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