Python OBS Exemples

Exemple #1

Fichier : Load_FAGAALU_Data.py Projet : gregmc31/Fagaalu-Sediment-Flux

start2013, stop2013 = datetime.datetime(2013,1,1,0,0), datetime.datetime(2013,12,31,11,59)
start2014, stop2014 = datetime.datetime(2014,1,1,0,0), datetime.datetime(2014,12,31,11,59)   
PT1 = PT1.reindex(pd.date_range(start2012,stop2014,freq='15Min'))
PT3 = PT3.reindex(pd.date_range(start2012,stop2014,freq='15Min'))
Fagaalu_stage_data = Fagaalu_stage_data.reindex(pd.date_range(start2012,stop2014,freq='15Min'))


#### Import T and SSC Data
from load_from_MASTER_XL import TS3000,YSI,OBS,loadTSS
## Turbidimeter Data DAM
DAM_TS3K = TS3000(XL,'DAM-TS3K')
DAM_YSI = YSI(XL,'DAM-YSI')

## Turbidimeter Data LBJ
LBJ_YSI = YSI(XL,'LBJ-YSI')
LBJ_OBSa = OBS(XL,'LBJ-OBSa').truncate(after=dt.datetime(2013,4,1))
LBJ_OBSb = OBS(XL,'LBJ-OBSb')
LBJ_OBSa=LBJ_OBSa.rename(columns={'Turb_SS_Avg':'NTU'})
LBJ_OBSb=LBJ_OBSb.rename(columns={'Turb_SS_Mean':'NTU'})
LBJ_OBS=LBJ_OBSa.append(LBJ_OBSb)

## TSS Data, equivalent to SSC but I don't want to change all the code and file names
TSSXL = pd.ExcelFile(datadir+'SSC/TSS_grab_samples.xlsx')
TSS = loadTSS(TSSXL,'ALL_MASTER')
TSS= TSS[TSS['TSS (mg/L)']>0]


#### Import NUTRIENT Data
from load_from_MASTER_XL import loadNUTES1,loadNUTES2and3
##NUTRIENTS1 (first field season)
NUTESXL = pd.ExcelFile(datadir+'NUTRIENTS/NUTRIENTS1.xlsx')

Exemple #2

Fichier : Load_FAGAALU_Data.py Projet : gregmc31/Fagaalu-Sediment-Flux

start2014, stop2014 = datetime.datetime(2014, 1, 1, 0, 0), datetime.datetime(
    2014, 12, 31, 11, 59)
PT1 = PT1.reindex(pd.date_range(start2012, stop2014, freq='15Min'))
PT3 = PT3.reindex(pd.date_range(start2012, stop2014, freq='15Min'))
Fagaalu_stage_data = Fagaalu_stage_data.reindex(
    pd.date_range(start2012, stop2014, freq='15Min'))

#### Import T and SSC Data
from load_from_MASTER_XL import TS3000, YSI, OBS, loadTSS
## Turbidimeter Data DAM
DAM_TS3K = TS3000(XL, 'DAM-TS3K')
DAM_YSI = YSI(XL, 'DAM-YSI')

## Turbidimeter Data LBJ
LBJ_YSI = YSI(XL, 'LBJ-YSI')
LBJ_OBSa = OBS(XL, 'LBJ-OBSa').truncate(after=dt.datetime(2013, 4, 1))
LBJ_OBSb = OBS(XL, 'LBJ-OBSb')
LBJ_OBSa = LBJ_OBSa.rename(columns={'Turb_SS_Avg': 'NTU'})
LBJ_OBSb = LBJ_OBSb.rename(columns={'Turb_SS_Mean': 'NTU'})
LBJ_OBS = LBJ_OBSa.append(LBJ_OBSb)

## TSS Data, equivalent to SSC but I don't want to change all the code and file names
TSSXL = pd.ExcelFile(datadir + 'SSC/TSS_grab_samples.xlsx')
TSS = loadTSS(TSSXL, 'ALL_MASTER')
TSS = TSS[TSS['TSS (mg/L)'] > 0]

#### Import NUTRIENT Data
from load_from_MASTER_XL import loadNUTES1, loadNUTES2and3
##NUTRIENTS1 (first field season)
NUTESXL = pd.ExcelFile(datadir + 'NUTRIENTS/NUTRIENTS1.xlsx')
NUTES1 = loadNUTES1(NUTESXL, 'Data')

Exemple #3

Fichier : Load_NUUULI_Data.py Projet : CaptainAL/Fagaalu-Sediment-Flux

## STAGE DATA FOR PT's
stage_data = pd.DataFrame({'N1':PT1['stage'],'N2':PT2['stage']})

## Year Interval Times
start2012, stop2012 = dt.datetime(2012,1,7,0,0), dt.datetime(2012,12,31,11,59)    
start2013, stop2013 = dt.datetime(2013,1,1,0,0), dt.datetime(2013,12,31,11,59)
start2014, stop2014 = dt.datetime(2014,1,1,0,0), dt.datetime(2014,12,31,11,59)   
PT1 = PT1.reindex(pd.date_range(start2012,stop2014,freq='15Min'))
PT2 = PT2.reindex(pd.date_range(start2012,stop2014,freq='15Min'))
stage_data = stage_data.reindex(pd.date_range(start2012,stop2014,freq='15Min'))

#### Import T and SSC Data
from load_from_MASTER_XL import OBS,loadTSS

N1_OBS = OBS(XL,sheet='N1-OBS')
N2_OBS = OBS(XL,sheet='N2-OBS').truncate(after=dt.datetime(2014,6,7,23,59))

N1_OBS = N1_OBS.rename(columns={'Turb_SS_Min':'NTU'})
N2_OBS = N2_OBS.rename(columns={'Turb_SS_Min':'NTU'})


## TSS Data, equivalent to SSC but I don't want to change all the code and file names
TSSXL = pd.ExcelFile(datadir+'SSC/TSS_grab_samples.xlsx')
TSS = loadTSS(TSSXL,'ALL_MASTER')
TSS= TSS[TSS['TSS (mg/L)']>0]


#### Import NUTRIENT Data
from load_from_MASTER_XL import loadNUTES1,loadNUTES2and3
##NUTRIENTS1 (first field season)

Exemple #4

## Year Interval Times
start2012, stop2012 = dt.datetime(2012, 1, 7, 0,
                                  0), dt.datetime(2012, 12, 31, 11, 59)
start2013, stop2013 = dt.datetime(2013, 1, 1, 0,
                                  0), dt.datetime(2013, 12, 31, 11, 59)
start2014, stop2014 = dt.datetime(2014, 1, 1, 0,
                                  0), dt.datetime(2014, 12, 31, 11, 59)
PT1 = PT1.reindex(pd.date_range(start2012, stop2014, freq='15Min'))
PT2 = PT2.reindex(pd.date_range(start2012, stop2014, freq='15Min'))
stage_data = stage_data.reindex(
    pd.date_range(start2012, stop2014, freq='15Min'))

#### Import T and SSC Data
from load_from_MASTER_XL import OBS, loadTSS

N1_OBS = OBS(XL, sheet='N1-OBS')
N2_OBS = OBS(XL, sheet='N2-OBS')

N1_OBS = N1_OBS.rename(columns={'Turb_SS_Min': 'NTU'})
N2_OBS = N2_OBS.rename(columns={'Turb_SS_Min': 'NTU'})

## TSS Data, equivalent to SSC but I don't want to change all the code and file names
TSSXL = pd.ExcelFile(datadir + 'SSC/TSS_grab_samples.xlsx')
TSS = loadTSS(TSSXL, 'ALL_MASTER')
TSS = TSS[TSS['TSS (mg/L)'] > 0]

#### Import NUTRIENT Data
from load_from_MASTER_XL import loadNUTES1, loadNUTES2and3
##NUTRIENTS1 (first field season)
NUTESXL = pd.ExcelFile(datadir + 'NUTRIENTS/NUTRIENTS1.xlsx')
NUTES1 = loadNUTES1(NUTESXL, 'Data')

Exemple #5

Fichier : Load_NUUULI_Data.py Projet : CaptainAL/Fagaalu-Sediment-Flux

## Year Interval Times
start2012, stop2012 = dt.datetime(2012, 1, 7, 0,
                                  0), dt.datetime(2012, 12, 31, 11, 59)
start2013, stop2013 = dt.datetime(2013, 1, 1, 0,
                                  0), dt.datetime(2013, 12, 31, 11, 59)
start2014, stop2014 = dt.datetime(2014, 1, 1, 0,
                                  0), dt.datetime(2014, 12, 31, 11, 59)
PT1 = PT1.reindex(pd.date_range(start2012, stop2014, freq='15Min'))
PT2 = PT2.reindex(pd.date_range(start2012, stop2014, freq='15Min'))
stage_data = stage_data.reindex(
    pd.date_range(start2012, stop2014, freq='15Min'))

#### Import T and SSC Data
from load_from_MASTER_XL import OBS, loadTSS

N1_OBS = OBS(XL, sheet='N1-OBS')
N2_OBS = OBS(XL,
             sheet='N2-OBS').truncate(after=dt.datetime(2014, 6, 7, 23, 59))

N1_OBS = N1_OBS.rename(columns={'Turb_SS_Min': 'NTU'})
N2_OBS = N2_OBS.rename(columns={'Turb_SS_Min': 'NTU'})

## TSS Data, equivalent to SSC but I don't want to change all the code and file names
TSSXL = pd.ExcelFile(datadir + 'SSC/TSS_grab_samples.xlsx')
TSS = loadTSS(TSSXL, 'ALL_MASTER')
TSS = TSS[TSS['TSS (mg/L)'] > 0]

#### Import NUTRIENT Data
from load_from_MASTER_XL import loadNUTES1, loadNUTES2and3
##NUTRIENTS1 (first field season)
NUTESXL = pd.ExcelFile(datadir + 'NUTRIENTS/NUTRIENTS1.xlsx')

Exemple #6

Fichier : Load_FAGAALU_Data.py Projet : CaptainAL/Fagaalu-Sediment-Flux

Fagaalu_stage_data = pd.DataFrame({'LBJ':PT1['stage'],'DT':PT2['stage'],'Dam':PT3['stage']})

Fagaalu_stage_data = Fagaalu_stage_data.reindex(pd.date_range(start2012,stop2014,freq='15Min'))

#### Import T and SSC Data
from load_from_MASTER_XL import TS3000,YSI,OBS,loadSSC
## Turbidimeter Data DAM
DAM_TS3K = TS3000(XL,'DAM-TS3K')
DAM_TS3K = DAM_TS3K[DAM_TS3K>=0]
DAM_YSI = YSI(XL,'DAM-YSI')
## Correct negative NTU values
DAM_YSI['NTU'][dt.datetime(2013,6,1):dt.datetime(2013,12,31)]=DAM_YSI['NTU'][dt.datetime(2013,6,1):dt.datetime(2013,12,31)]+6

## Turbidimeter Data LBJ
LBJ_YSI = YSI(XL,'LBJ-YSI')
LBJ_OBSa = OBS(XL,'LBJ-OBSa').truncate(after=dt.datetime(2013,4,1))
LBJ_OBSb = OBS(XL,'LBJ-OBSb')
LBJ_OBSa=LBJ_OBSa.rename(columns={'Turb_SS_Avg':'FNU'})
LBJ_OBSb=LBJ_OBSb.rename(columns={'Turb_SS_Mean':'FNU'})
LBJ_OBS=LBJ_OBSa.append(LBJ_OBSb)
LBJ_OBS['FNU'] = LBJ_OBS['FNU'][LBJ_OBS['FNU']<=4000]
LBJ_OBS['FNU'] = LBJ_OBS['FNU'].interpolate(limit=2)

## Turbidimeter Data LBJ
#QUARRYxl = pd.ExcelFile(datadir+'QUARRY-OBS.xlsx')
#QUARRY_OBS = QUARRYxl.parse('QUARRY-OBS',header=4,parse_cols='A:L',parse_dates=True,index_col=0)

QUARRY_OBS = OBS(XL,'QUARRY-OBS')
QUARRY_OBS=QUARRY_OBS.rename(columns={'Turb_SS_Mean':'FNU'})
QUARRY_OBS['FNU'] = QUARRY_OBS['FNU'][QUARRY_OBS['FNU']<=4000]
QUARRY_OBS['FNU'] = QUARRY_OBS['FNU']