datastream_file: File data stream

In RMOA: Connect R with MOA for Massive Online Analysis

File data stream

Description

Reference object of class datastream_file. This is a class which inherits from class datastream and which can be used to read in a stream from a file. A number of file readers have been implemented, namely datastream_table, datastream_csv, datastream_csv2, datastream_delim, datastream_delim2.
See the examples.

Arguments

description	The name how the stream is labelled
FUN	The function to use to read in the file. Defaults to read.table for datastream_table, read.csv for datastream_csv, read.csv2 for datastream_csv2, read.delim for datastream_delim, read.delim2 for datastream_delim2
columnnames	optional character vector of column to overwrite the column names of the data read in with in get_points
file	The file to read in. See e.g. read.table
...	parameters passed on to FUN. See e.g. read.table

Value

A class of type datastream_file which contains

FUN:

The function to use to read in the file

connection:

A connection to the file

columnnames:

A character vector of column names to overwrite the column names with in get_points

all fields of the datastream superclass:

See datastream

Methods

• get_points(n) Get data from a datastream object.

  n

  integer, indicating the number of instances to retrieve from the datastream

See Also

read.table, read.csv, read.csv2, read.delim, read.delim2

Examples

mydata <- iris
mydata$Species[2:3] <- NA
## Example of a CSV file stream
myfile <- tempfile()
write.csv(iris, file = myfile, row.names=FALSE, na = "")
x <- datastream_csv(file = myfile, na.strings = "")
x
x$get_points(n=10)
x
x$get_points(n=10)
x
x$stop()

## Create your own specific file stream
write.table(iris, file = myfile, row.names=FALSE, na = "")
x <- datastream_file(description="My file defintion stream", FUN=read.table, 
 file = myfile, header=TRUE, na.strings="")
x$get_points(n=10)
x
x$stop()


## Clean up for CRAN
file.remove(myfile)

RMOA documentation built on July 18, 2022, 1:05 a.m.