# Extract A Single Model or Data Object, Get Or Set Info, Description, Or Metadata. The function `getAMData` will extract an `amData` object from an `amModelLib`; the function `getAMModel` will extract an `amModel` object from an `amModelLib`. The function `ammlDesc` can be used to retrieve or set a description of an `amModelLib` object. The function `ammlInfo` can be used to retrieve or set information about an `amModelLib` object. `modelMeta` and `dataMeta` retrieve and set metadata within `amModelLib` objects. ```r getAMModel(amml, x, as.list = FALSE, ...) getAMData(amml, x, as.list = FALSE, ...) ammlDesc(amml) ammlDesc(amml) <- value ammlInfo(amml, x = NULL) ammlInfo(amml) <- value modelMeta(amml, x = NULL) modelMeta(amml, x) <- value dataMeta(amml, x = NULL) dataMeta(amml, x) <- value ``` ## Arguments - `amml`: An `amModelLib` object. - `x`: A name or length 1 integer index to extract from or set within the `amModelLib` object. - `as.list`: Logical; `FALSE` to return just the object, `TRUE` to return a list with both object and metadata. - ``...``: Additional arguments (not used). - `value`: A named list of metadata to set within `x`. ## Returns The model or data object in its original form, or if `as.list` a list with - **models**: The original model (or - **data**: The original data ) and - **metadata**: metadata. ## Details The objects created by `getAMData` and `getAMModel` are returned as their original class unless the argument `as.list` is set to `TRUE`. If `as.list`, a list is returned with the original object in the first element and metadata in the second. The setters for `ammlInfo`, `modelMeta`, and `dataMeta` replace individual elements in their respective lists with each call. To remove elements set their value to `NULL` in the named replacement list. ## Examples ```r # create dataset from lm helpfile ## Annette Dobson (1990) "An Introduction to Generalized Linear Models". ## Page 9: Plant Weight Data. # notice the models lm.D9 and lm.D90 are of class 'lm' ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14) trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69) group <- gl(2, 10, 20, labels = c("Ctl","Trt")) weight <- c(ctl, trt) lm.D9 <- lm(weight ~ group) lm.D90 <- lm(weight ~ group - 1) # omitting intercept # create two amModel objects with metadata and a soft link to the data full.model <- amModel( model = lm.D9, comment = 'full model', source = 'lm helpfile (R).', taxa = 'plants', data = 'plant.data' ) no.int.model <- amModel( model = lm.D90, comment = 'model without intercept', source = 'lm helpfile (R).', taxa = 'plants', data = 'plant.data' ) # create an amData object that includes metadata # the plant.data is of class data.frame plant.data <- data.frame(group = group, weight = weight) plant.data <- amData( data = plant.data, comment = 'Dataset from lm helpfile.' ) # create a second amData object that includes metadata log.plant.data <- data.frame(group, log.weight=log(weight)) log.plant.data <- amData( data = log.plant.data, comment = 'data to fit log model', source = 'lm helpfile (R).' ) # create an amModelLib that contains the two amModel objects and two amData objects # the models and data must be supplied as named lists mymodels <- amModelLib( models = list( full.model = full.model, no.int.model = no.int.model ), data = list( plant.data = plant.data, log.plant.data = log.plant.data ) ) # extract the dataset getAMData(amml = mymodels, 'plant.data', as.list = FALSE) # you can also extract by index getAMData(amml = mymodels, 1, as.list = FALSE) # extract the model getAMModel(amml = mymodels, 'full.model', as.list = FALSE) # you can also extract by index getAMModel(amml = mymodels, 1, as.list = FALSE) # extraction with '[' and '[[', which are identical here, focus on models mymodels[c(1,2)] mymodels[[1]] # Add a description to the amModelLib ammlDesc(mymodels) <- "This library demonstrates how to store models and data in a format that allows for descriptive metadata and easy retrieval for future reference." # Extract the description ammlDesc(mymodels) # Add some metadata 'info' to the amModelLib ammlInfo(mymodels) <- list(owner = 'me', organization = 'My Organization') # Extract all info for an amModelLib ammlInfo(mymodels) # Extract targeted info ammlInfo(amml = mymodels, 'owner') # Delete metadata by setting to NULL ammlInfo(mymodels) <- list(organization = NULL) # Extract all model metadata modelMeta(mymodels) # Extract metadata from specific model modelMeta(amml = mymodels, 'full.model') # Add metadata to 'full.model' modelMeta(amml = mymodels, 'full.model') <- list( url = "https://stat.ethz.ch/R-manual/R-devel/library/stats/html/lm.html" ) # remove metadata by setting value to NULL modelMeta(amml = mymodels, 'full.model') <- list(url = NULL) # Extract all data metadata dataMeta(mymodels) # Extract metadata from specific data dataMeta(amml = mymodels, 'plant.data') # Add metadata to 'plant.data' dataMeta(mymodels, 'plant.data') <- list( url = "https://stat.ethz.ch/R-manual/R-devel/library/stats/html/lm.html" ) # remove metadata by setting value to NULL dataMeta(mymodels, 'plant.data') <- list(url = NULL) ``` ## See Also Other amModelLib: `AMModels`, `amData`, `amModelLib`, `amModel`, `grepAMModelLib`, `insertAMModelLib`, `lsModels`, `rmModel`

getters function