leavoigt commited on
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c2f3090
1 Parent(s): c8b94cd

Delete appStore/classifier.py

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  1. appStore/classifier.py +0 -116
appStore/classifier.py DELETED
@@ -1,116 +0,0 @@
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- # set path
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- import glob, os, sys;
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- sys.path.append('../utils')
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- from setfit import SetFitModel
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- #import needed libraries
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- #import seaborn as sns
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- #import matplotlib.pyplot as plt
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- #import numpy as np
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- #import pandas as pd
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- #import streamlit as st
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- from utils.groups_classifier import load_groupsClassifier, groups_classification
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- #import logging
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- #logger = logging.getLogger(__name__)
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- from utils.config import get_classifier_params
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- #from utils.preprocessing import paraLengthCheck
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- #from io import BytesIO
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- #import xlsxwriter
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- #import plotly.express as px
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-
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- vg_model = SetFitModel.from_pretrained("leavoigt/vulnerable_groups")
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-
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-
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- # Retrieve the necessary paramaters
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- classifier_identifier = 'group_classification'
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- params = get_classifier_params(classifier_identifier)
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-
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- def app():
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-
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- ### Main app code ###
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- with st.container():
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-
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- # Classify groups
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- df = group_classification(haystack_doc=df, threshold= params['threshold'])
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-
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- def groups_display():
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- # if 'key1' in st.session_state:
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- # df = st.session_state.key1
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-
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-
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- # df['Action_check'] = df['Policy-Action Label'].apply(lambda x: True if 'Action' in x else False)
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- # hits = df[df['Action_check'] == True]
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- # # hits['GHG Label'] = hits['GHG Label'].apply(lambda i: _lab_dict[i])
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- # range_val = min(5,len(hits))
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- # if range_val !=0:
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- # count_action = len(hits)
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-
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- # st.write("")
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- # st.markdown("###### Top few Action Classified paragraph/text results from list of {} classified paragraphs ######".format(count_action))
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- # st.markdown("""<hr style="height:10px;border:none;color:#097969;background-color:#097969;" /> """, unsafe_allow_html=True)
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- # range_val = min(5,len(hits))
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- # for i in range(range_val):
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- # # the page number reflects the page that contains the main paragraph
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- # # according to split limit, the overlapping part can be on a separate page
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- # st.write('**Result {}** : `page {}`, `Sector: {}`,\
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- # `Indicators: {}`, `Adapt-Mitig :{}`'\
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- # .format(i+1,
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- # hits.iloc[i]['page'], hits.iloc[i]['Sector Label'],
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- # hits.iloc[i]['Indicator Label'],hits.iloc[i]['Adapt-Mitig Label']))
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- # st.write("\t Text: \t{}".format(hits.iloc[i]['text'].replace("\n", " ")))
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- # hits = hits.reset_index(drop =True)
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- # st.write('----------------')
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- # st.write('Explore the data')
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- # st.write(hits)
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- # df.drop(columns = ['Action_check'],inplace=True)
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- # df_xlsx = to_excel(df)
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-
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- # with st.sidebar:
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- # st.write('-------------')
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- # st.download_button(label='📥 Download Result',
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- # data=df_xlsx ,
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- # file_name= 'cpu_analysis.xlsx')
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-
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- # else:
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- # st.info("🤔 No Actions found")
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-
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-
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- # def groups_display():
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- # if 'key1' in st.session_state:
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- # df = st.session_state.key1
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-
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-
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- # df['Policy_check'] = df['Policy-Action Label'].apply(lambda x: True if 'Policies & Plans' in x else False)
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- # hits = df[df['Policy_check'] == True]
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- # # hits['GHG Label'] = hits['GHG Label'].apply(lambda i: _lab_dict[i])
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- # range_val = min(5,len(hits))
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- # if range_val !=0:
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- # count_policy = len(hits)
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-
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- # st.write("")
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- # st.markdown("###### Top few Policy/Plans Classified paragraph/text results from list of {} classified paragraphs ######".format(count_policy))
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- # st.markdown("""<hr style="height:10px;border:none;color:#097969;background-color:#097969;" /> """, unsafe_allow_html=True)
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- # range_val = min(5,len(hits))
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- # for i in range(range_val):
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- # # the page number reflects the page that contains the main paragraph
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- # # according to split limit, the overlapping part can be on a separate page
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- # st.write('**Result {}** : `page {}`, `Sector: {}`,\
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- # `Indicators: {}`, `Adapt-Mitig :{}`'\
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- # .format(i+1,
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- # hits.iloc[i]['page'], hits.iloc[i]['Sector Label'],
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- # hits.iloc[i]['Indicator Label'],hits.iloc[i]['Adapt-Mitig Label']))
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- # st.write("\t Text: \t{}".format(hits.iloc[i]['text'].replace("\n", " ")))
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- # hits = hits.reset_index(drop =True)
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- # st.write('----------------')
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- # st.write('Explore the data')
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- # st.write(hits)
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- # df.drop(columns = ['Policy_check'],inplace=True)
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- # df_xlsx = to_excel(df)
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-
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- # with st.sidebar:
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- # st.write('-------------')
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- # st.download_button(label='📥 Download Result',
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- # data=df_xlsx ,
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- # file_name= 'vulnerable_groups.xlsx')
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-
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- # else:
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- # st.info("🤔 No Groups found")