We Keep Coding

Wrap Around Grid - errors on east/west only

I have four methods that check whether or not a given grid location is next to an occupied location (value of 1). The grid is assumed to wrap around, ie, if in a 50x50 grid[0][1] is the given location and grid[49][1] is occupied, the method should return true/ My checkNorth and checkEast method are working fine, but I get an ArrayIndexOutofBoundsException: -1 error for either the south or west methods every time I run the program. I checked my math and I think it should work - am I using the modulo incorrectly, or am I missing something else?
EDIT: Clarified the wrapping criterion, word use correction.
boolean checkWest(int indexA, int indexB)
{
if (indexA-1 > 0)
{
if (grid[indexA-1][indexB] == 1)
{
return true;
}
}
if (indexA-1 < 0)
{
if (grid[(indexA-1)%width][indexB] == 1)
{return true;}
else return false;
}
return false;
}

I see a couple problems. First, Java arrays are zero-indexed, which means that the first element is at index 0. So it's okay to check grid[indexA-1][indexB] when indexA-1 is equal to 0. Second, you're not properly handling when indexA equals 0. Here is my implementation. I also simplified the logic a bit.
boolean checkWest(int indexA, int indexB)
{
if (indexA > 0)
return grid[indexA - 1][indexB] == 1;
else
return grid[width + indexA - 2][indexB] == 1;
}
EDIT: I'm pretty sure I butchered the math with the second return statement. It should be right now...

Calculus Limits with Java

I wish to calculate limits (calculus) with Java. I have the following class Limit that can calculate limits:
package calculus;
public final class Limit {
private Limit() {
}
public static final double limit(Function function, double approach) {
double below = Limit.limitFromBelow(function, approach);
double above = Limit.limitFromAbove(function, approach);
return below == above ? below : Double.NaN;
}
public static final double limitFromBelow(Function function, double approach) {
for (double d = approach - 10; d <= approach; d = approach
- ((approach - d) / 10)) {
if (function.apply(d) == Double.POSITIVE_INFINITY) {
return Double.POSITIVE_INFINITY;
} else if (function.apply(d) == Double.NEGATIVE_INFINITY) {
return Double.NEGATIVE_INFINITY;
} else if (Double.isNaN(function.apply(d))) {
return function.apply(approach + ((approach - d) * 10));
} else {
if (d == approach) {
return function.apply(d);
} else if (approach - d < 0.00000000001) {
d = approach;
}
}
}
return Double.NaN;
}
public static final double limitFromAbove(Function function, double approach) {
for (double d = approach + 10; d >= approach; d = approach
- ((approach - d) / 10)) {
if (function.apply(d) == Double.POSITIVE_INFINITY) {
return Double.POSITIVE_INFINITY;
} else if (function.apply(d) == Double.NEGATIVE_INFINITY) {
return Double.NEGATIVE_INFINITY;
} else if (Double.isNaN(function.apply(d))) {
return function.apply(approach + ((approach - d) * 10));
} else {
if (d == approach) {
return function.apply(d);
} else if (d - approach < 0.00000000001) {
d = approach;
}
}
}
return Double.NaN;
}
}
However, I was wondering: Is there another way to calculate limits other than exhaustion and recursive testing? Is there a more efficient method?

Your technique is called numerical approximation of a limit. It is widely used, simple to implement, and generally good enough for many applications. It is easy to use because all you need is a function that you can evaluate in order to apply it.
If you want another way, it is called symbolic or algebraic calculation of limits. In this case, you need to have more information than just the capability to evaluate an unknown function. You need to have an entire parse tree expression for a function including an indication of the independent variable. This is more than just the capability to evaluate the function at a given point. One example of this in Python is shown here:
http://scipy-lectures.github.io/advanced/sympy.html#limits
The symbolic style uses real math rules similar to how you might work out the limit by hand using rules of algebra or calculus.

Calculating many limit problems cannot be done numerically, ofter involves symbolic rules, such as L'Hopital's rule, and thererfore you need a symbolic algebra toolset, which aren't so great in java because there is no operation overloading, all the math guys go to python, or maple if you are doing some serious business.
A numerical implementation alone will not be very good, you can't simply use numerical approximations for limmits, once you enter symbolic maths numerical approximations are very limitted to what you can acheive with them, and you need to check for convergence and all sorts of things but anyway I guess you can have a go for what its worth but don't use this in any serious application.

Programming Assignments-Recursion

Still learning and I cant seem to wrap my head on what seemed like an easy task.
The computeMethods method's is where im totaly stumped, however the reverse method i just keep getting back the same integer without it being reversed.
/****************************
* For Method Computemethods1 i must compute series
* b(x)=1/3+2/5+3/7..... +x/2x+1
* For method ComputeMethod2
* 1/2+2/3+......... x/(x+1)
*******************************/
public static int computeMethod1(int x){
if (x==0)
return 0;
if (x==1)
return 1;
return computeMethod1(x-1/3/(x-1))+computeMethod1(x-2/3/(x-2));
}
public static int computeMethod2(int x){
if (x==0)
return 0;
return computeMethod2((x-1)/(x-1)+1)+computeMethod2((x-2)/(x-2)+1);
}
/********************
* For method reverseMethod i must reverse a user given int
**********************/
public static int reverseMethod(int x){
int reversedNum=0;
if (x!=0)
return x;
reversedNum=reversedNum *10 +x%10;
return reversedNum+reverseMethod(x/10);
}
/******************
* For method sumDigits i must use recursion
* to sum up each individual number within the int
********************/
public static long sumDigits(long n){
if( n==0)
return 0;
if (n==1)
return 1;
else
return n+sumDigits(n-1);
}
}

For reverse method, you are using: if (x!=0) return x;
May be you need to use: if (x==0) return x. So the logic is, if the given argument is 0, then return 0, else return reversed number.
P.S.: As somebody mentioned in comentaries, please take care of types, so for the division you are better using float or double, and take care of operations precedence for correct result, so (x+1)/2 will be different from x+1/2.

For each of your methods, follow through your code for small x.
For example, computeMethod1 should return:
1/3 for x == 1, whereas at the moment it simply returns 1 (Note, the return type will need to be something other than int.).
1/3 + 2/5 for x == 2.
1/3 + 2/5 + 3/7 for x == 3.
For each x, notice how we can use the previous result i.e. computeMethod1(x - 1).
When you come across code that doesn't seem to do what you expect, make your code simpler and simpler until you can narrow down where the problem is, then hopefully it will be obvious what the problem is, or online documentation can tell you.

Binary Search using Recursion in java

I am writing a program for a recursive binary search. I have an input file with a series of sorted numbers, which I added to an ArrayList. The program searches to see if a key given by user input is in the ArrayList.
public static int binarySearch(int key, int median){
if(key == (int)array.get(median)){
return key;
}else if(key < (int)array.get(median)){
binarySearch(key,median-1);
}else if(key > (int)array.get(median)){
binarySearch(key,median+1);
}
return -1;
}
For example, let's say the key is 90. I debugged and placed watches at key and array.get(median). After stepping through the program, I discovered that even when key and array.get(median) are equal to 90, the program continues through the loop without ever returning the key. I know that recursion isn't ideal for this, but it's what I need to use.

This does not look like a correct binary search, as a binary search uses a divide and conquer approach. You only divide your list initially once and then check every element from there on. It would be better to then just divide your list again and so on, see https://en.wikipedia.org/wiki/Binary_search_algorithm
Anyway, to get your code running, why you do not get an result is most likely because you do not return the result of the recursion, but instead -1.
Remove the return -1 and set a return before your recursive binarySearch calls. And you are missing a exit condition when you do not find the element.
Example (still not a correct binary search):
public static int binarySearch(int key, int median){
if (median < 0 || median > array.size() - 1) { // element not found
return -1;
}
if (key == (int)array.get(median)){
return key;
} else if(key < (int)array.get(median)){
return binarySearch(key,median-1);
} else{
return binarySearch(key,median+1);
}
}

If all you care about is whether it is in the data structure...
public static boolean binarySearch(int key, int median){
if(key == (int)array.get(median)){
return true;
}else if(key < (int)array.get(median)){
return binarySearch(key,median-1);
}else if(key > (int)array.get(median)){
return binarySearch(key,median+1);
}
}
your code could be better written, but copied to to get across the important part of it

You should change your code like this:
public static int binarySearch(int key, int median){
if(key == (int)array.get(median)){
return key;
}else if(key < (int)array.get(median)){
return binarySearch(key,median-1);
}else if(key > (int)array.get(median)){
return binarySearch(key,median+1);
}
return -1;
}
If you do this your recursion would end but I will leave it to you to test out your binary search code. There are some things like the start index and the end index that you are ignoring in this method The return statements should be added because if you don't the control moves to the next statement in the method which is undesirable. Hope that helps!

The code posted is not a Binary Search and is, in fact, a Linear Search using recursion. A Binary Search divides the search space in half each step, binary meaning "two halves" in context. The result is that this Linear Search runs in O(n) and not the expected O(lg n) bounds of a Binary Search
Problems/issues (other than it not being a Binary Search):
The values from the recursive cases are lost as they are not themselves returned. The result of a recursive case must be used in some way (or why call the function at all?). In this case the value should be returned directly, eg. return binarySearch(..). This causes "continues through the loop without ever returning the key" - it actually does find the key, but discards the recursive result.
The code does not correctly detect the out-of-bounds terminal condition. This may result in an IndexOutOfBoundsException when the key is not found.
The step-left/right approach might never terminate correctly without further logic. For example, when the list is {1,3,5,7} and the value being sought is 4 the original code will ping-pong between indices 1 (value 3) and 2 (value 4). This will result in a StackOverflowError being thrown.
The key is returned. This makes little sense as the key is already known and it also prevents -1 from being detectable. Return the index found instead, or a boolean if only an existence test is required.
Take some time to understand and fix these issues .. and then read on for a spoiler if needed.
Consider this rewrite fixing the issues outlined above. Note that it is overly complex1 while still employing an inferior algorithm and O(n) performance. In any case;
// By taking in the List we make this function universal and not
// dependent upon a static field. It should probably take in a List<Integer>
// but I don't know what the actual type of "array" is. A more advanced
// implementation would take in List<Comparable> and then be modified to work
// with any objects that correctly implement said interface.
public static int linearSearch(int key, List list, int index, int step) {
if (index < 0 || index >= list.size()) {
// Base case: not found, out of bounds
return -1;
}
int x = (int)list.get(index);
if (key < x && step <= 0) { // need to look left, NOT looking right
// Recursive case: look left, returning result
return linearSearch(key, list, index - 1, -1);
} else if (key > x && step >= 0){ // need to look right, NOT looking left
// Recursive case: look right, returning result
return linearSearch(key, list, index + 1, +1);
} else if (key == x) {
// Base case: found key, return index found
return index;
} else {
// Base case: key not equal, refusing to ping-pong
return -1;
}
}
And then consider the use of this helper/wrapper function;
// Returns the index in "array" where key was found, or -1 if it was not found
public static int linearSearch(int key) {
// Have to start somewhere, might as well be the middle..
// ..but it does NOT make the time complexity any better
// ..and it is still NOT a Binary Search.
return linearSearch(key, array, array.size() / 2, 0);
}
1 Alternatively, since it is a Linear Search it could be rewritten without the extra left/right movement and have the same complexity bounds. (It is also trivial to modify this simpler code to a recursive Binary Search.)
public static int linearSearch(int key, List list, int index) {
if (index >= list.size() {
// Base case: end of list
return -1;
}
int x = (int)list.get(index);
if (key < x) {
// Recursive case: not there yet, keep looking
return linearSearch(key, list, index + 1);
} else if (key == x) {
// Base case: found key, return index
return index;
} else { // -> key > x
// Base case: read past where the key would be found
return -1;
}
}

Here's binary search for ArrayList<Integer> :)
public int binarySearch(List<Integer> list, int find) {
int mid = list.size() / 2;
int val = list.get(mid);
if (val == find) {
return val;
} else if (list.size() == 1) {
return -1;
}
return val > find ?
binarySearch(list.subList(0, mid), find) :
binarySearch(list.subList(mid, list.size()), find);
}

Whats wrong with my syntax and am i doing this efficiently?

I'm trying to make a method that will tell me weather or not it is true or false that a number is prime. here's the code:
class prime
{
public static boolean prime (int a, int b)
{
if (a == 0)
{
return false;
}
else if (a%(b-1) == 0)
{
return false;
}
else if (b>1)
{
prime (a, b-1) ;
}
else
{
return true;
}
}
public static void main (String[] arg)
{
System.out.println (prime (45, 45)) ;
}
}
when i try to compile this i get this error message:
prime.java:23: missing return statement
}
^
1 error
I could be misinterpreting what the error message is saying but it seems to me that there isn't a missing return statement since i have a return statement for every possible set of conditions. if a is 0 then it returns false, if it isn't then it checks to see if a is dividable by b if it is then it returns if not then if b is greater than 1 it starts over again. if b isn't greater than 1 it also returns.
Also it seems a bit messy to have to
make this method take two ints that
are the same int.
What is wrong with my syntax/ why am i getting the error message? Is there a way to make it so that the method that i use in main only has to take one int (perhaps another method splits that int into two clones that are then passed to public static boolean primeproper?
or is there a more effective way of
going about this that i'm missing
entirely?

In your prime function, there are four possible code paths, one of which doesn't return anything. That is what the error message is complaining about. You need to replace:
prime (a, b-1) ;
with:
return prime (a, b-1) ;
in the else if (b>1) case.
Having said that, this is actually not a good way to calculate if a number is prime. The problem is that every recursive call allocates a stack frame and you'll get into serious stack overflow problems if you're trying to work out whether 99,999,999 is a prime number?
Recursion is a very nice tool for a certain subset of problems but you need to be aware of the stack depth. As to more efficient solutions, the are many tests you can carry out to determine a number is not prime, then only check the others with a brute force test.
One thing you should be aware of is to check divisibility against smaller numbers first since this will reduce your search scope quicker. And don't use divide where multiply will do, multiplication is typically faster (though not always).
And some possibly sneaky tricks along the lines of:
every number other than 2 that ends in 2, 4, 6, 8 or 0 is non-prime.
every number other than 5 that ends in 5 is non-prime.
Those two rules alone will reduce your search space by 60%. Assuming you get your test number as a string, it's a simple matter to test the last digit of that string even before converting to an integral type.
There are some more complex rules for divisibility checks. If you take a multiple of 9 and sum all the digits to get a new number, then do it again to that number, then keep going until you have a single digit, you'll find that it's always 9.
That will give you another 10% reduction in search space albeit with a more time-expensive check. Keep in mind that these checks are only advantageous for really large numbers. The advantages are not so great for, say, 32-bit integers since a pre-calculated bitmap would be much more efficient there (see below).
For a simplistic start, I would use the following iterative solution:
public static boolean prime (int num) {
int t = 2;
while (t * t <= num) {
if ((num % t) == 0) {
return false;
}
t++;
}
return true;
}
If you want real speed in your code, don't calculate it each time at all. Calculate it once to create a bit array (one of the sieve methods will do it) of all primes across the range you're interested in, then simply check your values against that bit array.
If you don't even want the cost of calculating the array every time your program starts, do it once and save the bit array to a disk file, loading it as your program starts.
I actually have a list of the first 100 million primes in a file and it's easier and faster for me to use grep to find if a number is prime, than to run some code to calculate it :-)
As to why your algorithm (fixed with a return statement) insists that 7 is not prime, it will insist that every number is non-prime (haven't checked with negative numbers, I'm pretty sure they would cause some serious problems - your first check should probably be if (a < 1) ...).
Let's examine what happens when you call prime(3,3).
First time through, it hits the third condition so calls prime(3,2).
Then it hits the second condition since 3 % (2-1) == 0 is true (N % 1 is always 0).
So it returns false. This could probably be fixed by changing the third condition to else if (b>2) although I haven't tested that thoroughly since I don't think a recursive solution is a good idea anyway.
The following complete code snippet will do what you need although I appreciate your curiosity in wanting to know what you did wrong. That's the mark of someone who's actually going to end up a good code cutter.
public class prime
{
public static boolean isPrime (int num) {
int t = 2;
while (t * t <= num) {
if ((num % t) == 0) {
return false;
}
t++;
}
return true;
}
public static void main (String[] arg)
{
System.out.println (isPrime (7)) ;
}
}

You seem to be under the impression that because the recursion will eventually find a base-case which will hit a return statement, then that return will bubble up through all of the recursive calls. That's not true. Each recursive call must pass out the result like this:
return prime(a, b - 1);

If b is larger than 1, your function won't return anything.
May it be return prime (a, b-1) ; ?

To improve efficiency, think more about your conditions. Do you really need test every factor from 2 to N? Is there a different stopping point that will help tests of prime numbers complete more quickly?
To make a better API, consider making the recursive method private, with a public entry point that helps bootstrap the process. For example:
public static boolean prime(int n) {
return recurse(n, n);
}
private static boolean recurse(int a, int b) {
...
}
Making a method private means that it can't be called from another class. It's effectively invisible to users of the class. The intent here is to hide the "ugly" extra parameter by providing a public helper method.
Think about the factors of some composite numbers. 10 factors to 5×2. 12 factors to 6×2. 14 factors to 7×2. Now think about 25. 25 factors to 5×5. What about 9? Do you see a pattern? By the way, if this isn't homework, please let me know. Being this didactic is hard on me.

In answer to why 7 isn't working, pretend you're the computer and work through your logic. Here's what you wrote.
class prime
{
public static boolean prime (int a, int b)
{
if (a == 0)
{
return false;
}
else if (a%(b-1) == 0)
{
return false;
}
else if (b>1)
{
// Have to add the return statement
// here as others have pointed out!
return prime(a, b-1);
}
else
{
return true;
}
}
public static void main (String[] arg)
{
System.out.println (prime (45, 45)) ;
}
}
So let's start with 7.
if(7 == 0) // not true, don't enter this block
else if(7 % 6 == 0) // not true
else if(7 > 1) // true, call prime(7, 6)
if(7 == 0) // not true, don't enter this block
else if(7 % 5 == 0) // not true
else if(6 > 1) // true, call prime(7, 5)
if(7 == 0) // not true, don't enter this block
else if(7 % 4 == 0) // not true
else if(5 > 1) // true, call prime(7, 4)
... keep going down to calling prime(7, 2)
if(7 == 0) // not true, don't enter this block
else if(7 % 1 == 0) true, return false
When you get down to calling prime(n, 2), it will always return false because you have a logic error.

Your recursive method must return a value so it can unroll.
public static boolean prime (int a, int b)
{
if (a == 0)
{
return false;
}
else if (a%(b-1) == 0)
{
return false;
}
else if (b>1)
{
return prime (a, b-1) ;
}
else
{
return true;
}
}
I might write it a different way, but that is the reason that you are not able to compile the code.

I think the original question was answered already - you need to insert return in the body of else if (b>1) - I just wanted to point out that your code still will crash when given 1 as the value for b, throwing an ArithmeticException since a%(b-1) will be evaluated to a%0, causing a division by zero.
You can avoid this by making the first if-statement if (a == 0 || b == 1) {}
This won't improve the way the program finds primes, it just makes sure there is one less way to crash it.

Similar to #paxdiblo's answer, but slightly more efficient.
public static boolean isPrime(int num) {
if (num <= 1 || (num & 1) == 0) return false;
for (int t = 3; t * t <= num; t += 2)
if (num % t == 0)
return false;
return true;
}
Once it is determined that the number is not even, all the even numbers can be skipped. This will halve the numbers which need to be checked.