Merge pull request #276 from primap-community/merge_logging_tests

Add tests for merge function logging

changelog/273.fix.md

@@ -0,0 +1 @@
+The function `nir_convert_df_to_long` now retains NaN values instead of removing them. This is more consistent with the rest of our data reading where we keep NaN values to check that everything has been processed.

changelog/276.improvement.md

@@ -0,0 +1 @@
+Added tests on log content and format for the `pr.merge()` function

primap2/_merge.py

@@ -105,7 +105,7 @@ def generate_log_message(da_error: xr.DataArray, tolerance: float) -> str:
     scalar_dims_str = ", ".join(scalar_dims_format)
     da_error_dequ = da_error.squeeze(drop=True).pint.dequantify()
     if np.ndim(da_error_dequ.data) == 0:
-        errors_str = str(da_error_dequ.data)
+        errors_str = f"{da_error_dequ.data:.2f}"
     else:
         errors_str = da_error_dequ.to_dataframe().dropna().to_string()
 

primap2/tests/test_merge.py

@@ -56,14 +56,17 @@ def test_merge_fail_tolerance(opulent_ds):
         da_start.pr.merge(da_merge, tolerance=0.01)
 
 
-def test_merge_fail_tolerance_warn(opulent_ds):
+def test_merge_fail_tolerance_warn(opulent_ds, caplog):
     da_start = opulent_ds["CO2"]
     data_to_modify = opulent_ds["CO2"].pr.loc[{"area": ["ARG"]}].pr.sum("area")
     data_to_modify.data = data_to_modify.data * 1.09
     da_merge = opulent_ds["CO2"].pr.set("area", "ARG", data_to_modify, existing="overwrite")
 
     da_result = da_start.pr.merge(da_merge, tolerance=0.01, error_on_discrepancy=False)
     assert_aligned_equal(da_result, da_start)
+    assert (
+        "pr.merge error: found discrepancies larger than tolerance " "(1.00%) for " in caplog.text
+    )
 
 
 def test_coords_not_matching_ds(opulent_ds):
@@ -198,3 +201,38 @@ def test_merge_message_time_daily(opulent_ds):
         match=r"found discrepancies larger than tolerance \(1\.00%\) for time=2000-01-02",
     ):
         da_start.pr.merge(da_merge)
+
+
+def test_log_formatting(minimal_ds, caplog):
+    da_start = minimal_ds["CO2"]
+    data_to_modify = (
+        minimal_ds["CO2"].pr.loc[{"area": ["ARG"], "time": ["2001", "2002"]}].pr.sum("area")
+    )
+    data_to_modify.data = data_to_modify.data * 1.09
+    da_merge = minimal_ds["CO2"].pr.set("area", "ARG", data_to_modify, existing="overwrite")
+
+    da_result = da_start.pr.merge(da_merge, tolerance=0.01, error_on_discrepancy=False)
+    assert_aligned_equal(da_result, da_start)
+    assert (
+        "pr.merge error: found discrepancies larger than tolerance (1.00%) "
+        "for area (ISO3)=ARG, source=RAND2020:" in caplog.text
+    )
+    assert (
+        "(CO2)\n             CO2\ntime            \n2001-01-01  0.09"
+        "\n2002-01-01  0.09" in caplog.text
+    )
+
+
+def test_log_formatting_single_date(minimal_ds, caplog):
+    da_start = minimal_ds["CO2"]
+    data_to_modify = minimal_ds["CO2"].pr.loc[{"area": ["ARG"], "time": ["2000"]}].pr.sum("area")
+    data_to_modify.data = data_to_modify.data * 1.09
+    da_merge = minimal_ds["CO2"].pr.set("area", "ARG", data_to_modify, existing="overwrite")
+
+    da_result = da_start.pr.merge(da_merge, tolerance=0.01, error_on_discrepancy=False)
+    assert_aligned_equal(da_result, da_start)
+    assert (
+        "pr.merge error: found discrepancies larger than tolerance (1.00%) "
+        "for time=2000, area (ISO3)=ARG, source=RAND2020:" in caplog.text
+    )
+    assert "(CO2)\n0.09" in caplog.text