Commit a6c47426 authored by Russell Jarvis's avatar Russell Jarvis 💬
Browse files

update

parent 4c568bda
......@@ -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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