{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# TriScale - The experiment design and analysis framework" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This notebook presents the _TriScale_ framework. _TriScale_ is composed of four modules, called\n", "* network profiling\n", "* experimental design\n", "* preprocessing\n", "* analysis.\n", "\n", "These modules support the experimenter at different stages of experimental campaigns: **before** (_network profiling_ and _experimental design_), **during** (_preprocessing_) and **after** (_analysis_).\n", "This notebook describe in details the functionalities provided by each of these modules, using a real experimental campain as illustration.\n", "\n", "\n", "We start by importing the _etalon_ module, which contains the implementation of the entire framework." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# Standard library imports\n", "from pathlib import Path\n", "\n", "import numpy as np\n", "\n", "import triscale\n", "\n", "%load_ext autoreload\n", "%autoreload 2" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1.16.4\n" ] } ], "source": [ "print(np.__version__)\n", "np.arange?" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ " \n", " " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "mode": "markers+lines", "name": "Sample Autocor. Coefficients", "showlegend": true, "type": "scatter", "x": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13 ], "y": [ 1, -0.08917225579731927, -0.2231801548716142, -0.08249100728746618, -0.07844506411518966, -0.09089719800553557, -0.09778514932567615, 0.36872650751034036, 0.03162739589704251, -0.11204017954326351, -0.07893974105134399, -0.07525951879917486, 0.01670747509511025, 0.011148890294090209 ] }, { "fill": "toself", "fillcolor": "rgba(0,100,80,0.2)", "hoverinfo": "skip", "line": { "color": "rgba(0,100,80,0)", "width": 4 }, "name": "95% CI on i.i.d. test", "showlegend": true, "type": "scatter", "x": [ 0, 14, 14, 0 ], "y": [ 0.5238320341483518, 0.5238320341483518, -0.5238320341483518, -0.5238320341483518 ] } ], "layout": { "title": { "text": "Autocorrelation" }, "xaxis": { "title": { "text": "Lag" } } } }, "text/html": [ "