bug fixes

src/caf/distribute/gravity_model/multi_area.py

@@ -93,16 +93,17 @@ class MultiDistInput(BaseConfig):
     furness_tolerance: float = 1e-6
     furness_jac: float = False
 
+
 @dataclass
 class GMCalibParams:
-    furness_jac: bool = False,
-    diff_step: float = 1e-8,
-    ftol: float = 1e-4,
-    xtol: float = 1e-4,
-    furness_tol=DEFAULT_FURNESS_TOL,
-    grav_max_iters: int = 100,
-    failure_tol: float = 0,
-    default_retry: bool = True,
+    furness_jac: bool = False
+    diff_step: float = 1e-8
+    ftol: float = 1e-4
+    xtol: float = 1e-4
+    furness_tol: float = DEFAULT_FURNESS_TOL
+    grav_max_iters: int = 100
+    failure_tol: float = 0
+    default_retry: bool = True
 
 
 @dataclass
@@ -429,7 +430,7 @@ def __init__(
             num_zeros = (data == 0).sum()  # casting bool as 1, 0
 
             LOG.info(
-                "There are %s 0s in %s (%s %)", num_zeros, name, (num_zeros / data.size) * 100
+                "There are %s 0s in %s (%s percent)", num_zeros, name, (num_zeros / data.size) * 100
             )
 
         zero_in_both = np.stack([row_targets == 0, col_targets == 0], axis=1).all(axis=1).sum()
@@ -498,7 +499,7 @@ def calibrate(
         self,
         distributions: MultiCostDistribution,
         running_log_path: Path,
-        gm_params: GMCalibParams, 
+        gm_params: GMCalibParams,
         verbose: int = 0,
         **kwargs,
     ) -> dict[str | int, GravityModelCalibrateResults]:
@@ -518,7 +519,7 @@ def calibrate(
         running_log_path: os.PathLike,
             path to a csv to log the model iterations and results
         gm_params: GMCalibParams
-            defines the detailed parameters, see `GMCalibParams` documentation for more info 
+            defines the detailed parameters, see `GMCalibParams` documentation for more info
         *args,
         **kwargs,
         Returns
@@ -533,7 +534,7 @@ def calibrate(
         `scipy.optimize.least_squares()`
         `caf.distribute.gravity_model.multi_area.GMCalibParams`
         """
-            
+
         self._validate_running_log(running_log_path)
         self._initialise_internal_params()
 
@@ -608,7 +609,9 @@ def calibrate(
         best_convergence = self.achieved_convergence
         best_params = result.x
 
-        if (not all(self.achieved_convergence) >= gm_params.failure_tol) and gm_params.default_retry:
+        if (
+            not all(self.achieved_convergence) >= gm_params.failure_tol
+        ) and gm_params.default_retry:
             LOG.info(
                 "%sachieved a convergence of %s, "
                 "however the failure tolerance is set to %s. Trying again with "