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BenchmarkRunner: save and load results

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This commit is contained in:
Alinson S. Xavier
2020-01-24 09:29:44 -06:00
parent 8f141e6a9d
commit 3644c59101
3 changed files with 63 additions and 12 deletions
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28
miplearn/benchmark.py
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@@ -19,11 +19,12 @@ class BenchmarkRunner:
solver.fit()
def parallel_solve(self, instances, n_jobs=1):
self.results = pd.DataFrame(columns=["Solver",
"Instance",
"Wallclock Time",
"Optimal Value",
])
if self.results is None:
self.results = pd.DataFrame(columns=["Solver",
"Instance",
"Wallclock Time",
"Obj Value",
])
for (name, solver) in self.solvers.items():
results = solver.parallel_solve(instances, n_jobs=n_jobs, label=name)
for i in range(len(instances)):
@@ -38,8 +39,21 @@ class BenchmarkRunner:
"Solver": name,
"Instance": i,
"Wallclock Time": wallclock_time,
"Optimal Value": results[i]["Problem"][0]["Lower bound"]
"Obj Value": results[i]["Problem"][0]["Lower bound"]
}, ignore_index=True)
groups = self.results.groupby("Instance")
best_obj_value = groups["Obj Value"].transform("max")
best_wallclock_time = groups["Wallclock Time"].transform("min")
self.results["Relative Obj Value"] = \
self.results["Obj Value"] / best_obj_value
self.results["Relative Wallclock Time"] = \
self.results["Wallclock Time"] / best_wallclock_time
def raw_results(self):
return self.results
return self.results
def save_results(self, filename):
self.results.to_csv(filename)
def load_results(self, filename):
self.results = pd.read_csv(filename, index_col=0)

10
miplearn/tests/test_benchmark.py
View File

@@ -8,6 +8,7 @@ from miplearn.problems.stab import MaxStableSetInstance, MaxStableSetGenerator
import networkx as nx
import numpy as np
import pyomo.environ as pe
import os.path
def test_benchmark():
@@ -38,4 +39,11 @@ def test_benchmark():
benchmark = BenchmarkRunner(test_solvers)
benchmark.load_fit("data.bin")
benchmark.parallel_solve(test_instances, n_jobs=2)
print(benchmark.raw_results())
assert benchmark.raw_results().values.shape == (6,6)
benchmark.save_results("/tmp/benchmark.csv")
assert os.path.isfile("/tmp/benchmark.csv")
benchmark = BenchmarkRunner(test_solvers)
benchmark.load_results("/tmp/benchmark.csv")
assert benchmark.raw_results().values.shape == (6,6)