mfdb_queries: MareFrame DB queries
In sCervino/mfdb: MareFrame DB querying library

Description Usage Arguments Details Value Examples

Aggregate data from the database in a variety of ways

mfdb_area_size(mdb, params)
mfdb_temperature(mdb, params)
mfdb_sample_count(mdb, cols, params)
mfdb_sample_meanlength(mdb, cols, params)
mfdb_sample_meanlength_stddev(mdb, cols, params)
mfdb_sample_meanweight(mdb, cols, params)
mfdb_sample_meanweight_stddev(mdb, cols, params)

`mdb`	An object created by `mfdb`()
`cols`	Any additonal columns to group by, see details.
`params`	A list of parameters, see details.

The items in the params list either restrict data that is returned, or groups data if they are also in the cols vector, or are 'year', 'timestep', or 'area'.

If you are grouping by the column, params should contain one of the following:

NULL: Don't do any grouping, instead put 'any' in the resulting column. For example, age = NULL results in "any".
character / numeric vector: Aggregate all samples together where they match. For example, year = 1990:2000 results in 1990, ... , 2000.
mfdb_unaggregated(): Don't do any aggregation for this column, return all possible values.
mfdb_group(): Group several discrete items together. For example, age = mfdb_group(young = 1:3, old = 4:5) results in "young" and "old".
mfdb_interval(): Group irregular ranges together. For example, length = mfdb_interval('len', c(0, 10, 100, 1000)) results in "len0", "len10", "len100", and "len1000".
mfdb_step_interval(): Group regular ranges together. For example, length = mfdb_step_interval('len', to = 100, by = 10) results in "len0", "len10", ... , "len100".

In addition, params can contain other arguments to purely restrict the data that is returned.

institute: A vector of institute names, see mfdb::institute for possible values
gear: A vector of gear names, see mfdb::gear for possible values
vessel: A vector of vessel names, see mfdb::vessel for possible values
sampling_type: A vector of sampling_type names, see mfdb::sampling_type for possible values
species: A vector of species names, see mfdb::species for possible values
sex: A vector of sex names, see mfdb::sex for possible values

To save specifying the same items repeatedly, you can use list concatenation to keep some defaults, for example:

1 2	defaults <- list(year = 1998:2000) mfdb_sample_meanlength(mdb, c('age'), c(list(), defaults))

All will return a list of data.frame objects. Precisely what columns these will contain depends on the function called.

mfdb_temperature: Returns year, step, area, (mean) temperature
mfdb_sample_count: Returns year,step,area,(group cols),number (of samples)
mfdb_sample_meanlength: Returns year,step,area,(group cols),number (of samples),mean (length in group)
mfdb_sample_meanlength_stddev: As mfdb_sample_meanlength, but also returns std. deviation.
mfdb_sample_meanweight: Returns year,step,area,(group cols),number (of samples),mean (weight of group)
mfdb_sample_meanweight_stddev: As mfdb_sample_meanweight, but also returns std. deviation.

## Not run: 
agg_data <- mfdb_sample_count(mdb, c('age', 'length'),
        params = c(list(
            year = c(1990, 1991),
            length = mfdb_interval("len", seq(0, 500, by = 30)),
            age = mfdb_group('young' = c(1,2,3)),
            null = NULL), opt_catch))
gadget_dir_write(gd, gadget_likelihood_component("catchdistribution",
        name = "cdist",
        weight = 0.9,
        data = agg_data[[1]],
        area = attr(agg_data[[1]], "area"),
        age = attr(agg_data[[1]], "age")))

## End(Not run)