![]() ![]() it does not verify that a couple of values of 'a' exists in 'b' but only if values of each column of 'a' exist in each columns of 'b'. Ps : the solution proposed here Python version of ismember with 'rows' and index does not correspond to the true matlab's ismember function since it does not work element by element i.e. Multidimensional arrays are an extension of 2-D matrices and use additional subscripts for indexing. ismembertol scales the tol input using the maximum absolute values in the input arrays A and B.Then ismembertol uses the resulting scaled comparison tolerance to determine which elements in A are also a member of B. Each element is defined by two subscripts, the row index and the column index. Comparison tolerance, specified as a positive real scalar. In a matrix, the two dimensions are represented by rows and columns. R2013a onward change the 'highest' to 'lowest. A multidimensional array in MATLAB is an array with more than two dimensions. For those elements of A that do not occur in S, ismember returns 0. ) returns an array loc containing the highest index in S for each element in A that is a member of S. The cell arrays are not the same size (can be in the range of thousands) and each entry can be be a different length (ranging from length 1 to length >1000). No, check the R2009a ismember() documentation: Theme. Why python does not have what I would think to be such an important function ? I use it countless times in my calculations. Accepted Answer: Jan I have two large cell-arrays (X and Y) where each field is a two dimensional array representing pixel positions. I guess it is because Matlab uses a built-in mex function. Moreover, even when the function works (because arrays are small enough), it is about a 100times slower than in Matlab. when doing np.all(a = b, axis=2).any(axis=1) it needs to create an array of size (ma,mb,2) and it is too big. Then it calls an internal binary search routine passing in A and sorted B average complexity of that is probably length (A) log2 (length (B)). ![]() If necessary it sorts it, which does not apply in your described case. The ismember module ( ) crashes because at some point i.e. The ismember code first checks the array with issorted (B), which is O (length (B)). I can't find an efficient way to conduct Matlab's "ismember(a,b,'rows')" with Python where a and b are arrays of size (ma,2) and (mb,2) respectively and m is the number of couples.
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