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| import streamlit as st | |
| import datetime | |
| # from .utils import PACKAGE_ROOT | |
| # from lrt.utils.functions import template | |
| APP_VERSION = 'v0.1.0' | |
| def render_sidebar(): | |
| icons = f''' | |
| <center> | |
| <a href="https://github.com/leoxiang66/research-trends-analysis"><img src = "https://cdn-icons-png.flaticon.com/512/733/733609.png" width="23"></img></a> <a href="mailto:[email protected]"><img src="https://cdn-icons-png.flaticon.com/512/646/646094.png" alt="email" width = "27" ></a> | |
| </center> | |
| ''' | |
| sidebar_markdown = f''' | |
| <center> | |
| <img src="https://raw.githubusercontent.com/leoxiang66/streamlit-tutorial/IDP/widgets/static/tum.png" alt="TUM" width="150"/> | |
| <h1> | |
| TrendFlow | |
| </h1> | |
| <code> | |
| {APP_VERSION} | |
| </code> | |
| </center> | |
| {icons} | |
| --- | |
| ## Choose the Paper Search Platforms''' | |
| st.sidebar.markdown(sidebar_markdown, unsafe_allow_html=True) | |
| # elvsier = st.sidebar.checkbox('Elvsier',value=True) | |
| # IEEE = st.sidebar.checkbox('IEEE',value=False) | |
| # google = st.sidebar.checkbox('Google Scholar') | |
| platforms = st.sidebar.multiselect('Platforms', options= | |
| [ | |
| # 'Elvsier', | |
| 'IEEE', | |
| # 'Google Scholar', | |
| 'Arxiv', | |
| 'Paper with Code' | |
| ], default=[ | |
| # 'Elvsier', | |
| 'IEEE', | |
| # 'Google Scholar', | |
| 'Arxiv', | |
| 'Paper with Code' | |
| ]) | |
| st.sidebar.markdown('## Choose the max number of papers to search') | |
| number_papers = st.sidebar.slider('number', 10, 100, 20, 5) | |
| st.sidebar.markdown('## Choose the start year of publication') | |
| this_year = datetime.date.today().year | |
| start_year = st.sidebar.slider('year start:', 2000, this_year, 2010, 1) | |
| st.sidebar.markdown('## Choose the end year of publication') | |
| end_year = st.sidebar.slider('year end:', 2000, this_year, this_year, 1) | |
| with st.sidebar: | |
| st.markdown('## Adjust hyperparameters') | |
| with st.expander('Clustering Options'): | |
| standardization = st.selectbox('1) Standardization before clustering', options=['no', 'yes'], index=0) | |
| dr = st.selectbox('2) Dimension reduction', options=['none', 'pca'], index=0) | |
| tmp = min(number_papers, 15) | |
| max_k = st.slider('3) Max number of clusters', 2, tmp, tmp // 2) | |
| cluster_model = st.selectbox('4) Clustering model', options=['Gaussian Mixture Model', 'K-means'], index=0) | |
| with st.expander('Keyphrases Generation Options'): | |
| model_cpt = st.selectbox(label='Model checkpoint', options=['KeyBart', 'KeyBartAdapter', 'keyphrase-transformer'], index=0) | |
| st.markdown('---') | |
| st.markdown(icons, unsafe_allow_html=True) | |
| st.markdown(f'''<center>Copyright © 2022 - {datetime.datetime.now().year} by Tao Xiang</center>''', unsafe_allow_html=True) | |
| # st.sidebar.markdown('## Choose the number of clusters') | |
| # k = st.sidebar.slider('number',1,10,3) | |
| return platforms, number_papers, start_year, end_year, dict( | |
| dimension_reduction=dr, | |
| max_k=max_k, | |
| model_cpt=model_cpt, | |
| standardization=True if standardization == 'yes' else False, | |
| cluster_model='gmm' if cluster_model == 'Gaussian Mixture Model' else 'kmeans-euclidean' | |
| ) |