some miscelaneous changes, merged TPI

Python/CURRENT_DEBUGGED_VERSION/TPI.py

@@ -106,7 +106,7 @@
 '''
 
 
-def SS_TPI_firstdoughnutring(guesses, winit, rinit, BQinit, T_H_init, j):
+def SS_TPI_firstdoughnutring(guesses, winit, rinit, BQinit, T_H_init, , initial_b, j, parameters, theta, tau_bq):
     '''
     Solves the first entries of the upper triangle of the twist doughnut.  This is
     separate from the main TPI function because the the values of b and n are scalars,
@@ -117,7 +117,11 @@ def SS_TPI_firstdoughnutring(guesses, winit, rinit, BQinit, T_H_init, j):
         rinit = initial rental rate (scalar)
         BQinit = initial aggregate bequest (scalar)
         T_H_init = initial lump sum tax (scalar)
+        initial_b = initial distribution of capital (SxJ array)
         j = which ability type is being solved for (scalar)
+        parameters = list of parameters (list)
+        theta = replacement rates (Jx1 array)
+        tau_bq = bequest tax rates (Jx1 array)
     Output:
         euler errors (2x1 list)
     '''

Python/dynamic/SS_graphs.py

@@ -5,6 +5,8 @@
 Creates graphs for steady state values.
 
 This py-file calls the following other file(s):
+            firm.py
+            household.py
             SSinit/ss_init_vars.pkl
             SS/ss_vars.pkl
             OUTPUT/Saved_moments/params_given.pkl
@@ -26,8 +28,8 @@
 from mpl_toolkits.mplot3d import Axes3D
 import cPickle as pickle
 
-import firm_funcs as firm
-import household_funcs as house
+import firm
+import household
 
 '''
 ------------------------------------------------------------------------
@@ -91,7 +93,7 @@ def the_inequalizer(dist, pop_weights, ability_weights, S, J):
 Kss_init = Kss
 Lss_init = Lss
 
-Css_init = house.get_C(cssmat, omega_SS.reshape(S, 1), lambdas)
+Css_init = household.get_C(cssmat, omega_SS.reshape(S, 1), lambdas)
 iss_init = firm.get_I(bssmat_splus1, bssmat_splus1, delta, g_y, g_n_ss)
 income_init = cssmat + iss_init
 # print (income_init*omega_SS).sum()
@@ -292,7 +294,7 @@ def the_inequalizer(dist, pop_weights, ability_weights, S, J):
 
 
 
-Css = house.get_C(cssmat, omega_SS.reshape(S, 1), lambdas)
+Css = household.get_C(cssmat, omega_SS.reshape(S, 1), lambdas)
 iss = firm.get_I(bssmat_splus1, bssmat_splus1, delta, g_y, g_n_ss)
 income = cssmat + iss
 # print (income*omega_SS).sum()

Python/dynamic/TPI_graphs.py

@@ -5,6 +5,7 @@
 Creates graphs for TPI values.
 
 This py-file calls the following other file(s):
+            firm.py
             SSinit/ss_init_vars.pkl
             TPIinit/TPIinit_vars.pkl
             SS/ss_vars.pkl
@@ -26,7 +27,7 @@
 from mpl_toolkits.mplot3d import Axes3D
 import cPickle as pickle
 
-import firm_funcs as firm
+import firm
 
 '''
 ------------------------------------------------------------------------

Python/dynamic/demographics.py

@@ -6,6 +6,7 @@
 demographics of the population
 
 This py-file calls the following other file(s):
+            utils.py
             data\demographic\demographic_data.csv
             data\demographic\mortality_rates.csv
 

Python/dynamic/firm.py

@@ -2,7 +2,7 @@
 ------------------------------------------------------------------------
 Last updated 7/16/2015
 
-Firm functions for taxes in SS and TPI.
+Firm functions for firms in SS and TPI.
 
 ------------------------------------------------------------------------
 '''

Python/dynamic/income.py

@@ -7,6 +7,8 @@
     percentiles, as it uses fitted polynomials to those percentiles.
     For a more generic version, see income_nopoly.py.
 
+This file calls the following files:
+    utils.py
 
 This py-file creates the following other file(s):
     (make sure that an OUTPUT folder exists)

Python/dynamic/wealth.py

@@ -6,6 +6,7 @@
 
 This py-file calls the following other file(s):
             data/wealth/scf2007to2013_wealth_age_all_percentiles.csv
+            utils.py
 
 This py-file creates the following other file(s):
     (make sure that an OUTPUT folder exists)