Benchmarks added

tests/benchmark_test.py

@@ -0,0 +1,55 @@
+import numpy as np
+import pyerrors as pe
+import pytest
+import time
+
+np.random.seed(0)
+
+def test_bench_mul(benchmark):
+    length = 1000
+    my_obs = pe.Obs([np.random.rand(length)], ['t1'])
+
+    def mul(x, y):
+        return x * y
+
+    benchmark(mul, my_obs, my_obs)
+
+
+def test_bench_cmul(benchmark):
+    length = 1000
+    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):
+    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):
+    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'])))
+    my_array = np.array(my_list).reshape((dim, dim))
+
+    benchmark(pe.linalg.matmul, my_array, my_array)
+
+
+def test_bench_gamma_method(benchmark):
+    length = 1000
+    my_obs = pe.Obs([np.random.rand(length)], ['t1'])
+    benchmark(my_obs.gamma_method)