-
Notifications
You must be signed in to change notification settings - Fork 1
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Merge pull request #2 from ayoshiaki/mdd
Mdd
- Loading branch information
Showing
17 changed files
with
1,289 additions
and
81 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,204 @@ | ||
| #include <iostream> | ||
| #include <vector> | ||
| #include <fstream> | ||
|
|
||
| #include "Consensus.hpp" | ||
| #include "ChiSquare.hpp" | ||
| #include "MaximalDependenceDecomposition.hpp" | ||
| #include "ProbabilisticModelCreatorClient.hpp" | ||
| #include "ContextTree.hpp" | ||
|
|
||
| using namespace tops; | ||
| using namespace std; | ||
|
|
||
| int main (int argc, char ** argv) | ||
| { | ||
| cout << "TesteMDD" << endl; | ||
|
|
||
| /***********************************************************/ | ||
| // Alphabet | ||
| AlphabetPtr alphabet = AlphabetPtr(new Alphabet()); | ||
| alphabet->createSymbol("A"); | ||
| alphabet->createSymbol("C"); | ||
| alphabet->createSymbol("G"); | ||
| alphabet->createSymbol("T"); | ||
|
|
||
| /***********************************************************/ | ||
| // Consensus Sequence | ||
| ConsensusSequence consensus_sequence; | ||
|
|
||
| vector<int> s1; | ||
| s1.push_back(0); s1.push_back(1); // a/c | ||
| Consensus c1(s1); | ||
| consensus_sequence.push_back(c1); | ||
|
|
||
| int x1[] = {0, 2, 2, 3}; // AGGT | ||
| for (int i = 0; i < 4; i++) { | ||
| vector<int> s; | ||
| s.push_back(x1[i]); | ||
| Consensus c(s); | ||
| consensus_sequence.push_back(c); | ||
| } | ||
|
|
||
| vector<int> s2; | ||
| s2.push_back(0); s2.push_back(2); // a/g | ||
| Consensus c2(s2); | ||
| consensus_sequence.push_back(c2); | ||
|
|
||
| int x2[] = {0, 2, 3}; // agt | ||
| for (int i = 0; i < 3; i++) { | ||
| vector<int> s; | ||
| s.push_back(x2[i]); | ||
| Consensus c(s); | ||
| consensus_sequence.push_back(c); | ||
| } | ||
|
|
||
| for (std::vector<Consensus>::iterator it = consensus_sequence.begin() ; it != consensus_sequence.end(); ++it) { | ||
| cout << it->str() << '\t'; | ||
| } | ||
| cout << endl; | ||
|
|
||
| /***********************************************************/ | ||
| // WMMs | ||
| ProbabilisticModelCreatorClient creator; | ||
| ProbabilisticModelPtr root = creator.create("_test2/root.txt"); | ||
| ProbabilisticModelPtr g5 = creator.create("_test2/g5.txt"); | ||
| ProbabilisticModelPtr h5 = creator.create("_test2/h5.txt"); | ||
| ProbabilisticModelPtr g5gm1 = creator.create("_test2/g5gm1.txt"); | ||
| ProbabilisticModelPtr g5hm1 = creator.create("_test2/g5hm1.txt"); | ||
| ProbabilisticModelPtr g5gm1am2 = creator.create("_test2/g5gm1am2.txt"); | ||
| ProbabilisticModelPtr g5gm1bm2 = creator.create("_test2/g5gm1bm2.txt"); | ||
| ProbabilisticModelPtr g5gm1am2u6 = creator.create("_test2/g5gm1am2u6.txt"); | ||
| ProbabilisticModelPtr g5gm1am2v6 = creator.create("_test2/g5gm1am2v6.txt"); | ||
|
|
||
| /***********************************************************/ | ||
| // MDD tree | ||
| MaximalDependenceDecompositionNodePtr mdd_root = MaximalDependenceDecompositionNodePtr( | ||
| new MaximalDependenceDecompositionNode("root", root, 7)); | ||
| MaximalDependenceDecompositionNodePtr mdd_g5 = MaximalDependenceDecompositionNodePtr( | ||
| new MaximalDependenceDecompositionNode("g5", g5, 2)); | ||
| MaximalDependenceDecompositionNodePtr mdd_h5 = MaximalDependenceDecompositionNodePtr( | ||
| new MaximalDependenceDecompositionNode("h5", h5, -1)); | ||
| MaximalDependenceDecompositionNodePtr mdd_g5gm1 = MaximalDependenceDecompositionNodePtr( | ||
| new MaximalDependenceDecompositionNode("g5gm1", g5gm1, 1)); | ||
| MaximalDependenceDecompositionNodePtr mdd_g5hm1 = MaximalDependenceDecompositionNodePtr( | ||
| new MaximalDependenceDecompositionNode("g5hm1", g5hm1, -1)); | ||
| MaximalDependenceDecompositionNodePtr mdd_g5gm1am2 = MaximalDependenceDecompositionNodePtr( | ||
| new MaximalDependenceDecompositionNode("g5gm1am2", g5gm1am2, 8)); | ||
| MaximalDependenceDecompositionNodePtr mdd_g5gm1bm2 = MaximalDependenceDecompositionNodePtr( | ||
| new MaximalDependenceDecompositionNode("g5gm1bm2", g5gm1bm2, -1)); | ||
| MaximalDependenceDecompositionNodePtr mdd_g5gm1am2u6 = MaximalDependenceDecompositionNodePtr( | ||
| new MaximalDependenceDecompositionNode("g5gm1am2u6", g5gm1am2u6, -1)); | ||
| MaximalDependenceDecompositionNodePtr mdd_g5gm1am2v6 = MaximalDependenceDecompositionNodePtr( | ||
| new MaximalDependenceDecompositionNode("g5gm1am2v6", g5gm1am2v6, -1)); | ||
|
|
||
| mdd_root->setChildern(mdd_g5, mdd_h5); | ||
| mdd_g5->setChildern(mdd_g5gm1, mdd_g5hm1); | ||
| mdd_g5gm1->setChildern(mdd_g5gm1am2, mdd_g5gm1bm2); | ||
| mdd_g5gm1am2->setChildern(mdd_g5gm1am2u6, mdd_g5gm1am2v6); | ||
|
|
||
| /***********************************************************/ | ||
| // MDD definition | ||
|
|
||
| MaximalDependenceDecompositionPtr mdd = MaximalDependenceDecompositionPtr(new MaximalDependenceDecomposition()); | ||
| mdd->setAlphabet(alphabet); | ||
| mdd->setMDDTree(mdd_root); | ||
| mdd->setConsensusSequence(consensus_sequence); | ||
| ProbabilisticModelPtr consensus_model = creator.create("_test2/consensus_model.txt"); | ||
| mdd->setConsensusModel(consensus_model); | ||
|
|
||
| /***********************************************************/ | ||
| // Evaluate | ||
|
|
||
| Sequence s; | ||
| s.push_back(1);s.push_back(0);s.push_back(2);s.push_back(2);s.push_back(3);s.push_back(2);s.push_back(0);s.push_back(0);s.push_back(3); | ||
| cout << mdd->evaluate(s, 0, 9) << endl; | ||
|
|
||
| /***********************************************************/ | ||
| // Choose | ||
|
|
||
| srand(time(NULL)); | ||
| Sequence new_sequence; | ||
| mdd->choose(new_sequence, 9); | ||
|
|
||
| for (int i = 0; i < 9; i++) { | ||
| cout << new_sequence[i] << "\t"; | ||
| } | ||
| cout << endl; | ||
|
|
||
| /***********************************************************/ | ||
| // Criando SequenceEntryList | ||
| SequenceEntryList sequences; | ||
| for (int i = 0; i < 10; i++) { | ||
| SequenceEntryPtr se = SequenceEntryPtr(new SequenceEntry(alphabet)); | ||
| Sequence random_sequence; | ||
| mdd->choose(random_sequence, 9); | ||
| se->setSequence(random_sequence); | ||
| se->setName("s"); | ||
| sequences.push_back(se); | ||
| } | ||
|
|
||
| for (int i = 0; i < 10; i++) { | ||
| for (int j = 0; j < 10; j++) { | ||
| cout << sequences[i]->getSequence()[j]; | ||
| } | ||
| cout << endl; | ||
| } | ||
|
|
||
| /***********************************************************/ | ||
| // Treinando MDD | ||
| MaximalDependenceDecompositionPtr trained_mdd = MaximalDependenceDecompositionPtr(new MaximalDependenceDecomposition()); | ||
| trained_mdd->setAlphabet(alphabet); | ||
| trained_mdd->setConsensusSequence(consensus_sequence); | ||
|
|
||
| // ProbabilisticModelPtr consensus_model = creator.create("_test2/consensus_model.txt"); | ||
| trained_mdd->setConsensusModel(consensus_model); | ||
|
|
||
| trained_mdd->train(sequences, 2); | ||
|
|
||
| cout << "-------------------------" << endl; | ||
| Sequence new_sequence_from_trained_mdd; | ||
| trained_mdd->choose(new_sequence_from_trained_mdd, 9); | ||
|
|
||
| for (int i = 0; i < 9; i++) { | ||
| cout << new_sequence_from_trained_mdd[i] << "\t"; | ||
| } | ||
| cout << endl; | ||
|
|
||
| // std::map<std::string, double> w; | ||
| // ContextTreePtr tree = ContextTreePtr(new ContextTree(alphabet)); | ||
| // tree->initializeCounter(sequences, 0, w); | ||
| // tree->normalize(); | ||
|
|
||
| // cout << tree->getContext(0)->getDistribution()->str() << endl; | ||
|
|
||
| // cout << mdd->str() << endl; | ||
|
|
||
| cout << "--------------------------" << endl; | ||
| ProbabilisticModelPtr mdd_from_config = creator.create("_test2/mdd.txt"); | ||
| // cout << mdd_from_config->str() << endl; | ||
|
|
||
| // cout << trained_mdd->evaluate(new_sequence, 0, 9) << endl; | ||
| // cout << trained_mdd->evaluate(new_sequence, 0, 1) << endl; | ||
|
|
||
| new_sequence.push_back(0); | ||
| new_sequence.push_back(0); | ||
| new_sequence.push_back(0); | ||
| new_sequence.push_back(0); | ||
|
|
||
| mdd->initialize_prefix_sum_array(new_sequence); | ||
| // cout << mdd->evaluate(new_sequence, 0, 8); | ||
| cout << mdd->prefix_sum_array_compute(0, 1) << endl; | ||
| cout << mdd->prefix_sum_array_compute(0, 8) << endl; | ||
| cout << mdd->prefix_sum_array_compute(1, 9) << endl; | ||
| cout << mdd->prefix_sum_array_compute(2, 10) << endl; | ||
| cout << mdd->prefix_sum_array_compute(3, 11) << endl; | ||
| cout << mdd->prefix_sum_array_compute(4, 12) << endl; | ||
|
|
||
| return 0; | ||
| } | ||
|
|
||
|
|
||
|
|
||
|
|
||
|
|
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,78 @@ | ||
| #include "ChiSquare.hpp" | ||
|
|
||
| namespace tops { | ||
|
|
||
| double CHI_QUARE[31][9] = { | ||
| {0.00098, 1.64, 2.71, 3.84, 5.02, 6.63, 7.88, 10.83, 12.12}, | ||
| {0.051, 3.22, 4.61, 5.99, 7.38, 9.21, 10.60, 13.82, 15.20}, | ||
| {0.216, 4.64, 6.25, 7.81, 9.35, 11.34, 12.84, 16.27, 17.73}, | ||
| {0.48, 5.99, 7.78, 9.49, 11.14, 13.28, 14.86, 18.47, 20.00}, | ||
| {0.83, 7.29, 9.24, 11.07, 12.83, 15.09, 16.75, 20.51, 22.11}, | ||
| {1.24, 8.56, 10.64, 12.59, 14.45, 16.81, 18.55, 22.46, 24.10}, | ||
| {1.69, 9.80, 12.02, 14.07, 16.01, 18.48, 20.28, 24.32, 26.02}, | ||
| {2.18, 11.03, 13.36, 15.51, 17.53, 20.09, 21.95, 26.12, 27.87}, | ||
| {2.70, 12.24, 14.68, 16.92, 19.02, 21.67, 23.59, 27.88, 29.67}, | ||
| {3.25, 13.44, 15.99, 18.31, 20.48, 23.21, 25.19, 29.59, 31.42}, | ||
| {3.82, 14.63, 17.28, 19.68, 21.92, 24.73, 26.76, 31.26, 33.14}, | ||
| {4.40, 15.81, 18.55, 21.03, 23.34, 26.22, 28.30, 32.91, 34.82}, | ||
| {5.01, 16.98, 19.81, 22.36, 24.74, 27.69, 29.82, 34.53, 36.48}, | ||
| {5.63, 18.15, 21.06, 23.68, 26.12, 29.14, 31.32, 36.12, 38.11}, | ||
| {6.26, 19.31, 22.31, 25.00, 27.49, 30.58, 32.80, 37.70, 39.72}, | ||
| {6.91, 20.47, 23.54, 26.30, 28.85, 32.00, 34.27, 39.25, 41.31}, | ||
| {7.56, 21.61, 24.77, 27.59, 30.19, 33.41, 35.72, 40.79, 42.88}, | ||
| {8.23, 22.76, 25.99, 28.87, 31.53, 34.81, 37.16, 42.31, 44.43}, | ||
| {8.91, 23.90, 27.20, 30.14, 32.85, 36.19, 38.58, 43.82, 45.97}, | ||
| {9.59, 25.04, 28.41, 31.41, 34.17, 37.57, 40.00, 45.31, 47.50}, | ||
| {10.28, 26.17, 29.62, 32.67, 35.48, 38.93, 41.40, 46.80, 49.01}, | ||
| {10.98, 27.30, 30.81, 33.92, 36.78, 40.29, 42.80, 48.27, 50.51}, | ||
| {11.69, 28.43, 32.01, 35.17, 38.08, 41.64, 44.18, 49.73, 52.00}, | ||
| {12.40, 29.55, 33.20, 36.42, 39.36, 42.98, 45.56, 51.18, 53.48}, | ||
| {13.12, 30.68, 34.38, 37.65, 40.65, 44.31, 46.93, 52.62, 54.95}, | ||
| {16.79, 36.25, 40.26, 43.77, 46.98, 50.89, 53.67, 59.70, 62.16}, | ||
| {24.43, 47.27, 51.81, 55.76, 59.34, 63.69, 66.77, 73.40, 76.10}, | ||
| {32.36, 58.16, 63.17, 67.50, 71.42, 76.15, 79.49, 86.66, 89.56}, | ||
| {40.48, 68.97, 74.40, 79.08, 83.30, 88.38, 91.95, 99.61, 102.7}, | ||
| {57.15, 90.41, 96.58, 101.9, 106.6, 112.3, 116.3, 124.8, 128.3}, | ||
| {74.22, 111.7, 118.5, 124.3, 129.6, 135.8, 140.2, 149.4, 153.2} | ||
| }; | ||
|
|
||
| int chiPi(double p) { | ||
| double prob[] = {0.975, 0.2, 0.1, 0.05, 0.025, 0.01, 0.005, 0.001, 0.0005}; | ||
| int pi = 0; | ||
| for (int i = 0; i < 9; i++) { | ||
| if (p >= prob[i]) { | ||
| if (i == 0) | ||
| pi = 0; | ||
| else if (abs(p - prob[i]) > abs(p - prob[i-1])) | ||
| pi = i-1; | ||
| else | ||
| pi = i; | ||
| break; | ||
| } | ||
| } | ||
| return pi; | ||
| } | ||
|
|
||
| int chiDfi(int df) { | ||
| if (df <= 25) | ||
| return df-1; | ||
|
|
||
| int dfi = 30; | ||
| while ((df - dfi) > 0) { | ||
| dfi += 10; | ||
| if (dfi == 80) { | ||
| if (abs(df - 80) > abs(df - 100)) | ||
| return 30; | ||
| else | ||
| return 29; | ||
| } | ||
| } | ||
| return ((dfi - 30)/10 + 25); | ||
| } | ||
|
|
||
| double chiSquare(double p, int df) { | ||
| int pi = chiPi(p); | ||
| int dfi = chiDfi(df); | ||
| return CHI_QUARE[dfi][pi]; | ||
| } | ||
| } |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,36 @@ | ||
| /* | ||
| * ConfigurationReader.hpp | ||
| * | ||
| * Copyright 2011 Andre Yoshiaki Kashiwabara <[email protected]> | ||
| * Ígor Bonadio <[email protected]> | ||
| * Vitor Onuchic <[email protected]> | ||
| * Alan Mitchell Durham <[email protected]> | ||
| * | ||
| * This program is free software; you can redistribute it and/or modify | ||
| * it under the terms of the GNU General Public License as published by | ||
| * the Free Software Foundation; either version 3 of the License, or | ||
| * (at your option) any later version. | ||
| * | ||
| * This program is distributed in the hope that it will be useful, | ||
| * but WITHOUT ANY WARRANTY; without even the implied warranty of | ||
| * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the | ||
| * GNU General Public License for more details. | ||
| * | ||
| * You should have received a copy of the GNU General Public License | ||
| * along with this program; if not, write to the Free Software | ||
| * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, | ||
| * MA 02110-1301, USA. | ||
| */ | ||
|
|
||
| #ifndef CHI_SQUARE_HPP | ||
| #define CHI_SQUARE_HPP | ||
| #include <boost/shared_ptr.hpp> | ||
|
|
||
| #include "crossplatform.hpp" | ||
|
|
||
|
|
||
| namespace tops { | ||
| double chiSquare(double p, int df); | ||
| } | ||
|
|
||
| #endif |
Oops, something went wrong.