add tests

src/xclim/indices/_agro.py

@@ -1145,7 +1145,7 @@ def standardized_precipitation_index(
         i.e. a monthly resampling, the window is an integer number of months.
     dist : {"gamma", "fisk"}
         Name of the univariate distribution. (see :py:mod:`scipy.stats`).
-    method : {"APP", "ML"}
+    method : {"APP", "ML", "PWM"}
         Name of the fitting method, such as `ML` (maximum likelihood), `APP` (approximate). The approximate method
         uses a deterministic function that does not involve any optimization.
     fitkwargs : dict, optional
@@ -1219,7 +1219,7 @@ def standardized_precipitation_index(
     >>> spi_3_fitted = standardized_precipitation_index(pr, params=params)
     """
     fitkwargs = fitkwargs or {}
-    dist_methods = {"gamma": ["ML", "APP"], "fisk": ["ML", "APP"]}
+    dist_methods = {"gamma": ["ML", "APP", "PWM"], "fisk": ["ML", "APP"]}
     if dist in dist_methods:
         if method not in dist_methods[dist]:
             raise NotImplementedError(
@@ -1313,7 +1313,7 @@ def standardized_precipitation_evapotranspiration_index(
     """
     fitkwargs = fitkwargs or {}
 
-    dist_methods = {"gamma": ["ML", "APP", "PWM"], "fisk": ["ML", "APP", "PWM"]}
+    dist_methods = {"gamma": ["ML", "APP", "PWM"], "fisk": ["ML", "APP"]}
     if dist in dist_methods:
         if method not in dist_methods[dist]:
             raise NotImplementedError(

src/xclim/indices/stats.py

@@ -808,7 +808,7 @@ def standardized_index_fit_params(
                 "Pass a value for `floc` in `fitkwargs`."
             )
 
-    dist_and_methods = {"gamma": ["ML", "APP"], "fisk": ["ML", "APP"]}
+    dist_and_methods = {"gamma": ["ML", "APP", "PWM"], "fisk": ["ML", "APP"]}
     dist = get_dist(dist)
     if dist.name not in dist_and_methods:
         raise NotImplementedError(f"The distribution `{dist.name}` is not supported.")

tests/test_indices.py

@@ -660,6 +660,38 @@ class TestStandardizedIndices:
                 [-1.08627775, -0.46491398, -0.77806462, 0.31759127, 0.03794528],
                 2e-2,
             ),
+            (
+                "D",
+                1,
+                "gamma",
+                "PWM",
+                [-0.13002, 1.346689, 0.965731, 0.245408, -0.427896],
+                2e-2,
+            ),
+            (
+                "D",
+                12,
+                "gamma",
+                "PWM",
+                [-0.209411, -0.086357, 0.636851, 1.022608, 0.634409],
+                2e-2,
+            ),
+            (
+                "MS",
+                1,
+                "gamma",
+                "PWM",
+                [1.364243, 1.478565, 1.915559, -3.055828, 0.905304],
+                2e-2,
+            ),
+            (
+                "MS",
+                12,
+                "gamma",
+                "PWM",
+                [0.577214, 1.522867, 1.634222, 0.967847, 0.689001],
+                2e-2,
+            ),
         ],
     )
     def test_standardized_precipitation_index(
@@ -671,6 +703,13 @@ def test_standardized_precipitation_index(
             and Version(__numpy_version__) < Version("2.0.0")
         ):
             pytest.skip("Skipping SPI/ML/D on older numpy")
+
+        # change `dist` to a lmoments3 object if needed
+        if method == "PWM":
+            lmom = pytest.importorskip("lmoments3.distr")
+            scipy2lmom = {"gamma": "gam"}
+            dist = getattr(lmom, scipy2lmom[dist])
+
         ds = open_dataset("sdba/CanESM2_1950-2100.nc").isel(location=1)
         if freq == "D":
             # to compare with ``climate_indices``
@@ -922,6 +961,42 @@ def test_zero_inflated(self, open_dataset):
             np.all(np.not_equal(spid[False].values, spid[True].values)), True
         )
 
+    def test_PWM_and_fitkwargs(self, open_dataset):
+        pr = (
+            open_dataset("sdba/CanESM2_1950-2100.nc")
+            .isel(location=1)
+            .sel(time=slice("1950", "1980"))
+        ).pr
+
+        lmom = pytest.importorskip("lmoments3.distr")
+        # for now, only one function used
+        scipy2lmom = {"gamma": "gam"}
+        dist = getattr(lmom, scipy2lmom["gamma"])
+        fitkwargs = {"floc": 0}
+        input_params = dict(
+            freq=None,
+            window=1,
+            method="PWM",
+            dist=dist,
+            fitkwargs=fitkwargs,
+            # doy_bounds=(180, 180),
+        )
+        # this should not cause a problem
+        params_d0 = xci.stats.standardized_index_fit_params(pr, **input_params).isel(
+            dayofyear=0
+        )
+        np.testing.assert_allclose(
+            params_d0, np.array([5.63e-01, 0, 3.37e-05]), rtol=0, atol=2e-2
+        )
+        # this should cause a problem
+        fitkwargs["fscale"] = 1
+        input_params["fitkwargs"] = fitkwargs
+        with pytest.raises(
+            ValueError,
+            match="Lmoments3 does not use `fitkwargs` arguments, except for `floc` with the Gamma distribution.",
+        ):
+            xci.stats.standardized_index_fit_params(pr, **input_params)
+
 
 class TestDailyFreezeThawCycles:
     @pytest.mark.parametrize(