[tor-commits] [tor/master] Doxygen: fix unrecognized commands.
nickm at torproject.org
nickm at torproject.org
Wed Oct 16 13:11:54 UTC 2019
commit 591420df20211c19c687bc8abcb9234732bbc529
Author: Nick Mathewson <nickm at torproject.org>
Date: Wed Oct 16 08:39:41 2019 -0400
Doxygen: fix unrecognized commands.
Doxygen seems to interpret anything starting with \ as a command,
even when we don't mean it that way.
---
src/core/or/circuitpadding_machines.c | 2 -
src/lib/math/prob_distr.c | 76 +++++++++++++++++------------------
src/lib/process/process.h | 4 +-
3 files changed, 40 insertions(+), 42 deletions(-)
diff --git a/src/core/or/circuitpadding_machines.c b/src/core/or/circuitpadding_machines.c
index 7220d657f..98767f9e8 100644
--- a/src/core/or/circuitpadding_machines.c
+++ b/src/core/or/circuitpadding_machines.c
@@ -5,8 +5,6 @@
* \file circuitpadding_machines.c
* \brief Circuit padding state machines
*
- * \detail
- *
* Introduce circuit padding machines that will be used by Tor circuits, as
* specified by proposal 302 "Hiding onion service clients using padding".
*
diff --git a/src/lib/math/prob_distr.c b/src/lib/math/prob_distr.c
index d44dc2826..f9d65073f 100644
--- a/src/lib/math/prob_distr.c
+++ b/src/lib/math/prob_distr.c
@@ -178,8 +178,8 @@ clz32(uint32_t x)
/**
* Compute the logistic function: f(x) = 1/(1 + e^{-x}) = e^x/(1 + e^x).
- * Maps a log-odds-space probability in [-\infty, +\infty] into a direct-space
- * probability in [0,1]. Inverse of logit.
+ * Maps a log-odds-space probability in [-infinity, +infinity] into a
+ * direct-space probability in [0,1]. Inverse of logit.
*
* Ill-conditioned for large x; the identity logistic(-x) = 1 -
* logistic(x) and the function logistichalf(x) = logistic(x) - 1/2 may
@@ -266,7 +266,7 @@ logistic(double x)
/**
* Compute the logit function: log p/(1 - p). Defined on [0,1]. Maps
* a direct-space probability in [0,1] to a log-odds-space probability
- * in [-\infty, +\infty]. Inverse of logistic.
+ * in [-infinity, +infinity]. Inverse of logistic.
*
* Ill-conditioned near 1/2 and 1; the identity logit(1 - p) =
* -logit(p) and the function logithalf(p0) = logit(1/2 + p0) may help
@@ -488,7 +488,7 @@ random_uniform_01(void)
/* Functions for specific probability distributions start here: */
/*
- * Logistic(mu, sigma) distribution, supported on (-\infty,+\infty)
+ * Logistic(mu, sigma) distribution, supported on (-infinity,+infinity)
*
* This is the uniform distribution on [0,1] mapped into log-odds
* space, scaled by sigma and translated by mu.
@@ -546,7 +546,7 @@ isf_logistic(double p, double mu, double sigma)
}
/*
- * LogLogistic(alpha, beta) distribution, supported on (0, +\infty).
+ * LogLogistic(alpha, beta) distribution, supported on (0, +infinity).
*
* This is the uniform distribution on [0,1] mapped into odds space,
* scaled by positive alpha and shaped by positive beta.
@@ -687,7 +687,7 @@ isf_log_logistic(double p, double alpha, double beta)
}
/*
- * Weibull(lambda, k) distribution, supported on (0, +\infty).
+ * Weibull(lambda, k) distribution, supported on (0, +infinity).
*
* pdf(x) = (k/lambda) (x/lambda)^{k - 1} e^{-(x/lambda)^k}
* cdf(x) = 1 - e^{-(x/lambda)^k}
@@ -753,7 +753,7 @@ isf_weibull(double p, double lambda, double k)
}
/*
- * GeneralizedPareto(mu, sigma, xi), supported on (mu, +\infty) for
+ * GeneralizedPareto(mu, sigma, xi), supported on (mu, +infinity) for
* nonnegative xi, or (mu, mu - sigma/xi) for negative xi.
*
* Samples:
@@ -793,19 +793,19 @@ cdf_genpareto(double x, double mu, double sigma, double xi)
/*
* log(1 + xi x_0)/xi
- * = (-1/xi) \sum_{n=1}^\infty (-xi x_0)^n/n
- * = (-1/xi) (-xi x_0 + \sum_{n=2}^\infty (-xi x_0)^n/n)
- * = x_0 - (1/xi) \sum_{n=2}^\infty (-xi x_0)^n/n
- * = x_0 - x_0 \sum_{n=2}^\infty (-xi x_0)^{n-1}/n
+ * = (-1/xi) \sum_{n=1}^infinity (-xi x_0)^n/n
+ * = (-1/xi) (-xi x_0 + \sum_{n=2}^infinity (-xi x_0)^n/n)
+ * = x_0 - (1/xi) \sum_{n=2}^infinity (-xi x_0)^n/n
+ * = x_0 - x_0 \sum_{n=2}^infinity (-xi x_0)^{n-1}/n
* = x_0 (1 - d),
*
- * where d = \sum_{n=2}^\infty (-xi x_0)^{n-1}/n. If |xi| <
+ * where d = \sum_{n=2}^infinity (-xi x_0)^{n-1}/n. If |xi| <
* eps/4|x_0|, then
*
- * |d| <= \sum_{n=2}^\infty (eps/4)^{n-1}/n
- * <= \sum_{n=2}^\infty (eps/4)^{n-1}
- * = \sum_{n=1}^\infty (eps/4)^n
- * = (eps/4) \sum_{n=0}^\infty (eps/4)^n
+ * |d| <= \sum_{n=2}^infinity (eps/4)^{n-1}/n
+ * <= \sum_{n=2}^infinity (eps/4)^{n-1}
+ * = \sum_{n=1}^infinity (eps/4)^n
+ * = (eps/4) \sum_{n=0}^infinity (eps/4)^n
* = (eps/4)/(1 - eps/4)
* < eps/2
*
@@ -855,20 +855,20 @@ icdf_genpareto(double p, double mu, double sigma, double xi)
* for xi near zero (note f(xi) --> -log U as xi --> 0), write
* the absolutely convergent Taylor expansion
*
- * f(xi) = (1/xi)*(-xi log U + \sum_{n=2}^\infty (-xi log U)^n/n!
- * = -log U + (1/xi)*\sum_{n=2}^\infty (-xi log U)^n/n!
- * = -log U + \sum_{n=2}^\infty xi^{n-1} (-log U)^n/n!
- * = -log U - log U \sum_{n=2}^\infty (-xi log U)^{n-1}/n!
- * = -log U (1 + \sum_{n=2}^\infty (-xi log U)^{n-1}/n!).
+ * f(xi) = (1/xi)*(-xi log U + \sum_{n=2}^infinity (-xi log U)^n/n!
+ * = -log U + (1/xi)*\sum_{n=2}^infinity (-xi log U)^n/n!
+ * = -log U + \sum_{n=2}^infinity xi^{n-1} (-log U)^n/n!
+ * = -log U - log U \sum_{n=2}^infinity (-xi log U)^{n-1}/n!
+ * = -log U (1 + \sum_{n=2}^infinity (-xi log U)^{n-1}/n!).
*
- * Let d = \sum_{n=2}^\infty (-xi log U)^{n-1}/n!. What do we
+ * Let d = \sum_{n=2}^infinity (-xi log U)^{n-1}/n!. What do we
* lose if we discard it and use -log U as an approximation to
* f(xi)? If |xi| < eps/-4log U, then
*
- * |d| <= \sum_{n=2}^\infty |xi log U|^{n-1}/n!
- * <= \sum_{n=2}^\infty (eps/4)^{n-1}/n!
- * <= \sum_{n=1}^\infty (eps/4)^n
- * = (eps/4) \sum_{n=0}^\infty (eps/4)^n
+ * |d| <= \sum_{n=2}^infinity |xi log U|^{n-1}/n!
+ * <= \sum_{n=2}^infinity (eps/4)^{n-1}/n!
+ * <= \sum_{n=1}^infinity (eps/4)^n
+ * = (eps/4) \sum_{n=0}^infinity (eps/4)^n
* = (eps/4)/(1 - eps/4)
* < eps/2,
*
@@ -1098,10 +1098,10 @@ sample_logistic(uint32_t s, double t, double p0)
* We carve up the interval (0, 1) into subregions to compute
* the inverse CDF precisely:
*
- * A = (0, 1/(1 + e)] ---> (-\infty, -1]
+ * A = (0, 1/(1 + e)] ---> (-infinity, -1]
* B = [1/(1 + e), 1/2] ---> [-1, 0]
* C = [1/2, 1 - 1/(1 + e)] ---> [0, 1]
- * D = [1 - 1/(1 + e), 1) ---> [1, +\infty)
+ * D = [1 - 1/(1 + e), 1) ---> [1, +infinity)
*
* Cases D and C are mirror images of cases A and B,
* respectively, so we choose between them by the sign chosen
@@ -1234,19 +1234,19 @@ sample_genpareto(uint32_t s, double p0, double xi)
* Write f(xi) = (e^{xi x} - 1)/xi for xi near zero as the
* absolutely convergent Taylor series
*
- * f(x) = (1/xi) (xi x + \sum_{n=2}^\infty (xi x)^n/n!)
- * = x + (1/xi) \sum_{n=2}^\inty (xi x)^n/n!
- * = x + \sum_{n=2}^\infty xi^{n-1} x^n/n!
- * = x + x \sum_{n=2}^\infty (xi x)^{n-1}/n!
- * = x (1 + \sum_{n=2}^\infty (xi x)^{n-1}/n!).
+ * f(x) = (1/xi) (xi x + \sum_{n=2}^infinity (xi x)^n/n!)
+ * = x + (1/xi) \sum_{n=2}^infinity (xi x)^n/n!
+ * = x + \sum_{n=2}^infinity xi^{n-1} x^n/n!
+ * = x + x \sum_{n=2}^infinity (xi x)^{n-1}/n!
+ * = x (1 + \sum_{n=2}^infinity (xi x)^{n-1}/n!).
*
- * d = \sum_{n=2}^\infty (xi x)^{n-1}/n! is the relative error
+ * d = \sum_{n=2}^infinity (xi x)^{n-1}/n! is the relative error
* of f(x) from x. If |xi| < eps/4x, then
*
- * |d| <= \sum_{n=2}^\infty |xi x|^{n-1}/n!
- * <= \sum_{n=2}^\infty (eps/4)^{n-1}/n!
- * <= \sum_{n=1}^\infty (eps/4)
- * = (eps/4) \sum_{n=0}^\infty (eps/4)^n
+ * |d| <= \sum_{n=2}^infinity |xi x|^{n-1}/n!
+ * <= \sum_{n=2}^infinity (eps/4)^{n-1}/n!
+ * <= \sum_{n=1}^infinity (eps/4)
+ * = (eps/4) \sum_{n=0}^infinity (eps/4)^n
* = (eps/4)/(1 - eps/4)
* < eps/2,
*
diff --git a/src/lib/process/process.h b/src/lib/process/process.h
index 05c091a5b..b28f55e0a 100644
--- a/src/lib/process/process.h
+++ b/src/lib/process/process.h
@@ -35,8 +35,8 @@ typedef enum {
const char *process_status_to_string(process_status_t status);
typedef enum {
- /** Pass complete \n-terminated lines to the
- * callback (with the \n or \r\n removed). */
+ /** Pass complete newline-terminated lines to the
+ * callback (with the LF or CRLF removed). */
PROCESS_PROTOCOL_LINE,
/** Pass the raw response from read() to the callback. */
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