refactor: fix Lapack function selection by array type

lib/numo/tiny_linalg.rb

@@ -279,22 +279,20 @@ def qr(a, mode: 'reduce')
     #   pp (b - a.dot(x)).abs.max
     #   # => 2.1081041547796492e-16
     #
-    # @param a [Numo::NArray] The n-by-n square matrix  (>= 2-dimensinal NArray).
+    # @param a [Numo::NArray] The n-by-n square matrix.
     # @param b [Numo::NArray] The n right-hand side vector, or n-by-nrhs right-hand side matrix (>= 1-dimensinal NArray).
     # @param driver [String] This argument is for compatibility with Numo::Linalg.solver, and is not used.
     # @param uplo [String] This argument is for compatibility with Numo::Linalg.solver, and is not used.
     # @return [Numo::NArray] The solusion vector / matrix `x`.
     def solve(a, b, driver: 'gen', uplo: 'U') # rubocop:disable Lint/UnusedMethodArgument
-      case blas_char(a, b)
-      when 'd'
-        Lapack.dgesv(a.dup, b.dup)[1]
-      when 's'
-        Lapack.sgesv(a.dup, b.dup)[1]
-      when 'z'
-        Lapack.zgesv(a.dup, b.dup)[1]
-      when 'c'
-        Lapack.cgesv(a.dup, b.dup)[1]
-      end
+      raise ArgumentError, 'input array a must be 2-dimensional' if a.ndim != 2
+      raise ArgumentError, 'input array a must be square' if a.shape[0] != a.shape[1]
+
+      bchr = blas_char(a, b)
+      raise ArgumentError, "invalid array type: #{a.class}, #{b.class}" if bchr == 'n'
+
+      gesv = "#{bchr}gesv".to_sym
+      Numo::TinyLinalg::Lapack.send(gesv, a.dup, b.dup)[1]
     end
 
     # Calculates the Singular Value Decomposition (SVD) of a matrix: `A = U * S * V^T`
@@ -336,33 +334,16 @@ def solve(a, b, driver: 'gen', uplo: 'U') # rubocop:disable Lint/UnusedMethodArg
     def svd(a, driver: 'svd', job: 'A')
       raise ArgumentError, "invalid job: #{job}" unless /^[ASN]/i.match?(job.to_s)
 
+      bchr = blas_char(a)
+      raise ArgumentError, "invalid array type: #{a.class}" if bchr == 'n'
+
       case driver.to_s
       when 'sdd'
-        s, u, vt, info = case a
-                         when Numo::DFloat
-                           Numo::TinyLinalg::Lapack.dgesdd(a.dup, jobz: job)
-                         when Numo::SFloat
-                           Numo::TinyLinalg::Lapack.sgesdd(a.dup, jobz: job)
-                         when Numo::DComplex
-                           Numo::TinyLinalg::Lapack.zgesdd(a.dup, jobz: job)
-                         when Numo::SComplex
-                           Numo::TinyLinalg::Lapack.cgesdd(a.dup, jobz: job)
-                         else
-                           raise ArgumentError, "invalid array type: #{a.class}"
-                         end
+        gesdd = "#{bchr}gesdd".to_sym
+        s, u, vt, info = Numo::TinyLinalg::Lapack.send(gesdd, a.dup, jobz: job)
       when 'svd'
-        s, u, vt, info = case a
-                         when Numo::DFloat
-                           Numo::TinyLinalg::Lapack.dgesvd(a.dup, jobu: job, jobvt: job)
-                         when Numo::SFloat
-                           Numo::TinyLinalg::Lapack.sgesvd(a.dup, jobu: job, jobvt: job)
-                         when Numo::DComplex
-                           Numo::TinyLinalg::Lapack.zgesvd(a.dup, jobu: job, jobvt: job)
-                         when Numo::SComplex
-                           Numo::TinyLinalg::Lapack.cgesvd(a.dup, jobu: job, jobvt: job)
-                         else
-                           raise ArgumentError, "invalid array type: #{a.class}"
-                         end
+        gesvd = "#{bchr}gesvd".to_sym
+        s, u, vt, info = Numo::TinyLinalg::Lapack.send(gesvd, a.dup, jobu: job, jobvt: job)
       else
         raise ArgumentError, "invalid driver: #{driver}"
       end