From d2d1428fbaf4e229c83e67c4075d9802ea4d8dcc Mon Sep 17 00:00:00 2001 From: cdeline Date: Thu, 10 Oct 2024 13:04:06 -0600 Subject: [PATCH] revert back to %.1f format for saving cumulative .csv file. --- bifacial_radiance/main.py | 15 ++++++--------- 1 file changed, 6 insertions(+), 9 deletions(-) diff --git a/bifacial_radiance/main.py b/bifacial_radiance/main.py index 6a167d83..dd922c34 100644 --- a/bifacial_radiance/main.py +++ b/bifacial_radiance/main.py @@ -273,7 +273,7 @@ def _subhourlydatatoGencumskyformat(gencumskydata, label='right'): try: gencumskydata = gencumskydata.resample('60min', closed='right', label='right').mean() except TypeError: # Pandas 2.0 error - gencumskydata = gencumskydata.resample('60min', closed='right', label='right').mean(numeric_only=True) + gencumskydata = gencumskydata.resample('60min', closed='right', label='right').mean(numeric_only=True) if label == 'left': #switch from left to right labeled by adding an hour gencumskydata.index = gencumskydata.index + pd.to_timedelta('1H') @@ -1142,8 +1142,7 @@ def _saveTempTMY(self, tmydata, filename=None, starttime=None, endtime=None, if gencumskydata is not None: csvfile = os.path.join('EPWs', filename) print('Saving file {}, # points: {}'.format(csvfile, gencumskydata.__len__())) - gencumskydata.to_csv(csvfile, index=False, header=False, sep=' ', - columns=['GHI','DHI'], float_format='%i') + gencumskydata.to_csv(csvfile, index=False, header=False, sep=' ', columns=['GHI','DHI']) self.gencumsky_metfile = csvfile if gencumdict is not None: @@ -1153,8 +1152,7 @@ def _saveTempTMY(self, tmydata, filename=None, starttime=None, endtime=None, newfilename = filename.split('.')[0]+'_year_'+str(ii)+'.csv' csvfile = os.path.join('EPWs', newfilename) print('Saving file {}, # points: {}'.format(csvfile, gencumskydata.__len__())) - gencumskydata.to_csv(csvfile, index=False, header=False, sep=' ', - columns=['GHI','DHI'], float_format='%i') + gencumskydata.to_csv(csvfile, index=False, header=False, sep=' ', columns=['GHI','DHI']) self.gencumsky_metfile.append(csvfile) return tmydata @@ -3602,8 +3600,8 @@ def _makeTrackerCSV(self, theta_list, trackingdata): else: # mask out irradiance at this time, since it # belongs to a different bin - ghi_temp.append(0) - dhi_temp.append(0) + ghi_temp.append(0.0) + dhi_temp.append(0.0) # save in 2-column GHI,DHI format for gencumulativesky -G savedata = pd.DataFrame({'GHI':ghi_temp, 'DHI':dhi_temp}, index = self.datetime).tz_localize(None) @@ -3617,8 +3615,7 @@ def _makeTrackerCSV(self, theta_list, trackingdata): index=False, header=False, sep=' ', - columns=['GHI','DHI'], - float_format='%i') + columns=['GHI','DHI']) return trackerdict