plot_ts {BINCOR}

Plot time series

Description

The plot_ts function plot and compare the irregular and the binned time series. plot_ts has several parameters that are described in the following lines.

Usage

plot_ts(ts1, ts2, bints1, bints2, varnamets1="", varnamets2="", colts1=1, colts2=1, 
 colbints1=2, colbints2=2, ltyts1=1, ltyts2=1, ltybints1=2, ltybints2=2, 
 device="screen", Hfig, Wfig, Hpdf, Wpdf, resfig, ofilename)

Arguments

ts1, ts2

ts1 and ts2 are the unevenly spaced time series.

bints1, bints2

The bints1 and bints2 are the binned time series.

varnamets1, varnamets2

varnamets[1][2] are the names of the variables under study.

colts1, colts2

colts[1][2] are the colours for the time series (irregular) under study (by default both curves are in black).

colbints1, colbints2

colbints[1][2] are the colours of the binned time series (by default both curves are in red).

ltyts1, ltyts2

ltyts[1][2] are the type of lines to be plotted for the irregular time series (by default is 1, i.e., solid). 1 = solid, 2 = dashed, 3 = dotted, 4 = dot-dashed, 5 = long-dashed, 6 = double-dashed.

ltybints1, ltybints2

ltybints[1][2] are the type of lines to be plotted for the binned time series (by default is 2, i.e., dashed). 1 = solid, 2 = dashed, 3 = dotted, 4 = dot-dashed, 5 = long-dashed, 6 = double-dashed.

device

The type of the output device (by default the option is “screen”, and the other options are “jpg”, “png” and “pdf”).

Hfig

The height for the plot in “jpg” or “png” format.

Wfig

The width for the plot in “jpg” or “png” format.

Hpdf

The height for the plot in “pdf” format.

Wpdf

The width for the plot in “pdf” format.

resfig

resfig is the plot resolution in 'ppi' (by default R does not record a resolution in the image file, except for BMP), an adequate value could be 150 ppi.

ofilename

The output filename for the plot.

Details

The plot_ts function is used to plot the irregular vs. the binned time series and this function uses the native R function “plot” (package:graphics).

Value

Output:

Output plot: screen or 'ofilename + .png, .jpg or .pdf'.

Author(s)

Josué M. Polanco-Martínez (a.k.a. jomopo).
BC3 - Basque Centre for Climate Change, Bilbao, SPAIN.
EPOC UMR CNRS 5805 - U. de Bordeaux, Pessac, FRANCE.
Web1: https://scholar.google.es/citations?user=8djLIhcAAAAJ&hl=en.
Web2: http://www.researchgate.net/profile/Josue_Polanco-Martinez.
Email: [e-mail]

References

Polanco-Martínez, J.M., Medina-Elizalde, M.A., Sánchez Goñi, M.F., M. Mudelsee. (2018). BINCOR: an R package to estimate the correlation between two unevenly spaced series. Ms. under review (second round).

Examples

 #####################################################################
 #::  Figure 1 (Polanco-Martínez et al. (2018), (mimeo)). 
 #####################################################################
 library("BINCOR") 

 #####################################################################
 #:: Loading the time series under analysis: example 1 (ENSO vs. NHSST) 
 #####################################################################
 data(ENSO) 
 data(NHSST)

 #####################################################################
 # Computing the binned time series though our bin_cor_function.R 
 #####################################################################
 bincor.tmp    <- bin_cor(ENSO.dat, NHSST.dat, FLAGTAU=3, "output_ENSO_NHSST.tmp")
 binnedts      <- bincor.tmp$Binned_time_series

 #####################################################################
 # Testing our plot_ts function
 #####################################################################
 # "Screen" 
 plot_ts(ENSO.dat, NHSST.dat, binnedts[,1:2], binnedts[,c(1,3)], "ENSO-Nino3", 
  "SST NH Mean", colts1=1, colts2=2, colbints1=3, colbints2=4, device="screen")
 
 # PDF format
 plot_ts(ENSO.dat, NHSST.dat, binnedts[,1:2], binnedts[,c(1,3)], "ENSO-Nino3", 
  "SST NH Mean", colts1=1, colts2=2, colbints1=3, colbints2=4, device="pdf", 
  Hpdf=6, Wpdf=9, resfig=300, ofilename="plot_ts_RAW_BIN_enso_sst") 

 # PNG format 
 plot_ts(ENSO.dat, NHSST.dat, binnedts[,1:2], binnedts[,c(1,3)], "ENSO-Nino3", 
  "SST NH Mean", colts1=1, colts2=2, colbints1=3, colbints2=4, device="png", 
  Hfig=900, Wfig=1200, resfig=150, ofilename="plot_ts_RAW_BIN_enso_sst") 

 #####################################################################
 #::  Figure 4 (Polanco-Martínez et al. (2017), (mimeo)). 
 #####################################################################

 #####################################################################
 #:: Loading the time series under analysis: example 2 (pollen ACER)  
 #####################################################################
 data(MD04_2845_siteID31)
 data(MD95_2039_siteID32)

 #####################################################################
 # Computing the binned time series though our bin_cor function 
 #####################################################################
 bincor.tmp <- bin_cor(ID31.dat, ID32.dat, FLAGTAU=3, "salida_ACER_ABRUPT.tmp")
 binnedts   <- bincor.tmp$Binned_time_series

 # To avoid NA's values  
 bin_ts1    <- na.omit(bincor.tmp$Binned_time_series[,1:2])
 bin_ts2    <- na.omit(bincor.tmp$Binned_time_series[,c(1,3)]) 

 #####################################################################
 # Testing our plot_ts function: plot_ts.R
 #####################################################################
 # "Screen" 
 plot_ts(ID31.dat, ID32.dat, bin_ts1, bin_ts2, "MD04-2845 (Temp. forest)", 
  "MD95-2039 (Temp. forest )", colts1=1, colts2=2, colbints1=3, colbints2=4,
  device="screen") 

 # PDF format
 plot_ts(ID31.dat, ID32.dat, bin_ts1, bin_ts2, "MD04-2845 (Temp. forest)", 
  "MD95-2039 (Temp. forest )", colts1=1, colts2=2, colbints1=3, colbints2=4, 
  device="pdf", Hpdf=6, Wpdf=9, resfig=300, ofilename="ts_ACER_ABRUPT") 

 # PNG format 
 plot_ts(ID31.dat, ID32.dat, bin_ts1, bin_ts2, "MD04-2845 (Temp. forest)", 
  "MD95-2039 (Temp. forest )", colts1=1, colts2=2, colbints1=3, colbints2=4, 
  device="png",  Hfig=900, Wfig=1200, resfig=150, ofilename="ts_ACER_ABRUPT")