A presentation at Code d'Armor in in 22300 Lannion, France by Horacio Gonzalez
Rediscover the known Universe with NASA datasets Horacio Gonzalez @LostInBrittany Introduction to Time Series @LostInBrittany
Horacio Gonzalez @LostInBrittany Spaniard lost in Brittany, developer, dreamer and all-around geek Introduction to Time Series @LostInBrittany
HelloExoWorld Looking for exoplanets in NASA datasets Introduction to Time Series @LostInBrittany
HelloExoWorld Once upon a time... Introduction to Time Series @LostInBrittany
An amateur astronomer Pierre Zemb, DevOps OVH Introduction to Time Series @LostInBrittany
What not to do if you love astronomy Live in Brest Introduction to Time Series @LostInBrittany
Looking for solutions Computer stuff Astronomy Mixing passions Introduction to Time Series @LostInBrittany
Google is your friend... Let's find a project Introduction to Time Series @LostInBrittany
Exoplanets? Planets orbiting stars far away Introduction to Time Series @LostInBrittany
How do we find them? The transit method seems the best Introduction to Time Series @LostInBrittany
The transit method Credits: NASA’s Goddard Space Flight Center Introduction to Time Series @LostInBrittany
How do we look for transits? Image credits : NASA Kepler Introduction to Time Series @LostInBrittany
Watching the sky By Carter Roberts [Public domain], via Wikimedia Commons Introduction to Time Series @LostInBrittany
And what kind of data we get? Pleiades By NASA, ESA, AURA/Caltech, Palomar Observatory. Via Wikimedia Common Introduction to Time Series @LostInBrittany
Well, that's the problem Seven stars, seven different profiles Introduction to Time Series @LostInBrittany
Kinda big data Over 40 million light curves Introduction to Time Series @LostInBrittany
Big AND open data Lots of datasets in #opendata Introduction to Time Series @LostInBrittany
And we can help with that! Let's use our tools to analyse the data Introduction to Time Series @LostInBrittany
A match made in heaven Warp 10, OVH Metrics and HelloExoWorld Introduction to Time Series @LostInBrittany
What we have done ● ● ● ● Downloaded and parsed 40 millions of FITS files Pushed it to OVH Metrics Select a cool subset as training set Verified we could find the same planets as NASA Introduction to Time Series @LostInBrittany
Choosing a star: Kepler 11 Image credit: NASA/Tim Pyle Introduction to Time Series @LostInBrittany
Looking at the raw signal... SAP_FLUX: The flux in units of electrons per second contained in the optimal aperture pixels collected by the spacecraft. Introduction to Time Series @LostInBrittany
Looking at the raw signal... ? SAP_FLUX: The flux in units of electrons per second contained in the optimal aperture pixels collected by the spacecraft. Introduction to Time Series @LostInBrittany
Looking at one record Perturbations in dirty signals Introduction to Time Series @LostInBrittany
Transits are tiny ~40 electrons per second Introduction to Time Series @LostInBrittany
First step: downsampling Introduction to Time Series @LostInBrittany
First step: downsampling You can see the transit candidates… but how can we teach the computer to see them? Introduction to Time Series @LostInBrittany
If you ♥ signal processing High pass filter Introduction to Time Series @LostInBrittany
Poor person's high pass filter Using the trend Introduction to Time Series @LostInBrittany
Signal - Trend Now you can see them well Introduction to Time Series @LostInBrittany
After some tuning We have our transit candidates Introduction to Time Series @LostInBrittany
What's next? Where do we go from here? Introduction to Time Series @LostInBrittany
Only the beginning Better detection New import method Explorer Deep learning satellite/star location Introduction to Time Series Yours? @LostInBrittany
A growing team Introduction to Time Series @LostInBrittany
And you! Join us! https://helloexo.world https://xkcd.com/1371/ Introduction to Time Series @LostInBrittany
Thank you! Introduction to Time Series @LostInBrittany
Want to know more? Analysing with WarpScript Introduction to Time Series @LostInBrittany
WarpScript Reverse Polish Notation Introduction to Time Series @LostInBrittany
Variables ‘hello, world!’ // Push Hello World String on the Stack ‘exo’ STORE // Store it in a variable called exo $exo // Then push back exo variable on the stack Introduction to Time Series @LostInBrittany
What are the available series? [ $readToken // Application authentication '~.*' // selector for classname {} // Selector for labels ] FIND Introduction to Time Series @LostInBrittany
Get raw data [ $readToken // Application authentication 'sap.flux' // selector for classname { 'KEPLERID' '6541920' } // Selector for labels '2009-05-02T00:56:10.000000Z' // Start date '2013-05-11T12:02:06.000000Z' // End date ] FETCH Introduction to Time Series @LostInBrittany
Kepler-11: Raw data Introduction to Time Series @LostInBrittany
Time manipulation Introduction to Time Series @LostInBrittany
Time related functions Introduction to Time Series @LostInBrittany
How to split a Time series $gts // Singleton (or list of) GTS 6h // Minimum of time without data-points 100 // Minimum of data-points required 'record' // New labels to subdivide the result TIMESPLIT Introduction to Time Series @LostInBrittany
Filtering [ $gts // Singleton (or list of) GTS [] // Equivalence classes { 'record' '5' } // Labels to select filter.bylabels // Type of filter ] FILTER Introduction to Time Series @LostInBrittany
Reference record: 5 Introduction to Time Series @LostInBrittany
Downsampling Introduction to Time Series @LostInBrittany
Bucketize Introduction to Time Series @LostInBrittany
Syntax Time series parameter [ $gts bucketizer.min 0 Singleton 2h 0 ] BUCKETIZE Time-series set Introduction to Time Series @LostInBrittany
Syntax Bucketizer [ $gts bucketizer.min 0 2h 0 ] BUCKETIZE Type of operator to apply on each bucket last, max, mean, and, count ... Introduction to Time Series @LostInBrittany
Syntax Lastbucket [ $gts bucketizer.min 0 2h 0 ] End timestamp of the more recent bucket BUCKETIZE Introduction to Time Series @LostInBrittany
Syntax Bucketspan [ $gts bucketizer.min 0 2h 0 ] Width of a bucket BUCKETIZE Introduction to Time Series @LostInBrittany
Syntax Bucketcount [ $gts bucketizer.min 0 2h 0 ] Number of buckets to keep BUCKETIZE Introduction to Time Series @LostInBrittany
Actual Introduction to Time Series @LostInBrittany
Trend Introduction to Time Series @LostInBrittany
Mapper Introduction to Time Series @LostInBrittany
Syntax Time series parameter [ $gts mapper.mean 2 Singleton 2 0 ] MAP Time-series set Introduction to Time Series @LostInBrittany
Syntax Mapper [ $gts mapper.mean 2 2 0 ] MAP Type of operator to apply on each window add, gt, rate, and, count... Introduction to Time Series @LostInBrittany
Syntax Pre [ $gts mapper.mean 2 2 0 ] Number of data-points before MAP Introduction to Time Series @LostInBrittany
Syntax Post [ $gts mapper.mean 2 2 0 ] Number of data-points after MAP Introduction to Time Series @LostInBrittany
Syntax Occurrence [ $gts mapper.mean 2 2 0 ] Maximal number of calculation for a data-point MAP Introduction to Time Series @LostInBrittany
Actual Introduction to Time Series @LostInBrittany
Trend Introduction to Time Series @LostInBrittany
Actual - trend Introduction to Time Series @LostInBrittany
Actual - trend Introduction to Time Series @LostInBrittany
Time to level-up! Introduction to Time Series @LostInBrittany
Time series operation [ $gts0 // First series pull … // … $gtsN // N series pull [ ‘record’ ] // Key labels list op.add // Type of operator ] APPLY Introduction to Time Series @LostInBrittany
Syntax Time series parameter [ $gts0 … $gtsN Singleton [ ‘record’ ] op.add ] APPLY Time-series set Introduction to Time Series @LostInBrittany
Syntax Equivalence class [ Records data $gts0 … $gtsN [ ‘record’ ] op.add ] Record 1 APPLY Record 3 Record 2 Introduction to Time Series @LostInBrittany
Syntax Operator [ $gts0 Record 1 Record 3 … Record 2 $gtsN [ ‘record’ ] op.add ] APPLY Type of operator to apply on each class sub, gt, mask, and, mul ... Introduction to Time Series @LostInBrittany
Final result Introduction to Time Series @LostInBrittany
Cela fait des années que l’humanité explore le ciel, rêvant de voyages intersidérales et de nouvelles colonies planétaires. Et toi, as-tu envie de partir 3h avec nous à la découverte de l’univers ?
Il se trouve que la NASA possède un formidable jeu de données publiques, notamment celui qui est utilisé pour la recherche d’exoplanètes, c’est-à-dire de planètes situées en dehors de notre système solaire.
C’est ainsi que le projet HelloExoWorld a vu le jour. Son objectif ? Voir des développeurs fans d’analyse de données sont capables de participer à la recherche d’exoplanètes en utilisant ces données publiques de la NASA. Vous découvrirez durant ce talk la création du projet, les résultats actuels, ainsi que son évolution vers une communauté active.
The following resources were mentioned during the presentation or are useful additional information.
