Use the distribution abstraction as an abstraction. (0f8253bd) · Commits · Mike Perry / Tor

src/core/or/circuitpadding.c

+10 −6

Original line number	Diff line number	Diff line
		@@ -545,7 +545,7 @@ circpad_distribution_sample(circpad_distribution_t dist)
		.a = dist.param1,
		.b = dist.param2,
		};
		return uniform_sample(&my_uniform.base);
		return dist_sample(&my_uniform.base);
		}
		case CIRCPAD_DIST_LOGISTIC:
		{
		@@ -555,7 +555,7 @@ circpad_distribution_sample(circpad_distribution_t dist)
		.mu = dist.param1,
		.sigma = dist.param2,
		};
		return logistic_sample(&my_logistic.base);
		return dist_sample(&my_logistic.base);
		}
		case CIRCPAD_DIST_LOG_LOGISTIC:
		{
		@@ -565,12 +565,16 @@ circpad_distribution_sample(circpad_distribution_t dist)
		.alpha = dist.param1,
		.beta = dist.param2,
		};
		return log_logistic_sample(&my_log_logistic.base);
		return dist_sample(&my_log_logistic.base);
		}
		case CIRCPAD_DIST_GEOMETRIC:
		{
		/* param1 is 'p' (success probability) */
		return geometric_sample(dist.param1);
		const struct geometric my_geometric = {
		.base = DIST_BASE(&geometric_ops),
		.p = dist.param1,
		};
		return dist_sample(&my_geometric.base);
		}
		case CIRCPAD_DIST_WEIBULL:
		{
		@@ -580,7 +584,7 @@ circpad_distribution_sample(circpad_distribution_t dist)
		.k = dist.param1,
		.lambda = dist.param2,
		};
		return weibull_sample(&my_weibull.base);
		return dist_sample(&my_weibull.base);
		}
		case CIRCPAD_DIST_PARETO:
		{
		@@ -591,7 +595,7 @@ circpad_distribution_sample(circpad_distribution_t dist)
		.sigma = dist.param1,
		.xi = dist.param2,
		};
		return genpareto_sample(&my_genpareto.base);
		return dist_sample(&my_genpareto.base);
		}
		}

src/lib/math/prob_distr.c

+159 −70

Original line number	Diff line number	Diff line
		@@ -1319,17 +1319,45 @@ sample_geometric(uint32_t s, double p0, double p)
		* (sample/cdf/sf/icdf/isf) as part of its dist_ops structure.
		*/

		/** Functions for uniform distribution */
		const struct dist_ops uniform_ops = {
		.name = "uniform",
		.sample = uniform_sample,
		.cdf = uniform_cdf,
		.sf = uniform_sf,
		.icdf = uniform_icdf,
		.isf = uniform_isf,
		};
		const char *
		dist_name(const struct dist *dist)
		{
		return dist->ops->name;
		}

		double
		dist_sample(const struct dist *dist)
		{
		return dist->ops->sample(dist);
		}

		double
		dist_cdf(const struct dist *dist, double x)
		{
		return dist->ops->cdf(dist, x);
		}

		double
		dist_sf(const struct dist *dist, double x)
		{
		return dist->ops->sf(dist, x);
		}

		double
		dist_icdf(const struct dist *dist, double p)
		{
		return dist->ops->icdf(dist, p);
		}

		double
		dist_isf(const struct dist *dist, double p)
		{
		return dist->ops->isf(dist, p);
		}

		/** Functions for uniform distribution */

		static double
		uniform_sample(const struct dist *dist)
		{
		const struct uniform *U = const_container_of(dist, struct uniform,
		@@ -1339,7 +1367,7 @@ uniform_sample(const struct dist *dist)
		return sample_uniform_interval(p0, U->a, U->b);
		}

		double
		static double
		uniform_cdf(const struct dist *dist, double x)
		{
		const struct uniform *U = const_container_of(dist, struct uniform,
		@@ -1353,7 +1381,7 @@ uniform_cdf(const struct dist *dist, double x)
		return 1;
		}

		double
		static double
		uniform_sf(const struct dist *dist, double x)
		{
		const struct uniform *U = const_container_of(dist, struct uniform,
		@@ -1367,7 +1395,7 @@ uniform_sf(const struct dist *dist, double x)
		return 1;
		}

		double
		static double
		uniform_icdf(const struct dist *dist, double p)
		{
		const struct uniform *U = const_container_of(dist, struct uniform,
		@@ -1377,7 +1405,7 @@ uniform_icdf(const struct dist *dist, double p)
		return (p < 0.5 ? (U->a + wp) : (U->b - w(1 - p)));
		}

		double
		static double
		uniform_isf(const struct dist *dist, double p)
		{
		const struct uniform *U = const_container_of(dist, struct uniform,
		@@ -1387,17 +1415,18 @@ uniform_isf(const struct dist *dist, double p)
		return (p < 0.5 ? (U->b - wp) : (U->a + w(1 - p)));
		}

		/** Functions for logistic distribution: */
		const struct dist_ops logistic_ops = {
		.name = "logistic",
		.sample = logistic_sample,
		.cdf = logistic_cdf,
		.sf = logistic_sf,
		.icdf = logistic_icdf,
		.isf = logistic_isf,
		const struct dist_ops uniform_ops = {
		.name = "uniform",
		.sample = uniform_sample,
		.cdf = uniform_cdf,
		.sf = uniform_sf,
		.icdf = uniform_icdf,
		.isf = uniform_isf,
		};

		double
		/** Functions for logistic distribution: */

		static double
		logistic_sample(const struct dist *dist)
		{
		const struct logistic *L = const_container_of(dist, struct logistic,
		@@ -1409,7 +1438,7 @@ logistic_sample(const struct dist *dist)
		return sample_logistic_locscale(s, t, p0, L->mu, L->sigma);
		}

		double
		static double
		logistic_cdf(const struct dist *dist, double x)
		{
		const struct logistic *L = const_container_of(dist, struct logistic,
		@@ -1418,7 +1447,7 @@ logistic_cdf(const struct dist *dist, double x)
		return cdf_logistic(x, L->mu, L->sigma);
		}

		double
		static double
		logistic_sf(const struct dist *dist, double x)
		{
		const struct logistic *L = const_container_of(dist, struct logistic,
		@@ -1427,7 +1456,7 @@ logistic_sf(const struct dist *dist, double x)
		return sf_logistic(x, L->mu, L->sigma);
		}

		double
		static double
		logistic_icdf(const struct dist *dist, double p)
		{
		const struct logistic *L = const_container_of(dist, struct logistic,
		@@ -1436,7 +1465,7 @@ logistic_icdf(const struct dist *dist, double p)
		return icdf_logistic(p, L->mu, L->sigma);
		}

		double
		static double
		logistic_isf(const struct dist *dist, double p)
		{
		const struct logistic *L = const_container_of(dist, struct logistic,
		@@ -1445,17 +1474,18 @@ logistic_isf(const struct dist *dist, double p)
		return isf_logistic(p, L->mu, L->sigma);
		}

		/** Functions for log-logistic distribution: */
		const struct dist_ops log_logistic_ops = {
		.name = "log logistic",
		.sample = log_logistic_sample,
		.cdf = log_logistic_cdf,
		.sf = log_logistic_sf,
		.icdf = log_logistic_icdf,
		.isf = log_logistic_isf,
		const struct dist_ops logistic_ops = {
		.name = "logistic",
		.sample = logistic_sample,
		.cdf = logistic_cdf,
		.sf = logistic_sf,
		.icdf = logistic_icdf,
		.isf = logistic_isf,
		};

		double
		/** Functions for log-logistic distribution: */

		static double
		log_logistic_sample(const struct dist *dist)
		{
		const struct log_logistic *LL = const_container_of(dist, struct
		@@ -1466,7 +1496,7 @@ log_logistic_sample(const struct dist *dist)
		return sample_log_logistic_scaleshape(s, p0, LL->alpha, LL->beta);
		}

		double
		static double
		log_logistic_cdf(const struct dist *dist, double x)
		{
		const struct log_logistic *LL = const_container_of(dist,
		@@ -1475,7 +1505,7 @@ log_logistic_cdf(const struct dist *dist, double x)
		return cdf_log_logistic(x, LL->alpha, LL->beta);
		}

		double
		static double
		log_logistic_sf(const struct dist *dist, double x)
		{
		const struct log_logistic *LL = const_container_of(dist,
		@@ -1484,7 +1514,7 @@ log_logistic_sf(const struct dist *dist, double x)
		return sf_log_logistic(x, LL->alpha, LL->beta);
		}

		double
		static double
		log_logistic_icdf(const struct dist *dist, double p)
		{
		const struct log_logistic *LL = const_container_of(dist,
		@@ -1493,7 +1523,7 @@ log_logistic_icdf(const struct dist *dist, double p)
		return icdf_log_logistic(p, LL->alpha, LL->beta);
		}

		double
		static double
		log_logistic_isf(const struct dist *dist, double p)
		{
		const struct log_logistic *LL = const_container_of(dist,
		@@ -1502,17 +1532,18 @@ log_logistic_isf(const struct dist *dist, double p)
		return isf_log_logistic(p, LL->alpha, LL->beta);
		}

		/** Functions for Weibull distribution */
		const struct dist_ops weibull_ops = {
		.name = "Weibull",
		.sample = weibull_sample,
		.cdf = weibull_cdf,
		.sf = weibull_sf,
		.icdf = weibull_icdf,
		.isf = weibull_isf,
		const struct dist_ops log_logistic_ops = {
		.name = "log logistic",
		.sample = log_logistic_sample,
		.cdf = log_logistic_cdf,
		.sf = log_logistic_sf,
		.icdf = log_logistic_icdf,
		.isf = log_logistic_isf,
		};

		double
		/** Functions for Weibull distribution */

		static double
		weibull_sample(const struct dist *dist)
		{
		const struct weibull *W = const_container_of(dist, struct weibull,
		@@ -1523,7 +1554,7 @@ weibull_sample(const struct dist *dist)
		return sample_weibull(s, p0, W->lambda, W->k);
		}

		double
		static double
		weibull_cdf(const struct dist *dist, double x)
		{
		const struct weibull *W = const_container_of(dist, struct weibull,
		@@ -1532,7 +1563,7 @@ weibull_cdf(const struct dist *dist, double x)
		return cdf_weibull(x, W->lambda, W->k);
		}

		double
		static double
		weibull_sf(const struct dist *dist, double x)
		{
		const struct weibull *W = const_container_of(dist, struct weibull,
		@@ -1541,7 +1572,7 @@ weibull_sf(const struct dist *dist, double x)
		return sf_weibull(x, W->lambda, W->k);
		}

		double
		static double
		weibull_icdf(const struct dist *dist, double p)
		{
		const struct weibull *W = const_container_of(dist, struct weibull,
		@@ -1550,7 +1581,7 @@ weibull_icdf(const struct dist *dist, double p)
		return icdf_weibull(p, W->lambda, W->k);
		}

		double
		static double
		weibull_isf(const struct dist *dist, double p)
		{
		const struct weibull *W = const_container_of(dist, struct weibull,
		@@ -1559,17 +1590,18 @@ weibull_isf(const struct dist *dist, double p)
		return isf_weibull(p, W->lambda, W->k);
		}

		/** Functions for generalized Pareto distributions */
		const struct dist_ops genpareto_ops = {
		.name = "generalized Pareto",
		.sample = genpareto_sample,
		.cdf = genpareto_cdf,
		.sf = genpareto_sf,
		.icdf = genpareto_icdf,
		.isf = genpareto_isf,
		const struct dist_ops weibull_ops = {
		.name = "Weibull",
		.sample = weibull_sample,
		.cdf = weibull_cdf,
		.sf = weibull_sf,
		.icdf = weibull_icdf,
		.isf = weibull_isf,
		};

		double
		/** Functions for generalized Pareto distributions */

		static double
		genpareto_sample(const struct dist *dist)
		{
		const struct genpareto *GP = const_container_of(dist, struct genpareto,
		@@ -1580,7 +1612,7 @@ genpareto_sample(const struct dist *dist)
		return sample_genpareto_locscale(s, p0, GP->mu, GP->sigma, GP->xi);
		}

		double
		static double
		genpareto_cdf(const struct dist *dist, double x)
		{
		const struct genpareto *GP = const_container_of(dist, struct genpareto,
		@@ -1589,7 +1621,7 @@ genpareto_cdf(const struct dist *dist, double x)
		return cdf_genpareto(x, GP->mu, GP->sigma, GP->xi);
		}

		double
		static double
		genpareto_sf(const struct dist *dist, double x)
		{
		const struct genpareto *GP = const_container_of(dist, struct genpareto,
		@@ -1598,7 +1630,7 @@ genpareto_sf(const struct dist *dist, double x)
		return sf_genpareto(x, GP->mu, GP->sigma, GP->xi);
		}

		double
		static double
		genpareto_icdf(const struct dist *dist, double p)
		{
		const struct genpareto *GP = const_container_of(dist, struct genpareto,
		@@ -1607,7 +1639,7 @@ genpareto_icdf(const struct dist *dist, double p)
		return icdf_genpareto(p, GP->mu, GP->sigma, GP->xi);
		}

		double
		static double
		genpareto_isf(const struct dist *dist, double p)
		{
		const struct genpareto *GP = const_container_of(dist, struct genpareto,
		@@ -1616,13 +1648,70 @@ genpareto_isf(const struct dist *dist, double p)
		return isf_genpareto(p, GP->mu, GP->sigma, GP->xi);
		}

		/* Deterministically sample from the geometric distribution with
		* per-trial success probability p. */
		double
		geometric_sample(double p)
		const struct dist_ops genpareto_ops = {
		.name = "generalized Pareto",
		.sample = genpareto_sample,
		.cdf = genpareto_cdf,
		.sf = genpareto_sf,
		.icdf = genpareto_icdf,
		.isf = genpareto_isf,
		};

		/** Functions for geometric distribution on number of trials before success */

		static double
		geometric_sample(const struct dist *dist)
		{
		const struct geometric *G = const_container_of(dist, struct geometric, base);
		uint32_t s = crypto_rand_u32();
		double p0 = random_uniform_01();
		return sample_geometric(s, p0, p);

		return sample_geometric(s, p0, G->p);
		}

		static double
		geometric_cdf(const struct dist *dist, double x)
		{
		const struct geometric *G = const_container_of(dist, struct geometric, base);

		if (x < 1)
		return 0;
		/* 1 - (1 - p)^floor(x) = 1 - e^{floor(x) log(1 - p)} */
		return -expm1(floor(x)*log1p(-G->p));
		}

		static double
		geometric_sf(const struct dist *dist, double x)
		{
		const struct geometric *G = const_container_of(dist, struct geometric, base);

		if (x < 1)
		return 0;
		/* (1 - p)^floor(x) = e^{ceil(x) log(1 - p)} */
		return exp(floor(x)*log1p(-G->p));
		}

		static double
		geometric_icdf(const struct dist *dist, double p)
		{
		const struct geometric *G = const_container_of(dist, struct geometric, base);

		return log1p(-p)/log1p(-G->p);
		}

		static double
		geometric_isf(const struct dist *dist, double p)
		{
		const struct geometric *G = const_container_of(dist, struct geometric, base);

		return log(p)/log1p(-G->p);
		}

		const struct dist_ops geometric_ops = {
		.name = "geometric (1-based)",
		.sample = geometric_sample,
		.cdf = geometric_cdf,
		.sf = geometric_sf,
		.icdf = geometric_icdf,
		.isf = geometric_isf,
		};

src/lib/math/prob_distr.h

+14 −32

Original line number	Diff line number	Diff line
		@@ -21,6 +21,13 @@ struct dist {

		#define DIST_BASE(OPS) { .ops = (OPS) }

		const char dist_name(const struct dist );
		double dist_sample(const struct dist *);
		double dist_cdf(const struct dist *, double x);
		double dist_sf(const struct dist *, double x);
		double dist_icdf(const struct dist *, double p);
		double dist_isf(const struct dist *, double p);

		struct dist_ops {
		const char *name;
		double (sample)(const struct dist );
		@@ -30,9 +37,14 @@ struct dist_ops {
		double (isf)(const struct dist , double p);
		};

		/* Geometric distribution */
		/* Geometric distribution on positive number of trials before first success */

		double geometric_sample(double p);
		struct geometric {
		struct dist base;
		double p; /* success probability */
		};

		extern const struct dist_ops geometric_ops;

		/* Pareto distribution */

		@@ -43,12 +55,6 @@ struct genpareto {
		double xi;
		};

		double genpareto_sample(const struct dist *dist);
		double genpareto_cdf(const struct dist *dist, double x);
		double genpareto_sf(const struct dist *dist, double x);
		double genpareto_icdf(const struct dist *dist, double p);
		double genpareto_isf(const struct dist *dist, double p);

		extern const struct dist_ops genpareto_ops;

		/* Weibull distribution */
		@@ -59,12 +65,6 @@ struct weibull {
		double k;
		};

		double weibull_sample(const struct dist *dist);
		double weibull_cdf(const struct dist *dist, double x);
		double weibull_sf(const struct dist *dist, double x);
		double weibull_icdf(const struct dist *dist, double p);
		double weibull_isf(const struct dist *dist, double p);

		extern const struct dist_ops weibull_ops;

		/* Log-logistic distribution */
		@@ -75,12 +75,6 @@ struct log_logistic {
		double beta;
		};

		double log_logistic_sample(const struct dist *dist);
		double log_logistic_cdf(const struct dist *dist, double x);
		double log_logistic_sf(const struct dist *dist, double x);
		double log_logistic_icdf(const struct dist *dist, double p);
		double log_logistic_isf(const struct dist *dist, double p);

		extern const struct dist_ops log_logistic_ops;

		/* Logistic distribution */
		@@ -91,12 +85,6 @@ struct logistic {
		double sigma;
		};

		double logistic_sample(const struct dist *dist);
		double logistic_cdf(const struct dist *dist, double x);
		double logistic_sf(const struct dist *dist, double x);
		double logistic_icdf(const struct dist *dist, double p);
		double logistic_isf(const struct dist *dist, double p);

		extern const struct dist_ops logistic_ops;

		/* Uniform distribution */
		@@ -107,12 +95,6 @@ struct uniform {
		double b;
		};

		double uniform_sample(const struct dist *dist);
		double uniform_cdf(const struct dist *dist, double x);
		double uniform_sf(const struct dist *dist, double x);
		double uniform_icdf(const struct dist *dist, double p);
		double uniform_isf(const struct dist *dist, double p);

		extern const struct dist_ops uniform_ops;

		/** Only by unittests */

src/test/test_prob_distr.c

+13 −9

Original line number	Diff line number	Diff line
		@@ -942,6 +942,10 @@ psi_test(const size_t C[PSI_DF], const double logP[PSI_DF], size_t N)
		static bool
		test_stochastic_geometric_impl(double p)
		{
		const struct geometric geometric = {
		.base = DIST_BASE(&geometric_ops),
		.p = p,
		};
		double logP[PSI_DF] = {0};
		unsigned ntry = NTRIALS, npass = 0;
		unsigned i;
		@@ -958,7 +962,7 @@ test_stochastic_geometric_impl(double p)
		size_t C[PSI_DF] = {0};

		for (j = 0; j < NSAMPLES; j++) {
		double n_tmp = geometric_sample(p);
		double n_tmp = dist_sample(&geometric.base);

		/* Must be an integer. (XXX -Wfloat-equal) */
		tor_assert(ceil(n_tmp) <= n_tmp && ceil(n_tmp) >= n_tmp);
		@@ -1006,10 +1010,10 @@ test_stochastic_geometric_impl(double p)
		static void
		bin_cdfs(const struct dist dist, double lo, double hi, double logP, size_t n)
		{
		#define CDF(x) dist->ops->cdf(dist, x)
		#define SF(x) dist->ops->sf(dist, x)
		#define CDF(x) dist_cdf(dist, x)
		#define SF(x) dist_sf(dist, x)
		const double w = (hi - lo)/(n - 2);
		double halfway = dist->ops->icdf(dist, 0.5);
		double halfway = dist_icdf(dist, 0.5);
		double x_0, x_1;
		size_t i;
		size_t n2 = ceil_to_size_t((halfway - lo)/w);
		@@ -1057,7 +1061,7 @@ bin_samples(const struct dist dist, double lo, double hi, size_t C, size_t n)
		size_t i;

		for (i = 0; i < NSAMPLES; i++) {
		double x = dist->ops->sample(dist);
		double x = dist_sample(dist);
		size_t bin;

		if (x < lo)
		@@ -1084,8 +1088,8 @@ test_psi_dist_sample(const struct dist *dist)
		{
		double logP[PSI_DF] = {0};
		unsigned ntry = NTRIALS, npass = 0;
		double lo = dist->ops->icdf(dist, 1/(double)(PSI_DF + 2));
		double hi = dist->ops->isf(dist, 1/(double)(PSI_DF + 2));
		double lo = dist_icdf(dist, 1/(double)(PSI_DF + 2));
		double hi = dist_isf(dist, 1/(double)(PSI_DF + 2));

		/* Create the null hypothesis in logP */
		bin_cdfs(dist, lo, hi, logP, PSI_DF);
		@@ -1102,10 +1106,10 @@ test_psi_dist_sample(const struct dist *dist)

		/* Did we fail or succeed? */
		if (npass >= NPASSES_MIN) {
		/* printf("pass %s sampler\n", dist->ops->name);*/
		/* printf("pass %s sampler\n", dist_name(dist));*/
		return true;
		} else {
		printf("fail %s sampler\n", dist->ops->name);
		printf("fail %s sampler\n", dist_name(dist));
		return false;
		}
		}