app.py

import leafmap.foliumap as leafmap
import rioxarray
import geopandas as gpd
import streamlit as st

# import altair as alt
# import ibis
# from ibis import _
# import ibis.selectors as s
from streamlit_folium import st_folium
import json
from leafmap import pmtiles_style

# Common Functions


# Actual Page content below
st.set_page_config(layout="wide", page_title="Huggingface Toy", page_icon="❦")
st.title("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,
)

# TODO: automate getting the polygon from the figrue
# TODO: Calculate some metrics given the area.
# TODO: add a raster to the toy
# TODO: Change calculation depending on what layers are present
# TODO: Dynamically check the center of the map and change what's displayed depending on that.

polygon_ex = '{"type":"Feature","properties":{},"geometry":{"type":"Polygon","coordinates":[[[-6.108398,40.780541],[-6.108398,54.342149],[15.908203,54.342149],[15.908203,40.780541],[-6.108398,40.780541]]]}}'
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
# NOTE: It is not possible to access user_roi_bounds from streamlit per: https://github.com/opengeos/leafmap/discussions/152#discussioncomment-1870416
# bounds = m.user_roi_bounds()
# if bounds is not None:
#     bounds.set_crs("epsg:4326")

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"))
st_data = m.to_streamlit(height=700, bidirectional=True)
polygon = st_data["last_active_drawing"]
if polygon is not None:
    "### The Polygon is: "
    st.write(f"{polygon}")

"## 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
"""