Format a crestObj with private data.
A dataframe containing the presence records of the studied proxies and their associated climate values.
A vector of the climate variables to extract. See
accClimateVariables for the list of accepted values.
A data frame containing the data to reconstruct (counts, percentages or presence/absence data).
A dataframe of climate values across the study area
useful to correct for the imbalance of the sampling data (see
'crest.calibrate for more details). Default is NA.
The records in the distributions can be weighted using the
percentages by setting weight=TRUE. Include a column called 'weight'
in the distributions table.
The minimum number of unique presence data necessary to estimate a species' climate response. Default is 20.
A data frame assigns which taxa should be used for each variable (1 if the taxon should be used, 0 otherwise). The colnames should be the climate variables' names and the rownames the taxa names. Default is 1 for all taxa and all variables.
A vector containing the coordinates of the study site.
Default c(NA, NA).
The name of the dataset (default NA).
The climate values at the location of the dataset
'(default NA).
A boolean to print non-essential comments on the terminal
(default TRUE).
A crestObj object containing the spatial distributions.
#> Reformating the example dataset to fit this function
distributions <- cbind('ProxyName'= rep('Taxon1', nrow(reconstr$modelling$distributions[[1]])),
reconstr$modelling$distributions[[1]],
stringsAsFactors = FALSE)
for(tax in names(reconstr$modelling$distributions)[-1]) {
distributions <- rbind(distributions,
cbind('ProxyName'= rep(tax, nrow(reconstr$modelling$distributions[[tax]])),
reconstr$modelling$distributions[[tax]],
stringsAsFactors = FALSE)
)
}
distributions <- distributions[, c(2,1,3:6)]
print(head(distributions))
#> taxonid ProxyName longitude latitude bio1 bio12
#> 1 1 Taxon1 12.75 1.75 23.8 277
#> 2 1 Taxon1 11.75 2.75 23.7 172
#> 3 1 Taxon1 13.75 2.75 24.0 93
#> 4 1 Taxon1 14.25 3.75 25.6 203
#> 5 1 Taxon1 14.75 4.25 26.4 171
#> 6 1 Taxon1 11.25 4.75 22.5 281
climate_space <- reconstr$modelling$climate_space
print(head(climate_space))
#> longitude latitude bio1 bio12
#> 1 0.25 0.25 15.4 3
#> 2 0.25 0.75 15.1 38
#> 3 0.25 1.25 18.2 37
#> 4 0.25 1.75 13.6 137
#> 5 0.25 2.25 15.5 178
#> 6 0.25 2.75 13.4 325
x <- crest.set_modern_data(distributions, df=crest_ex,
climate = c("bio1", "bio12"))
#>
#> ## Prepping data for database extraction
#> <> Checking parameters ................... [OK]
#> <> Checking climate variable names ....... [OK]
#> <> Checking/Defining selectedTaxa ........
#> Warning: One or more taxa were are not in the distribution table and have been ignored. Check 'x$misc$taxa_notes' for details.
#> [OK]
#> <> Checking the list of taxa ............. [OK]
#> <> Creating the crestObj ................. [OK]
#> <> Inserting the fossil data ............. [OK]
#> <> Formatting the modern distributions ... [OK]
#> <> Checking the climate space ............ [OK]
#> ## Data insertion completed.
#>
x <- crest.set_modern_data(distributions, df=crest_ex,
climate_space=climate_space,
climate = c("bio1", "bio12"))
#>
#> ## Prepping data for database extraction
#> <> Checking parameters ................... [OK]
#> <> Checking climate variable names ....... [OK]
#> <> Checking/Defining selectedTaxa ........
#> Warning: One or more taxa were are not in the distribution table and have been ignored. Check 'x$misc$taxa_notes' for details.
#> [OK]
#> <> Checking the list of taxa ............. [OK]
#> <> Creating the crestObj ................. [OK]
#> <> Inserting the fossil data ............. [OK]
#> <> Formatting the modern distributions ... [OK]
#> <> Checking the climate space ............ [OK]
#> ## Data insertion completed.
#>