:00:58.000", | ||
| "endTime": "00:01:04.000" | ||
| }, | ||
| { | ||
| "text": "Submit job for execution.", | ||
| "startTime": "00:01:20.000", | ||
| "endTime": "00:01:21.000" | ||
| }, | ||
| { | ||
| "text": "Once the job is finished, we can see the summary of various results.", | ||
| "startTime": "00:01:25.000", | ||
| "endTime": "00:01:29.000" | ||
| }, | ||
| { | ||
| "text": "Navigate to the files tab, and we will see all the output files are listed here.", | ||
| "startTime": "00:01:34.000", | ||
| "endTime": "00:01:39.000" | ||
| }, | ||
| { | ||
| "text": "Now, we would like to do the post-processing of these output files using Python Jupyter notebook.", | ||
| "startTime": "00:01:40.000", | ||
| "endTime": "00:01:45.000" | ||
| }, | ||
| { | ||
| "text": "There are a couple of different ways to run Jupyter notebook in our platform.", | ||
| "startTime": "00:01:46.000", | ||
| "endTime": "00:01:50.000" | ||
| }, | ||
| { | ||
| "text": "Perhaps, the quickest way to launch Jupyter lite. Click the console icon on the top right and select Jupyter lite.", | ||
| "startTime": "00:01:51.000", | ||
| "endTime": "00:01:57.000" | ||
| }, | ||
| { | ||
| "text": "Let's create a new notebook, <break time='2.0'/> and rename the notebook to bands analysis.", | ||
| "startTime": "00:02:01.000", | ||
| "endTime": "00:02:06.000" | ||
| }, | ||
| { | ||
| "text": "Let's also open an example notebook.", | ||
| "startTime": "00:02:10.000", | ||
| "endTime": "00:02:13.000" | ||
| }, | ||
| { | ||
| "text": "Here we will see that it is entirely possible to perform all the steps from a Jupyter notebook.", | ||
| "startTime": "00:02:16.000", | ||
| "endTime": "00:02:22.000" | ||
| }, | ||
| { | ||
| "text": "Including authentication, <break time='0.25'/> workflow creation, <break time='0.25'/> job submission, <break time='0.25'/> job monitoring and <break time='0.25'/> fetch results.", | ||
| "startTime": "00:02:22.500", | ||
| "endTime": "00:02:29.000" | ||
| }, | ||
| { | ||
| "text": "Now, let's copy the authentication part and run inside our bands analysis notebook.", | ||
| "startTime": "00:02:30.000", | ||
| "endTime": "00:02:35.000" | ||
| }, | ||
| { | ||
| "text": "It will generate API keys and authenticate user seamlessly.", | ||
| "startTime": "00:02:36.000", | ||
| "endTime": "00:02:39.000" | ||
| }, | ||
| { | ||
| "text": "It will also install a list of default packages.", | ||
| "startTime": "00:02:40.000", | ||
| "endTime": "00:02:43.000" | ||
| }, | ||
| { | ||
| "text": "Next we initialize the jobs endpoint.", | ||
| "startTime": "00:02:45.000", | ||
| "endTime": "00:02:47.000" | ||
| }, | ||
| { | ||
| "text": "Then we would like to fetch the output file.", | ||
| "startTime": "00:02:48.000", | ||
| "endTime": "00:02:50.000" | ||
| }, | ||
| { | ||
| "text": "For this we need the job ID.", | ||
| "startTime": "00:02:55.000", | ||
| "endTime": "00:02:57.000" | ||
| }, | ||
| { | ||
| "text": "Let's go back to job page.", | ||
| "startTime": "00:02:58.000", | ||
| "endTime": "00:03:00.000" | ||
| }, | ||
| { | ||
| "text": "And copy the job ID.", | ||
| "startTime": "00:03:02.000", | ||
| "endTime": "00:03:04.000" | ||
| }, | ||
| { | ||
| "text": "We would like to fetch the bands dot dat dot GNU file for bandstructure analysis.", | ||
| "startTime": "00:03:06.000", | ||
| "endTime": "00:03:10.000" | ||
| }, | ||
| { | ||
| "text": "Let's save the results in a file named data dot TXT.", | ||
| "startTime": "00:03:12.000", | ||
| "endTime": "00:03:15.000" | ||
| }, | ||
| { | ||
| "text": "Finally, we can use matplotlib to make our bandstructure plot.", | ||
| "startTime": "00:03:17.000", | ||
| "endTime": "00:03:21.000" | ||
| }, | ||
| { | ||
| "text": "This use case is not specific to DFT data analysis. You can use Python notebooks to analyze or postprocess any data in our platform.", | ||
| "startTime": "00:03:22.000", | ||
| "endTime": "00:03:31.000" | ||
| }, | ||
| { | ||
| "text": "Now, I hope you are excited to visit platform dot matera dot com, and give it a try.", | ||
| "startTime": "00:03:32.000", | ||
| "endTime": "00:03:36.000" | ||
| }, | ||
| { | ||
| "text": "Thank you for following this tutorial and using our platform.", | ||
| "startTime": "00:03:37.000", | ||
| "endTime": "00:03:41.000" | ||
| } | ||
| ], | ||
| "youTubeId": "PXosTghiAzs" | ||
| } |
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