Adding DAPPER

dapper/LICENCE.txt

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+The MIT License (MIT)
+
+Copyright (c) 2016, Patrick N. Raanes, NERSC
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

dapper/README.md

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+# Examples
+
+Here are some example scripts using DAPPER.
+They all consist of one (or more) synthetic experiments.
+
+Run them using `python examples/the_script.py`,
+or with the `%run` command inside `ipython`.
+
+Some of the scripts have also been converted to Jupyter notebooks (`.ipynb`).
+You can try them out without installing anything
+by pressing this button (but note that some plotting features won't work,
+and that it requires a Google login): [![Open In Collab](https://colab.research.google.com/assets/colab-badge.svg)](http://colab.research.google.com/github/nansencenter/DAPPER)
+
+## Description
+
+When adapting the scripts to your needs,
+you should begin with `examples/basic_1.py`
+before incorporating the aspects of `basic_2` and `basic_3`.
+
+- `basic_1.py`: A single experiment, with Liveplotting.
+- `basic_2.py`: Comparison of several DA methods.
+- `basic_3.py`: Comparison of *many* DA methods and other experiment settings.
+- `time-dep-obs-operator.py`: Similar to `basic_1`, but with "double" Lorenz-63 systems
+  evolving independently, and observations of each "half" at alternating times.
+- `param_estim.py`: Similar to `basic_2`, but with parameter estimation.
+- `stoch_model1.py`: A perfect-yet-random model, with various integration schemes.
+- `stoch_models.py`: As above, but studies the relationship between
+  model uncertainty and numerical discretization error.