Ignore:
Timestamp:
03/26/12 17:12:12 (2 years ago)
Author:
anze <anze.staric@…>
Branch:
default
Message:

Fixed failing tests.

File:
1 edited

Legend:

Unmodified
Added
Removed
  • Orange/projection/linear.py

    r10645 r10647  
    937937                                  in xrange(len(data_matrix))], False) 
    938938            pca = pca(data.Table(domain, data_matrix.T)) 
    939             vals, vectors = pca.eigen_values, pca.projection 
     939            vals, vectors = pca.variances, pca.projection 
    940940        elif method == DR_SPCA and self.graph.data_has_class: 
    941941            pca = Spca(standardize=False, max_components=ncomps, 
     
    945945            pca = pca(data.Table(domain, 
    946946                                 numpy.hstack([data_matrix.T, numpy.array(class_array, ndmin=2).T]))) 
    947             vals, vectors = pca.eigen_values, pca.projection 
     947            vals, vectors = pca.variances, pca.projection 
    948948        elif method == DR_PLS and self.graph.data_has_class: 
    949949            data_matrix = data_matrix.transpose() 
     
    13091309 
    13101310    def __init__(self, standardize=True, max_components=0, variance_covered=1, 
    1311                  use_generalized_eigenvectors=0): 
     1311                 use_generalized_eigenvectors=0, ddof=1): 
    13121312        self.standardize = standardize 
    13131313        self.max_components = max_components 
    13141314        self.variance_covered = min(1, variance_covered) 
    13151315        self.use_generalized_eigenvectors = use_generalized_eigenvectors 
     1316        self.ddof=ddof 
    13161317 
    13171318    def __call__(self, dataset): 
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