From a9d1f967f3b7ce9a5c4d52023c0860c42cbb5afe Mon Sep 17 00:00:00 2001
From: Qiusheng Wu <giswqs@gmail.com>
Date: Sat, 28 Sep 2024 21:01:49 -0400
Subject: [PATCH] Add find_max_value_coords function (#907)

---
 leafmap/common.py | 46 ++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 46 insertions(+)

diff --git a/leafmap/common.py b/leafmap/common.py
index 9df27f63c7..3cf17cc901 100644
--- a/leafmap/common.py
+++ b/leafmap/common.py
@@ -14782,3 +14782,49 @@ def get_nwi_by_huc8(
 
     gdf = gpd.read_file(filepath)
     return gdf
+
+
+def find_max_value_coords(
+    image: str, band_dix: int = 1, dst_crs: Optional[str] = None
+) -> Tuple[Union[float, int], Union[float, int], float]:
+    """
+    Find the coordinates of the pixel with the maximum value in a GeoTIFF file.
+
+    Args:
+        geotiff_file (str): Path to the GeoTIFF file.
+        band_dix (int, optional): The band index (default is 1).
+        dst_crs (str, optional): The destination CRS in EPSG format (e.g., "EPSG:4326").
+                                 If None, returns the original x, y coordinates.
+
+    Returns:
+        tuple: x, y coordinates of the pixel with the maximum value, and the maximum value.
+               If dst_crs is provided, returns the reprojected coordinates.
+    """
+    import rasterio
+    import numpy as np
+    from rasterio.transform import xy
+    from pyproj import Transformer
+
+    # Open the GeoTIFF file
+    with rasterio.open(image) as src:
+        # Read the raster data (assuming band 1)
+        data = src.read(band_dix)
+
+        # Find the index of the maximum value
+        max_value = np.max(data)
+        max_index = np.unravel_index(np.argmax(data), data.shape)
+
+        # Get the row and column of the pixel with the maximum value
+        row, col = max_index
+        x, y = col, row
+        print(f"Row: {row}, Column: {col}")
+
+        # Get the original coordinates (x, y) of the pixel
+
+        # If a destination CRS is provided, transform the coordinates
+        if dst_crs:
+            x, y = xy(src.transform, row, col)
+            transformer = Transformer.from_crs(src.crs, dst_crs, always_xy=True)
+            x, y = transformer.transform(x, y)
+
+        return x, y, max_value