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])
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])
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])
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])