def initSampleObj(powerDataObj): ''' initialize a spower.Sample() object using information contained in a pre-processed 'PowerData' object ''' sampleObj = Sample() sampleObj.seed(0, os.getpid()) sampleObj.set(**powerDataObj.data) return sampleObj
def initSampleAndPowerdata(configFile, srvResFile, srvGeneRep=None): ''' initialize a spower.Sample() object and a PowerData object srvGeneRep - gene replicate # to be used in powerdata, randomly sample a gene replicate if None ''' args, srvData = spowerArgsNData(configFile, srvResFile, srvGeneRep) powerdata = PowerData(args, [], srvData) powerdata.update_fixed() powerdata.update_random() sampleObj = Sample() sampleObj.seed(0, os.getpid()) sampleObj.set(**powerdata.data) return sampleObj, powerdata
from spower.utils import getLogger from spower.simulator.sampler import Sample if __name__ == "__main__": d = Sample(getLogger(1)) d.seed(0, 1) c = d.clone() c.seed(0, 1)
# ##### generate disease by PAR #s = Sample() #s.seed(0) #s.set(**powerdata.data) #L.GenotypeGenerator().apply(s.data) #L.PARModel(powerdata.data['par'], powerdata.data['PAR_variable']).apply(s.data)#L.ORModel(powerdata.data['odds_ratio']).apply(s.data) #L.DiseaseEffectGenerator(powerdata.data['baseline_effect']).apply(s.data) #L.DiseaseStatusGenerator().apply(s.data) #print powerdata.data['maf'] #print s.get('haplotype1'), s.get('haplotype2') #print s.get('effect'), #print s.get('phenotype') #### generate qt s = Sample() s.seed(0) print dir(s) s.set(**powerdata.data) #L.GenotypeGenerator().apply(s.data) s.set(haplotype1=[0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0], haplotype2=[1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1]) L.MeanShiftModel(powerdata.data['mean_shift']).apply(s.data) L.QtEffectGenerator().apply(s.data) L.QtValueGenerator().apply(s.data) print s.get('haplotype1'), s.get('haplotype2') print s.get('effect') print s.get('phenotype')