Update ref to examples/

README.md

@@ -27,7 +27,7 @@ and then estimate that truth given the models and noisy observations.
 ## Getting started
 
 [Install](#installation), then
-read, run and try to understand `examples/basic_{1,2,3}.py`.
+read, run and try to understand `docs/examples/basic_{1,2,3}.py`.
 Some of the examples also exist as Jupyter notebooks, and can be run in the cloud
 *without installation* (but requiring Google login): [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](http://colab.research.google.com/github/nansencenter/DAPPER).
 This [screencast](https://www.youtube.com/watch?v=YtalK0Zkzvg&t=6475s)
@@ -49,7 +49,7 @@ through a variety of typical [test cases](#test-cases-models) and statistics. It
 (b) facilitates comparative studies, thus promoting the
 (a) reliability and
 (b) relevance of the results.
-For example, the figure below is generated by `examples/basic_3.py`,
+For example, the figure below is generated by `docs/examples/basic_3.py`,
 reproduces figure 5.7 of [these lecture notes](http://cerea.enpc.fr/HomePages/bocquet/teaching/assim-mb-en.pdf).
 DAPPER is
 (c) open source, written in Python, and
@@ -62,7 +62,7 @@ and makes it easy to adapt and extend.
 ![Comparative benchmarks with Lorenz-96 plotted as a function of the ensemble size (N)](https://github.com/nansencenter/DAPPER/raw/master/docs/images/ex3.svg)
 
 DAPPER demonstrates how to parallelise ensemble forecasts (e.g., the QG model),
-local analyses (e.g., the LETKF), and independent experiments (e.g., `examples/basic_3.py`).
+local analyses (e.g., the LETKF), and independent experiments (e.g., `docs/examples/basic_3.py`).
 It includes a battery of diagnostics and statistics,
 which all get averaged over subdomains (e.g., "ocean" and "land") and then in time.
 Confidence intervals are computed, including correction for auto-correlations,
@@ -132,7 +132,7 @@ You should now be able to do run your script with
 `python path/to/script.py`.  
 For example, if you are in the DAPPER dir,
 
-    python examples/basic_1.py
+    python docs/examples/basic_1.py
 
 **PS**: If you closed the terminal (or shut down your computer),
 you'll first need to run `conda activate dapper-env`

dapper/mods/README.md

@@ -73,7 +73,7 @@ try not to import stuff from DAPPER outside of [`mods`][] and `liveplotting`.
 
         In parameter estimation problems, the parameters are treated as input
         variables to the "forward model". This does not *necessarily* require OOP.
-        See `examples/param_estim.py`.
+        See `docs/examples/param_estim.py`.
 
 - Optional: define a suggested/example initial state, `x0`.
   This facilitates the specification of initial conditions for different synthetic

dapper/mods/__init__.py

@@ -85,7 +85,7 @@ def __init__(
         sectors : dict, optional
             Labelled indices referring to parts of the state vector.
             When defined, field-mean statistics are computed for each sector.
-            Example use can be found in  `examples/param_estim.py`
+            Example use can be found in  `docs/examples/param_estim.py`
             and `dapper/mods/Lorenz96/miyoshi2011.py`
         name : str, optional
             Label for the `HMM`.
@@ -184,7 +184,8 @@ class TimeDependentOperator:
     The time instance should be specified by `ko`,
     i.e. the index of an observation time.
 
-    Examples: `examples/time-dep-obs-operator.py` and `dapper/mods/QG/sakov2008.py`.
+    Examples: `docs/examples/time-dep-obs-operator.py`
+    and `dapper/mods/QG/sakov2008.py`.
     """
 
     def __init__(self, **kwargs):

dapper/xp_launch.py

@@ -76,7 +76,7 @@ def run_experiment(
 ):
     """Used by [xp_launch.xpList.launch][] to run each single (DA) experiment ("xp").
 
-    This involves steps similar to `examples/basic_1.py`, i.e.:
+    This involves steps similar to `docs/examples/basic_1.py`, i.e.:
 
     - `setup`                    : Initialize experiment.
     - `xp.assimilate`            : run DA, pass on exception if fail_gently
@@ -227,7 +227,7 @@ class xpList(list):
 
     Also see
     --------
-    - Examples: `examples/basic_2`, `examples/basic_3`
+    - Examples: `docs/examples/basic_2`, `docs/examples/basic_3`
     - [`xp_process.xpSpace`][], which is used for experient result **presentation**,
       as opposed to this class (`xpList`), which handles **launching** experiments.
     """
@@ -482,7 +482,7 @@ def launch(self, HMM, save_as="noname", mp=False, fail_gently=None, **kwargs):
             - If this dict field is empty, then all python files
               in `sys.path[0]` are uploaded.
 
-        See `examples/basic_2.py` and `examples/basic_3.py` for example use.
+        See `docs/examples/basic_2.py` and `docs/examples/basic_3.py` for example use.
         """
         # Parse mp option
         if not mp:

docs/examples/README.md

@@ -3,7 +3,7 @@
 Here are some example scripts using DAPPER.
 They all consist of one (or more) synthetic experiments.
 
-Run them using `python examples/the_script.py`,
+Run them using `python docs/examples/the_script.py`,
 or with the `%run` command inside `ipython`.
 
 Some of the scripts have also been converted to Jupyter notebooks (`.ipynb`).
@@ -14,7 +14,7 @@ and that it requires a Google login): [![Open In Collab](https://colab.research.
 ## Description
 
 When adapting the scripts to your needs,
-you should begin with `examples/basic_1.py`
+you should begin with `docs/examples/basic_1.py`
 before incorporating the aspects of `basic_2` and `basic_3`.
 
 - `basic_1.py`: A single experiment, with Liveplotting.