Minor fixes (#30)

* fix notebook paths

* remove redundent title in left navbar

* remove input cell numbers

* get all data/ subfolders in gitignore

Author: scottyhq

.gitignore

@@ -3,9 +3,7 @@ _build
 _static 
 
 #Data 
-tutorial2/data/full_timeseries/asf_rtcs
-tutorial2/data/full_timeseries/intermediate_cubes/s1_pc_cube.zarr
-tutorial2/data/subset_timeseries/asf_rtcs
+**/data/*
 
 #Extra nbs
 tutorial2/subste_nbs
@@ -297,4 +295,4 @@ dmypy.json
 .idea
 
 # OSX
-.DS_Store
+.DS_Store

book/_config.yml

@@ -12,7 +12,7 @@ only_build_toc_files: false
 # Force re-execution of notebooks on each build.
 # See https://jupyterbook.org/content/execute.html
 execute:
-  execute_notebooks:  cache #'auto' 
+  execute_notebooks:  cache #'auto'
   allow_errors: true
   timeout: 1500
 
@@ -38,9 +38,10 @@ launch_buttons:
 # Add GitHub buttons to your book
 # See https://jupyterbook.org/customize/config.html#add-a-link-to-your-repository
 html:
+  home_page_in_navbar: false
   use_issues_button: true
   use_repository_button: true
-  announcement: > 
+  announcement: >
     🚧 March 2025 - This book is under construction! 🚧
 
 
@@ -124,7 +125,7 @@ sphinx:
       b1_its_nb2: "1) Arrange dataset in chronological order"
       b2_its_nb2: "2) Convert to a Dask-backed `Xarray.Dataset`"
 
-      #nb3 
+      #nb3
       a_its_nb3: "Read data using strategy identified in previous notebook"
       b_its_nb3: "Incorporate glacier outline (vector) data"
       b1_its_nb3: "1) Read and reproject vector data"
@@ -133,7 +134,7 @@ sphinx:
       c_its_nb3: "C. Combine raster and vector data"
       c1_its_nb3: "1) Use vector data to crop raster data"
       c2_its_nb3: "2) Write clipped raster data cube to disk"
-      
+
       #nb4
       a_its_nb4: "A. Data exploration"
       a1_its_nb4: "1) Load raster data and visualize with vector data"
@@ -149,7 +150,7 @@ sphinx:
       d_its_nb4: "D. Dimensional computations"
       d1_its_nb4: "1) Temporal resampling"
       d2_its_nb4: "2) Grouped analysis by season"
-    
+
       #nb5
       a_its_nb5: "A. Read and organize data"
       a1_its_nb5: "1) Raster data"
@@ -190,7 +191,7 @@ sphinx:
       d_s1_nb2: "D. Add metadata from a markdown file"
       d1_s1_nb2: "1) Extract granule ID"
       d2_s1_nb2: "2) Build coordinate `xr.DataArray`"
-      
+
       #sentinel nb3
       a_s1_nb3: "A. Read and prepare data"
       a1_s1_nb3: "1) Clip to spatial area of interest"

book/tutorial1/nbs/1_accessing_itslive_s3_data.ipynb

@@ -95,7 +95,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "metadata": {
     "tags": [
      "hide-input",
@@ -237,7 +237,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {
     "scrolled": true,
     "tags": [
@@ -298,7 +298,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -354,7 +354,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -386,7 +386,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -402,7 +402,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -468,7 +468,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -541,7 +541,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -572,7 +572,7 @@
  "metadata": {
   "celltoolbar": "Tags",
   "kernelspec": {
-   "display_name": "geospatial_datacube_book_env",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -586,7 +586,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.3"
+   "version": "3.13.2"
   }
  },
  "nbformat": 4,

book/tutorial1/nbs/2_larger_than_memory_data.ipynb

@@ -104,7 +104,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -258,7 +258,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -287,7 +287,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -506,7 +506,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -515,7 +515,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -545,7 +545,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "TEST_geospatial_datacube_book_env",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -559,9 +559,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.3"
+   "version": "3.13.2"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }

book/tutorial1/nbs/3_combining_raster_vector_data.ipynb

@@ -72,7 +72,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {
     "tags": [
      "hide-input",
@@ -115,7 +115,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -148,7 +148,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {
     "tags": [
      "hide-input"
@@ -251,7 +251,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -292,7 +292,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -390,7 +390,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -480,7 +480,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -523,7 +523,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -579,7 +579,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -603,7 +603,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -612,7 +612,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -657,7 +657,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "geospatial_datacube_book_env",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -671,9 +671,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.3"
+   "version": "3.13.2"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }