From 98fd4a453397cfc8f37c758f486ef6471d203d5e Mon Sep 17 00:00:00 2001
From: sb <sbenthall@gmail.com>
Date: Tue, 21 Jul 2020 12:30:45 -0400
Subject: [PATCH 01/11] storing sow_var states and initial values in namespace

---
 HARK/ConsumptionSaving/ConsAggShockModel.py | 41 +++++++++++++++------
 HARK/core.py                                | 33 ++++++++++++-----
 2 files changed, 52 insertions(+), 22 deletions(-)

diff --git a/HARK/ConsumptionSaving/ConsAggShockModel.py b/HARK/ConsumptionSaving/ConsAggShockModel.py
index 701a9d580..d172345c5 100644
--- a/HARK/ConsumptionSaving/ConsAggShockModel.py
+++ b/HARK/ConsumptionSaving/ConsAggShockModel.py
@@ -988,11 +988,12 @@ def __init__(self,
         '''
         agents = agents if agents is not None else list()
         params = init_cobb_douglas.copy()
+        params['sow_vars'] = ['MaggNow', 'AaggNow', 'RfreeNow',
+                              'wRteNow', 'PermShkAggNow',
+                              'TranShkAggNow', 'KtoLnow']
         params.update(kwds)
 
         Market.__init__(self, agents=agents,
-                        sow_vars=['MaggNow', 'AaggNow', 'RfreeNow',
-                                  'wRteNow', 'PermShkAggNow', 'TranShkAggNow', 'KtoLnow'],
                         reap_vars=['aLvlNow', 'pLvlNow'],
                         track_vars=['MaggNow', 'AaggNow'],
                         dyn_vars=['AFunc'],
@@ -1053,13 +1054,14 @@ def update(self):
         self.convertKtoY = lambda KtoY: KtoY**(1.0/(1.0 - self.CapShare))  # converts K/Y to K/L
         self.Rfunc = lambda k: (1.0 + self.CapShare*k**(self.CapShare-1.0) - self.DeprFac)
         self.wFunc = lambda k: ((1.0-self.CapShare)*k**(self.CapShare))
-        self.KtoLnow_init = self.kSS
-        self.MaggNow_init = self.kSS
-        self.AaggNow_init = self.kSS
-        self.RfreeNow_init = self.Rfunc(self.kSS)
-        self.wRteNow_init = self.wFunc(self.kSS)
-        self.PermShkAggNow_init = 1.0
-        self.TranShkAggNow_init = 1.0
+
+        self.sow_init['KtoLnow'] = self.kSS
+        self.sow_init['MaggNow'] = self.kSS
+        self.sow_init['AaggNow'] = self.kSS
+        self.sow_init['RfreeNow'] = self.Rfunc(self.kSS)
+        self.sow_init['wRteNow'] = self.wFunc(self.kSS)
+        self.sow_init['PermShkAggNow'] = 1.0
+        self.sow_init['TranShkAggNow'] = 1.0
         self.makeAggShkDstn()
         self.AFunc = AggregateSavingRule(self.intercept_prev, self.slope_prev)
 
@@ -1436,6 +1438,15 @@ def __init__(self,
                  agents=None,
                  tolerance=0.0001,
                  act_T=1200,
+                 sow_vars=['MaggNow',
+                           'AaggNow',
+                           'RfreeNow',
+                           'wRteNow',
+                           'PermShkAggNow',
+                           'TranShkAggNow',
+                           'KtoLnow',
+                           'MrkvNow' # This one is new
+                 ],
                  **kwds):
         '''
         Make a new instance of CobbDouglasMarkovEconomy by filling in attributes
@@ -1460,8 +1471,14 @@ def __init__(self,
         params = init_mrkv_cobb_douglas.copy()
         params.update(kwds)
 
-        CobbDouglasEconomy.__init__(self, agents=agents, tolerance=tolerance, act_T=act_T, **params)
-        self.sow_vars.append('MrkvNow')
+        CobbDouglasEconomy.__init__(self,
+                                    agents=agents,
+                                    tolerance=tolerance,
+                                    act_T=act_T,
+                                    sow_vars = sow_vars,
+                                    **params)
+
+        self.sow_init['MrkvNow'] = params['MrkvNow_init']
 
     def update(self):
         '''
@@ -1622,7 +1639,7 @@ def makeMrkvHist(self):
         cutoffs = np.cumsum(self.MrkvArray, axis=1)
         loops = 0
         go = True
-        MrkvNow = self.MrkvNow_init
+        MrkvNow = self.sow_init['MrkvNow']
         t = 0
         StateCount = self.MrkvArray.shape[0]
 
diff --git a/HARK/core.py b/HARK/core.py
index 269f8b926..3538b1765 100644
--- a/HARK/core.py
+++ b/HARK/core.py
@@ -12,6 +12,7 @@
 from builtins import str
 from builtins import range
 from builtins import object
+from collections import OrderedDict
 import sys
 import os
 from distutils.dir_util import copy_tree
@@ -944,6 +945,15 @@ def __init__(self, agents=None, sow_vars=None, reap_vars=None, const_vars=None,
         # "solveAgents" one time. If set to false, the error will never
         # print. See "solveAgents" for why this prints once or never.
 
+        # dictionaries for tracking initial and current values
+        # of the sow variables.
+        self.sow_init = OrderedDict({sow : None
+                                     for sow
+                                     in self.sow_vars})
+        self.sow_state = OrderedDict({sow: None
+                                      for sow
+                                      in self.sow_vars})
+
     def solveAgents(self):
         '''
         Solves the microeconomic problem for all AgentTypes in this market.
@@ -1037,10 +1047,11 @@ def sow(self):
         -------
         none
         '''
-        for var_name in self.sow_vars:
-            this_seed = getattr(self, var_name)
+        for sow_var in self.sow_state:
             for this_type in self.agents:
-                setattr(this_type, var_name, this_seed)
+                setattr(this_type,
+                        sow_var,
+                        self.sow_state[sow_var])
 
     def mill(self):
         '''
@@ -1066,10 +1077,10 @@ def mill(self):
 
         # Run the millRule and store its output in self
         product = self.millRule(**mill_dict)
-        for j in range(len(self.sow_vars)):
-            this_var = self.sow_vars[j]
-            this_product = getattr(product, this_var)
-            setattr(self, this_var, this_product)
+
+        for sow_var in self.sow_state:
+            this_product = getattr(product, sow_var)
+            self.sow_state[sow_var] = this_product
 
     def cultivate(self):
         '''
@@ -1105,8 +1116,7 @@ def reset(self):
         for var_name in self.track_vars:  # Reset the history of tracked variables
             self.history[var_name] = []
         for var_name in self.sow_vars:  # Set the sow variables to their initial levels
-            initial_val = getattr(self, var_name + '_init')
-            setattr(self, var_name, initial_val)
+            self.sow_state[var_name] = self.sow_init[var_name]
         for this_type in self.agents:  # Reset each AgentType in the market
             this_type.reset()
 
@@ -1124,7 +1134,10 @@ def store(self):
         none
         '''
         for var_name in self.track_vars:
-            value_now = getattr(self, var_name)
+            try:
+                value_now = getattr(self, var_name)
+            except:
+                value_now = self.sow_state[var_name]
             self.history[var_name].append(value_now)
 
     def makeHistory(self):

From fabec0cfd20d90d44279838d5257cb42f5466299 Mon Sep 17 00:00:00 2001
From: sb <sbenthall@gmail.com>
Date: Wed, 22 Jul 2020 14:13:31 -0400
Subject: [PATCH 02/11] updates to KS model to fit market refactoring

---
 HARK/ConsumptionSaving/ConsAggShockModel.py | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/HARK/ConsumptionSaving/ConsAggShockModel.py b/HARK/ConsumptionSaving/ConsAggShockModel.py
index db8da7aa9..a4285805b 100644
--- a/HARK/ConsumptionSaving/ConsAggShockModel.py
+++ b/HARK/ConsumptionSaving/ConsAggShockModel.py
@@ -616,7 +616,7 @@ def getEconomyData(self, Economy):
         '''
         self.T_sim = Economy.act_T                   # Need to be able to track as many periods as economy runs
         self.kInit = Economy.KSS                     # Initialize simulation assets to steady state
-        self.MrkvInit = Economy.MrkvNow_init         # Starting Markov state for the macroeconomy
+        self.MrkvInit = Economy.sow_init['MrkvNow']  # Starting Markov state for the macroeconomy
         self.Mgrid = Economy.MSS*self.MgridBase      # Aggregate market resources grid adjusted around SS capital ratio
         self.AFunc = Economy.AFunc                   # Next period's aggregate savings function
         self.DeprFac = Economy.DeprFac               # Rate of capital depreciation
@@ -2264,14 +2264,14 @@ def update(self):
         self.convertKtoY = lambda KtoY: KtoY**(1.0/(1.0 - self.CapShare))  # converts K/Y to K/L
         self.rFunc = lambda k: self.CapShare*k**(self.CapShare-1.0)
         self.Wfunc = lambda k: ((1.0-self.CapShare)*k**(self.CapShare))
-        self.KtoLnow_init = self.KtoLSS
-        self.Mnow_init = self.MSS
-        self.Aprev_init = self.KSS
-        self.Rnow_init = self.RSS
-        self.Wnow_init = self.WSS
+        self.sow_init['KtoLnow'] = self.KtoLSS
+        self.sow_init['Mnow'] = self.MSS
+        self.sow_init['Aprev'] = self.KSS
+        self.sow_init['Rnow'] = self.RSS
+        self.sow_init['Wnow'] = self.WSS
         self.PermShkAggNow_init = 1.0
         self.TranShkAggNow_init = 1.0
-        self.Mrkv_init = 0
+        self.sow_init['MrkvNow'] = 0
         self.makeMrkvArray()
         
     def reset(self):

From 15682cd91c1aaa5ffe58afb2bdcc6d5b08f7f495 Mon Sep 17 00:00:00 2001
From: sb <sbenthall@gmail.com>
Date: Wed, 22 Jul 2020 15:26:33 -0400
Subject: [PATCH 03/11] update SmallOpenEconomy

---
 HARK/ConsumptionSaving/ConsAggShockModel.py | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/HARK/ConsumptionSaving/ConsAggShockModel.py b/HARK/ConsumptionSaving/ConsAggShockModel.py
index 0fbc63a17..018d35591 100644
--- a/HARK/ConsumptionSaving/ConsAggShockModel.py
+++ b/HARK/ConsumptionSaving/ConsAggShockModel.py
@@ -1680,12 +1680,12 @@ def update(self):
         self.KtoLnow_init = self.kSS
         self.Rfunc = ConstantFunction(self.Rfree)
         self.wFunc = ConstantFunction(self.wRte)
-        self.RfreeNow_init = self.Rfunc(self.kSS)
-        self.wRteNow_init = self.wFunc(self.kSS)
-        self.MaggNow_init = self.kSS
-        self.AaggNow_init = self.kSS
-        self.PermShkAggNow_init = 1.0
-        self.TranShkAggNow_init = 1.0
+        self.sow_init['RfreeNow'] = self.Rfunc(self.kSS)
+        self.sow_init['wRteNow'] = self.wFunc(self.kSS)
+        self.sow_init['MaggNow'] = self.kSS
+        self.sow_init['AaggNow'] = self.kSS
+        self.sow_init['PermShkAggNow'] = 1.0
+        self.sow_init['TranShkAggNow'] = 1.0
         self.makeAggShkDstn()
         self.AFunc = ConstantFunction(1.0)
 

From 7444dc5957c2bbe9df0d0d0fa4329dad8e1102cd Mon Sep 17 00:00:00 2001
From: sb <sbenthall@gmail.com>
Date: Wed, 22 Jul 2020 16:36:28 -0400
Subject: [PATCH 04/11] const_vars now in dictionary

---
 HARK/core.py | 19 ++++++++-----------
 1 file changed, 8 insertions(+), 11 deletions(-)

diff --git a/HARK/core.py b/HARK/core.py
index 53f9a63f9..93ff4ebf5 100644
--- a/HARK/core.py
+++ b/HARK/core.py
@@ -929,7 +929,9 @@ def __init__(self, agents=None, sow_vars=None, reap_vars=None, const_vars=None,
         self.agents     = agents if agents is not None else list() # NOQA
         self.reap_vars  = reap_vars if reap_vars is not None else list() # NOQA
         self.sow_vars   = sow_vars if sow_vars is not None else list() # NOQA
-        self.const_vars = const_vars if const_vars is not None else list() # NOQA
+
+        const_vars = const_vars if const_vars is not None else list() # NOQA
+        self.const_vars =  OrderedDict([(var, None) for var in const_vars])
         self.track_vars = track_vars if track_vars is not None else list() # NOQA
         self.dyn_vars   = dyn_vars if dyn_vars is not None else list() # NOQA
         if millRule is not None:  # To prevent overwriting of method-based millRules
@@ -949,12 +951,8 @@ def __init__(self, agents=None, sow_vars=None, reap_vars=None, const_vars=None,
 
         # dictionaries for tracking initial and current values
         # of the sow variables.
-        self.sow_init = OrderedDict({sow : None
-                                     for sow
-                                     in self.sow_vars})
-        self.sow_state = OrderedDict({sow: None
-                                      for sow
-                                      in self.sow_vars})
+        self.sow_init = OrderedDict([(var, None) for var in self.sow_vars])
+        self.sow_state = OrderedDict([(var, None) for var in self.sow_vars])
 
     def solveAgents(self):
         '''
@@ -1072,10 +1070,9 @@ def mill(self):
         reap_vars_string = ''
         for name in self.reap_vars:
             reap_vars_string += ' \'' + name + '\' : self.' + name + ','
-        const_vars_string = ''
-        for name in self.const_vars:
-            const_vars_string += ' \'' + name + '\' : self.' + name + ','
-        mill_dict = eval('{' + reap_vars_string + const_vars_string + '}')
+
+        mill_dict = eval('{' + reap_vars_string + '}')
+        mill_dict.update(self.const_vars)
 
         # Run the millRule and store its output in self
         product = self.millRule(**mill_dict)

From e6f1022738d0503848c14f36b4d49a8afd170e23 Mon Sep 17 00:00:00 2001
From: sb <sbenthall@gmail.com>
Date: Wed, 22 Jul 2020 22:28:05 -0400
Subject: [PATCH 05/11] reap variables to dictionary

---
 HARK/core.py | 13 ++++++-------
 1 file changed, 6 insertions(+), 7 deletions(-)

diff --git a/HARK/core.py b/HARK/core.py
index 93ff4ebf5..75c9d286c 100644
--- a/HARK/core.py
+++ b/HARK/core.py
@@ -927,7 +927,10 @@ def __init__(self, agents=None, sow_vars=None, reap_vars=None, const_vars=None,
         None
     '''
         self.agents     = agents if agents is not None else list() # NOQA
-        self.reap_vars  = reap_vars if reap_vars is not None else list() # NOQA
+
+        reap_vars = reap_vars if reap_vars is not None else list() # NOQA
+        self.reap_vars  = OrderedDict([(var, []) for var in reap_vars])
+
         self.sow_vars   = sow_vars if sow_vars is not None else list() # NOQA
 
         const_vars = const_vars if const_vars is not None else list() # NOQA
@@ -1032,7 +1035,7 @@ def reap(self):
             harvest = []
             for this_type in self.agents:
                 harvest.append(getattr(this_type, var_name))
-            setattr(self, var_name, harvest)
+            self.reap_vars[var_name] = harvest
 
     def sow(self):
         '''
@@ -1067,11 +1070,7 @@ def mill(self):
         none
         '''
         # Make a dictionary of inputs for the millRule
-        reap_vars_string = ''
-        for name in self.reap_vars:
-            reap_vars_string += ' \'' + name + '\' : self.' + name + ','
-
-        mill_dict = eval('{' + reap_vars_string + '}')
+        mill_dict = copy(self.reap_vars)
         mill_dict.update(self.const_vars)
 
         # Run the millRule and store its output in self

From 0ef77f717ad0c80da72b88158b90abf2ff669648 Mon Sep 17 00:00:00 2001
From: sb <sbenthall@gmail.com>
Date: Wed, 22 Jul 2020 22:53:16 -0400
Subject: [PATCH 06/11] collect sow var dicts in with sow vars

---
 HARK/core.py | 11 +++++++----
 1 file changed, 7 insertions(+), 4 deletions(-)

diff --git a/HARK/core.py b/HARK/core.py
index 75c9d286c..c45706cf3 100644
--- a/HARK/core.py
+++ b/HARK/core.py
@@ -932,11 +932,18 @@ def __init__(self, agents=None, sow_vars=None, reap_vars=None, const_vars=None,
         self.reap_vars  = OrderedDict([(var, []) for var in reap_vars])
 
         self.sow_vars   = sow_vars if sow_vars is not None else list() # NOQA
+        # dictionaries for tracking initial and current values
+        # of the sow variables.
+        self.sow_init = OrderedDict([(var, None) for var in self.sow_vars])
+        self.sow_state = OrderedDict([(var, None) for var in self.sow_vars])
 
         const_vars = const_vars if const_vars is not None else list() # NOQA
         self.const_vars =  OrderedDict([(var, None) for var in const_vars])
+
+        ## TODO: track_vars handling is not right
         self.track_vars = track_vars if track_vars is not None else list() # NOQA
         self.dyn_vars   = dyn_vars if dyn_vars is not None else list() # NOQA
+
         if millRule is not None:  # To prevent overwriting of method-based millRules
             self.millRule = millRule
         if calcDynamics is not None:  # Ditto for calcDynamics
@@ -952,10 +959,6 @@ def __init__(self, agents=None, sow_vars=None, reap_vars=None, const_vars=None,
         # "solveAgents" one time. If set to false, the error will never
         # print. See "solveAgents" for why this prints once or never.
 
-        # dictionaries for tracking initial and current values
-        # of the sow variables.
-        self.sow_init = OrderedDict([(var, None) for var in self.sow_vars])
-        self.sow_state = OrderedDict([(var, None) for var in self.sow_vars])
 
     def solveAgents(self):
         '''

From b7b91abc08dd193d4a75d7fe69cabc8dd23d70ba Mon Sep 17 00:00:00 2001
From: sb <sbenthall@gmail.com>
Date: Thu, 23 Jul 2020 12:59:49 -0400
Subject: [PATCH 07/11] adding ConsAggShockModel tests for Market history
 tracking

---
 .../tests/test_ConsAggShockModel.py            | 18 +++++++++++++++++-
 1 file changed, 17 insertions(+), 1 deletion(-)

diff --git a/HARK/ConsumptionSaving/tests/test_ConsAggShockModel.py b/HARK/ConsumptionSaving/tests/test_ConsAggShockModel.py
index 62b65b732..70c615ed1 100644
--- a/HARK/ConsumptionSaving/tests/test_ConsAggShockModel.py
+++ b/HARK/ConsumptionSaving/tests/test_ConsAggShockModel.py
@@ -48,6 +48,9 @@ def test_macro(self):
         self.assertAlmostEqual(self.economy.AFunc.slope,
                                1.116259456228145)
 
+        self.assertAlmostEqual(self.economy.history['MaggNow'][10],
+                               7.456324335623432)
+
 
 class testAggShockMarkovConsumerType(unittest.TestCase):
 
@@ -81,7 +84,10 @@ def test_economy(self):
         self.economy.AFunc = self.economy.dynamics.AFunc
         self.assertAlmostEqual(self.economy.AFunc[0].slope,
                                1.0904698841958917)
-        
+
+        self.assertAlmostEqual(self.economy.history['AaggNow'][5],
+                               9.467758924955897)
+
         
 class testKrusellSmith(unittest.TestCase):
 
@@ -110,3 +116,13 @@ def test_economy(self):
         self.economy.AFunc = self.economy.dynamics.AFunc
         self.assertAlmostEqual(self.economy.AFunc[0].slope,
                                1.0014463644834282)
+
+        self.assertAlmostEqual(self.economy.history['Aprev'][4],
+                               11.009107526443584)
+
+        self.assertAlmostEqual(self.economy.history['MrkvNow'][40],
+                               1
+        )
+
+        self.assertAlmostEqual(self.economy.history['Urate'][12],
+                               0.040000000000000036)

From 7b78cd78a46a0a8f45ddfce821ea81519fba6c67 Mon Sep 17 00:00:00 2001
From: sb <sbenthall@gmail.com>
Date: Thu, 23 Jul 2020 13:32:57 -0400
Subject: [PATCH 08/11] fixing trak_vars

---
 HARK/core.py | 38 +++++++++++++++++++++++---------------
 1 file changed, 23 insertions(+), 15 deletions(-)

diff --git a/HARK/core.py b/HARK/core.py
index c45706cf3..4d8168c84 100644
--- a/HARK/core.py
+++ b/HARK/core.py
@@ -929,7 +929,7 @@ def __init__(self, agents=None, sow_vars=None, reap_vars=None, const_vars=None,
         self.agents     = agents if agents is not None else list() # NOQA
 
         reap_vars = reap_vars if reap_vars is not None else list() # NOQA
-        self.reap_vars  = OrderedDict([(var, []) for var in reap_vars])
+        self.reap_state  = OrderedDict([(var, []) for var in reap_vars])
 
         self.sow_vars   = sow_vars if sow_vars is not None else list() # NOQA
         # dictionaries for tracking initial and current values
@@ -940,7 +940,6 @@ def __init__(self, agents=None, sow_vars=None, reap_vars=None, const_vars=None,
         const_vars = const_vars if const_vars is not None else list() # NOQA
         self.const_vars =  OrderedDict([(var, None) for var in const_vars])
 
-        ## TODO: track_vars handling is not right
         self.track_vars = track_vars if track_vars is not None else list() # NOQA
         self.dyn_vars   = dyn_vars if dyn_vars is not None else list() # NOQA
 
@@ -1034,11 +1033,11 @@ def reap(self):
         -------
         none
         '''
-        for var_name in self.reap_vars:
-            harvest = []
-            for this_type in self.agents:
-                harvest.append(getattr(this_type, var_name))
-            self.reap_vars[var_name] = harvest
+        for var_name in self.reap_state:
+            harvest = [getattr(this_type, var_name)
+                       for this_type
+                       in self.agents]
+            self.reap_state[var_name] = harvest
 
     def sow(self):
         '''
@@ -1073,7 +1072,7 @@ def mill(self):
         none
         '''
         # Make a dictionary of inputs for the millRule
-        mill_dict = copy(self.reap_vars)
+        mill_dict = copy(self.reap_state)
         mill_dict.update(self.const_vars)
 
         # Run the millRule and store its output in self
@@ -1114,11 +1113,15 @@ def reset(self):
         -------
         none
         '''
-        for var_name in self.track_vars:  # Reset the history of tracked variables
-            self.history[var_name] = []
-        for var_name in self.sow_vars:  # Set the sow variables to their initial levels
+        # Reset the history of tracked variables
+        self.history = {var_name : [] for var_name in self.track_vars}
+
+        # Set the sow variables to their initial levels
+        for var_name in self.sow_state:  
             self.sow_state[var_name] = self.sow_init[var_name]
-        for this_type in self.agents:  # Reset each AgentType in the market
+
+        # Reset each AgentType in the market
+        for this_type in self.agents:
             this_type.reset()
 
     def store(self):
@@ -1135,10 +1138,15 @@ def store(self):
         none
         '''
         for var_name in self.track_vars:
-            try:
-                value_now = getattr(self, var_name)
-            except:
+            if var_name in self.sow_state:
                 value_now = self.sow_state[var_name]
+            elif var_name in self.reap_state:
+                value_now = self.reap_state[var_name]
+            elif var_name in self.const_vars:
+                value_now = self.const_vars[var_name]
+            else:
+                value_now = getattr(self, var_name)
+    
             self.history[var_name].append(value_now)
 
     def makeHistory(self):

From 2220fa5787916491dfc2d203dbb9877a3918b2a8 Mon Sep 17 00:00:00 2001
From: sb <sbenthall@gmail.com>
Date: Thu, 23 Jul 2020 16:12:37 -0400
Subject: [PATCH 09/11] millRule returning a tuple of values same size/order as
 sow_vars

---
 HARK/ConsumptionSaving/ConsAggShockModel.py | 175 +++++++++-----------
 HARK/core.py                                |  12 +-
 2 files changed, 82 insertions(+), 105 deletions(-)

diff --git a/HARK/ConsumptionSaving/ConsAggShockModel.py b/HARK/ConsumptionSaving/ConsAggShockModel.py
index 018d35591..169c0710f 100644
--- a/HARK/ConsumptionSaving/ConsAggShockModel.py
+++ b/HARK/ConsumptionSaving/ConsAggShockModel.py
@@ -24,7 +24,7 @@
 
 __all__ = ['MargValueFunc2D', 'AggShockConsumerType', 'AggShockMarkovConsumerType',
 'CobbDouglasEconomy', 'SmallOpenEconomy', 'CobbDouglasMarkovEconomy',
-           'SmallOpenMarkovEconomy', 'CobbDouglasAggVars', 'AggregateSavingRule', 'AggShocksDynamicRule','init_agg_shocks','init_agg_mrkv_shocks', 'init_cobb_douglas','init_mrkv_cobb_douglas']
+           'SmallOpenMarkovEconomy', 'AggregateSavingRule', 'AggShocksDynamicRule','init_agg_shocks','init_agg_mrkv_shocks', 'init_cobb_douglas','init_mrkv_cobb_douglas']
 
 utility = CRRAutility
 utilityP = CRRAutilityP
@@ -818,7 +818,7 @@ def getShocks(self):
         # Get boolean arrays for current employment states
         employed = self.EmpNow.copy()
         unemployed = np.logical_not(employed)
-        
+
         # Transition some agents between unemployment and employment
         emp_permute = self.emp_permute[self.MrkvPrev][self.MrkvNow]
         unemp_permute = self.unemp_permute[self.MrkvPrev][self.MrkvNow]
@@ -1547,10 +1547,20 @@ def calcRandW(self, aLvlNow, pLvlNow):
 
         Returns
         -------
-        AggVarsNow : CobbDouglasAggVars
-            An object containing the aggregate variables for the upcoming period:
-            capital-to-labor ratio, interest factor, (normalized) wage rate,
-            aggregate permanent and transitory shocks.
+        MaggNow : float
+            Aggregate market resources for this period normalized by mean permanent income
+        AaggNow : float
+            Aggregate savings for this period normalized by mean permanent income
+        RfreeNow : float
+            Interest factor on assets in the economy this period.
+        wRteNow : float
+            Wage rate for labor in the economy this period.
+        PermShkAggNow : float
+            Permanent shock to aggregate labor productivity this period.
+        TranShkAggNow : float
+            Transitory shock to aggregate labor productivity this period.
+        KtoLnow : float
+            Capital-to-labor ratio in the economy this period.
         '''
         # Calculate aggregate savings
         AaggPrev = np.mean(np.array(aLvlNow))/np.mean(pLvlNow)  # End-of-period savings from last period
@@ -1577,9 +1587,8 @@ def calcRandW(self, aLvlNow, pLvlNow):
         self.KtoLnow = KtoLnow   # Need to store this as it is a sow variable
 
         # Package the results into an object and return it
-        AggVarsNow = CobbDouglasAggVars(MaggNow, AaggPrev, KtoLnow, RfreeNow, wRteNow, PermShkAggNow, TranShkAggNow)
-        return AggVarsNow
-
+        return MaggNow, AaggPrev, RfreeNow, wRteNow, PermShkAggNow, TranShkAggNow, KtoLnow
+    
     def calcAFunc(self, MaggNow, AaggNow):
         '''
         Calculate a new aggregate savings rule based on the history
@@ -1781,8 +1790,21 @@ def getAggShocks(self):
 
         Returns
         -------
-        AggVarsNow : CobbDouglasAggVars
-            Aggregate state and shock variables for this period.
+        MaggNow : float
+            Aggregate market resources for this period normalized by mean permanent income
+        AaggNow : float
+            Aggregate savings for this period normalized by mean permanent income
+        RfreeNow : float
+            Interest factor on assets in the economy this period.
+        wRteNow : float
+            Wage rate for labor in the economy this period.
+        PermShkAggNow : float
+            Permanent shock to aggregate labor productivity this period.
+        TranShkAggNow : float
+            Transitory shock to aggregate labor productivity this period.
+        KtoLnow : float
+            Capital-to-labor ratio in the economy this period.
+        
         '''
         # Get this period's aggregate shocks
         PermShkAggNow = self.PermShkAggHist[self.Shk_idx]
@@ -1798,9 +1820,7 @@ def getAggShocks(self):
         MaggNow = 1.0
         KtoLnow = 1.0/PermShkAggNow
 
-        # Package the results into an object and return it
-        AggVarsNow = CobbDouglasAggVars(MaggNow, AaggNow, KtoLnow, RfreeNow, wRteNow, PermShkAggNow, TranShkAggNow)
-        return AggVarsNow
+        return MaggNow, AaggNow, RfreeNow, wRteNow, PermShkAggNow, TranShkAggNow, KtoLnow
 
 # Make a dictionary to specify a Markov Cobb-Douglas economy
 init_mrkv_cobb_douglas = init_cobb_douglas.copy()
@@ -2085,11 +2105,26 @@ def millRule(self, aLvlNow, pLvlNow):
         and adds the Markov state index.
 
         See documentation for calcRandW for more information.
+
+        Returns
+        -------
+        Mnow : float
+            Aggregate market resources for this period.
+        Aprev : float
+            Aggregate savings for the prior period.
+        KtoLnow : float
+            Capital-to-labor ratio in the economy this period.
+        Rnow : float
+            Interest factor on assets in the economy this period.
+        Wnow : float
+            Wage rate for labor in the economy this period.
+        MrkvNow : int
+            Binary indicator for bad (0) or good (1) macroeconomic state.
         '''
         MrkvNow = self.MrkvNow_hist[self.Shk_idx]
         temp = self.calcRandW(aLvlNow, pLvlNow)
-        temp(MrkvNow=MrkvNow)
-        return temp
+
+        return temp + (MrkvNow,)
 
     def calcAFunc(self, MaggNow, AaggNow):
         '''
@@ -2356,7 +2391,21 @@ def millRule(self, aNow, EmpNow):
         wage rate based on each agent's current state.  Just calls calcRandW().
 
         See documentation for calcRandW for more information.
+
+        Returns
+        -------
+        Mnow : float
+            Aggregate market resources for this period.
+        Aprev : float
+            Aggregate savings for the prior period.
+        MrkvNow : int
+            Binary indicator for bad (0) or good (1) macroeconomic state.
+        Rnow : float
+            Interest factor on assets in the economy this period.
+        Wnow : float
+            Wage rate for labor in the economy this period.
         '''
+        
         return self.calcRandW(aNow, EmpNow)
     
     def calcDynamics(self, Mnow, Aprev):
@@ -2383,10 +2432,16 @@ def calcRandW(self, aNow, EmpNow):
 
         Returns
         -------
-        AggVarsNow : CobbDouglasAggVars
-            An object containing the aggregate variables for the upcoming period:
-            capital-to-labor ratio, interest factor, (normalized) wage rate,
-            aggregate permanent and transitory shocks.
+        Mnow : float
+            Aggregate market resources for this period.
+        Aprev : float
+            Aggregate savings for the prior period.
+        MrkvNow : int
+            Binary indicator for bad (0) or good (1) macroeconomic state.
+        Rnow : float
+            Interest factor on assets in the economy this period.
+        Wnow : float
+            Wage rate for labor in the economy this period.
         '''
         # Calculate aggregate savings
         Aprev = np.mean(np.array(aNow))  # End-of-period savings from last period
@@ -2414,9 +2469,8 @@ def calcRandW(self, aNow, EmpNow):
         Mnow = Rnow*AggK + Wnow*AggL
         self.KtoLnow = KtoLnow   # Need to store this as it is a sow variable
 
-        # Package the results into an object and return it
-        AggVarsNow = KrusellSmithAggVars(Mnow, Aprev, KtoLnow, Rnow, Wnow, MrkvNow)
-        return AggVarsNow
+        # Returns a tuple of these values
+        return Mnow, Aprev,  MrkvNow, Rnow, Wnow
 
     def calcAFunc(self, Mnow, Aprev):
         '''
@@ -2472,81 +2526,6 @@ def calcAFunc(self, Mnow, Aprev):
         return AggShocksDynamicRule(AFunc_list)
 
 
-class CobbDouglasAggVars(HARKobject):
-    '''
-    A simple class for holding the relevant aggregate variables that should be
-    passed from the market to each type.  Includes the capital-to-labor ratio,
-    the interest factor, the wage rate, and the aggregate permanent and tran-
-    sitory shocks.
-    '''
-    def __init__(self, MaggNow, AaggNow, KtoLnow, RfreeNow, wRteNow, PermShkAggNow, TranShkAggNow):
-        '''
-        Make a new instance of CobbDouglasAggVars.
-
-        Parameters
-        ----------
-        MaggNow : float
-            Aggregate market resources for this period normalized by mean permanent income
-        AaggNow : float
-            Aggregate savings for this period normalized by mean permanent income
-        KtoLnow : float
-            Capital-to-labor ratio in the economy this period.
-        RfreeNow : float
-            Interest factor on assets in the economy this period.
-        wRteNow : float
-            Wage rate for labor in the economy this period.
-        PermShkAggNow : float
-            Permanent shock to aggregate labor productivity this period.
-        TranShkAggNow : float
-            Transitory shock to aggregate labor productivity this period.
-
-        Returns
-        -------
-        None
-        '''
-        self.MaggNow = MaggNow
-        self.AaggNow = AaggNow
-        self.KtoLnow = KtoLnow
-        self.RfreeNow = RfreeNow
-        self.wRteNow = wRteNow
-        self.PermShkAggNow = PermShkAggNow
-        self.TranShkAggNow = TranShkAggNow
-        
-        
-class KrusellSmithAggVars():
-    '''
-    Just a container class for aggregate data in the Krusell-Smith model.
-    '''
-    def __init__(self, Mnow, Aprev, KtoLnow, Rnow, Wnow, MrkvNow):
-        '''
-        Make a new instance of KrusellSmithAggVars.
-
-        Parameters
-        ----------
-        Mnow : float
-            Aggregate market resources for this period.
-        Aprev : float
-            Aggregate savings for the prior period.
-        KtoLnow : float
-            Capital-to-labor ratio in the economy this period.
-        Rnow : float
-            Interest factor on assets in the economy this period.
-        Wnow : float
-            Wage rate for labor in the economy this period.
-        MrkvNow : int
-            Binary indicator for bad (0) or good (1) macroeconomic state.
-
-        Returns
-        -------
-        None
-        '''
-        self.Mnow = Mnow
-        self.Aprev = Aprev
-        self.KtoLnow = KtoLnow
-        self.Rnow = Rnow
-        self.Wnow = Wnow
-        self.MrkvNow = MrkvNow
-
 
 class AggregateSavingRule(HARKobject):
     '''
diff --git a/HARK/core.py b/HARK/core.py
index 4d8168c84..5ed7bb1fd 100644
--- a/HARK/core.py
+++ b/HARK/core.py
@@ -906,8 +906,7 @@ def __init__(self, agents=None, sow_vars=None, reap_vars=None, const_vars=None,
         dyn_vars : [string]
             Names of variables that constitute a "dynamic rule".
         millRule : function
-            A function that takes inputs named in reap_vars and returns an object
-            with attributes named in sow_vars.  The "aggregate market process" that
+            A function that takes inputs named in reap_vars and returns a tuple the same size and order as sow_vars.  The "aggregate market process" that
             transforms individual agent actions/states/data into aggregate data to
             be sent back to agents.
         calcDynamics : function
@@ -1078,9 +1077,8 @@ def mill(self):
         # Run the millRule and store its output in self
         product = self.millRule(**mill_dict)
 
-        for sow_var in self.sow_state:
-            this_product = getattr(product, sow_var)
-            self.sow_state[sow_var] = this_product
+        for i, sow_var in enumerate(self.sow_state):
+            self.sow_state[sow_var] = product[i]
 
     def cultivate(self):
         '''
@@ -1117,7 +1115,7 @@ def reset(self):
         self.history = {var_name : [] for var_name in self.track_vars}
 
         # Set the sow variables to their initial levels
-        for var_name in self.sow_state:  
+        for var_name in self.sow_state:
             self.sow_state[var_name] = self.sow_init[var_name]
 
         # Reset each AgentType in the market
@@ -1146,7 +1144,7 @@ def store(self):
                 value_now = self.const_vars[var_name]
             else:
                 value_now = getattr(self, var_name)
-    
+
             self.history[var_name].append(value_now)
 
     def makeHistory(self):

From 3b678d157613d261f24c27ee3a2fc300f6aebf19 Mon Sep 17 00:00:00 2001
From: sb <sbenthall@gmail.com>
Date: Thu, 23 Jul 2020 16:24:05 -0400
Subject: [PATCH 10/11] missed a sow_var in Small Open

---
 HARK/ConsumptionSaving/ConsAggShockModel.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/HARK/ConsumptionSaving/ConsAggShockModel.py b/HARK/ConsumptionSaving/ConsAggShockModel.py
index 169c0710f..b6159f6be 100644
--- a/HARK/ConsumptionSaving/ConsAggShockModel.py
+++ b/HARK/ConsumptionSaving/ConsAggShockModel.py
@@ -1673,7 +1673,8 @@ def __init__(self, agents=None, tolerance=0.0001, act_T=1000, **kwds):
 
     def update(self):
         '''
-        Use primitive parameters to set basic objects.  This is an extremely stripped-down version
+        Use primitive parameters to set basic objects.
+        This is an extremely stripped-down version
         of update for CobbDouglasEconomy.
 
         Parameters
@@ -1686,7 +1687,7 @@ def update(self):
         '''
         self.kSS = 1.0
         self.MSS = 1.0
-        self.KtoLnow_init = self.kSS
+        self.sow_init['KtoLnow_init'] = self.kSS
         self.Rfunc = ConstantFunction(self.Rfree)
         self.wFunc = ConstantFunction(self.wRte)
         self.sow_init['RfreeNow'] = self.Rfunc(self.kSS)

From a6e2de92eeb4525a96192b58e38a8971be698106 Mon Sep 17 00:00:00 2001
From: sb <sbenthall@gmail.com>
Date: Thu, 30 Jul 2020 16:13:06 -0400
Subject: [PATCH 11/11] replace OrderedDict with dict -- 3.7 dicts ordered by
 default

---
 HARK/core.py | 9 ++++-----
 1 file changed, 4 insertions(+), 5 deletions(-)

diff --git a/HARK/core.py b/HARK/core.py
index 5ed7bb1fd..e0cc29dfa 100644
--- a/HARK/core.py
+++ b/HARK/core.py
@@ -12,7 +12,6 @@
 from builtins import str
 from builtins import range
 from builtins import object
-from collections import OrderedDict
 import sys
 import os
 from distutils.dir_util import copy_tree
@@ -928,16 +927,16 @@ def __init__(self, agents=None, sow_vars=None, reap_vars=None, const_vars=None,
         self.agents     = agents if agents is not None else list() # NOQA
 
         reap_vars = reap_vars if reap_vars is not None else list() # NOQA
-        self.reap_state  = OrderedDict([(var, []) for var in reap_vars])
+        self.reap_state  = dict([(var, []) for var in reap_vars])
 
         self.sow_vars   = sow_vars if sow_vars is not None else list() # NOQA
         # dictionaries for tracking initial and current values
         # of the sow variables.
-        self.sow_init = OrderedDict([(var, None) for var in self.sow_vars])
-        self.sow_state = OrderedDict([(var, None) for var in self.sow_vars])
+        self.sow_init = dict([(var, None) for var in self.sow_vars])
+        self.sow_state = dict([(var, None) for var in self.sow_vars])
 
         const_vars = const_vars if const_vars is not None else list() # NOQA
-        self.const_vars =  OrderedDict([(var, None) for var in const_vars])
+        self.const_vars =  dict([(var, None) for var in const_vars])
 
         self.track_vars = track_vars if track_vars is not None else list() # NOQA
         self.dyn_vars   = dyn_vars if dyn_vars is not None else list() # NOQA