Active region magnetograms for solar flare prediction: Extra images dataset

In this dataset, we provide a comprehensive collection of magnetograms from the National Aeronautics and Space Administration's (NASA's) Solar Dynamics Observatory (SDO).  The dataset incorporates data from three sources and provides SDO Helioseismic and Magnetic Imager (HMI) magnetograms of solar active regions as well as labels of corresponding flaring activity.  This dataset will be useful for image analysis or solar physics research related to magnetic structure, its evolution over time, and its relation to solar flares.  The dataset will be of interest to those researchers investigating automated solar flare prediction methods, including supervised and unsupervised machine learning (classical and deep), binary and multi-class classification, and regression.  This dataset contains those images that were removed from the preconfigured datasets (see usage notes below)., This dataset incorporates data from three main sources. First, in order to focus the image collection on ARs, we used the NOAA Space Weather Prediction Center (SWPC) Solar Region Summaries (SRS) (ftp://ftp.swpc.noaa.gov/pub/warehouse/) and parsed those text data to extract the date an AR appeared on disk and the number of days it was visible on disk.  Additionally, the SRS provide latitude and longitude of ARs which we use to postprocess the dataset. Second, we download magnetogram images from SDO/HMI using the Joint Science Operations Center (JSOC) interface (http://jsoc.stanford.edu/ajax/lookdata.html) at a cadence of 720 seconds, centered at the NOAA AR centroid (tracked according to the Carrington rate), and with a spatial extent of 600x600 pixels. Third, we used the SWPC Event Reports (ER) (ftp://ftp.swpc.noaa.gov/pub/warehouse/) to extract the AR number, peak flare time, and flare size in order to provide labels for those researchers investigating a supervised classification or re..., Image data are provided in supplementary files available on zenodo (see links under Related works) as .fits files which can be opened with with the python package astropy (https://www.astropy.org).  All other files included here are text files that can be opened with any standard text manipulation software.  We do note, however, that many text files are very large (~1M lines), and may take a while to load. 
This is one of three datasets related to the same study:
Reduced resolution dataset: Reduced resolution images (950,047 images, each of which is 224x224 pixels and 8-bit depth resolution), https://doi.org/10.5061/dryad.jq2bvq898.
Full resolution dataset: Full resolution images (950,047 images, each of which is 600x600 pixels and 17-bit depth resolution), https://doi.org/10.5061/dryad.dv41ns23n.
Extra images (this dataset): Images that were excluded from the main analyses in the first and second datasets (421,957 images that were excluded for latitude, longitude, and/or NaN pixels).  ..., # Active Region Magnetograms for Solar Flare Prediction: Extra Images

In this dataset we provide a comprehensive collection of magnetograms from the National Aeronautics and Space Administration's (NASA's) Solar Dynamics Observatory (SDO). The dataset incorporates data from three sources and provides SDO Helioseismic and Magnetic Imager (HMI) magnetograms of solar active regions as well as labels of corresponding flaring activity. This dataset will be useful for image analysis or solar physics research related to magnetic structure, its evolution over time, and its relation to solar flares. The dataset will be of interest to those researchers investigating automated solar flare prediction methods, including supervised and unsupervised machine learning (classical and deep), binary and multi-class classification, and regression.

This dataset consists of full resolution images generated from magnetograms of National Oceanic and Atmospheric Administration (NOAA) active regions (ARs) from ...