Crossover

README.rst

@@ -14,7 +14,7 @@ You can find the detailed documentation here: https://pymoo.org
 .. |python| image:: https://img.shields.io/badge/python-3.6-blue.svg
    :alt: python 3.6
 
-.. |license| image:: https://img.shields.io/badge/license-apache-blue.svg
+.. |license| image:: https://img.shields.io/badge/license-apache-orange.svg
    :alt: license apache
    :target: https://www.apache.org/licenses/LICENSE-2.0
 

doc/Makefile

@@ -51,7 +51,3 @@ html: Makefile
 	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
 	@echo
 	@echo "Build finished. The HTML pages are in $(BUILDDIR)/html."
-
-
-live:
-	sphinx-autobuild -b html "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

doc/README

@@ -0,0 +1 @@
+pip install requirements.txt

doc/github/README.template

@@ -1,24 +1,65 @@
 pymoo - Multi-Objective Optimization Framework
 ====================================================================
 
-You can find the detailed documentation here:
-https://www.egr.msu.edu/coinlab/blankjul/pymoo/
+You can find the detailed documentation here: https://pymoo.org
 
-.. image:: https://gitlab.msu.edu/blankjul/pymoo/badges/master/pipeline.svg
+
+|gitlab| |python| |license|
+
+
+.. |gitlab| image:: https://gitlab.msu.edu/blankjul/pymoo/badges/master/pipeline.svg
    :alt: build status
    :target: https://gitlab.msu.edu/blankjul/pymoo/commits/master
 
-.. image:: https://img.shields.io/badge/python-3.6-blue.svg
+.. |python| image:: https://img.shields.io/badge/python-3.6-blue.svg
    :alt: python 3.6
 
-.. image:: https://img.shields.io/badge/license-apache-blue.svg
-   :alt: python 3.6
+.. |license| image:: https://img.shields.io/badge/license-apache-orange.svg
+   :alt: license apache
    :target: https://www.apache.org/licenses/LICENSE-2.0
 
 
+We are currently working on a paper about *pymoo*.
+Meanwhile, if you have used our framework for research purposes, please cite us with:
+
+::
+
+   @misc{pymoo,
+       author = {Julian Blank and Kalyanmoy Deb},
+       title = {pymoo - {Multi-objective Optimization in Python}},
+       howpublished = {https://pymoo.org}
+   }
+
+
+
 Installation
 ====================================================================
-{% include 'docs/source/_installation.rst' %}
+
+First, make sure you have a Python 3 environment installed. We recommend miniconda3 or anaconda3.
+
+The official release is always available at PyPi:
+
+.. code:: bash
+
+    pip install Cython>=0.29 numpy>=1.15 pymoo
+
+
+For the current developer version:
+
+.. code:: bash
+
+    git clone https://github.com/msu-coinlab/pymoo
+    cd pymoo
+    pip install .
+
+
+Since for speedup some of the modules are also available compiled you can double check
+if the compilation worked. When executing the command be sure not already being in the local pymoo
+directory because otherwise not the in site-packages installed version will be used.
+
+.. code:: bash
+
+    python -c "from pymoo.cython.function_loader import is_compiled;print('Compiled Extensions: ', is_compiled())"
 
 
 Usage

doc/requirements.txt

@@ -0,0 +1,4 @@
+sphinx
+numpydoc
+nbsphinx
+sphinxcontrib-bibtex

doc/source/algorithms/differential_evolution.ipynb

@@ -24,16 +24,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Best solution found: \n",
-      "X = [-3.60438355e-11  9.94958640e-01 -2.52891937e-09]\n",
-      "F = [0.99495906]\n"
+      "X = [ 1.39583098e-09 -2.96314339e-09  1.06196328e-09]\n",
+      "F = [0.]\n"
      ]
     }
    ],
@@ -48,8 +48,9 @@
     "               method=get_algorithm('de',\n",
     "                                   variant = \"DE/rand/1/bin\",\n",
     "                                   pop_size = 100,\n",
-    "                                   CR = 2,\n",
-    "                                   F = 0.75),\n",
+    "                                   CR = 0.3,\n",
+    "                                   F = 0.5,\n",
+    "                                   seed=1),\n",
     "               termination=('n_gen', 200),\n",
     "               seed=1,\n",
     "               disp=False)\n",
@@ -73,6 +74,13 @@
     ".. autofunction:: pymoo.algorithms.so_de.de\n",
     "    :noindex:"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {

doc/source/algorithms/nsga2.ipynb

@@ -67,17 +67,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {
     "scrolled": true
    },
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Overwriting ../../../pymoo/usage/nsga2.py\n"
-     ]
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [

doc/source/algorithms/test.py

@@ -0,0 +1 @@
+print("Hello world!")

doc/source/components/crossover.ipynb

@@ -34,6 +34,29 @@
     "Details about the crossover can be found in <cite data-cite=\"sbx\"></cite>. Real values can be representated in a binary notation and then a the point crossovers can be performed. SBX simulated this operation by using a probability distribution *simulating* the binary crossover."
    ]
   },
+  {
+   "cell_type": "raw",
+   "metadata": {
+    "raw_mimetype": "text/restructuredtext"
+   },
+   "source": [
+    ".. _nb_crossover_point:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Point Crossover ('real_point', 'bin_point', 'int_point' )\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Text..."
+   ]
+  },
   {
    "cell_type": "raw",
    "metadata": {
@@ -47,7 +70,83 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Uniform Crossover ('real_uniform', 'bin_uniform')\n"
+    "### Uniform Crossover ('real_ux', 'bin_ux', 'int_ux')\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Text..."
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "metadata": {
+    "raw_mimetype": "text/restructuredtext"
+   },
+   "source": [
+    ".. _nb_crossover_half_uniform:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Half Uniform Crossover ('bin_hux', 'int_hux')\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Text..."
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "metadata": {
+    "raw_mimetype": "text/restructuredtext"
+   },
+   "source": [
+    ".. _nb_crossover_exponential:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Exponential Crossover ('real_exp', 'bin_exp', 'int_exp')\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Text..."
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "metadata": {
+    "raw_mimetype": "text/restructuredtext"
+   },
+   "source": [
+    ".. _nb_crossover_differential:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Differential Crossover ('real_de')\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Text..."
    ]
   },
   {