def plot(self, axes, labels, restocolor) :
"""
Plot the fractal on a pie chart
Parameters
axes : tuple of Axis object
the axis to draw the lower and upper leaflet pie chart
labels : tuple of strings
the labels to draw next to each axis
restocolor : list of int
residues to color
"""
def draw_pies(axis,fractal,cent,rad,reverseY) :
c = plt.Circle(cent.T,rad,ec='k',fc=None,fill=False)
axis.add_patch(c)
fractal2 = (fractal - self.minval) / (self.maxval - self.minval)
for val,e1,e2 in zip(fractal2,self.edges[:-1],self.edges[1:]) :
w = patches.Wedge(cent.T,rad,e1,e2,ec='k',fc='k',alpha=0.1)
axis.add_patch(w)
if reverseY :
x = -rad*np.cos(e1*np.pi/180.0)
y = rad*np.sin(e1*np.pi/180.0)
ee2 = 180.0*np.arctan2(y,x)/np.pi
x = -rad*np.cos(e2*np.pi/180.0)
y = rad*np.sin(e2*np.pi/180.0)
ee1 = 180.0*np.arctan2(y,x)/np.pi
w = patches.Wedge(cent.T,rad,ee1,ee2,ec=plt.cm.RdYlBu_r(val),fc=plt.cm.RdYlBu_r(val),width=5)
else :
w = patches.Wedge(cent.T,rad,e1,e2,ec=plt.cm.RdYlBu_r(val),fc=plt.cm.RdYlBu_r(val),width=5)
axis.add_patch(w)
if self.fractal_low is None : return
gpcr_lib.plot_density_xray(axes[0],0,"",0,0,self.xray,"low","Intra.",number=None,plotn=False,drawchol=False, specialres=restocolor)
gpcr_lib.plot_density_xray(axes[1],0,"",0,0,self.xray,"upp","Extra.",number=None,plotn=False,drawchol=False, specialres=restocolor)
rad = 30.0
cent = np.array([0.0,0.0])
draw_pies(axes[0],self.fractal_low,cent,rad,False)
draw_pies(axes[1],self.fractal_upp,cent,rad,True)
for a,l in zip(axes,labels) :
a.text(-40,38,l)
a.set_xticklabels([])
a.set_yticklabels([])
def plot(self, axes, labels, restocolor):
"""
Plot the fractal on a pie chart
Parameters
axes : tuple of Axis object
the axis to draw the lower and upper leaflet pie chart
labels : tuple of strings
the labels to draw next to each axis
restocolor : list of int
residues to color
"""
def draw_pies(axis, fractal, cent, rad, reverseY):
c = plt.Circle(cent.T, rad, ec='k', fc=None, fill=False)
axis.add_patch(c)
fractal2 = (fractal - self.minval) / (self.maxval - self.minval)
for val, e1, e2 in zip(fractal2, self.edges[:-1], self.edges[1:]):
w = patches.Wedge(cent.T,
rad,
e1,
e2,
ec='k',
fc='k',
alpha=0.1)
axis.add_patch(w)
if reverseY:
x = -rad * np.cos(e1 * np.pi / 180.0)
y = rad * np.sin(e1 * np.pi / 180.0)
ee2 = 180.0 * np.arctan2(y, x) / np.pi
x = -rad * np.cos(e2 * np.pi / 180.0)
y = rad * np.sin(e2 * np.pi / 180.0)
ee1 = 180.0 * np.arctan2(y, x) / np.pi
w = patches.Wedge(cent.T,
rad,
ee1,
ee2,
ec=plt.cm.RdYlBu_r(val),
fc=plt.cm.RdYlBu_r(val),
width=5)
else:
w = patches.Wedge(cent.T,
rad,
e1,
e2,
ec=plt.cm.RdYlBu_r(val),
fc=plt.cm.RdYlBu_r(val),
width=5)
axis.add_patch(w)
if self.fractal_low is None: return
gpcr_lib.plot_density_xray(axes[0],
0,
"",
0,
0,
self.xray,
"low",
"Intra.",
number=None,
plotn=False,
drawchol=False,
specialres=restocolor)
gpcr_lib.plot_density_xray(axes[1],
0,
"",
0,
0,
self.xray,
"upp",
"Extra.",
number=None,
plotn=False,
drawchol=False,
specialres=restocolor)
rad = 30.0
cent = np.array([0.0, 0.0])
draw_pies(axes[0], self.fractal_low, cent, rad, False)
draw_pies(axes[1], self.fractal_upp, cent, rad, True)
for a, l in zip(axes, labels):
a.text(-40, 38, l)
a.set_xticklabels([])
a.set_yticklabels([])
minval = min(densities1.min(args.plot),densities2.min(args.plot))
else :
minval = args.min
print "Max = %.2f and min = %E"%(maxval,minval)
# Convenient arrays to loop over
# we will use them below to make tighter code
densities = [densities1,densities2]
xray = [xray1,xray2]
sides = ["low","upp"]
# Lower leaflets
fig_low = plt.figure(1)
for i in range(2) : # Plot each density in its own subplot
a = fig_low.add_subplot(1,2,i+1)
im = gpcr_lib.plot_density_xray(a,densities[i].low,args.plot,minval,maxval,xray[i],"low",labels[i])
gpcr_lib.draw_colormap(fig_low,im)
fig_low.savefig(args.out+"_low.png",format="png")
# Upper leaflet
fig_upp = plt.figure(2)
for i in range(2) :
a = fig_upp.add_subplot(1,2,i+1)
im = gpcr_lib.plot_density_xray(a,densities[i].upp,args.plot,minval,maxval,xray[i],"upp",labels[i+2])
gpcr_lib.draw_colormap(fig_upp,im)
fig_upp.savefig(args.out+"_upp.png",format="png")
# Both leaflets
fig_both = plt.figure(10)
for i,(dxi,si,label,number) in enumerate(zip([0,1,0,1],[0,0,1,1,],labels[:4],["A)","B)","C)","D)"]),1) :
# dxi is the index into the densities and xray array,
# Read Xray structure and densities
xray = gpcr_lib.load_xray(args.mol)
densities = [gpcr_lib.standard_read_and_process(args.files,args.density)]
for r in args.replacement[1:] :
filenames = [f.replace(args.replacement[0],r) for f in args.files]
densities.append(gpcr_lib.standard_read_and_process(filenames,args.density))
if args.plot == "average" :
for d in densities : d.cutoff_av(cutoff=0.15)
if args.max is None :
maxval = max(*[d.max(args.plot) for d in densities])
else :
maxval = args.max
if args.min is None :
minval = min(*[d.min(args.plot) for d in densities])
else :
minval = args.min
print "Max = %.2f and min = %E"%(maxval,minval)
# Plot the series
for i,side in enumerate(["low","upp"],1) : # Loop over sides
f = plt.figure(i)
for i,(density,label,number) in enumerate(zip(densities,args.label,["A)","B)","C)","D)"]),1) :
a = f.add_subplot(2,2,i)
im = gpcr_lib.plot_density_xray(a,density[side],args.plot,minval,maxval,xray,side,label,number,plotn=True)
gpcr_lib.draw_colormap(f,im)
f.savefig("%s_%s_%s.png"%(args.out,args.density,side),format="png",dpi=300)
for i, (grid,
leaflet) in enumerate(zip([grid_low, grid_upp], ["low", "upp"]),
1):
a = fig.add_subplot(1, 2, i)
gridrm = np.ones([70, 70, 4])
gridrm[grid < 0.0, 3] = 0.0
if leaflet == "upp":
grid = grid[:, ::-1]
gridrm = gridrm[:, ::-1]
im = a.imshow(grid,
extent=[-35, 35, -35, 35],
origin="lower",
cmap=plt.cm.YlOrRd_r)
a.imshow(gridrm, extent=[-35, 35, -35, 35], origin="lower")
gpcr_lib.plot_density_xray(a,
None,
"",
0,
0,
xray,
leaflet,
gpcr_lib.side_name[leaflet].capitalize(),
number=None,
plotn=False,
drawchol=False)
ax = gpcr_lib.draw_colormap(fig, im, text='[kJ/mol]')
ax.text(1.03, 0.80, 'Energy')
fig.savefig("gridenergy.png", format="png")
if args.max is None:
maxval = max(*[d.max(args.plot) for d in densities])
else:
maxval = args.max
if args.min is None:
minval = min(*[d.min(args.plot) for d in densities])
else:
minval = args.min
print "Max = %.2f and min = %E" % (maxval, minval)
# Plot the series
for i, side in enumerate(["low", "upp"], 1): # Loop over sides
f = plt.figure(i)
for i, (density, label, number) in enumerate(
zip(densities, args.label, ["A)", "B)", "C)", "D)"]), 1):
a = f.add_subplot(2, 2, i)
im = gpcr_lib.plot_density_xray(a,
density[side],
args.plot,
minval,
maxval,
xray,
side,
label,
number,
plotn=True)
gpcr_lib.draw_colormap(f, im)
f.savefig("%s_%s_%s.png" % (args.out, args.density, side),
format="png",
dpi=300)
lj[diff2>(1.2*1.2)] = 0.0
grid[x+xylen/2-1,y+xylen/2-1,z+zlen/2-1] = lj.sum()
#print gridcoord*10.0,lj.sum()
grid[grid>0.0] = 0.0
# Write out the 3D grid
origin = midcoord + np.array([-xylen/2,-xylen/2,-zlen/2])
_writeDX(grid,origin,1.0,"gridenergy.dx")
# Plot 2D plot as average over z-dim
grid_low = grid[:,:,:zlen/2].mean(axis=2)
grid_upp = grid[:,:,zlen/2:].mean(axis=2)
fig = plt.figure(1)
for i,(grid,leaflet) in enumerate(zip([grid_low,grid_upp],["low","upp"]),1) :
a = fig.add_subplot(1,2,i)
gridrm = np.ones([70,70,4])
gridrm[grid<0.0,3] = 0.0
if leaflet == "upp" :
grid = grid[:,::-1]
gridrm = gridrm[:,::-1]
im = a.imshow(grid,extent=[-35,35,-35,35],origin="lower",cmap=plt.cm.YlOrRd_r)
a.imshow(gridrm,extent=[-35,35,-35,35],origin="lower")
gpcr_lib.plot_density_xray(a,None,"",0,0,xray,leaflet,gpcr_lib.side_name[leaflet].capitalize(),number=None,plotn=False,drawchol=False)
ax = gpcr_lib.draw_colormap(fig,im, text='')
ax.text(1.03,0.80,'$\mathrm{Energy}$')
fig.savefig("gridenergy.png",format="png")