mipplot_point: Point plot from IAMC data

In UTokyo-mip/mipplot: An Open-Source Tool for Visualization of Climate Mitigation Scenarios

Description

The function arguments include the input dataframe, labels for the plot/axes/legend, and faceting dimensions

Usage

mipplot_point(
  D,
  region = levels(D$region),
  variable = levels(D$variable),
  target_year = levels(as.factor(D$period)),
  colorby = "model",
  shapeby = "model",
  xby = "scenario",
  facetby = NULL,
  facet_x = NULL,
  facet_y = NULL,
  fontsize = 20,
  PRINT_OUT = FALSE,
  DEBUG = TRUE
)

Arguments

D	A dataframe of IAMC data in tibble format to produce plots.
region	A list of regions.
variable	A list of variables.
target_year	A list of target years.
colorby	An axis for color setting.
shapeby	An axis for shape setting.
xby	An axis for x locating setting.
facetby	facetby.
facet_x	facet_x.
facet_y	facet_y.
fontsize	font size.
PRINT_OUT	set TRUE to generate PDF image.
DEBUG	set TRUE to show debug messages.

Value

A list of point plots.

Examples

library(dplyr)
data_subset <- ar5_db_sample_data %>%
filter(variable == "Emissions|CO2|Land Use") %>%
filter(model %in% c("AIM-Enduse 12.1", "GCAM 3.0", "IMAGE 2.4")) %>%
filter(period == 2100) %>% filter(region == "OECD90")
mipplot_point(data_subset)

UTokyo-mip/mipplot documentation built on Aug. 7, 2021, 6:25 p.m.