scatteredinterpolant. e. scatteredinterpolant

 
escatteredinterpolant  griddata (points, values, xi, method = 'linear', fill_value = nan, rescale = False) [source] # Interpolate unstructured

random. In this case will be F = scatteredInterpolant (x,y,v), which the function itself is trying to get the F in v = F(x,y). However, it can only handle 2D and 3D scatter data, whereas this function can handle any number of dimensions. Learn more about TeamsLearn more about scatteredinterpolant, interpolation, matrix, time, column, griddata, slow MATLAB Hey guys, so I got the following problem: I want to interpolate my matrix (size 220x180x1801) onto a new grid (of course size 220x180). nan, rescale=False) #. griddata# scipy. 233029 0. There is no built-in Fortran functionality to do linear interpolation. Then I query the interpolant over a set of points. Then i m trying to plot the equation. Use scatteredInterpolant to perform interpolation on a 2-D or 3-D data set of scattered data . You can create the interpolant by calling scatteredInterpolant and passing the point locations and corresponding values, and optionally the interpolation and extrapolation methods. Your lat and lon are arranged in ndgrid format, not in meshgrid format. I'm sorry, but you simply cannot use scatteredInterpolant to produce a meaningful result from this data, as you are trying to do. Extrapolating Scattered Data Factors That Affect the Accuracy of Extrapolation. random. The plane is defined as normal to the midpoint between point. For linear, do they mean a tangent plane approximation or a distance weighted approach? also for nearest, how can we know how many nearest neighbours are being used. Dear Sir/Madam. That the HDF investigation revealed no stored data structure confirms suspicions raised by timing of loading the data. Extrapolar datos dispersos Factores que afectan a la precisión de la extrapolación. I have a geographically distributed data set with X-coordinate, Y-coordinate and corresponding target value of interest D. 25; 3 3. " Does this mean that the function discovered duplicate (x,y) grid points in my inputs, or that some adjacent z-points are duplicated?scatteredInterpolant supports (x, y, v, then options, or (x, y, z, v, then options, so building an interpolation object over 2d or over 3d, that you then invoke with the appropriate number of input parameters to get results. scatteredInterpolant provides functionality for approximating values at points that fall outside the convex hull. subroutine interp1 ( xData, yData, xVal, yVal ) ! Inputs: xData = a vector of the x-values of. m and the testPerfo2. Use griddedInterpolant to perform interpolation with gridded data. Now I have data for each 0. This. I have tried num = 1,3,4, and as you suggest in your notes 3 is best, but, by eye, still exaggerates the missing corner points. A simple way around is to add some noise to your data as with randn then ScatterInterpolant does not. After F is calculated, you can bring in the sampled point coordinate (x_s,y_s) in to F(x_s,y_s) to get the interpolate values. interpolate. A simple way around is to add some noise to your data as with randn then ScatterInterpolant does not consider the values to be equal and it works for me. 064604 0. The 'linear' extrapolation method is based on a least-squares approximation of the gradient at the boundary of the convex hull. My first attempt to solve this was the interpolation methods in MATLAB. Teams. Answered: Cris LaPierre on 5 Aug 2021. Connect and share knowledge within a single location that is structured and easy to search. I want to find the coordinates in the first data set that are closest to. So, I've noticed that interp2/interp3 is supported. The. scipy. Theme. For my project I have to write a C++ code, equivalent to the ScatteredInterpolant() function of Matlab. scatteredInterpolant provides functionality for approximating values at points that fall outside the convex hull. 974 5333045. interpolate. However, I do not understand exactly what happens if some of the. Interp = scatteredInterpolant (supportPts (:,1),supportPts (:,2),Fval); %evaluate at center of bottom left element. I tried to put the. 121444 0. m' (which creates the 'scatteredInterpolant' object). interpn expects gridded data in a full grid format, which is not what your Y represents, at least in its current form. x = sort (20*rand (100,1)); v = besselj (0,x); Create a. Surface plots are useful for visualizing matrices that are too large to display in numerical form and for graphing. % Shear area of I-beam when load is parallel to web. The MATLAB language is designed to give optimum performance when your application is structured into functions that reside in files. Asking for help, clarification, or responding to other answers. Furthermore, when you do your joining "along" the data, some of the points must be joined with a different Z layer, in order to be able to provide the surface. I tried to put the 'ExtrapolationMethod' option. I had the same problem with surface DEM's. interpolate. txt files which I import in the workspace in 3 column variables (no time dependency). In a previous discussion Kelly provided a means to convert a scattered vector to gridded information, but it can potentially take up a lot of memory. One trick you can do is to add one number to the end the array to remove the collinear correlation. Assuming I have some scattered points; then I used scattered interpolant to having a 0. julia> ]add ScatteredInterpolation. TLDR: The Y and xq you've constructed work for scatteredInterpolant but not for griddedInterpolant which uses a different format. scatteredInterpolant is not supported at all for code generation (at least in my MATLAB version, might be improved in recent Versions). This example shows how to extrapolate a well sampled 3-D gridded dataset using scatteredInterpolant. How to retain duplicate while using. Use scatteredInterpolant to perform interpolation on a 2-D or 3-D data set of scattered data . The support engineers are great, they really know how to choose a good subject line that will get a developer's attention and get a response back to the customer quickly. Contour does not capture the geometry boundaries properly and shape looks distorted. 24 25. The griddatan function supports scattered data interpolation in N-D; however, it is not practical in dimensions higher than 6-D for moderate to large point sets, due to the exponential growth in memory required by the underlying triangulation. (It also has definite advantages with respect to drawing lines on surfaces, if that becomes necessary. GitHub is where people build software. meshgrid(xi,yi. For instance, the testFunction. This program computes a Delaunay triangulation of the data points, and then constructs an interpolant triangle by triangle. My data points are scattered data in three dimension. Copy. I was using it for my research but after some playing around it seems to just be. 3, matplotlib provides a griddata function that behaves similarly to the matlab version. Learn more about interpolation, interpn, multivariate, optimization, numerical interpolation, griddatan MATLAB As far as I know, I know interp2,interp,griddata,scatteredInterpolant and other functions can achieve my non-aligned regular grid data for mapping, but the efficiency is very low, on the contrary, the remap function in opencv is very fast and only does mapping projection. F = scatteredInterpolant (X,v) creates an interpolant that fits a surface of the form v = F (X) to the sample data set (X,v). F = scatteredInterpolant (x_repeat,x1 (:,3)); %rather than throwing an error, shows a warning and cleans your data for you. Use scatteredInterpolant to perform interpolation on a 2-D or 3-D data set of scattered data . The second output FY is always the gradient along the 1st dimension of F, going across rows. The 'linear' extrapolation method is based on a least-squares approximation of the gradient at the boundary of the convex hull. You can evaluate F at a set of query points, such as (xq,yq) in 2-D, to produce interpolated values vq = F (xq,yq). You can evaluate F at a set of query points, such as (xq,yq) in. I would like to interpolate the data and have a 3D interpolated plot where the color is the interpolated value at each x,y,z coordinates (not the value of z). Please execute the attached files in the following order:a. 9. The MATLAB language is designed to give optimum performance when your application is structured into functions that reside in files. This can be done either switching to a Interpreded MATLAB block or using coder. Apply collocation with prediction and filtering for scattered data. scatteredInterpolant seems to do the job quite well for grid points within the boundaries of the original cloud; however, I still need the grid points falling outside the limits of the original dataset to be NaNs. F = scatteredInterpolant (x_raw,y_raw,z_raw,'natural'); ZGrid = F (XGrid,YGrid); For my work it would be very useful to find the number of points from the raw data which fall into each element (pixel) of the resulting image (2D array). Extract your vertices data in a matrix. For example, I have the following non-gridded data points, known v = F(x. This library provides the adaptive MBA algorithm from [1] implemented in C++11. If x and y represent a regular grid, consider using RectBivariateSpline. Es posible usar la interpolación para rellenar datos faltantes, suavizar datos existentes y hacer predicciones, entre otras cosas. scatteredInterpolant returns the interpolant F for the given data set. I haven't tried compiling or testing and my fortran may be a bit rusty, but something like the following should work. scatteredInterpolant supports (x, y, v, then options, or (x, y, z, v, then options, so building an interpolation object over 2d or over 3d, that you then invoke with the appropriate number of input parameters to get results. 184942 0. The size of the input v must match the size of the original data, either as a vector or a. problem with scatteredInterpolant: are there any. scatteredInterpolant giving null matrix. Clearly at this point you can add your own cleaning method, but if you are using this class chances are you are trying to avoid writing that sort of code in the first place. Multiple sample values into scatteredInterpolant . Suppose you have multidimensional data, for instance, for an underlying function \ (f (x, y)\) you only know the values at points (x [i], y [i]) that do not form a regular grid. After F is calculated, you can bring in the sampled point coordinate (x_s,y_s) in to F(x_s,y_s) to get the interpolate values. 使用 scatteredInterpolant 进行的散点数据插值使用数据的 Delaunay 三角剖分,因此对采样点 x、y、z 或 P 中的缩放问题非常敏感。出现这种情况时,您可以使用 normalize 重新缩放数据并改进结果。有关详细信息,请参阅对不同量级的数据进行归一化。ScatteredInterpolant just does what it is told, having no idea that when you try to interpolate some point in that volume, it is creating meaningless gibberish as a result. Correct me if I am mistaken but for me it looks like you are passing the arguments in different orders in each version. Use griddedInterpolant to perform interpolation with gridded data. You can provide the inputs in that form rather than a mxn array. m' (which creates the 'scatteredInterpolant' object). This makes it easy to swap interpolators. Both algorithms can be used to solve 2D and 3D problems with purely spatial coordinates (we recommend you to read notes on issues arising when RBF models are used to solve tasks with mixed, spatial and temporal coordinates). scatteredInterpolant returns the interpolant F for the given data set. Use griddedInterpolant to interpolate a 1-D data set. Finally, constructing the output, which in your case you seem to want a grid. The outer boundary surface of a Delaunay triangulation is in fact the convex hull of the data. I want to interpolate onto a regular grid. The values in the y-matrix are strictly. There will be some areas where you get garbage. F = scatteredInterpolant (X,v) creates an interpolant that fits a surface of the form v = F (X) to the sample data set (X,v). Best Answer. There are several general facilities available in SciPy for interpolation and smoothing for data in 1, 2, and higher dimensions. The scatteredInterpolant class supports scattered data interpolation in 2-D and 3-D space. Theme. Copy. V contains the corresponding function values at each sample point. However, the behavior of such fits is unpredictable between data points. Creation of arrays greater than this limit may take a long time and cause MATLAB to become unresponsive. MATLAB ® 中的插值技术可分为适用于网格上的数据点和散点数据点。. Merely not to your liking. scatteredInterpolant is not supported at all for code generation (at least in my MATLAB version, might be improved in recent Versions). scatteredInterpolant returns the interpolant F for the given data set. scatteredInterpolant contains data and it behaves like an array—in MATLAB language, it is called a value object. Besides splitting the creation of the object from the invocation for interpolation purposes, griddata simply does not. " regardless of whether there's an extrapolation method . The calling syntax is similar to griddata. Interpolate Two Sets of 2-D Sample Values. % Section Classification Flange width to thickness ratio in compression. scatteredInterpolant contains data and it behaves like an array—in MATLAB language, it is called a value object. A simple way around is to add some noise to your data as with randn then ScatterInterpolant does not consider the values to be equal and it works for me. This is a fast algorithm for scattered N-dimensional data interpolation and approximation. In a previous discussion Kelly provided a means to convert a scattered vector to gridded. The surface is always convex (as the name suggests)Use scatteredInterpolant to perform interpolation on a 2-D or 3-D data set of scattered data . pwl_interp_2d_scattered , a C++ code which produces a piecewise linear interpolant to 2D scattered data, that is, data that is not guaranteed to lie on a regular grid. This method fits smooth surfaces that also extrapolate well (for surfaces only). New in version 0. Show 2 older comments Hide 2 older comments. griddedinterpolant expects points on a regular grid pretty much like interp2 - so that function seems unsuitable for your case. Note that calling interp2d with NaNs present in input values results in undefined behaviour. griddedInterpolant evaluates each page in the 3-D image at. You can see the equation that i have mentioned. pos = [x y z] ef = [e_x e_y e_z] The matrices are 1000x3 in size, and the positions are located in a half sphere (cartesian coordinates). Extrapolating Scattered Data Factors That Affect the Accuracy of Extrapolation. For example, "griddata" cannot interpolate points on the surface of a sphere, but it can interpolate points on a hemisphere that is properly oriented to satisfy. I haven't tried the inpaint_nans function yet, but will do so and see how it compares. Parameters: points 2-D ndarray of floats with shape (n, D), or length D tuple of 1-D ndarrays with shape (n,). I gave u one part of the code. The values it returns for. 1 Link griddedInterpolant -- if you do not pass in vector x and vector v (1D case) -- if you have 2 or more dimensions -- then the input coordinates must be in full gridded form, not individual samples. The points. griddata# scipy. Use griddedInterpolant to perform interpolation with gridded data. So NaN is the solution for plotting holes. Learn more about scatteredinterpolant, interp2, interpolation Curve Fitting Toolbox Dear reader, I am trying to interpolate scatter data as an input for my model. If you have points which are described by vectors, and you want to plot them you could always use a Delauny triangulation. You can evaluate F at a set of query points, such as. " Does this mean that the function discovered duplicate (x,y) grid points in my inputs, or that some adjacent z-points are duplicated? ScatteredInterpolant just does what it is told, having no idea that when you try to interpolate some point in that volume, it is creating meaningless gibberish as a result. 974 5333045. PCHIP 1-D monotonic cubic interpolation. Interpolant surface fits use the MATLAB ® function scatteredInterpolant function for none, linear, and nearest neighbor extrapolation, and the MATLAB function griddata for biharmonic extrapolation. The solutions take a long time to run. To plot the data, I use scatteredInterpolant, then create a meshgrid of the interpolated data. Use griddedInterpolant to perform interpolation with gridded data. Use griddedInterpolant to perform interpolation with gridded data. It is just presented as being v = F(x,y) because effectively that is what it is. I have two data sets of different sizes, one of which is a 15x3 matrix of latitude, longitude, and concentration data and the other of which is a 2550x3 matrix, also composed of latitude, longitude, and concentration data. My intention is to compare visually (overlap) these two different surfaces. The interpolation will change slightly however, because in Cartesian you pretend that the lines connecting the neighbors are straight, and in polar, they are curved (from a Cartesian viewpoint). Each point will lie in one simplex of the tessellation. Depending on the input coordiantes and the query coordinates, it is not uncommon for the. On the other hand, you indicate that you want to be able. I would have expected that the value of the interpoland at the center of the bottom left element is the mean. class scipy. We know that we have some. F = scatteredInterpolant (x_c,y_c,z_c); Walter Roberson on 9 Dec 2015. Use scatteredInterpolant to perform interpolation on a 2-D or 3-D data set of scattered data . ". You can evaluate F at a set of query points, such as (xq,yq) in 2-D, to produce interpolated values vq = F (xq,yq). Theme. 128 1682. My data: I have a tooth as in the upload, which is the result of. 000 417826. ) #. 5 x 0. I recently had the need to create a smoothed curve from a series of X/Y data points in a C# application. See the syntax, input arguments, properties, and usage examples of this function in MATLAB. Create a PDE model and include the geometry of the built-in function squareg. So you're sort of on the right track with meshgrid, though not diag. These, I believe, are the same streaks as seen with griddata or scatteredInterpolant, which uses a triangular mesh. Use griddedInterpolant to perform interpolation with gridded data. I have created a 2D contour map using a 25x19 matrix and was wondering how to interpolate the value at certain user-input x-y coordinates? Essentially, I want the user to enter coordinates that are either integer or decimal, and for the code to output the value at that corresponding location. Learn more about scatteredinterpolant, griddata, v, interpolation, 3d Hello, I have a question that has been asked a few times on different ways but I have not been able to understand it. It is possible to fit a single polynomial interpolant to data, with a degree one less than the number of data points. It performs "natural neighbor interpolation" of irregularly spaced data a regular grid, which you can then plot with contour, imshow or pcolor. Others have suggested extrapolation. scatteredInterpolant returns the interpolant F for the given data set. Besides splitting the creation of the object from the invocation for interpolation purposes, griddata simply does not. interpolate. 3 3. Interpolation (. scipy. thanks for you reply @image. Sign in to answer this question. scatteredInterpolant returns the interpolant F for the given data set. "scatteredInterpolant(P_ent_mod,D_ent_mod,E_s_mod)" Launch diagnostic report. I process the data:scatteredInterpolant Scattered data interpolation scatteredInterpolant performs interpolation on scattered data that resides in 2-D or 3-D space. My question is : can we speed up the scatteredinterpolant function by using it with parallel too. Over a given triangle, the interpolant is the linear. Use scatteredInterpolant instead. Sign in to answer this question. The relevant part of the code is added below. I would assume the meta data saved with the scatteredInterpolant is likely an internal command telling MatLab how to rebuild the data on import, as you suggest. (PCHIP stands for Piecewise Cubic Hermite Interpolating. The surface can be evaluated at any query. Can I define the iregular geometry of the map as queery points so that there would no contour lines outside the map?By default, scatteredInterpolant with 'linear' method does not do extrapolation. Numerical gradients, returned as arrays of the same size as F. Below is a plot of the original (uninterpolated) data with shading interp turned on using "surf" and "trisurf" plotting. I tried to us…There, you apply scatteredInterpolant in order to map your original data on a (equidistant) grid that is easy to plot. One approach would be to replace the NaN values with nearest-neighbor interpolates using scatteredInterpolant (or TriScatteredInterp in older MATLAB versions) before performing the filtering, then replacing those points again with NaN values afterward. I get the following warning from scatteredInterpolant. scatteredInterpolant () does not do any kind of surface fitting. I am able to calculate the Delaunay tetrahedrals using the TetGen library. It is straightforward to do so with numpy, scipy. Example of 2D interpolation in C++: I am looking for a function in Matlab that constructs a cubic interpolation function, Z = f(X, Y), for irregularly spaced data. The MATLAB language is designed to give optimum performance when your application is structured into functions that reside in files. In some cases you can have a set of x and y data where the values of x and/or y are repeated as Aristo was showing. 21 -40. I have a big matrix M(100*10) and N(100*100). The surface always passes through the data points defined by x and v. You can evaluate F at a set of query points, such as (xq,yq) in 2-D, to produce interpolated values vq = F (xq,yq). I was wondering if anyone would know any alternative function to scatteredInterpolant (if possible that can be implemented also in Python) so that it can be equivalent to the one I show below. If z is a vector value, consider using interpn. Thanks Walter, I appreciate the quick response. The sample data can form a grid, or can be scattered. This i have calculated using multivariate linear regression. interp2 is a wrapper for griddedInterpolant. I would like to ask if it is possible to save the interpolant generated by scatteredInterpolant or griddedInterpolant for future use, so I can load it in the workspace and avoid to. You specify x and y as key / control points with the corresponding z and g output points. 01) xi,yi = np. To fix this on a code level, you could switch to interpreted MATLAB code. However, before doing that, I created a mesh as a querry points. Namely, scatteredInterpolant only offers nearest, linear, and natural interpolation Methods. Ideally the interpolation object. Answered: Anton Semechko on 4 Jul 2018. > > Now I’m using OCTAVE and it seemes, that. Piecewise linear interpolant in N > 1 dimensions. if your data is already sorted in arrays, consider to use MathNet. Installing No build system. scatteredInterpolant takes a set of sample points and returns what is essentially a function handle that can take a new point and return an interpolated value. if got a three vectors of scattered x, y and z data. however, as scatteredInterpolant requires at least 2 dimensions for its indices, this doesn't work for 1d interpolation. Francesc Purroy on 12 Nov 2018. I am at a loss on how to continue, advice, and suggestions would be greatly appreciated. But without seeing the data, I am left with suggesting that POSSIBLY, one of those alternatives would be a better choice than the use of. F= scatteredInterpolant(x,y,zi); contourf(X,Y,F(X,Y),100, 'LineColor', 'none') which is taking almost 3-4 minutes to plot a heatmap. I am going to use scatteredInterpolant for interpolation of missing data. scatteredInterpolant uses linear extrapolation by default. Vector x contains the sample points, and v contains the corresponding values, v ( x ). griddedInterpolant returns the interpolant F for the given data set. scatteredInterpolant contains data and it behaves like an array—in MATLAB language, it is called a value object. The MATLAB language is designed to give optimum performance when your application is structured into functions that reside in files. I use this to calculate the effective strain rate, which looks reasonable, but when I take the gradient of this data it seems to be "catching" on all the edges of my grid. 6. eps= (235/fy)^ (1/2); % required for section classification. La interpolación en MATLAB ® se divide en técnicas para puntos. Parameters: pointsndarray of floats, shape (npoints, ndims); or Delaunay. scatteredInterpolant will. Interpolant surface fits use the MATLAB function scatteredInterpolant for the linear and nearest. problem with scatteredInterpolant: are there any limits? min (x) = 417740; max (x) = 417870; min (y) = 4177412; max (y)= 5333100; min (z)= 0; max (z) = 11054;. griddata (points, values, xi, method = 'linear', fill_value = nan, rescale = False) [source] # Interpolate unstructured D-D data. >> F = scatteredInterpolant(xdata, ydata, vals, 'natural' , 'none' );Have you seen the interp2 function?. See the syntax, input arguments, properties, and usage examples of this. % X1 X2 X3 X4 V. This. The results always pass through the original sampling of the function. La interpolación es una técnica que se utiliza para agregar nuevos puntos de datos dentro del rango de un conjunto de puntos de datos conocidos. scatteredInterpolant returns the interpolant F for the given data set. Its still not working. In such a case, with linear. The intention was to load up this new. It makes sense since it does not have enough points to interpolate properly/sensibly. % Section Classification Flange width to thickness ratio in compression. Clearly at this point you can add your own cleaning method, but if you are using this class chances. Q&A for work. Currently. The data set is large (110k nodes). Unfortunately MATLAB does not have any scattered interpolation routines that work in more than 3 dimensions, but gridded interpolation can. You should have a look whether your ellipse is matching the used grid for plotting. 您可以使用插值来填充缺失的数据、对现有数据进行平滑处理以及进行预测等。. The sample points X must have size NPTS-by-2 in 2-D or NPTS-by-3 in 3-D, where NPTS is the number of points. 974 5333045. Edited: Alexander Schwarzwälder on 23 Nov 2020. If your data can always be viewed as gridded data with missing elements, and the idea is to to fill the missing data with something, you could try this FEX fileNo you can use griddata and scatteredInterpolant. [X,Y]=meshgrid (x,y). You can use scatteredInterpolant to do this for you. You can evaluate F at a set of query points, such as (xq,yq) in 2-D, to produce interpolated values vq = F (xq,yq). The first case is easy to fix: [x,ix] = sort (x); y = y (ix); xq = sort (xq); yq = interp1 (x,y,xq); There are a couple ways to deal with the second case, depending on your application. 24 25. Interpolating scattered data using scatteredInterpolant. griddata -- always x, y, v (scattered 2d input coordinates plus corresponding outputs). Besides splitting the creation of the object from the invocation for interpolation purposes, griddata simply does not. scattered data consist of other data arrangements. At first i have read the data from an excell sheet(. We also interpolate between multiple solutions, which leads to even higher. Quick summary. You can evaluate F at a set of query points, such as (xq,yq) in 2-D, to produce interpolated values vq = F (xq,yq). Vq = interp2 ( ___,method) specifies an alternative interpolation method: 'linear' , 'nearest', 'cubic' , 'makima', or 'spline'. interpolate) are the same (both involve Delaunay triangulation of data in a grid followed by linear. You can specify a point outside the convex hull of your scattered data and will still not get a NaN. 0884. You can evaluate F at a set of query points, such as (xq,yq) in 2-D, to produce interpolated values vq = F (xq,yq). So I did, and found to be twice slower for a 512 by 512 matrix. It faithfully preserves input data values and produces a continuous a surface as its output. This mesh is equivalent to the bounding box for Alaska. X and Y must be monotonic, and have the same format ("plaid") as. Use griddedInterpolant to perform interpolation with gridded data. For example, I have the following non-gridded data points, known v = F(x,y),. But if you look inside interp3, it seems like it re-packages your data into a griddedInterpolant object and then uses it. 5GB) array exceeds maximum array size preference. 创建对象 语法. qhull is a third-party library; if I recall correctly it is from a UK university. I have a set of data with a value at some x,y,z coordinates. Evaluate the interpolant at the query points with the syntax F ( {xq,yq}). I would like to simulate scatteredInterpolant by constructing delaunay triangulation of X, computing the barycentric weights of Q, and use the above results to interpolate the function values. 04 and I would like to find what z value is. A MATLAB Function does not support code generation (and rightly so) such that a transfer function may be implemented inside it. My variables are x, y, z coordinates (3D space) and the respective values for each combination of x,y,z. The only difference in my code was just using:Answered: Cris LaPierre on 5 Aug 2021. 2-D array of data point coordinates, or a precomputed Delaunay triangulation. To avoid confusion, you can hide warning messages during execution by changing their states from 'on' to 'off'. I want to specify that scatteredInterpolant worked well in a script but not in the simulink function block. 208 1744. and save to a mat file on disk. Based on your csv file, I am assuming you are trying to interpolate 2D data. I used scatteredInterpolant function to interpolate probability values all around the map. To use griddedinterpolant or interp2, a meshgrid or ndgrid needs to be created using lat, lon values.