def qite_plot(RR,TT,EE,FF,FCI,xrng,yrng,fname):
x0 = 7.00
xfig = 1.00*2*x0
yfig = 0.75*1*x0
fig,pan = plt.subplots(1,2,figsize=(xfig,yfig))
for js in range(2):
pan[js].get_xaxis().set_tick_params(which='both',direction='in',labelsize=18)
pan[js].get_yaxis().set_tick_params(which='both',direction='in',labelsize=18)
pan[0].set_xlabel(r'$\displaystyle{\beta}$',fontsize=18)
pan[0].set_ylabel(r'$\displaystyle{E(\beta)}$',fontsize=18)
pan[0].set_xlim(xrng[0])
pan[0].set_ylim(yrng[0])
pan[1].set_xlabel(r'$\displaystyle{\beta}$',fontsize=18)
pan[1].set_ylabel(r'$\displaystyle{|\langle \Psi_{0} | \Psi_\beta \rangle|}$',fontsize=18)
pan[1].set_xlim(xrng[1])
pan[1].set_ylim(yrng[1])
for ip in range(2):
u = np.arange(round(np.min(xrng[ip])),round(np.max(xrng[ip])),0.05)
v = [FCI[ip]]*len(u)
st.Palette[st.fci].dataplot(pan[ip],u,v,spline=True,connected=False)
for jR in range(len(Rlst)):
Lx = np.max(xrng[0])-np.min(xrng[0])
Ly = np.max(yrng[0])-np.min(yrng[0])
mask = st.equidistant_points(TT[:,jR],Lx,EE[:,jR],Ly*3.0,0.015)
st.Palette[jR].dataplot(pan[0],TT[mask,jR],EE[mask,jR] ,spline=True ,connected=False)
st.Palette[jR].dataplot(pan[0],TT[mask,jR],EE[mask,jR] ,spline=False,connected=False)
st.Palette[jR].dataplot(pan[0],TT[mask,jR],EE[mask,jR]-5e3,spline=False,connected=True)
Lx = np.max(xrng[1])-np.min(xrng[1])
Ly = np.max(yrng[1])-np.min(yrng[1])
mask = st.equidistant_points(TT[:,jR],Lx,FF[:,jR],Ly*3.0,0.015)
pt0,ps0 = st.Palette[jR].pt,st.Palette[jR].ps
st.Palette[jR].pt,st.Palette[jR].ps = '.',0
st.Palette[jR].dataplot(pan[1],TT[:,jR],FF[:,jR] ,spline=False,connected=True)
st.Palette[jR].pt,st.Palette[jR].ps = pt0,ps0
st.Palette[jR].dataplot(pan[1],TT[mask,jR],FF[mask,jR] ,spline=False,connected=False)
st.Palette[jR].dataplot(pan[1],TT[mask,jR],FF[mask,jR]-5e3,spline=False,connected=True)
x0 = -0.05
dx = 2.30
y0 = 1.00
dy = 0.10
order = [0]+[3*(x+1) for x in range(len(Rlst))]
nord = len(order)
#order = order[:nord-1]
lgd = st.make_legend(pan[0],order,ncol=range(len(Rlst)),bbox_to_anchor=(x0,y0,dx,dy),\
loc=3,mode="expand",borderaxespad=1,fontsize=18,handlelength=4,numpoints=2)
fig.savefig(fname,format='eps',bbox_inches='tight')
os.system('ps2epsi '+fname)
os.system('mv '+fname+'i '+fname)
def qite_plot(RR, TT, EE, FF, FCI, xrng, yrng, fname):
x0 = 7.00
xfig = 1.00 * 1 * x0
yfig = 0.75 * 1 * x0
fig, pan = plt.subplots(1, 1, figsize=(xfig, yfig))
pan.get_xaxis().set_tick_params(which='both', direction='in', labelsize=20)
pan.get_yaxis().set_tick_params(which='both', direction='in', labelsize=20)
pan.set_xlabel(r'$\displaystyle{\beta}$', fontsize=20)
pan.set_ylabel(r'$\displaystyle{E(\beta)}$', fontsize=20)
pan.set_xlim(xrng[0])
pan.set_ylim(yrng[0])
ip = 0
u = np.arange(round(np.min(xrng[ip])), round(np.max(xrng[ip])), 0.05)
v = [FCI[ip]] * len(u)
st.Palette[st.fci].dataplot(pan, u, v, spline=True, connected=False)
for jR in range(len(Rlst)):
Lx = np.max(xrng[0]) - np.min(xrng[0])
Ly = np.max(yrng[0]) - np.min(yrng[0])
mask = st.equidistant_points(TT[:, jR], Lx, EE[:, jR], Ly * 3.0, 0.015)
st.Palette[jR].dataplot(pan,
TT[mask, jR],
EE[mask, jR],
spline=True,
connected=False)
st.Palette[jR].dataplot(pan,
TT[mask, jR],
EE[mask, jR],
spline=False,
connected=False)
st.Palette[jR].dataplot(pan,
TT[mask, jR],
EE[mask, jR] - 5e3,
spline=False,
connected=True)
plt.text(3.55, -2.05, r'$(a)$', fontsize=21)
x0 = -0.04
dx = 1.08
y0 = 1.00
dy = 0.10
order = [0] + [3 * (x + 1) for x in range(len(Rlst))]
lgd = st.make_legend(pan,order,ncol=range(len(Rlst)),bbox_to_anchor=(x0,y0,dx,dy),\
loc=3,mode="expand",borderaxespad=1,fontsize=14,handlelength=3,numpoints=2)
fig.savefig(fname, format='eps', bbox_inches='tight')
os.system('ps2epsi ' + fname)
os.system('mv ' + fname + 'i ' + fname)
def qite_plot(RR, TT, EE, FF, FCI, xrng, yrng, fname):
x0 = 7.00
xfig = 1.00 * 2 * x0
yfig = 0.75 * 1 * x0
fig, pan = plt.subplots(1, 2, figsize=(xfig, yfig))
for js in range(2):
pan[js].get_xaxis().set_tick_params(which='both',
direction='in',
labelsize=18)
pan[js].get_yaxis().set_tick_params(which='both',
direction='in',
labelsize=18)
pan[0].set_xlabel(r'$\displaystyle{\beta}$', fontsize=18)
pan[0].set_ylabel(
r'$\displaystyle{E_{QITE}(\beta)}, \, E_{Q-Lanz}(\beta)$', fontsize=18)
pan[0].set_xlim(xrng[0])
pan[0].set_ylim(yrng[0])
pan[1].set_xlabel(r'$\displaystyle{\beta}$', fontsize=18)
pan[1].set_ylabel(
r'$\displaystyle{E_{QITE}(\beta)}, \, E_{Q-Lanz}(\beta)$', fontsize=18)
pan[1].set_xlim(xrng[1])
pan[1].set_ylim(yrng[1])
for ip in range(2):
u = np.arange(round(np.min(xrng[ip])), round(np.max(xrng[ip])), 0.05)
v = [FCI[ip]] * len(u)
st.Palette[st.fci].dataplot(pan[ip],
u,
v,
spline=True,
connected=False)
ipan = 0
for jR in range(len(Rlst)):
kR = jR + 10
Lx = np.max(xrng[0]) - np.min(xrng[0])
Ly = np.max(yrng[0]) - np.min(yrng[0])
mask = st.equidistant_points(TT[:, jR], Lx, EE[:, jR], Ly * 3.0, 0.015)
st.Palette[jR].dataplot(pan[ipan],
TT[mask, jR],
EE[mask, jR],
spline=True,
connected=False)
st.Palette[jR].dataplot(pan[ipan],
TT[mask, jR],
EE[mask, jR],
spline=False,
connected=False)
st.Palette[jR].dataplot(pan[ipan],
TT[mask, jR],
EE[mask, jR] - 5e3,
spline=False,
connected=True)
# for the legend
st.Palette[jR].dataplot(pan[0],
TT[mask, jR],
EE[mask, jR] - 5e3,
spline=True,
connected=False)
st.Palette[jR].dataplot(pan[0],
TT[mask, jR],
EE[mask, jR] - 5e3,
spline=False,
connected=False)
st.Palette[jR].dataplot(pan[0],
TT[mask, jR],
EE[mask, jR] - 5e3,
spline=False,
connected=True)
Lx = np.max(xrng[1]) - np.min(xrng[1])
Ly = np.max(yrng[1]) - np.min(yrng[1])
SS = [TT[2 * i, jR] for i in range(FF.shape[0])]
SS = np.asarray(SS)
mask = st.equidistant_points(SS, Lx, FF[:, jR], Ly * 3.0, 0.015)
pt0, ps0 = st.Palette[kR].pt, st.Palette[kR].ps
st.Palette[kR].pt, st.Palette[kR].ps = '.', 0
st.Palette[kR].dataplot(pan[ipan],
SS,
FF[:, jR],
spline=False,
connected=True)
st.Palette[kR].pt, st.Palette[kR].ps = pt0, ps0
st.Palette[kR].dataplot(pan[ipan],
SS[mask],
FF[mask, jR],
spline=False,
connected=False)
st.Palette[kR].dataplot(pan[ipan],
SS[mask],
FF[mask, jR] - 5e3,
spline=False,
connected=True)
# for the legend
st.Palette[kR].dataplot(pan[0],
SS,
FF[:, jR] - 5e3,
spline=False,
connected=True)
st.Palette[kR].dataplot(pan[0],
SS[mask],
FF[mask, jR] - 5e3,
spline=False,
connected=False)
st.Palette[kR].dataplot(pan[0],
SS[mask],
FF[mask, jR] - 5e3,
spline=False,
connected=True)
ipan += 1
x0 = -0.04
dx = 2.28
y0 = 1.002
dy = 0.10
order = [0, 3, 9, 15, 16]
lgd = st.make_legend(pan[0],
order,
ncol=5,
bbox_to_anchor=(x0, y0, dx, dy),
loc=3,
mode="expand",
borderaxespad=1,
fontsize=17,
handlelength=3,
numpoints=2)
fig.savefig(fname, format='eps', bbox_inches='tight')
os.system('ps2epsi ' + fname)
os.system('mv ' + fname + 'i ' + fname)
def qite_plot(RR,TT,EE,FF,FCI,xrng,yrng,gamma,fname):
x0 = 7.00
xfig = 1.00*1*x0
yfig = 0.75*1*x0
fig,pan = plt.subplots(1,1,figsize=(xfig,yfig))
pan.get_xaxis().set_tick_params(which='both',direction='in',labelsize=18)
pan.get_yaxis().set_tick_params(which='both',direction='in',labelsize=18)
'''
pan.set_xlabel(r'$\displaystyle{\beta}$',fontsize=14)
pan.set_ylabel(r'$\displaystyle{C(\beta)}$',fontsize=14)
pan.set_xlim(xrng[0])
pan.set_ylim(yrng[0])
'''
pan.set_xlabel(r'$\displaystyle{\beta}$',fontsize=18)
pan.set_ylabel(r'$P(C=C_{max})$',fontsize=18)
pan.set_xlim(xrng[1])
pan.set_ylim(yrng[1])
pan.set_yticks([0,0.2,0.4,0.6,0.8,1.0,1.2000000001],[r'$\displaystyle{\phantom{-}0.0}$',
r'$\displaystyle{\phantom{-}0.2}$',
r'$\displaystyle{\phantom{-}0.4}$',
r'$\displaystyle{\phantom{-}0.6}$',
r'$\displaystyle{\phantom{-}0.8}$',
r'$\displaystyle{\phantom{-}1.0}$',
r'$\displaystyle{\phantom{-}1.2]$'])
#for ip in range(2):
ip=1
u = np.arange(0,16,0.1) #round(np.min(xrng[ip])),round(np.max(xrng[ip])),0.05)
v = [FCI[ip]]*len(u)
st.Palette[st.fci].dataplot(pan,u,v,spline=False,connected=True)
for jR in range(len(Rlst)):
'''
Lx = np.max(xrng[0])-np.min(xrng[0])
Ly = np.max(yrng[0])-np.min(yrng[0])
mask = st.equidistant_points(TT[:,jR],Lx,EE[:,jR],Ly*3.0,0.01)
st.Palette[jR].dataplot(pan[0],TT[ :,jR],EE[ :,jR] ,spline=True ,connected=False)
st.Palette[jR].dataplot(pan[0],TT[mask,jR],EE[mask,jR] ,spline=False,connected=False)
st.Palette[jR].dataplot(pan[0],TT[mask,jR],EE[mask,jR]-5e3,spline=False,connected=True)
'''
Lx = np.max(xrng[1])-np.min(xrng[1])
Ly = np.max(yrng[1])-np.min(yrng[1])
mask = st.equidistant_points(TT[:,jR],Lx,FF[:,jR],Ly*3.0,0.006)
st.Palette[jR].dataplot(pan,TT[ :,jR],FF[ :,jR] ,spline=False,connected=True)
st.Palette[jR].dataplot(pan,TT[mask,jR],FF[mask,jR] ,spline=False,connected=False)
st.Palette[jR].dataplot(pan,TT[mask,jR],FF[mask,jR]-5e3,spline=False,connected=True)
# graph inset
from matplotlib.patches import Polygon
ins = plt.axes([0.48,0.10,0.40,0.40],aspect='equal')
nv,E,cut = gamma
ins.axis("off")
ins.set_xlim([-1.2,1.2])
ins.set_ylim([-1.2,1.2])
u = np.linspace(-np.pi,np.pi,100)
v = np.sin(u)
u = np.cos(u)
st.Palette[st.link].dataplot(ins,u, v,spline=False,connected=True)
st.Palette[st.link].dataplot(ins,u,-v,spline=False,connected=True)
for (iv,jv) in E:
phii = 2*np.pi*float(iv)/float(nv)
phij = 2*np.pi*float(jv)/float(nv)
xi,xj = np.cos(phii),np.cos(phij)
yi,yj = np.sin(phii),np.sin(phij)
u = np.linspace(xi,xj,10)
v = np.linspace(yi,yj,10)
idx = st.linkin
print iv,jv,iv in cut,jv in cut
if((iv in cut) and (not jv in cut)): idx = st.linkbtw
if((jv in cut) and (not iv in cut)): idx = st.linkbtw
st.Palette[idx].dataplot(ins,u,v,spline=False,connected=True)
for iv in range(nv):
if(iv in cut): idx = st.vertexin
else: idx = st.vertexout
phi = 2*np.pi*float(iv)/float(nv)
st.Palette[idx].dataplot(ins,[np.cos(phi)],[np.sin(phi)],spline=False,connected=False)
# figure label
plt.text(1.05,3.15,r'$(b)$',fontsize=21)
x0 = -0.04
dx = 1.08
y0 = 1.002
dy = 0.10
order = [0]+[3*(x+1) for x in range(len(Rlst))]
lgd = st.make_legend(pan,order,ncol=range(len(Rlst)),bbox_to_anchor=(x0,y0,dx,dy),\
loc=3,mode="expand",borderaxespad=1,fontsize=14,handlelength=3,numpoints=2)
fig.savefig(fname,format='eps',bbox_inches='tight')
os.system('ps2epsi '+fname)
os.system('mv '+fname+'i '+fname)