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	benchmarks simplified
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					 1 changed files with 11 additions and 17 deletions
				
			
		|  | @ -5,42 +5,37 @@ import time | |||
| 
 | ||||
| np.random.seed(0) | ||||
| 
 | ||||
| def test_bench_mul(benchmark): | ||||
|     length = 1000 | ||||
|     my_obs = pe.Obs([np.random.rand(length)], ['t1']) | ||||
| length = 1000 | ||||
| 
 | ||||
|     def mul(x, y): | ||||
|         return x * y | ||||
| def mul(x, y): | ||||
|     return x * y | ||||
| 
 | ||||
| 
 | ||||
| def test_b_mul(benchmark): | ||||
|     my_obs = pe.Obs([np.random.rand(length)], ['t1']) | ||||
| 
 | ||||
|     benchmark(mul, my_obs, my_obs) | ||||
| 
 | ||||
| 
 | ||||
| def test_bench_cmul(benchmark): | ||||
|     length = 1000 | ||||
| def test_b_cmul(benchmark): | ||||
|     my_obs = pe.CObs(pe.Obs([np.random.rand(length)], ['t1']), | ||||
|                      pe.Obs([np.random.rand(length)], ['t1'])) | ||||
| 
 | ||||
|     def mul(x, y): | ||||
|         return x * y | ||||
| 
 | ||||
|     benchmark(mul, my_obs, my_obs) | ||||
| 
 | ||||
| 
 | ||||
| def test_bench_matmul(benchmark): | ||||
| def test_b_matmul(benchmark): | ||||
|     dim = 4 | ||||
|     my_list = [] | ||||
|     length = 1000 | ||||
|     for i in range(dim ** 2): | ||||
|         my_list.append(pe.Obs([np.random.rand(length)], ['t1'])) | ||||
|     my_array = np.array(my_list).reshape((dim, dim)) | ||||
| 
 | ||||
|     benchmark(pe.linalg.matmul, my_array, my_array) | ||||
| 
 | ||||
| 
 | ||||
| def test_bench_cmatmul(benchmark): | ||||
| def test_b_cmatmul(benchmark): | ||||
|     dim = 4 | ||||
|     my_list = [] | ||||
|     length = 1000 | ||||
|     for i in range(dim ** 2): | ||||
|         my_list.append(pe.CObs(pe.Obs([np.random.rand(length)], ['t1']), | ||||
|                                pe.Obs([np.random.rand(length)], ['t1']))) | ||||
|  | @ -49,7 +44,6 @@ def test_bench_cmatmul(benchmark): | |||
|     benchmark(pe.linalg.matmul, my_array, my_array) | ||||
| 
 | ||||
| 
 | ||||
| def test_bench_gamma_method(benchmark): | ||||
|     length = 1000 | ||||
| def test_b_gamma(benchmark): | ||||
|     my_obs = pe.Obs([np.random.rand(length)], ['t1']) | ||||
|     benchmark(my_obs.gamma_method) | ||||
|  |  | |||
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