Distance Matrix (
Distance matrix. Extends
Items corresponding to matrix rows.
Items corresponding to matrix columns.
If axis=1 we calculate distances between rows, if axis=0 we calculate distances between columns.
Returns the single dimension of the symmetric square matrix.
A 1-D iterator over the array.
This is a numpy.flatiter instance, which acts similarly to, but is not a subclass of, Python’s built-in iterator object.
Return a copy of the array collapsed into one dimension.
>>> x = np.arange(1, 7).reshape(2, 3) >>> x array([[1, 2, 3], [4, 5, 6]]) >>> x.flat 4 >>> x.T array([[1, 4], [2, 5], [3, 6]]) >>> x.T.flat 5 >>> type(x.flat) <type 'numpy.flatiter'>
An assignment example:
>>> x.flat = 3; x array([[3, 3, 3], [3, 3, 3]]) >>> x.flat[[1,4]] = 1; x array([[3, 1, 3], [3, 1, 3]])
Return a submatrix
row_items – indices of rows
col_items – incides of columns
Load distance matrix from a file
The file should be preferrably encoded in ascii/utf-8. White space at the beginning and end of lines is ignored.
The first line of the file starts with the matrix dimension. It can be followed by a list flags
axis=<number>: the axis number
symmetric: the matrix is symmetric; when reading the element (i, j) it’s value is also assigned to (j, i)
asymmetric: the matrix is asymmetric
row_labels: the file contains row labels
col_labels: the file contains column labels
By default, matrices are symmetric, have axis 1 and no labels are given. Flags labeled and labelled are obsolete aliases for row_labels.
If the file has column labels, they follow in the second line. Row labels appear at the beginning of each row. Labels are arbitrary strings that cannot contain newlines and tabulators. Labels are stored as instances of Table with a single meta attribute named “label”.
The remaining lines contain tab-separated numbers, preceded with labels, if present. Lines are padded with zeros if necessary. If the matrix is symmetric, the file contains the lower triangle; any data above the diagonal is ignored.
filename – file name
Returns True if row labels can be automatically determined from data
For this, the row_items must be an instance of Orange.data.Table whose domain contains a single meta attribute, which has to be a string. The domain may contain other variables, but not meta attributes.
Returns True if column labels can be automatically determined from data
For this, the col_items must be an instance of Orange.data.Table whose domain contains a single meta attribute, which has to be a string. The domain may contain other variables, but not meta attributes.