intubate (version 1.0.0)

gplots: Interfaces for gplots package for data science pipelines.

Description

Interfaces to gplots functions that can be used in a pipeline implemented by magrittr.

Usage

ntbt_bandplot(data, ...)
ntbt_lowess(data, ...)
ntbt_overplot(data, ...)
ntbt_plotmeans(data, ...)

Arguments

data

data frame, tibble, list, ...

...

Other arguments passed to the corresponding interfaced function.

Value

Object returned by interfaced function.

Details

Interfaces call their corresponding interfaced function.

Examples

## Not run: 
# library(intubate)
# library(magrittr)
# library(gplots)
# 
# 
# ## ntbt_bandplot: Plot x-y Points with Locally Smoothed Mean and Standard Deviation
# x <- 1:1000
# y <- rnorm(1000, mean=1, sd=1 + x/1000 )
# dta <- data.frame(x, y)
# rm(x, y)
# 
# ## Original function to interface
# bandplot(y ~ x, data = dta)
# 
# ## The interface puts data as first parameter
# ntbt_bandplot(dta, y ~ x)
# 
# ## so it can be used easily in a pipeline.
# dta %>%
#   ntbt_bandplot(y ~ x)
# 
# 
# ## ntbt_lowess: Scatter Plot Smoothing
# ## Original function to interface
# lowess(dist ~ speed, data = cars)
# 
# ## The interface puts data as first parameter
# ntbt_lowess(cars, dist ~ speed)
# 
# ## so it can be used easily in a pipeline.
# cars %>%
#   ntbt_lowess(dist ~ speed)
# 
# cars %>%
#   ntbt_plot(dist ~ speed, main="lowess(cars)") %>%
#   ntbt_lowess(dist ~ speed) %>%
#   lines(col=2, lty=2)
# 
# 
# ## ntbt_overplot: Plot multiple variables on the same region,
# ##                with appropriate axes
# data(rtPCR)
# 
# ## Original function to interface
# overplot(RQ ~ Conc..ug.ml. | Test.Substance,
#          data = rtPCR,
#          subset = Detector == "ProbeType 1" & Conc..ug.ml. > 0,
#          same.scale = TRUE,
#          log="xy",
#          f=3/4,
#          main="Detector=ProbeType 1",
#          xlab="Concentration (ug/ml)",
#          ylab="Relative Gene Quantification"
# )## Original function to interface
# 
# ## The interface puts data as first parameter
# ntbt_overplot(rtPCR,
#               RQ ~ Conc..ug.ml. | Test.Substance,
#               subset = Detector == "ProbeType 1" & Conc..ug.ml. > 0,
#               same.scale = TRUE,
#               log="xy",
#               f=3/4,
#               main="Detector=ProbeType 1",
#               xlab="Concentration (ug/ml)",
#               ylab="Relative Gene Quantification"
# )## Original function to interface
# 
# ## so it can be used easily in a pipeline.
# rtPCR %>%
#   ntbt_overplot(RQ ~ Conc..ug.ml. | Test.Substance,
#                 subset = Detector == "ProbeType 1" & Conc..ug.ml. > 0,
#                 same.scale = TRUE,
#                 log="xy",
#                 f=3/4,
#                 main="Detector=ProbeType 1",
#                 xlab="Concentration (ug/ml)",
#                 ylab="Relative Gene Quantification"
#   )## Original function to interface
# 
# 
# ## ntbt_plotmeans: Plot Group Means and Confidence Intervals
# data(state)
# dta <- data.frame(state.abb, state.region)
# 
# ## Original function to interface
# plotmeans(state.area ~ state.region, data = dta)
# 
# ## The interface puts data as first parameter
# ntbt_plotmeans(dta, state.area ~ state.region)
# 
# ## so it can be used easily in a pipeline.
# dta %>%
#   ntbt_plotmeans(state.area ~ state.region)
# ## End(Not run)