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import leafmap.foliumap as leafmap
from leafmap import pmtiles_style
import rioxarray
import geopandas as gpd
import streamlit as st
st.set_page_config(layout="wide", page_title="Huggingface Toy", page_icon="❦")
"""
# Huggingface Streamlit Toy
This is a toy to play around with Huggingface, Leafmap, and Streamlit
I'm looking to implement at least these things:
* Visualize raster data from an S3 bucket
* Let the user (you!) draw polygons and calculate some stats (mean, median, etc.)
* Let user load pre-defined geometries (admin levels? country borders?)
* Load boundaries based on the center of the map
"""
hi = "https://data.source.coop/vizzuality/hfp-100/hfp_2021_100m_v1-2_cog.tif"
deforest = "https://data.source.coop/vizzuality/lg-land-carbon-data/deforest_carbon_100m_cog.tif"
# Euromap info
eurocrops_pmtiles = "https://s3.us-west-2.amazonaws.com/us-west-2.opendata.source.coop/cholmes/eurocrops/eurocrops-all.pmtiles"
ec_style = pmtiles_style(eurocrops_pmtiles)
m = leafmap.Map(center=[41, -69], zoom=5)
# Moved the cog layers into optional scripts to make the pmtile information easier to see.
# m.add_cog_layer(
# deforest,
# palette="reds",
# name="deforested",
# transparent_bg=True,
# opacity=0.5,
# zoom_to_layer=False,
# )
# m.add_cog_layer(
# hi,
# palette="purples",
# name="human impact",
# transparent_bg=True,
# opacity=0.5,
# zoom_to_layer=False,
# )
m.add_pmtiles(
eurocrops_pmtiles, name="euro crops", style=ec_style, overlay=True, show=True, zoom_to_layer=False
)
polygon_ex ='{"type":"Feature","properties":{},"geometry":{"type":"Polygon","coordinates":[[[-124.628906,34.741612],[-124.628906,42.423457],[-117.246094,42.423457],[-117.246094,34.741612],[-124.628906,34.741612]]]}}'
code_ex = '''
m.add_gdf(geo, layer_name="selection")
'''
## Map controls sidebar
with st.sidebar:
'''
# Map controls
### Polygon selector
'''
polygon = st.text_area(
label = "geometry",
value = polygon_ex,
height = 400)
'''
### python code for map layer:
adjust options or add additional layers using leafmap
'''
code = st.text_area(
label = "code:",
value = code_ex,
height = 400)
# Here we actually compute the total carbon in the requested polygon
geo = gpd.read_file(polygon, driver='GeoJSON')
geo.set_crs('epsg:4326')
x = (
rioxarray.
open_rasterio('/vsicurl/'+deforest, masked=True).
rio.clip(geo.geometry.values, geo.crs, from_disk=True).
mean()
)
value = x
"### Average of tons of carbon lost:"
st.write(f'{value:,}')
st.divider()
# run whatever python code is in the python box, just for fun
eval(compile(code, "<string>", "exec"))
m.to_streamlit(height=700)
"## Explore Further"
st.write('''
To modify the map, add code to the `code` section in the sidebar to the left. Some examples of code to add are below.
''')
st.code('''
# Show deforested areas:
m.add_cog_layer(
deforest,
palette="reds",
name="deforested",
transparent_bg=True,
opacity=0.5,
zoom_to_layer=False,
)
# Show human impacted areas
m.add_cog_layer(
hi,
palette="purples",
name="human impact",
transparent_bg=True,
opacity=0.5,
zoom_to_layer=False,
)
''')
"""
## Credits
This toy was inspired by boettiger-lab's Carbon Calculator Demo: https://huggingface.co/spaces/boettiger-lab/leafmap
### Data Sources
- Human Footprint by Vizzuality, on https://beta.source.coop/repositories/vizzuality/hfp-100, citation: https://doi.org/10.3389/frsen.2023.1130896, License: Public Domain
"""
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