Reading in a mesh file
Hello, I have mesh (more exactly: just a bunch of nodes) description with values associated to the nodes in a file, e.g. for a 3x3 mesh: 0 0 10 0 0.3 11 0 0.6 12 0.3 0 20 0.3 0.3 21 0.3 0.6 22 0.6 0 30 0.6 0.3 31 0.6 0.6 32 What is best way to read it in and get data structures like the ones I get from np.meshgrid? Of course, I know about np.loadtxt, but I'm having trouble getting the resulting arrays (x, y, values) in the right form and to retain association to the values. Thanks, Florian
On Wed, Aug 31, 2016 at 4:00 PM, Florian Lindner <mailinglists@xgm.de> wrote:
Hello,
I have mesh (more exactly: just a bunch of nodes) description with values
associated to the nodes in a file, e.g. for a
3x3 mesh:
0 0 10 0 0.3 11 0 0.6 12 0.3 0 20 0.3 0.3 21 0.3 0.6 22 0.6 0 30 0.6 0.3 31 0.6 0.6 32
What is best way to read it in and get data structures like the ones I get from np.meshgrid?
Of course, I know about np.loadtxt, but I'm having trouble getting the resulting arrays (x, y, values) in the right form and to retain association to the values.
For this particular case (known shape and ordering), this is what I would do. Maybe throw in a .T or three depending on exactly how you want them to be laid out. [~/scratch] |1> !cat mesh.txt 0 0 10 0 0.3 11 0 0.6 12 0.3 0 20 0.3 0.3 21 0.3 0.6 22 0.6 0 30 0.6 0.3 31 0.6 0.6 32 [~/scratch] |2> nodes = np.loadtxt('mesh.txt') [~/scratch] |3> nodes array([[ 0. , 0. , 10. ], [ 0. , 0.3, 11. ], [ 0. , 0.6, 12. ], [ 0.3, 0. , 20. ], [ 0.3, 0.3, 21. ], [ 0.3, 0.6, 22. ], [ 0.6, 0. , 30. ], [ 0.6, 0.3, 31. ], [ 0.6, 0.6, 32. ]]) [~/scratch] |4> reshaped = nodes.reshape((3, 3, -1)) [~/scratch] |5> reshaped array([[[ 0. , 0. , 10. ], [ 0. , 0.3, 11. ], [ 0. , 0.6, 12. ]], [[ 0.3, 0. , 20. ], [ 0.3, 0.3, 21. ], [ 0.3, 0.6, 22. ]], [[ 0.6, 0. , 30. ], [ 0.6, 0.3, 31. ], [ 0.6, 0.6, 32. ]]]) [~/scratch] |7> x = reshaped[..., 0] [~/scratch] |8> y = reshaped[..., 1] [~/scratch] |9> values = reshaped[..., 2] [~/scratch] |10> x array([[ 0. , 0. , 0. ], [ 0.3, 0.3, 0.3], [ 0.6, 0.6, 0.6]]) [~/scratch] |11> y array([[ 0. , 0.3, 0.6], [ 0. , 0.3, 0.6], [ 0. , 0.3, 0.6]]) [~/scratch] |12> values array([[ 10., 11., 12.], [ 20., 21., 22.], [ 30., 31., 32.]]) -- Robert Kern
Hello, thanks for your reply which was really helpful! My problem is that I discovered that the data I got is rather unordered. The documentation for reshape says: Read the elements of a using this index order, and place the elements into the reshaped array using this index order. ‘C’ means to read / write the elements using C-like index order, with the last axis index changing fastest, back to the first axis index changing slowest. ‘F’ means to read / write the elements using Fortran-like index order, with the first index changing fastest, and the last index changing slowest. With my data both dimensions change, so there is no specific ordering of the points, just a bunch of arbitrarily mixed "x y z value" data. My idea is: out = np.loadtxt(...) x = np.unique(out[:,0]) y = np.unique[out]:,1]) xx, yy = np.meshgrid(x, y) values = lookup(xx, yy, out) lookup is ufunc (I hope that term is correct here) that looks up the value of every x and y in out, like x_filtered = out[ out[:,0] == x, :] y_filtered = out[ out[:,1] == y, :] return y_filtered[2] (untested, just a sketch) Would this work? Any better way? Thanks, Florian Am 31.08.2016 um 17:06 schrieb Robert Kern:
On Wed, Aug 31, 2016 at 4:00 PM, Florian Lindner <mailinglists@xgm.de <mailto:mailinglists@xgm.de>> wrote:
Hello,
I have mesh (more exactly: just a bunch of nodes) description with values associated to the nodes in a file, e.g. for a 3x3 mesh:
0 0 10 0 0.3 11 0 0.6 12 0.3 0 20 0.3 0.3 21 0.3 0.6 22 0.6 0 30 0.6 0.3 31 0.6 0.6 32
What is best way to read it in and get data structures like the ones I get from np.meshgrid?
Of course, I know about np.loadtxt, but I'm having trouble getting the resulting arrays (x, y, values) in the right form and to retain association to the values.
For this particular case (known shape and ordering), this is what I would do. Maybe throw in a .T or three depending on exactly how you want them to be laid out.
[~/scratch] |1> !cat mesh.txt
0 0 10 0 0.3 11 0 0.6 12 0.3 0 20 0.3 0.3 21 0.3 0.6 22 0.6 0 30 0.6 0.3 31 0.6 0.6 32
[~/scratch] |2> nodes = np.loadtxt('mesh.txt')
[~/scratch] |3> nodes array([[ 0. , 0. , 10. ], [ 0. , 0.3, 11. ], [ 0. , 0.6, 12. ], [ 0.3, 0. , 20. ], [ 0.3, 0.3, 21. ], [ 0.3, 0.6, 22. ], [ 0.6, 0. , 30. ], [ 0.6, 0.3, 31. ], [ 0.6, 0.6, 32. ]])
[~/scratch] |4> reshaped = nodes.reshape((3, 3, -1))
[~/scratch] |5> reshaped array([[[ 0. , 0. , 10. ], [ 0. , 0.3, 11. ], [ 0. , 0.6, 12. ]],
[[ 0.3, 0. , 20. ], [ 0.3, 0.3, 21. ], [ 0.3, 0.6, 22. ]],
[[ 0.6, 0. , 30. ], [ 0.6, 0.3, 31. ], [ 0.6, 0.6, 32. ]]])
[~/scratch] |7> x = reshaped[..., 0]
[~/scratch] |8> y = reshaped[..., 1]
[~/scratch] |9> values = reshaped[..., 2]
[~/scratch] |10> x array([[ 0. , 0. , 0. ], [ 0.3, 0.3, 0.3], [ 0.6, 0.6, 0.6]])
[~/scratch] |11> y array([[ 0. , 0.3, 0.6], [ 0. , 0.3, 0.6], [ 0. , 0.3, 0.6]])
[~/scratch] |12> values array([[ 10., 11., 12.], [ 20., 21., 22.], [ 30., 31., 32.]])
-- Robert Kern
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On Thu, Sep 1, 2016 at 3:49 PM, Florian Lindner <mailinglists@xgm.de> wrote:
Hello,
thanks for your reply which was really helpful!
My problem is that I discovered that the data I got is rather unordered.
The documentation for reshape says: Read the elements of a using this
reshaped array using this index order. ‘C’ means to read / write the elements using C-like index order, with the last axis index changing fastest, back to the first axis index changing slowest. ‘F’ means to read / write the elements using Fortran-like index order, with the first index changing fastest, and the last index changing slowest.
With my data both dimensions change, so there is no specific ordering of
index order, and place the elements into the the points, just a bunch of arbitrarily mixed
"x y z value" data.
My idea is:
out = np.loadtxt(...) x = np.unique(out[:,0]) y = np.unique[out]:,1]) xx, yy = np.meshgrid(x, y)
values = lookup(xx, yy, out)
lookup is ufunc (I hope that term is correct here) that looks up the value of every x and y in out, like x_filtered = out[ out[:,0] == x, :] y_filtered = out[ out[:,1] == y, :] return y_filtered[2]
(untested, just a sketch)
Would this work? Any better way?
If the (x, y) values are actually drawn from a rectilinear grid, then you can use np.lexsort() to sort the rows before reshaping. [~/scratch] |4> !cat random-mesh.txt 0.3 0.3 21 0 0 10 0 0.3 11 0.3 0.6 22 0 0.6 12 0.6 0.3 31 0.3 0 20 0.6 0.6 32 0.6 0 30 [~/scratch] |5> scrambled_nodes = np.loadtxt('random-mesh.txt') # Note! Put the "faster" column before the "slower" column! [~/scratch] |6> i = np.lexsort([scrambled_nodes[:, 1], scrambled_nodes[:, 0]]) [~/scratch] |7> sorted_nodes = scrambled_nodes[i] [~/scratch] |8> sorted_nodes array([[ 0. , 0. , 10. ], [ 0. , 0.3, 11. ], [ 0. , 0.6, 12. ], [ 0.3, 0. , 20. ], [ 0.3, 0.3, 21. ], [ 0.3, 0.6, 22. ], [ 0.6, 0. , 30. ], [ 0.6, 0.3, 31. ], [ 0.6, 0.6, 32. ]]) Then carry on with the reshape()ing as before. If the grid points that "ought to be the same" are not actually identical, then you may end up with some problems, e.g. if you had "0.300000000001 0.0 20.0" as a row, but all of the other "x=0.3" rows had "0.3", then that row would get sorted out of order. You would have to clean up the grid coordinates a bit first. -- Robert Kern
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