som/som.py
def normalize(vectors):
    """Normalizes a collection of vectors feature-wise."""

    vectors = list(vectors)
    mins = [min(x) for x in zip(*vectors)]
    maxs = [max(x) for x in zip(*vectors)]
    for vector in vectors:
        yield [(number - min_) / (max_ - min_)
               for min_, max_, number in zip(mins, maxs, vector)]
Normalizes a collection of vectors feature-wise.
Normalizes a collection of vectors feature-wise.
Normalizes a collection of vectors feature - wise .
def normalize(vectors):
    vectors = list(vectors)
    mins = [min(x) for x in zip(*vectors)]
    maxs = [max(x) for x in zip(*vectors)]
    for vector in vectors:
        yield [(number - min_) / (max_ - min_)
               for min_, max_, number in zip(mins, maxs, vector)]
def normalize ( vectors ) : vectors = list ( vectors ) mins = [ min ( x ) for x in zip ( * vectors ) ] maxs = [ max ( x ) for x in zip ( * vectors ) ] for vector in vectors : yield [ ( number - min_ ) / ( max_ - min_ ) for min_ , max_ , number in zip ( mins , maxs , vector ) ]
Normalizes a collection of vectors feature-wise.
Normalizes a collection of vectors feature - wise .
"""Normalizes a collection of vectors feature-wise."""
vectors