Prepare the 0.2 release (#10)

* start preparing the 0.2 release

* rerun notebooks and add watermark

* remove gitkeep file

* update changelog

README.md

@@ -9,7 +9,7 @@
 
 Stats, linear algebra and einops for xarray
 
-> ⚠️  **Caution: This project is still in a very early development stage**
+> ⚠️  **Caution: This project is still in an early development stage**
 
 ## Installation
 

docs/source/changelog.md

@@ -2,6 +2,16 @@
 
 ## Unreleased (v0.x.x)
 ### New Features
+
+### Maintenance and fixes
+
+### Documentation
+
+### Developer facing changes
+
+
+## v0.2.0 (2022 Apr 2)
+### New Features
 * Added `skew`, `kurtosis` and `median_abs_deviation` to `stats` module {pull}`3`, {pull}`4`
 * Improve flexibility and autorenaming in `matmul` {pull}`8`
 
@@ -16,6 +26,7 @@
 * Added background/explanation page for the stats module. {pull}`5`
 * Improve citation guidance {pull}`6`
 * Add examples of summary stats usage on `xarray.Dataset` {pull}`9`
+* Update the installation instructions with stable and development commands {pull}`10`
 
 ### Developer facing changes
 * Added how-to release guide

docs/source/contributing/how_to.md

@@ -4,7 +4,7 @@
 
 1. Create a new branch
 1. Review the change log (`docs/source/changelog.md`)
-1. Update the version number, that is, remove the `dev` flag, it should not
+1. Update the version number in `__init__.py`. That is, remove the `dev` flag, it should not
    be increased.
 1. Rerun the notebooks in `docs/source/tutorials`
 1. Open a PR, make sure docs build correctly and all tests pass.
@@ -14,4 +14,5 @@
 1. Check the new version appears on the readthedocs version switcher. If it doesn't
    go to [readthedocs](https://readthedocs.org/projects/xarray-einstats/) and
    add it.
-1. Bump the minor version, set the patch version to 0 and add the `dev` flag
+1. Bump the minor version, set the patch version to 0 and add the `dev` flag.
+   It should look like `0.2.0.dev0`

docs/source/installation.md

@@ -3,19 +3,44 @@
 
 You can install `xarray-eistats` with
 
+::::{tab-set}
+:::{tab-item} Stable
+:sync: stable
+
+```
+pip install xarray-einstats
+```
+:::
+:::{tab-item} Development
+:sync: dev
+
 ```
 pip install xarray-einstats @ git+https://github.com/arviz-devs/xarray-einstats
 ```
+:::
+::::
 
-or with
+or, to install some of its optional dependencies, with
+
+::::{tab-set}
+:::{tab-item} Stable
+:sync: stable
+
+```
+pip install "xarray-einstats[<option>]"
+```
+:::
+:::{tab-item} Development
+:sync: dev
 
 ```
 pip install "xarray-einstats[<option>] @ git+https://github.com/arviz-devs/xarray-einstats"
 ```
+:::
+::::
 
-in case you want to install some optional dependencies, you can install multiple bundles
-of optional dependencies separating them with commas. Thus, to install all user facing
-optional dependencies you should use `xarray-einstats[einops,numba]`
+you can install multiple bundles of optional dependencies separating them with commas.
+Thus, to install all user facing optional dependencies you should use `xarray-einstats[einops,numba]`
 
 After installation, independently of the command chosen,
 you can import it with `import xarray_einstats`.

docs/source/tutorials/einops-basics-port.ipynb

@@ -436,7 +436,7 @@
        "Dimensions:  (batch: 6, height: 96, width: 96, channel: 3)\n",
        "Dimensions without coordinates: batch, height, width, channel\n",
        "Data variables:\n",
-       "    ims      (batch, height, width, channel) float64 1.0 0.902 ... 1.0 0.8039</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-cd05351d-e601-4a73-90f1-09ee56f8ca2a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cd05351d-e601-4a73-90f1-09ee56f8ca2a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>batch</span>: 6</li><li><span>height</span>: 96</li><li><span>width</span>: 96</li><li><span>channel</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-4becb687-03d2-40d7-b8c8-7cff203e796d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4becb687-03d2-40d7-b8c8-7cff203e796d' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-4f132dbb-089d-4cc2-9918-ced8b43bd005' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4f132dbb-089d-4cc2-9918-ced8b43bd005' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ims</span></div><div class='xr-var-dims'>(batch, height, width, channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 0.902 0.902 ... 1.0 1.0 0.8039</div><input id='attrs-c7844b5a-5926-4bef-9414-f1edbb617f1c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c7844b5a-5926-4bef-9414-f1edbb617f1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c81d603b-6a9f-470b-af8d-79f093ae3068' class='xr-var-data-in' type='checkbox'><label for='data-c81d603b-6a9f-470b-af8d-79f093ae3068' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[1.        , 0.90196078, 0.90196078],\n",
+       "    ims      (batch, height, width, channel) float64 1.0 0.902 ... 1.0 0.8039</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-7fd7506f-022d-40dd-83e1-0a6aa4971ff8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7fd7506f-022d-40dd-83e1-0a6aa4971ff8' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>batch</span>: 6</li><li><span>height</span>: 96</li><li><span>width</span>: 96</li><li><span>channel</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c9f4585d-8210-4b08-967d-53dae9d73c2f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c9f4585d-8210-4b08-967d-53dae9d73c2f' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-82463a68-6736-4990-adb6-fd5874bfe7de' class='xr-section-summary-in' type='checkbox'  checked><label for='section-82463a68-6736-4990-adb6-fd5874bfe7de' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ims</span></div><div class='xr-var-dims'>(batch, height, width, channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 0.902 0.902 ... 1.0 1.0 0.8039</div><input id='attrs-303451b1-3f2d-4b19-a0a2-6fe3084ba060' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-303451b1-3f2d-4b19-a0a2-6fe3084ba060' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f06f88b7-fbf0-4a56-b2e2-2214cb780885' class='xr-var-data-in' type='checkbox'><label for='data-f06f88b7-fbf0-4a56-b2e2-2214cb780885' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[1.        , 0.90196078, 0.90196078],\n",
        "         [1.        , 0.90196078, 0.90196078],\n",
        "         [1.        , 0.90196078, 0.90196078],\n",
        "         ...,\n",
@@ -476,7 +476,7 @@
        "         ...,\n",
        "         [1.        , 1.        , 0.80392157],\n",
        "         [1.        , 1.        , 0.80392157],\n",
-       "         [1.        , 1.        , 0.80392157]]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4a6ee234-c423-4cd2-8043-21c56b63e124' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4a6ee234-c423-4cd2-8043-21c56b63e124' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+       "         [1.        , 1.        , 0.80392157]]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ab4ebac0-f4ae-4943-a1c8-7837751614b8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ab4ebac0-f4ae-4943-a1c8-7837751614b8' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset>\n",
@@ -1672,6 +1672,37 @@
     "- composition and decomposition of axes are a corner stone, they can and should be used together"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Last updated: Sat Apr 02 2022\n",
+      "\n",
+      "Python implementation: CPython\n",
+      "Python version       : 3.9.10\n",
+      "IPython version      : 8.0.1\n",
+      "\n",
+      "einops         : 0.4.1\n",
+      "xarray_einstats: 0.2.0\n",
+      "\n",
+      "numpy : 1.21.5\n",
+      "xarray: 2022.3.0\n",
+      "\n",
+      "Watermark: 2.3.0\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "%load_ext watermark\n",
+    "%watermark -n -u -v -iv -w -p einops,xarray_einstats"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -1696,7 +1727,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.7"
+   "version": "3.9.10"
   }
  },
  "nbformat": 4,