Beispiel #1
0
def getemolt_latlon(site):
    """
    get data from emolt_site
    """
    urllatlon = 'http://gisweb.wh.whoi.edu:8080/dods/whoi/emolt_site?emolt_site.SITE,emolt_site.LAT_DDMM,emolt_site.LON_DDMM,emolt_site.ORIGINAL_NAME,emolt_site.BTM_DEPTH&emolt_site.SITE='
    dataset = open_url(urllatlon+'"'+site+'"')
    print dataset
    var = dataset['emolt_site']
    lat = list(var.LAT_DDMM)
    lon = list(var.LON_DDMM)
    original_name = list(var.ORIGINAL_NAME)
    bd=fth2m(list(var.BTM_DEPTH)[0])
    #bd=fth2m(bd[0])
    return lat[0], lon[0], original_name,bd
Beispiel #2
0
from matplotlib.dates import DateFormatter
from numpy import mean
import datetime as dt
import scipy
from getdata import get_dataset, getemolt_temp
from pandas.core.common import save

for k in range(len(site)):
    if site[k][0:3]=='DMF':
        minnumperday=10 # had to use this in DMF case since they only record every two hours
        numperday=12
    else:
        minnumperday=18
        numperday=24
    [datet,temp,depth_i]=getemolt_temp(site,k,input_time=[dt.datetime(1880,1,1),dt.datetime(2020,1,1)], dep=[0,1000])
    depth=int(fth2m(mean(depth_i)))# mean depth of instrument to be added to outputfilename
    for m in range(len(temp)):
           temp[m]=(temp[m]-32.0)/1.8
    tso=Series(temp,index=datet)
    tsod=tso.resample('D',how=['count','mean','median','min','max','std'],loffset=timedelta(hours=-12))
    tsod.ix[tsod['count']<minnumperday,['mean','median','min','max','std']] = 'NaN'
    #add columns for custom date format
    tsod['yy']=tsod.index.year
    tsod['mm']=tsod.index.month
    tsod['dd']=tsod.index.day
    output_fmt=['yy','mm','dd','count','mean','median','min','max','std']
    tsodp=tsod.reindex(columns=output_fmt)  
    tsodp.to_csv(outdir+site[k]+'_wtmp_da_'+str(depth)+'.csv',index=False,header=False,na_rep='NaN',float_format='%10.2f')

    #create a monthly mean
    tsom=tso.resample('m',how=['count','mean','median','min','max','std'],kind='period')