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Expanding biochemical model to IID data, experiments with replicates and multiple conditons #5

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Expanding biochemical model to IID data, experiments with replicates and multiple conditons #5

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a30c702
remove inference file
robertness Oct 27, 2018
0530b0e
seems like it should work
robertness Oct 27, 2018
c2d1e84
working with multiple dimensions
robertness Oct 27, 2018
1720e32
mod
robertness Jan 21, 2019
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21 changes: 0 additions & 21 deletions causal_demon/inference.py
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44 changes: 24 additions & 20 deletions causal_demon/transmitters.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,7 @@

import pyro
from pyro import sample
import torch
from torch import tensor

"""
Expand All @@ -17,7 +18,7 @@
marginals from conditioned programs will sometimes fail when this distribution
is used.
"""
Delta = partial(pyro.distributions.Normal, scale=1e-10)
Delta = partial(pyro.distributions.Normal, scale=1e-6)

constants = {
"sos_tot": 120000.,
Expand Down Expand Up @@ -152,26 +153,29 @@ def cancer_signaling(noise_dists):
equation modeling approach. This model assumes the ODEs have been solved
for steady state, and models the steady state with structural causal
models. For more details on this math, see the bianconi_math document.

"""
N_egf = sample('N_egf', noise_dists['N_egf'])
N_igf = sample('N_igf', noise_dists['N_igf'])
N_sos = sample('N_sos', noise_dists['N_sos'])
N_ras = sample('N_ras', noise_dists['N_ras'])
N_pi3k = sample('N_pi3k', noise_dists['N_pi3k'])
N_akt = sample('N_akt', noise_dists['N_akt'])
N_raf = sample('N_raf', noise_dists['N_raf'])
N_mek = sample('N_mek', noise_dists['N_mek'])
N_erk = sample('N_erk', noise_dists['N_erk'])

egf = f_egf(N_egf)
igf = f_igf(N_igf)
sos = f_sos(egf, igf, N_sos)
ras = f_ras(sos, N_ras)
pi3k = f_pi3k(ras, egf, igf, N_pi3k)
akt = f_akt(pi3k, N_akt)
raf = f_raf(ras, akt, N_raf)
mek = f_mek(raf, N_mek)
erk = f_erk(mek, N_erk)

with pyro.iarange("model"):
N_egf = sample('N_egf', noise_dists['N_egf'])
N_igf = sample('N_igf', noise_dists['N_igf'])
N_sos = sample('N_sos', noise_dists['N_sos'])
N_ras = sample('N_ras', noise_dists['N_ras'])
N_pi3k = sample('N_pi3k', noise_dists['N_pi3k'])
N_akt = sample('N_akt', noise_dists['N_akt'])
N_raf = sample('N_raf', noise_dists['N_raf'])
N_mek = sample('N_mek', noise_dists['N_mek'])
N_erk = sample('N_erk', noise_dists['N_erk'])

egf = f_egf(N_egf)
igf = f_igf(N_igf)
sos = f_sos(egf, igf, N_sos)
ras = f_ras(sos, N_ras)
pi3k = f_pi3k(ras, egf, igf, N_pi3k)
akt = f_akt(pi3k, N_akt)
raf = f_raf(ras, akt, N_raf)
mek = f_mek(raf, N_mek)
erk = f_erk(mek, N_erk)

return {
'egf': egf,
Expand Down
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