{ "cells": [ { "cell_type": "code", "execution_count": 10, "id": "a314a8ac", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[0. , 0. ],\n", " [0.26726124, 0.56694671]])" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn.metrics.pairwise import cosine_similarity\n", "import numpy as np\n", "X = [[0, 0, 0], [1, 2, 3]]\n", "Y = [[1, 0, 0], [1, 1, 0]]\n", "cosine_similarity(X, Y)" ] }, { "cell_type": "code", "execution_count": 11, "id": "4b560c4f", "metadata": {}, "outputs": [], "source": [ "sims = cosine_similarity(X)" ] }, { "cell_type": "code", "execution_count": null, "id": "d8d5d17a", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 34, "id": "a1098a5a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(3, 3)\n", "(array([0, 0, 1]), array([1, 2, 2]))\n", "(3,)\n", "mean sim: -0.3333333333333334 std: 0.47140452079103173\n" ] } ], "source": [ "# X = np.array([\n", "# [0, 0, 0], \n", "# [-1, 100, -1000],\n", "# [-1, -2, -4]\n", "# ]\n", "# )\n", "\n", "X = np.array([\n", " [0, 0, 0], \n", " [1,1,1],\n", " [-1, -1, -1]\n", " ]\n", " )\n", "print(X.shape)\n", "sims = cosine_similarity(X)\n", "\n", "triu_idxs = np.triu_indices_from(sims, k=1)\n", "print(triu_idxs)\n", "dist_vals = sims[triu_idxs]\n", "print(dist_vals.shape)\n", "print(\"mean sim:\", dist_vals.mean(), \"std:\", dist_vals.std())" ] }, { "cell_type": "code", "execution_count": 27, "id": "2dacad18", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([0.])" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dist_vals" ] }, { "cell_type": "code", "execution_count": null, "id": "76d25e07", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "venv", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.12" } }, "nbformat": 4, "nbformat_minor": 5 }