Plot data - ggplot2 geom_raster

Source: R/plot.R

Function plots data with ggplot2 geom_raster. Plot is returned as ggplot faced raster and is primary designed to be saved as .pdf file (recommended) or .png file. Plotting into R environment without saving any file is also possible. See details.

mc_plot_raster(
  data,
  filename = NULL,
  sensors = NULL,
  by_hour = TRUE,
  png_width = 1900,
  png_height = 1900,
  viridis_color_map = NULL,
  start_crop = NULL,
  end_crop = NULL,
  use_utc = TRUE
)

Arguments

data

myClim object see myClim-package

filename

output with the extension - supported formats are .pdf and .png (default NULL) If NULL then the plot is shown/returned into R environment as ggplot object, but not saved to file.

sensors

names of sensor; should have same physical unit see names(mc_data_sensors)

by_hour

if TRUE, then y axis is plotted as an hour, else original time step (default TRUE)

png_width

width for png output (default 1900)

png_height

height for png output (default 1900)

viridis_color_map

viridis color map option; if NULL, then used value from mc_data_physical

  • "A" - magma

  • "B" - inferno

  • "C" - plasma

  • "D" - viridis

  • "E" - cividis

  • "F" - rocket

  • "G" - mako

  • "H" - turbo

start_crop

POSIXct datetime in UTC for crop data (default NULL)

end_crop

POSIXct datetime in UTC for crop data (default NULL)

use_utc

if FALSE, then the time shift from tz_offset metadata is used to correct (shift) the output time-series (default TRUE)

In the Agg-format myClim object use_utc = FALSE is allowed only for steps shorter than one day. In myClim the day nd longer time steps are defined by the midnight, but this represent whole day, week, month, year... shifting daily, weekly, monthly... data (shift midnight) does not make sense in our opinion. But when user need more flexibility, then myClim Raw-format can be used, In Raw-format use_utc is not limited, user can shift an data without the restrictions. See myClim-package

Value

list of ggplot2 objects

Details

Saving as the .pdf file is recommended, because the plot is optimized to be paginate PDF (facet raster plot is distributed to pages), which is especially useful for bigger data. In case of plotting multiple sensors to PDF, the facet grids are grouped by sensor. I.e., all localities of sensor_1 followed by all localities of sensor_2 etc. When plotting only few localities, but multiple sensors, each sensor has own page. I.e., when plotting data from one locality, and 3 sensors resulting PDF has 3 pages. In case of plotting PNG, sensors are plotted in separated images (PNG files) by physical. I.e, when plotting 3 sensors in PNG it will save 3 PNG files named after sensors. Be careful with bigger data in PNG. Play with png_height and png_width. When too small height/width, image does not fit and is plotted incorrectly. Plotting into R environment instead of saving PDF or PNG is possible, but is recommended only for low number of localities (e.g. up to 10), because high number of localities plotted in R environment results in very small picture which is hard/impossible to read.

Examples

tmp_dir <- tempdir()
tmp_file <- tempfile(tmpdir = tmp_dir, fileext=".pdf")
mc_plot_raster(mc_data_example_agg, filename=tmp_file, sensors=c("TMS_T3","TM_T"))
#> [[1]]

#> 
file.remove(tmp_file)
#> [1] TRUE