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en/develop/advanced-hyperopt/index.html

@@ -1688,8 +1688,8 @@ For the sample below, you then need to add the command line parameter <code>--hy
         <span class="n">min_date</span><span class="p">:</span> <span class="n">datetime</span><span class="p">,</span>
         <span class="n">max_date</span><span class="p">:</span> <span class="n">datetime</span><span class="p">,</span>
         <span class="n">config</span><span class="p">:</span> <span class="n">Config</span><span class="p">,</span>
-        <span class="n">processed</span><span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">DataFrame</span><span class="p">],</span>
-        <span class="n">backtest_stats</span><span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">],</span>
+        <span class="n">processed</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">DataFrame</span><span class="p">],</span>
+        <span class="n">backtest_stats</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">],</span>
         <span class="o">**</span><span class="n">kwargs</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span>
 <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
@@ -1751,7 +1751,7 @@ For the sample below, you then need to add the command line parameter <code>--hy
                 <span class="n">SKDecimal</span><span class="p">(</span><span class="mf">0.01</span><span class="p">,</span> <span class="mf">0.20</span><span class="p">,</span> <span class="n">decimals</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;roi_p3&#39;</span><span class="p">),</span>
             <span class="p">]</span>
 
-        <span class="k">def</span> <span class="nf">generate_roi_table</span><span class="p">(</span><span class="n">params</span><span class="p">:</span> <span class="n">Dict</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="nb">float</span><span class="p">]:</span>
+        <span class="k">def</span> <span class="nf">generate_roi_table</span><span class="p">(</span><span class="n">params</span><span class="p">:</span> <span class="n">Dict</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="nb">float</span><span class="p">]:</span>
 
             <span class="n">roi_table</span> <span class="o">=</span> <span class="p">{}</span>
             <span class="n">roi_table</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">params</span><span class="p">[</span><span class="s1">&#39;roi_p1&#39;</span><span class="p">]</span> <span class="o">+</span> <span class="n">params</span><span class="p">[</span><span class="s1">&#39;roi_p2&#39;</span><span class="p">]</span> <span class="o">+</span> <span class="n">params</span><span class="p">[</span><span class="s1">&#39;roi_p3&#39;</span><span class="p">]</span>

en/develop/freqai-configuration/index.html

@@ -2178,10 +2178,10 @@ This docker-compose file also contains a (disabled) section to enable GPU resour
         <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
         <span class="n">config</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">freqai_info</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;model_training_parameters&quot;</span><span class="p">,</span> <span class="p">{})</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">learning_rate</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;learning_rate&quot;</span><span class="p">,</span>  <span class="mf">3e-4</span><span class="p">)</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">model_kwargs</span><span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]</span> <span class="o">=</span> <span class="n">config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;model_kwargs&quot;</span><span class="p">,</span>  <span class="p">{})</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">trainer_kwargs</span><span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]</span> <span class="o">=</span> <span class="n">config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;trainer_kwargs&quot;</span><span class="p">,</span>  <span class="p">{})</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">model_kwargs</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]</span> <span class="o">=</span> <span class="n">config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;model_kwargs&quot;</span><span class="p">,</span>  <span class="p">{})</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">trainer_kwargs</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]</span> <span class="o">=</span> <span class="n">config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;trainer_kwargs&quot;</span><span class="p">,</span>  <span class="p">{})</span>
 
-    <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data_dictionary</span><span class="p">:</span> <span class="n">Dict</span><span class="p">,</span> <span class="n">dk</span><span class="p">:</span> <span class="n">FreqaiDataKitchen</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Any</span><span class="p">:</span>
+    <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data_dictionary</span><span class="p">:</span> <span class="nb">dict</span><span class="p">,</span> <span class="n">dk</span><span class="p">:</span> <span class="n">FreqaiDataKitchen</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Any</span><span class="p">:</span>
 <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        User sets up the training and test data to fit their desired model here</span>
 <span class="sd">        :param data_dictionary: the dictionary holding all data for train, test,</span>
@@ -2234,10 +2234,10 @@ From top to bottom:</p>
         <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
         <span class="n">config</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">freqai_info</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;model_training_parameters&quot;</span><span class="p">,</span> <span class="p">{})</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">learning_rate</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;learning_rate&quot;</span><span class="p">,</span>  <span class="mf">3e-4</span><span class="p">)</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">model_kwargs</span><span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]</span> <span class="o">=</span> <span class="n">config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;model_kwargs&quot;</span><span class="p">,</span>  <span class="p">{})</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">trainer_kwargs</span><span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]</span> <span class="o">=</span> <span class="n">config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;trainer_kwargs&quot;</span><span class="p">,</span>  <span class="p">{})</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">model_kwargs</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]</span> <span class="o">=</span> <span class="n">config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;model_kwargs&quot;</span><span class="p">,</span>  <span class="p">{})</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">trainer_kwargs</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]</span> <span class="o">=</span> <span class="n">config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;trainer_kwargs&quot;</span><span class="p">,</span>  <span class="p">{})</span>
 
-    <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data_dictionary</span><span class="p">:</span> <span class="n">Dict</span><span class="p">,</span> <span class="n">dk</span><span class="p">:</span> <span class="n">FreqaiDataKitchen</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Any</span><span class="p">:</span>
+    <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data_dictionary</span><span class="p">:</span> <span class="nb">dict</span><span class="p">,</span> <span class="n">dk</span><span class="p">:</span> <span class="n">FreqaiDataKitchen</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Any</span><span class="p">:</span>
         <span class="n">n_features</span> <span class="o">=</span> <span class="n">data_dictionary</span><span class="p">[</span><span class="s2">&quot;train_features&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
         <span class="n">model</span> <span class="o">=</span> <span class="n">PyTorchMLPModel</span><span class="p">(</span>
             <span class="n">input_dim</span><span class="o">=</span><span class="n">n_features</span><span class="p">,</span>

en/develop/strategy-callbacks/index.html

@@ -2991,7 +2991,7 @@ Trades with long duration and 10s or even 100ds of position adjustments are ther
                               <span class="n">current_entry_rate</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span> <span class="n">current_exit_rate</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span>
                               <span class="n">current_entry_profit</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span> <span class="n">current_exit_profit</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span>
                               <span class="o">**</span><span class="n">kwargs</span>
-                              <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Union</span><span class="p">[</span><span class="n">Optional</span><span class="p">[</span><span class="nb">float</span><span class="p">],</span> <span class="n">Tuple</span><span class="p">[</span><span class="n">Optional</span><span class="p">[</span><span class="nb">float</span><span class="p">],</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]]]:</span>
+                              <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Union</span><span class="p">[</span><span class="n">Optional</span><span class="p">[</span><span class="nb">float</span><span class="p">],</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">Optional</span><span class="p">[</span><span class="nb">float</span><span class="p">],</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]]]:</span>
 <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Custom trade adjustment logic, returning the stake amount that a trade should be</span>
 <span class="sd">        increased or decreased.</span>

en/develop/strategy_migration/index.html

@@ -2957,7 +2957,7 @@ As such, the definition of features becomes much simpler with the new logic.</p>
 
     <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">,</span> <span class="n">unfiltered_df</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">,</span> <span class="n">dk</span><span class="p">:</span> <span class="n">FreqaiDataKitchen</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span>
-    <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tuple</span><span class="p">[</span><span class="n">DataFrame</span><span class="p">,</span> <span class="n">npt</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">int_</span><span class="p">]]:</span>
+    <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">DataFrame</span><span class="p">,</span> <span class="n">npt</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">int_</span><span class="p">]]:</span>
 
         <span class="c1"># ... your custom stuff</span>