1 | // (C) Copyright John Maddock 2006. |
2 | // Use, modification and distribution are subject to the |
3 | // Boost Software License, Version 1.0. (See accompanying file |
4 | // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) |
5 | |
6 | #ifndef BOOST_MATH_SF_ERF_INV_HPP |
7 | #define BOOST_MATH_SF_ERF_INV_HPP |
8 | |
9 | #ifdef _MSC_VER |
10 | #pragma once |
11 | #pragma warning(push) |
12 | #pragma warning(disable:4127) // Conditional expression is constant |
13 | #pragma warning(disable:4702) // Unreachable code: optimization warning |
14 | #endif |
15 | |
16 | namespace boost{ namespace math{ |
17 | |
18 | namespace detail{ |
19 | // |
20 | // The inverse erf and erfc functions share a common implementation, |
21 | // this version is for 80-bit long double's and smaller: |
22 | // |
23 | template <class T, class Policy> |
24 | T erf_inv_imp(const T& p, const T& q, const Policy&, const boost::integral_constant<int, 64>*) |
25 | { |
26 | BOOST_MATH_STD_USING // for ADL of std names. |
27 | |
28 | T result = 0; |
29 | |
30 | if(p <= 0.5) |
31 | { |
32 | // |
33 | // Evaluate inverse erf using the rational approximation: |
34 | // |
35 | // x = p(p+10)(Y+R(p)) |
36 | // |
37 | // Where Y is a constant, and R(p) is optimised for a low |
38 | // absolute error compared to |Y|. |
39 | // |
40 | // double: Max error found: 2.001849e-18 |
41 | // long double: Max error found: 1.017064e-20 |
42 | // Maximum Deviation Found (actual error term at infinite precision) 8.030e-21 |
43 | // |
44 | static const float Y = 0.0891314744949340820313f; |
45 | static const T P[] = { |
46 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.000508781949658280665617), |
47 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.00836874819741736770379), |
48 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.0334806625409744615033), |
49 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.0126926147662974029034), |
50 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.0365637971411762664006), |
51 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.0219878681111168899165), |
52 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.00822687874676915743155), |
53 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.00538772965071242932965) |
54 | }; |
55 | static const T Q[] = { |
56 | BOOST_MATH_BIG_CONSTANT(T, 64, 1.0), |
57 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.970005043303290640362), |
58 | BOOST_MATH_BIG_CONSTANT(T, 64, -1.56574558234175846809), |
59 | BOOST_MATH_BIG_CONSTANT(T, 64, 1.56221558398423026363), |
60 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.662328840472002992063), |
61 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.71228902341542847553), |
62 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.0527396382340099713954), |
63 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.0795283687341571680018), |
64 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.00233393759374190016776), |
65 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.000886216390456424707504) |
66 | }; |
67 | T g = p * (p + 10); |
68 | T r = tools::evaluate_polynomial(P, p) / tools::evaluate_polynomial(Q, p); |
69 | result = g * Y + g * r; |
70 | } |
71 | else if(q >= 0.25) |
72 | { |
73 | // |
74 | // Rational approximation for 0.5 > q >= 0.25 |
75 | // |
76 | // x = sqrt(-2*log(q)) / (Y + R(q)) |
77 | // |
78 | // Where Y is a constant, and R(q) is optimised for a low |
79 | // absolute error compared to Y. |
80 | // |
81 | // double : Max error found: 7.403372e-17 |
82 | // long double : Max error found: 6.084616e-20 |
83 | // Maximum Deviation Found (error term) 4.811e-20 |
84 | // |
85 | static const float Y = 2.249481201171875f; |
86 | static const T P[] = { |
87 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.202433508355938759655), |
88 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.105264680699391713268), |
89 | BOOST_MATH_BIG_CONSTANT(T, 64, 8.37050328343119927838), |
90 | BOOST_MATH_BIG_CONSTANT(T, 64, 17.6447298408374015486), |
91 | BOOST_MATH_BIG_CONSTANT(T, 64, -18.8510648058714251895), |
92 | BOOST_MATH_BIG_CONSTANT(T, 64, -44.6382324441786960818), |
93 | BOOST_MATH_BIG_CONSTANT(T, 64, 17.445385985570866523), |
94 | BOOST_MATH_BIG_CONSTANT(T, 64, 21.1294655448340526258), |
95 | BOOST_MATH_BIG_CONSTANT(T, 64, -3.67192254707729348546) |
96 | }; |
97 | static const T Q[] = { |
98 | BOOST_MATH_BIG_CONSTANT(T, 64, 1.0), |
99 | BOOST_MATH_BIG_CONSTANT(T, 64, 6.24264124854247537712), |
100 | BOOST_MATH_BIG_CONSTANT(T, 64, 3.9713437953343869095), |
101 | BOOST_MATH_BIG_CONSTANT(T, 64, -28.6608180499800029974), |
102 | BOOST_MATH_BIG_CONSTANT(T, 64, -20.1432634680485188801), |
103 | BOOST_MATH_BIG_CONSTANT(T, 64, 48.5609213108739935468), |
104 | BOOST_MATH_BIG_CONSTANT(T, 64, 10.8268667355460159008), |
105 | BOOST_MATH_BIG_CONSTANT(T, 64, -22.6436933413139721736), |
106 | BOOST_MATH_BIG_CONSTANT(T, 64, 1.72114765761200282724) |
107 | }; |
108 | T g = sqrt(-2 * log(q)); |
109 | T xs = q - 0.25f; |
110 | T r = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs); |
111 | result = g / (Y + r); |
112 | } |
113 | else |
114 | { |
115 | // |
116 | // For q < 0.25 we have a series of rational approximations all |
117 | // of the general form: |
118 | // |
119 | // let: x = sqrt(-log(q)) |
120 | // |
121 | // Then the result is given by: |
122 | // |
123 | // x(Y+R(x-B)) |
124 | // |
125 | // where Y is a constant, B is the lowest value of x for which |
126 | // the approximation is valid, and R(x-B) is optimised for a low |
127 | // absolute error compared to Y. |
128 | // |
129 | // Note that almost all code will really go through the first |
130 | // or maybe second approximation. After than we're dealing with very |
131 | // small input values indeed: 80 and 128 bit long double's go all the |
132 | // way down to ~ 1e-5000 so the "tail" is rather long... |
133 | // |
134 | T x = sqrt(-log(q)); |
135 | if(x < 3) |
136 | { |
137 | // Max error found: 1.089051e-20 |
138 | static const float Y = 0.807220458984375f; |
139 | static const T P[] = { |
140 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.131102781679951906451), |
141 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.163794047193317060787), |
142 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.117030156341995252019), |
143 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.387079738972604337464), |
144 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.337785538912035898924), |
145 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.142869534408157156766), |
146 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.0290157910005329060432), |
147 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.00214558995388805277169), |
148 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.679465575181126350155e-6), |
149 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.285225331782217055858e-7), |
150 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.681149956853776992068e-9) |
151 | }; |
152 | static const T Q[] = { |
153 | BOOST_MATH_BIG_CONSTANT(T, 64, 1.0), |
154 | BOOST_MATH_BIG_CONSTANT(T, 64, 3.46625407242567245975), |
155 | BOOST_MATH_BIG_CONSTANT(T, 64, 5.38168345707006855425), |
156 | BOOST_MATH_BIG_CONSTANT(T, 64, 4.77846592945843778382), |
157 | BOOST_MATH_BIG_CONSTANT(T, 64, 2.59301921623620271374), |
158 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.848854343457902036425), |
159 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.152264338295331783612), |
160 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.01105924229346489121) |
161 | }; |
162 | T xs = x - 1.125f; |
163 | T R = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs); |
164 | result = Y * x + R * x; |
165 | } |
166 | else if(x < 6) |
167 | { |
168 | // Max error found: 8.389174e-21 |
169 | static const float Y = 0.93995571136474609375f; |
170 | static const T P[] = { |
171 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.0350353787183177984712), |
172 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.00222426529213447927281), |
173 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.0185573306514231072324), |
174 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.00950804701325919603619), |
175 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.00187123492819559223345), |
176 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.000157544617424960554631), |
177 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.460469890584317994083e-5), |
178 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.230404776911882601748e-9), |
179 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.266339227425782031962e-11) |
180 | }; |
181 | static const T Q[] = { |
182 | BOOST_MATH_BIG_CONSTANT(T, 64, 1.0), |
183 | BOOST_MATH_BIG_CONSTANT(T, 64, 1.3653349817554063097), |
184 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.762059164553623404043), |
185 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.220091105764131249824), |
186 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.0341589143670947727934), |
187 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.00263861676657015992959), |
188 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.764675292302794483503e-4) |
189 | }; |
190 | T xs = x - 3; |
191 | T R = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs); |
192 | result = Y * x + R * x; |
193 | } |
194 | else if(x < 18) |
195 | { |
196 | // Max error found: 1.481312e-19 |
197 | static const float Y = 0.98362827301025390625f; |
198 | static const T P[] = { |
199 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.0167431005076633737133), |
200 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.00112951438745580278863), |
201 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.00105628862152492910091), |
202 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.000209386317487588078668), |
203 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.149624783758342370182e-4), |
204 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.449696789927706453732e-6), |
205 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.462596163522878599135e-8), |
206 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.281128735628831791805e-13), |
207 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.99055709973310326855e-16) |
208 | }; |
209 | static const T Q[] = { |
210 | BOOST_MATH_BIG_CONSTANT(T, 64, 1.0), |
211 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.591429344886417493481), |
212 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.138151865749083321638), |
213 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.0160746087093676504695), |
214 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.000964011807005165528527), |
215 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.275335474764726041141e-4), |
216 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.282243172016108031869e-6) |
217 | }; |
218 | T xs = x - 6; |
219 | T R = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs); |
220 | result = Y * x + R * x; |
221 | } |
222 | else if(x < 44) |
223 | { |
224 | // Max error found: 5.697761e-20 |
225 | static const float Y = 0.99714565277099609375f; |
226 | static const T P[] = { |
227 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.0024978212791898131227), |
228 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.779190719229053954292e-5), |
229 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.254723037413027451751e-4), |
230 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.162397777342510920873e-5), |
231 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.396341011304801168516e-7), |
232 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.411632831190944208473e-9), |
233 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.145596286718675035587e-11), |
234 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.116765012397184275695e-17) |
235 | }; |
236 | static const T Q[] = { |
237 | BOOST_MATH_BIG_CONSTANT(T, 64, 1.0), |
238 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.207123112214422517181), |
239 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.0169410838120975906478), |
240 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.000690538265622684595676), |
241 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.145007359818232637924e-4), |
242 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.144437756628144157666e-6), |
243 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.509761276599778486139e-9) |
244 | }; |
245 | T xs = x - 18; |
246 | T R = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs); |
247 | result = Y * x + R * x; |
248 | } |
249 | else |
250 | { |
251 | // Max error found: 1.279746e-20 |
252 | static const float Y = 0.99941349029541015625f; |
253 | static const T P[] = { |
254 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.000539042911019078575891), |
255 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.28398759004727721098e-6), |
256 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.899465114892291446442e-6), |
257 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.229345859265920864296e-7), |
258 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.225561444863500149219e-9), |
259 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.947846627503022684216e-12), |
260 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.135880130108924861008e-14), |
261 | BOOST_MATH_BIG_CONSTANT(T, 64, -0.348890393399948882918e-21) |
262 | }; |
263 | static const T Q[] = { |
264 | BOOST_MATH_BIG_CONSTANT(T, 64, 1.0), |
265 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.0845746234001899436914), |
266 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.00282092984726264681981), |
267 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.468292921940894236786e-4), |
268 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.399968812193862100054e-6), |
269 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.161809290887904476097e-8), |
270 | BOOST_MATH_BIG_CONSTANT(T, 64, 0.231558608310259605225e-11) |
271 | }; |
272 | T xs = x - 44; |
273 | T R = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs); |
274 | result = Y * x + R * x; |
275 | } |
276 | } |
277 | return result; |
278 | } |
279 | |
280 | template <class T, class Policy> |
281 | struct erf_roots |
282 | { |
283 | boost::math::tuple<T,T,T> operator()(const T& guess) |
284 | { |
285 | BOOST_MATH_STD_USING |
286 | T derivative = sign * (2 / sqrt(constants::pi<T>())) * exp(-(guess * guess)); |
287 | T derivative2 = -2 * guess * derivative; |
288 | return boost::math::make_tuple(((sign > 0) ? static_cast<T>(boost::math::erf(guess, Policy()) - target) : static_cast<T>(boost::math::erfc(guess, Policy())) - target), derivative, derivative2); |
289 | } |
290 | erf_roots(T z, int s) : target(z), sign(s) {} |
291 | private: |
292 | T target; |
293 | int sign; |
294 | }; |
295 | |
296 | template <class T, class Policy> |
297 | T erf_inv_imp(const T& p, const T& q, const Policy& pol, const boost::integral_constant<int, 0>*) |
298 | { |
299 | // |
300 | // Generic version, get a guess that's accurate to 64-bits (10^-19) |
301 | // |
302 | T guess = erf_inv_imp(p, q, pol, static_cast<boost::integral_constant<int, 64> const*>(0)); |
303 | T result; |
304 | // |
305 | // If T has more bit's than 64 in it's mantissa then we need to iterate, |
306 | // otherwise we can just return the result: |
307 | // |
308 | if(policies::digits<T, Policy>() > 64) |
309 | { |
310 | boost::uintmax_t max_iter = policies::get_max_root_iterations<Policy>(); |
311 | if(p <= 0.5) |
312 | { |
313 | result = tools::halley_iterate(detail::erf_roots<typename remove_cv<T>::type, Policy>(p, 1), guess, static_cast<T>(0), tools::max_value<T>(), (policies::digits<T, Policy>() * 2) / 3, max_iter); |
314 | } |
315 | else |
316 | { |
317 | result = tools::halley_iterate(detail::erf_roots<typename remove_cv<T>::type, Policy>(q, -1), guess, static_cast<T>(0), tools::max_value<T>(), (policies::digits<T, Policy>() * 2) / 3, max_iter); |
318 | } |
319 | policies::check_root_iterations<T>("boost::math::erf_inv<%1%>" , max_iter, pol); |
320 | } |
321 | else |
322 | { |
323 | result = guess; |
324 | } |
325 | return result; |
326 | } |
327 | |
328 | template <class T, class Policy> |
329 | struct erf_inv_initializer |
330 | { |
331 | struct init |
332 | { |
333 | init() |
334 | { |
335 | do_init(); |
336 | } |
337 | static bool is_value_non_zero(T); |
338 | static void do_init() |
339 | { |
340 | // If std::numeric_limits<T>::digits is zero, we must not call |
341 | // our initialization code here as the precision presumably |
342 | // varies at runtime, and will not have been set yet. |
343 | if(std::numeric_limits<T>::digits) |
344 | { |
345 | boost::math::erf_inv(static_cast<T>(0.25), Policy()); |
346 | boost::math::erf_inv(static_cast<T>(0.55), Policy()); |
347 | boost::math::erf_inv(static_cast<T>(0.95), Policy()); |
348 | boost::math::erfc_inv(static_cast<T>(1e-15), Policy()); |
349 | // These following initializations must not be called if |
350 | // type T can not hold the relevant values without |
351 | // underflow to zero. We check this at runtime because |
352 | // some tools such as valgrind silently change the precision |
353 | // of T at runtime, and numeric_limits basically lies! |
354 | if(is_value_non_zero(static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1e-130)))) |
355 | boost::math::erfc_inv(static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1e-130)), Policy()); |
356 | |
357 | // Some compilers choke on constants that would underflow, even in code that isn't instantiated |
358 | // so try and filter these cases out in the preprocessor: |
359 | #if LDBL_MAX_10_EXP >= 800 |
360 | if(is_value_non_zero(static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1e-800)))) |
361 | boost::math::erfc_inv(static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1e-800)), Policy()); |
362 | if(is_value_non_zero(static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1e-900)))) |
363 | boost::math::erfc_inv(static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1e-900)), Policy()); |
364 | #else |
365 | if(is_value_non_zero(static_cast<T>(BOOST_MATH_HUGE_CONSTANT(T, 64, 1e-800)))) |
366 | boost::math::erfc_inv(static_cast<T>(BOOST_MATH_HUGE_CONSTANT(T, 64, 1e-800)), Policy()); |
367 | if(is_value_non_zero(static_cast<T>(BOOST_MATH_HUGE_CONSTANT(T, 64, 1e-900)))) |
368 | boost::math::erfc_inv(static_cast<T>(BOOST_MATH_HUGE_CONSTANT(T, 64, 1e-900)), Policy()); |
369 | #endif |
370 | } |
371 | } |
372 | void force_instantiate()const{} |
373 | }; |
374 | static const init initializer; |
375 | static void force_instantiate() |
376 | { |
377 | initializer.force_instantiate(); |
378 | } |
379 | }; |
380 | |
381 | template <class T, class Policy> |
382 | const typename erf_inv_initializer<T, Policy>::init erf_inv_initializer<T, Policy>::initializer; |
383 | |
384 | template <class T, class Policy> |
385 | bool erf_inv_initializer<T, Policy>::init::is_value_non_zero(T v) |
386 | { |
387 | // This needs to be non-inline to detect whether v is non zero at runtime |
388 | // rather than at compile time, only relevant when running under valgrind |
389 | // which changes long double's to double's on the fly. |
390 | return v != 0; |
391 | } |
392 | |
393 | } // namespace detail |
394 | |
395 | template <class T, class Policy> |
396 | typename tools::promote_args<T>::type erfc_inv(T z, const Policy& pol) |
397 | { |
398 | typedef typename tools::promote_args<T>::type result_type; |
399 | |
400 | // |
401 | // Begin by testing for domain errors, and other special cases: |
402 | // |
403 | static const char* function = "boost::math::erfc_inv<%1%>(%1%, %1%)" ; |
404 | if((z < 0) || (z > 2)) |
405 | return policies::raise_domain_error<result_type>(function, "Argument outside range [0,2] in inverse erfc function (got p=%1%)." , z, pol); |
406 | if(z == 0) |
407 | return policies::raise_overflow_error<result_type>(function, 0, pol); |
408 | if(z == 2) |
409 | return -policies::raise_overflow_error<result_type>(function, 0, pol); |
410 | // |
411 | // Normalise the input, so it's in the range [0,1], we will |
412 | // negate the result if z is outside that range. This is a simple |
413 | // application of the erfc reflection formula: erfc(-z) = 2 - erfc(z) |
414 | // |
415 | result_type p, q, s; |
416 | if(z > 1) |
417 | { |
418 | q = 2 - z; |
419 | p = 1 - q; |
420 | s = -1; |
421 | } |
422 | else |
423 | { |
424 | p = 1 - z; |
425 | q = z; |
426 | s = 1; |
427 | } |
428 | // |
429 | // A bit of meta-programming to figure out which implementation |
430 | // to use, based on the number of bits in the mantissa of T: |
431 | // |
432 | typedef typename policies::precision<result_type, Policy>::type precision_type; |
433 | typedef boost::integral_constant<int, |
434 | precision_type::value <= 0 ? 0 : |
435 | precision_type::value <= 64 ? 64 : 0 |
436 | > tag_type; |
437 | // |
438 | // Likewise use internal promotion, so we evaluate at a higher |
439 | // precision internally if it's appropriate: |
440 | // |
441 | typedef typename policies::evaluation<result_type, Policy>::type eval_type; |
442 | typedef typename policies::normalise< |
443 | Policy, |
444 | policies::promote_float<false>, |
445 | policies::promote_double<false>, |
446 | policies::discrete_quantile<>, |
447 | policies::assert_undefined<> >::type forwarding_policy; |
448 | |
449 | detail::erf_inv_initializer<eval_type, forwarding_policy>::force_instantiate(); |
450 | |
451 | // |
452 | // And get the result, negating where required: |
453 | // |
454 | return s * policies::checked_narrowing_cast<result_type, forwarding_policy>( |
455 | detail::erf_inv_imp(static_cast<eval_type>(p), static_cast<eval_type>(q), forwarding_policy(), static_cast<tag_type const*>(0)), function); |
456 | } |
457 | |
458 | template <class T, class Policy> |
459 | typename tools::promote_args<T>::type erf_inv(T z, const Policy& pol) |
460 | { |
461 | typedef typename tools::promote_args<T>::type result_type; |
462 | |
463 | // |
464 | // Begin by testing for domain errors, and other special cases: |
465 | // |
466 | static const char* function = "boost::math::erf_inv<%1%>(%1%, %1%)" ; |
467 | if((z < -1) || (z > 1)) |
468 | return policies::raise_domain_error<result_type>(function, "Argument outside range [-1, 1] in inverse erf function (got p=%1%)." , z, pol); |
469 | if(z == 1) |
470 | return policies::raise_overflow_error<result_type>(function, 0, pol); |
471 | if(z == -1) |
472 | return -policies::raise_overflow_error<result_type>(function, 0, pol); |
473 | if(z == 0) |
474 | return 0; |
475 | // |
476 | // Normalise the input, so it's in the range [0,1], we will |
477 | // negate the result if z is outside that range. This is a simple |
478 | // application of the erf reflection formula: erf(-z) = -erf(z) |
479 | // |
480 | result_type p, q, s; |
481 | if(z < 0) |
482 | { |
483 | p = -z; |
484 | q = 1 - p; |
485 | s = -1; |
486 | } |
487 | else |
488 | { |
489 | p = z; |
490 | q = 1 - z; |
491 | s = 1; |
492 | } |
493 | // |
494 | // A bit of meta-programming to figure out which implementation |
495 | // to use, based on the number of bits in the mantissa of T: |
496 | // |
497 | typedef typename policies::precision<result_type, Policy>::type precision_type; |
498 | typedef boost::integral_constant<int, |
499 | precision_type::value <= 0 ? 0 : |
500 | precision_type::value <= 64 ? 64 : 0 |
501 | > tag_type; |
502 | // |
503 | // Likewise use internal promotion, so we evaluate at a higher |
504 | // precision internally if it's appropriate: |
505 | // |
506 | typedef typename policies::evaluation<result_type, Policy>::type eval_type; |
507 | typedef typename policies::normalise< |
508 | Policy, |
509 | policies::promote_float<false>, |
510 | policies::promote_double<false>, |
511 | policies::discrete_quantile<>, |
512 | policies::assert_undefined<> >::type forwarding_policy; |
513 | // |
514 | // Likewise use internal promotion, so we evaluate at a higher |
515 | // precision internally if it's appropriate: |
516 | // |
517 | typedef typename policies::evaluation<result_type, Policy>::type eval_type; |
518 | |
519 | detail::erf_inv_initializer<eval_type, forwarding_policy>::force_instantiate(); |
520 | // |
521 | // And get the result, negating where required: |
522 | // |
523 | return s * policies::checked_narrowing_cast<result_type, forwarding_policy>( |
524 | detail::erf_inv_imp(static_cast<eval_type>(p), static_cast<eval_type>(q), forwarding_policy(), static_cast<tag_type const*>(0)), function); |
525 | } |
526 | |
527 | template <class T> |
528 | inline typename tools::promote_args<T>::type erfc_inv(T z) |
529 | { |
530 | return erfc_inv(z, policies::policy<>()); |
531 | } |
532 | |
533 | template <class T> |
534 | inline typename tools::promote_args<T>::type erf_inv(T z) |
535 | { |
536 | return erf_inv(z, policies::policy<>()); |
537 | } |
538 | |
539 | } // namespace math |
540 | } // namespace boost |
541 | |
542 | #ifdef _MSC_VER |
543 | #pragma warning(pop) |
544 | #endif |
545 | |
546 | #endif // BOOST_MATH_SF_ERF_INV_HPP |
547 | |
548 | |