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);
apply_transform_to_points(hmgns_world_coords, comb_trans_mat)
# to get normalized view coordinates, we divide through by the fourth
# element
norm_view_coords = view_coords / (view_coords[:, 3].reshape(-1, 1))
# the last step is to transform from normalized view coordinates to
# display coordinates.
view_to_disp_mat = get_view_to_display_matrix(f.scene)
disp_coords = apply_transform_to_points(norm_view_coords, view_to_disp_mat)
# at this point disp_coords is an Nx4 array of homogenous coordinates
# where X and Y are the pixel coordinates of the X and Y 3D world
# coordinates, so lets take a screenshot of mlab view and open it
# with matplotlib so we can check the accuracy
img = mlab.screenshot()
pl.imshow(img)
for i in range(N):
print 'Point %d: (x, y) ' % i, disp_coords[:, 0:2][i]
pl.plot([disp_coords[:, 0][i]], [disp_coords[:, 1][i]], 'ro')
pl.show()
# you should check that the printed coordinates correspond to the
# proper points on the screen
mlab.show()
#EOF
