Nsm solver integration

VERSION

@@ -1 +1 @@
-1.0.0
+0.1.0

build_docs/conf.py

@@ -54,9 +54,9 @@
 # built documents.
 #
 # The short X.Y version.
-version = '1.0'
+version = '0.1'
 # The full version, including alpha/beta/rc tags.
-release = '1.0.0'
+release = '0.1.0'
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.
@@ -270,7 +270,7 @@
 epub_copyright = u'2019, Brian Drawert, Evie Hilton'
 
 # The basename for the epub file. It defaults to the project name.
-#epub_basename = u'PyURDME'
+#epub_basename = u'SpatialPy'
 
 # The HTML theme for the epub output. Since the default themes are not optimized
 # for small screen space, using the same theme for HTML and epub output is

build_docs/examples_coral_reef.rst

@@ -1,4 +1,4 @@
-PyURDME Example:  Coral Reef
+SpatialPy Example:  Coral Reef
 =============================
 
 Introduction

build_docs/index.rst

@@ -1,14 +1,14 @@
-.. PyURDME documentation master file, created by
+.. SpatialPy documentation master file, created by
    sphinx-quickstart on Mon Apr 21 11:09:45 2014.
    You can adapt this file completely to your liking, but it should at least
    contain the root `toctree` directive.
 
-Welcome to PyURDME's documentation!
+Welcome to SpatialPy's documentation!
 ===================================
 
-PyURDME is a general software framework for modeling and simulation of stochastic reaction-diffusion processes on unstructured, tetrahedral (3D) and triangular (2D) meshes. Unstructured meshes allow for a more flexible handling of complex geometries compared to structured, Cartesian meshes. The current core simulation algorithm is based on the mesoscopic reaction-diffusion master equation (RDME) model.
+SpatialPy is a general software framework for modeling and simulation of stochastic reaction-diffusion processes on unstructured, tetrahedral (3D) and triangular (2D) meshes. Unstructured meshes allow for a more flexible handling of complex geometries compared to structured, Cartesian meshes. The current core simulation algorithm is based on the mesoscopic reaction-diffusion master equation (RDME) model.
 
-PyURDME was originally based on the URDME software package, but has been completely rewritten in python and updated.  It depends on the FEniCS libraries for mesh generation and assembly, see http://fenicsproject.org/.  The core simulation routines are implemented in C, and requires GCC for compilation.  The default solver is an efficient implementation of the Next Subvolume Method (NSM).
+SpatialPy was originally based on the PyURDME software package, and before that the URDME software. It has been rewritted to use the Smoothed Disapative Particles Dynamics formunlation for the discretization of the diffusion equation.  The core simulation routines are implemented in C, and requires GCC for compilation.  The default solver is an efficient implementation of the Next Subvolume Method (NSM).
 
 Contents:
 

build_docs/spatialpy.rst

@@ -0,0 +1,21 @@
+SpatialPy API
+===============
+
+spatialpy module
+----------------------
+
+.. automodule:: spatialpy.spatialpy
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+
+spatialpy.nsmsolver module
+------------------------
+
+.. automodule:: spatialpy.nsmsolver
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+

install_ubuntu.sh

@@ -1,13 +1,7 @@
 #!/usr/bin/env bash
 apt-get -y update
-apt-get -y install git
 apt-get -y install build-essential python-dev
 apt-get -y install python-setuptools
 apt-get -y install python-matplotlib python-numpy python-scipy
 apt-get -y install make
-apt-get -y install python-software-properties
-add-apt-repository ppa:fenics-packages/fenics
-apt-get update
-apt-get -y install fenics
-apt-get -y install cython python-h5py
 python setup.py install

setup.py

@@ -1,23 +1,89 @@
-from setuptools import setup
+from setuptools import setup, find_packages
+from setuptools.command.develop import develop
+from setuptools.command.install import install
+from setuptools.command.bdist_egg import bdist_egg
+from setuptools.command.easy_install import easy_install
+import os
+
+SETUP_DIR = os.path.dirname(os.path.abspath(__file__))
+
+
+def stoch_path(command_subclass):
+    """
+    A decorator for classes subclassing one of the setuptools commands.
+    It modifies the run() method.
+    """
+    orig_run = command_subclass.run
+
+    def modified_run(self):
+        success = False
+        orig_run(self)
+
+    command_subclass.run = modified_run
+    return command_subclass
+
+
+# update all install classes with our new class
+@stoch_path
+class develop_new(develop):
+    pass
+
+
+@stoch_path
+class install_new(install):
+    pass
+
+
+@stoch_path
+class bdist_egg_new(bdist_egg):
+    pass
+
+
+@stoch_path
+class easy_install_new(easy_install):
+    pass
+
+
+with open('README.md', 'r') as fh:
+    full_description = fh.read()
+
+
 
 setup(name="spatialpy",
-      version="1.1.1",
+      version="0.1.0",
       packages=['spatialpy'],
+
+      include_package_data = True,
+      #package_data={'spatialpy':['data/*.c','data/three.js_templates/js/*','data/three.js_templates/*.html','spatialpy/AUTHORS','spatialpy/LICENCE','spatialpy/bin/*','spatialpy/build/*','spatialpy/include/*','spatialpy/src/*.c','spatialpy/src/nsm/*']},
 
-      #include_package_data = True,
-      package_data={'spatialpy':['data/*.c','data/three.js_templates/js/*','data/three.js_templates/*.html','spatialpy/AUTHORS','spatialpy/LICENCE','spatialpy/bin/*','spatialpy/build/*','spatialpy/include/*','spatialpy/src/*.c','spatialpy/src/nsm/*']},
-
+       description='Python Interface for Spatial Stochastic Biochemical Simulations', 
+
       install_requires = ["numpy",
-                          "scipy",
-                          "h5py"],
+                          "scipy"],
 
-      author="Brian Drawert",
-      author="Evie Hilton",
-      author_email=["[email protected]"],
-      author_email=["[email protected]"],
+      author="Brian Drawert, Evie Hilton",
+      author_email="[email protected]",
       license = "GPL",
       keywords = "spatialpy, spatial stochastic simulation, RDME",
-
-
+      url="https://spatialpy.github.io/SpatialPy/",
+      download_url="https://github.com/SpatialPy/SpatialPy/tarball/master/",
+
+
+      cmdclass={'bdist_egg': bdist_egg_new,
+                'install': install_new,
+                'develop': develop_new,
+                'easy_install': easy_install_new},
+      classifiers=[
+          'Development Status :: 5 - Production/Stable',
+          'License :: OSI Approved :: GNU General Public License v3 (GPLv3)',
+          'Operating System :: OS Independent',
+          'Programming Language :: Python :: 3',
+          'Topic :: Scientific/Engineering',
+          'Topic :: Scientific/Engineering :: Chemistry',
+          'Topic :: Scientific/Engineering :: Mathematics',
+          'Topic :: Scientific/Engineering :: Medical Science Apps.',
+          'Intended Audience :: Science/Research'
+      ],
+
       )
 

spatialpy/DataFunction.py

@@ -0,0 +1,22 @@
+import spatialpy
+
+
+class DataFunction():
+    """ Abstract class used to constuct the data vector. """
+    name = None
+    def __init__(self, name=None):
+        if name is not None:
+            self.name = name
+        if self.name is None:
+            raise Exception("DataFunction must have a 'name'")
+
+    def map(self, x):
+        """ map() takes the coordinate 'x' and returns a double.
+        Args:
+            x: a list of 3 ints.
+        Returns:
+            A float
+        """
+        raise Exception("DataFunction.map() not implemented.")
+
+

spatialpy/InitialCondition.py

@@ -0,0 +1,45 @@
+import numpy
+
+
+class InitialCondition():
+    """ Class used to defined initial conditions in SpatialPy.
+        SubClasses must implement the 'apply(model)' method, which 
+        direction modifies the model.u0[species,voxel] matrix.
+    """
+
+    def apply(self, model):
+        raise ModelError("spatialpy.InitialCondition subclasses must implement apply()")
+
+
+class ScatterInitialCondition(InitialCondition):
+
+    def __init__(self, species, count, subdomains=None):
+        """ Scatter 'count' of 'species' randomly over the list of subdomains
+            (all subdomains if None)."""
+        self.species = species
+        self.count = count
+        self.subdomains = subdomains
+
+    def apply(self, model):
+
+        spec_name = self.species.name
+        for spec_ndx in range(len(model.listOfSpecies)):
+            if model.listOfSpecies[spec_ndx] = self.species: break
+
+        if self.subdomains is None:
+            nvox = model.mesh.get_num_voxels()
+            for mol in range(self.count):
+                vtx = numpy.random.randint(0, nvox)
+                self.u0[spec_ndx, vtx] += 1
+        else:
+            allowed_voxels = []
+            for i in range(model.mesh.get_num_voxels()):
+                if model.sd[i] in self.subdomains:
+                    allowed_voxels.append(i)
+            nvox = len(alowed_voxels)
+            if nvox==0: raise ModelError("ScatterInitialCondition has zero voxels to scatter in")
+            for mol in range(self.count):
+                v_ndx = numpy.random.randint(0, nvox)
+                vtx = allowed_voxels[v_ndx]
+                self.u0[spec_ndx, vtx] += 1
+