Plots A Score Along The Forecast Time With Its Confidence Interval
Plots The Correlation (Corr()
) or the Root Mean Square Error
(RMS()
) between the forecasted values and their observational
counterpart or the slopes of their trends (Trend()
) or the
InterQuartile Range, Maximum-Mininum, Standard Deviation or Median Absolute
Deviation of the Ensemble Members (Spread()
), or the ratio between
the Ensemble Spread and the RMSE of the Ensemble Mean (RatioSDRMS()
)
along the forecast time for all the input experiments on the same figure
with their confidence intervals.
PlotVsLTime( var, toptitle = "", ytitle = "", monini = 1, freq = 12, nticks = NULL, limits = NULL, listexp = c("exp1", "exp2", "exp3"), listobs = c("obs1", "obs2", "obs3"), biglab = FALSE, hlines = NULL, leg = TRUE, siglev = FALSE, sizetit = 1, show_conf = TRUE, fileout = "output_plotvsltime.eps", width = 8, height = 5, size_units = "in", res = 100, ... )
var |
Matrix containing any Prediction Score with dimensions: |
toptitle |
Main title, optional. |
ytitle |
Title of Y-axis, optional. |
monini |
Starting month between 1 and 12. Default = 1. |
freq |
1 = yearly, 12 = monthly, 4 = seasonal, ... Default = 12. |
nticks |
Number of ticks and labels on the x-axis, optional. |
limits |
c(lower limit, upper limit): limits of the Y-axis, optional. |
listexp |
List of experiment names, optional. |
listobs |
List of observation names, optional. |
biglab |
TRUE/FALSE for presentation/paper plot. Default = FALSE. |
hlines |
c(a,b, ..) Add horizontal black lines at Y-positions a,b, ... |
leg |
TRUE/FALSE if legend should be added or not to the plot. Default = TRUE. |
siglev |
TRUE/FALSE if significance level should replace confidence
interval. |
sizetit |
Multiplicative factor to change title size, optional. |
show_conf |
TRUE/FALSE to show/not confidence intervals for input variables. |
fileout |
Name of output file. Extensions allowed: eps/ps, jpeg, png,
pdf, bmp and tiff. |
width |
File width, in the units specified in the parameter size_units (inches by default). Takes 8 by default. |
height |
File height, in the units specified in the parameter size_units (inches by default). Takes 5 by default. |
size_units |
Units of the size of the device (file or window) to plot in. Inches ('in') by default. See ?Devices and the creator function of the corresponding device. |
res |
Resolution of the device (file or window) to plot in. See ?Devices and the creator function of the corresponding device. |
... |
Arguments to be passed to the method. Only accepts the following
graphical parameters: |
Examples of input:
Model and observed output from Load()
then Clim()
then
Ano()
then Smoothing()
:
(nmod, nmemb, nsdate, nltime) and (nobs, nmemb, nsdate, nltime)
then averaged over the membersMean1Dim(var_exp/var_obs, posdim = 2)
:
(nmod, nsdate, nltime) and (nobs, nsdate, nltime)
then passed throughCorr(exp, obs, posloop = 1, poscor = 2)
orRMS(exp, obs, posloop = 1, posRMS = 2)
:
(nmod, nobs, 3, nltime)
would plot the correlations or RMS between each exp & each obs as a function
of the forecast time.
History:
0.1 - 2011-03 (V. Guemas, virginie.guemas@ic3.cat) - Original code
0.2 - 2013-03 (I. Andreu-Burillo, isabel.andreu-burillo@ic3.cat) - Introduced parameter sizetit
0.3 - 2013-10 (I. Andreu-Burillo, isabel.andreu-burillo@ic3.cat) - Introduced parameter show_conf
1.0 - 2013-11 (N. Manubens, nicolau.manubens@ic3.cat) - Formatting to CRAN
# Load sample data as in Load() example: example(Load) clim <- Clim(sampleData$mod, sampleData$obs) ano_exp <- Ano(sampleData$mod, clim$clim_exp) ano_obs <- Ano(sampleData$obs, clim$clim_obs) runmean_months <- 12 dim_to_smooth <- 4 # Smooth along lead-times smooth_ano_exp <- Smoothing(ano_exp, runmean_months, dim_to_smooth) smooth_ano_obs <- Smoothing(ano_obs, runmean_months, dim_to_smooth) dim_to_mean <- 2 # Mean along members required_complete_row <- 3 # Discard startdates for which there are NA leadtimes leadtimes_per_startdate <- 60 corr <- Corr(Mean1Dim(smooth_ano_exp, dim_to_mean), Mean1Dim(smooth_ano_obs, dim_to_mean), compROW = required_complete_row, limits = c(ceiling((runmean_months + 1) / 2), leadtimes_per_startdate - floor(runmean_months / 2))) PlotVsLTime(corr, toptitle = "correlations", ytitle = "correlation", monini = 11, limits = c(-1, 2), listexp = c('CMIP5 IC3'), listobs = c('ERSST'), biglab = FALSE, hlines = c(-1, 0, 1), fileout = 'tos_cor.eps')
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