update statistics test (simplistic)

test/test_helpers/test_statistics.py

@@ -4,7 +4,8 @@ import pytest
 import xarray as xr
 
 from mlair.helpers.statistics import standardise, standardise_inverse, standardise_apply, centre, centre_inverse, \
-    centre_apply, apply_inverse_transformation, min_max, min_max_inverse, min_max_apply, log, log_inverse, log_apply
+    centre_apply, apply_inverse_transformation, min_max, min_max_inverse, min_max_apply, log, log_inverse, log_apply, \
+    create_single_bootstrap_realization, calculate_average, create_n_bootstrap_realizations
 
 lazy = pytest.lazy_fixture
 
@@ -221,3 +222,47 @@ class TestLog:
         data_ref, opts = log(data_orig, dim)
         data_test = log_apply(data_orig, opts["mean"], opts["std"])
         assert np.testing.assert_array_almost_equal(data_ref, data_test) is None
+
+
+class TestCreateSingleBootstrapRealization:
+
+    @pytest.fixture
+    def data(self):
+        return xr.DataArray(np.array(range(20)).reshape(2 , -1).T,
+                            dims={'time': range(10), 'model': ['m1', 'm2']},
+                            coords={'time': range(10), 'model': ['m1', 'm2']})
+
+    def test_create_single_bootstrap_realization(self, data):
+        np.random.seed(42)
+        proc_data = create_single_bootstrap_realization(data, "time")
+        assert isinstance(proc_data, xr.DataArray)
+        assert (proc_data.coords['time'].values == np.array([6, 3, 7, 4, 6, 9, 2, 6, 7, 4])).all()
+        # check if all time index values of proc_data are from data
+        assert np.in1d(proc_data.indexes['time'].values, data.indexes['time'].values).all()
+
+    def test_calculate_average(self, data):
+        assert isinstance(data, xr.DataArray)
+        assert calculate_average(data) == data.mean()
+        assert (calculate_average(data, axis=0) == data.mean(axis=0)).all()
+
+    def test_create_n_bootstrap_realizations(self, data):
+        boot_data = create_n_bootstrap_realizations(data, dim_name_time='time', dim_name_model='model',
+                                                    n_boots=1000, dim_name_boots='boots')
+        assert isinstance(boot_data, xr.DataArray)
+        assert boot_data.shape == (1000, 2)
+
+        boot_data = create_n_bootstrap_realizations(data.sel(model='m1').squeeze(), dim_name_time='time',
+                                                    dim_name_model='model', n_boots=1000, dim_name_boots='boots')
+        assert isinstance(boot_data, xr.DataArray)
+        assert boot_data.shape == (1000,)
+
+
+
+
+
+class TestCalculateAverage:
+    pass
+
+
+class TestCreateNBootstrapRealizations:
+    pass
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