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import streamlit as st
import pandas as pd
import numpy as np
import json
from streamlit_echarts import st_echarts
from app.show_examples import *
from app.content import *
import pandas as pd
from model_information import get_dataframe
info_df = get_dataframe()
def draw_table(dataset_displayname, metrics):
with open('organize_model_results.json', 'r') as f:
organize_model_results = json.load(f)
dataset_nickname = displayname2datasetname[dataset_displayname]
model_results = organize_model_results[dataset_nickname][metrics]
model_name_mapping = {key.strip(): val for key, val in zip(info_df['Original Name'], info_df['Proper Display Name'])}
model_results = {model_name_mapping.get(key, key): val for key, val in model_results.items()}
# = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = =
'''
Show Table
'''
with st.container():
st.markdown('##### TABLE')
model_link_mapping = {key.strip(): val for key, val in zip(info_df['Proper Display Name'], info_df['Link'])}
chart_data_table = pd.DataFrame(list(model_results.items()), columns=["model_show", dataset_displayname])
chart_data_table["model_link"] = chart_data_table["model_show"].map(model_link_mapping)
def highlight_first_element(x):
# Create a DataFrame with the same shape as the input
df_style = pd.DataFrame('', index=x.index, columns=x.columns)
df_style.iloc[0, 1] = 'background-color: #b0c1d7'
return df_style
if dataset_displayname in [
'LibriSpeech-Clean',
'LibriSpeech-Other',
'CommonVoice-15-EN',
'Peoples-Speech',
'GigaSpeech-1',
'Earnings-21',
'Earnings-22',
'TED-LIUM-3',
'TED-LIUM-3-LongForm',
'AISHELL-ASR-ZH',
'MNSC-PART1-ASR',
'MNSC-PART2-ASR',
'MNSC-PART3-ASR',
'MNSC-PART4-ASR',
'MNSC-PART5-ASR',
'MNSC-PART6-ASR',
'CNA',
'IDPC',
'Parliament',
'UKUS-News',
'Mediacorp',
'IDPC-Short',
'Parliament-Short',
'UKUS-News-Short',
'Mediacorp-Short',
'YTB-ASR-Batch1',
'YTB-ASR-Batch2',
'SEAME-Dev-Man',
'SEAME-Dev-Sge',
'GigaSpeech2-Indo',
'GigaSpeech2-Thai',
'GigaSpeech2-Viet',
]:
chart_data_table = chart_data_table.sort_values(
by = chart_data_table.columns[1],
ascending = True
).reset_index(drop=True)
else:
chart_data_table = chart_data_table.sort_values(
by = chart_data_table.columns[1],
ascending = False
).reset_index(drop=True)
styled_df = chart_data_table.style.format(
{chart_data_table.columns[1]: "{:.3f}"}
).apply(
highlight_first_element, axis=None
)
st.dataframe(
styled_df,
column_config={
'model_show' : 'Model',
chart_data_table.columns[1]: {'alignment': 'left'},
"model_link" : st.column_config.LinkColumn("Model Link"),
},
hide_index=True,
use_container_width=True
)
# = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = =
'''
Show Chart
'''
# Initialize a session state variable for toggling the chart visibility
if "show_chart" not in st.session_state:
st.session_state.show_chart = False
# Create a button to toggle visibility
if st.button("Show Chart"):
st.session_state.show_chart = not st.session_state.show_chart
if st.session_state.show_chart:
with st.container():
st.markdown('##### CHART')
# Get Values
data_values = chart_data_table.iloc[:, 1]
# Calculate Q1 and Q3
q1 = data_values.quantile(0.25)
q3 = data_values.quantile(0.75)
# Calculate IQR
iqr = q3 - q1
# Define lower and upper bounds (1.5*IQR is a common threshold)
lower_bound = q1 - 1.5 * iqr
upper_bound = q3 + 1.5 * iqr
# Filter data within the bounds
filtered_data = data_values[(data_values >= lower_bound) & (data_values <= upper_bound)]
# Calculate min and max values after outlier handling
min_value = round(filtered_data.min() - 0.1 * filtered_data.min(), 3)
max_value = round(filtered_data.max() + 0.1 * filtered_data.max(), 3)
options = {
# "title": {"text": f"{dataset_name}"},
"tooltip": {
"trigger": "axis",
"axisPointer": {"type": "cross", "label": {"backgroundColor": "#6a7985"}},
"triggerOn": 'mousemove',
},
"legend": {"data": ['Overall Accuracy']},
"toolbox": {"feature": {"saveAsImage": {}}},
"grid": {"left": "3%", "right": "4%", "bottom": "3%", "containLabel": True},
"xAxis": [
{
"type": "category",
"boundaryGap": True,
"triggerEvent": True,
"data": chart_data_table['model_show'].tolist(),
}
],
"yAxis": [{"type": "value",
"min": min_value,
"max": max_value,
"boundaryGap": True
# "splitNumber": 10
}],
"series": [{
"name": f"{dataset_nickname}",
"type": "bar",
"data": chart_data_table[f'{dataset_displayname}'].tolist(),
}],
}
events = {
"click": "function(params) { return params.value }"
}
value = st_echarts(options=options, events=events, height="500px")
# = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = =
'''
Show Examples
'''
# Initialize a session state variable for toggling the chart visibility
if "show_examples" not in st.session_state:
st.session_state.show_examples = False
# Create a button to toggle visibility
if st.button("Show Examples"):
st.session_state.show_examples = not st.session_state.show_examples
if st.session_state.show_examples:
st.markdown('To be implemented')
# # if dataset_name in ['Earnings21-Test', 'Earnings22-Test', 'Tedlium3-Test', 'Tedlium3-Long-form-Test']:
# if dataset_name in []:
# pass
# else:
# show_examples(category_name, dataset_name, chart_data['Model'].tolist(), display_model_names)
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