Simplify setting constructors at initialization

As is, setting a non-default constructor at instantiation is a little obnoxious, because the user has to deepcopy the constructor dictionary, change some entries, and then put the altered copy into their parameter dictionary.

This commit makes it much easier to set non-default constructor functions at initialization. The user *only* needs to put entries into params["constructors"] for the constructors they want to change; the others will use their default. If the user wants to turn off a constructor with a default, they can set that entry to None.

Author: mnwhite

HARK/ConsumptionSaving/ConsWealthPortfolioModel.py

@@ -38,13 +38,13 @@ class ChiFromOmegaFunction:
     A class for representing a function that takes in values of omega = EndOfPrdvP / aNrm
     and returns the corresponding optimal chi = cNrm / aNrm. The only parameters
     that matter for this transformation are the coefficient of relative risk
-    aversion rho and the share of wealth in the Cobb-Douglas aggregator delta.
+    aversion (rho) and the share of wealth in the Cobb-Douglas aggregator (delta).
 
     Parameters
     ----------
-    rho : float
+    CRRA : float
         Coefficient of relative risk aversion.
-    delta : float
+    WealthShare : float
         Share for wealth in the Cobb-Douglas aggregator in CRRA utility function.
     N : int, optional
         Number of interpolating gridpoints to use (default 501).
@@ -65,10 +65,9 @@ def f(self, x):
         """
         Define the relationship between chi and omega, and evaluate on the vector
         """
-        return x ** (1 - self.WealthShare) * (
-            (1 - self.WealthShare) * x ** (-self.WealthShare)
-            - self.WealthShare * x ** (1 - self.WealthShare)
-        ) ** (-1 / self.CRRA)
+        r = self.CRRA
+        d = self.WealthShare
+        return x ** (1 - d) * ((1 - d) * x ** (-d) - d * x ** (1 - d)) ** (-1 / r)
 
     def update(self):
         """

HARK/core.py

@@ -817,6 +817,12 @@ class AgentType(Model):
         Indicator for whether this instance's construct() method should be run
         when initialized (default True). When False, an instance of the class
         can be created even if not all of its attributes can be constructed.
+    use_defaults : bool
+        Indicator for whether this instance should use the values in the class'
+        default_ dictionary to fill in parameters and constructors for those not
+        provided by the user (default True). Setting this to False is useful for
+        situations where the user wants to be absolutely sure that they know what
+        is being passed to the class initializer, without resorting to defaults.
 
     Attributes
     ----------
@@ -844,11 +850,23 @@ def __init__(
         quiet=False,
         seed=0,
         construct=True,
+        use_defaults=True,
         **kwds,
     ):
         super().__init__()
-        params = deepcopy(self.default_["params"])
+        params = deepcopy(self.default_["params"]) if use_defaults else {}
         params.update(kwds)
+
+        # Correctly handle constructors that have been passed in kwds
+        if "constructors" in self.default_["params"].keys() and use_defaults:
+            constructors = deepcopy(self.default_["params"]["constructors"])
+        else:
+            constructors = {}
+        if "constructors" in kwds.keys():
+            constructors.update(kwds["constructors"])
+        params["constructors"] = constructors
+
+        # Set model file name if possible
         try:
             self.model_file = copy(self.default_["model"])
         except (KeyError, TypeError):

tests/ConsumptionSaving/test_ConsMarkovModel.py

@@ -64,7 +64,7 @@ def setUp(self):
         init_serial_unemployment["Rfree"] = [np.array([1.03, 1.03, 1.03, 1.03])]
         init_serial_unemployment["LivPrb"] = [np.array([0.98, 0.98, 0.98, 0.98])]
         init_serial_unemployment["PermGroFac"] = [np.array([1.01, 1.01, 1.01, 1.01])]
-        init_serial_unemployment["constructors"].pop("MrkvArray")
+        init_serial_unemployment["constructors"]["MrkvArray"] = None
 
         self.model = MarkovConsumerType(**init_serial_unemployment)
         self.model.cycles = 0