Gpu batch 10 test

doc/distributions/inverse_gaussian.qbk

@@ -12,11 +12,11 @@
       typedef RealType value_type;
       typedef Policy   policy_type;
 
-      inverse_gaussian_distribution(RealType mean = 1, RealType scale = 1);
+      BOOST_MATH_GPU_ENABLED inverse_gaussian_distribution(RealType mean = 1, RealType scale = 1);
 
-      RealType mean()const; // mean default 1.
-      RealType scale()const; // Optional scale, default 1 (unscaled).
-      RealType shape()const; // Shape = scale/mean.
+      BOOST_MATH_GPU_ENABLED RealType mean()const; // mean default 1.
+      BOOST_MATH_GPU_ENABLED RealType scale()const; // Optional scale, default 1 (unscaled).
+      BOOST_MATH_GPU_ENABLED RealType shape()const; // Shape = scale/mean.
    };
    typedef inverse_gaussian_distribution<double> inverse_gaussian;
 
@@ -90,26 +90,28 @@ Another related parameterisation, the __wald_distrib (where mean [mu] is unity)
 
 [h4 Member Functions]
 
-   inverse_gaussian_distribution(RealType df = 1, RealType scale = 1); // optionally scaled.
+   BOOST_MATH_GPU_ENABLED inverse_gaussian_distribution(RealType df = 1, RealType scale = 1); // optionally scaled.
 
 Constructs an inverse_gaussian distribution with [mu] mean,
 and scale [lambda], with both default values 1.
 
 Requires that both the mean [mu] parameter and scale [lambda] are greater than zero,
 otherwise calls __domain_error.
 
-   RealType mean()const; 
+   BOOST_MATH_GPU_ENABLED RealType mean()const; 
 
 Returns the mean [mu] parameter of this distribution.
 
-   RealType scale()const; 
+   BOOST_MATH_GPU_ENABLED RealType scale()const; 
 
 Returns the scale [lambda] parameter of this distribution.
 
 [h4 Non-member Accessors]
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions] that are generic to all
 distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random variate is \[0,+[infin]).
 [note Unlike some definitions, this implementation supports a random variate 

doc/distributions/lognormal.qbk

@@ -17,10 +17,10 @@
       typedef RealType value_type;
       typedef Policy   policy_type;
       // Construct:
-      lognormal_distribution(RealType location = 0, RealType scale = 1);
+      BOOST_MATH_GPU_ENABLED lognormal_distribution(RealType location = 0, RealType scale = 1);
       // Accessors:
-      RealType location()const;
-      RealType scale()const;
+      BOOST_MATH_GPU_ENABLED RealType location()const;
+      BOOST_MATH_GPU_ENABLED RealType scale()const;
    };
 
    }} // namespaces
@@ -51,7 +51,7 @@ The next graph illustrates the effect of the scale parameter on the PDF:
 
 [h4 Member Functions]
 
-   lognormal_distribution(RealType location = 0, RealType scale = 1);
+   BOOST_MATH_GPU_ENABLED lognormal_distribution(RealType location = 0, RealType scale = 1);
 
 Constructs a lognormal distribution with location /location/ and 
 scale /scale/.
@@ -65,18 +65,20 @@ logarithm of the random variate.
 Requires that the scale parameter is greater than zero, otherwise calls
 __domain_error.
 
-   RealType location()const;
+   BOOST_MATH_GPU_ENABLED RealType location()const;
 
 Returns the /location/ parameter of this distribution.
 
-   RealType scale()const;
+   BOOST_MATH_GPU_ENABLED RealType scale()const;
 
 Returns the /scale/ parameter of this distribution.
 
 [h4 Non-member Accessors]
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions] that are generic to all
 distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random variable is \[0,+[infin]\].
 

doc/distributions/nc_beta.qbk

@@ -18,14 +18,14 @@
       typedef Policy    policy_type;
 
       // Constructor:
-      non_central_beta_distribution(RealType alpha, RealType beta, RealType lambda);
+      BOOST_MATH_GPU_ENABLED non_central_beta_distribution(RealType alpha, RealType beta, RealType lambda);
 
       // Accessor to shape parameters:
-      RealType alpha()const;
-      RealType beta()const;
+      BOOST_MATH_GPU_ENABLED RealType alpha()const;
+      BOOST_MATH_GPU_ENABLED RealType beta()const;
 
       // Accessor to non-centrality parameter lambda:
-      RealType non_centrality()const;
+      BOOST_MATH_GPU_ENABLED RealType non_centrality()const;
    };
 
    }} // namespaces
@@ -59,22 +59,22 @@ for different values of [lambda]:
 
 [h4 Member Functions]
 
-      non_central_beta_distribution(RealType a, RealType b, RealType lambda);
+      BOOST_MATH_GPU_ENABLED non_central_beta_distribution(RealType a, RealType b, RealType lambda);
 
 Constructs a noncentral beta distribution with shape parameters /a/ and /b/
 and non-centrality parameter /lambda/.
 
 Requires a > 0, b > 0 and lambda >= 0, otherwise calls __domain_error.
 
-      RealType alpha()const;
+      BOOST_MATH_GPU_ENABLED RealType alpha()const;
 
 Returns the parameter /a/ from which this object was constructed.
 
-      RealType beta()const;
+      BOOST_MATH_GPU_ENABLED RealType beta()const;
 
 Returns the parameter /b/ from which this object was constructed.
 
-      RealType non_centrality()const;
+      BOOST_MATH_GPU_ENABLED RealType non_centrality()const;
 
 Returns the parameter /lambda/ from which this object was constructed.
 
@@ -83,6 +83,8 @@ Returns the parameter /lambda/ from which this object was constructed.
 Most of the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 are supported: __cdf, __pdf, __quantile, __mean, __variance, __sd,
 __median, __mode, __hazard, __chf, __range and __support.
+For this distribution these functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 Mean and variance are implemented using hypergeometric pfq functions and relations given in
 [@http://reference.wolfram.com/mathematica/ref/NoncentralBetaDistribution.html Wolfram Noncentral Beta Distribution].

doc/distributions/nc_chi_squared.qbk

@@ -18,22 +18,22 @@
       typedef Policy    policy_type;
 
       // Constructor:
-      non_central_chi_squared_distribution(RealType v, RealType lambda);
+      BOOST_MATH_GPU_ENABLED non_central_chi_squared_distribution(RealType v, RealType lambda);
 
       // Accessor to degrees of freedom parameter v:
-      RealType degrees_of_freedom()const;
+      BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom()const;
 
       // Accessor to non centrality parameter lambda:
-      RealType non_centrality()const;
+      BOOST_MATH_GPU_ENABLED RealType non_centrality()const;
 
       // Parameter finders:
-      static RealType find_degrees_of_freedom(RealType lambda, RealType x, RealType p);
+      BOOST_MATH_GPU_ENABLED static RealType find_degrees_of_freedom(RealType lambda, RealType x, RealType p);
       template <class A, class B, class C>
-      static RealType find_degrees_of_freedom(const complemented3_type<A,B,C>& c);
+      BOOST_MATH_GPU_ENABLED static RealType find_degrees_of_freedom(const complemented3_type<A,B,C>& c);
 
-      static RealType find_non_centrality(RealType v, RealType x, RealType p);
+      BOOST_MATH_GPU_ENABLED static RealType find_non_centrality(RealType v, RealType x, RealType p);
       template <class A, class B, class C>
-      static RealType find_non_centrality(const complemented3_type<A,B,C>& c);
+      BOOST_MATH_GPU_ENABLED static RealType find_non_centrality(const complemented3_type<A,B,C>& c);
    };
 
    }} // namespaces
@@ -70,43 +70,42 @@ for different values of [lambda]:
 
 [h4 Member Functions]
 
-      non_central_chi_squared_distribution(RealType v, RealType lambda);
+      BOOST_MATH_GPU_ENABLED non_central_chi_squared_distribution(RealType v, RealType lambda);
 
 Constructs a Chi-Squared distribution with [nu] degrees of freedom
 and non-centrality parameter /lambda/.
 
 Requires [nu] > 0 and lambda >= 0, otherwise calls __domain_error.
 
-      RealType degrees_of_freedom()const;
+      BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom()const;
 
 Returns the parameter [nu] from which this object was constructed.
 
-      RealType non_centrality()const;
+      BOOST_MATH_GPU_ENABLED RealType non_centrality()const;
 
 Returns the parameter /lambda/ from which this object was constructed.
 
-
-   static RealType find_degrees_of_freedom(RealType lambda, RealType x, RealType p);
+      BOOST_MATH_GPU_ENABLED static RealType find_degrees_of_freedom(RealType lambda, RealType x, RealType p);
 
 This function returns the number of degrees of freedom [nu] such that:
 `cdf(non_central_chi_squared<RealType, Policy>(v, lambda), x) == p`
 
-   template <class A, class B, class C>
-   static RealType find_degrees_of_freedom(const complemented3_type<A,B,C>& c);
+      template <class A, class B, class C>
+      BOOST_MATH_GPU_ENABLED static RealType find_degrees_of_freedom(const complemented3_type<A,B,C>& c);
 
 When called with argument `boost::math::complement(lambda, x, q)`
 this function returns the number of degrees of freedom [nu] such that:
 
 `cdf(complement(non_central_chi_squared<RealType, Policy>(v, lambda), x)) == q`.
 
-   static RealType find_non_centrality(RealType v, RealType x, RealType p);
+      BOOST_MATH_GPU_ENABLED static RealType find_non_centrality(RealType v, RealType x, RealType p);
 
 This function returns the non centrality parameter /lambda/ such that:
 
 `cdf(non_central_chi_squared<RealType, Policy>(v, lambda), x) == p`
 
-   template <class A, class B, class C>
-   static RealType find_non_centrality(const complemented3_type<A,B,C>& c);
+      template <class A, class B, class C>
+      BOOST_MATH_GPU_ENABLED static RealType find_non_centrality(const complemented3_type<A,B,C>& c);
 
 When called with argument `boost::math::complement(v, x, q)`
 this function returns the non centrality parameter /lambda/ such that:
@@ -117,6 +116,8 @@ this function returns the non centrality parameter /lambda/ such that:
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 that are generic to all distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random variable is \[0, +[infin]\].
 

doc/distributions/nc_f.qbk

@@ -18,14 +18,14 @@
       typedef Policy    policy_type;
 
       // Constructor:
-      non_central_f_distribution(RealType v1, RealType v2, RealType lambda);
+      BOOST_MATH_GPU_ENABLED non_central_f_distribution(RealType v1, RealType v2, RealType lambda);
 
       // Accessor to degrees_of_freedom parameters v1 & v2:
-      RealType degrees_of_freedom1()const;
-      RealType degrees_of_freedom2()const;
+      BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom1()const;
+      BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom2()const;
 
       // Accessor to non-centrality parameter lambda:
-      RealType non_centrality()const;
+      BOOST_MATH_GPU_ENABLED RealType non_centrality()const;
    };
 
    }} // namespaces
@@ -55,29 +55,31 @@ for different values of [lambda]:
 
 [h4 Member Functions]
 
-      non_central_f_distribution(RealType v1, RealType v2, RealType lambda);
+      BOOST_MATH_GPU_ENABLED non_central_f_distribution(RealType v1, RealType v2, RealType lambda);
 
 Constructs a non-central beta distribution with parameters /v1/ and /v2/
 and non-centrality parameter /lambda/.
 
 Requires /v1/ > 0, /v2/ > 0 and lambda >= 0, otherwise calls __domain_error.
 
-      RealType degrees_of_freedom1()const;
+      BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom1()const;
 
 Returns the parameter /v1/ from which this object was constructed.
 
-      RealType degrees_of_freedom2()const;
+      BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom2()const;
 
 Returns the parameter /v2/ from which this object was constructed.
 
-      RealType non_centrality()const;
+      BOOST_MATH_GPU_ENABLED RealType non_centrality()const;
 
 Returns the non-centrality parameter /lambda/ from which this object was constructed.
 
 [h4 Non-member Accessors]
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 that are generic to all distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random variable is \[0, +[infin]\].
 

doc/distributions/negative_binomial.qbk

@@ -17,28 +17,28 @@
       typedef RealType value_type;
       typedef Policy   policy_type;
       // Constructor from successes and success_fraction:
-      negative_binomial_distribution(RealType r, RealType p);
+      BOOST_MATH_GPU_ENABLED negative_binomial_distribution(RealType r, RealType p);
 
       // Parameter accessors:
-      RealType success_fraction() const;
-      RealType successes() const;
+      BOOST_MATH_GPU_ENABLED RealType success_fraction() const;
+      BOOST_MATH_GPU_ENABLED RealType successes() const;
 
       // Bounds on success fraction:
-      static RealType find_lower_bound_on_p(
+      BOOST_MATH_GPU_ENABLED static RealType find_lower_bound_on_p(
          RealType trials,
          RealType successes,
          RealType probability); // alpha
-      static RealType find_upper_bound_on_p(
+      BOOST_MATH_GPU_ENABLED static RealType find_upper_bound_on_p(
          RealType trials,
          RealType successes,
          RealType probability); // alpha
 
       // Estimate min/max number of trials:
-      static RealType find_minimum_number_of_trials(
+      BOOST_MATH_GPU_ENABLED static RealType find_minimum_number_of_trials(
          RealType k,     // Number of failures.
          RealType p,     // Success fraction.
          RealType probability); // Probability threshold alpha.
-      static RealType find_maximum_number_of_trials(
+      BOOST_MATH_GPU_ENABLED static RealType find_maximum_number_of_trials(
          RealType k,     // Number of failures.
          RealType p,     // Success fraction.
          RealType probability); // Probability threshold alpha.
@@ -112,7 +112,7 @@ poisson([lambda]) = lim [sub r [rarr] [infin]] negative_binomial(r, r / ([lambda
 
 [h5 Construct]
 
-   negative_binomial_distribution(RealType r, RealType p);
+   BOOST_MATH_GPU_ENABLED negative_binomial_distribution(RealType r, RealType p);
 
 Constructor: /r/ is the total number of successes, /p/ is the
 probability of success of a single trial.
@@ -121,11 +121,11 @@ Requires: `r > 0` and `0 <= p <= 1`.
 
 [h5 Accessors]
 
-   RealType success_fraction() const; // successes / trials (0 <= p <= 1)
+   BOOST_MATH_GPU_ENABLED RealType success_fraction() const; // successes / trials (0 <= p <= 1)
 
 Returns the parameter /p/ from which this distribution was constructed.
 
-   RealType successes() const; // required successes (r > 0)
+   BOOST_MATH_GPU_ENABLED RealType successes() const; // required successes (r > 0)
 
 Returns the parameter /r/ from which this distribution was constructed.
 
@@ -134,7 +134,7 @@ see __binomial_distrib for more discussion.
 
 [h5 Lower Bound on Parameter p]
 
-      static RealType find_lower_bound_on_p(
+      BOOST_MATH_GPU_ENABLED static RealType find_lower_bound_on_p(
         RealType failures,
         RealType successes,
         RealType probability) // (0 <= alpha <= 1), 0.05 equivalent to 95% confidence.
@@ -170,7 +170,7 @@ Computational statistics and data analysis, 2005, vol. 48, no3, 605-621].
 
 [h5 Upper Bound on Parameter p]
 
-   static RealType find_upper_bound_on_p(
+   BOOST_MATH_GPU_ENABLED static RealType find_upper_bound_on_p(
       RealType trials,
       RealType successes,
       RealType alpha); // (0 <= alpha <= 1), 0.05 equivalent to 95% confidence.
@@ -206,7 +206,7 @@ Computational statistics and data analysis, 2005, vol. 48, no3, 605-621].
 
 [h5 Estimating Number of Trials to Ensure at Least a Certain Number of Failures]
 
-   static RealType find_minimum_number_of_trials(
+   BOOST_MATH_GPU_ENABLED static RealType find_minimum_number_of_trials(
       RealType k,     // number of failures.
       RealType p,     // success fraction.
       RealType alpha); // probability threshold (0.05 equivalent to 95%).
@@ -236,7 +236,7 @@ of observing k failures or fewer.
 
 [h5 Estimating Number of Trials to Ensure a Maximum Number of Failures or Less]
 
-   static RealType find_maximum_number_of_trials(
+   BOOST_MATH_GPU_ENABLED static RealType find_maximum_number_of_trials(
       RealType k,     // number of failures.
       RealType p,     // success fraction.
       RealType alpha); // probability threshold (0.05 equivalent to 95%).
@@ -266,6 +266,8 @@ of observing more than k failures.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 that are generic to all distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 However it's worth taking a moment to define what these actually mean in
 the context of this distribution: