Change lmoments3 behaviour with fitkwargs

CHANGELOG.rst

@@ -4,12 +4,16 @@ Changelog
 
 v0.55.0 (unreleased)
 --------------------
-Contributors to this version: Juliette Lavoie (:user:`juliettelavoie`)
+Contributors to this version: Juliette Lavoie (:user:`juliettelavoie`), Éric Dupuis (:user:`coxipi`).
 
 New features and enhancements
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 * New function ``ensemble.partition.general_partition`` (:pull:`2035`)
 
+Internal changes
+^^^^^^^^^^^^^^^^
+* There is now a warning stating that `fitkwargs` are not employed when using `lmoments3` distribution. One exception is the use of `floc` which is allowed with the gamma distribution. `floc`  is used to shift the distribution before computing fitting parameters with the lmoments3 distribution since `loc=0` is always assumed in the library.  (:issue:`2043`, :pull:`2045`).
+
 v0.54.0 (2024-12-16)
 --------------------
 Contributors to this version: Trevor James Smith (:user:`Zeitsperre`), Pascal Bourgault (:user:`aulemahal`), Éric Dupuis (:user:`coxipi`), Sascha Hofmann (:user:`saschahofmann`).

src/xclim/indices/stats.py

@@ -59,6 +59,21 @@ def _fitfunc_1d(arr, *, dist, nparams, method, **fitkwargs):
         # lmoments3 will raise an error if only dist.numargs + 2 values are provided
         if len(x) <= dist.numargs + 2:
             return np.asarray([np.nan] * nparams)
+        if (type(dist).__name__ != "GammaGen" and len(fitkwargs.keys()) != 0) or (
+            type(dist).__name__ == "GammaGen"
+            and set(fitkwargs.keys()) - {"floc"} != set()
+        ):
+            warnings.warn(
+                "Lmoments3 does not use `fitkwargs` arguments, except for `floc` with the Gamma distribution."
+            )
+        if "floc" in fitkwargs and type(dist).__name__ == "GammaGen":
+            # lmoments3 assumes `loc` is 0, so `x` may need to be shifted
+            # note that `floc` must already be in appropriate units for `x`
+            params = dist.lmom_fit(x - fitkwargs["floc"])
+            params["loc"] = fitkwargs["floc"]
+            params = list(params.values())
+        else:
+            params = list(dist.lmom_fit(x).values())
         params = list(dist.lmom_fit(x).values())
     elif method == "APP":
         args, kwargs = _fit_start(x, dist.name, **fitkwargs)