[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

tests/sample_data/example_hbn_actigraph_idle_sleep_mode_false.csv

@@ -36,9 +36,9 @@ def test_fill_false_blocks() -> None:
 
     result = analytics._fill_false_blocks(sleep_idx_array, gap_block)
 
-    assert np.array_equal(result, expected_result), (
-        f"Expected {expected_result}, but got {result}"
-    )
+    assert np.array_equal(
+        result, expected_result
+    ), f"Expected {expected_result}, but got {result}"
 
 
 def test_compute_abs_diff_mean_anglez(
@@ -55,9 +55,9 @@ def test_compute_abs_diff_mean_anglez(
 
     result = sleep_detection._compute_abs_diff_mean_anglez(sleep_detection.anglez)
 
-    assert np.array_equal(result.measurements, expected_result), (
-        f"Expected {expected_result}, but got {result.measurements}"
-    )
+    assert np.array_equal(
+        result.measurements, expected_result
+    ), f"Expected {expected_result}, but got {result.measurements}"
     assert np.array_equal(len(result.time), expected_length)
 
 
@@ -91,12 +91,12 @@ def test_spt_window(sleep_detection: analytics.GgirSleepDetection) -> None:
 
     result = sleep_detection._spt_window(sleep_detection.anglez)
 
-    assert np.array_equal(result.measurements, expected_result), (
-        f"Expected {expected_result}, but got {result.measurements}"
-    )
-    assert np.array_equal(len(result.time), expected_length), (
-        f"Expected {expected_length}, but got {len(result.time)}"
-    )
+    assert np.array_equal(
+        result.measurements, expected_result
+    ), f"Expected {expected_result}, but got {result.measurements}"
+    assert np.array_equal(
+        len(result.time), expected_length
+    ), f"Expected {expected_length}, but got {len(result.time)}"
 
 
 def test_spt_window_null(sleep_detection: analytics.GgirSleepDetection) -> None:
@@ -106,12 +106,12 @@ def test_spt_window_null(sleep_detection: analytics.GgirSleepDetection) -> None:
 
     result = sleep_detection._spt_window(sleep_detection.anglez)
 
-    assert np.array_equal(result.measurements, expected_result), (
-        f"Expected {expected_result}, but got {result.measurements}"
-    )
-    assert np.array_equal(len(result.time), expected_length), (
-        f"Expected {expected_length}, but got {len(result.time)}"
-    )
+    assert np.array_equal(
+        result.measurements, expected_result
+    ), f"Expected {expected_result}, but got {result.measurements}"
+    assert np.array_equal(
+        len(result.time), expected_length
+    ), f"Expected {expected_length}, but got {len(result.time)}"
 
 
 def test_calculate_sib_periods(sleep_detection: analytics.GgirSleepDetection) -> None:
@@ -121,12 +121,12 @@ def test_calculate_sib_periods(sleep_detection: analytics.GgirSleepDetection) ->
 
     result = sleep_detection._calculate_sib_periods(sleep_detection.anglez, 10)
 
-    assert np.array_equal(result.measurements, expected_result), (
-        f"Expected {expected_result}, but got {result.measurements}"
-    )
-    assert len(result.measurements) == expected_length, (
-        f"Expected {expected_length}, but got {len(result.measurements)}"
-    )
+    assert np.array_equal(
+        result.measurements, expected_result
+    ), f"Expected {expected_result}, but got {result.measurements}"
+    assert (
+        len(result.measurements) == expected_length
+    ), f"Expected {expected_length}, but got {len(result.measurements)}"
 
 
 def test_find_onset_wakeup_times(sleep_detection: analytics.GgirSleepDetection) -> None:

tests/sample_data/example_hbn_actigraph_idle_sleep_mode_true.csv

@@ -116,12 +116,12 @@ def test_closest_point_fit() -> None:
 
     linear_transform = calibrator._closest_point_fit((unit_sphere * scale) + offset)
 
-    assert np.allclose(linear_transform.scale, expected_scale, atol=1e-3), (
-        f"Scale is {linear_transform.scale} expected {expected_scale}"
-    )
-    assert np.allclose(linear_transform.offset, expected_offset, atol=1e-3), (
-        f"Offset is {linear_transform.offset} expected {expected_offset})"
-    )
+    assert np.allclose(
+        linear_transform.scale, expected_scale, atol=1e-3
+    ), f"Scale is {linear_transform.scale} expected {expected_scale}"
+    assert np.allclose(
+        linear_transform.offset, expected_offset, atol=1e-3
+    ), f"Offset is {linear_transform.offset} expected {expected_offset})"
 
 
 def test_closest_point_fit_constrainedmin() -> None:
@@ -137,12 +137,12 @@ def test_closest_point_fit_constrainedmin() -> None:
 
     linear_transform = calibrator._closest_point_fit((unit_sphere * scale) + offset)
 
-    assert np.allclose(linear_transform.scale, expected_scale, atol=1e-3), (
-        f"Scale is {linear_transform.scale} expected {expected_scale}"
-    )
-    assert np.allclose(linear_transform.offset, expected_offset, atol=1e-3), (
-        f"Offset is {linear_transform.offset} expected {expected_offset})"
-    )
+    assert np.allclose(
+        linear_transform.scale, expected_scale, atol=1e-3
+    ), f"Scale is {linear_transform.scale} expected {expected_scale}"
+    assert np.allclose(
+        linear_transform.offset, expected_offset, atol=1e-3
+    ), f"Offset is {linear_transform.offset} expected {expected_offset})"
 
 
 def test_closest_point_fit_constrainmin_calibration_error() -> None:
@@ -202,12 +202,12 @@ def test_ggir_calibration_successful() -> None:
 
     linear_transform = calibrator._calibrate(dummy_measure)
 
-    assert np.allclose(linear_transform.scale, expected_scale, atol=1e-3), (
-        f"Scale is {linear_transform.scale} expected {expected_scale}"
-    )
-    assert np.allclose(linear_transform.offset, expected_offset, atol=1e-3), (
-        f"Offset is {linear_transform.offset} expected {expected_offset}"
-    )
+    assert np.allclose(
+        linear_transform.scale, expected_scale, atol=1e-3
+    ), f"Scale is {linear_transform.scale} expected {expected_scale}"
+    assert np.allclose(
+        linear_transform.offset, expected_offset, atol=1e-3
+    ), f"Offset is {linear_transform.offset} expected {expected_offset}"
 
 
 @pytest.mark.parametrize(
@@ -276,12 +276,12 @@ def test_run_ggircalibration() -> None:
 
     result = calibrator.run_calibration(dummy_measure)
 
-    assert isinstance(result, models.Measurement), (
-        f"was expecting type models.Measurement, object is of type {type(result)}"
-    )
-    assert np.allclose(result.measurements, expected_data.measurements, atol=1e-3), (
-        "Measurement data did not match"
-    )
+    assert isinstance(
+        result, models.Measurement
+    ), f"was expecting type models.Measurement, object is of type {type(result)}"
+    assert np.allclose(
+        result.measurements, expected_data.measurements, atol=1e-3
+    ), "Measurement data did not match"
     assert result.time.equals(expected_data.time), "Time series are not equal"
 
 
@@ -309,12 +309,12 @@ def test_run_constrainedmincalibration() -> None:
 
     result = calibrator.run_calibration(dummy_measure)
 
-    assert isinstance(result, models.Measurement), (
-        f"was expecting type models.Measurement, object is of type {type(result)}"
-    )
-    assert np.allclose(result.measurements, expected_data.measurements, atol=1e-3), (
-        "Measurement data did not match"
-    )
+    assert isinstance(
+        result, models.Measurement
+    ), f"was expecting type models.Measurement, object is of type {type(result)}"
+    assert np.allclose(
+        result.measurements, expected_data.measurements, atol=1e-3
+    ), "Measurement data did not match"
     assert result.time.equals(expected_data.time), "Time series are not equal"
 
 
@@ -342,12 +342,12 @@ def test_run_chunked_calibration() -> None:
 
     result = calibrator.run_calibration(dummy_measure)
 
-    assert isinstance(result, models.Measurement), (
-        f"was expecting type models.Measurement, object is of type {type(result)}"
-    )
-    assert np.allclose(result.measurements, expected_data.measurements, atol=1e-3), (
-        "Measurement data did not match"
-    )
+    assert isinstance(
+        result, models.Measurement
+    ), f"was expecting type models.Measurement, object is of type {type(result)}"
+    assert np.allclose(
+        result.measurements, expected_data.measurements, atol=1e-3
+    ), "Measurement data did not match"
     assert result.time.equals(expected_data.time), "Time series are not equal"
 
 

tests/unit/test_analytics.py

@@ -181,9 +181,9 @@ def test_moving_median(window_size: int, expected_output: np.ndarray) -> None:
         f"measurements array are not the same shape. Expected {expected_output.shape}, "
         f"instead got: {test_result.measurements.shape}"
     )
-    assert np.all(np.isclose(test_result.measurements, expected_output)), (
-        "Test results do not match the expected output"
-    )
+    assert np.all(
+        np.isclose(test_result.measurements, expected_output)
+    ), "Test results do not match the expected output"
 
 
 def test_resample_downsample_simple() -> None:

tests/unit/test_calibration.py

@@ -55,13 +55,13 @@ def test_euclidean_norm_minus_one(
     expected_length = math.ceil(len(test_time) / 5)
     enmo_results = metrics.euclidean_norm_minus_one(test_acceleration)
 
-    assert np.all(np.isclose(enmo_results.measurements, expected_enmo)), (
-        f"Expected {expected_enmo}"
-    )
+    assert np.all(
+        np.isclose(enmo_results.measurements, expected_enmo)
+    ), f"Expected {expected_enmo}"
 
-    assert len(enmo_results.time) == expected_length, (
-        "Input time attribute does not match output time attribute."
-    )
+    assert (
+        len(enmo_results.time) == expected_length
+    ), "Input time attribute does not match output time attribute."
 
 
 @pytest.mark.parametrize(
@@ -91,9 +91,9 @@ def test_angle_relative_to_horizontal(
         np.isclose(angle_z_results.measurements, expected_anglez, equal_nan=True)
     ), f"Expected {expected_anglez}, got: {angle_z_results.measurements}"
 
-    assert len(angle_z_results.time) == expected_length, (
-        "Input time attribute does not match output time attribute."
-    )
+    assert (
+        len(angle_z_results.time) == expected_length
+    ), "Input time attribute does not match output time attribute."
 
 
 @pytest.mark.parametrize(
@@ -115,9 +115,9 @@ def test_cleanup_isolated_ones_nonwear_value(
     """Test the cleanup isolated ones nonwear value function."""
     test_result = metrics._cleanup_isolated_ones_nonwear_value(nonwear_value_array)
 
-    assert np.all(test_result == expected_result), (
-        f"Expected {expected_result}, got: {test_result}"
-    )
+    assert np.all(
+        test_result == expected_result
+    ), f"Expected {expected_result}, got: {test_result}"
 
 
 def test_group_acceleration_data_by_time() -> None:
@@ -158,9 +158,9 @@ def test_compute_nonwear_value_per_axis(
         acceleration_grouped["X"], std_criteria=modifier
     )
 
-    assert test_resultx == expected_result, (
-        f"Expected {expected_result}, got: {test_resultx}"
-    )
+    assert (
+        test_resultx == expected_result
+    ), f"Expected {expected_result}, got: {test_resultx}"
 
 
 def test_compute_nonwear_value_array(create_acceleration: pl.DataFrame) -> None:
@@ -179,12 +179,12 @@ def test_compute_nonwear_value_array(create_acceleration: pl.DataFrame) -> None:
         std_criteria=1,
     )
 
-    assert np.all(test_result == expected_result), (
-        f"Expected {expected_result}, got: {test_result}"
-    )
-    assert len(test_result) == expected_time_length, (
-        f"Expected time to be {expected_time_length}, got: {len(test_result)}"
-    )
+    assert np.all(
+        test_result == expected_result
+    ), f"Expected {expected_result}, got: {test_result}"
+    assert (
+        len(test_result) == expected_time_length
+    ), f"Expected time to be {expected_time_length}, got: {len(test_result)}"
 
 
 @pytest.mark.parametrize(
@@ -214,12 +214,12 @@ def test_detect_nonwear(
         std_criteria=modifier,
     )
 
-    assert np.all(test_result.measurements == modifier), (
-        f"Expected non-wear flag value to be {expected_result}, got: {test_result}"
-    )
-    assert len(test_result.time) == expected_time_length, (
-        f"Expected time to be {expected_time_length}, got: {len(test_result.time)}"
-    )
+    assert np.all(
+        test_result.measurements == modifier
+    ), f"Expected non-wear flag value to be {expected_result}, got: {test_result}"
+    assert (
+        len(test_result.time) == expected_time_length
+    ), f"Expected time to be {expected_time_length}, got: {len(test_result.time)}"
 
 
 def test_mean_amplitude_deviation_function(create_acceleration: pl.DataFrame) -> None:
@@ -230,12 +230,12 @@ def test_mean_amplitude_deviation_function(create_acceleration: pl.DataFrame) ->
 
     test_result = metrics.mean_amplitude_deviation(acceleration)
 
-    assert np.all(test_result.measurements == expected_result), (
-        f"Expected MAD value to be {expected_result}, got: {test_result}"
-    )
-    assert len(test_result.time) == expected_time, (
-        f"Expected time to be {expected_time}, got: {len(test_result.time)}"
-    )
+    assert np.all(
+        test_result.measurements == expected_result
+    ), f"Expected MAD value to be {expected_result}, got: {test_result}"
+    assert (
+        len(test_result.time) == expected_time
+    ), f"Expected time to be {expected_time}, got: {len(test_result.time)}"
 
 
 def test_ag_counts_null(create_acceleration: pl.DataFrame) -> None:
@@ -247,9 +247,9 @@ def test_ag_counts_null(create_acceleration: pl.DataFrame) -> None:
 
     ag_counts = metrics.actigraph_activity_counts(acceleration)
 
-    assert np.all(ag_counts.measurements == expected_result), (
-        f"Expected activity counts to be {expected_result}, got: {ag_counts}"
-    )
+    assert np.all(
+        ag_counts.measurements == expected_result
+    ), f"Expected activity counts to be {expected_result}, got: {ag_counts}"
     assert len(ag_counts.time) == expected_time
 
 
@@ -280,9 +280,9 @@ def test_ag_counts_max() -> None:
 
     ag_counts = metrics.actigraph_activity_counts(acceleration)
 
-    assert np.all(ag_counts.measurements[2:] == expected_result), (
-        f"Expected activity counts to be {expected_result}, got: {ag_counts}"
-    )
+    assert np.all(
+        ag_counts.measurements[2:] == expected_result
+    ), f"Expected activity counts to be {expected_result}, got: {ag_counts}"
 
 
 @pytest.mark.parametrize("temp_length", [498, 500])