diff --git a/README.md b/README.md index 2527adc54629f8eecd3f23ae60f7f43f0a47a4de..b5b8cc407a0ab4dd408574490bc52c952f9a3495 100644 --- a/README.md +++ b/README.md @@ -62,7 +62,14 @@ Software: ./main -d ../../database/elm_input.txt -c -m ../../database/marked_motifs.txt -r 4 -k NUMBER For each k, outputs the number of pairs of motifs with k discriminant positions: ./main -d ../../database/elm_input.txt -c -m ../../database/marked_motifs.txt -r 5 - - Python scripts: + + + We can as well generate any of the previous reports using a randomly selected subset of the database, for example to select 50% of motifs at random and calculate the number of aminoacids per coordinate: + ./main -d ../../database/elm_input.txt -c -m ../../database/marked_motifs.txt -r 1 -a 0.5 + + We can as well select a random sample of motifs, and in each of them uniformly at random we select uniformly at random a coordinate and set it to wildcard "." with the option -b %. For example if we select a motif class to modify with 0.5 of probability and the, over this modified datbaase we calculate the number of aminoacids per coordinate: + ./main -d ../../database/elm_input.txt -c -m ../../database/marked_motifs.txt -r 1 -b 0.5 + + Python scripts: Each python script has an input directoy and an output directory. To excecute the each python script it is enought to be inside the script folder and run 'python main.py' which will generate the output and place it in output directory. The rule is the script that has "empiric" in is name should have "structure_empiric_frequency.txt" in its input folder, while the script that has "theoretic" in its name should have "structure_theoretic_probabilities.txt" in its input folder. diff --git a/elm_processing/inc/Database.hpp b/elm_processing/inc/Database.hpp index a05ccd6d01ac95bfbbfa288c51f3eabd9fbf27e7..45b916ab984478332dac7f4d611a862bbba86b78 100644 --- a/elm_processing/inc/Database.hpp +++ b/elm_processing/inc/Database.hpp @@ -3,6 +3,8 @@ #include "Header.hpp" #include "Motif_class.hpp" +#include <random> +#include <chrono> class Database { @@ -13,6 +15,10 @@ private: std::vector<Motif_class> motifs_eliminated; bool clean_ends; bool clean_marked; + + float database_sample_weight; + float database_modif_weight; + /* {a,b} always choose a, and for | always take the shortest one. */ @@ -32,13 +38,17 @@ private: std::vector<Motif_class> motif_database; void clean_marked_motifs(); - + + void database_sample(); + void database_modif(); + Motif_class modif_motif_class(Motif_class); + public: Database(); /* input: string location of file, bool true if modif */ - Database(std::string , bool, std::string); + Database(std::string , bool, std::string, float, float); std::vector<Motif_class> get_motif_database(); }; diff --git a/elm_processing/inc/Mdp_toolbox.hpp b/elm_processing/inc/Mdp_toolbox.hpp index 72b5b72932896754f70fd70419fb2869bb4cf363..3e7af5539df83c95ff1b881271df877baeb6e923 100644 --- a/elm_processing/inc/Mdp_toolbox.hpp +++ b/elm_processing/inc/Mdp_toolbox.hpp @@ -26,7 +26,7 @@ private: public: Mdp_toolbox(); - Mdp_toolbox(std::string, bool, std::string); + Mdp_toolbox(Database); std::vector<Motif_pair> get_pairs_k_discriminant_positions(int); int get_mdp(Motif_pair); std::vector<Motif_class> get_k_discriminant_motifs(Motif_class, int); diff --git a/elm_processing/inc/Report_manager.hpp b/elm_processing/inc/Report_manager.hpp index 6b628398e82714333746359d5dd0013ae5c3ea92..0c8844eb4ad15b02224ca62b70250d9b2e702713 100644 --- a/elm_processing/inc/Report_manager.hpp +++ b/elm_processing/inc/Report_manager.hpp @@ -1,17 +1,19 @@ #ifndef _REPORT_MANAGER_ #define _REPORT_MANAGER_ +#include "Database.hpp" #include "Mdp_toolbox.hpp" #include "Statistical_toolbox.hpp" class Report_manager{ + Database database; Mdp_toolbox mdp_toolbox; Statistical_toolbox statistical_toolbox; std::string separator = "\t"; public: //first argument is database location, the second argument is if we want to remove the endpoint that have more than 10 characters - Report_manager(std::string, bool, std::string); + Report_manager(std::string, bool, std::string, float, float); //mdp_toolbox reports std::stringstream number_of_aminoacids_per_coordinate(void); diff --git a/elm_processing/src/Database.cpp b/elm_processing/src/Database.cpp index 5d9b6ae093586eb20808819ea5654c275b25f792..28231c05b3dc514958767338f2aa85bce651c39a 100644 --- a/elm_processing/src/Database.cpp +++ b/elm_processing/src/Database.cpp @@ -2,7 +2,7 @@ Database::Database(){} -Database::Database(std::string database_filename, bool clean_ends, std::string marked_motifs_filename) +Database::Database(std::string database_filename, bool clean_ends, std::string marked_motifs_filename, float database_sample_weight, float database_modif_weight) { load_motif_database(database_filename); @@ -13,6 +13,51 @@ Database::Database(std::string database_filename, bool clean_ends, std::string m this->clean_ends = clean_ends; if(clean_ends) clean_end_characters(); + + this->database_sample_weight = database_sample_weight; + if(database_sample_weight != 1) + database_sample(); + + this->database_modif_weight = database_modif_weight; + if(database_modif_weight != 0) + database_modif(); +} + + +void Database::database_sample() +{ + std::default_random_engine generator(std::chrono::steady_clock::now().time_since_epoch().count()); + std::bernoulli_distribution distribution(database_sample_weight); + + //keep the count of which entries to eliminate + std::vector<std::vector<Motif_class>::iterator> entries; + + for (std::vector<Motif_class>::iterator it = motif_database.begin(); it!= motif_database.end(); ++it) + if(!distribution(generator)) + entries.push_back(it); + + for(auto it : entries) + motif_database.erase(it); +} + +void Database::database_modif() +{ + std::default_random_engine generator; + std::bernoulli_distribution distribution(database_modif_weight); + + for (int i =0; i<motif_database.size(); i++) + if(distribution(generator)) + motif_database[i] = modif_motif_class(motif_database[i]); +} + +Motif_class Database::modif_motif_class(Motif_class motif_class) +{ + std::default_random_engine generator; + std::uniform_int_distribution<int> distribution(0, motif_class.get_structure().size()-1); + int index_to_modify = distribution(generator); + std::vector<std::string> new_sequence = motif_class.get_sequence(); + new_sequence[index_to_modify] = all; + return Motif_class(motif_class.get_name(), new_sequence); } void Database::clean_marked_motifs() diff --git a/elm_processing/src/Mdp_toolbox.cpp b/elm_processing/src/Mdp_toolbox.cpp index dc5201ca6b27de8a5ccde8a7892314288d0e6338..c67ace9c379fc7b83d0d580d25c79386b129f27b 100644 --- a/elm_processing/src/Mdp_toolbox.cpp +++ b/elm_processing/src/Mdp_toolbox.cpp @@ -2,9 +2,9 @@ Mdp_toolbox::Mdp_toolbox(){} -Mdp_toolbox::Mdp_toolbox(std::string database_location, bool clean_ends, std::string clean_marked_motifs) +Mdp_toolbox::Mdp_toolbox(Database database) { - database = Database(database_location, clean_ends, clean_marked_motifs); + this->database = database; for(auto motif_1: database.get_motif_database()) for(auto motif_2: database.get_motif_database()) diff --git a/elm_processing/src/Report_manager.cpp b/elm_processing/src/Report_manager.cpp index f9d06d025682236445c4e5b83d706a307048c314..092b4eaf966fe7c738adcd2814339ab9acf37fd7 100644 --- a/elm_processing/src/Report_manager.cpp +++ b/elm_processing/src/Report_manager.cpp @@ -1,8 +1,9 @@ #include "Report_manager.hpp" -Report_manager::Report_manager(std::string database_location, bool clean_ends, std::string marked_motifs_filename) +Report_manager::Report_manager(std::string database_location, bool clean_ends, std::string marked_motifs_filename, float database_sample, float database_modif) { - mdp_toolbox = Mdp_toolbox(database_location, clean_ends, marked_motifs_filename); + database = Database(database_location, clean_ends, marked_motifs_filename, database_sample, database_modif); + mdp_toolbox = Mdp_toolbox(database); statistical_toolbox = Statistical_toolbox(mdp_toolbox); } @@ -132,7 +133,7 @@ std::stringstream Report_manager::empiric_motif_probabilities() { std::stringstream output; - output << "Structure" << separator << "Probability" << std::endl; + //output << "Structure" << separator << "Probability" << std::endl; for(std::pair<std::vector<int>, float> element: statistical_toolbox.get_empiric_motif_probabilities()) output << element.first << separator << statistical_toolbox.compute_empiric_based_probability(element.first)<< separator << element.second << std::endl; @@ -143,7 +144,7 @@ std::stringstream Report_manager::all_lenghts_accumulated_probabilities() { std::stringstream output; - output << "Structure" << separator << "Probability" << std::endl; + //output << "Structure" << separator << "Probability" << std::endl; for(std::pair<std::vector<int>, float> element : statistical_toolbox.get_theoretic_motif_probabilities()) output << element.first << separator << element.second << std::endl; diff --git a/elm_processing/src/main.cpp b/elm_processing/src/main.cpp index eac45c76b394caa02d40f0486c29c080c02b6755..e2c16281119e5ca0a0ac43f35ab67a7890a32cc0 100644 --- a/elm_processing/src/main.cpp +++ b/elm_processing/src/main.cpp @@ -10,6 +10,7 @@ int main(int argc, char* argv[]) int report; int option; int discriminant_index = -1; + float database_sample = 1, database_modif = 0; std::stringstream help_message; help_message << "-h: Help message" << std::endl; @@ -18,9 +19,10 @@ int main(int argc, char* argv[]) help_message << "-m: Avoid motifs specified in the file" << std::endl; help_message << "-r: Number of report" << std::endl; help_message << "-k: Discriminant index" << std::endl;; + help_message << "-a: Percentage of database considered" << std::endl;; + help_message << "-b: Percentage of database to be modified" << std::endl; - - if((option = getopt(argc, argv, ":hd:cm:r:k:")) == -1) + if((option = getopt(argc, argv, ":hd:cm:r:k:a:b:")) == -1) { std::cout << help_message.str(); return 0; @@ -50,17 +52,27 @@ int main(int argc, char* argv[]) case 'r': report = std::atoi(optarg); break; + case 'a': + database_sample = std::strtof(optarg, NULL); + if(database_sample<0 or database_sample>1) + throw std::invalid_argument("The value of a must be between 0 and 1."); + break; + case 'b': + database_modif = std::strtof(optarg, NULL); + if(database_modif<0 or database_modif>1) + throw std::invalid_argument("The value of b must be between 0 and 1."); + break; case 'k': discriminant_index = std::atoi(optarg); break; } - }while((option = getopt(argc, argv, ":hd:cm:r:k:")) != -1); + }while((option = getopt(argc, argv, ":hd:cm:r:k:a:b:")) != -1); //Make sure that if report 3 or 4 is invoked we have specified the discriminant_index if((report == 3 or report == 4) and discriminant_index == -1) throw std::invalid_argument( "The parameter -k is missing." ); - Report_manager report_manager(database_location, clean_ends, marked_motifs_filename); + Report_manager report_manager(database_location, clean_ends, marked_motifs_filename, database_sample, database_modif); switch(report) { diff --git a/python_scripts/accumulated_probability_according_to_empiric_mdp/README.md b/python_scripts/accumulated_probability_according_to_empiric_mdp/README.md new file mode 100644 index 0000000000000000000000000000000000000000..b90496085419fd728c9bbc305c1b54c2810c768c --- /dev/null +++ b/python_scripts/accumulated_probability_according_to_empiric_mdp/README.md @@ -0,0 +1,70 @@ +Generate input: we execute the following commands from the folder elm_processing/bin +1) ./main -d ../../database/elm_input.txt -c -m ../../database/marked_motifs.txt -r 6 >> structure_empiric_frequency.txt +2) ./main -d ../../database/elm_input.txt -c -m ../../database/marked_motifs.txt -r 6 >> structure_empiric_frequency.txt -a 0.25 >> structure_empiric_frequency_sample_25_i.txt +3) ./main -d ../../database/elm_input.txt -c -m ../../database/marked_motifs.txt -r 6 >> structure_empiric_frequency.txt -a 0.5 >> structure_empiric_frequency_sample_5_i.txt +4) ./main -d ../../database/elm_input.txt -c -m ../../database/marked_motifs.txt -r 6 >> structure_empiric_frequency.txt -b 0.25 >> structure_empiric_frequency_modif_25_i.txt +5) ./main -d ../../database/elm_input.txt -c -m ../../database/marked_motifs.txt -r 6 >> structure_empiric_frequency.txt -b 0.5 >> structure_empiric_frequency_modif_50_i.txt +6) ./main -d ../../database/elm_input.txt -c -m ../../database/marked_motifs.txt -r 6 >> structure_empiric_frequency.txt -b 1 >> structure_empiric_frequency_modif_100_i.txt + +Moreover, we execute 2,3,4,5 and 6 a total of 10 times each, where the "i" stands for the number of execution. + +Usage: python main.py -i INPUT_FILE_NAME -o OUTPUT_FILE_NAME_PREFIX + +Generate output: execute the following commands, or run ./generate_output.sh. + +python main.py -i input/structure_empiric_frequency.txt -o output/all_database/accumulated_probability_according_to_mdp + +python main.py -i input/structure_empiric_frequency_sample_25_1.txt -o output/sample_database_25_1/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_sample_25_2.txt -o output/sample_database_25_2/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_sample_25_3.txt -o output/sample_database_25_3/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_sample_25_4.txt -o output/sample_database_25_4/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_sample_25_5.txt -o output/sample_database_25_5/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_sample_25_6.txt -o output/sample_database_25_6/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_sample_25_7.txt -o output/sample_database_25_7/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_sample_25_8.txt -o output/sample_database_25_8/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_sample_25_9.txt -o output/sample_database_25_9/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_sample_25_10.txt -o output/sample_database_25_10/accumulated_probability_according_to_mdp + +python main.py -i input/structure_empiric_frequency_sample_50_1.txt -o output/sample_database_50_1/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_sample_50_2.txt -o output/sample_database_50_2/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_sample_50_3.txt -o output/sample_database_50_3/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_sample_50_4.txt -o output/sample_database_50_4/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_sample_50_5.txt -o output/sample_database_50_5/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_sample_50_6.txt -o output/sample_database_50_6/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_sample_50_7.txt -o output/sample_database_50_7/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_sample_50_8.txt -o output/sample_database_50_8/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_sample_50_9.txt -o output/sample_database_50_9/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_sample_50_10.txt -o output/sample_database_50_10/accumulated_probability_according_to_mdp + +python main.py -i input/structure_empiric_frequency_modif_25_1.txt -o output/modif_database_25_1/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_25_2.txt -o output/modif_database_25_2/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_25_3.txt -o output/modif_database_25_3/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_25_4.txt -o output/modif_database_25_4/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_25_5.txt -o output/modif_database_25_5/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_25_6.txt -o output/modif_database_25_6/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_25_7.txt -o output/modif_database_25_7/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_25_8.txt -o output/modif_database_25_8/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_25_9.txt -o output/modif_database_25_9/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_25_10.txt -o output/modif_database_25_10/accumulated_probability_according_to_mdp + +python main.py -i input/structure_empiric_frequency_modif_50_1.txt -o output/modif_database_50_1/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_50_2.txt -o output/modif_database_50_2/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_50_3.txt -o output/modif_database_50_3/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_50_4.txt -o output/modif_database_50_4/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_50_5.txt -o output/modif_database_50_5/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_50_6.txt -o output/modif_database_50_6/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_50_7.txt -o output/modif_database_50_7/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_50_8.txt -o output/modif_database_50_8/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_50_9.txt -o output/modif_database_50_9/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_50_10.txt -o output/modif_database_50_10/accumulated_probability_according_to_mdp + +python main.py -i input/structure_empiric_frequency_modif_100_1.txt -o output/modif_database_100_1/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_100_2.txt -o output/modif_database_100_2/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_100_3.txt -o output/modif_database_100_3/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_100_4.txt -o output/modif_database_100_4/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_100_5.txt -o output/modif_database_100_5/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_100_6.txt -o output/modif_database_100_6/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_100_7.txt -o output/modif_database_100_7/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_100_8.txt -o output/modif_database_100_8/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_100_9.txt -o output/modif_database_100_9/accumulated_probability_according_to_mdp +python main.py -i input/structure_empiric_frequency_modif_100_10.txt -o output/modif_database_100_10/accumulated_probability_according_to_mdp diff --git a/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency.txt b/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency.txt index 1215e1c0d28f12c4e0e669807a4a6174105d0d90..4c24fbab0ecb8eb6a95c7df38f6c9874670f5c37 100644 --- a/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency.txt +++ b/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency.txt @@ -1,137 +1,137 @@ -1 0,00581395 0.00581395 -1,1 0,0181686 0.0116279 -1,2 0,0145349 0.0232558 -1,3 0,00363372 0.00581395 -1,6 0,00363372 0.00581395 -1,1,1 0,0184219 0.0290698 -1,1,2 0,010628 0.00581395 -1,1,9 0,0021256 0.00581395 -1,1,19 0,0042512 0.00581395 -1,1,20 0,00354267 0.00581395 -1,2,19 0,00163508 0.00581395 -1,2,20 0,00136256 0.00581395 -1,4,16 0,000327015 0.00581395 -2,6,20 0,000157219 0.0116279 -3,4,5 2,5155e-05 0.00581395 -5,6,20 6,28875e-05 0.00581395 -1,1,1,1 0,0094494 0.0116279 -1,1,1,2 0,02008 0.00581395 -1,1,1,20 0,00974469 0.0174419 -1,1,2,2 0,0160012 0.00581395 -1,1,2,3 0,00752999 0.00581395 -1,1,2,19 0,00470624 0.00581395 -1,1,2,20 0,0155306 0.0174419 -1,1,3,3 0,000885881 0.00581395 -1,1,4,5 0,000249154 0.00581395 -1,1,5,7 0,000581359 0.00581395 -1,1,6,20 0,000456782 0.00581395 -1,1,7,20 0,00319748 0.00581395 -1,1,9,20 0,000456782 0.00581395 -1,1,20,20 0,0025123 0.0174419 -1,2,2,2 0,0056671 0.00581395 -1,2,2,3 0,00400031 0.00581395 -1,2,2,20 0,00825063 0.00581395 -1,2,4,20 0,00145599 0.0116279 -1,2,7,20 0,00339732 0.00581395 -1,2,15,19 0,00014707 0.00581395 -1,2,20,20 0,00266932 0.0232558 -1,3,20,20 0,000628076 0.00581395 -1,5,20,20 0,000235528 0.00581395 -1,7,7,7 4,94559e-05 0.00581395 -2,2,2,3 0,000708387 0.00581395 -2,2,2,20 0,00146105 0.00581395 -2,2,3,19 0,000312524 0.00581395 -2,2,7,20 0,000902413 0.00581395 -2,3,19,19 4,59594e-05 0.00581395 -1,1,1,1,20 0,00740782 0.00581395 -1,1,1,2,3 0,00296194 0.00581395 -1,1,1,2,20 0,012144 0.0116279 -1,1,1,3,20 0,00291455 0.00581395 -1,1,1,4,20 0,00194304 0.00581395 -1,1,1,19,19 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a/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency_modif_100_1.txt b/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency_modif_100_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..6524a8ef6f06f91565548f684a8fb9311ea7f94c --- /dev/null +++ b/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency_modif_100_1.txt @@ -0,0 +1,120 @@ +1,1,1,1,1,1,1,1,1,1,20,20,20 0.000188182 0.00581395 +1,1,1,1,1,1,2,4,20,20,20,20,20,20 6.98122e-05 0.00581395 +1,1,1,1,1,2,3,4,20 1.52975e-05 0.00581395 +1,1,1,1,1,3,3,20,20,20,20 4.30549e-05 0.00581395 +1,1,1,1,2,2,2,3,3,20,20,20,20,20,20 0.0001011 0.00581395 +1,1,1,1,2,2,2,20 0.000139712 0.0116279 +1,1,1,1,20,20 0.00457185 0.00581395 +1,1,1,1,20,20,20,20 0.000102888 0.00581395 +1,1,1,1,20,20,20,20,20,20,20,20 6.18359e-05 0.00581395 +1,1,1,2,2,2,20 0.000101617 0.00581395 +1,1,1,2,2,2,20,20,20,20,20 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0.0212766 +1,3 0.01 0.0212766 +1,3,3,3,3,5,20,20 4.89214e-05 0.0212766 +1,3,20,20 0.000668449 0.0212766 +2,2,2,2,2,3,4,20,20 3.02664e-05 0.0212766 +2,2,2,3 0.000573293 0.0212766 +2,2,4,4,20,20,20 8.28977e-05 0.0212766 +3,3,3,4,16,16,20 1.27739e-05 0.0212766 diff --git a/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency_sample_25_7.txt b/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency_sample_25_7.txt new file mode 100644 index 0000000000000000000000000000000000000000..3b57efe40b572165dc57e99ff050ab6728af935e --- /dev/null +++ b/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency_sample_25_7.txt @@ -0,0 +1,34 @@ +1 0.027027 0.0294118 +1,1,1 0.0312813 0.0294118 +1,1,1,1,1,3,3,4,20,20,20 0.000852995 0.0294118 +1,1,1,1,1,20,20,20 0.00695925 0.0294118 +1,1,1,1,2,2 0.00351255 0.0294118 +1,1,1,1,2,2,2,2,3,3,20,20,20,20,20 0.000461202 0.0294118 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0.0294118 diff --git a/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency_sample_25_8.txt b/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency_sample_25_8.txt new file mode 100644 index 0000000000000000000000000000000000000000..d925a935378b7b92876e413ad728a3a8a8663d2c --- /dev/null +++ b/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency_sample_25_8.txt @@ -0,0 +1,37 @@ +1 0.0238095 0.025641 +1,1,1,1,1,20 0.00219387 0.025641 +1,1,1,1,2,2,2,2,3,3,20,20,20,20,20 0.000406297 0.025641 +1,1,1,1,2,2,2,3 0.000480603 0.025641 +1,1,1,2,20 0.00557511 0.025641 +1,1,1,2,20,20 0.0046277 0.0512821 +1,1,1,4,20 0.00139378 0.025641 +1,1,1,20,20 0.00174222 0.025641 +1,1,2,2,2,5,20,20,20,20,20,20,20 0.0006499 0.025641 +1,1,2,2,3,19,19,19,19 0.000115253 0.025641 +1,1,2,3 0.00867769 0.025641 +1,1,2,3,5 0.00119467 0.025641 +1,1,2,5,5,20,20,20,20,20,20,20 0.000108991 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b/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency_sample_25_9.txt new file mode 100644 index 0000000000000000000000000000000000000000..32de77f6a6e2a1deae835bc895a4e5e32f235aab --- /dev/null +++ b/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency_sample_25_9.txt @@ -0,0 +1,44 @@ +1 0.0192308 0.0204082 +1,1 0.0216346 0.0204082 +1,1,1 0.0405192 0.0408163 +1,1,1,1,1,20,20,20 0.000209066 0.0204082 +1,1,1,1,2,2,2,2,3,3,20,20,20,20,20 0.000328163 0.0204082 +1,1,1,1,2,2,2,3 0.000316108 0.0204082 +1,1,1,1,2,3,20 0.000310714 0.0204082 +1,1,1,1,5,10 0.000106088 0.0204082 +1,1,1,2,4,20,20 0.00124286 0.0204082 +1,1,1,2,20,20 0.00302038 0.0408163 +1,1,1,3,20 0.00653446 0.0204082 +1,1,1,19,19 0.000453782 0.0204082 +1,1,1,20,20 0.00490085 0.0612245 +1,1,2 0.0151947 0.0204082 +1,1,2,2 0.0118884 0.0204082 +1,1,2,2,2,5,20,20,20,20,20,20,20 0.000524919 0.0204082 +1,1,2,2,3,19,19,19,19 9.30887e-05 0.0204082 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--git a/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency_sample_50_1.txt b/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency_sample_50_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..f21e0b741d4312c722a4180736f9b250e3bb62a8 --- /dev/null +++ b/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency_sample_50_1.txt @@ -0,0 +1,78 @@ +1 0.0107527 0.0111111 +1,1 0.0168011 0.0111111 +1,1,1 0.0183513 0.0222222 +1,1,1,1 0.0170616 0.0222222 +1,1,1,1,1,1,1,1,1,1,1,20,20 0.00311241 0.0111111 +1,1,1,1,1,3,3,4,20,20,20 0.000113015 0.0111111 +1,1,1,1,1,20 0.00451108 0.0111111 +1,1,1,1,2,2 0.00211457 0.0111111 +1,1,1,1,2,2,2,3 8.05114e-05 0.0111111 +1,1,1,1,2,3,20 0.000152327 0.0111111 +1,1,1,2 0.0276236 0.0111111 +1,1,1,2,2,2,3,20,20,20,20 0.000139061 0.0111111 +1,1,1,2,2,3,4,4,6,7,9,20 2.55553e-07 0.0111111 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a/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency_sample_50_8.txt b/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency_sample_50_8.txt new file mode 100644 index 0000000000000000000000000000000000000000..207314c41110abcd70a02bac9987457eb6204ea0 --- /dev/null +++ b/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency_sample_50_8.txt @@ -0,0 +1,80 @@ +1 0.01 0.0103093 +1,1 0.018 0.0103093 +1,1,1 0.0282094 0.0412371 +1,1,1,1 0.0107104 0.0103093 +1,1,1,1,1,20,20,20 9.76563e-05 0.0103093 +1,1,1,1,2,2 0.00202312 0.0103093 +1,1,1,1,2,2,2,2,3,3,20,20,20,20,20 0.000170645 0.0103093 +1,1,1,1,5,10 3.344e-05 0.0103093 +1,1,1,1,20 0.00670722 0.0103093 +1,1,1,1,20,20 0.00524339 0.0103093 +1,1,1,1,20,20,20 6.52382e-05 0.0103093 +1,1,1,2 0.0230685 0.0103093 +1,1,1,2,2,2,2,3,3,4,20 7.2898e-05 0.0103093 +1,1,1,2,2,2,3,20,20,20,20 0.000431232 0.0103093 +1,1,1,2,2,3,4,4,6,7,9,20 1.23483e-07 0.0103093 +1,1,1,2,2,20,20,20,20,20,20,20 3.16776e-05 0.0103093 +1,1,1,2,4,20,20 0.000383217 0.0103093 +1,1,1,2,6,20,20,20 6.78168e-05 0.0103093 +1,1,1,2,20 0.0113819 0.0103093 +1,1,1,2,20,20 0.00623538 0.0206186 +1,1,1,3,3,20,20,20,20,20,20 3.62204e-05 0.0103093 +1,1,1,4,20 0.00243899 0.0103093 +1,1,1,4,20,20 0.00396797 0.0103093 +1,1,1,20 0.0115343 0.0206186 +1,1,1,20,20 0.00426823 0.0309278 +1,1,1,20,20,20 0.00264531 0.0103093 +1,1,2 0.0158678 0.0103093 +1,1,2,2 0.0186322 0.0103093 +1,1,2,2,2,5,20,20,20,20,20,20,20 0.000272958 0.0103093 +1,1,2,2,3,4,4 0.000161156 0.0103093 +1,1,2,2,3,20,20,20,20,20,20,20,20,20,20,20,20 0.000272116 0.0103093 +1,1,2,2,20 0.00724305 0.0206186 +1,1,2,3 0.0088725 0.0103093 +1,1,2,3,4,5,6,19,20 5.90094e-06 0.0103093 +1,1,2,3,20 0.00103472 0.0103093 +1,1,2,5,5,20,20,20,20,20,20,20 1.58388e-05 0.0103093 +1,1,2,19,19 0.000369544 0.0103093 +1,1,2,19,19,20 0.000120374 0.0103093 +1,1,2,20 0.0186322 0.0309278 +1,1,2,20,20 0.00543229 0.0103093 +1,1,2,20,20,20 0.00235933 0.0206186 +1,1,3,20,20,20,20,20 9.11458e-05 0.0103093 +1,1,4,4,20,20 0.00112605 0.0103093 +1,1,4,5 0.000169 0.0103093 +1,1,4,5,19,19,19,19 2.96699e-07 0.0103093 +1,1,5,20,20,20,20 1.27388e-05 0.0103093 +1,1,6,20 0.00088725 0.0103093 +1,1,6,20,20,20 0.000214485 0.0103093 +1,1,19 0.00528926 0.0103093 +1,1,20,20 0.00310537 0.0206186 +1,2 0.018 0.0309278 +1,2,2,2,20 0.00204854 0.0103093 +1,2,2,3,3,19,19,19,19,19,19,20,20,20,20,20,20,20,20,20 6.14417e-05 0.0103093 +1,2,2,3,4,7,20,20,20,20 7.168e-05 0.0103093 +1,2,2,4,4,4 5.47987e-05 0.0103093 +1,2,2,4,6,6,20 5.00924e-05 0.0103093 +1,2,2,4,20,20 0.00105214 0.0103093 +1,2,2,20 0.0100327 0.0103093 +1,2,3,4,4,5,6 4.95864e-05 0.0103093 +1,2,3,7,8,20,20,20,20,20,20,20,20,20 7.21622e-05 0.0103093 +1,2,4,5,6,19,19,20,20,20,20,20 6.20882e-06 0.0103093 +1,2,4,20 0.001911 0.0103093 +1,2,5,5,20 0.000125421 0.0103093 +1,2,7,20 0.0009555 0.0103093 +1,2,15,19 0.000364 0.0103093 +1,2,20,20 0.00334425 0.0309278 +1,3 0.006 0.0103093 +1,3,3,20,20,20 2.31876e-05 0.0103093 +1,3,20,20 0.00079625 0.0103093 +1,4,4,13,19 4.79927e-06 0.0103093 +1,6,11,20,20 2.35164e-05 0.0103093 +2,2,2,2,2,3,4,20,20 3.58482e-05 0.0103093 +2,2,2,2,3,20,20,20 8.58503e-06 0.0103093 +2,2,2,3 0.0008575 0.0103093 +2,2,3,19 0.00049 0.0103093 +2,2,20,20,20 0.000162952 0.0103093 +2,3,19,19 9.33333e-05 0.0103093 +2,6,20 0.000165289 0.0206186 +3,3,3,3,3,4,20,20 3.71028e-06 0.0103093 +3,3,3,4,16,16,20 1.98213e-06 0.0103093 diff --git a/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency_sample_50_9.txt b/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency_sample_50_9.txt new file mode 100644 index 0000000000000000000000000000000000000000..1f2db1f3ffad014a485ffc84c0ebe33874e704db --- /dev/null +++ b/python_scripts/accumulated_probability_according_to_empiric_mdp/input/structure_empiric_frequency_sample_50_9.txt @@ -0,0 +1,77 @@ +1,1 0.0143369 0.0111111 +1,1,1 0.0337232 0.0555556 +1,1,1,1 0.0106979 0.0111111 +1,1,1,1,1,1,1,1,1,1,1,20,20 0.00016187 0.0111111 +1,1,1,1,1,20 0.0033725 0.0111111 +1,1,1,1,1,20,20,20 5.34616e-05 0.0111111 +1,1,1,1,5,10 5.85503e-05 0.0111111 +1,1,1,2 0.0207846 0.0111111 +1,1,1,2,2,3,4,4,6,7,9,20 2.55553e-07 0.0111111 +1,1,1,2,2,20,20,20,20,20,20,20 5.25055e-05 0.0111111 +1,1,1,2,4,20,20 0.00152134 0.0111111 +1,1,1,2,6,20,20,20 3.80172e-05 0.0111111 +1,1,1,2,20 0.0118115 0.0111111 +1,1,1,2,20,20 0.00640248 0.0222222 +1,1,1,3,3,20,20,20,20,20,20 0.000772064 0.0111111 +1,1,1,3,20 0.00492144 0.0111111 +1,1,1,4,20,20 0.0026677 0.0111111 +1,1,1,20 0.0103923 0.0111111 +1,1,1,20,20 0.00516752 0.0444444 +1,1,1,20,20,20 0.00240093 0.0111111 +1,1,2 0.0159742 0.0111111 +1,1,2,2 0.015143 0.0111111 +1,1,2,2,2,3,4,20,20,20 0.000150503 0.0111111 +1,1,2,2,2,5,20,20,20,20,20,20,20 8.76104e-06 0.0111111 +1,1,2,2,2,20,20,20 8.11033e-05 0.0111111 +1,1,2,2,3,4,4 0.000120792 0.0111111 +1,1,2,3,4,5,6,19,20 3.1247e-06 0.0111111 +1,1,2,3,5 0.00136077 0.0111111 +1,1,2,3,20 0.00571523 0.0111111 +1,1,2,5,5,20,20,20,20,20,20,20 1.57516e-05 0.0111111 +1,1,2,5,20,20 0.00120046 0.0111111 +1,1,2,6,7 9.07179e-05 0.0111111 +1,1,2,19 0.00534461 0.0111111 +1,1,2,20 0.015143 0.0111111 +1,1,2,20,20 0.00600099 0.0222222 +1,1,2,20,20,20 0.00270105 0.0111111 +1,1,3,3 0.00130995 0.0111111 +1,1,3,20,20,20,20 0.000125743 0.0111111 +1,1,3,20,20,20,20,20 0.000120666 0.0111111 +1,1,4,5 0.000209592 0.0111111 +1,1,4,5,19,19,19,19 8.39896e-08 0.0111111 +1,1,4,20,20,20,20 0.000440102 0.0111111 +1,1,5,20,20,20,20 6.28717e-05 0.0111111 +1,1,6,20 0.000890768 0.0111111 +1,1,6,20,20,20 0.000225087 0.0111111 +1,1,9,20 0.000890768 0.0111111 +1,1,20,20 0.00252384 0.0222222 +1,2 0.00716846 0.0111111 +1,2,2,2,20 0.00176988 0.0111111 +1,2,2,2,20,20,20,20,20 5.14236e-05 0.0111111 +1,2,2,3,3,19,19,19,19,19,19,20,20,20,20,20,20,20,20,20 6.60663e-05 0.0111111 +1,2,2,3,20,20 0.000900349 0.0222222 +1,2,2,4,4,4 3.21627e-05 0.0111111 +1,2,2,4,6,6,20 7.3954e-05 0.0111111 +1,2,2,4,20,20 0.00112544 0.0111111 +1,2,2,20 0.0073552 0.0111111 +1,2,2,20,20 0.00232296 0.0111111 +1,2,4,20 0.00173063 0.0111111 +1,2,5,5,20 0.000331852 0.0111111 +1,2,7,20 0.000865317 0.0111111 +1,2,15,19 0.000305406 0.0111111 +1,2,20 0.00168149 0.0111111 +1,2,20,20 0.00245173 0.0222222 +1,3,3,3,3,5,20,20 0.000135407 0.0111111 +1,3,3,20,20,20 0.000112544 0.0111111 +1,3,20,20 0.000721098 0.0111111 +1,4,16 0.000560497 0.0111111 +1,6 0.00716846 0.0111111 +2,2,2,2,2,3,4,20,20 0.000113895 0.0111111 +2,2,2,2,3,20,20,20 2.30694e-05 0.0111111 +2,2,2,3 0.000700495 0.0111111 +2,2,3,19 0.00037085 0.0111111 +2,2,4,4,20,20,20 0.000232955 0.0111111 +2,6,20 0.000176999 0.0111111 +3,3,3,3,3,4,20,20 4.33303e-05 0.0222222 +3,3,4,20,20 1.30094e-05 0.0111111 +5,6,20 5.89997e-05 0.0111111 diff --git a/python_scripts/accumulated_probability_according_to_empiric_mdp/main.py b/python_scripts/accumulated_probability_according_to_empiric_mdp/main.py index c87353722a1a79443364628d6d40af0b7ba6ed80..aee5e4189fb4e2563af6e6a7b5ccd334fa83d9d1 100644 --- a/python_scripts/accumulated_probability_according_to_empiric_mdp/main.py +++ b/python_scripts/accumulated_probability_according_to_empiric_mdp/main.py @@ -1,6 +1,8 @@ import sys import getopt from math import factorial, ceil +import argparse +import os class Motivo: def __init__(self,e,proba,frecuencia,cota): @@ -31,61 +33,69 @@ def kDisjuntez(e,k): cota = cota*20.0/e[i] return ceil(cota) -def main(): - print "Disjuntez\t Probabilidad 0.5\t Probabilidad 0.9\n" - for k in xrange(-1,21): - inputFilePath = "input/structure_empiric_frequency.txt" - inputFile = open(inputFilePath, "r") - outputFilePath = "output/accumulated_probability_according_to_mdp"+str(k)+".txt" - outputFile = open(outputFilePath,"w") - - motivos = [] - - frecuenciaTotal = 0 - - for line in inputFile: - collumns = line.split("\t") - e = [] - for ei in collumns[0].split(","): - e.append(int(ei)) - proba = float(collumns[1].replace(",",".")) - frecuencia = float(collumns[2]) - cota = 0 - if len(e)>= k and e[0]<=10: - if k==-1: - cota = fuertementeDisj(e) - elif k==0: - cota = ceroDisj(e) - elif k>0: - cota = kDisjuntez(e,k) +def main(inputFilePath, output_file_prefix): + print "Disjuntez\t Probabilidad 0.5\t Probabilidad 0.9\n" + for k in xrange(-1,21): + #inputFilePath = "input/structure_empiric_frequency.txt" + inputFile = open(inputFilePath, "r") + + directory = output_file_prefix.split("/")[1] + + if not os.path.exists("output/"+directory): + os.makedirs("output/"+directory) + + + outputFilePath = output_file_prefix+str(k)+".txt" + outputFile = open(outputFilePath,"w") + motivos = [] + frecuenciaTotal = 0 + for line in inputFile: + collumns = line.split("\t") + e = [] + for ei in collumns[0].split(","): + e.append(int(ei)) + proba = float(collumns[1].replace(",",".")) + frecuencia = float(collumns[2]) + cota = 0 + if len(e)>= k and e[0]<=10: + if k==-1: + cota = fuertementeDisj(e) + elif k==0: + cota = ceroDisj(e) + elif k>0: + cota = kDisjuntez(e,k) - frecuenciaTotal = frecuenciaTotal + frecuencia - m = Motivo(e,proba,frecuencia,cota) - motivos.append(m) + frecuenciaTotal = frecuenciaTotal + frecuencia + m= Motivo(e,proba,frecuencia,cota) + motivos.append(m) - #ordenamos de mayor a menor - motivos.sort(key=lambda x: x.cota, reverse=True) - outputFile.write("Motivo lineal\t Cota\t Probabilidad\t Frecuencia\t Frecuencia Acumulada\n"); - frecuenciaAcumulada = 0; + #ordenamos de mayor a menor + motivos.sort(key=lambda x: x.cota, reverse=True) + outputFile.write("Motivo lineal\t Cota\t Probabilidad\t Frecuencia\t Frecuencia Acumulada\n"); + frecuenciaAcumulada = 0; - s= str(k)+"\t" - flag1=True - flag2=True + s= str(k)+"\t" + flag1=True + flag2=True - for motivo in motivos: - frecuenciaAcumulada=frecuenciaAcumulada+motivo.frecuencia*1.0/frecuenciaTotal - outputFile.write(str(motivo.e)+"\t"+str(motivo.cota)+"\t"+str(motivo.proba)+"\t"+str(motivo.frecuencia*1.0/frecuenciaTotal)+"\t"+str(frecuenciaAcumulada)+"\n"); + for motivo in motivos: + frecuenciaAcumulada=frecuenciaAcumulada+motivo.frecuencia*1.0/frecuenciaTotal + outputFile.write(str(motivo.e)+"\t"+str(motivo.cota)+"\t"+str(motivo.proba)+"\t"+str(motivo.frecuencia*1.0/frecuenciaTotal)+"\t"+str(frecuenciaAcumulada)+"\n"); - if frecuenciaAcumulada >=0.5 and flag1: - flag1=False - s=s+ str(motivo.cota)+"\t" + if frecuenciaAcumulada >=0.5 and flag1: + flag1=False + s=s+ str(motivo.cota)+"\t" - if frecuenciaAcumulada >=0.9 and flag2: - flag2=False - s=s+ str(motivo.cota)+"\n" - print s; - outputFile.close() - inputFile.close() + if frecuenciaAcumulada >=0.9 and flag2: + flag2=False + s=s+ str(motivo.cota)+"\n" + print s; + outputFile.close() + inputFile.close() if __name__ == "__main__": - sys.exit(main()) + parser = argparse.ArgumentParser() + parser.add_argument('-i', '--input') + parser.add_argument('-o', '--output') + args = parser.parse_args() + sys.exit(main(args.input, args.output))