From 9add285aa051cf74d99732e72668ef300d9039c4 Mon Sep 17 00:00:00 2001
From: Romain Hugonnet <romain.hugonnet@gmail.com>
Date: Thu, 5 Dec 2024 13:52:55 -0900
Subject: [PATCH] Linting

---
 doc/source/sliderule.md | 8 ++++----
 xdem/dem.py             | 4 ++--
 2 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/doc/source/sliderule.md b/doc/source/sliderule.md
index a5d70101..dca3e16f 100644
--- a/doc/source/sliderule.md
+++ b/doc/source/sliderule.md
@@ -16,10 +16,10 @@ kernelspec:
 
 # Pair with SlideRule for reference
 
-Most analysis of **xDEM relies on independent, high-precision elevation data to use as reference**, whether for 
+Most analysis of **xDEM relies on independent, high-precision elevation data to use as reference**, whether for
 coregistration, bias-corrections or uncertainty analysis.
 
-[SlideRule](https://slideruleearth.io/) provides the ideal way to retrieve such data by accessing big data archives 
+[SlideRule](https://slideruleearth.io/) provides the ideal way to retrieve such data by accessing big data archives
 of high-precision elevations, such as ICESat-2 or GEDI, efficiently in the cloud.
 
 Below, a short example to coregister and perform uncertainty analysis of a DEM with ICESat-2 ATL06.
@@ -53,7 +53,7 @@ inlier_mask = ~glacier_outlines.create_mask(dem)
 bounds = list(dem.get_bounds_projected(4326))
 region = sliderule.toregion(bounds)["poly"]
 
-# Initiliaze SlideRule client
+# Initialize SlideRule client
 sliderule.init("slideruleearth.io")
 
 # Define desired parameters for ICESat-2 ATL06
@@ -109,4 +109,4 @@ vect.plot(column="dh_aft", cmap='RdYlBu', vmin=-10, vmax=10, ax=ax[1], markersiz
 _ = ax[1].set_yticklabels([])
 plt.tight_layout()
 plt.savefig("/home/atom/ongoing/test.png", dpi=400)
-```
\ No newline at end of file
+```
diff --git a/xdem/dem.py b/xdem/dem.py
index 441d08e2..17f31bef 100644
--- a/xdem/dem.py
+++ b/xdem/dem.py
@@ -490,7 +490,7 @@ def coregister_3d(
     def estimate_uncertainty(
         self,
         other_elev: DEM | gpd.GeoDataFrame,
-        stable_terrain: Mask | NDArrayb = None,
+        stable_terrain: Mask = None,
         approach: Literal["H2022", "R2009", "Basic"] = "H2022",
         precision_of_other: Literal["finer"] | Literal["same"] = "finer",
         spread_estimator: Callable[[NDArrayf], np.floating[Any]] = nmad,
@@ -542,7 +542,7 @@ def estimate_uncertainty(
 
         # Stable terrain depending on input
         if stable_terrain is None:
-            stable_terrain = np.ones(self.shape, dtype="uint8")
+            stable_terrain = self.copy(new_array=np.ones(self.shape, dtype=bool))
 
         # Elevation change with the other DEM or elevation point cloud
         if isinstance(other_elev, DEM):