Optimize NVSPL file reading#93
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…columns Signed-off-by: arpitjain099 <arpitjain099@gmail.com>
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Addresses the TODO at models.py line 185 about speed and memory improvements for NVSPL parsing.
Three changes in Nvspl._read():
The float32 coercion on line 172 was silently discarded. The pandas astype() method returns a new DataFrame but the result was never assigned back, so the conversion never took effect. Fixed by assigning the result.
Added a dtype dict so numeric columns are read as float32 from the start instead of the default float64. For a typical multi-month deployment reading thousands of hourly NVSPL files (each 3600 rows x 54 columns), this cuts memory usage on numeric data roughly in half.
Drops columns that are consistently empty in standard NVSPL output (INVID, INSID, GChar2, AdjustmentsApplied, CalibrationAdjustment, GPSTimeAdjustment). Downstream code only accesses the octave bands, broadband levels, and the datetime index, so these empty columns just waste memory.