Python save_connection_matrix Beispiele

Beispiel #1

Datei: output_standardruns_smallerparams.py Projekt: bsmith89/mgs

TOT_PATHS = 150
TOT_ORGS = 100
GENES_PER_PATH = 15
PATHS_PER_ORG = 10
ORGS_PER_POP = 50
POPS = 10
SAMPLE_SIZE = int(1.5*TOT_GENES)
RUNS = 10

for run in range(RUNS):
    print run
    pops = make_pops.make_testable_pops(num_genes = TOT_GENES,
                                        num_pathways = TOT_PATHS,
                                        num_orgs = TOT_ORGS,
                                        genes_per_pathway = GENES_PER_PATH,
                                        pathways_per_org = PATHS_PER_ORG,
                                        orgs_per_pop = ORGS_PER_POP,
                                        num_pops = POPS)
    matrix = sample_pops.construct_network_matrix(pops, SAMPLE_SIZE)
    construct_matrix.save_connection_matrix("data_standardruns//data%s.dat" % \
                                            str(run).rjust(2,'0'), matrix)




##    print(make_pops.Pathway.extant_pathways.values()[0])
##    for pop in pops:
##        print(make_pops.Population.extant_populations[pop.id])
##        print(make_pops.Organism.extant_organisms[pop.id])
##        print(make_pops.Pathway.extant_pathways[pop.id])

Beispiel #2

Datei: output_standardruns_smallerparams_30pops.py Projekt: bsmith89/mgs

reload(construct_matrix)

TOT_GENES = 500
TOT_PATHS = 150
TOT_ORGS = 100
GENES_PER_PATH = 15
PATHS_PER_ORG = 10
ORGS_PER_POP = 50
POPS = 50
SAMPLE_SIZE = int(1.5 * TOT_GENES)
RUNS = 10

for run in range(RUNS):
    print run
    pops = make_pops.make_testable_pops(num_genes=TOT_GENES,
                                        num_pathways=TOT_PATHS,
                                        num_orgs=TOT_ORGS,
                                        genes_per_pathway=GENES_PER_PATH,
                                        pathways_per_org=PATHS_PER_ORG,
                                        orgs_per_pop=ORGS_PER_POP,
                                        num_pops=POPS)
    matrix = sample_pops.construct_network_matrix(pops, SAMPLE_SIZE)
    construct_matrix.save_connection_matrix("data_standardruns//data%s.dat" % \
                                            str(run).rjust(2,'0'), matrix)

##    print(make_pops.Pathway.extant_pathways.values()[0])
##    for pop in pops:
##        print(make_pops.Population.extant_populations[pop.id])
##        print(make_pops.Organism.extant_organisms[pop.id])
##        print(make_pops.Pathway.extant_pathways[pop.id])

Beispiel #3

Datei: output.py Projekt: bsmith89/mgs

reload(construct_matrix)

TOT_GENES = 1500
TOT_PATHS = 250
TOT_ORGS = 300
GENES_PER_PATH = 15
PATHS_PER_ORG = 50
ORGS_PER_POP = 200
POPS = 10
SAMPLE_SIZE = 1.5 * TOT_GENES
RUNS = 1

for run in range(10):
    print sample_size
    pops = make_pops.make_testable_pops(num_genes=TOT_GENES,
                                        num_pathways=TOT_PATHS,
                                        num_orgs=TOT_ORGS,
                                        genes_per_pathway=GENES_PER_PATH,
                                        pathways_per_org=PATHS_PER_ORG,
                                        orgs_per_pop=ORGS_PER_POP,
                                        num_pops=POPS)
    matrix = sample_pops.construct_network_matrix(pops, SAMPLE_SIZE)
    construct_matrix.save_connection_matrix(
        "data_standardruns//data%02d.dat" % run, matrix)

##    print(make_pops.Pathway.extant_pathways.values()[0])
##    for pop in pops:
##        print(make_pops.Population.extant_populations[pop.id])
##        print(make_pops.Organism.extant_organisms[pop.id])
##        print(make_pops.Pathway.extant_pathways[pop.id])

Beispiel #4

Datei: output.py Projekt: bsmith89/mgs

TOT_GENES = 1500
TOT_PATHS = 250
TOT_ORGS = 300
GENES_PER_PATH = 15
PATHS_PER_ORG = 50
ORGS_PER_POP = 200
POPS = 10
SAMPLE_SIZE = 1.5 * TOT_GENES
RUNS = 1

for run in range(10):
    print sample_size
    pops = make_pops.make_testable_pops(
        num_genes=TOT_GENES,
        num_pathways=TOT_PATHS,
        num_orgs=TOT_ORGS,
        genes_per_pathway=GENES_PER_PATH,
        pathways_per_org=PATHS_PER_ORG,
        orgs_per_pop=ORGS_PER_POP,
        num_pops=POPS,
    )
    matrix = sample_pops.construct_network_matrix(pops, SAMPLE_SIZE)
    construct_matrix.save_connection_matrix("data_standardruns//data%02d.dat" % run, matrix)


##    print(make_pops.Pathway.extant_pathways.values()[0])
##    for pop in pops:
##        print(make_pops.Population.extant_populations[pop.id])
##        print(make_pops.Organism.extant_organisms[pop.id])
##        print(make_pops.Pathway.extant_pathways[pop.id])

Beispiel #5

Datei: output_samplesize.py Projekt: bsmith89/mgs

TOT_GENES = 1500
TOT_PATHS = 250
TOT_ORGS = 300
GENES_PER_PATH = 15
PATHS_PER_ORG = 50
ORGS_PER_POP = 200
POPS = 10
RUNS = 2

for run in [1]:
    pops = make_pops.make_testable_pops(num_genes=TOT_GENES,
                                        num_pathways=TOT_PATHS,
                                        num_orgs=TOT_ORGS,
                                        genes_per_pathway=GENES_PER_PATH,
                                        pathways_per_org=PATHS_PER_ORG,
                                        orgs_per_pop=ORGS_PER_POP,
                                        num_pops=POPS)
    for sample_size in [100, 500, 1000, 1500, 2250, 3000, 9999]:
        print sample_size
        matrix = sample_pops.construct_network_matrix(pops, sample_size)
        construct_matrix.save_connection_matrix("data_samplesize//data%s_%s.dat"\
                                                % (str(sample_size).rjust(4,'0'),
                                                   str(run).rjust(2, '0')),
                                                matrix)

##  print(make_pops.Pathway.extant_pathways.values()[0])
##    for pop in pops:
##        print(make_pops.Population.extant_populations[pop.id])
##        print(make_pops.Organism.extant_organisms[pop.id])
##        print(make_pops.Pathway.extant_pathways[pop.id])

Beispiel #6

Datei: output_samplesize.py Projekt: bsmith89/mgs

TOT_PATHS = 250
TOT_ORGS = 300
GENES_PER_PATH = 15
PATHS_PER_ORG = 50
ORGS_PER_POP = 200
POPS = 10
RUNS = 2

for run in [1]:
    pops = make_pops.make_testable_pops(num_genes = TOT_GENES,
                                        num_pathways = TOT_PATHS,
                                        num_orgs = TOT_ORGS,
                                        genes_per_pathway = GENES_PER_PATH,
                                        pathways_per_org = PATHS_PER_ORG,
                                        orgs_per_pop = ORGS_PER_POP,
                                        num_pops = POPS)
    for sample_size in [100, 500, 1000, 1500, 2250, 3000, 9999]:
        print sample_size
        matrix = sample_pops.construct_network_matrix(pops, sample_size)
        construct_matrix.save_connection_matrix("data_samplesize//data%s_%s.dat"\
                                                % (str(sample_size).rjust(4,'0'),
                                                   str(run).rjust(2, '0')),
                                                matrix)


##  print(make_pops.Pathway.extant_pathways.values()[0])
##    for pop in pops:
##        print(make_pops.Population.extant_populations[pop.id])
##        print(make_pops.Organism.extant_organisms[pop.id])
##        print(make_pops.Pathway.extant_pathways[pop.id])