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danstowell/pilotters_tpor_1d.data.R

Last active December 24, 2015 16:29
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pilotters_tpor_1d.data.R
K <- 4
D <- 1000
M_trn <- 9
M_tst <- 3
proby_trn <- structure(c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 1, 1, 1, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 1, 1, 1), .Dim=c(9, 4))
tpor_trn <- structure(c(1.01207e-05, 8.78817e-05, 5.01181e-06, 1.19763e-06, 0.000143943, 3.11904e-08, 1.83136e-05, 2.91702e-05, 1.94456e-05, 4.31514e-05, 2.84705e-05, 6.11549e-06, 2.299e-06, 0.000180823, 2.78093e-08, 2.57135e-05, 0.000105035, 4.86663e-05, 2.35292e-05, 8.56379e-06, 3.44704e-06, 5.21752e-07, 2.61876e-05, 1.74499e-09, 1.07338e-05, 3.41347e-05, 3.77774e-05, 2.214e-05, 1.48449e-05, 4.70669e-06, 6.86431e-07, 1.33485e-05, 0, 5.44041e-06, 3.25767e-05, 8.47303e-06, 1.52004e-05, 9.99668e-06, 2.46284e-06, 7.87308e-07, 1.09859e-05, 0, 3.39304e-06, 1.239e-05, 2.67495e-06, 2.52913e-05, 1.10843e-05, 5.10063e-06, 6.15147e-07, 3.27169e-06, 0, 3.28779e-06, 1.93232e-06, 3.01899e-06, 2.03921e-05, 2.98715e-06, 4.00504e-06, 1.77206e-07, 7.91671e-06, 0, 2.11167e-06, 1.14282e-06, 2.8545e-07, 1.46677e-05, 1.96238e-06, 1.72603e-07, 6.73256e-07, 1.51484e-05, 0, 1.67988e-06, 3.28988e-07, 6.27241e-07, 6.70429e-06, 5.68485e-07, 2.97398e-07, 7.60541e-07, 9.67875e-06, 0, 1.85588e-07, 2.93878e-07, 5.44362e-07, 4.33461e-06, 1.46989e-07, 3.43346e-07, 2.0416e-06, 8.5319e-06, 0, 1.44231e-08, 2.7549e-07, 2.47479e-06, 4.43302e-05, 4.98237e-05, 1.53516e-05, 2.43934e-06, 0.000198902, 0, 1.34438e-05, 7.4261e-05, 3.13862e-05, 0.000334741, 0.00101212, 3.38105e-05, 3.62821e-05, 0.00177974, 2.40832e-05, 0.000948388, 0.00176449, 0.00190267, 0.00037475, 0.000657227, 3.12818e-05, 4.83176e-05, 0.000463474, 3.62148e-05, 0.00115969, 0.0012254, 0.00568672, 0.000152468, 0.000224199, 5.58473e-05, 1.63012e-05, 0.000124154, 7.42987e-06, 0.000386152, 0.00070734, 0.000341924, 0.000119626, 0.00013956, 6.18519e-05, 1.38579e-05, 5.77658e-05, 7.23745e-07, 2.70498e-05, 0.00014942, 0.000252727, 0.00014476, 0.000185953, 0.000124291, 6.64138e-06, 4.55077e-05, 3.99207e-07, 7.22225e-06, 3.07581e-06, 5.93866e-05, 0.000140489, 5.68761e-05, 2.9744e-05, 1.12336e-05, 6.70782e-05, 2.55358e-07, 7.22132e-06, 2.33821e-06, 3.06049e-05, 0.000109598, 1.19203e-05, 1.4978e-06, 1.02501e-05, 0.000153992, 7.85234e-07, 5.97252e-06, 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tpor_tst <- structure(c(6.15425e-06, 1.612e-05, 6.67992e-06, 1.8274e-05, 7.16458e-05, 2.44722e-05, 9.83242e-06, 2.51511e-05, 1.86932e-05, 3.76341e-06, 2.4207e-05, 6.41558e-06, 3.26639e-06, 1.11875e-05, 5.0085e-06, 3.18271e-06, 5.05332e-06, 3.20555e-06, 1.08079e-06, 1.53203e-06, 2.01494e-06, 3.016e-06, 3.81486e-07, 2.57385e-07, 3.09434e-06, 1.29187e-07, 9.11442e-07, 1.33599e-06, 1.23022e-07, 1.58449e-07, 1.22619e-05, 5.74187e-05, 1.80895e-05, 0.000772006, 0.00114387, 0.000912252, 0.00087953, 0.000967416, 0.00279704, 0.000296602, 0.000591244, 0.000184259, 3.71871e-05, 0.000149128, 0.000249197, 2.1387e-05, 8.136e-05, 0.000165264, 2.96989e-05, 2.35943e-05, 9.44174e-05, 4.12363e-05, 7.90364e-06, 5.94524e-06, 9.43615e-06, 4.17291e-06, 1.58199e-05, 4.39192e-06, 8.64199e-07, 4.42564e-06, 5.96846e-06, 8.91109e-06, 1.02656e-05, 0.000595337, 0.000952082, 0.00116614, 0.00422183, 0.00359884, 0.00818098, 0.00287068, 0.00268214, 0.00268348, 0.000797591, 0.00145752, 0.000879278, 0.000569517, 0.000488365, 0.0005818, 0.000201995, 0.000204037, 0.000186787, 0.000127291, 6.14333e-05, 3.33031e-05, 2.79155e-05, 5.94591e-06, 2.06761e-05, 7.06651e-06, 1.95177e-06, 1.3112e-05, 6.78392e-06, 8.9341e-06, 4.6366e-06, 0.000186345, 0.000321074, 0.000397261, 0.00155056, 0.00212996, 0.00735053, 0.0122049, 0.0105076, 0.0108603, 0.00401871, 0.00799936, 0.00704608, 0.00146544, 0.00292888, 0.00082304, 0.000694575, 0.00146314, 9.19636e-05, 0.000427715, 0.00134652, 5.52688e-05, 0.000200722, 0.000757025, 3.88222e-05, 7.30395e-06, 3.59343e-07, 1.6825e-05, 1.21896e-06, 9.36839e-06, 2.66197e-06, 0.000132411, 0.000172279, 0.000116685, 0.00108283, 0.000820909, 0.00207397, 0.00352716, 0.00576477, 0.00652194, 0.0139515, 0.0108294, 0.00988794, 0.00217009, 0.00261018, 0.0020824, 0.000802164, 0.000838618, 0.000175031, 0.000436121, 0.000747038, 0.000134724, 5.3492e-05, 0.000625744, 4.36201e-05, 2.86528e-06, 7.91943e-07, 6.195e-06, 8.29054e-07, 1.47382e-06, 6.1393e-07, 5.3892e-05, 7.61467e-05, 6.47855e-05, 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1.27811e-05), .Dim=c(3, 1000))
Raw
pilotters_tpor_1d.init.R
alpha <- 2
sigma <- 0.1
tpl <- structure(c(0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 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.Dim=c(4, 1000))
tendencies_alpha <- structure(c(1.0, 1.0, 1.0, 1.0), .Dim=c(4))
tendencies_beta <- structure(c(1.0, 1.0, 1.0, 1.0), .Dim=c(4))
proby_tst <- structure(c(0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5), .Dim=c(3, 4))
theta_trn <- structure(c(0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25), .Dim=c(9, 4))
theta_tst <- structure(c(0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25), .Dim=c(3, 4))
Raw
sumsemi.stan
/*
// semi-supervised modelling of 'tpor' data as a sparse(ish) sum of per-class components
// by Dan Stowell 2013
cd ~/dev/stan/stan && make ~/git/stored_docs/dev/stan/sumsemi
cd ~/git/stored_docs/dev/stan/
./sumsemi --data=pilotters_tpor_1d.data.R --init=pilotters_tpor_1d.init.R
*/
data {
int<lower=2> K; // num species ("topics")
int<lower=1> D; // dimensionality of the tpor features
int<lower=1> M_trn; // num audio files
int<lower=1> M_tst; // num audio files
vector<lower=1e-6,upper=1>[K] proby_trn[M_trn]; // species presence proby for each audio
vector<lower=0,upper=1>[D] tpor_trn[M_trn]; // feature data
vector<lower=0,upper=1>[D] tpor_tst[M_tst]; // feature data
}
parameters {
// NB: ARBITRARY UPPER LIMITS ADDED TO CONSTRAIN WHILE DEBUGGING
real<lower=1e-6,upper=10> alpha; // concentration parameter, controlling sparsity for the dirichlet
real<lower=1e-6,upper=10> sigma; // noise stdev
simplex[D] tpl[K]; // template for tpor for species k
// global tendencies for each species to be present (specified as beta params)
vector<lower=0.5,upper=2>[K] tendencies_alpha;
vector<lower=0.5,upper=2>[K] tendencies_beta;
vector<lower=1e-6,upper=1>[K] proby_tst[M_tst]; // species presence proby for each audio
simplex[K] theta_trn[M_trn]; // mixing parameters for audio M, derived from the probys and the concentration
simplex[K] theta_tst[M_tst]; // mixing parameters for audio M, derived from the probys and the concentration
}
model {
vector[D] tplsum;
print("lp__: ", lp__);
alpha ~ exponential(0.5);
sigma ~ exponential(2.0);
tendencies_alpha ~ exponential(0.5);
tendencies_beta ~ exponential(0.5);
print("alpha: ", alpha);
print("sigma: ", sigma);
print("tendencies_alpha: ", tendencies_alpha);
print("tendencies_beta: ", tendencies_beta);
for (m in 1:M_trn) {
proby_trn[m] ~ beta(tendencies_alpha, tendencies_beta);
theta_trn[m] ~ dirichlet(proby_trn[m] * alpha);
tplsum <- rep_vector(0.0, D);
for (k in 1:K){
tplsum <- tplsum + (theta_trn[m,k] * tpl[k]);
}
tpor_trn[m] ~ normal(tplsum, sigma);
}
for (m in 1:M_tst) {
proby_tst[m] ~ beta(tendencies_alpha, tendencies_beta);
theta_tst[m] ~ dirichlet(proby_tst[m] * alpha);
tplsum <- rep_vector(0.0, D);
for (k in 1:K){
tplsum <- tplsum + (theta_tst[m,k] * tpl[k]);
}
tpor_tst[m] ~ normal(tplsum, sigma);
}
}
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