Take two matrices, arr1, arr2 of size mxn and nxp respectively. I'm trying to find the cosine distance of their respected rows as a mxp matrix. Essentially I want to take the the pairwise dot product of the rows, then divide by the outer product of the norms of each rows.

import numpy as np def cosine_distance(arr1, arr2): numerator = np.dot(arr1, arr2.T) denominator = np.outer( np.sqrt(np.square(arr1).sum(1)), np.sqrt(np.square(arr2).sum(1))) return np.nan_to_num(np.divide(numerator, denominator)) 

I Think this should be returning an mxn matrix with entries in [-1.0, 1.0] but for some reason I'm getting values out of that interval. I'm thinking that my one of these numpy functions is doing something other than what I think it does.

Take two matrices, arr1, arr2 of size mxn and pxn respectively. I'm trying to find the cosine distance of their respected rows as a mxp matrix. Essentially I want to take the the pairwise dot product of the rows, then divide by the outer product of the norms of each rows.

import numpy as np def cosine_distance(arr1, arr2): numerator = np.dot(arr1, arr2.T) denominator = np.outer( np.sqrt(np.square(arr1).sum(1)), np.sqrt(np.square(arr2).sum(1))) return np.nan_to_num(np.divide(numerator, denominator)) 

I Think this should be returning an mxn matrix with entries in [-1.0, 1.0] but for some reason I'm getting values out of that interval. I'm thinking that my one of these numpy functions is doing something other than what I think it does.

Take two matrices, arr1, arr2 of size mxn and nxp respectively. I'm trying to find the cosine distance of their respected rows as a mxp matrix.

import numpy as np def cosine_distance(arr1, arr2): numerator = np.dot(arr1, arr2.T) denominator = np.outer( np.sqrt(np.square(arr1).sum(1)), np.sqrt(np.square(arr2).sum(1))) return np.nan_to_num(np.divide(numerator, denominator)) 

I Think this should be returning an mxn matrix with entries in [-1.0, 1.0] but for some reason I'm getting values out of that interval. I'm thinking that my one of these numpy functions is doing something other than what I think it does.

Take two matrices, arr1, arr2 of size mxn and nxp respectively. I'm trying to find the cosine distance of their respected rows as a mxp matrix. Essentially I want to take the the pairwise dot product of the rows, then divide by the outer product of the norms of each rows.

import numpy as np def cosine_distance(arr1, arr2): numerator = np.dot(arr1, arr2.T) denominator = np.outer( np.sqrt(np.square(arr1).sum(1)), np.sqrt(np.square(arr2).sum(1))) return np.nan_to_num(np.divide(numerator, denominator)) 

I Think this should be returning an mxn matrix with entries in [-1.0, 1.0] but for some reason I'm getting values out of that interval. I'm thinking that my one of these numpy functions is doing something other than what I think it does.