def linkstable(): N=Nodes() a,h,F=AtoKh_old(N) H=get_quant(0.99) CP=get_quant(1.0) D=H*0.4 #for f in F: # print f[0],"to",f[1]," & ",round(h[2*f[2]]/1000,2)," & ",round(D[2*f[2]]/1000,2)," & ",round(H[2*f[2]]/1000,2)," &",round(CP[2*f[2]]/1000,2)," & ",f[1],"to",f[0]," & ",round(h[1+2*f[2]]/1000,2)," & ",round(D[1+2*f[2]]/1000,2)," & ",round(H[1+2*f[2]]/1000,2)," &",round(CP[1+2*f[2]]/1000,2),"\\\\" print "Total of today's is ", sum(biggestpair(h)) print "Total of Interme's is ", sum(biggestpair(D)) print "Total of 99p's is ", sum(biggestpair(H)) print "Total of copper plate's is ", sum(biggestpair(CP))
def show_hist(link,tit,mean=None,filename='results/copper_flows.npy',b=250): plt.close() if mean==None: mean=1.0 flows=np.load(filename) f=[] # ax=subplot(1,1,1) for i in flows[link]: if i>1 or i<-1: f.append(i/mean) zzone=[-get_quant(0.9999)[link*2+1],get_quant(0.9999)[link*2]] zone=[-get_quant(0.999)[link*2+1],get_quant(0.999)[link*2]] one=[-get_quant(0.99)[link*2+1],get_quant(0.99)[link*2]] five=[-get_quant(0.95)[link*2+1],get_quant(0.95)[link*2]] plt.close() ax=subplot(1,1,1) a=hist(f,bins=(max(f)-min(f))/(0.01*0.9/2.5),normed=0,histtype='stepfilled',color=rolor,weights=np.zeros((len(f)))+ 1./70128) plt.ylabel('P($F_l$)',size="large") plt.xlabel(r'Directed power flow [normalised]',size="large") plt.text(-1.46,.009,"France to Spain",size="large") #plt.title(r'Histogram of Power Flows : '+str(tit)) vlines(zzone[0]/mean,0,0.0015,color='r',linewidth=1.2) plt.text(zzone[0]/mean*1.05,.0018,'0.01% Q',size=11) vlines(zone[0]/mean,0,0.003,color='r',linewidth=1.2) plt.text(zone[0]/mean*1.05,.0032,'0.1% Q',size=11) vlines(one[0]/mean,0,0.004,color='r',linewidth=1.2) plt.text(one[0]/mean*1.2,.0042,'1.0% Q',size=11) vlines(five[0]/mean,0,.0055,color='r',linewidth=1.2) plt.text(five[0]/mean*1.25,.0057,'5.0% Q',size=11) vlines(five[1]/mean,0,.0055,color='r',linewidth=1.2) plt.text(five[1]/mean*0.9,.0057,'95% Q',size=11) vlines(one[1]/mean,0,0.0040,color='r',linewidth=1.2) plt.text(one[1]/mean*0.8,0.0042,'99% Q',size=11) vlines(zone[1]/mean,0,0.003,color='r',linewidth=1.2) plt.text(zone[1]/mean*0.8,0.0032,'99.9% Q',size=11) vlines(zzone[1]/mean,0,0.0015,color='r',linewidth=1.2) plt.text(zzone[1]/mean*0.99,0.0017,'99.99% Q',size=11) plt.setp(ax.get_xticklabels(), fontsize=12) # rotation='vertical', plt.setp(ax.get_yticklabels(), fontsize=12) gcf().set_size_inches([1.3*dcolwidth,1.3*dcolwidth*0.5]) plt.ylim(0,.01001) plt.xlim(-1.5,1.0) plt.grid(which="major",axis='x') # plt.axis([-5.35,5.65,0,0.5])#plt.axis([0.5, 1, 0, 38000]) plt.tight_layout() savefig('./figures/' + str(link) +'.eps', dpi=400) plt.close() #show() filename='results/99PCap_flows.npy' plt.close() if mean==None: mean=1.0 flows=np.load(filename) f=[] # ax=subplot(1,1,1) for i in flows[link]: if i>1 or i<-1: f.append(i/mean) print plt.close() ax=subplot(1,1,1) a=hist(f,bins=(max(f)-min(f))/(0.01*0.9/2.5),normed=0,histtype='stepfilled',color=rolor,weights=np.zeros((len(f)))+ 1./70128) plt.ylabel('P($F_l$)',size="large") plt.xlabel(r'Transmission Magnitude ($\langle L_{DE} \rangle$)',size="large") plt.text(-0.48,2.35,"Germany to Denmark",size="large") #plt.title(r'Histogram of Power Flows : '+str(tit)) plt.setp(ax.get_xticklabels(), fontsize=12) # rotation='vertical', plt.setp(ax.get_yticklabels(), fontsize=12) gcf().set_size_inches([1.3*dcolwidth,1.3*dcolwidth*0.5]) plt.axis([-0.5,0.4,0.0,2.5])#plt.axis([0.5, 1, 0, 38000]) plt.grid(True) plt.tight_layout() savefig('./figures/' + str(tit) +'_constr.eps', dpi=400) plt.close()