remove scalar alpha sigs

Author: adamhaber

src/middle/Stan_math_signatures.ml

@@ -961,21 +961,11 @@ let () =
     , ReturnType UReal
     , [UArray UInt; URowVector; UVector; UVector]
     , AoS ) ;
-  add_unqualified
-    ( "bernoulli_logit_glm_rng"
-    , ReturnType (UArray UInt)
-    , [UMatrix; UReal; UVector]
-    , AoS ) ;
   add_unqualified
     ( "bernoulli_logit_glm_rng"
     , ReturnType (UArray UInt)
     , [UMatrix; UVector; UVector]
     , AoS ) ;
-  add_unqualified
-    ( "bernoulli_logit_glm_rng"
-    , ReturnType (UArray UInt)
-    , [URowVector; UReal; UVector]
-    , AoS ) ;
   add_unqualified
     ( "bernoulli_logit_glm_rng"
     , ReturnType (UArray UInt)

test/integration/good/function-signatures/distributions/pretty.expected

@@ -30,7 +30,6 @@ generated quantities {
   matrix[2, 3] d_x_m = [[1, 2, 3], [4, 5, 6]];
   row_vector[3] d_x_rv = [1, 2, 3];
   vector[3] d_beta_v = [1, 2, 3]';
-  real d_alpha = 3;
   vector[2] d_alpha_v = [0.5, 0.6]';
   n = bernoulli_logit_rng(0.0);
   N = bernoulli_logit_rng(alpha);
@@ -1734,9 +1733,7 @@ generated quantities {
   N = discrete_range_rng(n, N);
   N = discrete_range_rng(N, n);
   N = discrete_range_rng(N, N);
-  N = bernoulli_logit_glm_rng(d_x_m, d_alpha, d_beta_v);
   N = bernoulli_logit_glm_rng(d_x_m, d_alpha_v, d_beta_v);
-  N = bernoulli_logit_glm_rng(d_x_rv, d_alpha, d_beta_v);
   N = bernoulli_logit_glm_rng(d_x_rv, d_alpha_v, d_beta_v);
 }
 

test/integration/good/function-signatures/distributions/rngs.stan

@@ -29,7 +29,6 @@ generated quantities {
   matrix[2, 3] d_x_m = [[1, 2, 3], [4, 5, 6]];
   row_vector[3] d_x_rv = [1, 2, 3];
   vector[3] d_beta_v = [1, 2, 3]';
-  real d_alpha = 3;
   vector[2] d_alpha_v = [0.5, 0.6]';
   n = bernoulli_logit_rng(0.0);
   N = bernoulli_logit_rng(alpha);
@@ -1733,10 +1732,7 @@ generated quantities {
   N = discrete_range_rng(n, N);
   N = discrete_range_rng(N, n);
   N = discrete_range_rng(N, N);
-  N = bernoulli_logit_glm_rng(d_x_m, d_alpha, d_beta_v);
   N = bernoulli_logit_glm_rng(d_x_m, d_alpha_v, d_beta_v);
-  N = bernoulli_logit_glm_rng(d_x_rv, d_alpha, d_beta_v);
   N = bernoulli_logit_glm_rng(d_x_rv, d_alpha_v, d_beta_v);
-
 }
 

test/integration/signatures/stan_math_sigs.expected

@@ -463,9 +463,7 @@ bernoulli_logit_glm_lpmf(array[] int, row_vector, real, vector) => real
 bernoulli_logit_glm_lpmf(array[] int, row_vector, vector, vector) => real
 bernoulli_logit_glm_lpmf(array[] int, matrix, real, vector) => real
 bernoulli_logit_glm_lpmf(array[] int, matrix, vector, vector) => real
-bernoulli_logit_glm_rng(row_vector, real, vector) => array[] int
 bernoulli_logit_glm_rng(row_vector, vector, vector) => array[] int
-bernoulli_logit_glm_rng(matrix, real, vector) => array[] int
 bernoulli_logit_glm_rng(matrix, vector, vector) => array[] int
 bernoulli_logit_log(int, real) => real
 bernoulli_logit_log(int, vector) => real