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Merge pull request #1 from 0xSolidityWeb3/0xSolidityWeb3-patch-2
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Fix moest-np#84 Schools are not plotted in map in streamlit app
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@0xSolidityWeb3
0xSolidityWeb3 committed May 7, 2024
2 parents da8e6aa + 8086ea2 commit de3d861
Showing 1 changed file with 71 additions and 58 deletions.
129 changes: 71 additions & 58 deletions app.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,18 +6,16 @@
import streamlit as st
from streamlit_folium import st_folium


#Page Setup
# Page Setup
st.set_page_config(
page_title="MOEST Exam Center Calculator",
page_icon=":school:",
# page_icon="https://avatars.githubusercontent.com/u/167545222?s=200&v=4", # official logo
layout="wide",
initial_sidebar_state="expanded",
page_title="MOEST Exam Center Calculator",
page_icon=":school:",
layout="wide",
initial_sidebar_state="expanded",
theme="light", # Default theme is light
)

# Custom CSS
# Custom CSS
custom_css = """
<style>
.st-ag.st-e4.st-e5 {
Expand All @@ -41,11 +39,12 @@
if 'filter_value' not in st.session_state:
st.session_state.filter_value = None

#Maps setup
m = folium.Map(location=[27.7007, 85.3001], zoom_start=12, )
fg = folium.FeatureGroup(name="Allocated Centers")
# Maps setup
m = folium.Map(location=[27.7007, 85.3001], zoom_start=12)
fg_centers = folium.FeatureGroup(name="Allocated Centers")
fg_schools = folium.FeatureGroup(name="Schools")

#Sidebar
# Sidebar
with st.sidebar:

add_side_header = st.sidebar.title("Random Center Calculator")
Expand All @@ -66,8 +65,8 @@
"School Center Distance",
"View School Data",
"View Centers Data",
"View Pref Data"
])
"View Pref Data"
])

tab1.subheader("School Center")
tab2.subheader("School Center Distance")
Expand Down Expand Up @@ -126,15 +125,15 @@ def run_center_randomizer(schools_tsv, centers_tsv, prefs_tsv):
cmd = f"python school_center.py {schools_tsv} {centers_tsv} {prefs_tsv}"
subprocess.run(cmd, shell=True)

#Function to filter the data
# Function to filter the data
def filter_data(df, filter_type, filter_value):
if filter_type in df.columns:
df = df[df[filter_type] == filter_value]
return df
else:
st.error(f"{filter_type} is not a valid column in the DataFrame.")
return pd.DataFrame()
return pd.DataFrame()

# Run logic after the button is clicked
if calculate:
st.session_state.calculate_clicked = True
Expand Down Expand Up @@ -162,7 +161,7 @@ def save_file_to_temp(file_obj):
os.unlink(centers_path)
os.unlink(prefs_path)

# Set the paths for the output files[UPDATE LATER TO BE FLEXIBLE]
# Set the paths for the output files [UPDATE LATER TO BE FLEXIBLE]
school_center_file = "results/school-center.tsv"
school_center_distance_file = "results/school-center-distance.tsv"

Expand All @@ -189,51 +188,65 @@ def save_file_to_temp(file_obj):

# Display an input field based on the selected filter type
if st.session_state.filter_type:
if st.session_state.filter_type == 'school':
# Create filter options with school name and code
filter_options = [f"{code} | {name}" for name, code in zip(df_school_center['school'].unique(), df_school_center['scode'].unique())]

elif st.session_state.filter_type == 'center':
# Create filter options with center name and code
filter_options = [f"{code} | {name}" for name, code in zip(df_school_center['center'].unique(), df_school_center['cscode'].unique())]

# Display a selectbox for selection
st.session_state.filter_value = tab1.selectbox(f"Select a value for {st.session_state.filter_type}:", filter_options)

# Split the selected value to extract name and code
code, name = st.session_state.filter_value.split(' | ')

# Filter the DataFrame based on the selected type and value
filtered_df = filter_data(df_school_center, st.session_state.filter_type, name)

if st.session_state.filter_value:
# Remove thousand separator comma in scode and cscode
styled_df = filtered_df.style.format({
"cscode": lambda x: '{:.0f}'.format(x),
"scode": lambda x: '{:.0f}'.format(x)
})
tab1.dataframe(styled_df , hide_index=True)
tab1.subheader('Map')
tab1.divider()
for index, center in filtered_df.iterrows():
fg.add_child(
folium.Marker(
location=[center.center_lat, center.center_long],
popup=f"{(center.center).title()}\nAllocation: {center.allocation}",
tooltip=f"{center.center}",
icon=folium.Icon(color="red")
)
)
m.add_child(fg)
with tab1:
st_folium( m, width=1200, height=400 )

if st.session_state.filter_type == 'school':
# Create filter options with school name and code
filter_options = [f"{code} | {name}" for name, code in zip(df_school_center['school'].unique(), df_school_center['scode'].unique())]

elif st.session_state.filter_type == 'center':
# Create filter options with center name and code
filter_options = [f"{code} | {name}" for name, code in zip(df_school_center['center'].unique(), df_school_center['cscode'].unique())]

# Display a selectbox for selection
st.session_state.filter_value = tab1.selectbox(f"Select a value for {st.session_state.filter_type}:", filter_options)

# Split the selected value to extract name and code
code, name = st.session_state.filter_value.split(' | ')

# Filter the DataFrame based on the selected type and value
filtered_df = filter_data(df_school_center, st.session_state.filter_type, name)

if st.session_state.filter_value:
# Remove thousand separator comma in scode and cscode
filtered_df['scode'] = filtered_df['scode'].astype(int)
filtered_df['cscode'] = filtered_df['cscode'].astype(int)

# Reset index after filtering
filtered_df.reset_index(drop=True, inplace=True)

# Add serial number starting from 1
filtered_df.index = range(1, len(filtered_df) + 1)

# Plot schools and centers on the map
for index, center in filtered_df.iterrows():
if st.session_state.filter_type == 'school':
fg_schools.add_child(
folium.Marker(
location=[center.school_lat, center.school_long],
popup=f"{(center.school).title()}\nAllocation: {center.allocation}",
tooltip=f"{center.school}",
icon=folium.Icon(color="blue", icon="university", prefix='fa')
)
)
elif st.session_state.filter_type == 'center':
fg_centers.add_child(
folium.Marker(
location=[center.center_lat, center.center_long],
popup=f"{(center.center).title()}\nAllocation: {center.allocation}",
tooltip=f"{center.center}",
icon=folium.Icon(color="red", icon="heart", prefix='fa')
)
)
m.add_child(fg_centers)
m.add_child(fg_schools)
with tab1:
st_folium(m, width=1200, height=400)

tab1.divider()
tab1.subheader('All Data')
tab1.dataframe(df_school_center)
else:
tab1.info("No calculated data available.", icon="ℹ️")

if 'school_center_distance' in st.session_state.calculated_data:
df = pd.read_csv(st.session_state.calculated_data['school_center_distance'], sep="\t")
tab2.dataframe(df)
Expand Down

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