FIX: Stop inflating pluvio gauge variables by 5x in the column match - #42
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Ground instruments matched with resample="sum" were binned into a hard-coded 5-minute total and then linearly interpolated back onto the column's 1-minute time grid, so every output step received a whole 5-minute bin. Accumulations came out inflated by exactly the ratio of the two steps: a 19.29 mm day was written as 96.45 mm. The sum was also applied indiscriminately to every surviving pluvio variable, including two rain intensities (mm/hr) and the running bucket level, none of which may be summed. sgpradclssC1.c0 was reporting a mean intensity_rt of 139 mm/hr and a bucket_nrt of 3327 mm. - Integrate only true accumulations (accum_nrt, accum_rtnrt). Rates and the bucket level now take the same averaging path as every other instrument. - Regrid accumulations conservatively: integrate to a running total, interpolate that onto the column grid, then difference it back. This preserves the integral on regular and irregular (radar-based) time coordinates alike, and is an exact identity at native resolution. - Keep gaps missing. The old .sum() skipped NaNs with no min_count, so an all-NaN bin reported 0 mm and an outage read as "no rain". - Fix the closed="right" label. Pandas labels bin (t, t+step] as t, a timestamp the bin excludes, shifting data one step early. This also moves met, ldquants, vdisquants, wxt, kazr and sonde timing. - Only close datasets this function opened; _grd_raw was unbound whenever DataSet=True, breaking that match_datasets_act path. Existing c0 files need reprocessing, and the correction is not limited to accum_nrt. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
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There was an issue with the accumulations being done over 5 minute periods from the Pluvio instead of the 1 minute timestamps. This is a holdback from when we were doing RadClss over 5 minute periods, so it would only affect the data being currently under review.