def ok(_):
print('loading backup... ', self.backuppath, end='...')
self.df = load_dataframe(self.backuppath)
print('done.')
self.filter_table(query='')
self.update_layer_btns()
self.show_first_oct()
popup.dismiss()
def init_dataframe(args, input_file):
df = common.load_dataframe('aaws', input_file, 8)
df.index.name = 'time'
df.loc[:, 'air_temp'] += common.freezing_point_temp
df.loc[:, 'pressure'] *= common.pascal_per_millibar
df = df.where((pd.notnull(df)), get_fillvalue(args))
return df
def load_annotation(self):
"""Load pandas table with annotation data"""
print('loading annotation ...', self.annopath, end='...')
self.df = load_dataframe(self.annopath)
print('done.')
# self.df.info()
# print(self.df.head())
self.filter_table(query='')
self.update_layer_btns()
def get_station(args, input_file, stations):
df = common.load_dataframe('gcnet', input_file, 54, delim_whitespace=True)
station_number = df['station_number'][0]
if 30 <= station_number <= 32:
name = 'gcnet_lar{}'.format(station_number - 29)
station = stations[name]
else:
station = list(stations.values())[station_number]
return common.parse_station(args, station)
def init_dataframe(args, input_file):
convert_current = 1000
check_na = -999
df = common.load_dataframe('promice', input_file, 1, delim_whitespace=True)
df.index.name = 'time'
df.replace(check_na, np.nan, inplace=True)
df.loc[:, ['air_temperature', 'air_temperature_hygroclip', 'surface_temp',
'ice_temp_01', 'ice_temp_02', 'ice_temp_03', 'ice_temp_04',
'ice_temp_05', 'ice_temp_06', 'ice_temp_07', 'ice_temp_08',
'logger_temp']] += common.freezing_point_temp
df.loc[:, ['air_pressure']] *= common.pascal_per_millibar
df.loc[:, ['fan_current']] /= convert_current
df = df.where((pd.notnull(df)), get_fillvalue(args))
return df
def init_dataframe(args, input_file):
check_na = 999.0
df = common.load_dataframe('gcnet', input_file, 54, delim_whitespace=True)
df.index.name = 'time'
df['qc25'] = df['qc25'].astype(str) # To avoid 999 values marked as N/A
df.replace(check_na, np.nan, inplace=True)
temperature_keys = [
'temperature_tc_1', 'temperature_tc_2', 'temperature_cs500_1',
'temperature_cs500_2', 't_snow_01', 't_snow_02', 't_snow_03',
't_snow_04', 't_snow_05', 't_snow_06', 't_snow_07', 't_snow_08',
't_snow_09', 't_snow_10', 'max_air_temperature_1',
'max_air_temperature_2', 'min_air_temperature_1',
'min_air_temperature_2', 'ref_temperature']
df.loc[:, temperature_keys] += common.freezing_point_temp
df.loc[:, 'atmos_pressure'] *= common.pascal_per_millibar
df = df.where((pd.notnull(df)), get_fillvalue(args))
df['qc25'] = df['qc25'].astype(int) # Convert it back to int
return df