Integrate C++ objects with NumPy arrays via Python buffer protocol

doc/conf.py

@@ -44,7 +44,8 @@
     'sphinx.ext.coverage',
     'sphinx.ext.mathjax',
     'IPython.sphinxext.ipython_console_highlighting',
-    'IPython.sphinxext.ipython_directive']
+    'IPython.sphinxext.ipython_directive',
+    'nbsphinx']
     #'breathe']
 
 #if (os.environ.get('READTHEDOCS')=="True") is False:

doc/conf.py.in

@@ -44,7 +44,8 @@ extensions = ['sphinx.ext.autodoc',
     'sphinx.ext.coverage',
     'sphinx.ext.mathjax',
     'IPython.sphinxext.ipython_console_highlighting',
-    'IPython.sphinxext.ipython_directive']
+    'IPython.sphinxext.ipython_directive',
+    'nbsphinx']
     #'breathe']
 
 #if (os.environ.get('READTHEDOCS')=="True") is False:

doc/environment.yml

@@ -10,6 +10,7 @@ dependencies:
     - python==3.5
     - sphinx_rtd_theme==0.1.9
     - gsl
+    - nbsphinx
     - pip:
         - numpy
         - matplotlib

doc/examples/DataMatrix.rst

@@ -1,3 +1,5 @@
+.. _datamatrix:
+
 Representing samples from a population in matrix form
 ====================================================================================
 
@@ -30,6 +32,7 @@ The following example is a tour of the API:
 
     import fwdpy11 as fp11
     import fwdpy11.wright_fisher as wf
+    import fwdpy11.model_params
     import fwdpy11.sampling
     import numpy as np
     import pickle
@@ -89,17 +92,13 @@ The following example is a tour of the API:
 
     print(type(dm))
 
-    #Get the neutral genotypes out as a numpy array
-    n = dm.neutral()
+    #Get the neutral genotypes out as a 2d 2d numpy array
+    n = np.ndarray(dm.ndim_neutral(),buffer=dm.neutral,dtype=np.int8) 
     print(type(n))
     print(n.dtype)
-
-    #n is a 1d array, and we want a 2d array
-    #with rows as individuals and columns
-    #as sites
-    n = np.reshape(n,(dm.nrow,dm.ncol_neutral()))
+    print(n.ndim)
     #This must be pop.N = 1,000:
-    print(dm.nrow)
+    print(n.shape[0])
 
     #finally, the DataMatrix is picklable
     #As always with fwdpy11 types,
@@ -117,4 +116,5 @@ The output of the above code is:
     <class 'fwdpy11.sampling.DataMatrix'>
     <class 'numpy.ndarray'>
     int8
+    2
     1000

doc/examples/pickling.rst

@@ -36,6 +36,7 @@ In order to pickle a file, you must also use the latest pickling protocol.
     import fwdpy11 as fp11
     import fwdpy11.wright_fisher as wf
     import fwdpy11.ezparams
+    import fwdpy11.model_params
     import numpy as np
     import pickle
 

doc/examples/processingpops.rst

@@ -19,6 +19,7 @@ First, we'll quickly simulate a single deme for `N` generations:
     import fwdpy11.fitness
     import fwdpy11.model_params
     import fwdpy11.ezparams
+    import fwdpy11.wright_fisher
     import numpy as np
 
     rng = fwdpy11.GSLrng(42)

doc/index.rst

@@ -45,6 +45,13 @@ Welcome to fwdpy11's documentation!
     examples/qtrait
     examples/processingpops
 
+.. toctree::
+    :caption: Maximizing performance
+    :maxdepth: 1
+
+    performance/processingpops_np
+    performance/UsingCython.ipynb
+
 .. toctree::
     :caption: Advanced topics and examples
     :maxdepth: 1