You can specify D as either a full n-by-n matrix, or in upper triangle form such as is output by pdist. 5 4. The builtin function `pdist2` could be helpful, but it is inefficient for multiple timeframes data. So I looked into writing a fast implementation for R. matlab module contains a number of functions that emulate some of the functionality of MATLAB. For example, if one of A or B is a scalar, then the scalar is combined with each element of the other array. Therefore the similarity between all combinations is 1 - pdist (S1,'cosine') . I thought ij meant i*j. The pdist_inputs argument consists of the 'seuclidean', 'minkowski', or 'mahalanobis' metric and an additional distance metric option. Construct a Map Using Multidimensional Scaling. TagsObjectives: 1. This norm is also. E. Is there any workaround for this computational inefficiency. hi, I am having two Images I wanted compare these two Images by histograms I have read about pdist that provides 'chisq' but i think the way i am doing is not correct, and what to do to show the result afterwards because this is giving a black image. I'm producing m amount of nx1 vectors, and storing them all in an nxm matrix A (each column is a vector). MATLAB contains a function called pdist that calculates the ‘Pairwise distance between pairs of objects’. % Call a mex file to compute distances for the standard distance measures % and full real double or single data. % n = norm (v) returns the Euclidean norm of vector v. Accepted Answer. clear A = rand (132,6); % input matrix diss_mat = pdist (A,'@kullback_leibler_divergence'); % calculate the. If I have two points in 3d, A = [1579. 0 matlab use my own distance function for pdist. Learn more about pdist, distanceCreate a hierarchical cluster tree using the 'average' method and the 'chebychev' metric. cityblockSimilarity. linIdx = sub2allind ( size (A), 2:3, 1, 4:11 ); and then call A (linIdx) or A (linIdx (:)) or. Dear @zhang-chi-IGGCAS,. function D2 = distfun(ZI,ZJ) where. 这里 D 要特别注意，D 是一个长为m (m–1)/2的行向量. dist () in R will convert a matrix to a. ParameterSpace object as an input to the sdo. out = pdist(X, 'euclidian') 0. ^2 ). 9448. ) calls pdist with optional properties that use. If I calculate the distance between two points with my own code, it is much faster. All the points in the two clusters have large silhouette values (0. For a layer weight, set net. MATLAB - passing parameters to pdist custom distance function. A. Define an entry-point function named findNearestCentroid that accepts centroid positions and new data, and then find the nearest cluster by using pdist2. scipy. Go to MATLAB > Preferences > Workspace and ensure the Maximum array size limit is set to 100%. The software generates these samples using the distributions specified for each. distfun must accept a matrix XJ with an arbitrary number of rows. That would help answers like below to show you how to convert your data, rather than starting with “Given a matrix A of size. In thismatlab中自带的计算距离矩阵的函数有两个pdist和pdist2。 前者计算一个向量自身的距离矩阵，后者计算两个向量之间的距离矩阵。 基本调用形式如下： D=pdist(X) D=pdist2(X,Y) 这两个函数都提供多种距离度量形式，非常方便，还可以调用自己编写的距离. 1. . This function will compute the pairwise distance between every two points in your array. dim = dist ('size',S,R,FP) takes the layer dimension S, input dimension R, and function. distance. Right-click Group 18, then select Export Group to Workspace. You need to take the square root to get the distance. How can I perform K-means clustering on time series data? 2. Z (2,3) ans = 0. Goncalves. mY = mY + mY. You need to have the licence for the statistics toolbox to run pdist. Convert distance pairs to distance matrix to use in hierarchical clustering. Hi, I'm trying to perform hierarchical clustering on my data. . numberPositionsDifferent = size (A,2)*pdist (A,'hamming'); If that's not what you meant, you might want to give more information (including the answer to Walter's. 1. This distance represents how far y is from the mean in number of standard deviations. Learn more about clustergram, pearson correlation, pdist, columnpdist, rowpdist MATLAB, Bioinformatics Toolbox I am doing the Hierarchical cluster analysis. 5000 2. ^2,3)); This calculates the distance between any two points explicitly (thus, does twice as much work, and takes over twice as much space: 6400 instead of 3180 elements). I have a 70,000 x 300 matrix. MY-by-N data matrix Y. As I am not personally that familiar with the PDist function, and its limits and limitations, nor with Cluster & MAVEN data I am assigning this issue to @danbgraham who I hope can reply with a more details response. How to separately compute the Euclidean Distance in different dimension? 2. This example shows how to construct a map of 10 US cities based on the distances between those cities, using cmdscale. 2 Answers. pdist2 (X,Y,Distance): distance between each pair of observations in X and Y using the metric specified by Distance. Generate C code that assigns new data to the existing clusters. For the future, try typing edit pdist2 (or whatever other function) in Matlab, in most cases, you will see the Matlab function, which you can then convert to python. CanberraSimilarity. pdist2 (X,Y,Distance): distance between each pair of observations in X and Y using the metric specified by Distance. Pairwise distance between observations. Here's an example in 2D, but it works exactly the same in 3D:silhouette (X,clust) The silhouette plot shows that the data is split into two clusters of equal size. You can use one of the following methods for your utility: norm (): distance between two points as the norm of the difference between the vector elements. calculate_distance. See more linked questions. m. Idx = knnsearch (X,Y) finds the nearest neighbor in X for each query point in Y and returns the indices of the nearest neighbors in Idx, a column vector. Add the %#codegen compiler directive (or pragma) to the entry. % Requires the Statistics and Machine Learning Toolbox because of the pdist() and squareform() functions. The output from pdist is a symmetric dissimilarity matrix, stored as a vector containing only the (23*22/2) elements in its upper triangle. Generate Code. MATLAB - passing parameters to pdist custom distance function. spatial. . Implementation of some commonly used histogram distances (compatible with the pdist interface) 4. 9448. I have seen extensions of these functions that allow for weighting, but these extensions do not allow users to select different distance functions. Learn more about distance, euclidean, pdist, coordinates, optimisation MATLAB Hi all, Many of the codes I am currently using depend on a simple calculation: the distance between a single point and a set of other points. MY-by-N data matrix Y. distfun must return an m2-by-1 vector of distances d2, whose kth element is the distance between XI. Learn more about pdist, matrix, matrix manipulation, distances MATLAB, Statistics and Machine Learning Toolbox. You can try the following workarounds: 1. Matlab provides a knnsearch function that uses K-D-trees for this exact purpose. squareform时进行向量矩阵转换以及出现“The matrix argument must be square“报错的解决方案Use matlab's 'pdist' and 'squareform' functions 0 Comments. If you need to create a list with the indeces, see the method below to avoid loops, since that was the real time-consuming part of your code, rather than the distance method itself. c = cophenet(Z,Y) Description. 예제 D. D can also be a more general dissimilarity vector or matrix that conforms to the output format of pdist or pdist2, respectively. Puede especificar DistParameter solo cuando Distance sea 'seuclidean', 'minkowski' o 'mahalanobis'. com account, please see github. Note that generating C/C++ code requires MATLAB® Coder™. The statstics toolbox offers pdist and pdist2, which accept many different distance functions, but not weighting. To save your figure as a graphics-format file, specify a format switch and filename. end. D = pdist(X,distance) computes the distance between objects in the data matrix, X, using the method specified by distance, which can be any of the following: MetricMATLAB pdist function. matlab Pdist2 with mahalanobis metric. I have MATLAB installed. The Age values are in years, and the Weight values are in pounds. MATLAB Vectorised Pairwise Distance. The pdist function in MatLab, running on an AWS cloud computer, returns the following error: Requested 1x252043965036 (1877. This norm is also. However, it's easier to look up the distance between any two points. Generate C code that assigns new data to the existing clusters. Now, to Minkowski's distance, I want to add this part |-m (i)|^p. Documentation. Find the treasures in MATLAB Central and discover how the community can help you!. Accepted Answer: Anand. I don't know off-hand if pdist is overloaded for integer types or not. pdist is designed for pairwise diatances between vectors, using one of several distance measures. Z = linkage(X,method,pdist_inputs) passes pdist_inputs to the pdist function, which computes the distance between the rows of X. . Does anybody have general. I managed to use pdist(X) instead. Z = linkage(Y,'single') If 0 < c < 2, use cluster to define clusters from. Product of a multi-dimensional array (or tensor) and vectors. Compute the distance with naneucdist by passing the function handle as an. Answers (1) In my understanding you want to use your custom distance function (dtwdist) with kmediod (). dist=pdist ( [x (i);y (j)],'minkowski'); Up till here, the above command will do the equation shown in the link. All elements of the condensed distance matrix must be finite, i. m. Y contains the distances or dissimilarities used to construct Z, as output by the pdist function. 예: "maximal" Description. y = squareform (Z)Y = pdist(X,'euclidean') Create an agglomerative hierarchical cluster tree from Y by using linkage with the 'single' method for computing the shortest distance between clusters. For 8192 partcies the pdist version of this averaging is 2 seconds, while the suggested averaging takes 2 minutes. 9 I need to calculate the euclidean distance between 2 matrices in matlab. Explanation: pdist (S1,'cosine') calculates the cosine distance between all combinations of rows in S1. Y = pdist (X, 'canberra') Computes the Canberra distance between the points. Syntax. 计算 X 中各对行向量的相互距离 (X是一个m-by-n的矩阵). T = cluster (Z, 'maxclust' ,3); Create a dendrogram plot of Z. D = pdist(X,Distance,DistParameter) devuelve la distancia usando el método especificado por Distance y DistParameter. Find more on Random Number Generation in Help Center and File Exchange. cmdscale takes as an input a matrix of inter-point distances and creates a configuration of points. Add a comment. Plot distances between points matlab. 9448 The outputs y from squareform and D from. For example, you can find the distance between observations 2 and 3. 2 Answers. Y = pdist(X) Y= Columns 1 through 5 2. As stated in the error, knnimpute uses pdist, the pairwise distance. Answers (1) This issue could be due to RAM limitations. I need to add a toolbox to the existing installation. At higher values of N, the speed is much slower. Note that generating C/C++ code requires MATLAB® Coder™. 2. 【python】scipy中pdist和squareform; pdist()和squareform()函数实例详解; pdist函数; MATLAB pdist函数的使用; Matlab中 pdist 函数详解; MATLAB中dist与pdist、pdist2的区别与联系; 使用distance. More precisely, the distance is given by. Define an entry-point function named findNearestCentroid that accepts centroid positions and new data, and then find the nearest cluster by using pdist2. If it is then you could also use them depending what level of accuracy you requie. I am struggling a bit here, and hope somebody could help. Copy. This function can do both - it will function like pdist if only one set of observations is provided and will function like pdist2 if two. Hye, can anybody help me, what is the calculation to calculate euclidean distance for 3D data that has x,y and z value in Matlab? Thank you so much. Spectral clustering is a graph-based algorithm for partitioning data points, or observations, into k clusters. Feb 25, 2018 at 9:36. The pdist version runs much faster than rangesearch. Y = pdist(X) Y = pdist(X,'metric') Y = pdist(X,distfun,p1,p2,. Z = dist (W,P) takes an S -by- R weight matrix, W, and an R -by- Q matrix of Q input (column) vectors, P, and returns the S -by- Q matrix of vector distances, Z. first of all, sorry I did not see your comment. – Nicky Mattsson. example. Faster than pdist for cityblock on integers? . Categories MATLAB Mathematics Random Number Generation. mX = mX + mX. A data set might contain values that you want to treat as missing data, but are not standard MATLAB missing values in MATLAB such as NaN. I've implemented a custom distance function for k-medoids algorithm in Matlab, following the directions found in pdist. By default, the function calculates the average great-circle distance of the points from the geographic mean of the points. weightFcn to 'dist'. However, I use this matrix in a loop like this : for i:1:n find (Distance (i,:) <= epsilon);. Copy. When two matrices A and B are provided as input, this function computes the square Euclidean distances. 4 51. how can I add a dot product as a distance function in pdist of matlab. awpathum. You can also specify a function for the distance metric using a function handle. Create a hierarchical cluster tree using the 'average' method and the 'chebychev' metric. Tagsxtrack = 1 x 1166 ytrack = 1 x 1166. Goncalves. So the following answer applies to the problem of finding all pairwise distances in a N-by-D matrix, as your loop does for the case of D=2. dist_temp = pdist (X); dist = squareform (dist_temp); Construct the similarity matrix and confirm that it is symmetric. Finally, there is a function called pdist that would do everything for you :. 创建包含三个观测值和两个变量的矩阵。 rng ( 'default') % For reproducibility X = rand (3,2); 计算欧几里德距离。 D = pdist (X) D = 1×3 0. The most efficient pairwise distance computation. This #terms resulted after stopwords removal and stemming. The most efficient pairwise distance computation. You can use one of the following methods for your utility: norm (): distance between two points as the norm of the difference between the vector elements. This syntax is equivalent to [arclen,az] = distance (pt1 (:,1),pt1 (:,2),pt2. Pass Z to the squareform function to reproduce the output of the pdist function. Find more on Shifting and Sorting Matrices in Help Center and File Exchange. The Euclidean distances between points in Y approximate a monotonic transformation of the corresponding dissimilarities in D . 0. c = cophenet(Z,Y) computes the cophenetic correlation coefficient which compares the distance information in Z, generated by linkage, and the distance information in Y, generated by pdist. Pass Z to the squareform function to reproduce the output of the pdist function. y = squareform (Z) squareform returns a symmetric matrix where Z (i,j) corresponds to the pairwise distance between observations i and j. Euclidean distance between two points. Pairwise distances between observations, specified as a numeric row vector that is the output of pdist, numeric square matrix that is the output of pdist2, logical row vector, or logical square matrix. aN bN cN. ^2,3)); This calculates the distance between any two points explicitly (thus, does twice as much work, and takes over twice as much space: 6400 instead of 3180 elements). Where p = 1 (for now), n is as large as the number of points and d as large as the number of dimensions (3 in this case). is there an alternative to pdist2 that calculates the distance between a matrices with different column numbers. Pass Z to the squareform function to reproduce the output of the pdist function. 이 경우, MATLAB ® 에서 오류를 발생시킵니다. Commented: Walter Roberson on 4 Oct 2017. Feb 25, 2018 at 9:36. {"payload":{"allShortcutsEnabled":false,"fileTree":{"classify":{"items":[{"name":"private","path":"classify/private","contentType":"directory"},{"name":"Contents. Generate Code. Note that generating C/C++ code requires MATLAB® Coder™. Accepted Answer: Image Analyst. T = cluster (Z,'Cutoff',C) defines clusters from an agglomerative hierarchical cluster tree Z . You can define your own distance function to handle complex-valued data. If your compiler does not support the Open Multiprocessing (OpenMP) application interface or you disable OpenMP library, MATLAB Coder™ treats the parfor -loops as for -loops. hi every body. Description. Try something like E = pdist2 (X,Y-mean (X),'mahalanobis',S); to see if that gives you the same results as mahal. I have ~161 time series of heart rates taken during a vocalization. Y = pdist(X) Y = pdist(X,'metric') Y = pdist(X,distfun,p1,p2,. I don't know off-hand if pdist is overloaded for integer types or not. I have to calculate pairwise di. 2. If your compiler does not support the Open Multiprocessing (OpenMP) application interface or you disable OpenMP library, MATLAB Coder™ treats the parfor -loops as for -loops. Copy. Sorted by: 1. For the future, try typing edit pdist2 (or whatever other function) in Matlab, in most cases, you will see the Matlab function, which you can then convert to python. Get an overview of what functions in MATLAB® are, and learn how to use them. 1. Syntax. y = squareform (Z) Y = pdist(X,'euclidean') Create an agglomerative hierarchical cluster tree from Y by using linkage with the 'single' method for computing the shortest distance between clusters. By comparing the dendrograms produced by the clustergram object and the "manual" approach i. It shows a path (C:\Program Files\MATLAB. . Add a comment. Sign in to answer this question. I am looking for an alternative to this in. Add the %#codegen compiler directive (or pragma) to the entry. As others correctly noted, it is not a good practice to use a not pre-allocated array as it highly reduces your running speed. I am looking for a code that will result in a list of distances between two lists of xyz coordinates. D = pdist2 (X,Y) returns a matrix D containing the Euclidean distances. Generate C code that assigns new data to the existing clusters. 0000. If you realize that. Copy. Idx has the same number of rows as Y. Classical Multidimensional Scaling. Define an entry-point function named findNearestCentroid that accepts centroid positions and new data, and then find the nearest cluster by using pdist2. For example, you can find the distance between observations 2 and 3. My one-line implementation of both MATLAB's pdist and pdist2 functions which compute the univariate (pdist) or bivariate (pdist2) Euclidean distances between all pairs of input observations. Currently I am using bsxfun and calculating the distance as below ( i am attaching a. See Also. Note that generating C/C++ code requires MATLAB® Coder™. for i=1:m. I agree with Tal Darom, pdist2 is exactly the function you need. 4K Downloads. Z (2,3) ans = 0. BUT: The code shown here is 10-100 times faster, utilizing the. 否则，pdist 使用标准算法来计算欧几里德距离。 如果距离参数为 'fasteuclidean'、'fastsquaredeuclidean' 或 'fastseuclidean'，并且 cache 值太大或为 "maximal"，则 pdist 可能会尝试分配超出可用内存容量的格拉姆矩阵。在这种情况下，MATLAB ® 会引发错误。 示例： "maximal"pdist_oneLine. Associate values with predefined names using constant properties or enumeration classes. The generated code of pdist uses parfor (MATLAB Coder) to create loops that run in parallel on supported shared-memory multicore platforms in the generated code. 0 matlab Pdist2 with mahalanobis metric. Este argumento se aplica solo cuando Distance es 'fasteuclidean', 'fastsquaredeuclidean' o 'fastseuclidean'. Version History. Return the mapping of the original data points to the leaf nodes shown in the plot. Would be cool to see what you have in python, and how it compares. Or you can do k mediods which works with a distance matrix - as. Copy. Is there a way to make pdist ignore. You can easily locate the distance between observations i and j by using squareform. load arrhythmia isLabels = unique (Y); nLabels = numel (isLabels) nLabels = 13. ) The -r switch is also supported for Windows Enhanced Metafiles but is not supported for Ghostscript. Y = pdist (X, 'canberra') Computes the Canberra distance between the points. k = 2 B_kidx = knnsearch(B, A, 'K', k) then B_kidx will be the first two columns of B_idx, i. 0. % n = norm (v) returns the Euclidean norm of vector v. example. At the moment i am using the pdist function in Matlab, to calculate the euclidian distances between various points in a three dimensional cartesian system. Documentation, examples, videos, and other support resources for MathWorks products including MATLAB and Simulink. If the sizes of A and B are compatible, then the two arrays implicitly expand to match each other. How does condensed distance matrix work? (pdist) scipy. The pdist command requires the Statistics and Machine Learning toolbox. Pass Z to the squareform function to reproduce the output of the pdist function. Basically it compares two vectors, say A and B (which can also have different. pd = makedist (distname) creates a probability distribution object for the distribution distname , using the default parameter values. Nov 8, 2013 at 9:26. Follow. 2. % Learning toolbox. Specify a cell array if the distance metric requires extra arguments. 설명 예제 D = pdist (X) 는 X 에 포함된 관측값 쌍 간의 유클리드 거리를 반환합니다. . (Matlab pdist does support the option though, see here) you need to do the calculation "manually", i. layerWeights{i,j}. D = pdist2 (F (i). 357 views (last 30 days) Show older comments. You can use D = pdist (X) to calculate pairwise isdtance in MATLAB, default distance is Euclidean. It also produces an image where the pixel values are the distances of that pixel to the nearest foreground pixel. imputedData2 = knnimpute (yeastvalues,5); Change the distance metric to use the Minknowski distance. The apostrophe operator computes the complex conjugate transpose of X. @Masi step 1 is to understand what the results of pdist are. 0670 0. Pairwise Distance Matrix. matlab use my own distance function for pdist. D is a 1 -by- (M* (M-1)/2) row vector corresponding to the M* (M-1)/2 pairs of sequences in Seqs. For example |A| number of items that is not zero is 2, for |B| and |C| it is 1, and for |D| it is 2. Categories MATLAB Mathematics Random Number Generation. Hi everyone. What I want is to now create an mxm matrix B where B(i,j) = norm(vi -vj). The distance function must be of the form d2 = distfun(XI,XJ), where XI is a 1-by-n vector corresponding to a single row of the input matrix X, and XJ is an m 2-by-n matrix corresponding to multiple rows of X. There is a choice between a large number of distances for "pdist". If you don't have that toolbox, you can also do it with basic operations. Learn more about distance, euclidean, pdist, coordinates, optimisation MATLAB Hi all, Many of the codes I am currently using depend on a simple calculation: the distance between a single point and a set of other points. For example, you can find the distance between observations 2 and 3. The patristic distances are computed by following paths through the branches of the tree and adding the patristic branch distances originally created with the seqlinkage function. sum (any (isnan (imputedData1),2)) ans = 0. 可以这样理解 D 的生成：首先生成一个 X 的距离方阵，由于该方阵是对称的，令对角线上的元素为0，所以取此方阵的下三角元素. pdist admite varias métricas de distancia: distancia euclidiana, distancia euclidiana estandarizada, distancia de Mahalanobis, distancia Manhattan, distancia de Minkowski, distancia de Chebyshov, distancia del coseno, distancia de correlación, distancia de Hamming, distancia de Jaccard y distancia de. Now, it is confirmed that I do not have a license. d = ( y − μ) ∑ − 1 ( y − μ). ) Y = pdist(X,'minkowski',p) Description . I have a set of points from a complex function that I am trying to produce a 3D shape of, and have had no luck so far. The pairwise distances are arranged in the order (2,1), (3,1), (3,2). Find the treasures in MATLAB Central and discover how the community can help you! Start Hunting!Anyway, when you have a built-in function in Matlab, it will almost always outperform hardcoded ones so just go with pdist2. Now, to Minkowski's distance, I want to add this part |-m (i)|^p. d(u, v) = max i | ui − vi |. Classification is a type of supervised machine learning in which an algorithm “learns” to classify new. However, it is not a native Matlab structure. % n = norm (v) returns the Euclidean norm of vector v. Seeing that your matrix has a RGB pixel. pdist_oneLine. See Elements of Statistical Learning by Rob Tibshirani. All the points in the two clusters have large silhouette values (0. Ridwan Alam on 20 Nov 2019. y = squareform (Z) Theme. Following problem occuried:linkage. 1. The default for the pdist function, 'correlation', would include both the positive and. This norm is also. This syntax references the coordinates to a sphere and returns arclen and az as spherical distances in degrees. MATLAB - passing parameters to pdist custom distance function. ), however at the end, it shows an important message. pdist (X): Euclidean distance between pairs of observations in X. Function "pdist" in Matlab. From pdist documentation (emphasis mine):. The Mahalanobis distance from a vector y to a distribution with mean μ and covariance Σ is. Rather it seems that the correct answer for these places should be a '0' (as in, they do not have anything in common - calculating a similarity measure using 1-pdist) . y = squareform (Z) squareform returns a symmetric matrix where Z (i,j) corresponds to the pairwise distance between observations i and j. The function must accept a matrix ZJ with an arbitrary number of observations. Share. Cophenetic correlation coefficient. 1. Learn more about pdist, matrix, matrix manipulation, distances MATLAB, Statistics and Machine Learning Toolbox. 1. – Nicky Mattsson. Show -1 older comments Hide -1 older comments. *B multiplies arrays A and B by multiplying corresponding elements. Perform spectral clustering. Y = pdist (X, 'canberra') Computes the Canberra distance between the points. I have a naive so. Hye, can anybody help me, what is the calculation to calculate euclidean distance for 3D data that has x,y and z value in Matlab? Thank you so much. Description. Also remember that MATLAB now supports implicit expansion (also called broadcasting) so you can directly subtract a 1x3 to a 15x3x3. I have tried overwriting the values i want to ignore with NaN's, but pdist still uses them in the calculation. Description. clear A = rand (132,6); % input matrix diss_mat = pdist (A,'@kullback_leibler_divergence'); % calculate the. Use matlab's 'pdist' and 'squareform' functions 0 Comments. MATLAB Language Fundamentals Matrices and Arrays Resizing and Reshaping Matrices. Y = mdscale (D,p) performs nonmetric multidimensional scaling on the n -by- n dissimilarity matrix D, and returns Y, a configuration of n points (rows) in p dimensions (columns). You will need to look for it in the code you are using, and then put the function somewhere in your MATLAB search path. Sign in to answer this question. Edit. Then, plot the dendrogram for the complete tree (100 leaf nodes) by setting the input argument P equal to 0. You can use one of the following methods for your utility: norm (): distance between two points as the norm of the difference between the vector elements. Find Nearest Points Using Custom Distance Function. I would like to use the linkage function in matlab with a custom distance. D = pdist2 (X,Y) returns a matrix D containing the Euclidean distances. I would thus. Alternatively, a collection of (m) observation vectors in (n) dimensions may be passed as an (m) by (n) array. MATLAB - passing parameters to pdist custom distance function I've implemented a custom distance function for k-medoids algorithm in Matlab, following the directions found in pdist. 9448.