John Arban Lewis johnarban

## index.html
<head>
  <meta charset="utf-8" />
  <meta name="viewport" content="width=device-width,initial-scale=1" />
  <title>WWT Asteroid Orbit (Hosted Model)</title>
</head>

<body>
  <div id="wwtcanvas"></div>

  <div id="ui">

## Testing Vue Reactivity with Classes.vue

<script setup lang="ts">
import { ref, type Ref, reactive } from 'vue'
class Person {
  name: string
  age: number
  called = 0;
  constructor(name: string, age: number) {
    this.name = name
    this.age = age

## App.vue
<script setup>
import { ref } from 'vue'
import { useTest } from './test';

const notRefValue = 3
const refValue = ref(7)

const test = useTest(notRefValue, refValue)


## binaryajax.js
/*
 * Binary Ajax 0.1.10
 * Copyright (c) 2008 Jacob Seidelin, cupboy@gmail.com, http://blog.nihilogic.dk/
 * Licensed under the MPL License [http://www.nihilogic.dk/licenses/mpl-license.txt]
 */


var BinaryFile = function(strData, iDataOffset, iDataLength) {
        var data = strData;
        var dataOffset = iDataOffset || 0;

## view_nested.py
from pandas import DataFrame, concat, Series, isna
import json


def expand_subdict(df_col):
    """
    Expand a column of dictionaries into a Series
    Drop any all nan columns
    """
    # drop empty columns that are sometimes created.

## numba_absolute_minimum.ipynb

      
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                johnarban
                / numba_absolute_minimum.ipynb
            
            
              Created
              September 14, 2021 04:26
                — forked from safijari/numba_absolute_minimum.ipynb
            
          
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## WCSAxes Example.ipynb

      
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                johnarban
                / WCSAxes Example.ipynb
            
            
              Last active
              June 17, 2021 14:14
            
              
                Worked example plotting data with WCS defined axes
              
          
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## simple cutoff_filter.py
# adapted from > https://scipy-lectures.org/intro/scipy/auto_examples/plot_fftpack.html

import numpy as np
from scipy import fftpack
from matplotlib import pyplot as plt


def signal_gen(time_step):
  # generate a random signal with low and high frequency components
    np.random.seed(1234)

## IronFall.py
#this should work with a vanilla python install
from math import sqrt, acos

#equation from https://aapt.scitation.org/doi/pdf/10.1119/1.2344089
# derivation is included in their appendix. it is not openly available

# let's work in kg - m - s, SI units
G = 6.674e-11 # 6.674e-11 in SI units
M = 100 # kg
dens = 7847 # kg/m^3

## montyhall.py
# Simulate the monty hall probelm
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
#import tqdm # gives you a progress bar using tqdm.trange(n)


def monty_hall(switch = None):
    # get some doors
    door = np.array([0,1,2])
	<head>
	<meta charset="utf-8" />
	<meta name="viewport" content="width=device-width,initial-scale=1" />
	<title>WWT Asteroid Orbit (Hosted Model)</title>
	</head>

	<body>
	<div id="wwtcanvas"></div>

	<div id="ui">

	<script setup lang="ts">
	import { ref, type Ref, reactive } from 'vue'
	class Person {
	name: string
	age: number
	called = 0;
	constructor(name: string, age: number) {
	this.name = name
	this.age = age
	<script setup>
	import { ref } from 'vue'
	import { useTest } from './test';

	const notRefValue = 3
	const refValue = ref(7)

	const test = useTest(notRefValue, refValue)
	/*
	* Binary Ajax 0.1.10
	* Copyright (c) 2008 Jacob Seidelin, cupboy@gmail.com, http://blog.nihilogic.dk/
	* Licensed under the MPL License [http://www.nihilogic.dk/licenses/mpl-license.txt]
	*/


	var BinaryFile = function(strData, iDataOffset, iDataLength) {
	var data = strData;
	var dataOffset = iDataOffset \|\| 0;
	from pandas import DataFrame, concat, Series, isna
	import json


	def expand_subdict(df_col):
	"""
	Expand a column of dictionaries into a Series
	Drop any all nan columns
	"""
	# drop empty columns that are sometimes created.
	# adapted from > https://scipy-lectures.org/intro/scipy/auto_examples/plot_fftpack.html

	import numpy as np
	from scipy import fftpack
	from matplotlib import pyplot as plt


	def signal_gen(time_step):
	# generate a random signal with low and high frequency components
	np.random.seed(1234)
	#this should work with a vanilla python install
	from math import sqrt, acos

	#equation from https://aapt.scitation.org/doi/pdf/10.1119/1.2344089
	# derivation is included in their appendix. it is not openly available

	# let's work in kg - m - s, SI units
	G = 6.674e-11 # 6.674e-11 in SI units
	M = 100 # kg
	dens = 7847 # kg/m^3
	# Simulate the monty hall probelm
	import numpy as np
	import matplotlib as mpl
	import matplotlib.pyplot as plt
	#import tqdm # gives you a progress bar using tqdm.trange(n)


	def monty_hall(switch = None):
	# get some doors
	door = np.array([0,1,2])