Coerce

as_long(from, ...) as_count(from) as_abundance(from) as_incidence(from) as_occurrence(from) as_similarity(from) as_features(from) as_stratigraphy(from) # S4 method for ANY as_count(from) # S4 method for ANY as_abundance(from) # S4 method for ANY as_similarity(from) # S4 method for ANY as_occurrence(from) # S4 method for ANY as_incidence(from) # S4 method for ANY as_stratigraphy(from) # S4 method for DataMatrix as_long(from, as_factor = FALSE) # S4 method for DataMatrix as_features(from)

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

... | Currently not used. |

as_factor | A |

A coerced object.

The following methods coerce an object to a `Matrix`

object:

Method | Target | Details |

`as_count` | CountMatrix | absolute frequency data |

`as_abundance` | AbundanceMatrix | relative frequency data |

`as_incidence` | IncidenceMatrix | presence/absence data |

`as_occurrence` | OccurrenceMatrix | co-occurrence |

`as_similarity` | SimilarityMatrix | (dis)similarity |

`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`

.**

Method | Target | Details |

`as.matrix` | `matrix` | S3 matrix |

`as.data.frame` | `data.frame` | S3 data frame |

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

`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).

`as_features`

converts an DataMatrix 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:
`AbundanceMatrix-class`

,
`CountMatrix-class`

,
`DataMatrix-class`

,
`GenericMatrix-class`

,
`IncidenceMatrix-class`

,
`OccurrenceMatrix-class`

,
`SimilarityMatrix-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_abundance(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 7 8 6 2 1 #> row2 6 8 3 6 1 #> row3 4 7 6 6 4 #> row4 5 10 0 4 4 #> row5 3 3 0 5 9 #> row6 3 7 7 7 2## 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)