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author | Simon Chabot <simon.chabot@logilab.fr> |

Wed, 07 Nov 2012 10:29:40 +0100 | |

changeset 78 | 253d7f978ae3 |

parent 77 | 636e524739be |

child 79 | 36d35928dbaa |

[matrix] spelling mistakes

--- a/matrix.py Wed Nov 07 10:21:46 2012 +0100 +++ b/matrix.py Wed Nov 07 10:29:40 2012 +0100 @@ -124,23 +124,23 @@ `(weighting, input1, input2, distance_function, normalize, args)` - * `input1` : a list of "things" (names, dates, numbers) to align on - `input2`. If a value is unknown, set it as `None`. + * `input1` : a list of "things" (names, dates, numbers) to align onto + `input2`. If a value is unknown, set it as `None`. * `distance_function` : the distance function used to compute the distance matrix between `input1` and `input2` - * `weighting` : the weighting of the "things" computed, compared + * `weighting` : the weight of the "things" computed, compared with the others "things" of `items` - * `normalize` : boolean, if true, the matrix values will between 0 + * `normalize` : boolean, if true, the matrix values will be between 0 and 1, else the real result of `distance_function` will be stored * `args` : a dictionnay of the extra arguments the `distance_function` could take (as language or granularity) - - For each tuple of `items` as `Distancematrix` is built, then all the + - For each tuple of `items` a `Distancematrix` is built, then all the matrices are summed with their own weighting and the result is the global alignment matrix, which is returned.