wc.phasediff.image: Image plot of phase differences of periodic components for...
In WaveletComp: Computational Wavelet Analysis
Description
Usage
Arguments
Value
Author(s)
References
See Also
Examples
View source: R/wc.phasediff.image.R
Description
This function plots the phase difference image of two time series, which is
provided by an object of class "analyze.coherency".
The vertical axis shows the Fourier periods. The horizontal axis shows time step counts, but can
be easily transformed into a calendar axis if dates are provided in either row names or a variable
named "date" in the data frame at hand. Both axes can be relabeled.
In particular, an option is given to individualize the period and/or time axis
by specifying tick marks and labels.
The color levels are defined according to equidistant breakpoints
(covering the interval from -pi to +pi), with the number of levels
as a further parameter. In addition, there is an option to adopt
an individual color palette.
If the default palette is retained, colors indicate the following. Green:
phase differences close to zero, which means that the two time
series are in phase at the respective period. Yellowgreen: in
phase, series 1 leading. Turquoise: in phase, series 2 leading.
Red: phase differences are close to +pi, out of phase, series
2 leading. Blue: phase differences are close to -pi, out of
phase, series 1 leading.
Further plot design options concern: plot of the cone of
influence, plot of contour lines to border areas of significance
with respect to cross-wavelet power or wavelet coherence at a
given significance level.
Finally, there is an option to insert and format a color legend (a
right-hand vertical color bar) and to set the plot title. For
further processing of the plot, graphical parameters of plot
regions are provided as output.
Usage
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wc.phasediff.image(WC, use.sAngle = FALSE,
plot.coi = TRUE,
plot.contour = TRUE, which.contour = "wp",
siglvl = 0.1, col.contour = "white",
n.levels = 100,
color.palette = "rainbow(n.levels, start = 0, end = .7)",
useRaster = TRUE, max.contour.segments = 250000,
plot.legend = TRUE,
legend.params = list(width = 1.2, shrink = 0.9, mar = 5.1,
n.ticks = 6,
pi.style = TRUE,
label.digits = 1, label.format = "f",
lab = NULL, lab.line = 3),
label.time.axis = TRUE,
show.date = FALSE, date.format = NULL, date.tz = NULL,
timelab = NULL, timetck = 0.02, timetcl = 0.5,
spec.time.axis = list(at = NULL, labels = TRUE,
las = 1, hadj = NA, padj = NA),
label.period.axis = TRUE,
periodlab = NULL, periodtck = 0.02, periodtcl = 0.5,
spec.period.axis = list(at = NULL, labels = TRUE,
las = 1, hadj = NA, padj = NA),
main = NULL,
lwd = 2, lwd.axis = 1,
graphics.reset = TRUE,
verbose = FALSE)
Arguments
WC
an object of class "analyze.coherency"
use.sAngle
Use smoothed version of phase difference? Logical.
Default: FALSE.
plot.coi
Plot cone of influence? Logical. Default: TRUE
plot.contour
Plot contour lines to border the area of cross-wavelet power (or wavelet coherence,
depending on which.contour) significance? Logical.
Default: TRUE.
which.contour
Contour lines of which spectrum should be plotted?
"wp" : cross-wavelet power
"wc" : wavelet coherence
Default: "wp".
siglvl
level of cross-wavelet power (or wavelet coherence, depending on which.contour)
significance to be applied to the plot of contour lines.
Default: 0.1.
col.contour
color of contour lines. Default: "white".
n.levels
Number of color levels. Default: 100.
color.palette
Definition of color levels. (The color palette will be assigned to levels in reverse order!)
Default: "rainbow(n.levels, start = 0, end = .7)".
useRaster
Use a bitmap raster instead of polygons to plot the image? Logical.
Default: TRUE.
max.contour.segments
limit on the number of segments in a single contour line, positive integer.
Default: 250000 (options(...) default settings: 25000).
plot.legend
Plot color legend (a vertical bar of colors and breakpoints)? Logical.
Default: TRUE.
legend.params
a list of parameters for the plot of the color legend; parameter values can be set selectively
(style in parts adopted from image.plot in the R package fields by Douglas Nychka):
[width:] width of legend bar.
Default: 1.2.
[shrink:] a vertical shrinkage factor.
Default: 0.9.
[mar:] right margin of legend bar.
Default: 5.1.
[n.ticks:] number of ticks for labels.
Default: 6.
[pi.style:] style of labels, logical: if TRUE, the symbol "pi" is used to label the legend bar; otherwise, labels are numerals.
Default: TRUE.
[label.digits:] number of digits of (numerical factors of) labels.
Default: 1 if pi.style is TRUE, else 2.
[label.format:] format of labels.
Default: "f".
[lab:] axis label.
Default: NULL.
[lab.line:] line (in user coordinate units) where to put the axis label.
Default: 3.
label.time.axis
Label the time axis? Logical.
Default: TRUE.
show.date
Show calendar dates? (Effective only if dates are available as row names or by variable
date in the data frame which is analyzed.) Logical.
Default: FALSE.
date.format
the format of calendar date given as a character string, e.g. "%Y-%m-%d", or equivalently "%F";
see strptime for a list of implemented date conversion specifications. Explicit information given here will overturn any specification
stored in WC. If unspecified, date formatting is attempted according to as.Date.
Default: NULL.
date.tz
a character string specifying the time zone of calendar date; see strptime. Explicit information given here will overturn
any specification stored in WC. If unspecified, "" (the local time zone) is used.
Default: NULL.
timelab
Time axis label.
Default: "index"; in case of a calendar axis: "calendar date".
timetck
length of tick marks on the time axis as a fraction of the smaller of the width or height of the plotting region; see par.
If timetck >= 0.5, timetck is interpreted as a fraction of the length of the time axis, so if timetck = 1
(and timetcl = NULL), vertical grid lines will be drawn.
Setting timetck = NA is to use timetcl = -0.5 (which is the R default setting of tck and tcl).
Default here: 0.02.
timetcl
length of tick marks on the time axis as a fraction of the height of a line of text; see par.
With timetcl = -0.5 (which is the R default setting of tcl), ticks will be drawn outward.
Default here: 0.5.
spec.time.axis
a list of tick mark and label specifications for individualized time axis labeling
(only effective if label.time.axis = TRUE):
[at:] locations of tick marks (when NULL, default plotting will be applied).
Valid tick marks can be provided as numerical values or as dates. Dates are used only in the case show.date = TRUE, however,
and date formats should conform to as.Date or the format given in date.format.
Default: NULL.
[labels:] either a logical value specifying whether annotations at the tick marks are the tick marks themselves,
or any vector of labels. If labels is non-logical, at should be of same length.
Default: TRUE.
[las:] the style of axis labels, see par.
Default: 1 (always horizontal).
[hadj:] adjustment of labels horizontal to the reading direction, see axis.
Default: NA (centering is used).
[padj:] adjustment of labels perpendicular to the reading direction (this can be a vector of adjustments for each label),
see axis.
Default: NA (centering is used).
Mismatches will result in a reset to default plotting.
label.period.axis
Label the (Fourier) period axis? Logical.
Default: TRUE.
periodlab
(Fourier) period axis label.
Default: "period".
periodtck
length of tick marks on the period axis as a fraction of the smaller of the width or height
of the plotting region; see par. If periodtck >= 0.5, periodtck is interpreted as a fraction
of the length of the period axis, so if periodtck = 1 (and periodtcl = NULL), horizontal grid lines will be drawn.
Setting periodtck = NA is to use periodtcl = -0.5 (which is the R default setting of tck and tcl).
Default here: 0.02.
periodtcl
length of tick marks on the period axis as a fraction of the height of a line of text; see par.
With periodtcl = -0.5 (which is the R default setting of tcl) ticks will be drawn outward.
Default here: 0.5.
spec.period.axis
a list of tick mark and label specifications for individualized period axis labeling
(only effective if label.period.axis = TRUE):
[at:] locations of tick marks (when NULL, default plotting will be applied). Valid tick marks can be provided as
numerical and positive values only.
Default: NULL.
[labels:] either a logical value specifying whether annotations at the tick marks are the tick marks themselves,
or any vector of labels. If labels is non-logical, at should be of same length.
Default: TRUE.
[las:] the style of axis labels, see par.
Default: 1 (always horizontal).
[hadj:] adjustment of labels horizontal to the reading direction, see axis.
Default: NA (centering is used).
[padj:] adjustment of labels perpendicular to the reading direction (this can be a vector of adjustments for each label),
see axis.
Default: NA (centering is used).
Mismatches will result in a reset to default plotting.
main
an overall title for the plot.
Default: NULL.
lwd
line width of contour lines and ridge.
Default: 2.
lwd.axis
line width of axes (image and legend bar).
Default: 1.
graphics.reset
Reset graphical parameters? Logical.
Default: TRUE.
verbose
Print verbose output on the screen? Logical.
Default: FALSE.
Value
A list of class graphical parameters with the following elements:
op
original graphical parameters
image.plt
image plot region
legend.plt
legend plot region
Author(s)
Angi Roesch and Harald Schmidbauer
References
Aguiar-Conraria L., and Soares M.J., 2011.
Business cycle synchronization and the Euro: A wavelet analysis.
Journal of Macroeconomics 33 (3), 477–489.
Aguiar-Conraria L., and Soares M.J., 2011.
The Continuous Wavelet Transform: A Primer.
NIPE Working Paper Series 16/2011.
Cazelles B., Chavez M., Berteaux, D., Menard F., Vik J.O., Jenouvrier S., and Stenseth N.C., 2008.
Wavelet analysis of ecological time series.
Oecologia 156, 287–304.
Liu P.C., 1994.
Wavelet spectrum analysis and ocean wind waves.
In: Foufoula-Georgiou E., and Kumar P., (eds.), Wavelets in Geophysics, Academic Press, San Diego, 151–166.
Torrence C., and Compo G.P., 1998.
A practical guide to wavelet analysis.
Bulletin of the American Meteorological Society 79 (1), 61–78.
Veleda D., Montagne R., and Araujo M., 2012.
Cross-Wavelet Bias Corrected by Normalizing Scales.
Journal of Atmospheric and Oceanic Technology 29, 1401–1408.
See Also
analyze.coherency, wc.image, wc.avg, wc.sel.phases, wt.image, wt.avg, wt.sel.phases, wt.phase.image, reconstruct
Examples
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## Not run:
## The following example is modified from Veleda et al., 2012:
series.length <- 3*128*24
x1 <- periodic.series(start.period = 1*24, length = series.length)
x2 <- periodic.series(start.period = 2*24, length = series.length)
x3a <- periodic.series(start.period = 4*24, length = series.length)
x3b <- periodic.series(start.period = 4*24, length = series.length,
phase = 24)
x4 <- periodic.series(start.period = 8*24, length = series.length)
x5 <- periodic.series(start.period = 16*24, length = series.length)
x6 <- periodic.series(start.period = 32*24, length = series.length)
x7 <- periodic.series(start.period = 64*24, length = series.length)
x8 <- periodic.series(start.period = 128*24, length = series.length)
x <- x1 + x2 + x3a + x4 + 3*x5 + x6 + x7 + x8 + rnorm(series.length)
y <- x1 + x2 + x3b + x4 - 3*x5 + x6 + 3*x7 + x8 + rnorm(series.length)
matplot(data.frame(x, y), type = "l", lty = 1, xaxs = "i", col = 1:2,
xlab = "index", ylab = "",
main = "hourly series with periods of 1, 2, 4, 8, 16, 32, 64, 128 days",
sub = "(different phases at periods 4 and 16)")
legend("topright", legend = c("x","y"), col = 1:2, lty = 1)
## The following dates refer to the local time zone
## (possibly allowing for daylight saving time):
my.date <- seq(as.POSIXct("2014-10-14 00:00:00", format = "%F %T"),
by = "hour",
length.out = series.length)
my.data <- data.frame(date = my.date, x = x, y = y)
## Computation of cross-wavelet power and wavelet coherence, x over y:
## a natural choice of 'dt' in the case of hourly data is 'dt = 1/24',
## resulting in one time unit equaling one day.
## This is also the time unit in which periods are measured.
my.wc <- analyze.coherency(my.data, c("x","y"),
loess.span = 0,
dt = 1/24, dj = 1/20,
window.size.t = 1, window.size.s = 1/2,
lowerPeriod = 1/4,
make.pval = TRUE, n.sim = 10)
## Plot of cross-wavelet power spectrum,
## with color breakpoints according to quantiles:
wc.image(my.wc,
main = "cross-wavelet power spectrum, x over y",
legend.params = list(lab = "cross-wavelet power levels (quantiles)"),
periodlab = "period (days)")
## Default plot of phase differences
## (with contour lines referring to cross-wavelet power)
wc.phasediff.image(my.wc, which.contour = "wp",
main = "image of phase differences, x over y",
periodlab = "period (days)")
## With time elapsed in days
## (starting from 0 and proceeding in steps of 50 days)
## instead of the (default) time index:
index.ticks <- seq(1, series.length, by = 50*24)
index.labels <- (index.ticks-1)/24
wc.phasediff.image(my.wc, which.contour = "wp",
main = "image of phase differences, x over y",
periodlab = "period (days)",
timelab = "time elapsed (days)",
spec.time.axis = list(at = index.ticks, labels = index.labels))
## The same plot, but with (automatically produced) calendar axis:
wc.phasediff.image(my.wc, which.contour = "wp",
main = "image of phase differences, x over y",
periodlab = "period (days)",
show.date = TRUE, date.format = "%F %T")
## For further axis plotting options:
## Please see the examples in our guide booklet,
## URL http://www.hs-stat.com/projects/WaveletComp/WaveletComp_guided_tour.pdf.
## Plot of phase difference with numerals as labels of the color legend bar:
wc.phasediff.image(my.wc,
legend.params=list(pi.style = FALSE, label.digits = 2))
## End(Not run)
WaveletComp documentation built on May 2, 2019, 6:33 a.m.
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Description Usage Arguments Value Author(s) References See Also Examples
View source: R/wc.phasediff.image.R
Description
This function plots the phase difference image of two time series, which is
provided by an object of class "analyze.coherency".
The vertical axis shows the Fourier periods. The horizontal axis shows time step counts, but can
be easily transformed into a calendar axis if dates are provided in either row names or a variable
named "date" in the data frame at hand. Both axes can be relabeled.
In particular, an option is given to individualize the period and/or time axis
by specifying tick marks and labels.
The color levels are defined according to equidistant breakpoints
(covering the interval from -pi to +pi), with the number of levels
as a further parameter. In addition, there is an option to adopt
an individual color palette.
If the default palette is retained, colors indicate the following. Green:
phase differences close to zero, which means that the two time
series are in phase at the respective period. Yellowgreen: in
phase, series 1 leading. Turquoise: in phase, series 2 leading.
Red: phase differences are close to +pi, out of phase, series
2 leading. Blue: phase differences are close to -pi, out of
phase, series 1 leading.
Further plot design options concern: plot of the cone of influence, plot of contour lines to border areas of significance with respect to cross-wavelet power or wavelet coherence at a given significance level.
Finally, there is an option to insert and format a color legend (a right-hand vertical color bar) and to set the plot title. For further processing of the plot, graphical parameters of plot regions are provided as output.
Usage
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | wc.phasediff.image(WC, use.sAngle = FALSE,
plot.coi = TRUE,
plot.contour = TRUE, which.contour = "wp",
siglvl = 0.1, col.contour = "white",
n.levels = 100,
color.palette = "rainbow(n.levels, start = 0, end = .7)",
useRaster = TRUE, max.contour.segments = 250000,
plot.legend = TRUE,
legend.params = list(width = 1.2, shrink = 0.9, mar = 5.1,
n.ticks = 6,
pi.style = TRUE,
label.digits = 1, label.format = "f",
lab = NULL, lab.line = 3),
label.time.axis = TRUE,
show.date = FALSE, date.format = NULL, date.tz = NULL,
timelab = NULL, timetck = 0.02, timetcl = 0.5,
spec.time.axis = list(at = NULL, labels = TRUE,
las = 1, hadj = NA, padj = NA),
label.period.axis = TRUE,
periodlab = NULL, periodtck = 0.02, periodtcl = 0.5,
spec.period.axis = list(at = NULL, labels = TRUE,
las = 1, hadj = NA, padj = NA),
main = NULL,
lwd = 2, lwd.axis = 1,
graphics.reset = TRUE,
verbose = FALSE)
|
Arguments
WC |
an object of class |
use.sAngle |
Use smoothed version of phase difference? Logical. Default: |
plot.coi |
Plot cone of influence? Logical. Default: |
plot.contour |
Plot contour lines to border the area of cross-wavelet power (or wavelet coherence,
depending on Default: | ||||||||
which.contour |
Contour lines of which spectrum should be plotted?
Default: | ||||||||
siglvl |
level of cross-wavelet power (or wavelet coherence, depending on Default: | ||||||||
col.contour |
color of contour lines. Default: |
n.levels |
Number of color levels. Default: |
color.palette |
Definition of color levels. (The color palette will be assigned to levels in reverse order!) Default: |
useRaster |
Use a bitmap raster instead of polygons to plot the image? Logical. Default: |
max.contour.segments |
limit on the number of segments in a single contour line, positive integer. Default: |
plot.legend |
Plot color legend (a vertical bar of colors and breakpoints)? Logical. Default: |
legend.params |
a list of parameters for the plot of the color legend; parameter values can be set selectively
(style in parts adopted from
|
label.time.axis |
Label the time axis? Logical. Default: |
show.date |
Show calendar dates? (Effective only if dates are available as row names or by variable
Default: |
date.format |
the format of calendar date given as a character string, e.g. Default: |
date.tz |
a character string specifying the time zone of calendar date; see Default: |
timelab |
Time axis label. Default: |
timetck |
length of tick marks on the time axis as a fraction of the smaller of the width or height of the plotting region; see Default here: |
timetcl |
length of tick marks on the time axis as a fraction of the height of a line of text; see Default here: |
spec.time.axis |
a list of tick mark and label specifications for individualized time axis labeling
(only effective if
Mismatches will result in a reset to default plotting. |
label.period.axis |
Label the (Fourier) period axis? Logical. Default: |
periodlab |
(Fourier) period axis label. Default: |
periodtck |
length of tick marks on the period axis as a fraction of the smaller of the width or height
of the plotting region; see Default here: |
periodtcl |
length of tick marks on the period axis as a fraction of the height of a line of text; see Default here: |
spec.period.axis |
a list of tick mark and label specifications for individualized period axis labeling
(only effective if
Mismatches will result in a reset to default plotting. |
main |
an overall title for the plot. Default: |
lwd |
line width of contour lines and ridge. Default: |
lwd.axis |
line width of axes (image and legend bar). Default: |
graphics.reset |
Reset graphical parameters? Logical. Default: |
verbose |
Print verbose output on the screen? Logical. Default: |
Value
A list of class graphical parameters with the following elements:
op |
original graphical parameters |
image.plt |
image plot region |
legend.plt |
legend plot region |
Author(s)
Angi Roesch and Harald Schmidbauer
References
Aguiar-Conraria L., and Soares M.J., 2011. Business cycle synchronization and the Euro: A wavelet analysis. Journal of Macroeconomics 33 (3), 477–489.
Aguiar-Conraria L., and Soares M.J., 2011. The Continuous Wavelet Transform: A Primer. NIPE Working Paper Series 16/2011.
Cazelles B., Chavez M., Berteaux, D., Menard F., Vik J.O., Jenouvrier S., and Stenseth N.C., 2008. Wavelet analysis of ecological time series. Oecologia 156, 287–304.
Liu P.C., 1994. Wavelet spectrum analysis and ocean wind waves. In: Foufoula-Georgiou E., and Kumar P., (eds.), Wavelets in Geophysics, Academic Press, San Diego, 151–166.
Torrence C., and Compo G.P., 1998. A practical guide to wavelet analysis. Bulletin of the American Meteorological Society 79 (1), 61–78.
Veleda D., Montagne R., and Araujo M., 2012. Cross-Wavelet Bias Corrected by Normalizing Scales. Journal of Atmospheric and Oceanic Technology 29, 1401–1408.
See Also
analyze.coherency, wc.image, wc.avg, wc.sel.phases, wt.image, wt.avg, wt.sel.phases, wt.phase.image, reconstruct
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 | ## Not run:
## The following example is modified from Veleda et al., 2012:
series.length <- 3*128*24
x1 <- periodic.series(start.period = 1*24, length = series.length)
x2 <- periodic.series(start.period = 2*24, length = series.length)
x3a <- periodic.series(start.period = 4*24, length = series.length)
x3b <- periodic.series(start.period = 4*24, length = series.length,
phase = 24)
x4 <- periodic.series(start.period = 8*24, length = series.length)
x5 <- periodic.series(start.period = 16*24, length = series.length)
x6 <- periodic.series(start.period = 32*24, length = series.length)
x7 <- periodic.series(start.period = 64*24, length = series.length)
x8 <- periodic.series(start.period = 128*24, length = series.length)
x <- x1 + x2 + x3a + x4 + 3*x5 + x6 + x7 + x8 + rnorm(series.length)
y <- x1 + x2 + x3b + x4 - 3*x5 + x6 + 3*x7 + x8 + rnorm(series.length)
matplot(data.frame(x, y), type = "l", lty = 1, xaxs = "i", col = 1:2,
xlab = "index", ylab = "",
main = "hourly series with periods of 1, 2, 4, 8, 16, 32, 64, 128 days",
sub = "(different phases at periods 4 and 16)")
legend("topright", legend = c("x","y"), col = 1:2, lty = 1)
## The following dates refer to the local time zone
## (possibly allowing for daylight saving time):
my.date <- seq(as.POSIXct("2014-10-14 00:00:00", format = "%F %T"),
by = "hour",
length.out = series.length)
my.data <- data.frame(date = my.date, x = x, y = y)
## Computation of cross-wavelet power and wavelet coherence, x over y:
## a natural choice of 'dt' in the case of hourly data is 'dt = 1/24',
## resulting in one time unit equaling one day.
## This is also the time unit in which periods are measured.
my.wc <- analyze.coherency(my.data, c("x","y"),
loess.span = 0,
dt = 1/24, dj = 1/20,
window.size.t = 1, window.size.s = 1/2,
lowerPeriod = 1/4,
make.pval = TRUE, n.sim = 10)
## Plot of cross-wavelet power spectrum,
## with color breakpoints according to quantiles:
wc.image(my.wc,
main = "cross-wavelet power spectrum, x over y",
legend.params = list(lab = "cross-wavelet power levels (quantiles)"),
periodlab = "period (days)")
## Default plot of phase differences
## (with contour lines referring to cross-wavelet power)
wc.phasediff.image(my.wc, which.contour = "wp",
main = "image of phase differences, x over y",
periodlab = "period (days)")
## With time elapsed in days
## (starting from 0 and proceeding in steps of 50 days)
## instead of the (default) time index:
index.ticks <- seq(1, series.length, by = 50*24)
index.labels <- (index.ticks-1)/24
wc.phasediff.image(my.wc, which.contour = "wp",
main = "image of phase differences, x over y",
periodlab = "period (days)",
timelab = "time elapsed (days)",
spec.time.axis = list(at = index.ticks, labels = index.labels))
## The same plot, but with (automatically produced) calendar axis:
wc.phasediff.image(my.wc, which.contour = "wp",
main = "image of phase differences, x over y",
periodlab = "period (days)",
show.date = TRUE, date.format = "%F %T")
## For further axis plotting options:
## Please see the examples in our guide booklet,
## URL http://www.hs-stat.com/projects/WaveletComp/WaveletComp_guided_tour.pdf.
## Plot of phase difference with numerals as labels of the color legend bar:
wc.phasediff.image(my.wc,
legend.params=list(pi.style = FALSE, label.digits = 2))
## End(Not run)
|
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