np.ones * alpha -->> np.full(, alpah) in py files (#92)

Author: shlff

lectures/_static/lecture_specific/amss2/crra_utility.py

@@ -7,7 +7,7 @@ def __init__(self,
                  β=0.9,
                  σ=2,
                  γ=2,
-                 π=0.5*np.ones((2, 2)),
+                 π=np.full((2, 2), 0.5),
                  G=np.array([0.1, 0.2]),
                  Θ=np.ones(2),
                  transfers=False):

lectures/_static/lecture_specific/amss2/log_utility.py

@@ -5,7 +5,7 @@ class LogUtility:
     def __init__(self,
                  β=0.9,
                  ψ=0.69,
-                 π=0.5*np.ones((2, 2)),
+                 π=np.full((2, 2), 0.5),
                  G=np.array([0.1, 0.2]),
                  Θ=np.ones(2),
                  transfers=False):

lectures/_static/lecture_specific/amss2/recursive_allocation.py

@@ -184,7 +184,7 @@ def res(z):
             n = z[S:]
             return np.hstack([Θ * Uc(c, n) + Un(c, n), Θ * n - c - G])
 
-        res = root(res, 0.5 * np.ones(2 * S))
+        res = root(res, np.full(2 * S, 0.5))
         if not res.success:
             raise Exception('Could not find first best')
 

lectures/_static/lecture_specific/amss2/sequential_allocation.py

@@ -35,7 +35,7 @@ def res(z):
             n = z[S:]
             return np.hstack([Θ * Uc(c, n) + Un(c, n), Θ * n - c - G])
 
-        res = root(res, 0.5 * np.ones(2 * S))
+        res = root(res, np.full(2 * S, 0.5))
 
         if not res.success:
             raise Exception('Could not find first best')

lectures/_static/lecture_specific/opt_tax_recur/recursive_allocation.py

@@ -8,7 +8,7 @@ class RecursiveLS:
     def __init__(self,
                  pref,
                  x_grid,
-                 π=0.5*np.ones((2, 2)),
+                 π=np.full((2, 2), 0.5),
                  g=np.array([0.1, 0.2])):
 
         self.π, self.g, self.S = π, g, len(π)

lectures/_static/lecture_specific/opt_tax_recur/sequential_allocation.py

@@ -10,7 +10,7 @@ class SequentialLS:
 
     def __init__(self,
                  pref,
-                 π=0.5*np.ones((2, 2)),
+                 π=np.full((2, 2), 0.5),
                  g=np.array([0.1, 0.2])):
 
         # Initialize from pref object attributes
@@ -42,7 +42,7 @@ def find_first_best(self):
         '''
         S, g = self.S, self.g
 
-        res = root(self.FOC_first_best, 0.5 * np.ones(S), args=(g,))
+        res = root(self.FOC_first_best, np.full(S, 0.5), args=(g,))
 
         if (res.fun > 1e-10).any():
             raise Exception('Could not find first best')