The ⊗ icon I use on tommyogden.com, made in D3.
x y c | |
15.55 28.65 2 | |
14.9 27.55 2 | |
14.45 28.35 2 | |
14.15 28.8 2 | |
13.75 28.05 2 | |
13.35 28.45 2 | |
13 29.15 2 | |
13.45 27.5 2 | |
13.6 26.5 2 |
x y c | |
0.85 17.45 2 | |
0.75 15.6 2 | |
3.3 15.45 2 | |
5.25 14.2 2 | |
4.9 15.65 2 | |
5.35 15.85 2 | |
5.1 17.9 2 | |
4.6 18.25 2 | |
4.05 18.75 2 |
0.85 17.45 2 | |
0.75 15.6 2 | |
3.3 15.45 2 | |
5.25 14.2 2 | |
4.9 15.65 2 | |
5.35 15.85 2 | |
5.1 17.9 2 | |
4.6 18.25 2 | |
4.05 18.75 2 | |
3.4 19.7 2 |
# ! python | |
# coding: utf-8 | |
import os | |
import argparse | |
import glob | |
import nbformat | |
from nbconvert.preprocessors import ExecutePreprocessor | |
from nbconvert.preprocessors.execute import CellExecutionError |
height: 944 | |
border: no |
Monte Carlo integration of the function
We sample
$$ A(x,y) = \begin{cases} 1 & \text{if} ~ y \leq f(x) \
Plots the first ten Hermite polynomials (physicists' definition), defined using the recursion relation.
Fits a straight line to data using the Least Squares method.
"Least squares" means that the overall solution minimizes the sum of the squares of the errors made in the results of every single equation.
Least squares function by Ben van Dyke.
A set of 100 points are given a new uniform random distribution every 5 seconds.