From 8c2a961a3a82c5b7f54137d8e8867e0c20e3fbae Mon Sep 17 00:00:00 2001 From: Christian Kolset Date: Fri, 9 May 2025 12:35:08 -0600 Subject: Starting tutortial with 1. Theory 2. Engineering and 3. Code --- tutorials/module_3/numerical_differentiation.ipynb | 10 ++++++++++ 1 file changed, 10 insertions(+) (limited to 'tutorials') diff --git a/tutorials/module_3/numerical_differentiation.ipynb b/tutorials/module_3/numerical_differentiation.ipynb index f8091d0..a24a46f 100644 --- a/tutorials/module_3/numerical_differentiation.ipynb +++ b/tutorials/module_3/numerical_differentiation.ipynb @@ -6,6 +6,15 @@ "metadata": {}, "source": [ "# Numerical Differentiation\n", + "WHAT IS IT?\n", + "Numerical Differentiation is a way we can use \n", + "\n", + "WHAT IS A DERIVATIVE?\n", + "\n", + "\n", + "HOW CAN WE CALCULATE IT?\n", + "\n", + "\n", "We can find the derivate of both tabulated data and a continuous function using a finite difference method, which calculates rise over run of a function. To do this, we must first initalize our independant variable. Let's call this domain $x$ to be a vector such that $\\vec{x}$ =\n", "$\\pmatrix{x_0, x_1, x_2, ...}$. This domain is also known as the **numerical grid**, is either determined by our data (often time) or can be set by us if it's a continuous function. The **step size** is defined as the spacing between adjacent points on the grid ($h = x_{i+1} - x_i$). Next, let's introduce the dependent variable $y$, this can be any function of $x$.\n", "\n", @@ -41,6 +50,7 @@ "id": "9b79e5ba-4b71-4aeb-b3fb-878c2d728f7e", "metadata": {}, "source": [ + "---\n", "## Forward Difference\n", "The forward difference method takes the point at which we want to find the derivative and the point *forwards* on the grid.\n", "\n", -- cgit v1.2.3