Add formatting rules

promis/estimators/filters/extended_gmphd.py

@@ -22,7 +22,6 @@
 
 
 class ExtendedGaussianMixturePhd(GaussianMixturePhd):
-
     """The extended gaussian mixture PHD filter for non-linear multi-target tracking.
 
     The extended gaussian mixture PHD is a multi target tracker for non-linear state space models.

promis/estimators/filters/extended_kalman.py

@@ -23,7 +23,6 @@
 
 
 class ExtendedKalman:
-
     """The extended Kalman filter for non-linear state estimation.
 
     This filter behaves similarly to the standard Kalman filter, but utilizes nonlinear

promis/estimators/filters/gmphd.py

@@ -22,7 +22,6 @@
 
 
 class GaussianMixturePhd:
-
     """The gaussian mixture PHD filter for linear multi-target tracking.
 
     The gaussian mixture PHD filter is a multi target tracker for linear state space models.

promis/estimators/filters/kalman.py

@@ -23,7 +23,6 @@
 
 
 class Kalman:
-
     """The Kalman filter for linear state estimation.
 
     The Kalman filter is a single target tracker for linear state space models, i.e. models that

promis/estimators/filters/unscented_kalman.py

@@ -24,7 +24,6 @@
 
 
 class UnscentedKalman:
-
     """The unscented Kalman filter for non-linear state estimation.
 
     This filter behaves similarly to the standard Kalman filter, but utilizes the so-called

promis/estimators/smoothers/extended_rts.py

@@ -23,7 +23,6 @@
 
 
 class ExtendedRts(ExtendedKalman):
-
     """The Extended RTS smoother for non-linear state estimation.
 
     The Extended RTS smoother is a single target state estimator for non-linear

promis/estimators/smoothers/rts.py

@@ -23,7 +23,6 @@
 
 
 class Rts(Kalman):
-
     """The RTS smoother for linear state estimation.
 
     The RTS smoother is a state estimator for linear state space models, i.e. models that

promis/estimators/smoothers/unscented_rts.py

@@ -23,7 +23,6 @@
 
 
 class UnscentedRts(UnscentedKalman):
-
     """The unscented Kalman filter for non-linear state estimation.
 
     This filter behaves similarly to the standard Rts smoother, but utilizes the so-called

promis/geo/collection.py

@@ -76,7 +76,7 @@ def make_latin_hypercube(
         height: float,
         number_of_samples: int,
         number_of_values: int = 1,
-        include_corners: bool = False
+        include_corners: bool = False,
     ) -> "Collection":
         samples = LatinHypercube(d=2).random(n=number_of_samples)
         samples = scale(samples, [-width / 2, -height / 2], [width / 2, height / 2])
@@ -559,7 +559,6 @@ def to_cartesian(self) -> CartesianCollection:
 
 
 class HybridInterpolator:
-
     def __init__(self, coordinates, values):
         self.linear = LinearNDInterpolator(coordinates, values)
         self.nearest = NearestNDInterpolator(coordinates, values)

promis/geo/geospatial.py

@@ -19,7 +19,6 @@
 
 
 class Geospatial(ABC):
-
     """The common abstract base class for both polar and cartesian geospatial objects.
 
     See :meth:`~Geospatial.to_geo_json` on how this class can be used for visualizing geometries.
@@ -124,7 +123,7 @@ def to_geo_json(
             ),
         )
 
-    def send_to_gui(self, url: str ="http://localhost:8000/add_geojson", timeout: int = 1):
+    def send_to_gui(self, url: str = "http://localhost:8000/add_geojson", timeout: int = 1):
         """Send an HTTP POST-request to the GUI backend.
 
         Args:

promis/geo/helpers.py

@@ -68,7 +68,6 @@
 
 
 class Direction(float, Enum):
-
     """A simple collection of named "compass" bearings in degrees for self-documenting code."""
 
     NORTH = 0.0

promis/geo/location.py

@@ -408,7 +408,7 @@ def to_polar(self, origin: "PolarLocation | None" = None) -> PolarLocation:
     def distance(self, other: Any) -> float:
         return cast(float, self.geometry.distance(other.geometry))
 
-    def send_to_gui(self, url = "http://localhost:8000/add_geojson", timeout = 1):
+    def send_to_gui(self, url="http://localhost:8000/add_geojson", timeout=1):
         raise NotImplementedError("Cartesian Location does not have geospatial feature to send to gui!")
 
     def __repr__(self) -> str:

promis/geo/map.py

@@ -205,7 +205,7 @@ def to_cartesian(self) -> "CartesianMap":
 
         return CartesianMap(self.origin, cartesian_features)
 
-    def send_to_gui(self, url: str ="http://localhost:8000/add_geojson_map", timeout: int = 10):
+    def send_to_gui(self, url: str = "http://localhost:8000/add_geojson_map", timeout: int = 10):
         """Send an HTTP POST-request to the GUI backend to add all feature in the map to gui.
 
         Args:
@@ -221,12 +221,13 @@ def send_to_gui(self, url: str ="http://localhost:8000/add_geojson_map", timeout
         data = "["
         for feature in self.features:
             data += feature.to_geo_json()
-            data += ','
+            data += ","
         data = data[:-1]
-        data += ']'
+        data += "]"
         r = post(url=url, data=data, timeout=timeout)
         r.raise_for_status()
 
+
 class CartesianMap(Map):
     """A map containing geospatial objects based on local coordinates with a global reference point.
 

promis/geo/polygon.py

@@ -435,7 +435,7 @@ def plot(self, axis, **kwargs) -> None:
     def distance(self, other: Any) -> float:
         return self.geometry.distance(other.geometry)
 
-    def send_to_gui(self, url = "http://localhost:8000/add_geojson", timeout = 1):
+    def send_to_gui(self, url="http://localhost:8000/add_geojson", timeout=1):
         raise NotImplementedError("Cartesian Polygon does not have geospatial feature to send to gui!")
 
     def __repr__(self) -> str:

promis/geo/polyline.py

@@ -118,7 +118,6 @@ def to_numpy(self) -> ndarray:
 
 
 class PolarPolyLine(PolyLine):
-
     """A polyline (line string) based on WGS84 coordinates.
 
     Note:
@@ -211,7 +210,6 @@ def __repr__(self) -> str:
 
 
 class CartesianPolyLine(PolyLine):
-
     """A Cartesian polyline (line string) in local coordinates.
 
     Args:
@@ -316,7 +314,7 @@ def from_numpy(cls, data: ndarray, *args, **kwargs) -> "CartesianPolyLine":
     def distance(self, other: Any) -> float:
         return self.geometry.distance(other.geometry)
 
-    def send_to_gui(self, url = "http://localhost:8000/add_geojson", timeout = 1):
+    def send_to_gui(self, url="http://localhost:8000/add_geojson", timeout=1):
         raise NotImplementedError("Cartesian PolyLine does not have geospatial feature to send to gui!")
 
     def __repr__(self) -> str:

promis/geo/raster_band.py

@@ -97,7 +97,7 @@ def search_path(
         start: tuple[float, float],
         goal: tuple[float, float],
         cost_model: Callable[[float], float],
-        value_filter: Callable[[float], float]
+        value_filter: Callable[[float], float],
     ) -> NDArray:
         """Search the shortest path through this RasterBand using A*.
 
@@ -122,7 +122,7 @@ def heuristic(a, b):
             tuple(self.get_nearest_coordinate(start)),
             tuple(self.get_nearest_coordinate(goal)),
             heuristic=heuristic,
-            weight='weight'
+            weight="weight",
         )
 
         return array(path)

promis/loaders/osm_loader.py

@@ -28,7 +28,7 @@ def __init__(
         origin: PolarLocation,
         dimensions: tuple[float, float],
         feature_description: dict | None,
-        timeout: float = 5.0
+        timeout: float = 5.0,
     ):
         # Initialize Overpass API
         self.overpass_api = Overpass()

promis/logic/solver.py

@@ -17,7 +17,6 @@
 
 
 class Solver:
-
     """A solver for HPLP based ProMis.
 
     Args:

promis/logic/spatial/relation.py

@@ -241,10 +241,8 @@ def index_to_distributional_clause(self, index: int) -> str:
         else:
             relation = f"{self.problog_name}(x_{index}, {self.location_type})"
 
-        mean = self.parameters.data['v0'][index]
-        std = sqrt(clip(self.parameters.data['v1'][index], self.enforced_min_variance, None))
-        distribution = (
-            f"normal({mean}, {std})"
-        )
+        mean = self.parameters.data["v0"][index]
+        std = sqrt(clip(self.parameters.data["v1"][index], self.enforced_min_variance, None))
+        distribution = f"normal({mean}, {std})"
 
         return f"{relation} ~ {distribution}.\n"

promis/models/gaussian.py

@@ -17,7 +17,6 @@
 
 
 class Gaussian:
-
     """A weighted multivariate gaussian distribution.
 
     Examples:

promis/models/gaussian_mixture.py

@@ -20,7 +20,6 @@
 
 
 class GaussianMixture:
-
     """The Gaussian Mixture Model (GMM) for representing multi-modal probability distribution.
 
     Args:

promis/promis.py

@@ -141,7 +141,7 @@ def adaptive_solve(
         batch_size: int = 10,
         scaler: float = 10.0,
         interpolation_method: str = "linear",
-        acquisition_method: str = "entropy"
+        acquisition_method: str = "entropy",
     ):
         """Automatically add support points at locations where the uncertainty is high.
 

promis/star_map.py

@@ -184,7 +184,7 @@ def adaptive_sample(
         what: dict[str, Iterable[str | None]] | None = None,
         scaler: float = 10.0,
         value_index: int = 0,
-        acquisition_method: str = "entropy"
+        acquisition_method: str = "entropy",
     ):
         """Automatically add support points at locations where the uncertainty is high.
 
@@ -224,7 +224,7 @@ def value_function(points):
                     number_of_improvement_points=number_of_improvement_points,
                     scaler=scaler,
                     value_index=value_index,
-                    acquisition_method=acquisition_method
+                    acquisition_method=acquisition_method,
                 )
 
     def _make_r_trees(self, location_type: str, number_of_random_maps: int):
@@ -242,7 +242,7 @@ def _compute_parameters(
         relation: str,
         location_type: str,
         r_trees: list,
-        random_maps: list[CartesianMap]
+        random_maps: list[CartesianMap],
     ) -> NDArray:
         # Get the class of the spatial relation
         relation_class = self.relation_name_to_class(relation)
@@ -304,5 +304,5 @@ def sample(
                 # Update collection of sample points
                 self.relations[relation][location_type].parameters.append(
                     coordinates,
-                    self._compute_parameters(coordinates, relation, location_type, r_trees, random_maps)
+                    self._compute_parameters(coordinates, relation, location_type, r_trees, random_maps),
                 )

pyproject.toml

@@ -13,6 +13,14 @@ target-version = "py310"
 # GitLab CI code quality report
 output-format = "grouped" 
 
+[tool.ruff.format]
+
+# Quote style for strings: "single" or "double"
+quote-style = "double"
+
+# Automatically format docstrings
+docstring-code-format = false
+
 [tool.ruff.lint.pep8-naming]
 ignore-names = [
     "i",