Matrix to Array Transformation assistance required
Hello, I am trying to convert a numpy matrix to an array containing coordinate pairs, and I am having difficulty understanding the transformation process. I know there is a fairly simply way of doing this transformation but am unsure of the commands to use. The matrix I have is created with the following command vegetation_matrix = numpy.empty(shape=(x_bins,y_bins)) x_bins and y_bins are dynamic in size depending on the input data and the required precision. Some tests I need to perform could result in a 10 by 10 matrix and some could result in a 4000,5000 matrix, However, these values are dynamic and could be anything. For instance they COULD be 300,124 or 400,900 etc.. these are unknown values until the data has been collected. A sample matrix view will be:
a array([['x', 'o', 'o'], ['o', 'x', 'x'], ['o', 'x', 'o']], dtype='|S1')
I wish to convert this to: 0,0,x 0,1,o 0,2,o ... 2,2,o I have been given the following example which works on a known size of data.
a array([['x', 'o', 'o'], ['o', 'x', 'x'], ['o', 'x', 'o']], dtype='|S1')
numoy.array([numpy.arange(9)//3, numpy.arange(9)%3, a.flatten()]).transpose() array([['0', '0', 'x'], ['0', '1', 'o'], ['0', '2', 'o'], ['1', '0', 'o'], ['1', '1', 'x'], ['1', '2', 'x'], ['2', '0', 'o'], ['2', '1', 'x'], ['2', '2', 'o']], dtype='|S8')
But when I try and convert that line to work on my own matrix with its larger size, I do not understand how to make it work. Would somebody be able to provide a little assistance on how I can proceed here. (I am a little new to python and part of the problem I have is using the correct terminology for various processes etc) Regards, David
On Sun, Apr 3, 2011 at 8:03 PM, David Crisp
Hello,
I am trying to convert a numpy matrix to an array containing coordinate pairs, and I am having difficulty understanding the transformation process. I know there is a fairly simply way of doing this transformation but am unsure of the commands to use.
The matrix I have is created with the following command
vegetation_matrix = numpy.empty(shape=(x_bins,y_bins))
x_bins and y_bins are dynamic in size depending on the input data and the required precision. Some tests I need to perform could result in a 10 by 10 matrix and some could result in a 4000,5000 matrix, However, these values are dynamic and could be anything. For instance they COULD be 300,124 or 400,900 etc.. these are unknown values until the data has been collected.
A sample matrix view will be:
a array([['x', 'o', 'o'], ['o', 'x', 'x'], ['o', 'x', 'o']], dtype='|S1')
I wish to convert this to: 0,0,x 0,1,o 0,2,o ... 2,2,o
I have been given the following example which works on a known size of data.
a array([['x', 'o', 'o'], ['o', 'x', 'x'], ['o', 'x', 'o']], dtype='|S1')
numoy.array([numpy.arange(9)//3, numpy.arange(9)%3, a.flatten()]).transpose() array([['0', '0', 'x'], ['0', '1', 'o'], ['0', '2', 'o'], ['1', '0', 'o'], ['1', '1', 'x'], ['1', '2', 'x'], ['2', '0', 'o'], ['2', '1', 'x'], ['2', '2', 'o']], dtype='|S8')
But when I try and convert that line to work on my own matrix with its larger size, I do not understand how to make it work.
It looks to me that you just have to replace the 9 and the 3 with your 2d array size and shape, for example
a = np.arange(12).reshape(3,4) a array([[ 0, 1, 2, 3], [ 4, 5, 6, 7], [ 8, 9, 10, 11]]) np.column_stack((np.arange(a.size)//a.shape[1], np.arange(a.size)%a.shape[1], a.ravel())) array([[ 0, 0, 0], [ 0, 1, 1], [ 0, 2, 2], [ 0, 3, 3], [ 1, 0, 4], [ 1, 1, 5], [ 1, 2, 6], [ 1, 3, 7], [ 2, 0, 8], [ 2, 1, 9], [ 2, 2, 10], [ 2, 3, 11]])
Or do I misunderstand the question? Josef
Would somebody be able to provide a little assistance on how I can proceed here.
(I am a little new to python and part of the problem I have is using the correct terminology for various processes etc)
Regards, David _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
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