def newSurface(self):
processes = self.plotter.getProcesses()
if not self._cv_dlg:
self._cv_dlg = daeChooseVariable(daeChooseVariable.plot3D)
self._cv_dlg.updateProcessesList(processes)
self._cv_dlg.setWindowTitle('Choose variable for 3D plot')
if self._cv_dlg.exec_() != QtWidgets.QDialog.Accepted:
return False
variable, domainIndexes, domainPoints, xAxisLabel, yAxisLabel, zAxisLabel, xPoints, yPoints, zPoints, currentTime = self._cv_dlg.getPlot3DData(
)
xPoints = numpy.array(xPoints)
yPoints = numpy.array(yPoints)
xmax = numpy.max(xPoints)
ymax = numpy.max(yPoints)
zmax = numpy.max(zPoints)
xmin = numpy.min(xPoints)
ymin = numpy.min(yPoints)
zmin = numpy.min(zPoints)
warp = 'auto'
#if((xmax == xmin) or (ymax == ymin) or (zmax == zmin)):
# warp = 'auto'
#else:
# warp = math.sqrt( (xmax-xmin)*(ymax-ymin) ) / (zmax-zmin)
# colormap='gist_earth', 'RdBu'
stype = 'surface'
mlab.figure()
if (stype == 'surface'):
#print "warp=", warp
#print "[xmin, xmax, ymin, ymax, zmin, zmax]=", [xmin, xmax, ymin, ymax, zmin, zmax]
mlab.surf(xPoints,
yPoints,
zPoints,
warp_scale=warp,
representation='surface')
mlab.colorbar(orientation='vertical')
#mlab.title('polar mesh')
#mlab.outline()
mlab.axes(ranges=[xmin, xmax, ymin, ymax, zmin, zmax], nb_labels=3)
mlab.xlabel(xAxisLabel)
mlab.ylabel(yAxisLabel)
mlab.zlabel(zAxisLabel)
elif (stype == 'map'):
mlab.imshow(zPoints)
mlab.colorbar(orientation='vertical')
#mlab.title('polar mesh')
#mlab.outline()
mlab.axes(ranges=[xmin, xmax, ymin, ymax], nb_labels=3)
mlab.xlabel(xAxisLabel)
mlab.ylabel(yAxisLabel)
mlab.zlabel(zAxisLabel)
mlab.show()
def spin(fcm, idx0, idx1, idx2):
"""Plots 3D data as points in space."""
x = fcm[:, idx0]
y = fcm[:, idx1]
z = fcm[:, idx2]
s = trilinear_interpolate(x, y, z)
# bins = int(len(x)**(1/3.0))
# xfrac, xint = numpy.modf((x - numpy.min(x))/
# (numpy.max(x)-numpy.min(x))*(bins-1))
# yfrac, yint = numpy.modf((y - numpy.min(y))/
# (numpy.max(y)-numpy.min(y))*(bins-1))
# zfrac, zint = numpy.modf((z - numpy.min(z))/
# (numpy.max(z)-numpy.min(z))*(bins-1))
# xint = xint.astype('i')
# yint = yint.astype('i')
# zint = zint.astype('i')
# # not interpolated - kiv write trilinear_interpolate function
# h, edges = numpy.histogramdd(fcm[:,[idx0, idx1, idx2]], bins=bins)
# v = h[xint, yint, zint]
mlab.figure()
mlab.points3d(x, y, z, s, mode='point')
mlab.xlabel(fcm.channels[idx0])
mlab.ylabel(fcm.channels[idx1])
mlab.zlabel(fcm.channels[idx2])
def spin(fcm, idx0, idx1, idx2):
"""Plots 3D data as points in space."""
x = fcm[:, idx0]
y = fcm[:, idx1]
z = fcm[:, idx2]
s = trilinear_interpolate(x, y, z)
# bins = int(len(x)**(1/3.0))
# xfrac, xint = numpy.modf((x - numpy.min(x))/
# (numpy.max(x)-numpy.min(x))*(bins-1))
# yfrac, yint = numpy.modf((y - numpy.min(y))/
# (numpy.max(y)-numpy.min(y))*(bins-1))
# zfrac, zint = numpy.modf((z - numpy.min(z))/
# (numpy.max(z)-numpy.min(z))*(bins-1))
# xint = xint.astype('i')
# yint = yint.astype('i')
# zint = zint.astype('i')
# not interpolated - kiv write trilinear_interpolate function
# h, edges = numpy.histogramdd(fcm[:,[idx0, idx1, idx2]], bins=bins)
# v = h[xint, yint, zint]
mlab.figure()
mlab.points3d(x, y, z, s, mode='point')
mlab.xlabel(fcm.channels[idx0])
mlab.ylabel(fcm.channels[idx1])
mlab.zlabel(fcm.channels[idx2])
def plot_cartesian(traj,
xaxis=None,
yaxis=None,
zaxis=None,
color='b',
label='_nolegend_',
linewidth=2,
scatter_size=20):
''' xaxis - x axis for the graph (0,1 or 2)
zaxis - for a 3d plot. not implemented.
'''
import arm_trajectories as at
#if traj.__class__ == at.JointTrajectory:
if isinstance(traj, at.JointTrajectory):
traj = joint_to_cartesian(traj)
pts = np.matrix(traj.p_list).T
label_list = ['X coord (m)', 'Y coord (m)', 'Z coord (m)']
x = pts[xaxis, :].A1.tolist()
y = pts[yaxis, :].A1.tolist()
if zaxis == None:
pl.plot(x, y, c=color, linewidth=linewidth, label=label)
pl.scatter(
x, y, c=color, s=scatter_size, label='_nolegend_', linewidths=0)
pl.xlabel(label_list[xaxis])
pl.ylabel(label_list[yaxis])
pl.legend(loc='best')
pl.axis('equal')
else:
from numpy import array
from enthought.mayavi.api import Engine
engine = Engine()
engine.start()
if len(engine.scenes) == 0:
engine.new_scene()
z = pts[zaxis, :].A1.tolist()
time_list = [t - traj.time_list[0] for t in traj.time_list]
mlab.plot3d(x, y, z, time_list, tube_radius=None, line_width=4)
mlab.axes()
mlab.xlabel(label_list[xaxis])
mlab.ylabel(label_list[yaxis])
mlab.zlabel(label_list[zaxis])
mlab.colorbar(title='Time')
# -------------------------------------------
axes = engine.scenes[0].children[0].children[0].children[1]
axes.axes.position = array([0., 0.])
axes.axes.label_format = '%-#6.2g'
axes.title_text_property.font_size = 4
def plotsquare3d(us):
from enthought.mayavi.mlab import surf, show, colorbar, xlabel, ylabel, figure
for u in us:
figure()
Np = 60
points = uniformsquarepoints(Np)
x = points[:,0].reshape(Np,Np)
y = points[:,1].reshape(Np,Np)
up = np.real(u(points))
surf(x,y, up.reshape(Np,Np))
colorbar()
xlabel('x')
ylabel('y')
show()
def _plotbutton1_fired(self):
mlab.clf()
self.loaddata()
field=mlab.pipeline.scalar_field(self.sregion) # Generate a scalar field
mlab.pipeline.volume(field,vmax=self.datamax,vmin=self.datamin) # Render the field with dots
mlab.outline()
mlab.xlabel('RA(J2000)')
mlab.ylabel('DEC(J2000)')
mlab.zlabel('Velocity')
mlab.view(azimuth=0, elevation=0)
mlab.show()
self.field = field
def surface(fcm, idx0, idx1):
"""Plots a surface plot for 2D data."""
x = fcm[:, idx0]
y = fcm[:, idx1]
bins = int(numpy.sqrt(len(x)))
z, xedge, yedge = numpy.histogram2d(y, x, bins=[bins, bins],
range=[(numpy.min(y), numpy.max(y)),
(numpy.min(x), numpy.max(x))]
)
mlab.figure()
mlab.surf(xedge, yedge, z, warp_scale='auto')
mlab.xlabel(fcm.channels[idx0])
mlab.ylabel(fcm.channels[idx1])
mlab.zlabel('Density')
def plot_cartesian(traj, xaxis=None, yaxis=None, zaxis=None, color='b',label='_nolegend_',
linewidth=2, scatter_size=10, plot_velocity=False):
import arm_trajectories as at
#if traj.__class__ == at.JointTrajectory:
if isinstance(traj,at.JointTrajectory):
traj = joint_to_cartesian(traj)
pts = np.matrix(traj.p_list).T
label_list = ['X coord (m)', 'Y coord (m)', 'Z coord (m)']
x = pts[xaxis,:].A1.tolist()
y = pts[yaxis,:].A1.tolist()
if plot_velocity:
vels = np.matrix(traj.v_list).T
xvel = vels[xaxis,:].A1.tolist()
yvel = vels[yaxis,:].A1.tolist()
if zaxis == None:
mpu.plot_yx(y, x, color, linewidth, '-', scatter_size, label,
axis = 'equal', xlabel = label_list[xaxis],
ylabel = label_list[yaxis],)
if plot_velocity:
mpu.plot_quiver_yxv(y, x, np.matrix([xvel,yvel]),
width = 0.001, scale = 1.)
mpu.legend()
else:
from numpy import array
from enthought.mayavi.api import Engine
engine = Engine()
engine.start()
if len(engine.scenes) == 0:
engine.new_scene()
z = pts[zaxis,:].A1.tolist()
time_list = [t-traj.time_list[0] for t in traj.time_list]
mlab.plot3d(x,y,z,time_list,tube_radius=None,line_width=4)
mlab.axes()
mlab.xlabel(label_list[xaxis])
mlab.ylabel(label_list[yaxis])
mlab.zlabel(label_list[zaxis])
mlab.colorbar(title='Time')
# -------------------------------------------
axes = engine.scenes[0].children[0].children[0].children[1]
axes.axes.position = array([ 0., 0.])
axes.axes.label_format = '%-#6.2g'
axes.title_text_property.font_size=4
def plot_cartesian(traj, xaxis=None, yaxis=None, zaxis=None, color='b',label='_nolegend_',
linewidth=2, scatter_size=10, plot_velocity=False):
import matplotlib_util.util as mpu
import arm_trajectories as at
#if traj.__class__ == at.JointTrajectory:
if isinstance(traj,at.JointTrajectory):
traj = joint_to_cartesian(traj)
pts = np.matrix(traj.p_list).T
label_list = ['X coord (m)', 'Y coord (m)', 'Z coord (m)']
x = pts[xaxis,:].A1.tolist()
y = pts[yaxis,:].A1.tolist()
if plot_velocity:
vels = np.matrix(traj.v_list).T
xvel = vels[xaxis,:].A1.tolist()
yvel = vels[yaxis,:].A1.tolist()
if zaxis == None:
mpu.plot_yx(y, x, color, linewidth, '-', scatter_size, label,
axis = 'equal', xlabel = label_list[xaxis],
ylabel = label_list[yaxis],)
if plot_velocity:
mpu.plot_quiver_yxv(y, x, np.matrix([xvel,yvel]),
width = 0.001, scale = 1.)
mpu.legend()
else:
from numpy import array
from enthought.mayavi.api import Engine
engine = Engine()
engine.start()
if len(engine.scenes) == 0:
engine.new_scene()
z = pts[zaxis,:].A1.tolist()
time_list = [t-traj.time_list[0] for t in traj.time_list]
mlab.plot3d(x,y,z,time_list,tube_radius=None,line_width=4)
mlab.axes()
mlab.xlabel(label_list[xaxis])
mlab.ylabel(label_list[yaxis])
mlab.zlabel(label_list[zaxis])
mlab.colorbar(title='Time')
# -------------------------------------------
axes = engine.scenes[0].children[0].children[0].children[1]
axes.axes.position = array([ 0., 0.])
axes.axes.label_format = '%-#6.2g'
axes.title_text_property.font_size=4
def surface(fcm, idx0, idx1):
"""Plots a surface plot for 2D data."""
x = fcm[:, idx0]
y = fcm[:, idx1]
bins = int(numpy.sqrt(len(x)))
z, xedge, yedge = numpy.histogram2d(y,
x,
bins=[bins, bins],
range=[(numpy.min(y), numpy.max(y)),
(numpy.min(x), numpy.max(x))])
mlab.figure()
mlab.surf(xedge, yedge, z, warp_scale='auto')
mlab.xlabel(fcm.channels[idx0])
mlab.ylabel(fcm.channels[idx1])
mlab.zlabel('Density')
def _plotbutton2_fired(self):
mlab.clf()
self.loaddata()
field=mlab.contour3d(self.sregion,colormap='gist_ncar') # Generate a scalar field
field.contour.maximum_contour = self.datamax
field.contour.minimum_contour = self.datamin
field.actor.property.opacity = self.opacity
mlab.outline()
mlab.xlabel('RA(J2000)')
mlab.ylabel('DEC(J2000)')
mlab.zlabel('Velocity')
mlab.view(azimuth=0, elevation=0)
mlab.show()
self.field = field
def make_3d_graph(scalarfield, filename):
mlab.figure(bgcolor=(1,1,1),fgcolor=(0,0,0))
#mlab.options.offscreen = True
#win = e.new_scene()
#src = mlab.pipeline.scalar_scatter(Phi_graph)
#e.add_source(src)
#e.add_module(IsoSurface())
#e.add_module(
#win.scene.isometric_view()
#win.scene.save(filename,size=(800,600))
mlab.clf()
mlab.contour3d(scalarfield,opacity=.5,transparent=True)#,contours=[1.0])
# mlab.outline()
mlab.zlabel('Z')
mlab.xlabel('X')
mlab.ylabel('Y')
print 'saving %s' % filename
mlab.savefig(filename)
def mcrtmv(frames, dt, Lx, Ly, Nx, Ny, savemovie=False, mvname='test'):
x = np.linspace(0, Lx, Nx)
y = np.linspace(0, Lx, Nx)
X, Y = np.meshgrid(x, y)
size = 500, 500
fig = ml.figure(size=size, bgcolor=(1., 1., 1.))
#fig.scene.anti_aliasing_frames=07
#extent = [0,Nx-1,0,Ny-1,-30,30]
ml.clf(figure=fig)
u = np.loadtxt('data/solution_%06d.txt' % 1)
fname = 'data/_tmp%07d.png' % 1
s = ml.surf(x, y, u, figure=fig, vmin=-1, vmax=1)
ml.axes(extent=[0, Lx, 0, Ly, -2, 2])
ml.colorbar()
ml.xlabel('x position')
ml.ylabel('y position')
ml.zlabel('wave amplitude')
if savemovie == True:
pl.ion()
arr = ml.screenshot()
img = pl.imshow(arr)
pl.axis('off')
for i in range(2, frames):
u = np.loadtxt('data/solution_%06d.txt' % i)
s.mlab_source.scalars = u
fname = 'data/_tmp%07d.png' % i
if savemovie == True:
arr = ml.screenshot()
img.set_array(arr)
pl.savefig(filename=fname) #,figure=fig)
print 'Saving frame', fname
pl.draw()
fig.scene.disable_render = False
os.system(
"mencoder 'mf://data/_tmp*.png' -mf type=png:fps=20 -ovc lavc -lavcopts vcodec=wmv2 -oac copy -o %s.mpg"
% mvname)
def mcrtmv(frames, dt,Lx,Ly,Nx,Ny,savemovie=False, mvname='test'):
x = np.linspace(0,Lx,Nx);
y = np.linspace(0,Lx,Nx);
X,Y = np.meshgrid(x,y);
size = 500,500
fig = ml.figure(size= size, bgcolor=(1.,1.,1.));
#fig.scene.anti_aliasing_frames=07
#extent = [0,Nx-1,0,Ny-1,-30,30]
ml.clf(figure=fig)
u = np.loadtxt('data/solution_%06d.txt'%1);
fname = 'data/_tmp%07d.png' % 1
s = ml.surf(x,y,u,figure=fig,vmin=-1,vmax=1)
ml.axes(extent=[0,Lx,0,Ly,-2,2])
ml.colorbar()
ml.xlabel('x position')
ml.ylabel('y position')
ml.zlabel('wave amplitude')
if savemovie == True:
pl.ion()
arr = ml.screenshot()
img = pl.imshow(arr)
pl.axis('off')
for i in range(2,frames):
u = np.loadtxt('data/solution_%06d.txt'%i);
s.mlab_source.scalars = u
fname = 'data/_tmp%07d.png' % i
if savemovie == True:
arr = ml.screenshot()
img.set_array(arr)
pl.savefig(filename=fname)#,figure=fig)
print 'Saving frame', fname
pl.draw()
fig.scene.disable_render = False
os.system("mencoder 'mf://data/_tmp*.png' -mf type=png:fps=20 -ovc lavc -lavcopts vcodec=wmv2 -oac copy -o %s.mpg" % mvname);
from enthought.mayavi import mlab
## For volume rendering (problems in saving as a obj file)
#field=mlab.pipeline.scalar_field(sregion) # Generate a scalar field
#mlab.pipeline.volume(field,vmin=2000,vmax=10000) # Render the field with dots
## For surface rendering
field=mlab.contour3d(sregion,colormap='gist_ncar') # Generate a scalar field
#field.contour.maximum_contour = 13000
field.contour.minimum_contour = 2000
field.actor.property.opacity = 0.3
mlab.outline()
mlab.xlabel('RA(J2000)')
mlab.ylabel('DEC(J2000)')
mlab.zlabel('Velocity')
#mlab.axes()
#mlab.colorbar()
## Add 3-d text in the cube
mlab.text3d(30,80,23,'Outflows in L1551 IRS5',scale=2.)
#mlab.text(45,45,"outflows!",width=0.2,z=20)
## Draw arrows to show outflows etc.
vector1=mlab.quiver3d(55,55,30,1,1,0.2,mode='arrow',scale_factor=10.0,color=(0.0,0.0,1.0))
vector2=mlab.quiver3d(55,40,30,1,-1.2,0.2,mode='arrow',scale_factor=10.0,color=(0.0,0.0,1.0))
vector3=mlab.quiver3d(45,50,30,-0.8,1,0.2,mode='2dthick_arrow',scale_factor=10.0,color=(0.0,0.0,1.0))
vector4=mlab.quiver3d(49,48,30,0.2,0,1,mode='2darrow',scale_factor=8.0,color=(0.0,0.0,1.0))
ph_r.append(k)
s_r.append(v)
#elif v >= 0.5:
# r_a.append(i)
# th_a.append(j)
# ph_a.append(k)
# s_a.append(v)
if False:
from enthought.mayavi import mlab
fig1 = mlab.figure(bgcolor=(1,1,1),fgcolor=(0,0,0),size=(800,800))
#mlab.points3d(ph_a, th_a, r_a, s_a,opacity=0.1,scale_factor=3)#, color=(0,0,1))
mlab.points3d(ph_r, th_r, r_r, s_r,opacity=0.3,scale_factor=2)#, color=(1,0,0))
mlab.axes(ranges=[0.0, 90.0, 0.0, 90.0, 3.0, 9.0])
#mlab.orientation_axes()
mlab.xlabel("phi")
mlab.ylabel("theta")
mlab.zlabel("centroid\ndistance")
#mlab.colorbar(nb_labels=2,nb_colors=2,label_fmt='')
mlab.colorbar()
#mlab.text(0.1,0.1,"attraction",color=(0,0,1),width=0.1)
#mlab.text(0.8,0.1,"repulsion",color=(1,0,0),width=0.1)
mlab.text(0.1,0.8,"%s-%s (n=%i; x=%i); (%s)"%(res1,res2,ndata,countNone,pdblistfile),width=0.8)
mlab.title("Free Energy (%s,%s)"%(res1,res2),size=0.3,height=0.7,figure=fig1)
viewdist = 120
elevation = 60 # angle or 'rotate'
azimuth = 180+45 # angle or 'rotate'
mlab.view(distance=viewdist,elevation=elevation, azimuth=azimuth)
mlab.savefig(pdblistfile+"_%s_%s_r_theta_phi.png"%(res1,res2))
