def test_random_test(self):
for i in range(10):
n = random.randint(1, 2**20)
w = random.randint(1, 2**8)
x = np.random.rand(n)
y = rollingrank.rci(x, window=w, n_jobs=1)
y_parallel = rollingrank.rci(x, window=w)
np.testing.assert_array_equal(y_parallel, y)
def test_normal_case(self):
x = np.array([0.1, 0.2, 0.3, 0.4, 0.35, 0.25, 0.15])
y = rollingrank.rci(x, window=3)
y_ref = rollingrank.rci_reference(x, window=3)
np.testing.assert_array_equal(y, y_ref)
def test_pandas_series_input(self):
x = np.array([0.1, 0.2, 0.3, 0.2, 0.1, 0.2, 0.3])
y = rollingrank.rci(pd.Series(x), window=3)
y_ref = rollingrank.rci(x, window=3)
np.testing.assert_array_equal(y, y_ref)
def test_parallel(self):
x = np.random.rand(2**20)
y = rollingrank.rci(x, window=3, n_jobs=1)
y_parallel = rollingrank.rci(x, window=3)
np.testing.assert_array_equal(y_parallel, y)
def test_nan_window1(self):
x = np.array([1, np.nan, 2])
y = rollingrank.rci(x, window=1)
np.testing.assert_array_equal(y, [0, np.nan, 0])
def test_list_input(self):
x = [0.1, 0.2, 0.3, 0.4, 0.35, 0.25, 0.15]
y = rollingrank.rci(x, window=3)
y_ref = rollingrank.rci(np.array(x), window=3)
np.testing.assert_array_equal(y, y_ref)
def test_rollingrank_large_window(self):
x = np.array([0.1, 0.2, 0.3, 0.25, 0.1, 0.2, 0.3])
y = rollingrank.rci(x, window=8)
np.testing.assert_array_equal(
y, [np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan])
def test_nan(self):
x = np.array([1, np.nan, 2, np.nan, 3])
y = rollingrank.rci(x, window=3)
np.testing.assert_array_equal(y, [np.nan, np.nan, 1, np.nan, 1])
def test_method_average(self):
x = np.array([0.1, 0.1])
y = rollingrank.rci(x, window=2)
np.testing.assert_array_equal(y, [np.nan, 0])
def test_window1(self):
x = np.array([0.1, 0.2, 0.3, 0.25, 0.1, 0.2, 0.3])
y = rollingrank.rci(x, window=1)
np.testing.assert_array_equal(y, [0, 0, 0, 0, 0, 0, 0])
def test_float16(self):
x = np.array([0.1, 0.2, 0.3, 0.4, 0.35, 0.25, 0.15])
y = rollingrank.rci(x.astype(np.float16), window=3)
y_ref = rollingrank.rci(x, window=3)
np.testing.assert_array_equal(y, y_ref)
def bench_nan():
rollingrank.rci(x_nan, window=window)
def bench_float():
rollingrank.rci(x.astype('float32'), window=window)
def bench_single():
rollingrank.rci(x, window=window, n_jobs=1)
def bench():
rollingrank.rci(x, window=window)