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Default set of Data Lab notebooks, by DL team and contributed by users
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Generally, all notebooks should work with Python 3 and some may still work with Python 2 (we no longer develop for Python 2). Furthermore, an html version of the notebooks is included in order to show them fully rendered. DEFAULT DATALAB NOTEBOOKS ========================= 01- GETTING STARTED The notebooks in "01_GettingStartedWithDatalab/" provide a 101 intro to Python, Jupyter and SQL, and show for Data Lab basic steps such as loading modules, authenticating, making a list of available datasets, an example query, and an example image cutout. It is meant as a reference for these general basic steps. It shows how to obtain the statistics of catalog tables in order to determine the row and column counts while avoiding to count all rows on large tables, which can be slow. 02- DATA ACCESS OVERVIEW The notebook in "02_DataAccessOverview/" provides users with examples of typical functions and commands to explore and use some of the main datasets hosted by the Data Lab. It is a reference for scientific applications, though not as detailed as the specific science examples given below (item 4). 03- SCIENCE EXAMPLES The "03_ScienceExamples" folder contains notebooks that showcase scientific applications using the datasets hosted at Data Lab. Each science application contains at least one notebook, and each survey/dataset is featured in at least one notebook. In some instances, the same science case is featured with two or more surveys. - DwarfGalaxies: discover dwarf galaxies as stellar overdensities in the DES DR1, NSC DR1 and SMASH datasets - ExploringM31: explore the M31 galaxy with the PHAT dataset - GalacticStructure: probe stellar populations in different parts of the Galactic Plane using the DECaPS dataset - LargeScaleStructure: inspect large-scale structures using spectroscopic information from SDSS combined with photometric information from the DESI pre-imaging Legacy Survey (LS) - Pal5TidalTails: identify tidal tails of the globular cluster Palomar 5 in the NSC DR1 catalog, as well as a jointly with Gaia DR2 to explore the proper motion of the cluster and its tails - SpectralEnergyDistributions: (1) use narrow-band filters to construct SEDs of objects from the S-PLUS DR1 dataset, and (2) compare the mid- infrared photometry from unWISE DR1 and AllWISE (3.4 & 4.6 micron) - StarGalQSOSeparation: use photometric properties (colors, morphology/shape parameters, etc.) to distinguish between stars, galaxies, and QSOs in the DES DR1 and LS DR7 datasets - TimeSeriesAnalysisRrLyraeStar: analyze time-series to measure the period of RR Lyrae stars using photometry from SMASH The ScienceExamples notebooks are located here: https://datalab.noao.edu/notebooks/web/ScienceExamples/ 04- HOW-TOS The "04_HowTos/" folder contains sub-folders with notebooks that show how to use Data Lab services with more detail than the brief examples included in the GettingStarted and DataAccessOverview notebooks. The functionality is shown for the full set of keywords and options for the following: - AuthClient: authenticating with the Data Lab - CrossmatchTables: crossmatching a user-provided table against a table hosted by Data Lab - FileService: using files rather than database tables, including spectra from SDSS/BOSS - QueryClient: sending queries to the databases and retrieving results - RowVsCstore: using row-stored versus column-stored database tables - SIA service: obtaining cutouts using a Simple Image Access service [future] - StoreClient: storing data in virtual storage (vospace or mydb) The How-To notebooks are located here: https://datalab.noao.edu/notebooks/web/HowTos/ 05- CONTRIB The "05_Contrib/" directory holds user-contributed notebooks to Data Lab. Please see ./CONTRIBUTING file for detailed instructions. 06 - EPO The "06_EPO/" directory provides "Education and Public Outreach" notebooks, aimed at school students and teachers interested in astronomical research and in teaching astronomy. The notebooks were originally developed for the "Teen Astronomy Café" activities organized jointly by the LSST and NOAO EPO departments. :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: HOW TO UPDATE NOTEBOOKS ======================= Data Lab never modifies the notebooks that were placed in your notebooks/ directory during account creation. Over time, as the default notebooks evolve, they will diverge from those in notebooks/. To obtain a full copy of the newest default notebooks, click in the top-right corner of the Jupyter dashboard on "New", then on "Terminal", and use the `getlatest` function: # without argument: copies to a directory named with current date and time username@datalab>getlatest Copied /dlusers/username/notebooks-latest/ to notebooks_20180709_212650/ # with target directory as argument username@datalab>getlatest mydir Copied /dlusers/username/notebooks-latest/ to mydir/ All notebooks have a __version__ variable defined in the very first cell. Simply running 'grep version foofile.ipynb' will show the version of the given file. Finally, copies of this README.txt file as well as the latest notebooks are kept on: - the Data Lab website: https://datalab.noao.edu/notebooks/web/ - the Data Lab Github account: https://github.com/noaodatalab/notebooks-latest :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: DOCUMENTATION & RESOURCES ========================= The User Manual includes a tutorial on using Jupyter Notebooks with the Data Lab: https://datalab.noao.edu/docs/manual/UsingTheNOAODataLab/JupyterNotebooks/JupyterNotebooks.html The User Manual also includes additional information on the Science Examples featured in the notebooks: https://datalab.noao.edu/docs/manual/UsingTheNOAODataLab/ScienceExamples/ Helpful advice on using SQL and writing queries can be found here: https://datalab.noao.edu/docs/manual/UsingTheNOAODataLab/SQLGotchas/SQLGotchas.html Lastly, please visit the Helpdesk to see the FAQs or ask your questions: https://datalab.noao.edu/help/
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