Merge pull request #636 from LinkedEarth/doc_fixes

Doc fixes

README.md

@@ -19,7 +19,7 @@ Pyleoclim is a Python package primarily geared towards the analysis and visualiz
 
 There are many entry points to Pyleoclim, thanks to its underlying [data structures](https://pyleoclim-util.readthedocs.io/en/latest/core/api.html). Low-level modules work on [NumPy](http://www.numpy.org) arrays or [Pandas](https://pandas.pydata.org) dataframes.
 
-We've worked hard to make Pyleoclim accessible to a wide variety of users, from establisher researchers to high-school students, and from seasoned Pythonistas to first-time programmers. A progressive introduction to the package is available at [PyleoTutorials](http://linked.earth/PyleoTutorials/). Examples of scientific use are given [this paper](https://doi.org/10.1029/2022PA004509).  A growing collection of research-grade workflows using Pyleoclim and the LinkedEarth research ecosystem are available as Jupyter notebooks on [paleoBooks](http://linked.earth/PaleoBooks/index.html), with video tutorials on the LinkedEarth [YouTube channel](https://www.youtube.com/watch?v=LJaQBFMK2-Q&list=PL93NbaRnKAuF4WpIQf-4y_U4lo-GqcrcW). Python novices are encouraged to follow these [self-paced tutorials](http://linked.earth/LeapFROGS) before trying Pyleoclim.
+We've worked hard to make Pyleoclim accessible to a wide variety of users, from establisher researchers to high-school students, and from seasoned Pythonistas to first-time programmers. A progressive introduction to the package is available at [PyleoTutorials](http://linked.earth/PyleoTutorials/). Examples of scientific use are given [this paper](https://doi.org/10.1029/2022PA004509).  A growing collection of research-grade workflows using Pyleoclim and the LinkedEarth research ecosystem are available as Jupyter notebooks on [paleoBooks](http://linked.earth/PaleoBooks/), with video tutorials on the LinkedEarth [YouTube channel](https://www.youtube.com/watch?v=LJaQBFMK2-Q&list=PL93NbaRnKAuF4WpIQf-4y_U4lo-GqcrcW). Pyleoclim is part of the broader Python ecosystem of [Computational Tools for Climate Science](https://neuromatch.io/computational-tools-for-climate-science-course/).  Python novices are encouraged to follow these [self-paced tutorials](http://linked.earth/LeapFROGS) before trying Pyleoclim.
 
 Science-based training materials are also available from the [paleoHackathon repository](https://github.com/LinkedEarth/paleoHackathon). We also run live training workshops every so often. Follow us on [Twitter](https://twitter.com/Linked_Earth), or join our [Discourse Forum](https://discourse.linked.earth) for more information.
 

doc_build/index.rst

@@ -15,7 +15,11 @@ The GeoSeries class takes this one step further, enabling geolocation and associ
 These classes allow Pyleoclim to readily analyze datasets stored in the Linked Paleo Data (`LiPD <http://lipd.net>`_) format, through the `PyLiPD <https://pylipd.readthedocs.io/en/latest/>`_ package.
 In particular, the package can make use of age ensembles and uses them for time-uncertain analysis. The age ensembles must however be generated externally, e.g. through the `GeoChronR <http://nickmckay.github.io/GeoChronR/>`_ package, which natively stores them as ensemble tables in LiPD.
 
-Pyleoclim is by no means limited to LiPD-formatted data, and has been used in astronomy, finance, and robotics. Indeed, Pyleoclim is the workhorse supporting more general `machine-learning functionalities <https://github.com/KnowledgeCaptureAndDiscovery/autoTS>`_ for all manner of timeseries.
+However, Pyleoclim is by no means limited to LiPD-formatted data, and has been used in astronomy, finance, and robotics. Indeed, Pyleoclim is the workhorse supporting more general `machine-learning functionalities <https://github.com/KnowledgeCaptureAndDiscovery/autoTS>`_ for all manner of timeseries.
+
+This documentation explains the basic usage of Pyleoclim functionalities. A progressive introduction to scientific uses of the package is available at `PyleoTutorials <http://linked.earth/PyleoTutorials/>`_. 
+Examples of scientific use are given `this paper <https://doi.org/10.1029/2022PA004509>`_.  A growing collection of research-grade workflows using Pyleoclim and the LinkedEarth research ecosystem are available as `PaleoBooks <http://linked.earth/PaleoBooks/>`_, with video tutorials on the LinkedEarth `YouTube channel <https://www.youtube.com/watch?v=LJaQBFMK2-Q&list=PL93NbaRnKAuF4WpIQf-4y_U4lo-GqcrcW>`_. 
+Python novices are encouraged to follow these `self-paced tutorials <http://linked.earth/LeapFROGS>`_ before trying Pyleoclim.
 
 Getting Started
 ===============
@@ -54,7 +58,7 @@ There are many ways to get :ref:`involved in the development of Pyleoclim <contr
   * Report bugs and problems with the code or documentation to our `GitHub repository <https://github.com/LinkedEarth/Pyleoclim_util/issues>`_. Please make sure that there is not outstanding issues that cover the problem you're experiencing.
   * Contribute bug fixes
   * Contribute enhancements and new features
-  * Contribute to the code documentation, and share your Pyleoclim-supported scientific workflows via our public repository (`LiPDBooks <https://github.com/LinkedEarth/LiPDbooks>`_).
+  * Contribute to the code documentation, and share your Pyleoclim-supported scientific workflow as a (`PaleoBook <http://linked.earth/PaleoBooks/>`_).
 
 Search Pyleoclim
 ================

doc_build/rtd_env.yml

@@ -1,4 +1,8 @@
 name: rtd_env
+# Required
+version: 2
+sphinx:
+  configuration: docs/conf.py
 channels:
   - conda-forge
   - defaults