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-rw-r--r--numpy/random/mtrand/distributions.c82
1 files changed, 41 insertions, 41 deletions
diff --git a/numpy/random/mtrand/distributions.c b/numpy/random/mtrand/distributions.c
index d792cf86d..05f62f0cf 100644
--- a/numpy/random/mtrand/distributions.c
+++ b/numpy/random/mtrand/distributions.c
@@ -7,10 +7,10 @@
* distribute, sublicense, and/or sell copies of the Software, and to
* permit persons to whom the Software is furnished to do so, subject to
* the following conditions:
- *
+ *
* The above copyright notice and this permission notice shall be included
* in all copies or substantial portions of the Software.
- *
+ *
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
* OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
* MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
@@ -21,9 +21,9 @@
*/
/* The implementations of rk_hypergeometric_hyp(), rk_hypergeometric_hrua(),
- * and rk_triangular() were adapted from Ivan Frohne's rv.py which has this
+ * and rk_triangular() were adapted from Ivan Frohne's rv.py which has this
* license:
- *
+ *
* Copyright 1998 by Ivan Frohne; Wasilla, Alaska, U.S.A.
* All Rights Reserved
*
@@ -52,8 +52,8 @@
#ifndef M_PI
#define M_PI 3.14159265358979323846264338328
-#endif
-/* log-gamma function to support some of these distributions. The
+#endif
+/* log-gamma function to support some of these distributions. The
* algorithm comes from SPECFUN by Shanjie Zhang and Jianming Jin and their
* book "Computation of Special Functions", 1996, John Wiley & Sons, Inc.
*/
@@ -62,7 +62,7 @@ double loggam(double x)
{
double x0, x2, xp, gl, gl0;
long k, n;
-
+
static double a[10] = {8.333333333333333e-02,-2.777777777777778e-03,
7.936507936507937e-04,-5.952380952380952e-04,
8.417508417508418e-04,-1.917526917526918e-03,
@@ -162,7 +162,7 @@ double rk_standard_gamma(rk_state *state, double shape)
{
do
{
- X = rk_gauss(state);
+ X = rk_gauss(state);
V = 1.0 + c*X;
} while (V <= 0.0);
@@ -225,7 +225,7 @@ double rk_noncentral_chisquare(rk_state *state, double df, double nonc)
double rk_f(rk_state *state, double dfnum, double dfden)
{
- return ((rk_chisquare(state, dfnum) * dfden) /
+ return ((rk_chisquare(state, dfnum) * dfden) /
(rk_chisquare(state, dfden) * dfnum));
}
@@ -241,7 +241,7 @@ long rk_binomial_btpe(rk_state *state, long n, double p)
double a,u,v,s,F,rho,t,A,nrq,x1,x2,f1,f2,z,z2,w,w2,x;
long m,y,k,i;
- if (!(state->has_binomial) ||
+ if (!(state->has_binomial) ||
(state->nsave != n) ||
(state->psave != p))
{
@@ -380,7 +380,7 @@ long rk_binomial_inversion(rk_state *state, long n, double p)
double q, qn, np, px, U;
long X, bound;
- if (!(state->has_binomial) ||
+ if (!(state->has_binomial) ||
(state->nsave != n) ||
(state->psave != p))
{
@@ -404,12 +404,12 @@ long rk_binomial_inversion(rk_state *state, long n, double p)
while (U > px)
{
X++;
- if (X > bound)
+ if (X > bound)
{
X = 0;
px = qn;
U = rk_double(state);
- } else
+ } else
{
U -= px;
px = ((n-X+1) * p * px)/(X*q);
@@ -514,7 +514,7 @@ long rk_poisson_ptrs(rk_state *state, double lam)
return k;
}
-
+
}
}
@@ -525,11 +525,11 @@ long rk_poisson(rk_state *state, double lam)
{
return rk_poisson_ptrs(state, lam);
}
- else if (lam == 0)
+ else if (lam == 0)
{
return 0;
}
- else
+ else
{
return rk_poisson_mult(state, lam);
}
@@ -551,7 +551,7 @@ double rk_standard_t(rk_state *state, double df)
}
/* Uses the rejection algorithm compared against the wrapped Cauchy
- distribution suggested by Best and Fisher and documented in
+ distribution suggested by Best and Fisher and documented in
Chapter 9 of Luc's Non-Uniform Random Variate Generation.
http://cg.scs.carleton.ca/~luc/rnbookindex.html
(but corrected to match the algorithm in R and Python)
@@ -600,7 +600,7 @@ double rk_vonmises(rk_state *state, double mu, double kappa)
if (neg)
{
mod *= -1;
- }
+ }
return mod;
}
@@ -624,12 +624,12 @@ double rk_power(rk_state *state, double a)
double rk_laplace(rk_state *state, double loc, double scale)
{
double U;
-
+
U = rk_double(state);
if (U < 0.5)
{
U = loc + scale * log(U + U);
- } else
+ } else
{
U = loc - scale * log(2.0 - U - U);
}
@@ -639,7 +639,7 @@ double rk_laplace(rk_state *state, double loc, double scale)
double rk_gumbel(rk_state *state, double loc, double scale)
{
double U;
-
+
U = 1.0 - rk_double(state);
return loc - scale * log(-log(U));
}
@@ -647,7 +647,7 @@ double rk_gumbel(rk_state *state, double loc, double scale)
double rk_logistic(rk_state *state, double loc, double scale)
{
double U;
-
+
U = rk_double(state);
return loc + scale * log(U/(1.0 - U));
}
@@ -666,7 +666,7 @@ double rk_wald(rk_state *state, double mean, double scale)
{
double U, X, Y;
double mu_2l;
-
+
mu_2l = mean / (2*scale);
Y = rk_gauss(state);
Y = mean*Y*Y;
@@ -710,7 +710,7 @@ long rk_geometric_search(rk_state *state, double p)
double U;
long X;
double sum, prod, q;
-
+
X = 1;
sum = prod = p;
q = 1.0 - p;
@@ -744,10 +744,10 @@ long rk_hypergeometric_hyp(rk_state *state, long good, long bad, long sample)
{
long d1, K, Z;
double d2, U, Y;
-
+
d1 = bad + good - sample;
d2 = (double)min(bad, good);
-
+
Y = d2;
K = sample;
while (Y > 0.0)
@@ -772,7 +772,7 @@ long rk_hypergeometric_hrua(rk_state *state, long good, long bad, long sample)
double d4, d5, d6, d7, d8, d10, d11;
long Z;
double T, W, X, Y;
-
+
mingoodbad = min(good, bad);
popsize = good + bad;
maxgoodbad = max(good, bad);
@@ -783,39 +783,39 @@ long rk_hypergeometric_hrua(rk_state *state, long good, long bad, long sample)
d7 = sqrt((popsize - m) * sample * d4 *d5 / (popsize-1) + 0.5);
d8 = D1*d7 + D2;
d9 = (long)floor((double)((m+1)*(mingoodbad+1))/(popsize+2));
- d10 = (loggam(d9+1) + loggam(mingoodbad-d9+1) + loggam(m-d9+1) +
+ d10 = (loggam(d9+1) + loggam(mingoodbad-d9+1) + loggam(m-d9+1) +
loggam(maxgoodbad-m+d9+1));
d11 = min(min(m, mingoodbad)+1.0, floor(d6+16*d7));
/* 16 for 16-decimal-digit precision in D1 and D2 */
-
+
while (1)
{
X = rk_double(state);
Y = rk_double(state);
W = d6 + d8*(Y- 0.5)/X;
-
+
/* fast rejection: */
if ((W < 0.0) || (W >= d11)) continue;
-
+
Z = (long)floor(W);
T = d10 - (loggam(Z+1) + loggam(mingoodbad-Z+1) + loggam(m-Z+1) +
loggam(maxgoodbad-m+Z+1));
-
+
/* fast acceptance: */
if ((X*(4.0-X)-3.0) <= T) break;
-
+
/* fast rejection: */
if (X*(X-T) >= 1) continue;
if (2.0*log(X) <= T) break; /* acceptance */
}
-
+
/* this is a correction to HRUA* by Ivan Frohne in rv.py */
if (good > bad) Z = m - Z;
-
+
/* another fix from rv.py to allow sample to exceed popsize/2 */
if (m < sample) Z = good - Z;
-
+
return Z;
}
#undef D1
@@ -836,20 +836,20 @@ double rk_triangular(rk_state *state, double left, double mode, double right)
{
double base, leftbase, ratio, leftprod, rightprod;
double U;
-
+
base = right - left;
leftbase = mode - left;
ratio = leftbase / base;
leftprod = leftbase*base;
rightprod = (right - mode)*base;
-
+
U = rk_double(state);
if (U <= ratio)
{
return left + sqrt(U*leftprod);
- } else
+ } else
{
- return right - sqrt((1.0 - U) * rightprod);
+ return right - sqrt((1.0 - U) * rightprod);
}
}
@@ -857,7 +857,7 @@ long rk_logseries(rk_state *state, double p)
{
double q, r, U, V;
long result;
-
+
r = log(1.0 - p);
while (1) {
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