There are two problems here. Show
Table of Contents
First, you swapped the order of arguments in Second, python indexing starts with 0, while MATLAB indexing
starts with So the correct function call in Python is MATLAB:
Python:
Main Content Differences and approximate derivatives SyntaxDescriptionexample
example
example
Examplescollapse all Differences Between Vector ElementsCreate a vector, then compute the differences between the elements. X = [1 1 2 3 5 8 13 21]; Y = diff(X) Note that Differences Between Matrix RowsCreate a 3-by-3 matrix, then compute the first difference between the rows. X = [1 1 1; 5 5 5; 25 25 25]; Y = diff(X)
Multiple DifferencesCreate a vector and compute the second-order difference between the elements. X = [0 5 15 30 50 75 105]; Y = diff(X,2) Differences Between Matrix ColumnsCreate a 3-by-3 matrix, then compute the first-order difference between the columns. X = [1 3 5;7 11 13;17 19 23]; Y = diff(X,1,2)
Approximate Derivatives with diffUse the For example, the first derivative of h = 0.001; % step size X = -pi:h:pi; % domain f = sin(X); % range Y = diff(f)/h; % first derivative Z = diff(Y)/h; % second derivative plot(X(:,1:length(Y)),Y,'r',X,f,'b', X(:,1:length(Z)),Z,'k') In this plot the blue line corresponds to the original function, Differences Between Datetime ValuesCreate a sequence of equally-spaced datetime values, and find the time differences between them. t1 = datetime('now');
t2 = t1 + minutes(5);
t = t1:minutes(1.5):t2 t = 1x4 datetime
Columns 1 through 3
26-Feb-2022 12:12:08 26-Feb-2022 12:13:38 26-Feb-2022 12:15:08
Column 4
26-Feb-2022 12:16:38
dt = 1x3 duration
00:01:30 00:01:30 00:01:30
Input Argumentscollapse all X — Input array vector | matrix | multidimensional arrayInput array,
specified as a vector, matrix, or multidimensional array. Complex Number Support: Yes n — Difference order positive integer scalar | []Difference order, specified as a positive integer scalar or It is possible to specify Data Types: dim — Dimension to operate along positive integer scalarDimension to operate along, specified as a positive integer scalar. If you do not specify the dimension, then the default is the first array dimension of size greater than 1. Consider a two-dimensional p-by-m input array,
Data Types: Output Argumentscollapse all Y — Difference array scalar | vector | matrix | multidimensional arrayDifference array, returned as a scalar, vector, matrix, or multidimensional array. If Extended CapabilitiesTall Arrays Calculate with arrays that have more rows than fit in memory.This function supports tall arrays with the limitations: You must use the three-input syntax For more information, see Tall Arrays. C/C++ Code Generation Generate C and C++ code using MATLAB® Coder™.Usage notes and limitations:
Thread-Based Environment Run code in the background using MATLAB® backgroundPool or accelerate code with Parallel Computing Toolbox™ ThreadPool.This function fully supports thread-based environments. For more information, see Run MATLAB Functions in Thread-Based Environment. GPU Arrays Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.This function fully supports GPU arrays. For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox). Distributed Arrays Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.This function fully supports distributed arrays. For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox). Version HistoryIntroduced before R2006a expand all R2022a: Improved performance with large number of elementsThe For example, this code constructs a double with 2.5 x 107 elements and calculates differences between adjacent elements. It runs approximately 2.4x faster than in the previous release: function timingDiff rng default N = 5000; A = rand(N); tic for k = 1:40 D = diff(A); end toc end The approximate execution times are: R2021b: 2.43 s R2022a: 1.00 s The code was timed on a Windows® 10, Intel® Xeon® CPU E5-1650 v4 @ 3.60 GHz test system by calling the
Apa itu Len di Python?Kita masuk dalam pembahasan yang pertama yaitu fungsi Len(). Fungsi len() digunakan untuk mengidentifikasi dan mengetahui seberapa panjang jumlah item atau anggota pada suatu objek.
Apa itu tipe data set Python?Apa itu tipe data set? Set dalam bahasa pemrograman python adalah tipe data kolektif yang digunakan untuk menyimpan banyak nilai dalam satu variabel dengan ketentuan: nilai anggota yang disimpan harus unik (tidak duplikat) nilai anggota yang sudah dimasukkan tidak bisa diubah lagi.
Apa itu tuple pada Python?Sebuah tupel adalah urutan objek Python yang tidak berubah. Tupel adalah urutan, seperti daftar. Perbedaan utama antara tupel dan daftarnya adalah bahwa tupel tidak dapat diubah tidak seperti List Python. Tupel menggunakan tanda kurung, sedangkan List Python menggunakan tanda kurung siku.
Apa fungsi dari set?Fungsi set() menerima satu buah parameter, yaitu: iterable – sequence (string, tuple, list), maupun collection(set, dictionary, dan sebagainya) atau juga iterator yang akan diubah menjadi set.
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