Remove default values from parameter distributions

Author: larsevj

src/ert/config/distribution.py

@@ -35,8 +35,8 @@ def get_min_param_count(cls) -> int:
 
 class UnifSettings(TransSettingsValidation):
     name: Literal["uniform"] = "uniform"
-    min: float = 0.0
-    max: float = 1.0
+    min: float
+    max: float
 
     @model_validator(mode="after")
     def valid_unif_params(self) -> Self:
@@ -55,8 +55,8 @@ def transform_numpy(self, x: np.ndarray) -> np.ndarray:
 
 class LogUnifSettings(TransSettingsValidation):
     name: Literal["logunif"] = "logunif"
-    min: float = 0.1
-    max: float = 1.0
+    min: float
+    max: float
 
     @model_validator(mode="after")
     def valid_logunif_params(self) -> Self:
@@ -88,9 +88,9 @@ def transform_numpy(self, x: np.ndarray) -> np.ndarray:
 
 class DUnifSettings(TransSettingsValidation):
     name: Literal["dunif"] = "dunif"
-    steps: int = 1000
-    min: float = 0.0
-    max: float = 1.0
+    steps: int
+    min: float
+    max: float
 
     @model_validator(mode="after")
     def valid_dunif_params(self) -> Self:
@@ -123,8 +123,8 @@ def transform_numpy(self, x: np.ndarray) -> np.ndarray:
 
 class NormalSettings(TransSettingsValidation):
     name: Literal["normal"] = "normal"
-    mean: float = 0.0
-    std: float = 1.0
+    mean: float
+    std: float
 
     @field_validator("std")
     @classmethod
@@ -139,8 +139,8 @@ def transform_numpy(self, x: np.ndarray) -> np.ndarray:
 
 class LogNormalSettings(TransSettingsValidation):
     name: Literal["lognormal"] = "lognormal"
-    mean: float = 0.0
-    std: float = 1.0
+    mean: float
+    std: float
 
     @field_validator("std")
     @classmethod
@@ -189,10 +189,10 @@ def transform_numpy(self, x: np.ndarray) -> np.ndarray:
 
 class TruncNormalSettings(TransSettingsValidation):
     name: Literal["truncated_normal"] = "truncated_normal"
-    mean: float = 0.0
-    std: float = 1.0
-    min: float = 0.0
-    max: float = 1.0
+    mean: float
+    std: float
+    min: float
+    max: float
 
     @field_validator("std")
     @classmethod
@@ -225,17 +225,17 @@ def transform_numpy(self, x: np.ndarray) -> np.ndarray:
 
 class ConstSettings(TransSettingsValidation):
     name: Literal["const"] = "const"
-    value: float = 0.0
+    value: float
 
     def transform_numpy(self, x: np.ndarray) -> np.ndarray:
         return np.full_like(x, self.value, dtype=np.float64)
 
 
 class TriangularSettings(TransSettingsValidation):
     name: Literal["triangular"] = "triangular"
-    min: float = 0.0
-    mode: float = 0.5
-    max: float = 1.0
+    min: float
+    mode: float
+    max: float
 
     @model_validator(mode="after")
     def valid_triangular_params(self) -> Self:
@@ -280,10 +280,10 @@ def transform_numpy(self, x: np.ndarray) -> np.ndarray:
 
 class ErrfSettings(TransSettingsValidation):
     name: Literal["errf"] = "errf"
-    min: float = 0.0
-    max: float = 1.0
-    skewness: float = 0.0
-    width: float = 1.0
+    min: float
+    max: float
+    skewness: float
+    width: float
 
     @field_validator("width")
     @classmethod
@@ -318,11 +318,11 @@ def transform_numpy(self, x: np.ndarray) -> np.ndarray:
 
 class DerrfSettings(TransSettingsValidation):
     name: Literal["derrf"] = "derrf"
-    steps: float = 1000.0
-    min: float = 0.0
-    max: float = 1.0
-    skewness: float = 0.0
-    width: float = 1.0
+    steps: float
+    min: float
+    max: float
+    skewness: float
+    width: float
 
     @model_validator(mode="after")
     def valid_derrf_params(self) -> Self:
@@ -388,9 +388,9 @@ class PertSettings(TransSettingsValidation):
     model_config = {"allow_inf_nan": False}
 
     name: Literal["pert"] = "pert"
-    min: float = 0.0
-    mode: float = 0.5
-    max: float = 1.0
+    min: float
+    mode: float
+    max: float
     scale: float = 4.0
 
     @classmethod