From e9780817b78a6ef5f625cd1c4c6e066867133118 Mon Sep 17 00:00:00 2001
From: rachelmoan <moanrachel516@gmail.com>
Date: Thu, 17 Oct 2024 18:57:32 -0500
Subject: [PATCH] Separate out optimizer to be used by multiple problems
---
.../conflict_resolvers/traj_opt_resolver.py | 34 ++---------------
guided_mrmp/controllers/mpc.py | 35 ++----------------
guided_mrmp/optimizer.py | 37 +++++++++++++++++++
3 files changed, 44 insertions(+), 62 deletions(-)
create mode 100644 guided_mrmp/optimizer.py
diff --git a/guided_mrmp/conflict_resolvers/traj_opt_resolver.py b/guided_mrmp/conflict_resolvers/traj_opt_resolver.py
index 92e3a72..aab7dac 100644
--- a/guided_mrmp/conflict_resolvers/traj_opt_resolver.py
+++ b/guided_mrmp/conflict_resolvers/traj_opt_resolver.py
@@ -1,6 +1,7 @@
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Circle, Rectangle
+from guided_mrmp.optimizer import Optimizer
from casadi import *
class TrajOptResolver():
@@ -148,37 +149,8 @@ class TrajOptResolver():
return {'opti':opti, 'X':X, 'T':T}
def solve_optimization_problem(self, problem, initial_guesses=None, solver_options=None):
- opti = problem['opti']
-
- if initial_guesses:
- for param, value in initial_guesses.items():
- print(f"param = {param}")
- print(f"value = {value}")
- opti.set_initial(problem[param], value)
-
- # Set numerical backend, with options if provided
- if solver_options:
- opti.solver('ipopt', solver_options)
- else:
- opti.solver('ipopt')
-
- try:
- sol = opti.solve() # actual solve
- status = 'succeeded'
- except:
- sol = None
- status = 'failed'
-
- results = {
- 'status' : status,
- 'solution' : sol,
- }
-
- if sol:
- for var_name, var in problem.items():
- if var_name != 'opti':
- results[var_name] = sol.value(var)
-
+ opt = Optimizer(problem)
+ results = opt.solve_optimization_problem(initial_guesses, solver_options)
return results
def solve(self, N, x_range, y_range, initial_guesses):
diff --git a/guided_mrmp/controllers/mpc.py b/guided_mrmp/controllers/mpc.py
index f4c9c72..d87557c 100644
--- a/guided_mrmp/controllers/mpc.py
+++ b/guided_mrmp/controllers/mpc.py
@@ -1,5 +1,6 @@
import numpy as np
import casadi as ca
+from guided_mrmp.optimizer import Optimizer
np.seterr(divide="ignore", invalid="ignore")
@@ -95,37 +96,8 @@ class MPC:
}
def solve_optimization_problem(self, problem, initial_guesses=None, solver_options=None):
- opti = problem['opti']
-
- if initial_guesses:
- for param, value in initial_guesses.items():
- # print(f"param = {param}")
- # print(f"value = {value}")
- opti.set_initial(problem[param], value)
-
- # Set numerical backend, with options if provided
- if solver_options:
- opti.solver('ipopt', solver_options)
- else:
- opti.solver('ipopt')
-
- try:
- sol = opti.solve() # actual solve
- status = 'succeeded'
- except:
- sol = None
- status = 'failed'
-
- results = {
- 'status' : status,
- 'solution' : sol,
- }
-
- if sol:
- for var_name, var in problem.items():
- if var_name != 'opti':
- results[var_name] = sol.value(var)
-
+ opt = Optimizer(problem)
+ results = opt.solve_optimization_problem(initial_guesses, solver_options)
return results
def step(self, initial_state, target, prev_cmd, initial_guesses=None):
@@ -147,6 +119,7 @@ class MPC:
solver_options = {'ipopt.print_level': self.print_level,
'print_time': self.print_time,
+ 'ipopt.tol': self.acceptable_tol,
'ipopt.acceptable_tol': self.acceptable_tol,
'ipopt.acceptable_iter': self.acceptable_iter}
diff --git a/guided_mrmp/optimizer.py b/guided_mrmp/optimizer.py
new file mode 100644
index 0000000..5afa7cf
--- /dev/null
+++ b/guided_mrmp/optimizer.py
@@ -0,0 +1,37 @@
+class Optimizer:
+ def __init__(self, problem):
+ self.problem = problem
+
+ def solve_optimization_problem(self, initial_guesses=None, solver_options=None):
+ opti = self.problem['opti']
+
+ if initial_guesses:
+ for param, value in initial_guesses.items():
+ print(f"param = {param}")
+ print(f"value = {value}")
+ opti.set_initial(self.problem[param], value)
+
+ # Set numerical backend, with options if provided
+ if solver_options:
+ opti.solver('ipopt', solver_options)
+ else:
+ opti.solver('ipopt')
+
+ try:
+ sol = opti.solve() # actual solve
+ status = 'succeeded'
+ except:
+ sol = None
+ status = 'failed'
+
+ results = {
+ 'status' : status,
+ 'solution' : sol,
+ }
+
+ if sol:
+ for var_name, var in self.problem.items():
+ if var_name != 'opti':
+ results[var_name] = sol.value(var)
+
+ return results
--
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