app.py

import os
import numpy as np
import streamlit as st
import matplotlib.pyplot as plt

from sentinelhub import (
    SHConfig,
    SentinelHubRequest,
    DataCollection,
    MimeType,
    BBox,
    CRS,
    bbox_to_dimensions,
)

st.set_page_config(page_title="Sentinel-2 NDWI (B8A-B11 / B8A-B12)", layout="wide")

st.title("Sentinel-2 NDWI (agri) + détection de stress hydrique")
st.caption("NDWI agri: (B8A − SWIR) / (B8A + SWIR), avec SWIR = B11 (1610 nm) ou B12 (2200 nm)")

# ----------------------------
# Secrets / config
# ----------------------------
def make_sh_config():
    cfg = SHConfig()
    cfg.sh_client_id = st.secrets["SH_CLIENT_ID"]
    cfg.sh_client_secret = st.secrets["SH_CLIENT_SECRET"]

    # Sentinel Hub sur Copernicus Data Space
    cfg.sh_base_url = "https://sh.dataspace.copernicus.eu"
    cfg.sh_token_url = "https://identity.dataspace.copernicus.eu/auth/realms/CDSE/protocol/openid-connect/token"

    return cfg

config = make_sh_config()

# ----------------------------
# UI inputs
# ----------------------------
with st.sidebar:
    st.header("Zone (BBox WGS84)")
    st.write("Entrez les coordonnées en **lon/lat** (EPSG:4326).")
    col1, col2 = st.columns(2)
    with col1:
        min_lon = st.number_input("min_lon", value=3.85, format="%.6f")
        min_lat = st.number_input("min_lat", value=43.58, format="%.6f")
    with col2:
        max_lon = st.number_input("max_lon", value=3.95, format="%.6f")
        max_lat = st.number_input("max_lat", value=43.64, format="%.6f")

    st.divider()
    st.header("Dates")
    start_date = st.date_input("Début", value=None)
    end_date = st.date_input("Fin", value=None)

    st.divider()
    st.header("Paramètres NDWI")
    swir_choice = st.selectbox("Formule", ["B8A & B11 (1610 nm)", "B8A & B12 (2200 nm)"])
    p = st.slider("Percentile p (stress = NDWI < pᵉ percentile)", min_value=1, max_value=49, value=15, step=1)

    st.divider()
    st.header("Résolution")
    res_m = st.slider("Résolution (m/pixel) — approx", min_value=10, max_value=120, value=30, step=10)

    st.divider()
    run = st.button("🚀 Lancer", type="primary")

# Defaults for dates if user left empty
import datetime as dt
today = dt.date.today()
if start_date is None:
    start_date = today - dt.timedelta(days=14)
if end_date is None:
    end_date = today

if not (min_lon < max_lon and min_lat < max_lat):
    st.error("BBox invalide: vérifie min < max.")
    st.stop()

time_interval = (start_date.isoformat(), end_date.isoformat())

# ----------------------------
# DataCollection
# ----------------------------
# SentinelHub DataCollection standard
S2_L2A = DataCollection.SENTINEL2_L2A.define_from(
    name="s2l2a_cdse",
    api_id="sentinel-2-l2a",
    service_url="https://sh.dataspace.copernicus.eu"
)


# ----------------------------
# EvalScripts
# ----------------------------
evalscript_bands = """
//VERSION=3
function setup() {
  return {
    input: [{ bands: ["B8A", "B11", "B12", "dataMask"] }],
    output: { bands: 4, sampleType: "FLOAT32" }
  };
}
function evaluatePixel(s) { return [s.B8A, s.B11, s.B12, s.dataMask]; }
"""

evalscript_truecolor = """
//VERSION=3
function setup() {
  return {
    input: [{ bands: ["B04","B03","B02","dataMask"] }],
    output: { bands: 4, sampleType: "FLOAT32" }
  };
}
function evaluatePixel(s) { return [s.B04, s.B03, s.B02, s.dataMask]; }
"""

# ----------------------------
# Helpers
# ----------------------------
def request_tiff(evalscript: str, bbox: BBox, size: tuple[int, int]):
    req = SentinelHubRequest(
        evalscript=evalscript,
        input_data=[SentinelHubRequest.input_data(data_collection=S2_L2A, time_interval=time_interval)],
        responses=[SentinelHubRequest.output_response("default", MimeType.TIFF)],
        bbox=bbox,
        size=size,
        config=config,
    )
    return req.get_data()[0]

def normalize_rgb(rgb):
    # robust-ish normalization
    mx = np.nanpercentile(rgb, 99)
    if not np.isfinite(mx) or mx <= 0:
        mx = np.nanmax(rgb)
    if not np.isfinite(mx) or mx <= 0:
        mx = 1.0
    out = np.clip(rgb / mx, 0, 1)
    return out

# ----------------------------
# Run
# ----------------------------
if not run:
    st.info("Configure la zone + dates, puis clique **Lancer**.")
    st.stop()

with st.spinner("Téléchargement Sentinel-2 + calcul NDWI…"):
    bbox = BBox(bbox=[min_lon, min_lat, max_lon, max_lat], crs=CRS.WGS84)

    # On approx la taille via res_m (en mètres/pixel)
    # SentinelHub fait le calcul via bbox_to_dimensions (distance géodésique approx en WGS84)
    size = bbox_to_dimensions(bbox, resolution=res_m)

    # cap to avoid huge images in Spaces
    max_side = 1600
    if max(size) > max_side:
        scale = max_side / max(size)
        size = (max(64, int(size[0] * scale)), max(64, int(size[1] * scale)))

    bands = request_tiff(evalscript_bands, bbox, size)
    tc = request_tiff(evalscript_truecolor, bbox, size)

    b8a, b11, b12, m = bands[..., 0], bands[..., 1], bands[..., 2], bands[..., 3]
    rgb = tc[..., :3]
    mask_rgb = tc[..., 3]

    # masks
    b8a = np.where(m > 0, b8a, np.nan)
    b11 = np.where(m > 0, b11, np.nan)
    b12 = np.where(m > 0, b12, np.nan)

    rgb = np.where(mask_rgb[..., None] > 0, rgb, np.nan)
    rgb = normalize_rgb(rgb)
    rgb_raw = rgb.copy()  # même image true color, sans overlay


    eps = 1e-6
    ndwi_11 = (b8a - b11) / (b8a + b11 + eps)
    ndwi_12 = (b8a - b12) / (b8a + b12 + eps)

    ndwi_used = ndwi_11 if "B11" in swir_choice else ndwi_12

    thr = np.nanpercentile(ndwi_used, p)
    stress = (ndwi_used < thr).astype(float)
    stress = np.where(np.isfinite(ndwi_used), stress, np.nan)

# ----------------------------
# Visualisations
# ----------------------------
left, right = st.columns([1.2, 1.0], gap="large")

with left:
    st.subheader("Vraie couleur : raw vs stress")

    c1, c2 = st.columns(2, gap="medium")

    with c1:
        st.caption("Raw (true color)")
        fig_raw = plt.figure(figsize=(6, 6))
        plt.imshow(rgb_raw)
        plt.axis("off")
        st.pyplot(fig_raw, clear_figure=True)

    with c2:
        st.caption("Overlay stress hydrique")
        fig = plt.figure(figsize=(6, 6))
        plt.imshow(rgb)
        plt.imshow(stress, cmap="Reds", alpha=0.40, vmin=0, vmax=1)
        plt.axis("off")
        plt.title(f"Stress = NDWI < p{p} (seuil {thr:.3f})")
        st.pyplot(fig, clear_figure=True)


with right:
    st.subheader("Cartes NDWI")
    fig2 = plt.figure(figsize=(9, 4))
    ax1 = plt.subplot(1, 2, 1)
    im1 = ax1.imshow(ndwi_11, cmap="viridis")
    ax1.set_title("NDWI (B8A, B11)")
    ax1.axis("off")

    ax2 = plt.subplot(1, 2, 2)
    im2 = ax2.imshow(ndwi_12, cmap="viridis")
    ax2.set_title("NDWI (B8A, B12)")
    ax2.axis("off")

    st.pyplot(fig2, clear_figure=True)

st.divider()
st.write("**Détails**")
st.write(
    {
        "time_interval": time_interval,
        "bbox_wgs84": [min_lon, min_lat, max_lon, max_lat],
        "size_px": list(size),
        "resolution_m": res_m,
        "p": p,
        "threshold": float(thr),
        "formula_used": swir_choice,
    }
)