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Removing randomness from lqnash #752

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Merged
merged 2 commits into from
Dec 22, 2024
Merged

Removing randomness from lqnash #752

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d4366a5
Removing randomness from lqnash
hsalberti Oct 23, 2023
8ceb113
Replace random matrices with matrices with np.inf in lqnash
oyamad Dec 22, 2024
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13 changes: 3 additions & 10 deletions quantecon/_lqnash.py
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Original file line number Diff line number Diff line change
@@ -1,10 +1,9 @@
import numpy as np
from scipy.linalg import solve
from .util import check_random_state


def nnash(A, B1, B2, R1, R2, Q1, Q2, S1, S2, W1, W2, M1, M2,
beta=1.0, tol=1e-8, max_iter=1000, random_state=None):
beta=1.0, tol=1e-8, max_iter=1000):
r"""
Compute the limit of a Nash linear quadratic dynamic game. In this
problem, player i minimizes
Expand Down Expand Up @@ -63,11 +62,6 @@ def nnash(A, B1, B2, R1, R2, Q1, Q2, S1, S2, W1, W2, M1, M2,
This is the tolerance level for convergence
max_iter : scalar(int), optional(default=1000)
This is the maximum number of iteratiosn allowed
random_state : int or np.random.RandomState/Generator, optional
Random seed (integer) or np.random.RandomState or Generator
instance to set the initial state of the random number generator
for reproducibility. If None, a randomly initialized RandomState
is used.

Returns
-------
Expand Down Expand Up @@ -105,13 +99,12 @@ def nnash(A, B1, B2, R1, R2, Q1, Q2, S1, S2, W1, W2, M1, M2,
else:
k_2 = B2.shape[1]

random_state = check_random_state(random_state)
v1 = np.eye(k_1)
v2 = np.eye(k_2)
P1 = np.zeros((n, n))
P2 = np.zeros((n, n))
F1 = random_state.standard_normal((k_1, n))
F2 = random_state.standard_normal((k_2, n))
F1 = np.full((k_1, n), np.inf)
F2 = np.full((k_2, n), np.inf)

for it in range(max_iter):
# update
Expand Down
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