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Browse files- .gitattributes +1 -0
- app.py +146 -0
- hess_papers_details.json +3 -0
- requirements.txt +2 -0
.gitattributes
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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hess_papers_details.json filter=lfs diff=lfs merge=lfs -text
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app.py
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"""
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Reference: https://huggingface.co/spaces/gwf-uwaterloo/acl-spectrum (By Ehsan Khamallo)
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"""
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import os
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import re
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import pandas as pd
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import plotly.express as px
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import streamlit as st
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st.set_page_config(layout="wide")
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DATA_FILE = "hess_papers_details.json"
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st.markdown(
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"""
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<link href="https://cdn.jsdelivr.net/npm/[email protected]/dist/css/bootstrap.min.css" rel="stylesheet" integrity="sha256-DF7Zhf293AJxJNTmh5zhoYYIMs2oXitRfBjY+9L//AY=" crossorigin="anonymous">
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<link rel="preconnect" href="https://fonts.googleapis.com">
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<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
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<link href="https://fonts.googleapis.com/css2?family=Permanent+Marker&display=swap" rel="stylesheet">
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<style>
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.title {
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font-family: 'Permanent Marker', cursive;
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font-size: 2.0rem;
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}
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</style>""",
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unsafe_allow_html=True,
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)
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st.sidebar.write(
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"""<center><p class="title">
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HESS Papers Clustering 🌎🌿
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</p></center>""",
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unsafe_allow_html=True,
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)
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st.sidebar.write(
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"""<p class="text-justify">
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A clustered visualization of all papers submitted to the
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<a href=https://www.hydrology-and-earth-system-sciences.net/>Hydrology and Earth System Sciences</a> (HESS) conference.
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5318 papers are embedded using <a href="https://huggingface.co/allenai/specter2_base">spectre2</a> and reduced with
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t-SNE. Papers span from as early as 1997 to 2023.
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</p>""",
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unsafe_allow_html=True,
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)
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def to_string_authors(list_of_authors):
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if len(list_of_authors) > 5:
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return ", ".join(list_of_authors[:5]) + ", et al."
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elif len(list_of_authors) > 2:
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return ", ".join(list_of_authors[:-1]) + ", and " + list_of_authors[-1]
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else:
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return " and ".join(list_of_authors)
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def load_df(data_file: os.PathLike):
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df = pd.read_json(data_file, orient="records")
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df["x"] = df["t-SNE1"]
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df["y"] = df["t-SNE2"]
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df["authors_trimmed"] = df["authors_trimmed"]
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#sort dataframe by year
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df['year'] = pd.to_datetime(df['year'])
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df = df.sort_values('year', ascending=True)
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df['year'] = df['year'].dt.strftime('%Y')
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return df
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@st.cache_data
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def load_dataframe():
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return load_df(DATA_FILE)
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DF = load_dataframe()
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DF["opacity"] = 0.04
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min_year, max_year = DF["year"].min(), DF["year"].max()
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with st.sidebar:
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start_year, end_year = st.select_slider(
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"Publication year",
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options=[str(y) for y in range(min_year, max_year + 1)],
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value=(str(min_year), str(max_year)),
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)
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author_names = st.text_input("Author names (separated by comma)")
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title = st.text_input("Title")
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# Work on this
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# topics = st.multiselect(
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# "Topics",
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# ["Topics 1: "],
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# ["Topics 2: "],
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# )
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start_year = int(start_year)
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end_year = int(end_year)
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df_mask = (DF["year"] >= start_year) & (DF["year"] <= end_year)
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if author_names:
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authors = [a.strip() for a in author_names.split(",")]
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author_mask = DF.authors.apply(
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lambda row: all(any(re.match(rf".*{a}.*", x, re.IGNORECASE) for x in row) for a in authors)
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)
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df_mask = df_mask & author_mask
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if title:
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df_mask = df_mask & DF.title.apply(lambda x: title.lower() in x.lower())
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DF.loc[df_mask, "opacity"] = 1.0
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st.write(f"Number of points: {DF[df_mask].shape[0]}")
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fig = px.scatter(
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DF,
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x="x",
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y="y",
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opacity=DF["opacity"],
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color=DF["cluster"],
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width=1000,
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height=800,
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custom_data=("title", "authors_trimmed", "year"),
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color_continuous_scale="haline",
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)
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fig.update_traces(
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hovertemplate="<b>%{customdata[0]}</b><br>%{customdata[1]}<br>%{customdata[2]}<br><i>"
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)
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fig.update_layout(
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showlegend=False,
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font=dict(
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family="Times New Roman",
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size=30,
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),
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hoverlabel=dict(
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align="left",
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font_size=14,
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font_family="Rockwell",
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namelength=-1,
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),
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)
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fig.update_xaxes(title="")
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fig.update_yaxes(title="")
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a = fig.show(fig, use_container_width=True)
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hess_papers_details.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:c63e3d30332ede78cc6f180ef1b1470a171ec6459b905c839dab86ab718116d0
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size 13282576
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requirements.txt
ADDED
@@ -0,0 +1,2 @@
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pandas
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plotly
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