R: Registry of proximities

pr_DB {proxy} | R Documentation

## Registry of proximities

### Description

Registry containing similarities and distances.

### Usage

    pr_DB
    pr_DB$get_field(name)
    pr_DB$get_fields()
    pr_DB$get_field_names()
    pr_DB$set_field(name, default = NA, type = NA, is_mandatory = FALSE,
                    is_modifiable = TRUE, validity_FUN = NULL)

    pr_DB$entry_exists(name)
    pr_DB$get_entry(name)
    pr_DB$get_entries(name = NULL, pattern = NULL)
    pr_DB$get_entry_names(name)
    pr_DB$set_entry(...)
    pr_DB$modify_entry(...)
    pr_DB$delete_entry(name)

    ## S3 method for class 'pr_DB'
    summary(object, verbosity = c("short", "long"), ...)

### Arguments

`name` | character string representing the name of an entry (case-insensitive).
`pattern` | regular expression to be matched to all fields of class `"character"` in all entries.
`default` | optional default value for the field.
`type` | optional character string specifying the class to be required for this field. If `type` is a character vector with more than two elements, the entries will be used as fixed set of alternatives. If `type` is not a character string or vector, the class will be inferred from the argument given.
`is_mandatory` | logical specifying whether new entries are required to have a value for this field.
`is_modifiable` | logical specifying whether entries can be changed with respect to that field.
`validity_FUN` | optional function or character string with the name of a function that checks the validity of a field entry. Such a function gets the value to be investigated as argument, and should stop with an error message if the value is not correct.
`object` | a registry object.
`verbosity` | controlling the verbosity of the output of the summary method for the registry. `"short"` gives just a list, `"long"` also gives the formulas.
`...` | for `pr_DB$set_entry` and `pr_DB$modify_entry`: named list of fields to be modified in or added to the registry (see details). This must include the index field (`"names"`).

### Details

`pr_DB` represents the registry of all proximity measures available. For each measure, it comprises meta-information that can be queried and extended. Also, new measures can be added. This is done using the following accessor functions of the `pr_DB` object:

`get_field_names()` returns a character vector with all field names. `get_field()` returns the information for a specific field as a list with components named as described above. `get_fields()` returns a list with all field entries. `set_field()` is used to create new fields in the repository (the default value will be set in all entries).

`get_entry_names()` returns a character vector with (the first alias of) all entries. `entry_exists()` is a predicate checking if an entry with the specified alias exists in the registry. `get_entry()` returns the specified entry if it exists (and, by default, gives an error if it does not). `get_entries()` is used to query more than one entry: either those matching `name` exactly, or those where the regular expression in `pattern` matches any character field in an entry. By default, all values are returned. `delete_entry` removes an existing entry from the registry (note that only user-provided entries can be deleted). `set_entry` and `modify_entry` require a named list of arguments used as field entries. At least the `names` index field is required. `set_entry` will check for all other mandatory fields. If specified in the field meta data, each field entry and the entry as a whole is checked for validity. Note that only user-specified fields and/or entries can be modified, the data shipped with the package are read-only.

The registry fields currently available are as follows:

FUN

  Function to register (see below).

names

  Character vector with an alias(es) for the measure.

PREFUN

  Optional function (or function name) for preprocessing code (see below).

POSTFUN

  Optional function (or function name) for postprocessing code (see below).

distance

  logical indicating whether this measure is a distance (`TRUE`) or similarity (`FALSE`).

convert

  Optional Function or function name for converting between similarities and distances when needed.

type

  Optional, the scale the measure applies to (`"metric"`, `"ordinal"`, `"nominal"`, `"binary"`, or `"other"`). If `NULL`, it is assumed to apply to some other unknown scale.

loop

  logical indicating whether `FUN` is just a measure, and therefore, if `dist` shall do the loop over all pairs of observations/variables, or if `FUN` does the loop on its own.

`C_FUN`

  logical indicating whether `FUN` is a C function.

abcd

  logical; if `TRUE` and binary data (or data to be interpreted as such) are supplied, the number of concordant and discordant pairs is precomputed for every two binary data vectors and supplied to the measure function.

formula

  Optional character string with the symbolic representation of the formula.

reference

  Optional reference (character).

description

  Optional description (character). Ideally, describes the context in which the measure can be applied.

A function specified as `FUN` parameter has mandatory arguments `x` and `y` (if `abcd` is `FALSE`), and `a`, `b`, `c`, `d`, `n` otherwise. Additionally, it gets all optional parameters specified by the user in the `...` argument of the `dist` and `simil` functions, possibly changed and/or complemented by the corresponding (optional) `PREFUN` function. It must return the (diss-)similarity value computed from the arguments. `x` and `y` are two vectors from the data matrix (matrices) supplied. If `abcd` is `FALSE`, it is assumed that binary measures will be used, and the number of all `n` concordant and discordant pairs (x\_k, y\_k) precomputed and supplied instead of `x` and `y`. `a`, `b`, `c`, and `d` are the counts of all (TRUE, TRUE), (TRUE, FALSE), (FALSE, TRUE), and (FALSE, FALSE) pairs, respectively.

A function specified as `PREFUN` parameter has mandatory arguments `x`, `y`, `p`, and `reg_entry`, with `y` and `p` possibly being `NULL` depending on the task at hand. `x` and `y` are the data objects, `p` is a (possibly empty) list with all specified proximity parameters, and `reg_entry` is the registry entry (a named list containing all information specified in `reg_add`). The preprocessing function is allowed to change all these information, and if so, is required to return *all* arguments as a named list in the same order.

A function specified as `POSTFUN` parameter has two mandatory arguments: `result` and `p`. `result` will contain the computed raw data, i.e. a vector of length n * (n - 1) / 2 for auto-distances (see `dist` for details on `dist` objects), or a matrix for cross-distances. `p` contains the specified proximity parameters. Post-processing functions need to return the `result` object (even if unmodified).

A function specified as `convert` parameter should preserve the type of its argument.

### Author(s)

David Meyer David.Meyer@R-project.org

### See Also

`dist`

### Examples

    ## create a new distance measure
    mydist <- function(x,y) x * y

    ## create a new entry in the registry with two aliases
    pr_DB$set_entry(FUN = mydist, names = c("test", "mydist"))

    ## look it up (index is case insensitive):
    pr_DB$get_entry("TEST")

    ## modify the content of the description field in the new entry
    pr_DB$modify_entry(names = "test", description = "foo function")

    ## create a new field
    pr_DB$set_field("New")

    ## look up the test entry again (two ways)
    pr_DB$get_entry("test")
    pr_DB[["test"]]

    ## show total number of entries
    length(pr_DB)

    ## show all entries (short list)
    pr_DB$get_entries(pattern = "foo")

    ## show more details
    summary(pr_DB, "long")

    ## get all entries in a list (and extract first two ones)
    pr_DB$get_entries()[1:2]

    ## get all entries as a data frame (select first 3 fields)
    as.data.frame(pr_DB)[,1:3]

    ## delete test entry
    pr_DB$delete_entry("test")

    ## check if it is really gone
    pr_DB$entry_exists("test")

[Package proxy version 0.4-22 Index]