Distance Matrix Reader

Read a distance matrix from a given URL. The file (or URL) is plain ASCII file (possibly gzip'ed) of distance or similarity values. The file may either contain the (upper right) triangular distance matrix or the full distance matrix. A detailed description is given below.

Options

Input

Choose input file here. You can also provide an arbitrary URL here (such as http:// or ftp://).

Separator Char

Enter character separating entries in the table (for instance space, comma or semicolon). Consecutive separator characters will result in errors.

Missing value pattern

Pattern for missing values in the file.

Read Row Header

Check this when the file contains row header information (names of rows)

Read Column Header

Check this when the file contains column header information (will skip the first line then). If the "Read Row Header" option is on, the file is supposed to contain a place holder identifier in the upper left corner. That is, it must not immediately start with the first column name but some (ignored) row header column identifier.

Matrix Type

Select whether the file contains a full matrix or a triangular matrix.

• Lower Triangular: File contains lower triangular matrix
• Upper Triangular: File contains upper triangular matrix
• Full Matrix: File contains full matrix

Matrix is symmetric

Select this if the table contains the full matrix but the matrix is symmetric (i.e. the value at location (m,n) is equal to the value at (n,m)). Selecting this option will reduce the memory footprint since only the lower triangular matrix is read.

Contains Diagonal

Each row contains the self-distance of the respective row as first element, which is supposed to be 0.0 after normalization (if it is not a warning is printed).

Apply linear transformation

The values in the file should be linearly transformed by a given scale and offset value (whereby the scale operation precedes the offset operation, the new distance value is y = scale * x + offset). If the file contains similarity values, select offset = 1.0 and scale = -1.0.

Offset

The offset value for the linear transformation.

Scale

The scale value for the linear transformation.

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