Deployed 2cab0c3 with MkDocs version: 1.6.0

Author: bartzbeielstein

reference/spotpython/utils/repair/index.html

@@ -4917,7 +4917,10 @@ <h2 id="spotpython.utils.repair.apply_penalty_NA" class="doc doc-heading">
 
             <details class="quote">
               <summary>Source code in <code>spotpython/utils/repair.py</code></summary>
-              <div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal"> 94</span>
+              <div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal"> 91</span>
+<span class="normal"> 92</span>
+<span class="normal"> 93</span>
+<span class="normal"> 94</span>
 <span class="normal"> 95</span>
 <span class="normal"> 96</span>
 <span class="normal"> 97</span>
@@ -4966,10 +4969,7 @@ <h2 id="spotpython.utils.repair.apply_penalty_NA" class="doc doc-heading">
 <span class="normal">140</span>
 <span class="normal">141</span>
 <span class="normal">142</span>
-<span class="normal">143</span>
-<span class="normal">144</span>
-<span class="normal">145</span>
-<span class="normal">146</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span> <span class="nf">apply_penalty_NA</span><span class="p">(</span><span class="n">y</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">penalty_NA</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span> <span class="n">sd</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">stop_on_zero_return</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span> <span class="n">verbosity</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
+<span class="normal">143</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span> <span class="nf">apply_penalty_NA</span><span class="p">(</span><span class="n">y</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">penalty_NA</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span> <span class="n">sd</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">stop_on_zero_return</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span> <span class="n">verbosity</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
 <span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Replaces NaN values in y with a penalty value of penalty_NA and issues a warning if necessary.</span>
 
@@ -5202,10 +5202,7 @@ <h2 id="spotpython.utils.repair.remove_nan" class="doc doc-heading">
 <span class="normal">85</span>
 <span class="normal">86</span>
 <span class="normal">87</span>
-<span class="normal">88</span>
-<span class="normal">89</span>
-<span class="normal">90</span>
-<span class="normal">91</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span> <span class="nf">remove_nan</span><span class="p">(</span><span class="n">X</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">y</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">stop_on_zero_return</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tuple</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">]:</span>
+<span class="normal">88</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span> <span class="nf">remove_nan</span><span class="p">(</span><span class="n">X</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">y</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">stop_on_zero_return</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tuple</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">]:</span>
 <span class="w">    </span><span class="sd">&quot;&quot;&quot;Remove rows from X and y where y contains NaN values and issue a warning</span>
 <span class="sd">        if the dimension of the returned y array is smaller than the dimension of the original y array.</span>
 <span class="sd">        Handles both 1D (shape `(n,)`) and 2D (shape `(n, m)`) y arrays.</span>
@@ -5238,8 +5235,6 @@ <h2 id="spotpython.utils.repair.remove_nan" class="doc doc-heading">
 <span class="sd">        &gt;&gt;&gt; print(X_cleaned, y_cleaned)</span>
 <span class="sd">        [[1 2]] [[1. 2.]]</span>
 <span class="sd">    &quot;&quot;&quot;</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;remove_nan: X.shape=</span><span class="si">{</span><span class="n">X</span><span class="o">.</span><span class="n">shape</span><span class="si">}</span><span class="s2">, y.shape=</span><span class="si">{</span><span class="n">y</span><span class="o">.</span><span class="n">shape</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;remove_nan: X=</span><span class="si">{</span><span class="n">X</span><span class="si">}</span><span class="s2">,</span><span class="se">\n</span><span class="s2"> y=</span><span class="si">{</span><span class="n">y</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
     <span class="c1"># Get the original dimension of the y array</span>
     <span class="n">original_dim</span> <span class="o">=</span> <span class="n">y</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
 
@@ -5250,7 +5245,6 @@ <h2 id="spotpython.utils.repair.remove_nan" class="doc doc-heading">
         <span class="n">ind</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">all</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">isfinite</span><span class="p">(</span><span class="n">y</span><span class="p">),</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
     <span class="k">else</span><span class="p">:</span>
         <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;y must be a 1D or 2D array.&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;remove_nan: ind=</span><span class="si">{</span><span class="n">ind</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
 
     <span class="c1"># Update X and y by removing rows with NaN in y</span>
     <span class="n">X_cleaned</span> <span class="o">=</span> <span class="n">X</span><span class="p">[</span><span class="n">ind</span><span class="p">,</span> <span class="p">:]</span>