python - Create a Numpy Array from particular text format -

i have text file containing training vectors

<vector 1-dimension 1>       <vector 1 - dimension 2>   ....   <vector 1 - dimension n> .............  .............  .............  .............  .............   <vector m - dimension 1>     <vector m - dimension 2>   ....   <vector m - dimension n> 

another text file mentions class memberships of corresponding vectors

vector1-class vector2-class ............. vector n - class 

now, need convert these numpy arrays x , y, can give them input scikit learn linear svm function ; example in python code,

from sklearn import svm  x = [[1,1], [1,-1], [-1,1], [-1,-1]] y = [0, 1, 2, 3] clf = svm.svc() clf.fit(x, y) 

how can achieve this?

after bit of research, have used

x = np.genfromtxt("x.txt",delimiter=" ") y = np.genfromtxt("y.txt",delimiter=" ") 

to achieve same.

is there better way achieve same? if textfile written in sparse format, is, if nonzero elements mentioned ordered pairs, how can achieve same result?