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Results.py
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# -*- coding: utf-8 -*-
"""
Created on Thu Apr 14 10:34:00 2016
@author: vagrant
"""
import pickle
import os
import numpy as np
import matplotlib.pylab as plt
import pandas as pd
from dateutil.relativedelta import relativedelta
def C_balance(gy, de, ro, pe):
#temp
s=(ro.SH + ro.H + ro.LH + ro.F + ro.L)*10000.0
#------
soil = (de.cwdSto + (ro.SH + ro.H + ro.LH + ro.F + ro.L)*10000.0 + pe.peatStorage)*ro.massToC
standTot = (gy.BiBark + gy.BiBranch + gy.BiFoliage + gy.RootMass + gy.weedAbove + gy.weedBelow)*ro.massToC
standTot2 = (gy.BiStem + gy.BiBark + gy.BiBranch + gy.BiFoliage + gy.RootMass + gy.weedAbove + gy.weedBelow)*ro.massToC
bal = (soil[-1] -soil[0]) + (standTot[-1] - standTot[0])
soil_balance = soil[-1] -soil[0]
total_balance = (soil[-1] -soil[0]) + (standTot2[-1] - standTot2[0])
#print bal, (s[-1]-s[0])*ro.massToC , (pe.peatStorage[-1]-pe.peatStorage[0])*ro.massToC, sum(ro.miner)*ro.massToC
return soil_balance, bal, total_balance
def save_results(gy, de,ro, pe, N=None, P=None, K=None, fold= None, fname =None):
if fold==None:
fold="C:\Apps\WinPython-64bit-2.7.10.3\IPEWG\\"
if fname==None:
fname = "PDSS_results.p"
data={}
data['gy'] = gy.__dict__
data['de'] = de.__dict__
data['ro'] = ro.__dict__
data['pe'] = pe.__dict__
if N != None: data['N'] = N.__dict__
if P != None: data['P'] = P.__dict__
if K != None: data['K'] = K.__dict__
with open(fold+fname, 'wb') as wfp:
pickle.dump(data, wfp)
print ('PDSS simulation saved to ', fname)
for i in plt.get_fignums():
plt.figure(i)
plt.savefig(fold+'figure%d.png' % i)
def print_test(fold=None, fname=None):
if fname==None:
fname = "PDSS_results.p"
with open(fold+fname, 'rb') as wfp:
aaa=pickle.load(wfp)
return aaa
def save_nbal(gy, pe, N=None, P=None, K=None, fold=None):
if fold==None:
fold="C:\Apps\WinPython-64bit-2.7.10.3\IPEWG\\"
nb=pd.DataFrame(np.zeros((len(N.totalDemand),8)), columns = ['Nsupply', 'Ndemand', 'Psupply', 'Pdemand', 'Ksupply', 'Kdemand','Subs', 'Vol'])
if N != None:
nb['Nsupply']=N.totalSupply; nb['Ndemand']=N.totalDemand;
if P != None:
nb['Psupply']=P.totalSupply; nb['Pdemand']=P.totalDemand
if K != None:
nb['Ksupply']=K.totalSupply; nb['Kdemand']=K.totalDemand
ul = int(gy.g['DiamUpperLimit'][0]); nsteps = len(gy.age)
Vdist = np.reshape(gy.Vdist, (nsteps, ul))
nb['Vol'] = np.sum(Vdist, axis=1)
nb['Subs']= pe.subsidence
nb.to_csv(fold+'NutBal.csv')
def writeToPickle(pe, gy, pg, bal, Mrate, N, P, K, fname=None, measS=None):
if fname == None:
fname = "/home/vagrant/.spyder2/Plantation/MonteCarlo3.p"
data = {'simNo':[], 'annualSubsidence':[], 'meanSubs':[], 'subsidence':[],'rhoIni':[], 'rhoFin':[], 'siteIndex':[],
'Mrate': [], 'oxidShare':[], 'dwt':[], 'bal':[], 'measS':[],
'Nsupply':[], 'Psupply':[], 'Ksupply':[],'Ndemand':[], 'Pdemand':[], 'Kdemand':[],
'Ntreesupply':[], 'Ptreesupply':[], 'Ktreesupply':[],'Ntreedemand':[], 'Ptreedemand':[], 'Ktreedemand':[],
}
if os.path.exists(fname):
with open(fname,'rb') as rfp:
data = pickle.load(rfp)
else:
fi = open(fname, 'w')
pickle.dump(data, fi)
fi.close()
data['simNo'].append(len(data['siteIndex']))
data['annualSubsidence'].append(pe.annualSubsidence)
data['meanSubs'].append(np.mean(pe.annualSubsidence))
data['subsidence'].append(pe.subsidence)
data['rhoIni'].append(pe.peatRhoInit)
data['rhoFin'].append(pe.peatRhoFinal)
data['siteIndex'].append(gy.appSI)
data['Mrate'].append(Mrate)
data['oxidShare'].append(pe.oxidShare)
data['dwt'].append(pe.dwt)
data['bal'].append(bal)
data['measS'].append(measS)
data['Ndemand'].append(N.totalDemand)
data['Pdemand'].append(P.totalDemand)
data['Kdemand'].append(K.totalDemand)
data['Nsupply'].append(N.totalSupply)
data['Psupply'].append(P.totalSupply)
data['Ksupply'].append(K.totalSupply)
data['Ntreedemand'].append(N.treeDemand)
data['Ptreedemand'].append(P.treeDemand)
data['Ktreedemand'].append(K.treeDemand)
data['Ntreesupply'].append(N.treeSupply)
data['Ptreesupply'].append(P.treeSupply)
data['Ktreesupply'].append(K.treeSupply)
evans_subs = np.mean(pe.dwt)*-0.0334-1.88
with open(fname,'wb') as wfp:
pickle.dump(data, wfp)
print (np.round(np.mean(pe.annualSubsidence),2), np.mean(measS),
np.round(np.mean(pe.dwt),2), np.round(evans_subs,2))
def writeToPickle2(pe, gy, pg, bal, Mrate, N, P, K, fname=None, measS=None):
if fname == None:
fname = "/home/vagrant/.spyder2/Plantation/MonteCarlo3.p"
data = {'simNo':[], 'annualSubsidence':[], 'meanSubs':[], 'subsidence':[],'rhoIni':[], 'rhoFin':[], 'siteIndex':[],
'Mrate': [], 'oxidShare':[], 'dwt':[], 'bal':[], 'measS':[],
'Nsupply':[], 'Psupply':[], 'Ksupply':[],'Ndemand':[], 'Pdemand':[], 'Kdemand':[],
'Ntreesupply':[], 'Ptreesupply':[], 'Ktreesupply':[],'Ntreedemand':[], 'Ptreedemand':[], 'Ktreedemand':[],
'standLitter':[], 'weedLitter':[], 'CWD':[]}
if os.path.exists(fname):
with open(fname,'rb') as rfp:
data = pickle.load(rfp)
else:
fi = open(fname, 'wb')
pickle.dump(data, fi)
fi.close()
data['simNo'].append(len(data['siteIndex']))
data['annualSubsidence'].append(pe.annualSubsidence)
data['meanSubs'].append(np.mean(pe.annualSubsidence))
data['subsidence'].append(pe.subsidence)
data['rhoIni'].append(pe.peatRhoInit)
data['rhoFin'].append(pe.peatRhoFinal)
data['siteIndex'].append(gy.appSI)
data['Mrate'].append(Mrate)
data['oxidShare'].append(pe.oxidShare)
data['dwt'].append(pe.dwt)
data['bal'].append(bal)
data['measS'].append(measS)
data['Ndemand'].append(N.totalDemand)
data['Pdemand'].append(P.totalDemand)
data['Kdemand'].append(K.totalDemand)
data['Nsupply'].append(N.totalSupply)
data['Psupply'].append(P.totalSupply)
data['Ksupply'].append(K.totalSupply)
data['Ntreedemand'].append(N.treeDemand)
data['Ptreedemand'].append(P.treeDemand)
data['Ktreedemand'].append(K.treeDemand)
data['Ntreesupply'].append(N.treeSupply)
data['Ptreesupply'].append(P.treeSupply)
data['Ktreesupply'].append(K.treeSupply)
standlitter = gy.FineRLitL + gy.RootLitD + gy.BrLitD + gy.BrLitL + gy.BaLitD + gy.BaLitL + gy.FoLitD + gy.FoLitL # foliage litter from living trees, kg ha-1 timestep-1
data['standLitter'].append(standlitter)
weedlitter = gy.weedALitL + gy.weedBLitL + gy.weedALitD + gy.weedBLitD # below ground weed litter from dead weeds, kg ha-1 timestep-1
data['weedLitter'].append(weedlitter)
data['CWD'].append(gy.CWD)
with open(fname,'wb') as wfp:
pickle.dump(data, wfp)
evans_subs = np.mean(pe.dwt)*-0.0334-1.88
print (np.round(np.mean(pe.annualSubsidence),2), np.mean(measS),
np.round(np.mean(pe.dwt),2), np.round(evans_subs,2))
def readFromPickle(fname=None):
if fname == None:
fname = "/home/vagrant/.spyder2/Plantation/MonteCarlo4.p"
# Re-load our database
with open(fname,'rb') as rfp:
data = pickle.load(rfp)
#print data
#for p in range(len(data['siteIndex'])):
# print data['siteIndex'][p]
print (np.mean(data['meanSubs']), np.std(data['meanSubs']))
#print(data[0][1]['annualSubsidence'])
def spatial_out(gy,de,ro,pe,P):
"""
as time series:
-subsidence
-potential vol growth
-c balance (cumulative)
-p balance (instantanous)
"""
s=(ro.SH + ro.H + ro.LH + ro.F + ro.L)*10000.0
soil = (de.cwdSto + (ro.SH + ro.H + ro.LH + ro.F + ro.L)*10000.0 + pe.peatStorage)*ro.massToC
standTot = (gy.BiBark + gy.BiBranch + gy.BiFoliage + gy.RootMass + gy.weedAbove + gy.weedBelow)*ro.massToC
Cbal = (soil -soil[0]) + (standTot - standTot[0])
Pbal = P.totalSupply-P.totalDemand
Ps=P.totalSupply
s= pe.subsidence; v=gy.V; mv=gy.MV; sur=gy.Survival
return s,v, mv, sur, Cbal, Pbal, Ps
def saveSubsidence(pe, datesInp=None, start= None, nsteps= None, midDwtArr= None, sideDwtArr=None, fold = 'C:\Apps\WinPython-64bit-2.7.10.3\IPEWG\\', fname= 'subs.p'):
data={}
if datesInp is not None: data['dates']=datesInp
if datesInp is None:
end = start + relativedelta(months=+nsteps-1)
dr=pd.date_range(start,end)
dfD=pd.DataFrame(range(len(dr)),index=dr); dfD=dfD.resample('M', how='mean')
datesInp=dfD.index.values; data['dates']=datesInp
data['subs']=pe.subsidence
if midDwtArr is not None: data['midDwtArr'] = midDwtArr
if sideDwtArr is not None: data['sideDwtArr'] = sideDwtArr
with open(fold+fname,'wb') as wfp:
pickle.dump(data, wfp)