import os
import pyecharts.options as opts
from pyecharts.charts import Line
from pyecharts.faker import Faker


if __name__ == '__main__':
    outcome_dir = r'E:\Data\Research\Outcome'
    datasets_list = os.listdir(outcome_dir)
    inter_list = ['0', '0.5', '0.7', '0.9', '1']
    configs_dir = r'\Magellan+Smac+roberta-large-nli-stsb-mean-tokens+inter-'

    for _ in datasets_list:
        block_recall_list = []
        f1 = []
        interpretability = []
        for inter in inter_list:
            path = outcome_dir + rf'\{_}' + configs_dir + inter
            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('block_recall'):
                                lt = line.split(':')
                                value = float(lt[1])
                                block_recall_list.append(round(value, ndigits=3))
                            elif 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))
        interpretability[0] = 0

        c = (
            Line()
            .add_xaxis(inter_list)
            .add_yaxis("Block Recall", block_recall_list)
            .add_yaxis("F1", f1)
            .add_yaxis("Interpretability", interpretability)
            .set_global_opts(
                title_opts=opts.TitleOpts(title=_),
                # yaxis_opts=opts.AxisOpts(name="Block Recall", name_location="middle", name_gap=15, name_rotate=0),
                xaxis_opts=opts.AxisOpts(name="Interpretability Weight", name_location="middle", name_gap=25)
            )
            .render(outcome_dir + rf'\{_}\inter_weight_lines.html')
        )