From 29a0d8a4aca2fa39f32eba0a86f80a138ec6d830 Mon Sep 17 00:00:00 2001
From: Romain Hugonnet <romain.hugonnet@gmail.com>
Date: Mon, 21 Oct 2024 18:32:14 -0800
Subject: [PATCH 1/8] Start sliderule pairing example

---
 doc/source/sliderule.md | 106 ++++++++++++++++++++++++++++++++++++++++
 xdem/dem.py             |  24 +++++++++
 2 files changed, 130 insertions(+)
 create mode 100644 doc/source/sliderule.md

diff --git a/doc/source/sliderule.md b/doc/source/sliderule.md
new file mode 100644
index 00000000..f1bd4702
--- /dev/null
+++ b/doc/source/sliderule.md
@@ -0,0 +1,106 @@
+---
+file_format: mystnb
+mystnb:
+  execution_timeout: 60
+jupytext:
+  formats: md:myst
+  text_representation:
+    extension: .md
+    format_name: myst
+kernelspec:
+  display_name: xdem-env
+  language: python
+  name: xdem
+---
+(cheatsheet)=
+
+# Pair with SlideRule for reference
+
+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 
+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.
+
+```{code-cell} ipython3
+:tags: [remove-cell]
+
+# To get a good resolution for displayed figures
+from matplotlib import pyplot
+pyplot.rcParams['figure.dpi'] = 600
+pyplot.rcParams['savefig.dpi'] = 600
+pyplot.rcParams['font.size'] = 9  # Default 10 is a bit too big for coregistration plots
+```
+
+```{code-cell} ipython3
+from sliderule import sliderule, icesat2
+import geoutils as gu
+import xdem
+import numpy as np
+
+# Open example DEM
+dem = xdem.DEM(xdem.examples.get_path("longyearbyen_ref_dem"))
+
+# Derive inlier mask as glaciers
+glacier_outlines = gu.Vector(xdem.examples.get_path("longyearbyen_glacier_outlines"))
+inlier_mask = ~glacier_outlines.create_mask(dem)
+
+# Define region of interest as DEM footprint
+bounds = list(dem.get_bounds_projected(4326))
+region = sliderule.toregion(bounds)["poly"]
+
+# Initiliaze SlideRule client
+sliderule.init("slideruleearth.io")
+
+# Define desired parameters for ICESat-2 ATL06
+params = {
+    "poly": region,
+    "srt": icesat2.SRT_LAND,  # Surface-type
+    "cnf": icesat2.CNF_SURFACE_HIGH,  # Confidence level
+    "ats": 20.0,  # Minimum along-track spread
+    "cnt": 10,  # Minimum count
+}
+
+# Request ATL06 subsetting in parallel
+gdf = icesat2.atl06sp(params)
+gdf = gdf[np.isfinite(gdf["h_li"])] # Keep valid data
+gdf = gdf[gdf["atl06_quality_summary"]==0]  # Keep very high-confidence data
+```
+
+```{code-cell} ipython3
+# Run a translation coregistration
+nk = xdem.coreg.NuthKaab()
+aligned_dem = nk.fit_and_apply(reference_elev=gdf, to_be_aligned_elev=dem, inlier_mask=inlier_mask, z_name="h_li")
+```
+
+```{code-cell} ipython3
+:tags: [hide-input]
+:mystnb:
+:  code_prompt_show: "Show plotting code"
+:  code_prompt_hide: "Hide plotting code"
+
+hs = dem.hillshade()
+# Plot before and after
+import matplotlib.pyplot as plt
+gdf = gdf.to_crs(dem.crs)
+f, ax = plt.subplots(1, 2)
+ax[0].set_title("Before translations")
+hs.plot(cmap="Greys_r", add_cbar=False)
+z_pc = dem.interp_points((gdf.geometry.x.values, gdf.geometry.y.values))
+gdf["dh_bef"] = gdf["h_li"] - z_pc
+gdf.plot(column="dh_bef", cmap='RdYlBu', vmin=-30, vmax=30, ax=ax[0], markersize=0.5)
+ax[1].set_title("After translations")
+hs.plot(cmap="Greys_r", add_cbar=False)
+z_pc_aligned = aligned_dem.interp_points((gdf.geometry.x.values, gdf.geometry.y.values))
+gdf["dh_aft"] = gdf["h_li"] - z_pc_aligned
+gdf.plot(column="dh_aft", cmap='RdYlBu', vmin=-30, vmax=30, ax=ax[1], markersize=0.5)
+_ = ax[1].set_yticklabels([])
+plt.savefig("/home/atom/ongoing/test.png", dpi=400)
+```
+
+```{code-cell} ipython3
+# Run uncertainty analysis
+sig_dem, rho_sig = aligned_dem.estimate_uncertainty(other_elev=gdf, z_name="h_li")
+```
\ No newline at end of file
diff --git a/xdem/dem.py b/xdem/dem.py
index c235b897..3022825a 100644
--- a/xdem/dem.py
+++ b/xdem/dem.py
@@ -532,8 +532,32 @@ def estimate_uncertainty(
         :return: Uncertainty raster, Variogram of uncertainty correlation.
         """
 
+<<<<<<< Updated upstream
         # Elevation change
         dh = other_dem.reproject(self, silent=True) - self
+=======
+        # Summarize approach steps
+        approach_dict = {
+            "H2022": {"heterosc": True, "multi_range": True},
+            "R2009": {"heterosc": False, "multi_range": True},
+            "Basic": {"heterosc": False, "multi_range": False},
+        }
+
+        # Stable terrain depending on input
+        if stable_terrain is None:
+            stable_terrain = np.ones(self.shape, dtype="uint8")
+
+        # Elevation change with the other DEM or elevation point cloud
+        if isinstance(other_elev, DEM):
+            dh = other_elev.reproject(self, silent=True) - self
+        elif isinstance(other_elev, gpd.GeoDataFrame):
+            other_elev = other_elev.to_crs(self.crs)
+            points = (other_elev.geometry.x.values, other_elev.geometry.y.values)
+            dh = other_elev[z_name].values - self.interp_points(points)
+            stable_terrain = stable_terrain.interp_points(points, method="nearest")
+        else:
+            raise TypeError("Other elevation should be a DEM or elevation point cloud object.")
+>>>>>>> Stashed changes
 
         # If the precision of the other DEM is the same, divide the dh values by sqrt(2)
         # See Equation 7 and 8 of Hugonnet et al. (2022)

From d09cd68289296168db1f5722a3a7415d38f60d0b Mon Sep 17 00:00:00 2001
From: Romain Hugonnet <romain.hugonnet@gmail.com>
Date: Thu, 5 Dec 2024 13:49:39 -0900
Subject: [PATCH 2/8] Finalize coregistration section of example

---
 dev-environment.yml     |  1 +
 doc/source/sliderule.md | 34 ++++++++++++++++++++--------------
 2 files changed, 21 insertions(+), 14 deletions(-)

diff --git a/dev-environment.yml b/dev-environment.yml
index 73eddcd5..3bb0093a 100644
--- a/dev-environment.yml
+++ b/dev-environment.yml
@@ -48,6 +48,7 @@ dependencies:
   - graphviz
   - myst-nb
   - numpydoc
+  - sliderule  # To run pairing example
 
   - pip:
     # Optional dependency
diff --git a/doc/source/sliderule.md b/doc/source/sliderule.md
index f1bd4702..a5d70101 100644
--- a/doc/source/sliderule.md
+++ b/doc/source/sliderule.md
@@ -42,6 +42,8 @@ import numpy as np
 
 # Open example DEM
 dem = xdem.DEM(xdem.examples.get_path("longyearbyen_ref_dem"))
+dem.set_vcrs("EGM96")
+dem = dem.to_vcrs("Ellipsoid")
 
 # Derive inlier mask as glaciers
 glacier_outlines = gu.Vector(xdem.examples.get_path("longyearbyen_glacier_outlines"))
@@ -81,26 +83,30 @@ aligned_dem = nk.fit_and_apply(reference_elev=gdf, to_be_aligned_elev=dem, inlie
 :  code_prompt_show: "Show plotting code"
 :  code_prompt_hide: "Hide plotting code"
 
+# Derive hillshade for background
 hs = dem.hillshade()
+# Convert to same CRS
+gdf = gdf.to_crs(dem.crs)
+vect = gu.Vector(gdf)
+# Mask areas not in inlier mask (glaciers here)
+pc_mask = inlier_mask.astype("uint8").interp_points((gdf.geometry.x.values, gdf.geometry.y.values), method="nearest")
+vect.ds = vect.ds[pc_mask == 1]
+# Get point differences before and after
+z_pc = dem.interp_points((vect.ds.geometry.x.values, vect.ds.geometry.y.values))
+vect.ds["dh_bef"] = vect.ds["h_li"] - z_pc
+z_pc_aligned = aligned_dem.interp_points((vect.ds.geometry.x.values, vect.ds.geometry.y.values))
+vect.ds["dh_aft"] = vect.ds["h_li"] - z_pc_aligned
+
 # Plot before and after
 import matplotlib.pyplot as plt
-gdf = gdf.to_crs(dem.crs)
 f, ax = plt.subplots(1, 2)
-ax[0].set_title("Before translations")
+ax[0].set_title("Before\ncoregistration")
 hs.plot(cmap="Greys_r", add_cbar=False)
-z_pc = dem.interp_points((gdf.geometry.x.values, gdf.geometry.y.values))
-gdf["dh_bef"] = gdf["h_li"] - z_pc
-gdf.plot(column="dh_bef", cmap='RdYlBu', vmin=-30, vmax=30, ax=ax[0], markersize=0.5)
-ax[1].set_title("After translations")
+vect.plot(column="dh_bef", cmap='RdYlBu', vmin=-10, vmax=10, ax=ax[0], markersize=0.5, cbar_title="Elevation differences (m)")
+ax[1].set_title("After\ncoregistration")
 hs.plot(cmap="Greys_r", add_cbar=False)
-z_pc_aligned = aligned_dem.interp_points((gdf.geometry.x.values, gdf.geometry.y.values))
-gdf["dh_aft"] = gdf["h_li"] - z_pc_aligned
-gdf.plot(column="dh_aft", cmap='RdYlBu', vmin=-30, vmax=30, ax=ax[1], markersize=0.5)
+vect.plot(column="dh_aft", cmap='RdYlBu', vmin=-10, vmax=10, ax=ax[1], markersize=0.5, legend=True, cbar_title="Elevation differences (m)")
 _ = ax[1].set_yticklabels([])
+plt.tight_layout()
 plt.savefig("/home/atom/ongoing/test.png", dpi=400)
-```
-
-```{code-cell} ipython3
-# Run uncertainty analysis
-sig_dem, rho_sig = aligned_dem.estimate_uncertainty(other_elev=gdf, z_name="h_li")
 ```
\ No newline at end of file

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 3/8] 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):

From e0093aefdcc0a678fb9529bab8b1abeb28cbbbb8 Mon Sep 17 00:00:00 2001
From: Romain Hugonnet <romain.hugonnet@gmail.com>
Date: Thu, 5 Dec 2024 14:47:53 -0900
Subject: [PATCH 4/8] Fix errors

---
 doc/source/sliderule.md | 13 ++++++++++---
 xdem/dem.py             |  1 +
 2 files changed, 11 insertions(+), 3 deletions(-)

diff --git a/doc/source/sliderule.md b/doc/source/sliderule.md
index dca3e16f..45459b85 100644
--- a/doc/source/sliderule.md
+++ b/doc/source/sliderule.md
@@ -1,7 +1,7 @@
 ---
 file_format: mystnb
 mystnb:
-  execution_timeout: 60
+  execution_timeout: 150
 jupytext:
   formats: md:myst
   text_representation:
@@ -14,7 +14,7 @@ kernelspec:
 ---
 (cheatsheet)=
 
-# Pair with SlideRule for reference
+# Elevation reference with SlideRule
 
 Most analysis of **xDEM relies on independent, high-precision elevation data to use as reference**, whether for
 coregistration, bias-corrections or uncertainty analysis.
@@ -75,6 +75,9 @@ gdf = gdf[gdf["atl06_quality_summary"]==0]  # Keep very high-confidence data
 # Run a translation coregistration
 nk = xdem.coreg.NuthKaab()
 aligned_dem = nk.fit_and_apply(reference_elev=gdf, to_be_aligned_elev=dem, inlier_mask=inlier_mask, z_name="h_li")
+
+# Print the estimated translation parameters
+print([k+f': {nk.meta["outputs"]["affine"][k]:.2f} meters' for k in ["shift_x", "shift_y", "shift_z"]])
 ```
 
 ```{code-cell} ipython3
@@ -108,5 +111,9 @@ hs.plot(cmap="Greys_r", add_cbar=False)
 vect.plot(column="dh_aft", cmap='RdYlBu', vmin=-10, vmax=10, ax=ax[1], markersize=0.5, legend=True, cbar_title="Elevation differences (m)")
 _ = ax[1].set_yticklabels([])
 plt.tight_layout()
-plt.savefig("/home/atom/ongoing/test.png", dpi=400)
+```
+
+```{code-cell} ipython3
+# Show full coregistration summary
+nk.info()
 ```
diff --git a/xdem/dem.py b/xdem/dem.py
index 17f31bef..458f24ca 100644
--- a/xdem/dem.py
+++ b/xdem/dem.py
@@ -547,6 +547,7 @@ def estimate_uncertainty(
         # Elevation change with the other DEM or elevation point cloud
         if isinstance(other_elev, DEM):
             dh = other_elev.reproject(self, silent=True) - self
+            stable_terrain = stable_terrain.data
         elif isinstance(other_elev, gpd.GeoDataFrame):
             other_elev = other_elev.to_crs(self.crs)
             points = (other_elev.geometry.x.values, other_elev.geometry.y.values)

From d5cade7b30cea68a9124160ffd3e69cbf3414f82 Mon Sep 17 00:00:00 2001
From: Romain Hugonnet <romain.hugonnet@gmail.com>
Date: Thu, 5 Dec 2024 15:28:15 -0900
Subject: [PATCH 5/8] Add to index

---
 doc/source/index.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/doc/source/index.md b/doc/source/index.md
index d2be2649..d49c2f06 100644
--- a/doc/source/index.md
+++ b/doc/source/index.md
@@ -123,6 +123,7 @@ uncertainty
 
 guides
 cheatsheet
+sliderule
 ecosystem
 ```
 

From 71ed3e53f0658ae6690cb414b9b0e1aedfd65331 Mon Sep 17 00:00:00 2001
From: Romain Hugonnet <romain.hugonnet@gmail.com>
Date: Thu, 5 Dec 2024 16:50:17 -0900
Subject: [PATCH 6/8] Incremental changes

---
 doc/source/conf.py      |  1 +
 doc/source/sliderule.md | 31 ++++++++++++++++++++++++++-----
 2 files changed, 27 insertions(+), 5 deletions(-)

diff --git a/doc/source/conf.py b/doc/source/conf.py
index c8d5dd7a..19df486e 100644
--- a/doc/source/conf.py
+++ b/doc/source/conf.py
@@ -79,6 +79,7 @@
     "geopandas": ("https://geopandas.org/en/stable", None),
     "xarray": ("https://docs.xarray.dev/en/stable/", None),
     "rioxarray": ("https://corteva.github.io/rioxarray/stable/", None),
+    "sliderule": ("https://slideruleearth.io/web/rtd/", None),
 }
 
 sphinx_gallery_conf = {
diff --git a/doc/source/sliderule.md b/doc/source/sliderule.md
index 45459b85..e38eb365 100644
--- a/doc/source/sliderule.md
+++ b/doc/source/sliderule.md
@@ -14,7 +14,7 @@ kernelspec:
 ---
 (cheatsheet)=
 
-# Elevation reference with SlideRule
+# Pair with reference data
 
 Most analysis of **xDEM relies on independent, high-precision elevation data to use as reference**, whether for
 coregistration, bias-corrections or uncertainty analysis.
@@ -22,7 +22,7 @@ coregistration, bias-corrections or uncertainty analysis.
 [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.
+Below, a short example to coregister our example DEM with ICESat-2 ATL06 reference data.
 
 ```{code-cell} ipython3
 :tags: [remove-cell]
@@ -34,6 +34,10 @@ pyplot.rcParams['savefig.dpi'] = 600
 pyplot.rcParams['font.size'] = 9  # Default 10 is a bit too big for coregistration plots
 ```
 
+## Retrieving reference data
+
+We load our example DEM data, and define the region of interest from its footprint.
+
 ```{code-cell} ipython3
 from sliderule import sliderule, icesat2
 import geoutils as gu
@@ -52,7 +56,11 @@ inlier_mask = ~glacier_outlines.create_mask(dem)
 # Define region of interest as DEM footprint
 bounds = list(dem.get_bounds_projected(4326))
 region = sliderule.toregion(bounds)["poly"]
+```
 
+We can then initialize the SlideRule client, and fetch the ICESat-2 ATL06 reference data using {func}`icesat2.atl06sp`.
+
+```{code-cell} ipython3
 # Initialize SlideRule client
 sliderule.init("slideruleearth.io")
 
@@ -71,15 +79,22 @@ gdf = gdf[np.isfinite(gdf["h_li"])] # Keep valid data
 gdf = gdf[gdf["atl06_quality_summary"]==0]  # Keep very high-confidence data
 ```
 
+## Coregistration
+
+Running the coregistration is as simple as passing the geodataframe to {func}`~xdem.coreg.Coreg.fit_and_apply`,
+specifying the name of the column to use.
+
 ```{code-cell} ipython3
 # Run a translation coregistration
 nk = xdem.coreg.NuthKaab()
-aligned_dem = nk.fit_and_apply(reference_elev=gdf, to_be_aligned_elev=dem, inlier_mask=inlier_mask, z_name="h_li")
+aligned_dem = nk.fit_and_apply(reference_elev=gdf, to_be_aligned_elev=dem, inlier_mask=inlier_mask, z_name="h_li", random_state=42)
 
 # Print the estimated translation parameters
 print([k+f': {nk.meta["outputs"]["affine"][k]:.2f} meters' for k in ["shift_x", "shift_y", "shift_z"]])
 ```
 
+We can plot the improvement due to the coregistration.
+
 ```{code-cell} ipython3
 :tags: [hide-input]
 :mystnb:
@@ -96,9 +111,13 @@ pc_mask = inlier_mask.astype("uint8").interp_points((gdf.geometry.x.values, gdf.
 vect.ds = vect.ds[pc_mask == 1]
 # Get point differences before and after
 z_pc = dem.interp_points((vect.ds.geometry.x.values, vect.ds.geometry.y.values))
-vect.ds["dh_bef"] = vect.ds["h_li"] - z_pc
 z_pc_aligned = aligned_dem.interp_points((vect.ds.geometry.x.values, vect.ds.geometry.y.values))
-vect.ds["dh_aft"] = vect.ds["h_li"] - z_pc_aligned
+import warnings
+# GeoPandas raising unexpected warning
+with warnings.catch_warnings():
+    warnings.simplefilter("ignore")
+    vect["dh_bef"] = vect["h_li"] - z_pc
+    vect["dh_aft"] = vect["h_li"] - z_pc_aligned
 
 # Plot before and after
 import matplotlib.pyplot as plt
@@ -113,6 +132,8 @@ _ = ax[1].set_yticklabels([])
 plt.tight_layout()
 ```
 
+And the full information around the coregistration using {func}`~xdem.coreg.Coreg.info`.
+
 ```{code-cell} ipython3
 # Show full coregistration summary
 nk.info()

From e843376e783c56cd38dcaeda8a3ae6f7a9f04eaa Mon Sep 17 00:00:00 2001
From: Romain Hugonnet <romain.hugonnet@gmail.com>
Date: Thu, 5 Dec 2024 17:00:18 -0900
Subject: [PATCH 7/8] Streamlining

---
 doc/source/sliderule.md | 9 +++++----
 1 file changed, 5 insertions(+), 4 deletions(-)

diff --git a/doc/source/sliderule.md b/doc/source/sliderule.md
index e38eb365..274aa857 100644
--- a/doc/source/sliderule.md
+++ b/doc/source/sliderule.md
@@ -58,7 +58,8 @@ bounds = list(dem.get_bounds_projected(4326))
 region = sliderule.toregion(bounds)["poly"]
 ```
 
-We can then initialize the SlideRule client, and fetch the ICESat-2 ATL06 reference data using {func}`icesat2.atl06sp`.
+We can then initialize the SlideRule client, and fetch the ICESat-2 ATL06 reference data in the region of interest 
+using {func}`icesat2.atl06sp`.
 
 ```{code-cell} ipython3
 # Initialize SlideRule client
@@ -93,7 +94,7 @@ aligned_dem = nk.fit_and_apply(reference_elev=gdf, to_be_aligned_elev=dem, inlie
 print([k+f': {nk.meta["outputs"]["affine"][k]:.2f} meters' for k in ["shift_x", "shift_y", "shift_z"]])
 ```
 
-We can plot the improvement due to the coregistration.
+Let's visualize the improvement in elevation differences after coregistration.
 
 ```{code-cell} ipython3
 :tags: [hide-input]
@@ -132,9 +133,9 @@ _ = ax[1].set_yticklabels([])
 plt.tight_layout()
 ```
 
-And the full information around the coregistration using {func}`~xdem.coreg.Coreg.info`.
+We can print a coregistration summary using {func}`~xdem.coreg.Coreg.info`.
 
 ```{code-cell} ipython3
-# Show full coregistration summary
+# Show full coregistration information
 nk.info()
 ```

From 031e7612e492a00a7da559f301ac1eb81eca6b07 Mon Sep 17 00:00:00 2001
From: Romain Hugonnet <romain.hugonnet@gmail.com>
Date: Thu, 5 Dec 2024 17:00:35 -0900
Subject: [PATCH 8/8] Linting

---
 doc/source/sliderule.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/doc/source/sliderule.md b/doc/source/sliderule.md
index 274aa857..88c58ea4 100644
--- a/doc/source/sliderule.md
+++ b/doc/source/sliderule.md
@@ -58,7 +58,7 @@ bounds = list(dem.get_bounds_projected(4326))
 region = sliderule.toregion(bounds)["poly"]
 ```
 
-We can then initialize the SlideRule client, and fetch the ICESat-2 ATL06 reference data in the region of interest 
+We can then initialize the SlideRule client, and fetch the ICESat-2 ATL06 reference data in the region of interest
 using {func}`icesat2.atl06sp`.
 
 ```{code-cell} ipython3