Restructure: take wrappers and I/O from partialwrap, take function di…

…rectory from jams.

CHANGELOG.md

@@ -2,9 +2,12 @@
 
 All notable changes after its initial development up to January 2020 (v0.2) are documented in this file.
 
-### v1.3 (??? 2020)
+### v2.0 (Jun 2020)
+    - Use package partialwrap in docstrings and documentation.
+    - Remove utils directory: tee.py is now directly in pyeee directory.
+    - Sync const and functions of JAMS package.
     - Small refinements of documentation.
-    - Generalise setup structure.
+    - Generalise structure of setup.py.
     - Use python3 for *nix and python for Windows on TravisCI.
 
 ### v1.2 (Apr 2020)

CONTRIBUTING.md

@@ -16,8 +16,8 @@ with a clear description of the problem and if possible with a
 - please add the version number to the issue:
 
 ```python
-import pyeee
-print(pyeee.__version__)
+    import pyeee
+    print(pyeee.__version__)
 ```
 
 ## Do you have suggestions for new features?

README.md

@@ -1,10 +1,9 @@
 # pyeee - Parameter screening of computational models
 <!-- pandoc -f gfm -o README.html -t html README.md -->
 
-A Python library for parameter screening of computational models
-using Morris' method of Elementary Effects or its extension of
-Efficient/Sequential Elementary Effects by Cuntz, Mai et al. (Water
-Res Research, 2015).
+A Python library for parameter screening of computational models using Morris'
+method of Elementary Effects or its extension of Efficient/Sequential Elementary
+Effects by Cuntz, Mai et al. (Water Res Research, 2015).
 
 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3620909.svg)](https://doi.org/10.5281/zenodo.3620909)
 <!-- [![DOI](https://zenodo.org/badge/233405522.svg)](https://zenodo.org/badge/latestdoi/233405522)  -->
@@ -17,19 +16,23 @@ Res Research, 2015).
 
 ## About pyeee
 
-*pyeee* is a Python library for performing parameter screening of
-computational models. It uses Morris' method of  Elementary Effects
-and also its extension of Efficient or Sequential Elementary Effects published of
+*pyeee* is a Python library for performing parameter screening of computational
+models. It uses Morris' method of Elementary Effects and also its extension of
+Efficient or Sequential Elementary Effects published of
 
 Cuntz, Mai *et al.* (2015)  
   Computationally inexpensive identification of noninformative model
 parameters by sequential screening  
   *Water Resources Research* 51, 6417-6441,
  doi:[10.1002/2015WR016907](http://doi.org/10.1002/2015WR016907).
 
-*pyeee* can be used with Python functions but wrappers are provided
-to use it with executables as well. Function evaluation can be
-distributed with Python's multiprocessing or via MPI.
+The package uses several functions of the JAMS Python package
+https://github.com/mcuntz/jams_python  
+The JAMS package and *hesseflux* are synchronised irregularly.
+
+*pyeee* can be used with Python functions but also with external programs, using
+for example [partialwrap](http://partialwrap.readthedocs.org/en/latest).
+Function evaluation can be distributed with Python's multiprocessing or via MPI.
 
 
 ## Documentation
@@ -78,8 +81,8 @@ which gives the Elementary Effects ($\mu*$):
     # gives: 173.1 0.6 61.7
 ```
 
-Sequential Elementary Effects distinguish between informative and
-uninformative parameters using several times Morris' Elementary Effects:
+Sequential Elementary Effects distinguish between informative and uninformative
+parameters using several times Morris' Elementary Effects:
 
 ```python
     # screen
@@ -88,8 +91,8 @@ uninformative parameters using several times Morris' Elementary Effects:
     out = eee(ishigami1, lb, ub, ntfirst=10)
 ```
 
-which returns a logical ndarray with True for the informative
-parameters and False for the uninformative parameters:
+which returns a logical ndarray with True for the informative parameters and
+False for the uninformative parameters:
 
 ```python
     print(out)
@@ -98,8 +101,8 @@ parameters and False for the uninformative parameters:
 
 ### Python function with extra parameters
 
-The function for pyeee must be of the form `func(x)`. Use Python's
-partial from the functools module to pass other function parameters.
+The function for pyeee must be of the form `func(x)`. Use Python's partial from
+the functools module to pass other function parameters.
 
 For example pass the parameters $a$ and $b$ to the Ishigami-Homma function.
 
@@ -130,15 +133,16 @@ For example pass the parameters $a$ and $b$ to the Ishigami-Homma function.
     out = ee(func, lb, ub, 10)
 ```
 
-`partial` passes `a` and `b` to the
-function `call_func_ab` already during definition so that *pyeee*
-can then simply call it as `func(x)`, so that `x` is passed to
-`call_func_ab` as well.
+Figuratively speaking, `partial` passes `a` and `b` to the function
+`call_func_ab` already during definition so that *pyeee* can then simply call it
+as `func(x)`, so that `x` is passed to `call_func_ab` as well.
 
 
 ### Function wrappers
 
-*pyeee* provides wrappers to use with partial.
+We recommend to use the package
+[partialwrap](http://partialwrap.readthedocs.org/en/latest), which provides
+wrappers to use with partial.
 
 ```python
     from pyeee.utils import func_wrapper
@@ -151,8 +155,9 @@ can then simply call it as `func(x)`, so that `x` is passed to
 ```
 
 There are wrappers to use with Python functions with or without
-masking parameters, as well as wrappers for external executables. See the
-documentation for details.
+masking parameters, as well as wrappers for external programs.
+
+See the documentation for details:
 
    http://pyeee.readthedocs.org/en/latest/
 

docs/requirements.txt

@@ -1,2 +1,6 @@
 # required for readthedocs.org
 numpydoc
+numpy
+scipy
+schwimmbad
+partialwrap

docs/source/conf.py

@@ -248,14 +248,14 @@ def setup(app):
 
 # Example configuration for intersphinx: refer to the Python standard library.
 intersphinx_mapping = {
-    "Python 3.9": ("https://docs.python.org/3.9", None),
-    "Python 3.6": ("https://docs.python.org/3.6", None),
-    "Python": ("https://docs.python.org/", None),
-    "NumPy": ("http://docs.scipy.org/doc/numpy/", None),
-    "SciPy": ("http://docs.scipy.org/doc/scipy/reference/", None),
-    "matplotlib": ("http://matplotlib.org/", None),
-    "Sphinx": ("https://sphinx.readthedocs.io/en/latest/", None),
-    "schwimmbad": ("https://schwimmbad.readthedocs.io/en/latest/", None),
-    "mpi4py": ("https://mpi4py.readthedocs.io/en/latest/", None),
-    "emcee": ("https://emcee.readthedocs.io/en/latest/", None),
+    "Python":      ("https://docs.python.org/3/",                    None),
+    "NumPy":       ("https://numpy.org/doc/stable/",                 None),
+    "SciPy":       ("https://docs.scipy.org/doc/scipy/reference/",   None),
+    "matplotlib":  ("https://matplotlib.org/",                       None),
+    "cython":      ("https://cython.readthedocs.io/en/latest/",      None),
+    "Sphinx":      ("https://www.sphinx-doc.org/en/master/",         None),
+    "schwimmbad":  ("https://schwimmbad.readthedocs.io/en/latest/",  None),
+    "mpi4py":      ("https://mpi4py.readthedocs.io/en/latest/",      None),
+    "emcee":       ("https://emcee.readthedocs.io/en/latest/",       None),
+    "partialwrap": ("https://partialwrap.readthedocs.io/en/latest/", None),
 }

docs/source/functions.utils.rst → docs/source/const.const.rst

@@ -1,7 +1,7 @@
-pyeee.utils
+pyeee.const.const
 =================
 
-.. automodule:: pyeee.functions.utils
+.. automodule:: pyeee.const.const
    :members:
    :undoc-members:
    :inherited-members:

docs/source/utils.std_io.rst → docs/source/const.rst

@@ -1,7 +1,7 @@
-pyeee.std_io
-=======================
+pyeee.const
+===========
 
-.. automodule:: pyeee.utils.std_io
+.. automodule:: pyeee.const
    :members:
    :undoc-members:
    :inherited-members:

docs/source/eee.rst

@@ -1,5 +1,5 @@
 pyeee.eee
-=================
+=========
 
 .. automodule:: pyeee.eee
    :members:

docs/source/functions.fit_functions.rst

@@ -0,0 +1,12 @@
+pyeee.functions.fit_functions
+=============================
+
+.. automodule:: pyeee.functions.fit_functions
+   :members:
+   :undoc-members:
+   :inherited-members:
+   :show-inheritance:
+
+.. raw:: latex
+
+    \clearpage

docs/source/functions.general_functions.rst

@@ -1,5 +1,5 @@
-pyeee.general_functions
-=======================
+pyeee.functions.general_functions
+=================================
 
 .. automodule:: pyeee.functions.general_functions
    :members:

docs/source/functions.logistic_function.rst

@@ -0,0 +1,12 @@
+pyeee.functions.logistic_function
+=================================
+
+.. automodule:: pyeee.functions.logistic_function
+   :members:
+   :undoc-members:
+   :inherited-members:
+   :show-inheritance:
+
+.. raw:: latex
+
+    \clearpage

docs/source/functions.opti_test_functions.rst

@@ -0,0 +1,12 @@
+pyeee.functions.opti_test_functions
+===================================
+
+.. automodule:: pyeee.functions.opti_test_functions
+   :members:
+   :undoc-members:
+   :inherited-members:
+   :show-inheritance:
+
+.. raw:: latex
+
+    \clearpage

docs/source/utils.function_wrapper.rst → docs/source/functions.rst

@@ -1,7 +1,7 @@
-pyeee.function_wrapper
-=======================
+pyeee.functions
+===============
 
-.. automodule:: pyeee.utils.function_wrapper
+.. automodule:: pyeee.functions
    :members:
    :undoc-members:
    :inherited-members:

docs/source/functions.sa_test_functions.rst

@@ -1,5 +1,5 @@
-pyeee.sa_test_functions
-=======================
+pyeee.functions.sa_test_functions
+=================================
 
 .. automodule:: pyeee.functions.sa_test_functions
    :members:

docs/source/index.rst

@@ -2,9 +2,9 @@
 Quickstart
 ==========
 
-``pyeee``: A Python library for parameter screening of computational models
-using Morris' method of Elementary Effects or its extension of
-Efficient or Sequential Elementary Effects by Cuntz, Mai et al. (Water Res Research, 2015).
+``pyeee``: A Python library for parameter screening of computational models using Morris' method of
+Elementary Effects or its extension of Efficient or Sequential Elementary Effects by Cuntz, Mai et
+al. (Water Res Research, 2015).
 
 .. toctree::
    :maxdepth: 3
@@ -14,19 +14,25 @@ Efficient or Sequential Elementary Effects by Cuntz, Mai et al. (Water Res Resea
 About
 ============
 
-``pyeee`` is a Python library for performing parameter screening of
-computational models. It uses Morris' method of  Elementary Effects
-and also its extension of Efficient or Sequential Elementary Effects published by:
+``pyeee`` is a Python library for performing parameter screening of computational models. It uses
+Morris' method of Elementary Effects and also its extension of Efficient or Sequential Elementary
+Effects published by:
 
 Cuntz M, Mai J *et al.* (2015)  
 Computationally inexpensive identification of noninformative model
 parameters by sequential screening  
 *Water Resources Research* 51, 6417-6441,
 doi:`10.1002/2015WR016907 <http://doi.org/10.1002/2015WR016907>`_.
 
-``pyeee`` can be used with Python functions but wrappers are provided
-to use it with external executables as well. Function evaluation can be
-distributed with Python's multiprocessing or via MPI.
+``pyeee`` can be used with Python functions and external programs, using for example the package
+:mod:`partialwrap`. Function evaluation can be distributed with Python's multiprocessing or via
+MPI.
+
+The package uses several functions of the JAMS Python package
+
+   https://github.com/mcuntz/jams_python
+
+The JAMS package and hesseflux are synchronised irregularly.
 
 The complete documentation for ``pyeee`` is available from Read The Docs.
 
@@ -49,8 +55,8 @@ Taking :math:`a = b = 1` gives:
     def ishigami1(x):
         return np.sin(x[0]) + np.sin(x[1])**2 + x[2]**4 * np.sin(x[0])
 
-The three parameters :math:`x_0, x_1, x_2` follow uniform
-distributions between :math:`-\pi` and :math:`+\pi`.
+The three parameters :math:`x_0, x_1, x_2` follow uniform distributions between :math:`-\pi` and
+:math:`+\pi`.
 
 Morris' Elementary Effects can then be calculated like:
 
@@ -75,8 +81,8 @@ which gives the Elementary Effects (:math:`\mu*`):
     print("{:.1f} {:.1f} {:.1f}".format(*out[:,0]))
     # gives: 173.1 0.6 61.7
 
-Sequential Elementary Effects distinguish between informative and
-uninformative parameters using several times Morris' Elementary Effects:
+Sequential Elementary Effects distinguish between informative and uninformative parameters using
+several times Morris' Elementary Effects:
 
 .. code-block:: python
 
@@ -85,8 +91,8 @@ uninformative parameters using several times Morris' Elementary Effects:
     np.random.seed(seed=1021) # for reproducibility of examples
     out = eee(ishigami1, lb, ub)
 
-which returns a logical ndarray with True for the informative
-parameters and False for the uninformative parameters:
+which returns a logical ndarray with True for the informative parameters and False for the
+uninformative parameters:
 
 .. code-block:: python
 
@@ -97,8 +103,8 @@ parameters and False for the uninformative parameters:
 Python function with extra parameters
 -------------------------------------
 
-The function for ``pyeee`` must be of the form `func(x)`. Use Python's
-:func:`functools.partial` from the :mod:`functools` module to pass other function parameters.
+The function for ``pyeee`` must be of the form `func(x)`. Use Python's :func:`functools.partial`
+from the :mod:`functools` module to pass other function parameters.
 
 For example pass the parameters :math:`a` and :math:`b` to the Ishigami-Homma function:
 
@@ -127,30 +133,29 @@ For example pass the parameters :math:`a` and :math:`b` to the Ishigami-Homma fu
     np.random.seed(seed=1021) # for reproducibility of examples
     out = ee(func, lb, ub, 10)
 
-`partial` passes :math:`a` and :math:`b` to the
-function `call_func_ab` already during definition so that ``pyeee``
-can then simply call it as `func(x)`, so that `x` is passed to
-`call_func_ab` as well.
+Figuratively speaking, `partial` passes :math:`a` and :math:`b` to the function `call_func_ab`
+already during definition so that ``pyeee`` can then simply call it as `func(x)`, so that `x` is
+passed to `call_func_ab` as well.
 
 
 Function wrappers
 -----------------
 
-``pyeee`` provides wrappers to use with partial.
+We recommend to use the package :mod:`partialwrap`, which provides wrappers to use with partial.
 
 .. code-block:: python
 
-    from pyeee.utils import func_wrapper
+    from partialwrap import function_wrapper
     args = [a, b]
     kwargs = {}
-    func = partial(func_wrapper, ishigami, args, kwargs)
+    func = partial(function_wrapper, ishigami, args, kwargs)
 
     # screen
     np.random.seed(seed=1021) # for reproducibility of examples
     out = eee(func, lb, ub)
 
 There are wrappers to use with Python functions with or without
-masking parameters, as well as wrappers for external executables.
+masking parameters, as well as wrappers for external programs.
 
 
 Installation

docs/source/morris_method.rst

@@ -1,5 +1,5 @@
 pyeee.morris
-=================
+============
 
 .. automodule:: pyeee.morris_method
    :members: