ANL-CEEESA/UnitCommitment.jl
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Reformat Python scripts

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This commit is contained in:
Alinson S. Xavier
2021-05-27 22:26:38 -05:00
parent 3687d42733
commit a684419f33
2 changed files with 96 additions and 59 deletions
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90
benchmark/scripts/table.py
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@@ -9,8 +9,8 @@ from tabulate import tabulate
def process_all_log_files():
pathlist = list(Path(".").glob('results/*/*/*.log'))
pathlist += list(Path(".").glob('results/*/*.log'))
pathlist = list(Path(".").glob("results/*/*/*.log"))
pathlist += list(Path(".").glob("results/*/*.log"))
rows = []
for path in pathlist:
if ".ipy" in str(path):
@@ -22,8 +22,8 @@ def process_all_log_files():
df.index = range(len(df))
print("Writing tables/benchmark.csv")
df.to_csv("tables/benchmark.csv", index_label="Index")
def process(filename):
parts = filename.replace(".log", "").split("/")
group_name = "/".join(parts[1:-1])
@@ -45,56 +45,74 @@ def process(filename):
read_time, model_time, isf_time, total_time = None, None, None, None
cb_calls, cb_time = 0, 0.0
transmission_count, transmission_time, transmission_calls = 0, 0.0, 0
# m = re.search("case([0-9]*)", instance_name)
# n_buses = int(m.group(1))
n_buses = 0
with open(filename) as file:
for line in file.readlines():
m = re.search(r"Explored ([0-9.e+]*) nodes \(([0-9.e+]*) simplex iterations\) in ([0-9.e+]*) seconds", line)
m = re.search(
r"Explored ([0-9.e+]*) nodes \(([0-9.e+]*) simplex iterations\) in ([0-9.e+]*) seconds",
line,
)
if m is not None:
nodes += int(m.group(1))
simplex_iterations += int(m.group(2))
optimize_time += float(m.group(3))
m = re.search(r"Best objective ([0-9.e+]*), best bound ([0-9.e+]*), gap ([0-9.e+]*)\%", line)
m = re.search(
r"Best objective ([0-9.e+]*), best bound ([0-9.e+]*), gap ([0-9.e+]*)\%",
line,
)
if m is not None:
primal_bound = float(m.group(1))
dual_bound = float(m.group(2))
gap = round(float(m.group(3)), 3)
m = re.search(r"Root relaxation: objective ([0-9.e+]*), ([0-9.e+]*) iterations, ([0-9.e+]*) seconds", line)
m = re.search(
r"Root relaxation: objective ([0-9.e+]*), ([0-9.e+]*) iterations, ([0-9.e+]*) seconds",
line,
)
if m is not None:
root_obj = float(m.group(1))
root_iterations += int(m.group(2))
root_time += float(m.group(3))
m = re.search(r"Presolved: ([0-9.e+]*) rows, ([0-9.e+]*) columns, ([0-9.e+]*) nonzeros", line)
m = re.search(
r"Presolved: ([0-9.e+]*) rows, ([0-9.e+]*) columns, ([0-9.e+]*) nonzeros",
line,
)
if m is not None:
n_rows_presolved = int(m.group(1))
n_cols_presolved = int(m.group(2))
n_nz_presolved = int(m.group(3))
m = re.search(r"Optimize a model with ([0-9.e+]*) rows, ([0-9.e+]*) columns and ([0-9.e+]*) nonzeros", line)
m = re.search(
r"Optimize a model with ([0-9.e+]*) rows, ([0-9.e+]*) columns and ([0-9.e+]*) nonzeros",
line,
)
if m is not None:
n_rows_orig = int(m.group(1))
n_cols_orig = int(m.group(2))
n_nz_orig = int(m.group(3))
m = re.search(r"Variable types: ([0-9.e+]*) continuous, ([0-9.e+]*) integer \(([0-9.e+]*) binary\)", line)
m = re.search(
r"Variable types: ([0-9.e+]*) continuous, ([0-9.e+]*) integer \(([0-9.e+]*) binary\)",
line,
)
if m is not None:
n_cont_vars_presolved = int(m.group(1))
n_bin_vars_presolved = int(m.group(3))
n_bin_vars_presolved = int(m.group(3))
m = re.search(r"Read problem in ([0-9.e+]*) seconds", line)
if m is not None:
read_time = float(m.group(1))
m = re.search(r"Computed ISF in ([0-9.e+]*) seconds", line)
if m is not None:
isf_time = float(m.group(1))
m = re.search(r"Built model in ([0-9.e+]*) seconds", line)
if m is not None:
model_time = float(m.group(1))
@@ -103,7 +121,10 @@ def process(filename):
if m is not None:
total_time = float(m.group(1))
m = re.search(r"User-callback calls ([0-9.e+]*), time in user-callback ([0-9.e+]*) sec", line)
m = re.search(
r"User-callback calls ([0-9.e+]*), time in user-callback ([0-9.e+]*) sec",
line,
)
if m is not None:
cb_calls = int(m.group(1))
cb_time = float(m.group(2))
@@ -116,7 +137,7 @@ def process(filename):
m = re.search(r".*MW overflow", line)
if m is not None:
transmission_count += 1
return {
"Group": group_name,
"Instance": instance_name,
@@ -150,6 +171,7 @@ def process(filename):
"Transmission screening calls": transmission_calls,
}
def generate_chart():
import pandas as pd
import matplotlib.pyplot as plt
@@ -159,7 +181,9 @@ def generate_chart():
files = ["tables/benchmark.csv"]
for f in files:
table = pd.read_csv(f, index_col=0)
table.loc[:, "Instance"] = table.loc[:,"Group"] + "/" + table.loc[:,"Instance"]
table.loc[:, "Instance"] = (
table.loc[:, "Group"] + "/" + table.loc[:, "Instance"]
)
table.loc[:, "Filename"] = f
tables += [table]
benchmark = pd.concat(tables, sort=True)
@@ -168,16 +192,18 @@ def generate_chart():
plt.figure(figsize=(12, 0.50 * k))
sns.set_style("whitegrid")
sns.set_palette("Set1")
sns.barplot(y="Instance",
x="Total time (s)",
color="tab:red",
capsize=0.15,
errcolor="k",
errwidth=1.25,
data=benchmark);
sns.barplot(
y="Instance",
x="Total time (s)",
color="tab:red",
capsize=0.15,
errcolor="k",
errwidth=1.25,
data=benchmark,
)
plt.tight_layout()
print("Writing tables/benchmark.png")
plt.savefig("tables/benchmark.png", dpi=150);
plt.savefig("tables/benchmark.png", dpi=150)
if __name__ == "__main__":