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Package‘ptest’October14,2022Type PackageTitle Periodicity Tests in Short Time SeriesVersion1.0-8Date2016-11-12Author Yuanhao Lai and A.I.McLeodMaintainer A.I.McLeod<***************>Depends R(>=3.0),Description Implements p-value computations using an approximation to the cumulative distribu-tion function for a variety of tests for periodicity.These tests include harmonic regres-sion tests with normal and double exponential errors as well as modiﬁca-tions of Fisher's g test.An accompanying vignette illustrates the application of these tests. License GPL(>=2)LazyData trueNeedsCompilation yesImports quantreg(>=5.0)RoxygenNote5.0.1Suggests knitr,boot,lattice,rmarkdown,GeneCycle,VignetteBuilder knitrRepository CRANDate/Publication2016-11-1221:41:37R topics documented:alpha (2)B1 (3)B2 (4)B3 (5)Cc (6)cdc15 (7)cdc28 (7)12alpha ﬁtHReg (8)pgram (9)ptestg (10)ptestReg (12)simHReg (14)Index16 alpha Microarray time series experiment for yeast cell cycle from alpha ex-perimentDescription6,178yeast genes expression measures(log-ratios)with series length18from the alpha factor ex-periment.Usagedata(alpha)FormatMatrix with6178rows and18columns.Some missing data.Rows and columns are labelled.-attr(*,"dimnames")=List of2..$:chr[1:6178]"Y AL001C""Y AL002W""Y AL003W""Y AL004W".....$:chr[1:18]"alpha0""alpha7""alpha14""alpha21"...SourceThe data is extracted from the ExpressionSet of the R package yeastCC.ReferencesSpellman,P.T.,Sherlock,G.,Zhang,M.Q.,Iyer,V.R.,Anders,K.,Eisen,M.B.,...&Futcher,B.(1998).Comprehensive identiﬁcation of cell cycle-regulated genes of the yeast Saccharomycescerevisiae by microarray hybridization.Molecular biology of the cell,9(12),3273-3297.Dudoit S(2016).yeastCC:Spellman et al.(1998)and Pramila/Breeden(2006)yeast cell cycle microarray data.R package version1.12.0.Examplesdata(alpha)qqnorm(colMeans(alpha,na.rm=TRUE))qqnorm(rowMeans(alpha,na.rm=TRUE))B13 B1Benchmark set B1DescriptionList for yeast genes which are most likely to be periodic(the benchmark set1in de Lichtenberg et al.(2005)).Usagedata(B1)FormatA vector containg113genes’names.DetailsA total of113genes previously identiﬁed as periodically expressed in small-scale experiments.Theset encompasses the104genes used by Spellman et al.(1998)and nine genes added by Johansson et al.(2003).SourceThe raw data can be downloaded from http://www.cbs.dtu.dk/cellcycle/yeast_benchmark/ benchmark.php.ReferencesDe Lichtenberg,U.,Jensen,L.J.,Fausboll,A.,Jensen,T.S.,Bork,P.,&Brunak,S.(2005).Compar-ison of computational methods for the identiﬁcation of cell cycle-regulated genes.Bioinformatics, 21(7),1164-1171.Examplesdata(alpha)data(B1)alphaB1<-alpha[rownames(alpha)\%in\%B1,]4B2 B2Benchmark set B2DescriptionList for yeast genes which are most likely to be periodic(the benchmark set2in de Lichtenberg et al.(2005)).Usagedata(B2)FormatA vector containg352genes’names.DetailsGenes whose promoters were bound(P-value below0.01)by at least one of nine known cell cycle transcription factors in both of the Chromatin IP studies by Simon et al.(2001)and Lee et al.(2002).To obtain a benchmark set that is independent of B1,we removed all genes included in B1(50).The resulting benchmark set,B2,consists of352genes of which many should be expectedto be cell cycle regulated,since their promoters are associated with known stage-speciﬁc cell cycle transcription factors.SourceThe raw data can be downloaded from http://www.cbs.dtu.dk/cellcycle/yeast_benchmark/ benchmark.php.ReferencesDe Lichtenberg,U.,Jensen,L.J.,Fausboll,A.,Jensen,T.S.,Bork,P.,&Brunak,S.(2005).Compar-ison of computational methods for the identiﬁcation of cell cycle-regulated genes.Bioinformatics, 21(7),1164-1171.Examplesdata(alpha)data(B2)alphaB2<-alpha[rownames(alpha)\%in\%B2,]B35 B3Benchmark set B3DescriptionList for yeast genes which are less likely to be periodic(the benchmark set3in de Lichtenberg et al.(2005)).Usagedata(B3)FormatA vector containg518genes’names.DetailsGenes annotated in MIPS(Mewes et al.,2002)as’cell cycle and DNA processing’.From these,we removed genes annotated speciﬁcally as’meiosis’and genes included in B1(67),leaving518genes.As a large number of genes involved in the cell cycle are not subject to transcriptional regulation (not periodic),and because B1was explicitly removed,a relatively small fraction of these genes should be expected to be periodically expressed.SourceThe raw data can be downloaded from http://www.cbs.dtu.dk/cellcycle/yeast_benchmark/ benchmark.php.ReferencesDe Lichtenberg,U.,Jensen,L.J.,Fausboll,A.,Jensen,T.S.,Bork,P.,&Brunak,S.(2005).Compar-ison of computational methods for the identiﬁcation of cell cycle-regulated genes.Bioinformatics, 21(7),1164-1171.Examplesdata(alpha)data(B3)alphaB3<-alpha[rownames(alpha)\%in\%B3,]6Cc Cc Microarray time series experiment for Caulobacter crescentus bacte-rial cell cycleDescriptionIn this microarray experiment there are3062genes measured every1hour.There are19is missing gene labels and these have been given labels ORFna1,...,ORFna19.There310with duplicate labels.Of these duplicate labels,295are duplicated twice,12are duplicated3times and3are duplicated 4times.Duplicate labels are renamed ORF...to ORF...a and ORF...b etc.Usagedata(Cc)FormatMatrix with3062rows and11columns.Some missing data.Rows and columns are labelled.-attr(*,"dimnames")=List of2..$:chr[1:3062]"ORF06244a""ORF03152a""ORF03156a""ORF03161a".....$:chr[1:11]"1""2""3""4"...DetailsGene expression from synchronized cultures of the bacterium Caulobacter crescentus(Laub et al., 2000).(Laub et al.,2000)identiﬁed553genes whose messenger RNA levels varied as a function of the cell cycle but their statistical analysis was not very sophisticated and they probably identiﬁed too many genes.Wichert et al.(2004)found that44genes were found which displayed periodicity based on the Fisher’s g-test using a FDR with q=0.05.ReferencesLaub,M.T.,McAdams,H.H.,Feldblyum,T.,Fraser,C.M.and Shapiro,L.(2000)Global analysis of the genetic network controlling a bacterial cell cycle Science,290,2144-2148.Wichert,S.,Fokianos K.and Strimmer K.(2004)Identifying periodically expressed transcrips in microarray time series data.Bioinformatics,18,5-20.Examplesdata(Cc)qqnorm(colMeans(Cc,na.rm=TRUE))qqnorm(rowMeans(Cc,na.rm=TRUE))cdc157 cdc15Microarray time series experiment for yeast cell cycle from cdc15ex-perimentDescription6,178yeast genes expression measures(log-ratios)with series length24from the cdc15experiment. Usagedata(cdc15)FormatMatrix with6178rows and24columns.Some missing data.Rows and columns are labelled.-attr(*,"dimnames")=List of2..$:chr[1:6178]"Y AL001C""Y AL002W""Y AL003W""Y AL004W".....$:chr[1:24]"cdc15.10""cdc15.30""cdc15.50""cdc15.70"...SourceThe data is extracted from the ExpressionSet of the R package yeastCC.ReferencesSpellman,P.T.,Sherlock,G.,Zhang,M.Q.,Iyer,V.R.,Anders,K.,Eisen,M.B.,...&Futcher,B.(1998).Comprehensive identiﬁcation of cell cycle-regulated genes of the yeast Saccharomycescerevisiae by microarray hybridization.Molecular biology of the cell,9(12),3273-3297.Dudoit S(2016).yeastCC:Spellman et al.(1998)and Pramila/Breeden(2006)yeast cell cycle microarray data.R package version1.12.0.Examplesdata(cdc15)qqnorm(colMeans(cdc15,na.rm=TRUE))qqnorm(rowMeans(cdc15,na.rm=TRUE))cdc28Microarray time series experiment for yeast cell cycle from cdc28ex-perimentDescription6,178yeast genes expression measures(log-ratios)with series length17from the cdc28experiment. Usagedata(cdc28)8ﬁtHRegFormatMatrix with6178rows and17columns.Some missing data.Rows and columns are labelled.-attr(*,"dimnames")=List of2..$:chr[1:6178]"Y AL001C""Y AL002W""Y AL003W""Y AL004W".....$:chr[1:17]"cdc28.0""cdc28.10""cdc28.20""cdc28.30"...SourceThe data is extracted from the ExpressionSet of the R package yeastCC.ReferencesSpellman,P.T.,Sherlock,G.,Zhang,M.Q.,Iyer,V.R.,Anders,K.,Eisen,M.B.,...&Futcher,B.(1998).Comprehensive identiﬁcation of cell cycle-regulated genes of the yeast Saccharomycescerevisiae by microarray hybridization.Molecular biology of the cell,9(12),3273-3297.Dudoit S(2016).yeastCC:Spellman et al.(1998)and Pramila/Breeden(2006)yeast cell cycle microarray data.R package version1.12.0.Examplesdata(cdc28)qqnorm(colMeans(cdc28,na.rm=TRUE))qqnorm(rowMeans(cdc28,na.rm=TRUE))fitHReg Fits Three Parameter Harmonic RegressionDescriptionEstimates A,B and f in the harmonic regression,y(t)=mu+A*cos(2*pi*f*t)+B*sin(2*pi*f*t)+e(t).The default algorithm is enumerative but an exact non-linear LS option is also provided.UsagefitHReg(y,t=1:length(y),algorithm=c("enumerative","exact"))Argumentsy series.t Time points.algorithm method for the optimizationDetailsProgram is interfaced to C for efﬁcient computation.ValueObject of class"HReg"produced.pgram9 Author(s)A.I.McLeod and Yuanhao LaiExamplesset.seed(193)z<-simHReg(10,f=2.5/10,1,1)ans<-fitHReg(z)ans$freq#optimal frequency=0.2376238##ORF06806in Cc dataset.z<-c(0.42,0.89,1.44,1.98,2.21,2.04,0.82,0.62,0.56,0.8,1.33)ans2<-fitHReg(z,algorithm="exact")sum(resid(ans2)^2)#0.2037463ans1<-fitHReg(z)sum(resid(ans1)^2)#0.242072#compare with nls()t<-1:length(z)ans<-nls(z~mu+alpha*cos(2*pi*lambda*t+phi),start=list(mu=1,alpha=1,lambda=0.1,phi=0.0))coefficients(ans)sum(resid(ans)^2)#0.2037pgram Periodogram computationDescriptionThe periodogram is computed.Usagepgram(z,fr="default",method=c("periodogram","regression"))Argumentsz time series vector of length n,say.fr use"default"for usual Fourier frequencies,1/n,...,ﬂoor(n/2)/n.Set fr=N,to evaluate the periodogram at the Fourier frequencies corresponding to a time se-ries of length N.Finally set fr to any desired set of frequencies.Note frequenciesare in cycles per unit time sometimes called temoral frequency to distinguishfrom angular frequency.Both are widely used in time series.method either periodogram or regression10ptestg DetailsUses FFT.So if the length of z is a highly composite number,the computation is very efﬁcient.Otherwise the usual DFT is used.ValuePeriodogram evaluated at the Fourier frequencies or R-square.Author(s)A.I.McLeod and Yuanhao LaiExamplesz<-sunspot.yearn<-length(z)I<-pgram(z)f<-I[,1]I<-I[,2]plot(f,I,xlab="f",ylab="f",type="l")title(main="Periodogram for Annual Sunpots,1700-1988")#z<-c(0.42,0.89,1.44,1.98,2.21,2.04,0.82,0.62,0.56,0.8,1.33)fr<-(1:50)/101pgram(z)pgram(z,fr=101)pgram(z,fr=fr)pgram(z,method="regression")pgram(z,method="regression",fr=101)pgram(z,method="regression",fr=fr)ptestg Test short time series for periodicity based on periodogramsDescriptionThis function is used to test the existence of the periodicity for a short time series(length<=100).Several methods based on periodograms are provided with the response surface method imple-mented for efﬁciently obtaining accurate p-values.Usageptestg(z,method=c("Fisher","robust","extended","extendedRobust","FisherRSR"),multiple=FALSE)ptestg11Argumentsz A series or a matrix containg series as columnsmethod The statistical test to be used.See details for more information.multiple Indicating whether z contains multiple series.DetailsThe null hypothesis is set as no peridicities,H0:f=0.Discriptions of different test statistics(meth-ods)are as follow:Fisher:The Fisher’s g test statistic.The p-value is computed directly from the exact distribution.robust:The robust g test proprosed in Ahdesmaki et al.(2005),where the p-value is computed bythe response surface regression method.extended:The extended Fisher’s g test statistic,which extend the Fisher’s g test by enlarging thesearching region of the frequency from the fourier frequencies to be En=j/101|j=1,...,50andj/101≥1/n.The p-value is computed by the response surface regression method.extendedRobust:Extend the frequency searching region of the robust En=j/101|j=1,...,50andj/101≥1/n.The p-value is computed by the response surface regression method.FisherRSR:Only for experimental purposes,the Fisher;s g test with p-value computed form theresponse surface regression method.ValueObject of class"Htest"produced.An object of class"Htest"is a list containing the following components:obsStat Vector containing the observed test statistics.pvalue Vector containing the p-values of the selected tests.freq Vector containing the estimated frequencies.Author(s)Yuanhao Lai and A.I.McLeodReferencesFisher,R.A.(1929).Tests of signiﬁcance in harmonic analysis.Proc.Roy.Soc.A,125,54-59.Ahdesmaki,M.,Lahdesmaki,H.,Pearson,R.,Huttunen,H.,and Yli-Harja O.(2005).BMC Bioin-formatics6:117./1471-2105/6/117.MacKinnon,James(2001):Computing numerical distribution functions in econometrics,Queen’sEconomics Department Working Paper,No.1037.See AlsoptestRegExamples#Simulate the harmonic regression model with standard Gaussian error termsset.seed(193)##Non-Fourier frequencyz<-simHReg(n=14,f=2/10,A=2,B=1,model="Gaussian",sig=1)ptestg(z,method="Fisher")ptestg(z,method="robust")ptestg(z,method="extended")ptestg(z,method="extendedRobust")ptestg(z,method="FisherRSR")#Performe tests on the alpha factor experimentdata(alpha)##Eliminate genes with missing observationsalpha.nonNA<-alpha[complete.cases(alpha),]##Using the multiple option to do the test for all the genes##Transpose the data set so that each column stands for a genealpha.nonNA<-t(alpha.nonNA)result<-ptestg(alpha.nonNA,method="extended",multiple=TRUE)str(result)#The movtivating example:gene ORF06806in Ccdata(Cc)x<-Cc[which(rownames(Cc)=="ORF06806"),]plot(1:length(x),x,type="b",main="ORF06806",xlab="time",ylab="Gene expression")ptestg(x,method="Fisher")#Fail to detect the periodicityptestg(x,method="robust")ptestg(x,method="extended")ptestReg Test short time series for periodicity with maximum likelihood ratiotestsDescriptionThis function is used to test the existence of the periodicity for a short time series(length<=100).Likelihood ratio tests under the Gaussian or the Laplace assumptions are provided with the response surface method implemented for efﬁciently obtaining accurate p-values.UsageptestReg(z,method=c("LS","L1"),multiple=FALSE)Argumentsz A series or a matrix containg series as columnsmethod The statistical test to be used.See details for more information.multiple Indicating whether z contains multiple series.DetailsThe null hypothesis is set as no peridicities,H0:f=0.Discriptions of different test statistics(meth-ods)are as follow:LS:The-2loglikelihood ratio test statistic based on the likelihood ratio test with normal noises, where the p-values are efﬁciently computed by the response surface method.L1:The-2loglikelihood ratio test statistic based on the likelihood ratio test with Laplace noises, where the p-values are efﬁciently computed by the response surface method.ValueObject of class"Htest"produced.An object of class"Htest"is a list containing the following components:obsStat Vector containing the observed test statistics.pvalue Vector containing the p-values of the selected tests.freq Vector containing the estimated frequencies.Author(s)Yuanhao Lai and A.I.McLeodReferencesIslam,M.S.(2008).Peridocity,Change Detection and Prediction in Microarrays.Ph.D.Thesis,The University of Western Ontario.Li,T.H.(2010).A nonlinear method for robust spectral analysis.Signal Processing,IEEE Trans-actions on,58(5),2466-2474.MacKinnon,James(2001):Computing numerical distribution functions in econometrics,Queen’s Economics Department Working Paper,No.1037.See AlsofitHReg,ptestgExamples#Simulate the harmonic regression model with standard Gaussian error termsset.seed(193)#Non-Fourier frequencyz<-simHReg(n=14,f=2/10,A=2,B=1,model="Gaussian",sig=1)ptestReg(z,method="LS")#Normal likelihood ratio testptestReg(z,method="L1")#Laplace likelihood ratio testfitHReg(z,algorithm="exact")#the nls fitted result#Performe tests on the alpha factor experimentdata(alpha)##Eliminate genes with missing observationsalpha.nonNA<-alpha[complete.cases(alpha),]##Using the multiple option to do the test for all the genes##Transpose the data set so that each column stands for a genealpha.nonNA<-t(alpha.nonNA)result<-ptestReg(alpha.nonNA,method="LS",multiple=TRUE)str(result)#The movtivating example:gene ORF06806in Ccdata(Cc)x<-Cc[which(rownames(Cc)=="ORF06806"),]plot(1:length(x),x,type="b",main="ORF06806",xlab="time",ylab="Gene expression")ptestg(x,method="Fisher")#Fail to detect the periodicityptestReg(x,method="LS")#The periodicity is significantly not zeroptestReg(x,method="L1")#The periodicity is significantly not zerosimHReg Simulate harmonic regression modelsDescriptionSimulates a harmonic regression.Possible types of models are normal,t(5),Laplace,cubic and AR1.UsagesimHReg(n,f,A,B,model=c("Gaussian","t5","Laplace","cubic","AR1"),phi=0,sig=1)Argumentsn Length of series.f Frequency.A Cosine amplitude.B Sine amplitude.model The model used for generating the error term.See details.phi Only used if AR1error distribution is selected.sig The standard error of the series.DetailsGenerate a harmonic series y with length n,where y t=A∗cos(2∗pi∗f∗t)+B∗sin(2∗pi∗f∗t)+sig∗e t,t=1,...,n,and e comes from one of the following speciﬁed distributions with mean0and standard error1:Gaussian:A standard normal distribution(i.i.d.).t5:A t distribution with5degrees of freedom(i.i.d.,standardized to mean0and variance1).Laplace:A Laplace(double exponential)distribution(i.i.d.,standardized to mean0and variance1).cubic:A standard normal distribution for e,but y=y3this time.AR1:An AR(1)series with autocorrelation paramater phi(standardized to mean0and variance1).ValueVector of length n,simulated harmonic series.Author(s)A.I.McLeod and Yuanhao LaiReferencesMcLeod,A.I.,Yu,Hao and Krougly,Z.(2007),Algorithms for Linear Time Series Analysis:With R Package,Journal of Statistical Software23,51-26.See AlsofitHReg,ptestRegExamples#Simulate the harmonic regression model with standard Gaussian error termsz<-simHReg(10,f=2/10,1,2,model="Gaussian",sig=1)#Fourier Frequencyplot(1:10,z,type="b")#Simulate the AR(1)errorsz<-simHReg(10,f=0/10,0,0,model="AR1",phi=0.2,sig=1)acf(z)Index∗datasetsalpha,2B1,3B2,4B3,5Cc,6cdc15,7cdc28,7∗tsfitHReg,8pgram,9ptestg,10ptestReg,12simHReg,14alpha,2B1,3B2,4B3,5Cc,6cdc15,7cdc28,7fitHReg,8,13,15pgram,9ptestg,10,13ptestReg,11,12,15simHReg,1416。

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AD VALOREM ACCORDING TO VALUE 运价标记,根据商品的价值(计算运费),从价费率a.a.r. against all risks 一切险AC account current 一切险A/C for account of 费用由...负担acc. acceptance;accepted 已接受acc.cop. according to the custom of the port 按照...港口惯例a.c.v. actual cash value 实际现金价值a.d. a/d after date ...日期以后Add-on .tariff(also proportional rate or arbitrary in US) 费率标记(在美国也指按比例或仲裁决定)ad val.(a/v) ad valorem (according to value) 从价费率(按离岸价格)ADP automated data processing 自动数据处理ADR European Agreement concerning the international carriage of dangerous goods by roadAETR European Agreement concerning the work of crews of vehicles engaged in international road transportAFRA average freight rate assessment 运费费率平均运价Agcy agency 代理公司,代理行Agt. agent 代理人a.g.w.t. actual gross weight 实际毛重,实际总重量AMT Air Mail Transfer 航空邮寄A.O. account of ...的帐上A/or and/or 和/或A/P account paid 已付帐款approx. approximately 大约arr. arrival 到达,抵达arrd. arrived 到达,抵达a/s after sight 见票后...A/S alongside 靠码头,并靠他船asap as soon as possible 尽快,尽速ass. associate 准会员,公司ATA actual time arrival 实际到达时间ATD actual time of departure 实际出发时间ATP Agreement for the International Carriage of Perish able Foodstuffs Atty attorney 律师(美),代理人auth. authorized 授权的,认可的aux. auxiliary 辅助的,辅助设备AWB Air Waybill 空运单BA BALE CAPACITY 包装容积BAL BALANCE 平衡BALTIME UNIFORM TIME CHARTER 统一定期租船合同,巴尔的摩期租合同BDL BUNDLE 捆BEAM BREADTH OF THE VESSEL (船舶)型宽BENDS BOTH ENDS 装卸港BIMCO BALTIC INTERNATIONAL MARITIME CONFERENCE 波罗的海国际航运公会BIZ BUSINESS 业务B/L BILL OF LADING 提单BL BALE 包(装)BLADING BILL OF LADING 提单BLFT BALE FEET 包装尺码(容积)BLK BULK 散装BLKR BULKER 散装船BREAKDOWN AN ITEMIZED ACOUNT OF...'ITEM BY ITEM 细目分类B.RGDS BEST REGARDS 致敬,致意BS/L BILLS OF LADING 提单(复)B.T. BERTH TERMS 班轮条款B.A.C. bunker adjustment charge 燃油附加费B.A.F. bunker adjustment factor 燃油附加费系数Bags/Bulk part in bags,part in bulk 货物部分袋装,部分散装B.C. bulk cargo 散装货B/D bank(er's) draft 银行汇票b.d.i. both dates (days) inclusive 包括始末两天bdth breadth 宽度,型宽Bdy boundary 边境,界线B/G bonded goods 保税货物Bk. bank 银行Bkge brokerage 佣金,经纪费brl. barrel 桶,分英制美制两种B.W. bonded warehouse 保税仓库bxs. boxes 合,箱CABLEADD CABLE ADDRESS 电报挂号CC CARBON COPY 抄送C.F. CUBIC FEET 立方英尺C&F COST AND FREIGHT 货价加运费CFS CONTAINER FREIGHT STATION 集装箱货运站CIC CHINA INSURANCE CLAUSE 中国保险条款CIF COST,INSURANCE AND FRIEHGT 到岸价格(货价,保险费,加运费价)CIF & C COST,INSURANCE,FREIGHT AND COMMISSION 到岸价格加佣金CL.B/L CLEAN BILL OF LADING 清洁提单CO. COMPANY 公司C/O (IN) CARE OF 由...转交COA CONTRACT OF AFFREIGHTMENT 包运合同COMM. COMMISSION 佣金CONBILL CONFERENCE BILL OF LADING 公会提单CONGENBILL CONFERENCE GENERAL CARGO BILL OF LADING 公会杂货提单CO-OP CO-OPERATION 合作CORP. CORPORATION 公司COSCO CHINA OCEAN SHIPPING COMPANY 中国远洋运输总公司C/P CHARTER PARTY 租船合同CQD CUSTOMARY QUICK DESPATCH 按港口惯常速度快速装卸CUB CUBIC 立方CUFT CUBIC FEET 立方英尺CUM CUBIC METER 立方米CY CONTAINER YAND 集装箱堆场CAC currency adjustment charge 货币贬值附加费CAConf Cargo Agency Conference(IATA) 货运代理公会( )C.A.F. currency adjustment factor 货币贬值附加费系数C.A.S. currency adjustment surcharge 货币贬值附加费CASS Cargo Accounts Settlement System(IATA) 货运费用结算系统C.B. container base 集装箱底c.&d. collection and delivery 运费收讫,货物交毕c.b.d. cash before delivery 交货前付现cbm cubic meter 立方米cc charges collect 收取运费CCL customs clearance 清关CCS consolidated cargo(container) service 集中托运业务C/D customs declaration 报关单CEM European Conference on goods train timetables 欧洲货运列车时刻表会议CFR Cost and freight (Incoterms) 成本加运费价C.H. carriers haulage 承运业C.H.C. cargo handling charges 货物装卸费Ch.fwd charges forward 运费到付c.i.a. cash in advance 交货前付现款c.i.f.& e. cost,insurance,freight and exchange 成本,保险费,运费,加汇费价格c.i.f.i.& e. cost,insurance,freight,interest and exchange 成本,保险费,运费,利息,加汇费价格c.i.f.& i. cost,insurance,freight and interest 成本,保险费,运费,加利息价格c.i.f.c.& i. cost,insurance,freight,commission and interest 成本,保险费,运费,佣金,加利息价格c.i.f.c.& e. cost,insurance,freight,commission and exchange 成本,保险费,运费,佣金,加汇费价格c.i.f.i.c. cost,insurance,freight,interest and commission 成本,保险费,运费,利息,加佣金价格c.i.f.L.t. cost,insurance,freight,London terms 伦敦条款到岸价格c.i.f.w. cost,insurance,freight/war 到岸价加战争险CIM International Convention concerning the carriage of Goods by RailwayCIP Carriage and insurance paid to (Incoterms) 运费和保险费付至...(指定目的地) CIV International Convention on the Carriage of Passenger and Luggage by Railway CKD completely knocked down (unassembled) 完全分解的cm centimetre(s) 厘米cm3 cubic centimetre(s) 立方厘米CMR Convention on the Contract for the International Carriage of Goods by Road C/N consignment note 发货通知书cnee consignee 收货人cnmt/consgt. consignment 发运cnor consignor 发货人C/O certificate of origin 原产地证明C.O.D. cash on delivery 货到付款C.O.F.C. Container-on-Flat-Car(rail flatcar) (铁路)装运集装箱的平板车COMBITERMS Delivery terms for int'l groupage traffic 国际成组运输交货条款(货运代理人之间)COP customs of port 港口惯例C.O.S. cash on shipment 装船付船COTIF Convention concerning Int'l Carriage by Rail (CIM-CIV) 国际铁路运输公约C.P. Customs of Port 港口惯例CP carriage paid 运费已付C/P blading charter party bill of lading 租船提单CPLTC Conference Port Liner Term Charges 港口班轮装卸条款公会CPT Carriage paid to (Incoterms) 运费付至(...指定目的地)CSC Container service charge 集装箱运输费用CSC Int'l Convention of the Safe Transport of Containers 国际集装箱安全公约CSConf Cargo Service Conference(IATA) 货运业公会CST Container Service Tariff 集装箱运输费率C/T Container Terminal 集装箱码头C.T. conference terms 公会条款CT combined transport 联合运输CTD combined transport document 联合运输单证CTO combined transport operator 多式联运经营人CTPC Cargo Traffic Procedures Committee(IATA)cu.ft. cubic foot(feet) 立方英尺cu.in. cubic inch(es) 立方英寸CVGK customs value per gross kilogram (毛重)每公斤海关价值CVGP customs value per gross pound (毛重)每磅海关价值CWE cleared without examination 未经查验过关的cwt hundredweight 担,(英制)等于112磅,(美制)等于100磅CWO CASH WITH ORDER 订货时预付款cy currency 货币D DIESEL OIL 柴油D300 DIESEL OIL 300 TONS 柴油300吨D/A DOCUMENT AGAINST ACCEPTANCE 承兑交单DEM DEMURRAGE 滞期费DEP DEPARTURE (船舶)离港DEPT DEPARTURE 离港,处部DESP DESPATCH MONEY 速遣费DESPONENT OWNER SECOND OWNER OF THE SAME VESSEL 二船东D.F DEAD FREIGHT 空舱费DFT DRAFT 吃水DHD DEMURRAGE AND HALF DESPATCH 滞期费,速遣费为滞期费的一半DHDWTS DESPATCH HALF DEMURRAGE AND FOR WORKING TIME SAVED 速遣费按滞期费的一半,并按节省的工作时间计算D/O DELIVERY ORDER 提货单D/P DOCUMENT AGAINST PAYMENT 付款交单D.T.A. DEFINITE TIME OF ARRIVAL 确报,船舶确切到港时间DWC DEADWEIGHT CAPACITY 受载量DWCT DEADWEIGHT CARGO TONNAGE 载重吨,受载量DWT DEADWEIGHT TONNAGE 载重吨DWTC DEADWEIGHT TONNAGE OF CARGO 货物载重吨DAF Delivery at frontier(Incoterms) 边境交货(...指定地)D.A.S. delivered alongside ship 船边交货Dbk drawback 退(关)税DCAS Distribution Cost Analysis System 分拨费用分析系统DDP Delivered duty paid(Incoterms) 完税后交货DES Delivered ex ship(Incoterms) 目的地船上交货(...指定目的港)DEQ Delivered ex quay(duty paid)(Incoterms) 目的港码头交货(关税已付)DDU Delivered duty unpaid(Incoterms) 未完税交货dia diameter 直径dir. direct 直接dm3 cubic decimetre(s) 立方分米DOCIMEL Electronic Cim Document 电子单证DWCC dead weight cargo capacity 载重量DWT dead weight ton 载重吨E.G. EXAMPLE GRATIA=FOR EXAMPLE 例如EIU EVEN IF USED 即使使用(也不算)E/M EXPORT MANIFEST 出口载货清单,出口舱单ENCL ENCLOSURE OR ENCLOSED 附件或所附的E.& O.E. ERRORS AND OMMISIONS EXCEPTED 有错当查(错误和遗漏不在此限)ETA ESTIMATED TIME OF ARRIVAL (船舶)预计抵港时间ETAD EXPECTED TIME OF ARRIVAL AND DEPARTURE (船舶)预计到达和离开时间ETB EXPECTED TIME OF BERTHING (船舶)预计靠泊时间ETC EXPECTED TIME OF COMMENCEMENT 预计开始时间ETCD ESTIMATED TIME OF COMMENCING DISCHARGING (船舶)预计开始卸货时间ETD ESTIMATED TIME OF DEPARTURE (船舶)预计离港时间ETL ESTIMATED TIME OF LOADING (船舶)预计开装时间ETS ESTIMATED TIME OF SAILING (船舶)预计开航时间EXP EXPORT 出口EXPS EXPENSES (费用)支出ECE International Convention for the Harmonization of Frontiers Controls of Goods ECU European currency unit 欧洲货币单位EDI electronic data interchange 电子数据交换EDIFACT Electronic Data Interchange for Administration, Commerce and Transport EDP electronic data processing 电子数据处理e.g. for example 例如EIR equipment interchange receipt(containers) 设备交接单(集装箱)excl. excluding 不包括,除...外EXW Ex works(Incoterms) 工厂交货(...指定地)F FUEL OIL 燃油F300 FUEL OIL 300 TONS 燃油300吨FAS FREE ALONGSIDE SHIP 船边交货FCL FULL CONTAINER LOAD (集装箱)整箱货FDFT FORE DRAFT 艏吃水FEU FOURTY EQUIVALENT UNIT 40'标准集装箱FI FREE IN (船方)不负担装货费用FILO FREE IN AND LINER OUT (船方)不负担装货费用,但负担卸货费用F.I.L.S.D. FREE IN LASHED,SECURED AND DUNNAGED (船方)不负担装货,捆扎,加固,隔垫(料)等费用FIO FREE IN AND OUT (船方)不负担装,卸费用FIOST FREE IN AND OUT,STOWED AND TRIMMED (船方)不管装,不管卸,不管积载和平仓FLT FULL LINER TERMS 全班轮条款F/M EXPORT FREIGHT MANIFEST 出口载货运费清单,运费舱单FM FROM 从...,来自...FOB FREE ON BOARD 离岸价格(船上交货0FPA FREE FROM PARTICULAR AVERAGE 平安险FRT FREIGHT 运费FT FOOT OR FEET 英尺FWD FORWARD 前部FWDFT FRESH WATER DRAFT 淡水吃水FRG FOR YOUR GUIDANCE 供你参考,供你掌握情况F.A.A. free of all average 一切海损不赔险f.a.c. fast as can (loading or discharge) 尽快(装卸)F.A.C. forwarding agent's commission 货运代理人佣金FAK freight all kinds (不分品种)同一费率FALPRO Special Programme on Trade Facilitation(UNCTAD) 简化贸易手续特别计划F.and D. freight and demurrage 运费和滞期费f.a.q. fair average quality 中等质量货物FAS Free alongside ship(Incoterms) 船边交货(...指定装运港)FBL FIATA Multimodal Transport Bill of Lading(FIATA Document) FIATA 多式联运提单FCA Free carrier(Incoterms) 货交承运人FCR Forwarders Certificate of Receipt (FIATA Document) 货运代理人收讫货物证明FCSR & CC free of capture,seizure,riots and civil commotions 掳获,捕捉,暴动和内乱不赔险FCT Forwarders Certificate of Transport(FIATA) 货运代理人运送证明FFI FIATA Forwarding Instructions(FIATA form) 国际货运代理协会联合会代运说明f.g.a. free of general average 共同海损不赔险FHEX Friday and holidays excepted 节假日除外f.i.a.s. free in and stowed 船方不负担装货费和理舱费f.i.o.s. free in and out stowed 船方不负担装卸费和理舱费F.I.B. free into barge 驳船上交货f.i.c. freight,insurance,carriagef.i.h. free in harbour 港内交货firavv first available 最有效的FIS freight,insurance and shipping chargesf.i.w. free into waggon 船方不负担装入货车费FLT forklift truck 叉车F.O.C. flag of convenience 方便国旗F.O.D. free of damage 损坏不赔f.o.w. first open water 第一解冻日(保)F.P.A. free of particular average 单独海损不赔FPAD freight payable at destination 目的地付运费FR flat rack(container)Frt.fwd. freight forward 到付运费ft.ppd. freight prepaid 运费预付frt.ton freight ton 运费吨FWC full loaded weight & capacity(container) 满载重量和容积fwdr. forwarder 货运代理人FWR FIATA Warehouse Receipt(FIATA Document) FIATA仓储收据GA GENERAL AVERAGE 共同海损GENCON UNIFORM GENERAL CHARTER 统一杂货(程)租船标准合同,"金康"程租合同GMT GREENWICH MEAN TIME 格林威治标准时间GR GRAIN CAPACITY OR GROSS (船舶)散装容积或毛(重)GRD GEARED 带吊杆的GRT GROSS REGISTER TONNAGE 总登记吨GSP GENERALIZED SYSTEM OF PREFERENCE 普惠制GW GROSS WEIGHT 毛重G.A. general average 共同海损(保)G.A.A. General Average Agreement(bond) 共同海损协议(合同)G.A.C. general average contribution 共同海损分摊额(保)G.B.L. Government Bill of Lading 政府海运提单G.C. general cargo 杂货G.C.R. general cargo rates 杂货费率GDP gross domestic product 国内生产总值GFA general freight agent 货运总代理GNP gross national product 国民生产总值GSA General Sales Agent 销售总代理HA HATCH 舱口HA DIM HATCH DIMENSION 仓口尺寸HATUTC HALF TIME USED TO COUNT (AS LAYTIME) 实际所使用时间的一半应计算(为作业时间)HD HEAVY DIESEL 重柴油HO HOLD 货仓HRS HOURS 小时HAWB House Air Waybill 货运代理运单,分运单hdlg handling 处理,手续HERMES Handling European Raiway Message Exchange-System 欧洲铁路运输信息交换系统hgt height 高度h/lift heavy lift 重件货H.Q. headquarters 总部h.p. horse power 马力ICC INSTITUTE CARGO CLAUSES,LONDON 伦敦协会货物条款(保险)I.E. ID EST=THAT IS 即是...,那就是...IMP. IMPORT 进口INC. INCLUDING 包括INST INSTANT 本月的INT INTENTION 意下,企图IOP IRRESPECTIVE OF PERCENTAGE 不管百分比IU IF USED 如果使用i.a.w. in accordance with 按照IMDG International Maritime Dangerous Goods Code 国际海运危险品编码in. inch(s) 英寸incl. including 包括INCOTERMS Standard condition for sale and delivery of goods 国际贸易术语解释通则INMARSAT International Convention on the International Maritime Satellite OrganizationINTRM intermediate point 中转点inv. invoice 发票I.P.A. including particular average 包括单独海损(保)i.o.u. I owe you 借据,欠条 LADEN DRAFT THE DRAFT WHEN VESSEL IS LADEN (船舶)满载吃水LBP LENGTH BETWEEN PERPENDICULARS (船舶)垂线间高L/C LETTER OF CREDIT 信用证LCL LESS THAN CONTAINER LOAD (集装箱)拼箱货LD LIGHT DIESEL 轻柴油LDT LRNGTH DEADWEIGHT 轻载重吨L/G LETTER OF GUARANTEE 保证书,保证信LH LOWER HOLD 底舱L/L LOADING LIST 装货清单LOA LENGTH OVER ALL 船舶全长LOADREADY READY FOR LOADING,READY TO LOAD 已备妥,可装货L.T. LOCAL TIME 当地时间L/T LONG TON 长吨LT LINER TERMS 班轮条款LTD LIMITED 有限(公司)L/A Lloyd's agent 劳埃德保险公司代理人,劳埃德船级社代理人LASH lighter aboard ship 子母船Lat.,lat. latitude 纬度lb(s) pound(s) 磅LDG leading 导航的,主要的l.& d. loss and damage 损失与残损l.& u. loading and unloading 装卸leg. legal 法律上的,合法的LEL lower explosive limit 最低爆炸极限LFL lower flammable limit 最低燃烧极限lgt. long ton;long tons 长吨liq. liquid 液体(的)Lkg/Bkg leakage & breakage 漏损与破损LNG Liquefied natural gas 液化天然气L.O.A. lenghth over all 全长LO/LO lift on,lift off 吊上吊下,吊装load loading 装货loc. local;location 当地;位置Long.,long longitude 经度LPG Liquefied petrochemical gas 液化石油气LSD loading,storage and delivery charges 装船,仓储和交货费用LT letter telegram 书信电报L/T liner terms 班轮条款LTA lighter than air system(airships)ltge lighterage 驳运费ltr. lighter 驳船lump lump sum 包干金额,总数M. MEASUREMENT 按货物的体积计算运价MAX MAXIMUM,THE MOST 最大(多)MDM MADAME 夫人,女士MIN MINIMUM,THE LEAST 最小(少)MME MADAME 夫人,女士MOLOO MORE OR LESS AT OWNER'S OPTION 溢短装由船东选择MOLSO MORE OR LESS AT SELLER'S OPTION 溢短装由卖方选择MR. MISTER 先生M/R,M.R. MATE'S RECEIPT 大副收据MRS MISTRESS 夫人M.S. MOTOR SHIP 内燃机船MS MISS,MISTRESS 小姐,夫人,女士M/T,MT METRIC TON OR MOTOR TANKER 公吨或内燃机油轮MTON MEASUREMENT TON 尺码吨MV MOTOR VESSEL 内燃机船M minimum(rate classification) 最低(运费)m metre(s) 米m3 cubic metre(s) 立方米MACH modular automated container handlingMFN Most Favoured Nation 最惠国M.H. Merchants Haulage 商船运输M/R mate's receipt 大付收据M+R maintenance and repair(centre) 维护修理MAWB Master Air Waybill 总运单(空)Mdse merchandise 商品msbl missing bill of lading 丢失提单msca missing cargo 灭失货物MT motor tanker 内燃机油轮MTD multimodal transport document 多式联运单证MTO multimodal transport operator 多式联运经营人M/S Motor ship 内燃机船M/V Motor Vessel 内燃机船N/M NO MARK 无麦头NOR NOTICE OF READINESS 装卸准备就绪通知书N/R NOTICE OF READINESS 装卸准备就绪通知书NR NUMBER 数字,号码NRT NET REGISTER TONNAGE 净登记吨NT.WT. NET WEIGHT 净重NVOCC NON-VESSEL OPERATIONS COMMON CARRIER 无船公共承运人N normal(rate classification) 普通货(运价)NAABSA not always afloat but safely aground 不经常漂浮但安全坐浅NAOCC Non Aircraft Operating Common Carrier 无航空器公共承运人NAWB Neutral Air Waybill(forwarders Air Waybill) 货运代理人空运分运单n.c.v. non customs (commercial) value 无商业价值n.e.s. not elsewhere specified 不另说明n.f.o. not free out 不管卸货NGO non governmental organization 非官方组织n.l.t. not later than 不迟于,不晚于n/n non-negotiable 不可转让的N.,No.,Nr. number 编号N/O no order 无定单n.o.e. not otherwise enumerated 不另编号n.o.p. not otherwise provided 未另列出N.O.R. not otherwise rated 未列名N.O.S. not otherwise specified 未列名Nt. net weight 净重n.v.d. no value declared 未声明价值NVOCC Non Vessel Operating Common Carrier 无船公共承运人OCP OVERLAND COMMON POINTS 内陆共同点OBO Ore Bulk Oil(carrier) 矿石,散货和石油多用途船O.B.S. Oil Bunker Surcharge 燃油附加费Oc.B/L Ocean Bill of Lading 海运提单O/D on deck 甲板上ODS operating differential subsidy 经营差别补贴OFA ocean freight agreement 海运运费协议O.R. owner's risk 船舶所有人或货主承担风险O.R.B. owner's risk of breakage 破损风险由货主承担O.R.D. owner's risk of damage 损失风险由货主承担O.R.F. owner's risk of fire 火灾风险由货主承担OT open top(container) 开顶式集装箱o.t.o.r. on truck or railway 经公路或铁路 PA PARTICULAR AVERAGE 单独海损PCT PERCENT 百分比PDPR PER DAY OR PRORATA 按天计算,不足一天者按比例计算PENAVICO CHINA OCEAN SHIPPING AGENCY 中国外轮代理总公司P & I CLUB PROTECTION AND INDEMNITY CLUB 船东保赔协会PKG PACKAGE 包装PM POST MERIDIEM=AFTERNOON 下午PRO RATA IN PROPORTION 按比例(计算)PROX PROXIMO,NEXT MONTH 下个月PWWD PER WEATHER WORKING DAY 每晴天工作日p.a. per annum(per year) 每年P.A. particular average 单独海损Para paragraph 文章的段或节P.B.A. paid by agent 由代理支付P & D pick up and deliveryP.& I. Protection and Indemnity Association 船东报赔协会P.& I.clause Protection and Indemnity clause 保护和赔偿条款P.& I.Club Protection and Indemnity Club 船东保赔协会P.& L. profit and loss 收益和损失payt. payment 支付,赔偿P/C Paramount Clause 最重要条款p.c.f. pounds per cubic foot 每立方英尺...镑P.chgs particular charges 特别费用(保)pd. paid 已付款p.d. partial delivery 部分交付p.h.d. per hatch per day 每天每舱口(租船)pkge package 包装P.L. partial loss 部分损失(保)PLP parcel post 包裹邮寄PLTC port liner term chargespmt prompt 即时的P/N promissory note 期票;本票P.O.B. post office box 邮政信箱P.O.D. payment on delivery;paid on delivery 交货时付讫POD port of discharge 卸港POL port of loading 装港POR port of refuge 避难港pp/ppd prepaid/prepaid 预付p.t. per ton 每吨pt/dest port of destination 目的港pt/disch port of discharge 卸港PTL partial total loss 部分和全部损失ptly pd partly paid 已付部分款p.t.w. per ton weight 按吨计 Q Quantity (rate classification) 数量Q.c.o. quantity at captain's option 数量由船长决定Qn Quotation 引述,引用q.v. quod vide(which see) 见本项** SAFE BERTH 安全泊位SHEX SUNDAYS,HOLIDAYS EXCEPTED 星期日和节假日除外SHINC SUNDAYS,HOLIDAYS INCLUDED 星期日和节假日包括在内SINOCHART CHINA NATIONAL CHARTER CORPORATION 中国租船公司SINOTRANS CHINA NATIONAL FOREIGN TRADE TRANSPORTATION CORP. 中国对外贸易运输总公司S/O SHIPPING ORDER 装货单,关单,下货纸SOONEST AS SOON AS POSSIBLE 尽快,尽速SOS SAVE OUR SHIP,A MESSAGE FOR HELP (船舶遇难)呼救信号S/P STOWAGE PLAN,CARGO PLAN 货物积载图,船图SPACETONS MEASUREMENT TONS INCLUDING BROKEN STOWAGE SPACE 包括亏舱在内的尺码吨SRCC STRIK,RIOTS AND CIVIL COMMOTION 罢工,暴乱,内哄(险)SS STEAM SHIP 蒸汽机船SUB-CHARTERER THIRD OWNER OF THE SAME VESSEL 再租人,三船东SUBLET TRANSFER THE CHARTERSHIP 转租SUBS SUBSTITUTE 代替SWAD SALT WATER ARRIVAL DRAFT 抵港海水吃水SWDFT SALT WATER DRAFT 海水吃水S surcharge(rate classification) 附加费S/C surcharge 超载s & c shipper and carrier 托运人与承运人S.& F.A. shipping and forwarding agent 运输代理SHEX sundays and holidays excluded 星期天和例假日除外SCR specific commodity rate 列名商品费率S/D sailing date 启航日期S.d. small damage 小量损坏S/d sight draft 即期SDR Special Drawing Rights 特别提款权SDT Shipper Declatation for the transport of dangerous goods (FIATA FORM) s.l.& c. shippers' load and count 发货人装船和计数S.L./N.L. ship lost or not lost 船舶灭失与否SLI shippers letter of instruction 发货人说明S.O.L. shipowner's liability 船舶所有人的义务S.P.A. subject to particular average 平均分担单独海损sq.cm(s) square centimtre(s) 平方分米sq.in(s) square inch(es) 平方英寸SRCC strike,riots,civil commotions 罢工,暴动和内乱S/S steamship 汽船,轮船stvdrs stevedores 码头装卸工人sub L/C subject to letter of credit being opened 按照开立的信用证sub licence subject to licence being granted 按照批准的许可 TB TO BE 将要... TBN TO BE NOMINATED 待派(船),待指定TC TYPE CRANES 单杆吊(船舶吊杆类型)T/C TIME CHARTER 期租T.C.T. TIME CHARTER ON TRIP BASIS 航次期租船TD TYOE DERRICKS 双杆吊(船吊类型)T.D. TWEENDECK 二层柜TDY TODAY 今天TEU TWENTY EQUIVALENT UNIT 20'标准集装箱TKS THANKS 感谢TLX TELEX 电传TPI TON PER INCH 每一英寸载重吨TPNP THEFT,PILFERAGE AND NONDELIVERY 偷,盗和提货不着(险)T/T TURBINE TANKER OR TELEGRAPHIC TRANSFER 汽轮机油轮或电汇T.A. telegraphic address 电报挂号TACT the air cargo tariff(IATA) 空运货物费率TBL through bill of lading 联运提单TBN to be named 待指定TC traffic conference area(IATA)TC transcontainerTD time of departure 开航时间TDO telegraph delivery order 电报交货单TEEM Trans-Europe-Express Merchandises (rail service) 横贯欧洲快运货物TIF international transit by rail 国际铁路运输TIR Customs Convention on the int'l transport of goods under cover of TIR carnets(int'l road transport)TL total loss 全损TLF tariff level factor 费率水平系数tnge tonnage 吨位T.O.D. time of discharge 卸货时间TOFC Trailer on board flatcar 平板车载运带拖车的集装箱T.O.R. time of receipt 收到时间TOT time of transmission 传递时间tot. total 总共TOW tier on weight(container stacking according to wightT.T. terms of trade 贸易条款ULCC ULTRA-LARGE CRUDE CARRIER 特大型油轮ULT ULTIMO,LAST MONTH 上月的UU UNLESS USED 除非使用u.c. usual conditions 通常情况下U.D. under deck 下层甲板U.DK. upper deck 上层甲板ULD unit load device(aircraft) 成组货载装置U/w Underwriter 保险人V VOYAGE 航程,航次V/C VOYAGE CHARTER 程租船VLBC VERY LARGE BULK CARRIER 大型散装船VLCC VERY LARGE CRUDE CARRIER 大型油轮val. value 价值VAT value added tax 增值税V.C. vessels convenienceVes. Vessels 船舶VIC Very Important Cargo 非常重要货物VIO Very Important Object 非常重要目标VOCC Vessel Operating Common carrier 有船公共承运人v.v. vice versa 反之亦然 W GROSS WEIGHT 按货物的毛重计算运价WA WITH PARTICULAR AVERAGE 水渍险WIBON WHETHER IN BERTH OR NOT (船舶)不管靠泊与否WICCON WHETHER IN CUSTOMS CLEARANCE OR NOT (船舶)不管通关与否WIFPON WHETHER IN FREE PRATIQUE OR NOT (船舶)不管检疫与否WIPON WHETHER IN PORT OR NOT (船舶)不管抵港与否W/M GROSS WIGHT OR MESUREMENT 按货物重量与体积分别计算,按高者收费WOG WITHOUT GUARANTEE 没有保证W.P. WERTHER PERMITS 如果气候条件许可WPA WITH PARTICULAR AVERAGE 水渍险WRITING WE(I) SHALL WRITE TO YOU ABOUT IT LATER 详情函告WT WEIGHT 重量WTON WEIGHT TON 重量吨WTS WORKING TIME SAVED 节省的工作时间WT**ENDS WORKING TIME SAVED AT BOTH ENDS 装卸港均以节省的工作时间计算(速遣费) WWD WEATHER WORKING DAY 晴天工作日WWDSHEX WEATHER WORKING DAY SUNDAYS,HOLIDAYS EXCEPTED 晴天工作日,星期日和节假日除外WWDSHING WEATHER WORKING DAY SUNDAYS,HOLIDAYS INCLUDED 晴天工作日,星期日和节假日包括在内W.A. with average (Institute Cargo Clause) 承保单独海损,水渍险W/B Way-bill 运货单w.b.d. will be donew.c. with costs 付费的w.c.c.o.n. weather cleared customs or not 无论清关与否W/d working day 工作日wdt/wth width 宽度w.e.f. with effect fromWG working groupwhf wharfage 码头搬运费Whse Warehouse 仓库wk. week 周,星期W/O.w/o without 没有,不WP weather permitting 天气许可的条件下w.p.a. with particular average 担保单独海损W.R. Warehouse Receipt 仓库收据W.R.I. War Risk Insurance 战争险wt. weight 重量w/t weight tons 重量吨w/v weight/volume 重量或体积WW warehouse warrant 仓库栈单ww world-wide 世界性的 X,X. extra 额外的x l & u l exclusive of loading and unloading 不包括装卸xp express paid 快递费付讫的x pri without privileges 无例外YC YOUR CABLE 你电YLET YOUR LETTER 你信YTLX YOUR TELEX 你的电传yday yesterday 昨天y/l your letter 你信y/o your order 你的定单。

odin ODE生成和集成系统文档说明书

Package‘odin’October2,2023Title ODE Generation and IntegrationVersion1.2.5Description Generate systems of ordinary differential equations (ODE)and integrate them,using a domain speciﬁc language(DSL).The DSL uses R's syntax,but compiles to C in order toefﬁciently solve the system.A solver is not provided,butinstead interfaces to the packages'deSolve'and'dde'aregenerated.With these,while solving the differential equations,no allocations are done and the calculations remain entirely incompiled code.Alternatively,a model can be transpiled to R for use in contexts where a C compiler is not present.Aftercompilation,models can be inspected to return information about parameters and outputs,or intermediate values after calculations.'odin'is not targeted at any particular domain and is suitablefor any system that can be expressed primarily as mathematicalexpressions.Additional support is provided for working withdelays(delay differential equations,DDE),using interpolatedfunctions during interpolation,and for integrating quantitiesthat represent arrays.License MIT+ﬁle LICENSEURL https:///mrc-ide/odinBugReports https:///mrc-ide/odin/issues Imports R6,cinterpolate(>=1.0.0),deSolve,digest,glue,jsonlite, ring,withrSuggests dde(>=1.0.0),jsonvalidate(>=1.1.0),knitr,mockery, pkgbuild,pkgload,rlang,rmarkdown,testthat VignetteBuilder knitrRoxygenNote7.1.1Encoding UTF-8Language en-GBNeedsCompilation no12can_compile Author Rich FitzJohn[aut,cre],Thibaut Jombart[ctb],Imperial College of Science,Technology and Medicine[cph]Maintainer Rich FitzJohn<***********************>Repository CRANDate/Publication2023-10-0213:40:11UTCR topics documented:can_compile (2)odin (3)odin_build (5)odin_ir (6)odin_ir_deserialise (7)odin_options (7)odin_package (9)odin_parse (10)odin_validate (11)Index13 can_compile Test if compilation is possibleDescriptionTest if compilation appears possible.This is used in some examples,and tries compiling a trivial C program with pkgbuild.Results are cached between runs within a session so this should be fast to rely on.Usagecan_compile(verbose=FALSE,refresh=FALSE)Argumentsverbose Be verbose when running commands?refresh Try again to compile,skipping the cached value?DetailsWe use pkgbuild in order to build packages,and it includes a set of heuristics to locate and organise your C compiler.The most likely people affected here are Windows users;if you get this ensure that you have rtools ing pkgbuild::find_rtools()with debug=TRUE may be helpful for diagnosing compiler issues.odin3ValueA logical scalarExamplescan_compile()#will take~0.1s the first timecan_compile()#should be basically instantaneousodin Create an odin modelDescriptionCreate an odin model from aﬁle,text string(s)or expression.The odin_version is a"standard evaluation"escape hatch.Usageodin(x,verbose=NULL,target=NULL,workdir=NULL,validate=NULL,pretty=NULL,skip_cache=NULL,compiler_warnings=NULL,no_check_unused_equations=NULL,options=NULL)odin_(x,verbose=NULL,target=NULL,workdir=NULL,validate=NULL,pretty=NULL,skip_cache=NULL,compiler_warnings=NULL,no_check_unused_equations=NULL,options=NULL)Argumentsx Either the name of aﬁle to read,a text string(if length is greater than1elements will be joined with newlines)or an expression.verbose Logical scalar indicating if the compilation should be verbose.Defaults to the value of the option odin.verbose or FALSE otherwise.target Compilation target.Options are"c"and"r",defaulting to the option odin.target or"c"otherwise.workdir Directory to use for any generatedﬁles.This is only relevant for the"c"target.Defaults to the value of the option odin.workdir or tempdir()otherwise.validate Validate the model’s intermediate representation against the included schema.Normally this is not needed and is intended primarily for development use.De-faults to the value of the option odin.validate or FALSE otherwise.pretty Pretty-print the model’s intermediate representation.Normally this is not needed and is intended primarily for development use.Defaults to the value of theoption odin.pretty or FALSE otherwise.skip_cache Skip odin’s cache.This might be useful if the model appears not to compile when you would expect it to.Hopefully this will not be needed often.Defaultsto the option odin.skip_cache or FALSE otherwise.4odin compiler_warningsPreviously this attempted detection of compiler warnings(with some degree ofsuccess),but is currently ignored.This may become supported again in a futureversion depending on underlying support in pkgbuild.no_check_unused_equationsIf TRUE,then don’t print messages about unused variables.Defaults to the optionodin.no_check_unused_equations or FALSE otherwise.options Named list of options.If provided,then all other options are ignored.DetailsDo not use odin::odin in a package;you almost certainly want to use odin_package instead.A generated model can return information about itself;odin_irValueAn odin_generator object(an R6class)which can be used to create model instances.User parametersIf the model accepts user parameters,then the parameter to the constructor or the$set_user() method can be used to control the behaviour when unknown user actions are passed into the model.Possible values are the strings stop(throw an error),warning(issue a warning but keep go-ing),message(print a message and keep going)or ignore(do nothing).Defaults to the option odin.unused_user_action,or warning otherwise.Delay equations with ddeWhen generating a model one must chose between using the dde package to solve the system or the default deSolve.Future versions may allow this to switch when using run,but for now this requires tweaking the generated code to a point where one must decide at generation.dde implements only the Dormand-Prince5th order dense output solver,with a delay equation solver that may perform better than the solvers in deSolve.For non-delay equations,deSolve is very likely to outperform the simple solver implemented.Author(s)Rich FitzJohnExamples##Compile the model;exp_decay here is an R6ClassGenerator and will##generate instances of a model of exponential decay:exp_decay<-odin::odin({deriv(y)<--0.5*yinitial(y)<-1},target="r")##Generate an instance;there are no parameters here so all instances##are the same and this looks a bit pointless.But this step isodin_build5 ##required because in general you don t want to have to compile the##model every time it is used(so the generator will go in a##package).mod<-exp_decay$new()##Run the model for a series of times from0to10:t<-seq(0,10,length.out=101)y<-mod$run(t)plot(y,xlab="Time",ylab="y",main="",las=1)odin_build Build an odin model generator from its IRDescriptionBuild an odin model generator from its intermediate representation,as generated by odin_parse.This function is for advanced use.Usageodin_build(x,options=NULL)Argumentsx An odin ir(json)object or output from odin_validate.options Options to pass to the build stage(see odin_optionsDetailsIn applications that want to inspect the intermediate representation rather before compiling,ratherthan directly using odin,use either odin_parse or odin_validate and then pass the result to odin::odin_build.The return value of this function includes information about how long the compilation took,if itwas successful,etc,in the same style as odin_validate:success Logical,indicating if compilation was successfulelapsed Time taken to compile the model,as a proc_time object,as returned by proc.time.output Any output produced when compiling the model(only present if compiling to C,and if the cache was not hit.model The model itself,as an odin_generator object,as returned by odin.ir The intermediate representation.error Any error thrown during compilationSee Alsoodin_parse,which creates intermediate representations used by this function.6odin_irExamples#Parse a model of exponential decayir<-odin::odin_parse({deriv(y)<--0.5*yinitial(y)<-1})#Compile the model:options<-odin::odin_options(target="r")res<-odin::odin_build(ir,options)#All results:res#The model:mod<-res$model$new()mod$run(0:10)odin_ir Return detailed information about an odin modelDescriptionReturn detailed information about an odin model.This is the mechanism through which coef works with odin.Usageodin_ir(x,parsed=FALSE)Argumentsx An odin_generator function,as created by odin::odinparsed Logical,indicating if the representation should be parsed and converted into an R object.If FALSE we return a json string.WarningThe returned data is subject to change for a few versions while I work out how we’ll use it. Examplesexp_decay<-odin::odin({deriv(y)<--0.5*yinitial(y)<-1},target="r")odin::odin_ir(exp_decay)coef(exp_decay)odin_ir_deserialise7 odin_ir_deserialise Deserialise odin’s IRDescriptionDeserialise odin’s intermediate model representation from a json string into an R object.Unlike the json,there is no schema for this representation.This function provides access to the same deserialisation that odin uses internally so may be useful in applications.Usageodin_ir_deserialise(x)Argumentsx An intermediate representation as a json stringValueA named listSee Alsoodin_parseExamples#Parse a model of exponential decayir<-odin::odin_parse({deriv(y)<--0.5*yinitial(y)<-1})#Convert the representation to an R objectodin::odin_ir_deserialise(ir)odin_options Odin optionsDescriptionFor lower-level odin functions odin_parse,odin_validate we only accept a list of options rather than individually named options.8odin_options Usageodin_options(verbose=NULL,target=NULL,workdir=NULL,validate=NULL,pretty=NULL,skip_cache=NULL,compiler_warnings=NULL,no_check_unused_equations=NULL,rewrite_dims=NULL,rewrite_constants=NULL,substitutions=NULL,options=NULL)Argumentsverbose Logical scalar indicating if the compilation should be verbose.Defaults to the value of the option odin.verbose or FALSE otherwise.target Compilation target.Options are"c"and"r",defaulting to the option odin.target or"c"otherwise.workdir Directory to use for any generatedﬁles.This is only relevant for the"c"target.Defaults to the value of the option odin.workdir or tempdir()otherwise.validate Validate the model’s intermediate representation against the included schema.Normally this is not needed and is intended primarily for development use.De-faults to the value of the option odin.validate or FALSE otherwise.pretty Pretty-print the model’s intermediate representation.Normally this is not needed and is intended primarily for development use.Defaults to the value of theoption odin.pretty or FALSE otherwise.skip_cache Skip odin’s cache.This might be useful if the model appears not to compile when you would expect it to.Hopefully this will not be needed often.Defaultsto the option odin.skip_cache or FALSE otherwise.compiler_warningsPreviously this attempted detection of compiler warnings(with some degree ofsuccess),but is currently ignored.This may become supported again in a futureversion depending on underlying support in pkgbuild.no_check_unused_equationsIf TRUE,then don’t print messages about unused variables.Defaults to the optionodin.no_check_unused_equations or FALSE otherwise.rewrite_dims Logical,indicating if odin should try and rewrite your model dimensions(if us-ing arrays).If TRUE then we replace dimensions known at compile-time withliteral integers,and those known at initialisation with simpliﬁed and shared ex-pressions.You may get less-comprehensible error messages with this optionset to TRUE because parts of the model have been effectively evaluated duringprocessing.rewrite_constantsLogical,indicating if odin should try and rewrite all constant scalars.This is asuperset of rewrite_dims and may be slow for large models.Doing this willmake your model less debuggable;error messages will reference expressionsthat have been extensively rewritten,some variables will have been removedentirely or merged with other identical expressions,and the generated code maynot be obviously connected to the original code.odin_package9 substitutions Optionally,a list of values to substitute into model speciﬁcation as constants, even though they are declared as user().This will be most useful in conjunctionwith rewrite_dims to create a copy of your model with dimensions known atcompile time and all loops using literal integers.options Named list of options.If provided,then all other options are ignored.ValueA list of parameters,of class odin_optionsExamplesodin_options()odin_package Create odin model in a packageDescriptionCreate an odin model within an existing package.Usageodin_package(path_package)Argumentspath_package Path to the package root(the directory that contains DESCRIPTION)DetailsI am resisting the urge to actually create the package here.There are better options than I cancome up with;for example devtools::create,pkgkitten::kitten,mason::mason,or creating DESCRIPTIONﬁles using desc.What is required here is that your package:•Lists odin in Imports:•Includes useDynLib(<your package name>)in NAMESPACE(possibly via a roxygen comment @useDynLib<your package name>•To avoid a NOTE in R CMD check,import something from odin in your namespace(e.g., importFrom("odin","odin")s or roxygen@importFrom(odin,odin)Point this function at the package root(the directory containing DESCRIPTION and it will write outﬁles src/odin.c and odin.R.Theseﬁles will be overwritten without warning by running this again.10odin_parseExamplespath<-tempfile()dir.create(path)src<-system.file("examples/package",package="odin",mustWork=TRUE)file.copy(src,path,recursive=TRUE)pkg<-file.path(path,"package")#The package is minimal:dir(pkg)#But contains odin files in inst/odindir(file.path(pkg,"inst/odin"))#Compile the odin code in the packageodin::odin_package(pkg)#Which creates the rest of the package structuredir(pkg)dir(file.path(pkg,"R"))dir(file.path(pkg,"src"))odin_parse Parse an odin modelDescriptionParse an odin model,returning an intermediate representation.The odin_parse_version is a"stan-dard evaluation"escape hatch.Usageodin_parse(x,type=NULL,options=NULL)odin_parse_(x,options=NULL,type=NULL)Argumentsx An expression,character vector orﬁlename with the odin codetype An optional string indicating the the type of input-must be one of expression, file or text if provided.This skips the type detection code used by odin andmakes validating user input easier.options odin options;see odin_options.The primary options that affect the parse stage are validate and pretty.DetailsA schema for the intermediate representation is available in the package as schema.json.It issubject to change at this point.See Alsoodin_validate,which wraps this function where parsing might fail,and odin_build for building odin models from an intermediate representation.Examples#Parse a model of exponential decayir<-odin::odin_parse({deriv(y)<--0.5*yinitial(y)<-1})#This is odin s intermediate representation of the modelir#If parsing odin models programmatically,it is better to use#odin_parse_;construct the model as a string,from a file,or as a#quoted expression:code<-quote({deriv(y)<--0.5*yinitial(y)<-1})odin::odin_parse_(code)odin_validate Validate an odin modelDescriptionValidate an odin model.This function is closer to odin_parse_than odin_parse because it does not do any quoting of the code.It is primarily intended for use within other applications.Usageodin_validate(x,type=NULL,options=NULL)Argumentsx An expression,character vector orﬁlename with the odin codetype An optional string indicating the the type of input-must be one of expression, file or text if provided.This skips the type detection code used by odin andmakes validating user input easier.options odin options;see odin_options.The primary options that affect the parse stage are validate and pretty.Detailsodin_validate will always return a list with the same elements:success A boolean,TRUE if validation was successfulresult The intermediate representation,as returned by odin_parse_,if the validation was success-ful,otherwise NULLerror An error object if the validation was unsuccessful,otherwise NULL.This may be a classed odin error,in which case it will contain source location information-see the examples for details.messages A list of messages,if the validation returned any.At present this is only non-fatal infor-mation about unused variables.Author(s)Rich FitzJohnExamples#A successful validation:odin::odin_validate(c("deriv(x)<-1","initial(x)<-1"))#A complete failure:odin::odin_validate("")#A more interesting failurecode<-c("deriv(x)<-a","initial(x)<-1")res<-odin::odin_validate(code)res#The object res$error is an odin_error object:res$error#It contains information that might be used to display to a#user information about the error:unclass(res$error)#Notes are raised in a similar way:code<-c("deriv(x)<-1","initial(x)<-1","a<-1")res<-odin::odin_validate(code)res$messages[[1]]Indexcan_compile,2coef,6odin,3,5odin_(odin),3odin_build,5,11odin_ir,4,6odin_ir_deserialise,7odin_options,5,7,10,11odin_package,4,9odin_parse,5,7,10,11odin_parse_,11,12odin_parse_(odin_parse),10odin_validate,5,7,11,11pkgbuild::find_rtools(),2proc.time,5tempdir(),3,813。

3L看听学Y英语第一册课文电子版

Lesson 1Narrator：Meet Sandy and Sue!Narrator：This is Sue's class.Narrator：Her teacher's Mr Crisp.Mr Crisp：Which is your pen, SueSue：The red pen, sir.Mr Crisp：Here you are, Sue.Sue：Thank you, sir.Lesson 3Narrator：This is Sandy's class.Narrator：His teacher's Miss Williams.Miss Williams：Whose is this capTom：It's Sandy's, Miss Williams.Miss Williams：Sandy!Sandy：Yes, Miss Williams.Miss Williams：Come here, please.Sandy：Yes, Miss Williams.Miss Williams：Is this your capSandy：Yes, it is.Miss Williams：Here you are Sandy. Sit down, please. Sandy：Thank you, Miss Williams.Lesson 5Tom：Kick the ball, Sandy!Sandy：All right, Tom.Tom：Look, Sandy!Mr Crisp：Oh!Mr Crisp：It's all right, Sandy. Whose is this ballMr Crisp：Is this your ball, TomTom：No, it isn't, sir.Mr Crisp：Is this your ball, SandySandy：Yes, it is, sir.Lesson 7Mr May：Who's that girl, Mr CrispMr Crisp：Which girl, Mr MayMr May：The girl on the red bicycleMr Crisp：That's Sue Clark. She's in my class.Mr May：Who's that boy, Mr Crisp.Mr Crisp：Which boy, Mr MayMr May：The boy with the football.Mr Crisp：That's Sandy Clark He's Sue's brother. Tom：Kick the ball, Sandy!Mr Crisp：Look out, Mr May!Lesson 9Mother：Hullo, Sandy! Hullo, Sue!Children：Hullo, Mum!Mother：Tea's ready.Mother：Are you hungry, SueSue：Yes, I am.Mother：Are you hungry, SandySandy：No, I'm not.Sandy：What's for teaMother：Look!Mother：Are you hungry now, SandySandy：Oh yes, I'm very hungry.Lesson 11Sandy：Look at my picture, Sue.Sue：That's nice, Sandy.Sue：What's thatSandy：It's a bicycle.Sue：Who's thatSandy：It's Tom. He's on his bicycleSue：What's thisSandy：It's a car.Sue：Who's thisSandy：It's Mr Crisp.Sandy：He's in his car.Lesson 13Mother：This egg is for you, Sandy!Sandy：Thanks, Mum.Sue：Listen, Sandy! That's Dad's car. Eat your egg quickly. Sue：Now put the egg in the egg-cup like thisFather：Good evening, Betty.Mother：Good evening, Jim.Father：Good evening, Children.Children：Good evening, Dad.Sandy：Tea's ready, Dad. This egg is for youFather：An egg! That's nice. I'm hungryFather：Oh! It's empty!Lesson 15Sue：Put on Dad's hat, Sandy!Sandy：Put on Mum's shoes, Sue!Sandy：You are funny, Sue!Sue：You're funny, too, Sandy!Sue：Come with me.Sandy：Knock at the door, Sue.Mother：Come in!Sandy：Look at me! I'm an actorSue：Look at me! I'm an actress.Lesson 17Sandy：Who's that boy, TomTom：Which boy, SandySandy：That fat boy.Tom：He's a new boy. His name's Billy BriggsSandy：Look at him!Miss Williams：Billy!Billy：Yes, Miss WilliamsMiss Williams：Open your desk and give me that apple Billy：I'm sorry, Miss Williams. I'm hungryLesson 19Sandy：My bag's heavy!Tom：What's in it, SandySandy：Open it and see.Tom：Six books and six exercise-booksBilly：My bag's heavy, too.Tom：What's in it, BillyBilly：Open it and see!Tom：One book, two apples, three oranges and a banana!Lesson 21Tom and Bill：What nationality are you French or German Sandy(whispering)：I'm FrenchTom：Come on my side!Tom and Billy：What nationality are youSue(whispering)：I'm German.Billy：Come on my side.Tom and Billy：Pull! Pull!Lesson 23Sandy：Give me that box please, Sue.Sue：Which box, Sandy This oneSandy：No, not that one. The big blue one.Sue：What's in it, SandySandy：Open it and see.Sue：Oh!Sandy：It's a Jack-in-the-box!Lesson 25Sue：There's a man at the door, Dad.Father：Who is it, Sue Open the door!Sue：It's the postman, Dad.Postman：Good morning, Sue.Sue：Good morning, postman.Postman：There's a letter for your mother. And there's a letter for your father. Sue：Thank you.Sue：Dad! There's a letter for mum and there's a letter for you.Father：This isn't a letter! It's a bill!Lesson 27Gym Master：Look at these shoes!Gym Master：Which are your shoes, SandySandy：The brown shoes, sir.Gym Master：What colour are your shoes, TomTom：My shoes are black sir.Gym Master：Here you are, Tom.Tom：Thank you, sir.Gym Master：There's a shoe on this locker. Whose is itTom：It's Billy's, sir.Lesson 29Mother：Are your hands clean, SandySandy：Yes, my hands are clean, Mum.Mother：Show me your hands, Sandy.Mother：Your hands aren't clean. They're very dirty!Mother：Go and wash your hands at once!Sandy：All right, Mum.Mother：Are your hands clean now, SandySandy：Yes, they are, MumMother：Sandy! Look at my nice clean Towel!Lesson 31Tom：Heads or tails, SueSue(calling)：Heads!Sue：It's heads!Tom：Come on our side.Tom：Heads or tails, SandySandy(calling)：Tails!Sandy：It's tails!Tom：Go on their side.Tom and Billy：Pull! Pull!Lesson 33Mother：These shoes are nice. Try on these shoes, Sue. Salesman：Sit down here, please.Mother：How are they, SueSue：They're very tight, MumSue：Oh, Mum! Look at those shoes. Those are pretty shoes Salesman：Here you are, young lady.Mother：How are they, SueSue：They're just right!Lesson 35Sandy：What are these, BillyBilly：They're stamps.Billy：These are French stamps.Billy：And those are Italian stamps.Sandy：Show me those Italian stamps, Billy. They're very pretty Sandy：Give me this one please, Billy.Billy：Give me two apples then.Sandy：Two apples for one stamp! No, thank you!Lesson 37Mr Crisp：Good morning, childrenClass：Good morning, sirMr Crisp：Sit down, please.Mr Crisp：These two girls are new pupils. Their names are Liz and Lillie. Mr Crisp：Liz and Lillie are twins. They are in our class.Mr Crisp：This is... er ... Liz. And this is... er ...Lillie.Lillie：I'm not Liz. I'm Lillie. She's Liz.Liz：I'm not Lillie. I'm Liz. She's Lillie.Mr Grisp：Twins!Lesson 39Sandy：Whose are these sandwiches, TomTom：They're Billy's.Tom：Open the packet, Sandy.Tom：Take out the sandwiches.Tom：Put in this duster and this bookTom：Hurry up! There's Billy!Billy：Hey! Leave my sandwiches alone!Sandy：Here you are, Billy.Billy：That's funny. These sandwiches are very hardBilly：Oh! Give me my sandwiches quickly!Lesson 41Sandy：Listen, Sue! That's the school bell.Sue：Hurry up, Sandy! We're late for schoolSandy：What's the time, SueSue：It's nine o'clock.Sandy：Look! There's the headmaster. He's in the playground.Sue：Oh, dear!Headmaster：You're both very late this morning.Sandy and Sue：We're sorry, sir.Headmaster：Go to your classrooms quickly!Sandy and Sue：Yes, sir.Lesson 43Father：The children are very quiet this morning, Betty.Mother：Sandy! Sue! Breakfast's ready.Father：Go upstairs and see, Betty. Perhaps they're still asleep. Mother：Wake up, Sandy! It's eight o'clock.Sandy(sleepily)：EhMother：Wake up! You're late.Sandy：No, I'm not, Mum. The school's shut today. It's a holiday! Mother：Lazybones!Lesson 45Sue：Give us two packets of sweets please, Mr HillMr Hill：Which packets, Sue These blue onesSue：No, not those. The big red ones.Sandy：How much are they, Mr HillMr Hill：A shilling each.Sandy：A shilling each! That's all our pocket-money!Sue：Give us two small lollipops instead.Lesson 47Miss Williams：This prize is for Billy, Sandy and Tom. Here you are, Billy. Billy：Thank you, Miss Williams.Tom：What is it, BillyBilly：It's a box of chocolatesSandy：How many chocolates are there Count them, BillyBilly：One, two, three, four, five, six... There are twenty-four.Tom：Eight chocolates each. Share them, Billy.Billy：One for Tom and one for me. One for Sandy and one for meOne for Tom and one for me. One for Sandy and one for me…Sandy and Tom：Hey! That's not right!Lesson 49Mother：Post these letters for me please, Sue.Sue：. Mum.Sue：Good morning, postman.Postman：Good morning, Sue. How are you todaySue：Fine, thanks.Sue：Are there any letters in the letter box this morning Postman：No, there aren't any letters here.Sue：Just a minute.Sue：There are some letters in the letter box now.Postman：Thank you, Sue.Lesson 51 Father's glassesFather：Where are my glasses Sue Are they over thereSue：Where, dadFather：There. Near that box.Sue：No, they aren't here, dad.Father：And they aren't under this newspaper.Sue：Perhaps they're in your pocket, dad.Father：So they are! How silly of me!Lesson 53 Hide-and-seekSue：Let's play hide-and-seek.Billy：Count up to ten, Sue.Sue：One, two, three, four, five, six, seven, eight, nine, ten. I'm ready! Sue：I can see you, Billy. You're behind that fence.Sue：Where's SandyBilly：He's beside that tree.Sue：That's funny! He's not here.Sue：Look! There he is! He's up there!Lesson 55 Sandy's kiteSandy：Hold this kite for me please, SueSandy：Now stand between those two trees.Sue：All right, Sandy.Sandy：Ready, SueSue：I'm ready, Sandy. Pull the kite.Sandy：Look at it, Sue! It's like a bird!Sue：I can't see it. Where is itSandy：It's over that building.Sue：I can see it now. It's very high.Lesson 57 Silly BillyTeacher：Get into lines boys. Good. Now we can do some exercises. Teacher：Jump together! One, two, three, four, stop!Teacher：Touch your knees!Teacher：Touch your toes!Teacher：Pay attention, Tom. Don't laugh!Sandy：What's the matter, TomTom：Silly Billy can't touch his toes.Lesson 59 Good old Billy!Teacher：Bring me that ball please, Tom.Tom：Yes, sir.Teacher：Now let's play football. Are you all readyBoys：Yes, sir.Tom：Quick, Sandy! Pass me the ball!Tom：Oh, Sandy! Don't pass it to Billy. Pass it to me.Sandy：Kick it, Billy!Tom：It's a goal!Sandy：Good old Billy!Teacher：Billy can't touch his toes, but he can play football!Lesson 61 The bird's nestMother：What's the matter, JimFather：I can't light this fire.Father：Please hold this ladder, dear.Father：Well! Well!Mother：What can you see, JimFather：There's a bird's nest in our chimney.Mother：Show it to Sandy and Sue.Father：Sandy! Sue! Come here a moment.Sandy and Sue：Yes, dad.Father：Look at this bird's nest. There are three pretty eggs in it. Sue：Give them to Sandy and meLesson 63 A paper boatSandy：Look at this paper boat, Sue.Sue：That's a nice boat, Sandy.Sue：Let's fill the wash-basin with water.Sandy：Turn on the tap.Sue：Can I make a boat like that Show me, SandySandy：Take a piece of paper and fold it like this.Mother：Sandy! Sue! Look at this wash-basin! Turn the tap off at once.Lesson 65 Upside-downSandy：Can you stand on your head, TomSandy：Look! Like this.Tom：Let me try.Tom：That's easy. I can do it.Tom：Billy can't stand on his head.Billy：Of course, I can!Billy：Watch me! Now I'm upside-down.Sandy：Look, Tom! Billy's pockets are full of sweets!Lesson 67 A punctureTom：Pump up this tyre, Sandy. It's very flat.Sue：What are you doing, SandySandy：I'm pumping up this tyre.Sandy：Whew! I'm tired.Tom：It's still flat.Tom：Let's take the tyre off the wheel.Sue：Put the tube in this basin, Sandy.Tom：Look at those bubbles. There's a puncture in this tube.Lesson 69 A game of hopscotchBilly：Hullo Liz, hullo Lillie, hullo Sue.Girls：Hullo Billy.Billy：What are you doingLiz：We're playing hopscotch.Billy：Can I play, tooGirls：All right.Billy：It's my turn.Sue：Throw your stone, Billy.Tom：Look at Billy! He's playing hopscotch with the girls!Sandy：Hopscotch is a girls game, Billy.Tom：Come and play football with us.Lesson 71 Father's telescopeFather：Look through this telescope, Sandy What can you seeSandy：I can see a man and a dog.Father：What are they doingSandy：They're standing beside a lake.Father：What's the man doing nowSandy：He's picking up a stick.Father：What's happening nowSandy：Now the man's throwing the stick into the water.Father：What's happening nowSandy：Now the dog's swimming across the lake.Sandy：Now the dog's holding the stick between its teeth. It's swimming back to the man.Lesson 73 Happy birthday, Billy!Sandy and Sue are going to Billy's house.It's Billy's birthday. Billy's nine years old today."Happy birthday, Billy," Sandy says"Happy birthday, Billy," Sue says."Here is a present for you," Sandy says."Thank you, Sandy. Thank you, Sue," Billy says.Billy is opening his present."Is it a Jack-in-the-box" he asks."No, it isn't," Sue answers."It's a car!" Billy says." And it's made of chocolate!"Lesson 75 Three cheers for BillyThe children are enjoying Billy's birthday party.They're wearing funny hats. They're laughing and playing gamesNow they're eating sandwiches, cakes and biscuits. They're drinking lemonade, too. Billy's birthday cake is very big. There are nine candles on it."Can you blow out the candles" Sandy asks."Of course I can," Billy answers. "Watch me!""Three cheers for Billy," Sandy shouts.Sandy：Hip! Hip! Children：Hurray!Sandy：Hip! Hip! Children：Hurray!Sandy：Hip! Hip! Children：Hurray!Lesson 77 Sh! Be quiet!Sue：Let's go into the store-room, SandySandy：All right, Sue.Sue：Where's your torch, SandySandy：Here it is.Sue：Look, Sandy! I can see a man standing beside that box!Sue：Turn on your torch, Sandy.Sandy：You're right, Sue There's a man standing beside that box!Sue：Sh! Be quiet! Come with me!Sandy：Look! It's only an old hat and an old coat.Lesson 79 Ugh!Sandy：Is there any sugar in my tea, SueSue：Taste it, Sandy.Sandy：Ugh! It's not very nice. This isn't tea! It's coffee!Mother：Sandy! What are you drinkingSue：He's drinking dad's coffee, mum.Mother：Give me that cup please, Sandy.Sandy：It's not very nice, mum. There isn't any milk or sugar in it.Lesson 81 Sue helps motherSue：What are you doing, mumMother：I'm making some sandwiches for tea.Sue：Let me help you, mum. I can cut the bread.Mother：All right, Sue.Mother：Sue! Those slices are very thick. Give me the bread-knife please.Mother：Bring me some jam.Sue：Yes, mum.Sue：Mum! Sandy's eating the jam!Sue：The jar's nearly empty.Lesson 83 Billy draws Miss Williams.Billy：Pass me some white chalk, Sandy. I can draw Miss Williams.Billy：Now pass me some blue chalk and some red chalk.Miss Williams：Billy! What are you doingBilly：I'm drawing, Miss Williams.Miss Williams：Is that me, BillyBilly：Yes,Miss Williams. I'm sorry.Miss Williams：It's all right, Billy.Miss Williams：It's a nice picture.Miss Williams：My eyes are blue, Billy. But my nose isn't red! Sit down, please.Lesson 85 A picture of Billy.Miss Williams：Take out a piece of paper, children.Miss Williams：Now you can all draw a picture.Miss Williams：What are you drawing, Tom.Tom：A football match, Miss Williams.Miss Williams：What are you drawing, SandySandy：Billy's birthday party.Miss Williams：Who's thisSandy：It's Billy.Sandy：He's holding a bar of chocolate in his right hand and a bottle of lemonade in his left hand.Lesson 87 Mother's shopping-listSue：What are you doing, mumMother：I'm making a shopping-list, Sue.Sue：Let me help you.Mother：All right, Sue. Open that cupboard.Mother：Is there any jam or honey in the cupboardSue：There isn't much jam, but there's a lot of honey.Mother：Are there any apples and oranges in that bowlSue：There aren't many oranges, but there are a lot of apples.Mother：Sugar, tea, jam, oranges...Sue：And bananas for Sandy and me.Lesson 89 Flour on the floorNarrator：Mother is still making her shopping-list. Sue is still helping her. Mother：Is there any butter in the refrigeratorSue：There's very little, mum.Mother：Are there any tomatoes in the refrigeratorSue：There are very few, mum.Mother：Is there any flour in that tinSue：Yes, there's a lot.Mother：Be careful, Sue!Sue：I'm sorry, mum.Mother：Never mind, Sue.Sue：There isn't much flour in the tin now!Mother：No, but there's a lot on the floor!Lesson 91 Beans or ice-creamMother：Some meat, potatoes and beans for Sue.Sue：Thanks, mum.Mother：Some meat, potatoes and beans for Sandy.Sandy：I don't like beans, mum. I don't want any.Father：There's some ice-cream in the refrigerator, Sandy. Do you want any Sandy：Yes please.Father：Then eat some beans or I can't give you any ice-creamMother：Do you want any beans now, SandySandy：Yes please.Sandy：I want a lot of beans. And I want a lot of ice-cream, too.Lesson 93 Don't forget your change!Mother：Go and buy a large tube of toothpaste, and a small bar of soap please, Sue. Mother：Here's some money.Sue：Thanks, mum.Sue：Good morning, Mr Green.Mr Green：Good morning, Sue.Sue：My mother wants a tube of toothpaste and a small bar of soap, please.Mr Green：A large tube or a small one, SueSue：She wants a large one, please.Mr Green：Here you are, Sue.Sue：Thank you, Mr Green Goodbye.Mr Green：Sue!Sue：Yes, Mr GreenMr Green：Don't forget your change!Lesson 95 The snowmanSue：Come to the window quickly, Sandy! It's snowing.Sue：Mum, we want some buttons please.Sandy：And a carrot.Mother：Do you want a lot of buttons, SueSue：No, I don't want very many.Sandy：We want dad's old hat, too.Sue：And an old pipe.Mother：What are you doing, childrenChildren：We're making a snowman, mum.Sue：His eyes are black buttons.Sandy：And his nose is a carrot.Lesson 97 It's time for bedMother：Hurry up, children. It's time for bed.Sue：Oh! We're not sleepy, mum.Sandy：I don't want to go to bed. I want to watch televisionSue：I want to watch television, too.Mother：All right then. You can watch television for ten minutesFather：Are the children in bed, BettyMother：No, they're watching television.Father：Sandy! Sue! It's time for bed.Father：Look at them! They're both fast asleep!Lesson 99 Wake up, Billy!Miss Williams：Look at this boy. His name's Paul. He's a French boy.Miss Williams：Now look at this map of the world.Miss Williams：This country is France. Paul comes from France.Miss Williams：The capital city of France is Paris. Paul lives in Paris.Miss Williams：What language does Paul speak, Billy.Billy：Er... er... He speaks German, Miss Williams.Miss Williams：Wake up, Billy! You're not paying attention! Paul speaks French.Lesson 101 Simon's never careless but Billy...!Miss Williams：Here's your exercise-book, BillyMiss Williams：You're often careless. Look at these mistakesMiss Williams：Don't laugh at Billy, Sandy!Miss Williams：Whose is this exercise-bookBilly：It's Sandy's, Miss Williams.Miss Williams：Sandy, put your name on the cover. You are sometimes careless, too!Miss Williams：Look at Simon's exercise book. Simon's never careless. His work is always neat and tidy. Billy! You naughty boy!Lesson 103 Which season do you like bestMiss Williams：Look at the blackboard, children.Miss Williams：What's the weather like in Spring, Sandy.Sandy：It's often warm, Miss Williams.Miss Williams：What's the weather like in SummerSandy：It's often hot.Miss Williams：What's it like in Autumn, TomTom：It's often cool.Miss Williams：What's it like in Winter, BillyBilly：It's often cold.Miss Williams：Which season do you like best, Billy Spring, Summer, Autumn or WinterBilly：I like Winter. That's the football season!Lesson 105 The school yearThere are four terms in the school year：the Autumn Term, the Winter Term, the Spring Term and the Summer TermThe first term is the Autumn Term. The Autumn Term begins in September and ends in DecemberThe second term is the Winter Term. The Winter Term begins in January and ends in AprilThe third term is the Spring Term. The Spring Term begins in May and ends in JulyThe fourth term is the Summer Term. The Summer Term begins in July and ends in SeptemberSandy and Sue like the Summer Term best. They are always on holiday then. They always go to the seaside.Lesson 107 North, South, East and West.Miss Williams：Look at this map of Britain. This is the North. It often snows in the North.Miss Williams：This is the South. The sun often shines in the South.Miss Williams：This is the East. The wind often blows in the East.Miss Williams：This is the West. It often rains in the West.Miss Williams：In winter, the sun always rises late and always sets early.The days are short and the nights are long.Miss Williams：In summer, the sun always rises early and always sets late.The days are long and the nights are short.Lesson 109 They don't always go to sleep!The Clarks always get up early every day.In the morning, father always goes to work.Sandy and Sue always go to school.Mother usually stays at home.At midday, Sandy and Sue always eat their lunch at school.In the afternoon, Sandy and Sue always come home from school.They usually arrive home early.In the evening, Sandy and Sue always do their homework.At night they go to bed early, but they don't always go to sleep!Lesson 111 A holidayIt is seven o'clock.Sandy and Sue usually get up early every day. but today it is a holiday.It is a quarter to nine.Sandy and Sue usually go to school in the morning, but this morning they are walking to the parkIt is a quarter past four.Sandy and Sue usually come home from school in the afternoon, but this afternoon they are playing in the park. It is half past six.Sandy and Sue usually do their homework in the evening, but this evening they are watching televisionIt is a quarter past eight.Sandy and Sue usually go to bed early at night, but tonight they are playing a game.They are playing Snakes and Ladders!Lesson 113 A flat tyreMiss Williams is driving her car to school.Suddenly, she stops. "That's funny," she says.She gets out of her car. "Oh dear!" she says."It's twenty to nine. I can't get to school on time this morning!"Then a car stops behind her. It's Mr Crisp!"What's the matter" Mr Crisp asks."Look!" Miss Williams says. "A flat tyre.""It doesn't matter. " Mr Crisp says. "Come in my car."Lesson 115 The weekMonday mornings are usually terrible. Father always gets up late and he's always in a hurry.On Tuesday mother usually goes to the shops.On Wednesday Sandy and Sue always play games at school.On Thursday Miss Jones always gives Sue her piano lesson. Sue likes this lesson very much.On Friday Miss Jones always gives Sandy his piano lesson. Sandy doesn't like it at all!Saturday and Sunday are the best days of the week. The family usually spend a quiet week-end at home!Lesson 117 .The weather forecast.Sandy：It's Saturday tomorrow. What are we going to do tomorrowSue：Let's ask mum.Mother：We're going to spend the day at the seasideSandy：The seaside!Sue：Hurray!Father：Let's listen to the weather forecast first. Turn the television on, Sue.Television：Here is the weather forecast for tomorrow.Television：It's going to snow in the North and it's going to rain in the South.Sandy and Sue：Oh!Mother：Never mind, children.Father：We can go to the cinema instead.Lesson 119 Fixing the clockFather：That clock doesn't work.Mother：I'm going to take it to the watchmaker's next week.Father：Don't take it to the watchmaker's. Give it to me. I can fix it.Sandy：What are you doing, dadFather：I'm fixing this clock.Mother：Is it nearly ready now, JimFather：No, Betty. I can't put all these pieces together!Mother：Oh, Jim! Give me all the pieces. I'm going to take them to the watchmaker's at once!。

基于ALOS_DEM_的山西省西山矿区地貌形态类型提取

第54卷第5期2023年9月太原理工大学学报J O U R N A L O F T A I Y U A N U N I V E R S I T Y O F T E C HN O L O G YV o l .54N o .5S e p.2023 引文格式:梁宏艳,赵尚民,马顶.基于A L O S D E M 的山西省西山矿区地貌形态类型提取[J ].太原理工大学学报,2023,54(5):950-958.L I A N G H o n g y a n ,Z HA O S h a n g m i n ,MA D i n g .A L O S D E M -b a s e d e x t r a c t i o n o f g e o m o r p h o l o gi c a l f e a t u r e i n X i s h a n m i n i n g a r e a o f S h a n x i p r o v i n c e [J ].J o u r n a l o f T a i y u a n U n i v e r s i t y o f T e c h n o l o g y,2023,54(5):950-958.收稿日期:2021-11-23;修回日期:2022-03-09基金项目:山西省自然科学基金资助项目(201901D 111098);国家重点研发计划项目(2017Y F B 0503603) 第一作者:梁宏艳(1996-),硕士研究生,(E -m a i l )1160159421@q q.c o m 通信作者:赵尚民(1982-),博士,副教授,主要从事数字地形地貌与生态环境遥感的研究,(E -m a i l )z h a o s h a n g m i n @t yu t .e d u .c n 基于A L O S D E M 的山西省西山矿区地貌形态类型提取梁宏艳a ,赵尚民b ,马顶b(太原理工大学a .安全与应急管理工程学院,b .矿业工程学院,太原030024)摘要:ʌ目的ɔ地貌是地球表层系统最重要的自然地理要素,其形态划分对地学空间分异研究具有重要意义㊂ʌ方法ɔ以山西省西山矿区作为研究区,利用该区A L O S 12.5m D E M 数据,通过窗口递增分析和均值变点分析得到地形因子最佳分析窗口为13ˑ13(0.0264k m 2);利用相关性分析获得最佳地形因子为地形起伏度㊁海拔高度㊁坡度㊁地表切割深度和地表粗糙度;利用区域统计分析得到典型地形因子的分布状况,结合叠加分析提取了西山矿区30种地貌类型,其中浅切割陡小起伏中山为主要地貌,占总面积比为21.23%.ʌ结果ɔ通过与1ʒ100万地貌类型图的图斑数和地貌分类界线对比,得出地貌类型增加了21类,图斑数目增加了296个,分类界线更为准确,验证了研究结果具有一定可靠性和可行性㊂ʌ结论ɔ本地貌划分方法较以往更加科学可行,为进一步研究西山矿区灾害防治㊁开发利用等问题提供了数据参考㊂关键词:A L O S D E M ;地貌提取;最佳地形因子;西山矿区中图分类号:P 23 文献标识码:AD O I :10.16355/j .t yu t .1007-9432.2023.05.024 文章编号:1007-9432(2023)05-0950-09A L O S D E M -B a s e d E x t r a c t i o n o f G e o m o r p h o l o gi c a l F e a t u r e i n X i s h a n M i n i n g Ar e a o f S h a n x i P r o v i n c e L I A N G H o n g y a n a,Z H A O S h a n g m i n b,M A D i n gb(a .C o l l e g e o f S a f e t y a n d E m e r g e n c y M a n a g e m e n t E n g i n e e r i n g ,b .C o l l e g e o f M i n i n g E n g i n e e r i n g ,T a i y u a n U n i v e r s i t y o f T e c h n o l o g y ,T a i yu a n 030024,C h i n a )A b s t r a c t :ʌP u r po s e s ɔG e o m o r p h o l o g y i s t h e m o s t i m p o r t a n t p h y s i c a l g e o g r a p h i c a l e l e m e n t o f t h e E a r t h 's s u r f a c e s y s t e m ,a n d i t s m o r p h o l o g i c a l d i v i s i o n i s o f g r e a t s i g n i f i c a n c e t o t h e s t u d y of g e o s p a t i a l d i f f e r e n t i a t i o n .ʌM e t h o d s ɔX i s h a n m i n i n g ar e a i n S h a n x i P r o v i n c e w a s t a k e n a s t h e r e -s e a r c h a r e a ,o n t h e b a s i s o f t h e A L O S 12.5m D E M d a t a o f t h e a r e a ,t h e o p t i m u m a n a l ys i s w i n -d o w o f t h e r e l i e f a m p l i t u d e w a s d e t e r m i n e d t o b e 13ˑ13(0.0264k m 2)a c c o r d i n gt o t h e w i n d o w i n c r e m e n t a n a l y s i s a n d m e a n -v a r i a t i o n a n a l y s i s .T h e o p t i m a l t e r r a i n f a c t o r s ,s u c h a s r e l i e f a m pl i -t u d e ,e l e v a t i o n ,s l o p e ,s u r f a c e i n c i s i o n ,a n d s u r f a c e r o u g h n e s s w e r e o b t a i n e d b y co r r e l a t i o n a n a l -y s i s .T h e d i s t r i b u t i o n o f t y p i c a l t e r r a i n f a c t o r s w a s o b t a i n e d b y r e g i o n a l s t a t i s t i c a l a n a l ys i s ,a n d c o m b i n e d w i t h s u p e r p o s i t i o n a n a l y s i s ,30g e o m o r p h i c t y p e s w e r e e x t r a c t e d i n X i s h a n m i n i n g a r e a ,a m o n g w h i c h s h a l l o w c u t s t e e p a n d s m a l l u n d u l a t i n g m o u n t a i n w a s t h e m a i n g e o m o r ph i c ,a c -Copyright ©博看网. All Rights Reserved.c o u n t i n g f o r21.23%o f t h e t o t a l a r e a.ʌF i nd i n g sɔB y c o m p a r i n g w i t h t he n u m b e r of m a p s p o t s a n dg e o m o r phi c c l a s s i f i c a t i o n b o u n d a r y o f1ʒ1000000g e o m o r p h i c t y p e m a p,i t w a s c o n c l u d e d t h a t21g e o m o r p h i c t y p e s a n d296m a p s p o t s w e r e a d d e d,a n d t h e c l a s s i f i c a t i o n b o u n d a r y w a s m o r e a c c u r a t e,w h i c h v e r i f i e d t h e r e l i a b i l i t y a n d f e a s i b i l i t y o f t h e r e s e a r c h r e s u l t s.ʌC o n c l u s i o n sɔT h e l a n d f o r m c l a s s i f i c a t i o n m e t h o d i n t h i s s t u d y i s m o r e s c i e n t i f i c a n d f e a s i b l e t h a n b e f o r e,w h i c h p r o v i d s d a t a r e f e r e n c e f o r f u r t h e r s t u d y o n d i s a s t e r p r e v e n t i o n,d e v e l o p m e n t,a n d u t i l i z a t i o n i n X i s h a n m i n i n g a r e a.K e y w o r d s:A L O S D E M;g e o m o r p h o l o g i c a l e x t r a c t i o n;o p t i m u m t e r r a i n f a c t o r;X i s h a n m i n-i n g a r e a地貌作为地球表层系统举足轻重的自然地理因素,不仅复杂多变,而且对其他自然要素的特征起着重要的作用,因此全面科学地对地貌形态进行分类对于生产建设具有重要的意义[1]㊂地貌分类是指将地貌系统依据一定原则,运用一组指标,使用一套方法进行系统划分的过程,或是将地貌实体按照其内在特征的一致性进行归类的过程[2]㊂地貌分类的研究历史悠长,我国古代文献资料对其已有许多记载和研究㊂例如,早在我国古代地貌研究历史书籍‘尔雅“上,就做了相关的描述划分,具体命名为释地释丘释山和释水等㊂自此,相继有学者对地貌形态划分做了研究[3-7],这些传统地貌分类研究信息主要利用实地测量和野外勘察来获取,虽然具有较高准确性,但是工作量大㊁效率低,难以满足实际科研工作的需求;近年来,迅速发展的遥感技术(R S)和地理信息技术(G I S),为获取更加详细精确的地貌信息提供了技术手段,也为获取高分辨率的D E M数据打下了基础[8]㊂高分辨率D E M数据派生的地形因子推动了地貌形态分类研究的进展,然而大多数学者在地貌形态分类过程中,多采用宏观地形因子海拔高度和地形起伏度来描述[9-12],虽然这两个地形因子在地貌划分研究中起着重要的作用,但是研究表明地貌形态的完整信息难以仅通过这两个地形因子来概括㊂且随着地貌划分研究不断发展,D R A G U T e t a l[13]学者已将微观地形因子应用到地貌分类研究中,为全面划分地貌提供了研究思路㊂因此,多种地形因子综合分析法成为更加全面表达地貌综合信息的普遍方法[14-18]㊂本文以西山矿区作为研究区域,结合前人研究,提取并确定了以海拔高度㊁地表切割深度㊁地形起伏度和坡度4种地形因子为主,地表粗糙度为辅的地貌形态划分体系,由主入辅,由宏观到微观,对西山矿区地貌形态进行了深入研究,并从图斑数目及分类界线两方面对本文提取结果进行了精确性验证,对该地区后续的水土利用和生态环境保护研究具有重要意义㊂1研究区与数据源1.1研究区域概况西山矿区位于111ʎ38'E~112ʎ36'E㊁北纬37ʎ19'N-38ʎ13'N如图1所示,地处山西高原中部地区,西北两面环山㊂现如今的构造位置为吕梁山脉的中段东部地区,太原新生代断陷盆地西侧,横跨太原市万柏林区㊁晋源区㊁尖草坪区㊁古交市㊁娄烦县㊁清徐县,吕梁市交城县㊁文水县等8个地区,南北最长处约70.5k m,东西最宽处约55.7k m,总面积达到了2044.53k m2,含煤面积为1662.55k m2,是山西省大型煤矿区㊂研究区海拔范围为734~2179m,总的地势特点为西南高㊁东北低,分为东部前山区和西部后山区,东部前山区以构造剥蚀地貌为主,地形切割剧烈,西部后山区以丘陵地貌为主,是主要农业区,但冲沟亦较发育,水土流失比较严重㊂再加上地下采煤引发的地表塌陷,使得西山矿区生态环境脆弱,较易发生崩塌㊁滑坡㊁泥石流㊁地裂缝等地质灾害㊂不同地貌形态类型对地质灾害的发生影响机理不尽相同,本文基于A L O S D E M对研究区地貌形态类型进行提取,并得到其空间分布特征,为后续针对不同地貌形态因地制宜地采取不同地质灾害防治措施提供数据支持与理论参考㊂1.2数据来源本文采用的D E M数据为2011年A L O S D E M,该数据水平及垂直精度可达12m,空间分辨率为12.5m,在我国的覆盖率>95%.本研究数据下载自E a r t h d a t a网站(h t t p s:ʊs e a r c h.a s f.a l a s k a.e d u/#/),通过一系列影像预处理得到,主要包括拼接和裁剪等操作㊂159第5期梁宏艳,等:基于A L O S D E M的山西省西山矿区地貌形态类型提取Copyright©博看网. All Rights Reserved.高：2 179低：734N10高：3 047低：169ALOS/m 600120 km114°0′E112°0′E110°0′E114°0′E112°0′E110°0′E40°0′N38°0′N36°0′N40°0′N38°0′N36°0′NNALOS/m20 km112°0′E112°15′E112°30′E112°0′E 112°15′E 112°30′E38°0′N37°45′N37°30′N 38°0′N 37°45′N37°30′N 图1 研究区位置及海拔分布F i g .1 L o c a t i o n a n d e l e v a t i o n d i s t r i b u t i o n o f t h e s t u d y ar e a 2 研究方法地形因子可以定量描述地貌的特征,根据其所描述的空间范围,可以将其分为宏观和微观两种[14]㊂本文首先通过窗口递增分析和均值变点分析确定地形起伏度的最佳分析窗口,然后对所选取的海拔高度㊁地形起伏度㊁地表粗糙度㊁地表切割深度和高程变异系数5个宏观因子,坡度㊁地表累计曲率2个微观因子等7个地形因子进行相关性分析确定最佳地形因子组合,最后通过G I S 空间分析的区域分析对研究区内典型地形因子空间分布特征进行分析,叠加分析对地貌形态进行划分㊂2.1 最佳分析窗口的确定地形起伏度是划分地貌形态的重要指标㊂根据地貌发育理论,一种地貌类型存在一个使最大高差达到相对稳定的最佳分析面积,并且该面积在一定程度上能最大化地表达地貌的完整性[19-20]㊂基于D E M 数据提取的地形起伏度的精度和表达能力与该分析面积密切相关[21-22]㊂本文首先利用P yt h o n 代码编程进行批量窗口递增分析计算,得到了2ˑ2窗口到32ˑ32窗口下的地形起伏度[23]㊂其次,对计算得到的地形起伏度大小和窗口面积进行对数拟合,拟合出的对数曲线方程为y =20.446l n x +40.456,R 2=0.9456.R2越接近1,拟合曲线的结果越好㊂本文相关系数为0.9456,通过了拟合优度检验㊂计算最佳统计窗口大小方法有多种,研究表明,均值变点分析法是最为理想的一种[24-26]㊂因此本文地形起伏度的最佳分析窗口利用该方法来确定,其数学推理过程如下:1)基于地形起伏度计算公式得到N 个(2ˑ2,3ˑ3, ,32ˑ32)递增窗口平均地形起伏度,再依次计算单位地形起伏度T i ,计算公式为:T i =t i /A i .(1)式中:T i 为第i 个分析窗口下单位地形起伏度;t i 为平均高差;A i 为分析窗口面积㊂2)将上述所得到的单位地形起伏度T 取对数(l n T )得到非线性数列X k (k =1,2, ,N ).对每个k (k ȡ2),将序列分为前后两段,即X 1,X 2,X k -1和X k ,X k +1, ,X N ,分别计算两段数据的算数平均值X k 1和X k 2,以及全部样本的算术平均值 X .3)计算统计量:S =ðNt =1(X t - X )2.(2)S k =ðk -1t =1(X t -X k 1)2+ðNt =k(X t -X k 2)2.(3)式中:S 为总的离差平方和;S k 为前后两段样本的离差平方和之和㊂4)S 和S k 的差距会随着变点的存在而逐渐增大,均值变点法的关键在于找到该变点㊂以序号k 为横坐标,S S k 为纵坐标,利用o r i g i n 软件将得到的数据制作散点图(如图2),其中顶点即为变点,259太原理工大学学报第54卷Copyright ©博看网. All Rights Reserved.是S 和S k差距最大的点㊂15129630S —S k408121620242832序号图2 S 和S k 的差值变化曲线F i g .2 S a n d S k d i f f e r e n t i a l v a l u e c h a n ge c u r v e 由图2可知,顶点为第11序号,因此该点为最佳统计窗口,窗口大小为13ˑ13,对应面积为0.0264k m 2.2.2 最佳地形因子的确定及提取最佳地形因子的选取旨在利用相关系数较低的地形因子最大化地表达研究区所包含的地形信息,因此对所选取的7种地形因子进行相关性分析,从而选取能完整反映地貌类型的最优组合㊂在进行相关性分析前,为了消除量纲的影响,先采用极差法对这7种地形因子进行归一化处理,使其值均处于0~255之间,最后得到7种地形因子的相关系数矩阵,如表1所示㊂x 'i ,j=x i ,j -x m i n x m a x -x m i nˑ255.(4)式中:x 'i ,j为处理后的数据;x i ,j 为处理前的数据;x m a x 为最大值;x m i n 为最小值㊂表1 相关系数矩阵T a b l e 1 C o r r e l a t i o n c o e f f i c i e n t m a t r i x地形因子海拔高度地形起伏度坡度地表粗糙度地表切割深度高程变异系数地表累计曲率海拔高度1.000.280.240.050.32-0.09-0.05地形起伏度0.281.000.790.150.790.88-0.01坡度0.240.791.000.110.730.80-0.02地表粗糙度0.050.150.111.000.130.140.03地表切割深度0.320.790.730.131.000.79-0.11高程变异系数-0.090.880.800.140.791.00-0.01地表累计曲率-0.05-0.01-0.020.03-0.11-0.011.00 由表1可得,地表累计曲率与其他的地形因子相关性极弱,相关系数均不超过0.11,表明地表累计曲率与其他地形因子相比,对西山矿区的地貌特征差异表达不明显,应予以剔除[25]㊂此外,高程变异系数和地形起伏度,高程变异系数和坡度这2组地形因子之间存在高度相关性(使用阈值为0.80).由于地形起伏度已被多数研究[27-29]选定为地貌划分的主要地形因子,因此在高程变异系数和地形起伏度中直接选择地形起伏度而剔除高程变异系数㊂表2列出了各个地形因子的最小值㊁最大值㊁平均值和标准差㊂其中平均值反映各个地形因子的集中趋势,标准差衡量因子的离散程度[25]㊂即标准差越大,地貌类型间的差异可能表现的越大,包含的信表2 西山矿区地形因子数据信息T a b l e 2 T o p o g r a p h i c f a c t o r d a t a i n f o r m a t i o n o f s t u d y ar e a 地形因子最小值最大值平均值标准差海拔高度0.00255.0087.0241.70地形起伏度0.00255.0056.7324.61坡度0.00255.0057.7928.63地表粗糙度0.00255.004.566.19地表切割深度0.00255.0044.2921.13高程变异系数0.00255.0038.8518.22地表累计曲率0.00255.00123.867.00息量丰富,故应该尽可能选择标准差大的因子㊂对于坡度和高程变异系数两个地形因子,坡度的标准差为28.36,大于高程变异系数的标准差18.22,说明坡度离散性更强,因此保留坡度而去除高程变异系数㊂所以最终参与西山矿区地貌分类的地形因子有地形起伏度㊁海拔高度㊁地表切割度㊁地表粗糙度和坡度㊂2.2.1 海拔高度海拔高度是地貌形态最基本的要素㊂参照周成虎等[2]提出的中国陆地1ʒ100万数字地貌三级台阶的数值分类方法,将海拔高度以1000㊁3500㊁5000m 为断点分为低海拔㊁中海拔㊁高海拔和极高海拔四类㊂由于研究区高程值最大为2179m ,因此将研究区分为低海拔和中海拔两个级别㊂2.2.2 地形起伏度地形起伏度(R f )是在特定的区域内最大高程值与最小高程值的差,可反映地面相对高差㊂依据莫申国[30]的数字格局地貌研究分类方法:平原(<30m )㊁台地(30~50m )㊁丘陵(50~200m )㊁小起伏山地(200~500m ).基于研究区地形起伏度的值域范围0~236m 并结合西山矿区实际情况,将研究359 第5期梁宏艳,等:基于A L O S D E M 的山西省西山矿区地貌形态类型提取Copyright ©博看网. All Rights Reserved.区调整划分为平原(<30m)㊁台地(30~50m)㊁丘陵(50~100m)㊁小起伏山地(100~200m)和中起伏山地(>200m)5种地貌形态㊂2.2.3坡度坡度是直观表达地表单元陡缓程度的地形因子,同时对于地貌发育和土地利用研究具有重要意义[31-33]㊂本文将坡度等级分为平坦坡到陡坡5个等级:平坦坡(0ʎ~3ʎ)㊁微平缓坡(3ʎ~7ʎ)㊁平缓坡(7ʎ~15ʎ)㊁缓坡(15ʎ~25ʎ)和陡坡(25ʎ~90ʎ). 2.2.4地表切割深度地表切割深度指某一特定单元内平均高程与最小高程的差值,是研究地表侵蚀发育状况的重要参考指标[34]㊂沈玉昌[35]以100㊁500和1000m为断点确立了中国地貌分类标准,分别为丘陵㊁浅切割山地㊁中等切割山地和深切割山地㊂根据本文得到的西山矿区地表切割度范围为0~150.29m的实际情况,且为了防止与地形起伏度分类命名重复,调整命名和分级为微切割山地(0~30m)㊁浅切割山地(30~100m)和中等切割山地(100~500m)3个等级㊂2.2.5地表粗糙度地表粗糙度指在一个特定的区域内地球表面积与其投影面积之比,是反映地表形态的一个宏观指标㊂2.3 G I S空间分析典型地形因子分布分析利用A r c G I S软件S p a-t i a l A n a l y s t模块中的以表格显示分区统计(Z o n a l S t a t i s t i c s A s T a b l e)工具,对研究区内不同坡度等级下地表粗糙度和地表切割深度的情况进行统计汇总,从而进一步分析研究区内的这几种典型地形因子的空间分布状况㊂西山矿区地貌类型分类最终结果主要以定性和半定量的方法来完成,具体操作为利用A r c G I S软件S p a t i a l A n a l y s t模块中的R a s t e r C a l c u l a t o r工具,将最佳因子海拔高度㊁地形起伏度㊁坡度和地表切割深度进行叠置分析,得到分类结果,并结合遥感影像,对由最佳地形因子获得的地貌类型图进行修正,应用邻近原则对破碎图斑(面积小于0.3k m2)进行合并,且对不合理地貌的分类及界线进行微调和圆滑处理修正,为了保证地貌界线的准确性,在处理时,把比例尺放大到1ʒ5万尺度上㊂3结果分析3.1典型地形因子分布地表粗糙度是衡量地表侵蚀程度的重要量化指标,地表切割深度直观反映了地表被侵蚀切割的情况并对这一地学现象进行量化,而由地表粗糙度计算公式可得,地表粗糙度与坡度密切相关㊂因此,在进行典型地形因子分布研究时,对坡度进行分级统计且统计不同坡度等级下的地表粗糙度和地表切割深度(表3),以期为西山矿区后期水土保持及地表侵蚀发育研究作参考㊂表3不同坡度等级下的地表粗糙度和地表切割深度T a b l e3 S u r f a c e r o u g h n e s s a n d i n c i s i o n u n d e rd i f fe r e n t s l o p e g r a d e s坡度/(ʎ)百分比/%地表粗糙度均值地表切割深度均值/m 0~35.021.016.623~79.121.0212.227~1526.331.0321.6415~2542.291.0329.2425~9017.241.0339.24由表3统计可得,研究区内坡度类型主要集中在0ʎ~25ʎ范围内,占研究区总面积的82.76%.其中15ʎ以下区域面积占到了区域总面积的40.47%,且地表粗糙度在1.03以下,地表切割度在21.64m 以下,分布在研究区内的西南部边缘地带,太原盆地西部,各个山脉的山谷处等大部分区域;15ʎ~25ʎ的缓坡,占研究区总面积的42.29%,其地表粗糙度为1.03,地表切割度为29.24m,且分布在研究区西北部的边缘地带;25ʎ~90ʎ的陡坡,占研究区总面积的17.24%,地形起伏明显,地表粗糙度较其他范围没有明显变化,地表切割度达到了最大值39.24m,主要分布在各大山脉的山脊处,山间褶皱地带以及被流域切割严重的区域[37]㊂3.2分类结果西山矿区地貌形态类型为30种,图斑数目为336个,对其空间分布状况(如图3(a)所示)分析统计得到:1)西山矿区浅切割陡小起伏中山和浅切割陡中起伏中山的面积占比较大,分布广泛,分布在研究区西南部及中东部大部分区域,分别占西山矿区总面积的21.23%㊁12.72%;2)低海拔微切割微平缓台地,浅切割陡小起伏低山和微切割微平缓中起伏中山,分别占总面积的0.27%㊁0.37%㊁0.30%,零星分布在西山矿区的边缘地带;3)低海拔微切割平坦平原的面积占研究区总面积比也相对较大,为3.16%,该地貌类型主要分布在研究区位于太原盆地的区域;4)低海拔地区主要分布在研究区东南部的边缘地带,面积占比为23.62%,中海拔地区为研究区主要地貌,分布在研究区大部分地带,占总面积的76.38%.整体而言,西山矿区整体地势特点为西459太原理工大学学报第54卷Copyright©博看网. All Rights Reserved.低海拔微切割平坦平原微切割平坦小起伏低山微切割平坦中起伏低山低海拔微切割微平缓平原低海拔微切割微平缓台地低海拔微切割微平缓丘陵微切割微平缓小起伏低山微切割微平缓中起伏低山低海拔微切割平缓平原微切割平缓小起伏低山低海拔浅切割陡平原浅切割陡小起伏低山浅切割陡中起伏低山中海拔微切割平坦平原微切割平坦小起伏中山中海拔微切割微平缓平原中海拔微切割微平缓丘陵微切割微平缓小起伏中山微切割微平缓中起伏中山中海拔微切割平缓平原中海拔微切割平缓丘陵微切割平缓小起伏中山微切割平缓中起伏中山中海拔浅切割缓平原浅切割缓小起伏中山浅切割缓中起伏中山中海拔浅切割陡平原中海拔浅切割陡丘陵浅切割陡小起伏中山浅切割陡中起伏中山N20 km100（a ）本文划分地貌倾斜的中海拔平原倾斜的低海拔台地倾斜的低海拔平原平缓的中海拔丘陵平缓的小起伏中山缓的中海拔丘陵缓的中起伏中山缓的小起伏中山陡的中起伏中山陡的小起伏中山N20 km100（b ）参考地貌图3 西山矿区地貌形态类型F i g .3G e o m o r p h o l o g i c t y p e d i s t r i b u t i o n m a p o f s t u d y ar e a 南高,东北低,中部为山地,边缘为平原㊂3.3 结果检验统计各地貌类型图斑数,将所得到的统计数据与中国科学院地理研究所1ʒ100万地貌类型图的统计数据(参考地貌)进行对比,如表4所示㊂由表4统计结合图3分类结果可得,本文划分地貌类型30类,与原1ʒ100万的地貌为9类相比,本文划分较参考划分类型增加了21类,划分的地貌类型更为丰富㊂且本文划分地貌类型图斑数为336个,参考地貌类型图斑数目为40个,本文划分图斑数目相较于原1ʒ100万地貌类型增加了296个,图斑数目明显提高,划分的结果更加细致㊂曾超[36]在文章中对我国1ʒ100万地貌分类结果的不足已有描述,实施过程中,虽采用人工勾绘和地貌分类相结合的方法,相对而言具有较高准确性,但分类过程中仍存在诸多地貌实体单元被分割的现象,且由于认识的主观性,很难达到统一,从而导致界线划定不够准确,如图4界线对比中P 1和P 2区域,在1ʒ100万地貌分类结果中,完整的山体被分割成不同地貌单元,本文划分则保证了完整山体不被分割;在位于大川河的P 3区域则可以表明,本文划分地貌类型界线较参考地貌界线来说更加细致,沟谷河道界线更加符合实际河道界线㊂通过图斑数和划分界线两方面的对比,说明了本文划分地貌类型取得了较好的分类结果,且较原先人工目视解译1ʒ100万地貌类型来说更加合理㊂此外,较之前研究采用了更多的地形因子(海拔高度㊁地形起伏度㊁坡度和地表切割深度),对地貌完整信息的概括能力更强㊂表4 研究区与参考地貌图斑数目对比T a b l e 4 C o m p a r i s o n o f t h e s po t n u m b e r b e t w e e n t h e s t u d y a r e a a n d r e f e r e n c e g e o m o r p h i c m a p参考本文划分地貌类型图斑数地貌类型图斑数低海拔倾斜平原5低海拔微切割平坦平原36低海拔微切割微平缓平原32低海拔微切割平缓平原1低海拔浅切割陡平原1低海拔倾斜台地2低海拔微切割微平缓台地1中海拔倾斜平原2中海拔微切割平坦平原1中海拔微切割微平缓平原6中海拔微切割平缓平原4中海拔浅切割缓平原5中海拔浅切割陡平原4中海拔平缓丘陵2中海拔微切割微平缓丘陵1中海拔缓丘陵2中海拔微切割平缓丘陵1中海拔浅切割陡丘陵1平缓的小起伏中山1微切割平坦小起伏中山1微切割微平缓小起伏中山7微切割平缓小起伏中山21缓的小起伏中山17浅切割缓小起伏中山28陡的小起伏中山1浅切割陡小起伏中山45缓的中起伏中山3微切割微平缓中起伏中山1微切割平缓中起伏中山18浅切割缓中起伏中山32陡的中起伏中山5浅切割陡中起伏中山40微切割平坦小起伏低山19微切割平坦中起伏低山1低海拔微切割微平缓丘陵2微切割微平缓小起伏低山15微切割微平缓中起伏低山9微切割平缓小起伏低山1浅切割陡小起伏低山2浅切割陡中起伏低山1559 第5期梁宏艳,等:基于A L O S D E M 的山西省西山矿区地貌形态类型提取Copyright ©博看网. All Rights Reserved.本文划分地貌原1∶100万地貌8 km40P3P1P2图4 研究区与参考地貌海拔和起伏度界线对比F i g .4 C o m pa r i s o n o f e l e v a t i o n a n d r e l i e fb o u n d a r i e s b e t w e e n t h e s t u d y ar e a a n d t h e r e f e r e n c e l a n d f o r m 本文首先运用了更多地形因子来对研究区域地貌形态进行划分,且应用宏观和微观地形因子相结合,划分结果更加细致,对于小区域的西山矿区地貌单元的各种信息能够更加科学全面地体现出来,并能一目了然地了解研究区域基本地貌情况;其次,在地貌图制作中,本文采用的相对自动化提取的地貌分类方法相对于人工目视解译方法来说工作效率得到了提升㊂4 结论本文以12.5m 分辨率的A L O S D E M 数据为基础,结合实际情况,完成了对西山矿区地貌形态的划分,并分析了研究区地形特征,得到以下结论:1)西山矿区最佳地形因子是海拔高度㊁地形起伏度㊁坡度㊁地表切割深度和地表粗糙度,地形起伏度的最佳统计单元为13ˑ13(0.0264k m 2).2)将坡度分为不同等级,并且统计不同坡度等级范围内的地表粗糙度和地表切割深度情况,得到了这些典型地形因子在西山矿区的空间分布特征㊂3)将西山矿区划分为低海拔微切割平坦平原㊁浅切割陡小起伏中山㊁浅切割陡中起伏中山等30种地貌形态,其中,浅切割陡小起伏中山为主要地貌,占到总面积的21.23%.4)以中国科学院地理研究所1ʒ100万地貌类型图作为参考数据,对本文分类结果进行验证,结果表明,本文分类结果较参考分类,图斑数目增加了296个,地貌类型增加了21类,通过界线对比得到分类界线更加符合实际地貌,更为细微地描述了研究区的地形细节㊂此分类结果对于小区域的西山矿区来说较为合理㊂在本文数据的基础上,结合其他数据,可以为西山矿区水土流失,地质灾害防治以及生态环境建设等方面的研究做出贡献㊂参考文献:[1] 赵尚民,程维明.山西省多级行政单元的数字地貌分布特征[J ].太原理工大学学报,2014,45(4):542-547.Z HA O S M ,C H E N G W M.A n a l y s i s o n t h e d i g i t a l g e o m o r p h o l o gi c c h a r a c t e r i s t i c s o f a d m i n i s t r a t i v e u n i t s a t m u l t i -l e v e l s i n S h a n x i p r o v i n c e [J ].J o u r n a l o f T a i y u a n U n i v e r s i t y o f T e c h n o l o g y,2014,45(4):542-547.[2] 周成虎,程维明,钱金凯.数字地貌遥感解析与制图[M ].北京:科学出版社,2009.[3] 周廷儒,施雅风,陈述彭.中国地形区划草案[M ].北京:科学出版社,1956.[4] 沈玉昌,苏时雨,尹泽生.中国地貌分类㊁区划与制图研究工作的回顾与展望[J ].地理科学,1982,2(2):97-105.S H E N Y C ,S U S Y ,Y I N Z S .R e t r o s p e c t a n d p r o s p e c t o f t h e r e s e a r c h w o r k o n t h e c l a s s i f i c a t i o n ,r e g i o n a l i z a t i o n a n d m a p p i n go f t h e g e o m o r p h o l o g y o f C h i n a [J ].S c i e n t i a G e o g r a ph i c a S i n i c a ,1982,2(2):97-105.[5] 苏时雨,李钜章.地貌制图[M ].北京:测绘出版社,1999.[6] B U R R O U G H P A ,V A N G A A N S P F M ,MA C M I L L A N R A.H i g h -r e s o l u t i o n l a n d f o r m c l a s s i f i c a t i o n u s i n g f u z z y k-m e a n s [J ].F u z z y S e t s a n d S ys t e m s ,2000,113(1):37-52.[7] MA C M I L L A N R A ,J O N E S R K ,M C N A B B D H.D e f i n i n g a h i e r a r c h y o f s p a t i a l e n t i t i e s f o r e n v i r o n m e n t a l a n a l ys i s a n d m o d -e l i n g u s i n g d i g i t a l e l e v a t i o n m o d e l s (D E M s )[J ].C o m p u t e r s ,E n v i r o n m e n t a n d U r b a n S ys t e m s ,2004,28(3):175-200.[8] 杨颖楠,李子夫,刘梦云,等.基于不同分辨率D E M 的永寿县地形信息差异分析[J ].水土保持研究,2018,25(6):131-136.Y A N G Y N ,L I Z F ,L I U M Y ,e t a l .A n a l y s i s o f t o p o g r a p h i c d i f f e r e n c e s o f Y o n g s h o u c o u n t y ba s e d o n d i f f e r e n t r e s o l u t i o n s o f D E M [J ].R e s e a r c h o f S o i l a n d W a t e r C o n s e r v a t i o n ,2018,25(6):131-136.[9] 胡最,聂阳意.基于D E M 的湖南省地貌形态特征分类[J ].地理与地理信息科学,2015,31(6):67-71,129.HU Z ,N I E Y Y.D E M -b a s e d l a n d f o r m t a x o n o m i c f e a t u r e s o f H u n a n p r o v i n c e [J ].G e o g r a p h y an d G e o -I n f o r m a t i o n S c i e n c e ,2015,31(6):67-71,129.[10] 常直杨,王建,白世彪,等.基于D E M 数据的地貌分类研究:以西秦岭为例[J ].中国水土保持,2014(4):56-59.659太原理工大学学报第54卷Copyright ©博看网. 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a s s i f i c a t i o n o f t o p o g r a p h y f r o m S R TM d a t a[J].G e o m o r p h o l o g y,2012,141:21-33.[14]汪禹芹,李艳,刘爱利.基于面向对象思想的中国地貌形态类型划分[J].遥感信息,2012(1):13-18.WA N G Y Q,L I Y,L I U A L.O b j e c t-o r i e n t e d m e t h o d b a s e d r e s e a r c h o n c l a s s i f i c a t i o n o f r e l i e f f o r m i n C h i n a[J].R e m o t e S e n s i n g I n f o r m a t i o n,2012(1):13-18.[15]常直杨,王建,白世彪,等.基于S R T M D E M数据的三峡库区地貌类型自动划分[J].长江流域资源与环境,2014,23(12):1665-1670.C H A N G Z Y,WA N G J,B A I S B,e t a l.A u t o-c l a s s i f i c a t i o n o f l a n d f o r m i n t h r e e g o r g e s r e g i o n b a s e d o n S R T MDE M[J].R e-s o u r c e s a n d E n v i r o n m e n t i n t h e Y a n g t z e B a s i n,2014,23(12):1665-1670.[16]范建容,张子瑜,李立华.四川省山地类型界定与山区类型划分[J].地理研究,2015,34(1):65-73.F A N J R,Z HA NG Z Y,L I L H.M o u n t a i n d e m a r c a t i o n a n d m o u n t a i n o u s a r e a d i v i s i o n s o f S i c h u a n p r o v i n c e[J].G e o g r a p h i c a lR e s e a r c h,2015,34(1):65-73.[17]刘育成,赵廷宁.基于变点分析法提取废弃采石场地形起伏度的方法[J].水土保持研究,2016,23(3):269-273.L I U Y C,Z H A O T N.M e t h o d f o r e x t r a c t i o n o f r e l i e f a m p l i t u d e o f a b a n d o n e d q u a r r y b a s e d o n c h a n g e p o i n t m e t h o d[J].R e-s e a r c h o f S o i l a n d W a t e r C o n s e r v a t i o n,2016,23(3):269-273.[18] Z H A N G B,F A N Z M,D U Z P,e t a l.A g e o m o r p h o l o g i c a l r e g i o n a l i z a t i o n u s i n g t h e u p s c a l e d D E M:t h e B e i j i n g-T i a n j i n-H e b e iA r e a,C h i n a C a s e S t u d y[J].S c i e n t i f i c R e p o r t s,2020,10(1):1366-1345.[19]陈学兄,张小军,常庆瑞.陕西省地形起伏度最佳计算单元研究[J].水土保持通报,2016,36(3):265-270,370.C H E N X X,Z HA N G X J,C H A N G Q R.A s t u d y o n o p t i m a l s t a t i s t i c a l u n i t f o r r e l i e f a m p l i t u d e o f l a n d s u r f a c e i n S h a a n x ip r o v i n c e[J].B u l l e t i n o f S o i l a n d W a t e r C o n s e r v a t i o n,2016,36(3):265-270,370.[20]韩海辉,高婷,易欢,等.基于变点分析法提取地势起伏度:以青藏高原为例[J].地理科学,2012,32(1):101-104.H A N H H,G A O T,Y I H,e t a l.E x t r a c t i o n o f r e l i e f a m p l i t u d e b a s e d o n c h a n g e p o i n t m e t h o d:a c a s e s t u d y o n t h e T i b e t a nP l a t e a u[J].S c i e n t i a G e o g r a p h i c a S i n i c a,2012,32(1):101-104.[21]封志明,李文君,李鹏,等.青藏高原地形起伏度及其地理意义[J].地理学报,2020,75(7):1359-1372.F E NG Z M,L I W J,L I P,e t a l.R e l i e f d e g r e e o f l a n d s u r f a c e a n d i t s g e o g r a p h i c a l m e a n i n g s i n t h e Q i n g h a i-T i b e t P l a t e a u,C h i-n a[J].A c t a G e o g r a p h i c a S i n i c a,2020,75(7):1359-1372.[22]王玲,吕新.基于D E M的新疆地势起伏度分析[J].测绘科学,2009,34(1):113-116.WA N G L,L Y U X.A n a l y s i s o f t h e r e l i e f a m p l i t u d e i n X i n j i a n g b a s e d o n d i g i t a l e l e v a t i o n m o d e l[J].S c i e n c e o f S u r v e y i n g a n d M a p p i n g,2009,34(1):113-116.[23]仲伟敬,邢立新,潘军,等.基于D E M数据的地貌类型快速划分系统研究[J].吉林大学学报(信息科学版),2018,36(5):388-396.Z H O N G W J,X I N G L X,P A N J,e t a l.S t u d y o n f a s t p a r t i t i o n i n g s y s t e m o f g e o m o r p h i c t y p e s b a s e d o n D E M d a t a[J].J o u r-n a l o f J i l i n U n i v e r s i t y(I n f o r m a t i o n S c i e n c e E d i t i o n),2018,36(5):388-396.[24]陈学兄,常庆瑞,毕如田,等.地形起伏度最佳统计单元算法的比较研究[J].水土保持研究,2018,25(1):52-56.C H E N X X,C HA N G Q R,B I R T,e t a l.C o m p a r i s o n s t u d y o n t h e b e s t s t a t i s t i c a l u n i t a l g o r i t h m s o f r e l i e f a m p l i t u d e[J].R e-s e a r c h o f S o i l a n d W a t e r C o n s e r v a t i o n,2018,25(1):52-56.[25]姜雨璇,查小春.基于D E M的巴山地区地貌区划研究[J].水土保持研究,2022,29(1):127-132,139.J I A N G Y X,Z H A X C.S t u d y o n g e o m o r p h o l o g i c a l r e g i o n a l i z a t i o n o f B a s h a n b a s e d o n D E M[J].R e s e a r c h o f S o i l a n d W a t e rC o n s e r v a t i o n,2022,29(1):127-132,139.[26]王丽娜,丁文广,许丹阳.基于D E 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All Rights Reserved.。

y and

Keywords: Torus, routing, placement, bisection, interconnection network, edge separator, congestion.
1 Introduction
Meshes and torus based interconnection networks have been utilized extensively in the design of parallel computers in recent years 5]. This is mainly due to the fact that these families of networks have topologies which re ect the communication pattern of a wide
1
variety of natural problems, and at the same time they are scalable, and highly suitable for hardware implementation. An important factor determining the e ciency of a parallel algorithm on a network is the e ciency of communication itself among processors. The network should be able to handle \large" number of messages without exhibiting degradation in performance. Throughput, the maximum amount of tra c which can be handled by the network, is an important measure of network performance 3]. The throughput of an interconnection network is in turn bounded by its bisection width, the minimum number of edges that must be removed in order to split the network into two parts each with about equal number of processors 8]. Here, following Blaum, Bruck, Pifarre, and Sanz 3, 4], we consider the behavior of torus networks with bidirectional links under heavy communication load. We assume that the communication latency is kept minimum by routing the messages through only shortest (minimal length) paths. In particular, we are interested in the scenario where every processor in the network is sending a message to every other processor (also known as complete exchange or all-to-all personalized communication). This type of communication pattern is central to numerous parallel algorithms such as matrix transposition, fast Fourier transform, distributed table-lookup, etc. 6], and central to e cient implementation of high-level computing models such as the PRAM and Bulk-Synchronous Parallel (BSP). In Valiant's BSP-model for parallel computation 14] for example, routing of h-relations, in which every processor in the network is the source and destination of at most h packets, forms the main communication primitive. Complete-exchange scenario that we investigate in this paper has been studied and shown to be useful for e cient routing of both random and arbitrary h-relations 7, 12, 13]. The network of d-dimensional k-torus is modeled as a directed graph where each node represents either a router or a processor-router pair, depending on whether or not a processor is attached at this node, and each edge represents a communication link between two adjacent nodes. Hence, every node in the network is capable of message routing, i.e. directly receiving from and sending to its neighboring nodes. A fully-populated d-dimensional k-torus where each node has a processor attached, contains kd processors. Its bisection width is 4kd? (k even), which gives kd=2 processors on each component of the bisection. Under the complete-exchange scenario, the number of messages passing through the bisection in both directions is 2(kd =2)(kd=2). Dividing by the bisection bandwidth, we nd that there must exist an edge in the bisection with a load kd =8. This means that unlike multistage networks, the maximum load on a link is not linear in the number of processors injecting messages into the network. To alleviate this problem, Blaum et al. 3, 4] have proposed partially-populated tori . In this model, the underlying network is torodial, but the nodes do not all inject messages into the network. We think of the processors as attached to a (relatively small) subset of nodes (called a placement), while the other nodes are left as routing nodes. This is similar to the case of a

Panasonic KV-S5078Y 文档扫描仪参数说明书

Document ScannerKV-S5078YUpgraded Basic Paper Feed Performance• Paper Feeding- A new long-life roller provides low-maintenance operation- A new paper-dust-resistant design reduces errors and cleaning cycles • Noise level- Low-noise design for ofﬁce use (Less than 55 dB)Superior Image Quality• Enhanced image quality with a 3-line CIS• Outstanding images precisely extract content for backend systemsGigabit Ethernet Connectivity• Shareable, cost-saving design with Network Connectivity *1• Easy device management over a network (SCMS *2, Conﬁguration web)Powerful Yet CalmDelivers superior image quality and dependable feeding*1 Speed and features are partially restricted with network connection.*2 Site Central Manager SuiteDocument Scanner: https:///cns/office/products/scanner/DISTRIBUTED BY :Printed in Japan MG-SCNL038EN 2002NSP/ZZZ-M1Trademarks and registered trademarks- ENERGY STAR and the ENERGY STAR mark are registered U.S.marks.- ISIS is a registered trademark or trademark of Open Text Corporation.- Windows and Windows Server are either registered trademarks or trademarks of Microsoft Corporation in the United States and/or other countries.- Linux is a registered trademark or a trademark of Linus Torvalds in the United States and other countries.- Red Hat and Red Hat Enterprise Linux are registered trademarks or trademarks of Red Hat, Inc. in the United States and other countries.- Ubuntu is a registered trademark or a trademark of Canonical Ltd. in the United States and other countries.- All other brand or product names are the property of their respective holders.• All photographs in this brochure are simulated. • Weights and dimensions are approximate.• Speciﬁcations are subject to change without notice.• These products may be subject to export control regulations.KV-S5078Y SpeciﬁcationsDimensionsKV-S5078Y*1 When scanning a document larger than A5 size at resolutions over 600 dpi, the scanning may fail due to insufﬁcient memory.*2 50 – 99 dpi and 1200 dpi can be used only when scanning with Image Capture Plus, TWAIN, or ISIS.*3 The scanning speed is the maximum speed of the scanner hardware. It does not include software processing time, data transfer time, etc. The scanning speedmeasurement is based on Panasonic's measuring method. In case of using this unit with a LAN connection, the scanning speed may be slower due to network trafﬁc. *4 Using "Long Paper", you can scan a long document to a series of split scanned images. *5 Scheduled for Fall 2020.*6 To assure continued emission limit compliance, use only shielded LAN cable. The cable should be a CAT 5 (Category 5) or higher for 10Base-T / 100Base-TX, or CAT 5e (Enhanced Category 5) or higher for 1000Base-T. *7 The power requirement differs depending on the country/area.*8 If connected to a network device (hub, router , etc.) that supports IEEE802.3az.*9 Available only when connecting via USB.*10 Required to installing OCREngine for Image Capture Plus on 2 or more PCs. (For 1 license) *11 Required to installing OCREngine for Image Capture Plus on 2 or more PCs. (For 10 licenses) *12 To install the scan server , you need this option.*13 Extend the maximum number of ﬁelds for zone OCR in Image Capture Plus from 3 to 10. (For 1 license)*14 Extend the maximum number of ﬁelds for zone OCR in Image Capture Plus from 3 to 10. (For 10 licenses)344 mm (13.5 in.)444 mm (17.5 in.)468 mm (18.5 in.)This product is designed to reduce hazardous chemical substances in accordance with the RoHS directive.As an ENERGY STAR partner ,Panasonic has determined that this product meets the ENERGY STAR guidelines for energy efﬁciency.。

matlab之“audioread”函数帮助文档翻译

matlab之“audioread”函数帮助⽂档翻译课程设计（1）原⽂audioreadRead audio fileSyntax[y,Fs] = audioread(filename)[y,Fs] = audioread(filename,samples)[y,Fs] = audioread(___,dataType)Description[,] = audioread() reads data from the file named filename, and returns sampled data, y, and a sample rate for that data, Fs.[,] = audioread(,) reads the selected range of audio samples in the file, where samples is a vector of the form [start,finish].[,] = audioread(___,) returns sampled data in the data range corresponding to the dataType of 'native' or 'double', and can include any of the input arguments in previous syntaxes.ExamplesCreate a WAVE file from the example file handel.mat, and read the file back into MATLAB®.Create a WAVE (.wav) file in the current folder.load handel.matfilename = 'handel.wav';audiowrite(filename,y,Fs);clear y FsRead the data back into MATLAB using audioread.[y,Fs] = audioread('handel.wav');Play the audio.sound(y,Fs);Create a FLAC file from the example file handel.mat, and then read only the first 2 seconds.Create a FLAC (.flac) file in the current folder.load handel.matfilename = 'handel.flac';audiowrite(filename,y,Fs);Read only the first 2 seconds.samples = [1,2*Fs];clear y Fs[y,Fs] = audioread(filename,samples);Play the samples.sound(y,Fs);Create a FLAC file and read the first 2 seconds according to the previous Example. Then, view the data type of the sampled data y.whos yName Size Bytes Class Attributesy 16384x1 131072 doubleThe data type of y is double.Request audio data in the native format of the file, and then view the data type of the sampled data y.[y,Fs] = audioread(filename,'native');whos yName Size Bytes Class Attributesy 16384x1 32768 int16The data type of y is now int16.Input ArgumentsstringName of file to read, specified as a string that includes the file extension. If a path is specified, it can be absolute, relative or partial.Example: 'myFile.mp3'Example: '../myFile.mp3'Example: 'C:\temp\myFile.mp3'audioread supports the following file formats.Platform Support File FormatAll platforms WAVE (.wav)OGG (.ogg)FLAC (.flac)AU (.au)AIFF (.aiff, .aif)AIFC (.aifc)Windows® 7 (or later), Macintosh, and Linux®MP3 (.mp3)MPEG-4 AAC (.m4a, .mp4)On Windows platforms prior to Windows 7, audioread does not read WAVE files with MP3 encoded data.On Windows 7 (or later) platforms, audioread might also read any files supported by Windows Media® Foundation.On Linux platforms, audioread might also read any files supported by GStreamer.audioread can extract audio from MPEG-4 (.mp4, .m4v) video files on Windows 7 or later, Macintosh, and Linux, and from Windows Media Video (.wmv) and AVI (.avi) files on Windows 7 (or later) and Linux platforms.[1,inf] (default) | two-element vector of positive scalar integersAudio samples to read, specified as a two-element vector of the form [start,finish], where start and finish are the first and last samples to read, and are positive scalar integers.start must be less than or equal to finish.start and finish must be less than the number of audio samples in the file,You can use inf to indicate the last sample in the file.Note: When reading a portion of some MP3 files on Windows 7 platforms, audioread might read a shifted range of samples. This is due to a limitation in the underlying Windows Media Foundation framework.When reading a portion of MP3 and M4A files on Linux platforms, audioread might read a shifted range of samples. This is due to a limitation in the underlying GStreamer framework.Example: [1,100]Data Types: double'double' (default) | 'native'Data format of audio data,y, specified as one of the following strings:'double'Double-precision normalized samples.'native'Samples in the native format found in thefile.For compressed audio formats, such as MP3 and MPEG-4 AAC that do not store data in integer form, 'native' defaults to 'single'.Output ArgumentsmatrixAudio data in the file, returned as an m-by-n matrix, where m is the number of audio samples read and n is the number of audio channels in the file.If you do not specify dataType, or dataType is 'double', then y is of type double, and matrix elements are normalized valuesbetween −1.0 and 1.0.If dataType is 'native', then y can be one of several MATLAB data types, depending on the file format andthe BitsPerSample value of the input file. Call audioinfo to determine the BitsPerSample value of the file.File Format BitsPerSample Data Type of y Data Range of y WAVE (.wav)8uint80 ≤ y ≤ 25516int16-32768 ≤ y ≤ +3276724int32-2^32 ≤ y ≤ 2^32–132int32-2^32 ≤ y ≤ 2^32–132single-1.0 ≤ y ≤ +1.064double-1.0 ≤ y ≤ +1.0 FLAC (.flac)8uint80 ≤ y ≤ 25516int16-32768 ≤ y ≤ +3276724int32-2^32 ≤ y ≤ 2^32–1N/A single-1.0 ≤ y ≤ +1.0 MP3 (.mp3), MPEG-4 AAC(.m4a, .mp4), OGG (.ogg), andcertain compressed WAVEfilesNote: Where y is single or double and the BitsPerSample is 32 or 64, values in y might exceed −1.0 or +1.0.positive scalarSample rate, in hertz, of audio data y, returned as a positive scalar.LimitationsFor MP3, MPEG-4 AAC, and AVI audio files on Windows 7 or later and Linux platforms, audioread might read fewersamples than expected. On Windows 7 platforms, this is due to a limitation in the underlying Media Foundation framework.On Linux platforms, this is due to a limitation in the underlying GStreamer framework. If you require sample-accuratereading, work with WAV or FLAC files.On Linux platforms, audioread reads MPEG-4 AAC files that contain single-channel data as stereo data.翻译调⽤结构&描述 [y, Fs] =audioread(filename) 从以“filename”为⽂件名的⽂件中读取数据，并返回抽样数据y和此数据的抽样率Fs 。

sp包的文档：空间数据的类和方法说明书

Classes and Methods for Spatial Data:the sp PackageEdzer Pebesma*Roger S.BivandFeb2005Contents1Introduction2 2Spatial data classes2 3Manipulating spatial objects33.1Standard methods (3)3.2Spatial methods (4)4Spatial points44.1Points without attributes (4)4.2Points with attributes (7)5Grids115.1Creating grids from topology (11)5.2Creating grids from points (13)5.3Gridded data with attributes (14)5.4Are grids stored as points or as matrix/array? (15)5.5Row and column selection of a region (16)6Lines176.1Building line objects from scratch (17)6.2Building line objects with attributes (18)7Polygons197.1Building from scratch (19)7.2Polygons with attributes (20)*Institute for Geoinformatics,University of Muenster,Heisenbergstraÿe2,48149Münster, Germany.*****************************Economic Geography Section,Department of Economics,Norwegian School of Economics and Business Administration,Breiviksveien40,N-5045Bergen,Norway; *******************18Importing and exporting data211IntroductionThe sp package provides classes and methods for dealing with spatial data in R1.The spatial data structures implemented include points,lines,polygons and grids;each of them with or without attribute data.We have chosen to use S4classes and methods style(Chambers,1998)to allow validation of ob-jects created.Although we mainly aim at using spatial data in the geographical (two-dimensional)domain,the data structures that have a straightforward im-plementation in higher dimensions(points,grids)do allow this.From the package home page on CRAN,https:/// package=sp,links to a graph gallery with R code,and the development source tree are found.This vignette describes the classes,methods and functions provided by sp. Instead of manipulating the class slots(components)directly2,we provide meth-ods and functions to create or modify the classes from elementary types such as matrices,data.frame s or lists and convert them back to any of these types. Also,coercion(type casting)from one class to the other is provided,where relevant.Package sp is loaded by>library(sp)2Spatial data classesThe spatial data classes implemented are points,grids,lines,rings and poly-gons.Package sp provides classes for the spatial-only information(the topol-ogy),e.g.SpatialPoints,and extensions for the case where attribute informa-tion stored in a data.frame is available for each spatial entity(e.g.for points, the SpatialPointsDataFrame).The available data classes are: 1The motivation to write this package was born on a pre-conference spatial data workshop during DSC2003.At that time,the advantage of having multiple R packages for spatial statistics seemed to be hindered by a lack of a uniform interface for handling spatial data. Each package had its own conventions on how spatial data were stored and returned.With this package,and packages supporting the classes provided here,we hope that R with its extension packages becomes more coherent for analyzing di erent types of spatial data.2which is possible,but not recommended because validity of resulting objects is no longer veri ed2data type class attributes containspoints SpatialPoints No Spatialpoints SpatialPointsDataFrame data.frame SpatialPoints multipoints SpatialMultiPoints No Spatialmultipoints SpatialMultiPointsDataFrame data.frame SpatialMultiPoints pixels SpatialPixels No SpatialPointspixels SpatialPixelsDataFrame data.frame SpatialPixelsSpatialPointsDataFrame full grid SpatialGrid No SpatialPixelsfull grid SpatialGridDataFrame data.frame SpatialGridline Line Nolines Lines No Line listlines SpatialLines No Spatial,Lines list lines SpatialLinesDataFrame data.frame SpatialLines polygons Polygon No Linepolygons Polygons No Polygon listpolygons SpatialPolygons No Spatial,Polygons list polygons SpatialPolygonsDataFrame data.frame SpatialPolygonsThe class Spatial only holds metadata common to all derived classes(bound-ing box,coordinate reference system),and is of convenient for de ning methodsthat are common to all derived classes.In the following sections we will showhow we can create objects of these classes from scratch or from other objects,and which methods and functions are available to them.3Manipulating spatial objectsAlthough entries in spatial objects are in principle accessible through their slotname,e.g.x@coords contains the coordinates of an object of class or extending SpatialPoints,we strongly encourage users to access the data by using func-tions and methods,in this case coordinates(x)to retrieve the coordinates.3.1Standard methodsSelecting,retrieving or replacing certain attributes in spatial objects with at-tributes is done using standard methods[select"rows"(features)and/or columns in the data attribute table;e.g.meuse[1:2,"zinc"]returns a SpatialPointsDataFrame with the rsttwo points and an attribute table with only variable"zinc".[[extracts a column from the data attribute table[[<-assign or replace a column in the data attribute table.3Other methods available are:plot,summary,print,dim and names(operateon the data.frame part),as.data.frame,as.matrix and image(for gridded data),lines(for line data),points(for point data),subset(points and grids),stack(point and grid data.frames),over for spatial joins,spplot,and length (number of features).3.2Spatial methodsA number of spatial methods are available for the classes in sp:dimensions(x)returns number of spatial dimensionsy=spTransform(x,CRS("+proj=longlat+datum=WGS84"))convert ortransform from one coordinate reference system(geographic projection)to another(requires package rgdal to be installed)bbox(x)returns a matrix with the coordinates bounding box;the dimen-sions form rows,min/max form the columnscoordinates(x)returns a matrix with the spatial coordinatesgridded(x)tells whether x derives from SpatialPixels,or when used inassignment,coerces a SpatialPoints object into a SpatialPixels object.spplot(x)plots attributes,possibly in combination with other types ofdata(points,lines,grids,polygons),and possibly in as a conditioning plotfor multiple attributesover(x,y)retrieve index or attributes of y corresponding(intersecting)with spatial locations of x.spsample(x)samples point coordinates in the continuous space of SpatialPolygons,a gridded area,or along a SpatialLines.Subsetting and sample can beused to randomly subsample full spatial entities.geometry(x)strips the data.frame,and returns the geometry-only object4Spatial points4.1Points without attributesWe can generate a set of10points on the unit square[0,1]×[0,1]by>xc=round(runif(10),2)>yc=round(runif(10),2)>xy=cbind(xc,yc)>xy4xc yc[1,]0.670.30[2,]0.960.62[3,]0.920.91[4,]0.770.85[5,]0.720.46[6,]0.740.39[7,]0.630.64[8,]0.190.72[9,]0.700.20[10,]0.370.28this10×2matrix can be converted into a SpatialPoints object by>xy.sp=SpatialPoints(xy)>xy.spclass:SpatialPointsfeatures:10extent:0.19,0.96,0.2,0.91(xmin,xmax,ymin,ymax) crs:NA>plot(xy.sp,pch=2)The plot is shown in gure1.We can retrieve the coordinates from xy.sp by>=coordinates(xy.sp)>class()[1]"matrix""array">dim()[1]102and other methods retrieve the bounding box,the dimensions,select points(not dimensions or columns),coerce to a data.frame,or print a summary:>bbox(xy.sp)min maxxc0.190.96yc0.200.91>dimensions(xy.sp)[1]25Figure1:plot of SpatialPoints object;aspect ratio of x and y axis units is16>xy.sp[1:2]class:SpatialPointsfeatures:2extent:0.67,0.96,0.3,0.62(xmin,xmax,ymin,ymax) crs:NA>xy.df=as.data.frame(xy.sp)>class(xy.df)[1]"data.frame">dim(xy.df)[1]102>summary(xy.sp)Object of class SpatialPointsCoordinates:min maxxc0.190.96yc0.200.91Is projected:NAproj4string:[NA]Number of points:104.2Points with attributesOne way of creating a SpatialPointsDataFrame object is by building it from a a SpatialPoints object and a data.frame containing the attributes:>df=data.frame(z1=round(5+rnorm(10),2),z2=20:29)>dfz1z21 3.10202 4.15213 3.68224 4.45235 6.62246 5.57257 3.66268 3.75279 5.1928105.0229>xy.spdf=SpatialPointsDataFrame(xy.sp,df)>xy.spdf7class:SpatialPointsDataFramefeatures:10extent:0.19,0.96,0.2,0.91(xmin,xmax,ymin,ymax)crs:NAvariables:2names:z1,z2min values: 3.1,20max values:6.62,29>summary(xy.spdf)Object of class SpatialPointsDataFrameCoordinates:min maxxc0.190.96yc0.200.91Is projected:NAproj4string:[NA]Number of points:10Data attributes:z1z2Min.:3.100Min.:20.001st Qu.:3.6971st Qu.:22.25Median:4.300Median:24.50Mean:4.519Mean:24.503rd Qu.:5.1473rd Qu.:26.75Max.:6.620Max.:29.00>dimensions(xy.spdf)[1]2>xy.spdf[1:2,]#selects row1and2class:SpatialPointsDataFramefeatures:2extent:0.67,0.96,0.3,0.62(xmin,xmax,ymin,ymax)crs:NAvariables:2names:z1,z2min values: 3.1,20max values:4.15,21>xy.spdf[1]#selects attribute column1,along with the coordinates class:SpatialPointsDataFramefeatures:108extent:0.19,0.96,0.2,0.91(xmin,xmax,ymin,ymax)crs:NAvariables:1names:z1min values: 3.1max values:6.62>xy.spdf[1:2,"z2"]#select row1,2and attribute"z2"class:SpatialPointsDataFramefeatures:2extent:0.67,0.96,0.3,0.62(xmin,xmax,ymin,ymax)crs:NAvariables:1names:z2min values:20max values:21>xy.df=as.data.frame(xy.spdf)>xy.df[1:2,]z1z2xc yc13.10200.670.3024.15210.960.62>=coordinates(xy.spdf)>class()[1]"matrix""array">dim()[1]102A note on selection with[:the behaviour is as much as possible copied from that of data.frame s,but coordinates are always sticky and a SpatialPointsDataFrame is always returned;drop=FALSE is not allowed.If coordinates should be dropped, use the as.data.frame method and select the non-coordinate data,or use[[ to select a single attribute column(example below).SpatialPointsDataFrame objects can be created directly from data.frames by specifying which columns contain the coordinates:>df1=data.frame(xy,df)>coordinates(df1)=c("xc","yc")>df1class:SpatialPointsDataFramefeatures:109extent:0.19,0.96,0.2,0.91(xmin,xmax,ymin,ymax)crs:NAvariables:2names:z1,z2min values: 3.1,20max values:6.62,29or>df2=data.frame(xy,df)>coordinates(df2)=~xc+yc>df2[1:2,]class:SpatialPointsDataFramefeatures:2extent:0.67,0.96,0.3,0.62(xmin,xmax,ymin,ymax)crs:NAvariables:2names:z1,z2min values: 3.1,20max values:4.15,21>as.data.frame(df2)[1:2,]xc yc z1z210.670.303.102020.960.624.1521Note that in this form,coordinates by setting(specifying)the coordinates promotes its argument,an object of class data.frame to an object of class SpatialPointsDataFrame.The method as.data.frame coerces back to the original data.frame.When used on a right-hand side of an equation,coordinates retrieves the matrix with coordinates:>coordinates(df2)[1:2,]xc yc10.670.3020.960.62Elements(columns)in the data.frame part of an object can be manipulated (retrieved,assigned)directly:>df2[["z2"]][1]20212223242526272829>df2[["z2"]][10]=20>df2[["z3"]]=1:10>summary(df2)10Object of class SpatialPointsDataFrameCoordinates:min maxxc0.190.96yc0.200.91Is projected:NAproj4string:[NA]Number of points:10Data attributes:z1z2z3Min.:3.100Min.:20.00Min.:1.001st Qu.:3.6971st Qu.:21.251st Qu.:3.25Median:4.300Median:23.50Median:5.50Mean:4.519Mean:23.60Mean:5.503rd Qu.:5.1473rd Qu.:25.753rd Qu.:7.75Max.:6.620Max.:28.00Max.:10.00Plotting attribute data can be done by using either spplot to colour symbols,or bubble which uses symbol size:>bubble(df2,"z1",key.space="bottom")>spplot(df2,"z1",key.space="bottom")the resulting plots are shown in gure2.5GridsPackage sp has two classes for grid topology:SpatialPixels and SpatialGrid.The pixels form stores coordinates and is for partial grids,or unordered points;the SpatialGrid form does not store coordinates but holds full grids(i.e., SpatialGridDataFrame holds attribute values for each grid cell).Objects canbe coerced from one representation to the other.5.1Creating grids from topologyWhen we know the o set,the cell sizes and the dimensions of a grid,we canspecify this by using the function GridTopology:>gt=GridTopology(cellcentre.offset=c(1,1,2),cellsize=c(1,1,1),cells.dim=c(3,4,6)) >grd=SpatialGrid(gt)>summary(grd)Object of class SpatialGridCoordinates:min max[1,]0.53.5[2,]0.54.511z13.13.6984.35.1486.62[3.1,3.804](3.804,4.508](4.508,5.212](5.212,5.916] (5.916,6.62]Figure2:plot of SpatialPointsDataFrame object,using symbol size(bubble, top)or colour(spplot,bottom)12[3,]1.57.5Is projected:NAproj4string:[NA]Grid attributes:cellcentre.offset cellsize cells.dim111321143216The grid parameters can be retrieved by the function>gridparameters(grd)cellcentre.offset cellsize cells.dim1113211432165.2Creating grids from pointsIn the following example a three-dimensional grid is constructed from a set of point coordinates:>pts=expand.grid(x=1:3,y=1:4,z=2:7)>grd.pts=SpatialPixels(SpatialPoints(pts))>summary(grd.pts)Object of class SpatialPixelsCoordinates:min maxx0.53.5y0.54.5z1.57.5Is projected:NAproj4string:[NA]Number of points:72Grid attributes:cellcentre.offset cellsize cells.dimx113y114z216>grd=as(grd.pts,"SpatialGrid")>summary(grd)Object of class SpatialGridCoordinates:min max13x0.53.5y0.54.5z1.57.5Is projected:NAproj4string:[NA]Grid attributes:cellcentre.offset cellsize cells.dimx113y114z216Note that when passed a points argument,SpatialPixels accepts a tolerance (default10*.Machine$double.eps)to specify how close the points have to be to being exactly on a grid.For very large coordinates,this value may have to be increased.A warning is issued if full rows and/or columns are missing.5.3Gridded data with attributesSpatial,gridded data are data with coordinates on a regular lattice.To form such a grid we can go from coordinates:>attr=expand.grid(xc=1:3,yc=1:3)>grd.attr=data.frame(attr,z1=1:9,z2=9:1)>coordinates(grd.attr)=~xc+yc>gridded(grd.attr)[1]FALSE>gridded(grd.attr)=TRUE>gridded(grd.attr)[1]TRUE>summary(grd.attr)Object of class SpatialPixelsDataFrameCoordinates:min maxxc0.53.5yc0.53.5Is projected:NAproj4string:[NA]Number of points:9Grid attributes:cellcentre.offset cellsize cells.dimxc113yc113Data attributes:14z1z2Min.:1Min.:11st Qu.:31st Qu.:3Median:5Median:5Mean:5Mean:53rd Qu.:73rd Qu.:7Max.:9Max.:9Package raster provides dedicated methods to deal with raster data,and can deal with grids that are too large to be stored in memory.5.4Are grids stored as points or as matrix/array?The form in which gridded data comes depends on whether the grid was created from a set of points or from a matrix or external grid format(e.g.read through rgdal).Retrieving the form,or conversion to another can be done by as(x, "class"),or by using the function fullgrid:>fullgrid(grd)[1]TRUE>fullgrid(grd.pts)[1]FALSE>fullgrid(grd.attr)[1]FALSE>fullgrid(grd.pts)=TRUE>fullgrid(grd.attr)=TRUE>fullgrid(grd.pts)[1]TRUE>fullgrid(grd.attr)[1]TRUEThe advantage of having grids in cell form is that when a large part of the grid contains missing values,these cells are not stored.In addition,no ordering of grid cells is required.For plotting by a grid with levelplot,this form is required and spplot(for grids a front-end to levelplot)will convert grids that are not in this form.In contrast,image requires a slightly altered version of the the full grid form.A disadvantage of the cell form is that the coordinates for each point have to be stored,which may be prohibitive for large grids.Grids in cell form do have an index to allow for fast transformation to the full grid form.Besides print,summary,plot,objects of class SpatialGridDataFrame have methods for15[select rows(points)and/or columns(variables)[[extract a column from the attribute table[[<-assign or replace a column in the attribute tablecoordinates retrieve the coordinates of grid cellsas.matrix,as.array retrieve the data as a matrix or array.The rst in-dex(rows)is the x-column,the second index(columns)the y-coordinate, di erent attributes the third index.Row index1is the smallest x-coordinate;column index1is the larges y-coordinate(top-to-bottom).as coercion methods for data.frame,SpatialPointsDataFrameimage plot an image of the gridFinally,spplot,a front-end to levelplot allows the plotting of a single grid plot or a lattice of grid plots.5.5Row and column selection of a regionRows/columns selection can be done when gridded data is in the full grid form (as SpatialGridDataFrame).In this form also rows and/or columns can be de-selected(in which case a warning is issued):>fullgrid(grd.attr)=FALSE>grd.attr[1:5,"z1"]Object of class SpatialPixelsDataFrameObject of class SpatialPixelsGrid topology:cellcentre.offset cellsize cells.dimxc113yc113SpatialPoints:xc yc[1,]13[2,]23[3,]33[4,]12[5,]22Coordinate Reference System(CRS)arguments:NAData summary:z1Min.:4.01st Qu.:5.0Median:7.016Mean:6.63rd Qu.:8.0Max.:9.0>fullgrid(grd.attr)=TRUE>grd.attr[1:2,-2,c("z2","z1")]Object of class SpatialGridDataFrameObject of class SpatialGridGrid topology:cellcentre.offset cellsize cells.dimxc122yc212SpatialPoints:xc yc[1,]13[2,]33[3,]12[4,]32Coordinate Reference System(CRS)arguments:NAData summary:z2z1Min.:1.0Min.:4.01st Qu.:2.51st Qu.:5.5Median:3.5Median:6.5Mean:3.5Mean:6.53rd Qu.:4.53rd Qu.:7.5Max.:6.0Max.:9.06Lines6.1Building line objects from scratchIn many instances,line coordinates will be retrieved from external sources.The following example shows how to build an object of class SpatialLines from scratch.Note that the Lines objects have to be given character ID values,and that these values must be unique for Lines objects combined in a SpatialLines object.>l1=cbind(c(1,2,3),c(3,2,2))>l1a=cbind(l1[,1]+.05,l1[,2]+.05)>l2=cbind(c(1,2,3),c(1,1.5,1))>Sl1=Line(l1)>Sl1a=Line(l1a)>Sl2=Line(l2)17>S1=Lines(list(Sl1,Sl1a),ID="a")>S2=Lines(list(Sl2),ID="b")>Sl=SpatialLines(list(S1,S2))>summary(Sl)Object of class SpatialLinesCoordinates:min maxx13.05y13.05Is projected:NAproj4string:[NA]>plot(Sl,col=c("red","blue"))6.2Building line objects with attributesThe class SpatialLinesDataFrame is designed for holding lines data that havean attribute table(data.frame)attached to it:>df=data.frame(z=c(1,2),s=sapply(slot(Sl,"lines"),function(x)slot(x,"ID")) >Sldf=SpatialLinesDataFrame(Sl,data=df)>summary(Sldf)18Object of class SpatialLinesDataFrameCoordinates:min maxx13.05y13.05Is projected:NAproj4string:[NA]Data attributes:zMin.:1.001st Qu.:1.25Median:1.50Mean:1.503rd Qu.:1.75Max.:2.00Not many useful methods for it are available yet.The plot method only plots the lines,ignoring attribute table values.Suggestions for useful methods are welcome.7Polygons7.1Building from scratchThe following example shows how a set of polygons are built from scratch. Note that Sr4has the opposite direction(anti-clockwise)as the other three (clockwise);it is meant to represent a hole in the Sr3polygon.The default value for the hole colour pbg is"transparent,which will not show,but which often does not matter,because another polygon lls the hole here it is set to"white".Note that the Polygons objects have to be given character ID values,and that these values must be unique for Polygons objects combined in a SpatialPolygons object.>Sr1=Polygon(cbind(c(2,4,4,1,2),c(2,3,5,4,2)))>Sr2=Polygon(cbind(c(5,4,2,5),c(2,3,2,2)))>Sr3=Polygon(cbind(c(4,4,5,10,4),c(5,3,2,5,5)))>Sr4=Polygon(cbind(c(5,6,6,5,5),c(4,4,3,3,4)),hole=TRUE)>Srs1=Polygons(list(Sr1),"s1")>Srs2=Polygons(list(Sr2),"s2")>Srs3=Polygons(list(Sr3,Sr4),"s3/4")>SpP=SpatialPolygons(list(Srs1,Srs2,Srs3),1:3)>plot(SpP,col=1:3,pbg="white")>#plot(SpP)197.2Polygons with attributesPolygons with attributes,objects of class SpatialPolygonsDataFrame,are built from the SpatialPolygons object(topology)and the attributes(data.frame). The s of the attributes data frame are matched with the ID slots of the SpatialPolygons object,and the rows of the data frame will be re-ordered if necessary.>attr=data.frame(a=1:3,b=3:1,s=c("s3/4","s2","s1")) >SrDf=SpatialPolygonsDataFrame(SpP,attr)>as(SrDf,"data.frame")a bs131s222s3/413>spplot(SrDf)201.01.52.02.53.0or,as another way to create the SpatialPolygonsDataFrame object:>SrDf=attr>polygons(SrDf)=SpP8Importing and exporting dataData import and export from external data sources and le formats is han-dled inthe rgdal package in the rst instance,using the available OGR/GDAL drivers for vector and raster data.This keeps the range of drivers up to date, and secures code maintenance through working closely with the open source geospatial community.Mac OSX users unable or unwilling to install rgdal from source after installing its external dependencies will nd some functions in the maptools package to import and export a limited range of formats.ReferencesChambers,J.M.,1998,Programming with data,a guide to the S language.Springer,New York.21。

kneighborsclassifier 的函数文档

`KNeighborsClassifier` 是scikit-learn 库中的一个类，用于实现k-近邻算法。

以下是`KNeighborsClassifier` 的函数文档：```pythonfrom sklearn.neighbors import KNeighborsClassifierclass KNeighborsClassifier(base.BaseEstimator, base.ClassifierMixin):def __init__(self, n_neighbors=5, weights=None, algorithm='auto'):self.n_neighbors = n_neighborsself.weights = weightsself.algorithm = algorithmdef fit(self, X, y):"""Fit the KNeighborsClassifier to the data X and y.Parameters----------X : array-like or BallTree, shape=(n_samples, n_features)Sample data, where n_samples is the number ofsamplesand n_features is the number of features.Note that this estimator may work in other array-likeobjects than scipy.sparse.csr_matrix, but not yet on mostof them.y : array-like, shape=(n_samples,) or (n_samples, n_outputs)Target values (integers or floating).Returns-------self : objectReturns the instance itself."""# XXX: this docstring is not updated yet! It should be refactored to# include the input data type requirements and algorithm details. This is# especially important because of the changing estimator API in scikit-learn# 0.18! The following line should be uncommented once this is done:# "X, y = check_X_y(X, y, ['csr', 'csc', 'coo'])"return selfdef predict(self, X):"""Predict the class labels for the provided data.Parameters----------X : array-like, shape=(n_new_samples, n_features)The data to predict on.Returns-------C : array-like, shape=(n_new_samples,) or (n_new_samples, n_outputs)Array of predicted class labels. Possible vectors of class labels ifthe class is nominal and outputs are integers. Note that before 0.16,predict always returned floats."""check_is_fitted(self)return self._predict(X) # XXX: this line should be uncommented once this is done: "X = check_array(X, accept_sparse=['csr', 'csc', 'coo'])")```这个文档描述了`KNeighborsClassifier` 的构造函数和两个主要方法：`fit` 和`predict`。

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吉林大学英语语言文学2010年招生目录专业代码：050201本专业招生25人
研究方向01．英语语言学（含跨文化交际和英语国家文化研究）02．英语国家文学
03．翻译研究
初试科目①101政治
②246二外（俄语）或247二外（日语）或248二外（德语）或249二外（法语）
③612英语实践
④814英语专业基础及综合（英语语言学、英美文学、英美概况、现代汉语及中国现当代文学基础）
复试科目英语语言学与英美文学基础
参考书目①初试参考书目：
246二外（俄语）《俄语》（修订2）黑龙江大学俄语系编，外语教学与研究出版社，1996年版；
247二外（日语）《新大学日语标准教程》（基础篇1-2册）（提高篇1-2册）陈俊森总主编，高等教育出版社2008年版
248二外（德语）《新求精德语强化教程》（初级1，2册）同济大学出版社；
249二外（法语）《法语》（1－3册），马晓宏编，外语教学与研究出版社；
612英语实践《高级英语》张汉熙编，商务印书馆；
814英语专业基础及综合（语言学、文学、概况、现代汉语及中国现当代文学基础）
《语言学导论》陈林华编著，吉林大学出版社，1999年版；
《语言学教程》（新版）胡壮麟编著，北京大学出版社，2006年第三版；
《现代英语词汇学概论》张韵斐编著，北京师范大学出版社，2004年版；
《英国文学简史》刘炳善编著，河南人民出版社，1993年版；
《美国文学简史》常耀信编著，南开大学出版社，2003年版；
《英美概况》张奎武编著，吉林科技出版社，2002年版；
《新编英美概况》来安方编著，河南人民出版社，2002年版；
《现代汉语》（增订本）胡裕树著，上海外语教育出版社，1987年版；
备注学制3年，除亚非语言文学外不招跨专业考生，跨专业不需加试
专业代码：050211本专业招生20人
研究方向01.应用语言学
02.跨文化交际学
03.翻译理论与实践
初试科目①101政治
②246二外（俄语）或247二外（日语）或248二外（德语）或249二外（法语）
③617英语实践技能
④819英语相关研究专业基础（语言学概论、英美概况、现代汉语及中国现当代文学基础）
复试科目英语专业相关知识与技能
参考书目①初试参考书目：
246二外（俄语）
《俄语》（修订2）黑龙江大学俄语系编，外语教学与研究出版社，1996年版；
247二外（日语）
《新大学日语标准教程》（基础篇1-2册）（提高篇1-2册）陈俊森总主编，高等教育出版社2008年版248二外（德语）
《新求精德语强化教程》（初级1，2册）同济大学出版社；
249二外（法语）
《法语》（1－3册），马晓宏编，外语教学与研究出版社；
819英语相关研究专业基础（语言学、英美概况、现代汉语及中国现当代文学基础）；
《语言学教程》（第三版）胡壮麟主编，北京大学出版社，2006年第3版；
《语言学导论》（修订版）陈林华编著，吉林大学出版社，1999年第2版；
《现代汉语》（增订本）胡裕树著，上海外语教育出版社，1987年版；
《英美概况（上、下）》张奎武主编，吉林科学技术出版社，2000年第3版；
《新编英美概况》来安芳编著，河南人民出版社，2002年第2版。

专业代码：050211本专业招生75人
研究方向01．英语各方向02．日语各方向03．俄语各方向
初试科目01．方向
①101政治
②246二外（俄语）或247二外（日语）或248二外（德语）或249二外（法语）
③654 英语语言实践
④940 英语专业基础（现代汉语、语言学概论、英美文学）
复试科目01．方向复试科目：英语专业口语
英语专业综合
参考书目01英语各方向参考书目：
《新大学日语标准教程》（基础篇1-2册）（提高篇1-2册）陈俊森总主编，高等教育出版社2008年版；《俄语》（修订版）（1—3册）黑龙江大学俄语系编，外语教学与研究出版社出版；
《新求精德语强化教程》（初级1、2册）（第三版）上海同济大学出版社；
《法语》（1—3册）马晓宏编，外语教学与研究出版社；
《语言学教程》胡壮麟主编，北京大学出版社2008年版；
《现代汉语》（重订本）胡裕树编，上海教育出版社2006年版；
《现代汉语》（增订第四版上、下册）黄伯荣、廖序东编，北京高教出版社2007年版；
《英美文学史及选读》吴伟仁编，外语教学与研究出版社。

复试用参考书目：
《英美概况》张奎武编，吉林科技出版社2008年版；
《英美概况（最新修订版）》来安芳编，河南教育出版社2002年版。

备注学制3年,不招收同等学力和跨专业考生。