def model(self, noise):
N_SARS_COV2 = sample('N_SARS_COV2', Normal(noise['N_SARS_COV2'][0], noise['N_SARS_COV2'][1]))
N_TOCI = sample('N_TOCI', Normal(noise['N_TOCI'][0], noise['N_TOCI'][1]))
N_ACE2 = sample('N_ACE2', Normal(noise['N_ACE2'][0], noise['N_ACE2'][1]))
N_PRR = sample('N_PRR', Normal(noise['N_PRR'][0], noise['N_PRR'][1]))
N_AngII = sample('N_AngII', Normal(noise['N_AngII'][0], noise['N_AngII'][1]))
N_AGTR1 = sample('N_AGTR1', Normal(noise['N_AGTR1'][0], noise['N_AGTR1'][1]))
N_ADAM17 = sample('N_ADAM17', Normal(noise['N_ADAM17'][0], noise['N_ADAM17'][1]))
N_sIL_6_alpha = sample('N_sIL_6_alpha', Normal(noise['N_sIL_6_alpha'][0], noise['N_sIL_6_alpha'][1]))
N_TNF = sample('N_TNF', Normal(noise['N_TNF'][0], noise['N_TNF'][1]))
N_EGF = sample('N_EGF', Normal(noise['N_EGF'][0], noise['N_EGF'][1]))
N_EGFR = sample('N_EGFR', Normal(noise['N_EGFR'][0], noise['N_EGFR'][1]))
N_IL6_STAT3 = sample('N_IL6_STAT3', Normal(noise['N_IL6_STAT3'][0], noise['N_IL6_STAT3'][1]))
N_NF_xB = sample('N_NF_xB', Normal(noise['N_NF_xB'][0], noise['N_NF_xB'][1]))
N_IL_6_AMP = sample('N_IL_6_AMP', Normal(noise['N_IL_6_AMP'][0], noise['N_IL_6_AMP'][1]))
N_cytokine = sample('N_cytokine', Normal(noise['N_cytokine'][0], noise['N_cytokine'][1]))
SARS_COV2 = sample('SARS_COV2', Normal(self.f_SARS_COV2(50, 10, N_SARS_COV2), 1.0))
TOCI = sample('TOCI', Normal(self.f_TOCI(50, 10, N_TOCI), 1.0))
PRR = sample('PRR', Delta(self.f_PRR(SARS_COV2, N_PRR)))
ACE2 = sample('ACE2', Delta(self.f_ACE2(SARS_COV2, N_ACE2)))
AngII = sample('AngII', Delta(self.f_AngII(ACE2, N_AngII)))
AGTR1 = sample('AGTR1', Delta(self.f_AGTR1(AngII, N_AGTR1)))
ADAM17 = sample('ADAM1Spike7', Delta(self.f_ADAM17(AGTR1, N_ADAM17)))
TNF = sample('TNF', Delta(self.f_TNF(ADAM17, N_TNF)))
sIL_6_alpha = sample('sIL_6_alpha', Delta(self.f_sIL_6_alpha(ADAM17, TOCI, N_sIL_6_alpha)))
EGF = sample('EGF', Delta(self.f_EGF(ADAM17, N_EGF)))
EGFR = sample('EGFR', Delta(self.f_EGFR(EGF, N_EGFR)))
NF_xB = sample('NF_xB', Delta(self.f_NF_xB(PRR, EGFR, TNF, N_NF_xB)))
IL6_STAT3 = sample('IL6_STAT3', Delta(self.f_IL6_STAT3(sIL_6_alpha, N_IL6_STAT3)))
IL_6_AMP = sample('IL_6_AMP', Delta(self.f_IL_6_AMP(NF_xB, IL6_STAT3, N_IL_6_AMP)))
cytokine = sample('cytokine', Delta(self.f_cytokine(IL_6_AMP, N_cytokine)))
noise_samples = (
N_PRR,
N_ACE2,
N_AngII,
N_AGTR1,
N_ADAM17,
N_TNF,
N_sIL_6_alpha,
N_EGF,
N_EGFR,
N_NF_xB,
N_IL6_STAT3,
N_IL_6_AMP,
N_cytokine,
)
if self.noise_type == NOISE_TYPE_OBSERVATIONAL:
# Use the dictionary structure for generating observational dataset
samples = {
'a(SARS_COV2)': SARS_COV2.numpy(),
'a(PRR)': PRR.numpy(),
'a(ACE2)': ACE2.numpy(),
'a(AngII)': AngII.numpy(),
'a(AGTR1)': AGTR1.numpy(),
'a(ADAM17)': ADAM17.numpy(),
'a(TOCI)': TOCI.numpy(),
'a(TNF)': TNF.numpy(),
'a(sIL_6_alpha)': sIL_6_alpha.numpy(),
'a(EGF)': EGF.numpy(),
'a(EGFR)': EGFR.numpy(),
'a(IL6_STAT3)': IL6_STAT3.numpy(),
'a(NF_xB)': NF_xB.numpy(),
'a(IL6_AMP)': IL_6_AMP.numpy(),
'a(cytokine)': cytokine.numpy(),
}
elif self.noise_type == NOISE_TYPE_SAMPLES:
## Use the variable list for generating samples for causal effect
samples = (
SARS_COV2,
PRR,
ACE2,
AngII,
AGTR1,
ADAM17,
TOCI,
TNF,
sIL_6_alpha,
EGF,
EGFR,
NF_xB,
IL6_STAT3,
IL_6_AMP,
cytokine,
)
else:
raise InvalidNoiseType(self.noise_type)
return samples, noise_samples
def wrapped_model(x_data, y_data):
pyro.sample("prediction", Delta(model(x_data, y_data)))
def get_posterior(self, *args, **kwargs):
svgd_particles = pyro.param("svgd_particles", self._init_loc)
return Delta(svgd_particles, event_dim=1)