{ "cells": [ { "cell_type": "markdown", "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "source": [ "# MatRepr NumPy\n", "\n", "Compare the native NumPy repr with MatRepr's formatting." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2023-09-12T06:17:06.024081Z", "start_time": "2023-09-12T06:17:05.936502Z" }, "collapsed": false, "jupyter": { "outputs_hidden": false } }, "outputs": [], "source": [ "import numpy as np\n", "np.random.seed(123)\n", "\n", "# so matrepr can be imported from the source tree.\n", "import sys\n", "sys.path.insert(0, '..')\n", "\n", "from matrepr import mdisplay, mprint" ] }, { "cell_type": "markdown", "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "source": [ "### 1D vector" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "ExecuteTime": { "end_time": "2023-09-12T06:17:06.050918Z", "start_time": "2023-09-12T06:17:06.030799Z" }, "collapsed": false, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33\n", " 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49]\n" ] } ], "source": [ "v1 = np.arange(10, 50)\n", "print(v1)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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