plot.wd(wavethresh)
plot.wd()所属R语言包：wavethresh
Plot wavelet transform coefficients.
图小波变换系数。
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function plots discrete wavelet transform coefficients arising from a wd object.
此函数曲线离散小波变换系数所产生的一个wd对象。
用法----------Usage----------
## S3 method for class 'wd':
plot(x,xlabvals, xlabchars, ylabchars, first.level = 0,
main = "Wavelet Decomposition Coefficients", scaling = "global",
rhlab = FALSE, sub, NotPlotVal = 0.005, xlab = "Translate",
ylab = "Resolution Level",
aspect = "Identity", ...)
参数----------Arguments----------
参数：x
The wd class object you wish to plot
你想绘制的WD类对象
参数：xlabvals
A vector containing the "true" x-axis numbers that went with the vector that was transformed to produce the wd object supplied as the first argument to this function. If this argument is missing then the function tries to make up a sensible set of x-axis labels.
“真正的”x轴号码的向量，转化为生产的wd对象作为这个函数的第一个参数提供了一个向量。如果此参数丢失，则该函数尝试做了一个明智的x轴的标签。
参数：xlabchars
Tickmark labels for the x axis
为x轴的刻度标记标签
参数：ylabchars
Tickmark labels for the y axis
为y轴的刻度标记标签
参数：first.level
The first resolution level to begin plotting at. This argument can be quite useful when you want to supress some of the coarser levels in the diagram.
第一项决议，开始图。当你想来说，拦截一些粗糙的水平在图中，此参数可以是非常有用的。
参数：main
The main title of the plot.
主标题的图。
参数：scaling
How you want the coefficients to be scaled. The options are: global - one scale factor is chosen for the whole plot. The scale factor depends on the coefficient to be included on the plot that has the largest absolute value. The global option is useful when comparing coefficients that might appear anywhere in the plot; by.level - a scale factor is chosen for each resolution level in the plot. The scale factor for a level depends on the coefficient in that level that has the largest absolute value. The by.level option is useful when you wish to compare coefficients within a resolution level.
你怎么想的系数进行调整。选项有：global - 选择一个比例因子是整个小区。规模因素取决于系数的绝对值最大的图，被列入。 global选项是很有用的比较系数时，可能出现在任何地方的图，“by.level - 选择比例因子为每个分辨率级别的图。的比例因子的水平依赖于在该级别的系数，具有最大绝对值。 by.level选项是有用的，当你想比较的分辨率级别内的系数。
The two other options are compensated and super which are the same as global except for that finer scales' coefficients are scaled up by a factor of SQRT(2) for compensated and 2 for super. These latter two options are sometimes useful (more useful for non-decimated wd objects, where they act as a sort of ipndacw matrix operator).
其它两种选择补偿和超级这是相同的，更精细的尺度系数除外global缩放SQRT（2）的一个因素补偿和2的超。有时后两个选项是很有用的（更适用于非锐减wd对象，他们作为一种ipndacw矩阵算）。
参数：rhlab
If TRUE then a set of labels is produced on the right hand axis. The axis labels in this case refer to the scale factors used to scale each level and correspond to value of the largest coefficient (in absolute value) in each scale (when scaling=="by.level") or absolutely (when scaling="global"). If the rhlab argument is FALSE then no right hand axis labels are produced.
如果TRUE然后右手轴线上产生一组标签。在这种情况下的轴标签是指使用的比例因子缩放每个级别对应的值在每个尺度最大的系数（绝对值）（当scaling=="by.level"）或绝对（scaling="global"） 。如果rhlab论点是FALSE然后没有右手轴标签。
参数：sub
A subtitle for the plot.
字幕的图。
参数：NotPlotVal
This argument ensures that if all (scaled) coefficients in a resolution level are below NotPlotVal in absolute value then the whole resolution level is not plotted. This can be useful when plotting a wd object that is sparse (or has been thresholded and necessarily many coefficients might well be zero) as it speeds up the plot because whole levels do not have to be plotted (the function that does the plotting [segments()] is quite a slow function). Note that the value of NotPlotVal refers to scaled coefficients, those that have been scaled by this function (on any resolution level all coefficients are scaled to lie between -0.5 and 0.5).
这个论点保证，如果所有的系数（缩放）分辨率级别下面的NotPlotVal的绝对值，然后整个决议不绘制。这可能是有用的，当策划wd对象是稀疏的（或已阈值和一定系数可能为零），因为它加快了总体水平的图，因为没有被绘制（的功能的绘制[segments()方向]是一个相当缓慢的功能）。需要注意的是NotPlotVal指scaled系数，已缩放功能（在任何分辨率级别的所有系数被调整为-0.5和0.5之间）的。
参数：xlab
A title for the x-axis
一个标题为x轴
参数：ylab
A title for the y-axis
一个标题为y轴
参数：aspect
This argument describes the name (as a character string) of a function to be applied to the coefficients before plotting. By default the argument is "Identity", i.e. the coefficients are plotted as is. This argument is most useful when a complex-valued wavelets are plotted you could use "Mod" to plot the modulus of the coefficients, or "Re" to plot the real parts of the coefficients or "Arg" to plot the argument of the coefficients. Also, the aspect argument can be useful for the ordinary wavelet transforms as well if you are interested in a particular transform of the coefficients.
此参数描述的名称（作为一个字符串）的打印之前，要施加到所述系数的函数。默认情况下的说法是“Identity”，即系数被绘制成是。这种说法是最有用的，当绘制一个复值小波，你可以使用“Mod”绘制模量的系数，或“Re”绘制的实部系数或者“ Arg“绘制参数的系数。此外，aspect参数可以是有用的，对于普通的小波变换，以及如果你有兴趣在一个特定的变换系数。
参数：...
fine tuning
微调
Details
详细信息----------Details----------
Produces a plot similar to the ones in Donoho and Johnstone, 1994.
产生类似的，在Donoho和Johnstone，1994年的一个图。
A wavelet decomposition of a signal consists of discrete wavelet coefficients at different scales (resolution levels) and locations. This function plots the coefficients as a pyramid (derived from Mallat's pyramid algorithm). See the examples below.
小波分解的信号由离散小波系数在不同尺度（分辨率级别）和地点。此函数曲线看成一个金字塔（来自Mallat的金字塔算法）的系数。请参见下面的例子。
The resolution levels are stacked one above the other: coarse scale coefficients are always towards the top of the plot, fine scale coefficients are always located toward the bottom of the plot. The location of coefficients increases from left to right across the plot in synchrony with the input signal to the wd object. In other words the position of a coefficient along a line is indicative of the associated wavelet basis function's translate number. The actual coefficients are plotted using S-Plus's segments() function. This plots each coefficient as a vertical line with positive coefficients being plotted above an imaginary centre line and negative coefficients being plotted below.
堆叠以上的分辨率级别：大尺度系数总是朝上方的图，判罚尺度系数始终位于向底部的图。系数增加的位置从左边到右边的输入信号同步的图wd对象。换句话说，沿一条直线的系数的位置是指示相关的小波基础函数的翻译号码。使用S-Plus的segments()函数绘制的实际系数。这绘制每个系数具有正系数的上面被绘制的假想中心线和负系数被下面的曲线所示为垂直线。
The resolution levels are labelled on the left-hand side axis, and if rhlab==T the maximum values of the absolute values of the coefficients, for the particular level, are plotted on the right-hand axis.
分辨率级别上的左手侧轴线被标记，并且如果rhlab==T的系数的绝对值的最大值，为特定的水平，绘制上右手的轴线。
The coefficients in the plot may be scaled in 4 ways. If you are interested in comparing coefficients in different levels then the default scaling option scaling=="global" is what you need. This works by finding the coefficient with the largest absolute value amongst all coeffients to be plotted and then scales all the other coefficients by the largest so that all coefficients lie in the range -1/2 to 1/2. The scaled coefficients are then plotted. If you are not interested in comparing relative resolution levels and want to see all that goes on within a particular scale then you should use the scaling option scaling=="by.level" which picks out the largest coefficient (in absolute value) from each level and scales each level separately. The "compensated" and super options are like the "global" option except that finer levels are scaled up (as discussed in the arguments list above): this can be useful when plotting non-decimated wavelet transform coefficients as it emphasizes the higher frequencies.
在4种可缩放系数的图。如果你有兴趣在比较不同层次的系数，那么默认缩放选项“scaling=="global"是你所需要的。找到要绘制在所有coeffients然后尺度系数与最大的绝对值的所有其他由最大系数在-1 / 2到1/2的范围内，让所有的系数在于这作品。然后，按比例缩放系数绘制。如果你不感兴趣比较相对的分辨率水平，并希望看到，在一个特定的范围内，那么你应该使用缩放选项scaling=="by.level"挑选出的各个层次，尺度系数最大（绝对值）每个级别分别。 “compensated”和超选项如“global”以外的选项，更精细的水平缩放（所讨论的在上述参数列表）：这可能是有用的，当绘制非抽取小波变换系数，因为它强调的是更高的频率。
值----------Value----------
If rhlab==T then the scaling factors applied to each scale level are returned. Otherwise NULL is returned.
如果rhlab==T然后返回适用于每个级的比例因子。否则返回NULL。
RELEASE----------RELEASE----------
Version 3.5.3 Copyright Guy Nason 1994
版本3.5.3版权盖利晨1994年
注意----------Note----------
A plot of the coefficients contained within the wd object is produced.
图wd对象内包含的系数。
（作者）----------Author(s)----------
G P Nason
参见----------See Also----------
wd
wd
实例----------Examples----------
#[]
# Generate some test data[生成一些测试数据。]
#[]
test.data <- example.1()$y
## Not run: ts.plot(test.data)[＃不运行：ts.plot（test.data）]
#[]
# Decompose test.data and plot the wavelet coefficients[分解test.data和绘制的小波系数]
#[]
wds <- wd(test.data)
## Not run: plot(wds)[＃未运行图（WDS）]
#[]
# Now do the time-ordered non-decimated wavelet transform of the same thing[现在做的时间顺序的非抽取小波变换，同样的事情]
#[]
## Not run: wdS <- wd(test.data, type="station")[＃不运行：WDS - WD（test.data，类型=“站”）]
## Not run: plot(wdS)[＃未运行图（WDS）]
#[]
# Next examples[下面的例子]
# ------------[------------]
# The chirp signal is also another good examples to use.[线性调频信号是另一个很好的例子使用。]
#[]
# Generate some test data[生成一些测试数据。]
#[]
test.chirp <- simchirp()$y
## Not run: ts.plot(test.chirp, main="Simulated chirp signal")[＃不运行：ts.plot（test.chirp，主要=“模拟线性调频信号”）]
#[]
# Now let's do the time-ordered non-decimated wavelet transform.[现在，让我们做的时间排序的非抽取小波变换。]
# For a change let's use Daubechies least-asymmetric phase wavelet with 8[对于改变我们的使用Daubechies小，至少不对称相小波的8]
# vanishing moments (a totally arbitrary choice, please don't read[消失矩（完全任意选择，请不要阅读]
# anything into it).[任何东西进去）。]
#[]
chirpwdS <- wd(test.chirp, filter.number=8, family="DaubLeAsymm", type="station")
## Not run: plot(chirpwdS, main="TOND WT of Chirp signal")[＃不运行：的图（chirpwdS，主要=“TOND的线性调频信号的WT”）]
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
|
发表于 2012-10-1 17:29:26
