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benchmarks simplified

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This commit is contained in:
Fabian Joswig 2021-10-26 10:41:36 +01:00
parent f38f86ae32
commit 7874bdb1fd
1 changed files with 11 additions and 17 deletions
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28
tests/benchmark_test.py
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@ -5,42 +5,37 @@ import time
np.random.seed(0) np.random.seed(0)
def test_bench_mul(benchmark): length = 1000
length = 1000
my_obs = pe.Obs([np.random.rand(length)], ['t1'])
def mul(x, y): def mul(x, y):
return 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) benchmark(mul, my_obs, my_obs)
def test_bench_cmul(benchmark): def test_b_cmul(benchmark):
length = 1000
my_obs = pe.CObs(pe.Obs([np.random.rand(length)], ['t1']), my_obs = pe.CObs(pe.Obs([np.random.rand(length)], ['t1']),
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) benchmark(mul, my_obs, my_obs)
def test_bench_matmul(benchmark): def test_b_matmul(benchmark):
dim = 4 dim = 4
my_list = [] my_list = []
length = 1000
for i in range(dim ** 2): for i in range(dim ** 2):
my_list.append(pe.Obs([np.random.rand(length)], ['t1'])) my_list.append(pe.Obs([np.random.rand(length)], ['t1']))
my_array = np.array(my_list).reshape((dim, dim)) my_array = np.array(my_list).reshape((dim, dim))
benchmark(pe.linalg.matmul, my_array, my_array) benchmark(pe.linalg.matmul, my_array, my_array)
def test_b_cmatmul(benchmark):
def test_bench_cmatmul(benchmark):
dim = 4 dim = 4
my_list = [] my_list = []
length = 1000
for i in range(dim ** 2): for i in range(dim ** 2):
my_list.append(pe.CObs(pe.Obs([np.random.rand(length)], ['t1']), my_list.append(pe.CObs(pe.Obs([np.random.rand(length)], ['t1']),
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) benchmark(pe.linalg.matmul, my_array, my_array)
def test_bench_gamma_method(benchmark): def test_b_gamma(benchmark):
length = 1000
my_obs = pe.Obs([np.random.rand(length)], ['t1']) my_obs = pe.Obs([np.random.rand(length)], ['t1'])
benchmark(my_obs.gamma_method) benchmark(my_obs.gamma_method)