Converting a list of points to a numpy 2D array
I'm using genfromtxt to import essentially a 2D array that has all its values listed in a text file of the form (x's and y's are integers):
x1 y1 z1
x2 y2 z2
: : :
I'm using the for loop below but I'm pretty sure there must be a one line way to do it. What would be a more efficient way to do this conversion?
raw = genfromtxt(file,skip_header = 6)
xrange = ( raw[:,0].min() , raw[:,0].max() )
yrange = ( raw[:,1].min() , raw[:,1].max() )
Z = zeros(( xrange[1] - xrange[0] +1 , yrange[1] - yrange[0] +1 ))
for row in raw:
Z[ row[0]-xrange[0] , row[1]-yrange[0] ] = row[2]
你可以用下面的代码替换for循环：
xidx = (raw[:,0]-xrange[0]).astype(int)
yidx = (raw[:,1]-yrange[0]).astype(int)
Z[xidx, yidx] = raw[:,2]
To import a matrix from a file you can just split the lines and then convert to int.
[[int(i) for i in j.split()] for j in open('myfile').readlines()]
of course, I'm supposing your file contains only the matrix.
At the end, you can convert this 2-D array to numpy.
You may try something like this:
>>> Z = zeros((3, 3))
>>> test = array([[0, 1, 2], [1, 1, 6], [2, 0, 4]])
>>> Z[test[:, 0:2].T.tolist()]
array([ 0., 0., 0.])
>>> Z[test[:, 0:2].T.tolist()] = test[:, 2]
>>> Z
array([[ 0., 2., 0.],
[ 0., 6., 0.],
[ 4., 0., 0.]])
In your case:
Z[(raw[:, 0:2] - minimum(raw[:, 0:2], axis=0)).T.tolist()] = raw[:, 2]
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