ruff fixes

econ-ark · Jul 2, 2024 · 6d62587 · 6d62587
1 parent e92e249
commit 6d62587
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Showing 3 changed files with 18 additions and 17 deletions.
diff --git a/HARK/distribution.py b/HARK/distribution.py
@@ -311,8 +311,8 @@ def __new__(
         mu: Union[float, np.ndarray] = 0.0,
         sigma: Union[float, np.ndarray] = 1.0,
         seed: Optional[int] = 0,
-        mean = None,
-        std = None
+        mean=None,
+        std=None,
     ):
         """
         Create a new Lognormal distribution. If sigma is zero, return a
@@ -348,8 +348,8 @@ def __init__(
         mu: Union[float, np.ndarray] = 0.0,
         sigma: Union[float, np.ndarray] = 1.0,
         seed: Optional[int] = 0,
-        mean = None,
-        std = None
+        mean=None,
+        std=None,
     ):
         if mean is not None and sigma is not None:
             mean_squared = mean**2

diff --git a/HARK/model.py b/HARK/model.py
@@ -77,6 +77,7 @@ def discretized_shock_dstn(shocks, disc_params):
 
     return all_shock_dstn
 
+
 def construct_shocks(shock_data, scope):
     """
     Returns a dictionary from shock labels to Distributions.
@@ -110,12 +111,14 @@ def construct_shocks(shock_data, scope):
         if isinstance(sd[v], tuple):
             dist_class = sd[v][0]
 
-            dist_args = sd[v][1] # should be a dictionary
+            dist_args = sd[v][1]  # should be a dictionary
 
             for a in dist_args:
                 if isinstance(dist_args[a], str):
                     arg_lambda = math_text_to_lambda(dist_args[a])
-                    arg_value = arg_lambda(*[scope[var] for var in signature(arg_lambda).parameters])
+                    arg_value = arg_lambda(
+                        *[scope[var] for var in signature(arg_lambda).parameters]
+                    )
 
                     dist_args[a] = arg_value
 
@@ -128,6 +131,7 @@ def construct_shocks(shock_data, scope):
 
     return sd
 
+
 def simulate_dynamics(
     dynamics: Mapping[str, Union[Callable, Control]],
     pre: Mapping[str, Any],

diff --git a/HARK/models/consumer.py b/HARK/models/consumer.py
@@ -16,17 +16,17 @@
     "LivPrb": 0.98,
     "PermGroFac": 1.01,
     "BoroCnstArt": None,
-    "TranShkStd" : 0.1,
-    "LivPrb" : 0.98,
-    "RiskyStd" : 0.1
+    "TranShkStd": 0.1,
+    "LivPrb": 0.98,
+    "RiskyStd": 0.1,
 }
 
 consumption_block = DBlock(
     **{
         "name": "consumption",
         "shocks": {
-            "live": (Bernoulli, {'p' : 'LivPrb'}),  # Move to tick or mortality block?
-            "theta": (MeanOneLogNormal, {'sigma' : 'TranShkStd'}),
+            "live": (Bernoulli, {"p": "LivPrb"}),  # Move to tick or mortality block?
+            "theta": (MeanOneLogNormal, {"sigma": "TranShkStd"}),
         },
         "dynamics": {
             "b": lambda k, R: k * R,
@@ -44,8 +44,8 @@
     **{
         "name": "consumption normalized",
         "shocks": {
-            "live": (Bernoulli, {"p" : "LivPrb"}),  # Move to tick or mortality block?
-            "theta": (MeanOneLogNormal, {"sigma" : "TranShkStd"}),
+            "live": (Bernoulli, {"p": "LivPrb"}),  # Move to tick or mortality block?
+            "theta": (MeanOneLogNormal, {"sigma": "TranShkStd"}),
         },
         "dynamics": {
             "b": lambda k, R, PermGroFac: k * R / PermGroFac,
@@ -61,10 +61,7 @@
     **{
         "name": "portfolio",
         "shocks": {
-            "risky_return": (Lognormal,{
-                "mean" : "Rfree + EqP",
-                "std" : "RiskyStd"
-            })
+            "risky_return": (Lognormal, {"mean": "Rfree + EqP", "std": "RiskyStd"})
         },
         "dynamics": {
             "stigma": Control(["a"]),