diff --git a/examples/07_data_management.ipynb b/examples/07_data_management.ipynb new file mode 100644 index 00000000..d317456a --- /dev/null +++ b/examples/07_data_management.ipynb @@ -0,0 +1,554 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Data management" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import pyerrors as pe" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Data has been written using pyerrors 2.0.0.\n", + "Format version 0.1\n", + "Written by fjosw on 2022-01-06 11:11:19 +0100 on host XPS139305, Linux-5.11.0-44-generic-x86_64-with-glibc2.29\n", + "\n", + "Description: Test data for the correlator example\n" + ] + } + ], + "source": [ + "correlator_data = pe.input.json.load_json(\"./data/correlator_test\")\n", + "my_correlator = pe.Corr(correlator_data)\n", + "my_correlator.gamma_method()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "import autograd.numpy as anp\n", + "def func_exp(a, x):\n", + " return a[1] * anp.exp(-a[0] * x)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "rows = []\n", + "for t_start in range(12, 17):\n", + " for t_stop in range(30, 35):\n", + " fr = my_correlator.fit(func_exp, [t_start, t_stop], silent=True)\n", + " fr.gamma_method()\n", + " row = {\"t_start\": t_start,\n", + " \"t_stop\": t_stop,\n", + " \"datapoints\": t_stop - t_start + 1,\n", + " \"chisquare_by_dof\": fr.chisquare_by_dof,\n", + " \"mass\": fr[0]}\n", + " rows.append(row)\n", + "my_df = pd.DataFrame(rows)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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