{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Benchmarking metrics" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this tutorial we will introduce the `galpynostatic.metric` module for benchmarking fast charging electrode materials.\n", "\n", "First, we will import the libraries that we will use throughout this example." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import galpynostatic as gp\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import pandas as pd" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "and load the experimental dataset collected and used by [Xia et al.](https://doi.org/10.1021/acsnano.2c03922)" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "dataset = pd.read_csv(\"../_static/benchmarking_experimental_data.csv\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Data cleaning\n", "\n", "First we will clean the experimental dataset to have it in a proper form for the metric module." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
| \n", " | Material | \n", "particle_size_micro | \n", "dcoeff_cm2s | \n", "
|---|---|---|---|
| 0 | \n", "Ternary | \n", "10 | \n", "7.8e-11 | \n", "
| 1 | \n", "Ternary | \n", "8 | \n", "1.7e-11 to 6.5e-9 | \n", "
| 2 | \n", "Ternary | \n", "2-5 | \n", "1e-11 to 3e-11 | \n", "
| 3 | \n", "LCO | \n", "5-10 | \n", "1e-11 to 1e-7 | \n", "
| 4 | \n", "LCO | \n", "NaN | \n", "1e-10 to 1.5e-9 | \n", "