Description Usage Arguments Value Examples
Wrapper to GMQL ORDER operator
It is used to order either samples or sample regions or both, according to a set of metadata and/or region attributes. Order can be specified as ascending / descending for every attribute. The number of samples and their regions remain the same (unless fetching options are specified), as well as their attributes, but a new ordering metadata and/or region attribute is added. Sorted samples or regions have a new attribute "_order", added to their metadata, or "order" added to their regions, or to both of them as specified in input.
1 2 3 4 |
.data |
GMQLDataset class object |
metadata_ordering |
list of ordering functions containing name of
metadata attribute.
The functions available are: |
regions_ordering |
list of ordering functions containing name of
region attribute.
The functions available are: |
fetch_opt |
string indicating the option used to fetch the first k samples; it can assume the values:
if NULL, num_fetch is not considered |
num_fetch |
integer value identifying the number of samples to fetch; by default it is 0, that means all samples are fetched |
reg_fetch_opt |
string indicating the option used to fetch the first k regions; it can assume the values:
if NULL, reg_num_fetch is not considered |
reg_num_fetch |
integer value identifying the number of regions to fetch; by default it is 0, that means all regions are fetched |
GMQLDataset object. It contains the value to use as input for the subsequent GMQLDataset method
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ## This statement initializes and runs the GMQL server for local execution
## and creation of results on disk. Then, with system.file() it defines
## the path to the folder "DATASET" in the subdirectory "example"
## of the package "RGMQL" and opens such file as a GMQL dataset named
## "data" using CustomParser
init_gmql()
test_path <- system.file("example", "DATASET", package = "RGMQL")
data = read_gmql(test_path)
## The following statement orders the samples according to the Region_Count
## metadata attribute and takes the two samples that have the highest count.
o = arrange(data, list(ASC("Region_Count")), fetch_opt = "mtop",
num_fetch = 2)
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