From a6c47426d4d9888bea4818b21a461f1ac8b75cd8 Mon Sep 17 00:00:00 2001
From: Russell Jarvis <russelljarvis@protonmail.com>
Date: Fri, 10 Dec 2021 13:05:19 +1100
Subject: [PATCH] update
---
app.py | 72 +++++++++++++++++++++++++++++-----------------------------
1 file changed, 36 insertions(+), 36 deletions(-)
diff --git a/app.py b/app.py
index 835e8ac..8942437 100644
--- a/app.py
+++ b/app.py
@@ -310,8 +310,8 @@ def main():
# get_table_download_link_csv(df_author,author_name)
st.markdown(
- """Note below, the reference data set in the "the Science of Writing is Declining Over Time, was measured using a custom Flestch algorithm. It contains negative values and is downward biased.
- To illustrate the strength of the new approach. Toggle the data set to the ART corpus, which was analysed using the newer textstat standard algorithm.
+ """Note below, the reference data set in the "the Science of Writing is Declining Over Time, was measured using a custom Flestch algorithm, and it contains negative values and is downward biased.
+ The second plot contains a comparison to the ART corpus data set, which was analysed using the newer textstat standard algorithm.
"""
)
@@ -323,27 +323,27 @@ def main():
# ref_choice = "ART Corpus"
ref_choice = "Decline"
df_concat_art = pd.concat([art_df, df_author])
- df_concat_decline = pd.concat([rd_df, df_author])
+ df_concat_art = pd.concat([rd_df, df_concat_art])
+
+ fig_art0 = px.box(
+ df_concat_art,
+ x="Origin",
+ y="Reading_Level",
+ points="all",
+ color="Origin",
+ )
- if ref_choice == "ART Corpus":
- fig_art = px.box(
- df_concat_art,
- x="Origin",
- y="Reading_Level",
- points="all",
- color="Origin",
- )
- if ref_choice == "Decline":
- fig_art = px.box(
- df_concat_decline,
- x="Origin",
- y="Reading_Level",
- points="all",
- color="Origin",
- )
- st.write(fig_art)
+ #fig_art1 = px.box(
+ # df_concat_decline,
+ # x="Origin",
+ # y="Reading_Level",
+ # points="all",
+ # color="Origin",
+ #)
+ st.write(fig_art1)
+ #st.write(fig_art2)
#if "pie charts" in genre:
# temp = "{0} Summary Readability versus large sample of science".format(
@@ -381,7 +381,7 @@ def main():
if np.mean(author_score) < np.mean(bio_chem_level):
st.markdown(
"""
- ### {0} was on average easier to read relative to the ART Corpus.
+ {0} was on average easier to read relative to the ART Corpus.
""".format(
author_name
)
@@ -390,7 +390,7 @@ def main():
if np.mean(author_score) >= np.mean(bio_chem_level):
st.markdown(
"""
- ### {0} was on average more difficult to read relative to the [ART Corpus](https://www.aber.ac.uk/en/cs/research/cb/projects/art/art-corpus/), an existing library of publicly licenced scientific papers.
+ {0} was on average more difficult to read relative to the [ART Corpus](https://www.aber.ac.uk/en/cs/research/cb/projects/art/art-corpus/), an existing library of publicly licenced scientific papers.
""".format(
author_name
)
@@ -474,28 +474,28 @@ def main():
grab_set_auth.extend(paper["tokens"])
sci_corpus = create_giant_strings(grab_set_auth, not_want_list)
clouds_big_words(sci_corpus)
- alias_list = semantic_scholar_alias(author_name)
- st.text(alias_list)
+ #alias_list = semantic_scholar_alias(author_name)
+ #st.text(alias_list)
# my_expander = st.expander("Full Text Score Re calculation")
# ft = my_expander.radio("Do Full Text",("Yes","No"))
# if ft=="Yes":
# if "full text" in genre:
- if len(alias_list):
+ #if len(alias_list):
- st.markdown(
- """## Conduct a slower but more rigorous search of the full texts..."""
- )
+ # st.markdown(
+ # """## Conduct a slower but more rigorous search of the full texts..."""
+ # )
- st.markdown(
- """The exact search string match in literature search has an import relationship to the results.
- Here are some different aliases this author may have published under:"""
- )
+ # st.markdown(
+ # """The exact search string match in literature search has an import relationship to the results.
+ # Here are some different aliases this author may have published under:"""
+ # )
# for al in alias_list:
# st.markdown(al)
- alias_list.insert(0, "previously selected name")
- author_name1 = st.radio("choose name", alias_list)
- if author_name == "previously selected name":
- author_name = author_name1
+ # alias_list.insert(0, "previously selected name")
+ # author_name1 = st.radio("choose name", alias_list)
+ # if author_name == "previously selected name":
+ # author_name = author_name1
full_ar_new = call_from_front_end(author_name, tns=9, fast=False)
scraped_labels_new, author_score = frame_to_lists(full_ar_new)
--
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