def traverseplot(Xin,Yin,Field,name):
string,nodeind,leaf,label=TraverseTree(regTree,Xin,Field)
nband=Yin.shape[1]
k=0
for j in leaf:
Ytemp=Yin[nodeind[j],:]
Xtemp=Xin[nodeind[j],:]
Yptemp=regTreeModel.predict(Xtemp)
fitmodel=fitModelList[k]
if predind.ndim==1:
Ypnewtemp=fitmodel.predict(Xtemp[:,predind.astype(int)])
else:
Ypnewtemp=fitmodel.predict(Xtemp[:,predind[k,:].astype(int)])
rmse,rmse_band=RMSECal(Yptemp,Ytemp)
rmsenew,rmse_bandnew=RMSECal(Ypnewtemp,Ytemp)
n=nband
f, axarr = plt.subplots(int(np.ceil(n/2)), 2,figsize=(10,12))
for i in range(n):
pj=int(np.ceil(i/2))
pi=int(i%2)
axarr[pj, pi].plot(Yptemp[:,i],Ytemp[:,i],'.')
axarr[pj, pi].plot(Ypnewtemp[:,i],Ytemp[:,i],'.r')
axarr[pj, pi].set_title('cluster %s,\n cc=%.3f -> %.3f, r=%.3f -> %.3f'\
%(i,np.corrcoef(Yptemp[:,i],Ytemp[:,i])[0,1],np.corrcoef(Ypnewtemp[:,i],Ytemp[:,i])[0,1],
rmse_band[i],rmse_bandnew[i]))
plotFun.plot121line(axarr[pj, pi])
f.tight_layout()
f.suptitle(string[j],fontsize=8)
f.subplots_adjust(top=0.9)
plt.savefig(savedir+name+"_node%i"%j)
plt.close()
k=k+1
def Regression_plot(Yp, Ytest, doplot):
rmse, rmse_band = RMSECal(Yp, Ytest)
if doplot == 1: # box plot for all bands
nband = Yp.shape[1]
plt.figure()
plt.boxplot(Yp - Ytest)
#plt.title("Pred - Truth, total rmse %.3f"%np.mean(rmse_band))
elif doplot == 2:
nband = Yp.shape[1]
n = nband
f, axarr = plt.subplots(int(np.ceil(n / 2)), 2)
f.tight_layout()
f.subplots_adjust(top=0.9)
#plt.suptitle('Silhouette Coefficient=%s'%score)
for i in range(n):
pj = int(np.ceil(i / 2))
pi = int(i % 2)
axarr[pj, pi].plot(Ytest[:, i], Yp[:, i], '.')
axarr[pj, pi].set_title('cluster %s,\n corrcoef=%.3f, rmse=%.3f'\
%(i,np.corrcoef(Ytest[:,i],Yp[:,i])[0,1],rmse_band[i]))
plotFun.plot121line(axarr[pj, pi])
f.tight_layout()
def Regression_plot(Yp,Ytest,doplot):
rmse,rmse_band=RMSECal(Yp,Ytest)
if doplot==1: # box plot for all bands
nband = Yp.shape[1]
plt.figure()
plt.boxplot(Yp-Ytest)
#plt.title("Pred - Truth, total rmse %.3f"%np.mean(rmse_band))
elif doplot==2:
nband = Yp.shape[1]
n=nband
f, axarr = plt.subplots(int(np.ceil(n/2)), 2)
f.tight_layout()
f.subplots_adjust(top=0.9)
#plt.suptitle('Silhouette Coefficient=%s'%score)
for i in range(n):
pj=int(np.ceil(i/2))
pi=int(i%2)
axarr[pj, pi].plot(Ytest[:,i],Yp[:,i],'.')
axarr[pj, pi].set_title('cluster %s,\n corrcoef=%.3f, rmse=%.3f'\
%(i,np.corrcoef(Ytest[:,i],Yp[:,i])[0,1],rmse_band[i]))
plotFun.plot121line(axarr[pj, pi])
f.tight_layout()
def traverseplot(Xin, Yin, Field, name):
string, nodeind, leaf, label = TraverseTree(regTree, Xin, Field)
nband = Yin.shape[1]
k = 0
for j in leaf:
Ytemp = Yin[nodeind[j], :]
Xtemp = Xin[nodeind[j], :]
Yptemp = regTreeModel.predict(Xtemp)
fitmodel = fitModelList[k]
if predind.ndim == 1:
Ypnewtemp = fitmodel.predict(Xtemp[:, predind.astype(int)])
else:
Ypnewtemp = fitmodel.predict(Xtemp[:,
predind[k, :].astype(int)])
rmse, rmse_band = RMSECal(Yptemp, Ytemp)
rmsenew, rmse_bandnew = RMSECal(Ypnewtemp, Ytemp)
n = nband
f, axarr = plt.subplots(int(np.ceil(n / 2)), 2, figsize=(10, 12))
for i in range(n):
pj = int(np.ceil(i / 2))
pi = int(i % 2)
axarr[pj, pi].plot(Yptemp[:, i], Ytemp[:, i], '.')
axarr[pj, pi].plot(Ypnewtemp[:, i], Ytemp[:, i], '.r')
axarr[pj, pi].set_title('cluster %s,\n cc=%.3f -> %.3f, r=%.3f -> %.3f'\
%(i,np.corrcoef(Yptemp[:,i],Ytemp[:,i])[0,1],np.corrcoef(Ypnewtemp[:,i],Ytemp[:,i])[0,1],
rmse_band[i],rmse_bandnew[i]))
plotFun.plot121line(axarr[pj, pi])
f.tight_layout()
f.suptitle(string[j], fontsize=8)
f.subplots_adjust(top=0.9)
plt.savefig(savedir + name + "_node%i" % j)
plt.close()
k = k + 1
