I'm trying to break down a program line by line. Y
is a matrix of data but I can't find any concrete data on what .shape[0]
does exactly.
for i in range(Y.shape[0]):
if Y[i] == -1:
This program uses numpy, scipy, matplotlib.pyplot, and cvxopt.
The shape
attribute for numpy arrays returns the dimensions of the array. If Y
has n
rows and m
columns, then Y.shape
is (n,m)
. So Y.shape[0]
is n
.
In [46]: Y = np.arange(12).reshape(3,4)
In [47]: Y
Out[47]:
array([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
In [48]: Y.shape
Out[48]: (3, 4)
In [49]: Y.shape[0]
Out[49]: 3