#timeseries — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #timeseries, aggregated by home.social.
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I had a bunch of JSONL files with sensor readings and needed a quick way to check field cardinality and fill rates, filter records, and look up specific entries. Sure, I could have used Databricks, but where’s the fun in that? 😉
So I ended up building a TUI for viewing and filtering JSONL data, with some basic statistics included.
https://github.com/jsynowiec/tav
#textual #textualize #python #tui #jsonl #dataEngineering #timeSeries
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I had a bunch of JSONL files with sensor readings and needed a quick way to check field cardinality and fill rates, filter records, and look up specific entries. Sure, I could have used Databricks, but where’s the fun in that? 😉
So I ended up building a TUI for viewing and filtering JSONL data, with some basic statistics included.
https://github.com/jsynowiec/tav
#textual #textualize #python #tui #jsonl #dataEngineering #timeSeries
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New #Blog: Deduplicating My VictoriaMetrics Data
Author: Ben Tasker -
New #Blog: Deduplicating My VictoriaMetrics Data
Author: Ben Tasker -
New #Blog: Deduplicating My VictoriaMetrics Data
Author: Ben Tasker -
New #Blog: Deduplicating My VictoriaMetrics Data
Author: Ben Tasker -
Working with time-series data at scale? “How Prometheus Keeps Its TSDB Sane” breaks down how Prometheus keeps its own storage manageable and safe.
Read More: https://zalt.me/blog/2026/04/prometheus-tsdb-sanity
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You already know that you can visualize your metrics from #Prometheus in #OpenSearch Dashboard's Discover Metrics experience (if not, check the comments).
But what if we could add some #AI sauce to detect anomalies and extrapolate forecasts?
Check out the new RFC for time series #anomalyDetection and #forecasting in @OpenSearchProject and chime in with your feedback.
https://github.com/opensearch-project/OpenSearch-Dashboards/issues/11439#OpenSearchAmbassador #timeseries #metrics #monitoring #cloudnative
@Prometheus -
You already know that you can visualize your metrics from #Prometheus in #OpenSearch Dashboard's Discover Metrics experience (if not, check the comments).
But what if we could add some #AI sauce to detect anomalies and extrapolate forecasts?
Check out the new RFC for time series #anomalyDetection and #forecasting in @OpenSearchProject and chime in with your feedback.
https://github.com/opensearch-project/OpenSearch-Dashboards/issues/11439#OpenSearchAmbassador #timeseries #metrics #monitoring #cloudnative
@Prometheus -
You already know that you can visualize your metrics from #Prometheus in #OpenSearch Dashboard's Discover Metrics experience (if not, check the comments).
But what if we could add some #AI sauce to detect anomalies and extrapolate forecasts?
Check out the new RFC for time series #anomalyDetection and #forecasting in @OpenSearchProject and chime in with your feedback.
https://github.com/opensearch-project/OpenSearch-Dashboards/issues/11439#OpenSearchAmbassador #timeseries #metrics #monitoring #cloudnative
@Prometheus -
You already know that you can visualize your metrics from #Prometheus in #OpenSearch Dashboard's Discover Metrics experience (if not, check the comments).
But what if we could add some #AI sauce to detect anomalies and extrapolate forecasts?
Check out the new RFC for time series #anomalyDetection and #forecasting in @OpenSearchProject and chime in with your feedback.
https://github.com/opensearch-project/OpenSearch-Dashboards/issues/11439#OpenSearchAmbassador #timeseries #metrics #monitoring #cloudnative
@Prometheus -
You already know that you can visualize your metrics from #Prometheus in #OpenSearch Dashboard's Discover Metrics experience (if not, check the comments).
But what if we could add some #AI sauce to detect anomalies and extrapolate forecasts?
Check out the new RFC for time series #anomalyDetection and #forecasting in @OpenSearchProject and chime in with your feedback.
https://github.com/opensearch-project/OpenSearch-Dashboards/issues/11439#OpenSearchAmbassador #timeseries #metrics #monitoring #cloudnative
@Prometheus -
Improving Forest Loss Mapping In Nepal Using Landtrendr Time-Series And Machine Learning
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https://doi.org/10.1016/j.rsase.2025.101864 <-- share paper
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“HIGHLIGHTS:
• ViT-based forest mask, multispectral ensemble LandTrendr and terrain shadow mask.
• District-level RF/XGBoost model training with expert-weighted validation.
• Outperformed GFC and REDD + AI benchmarks in accuracy and F1 performance.
• RF excelled in High Mountains/Himalayas; XGBoost in the lower Mountain regions.
• NBR contributed the most; snow-impacted forest loss uncertainty was observed..."
#Forestdisturbance #forest #disturbance #remotesensing #LandTrendr #workflow #timeseries #ViT #RF #XGBoost #GEE #Nepal #ForestNepal #spatial #GIS #mapping #earthobservation #landsat #Himalayas #mountains #alpine #vegetation #AI #multispectral #monitoring #spatialanalysis #spatiotemporal #loss #change #machinelearning #NDR #conservation #planning #policy #mitagion #ecology #Karnali #Bagmati, #Darchula #Siwalik #GlobalForestChange #Degradation -
Improving Forest Loss Mapping In Nepal Using Landtrendr Time-Series And Machine Learning
--
https://doi.org/10.1016/j.rsase.2025.101864 <-- share paper
--
“HIGHLIGHTS:
• ViT-based forest mask, multispectral ensemble LandTrendr and terrain shadow mask.
• District-level RF/XGBoost model training with expert-weighted validation.
• Outperformed GFC and REDD + AI benchmarks in accuracy and F1 performance.
• RF excelled in High Mountains/Himalayas; XGBoost in the lower Mountain regions.
• NBR contributed the most; snow-impacted forest loss uncertainty was observed..."
#Forestdisturbance #forest #disturbance #remotesensing #LandTrendr #workflow #timeseries #ViT #RF #XGBoost #GEE #Nepal #ForestNepal #spatial #GIS #mapping #earthobservation #landsat #Himalayas #mountains #alpine #vegetation #AI #multispectral #monitoring #spatialanalysis #spatiotemporal #loss #change #machinelearning #NDR #conservation #planning #policy #mitagion #ecology #Karnali #Bagmati, #Darchula #Siwalik #GlobalForestChange #Degradation -
Improving Forest Loss Mapping In Nepal Using Landtrendr Time-Series And Machine Learning
--
https://doi.org/10.1016/j.rsase.2025.101864 <-- share paper
--
“HIGHLIGHTS:
• ViT-based forest mask, multispectral ensemble LandTrendr and terrain shadow mask.
• District-level RF/XGBoost model training with expert-weighted validation.
• Outperformed GFC and REDD + AI benchmarks in accuracy and F1 performance.
• RF excelled in High Mountains/Himalayas; XGBoost in the lower Mountain regions.
• NBR contributed the most; snow-impacted forest loss uncertainty was observed..."
#Forestdisturbance #forest #disturbance #remotesensing #LandTrendr #workflow #timeseries #ViT #RF #XGBoost #GEE #Nepal #ForestNepal #spatial #GIS #mapping #earthobservation #landsat #Himalayas #mountains #alpine #vegetation #AI #multispectral #monitoring #spatialanalysis #spatiotemporal #loss #change #machinelearning #NDR #conservation #planning #policy #mitagion #ecology #Karnali #Bagmati, #Darchula #Siwalik #GlobalForestChange #Degradation -
Improving Forest Loss Mapping In Nepal Using Landtrendr Time-Series And Machine Learning
--
https://doi.org/10.1016/j.rsase.2025.101864 <-- share paper
--
“HIGHLIGHTS:
• ViT-based forest mask, multispectral ensemble LandTrendr and terrain shadow mask.
• District-level RF/XGBoost model training with expert-weighted validation.
• Outperformed GFC and REDD + AI benchmarks in accuracy and F1 performance.
• RF excelled in High Mountains/Himalayas; XGBoost in the lower Mountain regions.
• NBR contributed the most; snow-impacted forest loss uncertainty was observed..."
#Forestdisturbance #forest #disturbance #remotesensing #LandTrendr #workflow #timeseries #ViT #RF #XGBoost #GEE #Nepal #ForestNepal #spatial #GIS #mapping #earthobservation #landsat #Himalayas #mountains #alpine #vegetation #AI #multispectral #monitoring #spatialanalysis #spatiotemporal #loss #change #machinelearning #NDR #conservation #planning #policy #mitagion #ecology #Karnali #Bagmati, #Darchula #Siwalik #GlobalForestChange #Degradation -
Improving Forest Loss Mapping In Nepal Using Landtrendr Time-Series And Machine Learning
--
https://doi.org/10.1016/j.rsase.2025.101864 <-- share paper
--
“HIGHLIGHTS:
• ViT-based forest mask, multispectral ensemble LandTrendr and terrain shadow mask.
• District-level RF/XGBoost model training with expert-weighted validation.
• Outperformed GFC and REDD + AI benchmarks in accuracy and F1 performance.
• RF excelled in High Mountains/Himalayas; XGBoost in the lower Mountain regions.
• NBR contributed the most; snow-impacted forest loss uncertainty was observed..."
#Forestdisturbance #forest #disturbance #remotesensing #LandTrendr #workflow #timeseries #ViT #RF #XGBoost #GEE #Nepal #ForestNepal #spatial #GIS #mapping #earthobservation #landsat #Himalayas #mountains #alpine #vegetation #AI #multispectral #monitoring #spatialanalysis #spatiotemporal #loss #change #machinelearning #NDR #conservation #planning #policy #mitagion #ecology #Karnali #Bagmati, #Darchula #Siwalik #GlobalForestChange #Degradation -
Sử dụng LLM để kiểm tra logic phát hiện bất thường trong dữ liệu giá sản phẩm (ví dụ: tăng giá ảo trước khi giảm giá). LLM giúp phát hiện các trường hợp biên, tạo dữ liệu kiểm thử đối nghịch & làm rõ các giả định trong logic. Rất hữu ích trong giai đoạn thiết kế!
#LLM #AI #Programming #AnomalyDetection #TimeSeries #VietNam #CôngNghệ #TríTuệNhânTạo
https://www.reddit.com/r/programming/comments/1pbzinp/using_llms_to_reason_over_pricehistory_time/
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Surface Water Transitions 1984–2022 - A Global Dataset at Annual Resolution
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https://doi.org/10.1038/s41597-025-06013-5 <-- shared paper
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#water #hydrology #hydrospatial #globe #global #remotesensing #spatialanalysis #spatiotemporal #GIS #spatial #mapping #watertransition #river #stream #lake #coast #coastal #landsat #timeseries #WCD #WTTD #OTSU #NDWI #landuse #landcover #NLDI #soil #vegetation #forest #urban #industrial #advance #recession #wetland #engineered #agriculture #floodplain #deforestration #reservior #delta #model #modeling #surfacewater #change #seasonal #climate #annual #historic #recenthistory #waterresources #watermanagement #watersecurity -
Surface Water Transitions 1984–2022 - A Global Dataset at Annual Resolution
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https://doi.org/10.1038/s41597-025-06013-5 <-- shared paper
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#water #hydrology #hydrospatial #globe #global #remotesensing #spatialanalysis #spatiotemporal #GIS #spatial #mapping #watertransition #river #stream #lake #coast #coastal #landsat #timeseries #WCD #WTTD #OTSU #NDWI #landuse #landcover #NLDI #soil #vegetation #forest #urban #industrial #advance #recession #wetland #engineered #agriculture #floodplain #deforestration #reservior #delta #model #modeling #surfacewater #change #seasonal #climate #annual #historic #recenthistory #waterresources #watermanagement #watersecurity -
🎉 Gretl 2025c is here!
Exciting updates to your favorite econometrics toolkit! Version 2025c brings powerful new features and improvements:✨ New Features:
Gibbs sampler command for Bayesian analysis is available now!🚀 Performance & Quality:
Faster forward stepwise regression🎨 GUI Enhancements:
Better dbnomics search integration
Improved dark theme supportFull changelog:
https://gretl.sourceforge.net/ChangeLog.html
#gretl #econometrics #opensource #statistics #datascience #economics #timeseries
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📢 Don’t forget!
Join us today at 6PM CEST for our R-Ladies Rome workshop with @@ramikrispin:
“Forecasting Time Series with Linear Regression: A Feature-Driven Approach” 📈🔗 https://www.meetup.com/rladies-rome/events/308574280
#rstats #timeseries #DataScience #RLadiesRome #Rusers #MachineLearning #OpenSource
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📢 Don’t forget!
Join us today at 6PM CEST for our R-Ladies Rome workshop with @@ramikrispin:
“Forecasting Time Series with Linear Regression: A Feature-Driven Approach” 📈🔗 https://www.meetup.com/rladies-rome/events/308574280
#rstats #timeseries #DataScience #RLadiesRome #Rusers #MachineLearning #OpenSource
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#binjr has a new home on the Fediverse!
The social account for binjr on the Fediverse is now hosted on its own dedicated and independently run instance: https://social.binjr.eu.
(Shout out to the great folks at @gotosocial for making this so easy with their incredibly lightweight ActivityPub server. Go check it out!)If you were already following the old @binjr account: no worries! There’s nothing for you to do: your subscription should have automatically carried over to the new account.
Of course, our brand new lil' instance is quite expectedly off to some rather modest beginnings—it is not open for registration to new users (that is not the point) but it would help "prime the federation pump" if folks from all parts of the Fediverse interacted with it, just once.
So please consider boosting this, if you feel so inclined!Cheers!
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#binjr has a new home on the Fediverse!
The social account for binjr on the Fediverse is now hosted on its own dedicated and independently run instance: https://social.binjr.eu.
(Shout out to the great folks at @gotosocial for making this so easy with their incredibly lightweight ActivityPub server. Go check it out!)If you were already following the old @binjr account: no worries! There’s nothing for you to do: your subscription should have automatically carried over to the new account.
Of course, our brand new lil' instance is quite expectedly off to some rather modest beginnings—it is not open for registration to new users (that is not the point) but it would help "prime the federation pump" if folks from all parts of the Fediverse interacted with it, just once.
So please consider boosting this, if you feel so inclined!Cheers!
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Integrated Topographic Corrections Improve Forest Mapping Using Landsat Imagery
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https://doi.org/10.1016/j.jag.2022.102716 <-- shared 2022 paper
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“HIGHLIGHTS:
• [They] evaluated the impacts of topographic correction on forest mapping in the mountains.
• The enhanced C-correction and the physical model reduced topographic effects.
• The corrected Landsat imagery time series resulted in higher accuracy.
• Terrain information improved classification but not as much as topographic correction.
• [They] recommend using topographic correction for forest cover mapping..."
#GIS #spatial #AtmosphericCorrection #IlluminationCondition #LandCover #ModelComparison #TimeSeries #TopographicCorrection #remotesensing #comparasion #topographic #correction #NDVI #forest #vegetation #model #modeling #spatialanalyis #accuracy #forestcover #Russia #Georgia #CaucasusMountains #spatiotemporal #landsat #elevation #DEM -
Integrated Topographic Corrections Improve Forest Mapping Using Landsat Imagery
--
https://doi.org/10.1016/j.jag.2022.102716 <-- shared 2022 paper
--
“HIGHLIGHTS:
• [They] evaluated the impacts of topographic correction on forest mapping in the mountains.
• The enhanced C-correction and the physical model reduced topographic effects.
• The corrected Landsat imagery time series resulted in higher accuracy.
• Terrain information improved classification but not as much as topographic correction.
• [They] recommend using topographic correction for forest cover mapping..."
#GIS #spatial #AtmosphericCorrection #IlluminationCondition #LandCover #ModelComparison #TimeSeries #TopographicCorrection #remotesensing #comparasion #topographic #correction #NDVI #forest #vegetation #model #modeling #spatialanalyis #accuracy #forestcover #Russia #Georgia #CaucasusMountains #spatiotemporal #landsat #elevation #DEM -
Integrated Topographic Corrections Improve Forest Mapping Using Landsat Imagery
--
https://doi.org/10.1016/j.jag.2022.102716 <-- shared 2022 paper
--
“HIGHLIGHTS:
• [They] evaluated the impacts of topographic correction on forest mapping in the mountains.
• The enhanced C-correction and the physical model reduced topographic effects.
• The corrected Landsat imagery time series resulted in higher accuracy.
• Terrain information improved classification but not as much as topographic correction.
• [They] recommend using topographic correction for forest cover mapping..."
#GIS #spatial #AtmosphericCorrection #IlluminationCondition #LandCover #ModelComparison #TimeSeries #TopographicCorrection #remotesensing #comparasion #topographic #correction #NDVI #forest #vegetation #model #modeling #spatialanalyis #accuracy #forestcover #Russia #Georgia #CaucasusMountains #spatiotemporal #landsat #elevation #DEM -
Integrated Topographic Corrections Improve Forest Mapping Using Landsat Imagery
--
https://doi.org/10.1016/j.jag.2022.102716 <-- shared 2022 paper
--
“HIGHLIGHTS:
• [They] evaluated the impacts of topographic correction on forest mapping in the mountains.
• The enhanced C-correction and the physical model reduced topographic effects.
• The corrected Landsat imagery time series resulted in higher accuracy.
• Terrain information improved classification but not as much as topographic correction.
• [They] recommend using topographic correction for forest cover mapping..."
#GIS #spatial #AtmosphericCorrection #IlluminationCondition #LandCover #ModelComparison #TimeSeries #TopographicCorrection #remotesensing #comparasion #topographic #correction #NDVI #forest #vegetation #model #modeling #spatialanalyis #accuracy #forestcover #Russia #Georgia #CaucasusMountains #spatiotemporal #landsat #elevation #DEM -
Integrated Topographic Corrections Improve Forest Mapping Using Landsat Imagery
--
https://doi.org/10.1016/j.jag.2022.102716 <-- shared 2022 paper
--
“HIGHLIGHTS:
• [They] evaluated the impacts of topographic correction on forest mapping in the mountains.
• The enhanced C-correction and the physical model reduced topographic effects.
• The corrected Landsat imagery time series resulted in higher accuracy.
• Terrain information improved classification but not as much as topographic correction.
• [They] recommend using topographic correction for forest cover mapping..."
#GIS #spatial #AtmosphericCorrection #IlluminationCondition #LandCover #ModelComparison #TimeSeries #TopographicCorrection #remotesensing #comparasion #topographic #correction #NDVI #forest #vegetation #model #modeling #spatialanalyis #accuracy #forestcover #Russia #Georgia #CaucasusMountains #spatiotemporal #landsat #elevation #DEM -
We got a #paper out! We demonstrate that you can retrieve **all** of PROSAIL #RadiativeTransfer model parameters from #timeseries of #Sentinel2 #reflectance. You can then even explain ~90% of the full #Hyperspectral data. At least over #crops https://doi.org/10.1016/j.rse.2024.114510
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We got a #paper out! We demonstrate that you can retrieve **all** of PROSAIL #RadiativeTransfer model parameters from #timeseries of #Sentinel2 #reflectance. You can then even explain ~90% of the full #Hyperspectral data. At least over #crops https://doi.org/10.1016/j.rse.2024.114510
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New UI feature: splittable visualization area
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#binjr 3.20 is now available! 🎉
In this release:
* Quality-of-life improvements for users of the CSV adapter, like the ability to reload the file from disk using Ctrl+F5, or the possibility to relax the parsing rules and ignore lines with misformatted time stamps.
* Updates to the latest release of #OpenJDK and #OpenJFX
* Many bugs fixed, some particularly old and nagging!And more! Read the full changelog and download it at https://binjr.eu
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You won't be surprised that I eagerly watch James Hoffmann's videos. Especially the "if you were to plan some small experiment on your own - WITH COFFEE!" videos are really good.
So his new test of the "delay your morning #coffee" hypothesis was right down my street!
https://www.youtube.com/watch?v=yCJr49GU9yY
#HubermanLabOne thing I was wondering and which was not discussed in the comments I managed to read:
Were the data analysed in a way that took nesting / #RepeatedMeasures into account? -
#binjr 3.19 is now available! 🎉
The main feature for this update, is that it does *not* put your machine into an endless cycle of BSOD!, (err... sorry was that too soon 😬)
Aside from that, it's mostly fixes and updated dependencies, like the most recent security update for #openjdk and #openjfx.
Read the full changelog and download it at https://binjr.eu
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Remote Sensing Of Coccolithophore Blooms In Selected Oceanic Regions Using The Phytodoas Method Applied To Hyper-Spectral Satellite Data
-- https://doi.org/10.5194/bg-9-2127-2012 <-- shared paper
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#GIS #spatial #mapping #marine #ocean #remotesensing #earthobservation #coccolithophore #bloom #satellite #SCIAMACHY #hyperspectral #ENVISAT #PhytoDOAS #GlobColour #phytoplankton #plankton #geophysics #seasurface #temperature #mixedlayerdepth #windspeed #modeling #corrleation #biomass #spatialanalysis #spatiotemporal #timeseries -
Remote Sensing Of Coccolithophore Blooms In Selected Oceanic Regions Using The Phytodoas Method Applied To Hyper-Spectral Satellite Data
-- https://doi.org/10.5194/bg-9-2127-2012 <-- shared paper
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#GIS #spatial #mapping #marine #ocean #remotesensing #earthobservation #coccolithophore #bloom #satellite #SCIAMACHY #hyperspectral #ENVISAT #PhytoDOAS #GlobColour #phytoplankton #plankton #geophysics #seasurface #temperature #mixedlayerdepth #windspeed #modeling #corrleation #biomass #spatialanalysis #spatiotemporal #timeseries -
#binjr 3.18 is now available! 🎉
The highlight of this release is the addition of an option to dynamically set the application's theme according to the system's settings.
Read the full changelog and download it at https://binjr.eu
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binjr 3.17 is now available!
It is now possible to set a custom zoom factor for the binjr window, there are new options to deal with badly formatted CSV files, and the embedded #java and #javafx runtimes have been updated to 22.
Read the full changelog and download it at https://binjr.eu
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There are new ways to install #binjr and keep it up-to-date! 🎉
For #ArchLinux users, you can get it from the #AUR: https://aur.archlinux.org/packages/binjr-bin
And for #Windows users, it is now available via #winget: just type `winget install binjr` and you're good to go!
These new options come in addition to the existing repos for #deb and #rpm based distros, available at https://repos.binjr.eu/
And if all else fails, get your binaries straight from https://binjr.eu/download/latest_release/
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There's a new blog post that discusses upcoming features in the next release of binjr!
TL;DR: New graphics settings are coming to binjr.Find out more and give feedback here:
https://binjr.eu/blog/2024/02/new-graphics-settings-are-coming-to-binjr/ -
binjr 3.16 is now available!
Most of the changes are solely under the hood for this release; bug fixes and updates to dependencies.
Read the full changelog and download it at https://binjr.eu
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binjr 3.15 is now available!
It adds options on how to represent missing values on charts, better progress notifications while the app is being updated and, of course, the usual dependency updates and bug fixes.
Read the full changelog and download it at https://binjr.eu
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binjr 3.14 is now available!
This releases features an update to the embedded Java runtime to #Java21 as well as a couple of "quality of life" improvements, like the ability set a preference for default chart type and search fields becoming active as soon as they are shown.
Read the full changelog and download it at https://binjr.eu
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binjr 3.13 is now available!
This release features the new #JFR data adapter that was revealed some time ago, alongside a few UI enhancements to better support it and some most welcome bug fixes, of course.
Read the full changelog and download it at https://binjr.eu
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The next release of binjr will feature a new data adapter for JDK Flight Recorder files!
It is still under development but you can give it a try and share your feedback via this github discussion: https://github.com/orgs/binjr/discussions/139
#binjr #java #javafx #visualization #dataViz #JFR #JMC #profiler #timeseries #foss #app
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This place is now the only home for #binjr on social media (well, its *real* home is wherever anyone clones a repo from https://github.com/binjr/binjr/ I guess):
as of now, the account over on Twitter/whatever-its-called-this-week will no longer be updated.It's all a bit quiet around here for the moment though, so please follow and boost this post and help spread the word, if you feel so inclined!
#binjr #java #javafx #visualization #dataViz #logs #graphs #timeseries #foss #app
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binjr 3.12 is now available!
This is a pretty featureful release, whose highlight is a new indexing mode for log files that makes is easy to search for arbitrary strings of character without the need for wildcards while maintaining the same level of performance, even on very large files.
It also features several other smaller enhancements and many bug fixes: full release notes available at https://binjr.eu/download/CHANGELOG/#binjr-v3120
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#Midjourney generated #illustrations using prompts from #science paper abstracts.
1-disentangle the interacting drivers of solute loading to streams
2-Anomalous patterns occurring in hydrological time series data
3-Salt marshes
4-space-for-time substitution
#TimeSeries #SciComm #CriticalZone
Outtakes from content created during #AGU22.