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.
