accessC.mwd(wavethresh)
accessC.mwd()所属R语言包:wavethresh
Get Smoothed Data from Wavelet Structure
平滑后的数据小波结构
译者:生物统计家园网 机器人LoveR
描述----------Description----------
The smoothed and original data from a multiple wavelet decomposition structure, mwd.object ect (e.g. returned from mwd) are packed into a single matrix in that structure. TRUE his function extracts the data corresponding to a particular resolution level.
平滑的,原始数据从多小波分解结构,mwd.object等(例如返回mwd)打包成一个矩阵在该结构中。 TRUE他的功能提取的数据对应于一个特定的分辨率等级。
用法----------Usage----------
## S3 method for class 'mwd':
accessC(mwd, level = nlevels(mwd), ...)
参数----------Arguments----------
参数:mwd
Multiple wavelet decomposition structure from which you wish to extract the smoothed or original data if the structure is from a wavelet decomposition, or the reconstructed data if the structure is from a wavelet reconstruction.
多小波分解结构,从中提取的平滑或原始数据的结构是从小波分解,或重建的数据结构是从小波重建。
参数:level
The level that you wish to extract. By default, this is the level with most detail (in the case of structures from a decomposition this is the original data, in the case of structures from a reconstruction this is the top-level reconstruction).
的水平,你要提取。默认情况下,这是最详细的(从分解结构的情况下,这是原始数据结构的情况下,从重建这是顶级重建),水平。
参数:...
any other arguments
任何其他参数
Details
详细信息----------Details----------
The mwd function produces a wavelet decomposition structure.
随钻测量功能产生的小波分解结构。
For decomposition, the top level contains the original data, and subsequent lower levels contain the successively smoothed data. So if there are mwd$filter$npsi*2^m original data points (mwd$filter$npsi is the multiplicity of wavelets), there will be m+1 levels indexed 0,1,...,m. So
分解,顶层包含原始数据,和随后的较低级别包含的连续平滑的数据。因此,如果有mwd$filter$npsi*2^m原始数据点(mwd$filter$npsi是小波的多重性),将m+1水平索引0,1,...,M。所以
accessC.mwd(Mwd, level=m)
accessC.mwd(Mwd, level=m)
pulls out the original data, as does
拉出的原始数据,一样
accessC.mwd(mwd)
accessC.mwd(mwd)
To get hold of lower levels just specify the level that you're interested in, e.g.
弄个水平较低,只是指定你感兴趣的,例如:
accessC.mwd(mwd, level=2)
accessC.mwd(mwd, level=2)
Gets hold of the second level.
获取保持的第二个层次。
The need for this function is a consequence of the pyramidal structure of Mallat's algorithm and the memory efficiency gain achieved by storing the pyramid as a linear matrix of coefficients. AccessC obtains information about where the smoothed data appears from the fl.dbase component of mwd, in particular the array fl.dbase$first.last.c which gives a complete specification of index numbers and offsets for mwd$C.
此功能的必要性是Mallat的算法和实现作为线性矩阵系数存储金字塔内存效率增益的金字塔结构的一个后果。 AccessC获得有关下列内容的信息的平滑化数据出现从MWD的fl.dbase组件,特别是阵列fl.dbase$first.last.c为mwd$C索引号和偏移量给出了一个完整的产品规格。
Note also that this function only gets information from mwd class objects. To put coefficients into mwd structures you have to use the putC.mwd function.
还要注意的是此功能只获取信息从MWD类对象。系数到MWD结构有使用的putC.mwd功能。
See Downie and Silverman, 1998.
请参阅:唐尼和Silverman,1998年。
值----------Value----------
A matrix with mwd$filter$npsi rows containing the extracted data of all the coefficients at that level.
A矩阵与mwd$filter$npsi行包含提取的数据的所有系数在这一水平。
RELEASE----------RELEASE----------
Version 3.9.6 (Although Copyright Tim Downie 1995-6.)
版本3.9.6(,虽然版权蒂姆·唐尼1995-96。)
(作者)----------Author(s)----------
G P Nason
参见----------See Also----------
accessD.mwd, draw.mwd, mfirst.last, mfilter.select, mwd, mwd.object, mwr, plot.mwd, print.mwd, putC.mwd, putD.mwd, summary.mwd, threshold.mwd, wd
accessD.mwd,draw.mwd,mfirst.last,mfilter.select,mwd,mwd.object,mwr,plot.mwd,<所述>,print.mwd,putC.mwd,putD.mwd,summary.mwd,threshold.mwd
实例----------Examples----------
#[]
# Get the 3rd level of smoothed data from a decomposition[第3级平滑后的数据分解]
#[]
dat <- rnorm(32)
accessC.mwd(mwd(dat), level=3)
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。
|