import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import matplotlib
def main():
sns.set(style="ticks")
matplotlib.rcParams['font.sans-serif'] = "Fira Sans"
matplotlib.rcParams['font.size'] = 10
matplotlib.rcParams['axes.titlesize'] = 14
matplotlib.rcParams['axes.titleweight'] = "bold"
print("Read raw data")
latencies = pd.read_csv("result/arm_cm4-combined.csv", index_col=0)
stats = latencies.describe()
stats.to_csv("result/stats.csv")
columns = latencies.columns
new_columns = []
for column in columns:
column = column.replace("arm_cm4-", "")
column = column.replace("latency-", "")
column = column.replace("_release", "")
new_columns.append(column)
latencies.columns = new_columns
print("Plot histogram")
for column in latencies.columns:
plt.clf()
sns.histplot(latencies, x=column, stat="probability")
plt.title(column)
plt.xlabel("Latency / s")
plt.savefig("result/{}-hist.svg".format(column), bbox_inches='tight')
plt.clf()
sns.histplot(latencies, bins=100)
plt.title("Latency combined")
plt.xlabel("Latency / s")
plt.savefig("result/hist.svg", bbox_inches='tight')
print("Plot boxplot")
plt.clf()
sns.boxplot(data=latencies)
plt.ylabel("Latency / s")
plt.yscale('log')
plt.xticks(rotation=60)
plt.savefig("result/box.svg", bbox_inches='tight')
if __name__ == "__main__":
main()