I had the following question in my exam:
This problem involves a circular DHT in which every peer node tracks just its predecessor and the successor. No shortcuts are available.
Consider the following three constructions below. In all these three construction, the node IDs range
from 0 to N − 1 and so do the key IDs. At a given time, the number of peer nodes participating in
the DHT is M and this number is readily known to all peer nodes. The ‘value’ in the (key, value)
pair is the set of IDs of the nodes that independently store the data of interest.
C-1: Every stored (key, value) pair (k, v) is stored at a random node (from among the ones that are online then).
C-2: Every stored (key, value) pair (k, v) is stored at a node whose ID is given by k mod M.
C-3: Every stored (key, value) pair (k, v) is stored at a node whose ID is k (if it is online) or its closest online successor (with wraparound).
(a) An online peer wants to find out a key k to get the corresponding value. What is the
complexity (i.e., the big-oh O( )) of this operation in each of the three constructions. If you are
not familiar with the O( ) notation, just state the average number of queries launched.
(b) An online node launches a query for key k and gets a set of two node IDs in return.
What are the chances at least one of those nodes is online (such that the querying node can get
the data of interest)? Provide your answer for each construction; your answer may be in terms of
k, M, N, or any other parameter.
(c) What would be your (numerical) answer to above part (for each construction) if on
average 30% nodes are online.
I have confusion over the answers I wrote. I want to know whether what I did is correct or not.
I wrote the following answers :
a) C1: O(N) - in the case there are N nodes online
C2: O(M) - in the case the keys are from 0 to M-1
C3: O(1) - worst case node with key k is offline the next one is looked at
b) p=probability of being online
C1: 2C1 * p * (1-p) + 2C2 * p
C2: 2C1 * p * (1-p) + 2C2 * p
C3: 2C1 * p * (1-p) + 2C2 * p
c) C1 : 2C1 * 0.3 * 0.7 + 2C2 * 0.3
C2 : 2C1 * 0.3 * 0.7 + 2C2 * 0.3
C3 : 2C1 * 0.3 * 0.7 + 2C2 * 0.3
a) For C1 you have stated the answer for the case when M = N, this may not always hold so you should change it to O(M) since it will search all the online nodes as any one of them can hold the key at random.
C2: O(M) is correct as well as the reason you stated.
C3: this too will be O(M), as on average you are going to have to traverse the whole DHT to find the key.
b)
You have used the wrong formula for the binomial theorem.
The correct formula is:
nCk * p^k * (1-p) ^ (n-k)
So your answers should be:
C1: 2C1 * p * (1-p) + 2C2 * p^2
C2: 2C1 * p * (1-p) + 2C2 * p^2
C3: 2C1 * p * (1-p) + 2C2 * p^2
Also, note that here p = M/N (since M nodes online from N nodes)
c)
Now p = 0.3
C1 : 2C1 * 0.3 * 0.7 + 2C2 * 0.3^2 = 0.51
C2 : 2C1 * 0.3 * 0.7 + 2C2 * 0.3^2 = 0.51
C3 : 2C1 * 0.3 * 0.7 + 2C2 * 0.3^2 = 0.51
Related
I see there are a few other questions around this exercise but none specifically are asking what is meant within the hint... "define the state transition in such a way that the product abn is unchanged from state to state".
They also mention that this idea of using an "invariant quantity" is a powerful idea with respect to "iterative algorithms". By the way, this problem calls for the design of a "logarithmic" exponent algorithm that has a space complexity of O(1).
Mainly I just have no idea what is meant by this hint and am pretty confused. Can anyone give me a nudge in what is meant by this? The only thing I can really find about "invariant quantities" are described using examples in physics which only makes this concept more opaque.
Exercise description in full:
Exercise 1.16: Design a procedure that evolves an iterative exponentiation process that uses successive squaring and uses a logarithmic number of steps, as does fast-expt. (Hint: Using the observation that (bn/2)2 = (b2)n/2, keep, along with the exponent n and the base b, an additional state variable a, and define the state transformation in such a way that the product abn is unchanged from state to state.
At the beginning of the process a is taken to be 1, and the answer is given by the value of a at the end of the process. In general, the technique of defining an invariant quantity that remains unchanged from state to state is a powerful way to think about the design of iterative algorithms.)
Thanks in advance.
This is not about any "logarithmic exponentiation", which is a very vague and confusing terminology.
As the quote you provided says, it is about exponentiation function that takes logarithmic number of steps to get its final result.
So we want to develop a function, exp(b,n), which would take O(log n) time to finish.
The numbers involved are all integers.
So how do we calculate bn? We notice that
b^n = b * b * b * b *... * b
`------n times------/ O(n) time process
and, when n is even,
b^n = b * b * b * b * ... * b *
`------n/2 times-----/
b * b * b * b * ... * b
`------n/2 times-----/
= (b^(n/2))^2 ; viewed from the side
= (b^2)^(n/2) ; viewed from above
and when n is odd,
b^n = b * b * b * b * ... * b *
`------n/2 times-----/
b * b * b * b * ... * b *
`------n/2 times-----/
b
`--1 time--/
= (b^(n/2))^2 * b
= (b^2)^(n/2) * b
Note that both expression fall into same category if we write the first one as (b^2)^(n/2) * 1.
Also note that the equation
b^n = (b )^(n ) * { a where a = 1 }
= (b ^2)^(n/2) * { a where a = ... }
= (b' )^(n' ) * { a' }
means that to calculate b^n * a is the same as to calculate b'^n' * a' with the changed values of { b' = b^2 ; n' = n/2 ; a' = {if {n is even} then {a} else {a * b}} }.
So we don't actually compute either of the sides of that equation. Instead we keep the triples { b, n, a } at each step and transform them according to that rule
{ b, n, a } --> { b', n', a' } --> ...
with the initial values of b and n as given to us, and the first a equal to 1; and know that the final result calculated from any of the triples would be the same if we'd actually calculated it somehow. We still don't know how exactly we'd do that; just that it would be the same. That's the "invariant" part.
So what all this is good for? Well, since the chain { n --> n/2 --> ... } will certainly reach a point where n == 1, we know that at that point we can break the chain since
c^1 * d == c * d
and this one simple multiplication of these two numbers will produce the same result as the initial formula.
Which is the final result of the function.
And that's the meaning of the hint: maintain the state of the computation as a (here) triple of numbers (or just three variables named b, n, a), and implement your computation as a chain of state-transforming steps. When the chain is broken according to some test (here, n == 1), we've reached our destination and can calculate the final result according to some simple rule (here, c * d).
This gives us a nice and powerful methodology for problem solving.
Oh, and we also know that the length of that chain of changing states is O(log n), since we halve that n at each step.
when fast-exp execute, the trace looks something like this
b^14 = (b^2)^7 ; where: b' = b^2; a = 1, n = 7
b^14 = (b^2)^6 * b^2 ; where: b' = b^2; a = b^2, n = 6
b^14 = ((b^2)^2)^3 *b^2 ; where: b' = b^2^2 ; a = b^2, n = 3
b^14 = ((b^2)^2)^2 *b^2 *(b^2)^2 ; where: b' = b^2^2; a = b^2*(b^2)^2, n = 2
notice that all these statements have the general form of b^n = b'^n' * a', and this does not change
What is the algorithm to find the number way to separate number M to p part and no two part equal.
Example:
M = 5, P = 2
they are (1,4) (2,3). If P = 3 then no partition availabe, i.e
not (1,2,2) because there two 2 in partition.
In the expanded product
(1+x)(1+x2)(1+x3)...(1+xn)
find the coefficient of x^n. This gives the number of any possibility to represent n as sum of different numbers, i.e., a variable number of terms.
You want the number of possibilites to have
n = i1+i2+...+iP with i1 < i2 < ... < iP
which can be realized by setting
i1=j1, i2=i1+j2=j1+j2, ...
iP=iP-1+jP=j1+j2+...+jP with all jk > 0
so that the original task is the same as counting all the ways that one can solve
n = P * j1+(P-1) * j2+...+1 * jP with all jk > 0, but unrelated among each other.
The corresponding generator function is the product of the geometric series of the powers of x, omitting the constant term,
(x+x2+x3+...) * (x2+x4+x6+...) * (x3+x6+x9+...) * ... * (xP+x2*P+x3*P+...)
= xP*(P+1)/2 * (1+x+x2+...) * (1+x2+x4+...) * (1+x3+x6+...) * ... * (1+xP+x2*P+...)
Clearly, one needs n >= P*(P+1)/2 to get any solution at all. For P=3 that bound is n >= 6, so that n=5 has indeed no solutions in that case.
Algorithm
count = new double[N]
for k=0..N-1 do count[k] = 1
for j=2..P do
for k=j..N-1 do
count[k] += count[k-j]
Then count[k] contains the number of combinations for n=P*(P+1)/2+k.
Assuming I have a spaceship (source); And an asteroid (target) is somewhere near it.
I know, in 3D space (XYZ vectors):
My ship's position (sourcePos) and velocity (sourceVel).
The asteroid's position (targetPos) and velocity (targetVel).
(eg. sourcePos = [30, 20, 10]; sourceVel = [30, 20, 10]; targetPos = [600, 400, 200]; targetVel = [300, 200, 100]`)
I also know that:
The ship's velocity is constant.
The asteroid's velocity is constant.
My ship's projectile speed (projSpd) is constant.
My ship's projectile trajectory, after being shot, is linear (/straight).
(eg. projSpd = 2000.00)
How can I calculate the interception coordinates I need to shoot at in order to hit the asteroid?
Notes:
This question is based on this Yahoo - Answers page.
I also searched for similar problems on Google and here on SO, but most of the answers are for 2D-space, and, of the few for 3D, neither the explanation nor the pseudo-codes explain what is doing what and/or why, so I couldn't really understand enough to apply them on my code successfully. Here are some of the pages I visited:
Danik Games Devlog, Blitz3D Forums thread, UnityAnswers, StackOverflow #1, StackOverflow #2
I really can't figure out the maths / execution-flow on the linked pages as they are, unless someone dissects it (further) into what is doing what, and why;
Provides a properly-commented pseudo-code for me to follow;
Or at least points me to links that actually explain how the equations work instead of just throwing even more random numbers and unfollowable equations in my already-confused psyche.
I find the easiest approach to these kind of problems to make sense of them first, and have a basic high school level of maths will help too.
Solving this problem is essentially solving 2 equations with 2 variables which are unknown to you:
The vector you want to find for your projectile (V)
The time of impact (t)
The variables you know are:
The target's position (P0)
The target's vector (V0)
The target's speed (s0)
The projectile's origin (P1)
The projectile's speed (s1)
Okay, so the 1st equation is basic. The impact point is the same for both the target and the projectile. It is equal to the starting point of both objects + a certain length along the line of both their vectors. This length is denoted by their respective speeds, and the time of impact. Here's the equation:
P0 + (t * s0 * V0) = P1 + (t * s0 * V)
Notice that there are two missing variables here - V & t, and so we won't be able to solve this equation right now. On to the 2nd equation.
The 2nd equation is also quite intuitive. The point of impact's distance from the origin of the projectile is equal to the speed of the projectile multiplied by the time passed:
We'll take a mathematical expression of the point of impact from the 1st equation:
P0 + (t * s0 * V0) <-- point of impact
The point of origin is P1
The distance between these two must be equal to the speed of the projectile multiplied by the time passed (distance = speed * time).
The formula for distance is: (x0 - x1)^2 + (y0 - y1)^2 = distance^2, and so the equation will look like this:
((P0.x + s0 * t * V0.x) - P1.x)^2 + ((P0.y + s0 * t * V0.y) - P1.y)^2 = (s1 * t)^2
(You can easily expand this for 3 dimensions)
Notice that here, you have an equation with only ONE unknown variable: t!. We can discover here what t is, then place it in the previous equation and find the vector V.
Let me solve you some pain by opening up this formula for you (if you really want to, you can do this yourself).
a = (V0.x * V0.x) + (V0.y * V0.y) - (s1 * s1)
b = 2 * ((P0.x * V0.x) + (P0.y * V0.y) - (P1.x * V0.x) - (P1.y * V0.y))
c = (P0.x * P0.x) + (P0.y * P0.y) + (P1.x * P1.x) + (P1.y * P1.y) - (2 * P1.x * P0.x) - (2 * P1.y * P0.y)
t1 = (-b + sqrt((b * b) - (4 * a * c))) / (2 * a)
t2 = (-b - sqrt((b * b) - (4 * a * c))) / (2 * a)
Now, notice - we will get 2 values for t here.
One or both may be negative or an invalid number. Obviously, since t denotes time, and time can't be invalid or negative, you'll need to discard these values of t.
It could very well be that both t's are bad (in which case, the projectile cannot hit the target since it's faster and out of range). It could also be that both t's are valid and positive, in which case you'll want to choose the smaller of the two (since it's preferable to hit the target sooner rather than later).
t = smallestWhichIsntNegativeOrNan(t1, t2)
Now that we've found the time of impact, let's find out what the direction the projectile should fly is. Back to our 1st equation:
P0 + (t * s0 * V0) = P1 + (t * s0 * V)
Now, t is no longer a missing variable, so we can solve this quite easily. Just tidy up the equation to isolate V:
V = (P0 - P1 + (t * s0 * V0)) / (t * s1)
V.x = (P0.x - P1.x + (t * s0 * V0.x)) / (t * s1)
V.y = (P0.y - P1.y + (t * s0 * V0.y)) / (t * s1)
And that's it, you're done!
Assign the vector V to the projectile and it will go to where the target will be rather than where it is now.
I really like this problem since it takes math equations we learnt in high school where everyone said "why are learning this?? we'll never use it in our lives!!", and gives them a pretty awesome and practical application.
I hope this helps you, or anyone else who's trying to solve this.
If you want a projectile to hit asteroid, it should be shoot at the point interceptionPos that satisfy the equation:
|interceptionPos - sourcePos| / |interceptionPos - targetPos| = projSpd / targetVel
where |x| is a length of vector x.
In other words, it would take equal amount of time for the target and the projectile to reach this point.
This problem would be solved by means of geometry and trigonometry, so let's draw it.
A will be asteroid position, S - ship, I - interception point.
Here we have:
AI = targetVel * t
SI = projSpd * t
AS = |targetPos - sourcePos|
vector AS and AI direction is defined, so you can easily calculate cosine of the SAI angle by means of simple vector math (take definitions from here and here). Then you should use the Law of cosines with the SAI angle. It will yield a quadratic equation with variable t that is easy to solve (no solutions = your projectile is slower than asteroid). Just pick the positive solution t, your point-to-shoot will be
targetPos + t * targetVel
I hope you can write a code to solve it by yourself. If you cannot get something please ask in comments.
I got a solution. Notice that the ship position, and the asteroid line (position and velocity) define a 3D plane where the intercept point lies. In my notation below | [x,y,z] | denotes the magnitude of the vector or Sqrt(x^2+y^2+z^2).
Notice that if the asteroid travels with targetSpd = |[300,200,100]| = 374.17 then to reach the intercept point (still unknown, called hitPos) will require time equal to t = |hitPos-targetPos|/targetSpd. This is the same time the projectile needs to reach the intercept point, or t = |hitPos - sourcePos|/projSpd. The two equations are used to solve for the time to intercept
t = |targetPos-sourcePos|/(projSpd - targetSpd)
= |[600,400,200]-[30,20,10]|/(2000 - |[300,200,100]|)
= 710.81 / ( 2000-374.17 ) = 0.4372
Now the location of the intetception point is found by
hitPos = targetPos + targetVel * t
= [600,400,200] + [300,200,100] * 0.4372
= [731.18, 487.45, 243.73 ]
Now that I know the hit position, I can calculate the direction of the projectile as
projDir = (hitPos-sourcePos)/|hitPos-sourcePos|
= [701.17, 467.45, 233.73]/874.52 = [0.8018, 0.5345, 0.2673]
Together the projDir and projSpd define the projectile velocity vector.
Credit to Gil Moshayof's answer, as it really was what I worked off of to build this. But they did two dimensions, and I did three, so I'll share my Unity code in case it helps anyone along. A little long winded and redundant. It helps me to read it and know what's going on.
Vector3 CalculateIntercept(Vector3 targetLocation, Vector3 targetVelocity, Vector3 interceptorLocation, float interceptorSpeed)
{
Vector3 A = targetLocation;
float Ax = targetLocation.x;
float Ay = targetLocation.y;
float Az = targetLocation.z;
float As = targetVelocity.magnitude;
Vector3 Av = Vector3.Normalize(targetVelocity);
float Avx = Av.x;
float Avy = Av.y;
float Avz = Av.z;
Vector3 B = interceptorLocation;
float Bx = interceptorLocation.x;
float By = interceptorLocation.y;
float Bz = interceptorLocation.z;
float Bs = interceptorSpeed;
float t = 0;
float a = (
Mathf.Pow(As, 2) * Mathf.Pow(Avx, 2) +
Mathf.Pow(As, 2) * Mathf.Pow(Avy, 2) +
Mathf.Pow(As, 2) * Mathf.Pow(Avz, 2) -
Mathf.Pow(Bs, 2)
);
if (a == 0)
{
Debug.Log("Quadratic formula not applicable");
return targetLocation;
}
float b = (
As * Avx * Ax +
As * Avy * Ay +
As * Avz * Az +
As * Avx * Bx +
As * Avy * By +
As * Avz * Bz
);
float c = (
Mathf.Pow(Ax, 2) +
Mathf.Pow(Ay, 2) +
Mathf.Pow(Az, 2) -
Ax * Bx -
Ay * By -
Az * Bz +
Mathf.Pow(Bx, 2) +
Mathf.Pow(By, 2) +
Mathf.Pow(Bz, 2)
);
float t1 = (-b + Mathf.Pow((Mathf.Pow(b, 2) - (4 * a * c)), (1 / 2))) / (2 * a);
float t2 = (-b - Mathf.Pow((Mathf.Pow(b, 2) - (4 * a * c)), (1 / 2))) / (2 * a);
Debug.Log("t1 = " + t1 + "; t2 = " + t2);
if (t1 <= 0 || t1 == Mathf.Infinity || float.IsNaN(t1))
if (t2 <= 0 || t2 == Mathf.Infinity || float.IsNaN(t2))
return targetLocation;
else
t = t2;
else if (t2 <= 0 || t2 == Mathf.Infinity || float.IsNaN(t2) || t2 > t1)
t = t1;
else
t = t2;
Debug.Log("t = " + t);
Debug.Log("Bs = " + Bs);
float Bvx = (Ax - Bx + (t * As + Avx)) / (t * Mathf.Pow(Bs, 2));
float Bvy = (Ay - By + (t * As + Avy)) / (t * Mathf.Pow(Bs, 2));
float Bvz = (Az - Bz + (t * As + Avz)) / (t * Mathf.Pow(Bs, 2));
Vector3 Bv = new Vector3(Bvx, Bvy, Bvz);
Debug.Log("||Bv|| = (Should be 1) " + Bv.magnitude);
return Bv * Bs;
}
I followed the problem formulation as described by Gil Moshayof's answer, but found that there was an error in the simplification of the quadratic formula. When I did the derivation by hand I got a different solution.
The following is what worked for me when finding the intersect in 2D:
std::pair<double, double> find_2D_intersect(Vector3 sourcePos, double projSpd, Vector3 targetPos, double targetSpd, double targetHeading)
{
double P0x = targetPos.x;
double P0y = targetPos.y;
double s0 = targetSpd;
double V0x = std::cos(targetHeading);
double V0y = std::sin(targetHeading);
double P1x = sourcePos.x;
double P1y = sourcePos.y;
double s1 = projSpd;
// quadratic formula
double a = (s0 * s0)*((V0x * V0x) + (V0y * V0y)) - (s1 * s1);
double b = 2 * s0 * ((P0x * V0x) + (P0y * V0y) - (P1x * V0x) - (P1y * V0y));
double c = (P0x * P0x) + (P0y * P0y) + (P1x * P1x) + (P1y * P1y) - (2 * P1x * P0x) - (2 * P1y * P0y);
double t1 = (-b + std::sqrt((b * b) - (4 * a * c))) / (2 * a);
double t2 = (-b - std::sqrt((b * b) - (4 * a * c))) / (2 * a);
double t = choose_best_time(t1, t2);
double intersect_x = P0x + t * s0 * V0x;
double intersect_y = P0y + t * s0 * V0y;
return std::make_pair(intersect_x, intersect_y);
}
Question is about the modulo operator on very large numbers.
For example consider a question where the total number of permutations are to be calculated.
Consider a number of 90 digits with each of the 9 numbers (1 to 9) repeating 10 times
so 90!/(10!)^9) is to be calculated
After reading many answers on StackOverflow I used logarithms to do it.
Now consider the log value to be 1923.32877864.
Now my question is how can I display the answer (i.e. 10 ^ log10(value) ) modulo of "m"?
And is this the best method for calculating the possible number of permutations?
Edit
Got the solution :)
Thanks to duedl0r.
Did it the way you specified using Modular Multiplicative Inverse.Thanks :)
I'm not sure whether this is actually possible and correct, but let me summarize my comments and extend the answer from Miky Dinescu.
As Miky already wrote:
a × b ≣m am × bm
You can use this in your equality:
90! / 10!^9 ≣m x
Calculate each term:
90!m / 10!^9m ≣m x
Then find out your multiplicative inverse from 10!^9m. Then multiplicate the inverse with 90!m.
update
This seems to be correct (at least for this case :)). I checked with wolfram:
(90!/10!^9) mod (10^9+7) = 998551163
This leads to the same result:
90! mod (10^9+7) = 749079870
10!^9 mod (10^9+7) = 220052161
do the inverse:
(220052161 * x) mod(10^9+7) = 1 = 23963055
then:
(749079870*23963055) mod (10^9+7) = 998551163
No proof, but some evidence that it might work :)
I would argue that the way to compute the total number of permutations modulo m, where m is an arbitrary integer (usually chosen to be a large prime number) is to use the following property:
(a * b) % m = ((a % m) * (b % m)) % m
Considering that the total number of permutations of N is N! = 1 * 2 * 3 * .. * N, if you need to compute N! % m, you can essentially apply the property above for multiplication modulo m, and you have:
((((1 * (2 % m)) % m) * (3 % m)) % m) * ..
EDIT
In order to compute the 90! / (10! ^ 9) value you could simplify the factors and then use multiplication modulo m to compute the final result modulo m.
Here's what I'm thinking:
90! = 10! * (11 * 12 * .. * 20) * (21 * 22 * .. * 30) * .. * (81 * 82 * .. * 90)
You can then rewrite the original expression as:
(10! * (11 * 12 * .. * 20) * (21 * 22 * .. * 30) * .. * (81 * 82 * .. * 90)) / (10! * 10! * ... * 10!)
At the numerator, you have a product of 9 factors - considering each expression in parenthesis a factor. The same is true for the denominator (you have 9 factors, each equal to 10!).
The first factor at the denominator is trivial to simplify. After that you still have 8 pairs that need simplification.
So, you can factor each term of the products and simplify the denominator away. For example:
11 * 12 * 13 * 14 * 15 * 16 * 17 * 18 * 19 * 20 <=> 11 * 2 * 2 * 3 * 13 * 2 * 7 * 3 * 5 * 2 * 2 * 2 * 2 * 17 * 2 * 9 * 2 * 2 * 5
The denominator will always be: 2 * 3 * 2 * 2 * 5 * 2 * 3 * 7 * 2 * 2 * 2 * 2 * 3 * 3 * 2 * 5
After the simplification the second pair reduces to : 2 * 2 * 11 * 13 * 17 * 19
The same can be applied to each subsequent pair and you will end up with a simple product that can be computed modulo m using the formula above.
Of course, efficiently implementing the algorithm to perform the simplification will be tricky so ultimately there has to be a better way that eludes me now.
The length of three sides of the triangle, a, b and c will be given, and I need to find the coordinates of the vertices. The center (probably the circumcenter) can either be the origin or (x,y).
Can anyone point me in the right direction?
I've read brainjam's answer and checked whether his answer is true and he is right.
Calculation:
O(0;0), A(a;0) and B(x;y) are the three points of the triangle. C1 is the circle around A and r1 = c; C2 is the circle around O and r2 = b. B(X;Y) is the intersection of C1 and C2, which means that the point is on both of the circles.
C1: (x - a) * (x - a) + y * y = c * c
C2: x * x + y * y = b * b
y * y = b * b - x * x
(x - a) * (x - a) + b * b - x * x = c * c
x * x - 2 * a * x + a * a + b * b - x * x - c * c = 0
2 * a * x = (a * a + b * b - c * c)
x = (a * a + b * b - c * c) / (2 * a)
y * y = b * b - ((a * a + b * b - c * c) / (2 * a)) * ((a * a + b * b - c * c) / (2 * a))
y = +- sqrt(b * b - ((a * a + b * b - c * c) / (2 * a)) * ((a * a + b * b - c * c) / (2 * a)))
Place the first vertex at the origin (0,0). Place the second vertex at (a,0). To compute the third vertex, find the intersection of the two circles with centers (0,0) and (a,0) and radii b and c.
Update: Lajos Arpad has given the details of computing the location of the third point in this answer. It boils down to (x,y) where x = (b2+a2-c2)/2a and y=±sqrt(b2-x2)
This question and the answers helped me out today in implementing this. It will calculate the unknown vertices, "c" of circle intersections given 2 known points (a, b) and the distances (ac_length, bc_length) to the 3rd unknown vertex, "c".
Here is my resulting python implementation for anyone interested.
I also referenced the following:
http://mathworld.wolfram.com/RadicalLine.html
http://mathworld.wolfram.com/Circle-CircleIntersection.html
Using django's geos module for the Point() object, which could be replaced with shapely, or point objects removed altogether really.
from math import sqrt
from django.contrib.gis.geos import Point
class CirclesSeparate(BaseException):
pass
class CircleContained(BaseException):
pass
def discover_location(point_a, point_b, ac_length, bc_length):
"""
Find point_c given:
point_a
point_b
ac_length
bc_length
point_d == point at which the right-angle to c is formed.
"""
ab_length = point_a.distance(point_b)
if ab_length > (ac_length + bc_length):
raise CirclesSeparate("Given points do not intersect!")
elif ab_length < abs(ac_length - bc_length):
raise CircleContained("The circle of the points do not intersect")
# get the length to the vertex of the right triangle formed,
# by the intersection formed by circles a and b
ad_length = (ab_length**2 + ac_length**2 - bc_length**2)/(2.0 * ab_length)
# get the height of the line at a right angle from a_length
h = sqrt(abs(ac_length**2 - ad_length**2))
# Calculate the mid point (point_d), needed to calculate point_c(1|2)
d_x = point_a.x + ad_length * (point_b.x - point_a.x)/ab_length
d_y = point_a.y + ad_length * (point_b.y - point_a.y)/ab_length
point_d = Point(d_x, d_y)
# get point_c location
# --> get x
c_x1 = point_d.x + h * (point_b.y - point_a.y)/ab_length
c_x2 = point_d.x - h * (point_b.y - point_a.y)/ab_length
# --> get y
c_y1 = point_d.y - h * (point_b.x - point_a.x)/ab_length
c_y2 = point_d.y + h * (point_b.x - point_a.x)/ab_length
point_c1 = Point(c_x1, c_y1)
point_c2 = Point(c_x2, c_y2)
return point_c1, point_c2
When drawing an unknown triangle, it's usually easiest to pick one side (say, the longest) and place it horizontally or vertically. The endpoints of that side make up two of the triangle's vertices, and you can calculate the third by subdividing the triangle into two right triangles (the other two sides are the hypotenuses) and using the inverse sine/cosine functions to figure out the missing angles. By subdividing into right triangles, I mean something that looks like the image here: http://en.wikipedia.org/wiki/File:Triangle.TrigArea.svg Your first side would be AC in that drawing.
Once you have the triangle figured out, it should be easy to calculate it's center and translate it so that it is centered on whatever arbitrary center point you like.
First check the that the triangle is possible:
a+b >= c
b+c >= a
c+a >= b
Then, if it is, solve for the intersection of the two circles. The basic vertices are
{0,0}, {a,0}, {x,y}
where
x = (a^2-b^2+c^2)/(2a)
y = sqrt(c^2-x^2)
Finding the circumcenter is pretty easy from this point.