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%pylab notebook
import datetime as dt
import matplotlib.pyplot as plt
from charistools.timeSeries import TimeSeries
import pandas as pd
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#drainageids = ['AM_Vakhsh_at_Komsomolabad',
# 'IN_Hunza_at_DainyorBridge',
# 'GA_Karnali_at_Benighat',
# 'GA_Narayani_at_Devghat',
# 'GA_SaptaKosi_at_Chatara']
drainageids = ['SY_Naryn_at_NarynTown']
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fig, ax = plt.subplots(len(drainageids),1, figsize=(8,10))
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def orig_rainfile(source, id):
if 'MERRA' == source:
return "/Users/brodzik/projects/CHARIS/rainfall/MERRA/%s.MERRA_rainfall_km3.monthly.csv" % id
else:
return "/Users/brodzik/projects/CHARIS/rainfall/Aphrodite_V1101R2/monthly_by_drainage/%s.APHRODITE_rainfall_km3.monthly.v01.csv" % id
def new_rainfile(source, id):
if 'MERRA' == source:
return "/Users/brodzik/projects/CHARIS/rainfall/MERRA_rainfall_less_ET/%s.MERRA_rainfall_adj_mod16_ET_km3.monthly.csv" % id
else:
return "/Users/brodzik/projects/CHARIS/rainfall/Aphrodite_V1101R2/monthly_by_drainage_less_et/%s.APHRODITE_rainfall_adj_mod16_ET_km3.monthly.v01.csv" % id
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for source in ['MERRA', 'Aphrodite']:
print(source)
print(orig_rainfile(source, drainageids[0]))
print(new_rainfile(source, drainageids[0]))
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for i, id in enumerate(drainageids):
source = "Aphrodite"
rainfallFile = orig_rainfile(source, id)
ETFile = '/Users/brodzik/projects/CHARIS/evapotranspiration/mod16/' + id + '.mod16.ET.csv'
rainfall = TimeSeries(rainfallFile)
et = TimeSeries(ETFile)
rainfall.data['et_km3'] = et.data["et"]
rainfall.data['diff_km3'] = rainfall.data["rainfall"] - rainfall.data["et_km3"]
rainfall.data['rainfall-et_km3'] = rainfall.data['diff_km3']
rainfall.data.loc[rainfall.data['rainfall-et_km3'] < 0., 'rainfall-et_km3'] = 0.
#print(rainfall.data)
if len(drainageids) > 1:
ax[i].plot(rainfall.data['rainfall'], color='b', label="%s rainfall" % source)
ax[i].plot(rainfall.data['et_km3'], color='g', label='ET')
ax[i].plot(rainfall.data['rainfall-et_km3'], color='r', label="%s rainfall-ET" % source)
ax[i].set_title(id)
ax[i].legend()
else:
ax.plot(rainfall.data['rainfall'], color='b', label="%s rainfall" % source)
ax.plot(rainfall.data['et_km3'], color='g', label='ET')
ax.plot(rainfall.data['rainfall-et_km3'], color='r', label="%s rainfall-ET > 0" % source)
ax.plot(rainfall.data['diff_km3'], color='y', label="%s rainfall-ET" % source)
ax.set_title(id)
ax.legend()
newFile = new_rainfile(source, id)
rainfall.comments.insert(-2,"# Added ET by MJB on %s" % str(dt.datetime.now()))
rainfall.comments.insert(-2,"# ET from : %s" % ETFile)
rainfall.write(newFile)
plt.tight_layout()
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plt.savefig('/Users/brodzik/projects/CHARIS/rainfall/Aphrodite_V1101R2/%s.Aphrodite.rainfall-ET.png' % drainageids[0])
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%pwd
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%cd /Users/brodzik/projects/CHARIS/rainfall/MERRA
%ls
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file = 'AM_Vakhsh_at_Komsomolabad.MERRA_rainfall_km3.monthly.csv'
data = TimeSeries(file)
data.data
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fig, ax = plt.subplots(len(drainageids),1, figsize=(8,10))
for i, id in enumerate(drainageids):
merraRainfallFile = new_rainfile('MERRA', id)
aphRainfallFile = new_rainfile('Aphrodite', id)
merraRainfall = TimeSeries(merraRainfallFile)
aphRainfall = TimeSeries(aphRainfallFile)
ax[i].plot(aphRainfall.data['rainfall-et_km3'], color='r',
label='Aphrodite rainfall-ET')
ax[i].plot(merraRainfall.data['rainfall-et_km3'], color='k',
label='MERRA rainfall-ET')
ax[i].set_title(id)
ax[i].legend()
plt.tight_layout()
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plt.savefig('/Users/brodzik/projects/CHARIS/rainfall/MERRA_rainfall_less_ET/calibration_basins.Aphrodite.v01_vs_MERRA.rainfall-ET.png')
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