def DoEXP01inner():
"""
Executes the inner CV loop for all methods, networks and parameters and the two datasets.
"""
#We need to know how the outer loop looks like
nr_crossvals = 1
nr_folds = 5
#Parameters for the inner loop
nr_crossvals_inner = 1
nr_folds_inner = 5
#Combine data, networks methods and other parameters
DataAndFeatureExtractors = CombineDataExperiment01()
#Create tokens.
#For each possible combination of outer and inner crossval, outer and inner fold and parameters in DataAndFeatureExtractors
#we receive one token. They all carry the Prefix EXP01.
#If you work with a HPC you can store them as tokens in a database or other tool.
tokens = generate_tokens_innerloop(DataAndFeatureExtractors, nr_crossvals, nr_folds, nr_crossvals_inner, nr_folds_inner, 'EXP01InnerLoop')
#Execute calculations and store results
#1) Locally process tokens
doneTokens = []
for token in tokens:
#db may be a couchDB db
doneTokens.append(localProcess(token, db = None))
#2) For a couchDB use the pipeline script
#Write results to an sql database
sqlName = "_"+datetime.datetime.now().strftime('%b-%d-%G')
sqlPath = "Results/"
sqlFilename = sqlPath+"EXP01InnerLoop"+sqlName+".sqlite3"
TokenToSqliteExperiment01InnerLoop(tokens, sqlFilename)
def DoEXP01outer():
"""
Executes the outer CV loop for all methods, networks and parameters and the two datasets.
"""
#Do not repeat the CV
nr_crossvals = 1
#Split data in five parts
nr_folds = 5
#Combine data, networks methods and other parameters
DataAndFeatureExtractors = CombineDataExperiment01()
#Create tokens that also contain the info about the splits and number CVs we want to execute
#For each possible combination of crossval, fold and parameters in DataAndFeatureExtractors
#we receive one token. They all carry the Prefix EXP01.
#If you work with a HPC you can store them as tokens in a database or other tool.
tokens = generate_tokens(DataAndFeatureExtractors, nr_crossvals, nr_folds, 'EXP01')
#Execute calculations and store results
#1) Locally process tokens
doneTokens = []
for token in tokens:
#db may be a couchDB db
doneTokens.append(localProcess(token, db = None))
#2) For a couchDB use the pipeline script
#Write results to an sql database
sqlName = "_"+datetime.datetime.now().strftime('%b-%d-%G')
sqlPath = "Results/"
sqlFilename = sqlPath+"EXP01"+sqlName+".sqlite3"
TokenToSqliteExperiment01(tokens, sqlFilename)
def DoEXP04outer():
"""
Executes the outer CV loop for all methods, networks and parameters and the two datasets with the ER positive patients only.
"""
#Comments as in DoEXP01outer
nr_crossvals = 1
nr_folds = 5
DataAndFeatureExtractors = CombineDataExperiment01()
tokens = generate_tokens(DataAndFeatureExtractors, nr_crossvals, nr_folds, 'EXP04')
doneTokens = []
for token in tokens:
doneTokens.append(localProcess(token, db = None))
sqlName = "_"+datetime.datetime.now().strftime('%b-%d-%G')
sqlPath = "Results/"
sqlFilename = sqlPath+"EXP04"+sqlName+".sqlite3"
TokenToSqliteExperiment01(tokens, sqlFilename)
def DoEXP05outer():
"""
As DoEXP01outer but also shuffling the network and pathway data.
"""
#Comments as in DoEXP01outer
nr_crossvals = 1
nr_folds = 5
#Shuffle networks and pathways 25 times
num_shuffles = 25
DataAndFeatureExtractors = CombineDataExperiment05()
tokens = generate_tokens(DataAndFeatureExtractors, nr_crossvals, nr_folds, 'EXP05')
doneTokens = []
for token in tokens:
doneTokens.append(localProcess(token, db = None))
sqlName = "_"+datetime.datetime.now().strftime('%b-%d-%G')
sqlPath = "Results/"
sqlFilename = sqlPath+"EXP05"+sqlName+".sqlite3"
TokenToSqliteExperiment05(tokens, sqlFilename)