I started creating computer programs the Summer Semester of 2002 at Auburn University. I took a course named “Hand Held Software Development”. The course was taught by my research advisor Associate Professor Richard O. Chapman. I created a distributed chess playing client-server Internet system for human chess players. The program was built using the Palm Pilot’s Palm OS and its C language compiler. Later in circa 2006 I built a rule based and neural network chess program for a computer to play itself and for a human observer (voyeur). The language was Java. Then in 2015 I translated and enhanced my Java program by rewriting the code in C#. Below are pictures of one game.
The description of this alphabetic letter game is very facile. Given a word make as many other words as possible using the letters of the given initial word. But first before we enumerate the game solution, we need to refresh the reader’s memory of some elementary mathematics.
The binary number system also known as the base 2 number system is used by computers to perform arithmetic. The digits in the binary number system are 0 and 1. The numbers 0 to 15 in binary using only four binary digits are where ^ is the exponentiation operator (raising a number to a power) are:
0 0000
1 0001 2 ^ 0 = 1
2 0010 2 ^ 1 = 2
3 0011 2 ^ 1 + 2 ^ 0 = 2 + 1 = 3
4 0100 2 ^ 2 = 4
5 0101 2 ^ 2 + 2 ^ 0 = 4 + 1 = 5
6 0110 2 ^ 2 + 2 ^ 1 = 4 + 2 = 6
7 0111 2 ^ 2 + 2 ^ 1 + 2 ^ 0 = 4 + 2 + 1 = 7
8 1000 2 ^ 3 = 8
9 1001 2 ^ 3 + 2 ^ 0 = 8 + 1 = 9
10 1010 2 ^ 3 + 2 ^ 1 = 8 + 2 = 10
11 1011 2 ^ 3 + 2 ^ 1 + 2 ^ 0 = 8 + 2 + 1 = 11
12 1100 2 ^ 3 + 2 ^ 2 = 8 + 4 = 12
13 1101 2 ^ 3 + 2 ^ 2 + 2 ^ 0 = 8 + 4 + 1 = 13
14 1110 2 ^ 3 + 2 ^ 2 + 2 ^ 1 = 8 + 4 + 2 = 14
15 1111 2 ^ 3 + 2 ^ 2 + 2 ^ 1 + 2 ^ 0 = 8 + 4 + 2 + 1 = 15
An algorithm to convert a base 10 (decimal) number to base 2 (binary) number is given below:
Input n a base 10 number
Output b[0], b[1], b[2], … a finite binary string representing the decimal number
Integer i = 0
Do
Integer nmod2 = n mod 2
Integer ndiv2 = n / 2
b[i] = nmod2 + ‘0’
i = i + 1
n = ndiv2
While n > 0
The b[i] will be in reverse order. For example, convert 12 from decimal to using four binary digits:
12 mod 2 = 0
12 div 2 = 6
b[0] = ‘0’
i = 1
n = 6
6 mod 2 = 0
6 div 2 = 3
b[1] = ‘0’
i = 2
n = 3
3 mod 2 = 1
3 div 2 = 1
i = 3
b[2] = ‘1’
n = 1
1 mod 2 = 1
1 div 2 = 0
b[3] = ‘1’
n = 0
So, the reversed binary string of digits is “0011”. And after reversing the string we have 12 is represented by the binary digits “1100”.
Next, we need to define a power set and its binary representation. The index power set of 4 objects which has 2 ^ 4 = 16 entries is specified in the following table:
0 0000
1 0001
2 0010
3 0011
4 0100
5 0101
6 0110
7 0111
8 1000
9 1001
10 1010
11 1011
12 1100
13 1101
14 1110
15 1111
A permutation of the set of three indices is given by the following list:
012, 021, 102, 120, 201, 210
A permutation of n objects is a list of n! = n * (n – 1) * … * 2 * 1. A permutation of 4 objects has a list of 24 – 4-digit indices list since 4! = 4 * 3 * 2 * 1 = 24 has the table:
0123, 0132, 0213, 0231, 0312, 0321,
1023, 1032, 1203, 1230, 1320, 1302,
2013, 2031, 2103, 2130, 2301, 2310,
3012, 3021, 3102, 3120, 3201, 3210
Suppose our word is “lost” then we first find the power set:
1 0001 t
2 0010 s
3 0011 st ts
4 0100 o
5 0101 ot to
6 0110 os so
7 0111 ost ots sot sto tos tso
8 1000 l
9 1001 lt tl
10 1010 ls sl
11 1011 lst lts slt stl tsl tls
12 1100 lo ol
13 1101 lot lto olt otl tlo tol
14 1110 los lso slo sol osl ols
15 1111 lost lots slot etc.
Using a dictionary of 152,512 English words my program finds 16 hits for the letters of “lost”:
Dictionary Length: 152512
Word: lost
0 l
1 lo
2 lost
3 lot
4 lots
5 ls
6 o
7 s
8 slot
9 so
10 sol
11 sot
12 st
13 t
14 to
15 ts
Total letters and/or words 16
Next, we use “tear” as our word:
Dictionary Length: 152512
Word: tear
0 a
1 are
2 art
3 at
4 ate
5 e
6 ea
7 ear
8 eat
9 era
10 et
11 eta
12 r
13 rat
14 rate
15 re
16 rt
17 rte
18 t
19 tar
20 tare
21 tea
22 tear
23 tr
Total letters and/or words 24
Finally, we use the word “company”:
Dictionary Length: 152512
Word: company
0 a
1 ac
2 am
3 amp
4 an
5 any
6 c
7 ca
8 cam
9 camp
10 campy
11 can
12 canopy
13 cap
14 capo
15 capon
16 cay
17 cm
18 co
19 com
20 coma
21 comp
22 company
23 con
24 cony
25 cop
26 copay
27 copy
28 coy
29 cyan
30 m
31 ma
32 mac
33 man
34 many
35 map
36 may
37 mayo
38 mo
39 moan
40 mop
41 mp
42 my
43 myna
44 n
45 nap
46 nay
47 nm
48 no
49 o
50 om
51 on
52 op
53 p
54 pa
55 pan
56 pay
57 pm
58 pony
59 y
60 ya
61 yam
62 yap
63 yo
64 yon
Total letters and/or words 65
The C++ program's source code is given below:
// WordToWords.cpp : This file contains the 'main' function. Program execution begins and ends there.
//
#include "pch.h"
#include <algorithm>
#include <fstream>
#include <iomanip>
#include <iostream>
#include <string>
#include <vector>
using namespace std;
vector<string> dictWords;
bool ReadDictionaryFile()
{
fstream newfile;
newfile.open("C:\\Users\\james\\source\\repos\\WordToWords\\Dictionary.txt", ios::in);
if (newfile.is_open()) {
int index = 0, length = 128;
char cstr[128];
while (newfile.getline(cstr, length)) {
string str;
str.clear();
for (int i = 0; i < (int)strlen(cstr); i++)
str.push_back(cstr[i]);
dictWords.push_back(str);
}
newfile.close();
sort(dictWords.begin(), dictWords.end());
return true;
}
else
return false;
}
string ConvertBase2(char cstr[], int n, int len)
{
int count = 0;
string str, rev;
do
{
int nMod2 = n % 2;
int nDiv2 = n / 2;
str.push_back(nMod2 + '0');
n = nDiv2;
} while (n > 0);
n = str.size();
for (int i = n; i < len; i++)
str.push_back('0');
n = str.size();
for (int i = n - 1; i >= 0; i--)
if (str[i] == '1')
rev.push_back(cstr[i]);
return rev;
}
vector<string> PowerSet(char cstr[], int len)
{
vector<int> index;
vector<string> match;
for (long ps = 0; ps <= pow(2, len); ps++)
{
string str = ConvertBase2(cstr, ps, len);
int psf = 1;
for (int i = 2; i <= len; i++)
psf *= i;
for (int i = 0; i < psf; i++)
{
if (binary_search(dictWords.begin(), dictWords.end(), str))
{
if (!binary_search(match.begin(), match.end(), str))
{
match.push_back(str);
sort(match.begin(), match.end());
}
}
next_permutation(str.begin(), str.end());
}
sort(match.begin(), match.end());
}
return match;
}
int main()
{
bool done = false;
char cstr[128];
int len;
string str;
vector<int> index;
vector<string> match;
if (!ReadDictionaryFile())
return -1;
cout << "Dictionary Length: " << dictWords.size() << endl << endl;
cout << "Word: ";
cin >> cstr;
cout << endl;
len = strlen(cstr);
if (len != 0)
{
vector<string> match = PowerSet(cstr, len);
for (int i = 0; i < match.size(); i++)
{
cout << setprecision(3) << setw(3) << i << "\t";
cout << match[i] << endl;
}
cout << endl;
cout << "Total letters and/or words " << match.size() << endl;
cout << endl;
}
}
The Rosette motion of the perihelion precession of a massive object orbiting a black hole (Schwarzschild solution Einstein’s general relativity field equations is illustrated by the graphs below for varying values of eccentricity of the ellipsoidal orbit 0.00, 0.01, 0.02, 0.03, 0.04, and 0.05. The angular momentum constant is B = 1, and the mass is M = 10.
using System;
using System.Drawing;
using System.Windows.Forms;
namespace SchwarzschildOrbit
{
public partial class GraphForm : Form
{
private double B, B2, B4, M, M2, M3, epsilon;
public GraphForm(double B, double M, double epsilon)
{
InitializeComponent();
this.B = B;
this.M = M;
this.epsilon = epsilon;
B2 = B * B;
B4 = B2 * B2;
M2 = M * M;
M3 = M * M2;
panel1.Paint += Panel1_Paint;
}
private double u0(double phi)
{
return M * (1.0 + epsilon * Math.Cos(phi)) / B2;
}
private double u1(double phi)
{
return u0(phi) + 3.0 * M3 * (1.0 + epsilon * phi * Math.Sin(phi)
+ epsilon * epsilon * (0.5 - Math.Cos(2.0 * phi) / 6.0)) / B4;
}
private double X(double r, double phi)
{
return r * Math.Cos(phi);
}
private double Y(double r, double phi)
{
return r * Math.Sin(phi);
}
private void Maximums(out double maxR, out double maxPhi,
out double XMax, out double XMin, out double YMax, out double YMin)
{
double phi = 0.0, r = 0.0, XC = 0.0, YC = 0.0;
maxPhi = 0.0;
maxR = double.MinValue;
XMax = double.MinValue;
YMax = double.MinValue;
XMin = double.MaxValue;
YMin = double.MaxValue;
while (phi <= 8.0 * Math.PI)
{
r = 1.0 / u1(phi);
if (r > maxR)
{
maxR = r;
maxPhi = phi;
}
XC = X(r, phi);
if (XC > XMax)
XMax = XC;
YC = Y(r, phi);
if (YC > YMax)
YMax = YC;
if (XC < XMin)
XMin = XC;
if (YC < YMin)
YMin = YC;
phi += 0.001;
}
}
private void Minimums(out double minR, out double minPhi,
out double XMax, out double XMin, out double YMax, out double YMin)
{
double phi = 0.0, r = 0.0, XC = 0.0, YC = 0.0;
minPhi = 0.0;
minR = double.MaxValue;
XMax = double.MinValue;
YMax = double.MinValue;
XMin = double.MaxValue;
YMin = double.MaxValue;
while (phi <= 8.0 * Math.PI)
{
r = 1.0 / u1(phi);
if (r < minR)
{
minR = r;
minPhi = phi;
}
XC = X(r, phi);
if (XC > XMax)
XMax = XC;
YC = Y(r, phi);
if (YC > YMax)
YMax = YC;
if (XC < XMin)
XMin = XC;
if (YC < YMin)
YMin = YC;
phi += 0.001;
}
}
private void Panel1_Paint(object sender, PaintEventArgs e)
{
panel1.Size = ClientSize;
int width = ClientSize.Width;
int height = ClientSize.Height;
int deltaX = width / 6;
int deltaY = height / 6;
int minX = deltaX;
int maxX = 5 * deltaX;
int minY = deltaY;
int maxY = 5 * deltaY;
double maxPhi, minPhi, maxR, minR;
double XMax, XMin, YMax, YMin;
double UMax, UMin, VMax, VMin;
Maximums(out maxR, out maxPhi, out XMax, out XMin, out YMax, out YMin);
Minimums(out minR, out minPhi, out UMax, out UMin, out VMax, out VMin);
double slopeX = (maxX - minX) / (XMax - XMin);
double slopeY = (minY - maxY) / (YMax - YMin);
double interX = minX - slopeX * XMin;
double interY = maxY - slopeY * YMin;
double chi = 0.0, eta = 0.0, phi = 0.0, r = 0.0, x, y;
Graphics g = e.Graphics;
Pen bp = new Pen(Color.Black);
SolidBrush rb = new SolidBrush(Color.Red);
g.Clip = new Region(new Rectangle(minX, minY, maxX - minX + 1, maxY - minY + 1));
for (int i = 0; i < 5; i++)
g.DrawLine(bp, (i + 1) * deltaX, minY, (i + 1) * deltaX, maxY);
for (int i = 0; i < 5; i++)
g.DrawLine(bp, minX, (i + 1) * deltaY, maxX, (i + 1) * deltaY);
while (phi <= 8.0 * Math.PI)
{
r = 1.0 / u1(phi);
x = X(r, phi);
y = Y(r, phi);
chi = slopeX * x + interX;
eta = slopeY * y + interY;
g.FillEllipse(rb, (float)chi, (float)eta, 1, 1);
phi += 0.001;
}
}
}
}
I implemented a computerized version of a game similar to the board game Boggle. Given a jumble of letters find as many words as possible. Suppose we have the jumbled letters “sldfie” then my C++ program outputs:
Now suppose the scrambled letters are “nifrsmo”:
The program uses permutations and power sets. All permutations of the set of three numbers 1, 2, and 3 are:
123 132 213 231 312 321
The total number of permutations of n objects is n! where n! = n * (n – 1) * … * 2 * 1. So we have 3! = 3 * 2 * 1 = 6 and 4! = 4 * 3 * 2 * 1 = 24.
A power set of three objects can generated by using the binary representation of all binary numbers 0 to 2 * 2 * 2 – 1 = 8 – 1 = 7.
And my new code from the more efficient pseudo code found online:
New and Better CodeCommon Swap Function (Procedure)
Both implementations require n * (n – 1) / 2 comparisons which for an array of length 15 is 15 * 14 /2 = 15 * 7 = 105. The second implementation requires typically fewer calls to the swap function.
Selection Sort Test 15-Element Random ArraySelection Sort Test 15-Element Reverse Ordered ArraySelection Sort Test 15-Element Sorted Array
The first number after the unsorted array is the number of comparisons which is always 105 in our 15-element test cases. The second number is the tally of the swap function calls.
An anagram is also known as a word jumble. You take a word and apply a permutation to the word to get an alphabetic jumble of the word. A permutation of three distinct characters is based on three index permutation table:
123 132 213 231 312 321.
So, the scrambling of the word “THE” is as follows:
THE TEH HTE HET ETH EHT.
As you can see there are n-factorial permutations of n objects.
0! = 1
1! = 1
2! = 2 * 1 = 2
3! = 3 * 2 * 1 = 6
4! = 4 * 3 * 2 * 1 = 4 * 3! = 24
Etc. Several years ago I created a program to solve single word anagrams of length less than or equal about a dozen.
12! = 479,001,600
This is about the limit of finding all the permutations of up to length twelve on a desktop computer. The algorithm is extremely easy to understand and implement. First find a suitable list of English words and if the list is unsorted then sort the list alphabetically in ascending order. Hash the dictionary words using a hash table of length 128 * 128 + 128 = 16,512 elements. The dictionary I used has 152,512 words so there are hash table collisions. The hash value is computed using the first three characters of the word in ASCII (7-bit) encoding. Then for each permutation of the anagram a hash value is computed and if the current permutation is found in the hash table the word associated with the hash table entry is returned and the algorithm is finished.
I first implemented Singleton’s sorting algorithm in the Summer of 1979. The programming language was Data General’s version of Dayton BASIC (Beginner’s All-purpose Symbolic Instruction Code). This variant of BASIC was interpretive like C#, Java, and Pascal. Below is my BASIC version and run-times for double precision numbers in an inverted sequence.
Summer of 1979 BASIC Singleton’s Sorting Algorithm
Zoom forward to my current computer and C# programming language in 2018.
C# Singleton’s Sorting Algorithm 2008 – 2018 Random Lists of Double Precision Numbers