Page MenuHomec4science
Files F61918428

plot.py
No OneTemporary
Actions

File Metadata

Created
Thu, May 9, 19:45

plot.py
View Options

#!/usr/bin/env python3
import pandas as pd
import numpy as np
import matplotlib
matplotlib.use("TKAgg")
import matplotlib.pyplot as plt
# Same font as JOSS
plt.rcParams['font.sans-serif'] = 'cmss10'
print("Using:", matplotlib.get_backend())
plots = {
"elastic_gcc": {"prefix": "timmings_", "suffix": "_jed"},
"cohesive_gcc": {"prefix": "timmings_", "suffix": "_jed"},
}
axes = {}
fig, (axes["elastic"], axes["cohesive"]) = plt.subplots(2, 1, sharex=True)
handles = []
for plot_name, data in plots.items():
mat, compiler = plot_name.split("_")
data["df"] = pd.read_csv(
f"""{data["prefix"]}{plot_name}{data["suffix"]}.csv""",
sep=",",
skipinitialspace=True,
)
plotting = "TTS"
psize = np.array(sorted(set(plots[list(plots.keys())[0]]["df"]["psize"])))
for plot_name, data in plots.items():
mat, compiler = plot_name.split("_")
df = data["df"]
measures = {}
if mat == "elastic":
step = df["solve_step"]
elif mat == "cohesive":
step = df["check_cohesive_stress"] + df["solve_step"]
measures["TTS"] = step * df["solve_step nb_rep"]
measures["speedup"] = step[0] / step
measures["mumps"] = df["static_solve"]
for name, measure in measures.items():
data[name] = {
"values": measure,
"median": [],
"mean": [],
"std": [],
"max": [],
"min": [],
"grouped": [],
"nb_measure": [],
}
for s in psize:
values = measure[df["psize"] == s]
data[name]["std"].append(values.std())
data[name]["mean"].append(values.mean())
data[name]["median"].append(values.median())
data[name]["max"].append(values.max())
data[name]["min"].append(values.min())
data[name]["grouped"].append(values)
data[name]["nb_measure"].append(len(values))
# axes[mat].boxplot(
# data[plotting]["grouped"], positions=psize, widths=[0.1 * s for s in psize]
# )
print(f"""{mat}: {data[plotting]["nb_measure"]}\n {psize}""")
axes[mat].plot(
psize,
data[plotting]["median"],
"-o",
label=f"""Median {plotting}.""",
)
axes[mat].fill_between(
psize,
data[plotting]["min"],
data[plotting]["max"],
alpha=0.2,
label=f"Min/Max {plotting}.",
)
axes[mat].plot(
psize,
data[plotting]["median"][0] / psize if plotting == "TTS" else psize,
"-",
label=f"Ideal {plotting}.",
)
labels = [psize[0]]
for label in psize:
if label >= labels[-1] * 2:
labels.append(label)
del labels[-1]
labels.append(psize[-1])
print(labels)
for name, ax in axes.items():
ax.set_xscale("log", base=2)
ax.set_yscale("log")
ax.set_ylabel(f"""{plotting} [{"s" if plotting == "TTS" else "-"}]""")
ax.set_xticks(ticks=labels, labels=[str(label) for label in labels])
axes["cohesive"].set_title("With cohesive insertion")
axes["elastic"].set_title("Without cohesive insertion")
plt.xlabel("Nb Cores [-]")
plt.legend(bbox_to_anchor=(1.04, 2), loc="center left", borderaxespad=0)
plt.subplots_adjust(right=0.7)
plt.savefig(f"{plotting}.svg", bbox_inches="tight")
plt.show()

Event Timeline

c4science · Help