[pre-commit.ci] pre-commit autoupdate

[pre-commit-ci]

updates:

• github.com/astral-sh/ruff-pre-commit: v0.15.14 → v0.15.21

[codecov]

❌ 5 Tests Failed:

Tests completed	Failed	Passed	Skipped
467	5	462	0

View the full list of 5 ❄️ flaky test(s)

primap2/_setters.py::DataArraySettersAccessor.set:0

Flake rate in main: 82.76% (Passed 5 times, Failed 24 times)

Stack Traces | 0.009s run time

* REASON: GotWantException
DOCTEST DEBUG INFO
  XDoc ".../primap2/primap2/_setters.py::DataArraySettersAccessor.set:0", line 12 <- wrt doctest
  File ".../primap2/primap2/_setters.py", line 80, <- wrt source file
DOCTEST PART BREAKDOWN
Passed Parts:
      1 >>> import pandas as pd
      2 >>> import xarray as xr
      3 >>> import numpy as np
      4 >>> da = xr.DataArray(
      5 ...     [[0.0, 1.0, 2.0, 3.0], [2.0, 3.0, 4.0, 5.0]],
      6 ...     coords=[
      7 ...         ("area (ISO3)", ["COL", "MEX"]),
      8 ...         ("time", pd.date_range("2000", "2003", freq="YS")),
      9 ...     ],
     10 ... )
Failed Part:
     11 >>> da
Remaining Parts:
     21 >>> da.pr.set("area", "COL", np.array([0.5, 0.6, 0.7, 0.8]))
     25 >>> da.pr.set("area", "COL", np.array([0.5, 0.6, 0.7, 0.8]), existing="overwrite")
     36 >>> da_partly_empty = da.copy(deep=True)
     37 >>> da_partly_empty.pr.loc[{"area": "COL"}] = np.nan
     38 >>> da_partly_empty
     45 >>> da_partly_empty.pr.set("area", "COL", np.array([0.5, 0.6, 0.7, 0.8]))
     52 >>> # if even one value contains data, the default is to raise an Error
     53 >>> da_partly_empty.pr.loc[{"area": "COL", "time": "2001"}] = 0.6
     54 >>> da_partly_empty
     61 >>> da_partly_empty.pr.set("area", "COL", np.array([0.5, 0.6, 0.7, 0.8]))
     68 >>> da.pr.set("area", "ARG", np.array([0.5, 0.6, 0.7, 0.8]))
     79 >>> da.pr.set(
     80 ...     "area",
     81 ...     ["COL", "ARG"],
     82 ...     np.array([[0.5, 0.6, 0.7, 0.8], [5, 6, 7, 8]]),
     83 ...     existing="overwrite",
     84 ... )
     96 >>> da.pr.set("area", "ARG", np.array([0.5, 0.6, 0.7, 0.8]), new="error")
    105 >>> da.pr.set(
    106 ...     "area",
    107 ...     ["COL", "ARG"],
    108 ...     np.array([0.5, 0.6, 0.7, 0.8]),
    109 ...     existing="overwrite",
    110 ... )
    114 >>> da.pr.set(
    115 ...     "area",
    116 ...     ["COL", "ARG"],
    117 ...     np.array([0.5, 0.6, 0.7, 0.8]),
    118 ...     value_dims=["time"],
    119 ...     existing="overwrite",
    120 ... )
    132 >>> da.pr.loc[{"area": "COL", "time": "2001"}] = np.nan
    133 >>> da
    140 >>> da.pr.set(
    141 ...     "area",
    142 ...     ["COL", "ARG"],
    143 ...     np.array([0.5, 0.6, 0.7, 0.8]),
    144 ...     value_dims=["time"],
    145 ...     existing="fillna",
    146 ... )
    158 >>> da.pr.set("area", "ARG", da.pr.loc[{"area": "COL"}] * 2)
DOCTEST TRACEBACK
Differences (unified diff with -expected +actual):
    @@ -4,3 +4,3 @@
     Coordinates:
       * area (ISO3)  (area (ISO3)) <U3 24B 'COL' 'MEX'
    -  * time         (time) datetime64[ns] 32B 2000-01-01 2001-01-01 ... 2003-01-01
    +  * time         (time) datetime64[us] 32B 2000-01-01 2001-01-01 ... 2003-01-01
    
Repr Difference:
    got  = "<xarray.DataArray (area (ISO3): 2, time: 4)> Size: 64B\narray([[0., 1., 2., 3.],\n       [2., 3., 4., 5.]])\nCoordinates:\n  * area (ISO3)  (area (ISO3)) <U3 24B 'COL' 'MEX'\n  * time         (time) datetime64[us] 32B 2000-01-01 2001-01-01 ... 2003-01-01"
    want = "<xarray.DataArray (area (ISO3): 2, time: 4)> Size: 64B\narray([[0., 1., 2., 3.],\n       [2., 3., 4., 5.]])\nCoordinates:\n  * area (ISO3)  (area (ISO3)) <U3 24B 'COL' 'MEX'\n  * time         (time) datetime64[ns] 32B 2000-01-01 2001-01-01 ... 2003-01-01"
DOCTEST REPRODUCTION
CommandLine:
    pytest .../primap2/primap2/_setters.py::DataArraySettersAccessor.set:0
.../primap2/primap2/_setters.py:80: GotWantException

primap2/_setters.py::DatasetSettersAccessor.set:0

Flake rate in main: 82.76% (Passed 5 times, Failed 24 times)

Stack Traces | 0.01s run time

* REASON: GotWantException
DOCTEST DEBUG INFO
  XDoc ".../primap2/primap2/_setters.py::DatasetSettersAccessor.set:0", line 20 <- wrt doctest
  File ".../primap2/primap2/_setters.py", line 429, <- wrt source file
DOCTEST PART BREAKDOWN
Passed Parts:
      1 >>> import pandas as pd
      2 >>> import xarray as xr
      3 >>> import numpy as np
      4 >>> area = ("area (ISO3)", ["COL", "MEX"])
      5 >>> time = ("time", pd.date_range("2000", "2003", freq="YS"))
      6 >>> ds = xr.Dataset(
      7 ...     {
      8 ...         "CO2": xr.DataArray(
      9 ...             [[0.0, 1.0, 2.0, 3.0], [2.0, 3.0, 4.0, 5.0]],
     10 ...             coords=[area, time],
     11 ...         ),
     12 ...         "SF4": xr.DataArray(
     13 ...             [[0.5, 1.5, 2.5, 3.5], [2.5, 3.5, np.nan, 5.5]],
     14 ...             coords=[area, time],
     15 ...         ),
     16 ...     },
     17 ...     attrs={"area": "area (ISO3)"},
     18 ... )
Failed Part:
     19 >>> ds
Remaining Parts:
     33 >>> ds.pr.set("area", "MEX", ds.pr.loc[{"area": "COL"}] * 20)
     37 >>> ds.pr.set("area", "MEX", ds.pr.loc[{"area": "COL"}] * 20, existing="overwrite")
     52 >>> ds.pr.set("area", "MEX", ds.pr.loc[{"area": "COL"}] * 20, existing="fillna")
     67 >>> ds_partly_empty = ds.copy(deep=True)
     68 >>> ds_partly_empty["CO2"].pr.loc[{"area": "COL"}] = np.nan
     69 >>> ds_partly_empty["SF4"].pr.loc[{"area": "COL"}] = np.nan
     70 >>> ds_partly_empty
     81 >>> ds_partly_empty.pr.set("area", "COL", ds_partly_empty.pr.loc[{"area": "MEX"}] * 10)
     92 >>> # if even one value is non-nan, this fails by default
     93 >>> ds_partly_empty["SF4"].pr.loc[{"area": "COL", "time": "2001"}] = 2
     94 >>> ds_partly_empty.pr.set("area", "COL", ds_partly_empty.pr.loc[{"area": "MEX"}] * 10)
    101 >>> ds.pr.set("area", "BOL", ds.pr.loc[{"area": "COL"}] * 20)
    116 >>> ds.pr.set("area", "BOL", ds.pr.loc[{"area": "COL"}] * 20, new="error")
    124 >>> ds["population"] = xr.DataArray([1e6, 1.2e6, 1.3e6, 1.4e6], coords=(time,))
    125 >>> ds
    137 >>> ds.pr.set("area", "BOL", ds.pr.loc[{"area": "COL"}] * 20)
DOCTEST TRACEBACK
Differences (unified diff with -expected +actual):
    @@ -1,7 +1,7 @@
    -<xarray.Dataset> Size: ...
    +<xarray.Dataset> Size: 184B
     Dimensions:      (area (ISO3): 2, time: 4)
     Coordinates:
       * area (ISO3)  (area (ISO3)) <U3 24B 'COL' 'MEX'
    -  * time         (time) datetime64[ns] 32B 2000-01-01 2001-01-01 ... 2003-01-01
    +  * time         (time) datetime64[us] 32B 2000-01-01 2001-01-01 ... 2003-01-01
     Data variables:
         CO2          (area (ISO3), time) float64 64B 0.0 1.0 2.0 3.0 2.0 3.0 4.0 5.0
    
Repr Difference:
    got  = "<xarray.Dataset> Size: 184B\nDimensions:      (area (ISO3): 2, time: 4)\nCoordinates:\n  * area (ISO3)  (area (ISO3)) <U3 24B 'COL' 'MEX'\n  * time         (time) datetime64[us] 32B 2000-01-01 2001-01-01 ... 2003-01-01\nData variables:\n    CO2          (area (ISO3), time) float64 64B 0.0 1.0 2.0 3.0 2.0 3.0 4.0 5.0\n    SF4          (area (ISO3), time) float64 64B 0.5 1.5 2.5 3.5 2.5 3.5 nan 5.5\nAttributes:\n    area:     area (ISO3)"
    want = "<xarray.Dataset> Size: ...\nDimensions:      (area (ISO3): 2, time: 4)\nCoordinates:\n  * area (ISO3)  (area (ISO3)) <U3 24B 'COL' 'MEX'\n  * time         (time) datetime64[ns] 32B 2000-01-01 2001-01-01 ... 2003-01-01\nData variables:\n    CO2          (area (ISO3), time) float64 64B 0.0 1.0 2.0 3.0 2.0 3.0 4.0 5.0\n    SF4          (area (ISO3), time) float64 64B 0.5 1.5 2.5 3.5 2.5 3.5 nan 5.5\nAttributes:\n    area:     area (ISO3)"
DOCTEST REPRODUCTION
CommandLine:
    pytest .../primap2/primap2/_setters.py::DatasetSettersAccessor.set:0
.../primap2/primap2/_setters.py:429: GotWantException

primap2/tests/csg/test_gaps.py::test_calculate_boundary_trend_inner_left

Flake rate in main: 82.76% (Passed 5 times, Failed 24 times)

Stack Traces | 0.059s run time

test_ts = <xarray.DataArray 'test_ts' (time: 74)> Size: 592B
array([        nan,         nan,         nan,         nan,  6.     ...Coordinates:
  * time      (time) datetime64[us] 592B 1952-01-01 1953-01-01 ... 2025-01-01
    category  <U4 16B 'test'
fit_params_linear = FitParameters(fit_degree=1, fallback_degree=0, trend_length=10, trend_length_unit='YS', min_trend_points=5)
fit_params_constant = FitParameters(fit_degree=0, fallback_degree=0, trend_length=10, trend_length_unit='YS', min_trend_points=5)
caplog = <_pytest.logging.LogCaptureFixture object at 0x7f2a0d4708d0>

    def test_calculate_boundary_trend_inner_left(
        test_ts, fit_params_linear, fit_params_constant, caplog
    ):
        gaps = get_gaps(test_ts)
    
        # linear trend for a left boundary
        fit_degree = 1
        # expected result
        data_to_interpolate = test_ts.pr.loc[{"time": slice("1996", "2005")}].data
        coeff = np.polyfit(range(0, 10), data_to_interpolate, deg=fit_degree)
        expected_value = np.polyval(coeff, 9)
        trend_value = calculate_boundary_trend_inner(
            test_ts,
            side="left",
            boundary=gaps[1].left,
            fit_params=fit_params_linear,
        )
        assert np.allclose(expected_value, trend_value)
    
        # constant trend for a right boundary
        fit_degree = 0
        # expected result
        coeff = np.polyfit(range(0, 10), data_to_interpolate, deg=fit_degree)
        expected_value = np.polyval(coeff, 9)
        trend_value = calculate_boundary_trend_inner(
            test_ts,
            side="left",
            boundary=gaps[1].left,
            fit_params=fit_params_constant,
        )
        assert np.allclose(expected_value, trend_value)
    
        # test logging if not enough data points
        test_ts.loc[{"time": slice("1997", "2002")}] = (
            test_ts.loc[{"time": slice("1997", "2002")}] * np.nan
        )
        trend_value = calculate_boundary_trend_inner(
            test_ts, side="left", boundary=gaps[1].left, fit_params=fit_params_linear
        )
        assert np.isnan(trend_value)
    
        log_str = (
            "Not enough values to calculate fit for left boundary at "
            "2005-01-01T00:00:00.000000000.\nfit_degree: 1, trend_length: 10, "
            "trend_length_unit: YS, min_trend_points: 5.\nTimeseries info: "
            "{'category': 'test'}"
        )
    
>       assert log_str in caplog.text
E       assert "Not enough values to calculate fit for left boundary at 2005-01-01T00:00:00.000000000.\nfit_degree: 1, trend_length: 10, trend_length_unit: YS, min_trend_points: 5.\nTimeseries info: {'category': 'test'}" in "INFO     primap2.csg._strategies.gaps:gaps.py:328 Not enough values to calculate fit for left boundary at 2005-01-01T...t_degree: 1, trend_length: 10, trend_length_unit: YS, min_trend_points: 5.\nTimeseries info: {'category': 'test'} {}\n"
E        +  where "INFO     primap2.csg._strategies.gaps:gaps.py:328 Not enough values to calculate fit for left boundary at 2005-01-01T...t_degree: 1, trend_length: 10, trend_length_unit: YS, min_trend_points: 5.\nTimeseries info: {'category': 'test'} {}\n" = <_pytest.logging.LogCaptureFixture object at 0x7f2a0d4708d0>.text

.../tests/csg/test_gaps.py:252: AssertionError

primap2/tests/csg/test_gaps.py::test_calculate_boundary_trend_inner_right

Flake rate in main: 82.76% (Passed 5 times, Failed 24 times)

Stack Traces | 0.054s run time

test_ts = <xarray.DataArray 'test_ts' (time: 74)> Size: 592B
array([        nan,         nan,         nan,         nan,  6.     ...Coordinates:
  * time      (time) datetime64[us] 592B 1952-01-01 1953-01-01 ... 2025-01-01
    category  <U4 16B 'test'
fit_params_linear = FitParameters(fit_degree=1, fallback_degree=0, trend_length=10, trend_length_unit='YS', min_trend_points=5)
fit_params_constant = FitParameters(fit_degree=0, fallback_degree=0, trend_length=10, trend_length_unit='YS', min_trend_points=5)
caplog = <_pytest.logging.LogCaptureFixture object at 0x7f2a0d2dfc90>

    def test_calculate_boundary_trend_inner_right(
        test_ts, fit_params_linear, fit_params_constant, caplog
    ):
        gaps = get_gaps(test_ts)
    
        # linear trend for a right boundary
        fit_degree = 1
        # expected result
        data_to_interpolate = test_ts.pr.loc[{"time": slice("1956", "1965")}].data
        coeff = np.polyfit(range(0, 10), data_to_interpolate, deg=fit_degree)
        expected_value = np.polyval(coeff, 0)
    
        trend_value = calculate_boundary_trend_inner(
            test_ts,
            side="right",
            boundary=gaps[0].right,
            fit_params=fit_params_linear,
        )
    
        assert np.allclose(expected_value, trend_value, rtol=1e-04)
    
        # constant trend for a right boundary
        fit_degree = 0
        # expected result
        coeff = np.polyfit(range(0, 10), data_to_interpolate, deg=fit_degree)
        expected_value = np.polyval(coeff, 0)
    
        trend_value = calculate_boundary_trend_inner(
            test_ts,
            side="right",
            boundary=gaps[0].right,
            fit_params=fit_params_constant,
        )
    
        assert np.allclose(expected_value, trend_value, rtol=1e-04)
    
        # test logging if not enough data points
        test_ts.loc[{"time": slice("1958", "1964")}] = (test_ts.loc)[
            {"time": slice("1958", "1964")}
        ] * np.nan
        trend_value = calculate_boundary_trend_inner(
            test_ts,
            side="right",
            boundary=gaps[0].right,
            fit_params=fit_params_linear,
        )
        assert np.isnan(trend_value)
    
        log_str = (
            "Not enough values to calculate fit for right boundary at "
            "1956-01-01T00:00:00.000000000.\nfit_degree: 1, trend_length: 10, "
            "trend_length_unit: YS, min_trend_points: 5.\nTimeseries info: "
            "{'category': 'test'}"
        )
    
>       assert log_str in caplog.text
E       assert "Not enough values to calculate fit for right boundary at 1956-01-01T00:00:00.000000000.\nfit_degree: 1, trend_length: 10, trend_length_unit: YS, min_trend_points: 5.\nTimeseries info: {'category': 'test'}" in "INFO     primap2.csg._strategies.gaps:gaps.py:328 Not enough values to calculate fit for right boundary at 1956-01-01...t_degree: 1, trend_length: 10, trend_length_unit: YS, min_trend_points: 5.\nTimeseries info: {'category': 'test'} {}\n"
E        +  where "INFO     primap2.csg._strategies.gaps:gaps.py:328 Not enough values to calculate fit for right boundary at 1956-01-01...t_degree: 1, trend_length: 10, trend_length_unit: YS, min_trend_points: 5.\nTimeseries info: {'category': 'test'} {}\n" = <_pytest.logging.LogCaptureFixture object at 0x7f2a0d2dfc90>.text

.../tests/csg/test_gaps.py:310: AssertionError

primap2/tests/csg/test_gaps.py::test_calculate_scaling_factor

Flake rate in main: 82.76% (Passed 5 times, Failed 24 times)

Stack Traces | 0.095s run time

test_ts = <xarray.DataArray 'test_ts' (time: 74)> Size: 592B
array([        nan,         nan,         nan,         nan,  6.     ...Coordinates:
  * time      (time) datetime64[us] 592B 1952-01-01 1953-01-01 ... 2025-01-01
    category  <U4 16B 'test'
fill_ts = <xarray.DataArray 'test_ts' (time: 74)> Size: 592B
array([ 7.        ,  6.66666667,  6.33333333,  6.        , 18.     ...Coordinates:
  * time      (time) datetime64[us] 592B 1952-01-01 1953-01-01 ... 2025-01-01
    category  <U4 16B 'test'
fit_params_linear = FitParameters(fit_degree=1, fallback_degree=0, trend_length=10, trend_length_unit='YS', min_trend_points=5)
caplog = <_pytest.logging.LogCaptureFixture object at 0x7f2a0d4909d0>

    def test_calculate_scaling_factor(test_ts, fill_ts, fit_params_linear, caplog):
        gaps = get_gaps(test_ts)
    
        factor = calculate_scaling_factor(
            ts=test_ts, fill_ts=fill_ts, fit_params=fit_params_linear, gap=gaps[2]
        )
        assert np.allclose([0.33333, 1], factor)
        # as fallback will be used we also check for the log message (not strictly necessary
        # to test his as it's raise by a different function)
>       assert (
            "Not enough values to calculate fit for right boundary "
            "at 1973-01-01T00:00:00.000000000.\nfit_degree: 1, trend_length: 10, "
            "trend_length_unit: YS, min_trend_points: 5.\n"
            "Timeseries info: {'category': 'test'}" in caplog.text
        )
E       assert "Not enough values to calculate fit for right boundary at 1973-01-01T00:00:00.000000000.\nfit_degree: 1, trend_length: 10, trend_length_unit: YS, min_trend_points: 5.\nTimeseries info: {'category': 'test'}" in "INFO     primap2.csg._strategies.gaps:gaps.py:328 Not enough values to calculate fit for right boundary at 1973-01-01...t_degree: 1, trend_length: 10, trend_length_unit: YS, min_trend_points: 5.\nTimeseries info: {'category': 'test'} {}\n"
E        +  where "INFO     primap2.csg._strategies.gaps:gaps.py:328 Not enough values to calculate fit for right boundary at 1973-01-01...t_degree: 1, trend_length: 10, trend_length_unit: YS, min_trend_points: 5.\nTimeseries info: {'category': 'test'} {}\n" = <_pytest.logging.LogCaptureFixture object at 0x7f2a0d4909d0>.text

.../tests/csg/test_gaps.py:428: AssertionError

To view more test analytics, go to the Test Analytics Dashboard
_{📋 Got 3 mins? Take this short survey to help us improve Test Analytics.}