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import pandas as pd
import pastas as ps
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
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head = pd.read_csv("../data/head_wellex.csv", index_col="Date", parse_dates=True)
head = pd.read_csv("../data/head_wellex.csv", index_col="Date", parse_dates=True)
head = pd.read_csv("../data/head_wellex.csv", index_col="Date", parse_dates=True)
head = pd.read_csv("../data/head_wellex.csv", index_col="Date", parse_dates=True)
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plt.figure(figsize=(14, 9))
ax1 = plt.axes([0.125, 0.68, 0.775, 0.2])
xticks = pd.date_range(start=pd.Timestamp('1995-01-01'), end=pd.Timestamp('2015-01-01'), freq='5AS-Jan')
mlw.oseries['1995':'2015'].plot(style='k.', label='observed', xticks=xticks, markersize=8)
plt.xlim(pd.Timestamp('1995-01-01'), pd.Timestamp('2015-01-01') )
plt.setp(ax1.get_xticklabels(), visible=False)
plt.xlabel('')
plt.ylabel('m')
ax2 = plt.axes([0.125, 0.54, 0.775, 0.1])
rainw['1995':'2015'].plot(color='C0')
#evapw['1995':'2015'].plot(color='C1')
plt.ylim(0, 0.05)
plt.xlim(pd.Timestamp('1995-01-01'), pd.Timestamp('2015-01-01') )
plt.setp(ax2.get_xticklabels(), visible=False)
plt.xlabel('')
plt.ylabel('m/d')
ax2b = plt.axes([0.125, 0.4, 0.775, 0.1])
#rainw['1995':'2015'].plot(color='C0')
evapw['1995':'2015'].plot(color='C2')
plt.ylim(0, 0.05)
plt.xlim(pd.Timestamp('1995-01-01'), pd.Timestamp('2015-01-01') )
plt.setp(ax2b.get_xticklabels(), visible=False)
plt.xlabel('')
plt.ylabel('m/d')
#plt.legend()
ax3 = plt.axes([0.125, 0.26, 0.775, 0.1])
wellq[:'2015'].plot(color='C1')
plt.xlim(pd.Timestamp('1995-01-01'), pd.Timestamp('2015-01-01') )
#plt.ylim(-2.1, -0.6)
plt.xlabel('Year')
plt.ylabel('Discharge')
#plt.legend(loc='upper left')
plt.savefig('figwellinput.eps', bbox_inches='tight')
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head
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