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%run basics
%matplotlib
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site_list = ["AdelaideRiver","AliceSpringsMulga","Calperum","CapeTribulation",
"CumberlandPlains","DalyUncleared","Gingin",
"GreatWesternWoodlands","HowardSprings","RiggsCreek","RobsonCreek",
"Samford","SturtPlains","TiTreeEast","Tumbarumba","Whroo"]
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for site in site_list:
print "Processing "+site
# file names
access_archive_mame = "../Sites/"+site+"/Data/ACCESS/"+site+"_ACCESS.nc"
access_dap_name = "../ACCESS/201505/"+site+"_ACCESS_201505.nc"
# read the files
ds_archive = qcio.nc_read_series(access_archive_mame)
ds_dap = qcio.nc_read_series(access_dap_name)
site_name = ds_archive.globalattributes["site_name"]
# get the start and end datetimes of the overlap period
dt_archive = ds_archive.series["DateTime"]["Data"]
dt_dap = ds_dap.series["DateTime"]["Data"]
start_date = max([dt_archive[0],dt_dap[0]])
end_date = min([dt_archive[-1],dt_dap[-1]])
print start_date,end_date
# get the indices of the overlap period
si_archive = qcutils.GetDateIndex(dt_archive,str(start_date))
ei_archive = qcutils.GetDateIndex(dt_archive,str(end_date))
si_dap = qcutils.GetDateIndex(dt_dap,str(start_date))
ei_dap = qcutils.GetDateIndex(dt_dap,str(end_date))
# get the data for the overlap period
ldt_archive = dt_archive[si_archive:ei_archive+1]
ldt_dap = dt_dap[si_dap:ei_dap+1]
archive = {}
dap = {}
series_list = ["Fsd","Ta","Ah","Ws","Precip"]
for item in series_list:
label = item+"_11"
archive[item],flag,attr = qcutils.GetSeriesasMA(ds_archive,label,si=si_archive,ei=ei_archive)
dap[item],flag,attr = qcutils.GetSeriesasMA(ds_dap,label,si=si_dap,ei=ei_dap)
# plot
title = site+": ACCESS Archive versus DAP"
fig = plt.figure()
plt.figtext(0.5,0.95,title,ha='center',size=16)
ax1 = plt.subplot(511)
ax1.plot(ldt_archive,archive["Fsd"],'b.',label="Archive")
ax1.plot(ldt_dap,dap["Fsd"],'r+',label="DAP")
plt.ylabel("Fsd (W/m2)")
ax2 = plt.subplot(512,sharex=ax1)
ax2.plot(ldt_archive,archive["Ta"],'b.',label="Archive")
ax2.plot(ldt_dap,dap["Ta"],'r+',label="DAP")
plt.ylabel("Ta (C)")
ax3 = plt.subplot(513,sharex=ax1)
ax3.plot(ldt_archive,archive["Ah"],'b.',label="Archive")
ax3.plot(ldt_dap,dap["Ah"],'r+',label="DAP")
plt.ylabel("Ah (g/m3)")
ax4 = plt.subplot(514,sharex=ax1)
ax4.plot(ldt_archive,archive["Ws"],'b.',label="Archive")
ax4.plot(ldt_dap,dap["Ws"],'r+',label="DAP")
plt.ylabel("Ws (m/s)")
ax5 = plt.subplot(515,sharex=ax1)
ax5.plot(ldt_archive,archive["Precip"],'b.',label="Archive")
ax5.plot(ldt_dap,dap["Precip"],'r+',label="DAP")
plt.ylabel("Precip (mm)")
plt.legend(loc='upper left',frameon=False,prop={'size':10})
figname = "plots/"+site+"_DAP_vs_Archive.png"
fig.savefig(figname,format='png')
plt.show()
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