pysilcam/silcamgui/interactive_summary.py
def load_from_timeseries(self):
        '''uses timeseries xls sheets assuming they are available'''
        timeseriesgas_file = self.stats_filename.replace('-STATS.csv', '-TIMESERIESgas.xlsx')
        timeseriesoil_file = self.stats_filename.replace('-STATS.csv', '-TIMESERIESoil.xlsx')

        gas = pd.read_excel(timeseriesgas_file, parse_dates=['Time'])
        oil = pd.read_excel(timeseriesoil_file, parse_dates=['Time'])

        self.dias = np.array(oil.columns[0:52], dtype=float)
        self.vd_oil = oil.as_matrix(columns=oil.columns[0:52])
        self.vd_gas = gas.as_matrix(columns=gas.columns[0:52])
        self.vd_total = self.vd_oil + self.vd_gas
        self.u = pd.to_datetime(oil['Time'].values).tz_localize('UTC')
        self.d50_gas = gas['D50']
        self.d50_oil = oil['D50']

        self.d50_total = np.zeros_like(self.d50_oil)
        self.cos = np.zeros_like(self.d50_total)
        for i, vd in enumerate(self.vd_total):
            self.d50_total[i] = scpp.d50_from_vd(vd, self.dias)
            self.cos[i] = scog.cos_check(self.dias, self.vd_total[i,:])
uses timeseries xls sheets assuming they are available
uses timeseries xls sheets assuming they are available
uses timeseries xls sheets assuming they are available
def load_from_timeseries(self):
        timeseriesgas_file = self.stats_filename.replace('-STATS.csv', '-TIMESERIESgas.xlsx')
        timeseriesoil_file = self.stats_filename.replace('-STATS.csv', '-TIMESERIESoil.xlsx')
        gas = pd.read_excel(timeseriesgas_file, parse_dates=['Time'])
        oil = pd.read_excel(timeseriesoil_file, parse_dates=['Time'])
        self.dias = np.array(oil.columns[0:52], dtype=float)
        self.vd_oil = oil.as_matrix(columns=oil.columns[0:52])
        self.vd_gas = gas.as_matrix(columns=gas.columns[0:52])
        self.vd_total = self.vd_oil + self.vd_gas
        self.u = pd.to_datetime(oil['Time'].values).tz_localize('UTC')
        self.d50_gas = gas['D50']
        self.d50_oil = oil['D50']
        self.d50_total = np.zeros_like(self.d50_oil)
        self.cos = np.zeros_like(self.d50_total)
        for i, vd in enumerate(self.vd_total):
            self.d50_total[i] = scpp.d50_from_vd(vd, self.dias)
            self.cos[i] = scog.cos_check(self.dias, self.vd_total[i,:])
def load_from_timeseries ( self ) : timeseriesgas_file = self . stats_filename . replace ( '-STATS.csv' , '-TIMESERIESgas.xlsx' ) timeseriesoil_file = self . stats_filename . replace ( '-STATS.csv' , '-TIMESERIESoil.xlsx' ) gas = pd . read_excel ( timeseriesgas_file , parse_dates = [ 'Time' ] ) oil = pd . read_excel ( timeseriesoil_file , parse_dates = [ 'Time' ] ) self . dias = np . array ( oil . columns [ 0 : 52 ] , dtype = float ) self . vd_oil = oil . as_matrix ( columns = oil . columns [ 0 : 52 ] ) self . vd_gas = gas . as_matrix ( columns = gas . columns [ 0 : 52 ] ) self . vd_total = self . vd_oil + self . vd_gas self . u = pd . to_datetime ( oil [ 'Time' ] . values ) . tz_localize ( 'UTC' ) self . d50_gas = gas [ 'D50' ] self . d50_oil = oil [ 'D50' ] self . d50_total = np . zeros_like ( self . d50_oil ) self . cos = np . zeros_like ( self . d50_total ) for i , vd in enumerate ( self . vd_total ) : self . d50_total [ i ] = scpp . d50_from_vd ( vd , self . dias ) self . cos [ i ] = scog . cos_check ( self . dias , self . vd_total [ i , : ] )
uses timeseries xls sheets assuming they are available
uses timeseries xls sheets assuming they are available
'''uses timeseries xls sheets assuming they are available'''
self