def IndexSearchMultiple()

in source/lib/indexing.py [0:0]

• 32 lines of code
• 11 McCabe index (conditional complexity)

def IndexSearchMultiple(data, idx, verbose=False, texts=None, print_errors=False):
    nl = len(data)
    nbex = data[0].shape[0]
    err = np.zeros((nl, nl)).astype(float)
    ref = np.linspace(0, nbex-1, nbex).astype(int)  # [0, nbex)
    if verbose:
        if texts is None: 
            print('Calculating similarity error (indices):')
        else:
            print('Calculating similarity error (textual):')
    for i1 in range(nl):
        for i2 in range(nl):
            if i1 != i2:
                D, I = idx[i2].search(data[i1], 1)
                if texts: # do textual comparison
                    e1 = 0
                    for p in range(I.shape[0]):
                        if texts[i2][p] != texts[i2][I[p,0]]:
                            e1 += 1
                            if print_errors:
                                print('Error {:s}\n      {:s}'
                                      .format(texts[i2][p].strip(), texts[i2][I[p,0]].strip()))
                    err[i1, i2] = e1 / nbex
                else:  # do index based comparision
                    err[i1, i2] \
                        = (nbex - np.equal(I.reshape(nbex), ref)
                           .astype(int).sum()) / nbex
                if verbose:
                    print(' - similarity error {:s}/{:s}: {:5d}={:5.2f}%'
                          .format(args.langs[i1], args.langs[i2],
                                  err[i1, i2], 100.0 * err[i1, i2]))
    return err