Merge branch 'master' into i538

econ-ark · Apr 30, 2020 · e18813a · e18813a
2 parents 3c9c81a + 0bb26c5
commit e18813a
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Showing 12 changed files with 1,242 additions and 196 deletions.
diff --git a/.gitignore b/.gitignore
@@ -263,8 +263,9 @@ Web
 # Mac system files
 .DS_Store
 
-# Emacs automatic backup files
+# Emacs automatic backup and hash files
 *~
+\#*#
 
 # Vim swap files
 *.swp

diff --git a/HARK/ConsumptionSaving/ConsAggShockModel.py b/HARK/ConsumptionSaving/ConsAggShockModel.py
@@ -10,7 +10,7 @@
 from builtins import range
 import numpy as np
 import scipy.stats as stats
-from HARK.distribution import DiscreteDistribution, combineIndepDstns, approxMeanOneLognormal
+from HARK.distribution import DiscreteDistribution, combineIndepDstns, MeanOneLogNormal
 from HARK.interpolation import LinearInterp, LinearInterpOnInterp1D, ConstantFunction, IdentityFunction,\
                                VariableLowerBoundFunc2D, BilinearInterp, LowerEnvelope2D, UpperEnvelope
 from HARK.utilities import CRRAutility, CRRAutilityP, CRRAutilityPP, CRRAutilityP_inv,\
@@ -1095,8 +1095,12 @@ def makeAggShkDstn(self):
         -------
         None
         '''
-        self.TranShkAggDstn = approxMeanOneLognormal(sigma=self.TranShkAggStd, N=self.TranShkAggCount)
-        self.PermShkAggDstn = approxMeanOneLognormal(sigma=self.PermShkAggStd, N=self.PermShkAggCount)
+        self.TranShkAggDstn = MeanOneLogNormal(
+            sigma=self.TranShkAggStd
+        ).approx(N=self.TranShkAggCount)
+        self.PermShkAggDstn = MeanOneLognormal(
+            sigma=self.PermShkAggStd
+        ).approx(N=self.PermShkAggCount)
         self.AggShkDstn = combineIndepDstns(self.PermShkAggDstn, self.TranShkAggDstn)
 
     def reset(self):
@@ -1312,8 +1316,12 @@ def makeAggShkDstn(self):
         -------
         None
         '''
-        self.TranShkAggDstn = approxMeanOneLognormal(sigma=self.TranShkAggStd, N=self.TranShkAggCount)
-        self.PermShkAggDstn = approxMeanOneLognormal(sigma=self.PermShkAggStd, N=self.PermShkAggCount)
+        self.TranShkAggDstn = MeanOneLogNormal(
+            sigma=self.TranShkAggStd
+        ).approx(N=self.TranShkAggCount)
+        self.PermShkAggDstn = MeanOneLogNormal(
+            sigma=self.PermShkAggStd
+        ).approx(N=self.PermShkAggCount)
         self.AggShkDstn = combineIndepDstns(self.PermShkAggDstn, self.TranShkAggDstn)
 
     def millRule(self):
@@ -1526,8 +1534,8 @@ def makeAggShkDstn(self):
         StateCount = self.MrkvArray.shape[0]
 
         for i in range(StateCount):
-            TranShkAggDstn.append(approxMeanOneLognormal(sigma=self.TranShkAggStd[i], N=self.TranShkAggCount))
-            PermShkAggDstn.append(approxMeanOneLognormal(sigma=self.PermShkAggStd[i], N=self.PermShkAggCount))
+            TranShkAggDstn.append(MeanOneLogNormal(sigma=self.TranShkAggStd[i]).approx(N=self.TranShkAggCount))
+            PermShkAggDstn.append(MeanOneLogNormal(sigma=self.PermShkAggStd[i]).approx(N=self.PermShkAggCount))
             AggShkDstn.append(combineIndepDstns(PermShkAggDstn[-1], TranShkAggDstn[-1]))
 
         self.TranShkAggDstn = TranShkAggDstn

diff --git a/HARK/ConsumptionSaving/ConsIndShockModel.py b/HARK/ConsumptionSaving/ConsIndShockModel.py
@@ -24,8 +24,8 @@
 from HARK import AgentType, Solution, NullFunc, HARKobject
 from HARK.utilities import warnings  # Because of "patch" to warnings modules
 from HARK.interpolation import CubicInterp, LowerEnvelope, LinearInterp
-from HARK.distribution import Lognormal, Uniform
-from HARK.distribution import DiscreteDistribution, approxMeanOneLognormal, addDiscreteOutcomeConstantMean, combineIndepDstns 
+from HARK.distribution import Lognormal, MeanOneLogNormal, Uniform
+from HARK.distribution import DiscreteDistribution, addDiscreteOutcomeConstantMean, combineIndepDstns 
 from HARK.utilities import makeGridExpMult, CRRAutility, CRRAutilityP, \
                            CRRAutilityPP, CRRAutilityP_inv, CRRAutility_invP, CRRAutility_inv, \
                            CRRAutilityP_invP
@@ -2257,11 +2257,19 @@ def makeEulerErrorFunc(self,mMax=100,approx_inc_dstn=True):
         if approx_inc_dstn:
             IncomeDstn = self.IncomeDstn[0]
         else:
-            TranShkDstn = approxMeanOneLognormal(N=200,sigma=self.TranShkStd[0],
-                                                 tail_N=50,tail_order=1.3, tail_bound=[0.05,0.95])
+            TranShkDstn = MeanOneLognormal(
+                sigma=self.TranShkStd[0]
+            ).approx(N=200,
+                     tail_N=50,
+                     tail_order=1.3,
+                     tail_bound=[0.05,0.95])
             TranShkDstn = addDiscreteOutcomeConstantMean(TranShkDstn,self.UnempPrb,self.IncUnemp)
-            PermShkDstn = approxMeanOneLognormal(N=200,sigma=self.PermShkStd[0],
-                                                 tail_N=50,tail_order=1.3, tail_bound=[0.05,0.95])
+            PermShkDstn = MeanOneLogNormal(
+                sigma=self.PermShkStd[0]
+            ).approx(N=200,
+                     tail_N=50,
+                     tail_order=1.3,
+                     tail_bound=[0.05,0.95])
             IncomeDstn  = combineIndepDstns(PermShkDstn,TranShkDstn)
 
         # Make a grid of market resources
@@ -2634,10 +2642,16 @@ def constructLognormalIncomeProcessUnemployment(self):
                 TranShkDstn.append([ShkPrbsRet,TranShkValsRet])
             else:
                 # We are in the "working life" periods.
-                TranShkDstn_t    = approxMeanOneLognormal(N=TranShkCount, sigma=TranShkStd[t], tail_N=0)
+                TranShkDstn_t    = MeanOneLogNormal(
+                    sigma=TranShkStd[t] 
+                ).approx(TranShkCount, tail_N=0)
                 if UnempPrb > 0:
                     TranShkDstn_t = addDiscreteOutcomeConstantMean(TranShkDstn_t, p=UnempPrb, x=IncUnemp)
-                PermShkDstn_t    = approxMeanOneLognormal(N=PermShkCount, sigma=PermShkStd[t], tail_N=0)
+                PermShkDstn_t    = MeanOneLogNormal(
+                    sigma=PermShkStd[t]
+                ).approx(PermShkCount, tail_N=0)
+                ### REPLACE
+                ###REPLACE
                 IncomeDstn.append(combineIndepDstns(PermShkDstn_t,TranShkDstn_t)) # mix the independent distributions
                 PermShkDstn.append(PermShkDstn_t)
                 TranShkDstn.append(TranShkDstn_t)
@@ -2809,8 +2823,6 @@ def checkConditions(self,verbose=False):
         '''
         raise NotImplementedError()
 
-
-
 def applyFlatIncomeTax(IncomeDstn,tax_rate,T_retire,unemployed_indices=[],transitory_index=2):
     '''
     Applies a flat income tax rate to all employed income states during the working