tokens: the marked outliers are not reliable enough for searching for flare candidates alone (see Fig. 1 ): it sometimes also marks the beginning of the light-curve windows. Thus we only used the RANSAC estimate of the inlier points for statistics and calculated the standard deviation of the light curve (with the rotational modulation and most of the flare points removed). We considered those points as first-order flare candidates that were above a given detection level (above 3 σ by default). To achieve more robust results, we shifted the search window through the light curve, by default in steps of one-fourth of the light-curve window (see Fig. 2 , e.g.). In this way, every light-curve point was analyzed multiple times (with the exception of those that are at the beginning or at the end of the data set or large observational gaps), and if a light-curve point is considered as an outlier, that is, a flare point candidate, it received a “vote”. A light-curve section was considered a flare when it received enough votes (≥3, by default) in overlapping search windows and had at least a given number (2, by default) of consecutive points. We note that this last step was performed only after evaluating each light-curve segment. These criteria are basically the same as those defined by Eqs. (3a)– (3d) of Chang et al. (2015) and are consistent with adaptations made by Davenport (2016) . When running FLATW’RM from command line, the user can change the number of flare points needed for a flare, the detection level of the flares, and the full with at half maximum (FWHM) that is used for the analytic fit of the events. Optionally, the rotation period can be given as an input to run the code faster, or to fix it to a chosen value if the rotational modulation is too weak, and the polynomial degree can also be fixed. The number of votes needed for a flare candidate to be kept, the window size (compared to the rotation period), and the step length with which the search window is shifted cannot be changed from command line, but can be easily modified if the flare-finding function is imported to another code. Fig. 2. Demonstration of the voting algorithm on a light-curve section of KIC 1722506. The top plot shows the original light curve (in blue, near a normalized flux of 1), and each light-curve segment in individual windows tested by FLATW’RM (each a different color), and the flare candidates are marked for the given run with circles. In the bottom plot , the candidates with one (light gray), two (medium gray), and at least three (black) votes are plotted. In this setup, the flares plotted in black are kept as final flare candidates. 2.4. Summary of the selection process For clarity, we explicitly state the procedure that FLATW’RM steps through in locating the flares in the light curve. A period search is first performed on the input light curve. The input light curve is divided into windows of 1.5 × P that can be effectively fit with polynomials. Each light-curve
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