Menu
I am new to numpy and I am implementing clustering with random forest in python. My question is:
How could I find the index of the exact row in an array? For example
[[ 0. 5. 2.] [ 0. 0. 3.] [ 0. 0. 0.]] and I look for [0. 0. 3.] and get as result 1(the index of the second row).
Any suggestion? Follows the code (not working...)
for index, element in enumerate(leaf_node.x): for index_second_element, element_two in enumerate(leaf_node.x): if (index <= index_second_element): index_row = np.where(X == element) index_column = np.where(X == element_two) self.similarity_matrix[index_row][index_column] += 1 
775
In the NumPy with the help of shape() function, we can find the number of rows and columns. In this function, we pass a matrix and it will return row and column number of the matrix. Return: The number of rows and columns.
We can use [][] operator to select an element from Numpy Array i.e. Example 1: Select the element at row index 1 and column index 2. Or we can pass the comma separated list of indices representing row index & column index too i.e.
Why not simply do something like this?
>>> a array([[ 0., 5., 2.], [ 0., 0., 3.], [ 0., 0., 0.]]) >>> b array([ 0., 0., 3.]) >>> a==b array([[ True, False, False], [ True, True, True], [ True, True, False]], dtype=bool) >>> np.all(a==b,axis=1) array([False, True, False], dtype=bool) >>> np.where(np.all(a==b,axis=1)) (array([1]),) If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With
