Difference between revisions of "TADM2E 3.13"
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Before outlining the solution, consider that a binary tree can satisfy the O(logn) requirement for both the Add(i, y) and Partial-sum(i) functions. In so doing, we initialize the binary tree with all non-leaf nodes equal to the sum of all values of nodes of their children, where each node has the following structure: | Before outlining the solution, consider that a binary tree can satisfy the O(logn) requirement for both the Add(i, y) and Partial-sum(i) functions. In so doing, we initialize the binary tree with all non-leaf nodes equal to the sum of all values of nodes of their children, where each node has the following structure: | ||
| − | class BNode { | + | class BNode { |
| − | + | int min; // minimum index of A[] contained by a child | |
| − | + | int max; // maximum index of A[] contained by a child | |
| − | + | int value; // sum of A[min..max] | |
| − | } | + | } |
| − | Then, Add(i, y) will add y | + | Then, <math>Add(i, y)</math> will add <math>y</math> to the value of each tree node, starting from the root, as well as the leaves defined in <math>A</math>. Likewise, <math>Partial-sum(i)</math> is implemented recursively using the structure of the tree to ensure a clean partition of sections of A. |
Unfortunately, the problem allows only an n-size array as a workspace. However, consider that a binary tree with n leaves will have no more than n - 1 non-leaf nodes. Using the heapsort's method of organizing the non-leaf nodes in an array (see heapsort), we can satisfy this requirement: | Unfortunately, the problem allows only an n-size array as a workspace. However, consider that a binary tree with n leaves will have no more than n - 1 non-leaf nodes. Using the heapsort's method of organizing the non-leaf nodes in an array (see heapsort), we can satisfy this requirement: | ||
| − | Let S[1..m] (m < n) be such an array of BNode objects. | + | Let <math>S[1..m] (m < n)</math> be such an array of BNode objects. |
| + | |||
| + | <math>S[0]</math> is the root, with value equal to the sum of <math>A[0..n]</math>. | ||
| + | <math>S[1]</math> is root's left child, with value equal to the sum <math>A[0..n/2]</math>. | ||
| + | <math>S[2]</math> is root's right child, with value equal to the sum of <math>A[n/2+1..n]</math>. | ||
| − | S[ | + | In general, <math>S[i]</math> will have value equal to the sum of <math>S[i]</math>'s children at <math>S[2*i+1]</math> and <math>S[2*i +2]</math>. See solution in Java below. |
| − | S[ | ||
| − | S[2] | ||
| − | + | public class SumKeeper { | |
| + | private float[] A; | ||
| + | private BNode[] S; | ||
| + | private int sMax; | ||
| + | class BNode { | ||
| + | BNode(int min, int max, float value) { | ||
| + | this.min = min; | ||
| + | this.max = max; | ||
| + | this.value = value; | ||
| + | } | ||
| + | int min; | ||
| + | int max; | ||
| + | float value; | ||
| + | } | ||
| + | public SumKeeper(float[] A) { | ||
| + | this.A = A; | ||
| + | int ln2 = (int)Math.ceil(Math.log(A.length) / Math.log(2)); | ||
| + | this.S = new BNode[(0x1 << ln2) - 1]; | ||
| + | initS(0, A.length - 1, 0); | ||
| + | } | ||
| + | private void initS(int min, int max, int sNode) { | ||
| + | if(sNode > sMax) sMax = sNode; | ||
| + | if(min >= max) | ||
| + | S[sNode] = new BNode(min, max, A[min]); | ||
| + | else if (min == max - 1) | ||
| + | S[sNode] = new BNode(min, max, A[min] + A[max]); | ||
| + | else { | ||
| + | int mid = min + (max - min) / 2; | ||
| + | initS(min, mid, 2 * sNode + 1); | ||
| + | initS(mid + 1, max, 2 * sNode + 2); | ||
| + | float sum = S[2 * sNode + 1].value + S[2 * sNode + 2].value; | ||
| + | S[sNode] = new BNode(min, max, sum); | ||
| + | } | ||
| + | } | ||
| + | public void add(int i, float y) { | ||
| + | if(i - 1 > A.length) throw new IndexOutOfBoundsException(); | ||
| + | A[i] += y; | ||
| + | addS(i, y, 0); | ||
| + | } | ||
| + | private void addS(int i, float y, int sNode) { | ||
| + | if(sNode > sMax) return; | ||
| + | S[sNode].value += y; | ||
| + | int mid = S[sNode].min + (S[sNode].max - S[sNode].min) / 2; | ||
| + | if(mid >= i) { | ||
| + | addS(i, y, 2 * sNode + 1); | ||
| + | } else { | ||
| + | addS(i, y, 2 * sNode + 2); | ||
| + | } | ||
| + | } | ||
| + | public float partialSum(int i) { | ||
| + | return partialSum(i, 0); | ||
| + | } | ||
| + | private float partialSum(int i, int sNode) { | ||
| + | if(sNode > sMax) return A[i]; | ||
| + | int mid = S[sNode].min + (S[sNode].max - S[sNode].min) / 2; | ||
| + | if(S[sNode].max == i) { | ||
| + | return S[sNode].value; | ||
| + | } else if(mid >= i) { | ||
| + | return partialSum(i, 2 * sNode + 1); | ||
| + | } else { | ||
| + | return S[2 * sNode + 1].value + partialSum(i, 2 * sNode + 2); | ||
| + | } | ||
| + | } | ||
| + | } | ||
Revision as of 19:53, 9 July 2017
Before outlining the solution, consider that a binary tree can satisfy the O(logn) requirement for both the Add(i, y) and Partial-sum(i) functions. In so doing, we initialize the binary tree with all non-leaf nodes equal to the sum of all values of nodes of their children, where each node has the following structure:
class BNode {
int min; // minimum index of A[] contained by a child
int max; // maximum index of A[] contained by a child
int value; // sum of A[min..max]
}
Then, $ Add(i, y) $ will add $ y $ to the value of each tree node, starting from the root, as well as the leaves defined in $ A $. Likewise, $ Partial-sum(i) $ is implemented recursively using the structure of the tree to ensure a clean partition of sections of A.
Unfortunately, the problem allows only an n-size array as a workspace. However, consider that a binary tree with n leaves will have no more than n - 1 non-leaf nodes. Using the heapsort's method of organizing the non-leaf nodes in an array (see heapsort), we can satisfy this requirement:
Let $ S[1..m] (m < n) $ be such an array of BNode objects.
$ S[0] $ is the root, with value equal to the sum of $ A[0..n] $. $ S[1] $ is root's left child, with value equal to the sum $ A[0..n/2] $. $ S[2] $ is root's right child, with value equal to the sum of $ A[n/2+1..n] $.
In general, $ S[i] $ will have value equal to the sum of $ S[i] $'s children at $ S[2*i+1] $ and $ S[2*i +2] $. See solution in Java below.
public class SumKeeper {
private float[] A;
private BNode[] S;
private int sMax;
class BNode {
BNode(int min, int max, float value) {
this.min = min;
this.max = max;
this.value = value;
}
int min;
int max;
float value;
}
public SumKeeper(float[] A) {
this.A = A;
int ln2 = (int)Math.ceil(Math.log(A.length) / Math.log(2));
this.S = new BNode[(0x1 << ln2) - 1];
initS(0, A.length - 1, 0);
}
private void initS(int min, int max, int sNode) {
if(sNode > sMax) sMax = sNode;
if(min >= max)
S[sNode] = new BNode(min, max, A[min]);
else if (min == max - 1)
S[sNode] = new BNode(min, max, A[min] + A[max]);
else {
int mid = min + (max - min) / 2;
initS(min, mid, 2 * sNode + 1);
initS(mid + 1, max, 2 * sNode + 2);
float sum = S[2 * sNode + 1].value + S[2 * sNode + 2].value;
S[sNode] = new BNode(min, max, sum);
}
}
public void add(int i, float y) {
if(i - 1 > A.length) throw new IndexOutOfBoundsException();
A[i] += y;
addS(i, y, 0);
}
private void addS(int i, float y, int sNode) {
if(sNode > sMax) return;
S[sNode].value += y;
int mid = S[sNode].min + (S[sNode].max - S[sNode].min) / 2;
if(mid >= i) {
addS(i, y, 2 * sNode + 1);
} else {
addS(i, y, 2 * sNode + 2);
}
}
public float partialSum(int i) {
return partialSum(i, 0);
}
private float partialSum(int i, int sNode) {
if(sNode > sMax) return A[i];
int mid = S[sNode].min + (S[sNode].max - S[sNode].min) / 2;
if(S[sNode].max == i) {
return S[sNode].value;
} else if(mid >= i) {
return partialSum(i, 2 * sNode + 1);
} else {
return S[2 * sNode + 1].value + partialSum(i, 2 * sNode + 2);
}
}
}