n_iter --> max_iter

Pyrimidine(article).md

@@ -102,7 +102,7 @@ class MyPopulation(SGAPopulation):
     default_size = 20
 
 pop = MyPopulation.random(size=n)  # Size: length of the chromosome
-pop.evolve(n_iter=100)
+pop.evolve(max_iter=100)
 ```
 
 Finally, the optimal individual can be found using `pop.best_individual` as the solution. Setting `verbose=True` prints the iteration process. The equivalent expression is as follows:
@@ -121,7 +121,7 @@ To assess the algorithm's performance, it is common to plot fitness curves or ot
 
 ```python
 stat = {'Mean Fitness': 'mean_fitness', 'Best Fitness': 'best_fitness'}
-data = pop.history(stat=stat, n_iter=100)
+data = pop.history(stat=stat, max_iter=100)
 import matplotlib.pyplot as plt
 fig = plt.figure()
 ax = fig.add_subplot(111)

docs/build/html/Customization.html

@@ -228,7 +228,7 @@ <h3>Evolutionary Strategy<a class="headerlink" href="#evolutionary-strategy" tit
 <span class="n">ind</span> <span class="o">=</span> <span class="n">MyIndividual</span><span class="o">.</span><span class="n">random</span><span class="p">()</span>
 
 <span class="n">stat</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;Fitness&#39;</span><span class="p">:</span><span class="s1">&#39;_fitness&#39;</span><span class="p">}</span>
-<span class="n">data</span> <span class="o">=</span> <span class="n">ind</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">stat</span><span class="o">=</span><span class="n">stat</span><span class="p">,</span> <span class="n">n_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="n">data</span> <span class="o">=</span> <span class="n">ind</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">stat</span><span class="o">=</span><span class="n">stat</span><span class="p">,</span> <span class="n">max_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
 
 
 <span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>

docs/build/html/Examples.html

@@ -98,7 +98,7 @@ <h4>Codes<a class="headerlink" href="#codes" title="Link to this heading">¶</a>
     <span class="p">}</span>
 
 <span class="c1"># Do statistical task and print the results through the evoluation</span>
-<span class="n">data</span> <span class="o">=</span> <span class="n">pop</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">stat</span><span class="o">=</span><span class="n">stat</span><span class="p">,</span> <span class="n">n_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="n">data</span> <span class="o">=</span> <span class="n">pop</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">stat</span><span class="o">=</span><span class="n">stat</span><span class="p">,</span> <span class="n">max_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
 
 <span class="c1"># Print the solution(the best individual in the population)</span>
 <span class="nb">print</span><span class="p">(</span><span class="n">pop</span><span class="o">.</span><span class="n">best_individual</span><span class="p">)</span> <span class="c1"># or print(pop.solution)</span>
@@ -169,7 +169,7 @@ <h3>Another Problem<a class="headerlink" href="#another-problem" title="Link to
 <span class="sd">    &#39;Best Fitness&#39;:&#39;max_fitness&#39;} by default;</span>
 <span class="sd">    need not set `stat` explicitly.</span>
 <span class="sd">    &quot;&quot;&quot;</span>
-    <span class="n">data</span> <span class="o">=</span> <span class="n">pop</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">n_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+    <span class="n">data</span> <span class="o">=</span> <span class="n">pop</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">max_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
 
     <span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
     <span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>
@@ -272,10 +272,10 @@ <h3>Comparison of Algorithms<a class="headerlink" href="#comparison-of-algorithm
 <span class="n">_Population</span> <span class="o">=</span> <span class="n">StandardPopulation</span><span class="p">[</span><span class="n">_Individual</span><span class="p">]</span>
 <span class="n">pop</span> <span class="o">=</span> <span class="n">MyPopulation</span><span class="o">.</span><span class="n">random</span><span class="p">(</span><span class="n">n_individuals</span><span class="o">=</span><span class="mi">20</span><span class="p">,</span> <span class="n">sizes</span><span class="o">=</span><span class="p">[</span><span class="mi">8</span><span class="p">]</span><span class="o">*</span><span class="n">ndim</span><span class="o">+</span><span class="p">[</span><span class="mi">8</span><span class="p">])</span>
 <span class="n">cpy</span> <span class="o">=</span> <span class="n">pop</span><span class="o">.</span><span class="n">copy</span><span class="p">(</span><span class="n">type_</span><span class="o">=</span><span class="n">_Population</span><span class="p">)</span>
-<span class="n">d</span> <span class="o">=</span> <span class="n">cpy</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">stat</span><span class="o">=</span><span class="n">stat</span><span class="p">,</span> <span class="n">n_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="n">d</span> <span class="o">=</span> <span class="n">cpy</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">stat</span><span class="o">=</span><span class="n">stat</span><span class="p">,</span> <span class="n">max_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
 <span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">d</span><span class="o">.</span><span class="n">index</span><span class="p">,</span> <span class="n">d</span><span class="p">[</span><span class="s1">&#39;Mean Fitness&#39;</span><span class="p">],</span> <span class="n">d</span><span class="o">.</span><span class="n">index</span><span class="p">,</span> <span class="n">d</span><span class="p">[</span><span class="s1">&#39;Best Fitness&#39;</span><span class="p">],</span> <span class="s1">&#39;.-&#39;</span><span class="p">)</span>
 
-<span class="n">d</span> <span class="o">=</span> <span class="n">pop</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">n_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">stat</span><span class="o">=</span><span class="n">stat</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="n">d</span> <span class="o">=</span> <span class="n">pop</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">max_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">stat</span><span class="o">=</span><span class="n">stat</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
 <span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">d</span><span class="o">.</span><span class="n">index</span><span class="p">,</span> <span class="n">d</span><span class="p">[</span><span class="s1">&#39;Mean Fitness&#39;</span><span class="p">],</span> <span class="n">d</span><span class="o">.</span><span class="n">index</span><span class="p">,</span> <span class="n">d</span><span class="p">[</span><span class="s1">&#39;Best Fitness&#39;</span><span class="p">],</span> <span class="s1">&#39;.-&#39;</span><span class="p">)</span>
 <span class="n">ax</span><span class="o">.</span><span class="n">legend</span><span class="p">((</span><span class="s1">&#39;Traditional mean&#39;</span><span class="p">,</span><span class="s1">&#39;Traditional best&#39;</span><span class="p">,</span> <span class="s1">&#39;New mean&#39;</span><span class="p">,</span> <span class="s1">&#39;New best&#39;</span><span class="p">))</span>
 <span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
@@ -337,7 +337,7 @@ <h2>Example 3 — Evolution Strategy<a class="headerlink" href="#example-3-evolu
 
 
 <span class="n">ind</span> <span class="o">=</span> <span class="n">MyPopulation</span><span class="o">.</span><span class="n">random</span><span class="p">()</span>
-<span class="n">data</span> <span class="o">=</span> <span class="n">ind</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">n_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="n">data</span> <span class="o">=</span> <span class="n">ind</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">max_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
 
 
 <span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
@@ -426,8 +426,8 @@ <h3>Visualization and comparison<a class="headerlink" href="#visualization-and-c
 <span class="n">mypop</span> <span class="o">=</span> <span class="n">MyPopulation</span><span class="o">.</span><span class="n">random</span><span class="p">()</span>
 <span class="n">yourpop</span> <span class="o">=</span> <span class="n">YourPopulation</span><span class="p">([</span><span class="n">YourIndividual</span><span class="p">(</span><span class="n">i</span><span class="o">.</span><span class="n">decode</span><span class="p">())</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">mypop</span><span class="p">])</span>
 
-<span class="n">mydata</span> <span class="o">=</span> <span class="n">mypop</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">n_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">stat</span><span class="o">=</span><span class="n">stat</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
-<span class="n">yourdata</span> <span class="o">=</span> <span class="n">yourpop</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">n_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">stat</span><span class="o">=</span><span class="n">stat</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="n">mydata</span> <span class="o">=</span> <span class="n">mypop</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">max_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">stat</span><span class="o">=</span><span class="n">stat</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="n">yourdata</span> <span class="o">=</span> <span class="n">yourpop</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">max_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">stat</span><span class="o">=</span><span class="n">stat</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
 
 <span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
 <span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>
@@ -475,7 +475,7 @@ <h2>Example 5 — MultiPopulation<a class="headerlink" href="#example-5-multipop
 
 
 <span class="n">mp</span> <span class="o">=</span> <span class="n">_MultiPopulation</span><span class="o">.</span><span class="n">random</span><span class="p">()</span>
-<span class="n">data</span> <span class="o">=</span> <span class="n">mp</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">n_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="n">data</span> <span class="o">=</span> <span class="n">mp</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">max_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
 </pre></div>
 </div>
 <p>Equivalently</p>
@@ -499,7 +499,7 @@ <h2>Example 5 — MultiPopulation<a class="headerlink" href="#example-5-multipop
 <span class="c1"># _MultiPopulation = MultiPopulation[HOFPopulation[BinaryChromosome // n_bags] // 10].set_fitness(_evaluate) // 2</span>
 
 <span class="n">mp</span> <span class="o">=</span> <span class="n">_MultiPopulation</span><span class="o">.</span><span class="n">random</span><span class="p">()</span>
-<span class="n">data</span> <span class="o">=</span> <span class="n">mp</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">n_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="n">data</span> <span class="o">=</span> <span class="n">mp</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">max_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
 </pre></div>
 </div>
 <p>Plot the fitness curves as usual.</p>
@@ -562,7 +562,7 @@ <h3>Hybrid-population<a class="headerlink" href="#hybrid-population" title="Link
 
 
 <span class="n">sp</span> <span class="o">=</span> <span class="n">_HybridPopulation</span><span class="o">.</span><span class="n">random</span><span class="p">()</span>
-<span class="n">data</span> <span class="o">=</span> <span class="n">sp</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">n_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="n">data</span> <span class="o">=</span> <span class="n">sp</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">max_iter</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
 
 
 <span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>

docs/build/html/Helpers.html

@@ -145,8 +145,8 @@ <h3>Memory<a class="headerlink" href="#memory" title="Link to this heading">¶</
 <span class="n">mypop</span> <span class="o">=</span> <span class="n">MyPopulation</span><span class="o">.</span><span class="n">random</span><span class="p">()</span>
 
 <span class="n">yourpop</span> <span class="o">=</span> <span class="n">mypop</span><span class="o">.</span><span class="n">clone</span><span class="p">(</span><span class="n">type_</span><span class="o">=</span><span class="n">YourPopulation</span><span class="p">)</span>
-<span class="n">mydata</span> <span class="o">=</span> <span class="n">mypop</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">n_iter</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span> <span class="n">stat</span><span class="o">=</span><span class="n">stat</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
-<span class="n">yourdata</span> <span class="o">=</span> <span class="n">yourpop</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">n_iter</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span> <span class="n">stat</span><span class="o">=</span><span class="n">stat</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="n">mydata</span> <span class="o">=</span> <span class="n">mypop</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">max_iter</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span> <span class="n">stat</span><span class="o">=</span><span class="n">stat</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="n">yourdata</span> <span class="o">=</span> <span class="n">yourpop</span><span class="o">.</span><span class="n">evolve</span><span class="p">(</span><span class="n">max_iter</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span> <span class="n">stat</span><span class="o">=</span><span class="n">stat</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
 
 <span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
 <span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>