#Matlab return index of nonzero elements how to
If someone know how to do this much more efficiently it would be greatly appreciated. Test_matrix=1īackground: In my code, these two lines take 75% of the time for a 4000x4000 matrix whereas the ensuing topological sort and DP algorithm take only the rest of the quarter. I don't necessarily need to use these types if a faster option exists.įor timing purposes, the following matrix is a good representative: test_matrix = np.zeros(shape=(4096,4096),dtype=np.float32) I was wondering whether this might be doable with some sort of sparse matrix (CSR, CSC, COO etc.) from scipy.sparse but I am unfamiliar with them and have not got that working. i,j find (X) returns the row and column indices of the nonzero entries in the matrix X. If none is found, find returns an empty matrix. (The lists are called preds and descs because they refer to the predecessors and descendants in a DAG when the matrix is interpreted as an adjacency matrix but this is not essential to the question.) Description k find (X) returns the indices of the array X that point to nonzero elements. nonzero() for v in range(matrix.shape)]Įxample input: matrix = np.array(,])Įxample output preds = ), array(), array(), array(, dtype=int64)]ĭescs =, dtype=int64), array(), array(), array()] nonzero() for v in range(matrix.shape)]ĭescs =. The following is a working piece of code: preds =. This explains the algorithm.I am looking for the fastest way to obtain a list of the nonzero indices of a 2D array per row and per column. We can again typecast it to a list and print the new list. NumPy provides us with a nonzero() method which returns a tuple of arrays containing indices of the nonzero elements. Then we convert the given list into a numpy array as shown below. We can also access non-zero elements of a list using numpy. Li_new = Īs you can see, the program returns indices for the non-zero elements. We are also using list comprehension to keep it short. If you don’t know about the enumerate() method, do give it a read: Enumerate() Method in Python In this method, we are using the enumerate() method to convert the list into iterable. at 1:49 s zeros (size (x1)) for i2:length (x1) if (x1 (i-1)0) s (i) 1 + s (i-1) end end display (S) for a vector x1 which has a max chain of 72 but I dont know how to find the max chain and return its first value, so i know where to trim. This is a shorthand implementation of the above algorithm. Using enumerate() and list comprehensionĪnother way to find the indices of the non-zero elements is the method followed in the given example program. li = Īs it’s clear from the output, the list has non-zero values at indexes 0, 2, 3 and 5. We have done this implementation in the following program. Well, if we want to find the index of non-zero elements of a list, we can use a for loop to iterate the list and store the index values in a different list. If astuple is True, one 1-D tensor for each dimension, containing the indices of each nonzero element along that dimension. Finding indices of non-zero elements in Matlab matrix Ask Question Asked 9 years, 3 months ago Modified 9 years, 3 months ago Viewed 4k times 2 I have a matrix like A 0 1 1 0 0 0 1 1 0 For this, I wish to know indices of 1 's in such a manner that: For row 1, I need values of indices of column where its coming equal 1. We can use the following methods in such cases. Returns: If astuple is False, the output tensor containing indices.
There may be instances when we need to access only the non-zero elements in the list. When the input is a multidimensional array (N > 2), find returns col as a linear index over the N-1 trailing dimensions of X. Specify two outputs, row and col, to return the row and column subscripts of the nonzero elements. In this tutorial, we are going to see how to find indices of the non-zero elements in the Python list. Find the nonzero elements in a 4-by-2-by-3 array.
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