[Numpy-discussion] [numpy-discussion] Transform 3d data
Nadav Horesh
nadavh at visionsense.com
Tue Oct 19 12:20:24 EDT 2010
Of course there is an (at least one) error:
the line should be:
XYZ =
np.mgrid[lwrbnd[0]:uprbnd[0]:shape[0]*1j,lwrbnd[1]:uprbnd[1]:shape[1]*1j, lwrbnd[2]:uprbnd[2]:shape[2]*1j]
On Tue, 2010-10-19 at 14:10 +0200, Nadav Horesh wrote:
> You can aid mgrid, riughy as the follows (I may have mistakes, but the
> direction should be clear):
>
> def transform_3d_data_(field,lwrbnd,uprbnd):
> shape = field.shape
> XYZ = np.mgrid[lwrbnd[0]:uprbnd[0]:shape[0],
> lwrbnd[1]:uprbnd[1]:shape[1], lwrbnd[2]:uprbnd[2]:shape[2]]
> vectors = fields.reshape(-1,3)
> np.savetxt(np.hstack((XYZ.reshape(3,-1).T, vectors)))
>
>
> Nadav
>
>
>
> -----Original Message-----
> From: numpy-discussion-bounces at scipy.org on behalf of Thomas
> Königstein
> Sent: Tue 19-Oct-10 12:05
> To: numpy-discussion at scipy.org
> Subject: [Numpy-discussion] [numpy-discussion] Transform 3d data
>
> Hello everyone,
>
> I have the following problem:
>
> I acquire a (evenly spaced) 3d field of 3d vectors from a HDF5 data
> file:
>
> >>> import tables
> >>> field=tables.openFile("test.h5").root.YeeMagField.read()
>
> now, the data is organized in "nested arrays"... so, when I have, say,
> 300
> data points on the x-axis, 200 data points on the y-axis and 100 data
> points
> on the z-axis, I get an array with the shape
>
> >>> field.shape
> >>> (300, 200, 100, 3)
>
> When I now want to see a 3D arrow-plot of this field, I use:
>
> >>> from enthought.mayavi import mlab as m
> >>> x,y,z=field.transpose()
> >>> m.quiver3d(x,y,z)
>
> and this works just fine. Here, the arrays (x and y and z) *each*
> contain
> one field component (i,e. into one spatial direction) at 300x200x100
> points
> in a 3D array.
>
> Now, I would like to have this data in another format, so I can for
> example
> save it to a textfile with pylab.savetxt. What I would like are six
> arrays,
> each 1d, three for the coordinates and three for the field components.
> Since
> I didn't know any better, I wrote the following procedure:
>
> def transform_3d_data_(field,lowerBounds,upperBounds): #field is the
> same as
> above, lowerBounds and upperBounds each contain three values for
> x,y,z
> min/max
> import pylab as p
> xx,yy,zz,ex,ey,ez=list(),list(),list(),list(),list(),list()
> #xx,yy,zz
> will become the spatial coordinates, ex,ey,ez will become the field
> components
> for xi in range(field.shape[0]): #for each x coordinate...
> for yi in range(field.shape[1]): #for each y coordinate...
> for zi in range(field.shape[2]): #for each z coordinate...
>
> xx.append(lowerBounds[0]+xi*(upperBounds[0]-lowerBounds[0])/float(field.shape[0]))
> #append this
>
> yy.append(lowerBounds[1]+yi*(upperBounds[1]-lowerBounds[1])/float(field.shape[1]))
> #x, y, z coordinate
>
> zz.append(lowerBounds[2]+zi*(upperBounds[2]-lowerBounds[2])/float(field.shape[2]))
> #to xx, yy, zz ....
> ex.append(field[xi][yi][zi][0]) #and also
> ey.append(field[xi][yi][zi][1]) #add this field
> composition
> ez.append(field[xi][yi][zi][2]) #to ex, ey, ez.
> xx,yy,zz,ex,ey,ez=[p.array(_) for _ in [xx,yy,zz,ex,ey,ez]]
> return xx,yy,zz,ex,ey,ez
>
> , so I get the desired six 1D-arrays xx,yy,zz for the coordinates and
> ex,ey,ez for the field components. It works.
>
> Now my question: there has to be a better way to get this
> re-organization,
> right? This one here is much too slow, obviously. Is there maybe a
> single
> command for pylab that does this?
>
> Thanks in advance, cheers
>
> Thomas
>
> PS. I'm new to this messaging board, and I was wondering if there is
> a
> "normal" forum as well? I can't even search through the archives at
> http://mail.scipy.org/pipermail/numpy-discussion/ :( have there ever
> been
> discussions/initiatives about porting the mailing list archives for
> example
> to a phpBB based forum?
>
More information about the NumPy-Discussion
mailing list