{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "5a38ed25", "metadata": { "ExecuteTime": { "end_time": "2023-04-01T08:27:04.086911Z", "start_time": "2023-04-01T08:27:00.587395Z" }, "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "not found\n" ] } ], "source": [ "import numpy as np\n", "import matplotlib\n", "import matplotlib.pyplot as plt\n", "from sklearn.neighbors import NearestNeighbors\n", "import joblib\n", "from tqdm import tqdm\n", "try:\n", " import csiborgtools\n", "except ModuleNotFoundError:\n", " print(\"not found\")\n", " import sys\n", " sys.path.append(\"../\")\n", " import csiborgtools\n", "\n", "\n", "%matplotlib notebook\n", "%load_ext autoreload\n", "%autoreload 2" ] }, { "cell_type": "code", "execution_count": 2, "id": "4218b673", "metadata": { "ExecuteTime": { "end_time": "2023-04-01T08:27:07.868868Z", "start_time": "2023-04-01T08:27:04.088778Z" } }, "outputs": [], "source": [ "cat1 = csiborgtools.read.HaloCatalogue(7444, min_mass=1e13, max_dist=155 / 0.705)\n", "cat2 = csiborgtools.read.HaloCatalogue(7468, min_mass=1e13, max_dist=155 / 0.705)" ] }, { "cell_type": "code", "execution_count": 3, "id": "5ff7a1b6", "metadata": { "ExecuteTime": { "end_time": "2023-04-01T08:27:07.923418Z", "start_time": "2023-04-01T08:27:07.870519Z" } }, "outputs": [ { "data": { "text/html": [ "
NearestNeighbors()In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
NearestNeighbors()