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import glob, os, sys; |
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sys.path.append('../utils') |
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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 st_aggrid import AgGrid |
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import logging |
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logger = logging.getLogger(__name__) |
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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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from pandas.api.types import ( |
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is_categorical_dtype, |
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is_datetime64_any_dtype, |
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is_numeric_dtype, |
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is_object_dtype, |
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is_list_like) |
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def targets(): |
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if 'key1' in st.session_state: |
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df = st.session_state['key1'].copy() |
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idx = df['NetzeroLabel_Score'].idxmax() |
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netzero_placeholder = df.loc[idx, 'text'] |
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df = df.drop(df.filter(regex='Score').columns, axis=1) |
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df = df[df.TargetLabel==True].reset_index(drop=True) |
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df['keep'] = True |
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df.drop(columns = ['ActionLabel','PolicyLabel','PlansLabel'], inplace=True) |
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st.session_state['target_hits'] = df |
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st.session_state['netzero'] = netzero_placeholder |
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def target_display(): |
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if 'key1' in st.session_state: |
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st.caption(""" **{}** is splitted into **{}** paragraphs/text chunks."""\ |
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.format(os.path.basename(st.session_state['filename']), |
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len(st.session_state['key0']))) |
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hits = st.session_state['target_hits'] |
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if len(hits) !=0: |
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count_target = sum(hits['TargetLabel'] == True) |
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count_ghg = sum(hits['GHGLabel'] == True) |
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count_netzero = sum(hits['NetzeroLabel'] == True) |
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count_nonghg = sum(hits['NonGHGLabel'] == True) |
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count_mitigation = sum(hits['MitigationLabel'] == True) |
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count_adaptation = sum(hits['AdaptationLabel'] == True) |
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c1, c2 = st.columns([1,1]) |
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with c1: |
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st.write('**Target Related Paragraphs**: `{}`'.format(count_target)) |
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st.write('**Netzero Related Paragraphs**: `{}`'.format(count_netzero)) |
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st.write('**Mitigation Related Paragraphs**: `{}`'.format(count_mitigation)) |
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with c2: |
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st.write('**GHG Target Related Paragraphs**: `{}`'.format(count_ghg)) |
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st.write('**NonGHG Target Related Paragraphs**: `{}`'.format(count_nonghg)) |
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st.write('**Adaptation Related Paragraphs**: `{}`'.format(count_adaptation)) |
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st.write('----------------') |
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st.markdown("<h4 style='text-align: left; color: black;'> Sectoral Target Related Paragraphs Count </h4>", unsafe_allow_html=True) |
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cols = list(hits.columns) |
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sector_cols = list(set(cols) - {'TargetLabel','MitigationLabel','AdaptationLabel','GHGLabel','NetzeroLabel','NonGHGLabel','text','keep','page'}) |
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sector_cols.sort() |
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hits['Sector'] = hits.apply(lambda x: [col for col in sector_cols if x[col] == True],axis=1) |
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hits['Sub-Target'] = hits.apply(lambda x: [col for col in ['GHGLabel','NetzeroLabel','NonGHGLabel'] if x[col] == True ],axis=1) |
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placeholder= [] |
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for col in sector_cols: |
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placeholder.append({'Sector':col,'Count':sum(hits[col] == True)}) |
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hits['Sector'] |
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sector_df = pd.DataFrame.from_dict(placeholder) |
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fig = px.bar(sector_df, x='Sector', y='Count') |
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st.plotly_chart(fig,use_container_width= True) |
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st.dataframe(hits[['text','page','keep','MitigationLabel','AdaptationLabel','Sector','Sub-Target',]]) |
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else: |
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st.info("🤔 No Targets Found") |
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def actions(): |
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if 'key1' in st.session_state: |
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df = st.session_state['key1'].copy() |
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df = df.drop(df.filter(regex='Score').columns, axis=1) |
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df = df[df.ActionLabel==True].reset_index(drop=True) |
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df['keep'] = True |
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df.drop(columns = ['TargetLabel','PolicyLabel','PlansLabel','GHGLabel','NetzeroLabel','NonGHGLabel'], inplace=True) |
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st.session_state['action_hits'] = df |
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def action_display(): |
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if 'key1' in st.session_state: |
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st.caption(""" **{}** is splitted into **{}** paragraphs/text chunks."""\ |
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.format(os.path.basename(st.session_state['filename']), |
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len(st.session_state['key0']))) |
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hits = st.session_state['action_hits'] |
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if len(hits) !=0: |
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count_action = sum(hits['ActionLabel'] == True) |
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count_mitigation = sum(hits['MitigationLabel'] == True) |
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count_adaptation = sum(hits['AdaptationLabel'] == True) |
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c1, c2 = st.columns([1,1]) |
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with c1: |
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st.write('**Action Related Paragraphs**: `{}`'.format(count_action)) |
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st.write('**Mitigation Related Paragraphs**: `{}`'.format(count_mitigation)) |
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with c2: |
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st.write('**Adaptation Related Paragraphs**: `{}`'.format(count_adaptation)) |
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st.write('----------------') |
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st.markdown("<h4 style='text-align: left; color: black;'> Sectoral Action Related Paragraphs Count </h4>", unsafe_allow_html=True) |
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cols = list(hits.columns) |
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sector_cols = list(set(cols) - {'ActionLabel','MitigationLabel','AdaptationLabel','GHGLabel','NetzeroLabel','NonGHGLabel','text','keep','page'}) |
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placeholder= [] |
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for col in sector_cols: |
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placeholder.append({'Sector':col,'Count':sum(hits[col] == True)}) |
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sector_df = pd.DataFrame.from_dict(placeholder) |
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fig = px.bar(sector_df, x='Sector', y='Count') |
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st.plotly_chart(fig,use_container_width= True) |
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st.dataframe(hits) |
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else: |
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st.info("🤔 No Actions Found") |
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def policy(): |
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if 'key1' in st.session_state: |
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df = st.session_state['key1'].copy() |
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df = df.drop(df.filter(regex='Score').columns, axis=1) |
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df = df[df.PolicyLabel==True].reset_index(drop=True) |
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df['keep'] = True |
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df.drop(columns = ['TargetLabel','ActionLabel','PlansLabel','GHGLabel','NetzeroLabel','NonGHGLabel'], inplace=True) |
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st.session_state['policy_hits'] = df |
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def policy_display(): |
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if 'key1' in st.session_state: |
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st.caption(""" **{}** is splitted into **{}** paragraphs/text chunks."""\ |
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.format(os.path.basename(st.session_state['filename']), |
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len(st.session_state['key0']))) |
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hits = st.session_state['policy_hits'] |
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if len(hits) !=0: |
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count_action = sum(hits['PolicyLabel'] == True) |
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count_mitigation = sum(hits['MitigationLabel'] == True) |
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count_adaptation = sum(hits['AdaptationLabel'] == True) |
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c1, c2 = st.columns([1,1]) |
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with c1: |
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st.write('**Policy Related Paragraphs**: `{}`'.format(count_action)) |
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st.write('**Mitigation Related Paragraphs**: `{}`'.format(count_mitigation)) |
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with c2: |
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st.write('**Adaptation Related Paragraphs**: `{}`'.format(count_adaptation)) |
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st.write('----------------') |
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st.markdown("<h4 style='text-align: left; color: black;'> Sectoral Policy Related Paragraphs Count </h4>", unsafe_allow_html=True) |
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cols = list(hits.columns) |
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sector_cols = list(set(cols) - {'PolicyLabel','MitigationLabel','AdaptationLabel','GHGLabel','NetzeroLabel','NonGHGLabel','text','keep','page'}) |
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placeholder= [] |
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for col in sector_cols: |
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placeholder.append({'Sector':col,'Count':sum(hits[col] == True)}) |
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sector_df = pd.DataFrame.from_dict(placeholder) |
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fig = px.bar(sector_df, x='Sector', y='Count') |
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st.plotly_chart(fig,use_container_width= True) |
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st.dataframe(hits) |
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else: |
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st.info("🤔 No Policy Found") |
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def plans(): |
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if 'key1' in st.session_state: |
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df = st.session_state['key1'].copy() |
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df = df.drop(df.filter(regex='Score').columns, axis=1) |
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df = df[df.PlansLabel==True].reset_index(drop=True) |
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df['keep'] = True |
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df.drop(columns = ['TargetLabel','PolicyLabel','ActionLabel','GHGLabel','NetzeroLabel','NonGHGLabel'], inplace=True) |
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st.session_state['plan_hits'] = df |
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def plans_display(): |
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if 'key1' in st.session_state: |
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st.caption(""" **{}** is splitted into **{}** paragraphs/text chunks."""\ |
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.format(os.path.basename(st.session_state['filename']), |
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len(st.session_state['key0']))) |
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hits = st.session_state['plan_hits'] |
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if len(hits) !=0: |
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count_action = sum(hits['PlansLabel'] == True) |
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count_mitigation = sum(hits['MitigationLabel'] == True) |
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count_adaptation = sum(hits['AdaptationLabel'] == True) |
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c1, c2 = st.columns([1,1]) |
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with c1: |
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st.write('**Plans Related Paragraphs**: `{}`'.format(count_action)) |
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st.write('**Mitigation Related Paragraphs**: `{}`'.format(count_mitigation)) |
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with c2: |
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st.write('**Adaptation Related Paragraphs**: `{}`'.format(count_adaptation)) |
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st.write('----------------') |
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st.markdown("<h4 style='text-align: left; color: black;'> Sectoral Plans Related Paragraphs Count </h4>", unsafe_allow_html=True) |
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cols = list(hits.columns) |
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sector_cols = list(set(cols) - {'PlanLabel','MitigationLabel','AdaptationLabel','GHGLabel','NetzeroLabel','NonGHGLabel','text','keep','page'}) |
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placeholder= [] |
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for col in sector_cols: |
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placeholder.append({'Sector':col,'Count':sum(hits[col] == True)}) |
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sector_df = pd.DataFrame.from_dict(placeholder) |
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fig = px.bar(sector_df, x='Sector', y='Count') |
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st.plotly_chart(fig,use_container_width= True) |
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st.dataframe(hits) |
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else: |
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st.info("🤔 No Plans Found") |
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