Bugfix release v0.23.1 (#517)

doc/conf.py

@@ -129,6 +129,7 @@
 
 # -- Generating references and publications lists -------------------------
 
+
 # support Round brackets
 def bracket_style() -> BracketStyle:
     return BracketStyle(

pastas/decorators.py

@@ -51,7 +51,7 @@ def _model_tmin_tmax(
         tmin: Optional[TimestampType] = None,
         tmax: Optional[TimestampType] = None,
         *args,
-        **kwargs
+        **kwargs,
     ):
         if tmin is None:
             tmin = self.ml.settings["tmin"]

pastas/model.py

@@ -95,7 +95,6 @@ def __init__(
         metadata: Optional[dict] = None,
         freq: str = "D",
     ) -> None:
-
         self.logger = getLogger(__name__)
 
         # Construct the different model components

pastas/modelplots.py

@@ -844,7 +844,6 @@ def custom_sort(t):
 
         # loop over axes showing stressmodel contributions
         for i, sm in zip(range(3, 3 + 2 * nsm, 2), self.ml.stressmodels.keys()):
-
             # Get the contributions for StressModels with multiple stresses
             contributions = []
             sml = self.ml.stressmodels[sm]

pastas/modelstats.py

@@ -79,7 +79,7 @@ def rmse(
         tmin: Optional[TimestampType] = None,
         tmax: Optional[TimestampType] = None,
         weighted: bool = False,
-        **kwargs
+        **kwargs,
     ) -> float:
         """Root mean squared error of the residuals.
 
@@ -104,7 +104,7 @@ def rmsn(
         tmin: Optional[TimestampType] = None,
         tmax: Optional[TimestampType] = None,
         weighted: bool = False,
-        **kwargs
+        **kwargs,
     ) -> float:
         """Root mean squared error of the noise.
 
@@ -155,7 +155,7 @@ def mae(
         tmin: Optional[TimestampType] = None,
         tmax: Optional[TimestampType] = None,
         weighted: bool = False,
-        **kwargs
+        **kwargs,
     ) -> float:
         """Mean Absolute Error (MAE) of the residuals.
 
@@ -180,7 +180,7 @@ def nse(
         tmin: Optional[TimestampType] = None,
         tmax: Optional[TimestampType] = None,
         weighted: bool = False,
-        **kwargs
+        **kwargs,
     ) -> float:
         """Nash-Sutcliffe coefficient for model fit .
 
@@ -206,7 +206,7 @@ def pearsonr(
         tmin: Optional[TimestampType] = None,
         tmax: Optional[TimestampType] = None,
         weighted: bool = False,
-        **kwargs
+        **kwargs,
     ) -> float:
         """Compute the (weighted) Pearson correlation (r).
 
@@ -232,7 +232,7 @@ def evp(
         tmin: Optional[TimestampType] = None,
         tmax: Optional[TimestampType] = None,
         weighted: bool = False,
-        **kwargs
+        **kwargs,
     ) -> float:
         """Explained variance percentage.
 
@@ -258,7 +258,7 @@ def rsq(
         tmin: Optional[TimestampType] = None,
         tmax: Optional[TimestampType] = None,
         weighted: bool = False,
-        **kwargs
+        **kwargs,
     ) -> float:
         """R-squared.
 
@@ -284,7 +284,7 @@ def kge_2012(
         tmin: Optional[TimestampType] = None,
         tmax: Optional[TimestampType] = None,
         weighted: bool = False,
-        **kwargs
+        **kwargs,
     ) -> float:
         """Kling-Gupta Efficiency.
 

pastas/plots.py

@@ -564,7 +564,6 @@ def __init__(
         tmax: Optional[TimestampType] = None,
         update_iter: Optional[int] = None,
     ) -> None:
-
         logger.warning(
             "TrackSolve feature under development. If you find any bugs please post "
             "an issue on GitHub: https://github.com/pastas/pastas/issues"

pastas/recharge.py

@@ -235,7 +235,7 @@ def simulate(
         p: ArrayLike,
         dt: float = 1.0,
         return_full: bool = False,
-        **kwargs
+        **kwargs,
     ) -> ArrayLike:
         """Simulate the soil water balance model.
 
@@ -498,7 +498,7 @@ def get_water_balance(
         temp: ArrayLike,
         p: ArrayLike,
         dt: float = 1.0,
-        **kwargs
+        **kwargs,
     ) -> DataFrame:
         data = self.simulate(
             prec=prec, evap=evap, temp=temp, p=p, dt=dt, return_full=True, **kwargs
@@ -611,7 +611,7 @@ def simulate(
         p: ArrayLike,
         dt: ArrayLike = 1.0,
         return_full: bool = False,
-        **kwargs
+        **kwargs,
     ) -> Union[ArrayLike, Tuple[ArrayLike, ArrayLike, ArrayLike, ArrayLike]]:
         """Simulate the recharge flux.
 
@@ -760,7 +760,7 @@ def simulate(
         p: ArrayLike,
         dt: float = 1.0,
         return_full: bool = False,
-        **kwargs
+        **kwargs,
     ) -> Union[ArrayLike, Tuple[ArrayLike, ArrayLike, ArrayLike, ArrayLike]]:
         """Simulate the recharge flux.
 

pastas/rfunc.py

@@ -1277,7 +1277,6 @@ def step(
         cutoff: Optional[float] = None,
         maxtmax: Optional[int] = None,
     ) -> ArrayLike:
-
         # Because Model.get_response_tmax() provides parameters for the stressmodel,
         # not only the response functions
         if len(p) > 4:
@@ -1293,7 +1292,6 @@ def step(
             return s
 
         else:
-
             t1 = -np.sqrt(3 / 5)
             t2 = 0
             t3 = np.sqrt(3 / 5)

pastas/solver.py

@@ -607,7 +607,6 @@ def solve(
         method: Optional[str] = "leastsq",
         **kwargs,
     ) -> Tuple[bool, ArrayLike, ArrayLike]:
-
         # Deal with the parameters
         parameters = lmfit.Parameters()
         p = self.ml.parameters.loc[:, ["initial", "pmin", "pmax", "vary"]]

pastas/stressmodels.py

@@ -719,7 +719,7 @@ def __init__(
 
             distances = np.sort(distances)
 
-        if settings is None or isinstance(settings, str):
+        if settings is None or isinstance(settings, str) or isinstance(settings, dict):
             settings = len(stress) * [settings]
 
         # convert stresses to TimeSeries if necessary

pyproject.toml

@@ -5,7 +5,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "pastas"
-version = "0.23.0"
+version = "0.23.1"
 description = "Pastas is an open-source Python framework for the analysis of groundwater time series."
 license = { file = "LICENSE" }
 readme = "README.rst"