sample_toydata: Sample Toydata

In RGAN: Generative Adversarial Nets (GAN) in R

Sample Toydata

Description

Sample Toydata to reproduce the examples in the paper.

Usage

sample_toydata(n = 1000, sd = 0.3, seed = 20211111)

Arguments

n	Number of observations to generate
sd	Standard deviation of the normal distribution to generate y
seed	A seed for the pseudo random number generator

Value

A matrix with two columns x and y

Examples

## Not run: 
# Before running the first time the torch backend needs to be installed
torch::install_torch()
# Load data
data <- sample_toydata()
# Build new transformer
transformer <- data_transformer$new()
# Fit transformer to data
transformer$fit(data)
# Transform data and store as new object
transformed_data <-  transformer$transform(data)
# Train the default GAN
trained_gan <- gan_trainer(transformed_data)
# Sample synthetic data from the trained GAN
synthetic_data <- sample_synthetic_data(trained_gan, transformer)
# Plot the results
GAN_update_plot(data = data,
synth_data = synthetic_data,
main = "Real and Synthetic Data after Training")

## End(Not run)

RGAN documentation built on March 30, 2022, 1:07 a.m.