Incremental commit on doc

doc/source/distance_ops.md

@@ -57,12 +57,27 @@ vect = gu.Vector(gu.examples.get_path("everest_rgi_outlines"))
 ```{code-cell} ipython3
 # Compute proximity to vector outlines
 proximity = vect.proximity(rast)
-proximity.plot(cmap="viridis", cbar_title="Proximity (m)")
+```
+
+```{code-cell} ipython3
+:tags: [hide-input]
+:mystnb:
+:  code_prompt_show: "Show the code for plotting the figure"
+:  code_prompt_hide: "Hide the code for plotting the figure"
+
+f, ax = plt.subplots(1, 2)
+ax[0].set_title("Raster and vector")
+rast.plot(ax=ax[0], cmap="gray", add_cbar=False)
+vect.plot(ref_crs=rast, ax=ax[0], ec="k", fc="none")
+ax[1].set_title("Proximity")
+proximity.plot(ax=ax[1], cmap="viridis", cbar_title="Distance to outlines (m)")
+_ = ax[1].set_yticklabels([])
+plt.tight_layout()
 ```
 
 ## Buffering without overlap
 
-Buffering consists in expanding vector geometries equally in all directions. However, this can often lead to overlap 
+Buffering consists in **expanding or collapsing vector geometries equally in all directions**. However, this can often lead to overlap 
 between shapes, which is sometimes undesirable. Using Voronoi polygons, we provide a buffering method with overlap.
 
 {func}`geoutils.Vector.buffer_without_overlap`
@@ -72,5 +87,5 @@ between shapes, which is sometimes undesirable. Using Voronoi polygons, we provi
 vect_buff_nolap = vect.buffer_without_overlap(buffer_size=500)
 # Plot with color to see that the attributes are retained for every feature
 vect.plot(ax="new", ec="k", column="Area", alpha=0.5, add_cbar=False)
-vect_buff_nolap.plot(column="Area", cbar_title="Glacier area (km)")
-```
+vect_buff_nolap.plot(column="Area", cbar_title="Buffer around initial features\ncolored by glacier area (km)")
+```

doc/source/index.md

@@ -31,7 +31,7 @@ GeoUtils ``v0.1`` is released, with most features drafted 3 years ago now finali
 
 ----------------
 
-GeoUtils is built on top of core geospatial packages (Rasterio, GeoPandas) and numerical packages 
+GeoUtils is built on top of core geospatial packages (Rasterio, GeoPandas, PyProj) and numerical packages 
 (NumPy, Xarray, SciPy) to provide **consistent higher-level functionalities at the interface of raster, vector and point 
 cloud objects** (such as match-reference reprojection, point interpolation or gridding).
 

doc/source/pointcloud_class.md

@@ -1,3 +1,11 @@
 (point-cloud)=
 # The georeferenced point cloud ({class}`~geoutils.PointCloud`)
 
+Coming soon!
+
+In the meantime, most point cloud operations (for instance in {ref}`raster-vector-point`) return a 
+{class}`~geoutils.Vector` with only point geometries and a specific `data_column_name` corresponding to the point 
+cloud values.
+
+
+

doc/source/raster_vector_point.md

@@ -59,7 +59,22 @@ vect = gu.Vector(gu.examples.get_path("everest_rgi_outlines"))
 ```{code-cell} ipython3
 # Rasterize the vector features based on their glacier ID number
 rasterized_vect = vect.rasterize(rast)
-rasterized_vect.plot(ax="new", cmap="viridis", cbar_title="Feature index")
+```
+
+```{code-cell} ipython3
+:tags: [hide-input]
+:mystnb:
+:  code_prompt_show: "Show the code for plotting the figure"
+:  code_prompt_hide: "Hide the code for plotting the figure"
+
+f, ax = plt.subplots(1, 2)
+ax[0].set_title("Raster and vector")
+rast.plot(ax=ax[0], cmap="gray", add_cbar=False)
+vect.plot(ref_crs=rast, ax=ax[0], ec="k", fc="none")
+ax[1].set_title("Rasterized vector")
+rasterized_vect.plot(ax=ax[1], cmap="viridis", cbar_title="Feature index")
+_ = ax[1].set_yticklabels([])
+plt.tight_layout()
 ```
 
 ### Create mask
@@ -72,7 +87,22 @@ Mask creation from a vector **is a rasterization of all vector features that onl
 ```{code-cell} ipython3
 # Create a boolean mask from all vector features
 mask = vect.create_mask(rast)
-mask.plot(ax="new", cbar_title="Glacierized areas")
+```
+
+```{code-cell} ipython3
+:tags: [hide-input]
+:mystnb:
+:  code_prompt_show: "Show the code for plotting the figure"
+:  code_prompt_hide: "Hide the code for plotting the figure"
+
+f, ax = plt.subplots(1, 2)
+ax[0].set_title("Raster and vector")
+rast.plot(ax=ax[0], cmap="gray", add_cbar=False)
+vect.plot(ref_crs=rast, ax=ax[0], ec="k", fc="none")
+ax[1].set_title("Mask from vector")
+mask.plot(ax=ax[1], cbar_title="Intersects vector (1=yes, 0=no)")
+_ = ax[1].set_yticklabels([])
+plt.tight_layout()
 ```
 
 It returns a {class}`~geoutils.Mask`, a georeferenced boolean raster (or optionally, a boolean NumPy array), which 
@@ -96,7 +126,23 @@ the targets are implicitly the valid values of the mask.
 rasterized_vect.set_mask(rasterized_vect == 0)
 # Polygonize all non-zero values
 vect_repolygonized = rasterized_vect.polygonize()
-vect_repolygonized.plot(ax="new", column="id", fc="none", cbar_title="Feature index")
+
+```
+
+```{code-cell} ipython3
+:tags: [hide-input]
+:mystnb:
+:  code_prompt_show: "Show the code for plotting the figure"
+:  code_prompt_hide: "Hide the code for plotting the figure"
+
+f, ax = plt.subplots(1, 2)
+ax[0].set_title("Raster (vector\n rasterized above)")
+rasterized_vect.plot(ax=ax[1], cmap="viridis", cbar_title="Feature index")
+vect.plot(ref_crs=rast, ax=ax[0], ec="k", fc="none")
+ax[1].set_title("Polgonized raster")
+vect_repolygonized.plot(ax=ax[1], column="id", fc="none", cbar_title="Feature index")
+_ = ax[1].set_yticklabels([])
+plt.tight_layout()
 ```
 
 ## Raster–point operations