26 | | Array<int> to_Arr ( const ivec &indices ) { |
27 | | Array<int> a ( indices.size() ); |
28 | | for ( int i = 0; i < a.size(); i++ ) { |
29 | | a ( i ) = indices ( i ); |
30 | | } |
31 | | return a; |
32 | | } |
33 | | |
34 | | ivec linspace ( int from, int to ) { |
35 | | int n=to-from+1; |
36 | | int i; |
37 | | it_assert_debug ( n>0,"wrong linspace" ); |
38 | | ivec iv ( n ); for ( i=0;i<n;i++ ) iv ( i ) =from+i; |
39 | | return iv; |
40 | | }; |
41 | | |
42 | | void set_subvector ( vec &ov, const ivec &iv, const vec &v ) |
43 | | { |
44 | | it_assert_debug ( ( iv.length() <=v.length() ), |
45 | | "Vec<>::set_subvector(ivec, vec<Num_T>): Indexing out " |
46 | | "of range of v" ); |
47 | | for ( int i = 0; i < iv.length(); i++ ) { |
48 | | it_assert_debug ( iv ( i ) <ov.length(), |
49 | | "Vec<>::set_subvector(ivec, vec<Num_T>): Indexing out " |
50 | | "of range of v" ); |
51 | | ov ( iv ( i ) ) = v ( i ); |
52 | | } |
53 | | } |
54 | | |
55 | | vec get_vec(const vec &v, const ivec &indexlist){ |
56 | | int size = indexlist.size(); |
57 | | vec temp(size); |
58 | | for (int i = 0; i < size; ++i) { |
59 | | temp(i) = v._data()[indexlist(i)]; |
60 | | } |
61 | | return temp; |
62 | | } |
| 26 | Array<int> to_Arr ( const ivec &indices ) { |
| 27 | Array<int> a ( indices.size() ); |
| 28 | for ( int i = 0; i < a.size(); i++ ) { |
| 29 | a ( i ) = indices ( i ); |
| 30 | } |
| 31 | return a; |
| 32 | } |
| 33 | |
| 34 | ivec linspace ( int from, int to ) { |
| 35 | int n = to - from + 1; |
| 36 | int i; |
| 37 | it_assert_debug ( n > 0, "wrong linspace" ); |
| 38 | ivec iv ( n ); |
| 39 | for ( i = 0; i < n; i++ ) iv ( i ) = from + i; |
| 40 | return iv; |
| 41 | }; |
| 42 | |
| 43 | void set_subvector ( vec &ov, const ivec &iv, const vec &v ) { |
| 44 | it_assert_debug ( ( iv.length() <= v.length() ), |
| 45 | "Vec<>::set_subvector(ivec, vec<Num_T>): Indexing out " |
| 46 | "of range of v" ); |
| 47 | for ( int i = 0; i < iv.length(); i++ ) { |
| 48 | it_assert_debug ( iv ( i ) < ov.length(), |
| 49 | "Vec<>::set_subvector(ivec, vec<Num_T>): Indexing out " |
| 50 | "of range of v" ); |
| 51 | ov ( iv ( i ) ) = v ( i ); |
| 52 | } |
| 53 | } |
| 54 | |
| 55 | vec get_vec ( const vec &v, const ivec &indexlist ) { |
| 56 | int size = indexlist.size(); |
| 57 | vec temp ( size ); |
| 58 | for ( int i = 0; i < size; ++i ) { |
| 59 | temp ( i ) = v._data() [indexlist ( i ) ]; |
| 60 | } |
| 61 | return temp; |
| 62 | } |
70 | | bvec operator>(const vec &t1, const vec &t2) { |
71 | | it_assert_debug(t1.length() == t2.length(), "Vec<>::operator>(): different size of vectors"); |
72 | | bvec temp(t1.length()); |
73 | | for (int i = 0; i < t1.length(); i++) |
74 | | temp(i) = (t1[i] > t2[i]); |
75 | | return temp; |
76 | | } |
77 | | |
78 | | bvec operator<(const vec &t1, const vec &t2) { |
79 | | it_assert_debug(t1.length() == t2.length(), "Vec<>::operator>(): different size of vectors"); |
80 | | bvec temp(t1.length()); |
81 | | for (int i = 0; i < t1.length(); i++) |
82 | | temp(i) = (t1[i] < t2[i]); |
83 | | return temp; |
84 | | } |
85 | | |
86 | | |
87 | | bvec operator& ( const bvec &a, const bvec &b ) { |
88 | | it_assert_debug ( b.size() ==a.size(), "operator&(): Vectors of different lengths" ); |
89 | | |
90 | | bvec temp ( a.size() ); |
91 | | for ( int i = 0;i < a.size();i++ ) { |
92 | | temp ( i ) = a ( i ) & b ( i ); |
93 | | } |
94 | | return temp; |
95 | | } |
96 | | |
97 | | bvec operator| ( const bvec &a, const bvec &b ) { |
98 | | it_assert_debug ( b.size() !=a.size(), "operator&(): Vectors of different lengths" ); |
99 | | |
100 | | bvec temp ( a.size() ); |
101 | | for ( int i = 0;i < a.size();i++ ) { |
102 | | temp ( i ) = a ( i ) | b ( i ); |
103 | | } |
104 | | return temp; |
105 | | } |
| 70 | bvec operator> ( const vec &t1, const vec &t2 ) { |
| 71 | it_assert_debug ( t1.length() == t2.length(), "Vec<>::operator>(): different size of vectors" ); |
| 72 | bvec temp ( t1.length() ); |
| 73 | for ( int i = 0; i < t1.length(); i++ ) |
| 74 | temp ( i ) = ( t1[i] > t2[i] ); |
| 75 | return temp; |
| 76 | } |
| 77 | |
| 78 | bvec operator< ( const vec &t1, const vec &t2 ) { |
| 79 | it_assert_debug ( t1.length() == t2.length(), "Vec<>::operator>(): different size of vectors" ); |
| 80 | bvec temp ( t1.length() ); |
| 81 | for ( int i = 0; i < t1.length(); i++ ) |
| 82 | temp ( i ) = ( t1[i] < t2[i] ); |
| 83 | return temp; |
| 84 | } |
| 85 | |
| 86 | |
| 87 | bvec operator& ( const bvec &a, const bvec &b ) { |
| 88 | it_assert_debug ( b.size() == a.size(), "operator&(): Vectors of different lengths" ); |
| 89 | |
| 90 | bvec temp ( a.size() ); |
| 91 | for ( int i = 0; i < a.size(); i++ ) { |
| 92 | temp ( i ) = a ( i ) & b ( i ); |
| 93 | } |
| 94 | return temp; |
| 95 | } |
| 96 | |
| 97 | bvec operator| ( const bvec &a, const bvec &b ) { |
| 98 | it_assert_debug ( b.size() != a.size(), "operator&(): Vectors of different lengths" ); |
| 99 | |
| 100 | bvec temp ( a.size() ); |
| 101 | for ( int i = 0; i < a.size(); i++ ) { |
| 102 | temp ( i ) = a ( i ) | b ( i ); |
| 103 | } |
| 104 | return temp; |
| 105 | } |
108 | | Gamma_RNG::Gamma_RNG ( double a, double b ) { |
109 | | setup ( a,b ); |
110 | | } |
111 | | double Gamma_RNG::sample() { |
112 | | //A copy of rgamma code from the R package!! |
113 | | // |
114 | | |
115 | | /* Constants : */ |
116 | | const static double sqrt32 = 5.656854; |
117 | | const static double exp_m1 = 0.36787944117144232159;/* exp(-1) = 1/e */ |
118 | | |
119 | | /* Coefficients q[k] - for q0 = sum(q[k]*a^(-k)) |
120 | | * Coefficients a[k] - for q = q0+(t*t/2)*sum(a[k]*v^k) |
121 | | * Coefficients e[k] - for exp(q)-1 = sum(e[k]*q^k) |
122 | | */ |
123 | | const static double q1 = 0.04166669; |
124 | | const static double q2 = 0.02083148; |
125 | | const static double q3 = 0.00801191; |
126 | | const static double q4 = 0.00144121; |
127 | | const static double q5 = -7.388e-5; |
128 | | const static double q6 = 2.4511e-4; |
129 | | const static double q7 = 2.424e-4; |
130 | | |
131 | | const static double a1 = 0.3333333; |
132 | | const static double a2 = -0.250003; |
133 | | const static double a3 = 0.2000062; |
134 | | const static double a4 = -0.1662921; |
135 | | const static double a5 = 0.1423657; |
136 | | const static double a6 = -0.1367177; |
137 | | const static double a7 = 0.1233795; |
138 | | |
139 | | /* State variables [FIXME for threading!] :*/ |
140 | | static double aa = 0.; |
141 | | static double aaa = 0.; |
142 | | static double s, s2, d; /* no. 1 (step 1) */ |
143 | | static double q0, b, si, c;/* no. 2 (step 4) */ |
144 | | |
145 | | double e, p, q, r, t, u, v, w, x, ret_val; |
146 | | double a=alpha; |
147 | | double scale=1.0/beta; |
148 | | |
149 | | if ( !R_FINITE ( a ) || !R_FINITE ( scale ) || a < 0.0 || scale <= 0.0 ) |
150 | | {it_error ( "Gamma_RNG wrong parameters" );} |
151 | | |
152 | | if ( a < 1. ) { /* GS algorithm for parameters a < 1 */ |
153 | | if ( a == 0 ) |
154 | | return 0.; |
155 | | e = 1.0 + exp_m1 * a; |
156 | | for ( ;; ) { //VS repeat |
157 | | p = e * unif_rand(); |
158 | | if ( p >= 1.0 ) { |
159 | | x = -log ( ( e - p ) / a ); |
160 | | if ( exp_rand() >= ( 1.0 - a ) * log ( x ) ) |
161 | | break; |
162 | | } |
163 | | else { |
164 | | x = exp ( log ( p ) / a ); |
165 | | if ( exp_rand() >= x ) |
166 | | break; |
167 | | } |
| 108 | Gamma_RNG::Gamma_RNG ( double a, double b ) { |
| 109 | setup ( a, b ); |
| 110 | } |
| 111 | double Gamma_RNG::sample() { |
| 112 | //A copy of rgamma code from the R package!! |
| 113 | // |
| 114 | |
| 115 | /* Constants : */ |
| 116 | const static double sqrt32 = 5.656854; |
| 117 | const static double exp_m1 = 0.36787944117144232159;/* exp(-1) = 1/e */ |
| 118 | |
| 119 | /* Coefficients q[k] - for q0 = sum(q[k]*a^(-k)) |
| 120 | * Coefficients a[k] - for q = q0+(t*t/2)*sum(a[k]*v^k) |
| 121 | * Coefficients e[k] - for exp(q)-1 = sum(e[k]*q^k) |
| 122 | */ |
| 123 | const static double q1 = 0.04166669; |
| 124 | const static double q2 = 0.02083148; |
| 125 | const static double q3 = 0.00801191; |
| 126 | const static double q4 = 0.00144121; |
| 127 | const static double q5 = -7.388e-5; |
| 128 | const static double q6 = 2.4511e-4; |
| 129 | const static double q7 = 2.424e-4; |
| 130 | |
| 131 | const static double a1 = 0.3333333; |
| 132 | const static double a2 = -0.250003; |
| 133 | const static double a3 = 0.2000062; |
| 134 | const static double a4 = -0.1662921; |
| 135 | const static double a5 = 0.1423657; |
| 136 | const static double a6 = -0.1367177; |
| 137 | const static double a7 = 0.1233795; |
| 138 | |
| 139 | /* State variables [FIXME for threading!] :*/ |
| 140 | static double aa = 0.; |
| 141 | static double aaa = 0.; |
| 142 | static double s, s2, d; /* no. 1 (step 1) */ |
| 143 | static double q0, b, si, c;/* no. 2 (step 4) */ |
| 144 | |
| 145 | double e, p, q, r, t, u, v, w, x, ret_val; |
| 146 | double a = alpha; |
| 147 | double scale = 1.0 / beta; |
| 148 | |
| 149 | if ( !R_FINITE ( a ) || !R_FINITE ( scale ) || a < 0.0 || scale <= 0.0 ) { |
| 150 | it_error ( "Gamma_RNG wrong parameters" ); |
| 151 | } |
| 152 | |
| 153 | if ( a < 1. ) { /* GS algorithm for parameters a < 1 */ |
| 154 | if ( a == 0 ) |
| 155 | return 0.; |
| 156 | e = 1.0 + exp_m1 * a; |
| 157 | for ( ;; ) { //VS repeat |
| 158 | p = e * unif_rand(); |
| 159 | if ( p >= 1.0 ) { |
| 160 | x = -log ( ( e - p ) / a ); |
| 161 | if ( exp_rand() >= ( 1.0 - a ) * log ( x ) ) |
| 162 | break; |
| 163 | } else { |
| 164 | x = exp ( log ( p ) / a ); |
| 165 | if ( exp_rand() >= x ) |
| 166 | break; |
169 | | return scale * x; |
170 | | } |
171 | | |
172 | | /* --- a >= 1 : GD algorithm --- */ |
173 | | |
174 | | /* Step 1: Recalculations of s2, s, d if a has changed */ |
175 | | if ( a != aa ) { |
176 | | aa = a; |
177 | | s2 = a - 0.5; |
178 | | s = sqrt ( s2 ); |
179 | | d = sqrt32 - s * 12.0; |
180 | | } |
181 | | /* Step 2: t = standard normal deviate, |
182 | | x = (s,1/2) -normal deviate. */ |
183 | | |
184 | | /* immediate acceptance (i) */ |
185 | | t = norm_rand(); |
186 | | x = s + 0.5 * t; |
187 | | ret_val = x * x; |
188 | | if ( t >= 0.0 ) |
| 168 | } |
| 169 | return scale * x; |
| 170 | } |
| 171 | |
| 172 | /* --- a >= 1 : GD algorithm --- */ |
| 173 | |
| 174 | /* Step 1: Recalculations of s2, s, d if a has changed */ |
| 175 | if ( a != aa ) { |
| 176 | aa = a; |
| 177 | s2 = a - 0.5; |
| 178 | s = sqrt ( s2 ); |
| 179 | d = sqrt32 - s * 12.0; |
| 180 | } |
| 181 | /* Step 2: t = standard normal deviate, |
| 182 | x = (s,1/2) -normal deviate. */ |
| 183 | |
| 184 | /* immediate acceptance (i) */ |
| 185 | t = norm_rand(); |
| 186 | x = s + 0.5 * t; |
| 187 | ret_val = x * x; |
| 188 | if ( t >= 0.0 ) |
| 189 | return scale * ret_val; |
| 190 | |
| 191 | /* Step 3: u = 0,1 - uniform sample. squeeze acceptance (s) */ |
| 192 | u = unif_rand(); |
| 193 | if ( ( d * u ) <= ( t * t * t ) ) |
| 194 | return scale * ret_val; |
| 195 | |
| 196 | /* Step 4: recalculations of q0, b, si, c if necessary */ |
| 197 | |
| 198 | if ( a != aaa ) { |
| 199 | aaa = a; |
| 200 | r = 1.0 / a; |
| 201 | q0 = ( ( ( ( ( ( q7 * r + q6 ) * r + q5 ) * r + q4 ) * r + q3 ) * r |
| 202 | + q2 ) * r + q1 ) * r; |
| 203 | |
| 204 | /* Approximation depending on size of parameter a */ |
| 205 | /* The constants in the expressions for b, si and c */ |
| 206 | /* were established by numerical experiments */ |
| 207 | |
| 208 | if ( a <= 3.686 ) { |
| 209 | b = 0.463 + s + 0.178 * s2; |
| 210 | si = 1.235; |
| 211 | c = 0.195 / s - 0.079 + 0.16 * s; |
| 212 | } else if ( a <= 13.022 ) { |
| 213 | b = 1.654 + 0.0076 * s2; |
| 214 | si = 1.68 / s + 0.275; |
| 215 | c = 0.062 / s + 0.024; |
| 216 | } else { |
| 217 | b = 1.77; |
| 218 | si = 0.75; |
| 219 | c = 0.1515 / s; |
| 220 | } |
| 221 | } |
| 222 | /* Step 5: no quotient test if x not positive */ |
| 223 | |
| 224 | if ( x > 0.0 ) { |
| 225 | /* Step 6: calculation of v and quotient q */ |
| 226 | v = t / ( s + s ); |
| 227 | if ( fabs ( v ) <= 0.25 ) |
| 228 | q = q0 + 0.5 * t * t * ( ( ( ( ( ( a7 * v + a6 ) * v + a5 ) * v + a4 ) * v |
| 229 | + a3 ) * v + a2 ) * v + a1 ) * v; |
| 230 | else |
| 231 | q = q0 - s * t + 0.25 * t * t + ( s2 + s2 ) * log ( 1.0 + v ); |
| 232 | |
| 233 | |
| 234 | /* Step 7: quotient acceptance (q) */ |
| 235 | if ( log ( 1.0 - u ) <= q ) |
193 | | if ( ( d * u ) <= ( t * t * t ) ) |
194 | | return scale * ret_val; |
195 | | |
196 | | /* Step 4: recalculations of q0, b, si, c if necessary */ |
197 | | |
198 | | if ( a != aaa ) { |
199 | | aaa = a; |
200 | | r = 1.0 / a; |
201 | | q0 = ( ( ( ( ( ( q7 * r + q6 ) * r + q5 ) * r + q4 ) * r + q3 ) * r |
202 | | + q2 ) * r + q1 ) * r; |
203 | | |
204 | | /* Approximation depending on size of parameter a */ |
205 | | /* The constants in the expressions for b, si and c */ |
206 | | /* were established by numerical experiments */ |
207 | | |
208 | | if ( a <= 3.686 ) { |
209 | | b = 0.463 + s + 0.178 * s2; |
210 | | si = 1.235; |
211 | | c = 0.195 / s - 0.079 + 0.16 * s; |
212 | | } |
213 | | else if ( a <= 13.022 ) { |
214 | | b = 1.654 + 0.0076 * s2; |
215 | | si = 1.68 / s + 0.275; |
216 | | c = 0.062 / s + 0.024; |
217 | | } |
218 | | else { |
219 | | b = 1.77; |
220 | | si = 0.75; |
221 | | c = 0.1515 / s; |
222 | | } |
223 | | } |
224 | | /* Step 5: no quotient test if x not positive */ |
225 | | |
226 | | if ( x > 0.0 ) { |
227 | | /* Step 6: calculation of v and quotient q */ |
| 245 | u = u + u - 1.0; |
| 246 | if ( u < 0.0 ) |
| 247 | t = b - si * e; |
| 248 | else |
| 249 | t = b + si * e; |
| 250 | /* Step 9: rejection if t < tau(1) = -0.71874483771719 */ |
| 251 | if ( t >= -0.71874483771719 ) { |
| 252 | /* Step 10: calculation of v and quotient q */ |
234 | | |
235 | | |
236 | | /* Step 7: quotient acceptance (q) */ |
237 | | if ( log ( 1.0 - u ) <= q ) |
238 | | return scale * ret_val; |
239 | | } |
240 | | |
241 | | for ( ;; ) { //VS repeat |
242 | | /* Step 8: e = standard exponential deviate |
243 | | * u = 0,1 -uniform deviate |
244 | | * t = (b,si)-double exponential (laplace) sample */ |
245 | | e = exp_rand(); |
246 | | u = unif_rand(); |
247 | | u = u + u - 1.0; |
248 | | if ( u < 0.0 ) |
249 | | t = b - si * e; |
250 | | else |
251 | | t = b + si * e; |
252 | | /* Step 9: rejection if t < tau(1) = -0.71874483771719 */ |
253 | | if ( t >= -0.71874483771719 ) { |
254 | | /* Step 10: calculation of v and quotient q */ |
255 | | v = t / ( s + s ); |
256 | | if ( fabs ( v ) <= 0.25 ) |
257 | | q = q0 + 0.5 * t * t * |
258 | | ( ( ( ( ( ( a7 * v + a6 ) * v + a5 ) * v + a4 ) * v + a3 ) * v |
259 | | + a2 ) * v + a1 ) * v; |
260 | | else |
261 | | q = q0 - s * t + 0.25 * t * t + ( s2 + s2 ) * log ( 1.0 + v ); |
262 | | /* Step 11: hat acceptance (h) */ |
263 | | /* (if q not positive go to step 8) */ |
264 | | if ( q > 0.0 ) { |
265 | | // TODO: w = expm1(q); |
266 | | w = exp ( q )-1; |
267 | | /* ^^^^^ original code had approximation with rel.err < 2e-7 */ |
268 | | /* if t is rejected sample again at step 8 */ |
269 | | if ( ( c * fabs ( u ) ) <= ( w * exp ( e - 0.5 * t * t ) ) ) |
270 | | break; |
271 | | } |
| 260 | /* Step 11: hat acceptance (h) */ |
| 261 | /* (if q not positive go to step 8) */ |
| 262 | if ( q > 0.0 ) { |
| 263 | // TODO: w = expm1(q); |
| 264 | w = exp ( q ) - 1; |
| 265 | /* ^^^^^ original code had approximation with rel.err < 2e-7 */ |
| 266 | /* if t is rejected sample again at step 8 */ |
| 267 | if ( ( c * fabs ( u ) ) <= ( w * exp ( e - 0.5 * t * t ) ) ) |
| 268 | break; |
273 | | } /* repeat .. until `t' is accepted */ |
274 | | x = s + 0.5 * t; |
275 | | return scale * x * x; |
276 | | } |
277 | | |
278 | | |
279 | | bool qr ( const mat &A, mat &R ) { |
280 | | int info; |
281 | | int m = A.rows(); |
282 | | int n = A.cols(); |
283 | | int lwork = n; |
284 | | int k = std::min ( m, n ); |
285 | | vec tau ( k ); |
286 | | vec work ( lwork ); |
287 | | |
288 | | R = A; |
289 | | |
290 | | // perform workspace query for optimum lwork value |
291 | | int lwork_tmp = -1; |
292 | | dgeqrf_ ( &m, &n, R._data(), &m, tau._data(), work._data(), &lwork_tmp, |
293 | | &info ); |
294 | | if ( info == 0 ) { |
295 | | lwork = static_cast<int> ( work ( 0 ) ); |
296 | | work.set_size ( lwork, false ); |
297 | | } |
298 | | dgeqrf_ ( &m, &n, R._data(), &m, tau._data(), work._data(), &lwork, &info ); |
299 | | |
300 | | // construct R |
301 | | for ( int i=0; i<m; i++ ) |
302 | | for ( int j=0; j<std::min ( i,n ); j++ ) |
303 | | R ( i,j ) = 0; |
304 | | |
305 | | return ( info==0 ); |
306 | | } |
| 270 | } |
| 271 | } /* repeat .. until `t' is accepted */ |
| 272 | x = s + 0.5 * t; |
| 273 | return scale * x * x; |
| 274 | } |
| 275 | |
| 276 | |
| 277 | bool qr ( const mat &A, mat &R ) { |
| 278 | int info; |
| 279 | int m = A.rows(); |
| 280 | int n = A.cols(); |
| 281 | int lwork = n; |
| 282 | int k = std::min ( m, n ); |
| 283 | vec tau ( k ); |
| 284 | vec work ( lwork ); |
| 285 | |
| 286 | R = A; |
| 287 | |
| 288 | // perform workspace query for optimum lwork value |
| 289 | int lwork_tmp = -1; |
| 290 | dgeqrf_ ( &m, &n, R._data(), &m, tau._data(), work._data(), &lwork_tmp, |
| 291 | &info ); |
| 292 | if ( info == 0 ) { |
| 293 | lwork = static_cast<int> ( work ( 0 ) ); |
| 294 | work.set_size ( lwork, false ); |
| 295 | } |
| 296 | dgeqrf_ ( &m, &n, R._data(), &m, tau._data(), work._data(), &lwork, &info ); |
| 297 | |
| 298 | // construct R |
| 299 | for ( int i = 0; i < m; i++ ) |
| 300 | for ( int j = 0; j < std::min ( i, n ); j++ ) |
| 301 | R ( i, j ) = 0; |
| 302 | |
| 303 | return ( info == 0 ); |
| 304 | } |
325 | | double psi(double x) { |
326 | | double s,ps,xa,x2; |
327 | | int n,k; |
328 | | static double a[] = { |
329 | | -0.8333333333333e-01, |
330 | | 0.83333333333333333e-02, |
331 | | -0.39682539682539683e-02, |
332 | | 0.41666666666666667e-02, |
333 | | -0.75757575757575758e-02, |
334 | | 0.21092796092796093e-01, |
335 | | -0.83333333333333333e-01, |
336 | | 0.4432598039215686}; |
337 | | |
338 | | xa = fabs(x); |
339 | | s = 0.0; |
340 | | if ((x == (int)x) && (x <= 0.0)) { |
341 | | ps = 1e308; |
342 | | return ps; |
343 | | } |
344 | | if (xa == (int)xa) { |
345 | | n = xa; |
346 | | for (k=1;k<n;k++) { |
347 | | s += 1.0/k; |
348 | | } |
349 | | ps = s-el; |
350 | | } |
351 | | else if ((xa+0.5) == ((int)(xa+0.5))) { |
352 | | n = xa-0.5; |
353 | | for (k=1;k<=n;k++) { |
354 | | s += 1.0/(2.0*k-1.0); |
355 | | } |
356 | | ps = 2.0*s-el-1.386294361119891; |
357 | | } |
358 | | else { |
359 | | if (xa < 10.0) { |
360 | | n = 10-(int)xa; |
361 | | for (k=0;k<n;k++) { |
362 | | s += 1.0/(xa+k); |
363 | | } |
364 | | xa += n; |
365 | | } |
366 | | x2 = 1.0/(xa*xa); |
367 | | ps = log(xa)-0.5/xa+x2*(((((((a[7]*x2+a[6])*x2+a[5])*x2+ |
368 | | a[4])*x2+a[3])*x2+a[2])*x2+a[1])*x2+a[0]); |
369 | | ps -= s; |
370 | | } |
371 | | if (x < 0.0) |
372 | | ps = ps - M_PI*std::cos(M_PI*x)/std::sin(M_PI*x)-1.0/x; |
373 | | return ps; |
374 | | } |
375 | | |
376 | | } |
| 323 | double psi ( double x ) { |
| 324 | double s, ps, xa, x2; |
| 325 | int n, k; |
| 326 | static double a[] = { |
| 327 | -0.8333333333333e-01, |
| 328 | 0.83333333333333333e-02, |
| 329 | -0.39682539682539683e-02, |
| 330 | 0.41666666666666667e-02, |
| 331 | -0.75757575757575758e-02, |
| 332 | 0.21092796092796093e-01, |
| 333 | -0.83333333333333333e-01, |
| 334 | 0.4432598039215686 |
| 335 | }; |
| 336 | |
| 337 | xa = fabs ( x ); |
| 338 | s = 0.0; |
| 339 | if ( ( x == ( int ) x ) && ( x <= 0.0 ) ) { |
| 340 | ps = 1e308; |
| 341 | return ps; |
| 342 | } |
| 343 | if ( xa == ( int ) xa ) { |
| 344 | n = xa; |
| 345 | for ( k = 1; k < n; k++ ) { |
| 346 | s += 1.0 / k; |
| 347 | } |
| 348 | ps = s - el; |
| 349 | } else if ( ( xa + 0.5 ) == ( ( int ) ( xa + 0.5 ) ) ) { |
| 350 | n = xa - 0.5; |
| 351 | for ( k = 1; k <= n; k++ ) { |
| 352 | s += 1.0 / ( 2.0 * k - 1.0 ); |
| 353 | } |
| 354 | ps = 2.0 * s - el - 1.386294361119891; |
| 355 | } else { |
| 356 | if ( xa < 10.0 ) { |
| 357 | n = 10 - ( int ) xa; |
| 358 | for ( k = 0; k < n; k++ ) { |
| 359 | s += 1.0 / ( xa + k ); |
| 360 | } |
| 361 | xa += n; |
| 362 | } |
| 363 | x2 = 1.0 / ( xa * xa ); |
| 364 | ps = log ( xa ) - 0.5 / xa + x2 * ( ( ( ( ( ( ( a[7] * x2 + a[6] ) * x2 + a[5] ) * x2 + |
| 365 | a[4] ) * x2 + a[3] ) * x2 + a[2] ) * x2 + a[1] ) * x2 + a[0] ); |
| 366 | ps -= s; |
| 367 | } |
| 368 | if ( x < 0.0 ) |
| 369 | ps = ps - M_PI * std::cos ( M_PI * x ) / std::sin ( M_PI * x ) - 1.0 / x; |
| 370 | return ps; |
| 371 | } |
| 372 | |
| 373 | } |