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matching_dependency/draw/draw_f1_inter_bars.py

45 lines
1.7 KiB

import os
import pyecharts
from pyecharts.charts import Line
from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.globals import ThemeType
if __name__ == '__main__':
outcome_dir = r'E:\Data\Research\Outcome'
12 months ago
configs_dir = r'\Magellan+Smac+roberta-large-nli-stsb-mean-tokens+inter-0.5'
datasets_list = os.listdir(outcome_dir)
f1 = []
interpretability = []
for _ in datasets_list:
path = outcome_dir + rf'\{_}' + configs_dir
statistics_files = os.listdir(path)
for i in statistics_files:
if i.startswith('eval_result'):
with open(path + rf'\{i}', 'r') as f:
# 读取每一行的md加入该文件的md列表
for line in f.readlines():
if line.startswith('F1'):
lt = line.split(' ')
value = float(lt[2].replace('%', ''))/100
f1.append(round(value, ndigits=3))
elif line.startswith('interpretability'):
lt = line.split(':')
value = float(lt[1])
interpretability.append(round(value, ndigits=3))
c = (
Bar()
.add_xaxis(
datasets_list
)
.add_yaxis('F1', f1)
.add_yaxis('Interpretability', interpretability)
.set_global_opts(
xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=-15)),
title_opts=opts.TitleOpts(title="各数据集F1值与预测结果可解释比例", subtitle="可解释性比重0.5"),
)
.render("output/F1_Inter_bars.html")
)