Drop support for array.array & cython.view.array

Author: bjodah

benchmarks/Lambdify.py

@@ -12,9 +12,11 @@
 args = np.concatenate((x, p))
 exp = sp.exp
 exprs = [x[0] + x[1] - x[4] + 36.252574322669, x[0] - x[2] + x[3] + 21.3219379611249, x[3] + x[5] - x[6] + 9.9011158998744, 2*x[3] + x[5] - x[7] + 18.190422234653, 3*x[3] + x[5] - x[8] + 24.8679190043357, 4*x[3] + x[5] - x[9] + 29.9336062089226, -x[10] + 5*x[3] + x[5] + 28.5520551531262, 2*x[0] + x[11] - 2*x[4] - 2*x[5] + 32.4401680272417, 3*x[1] - x[12] + x[5] + 34.9992934135095, 4*x[1] - x[13] + x[5] + 37.0716199972041, p[0] - p[1] + 2*p[10] + 2*p[11] - p[12] - 2*p[13] + p[2] + 2*p[5] + 2*p[6] + 2*p[7] + 2*p[8] + 2*p[9] - exp(x[0]) + exp(x[1]) - 2*exp(x[10]) - 2*exp(x[11]) + exp(x[12]) + 2*exp(x[13]) - exp(x[2]) - 2*exp(x[5]) - 2*exp(x[6]) - 2*exp(x[7]) - 2*exp(x[8]) - 2*exp(x[9]), -p[0] - p[1] - 15*p[10] - 2*p[11] - 3*p[12] - 4*p[13] - 4*p[2] - 3*p[3] - 2*p[4] - 3*p[6] - 6*p[7] - 9*p[8] - 12*p[9] + exp(x[0]) + exp(x[1]) + 15*exp(x[10]) + 2*exp(x[11]) + 3*exp(x[12]) + 4*exp(x[13]) + 4*exp(x[2]) + 3*exp(x[3]) + 2*exp(x[4]) + 3*exp(x[6]) + 6*exp(x[7]) + 9*exp(x[8]) + 12*exp(x[9]), -5*p[10] - p[2] - p[3] - p[6] - 2*p[7] - 3*p[8] - 4*p[9] + 5*exp(x[10]) + exp(x[2]) + exp(x[3]) + exp(x[6]) + 2*exp(x[7]) + 3*exp(x[8]) + 4*exp(x[9]), -p[1] - 2*p[11] - 3*p[12] - 4*p[13] - p[4] + exp(x[1]) + 2*exp(x[11]) + 3*exp(x[12]) + 4*exp(x[13]) + exp(x[4]), -p[10] - 2*p[11] - p[12] - p[13] - p[5] - p[6] - p[7] - p[8] - p[9] + exp(x[10]) + 2*exp(x[11]) + exp(x[12]) + exp(x[13]) + exp(x[5]) + exp(x[6]) + exp(x[7]) + exp(x[8]) + exp(x[9])]
+
 lmb_sp = sp.lambdify(args, exprs)
-lbm_se = se.Lambdify(args, exprs)
-lbm_se_llvm = se.Lambdify(args, exprs, backend='llvm')
+lmb_se = se.Lambdify(args, exprs)
+lmb_se_cse = se.LambdifyCSE(args, exprs)
+lmb_se_llvm = se.Lambdify(args, exprs, backend='llvm')
 
 inp = np.ones(28)
 
@@ -24,25 +26,35 @@
     res_sympy = lmb_sp(*inp)
 tim_sympy = clock() - tim_sympy
 
-lbm_se(inp)
+lmb_se(inp)
 tim_se = clock()
 res_se = np.empty(len(exprs))
 for i in range(500):
-    res_se = lbm_se(inp)
+    res_se = lmb_se(inp)
 tim_se = clock() - tim_se
 
-lbm_se_llvm(inp)
+lmb_se_cse(inp)
+tim_se_cse = clock()
+res_se_cse = np.empty(len(exprs))
+for i in range(500):
+    res_se_cse = lmb_se_cse(inp)
+tim_se_cse = clock() - tim_se_cse
+
+lmb_se_llvm(inp)
 tim_se_llvm = clock()
 res_se_llvm = np.empty(len(exprs))
 for i in range(500):
-    res_se_llvm = lbm_se_llvm(inp)
+    res_se_llvm = lmb_se_llvm(inp)
 tim_se_llvm = clock() - tim_se_llvm
 
 
-print('SymEngine (lambda double) speed-up factor (higher is better) vs sympy: %12.5g' %
+print('SymEngine (lambda double)       speed-up factor (higher is better) vs sympy: %12.5g' %
       (tim_sympy/tim_se))
 
-print('symengine (LLVM)          speed-up factor (higher is better) vs sympy: %12.5g' %
+print('symengine (lambda double + CSE) speed-up factor (higher is better) vs sympy: %12.5g' %
+      (tim_sympy/tim_se_cse))
+
+print('symengine (LLVM)                speed-up factor (higher is better) vs sympy: %12.5g' %
       (tim_sympy/tim_se_llvm))
 
 import itertools
@@ -64,14 +76,14 @@ def func(*args):
         return result
     return func
 
-lbm_se_llvm_manual = ManualLLVM(args, np.array(exprs))
-lbm_se_llvm_manual(inp)
+lmb_se_llvm_manual = ManualLLVM(args, np.array(exprs))
+lmb_se_llvm_manual(inp)
 tim_se_llvm_manual = clock()
 res_se_llvm_manual = np.empty(len(exprs))
 for i in range(500):
-    res_se_llvm_manual = lbm_se_llvm_manual(inp)
+    res_se_llvm_manual = lmb_se_llvm_manual(inp)
 tim_se_llvm_manual = clock() - tim_se_llvm_manual
-print('symengine (ManualLLVM)    speed-up factor (higher is better) vs sympy: %12.5g' %
+print('symengine (ManualLLVM)          speed-up factor (higher is better) vs sympy: %12.5g' %
       (tim_sympy/tim_se_llvm_manual))
 
 if tim_se_llvm_manual < tim_se_llvm:
@@ -87,5 +99,5 @@ def func(*args):
 for i in range(500):
     res_ref = lmb_ref(inp)
 tim_ref = clock() - tim_ref
-print('Hard-coded Cython code    speed-up factor (higher is better) vs sympy: %12.5g' %
+print('Hard-coded Cython code          speed-up factor (higher is better) vs sympy: %12.5g' %
       (tim_sympy/tim_ref))