# set path
import glob, os, sys;
sys.path.append('../utils')
import streamlit as st
import ast
# Reading data and Declaring necessary variables
with open('ndcs/countryList.txt') as dfile:
countryList = dfile.read()
countryList = ast.literal_eval(countryList)
countrynames = list(countryList.keys())
with open('ndcs/cca.txt', encoding='utf-8', errors='ignore') as dfile:
cca_sent = dfile.read()
cca_sent = ast.literal_eval(cca_sent)
with open('ndcs/ccm.txt', encoding='utf-8', errors='ignore') as dfile:
ccm_sent = dfile.read()
ccm_sent = ast.literal_eval(ccm_sent)
def app():
#### APP INFO #####
with st.container():
st.markdown("
Check NDC Coherence
",
unsafe_allow_html=True)
st.write(' ')
st.write(' ')
with st.expander("ℹ️ - About this app", expanded=False):
st.write(
"""
The *Check NDC Coherence* application provides easy evaluation of
coherence between a given policy document and a country’s (Intended)\
Nationally Determined Contribution (INDCs/NDCs) using open-source \
data from the German Institute of Development and Sustainability’s \
(IDOS) [NDC Explorer](https://klimalog.idos-research.de/ndc/#NDCExplorer/worldMap?NewAndUpdatedNDC??income???catIncome).\
""")
st.write("")
st.write(""" User can select a country context via the drop-down menu \
on the left-hand side of the application. Subsequently, the user is \
given the opportunity to manually upload another policy document \
from the same national context or to select a pre-loaded example \
document. Thereafter, the user can choose between two categories \
to compare coherence between the documents: climate change adaptation \
and climate change mitigation. Based on the selected information, \
the application identifies relevant paragraphs in the uploaded \
document and assigns them to the respective indicator from the NDC \
Explorer. Currently, the NDC Explorer has 20 indicators under \
climate change mitigation (e.g., fossil fuel production, REDD+) and \
22 indicators under climate change adaptation (e.g., sea level rise,\
investment needs). The assignment of the paragraph to a corresponding\
indicator is based on vector similarities in which only paragraphs \
with similarity above 0.55 to the indicators are considered. """)
option = st.sidebar.selectbox('Select Country', (countrynames))
countryCode = countryList[option]