delete due to wrong path
Browse files- draw_diagram.py +0 -223
draw_diagram.py
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import streamlit as st
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import pandas as pd
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import numpy as np
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from streamlit_echarts import st_echarts
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from app.show_examples import *
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from app.content import *
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import pandas as pd
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from model_information import get_dataframe
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info_df = get_dataframe()
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def draw(folder_name, category_name, displayname, metrics, cus_sort=True):
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folder = f"./results_organized/{metrics}/"
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# Load the results from CSV
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data_path = f'{folder}/{category_name.lower()}.csv'
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chart_data = pd.read_csv(data_path).round(3)
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dataset_name = displayname2datasetname[displayname]
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chart_data = chart_data[['Model', dataset_name]]
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# Rename to proper display name
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chart_data = chart_data.rename(columns=datasetname2diaplayname)
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st.markdown("""
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<style>
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.stMultiSelect [data-baseweb=select] span {
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max-width: 800px;
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font-size: 0.9rem;
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background-color: #3C6478 !important; /* Background color for selected items */
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color: white; /* Change text color */
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back
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}
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</style>
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""", unsafe_allow_html=True)
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# remap model names
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display_model_names = {key.strip() :val.strip() for key, val in zip(info_df['Original Name'], info_df['Proper Display Name'])}
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chart_data['model_show'] = chart_data['Model'].map(lambda x: display_model_names.get(x, x))
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models = st.multiselect("Please choose the model",
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sorted(chart_data['model_show'].tolist()),
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default = sorted(chart_data['model_show'].tolist()),
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)
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chart_data = chart_data[chart_data['model_show'].isin(models)]
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chart_data = chart_data.sort_values(by=[displayname], ascending=cus_sort).dropna(axis=0)
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if len(chart_data) == 0: return
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# = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = =
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'''
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Show Table
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'''
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with st.container():
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st.markdown('##### TABLE')
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model_link = {key.strip(): val for key, val in zip(info_df['Proper Display Name'], info_df['Link'])}
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chart_data['model_link'] = chart_data['model_show'].map(model_link)
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chart_data_table = chart_data[['model_show', chart_data.columns[1], chart_data.columns[3]]]
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# Format numeric columns to 2 decimal places
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#chart_data_table[chart_data_table.columns[1]] = chart_data_table[chart_data_table.columns[1]].apply(lambda x: round(float(x), 3) if isinstance(float(x), (int, float)) else float(x))
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cur_dataset_name = chart_data_table.columns[1]
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def highlight_first_element(x):
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# Create a DataFrame with the same shape as the input
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df_style = pd.DataFrame('', index=x.index, columns=x.columns)
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# Apply background color to the first element in row 0 (df[0][0])
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# df_style.iloc[0, 1] = 'background-color: #b0c1d7; color: white'
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df_style.iloc[0, 1] = 'background-color: #b0c1d7'
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return df_style
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if cur_dataset_name in [
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'LibriSpeech-Clean',
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'LibriSpeech-Other',
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'CommonVoice-15-EN',
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'Peoples-Speech',
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'GigaSpeech-1',
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'Earnings-21',
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'Earnings-22',
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'TED-LIUM-3',
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'TED-LIUM-3-LongForm',
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'AISHELL-ASR-ZH',
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'MNSC-PART1-ASR',
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'MNSC-PART2-ASR',
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'MNSC-PART3-ASR',
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'MNSC-PART4-ASR',
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'MNSC-PART5-ASR',
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'MNSC-PART6-ASR',
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'CNA',
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'IDPC',
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'Parliament',
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'UKUS-News',
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'Mediacorp',
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'IDPC-Short',
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'Parliament-Short',
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'UKUS-News-Short',
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'Mediacorp-Short',
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'YTB-ASR-Batch1',
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'YTB-ASR-Batch2',
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'SEAME-Dev-Man',
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'SEAME-Dev-Sge',
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]:
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chart_data_table = chart_data_table.sort_values(
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by=chart_data_table.columns[1],
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ascending=True
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).reset_index(drop=True)
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else:
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chart_data_table = chart_data_table.sort_values(
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by=chart_data_table.columns[1],
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ascending=False
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).reset_index(drop=True)
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styled_df = chart_data_table.style.format(
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{chart_data_table.columns[1]: "{:.3f}"}
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).apply(
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highlight_first_element, axis=None
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)
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st.dataframe(
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styled_df,
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column_config={
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'model_show': 'Model',
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chart_data_table.columns[1]: {'alignment': 'left'},
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"model_link": st.column_config.LinkColumn(
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"Model Link",
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),
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},
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hide_index=True,
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use_container_width=True
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)
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# = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = =
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'''
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Show Chart
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'''
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# Initialize a session state variable for toggling the chart visibility
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if "show_chart" not in st.session_state:
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st.session_state.show_chart = False
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# Create a button to toggle visibility
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if st.button("Show Chart"):
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st.session_state.show_chart = not st.session_state.show_chart
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if st.session_state.show_chart:
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with st.container():
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st.markdown('##### CHART')
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# Get Values
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data_values = chart_data.iloc[:, 1]
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# Calculate Q1 and Q3
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q1 = data_values.quantile(0.25)
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q3 = data_values.quantile(0.75)
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# Calculate IQR
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iqr = q3 - q1
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# Define lower and upper bounds (1.5*IQR is a common threshold)
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lower_bound = q1 - 1.5 * iqr
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upper_bound = q3 + 1.5 * iqr
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# Filter data within the bounds
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filtered_data = data_values[(data_values >= lower_bound) & (data_values <= upper_bound)]
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# Calculate min and max values after outlier handling
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min_value = round(filtered_data.min() - 0.1 * filtered_data.min(), 3)
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max_value = round(filtered_data.max() + 0.1 * filtered_data.max(), 3)
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options = {
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# "title": {"text": f"{dataset_name}"},
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"tooltip": {
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"trigger": "axis",
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"axisPointer": {"type": "cross", "label": {"backgroundColor": "#6a7985"}},
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"triggerOn": 'mousemove',
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},
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"legend": {"data": ['Overall Accuracy']},
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"toolbox": {"feature": {"saveAsImage": {}}},
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"grid": {"left": "3%", "right": "4%", "bottom": "3%", "containLabel": True},
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"xAxis": [
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{
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"type": "category",
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"boundaryGap": True,
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"triggerEvent": True,
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"data": chart_data['model_show'].tolist(),
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}
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],
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"yAxis": [{"type": "value",
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"min": min_value,
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"max": max_value,
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"boundaryGap": True
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# "splitNumber": 10
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}],
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"series": [{
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"name": f"{dataset_name}",
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"type": "bar",
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"data": chart_data[f'{displayname}'].tolist(),
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}],
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}
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events = {
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"click": "function(params) { return params.value }"
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}
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value = st_echarts(options=options, events=events, height="500px")
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