Coerce

as_long(from, ...) as_count(from) as_composition(from) as_abundance(from) as_incidence(from) as_occurrence(from) as_features(from) as_stratigraphy(from) # S4 method for ANY as_count(from) # S4 method for ANY as_composition(from) # S4 method for ANY as_abundance(from) # S4 method for ANY as_incidence(from) # S4 method for ANY as_occurrence(from) # S4 method for ANY as_stratigraphy(from) # S4 method for matrix as_long(from, factor = FALSE, reverse = FALSE) # S4 method for AbundanceMatrix as_long(from, factor = FALSE, reverse = FALSE) # S4 method for AbundanceMatrix as_features(from)

from | An object to be coerced. |
---|---|

... | Currently not used. |

factor | A |

reverse | A |

A coerced object.

The following methods coerce an object to a `*Matrix`

object:

Method | Target | Details |

`as_count()` | CountMatrix | absolute frequency data |

`as_composition()` | CompositionMatrix | relative frequency data |

`as_incidence()` | IncidenceMatrix | presence/absence data |

`as_occurrence()` | OccurrenceMatrix | co-occurrence |

`as_stratigraphy()` | StratigraphicMatrix | stratigraphic relationships |

**Note that as_count rounds numeric values to zero decimal places and
then coerces to integer as by as.integer().**

`as_stratigraphy()`

converts a set of stratigraphic relationships (edges)
to a stratigraphic (adjacency) matrix. `from`

can be a `matrix`

, `list`

,
or `data.frame`

: the first column/component is assumed to contain the
bottom units and the second the top units (adjacency).

Method | Target | Details |

`as_long()` | `data.frame` | long S3 data frame |

`as_features()` | `data.frame` | wide S3 data frame |

`as_features()`

converts a `*Matrix`

object to a collection of features:
a `data.frame`

with all informations as extra columns (result may differ
according to the class of `from`

).

Other matrix:
`CompositionMatrix-class`

,
`CountMatrix-class`

,
`DataMatrix`

,
`IncidenceMatrix-class`

,
`OccurrenceMatrix-class`

,
`StratigraphicMatrix-class`

N. Frerebeau

## Create a count matrix A0 <- matrix(data = sample(0:10, 100, TRUE), nrow = 10, ncol = 5) ## Coerce to absolute frequencies A1 <- as_count(A0) ## Coerce to relative frequencies B <- as_composition(A1) ## Row sums are internally stored before coercing to relative frequencies ## (use get_totals() to retrieve these values) ## This allows to restore the source data A2 <- as_count(B) all(A1 == A2)#> [1] TRUE## Coerce to presence/absence C <- as_incidence(A1) ## Coerce to a co-occurrence matrix D <- as_occurrence(A1) ## Coerce to an S3 matrix or data.frame X <- as.matrix(A1) all(A0 == X)#> [1] TRUE#> col1 col2 col3 col4 col5 #> row1 10 10 1 9 1 #> row2 9 0 3 7 5 #> row3 3 4 9 0 10 #> row4 7 1 7 1 0 #> row5 6 8 6 3 2 #> row6 6 0 3 0 1## Collection of features # set_dates(A1) <- matrix(sample(0:10, 20, TRUE), nrow = 10, ncol = 2) # set_coordinates(A1) <- matrix(sample(0:10, 30, TRUE), nrow = 10, ncol = 3) # as_features(A1)