diff options
| -rw-r--r-- | experiments/Makefile | 6 | ||||
| -rw-r--r-- | experiments/analyze.py | 4 | ||||
| -rw-r--r-- | experiments/ml.pyx | 59 | ||||
| -rw-r--r-- | experiments/process.py | 50 |
4 files changed, 119 insertions, 0 deletions
diff --git a/experiments/Makefile b/experiments/Makefile new file mode 100644 index 0000000..991c178 --- /dev/null +++ b/experiments/Makefile @@ -0,0 +1,6 @@ +all: + cython -a ml.pyx + gcc -pthread -fno-strict-aliasing -march=x86-64 -mtune=generic -O3 -pipe -fstack-protector-strong --param=ssp-buffer-size=4 -DNDEBUG -march=x86-64 -mtune=generic -O3 -pipe -fstack-protector-strong --param=ssp-buffer-size=4 -fPIC -I/usr/include/python2.7 -c ml.c -o ml.o + gcc -pthread -shared -Wl,-O3,--sort-common,--as-needed,-z,relro ml.o -L/usr/lib -lpython2.7 -o ml.so + + diff --git a/experiments/analyze.py b/experiments/analyze.py new file mode 100644 index 0000000..6a6896b --- /dev/null +++ b/experiments/analyze.py @@ -0,0 +1,4 @@ +import pstats + +p = pstats.Stats("run.stats") +p.print_stats() diff --git a/experiments/ml.pyx b/experiments/ml.pyx new file mode 100644 index 0000000..c6291c5 --- /dev/null +++ b/experiments/ml.pyx @@ -0,0 +1,59 @@ +# cython: boundscheck=False, cdivision=True +import numpy as np +cimport numpy as np +from libc.math cimport log + +DTYPE = np.float64 +ctypedef np.float_t DTYPE_t + +cdef DTYPE_t weight_victim(int dist, int dt, DTYPE_t alpha, + DTYPE_t delta, DTYPE_t gamma): + cdef DTYPE_t structural, temporal + structural = delta ** dist + temporal = (gamma - 1. / alpha) * 1. / (1. + dt / alpha) ** gamma + return structural * temporal + + +cdef DTYPE_t weight_non_victim(int dist, int t, DTYPE_t alpha, + DTYPE_t delta, DTYPE_t gamma): + cdef DTYPE_t structural, temporal + structural = delta ** dist + temporal = 1. - 1. / (1. + (3012. - t) / alpha) ** gamma + return 1. - structural * temporal + + +def ml(dict root_victims, dict victims, dict non_victims, + DTYPE_t alpha, DTYPE_t delta, DTYPE_t gamma=1.01): + cdef: + int n_roots, n_victims, n_nodes, roots, i, dist, dt, t + DTYPE_t beta + list parents, parents_weights + n_roots, n_victims = len(root_victims), len(victims) + n_nodes = n_victims + len(non_victims) + cdef: + np.ndarray[DTYPE_t] probs = np.zeros(n_victims, dtype=DTYPE) + np.ndarray[DTYPE_t] probs_nv = np.zeros(len(non_victims), dtype=DTYPE) + for i, parents in enumerate(victims.itervalues()): + parents_weights = [weight_victim(dist, dt, alpha, delta, gamma) + for (dist, dt) in parents] + probs[i] = max(parents_weights) + for i, parents in enumerate(non_victims.itervalues()): + parents_weights = [weight_non_victim(dist, t, alpha, delta, gamma) + for (dist, t) in parents] + probs_nv[i] = max(parents_weights) + probs.sort() + probs = probs[::-1] + cdef: + np.ndarray[DTYPE_t] betas = probs / (1. + probs) + np.ndarray[DTYPE_t] cums = np.log(probs.cumsum()) + for i in xrange(n_victims - 1, 0, -1): + roots = n_roots + n_victims - 1 - i + if betas[i] > roots / float(n_nodes): + break + else: + print "alpha: {0}, delta: {1}. Everyone is a root".format(alpha, delta) + roots = n_roots + n_victims + beta = roots / float(n_nodes) + return (beta, roots, + roots * log(beta) + (n_nodes - roots) * log(1 - beta) + cums[i] + + np.log(probs_nv).sum()) diff --git a/experiments/process.py b/experiments/process.py new file mode 100644 index 0000000..1ec917e --- /dev/null +++ b/experiments/process.py @@ -0,0 +1,50 @@ +from csv import DictReader +import sys +from ml import ml +import numpy as np +from cPickle import dump, load +from itertools import product + + +def build_network(filename): + victims = {} + non_victims = {} + with open(filename) as fh: + reader = DictReader(fh) + for row in reader: + from_, to = int(float(row["from"])), int(float(row["to"])) + if row["t2"] != "NA": + dt = int(row["t2"]) - int(row["t1"]) + parent = (int(row["dist"]), dt) + if to not in victims: + victims[to] = [] + victims[to].append(parent) + if from_ not in victims: + victims[from_] = [] + else: + from_, to = int(float(row["from"])), int(float(row["to"])) + parent = (int(row["dist"]), int(row["t1"])) + if to not in victims: + non_victims[to] = [] + non_victims[to].append(parent) + if from_ not in victims: + victims[from_] = [] + root_victims = {} + for victim in victims.keys(): + if not victims[victim]: + del victims[victim] + root_victims[victim] = [] + return root_victims, victims, non_victims + + +if __name__ == "__main__": + #root_victims, victims, non_victims = build_network(sys.argv[1]) + #dump((root_victims, victims, non_victims), open("network.pickle", "w")) + root_victims, victims, non_victims = load(open("network.pickle")) + + alpha = np.arange(1000006., 1000007., 1.) + delta = np.arange(0.1, 1., 0.01) + with open("out.log", "a") as fh: + for a, d in product(alpha, delta): + beta, roots, ll = ml(root_victims, victims, non_victims, a, d) + fh.write("\t".join(map(str, [a, d, beta, roots, ll])) + "\n") |