deploy: 7dbf33d

Author: AnneHartebrodt

.doctrees/environment.pickle

@@ -348,10 +348,10 @@
 <h1>netmap.model.nbautoencoder.NegativeBinomialAutoencoder<a class="headerlink" href="#netmap-model-nbautoencoder-negativebinomialautoencoder" title="Link to this heading">¶</a></h1>
 <dl class="py class">
 <dt class="sig sig-object py" id="netmap.model.nbautoencoder.NegativeBinomialAutoencoder">
-<em class="property"><span class="k"><span class="pre">class</span></span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">netmap.model.nbautoencoder.</span></span><span class="sig-name descname"><span class="pre">NegativeBinomialAutoencoder</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">input_dim</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">latent_dim</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dropout_rate</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hidden_dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[64,</span> <span class="pre">64,</span> <span class="pre">64]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">activation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'relu'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#netmap.model.nbautoencoder.NegativeBinomialAutoencoder" title="Link to this definition">¶</a></dt>
+<em class="property"><span class="k"><span class="pre">class</span></span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">netmap.model.nbautoencoder.</span></span><span class="sig-name descname"><span class="pre">NegativeBinomialAutoencoder</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">input_dim</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">latent_dim</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dropout_rate</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hidden_dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[64]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">activation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'relu'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#netmap.model.nbautoencoder.NegativeBinomialAutoencoder" title="Link to this definition">¶</a></dt>
 <dd><dl class="py method">
 <dt class="sig sig-object py" id="netmap.model.nbautoencoder.NegativeBinomialAutoencoder.__init__">
-<span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">input_dim</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">latent_dim</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dropout_rate</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hidden_dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[64,</span> <span class="pre">64,</span> <span class="pre">64]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">activation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'relu'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#netmap.model.nbautoencoder.NegativeBinomialAutoencoder.__init__" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">input_dim</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">latent_dim</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dropout_rate</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hidden_dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[64]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">activation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'relu'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#netmap.model.nbautoencoder.NegativeBinomialAutoencoder.__init__" title="Link to this definition">¶</a></dt>
 <dd><p>Initialize internal Module state, shared by both nn.Module and ScriptModule.</p>
 </dd></dl>
 

.doctrees/generated/netmap.model.nbautoencoder.NegativeBinomialAutoencoder.doctree

@@ -348,7 +348,7 @@
 <h1>netmap.model.train_model.create_model_zoo<a class="headerlink" href="#netmap-model-train-model-create-model-zoo" title="Link to this heading">¶</a></h1>
 <dl class="py function">
 <dt class="sig sig-object py" id="netmap.model.train_model.create_model_zoo">
-<span class="sig-prename descclassname"><span class="pre">netmap.model.train_model.</span></span><span class="sig-name descname"><span class="pre">create_model_zoo</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data_tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_models</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_epochs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'ZINBAutoencoder'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dropout_rate</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.02</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">latent_dim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hidden_dim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[128]</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#netmap.model.train_model.create_model_zoo" title="Link to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">netmap.model.train_model.</span></span><span class="sig-name descname"><span class="pre">create_model_zoo</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data_tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_models</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_epochs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'ZINBAutoencoder'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dropout_rate</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">latent_dim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hidden_dim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[64]</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#netmap.model.train_model.create_model_zoo" title="Link to this definition">¶</a></dt>
 <dd><p>Creates a set of Autoencoders of the data using the speicified architecture. The architecture of the encoder can be specified using
 the <cite>hidden_dim</cite> parameter, the decoder architecture is mirrored. Early stopping is used by default.</p>
 <dl class="field-list simple">