Commit 7664f262 authored by Sebastian Alexander Uerlich's avatar Sebastian Alexander Uerlich
Browse files

Fix stopping criterion in all Exchange ADMM algorithms

parent 51975719
......@@ -214,10 +214,7 @@ def exchange_admm(city_district, models=None, beta=1.0, eps_primal=0.1,
# ------------------------------------------
# Calculate parameters for stopping criteria
# ------------------------------------------
# TODO: Think about stopping criteria
# From an interpretational perspective it would make sense to remove
# the `n *` for the r norm and introduce a `1/n` factor for the s norm
r_norms.append(n * np.linalg.norm(x_))
r_norms.append(np.math.sqrt(n) * np.linalg.norm(x_))
np.copyto(
s[0:op_horizon],
- rho * (
......
......@@ -228,10 +228,7 @@ def exchange_admm_mpi(city_district, models=None, beta=1.0, eps_primal=0.1,
# ------------------------------------------
# Calculate parameters for stopping criteria
# ------------------------------------------
# TODO: Think about stopping criteria
# From an interpretational perspective it would make sense to remove
# the `n *` for the r norm and introduce a `1/n` factor for the s norm
r_norms.append(n * np.linalg.norm(x_))
r_norms.append(np.math.sqrt(n) * np.linalg.norm(x_))
np.copyto(
s[0:op_horizon],
- rho * (
......
......@@ -298,10 +298,7 @@ def exchange_admm_r_and_f_mpi(city_district, models=None, beta=1.0, eps_primal=0
# ------------------------------------------
# Calculate parameters for stopping criteria
# ------------------------------------------
# TODO: Think about stopping criteria
# From an interpretational perspective it would make sense to remove
# the `n *` for the r norm and introduce a `1/n` factor for the s norm
r_norms.append(n * np.linalg.norm(x_))
r_norms.append(np.math.sqrt(n) * np.linalg.norm(x_))
np.copyto(
s[0:op_horizon],
- rho * (
......
......@@ -246,10 +246,7 @@ def exchange_admm_varying_mpi(city_district, models=None, beta=1.0, eps_primal=0
# ------------------------------------------
# Calculate parameters for stopping criteria
# ------------------------------------------
# TODO: Think about stopping criteria
# From an interpretational perspective it would make sense to remove
# the `n *` for the r norm and introduce a `1/n` factor for the s norm
r_norms.append(n * np.linalg.norm(x_))
r_norms.append(np.math.sqrt(n) * np.linalg.norm(x_))
np.copyto(
s[0:op_horizon],
- rho * (
......
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