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import os
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import pandas as pd
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from pyecharts import options as opts
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from pyecharts.charts import Bar
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from pyecharts.faker import Faker
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from pyecharts.globals import ThemeType
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if __name__ == '__main__':
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outcome_dir = r'E:\Data\Research\Outcome'
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inter_list = ['0', '0.5', '0.7', '0.9', '1']
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configs_dir = r'\Magellan+Smac+roberta-large-nli-stsb-mean-tokens+inter-'
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datasets_list = os.listdir(outcome_dir)
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for _ in datasets_list:
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for inter in inter_list:
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path = outcome_dir + rf'\{_}' + configs_dir + inter
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statistics_files = os.listdir(path)
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length = 0
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for file in statistics_files:
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if file.startswith('predictions'):
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preds = pd.read_csv(path + rf'\{file}', encoding='ISO-8859-1')
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preds = preds[['predicted', 'confidence']]
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preds = preds.astype(float)
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preds = preds[preds['predicted'] == 1.0]
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length = len(preds)
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li = []
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zeros = len(preds[preds['confidence'] == 0])
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dot_02 = len(preds[(preds['confidence'] > 0) & (preds['confidence'] <= 0.2)])
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dot_24 = len(preds[(preds['confidence'] > 0.2) & (preds['confidence'] <= 0.4)])
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dot_46 = len(preds[(preds['confidence'] > 0.4) & (preds['confidence'] <= 0.6)])
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dot_68 = len(preds[(preds['confidence'] > 0.6) & (preds['confidence'] <= 0.8)])
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dot_80 = len(preds[(preds['confidence'] > 0.8) & (preds['confidence'] <= 1.0)])
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for number in [zeros, dot_02, dot_24, dot_46, dot_68, dot_80]:
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li.append(round(number * 100 / length, ndigits=3))
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c = (
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Bar(init_opts=opts.InitOpts(theme=ThemeType.WALDEN))
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.add_xaxis(['conf=0', '0<conf≤0.2', '0.2<conf≤0.4', '0.4<conf≤0.6', '0.6<conf≤0.8', '0.8<conf≤1'])
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.add_yaxis(_, li, category_gap=2)
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.set_global_opts(
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yaxis_opts=opts.AxisOpts(
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name="Proportion",
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type_="value",
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min_=0,
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max_=100,
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position="left",
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axisline_opts=opts.AxisLineOpts(
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linestyle_opts=opts.LineStyleOpts()
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),
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axislabel_opts=opts.LabelOpts(formatter="{value}%"),
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),
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title_opts=opts.TitleOpts(title="Confidence Histogram"),
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xaxis_opts=opts.AxisOpts(name="Intervals")
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)
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.render(path + r"\confidence_histogram.html")
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)
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