Update app.py
Browse files
app.py
CHANGED
@@ -71,11 +71,13 @@ def visualize_isnad(taraf_num, yaxis):
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taraf_author = matn_info[matn_info['taraf_ID'] == taraf_num]['Author'].to_list()
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taraf_hadith_number = matn_info[matn_info['taraf_ID'] == taraf_num]['Hadith Number'].to_list()
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lst_hadith = []
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for i in range(len(taraf_hadith_split)):
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# This checks each hadith in the Taraf, is that book id hadith id found in each of the edges of isnad_info
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#This loop get the end transmitter of each Hadith in the Taraf
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isnad_in_hadith1 =
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isnad_hadith1 =
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G = nx.from_pandas_edgelist(isnad_hadith1, source = 'Source', target = 'Destination', create_using = nx.DiGraph())
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node = [int(n) for n, d in G.out_degree() if d == 0][0]
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gen_node = narrator_bios[narrator_bios['Rawi ID']==node]['Generation'].iloc[0]
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@@ -84,8 +86,7 @@ def visualize_isnad(taraf_num, yaxis):
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df = pd.DataFrame(lst_hadith, columns = ['Matn', 'Generation', 'Name', 'Book_Name', 'Author', 'Book Hadith Number', 'End Transmitter ID', 'Hadith Number'])
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#hadith_cleaned = isnad_info['Hadiths Cleaned'].apply(lambda x: any(i in x for i in taraf_hadith_split) )
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isnad_hadith = isnad_info[hadith_cleaned]
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isnad_hadith['Teacher'] = isnad_hadith['Source'].apply(lambda x: narrator_bios[narrator_bios['Rawi ID'].astype(int) == int(x)]['Famous Name'].to_list())
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isnad_hadith['Student'] = isnad_hadith['Destination'].apply(lambda x: narrator_bios[narrator_bios['Rawi ID'].astype(int) == int(x)]['Famous Name'].to_list())
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isnad_hadith['Teacher'] = isnad_hadith['Teacher'].apply(lambda x: x[0] if len(x)==1 else 'فلان')
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taraf_author = matn_info[matn_info['taraf_ID'] == taraf_num]['Author'].to_list()
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taraf_hadith_number = matn_info[matn_info['taraf_ID'] == taraf_num]['Hadith Number'].to_list()
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lst_hadith = []
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hadith_cleaned = isnad_info['Tarafs Cleaned'].apply(lambda x: taraf_num in x)
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isnad_hadith = isnad_info[hadith_cleaned]
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for i in range(len(taraf_hadith_split)):
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# This checks each hadith in the Taraf, is that book id hadith id found in each of the edges of isnad_info
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#This loop get the end transmitter of each Hadith in the Taraf
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isnad_in_hadith1 = isnad_hadith['Hadiths Cleaned'].apply(lambda x: taraf_hadith_split[i] in x )
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isnad_hadith1 = isnad_hadith[isnad_in_hadith1][['Source', 'Destination']]
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G = nx.from_pandas_edgelist(isnad_hadith1, source = 'Source', target = 'Destination', create_using = nx.DiGraph())
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node = [int(n) for n, d in G.out_degree() if d == 0][0]
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gen_node = narrator_bios[narrator_bios['Rawi ID']==node]['Generation'].iloc[0]
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df = pd.DataFrame(lst_hadith, columns = ['Matn', 'Generation', 'Name', 'Book_Name', 'Author', 'Book Hadith Number', 'End Transmitter ID', 'Hadith Number'])
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#hadith_cleaned = isnad_info['Hadiths Cleaned'].apply(lambda x: any(i in x for i in taraf_hadith_split) )
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isnad_hadith['Teacher'] = isnad_hadith['Source'].apply(lambda x: narrator_bios[narrator_bios['Rawi ID'].astype(int) == int(x)]['Famous Name'].to_list())
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isnad_hadith['Student'] = isnad_hadith['Destination'].apply(lambda x: narrator_bios[narrator_bios['Rawi ID'].astype(int) == int(x)]['Famous Name'].to_list())
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isnad_hadith['Teacher'] = isnad_hadith['Teacher'].apply(lambda x: x[0] if len(x)==1 else 'فلان')
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