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<a href="Bio-module.html">Package Bio</a> ::
Module MarkovModel
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<h1 class="epydoc">Source Code for <a href="Bio.MarkovModel-module.html">Module Bio.MarkovModel</a></h1>
<pre class="py-src">
<a name="L1"></a><tt class="py-lineno"> 1</tt> <tt class="py-line"><tt class="py-docstring">"""</tt> </tt>
<a name="L2"></a><tt class="py-lineno"> 2</tt> <tt class="py-line"><tt class="py-docstring">This is an implementation of a state-emitting MarkovModel. I am using</tt> </tt>
<a name="L3"></a><tt class="py-lineno"> 3</tt> <tt class="py-line"><tt class="py-docstring">terminology similar to Manning and Schutze.</tt> </tt>
<a name="L4"></a><tt class="py-lineno"> 4</tt> <tt class="py-line"><tt class="py-docstring"></tt> </tt>
<a name="L5"></a><tt class="py-lineno"> 5</tt> <tt class="py-line"><tt class="py-docstring"></tt> </tt>
<a name="L6"></a><tt class="py-lineno"> 6</tt> <tt class="py-line"><tt class="py-docstring"></tt> </tt>
<a name="L7"></a><tt class="py-lineno"> 7</tt> <tt class="py-line"><tt class="py-docstring">Functions:</tt> </tt>
<a name="L8"></a><tt class="py-lineno"> 8</tt> <tt class="py-line"><tt class="py-docstring">train_bw Train a markov model using the Baum-Welch algorithm.</tt> </tt>
<a name="L9"></a><tt class="py-lineno"> 9</tt> <tt class="py-line"><tt class="py-docstring">train_visible Train a visible markov model using MLE.</tt> </tt>
<a name="L10"></a><tt class="py-lineno"> 10</tt> <tt class="py-line"><tt class="py-docstring">find_states Find the a state sequence that explains some observations.</tt> </tt>
<a name="L11"></a><tt class="py-lineno"> 11</tt> <tt class="py-line"><tt class="py-docstring"></tt> </tt>
<a name="L12"></a><tt class="py-lineno"> 12</tt> <tt class="py-line"><tt class="py-docstring">load Load a MarkovModel.</tt> </tt>
<a name="L13"></a><tt class="py-lineno"> 13</tt> <tt class="py-line"><tt class="py-docstring">save Save a MarkovModel.</tt> </tt>
<a name="L14"></a><tt class="py-lineno"> 14</tt> <tt class="py-line"><tt class="py-docstring"></tt> </tt>
<a name="L15"></a><tt class="py-lineno"> 15</tt> <tt class="py-line"><tt class="py-docstring">Classes:</tt> </tt>
<a name="L16"></a><tt class="py-lineno"> 16</tt> <tt class="py-line"><tt class="py-docstring">MarkovModel Holds the description of a markov model</tt> </tt>
<a name="L17"></a><tt class="py-lineno"> 17</tt> <tt class="py-line"><tt class="py-docstring">"""</tt> </tt>
<a name="L18"></a><tt class="py-lineno"> 18</tt> <tt class="py-line"><tt class="py-keyword">import</tt> <tt class="py-name">math</tt> </tt>
<a name="L19"></a><tt class="py-lineno"> 19</tt> <tt class="py-line"> </tt>
<a name="L20"></a><tt class="py-lineno"> 20</tt> <tt class="py-line"><tt class="py-keyword">from</tt> <tt class="py-name">Numeric</tt> <tt class="py-keyword">import</tt> <tt class="py-op">*</tt> </tt>
<a name="L21"></a><tt class="py-lineno"> 21</tt> <tt class="py-line"><tt class="py-keyword">import</tt> <tt class="py-name">RandomArray</tt> </tt>
<a name="L22"></a><tt class="py-lineno"> 22</tt> <tt class="py-line"> </tt>
<a name="L23"></a><tt class="py-lineno"> 23</tt> <tt class="py-line"><tt class="py-keyword">import</tt> <tt class="py-name">StringIO</tt> <tt class="py-comment"># StringIO is in Numeric's namespace, so import this after.</tt> </tt>
<a name="L24"></a><tt class="py-lineno"> 24</tt> <tt class="py-line"> </tt>
<a name="L25"></a><tt class="py-lineno"> 25</tt> <tt class="py-line"><tt class="py-keyword">from</tt> <tt id="link-0" class="py-name" targets="Package Bio=Bio-module.html"><a title="Bio" class="py-name" href="#" onclick="return doclink('link-0', 'Bio', 'link-0');">Bio</a></tt> <tt class="py-keyword">import</tt> <tt id="link-1" class="py-name" targets="Module Bio.listfns=Bio.listfns-module.html"><a title="Bio.listfns" class="py-name" href="#" onclick="return doclink('link-1', 'listfns', 'link-1');">listfns</a></tt> </tt>
<a name="L26"></a><tt class="py-lineno"> 26</tt> <tt class="py-line"> </tt>
<a name="L27"></a><tt class="py-lineno"> 27</tt> <tt class="py-line"> </tt>
<a name="L28"></a><tt class="py-lineno"> 28</tt> <tt class="py-line"><tt class="py-comment">#RandomArray.seed(0, 0) # use 0 for debugging</tt> </tt>
<a name="L29"></a><tt class="py-lineno"> 29</tt> <tt class="py-line"><tt class="py-comment"></tt><tt class="py-name">RandomArray</tt><tt class="py-op">.</tt><tt class="py-name">seed</tt><tt class="py-op">(</tt><tt class="py-op">)</tt> </tt>
<a name="L30"></a><tt class="py-lineno"> 30</tt> <tt class="py-line"> </tt>
<a name="L31"></a><tt class="py-lineno"> 31</tt> <tt class="py-line"><tt id="link-2" class="py-name" targets="Variable Bio.MarkovModel.VERY_SMALL_NUMBER=Bio.MarkovModel-module.html#VERY_SMALL_NUMBER"><a title="Bio.MarkovModel.VERY_SMALL_NUMBER" class="py-name" href="#" onclick="return doclink('link-2', 'VERY_SMALL_NUMBER', 'link-2');">VERY_SMALL_NUMBER</a></tt> <tt class="py-op">=</tt> <tt class="py-number">1E-300</tt> </tt>
<a name="L32"></a><tt class="py-lineno"> 32</tt> <tt class="py-line"><tt id="link-3" class="py-name" targets="Variable Bio.MarkovModel.LOG0=Bio.MarkovModel-module.html#LOG0"><a title="Bio.MarkovModel.LOG0" class="py-name" href="#" onclick="return doclink('link-3', 'LOG0', 'link-3');">LOG0</a></tt> <tt class="py-op">=</tt> <tt id="link-4" class="py-name" targets="Variable Bio.Affy.CelFile.log=Bio.Affy.CelFile-module.html#log,Variable Bio.LogisticRegression.log=Bio.LogisticRegression-module.html#log,Variable Bio.MarkovModel.log=Bio.MarkovModel-module.html#log,Variable Bio.MaxEntropy.log=Bio.MaxEntropy-module.html#log,Variable Bio.NaiveBayes.log=Bio.NaiveBayes-module.html#log,Variable Bio.Statistics.lowess.log=Bio.Statistics.lowess-module.html#log,Variable Bio.distance.log=Bio.distance-module.html#log,Variable Bio.kNN.log=Bio.kNN-module.html#log"><a title="Bio.Affy.CelFile.log
Bio.LogisticRegression.log
Bio.MarkovModel.log
Bio.MaxEntropy.log
Bio.NaiveBayes.log
Bio.Statistics.lowess.log
Bio.distance.log
Bio.kNN.log" class="py-name" href="#" onclick="return doclink('link-4', 'log', 'link-4');">log</a></tt><tt class="py-op">(</tt><tt id="link-5" class="py-name"><a title="Bio.MarkovModel.VERY_SMALL_NUMBER" class="py-name" href="#" onclick="return doclink('link-5', 'VERY_SMALL_NUMBER', 'link-2');">VERY_SMALL_NUMBER</a></tt><tt class="py-op">)</tt> </tt>
<a name="L33"></a><tt class="py-lineno"> 33</tt> <tt class="py-line"> </tt>
<a name="L34"></a><tt class="py-lineno"> 34</tt> <tt class="py-line"><tt id="link-6" class="py-name" targets="Variable Bio.MarkovModel.MATCODE=Bio.MarkovModel-module.html#MATCODE"><a title="Bio.MarkovModel.MATCODE" class="py-name" href="#" onclick="return doclink('link-6', 'MATCODE', 'link-6');">MATCODE</a></tt> <tt class="py-op">=</tt> <tt id="link-7" class="py-name" targets="Variable Bio.Affy.CelFile.Float64=Bio.Affy.CelFile-module.html#Float64,Variable Bio.LogisticRegression.Float64=Bio.LogisticRegression-module.html#Float64,Variable Bio.MarkovModel.Float64=Bio.MarkovModel-module.html#Float64,Variable Bio.MaxEntropy.Float64=Bio.MaxEntropy-module.html#Float64,Variable Bio.NaiveBayes.Float64=Bio.NaiveBayes-module.html#Float64,Variable Bio.Statistics.lowess.Float64=Bio.Statistics.lowess-module.html#Float64,Variable Bio.distance.Float64=Bio.distance-module.html#Float64,Variable Bio.kNN.Float64=Bio.kNN-module.html#Float64"><a title="Bio.Affy.CelFile.Float64
Bio.LogisticRegression.Float64
Bio.MarkovModel.Float64
Bio.MaxEntropy.Float64
Bio.NaiveBayes.Float64
Bio.Statistics.lowess.Float64
Bio.distance.Float64
Bio.kNN.Float64" class="py-name" href="#" onclick="return doclink('link-7', 'Float64', 'link-7');">Float64</a></tt> </tt>
<a name="L35"></a><tt class="py-lineno"> 35</tt> <tt class="py-line"> </tt>
<a name="MarkovModel"></a><div id="MarkovModel-def"><a name="L36"></a><tt class="py-lineno"> 36</tt> <a class="py-toggle" href="#" id="MarkovModel-toggle" onclick="return toggle('MarkovModel');">-</a><tt class="py-line"><tt class="py-keyword">class</tt> <a class="py-def-name" href="Bio.MarkovModel.MarkovModel-class.html">MarkovModel</a><tt class="py-op">:</tt> </tt>
</div><div id="MarkovModel-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="MarkovModel-expanded"><a name="MarkovModel.__init__"></a><div id="MarkovModel.__init__-def"><a name="L37"></a><tt class="py-lineno"> 37</tt> <a class="py-toggle" href="#" id="MarkovModel.__init__-toggle" onclick="return toggle('MarkovModel.__init__');">-</a><tt class="py-line"> <tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel.MarkovModel-class.html#__init__">__init__</a><tt class="py-op">(</tt><tt class="py-param">self</tt><tt class="py-op">,</tt> <tt class="py-param">states</tt><tt class="py-op">,</tt> <tt class="py-param">alphabet</tt><tt class="py-op">,</tt> </tt>
<a name="L38"></a><tt class="py-lineno"> 38</tt> <tt class="py-line"> <tt class="py-param">p_initial</tt><tt class="py-op">=</tt><tt class="py-name">None</tt><tt class="py-op">,</tt> <tt class="py-param">p_transition</tt><tt class="py-op">=</tt><tt class="py-name">None</tt><tt class="py-op">,</tt> <tt class="py-param">p_emission</tt><tt class="py-op">=</tt><tt class="py-name">None</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="MarkovModel.__init__-collapsed" style="display:none;" pad="+++" indent="++++++++"></div><div id="MarkovModel.__init__-expanded"><a name="L39"></a><tt class="py-lineno"> 39</tt> <tt class="py-line"> <tt class="py-name">self</tt><tt class="py-op">.</tt><tt class="py-name">states</tt> <tt class="py-op">=</tt> <tt class="py-name">states</tt> </tt>
<a name="L40"></a><tt class="py-lineno"> 40</tt> <tt class="py-line"> <tt class="py-name">self</tt><tt class="py-op">.</tt><tt id="link-8" class="py-name" targets="Variable Bio.Prosite.Pattern.Prosite.alphabet=Bio.Prosite.Pattern.Prosite-class.html#alphabet,Function Bio.Std.alphabet()=Bio.Std-module.html#alphabet"><a title="Bio.Prosite.Pattern.Prosite.alphabet
Bio.Std.alphabet" class="py-name" href="#" onclick="return doclink('link-8', 'alphabet', 'link-8');">alphabet</a></tt> <tt class="py-op">=</tt> <tt id="link-9" class="py-name"><a title="Bio.Prosite.Pattern.Prosite.alphabet
Bio.Std.alphabet" class="py-name" href="#" onclick="return doclink('link-9', 'alphabet', 'link-8');">alphabet</a></tt> </tt>
<a name="L41"></a><tt class="py-lineno"> 41</tt> <tt class="py-line"> <tt class="py-name">self</tt><tt class="py-op">.</tt><tt class="py-name">p_initial</tt> <tt class="py-op">=</tt> <tt class="py-name">p_initial</tt> </tt>
<a name="L42"></a><tt class="py-lineno"> 42</tt> <tt class="py-line"> <tt class="py-name">self</tt><tt class="py-op">.</tt><tt class="py-name">p_transition</tt> <tt class="py-op">=</tt> <tt class="py-name">p_transition</tt> </tt>
<a name="L43"></a><tt class="py-lineno"> 43</tt> <tt class="py-line"> <tt class="py-name">self</tt><tt class="py-op">.</tt><tt class="py-name">p_emission</tt> <tt class="py-op">=</tt> <tt class="py-name">p_emission</tt> </tt>
</div><a name="MarkovModel.__str__"></a><div id="MarkovModel.__str__-def"><a name="L44"></a><tt class="py-lineno"> 44</tt> <a class="py-toggle" href="#" id="MarkovModel.__str__-toggle" onclick="return toggle('MarkovModel.__str__');">-</a><tt class="py-line"> <tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel.MarkovModel-class.html#__str__">__str__</a><tt class="py-op">(</tt><tt class="py-param">self</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="MarkovModel.__str__-collapsed" style="display:none;" pad="+++" indent="++++++++"></div><div id="MarkovModel.__str__-expanded"><a name="L45"></a><tt class="py-lineno"> 45</tt> <tt class="py-line"> <tt id="link-10" class="py-name" targets="Variable Bio.LocusLink.web_parse.handle=Bio.LocusLink.web_parse-module.html#handle,Variable Bio.Ndb.handle=Bio.Ndb-module.html#handle"><a title="Bio.LocusLink.web_parse.handle
Bio.Ndb.handle" class="py-name" href="#" onclick="return doclink('link-10', 'handle', 'link-10');">handle</a></tt> <tt class="py-op">=</tt> <tt class="py-name">StringIO</tt><tt class="py-op">.</tt><tt class="py-name">StringIO</tt><tt class="py-op">(</tt><tt class="py-op">)</tt> </tt>
<a name="L46"></a><tt class="py-lineno"> 46</tt> <tt class="py-line"> <tt id="link-11" class="py-name" targets="Method Bio.Cluster.Record.save()=Bio.Cluster.Record-class.html#save,Function Bio.MarkovModel.save()=Bio.MarkovModel-module.html#save,Method Bio.PDB.PDBIO'.PDBIO.save()=Bio.PDB.PDBIO%27.PDBIO-class.html#save"><a title="Bio.Cluster.Record.save
Bio.MarkovModel.save
Bio.PDB.PDBIO'.PDBIO.save" class="py-name" href="#" onclick="return doclink('link-11', 'save', 'link-11');">save</a></tt><tt class="py-op">(</tt><tt class="py-name">self</tt><tt class="py-op">,</tt> <tt id="link-12" class="py-name"><a title="Bio.LocusLink.web_parse.handle
Bio.Ndb.handle" class="py-name" href="#" onclick="return doclink('link-12', 'handle', 'link-10');">handle</a></tt><tt class="py-op">)</tt> </tt>
<a name="L47"></a><tt class="py-lineno"> 47</tt> <tt class="py-line"> <tt id="link-13" class="py-name"><a title="Bio.LocusLink.web_parse.handle
Bio.Ndb.handle" class="py-name" href="#" onclick="return doclink('link-13', 'handle', 'link-10');">handle</a></tt><tt class="py-op">.</tt><tt id="link-14" class="py-name" targets="Method Bio.EUtils.ReseekFile.ReseekFile.seek()=Bio.EUtils.ReseekFile.ReseekFile-class.html#seek,Method Bio.File.UndoHandle.seek()=Bio.File.UndoHandle-class.html#seek,Method Martel.msre_parse.Tokenizer.seek()=Martel.msre_parse.Tokenizer-class.html#seek"><a title="Bio.EUtils.ReseekFile.ReseekFile.seek
Bio.File.UndoHandle.seek
Martel.msre_parse.Tokenizer.seek" class="py-name" href="#" onclick="return doclink('link-14', 'seek', 'link-14');">seek</a></tt><tt class="py-op">(</tt><tt class="py-number">0</tt><tt class="py-op">)</tt> </tt>
<a name="L48"></a><tt class="py-lineno"> 48</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt id="link-15" class="py-name"><a title="Bio.LocusLink.web_parse.handle
Bio.Ndb.handle" class="py-name" href="#" onclick="return doclink('link-15', 'handle', 'link-10');">handle</a></tt><tt class="py-op">.</tt><tt id="link-16" class="py-name" targets="Method Bio.AlignAce.Motif.Motif.read()=Bio.AlignAce.Motif.Motif-class.html#read,Function Bio.AlignIO.read()=Bio.AlignIO-module.html#read,Function Bio.Cluster.read()=Bio.Cluster-module.html#read,Method Bio.EUtils.ReseekFile.ReseekFile.read()=Bio.EUtils.ReseekFile.ReseekFile-class.html#read,Function Bio.Entrez.read()=Bio.Entrez-module.html#read,Method Bio.File.SGMLHandle.read()=Bio.File.SGMLHandle-class.html#read,Method Bio.File.UndoHandle.read()=Bio.File.UndoHandle-class.html#read,Method Bio.FilteredReader.FilteredReader.read()=Bio.FilteredReader.FilteredReader-class.html#read,Method Bio.NeuralNetwork.Gene.Pattern.PatternIO.read()=Bio.NeuralNetwork.Gene.Pattern.PatternIO-class.html#read,Method Bio.Nexus.Nexus.Nexus.read()=Bio.Nexus.Nexus.Nexus-class.html#read,Function Bio.Prosite.Prodoc.read()=Bio.Prosite.Prodoc-module.html#read,Function Bio.Prosite.read()=Bio.Prosite-module.html#read,Method Bio.SGMLExtractor.SGMLExtractorHandle.read()=Bio.SGMLExtractor.SGMLExtractorHandle-class.html#read,Function Bio.SeqIO.read()=Bio.SeqIO-module.html#read,Function Bio.SwissProt.read()=Bio.SwissProt-module.html#read"><a title="Bio.AlignAce.Motif.Motif.read
Bio.AlignIO.read
Bio.Cluster.read
Bio.EUtils.ReseekFile.ReseekFile.read
Bio.Entrez.read
Bio.File.SGMLHandle.read
Bio.File.UndoHandle.read
Bio.FilteredReader.FilteredReader.read
Bio.NeuralNetwork.Gene.Pattern.PatternIO.read
Bio.Nexus.Nexus.Nexus.read
Bio.Prosite.Prodoc.read
Bio.Prosite.read
Bio.SGMLExtractor.SGMLExtractorHandle.read
Bio.SeqIO.read
Bio.SwissProt.read" class="py-name" href="#" onclick="return doclink('link-16', 'read', 'link-16');">read</a></tt><tt class="py-op">(</tt><tt class="py-op">)</tt> </tt>
</div></div><a name="L49"></a><tt class="py-lineno"> 49</tt> <tt class="py-line"> </tt>
<a name="_readline_and_check_start"></a><div id="_readline_and_check_start-def"><a name="L50"></a><tt class="py-lineno"> 50</tt> <a class="py-toggle" href="#" id="_readline_and_check_start-toggle" onclick="return toggle('_readline_and_check_start');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#_readline_and_check_start">_readline_and_check_start</a><tt class="py-op">(</tt><tt class="py-param">handle</tt><tt class="py-op">,</tt> <tt class="py-param">start</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="_readline_and_check_start-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="_readline_and_check_start-expanded"><a name="L51"></a><tt class="py-lineno"> 51</tt> <tt class="py-line"> <tt class="py-name">line</tt> <tt class="py-op">=</tt> <tt id="link-17" class="py-name"><a title="Bio.LocusLink.web_parse.handle
Bio.Ndb.handle" class="py-name" href="#" onclick="return doclink('link-17', 'handle', 'link-10');">handle</a></tt><tt class="py-op">.</tt><tt id="link-18" class="py-name" targets="Method Bio.EUtils.ReseekFile.ReseekFile.readline()=Bio.EUtils.ReseekFile.ReseekFile-class.html#readline,Method Bio.File.SGMLHandle.readline()=Bio.File.SGMLHandle-class.html#readline,Method Bio.File.UndoHandle.readline()=Bio.File.UndoHandle-class.html#readline,Method Bio.SGMLExtractor.SGMLExtractorHandle.readline()=Bio.SGMLExtractor.SGMLExtractorHandle-class.html#readline"><a title="Bio.EUtils.ReseekFile.ReseekFile.readline
Bio.File.SGMLHandle.readline
Bio.File.UndoHandle.readline
Bio.SGMLExtractor.SGMLExtractorHandle.readline" class="py-name" href="#" onclick="return doclink('link-18', 'readline', 'link-18');">readline</a></tt><tt class="py-op">(</tt><tt class="py-op">)</tt> </tt>
<a name="L52"></a><tt class="py-lineno"> 52</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-keyword">not</tt> <tt class="py-name">line</tt><tt class="py-op">.</tt><tt class="py-name">startswith</tt><tt class="py-op">(</tt><tt id="link-19" class="py-name" targets="Method Bio.GFF.easy.Location.start()=Bio.GFF.easy.Location-class.html#start,Method Bio.Prosite.Pattern.PrositeMatch.start()=Bio.Prosite.Pattern.PrositeMatch-class.html#start,Variable Bio.Restriction._Update.RestrictionCompiler.start=Bio.Restriction._Update.RestrictionCompiler-module.html#start,Method Martel.LAX.LAX.start()=Martel.LAX.LAX-class.html#start"><a title="Bio.GFF.easy.Location.start
Bio.Prosite.Pattern.PrositeMatch.start
Bio.Restriction._Update.RestrictionCompiler.start
Martel.LAX.LAX.start" class="py-name" href="#" onclick="return doclink('link-19', 'start', 'link-19');">start</a></tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L53"></a><tt class="py-lineno"> 53</tt> <tt class="py-line"> <tt class="py-keyword">raise</tt> <tt class="py-name">ValueError</tt><tt class="py-op">,</tt> <tt class="py-string">"I expected %r but got %r"</tt> <tt class="py-op">%</tt> <tt class="py-op">(</tt><tt id="link-20" class="py-name"><a title="Bio.GFF.easy.Location.start
Bio.Prosite.Pattern.PrositeMatch.start
Bio.Restriction._Update.RestrictionCompiler.start
Martel.LAX.LAX.start" class="py-name" href="#" onclick="return doclink('link-20', 'start', 'link-19');">start</a></tt><tt class="py-op">,</tt> <tt class="py-name">line</tt><tt class="py-op">)</tt> </tt>
<a name="L54"></a><tt class="py-lineno"> 54</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt class="py-name">line</tt> </tt>
</div><a name="L55"></a><tt class="py-lineno"> 55</tt> <tt class="py-line"> </tt>
<a name="load"></a><div id="load-def"><a name="L56"></a><tt class="py-lineno"> 56</tt> <a class="py-toggle" href="#" id="load-toggle" onclick="return toggle('load');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#load">load</a><tt class="py-op">(</tt><tt class="py-param">handle</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="load-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="load-expanded"><a name="L57"></a><tt class="py-lineno"> 57</tt> <tt class="py-line"> <tt class="py-docstring">"""load(handle) -> MarkovModel()"""</tt> </tt>
<a name="L58"></a><tt class="py-lineno"> 58</tt> <tt class="py-line"> <tt class="py-comment"># Load the states.</tt> </tt>
<a name="L59"></a><tt class="py-lineno"> 59</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">line</tt> <tt class="py-op">=</tt> <tt id="link-21" class="py-name" targets="Function Bio.MarkovModel._readline_and_check_start()=Bio.MarkovModel-module.html#_readline_and_check_start"><a title="Bio.MarkovModel._readline_and_check_start" class="py-name" href="#" onclick="return doclink('link-21', '_readline_and_check_start', 'link-21');">_readline_and_check_start</a></tt><tt class="py-op">(</tt><tt id="link-22" class="py-name"><a title="Bio.LocusLink.web_parse.handle
Bio.Ndb.handle" class="py-name" href="#" onclick="return doclink('link-22', 'handle', 'link-10');">handle</a></tt><tt class="py-op">,</tt> <tt class="py-string">"STATES:"</tt><tt class="py-op">)</tt> </tt>
<a name="L60"></a><tt class="py-lineno"> 60</tt> <tt class="py-line"> <tt class="py-name">states</tt> <tt class="py-op">=</tt> <tt class="py-name">line</tt><tt class="py-op">.</tt><tt id="link-23" class="py-name" targets="Method Bio.Nexus.Trees.Tree.split()=Bio.Nexus.Trees.Tree-class.html#split,Method Bio.Restriction.Restriction.RestrictionBatch.split()=Bio.Restriction.Restriction.RestrictionBatch-class.html#split"><a title="Bio.Nexus.Trees.Tree.split
Bio.Restriction.Restriction.RestrictionBatch.split" class="py-name" href="#" onclick="return doclink('link-23', 'split', 'link-23');">split</a></tt><tt class="py-op">(</tt><tt class="py-op">)</tt><tt class="py-op">[</tt><tt class="py-number">1</tt><tt class="py-op">:</tt><tt class="py-op">]</tt> </tt>
<a name="L61"></a><tt class="py-lineno"> 61</tt> <tt class="py-line"> </tt>
<a name="L62"></a><tt class="py-lineno"> 62</tt> <tt class="py-line"> <tt class="py-comment"># Load the alphabet.</tt> </tt>
<a name="L63"></a><tt class="py-lineno"> 63</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">line</tt> <tt class="py-op">=</tt> <tt id="link-24" class="py-name"><a title="Bio.MarkovModel._readline_and_check_start" class="py-name" href="#" onclick="return doclink('link-24', '_readline_and_check_start', 'link-21');">_readline_and_check_start</a></tt><tt class="py-op">(</tt><tt id="link-25" class="py-name"><a title="Bio.LocusLink.web_parse.handle
Bio.Ndb.handle" class="py-name" href="#" onclick="return doclink('link-25', 'handle', 'link-10');">handle</a></tt><tt class="py-op">,</tt> <tt class="py-string">"ALPHABET:"</tt><tt class="py-op">)</tt> </tt>
<a name="L64"></a><tt class="py-lineno"> 64</tt> <tt class="py-line"> <tt id="link-26" class="py-name"><a title="Bio.Prosite.Pattern.Prosite.alphabet
Bio.Std.alphabet" class="py-name" href="#" onclick="return doclink('link-26', 'alphabet', 'link-8');">alphabet</a></tt> <tt class="py-op">=</tt> <tt class="py-name">line</tt><tt class="py-op">.</tt><tt id="link-27" class="py-name"><a title="Bio.Nexus.Trees.Tree.split
Bio.Restriction.Restriction.RestrictionBatch.split" class="py-name" href="#" onclick="return doclink('link-27', 'split', 'link-23');">split</a></tt><tt class="py-op">(</tt><tt class="py-op">)</tt><tt class="py-op">[</tt><tt class="py-number">1</tt><tt class="py-op">:</tt><tt class="py-op">]</tt> </tt>
<a name="L65"></a><tt class="py-lineno"> 65</tt> <tt class="py-line"> </tt>
<a name="L66"></a><tt class="py-lineno"> 66</tt> <tt class="py-line"> <tt class="py-name">mm</tt> <tt class="py-op">=</tt> <tt id="link-28" class="py-name" targets="Module Bio.HMM.MarkovModel=Bio.HMM.MarkovModel-module.html,Module Bio.MarkovModel=Bio.MarkovModel-module.html,Class Bio.MarkovModel.MarkovModel=Bio.MarkovModel.MarkovModel-class.html"><a title="Bio.HMM.MarkovModel
Bio.MarkovModel
Bio.MarkovModel.MarkovModel" class="py-name" href="#" onclick="return doclink('link-28', 'MarkovModel', 'link-28');">MarkovModel</a></tt><tt class="py-op">(</tt><tt class="py-name">states</tt><tt class="py-op">,</tt> <tt id="link-29" class="py-name"><a title="Bio.Prosite.Pattern.Prosite.alphabet
Bio.Std.alphabet" class="py-name" href="#" onclick="return doclink('link-29', 'alphabet', 'link-8');">alphabet</a></tt><tt class="py-op">)</tt> </tt>
<a name="L67"></a><tt class="py-lineno"> 67</tt> <tt class="py-line"> <tt class="py-name">N</tt><tt class="py-op">,</tt> <tt class="py-name">M</tt> <tt class="py-op">=</tt> <tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">states</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> <tt class="py-name">len</tt><tt class="py-op">(</tt><tt id="link-30" class="py-name"><a title="Bio.Prosite.Pattern.Prosite.alphabet
Bio.Std.alphabet" class="py-name" href="#" onclick="return doclink('link-30', 'alphabet', 'link-8');">alphabet</a></tt><tt class="py-op">)</tt> </tt>
<a name="L68"></a><tt class="py-lineno"> 68</tt> <tt class="py-line"> </tt>
<a name="L69"></a><tt class="py-lineno"> 69</tt> <tt class="py-line"> <tt class="py-comment"># Load the initial probabilities.</tt> </tt>
<a name="L70"></a><tt class="py-lineno"> 70</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">mm</tt><tt class="py-op">.</tt><tt class="py-name">p_initial</tt> <tt class="py-op">=</tt> <tt class="py-name">zeros</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt> <tt id="link-31" class="py-name"><a title="Bio.MarkovModel.MATCODE" class="py-name" href="#" onclick="return doclink('link-31', 'MATCODE', 'link-6');">MATCODE</a></tt><tt class="py-op">)</tt> </tt>
<a name="L71"></a><tt class="py-lineno"> 71</tt> <tt class="py-line"> <tt class="py-name">line</tt> <tt class="py-op">=</tt> <tt id="link-32" class="py-name"><a title="Bio.MarkovModel._readline_and_check_start" class="py-name" href="#" onclick="return doclink('link-32', '_readline_and_check_start', 'link-21');">_readline_and_check_start</a></tt><tt class="py-op">(</tt><tt id="link-33" class="py-name"><a title="Bio.LocusLink.web_parse.handle
Bio.Ndb.handle" class="py-name" href="#" onclick="return doclink('link-33', 'handle', 'link-10');">handle</a></tt><tt class="py-op">,</tt> <tt class="py-string">"INITIAL:"</tt><tt class="py-op">)</tt> </tt>
<a name="L72"></a><tt class="py-lineno"> 72</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt id="link-34" class="py-name" targets="Variable Bio.PDB.Polypeptide.i=Bio.PDB.Polypeptide-module.html#i"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-34', 'i', 'link-34');">i</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">states</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L73"></a><tt class="py-lineno"> 73</tt> <tt class="py-line"> <tt class="py-name">line</tt> <tt class="py-op">=</tt> <tt id="link-35" class="py-name"><a title="Bio.MarkovModel._readline_and_check_start" class="py-name" href="#" onclick="return doclink('link-35', '_readline_and_check_start', 'link-21');">_readline_and_check_start</a></tt><tt class="py-op">(</tt><tt id="link-36" class="py-name"><a title="Bio.LocusLink.web_parse.handle
Bio.Ndb.handle" class="py-name" href="#" onclick="return doclink('link-36', 'handle', 'link-10');">handle</a></tt><tt class="py-op">,</tt> <tt class="py-string">" %s:"</tt> <tt class="py-op">%</tt> <tt class="py-name">states</tt><tt class="py-op">[</tt><tt id="link-37" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-37', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">)</tt> </tt>
<a name="L74"></a><tt class="py-lineno"> 74</tt> <tt class="py-line"> <tt class="py-name">mm</tt><tt class="py-op">.</tt><tt class="py-name">p_initial</tt><tt class="py-op">[</tt><tt id="link-38" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-38', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt class="py-name">float</tt><tt class="py-op">(</tt><tt class="py-name">line</tt><tt class="py-op">.</tt><tt id="link-39" class="py-name"><a title="Bio.Nexus.Trees.Tree.split
Bio.Restriction.Restriction.RestrictionBatch.split" class="py-name" href="#" onclick="return doclink('link-39', 'split', 'link-23');">split</a></tt><tt class="py-op">(</tt><tt class="py-op">)</tt><tt class="py-op">[</tt><tt class="py-op">-</tt><tt class="py-number">1</tt><tt class="py-op">]</tt><tt class="py-op">)</tt> </tt>
<a name="L75"></a><tt class="py-lineno"> 75</tt> <tt class="py-line"> </tt>
<a name="L76"></a><tt class="py-lineno"> 76</tt> <tt class="py-line"> <tt class="py-comment"># Load the transition.</tt> </tt>
<a name="L77"></a><tt class="py-lineno"> 77</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">mm</tt><tt class="py-op">.</tt><tt class="py-name">p_transition</tt> <tt class="py-op">=</tt> <tt class="py-name">zeros</tt><tt class="py-op">(</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt> <tt class="py-name">N</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> <tt id="link-40" class="py-name"><a title="Bio.MarkovModel.MATCODE" class="py-name" href="#" onclick="return doclink('link-40', 'MATCODE', 'link-6');">MATCODE</a></tt><tt class="py-op">)</tt> </tt>
<a name="L78"></a><tt class="py-lineno"> 78</tt> <tt class="py-line"> <tt class="py-name">line</tt> <tt class="py-op">=</tt> <tt id="link-41" class="py-name"><a title="Bio.MarkovModel._readline_and_check_start" class="py-name" href="#" onclick="return doclink('link-41', '_readline_and_check_start', 'link-21');">_readline_and_check_start</a></tt><tt class="py-op">(</tt><tt id="link-42" class="py-name"><a title="Bio.LocusLink.web_parse.handle
Bio.Ndb.handle" class="py-name" href="#" onclick="return doclink('link-42', 'handle', 'link-10');">handle</a></tt><tt class="py-op">,</tt> <tt class="py-string">"TRANSITION:"</tt><tt class="py-op">)</tt> </tt>
<a name="L79"></a><tt class="py-lineno"> 79</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt id="link-43" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-43', 'i', 'link-34');">i</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">states</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L80"></a><tt class="py-lineno"> 80</tt> <tt class="py-line"> <tt class="py-name">line</tt> <tt class="py-op">=</tt> <tt id="link-44" class="py-name"><a title="Bio.MarkovModel._readline_and_check_start" class="py-name" href="#" onclick="return doclink('link-44', '_readline_and_check_start', 'link-21');">_readline_and_check_start</a></tt><tt class="py-op">(</tt><tt id="link-45" class="py-name"><a title="Bio.LocusLink.web_parse.handle
Bio.Ndb.handle" class="py-name" href="#" onclick="return doclink('link-45', 'handle', 'link-10');">handle</a></tt><tt class="py-op">,</tt> <tt class="py-string">" %s:"</tt> <tt class="py-op">%</tt> <tt class="py-name">states</tt><tt class="py-op">[</tt><tt id="link-46" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-46', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">)</tt> </tt>
<a name="L81"></a><tt class="py-lineno"> 81</tt> <tt class="py-line"> <tt class="py-name">mm</tt><tt class="py-op">.</tt><tt class="py-name">p_transition</tt><tt class="py-op">[</tt><tt id="link-47" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-47', 'i', 'link-34');">i</a></tt><tt class="py-op">,</tt><tt class="py-op">:</tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt id="link-48" class="py-name" targets="Method Bio.GFF.FeatureAggregate.map()=Bio.GFF.FeatureAggregate-class.html#map"><a title="Bio.GFF.FeatureAggregate.map" class="py-name" href="#" onclick="return doclink('link-48', 'map', 'link-48');">map</a></tt><tt class="py-op">(</tt><tt class="py-name">float</tt><tt class="py-op">,</tt> <tt class="py-name">line</tt><tt class="py-op">.</tt><tt id="link-49" class="py-name"><a title="Bio.Nexus.Trees.Tree.split
Bio.Restriction.Restriction.RestrictionBatch.split" class="py-name" href="#" onclick="return doclink('link-49', 'split', 'link-23');">split</a></tt><tt class="py-op">(</tt><tt class="py-op">)</tt><tt class="py-op">[</tt><tt class="py-number">1</tt><tt class="py-op">:</tt><tt class="py-op">]</tt><tt class="py-op">)</tt> </tt>
<a name="L82"></a><tt class="py-lineno"> 82</tt> <tt class="py-line"> </tt>
<a name="L83"></a><tt class="py-lineno"> 83</tt> <tt class="py-line"> <tt class="py-comment"># Load the emission.</tt> </tt>
<a name="L84"></a><tt class="py-lineno"> 84</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">mm</tt><tt class="py-op">.</tt><tt class="py-name">p_emission</tt> <tt class="py-op">=</tt> <tt class="py-name">zeros</tt><tt class="py-op">(</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt> <tt class="py-name">M</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> <tt id="link-50" class="py-name"><a title="Bio.MarkovModel.MATCODE" class="py-name" href="#" onclick="return doclink('link-50', 'MATCODE', 'link-6');">MATCODE</a></tt><tt class="py-op">)</tt> </tt>
<a name="L85"></a><tt class="py-lineno"> 85</tt> <tt class="py-line"> <tt class="py-name">line</tt> <tt class="py-op">=</tt> <tt id="link-51" class="py-name"><a title="Bio.MarkovModel._readline_and_check_start" class="py-name" href="#" onclick="return doclink('link-51', '_readline_and_check_start', 'link-21');">_readline_and_check_start</a></tt><tt class="py-op">(</tt><tt id="link-52" class="py-name"><a title="Bio.LocusLink.web_parse.handle
Bio.Ndb.handle" class="py-name" href="#" onclick="return doclink('link-52', 'handle', 'link-10');">handle</a></tt><tt class="py-op">,</tt> <tt class="py-string">"EMISSION:"</tt><tt class="py-op">)</tt> </tt>
<a name="L86"></a><tt class="py-lineno"> 86</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt id="link-53" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-53', 'i', 'link-34');">i</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">states</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L87"></a><tt class="py-lineno"> 87</tt> <tt class="py-line"> <tt class="py-name">line</tt> <tt class="py-op">=</tt> <tt id="link-54" class="py-name"><a title="Bio.MarkovModel._readline_and_check_start" class="py-name" href="#" onclick="return doclink('link-54', '_readline_and_check_start', 'link-21');">_readline_and_check_start</a></tt><tt class="py-op">(</tt><tt id="link-55" class="py-name"><a title="Bio.LocusLink.web_parse.handle
Bio.Ndb.handle" class="py-name" href="#" onclick="return doclink('link-55', 'handle', 'link-10');">handle</a></tt><tt class="py-op">,</tt> <tt class="py-string">" %s:"</tt> <tt class="py-op">%</tt> <tt class="py-name">states</tt><tt class="py-op">[</tt><tt id="link-56" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-56', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">)</tt> </tt>
<a name="L88"></a><tt class="py-lineno"> 88</tt> <tt class="py-line"> <tt class="py-name">mm</tt><tt class="py-op">.</tt><tt class="py-name">p_emission</tt><tt class="py-op">[</tt><tt id="link-57" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-57', 'i', 'link-34');">i</a></tt><tt class="py-op">,</tt><tt class="py-op">:</tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt id="link-58" class="py-name"><a title="Bio.GFF.FeatureAggregate.map" class="py-name" href="#" onclick="return doclink('link-58', 'map', 'link-48');">map</a></tt><tt class="py-op">(</tt><tt class="py-name">float</tt><tt class="py-op">,</tt> <tt class="py-name">line</tt><tt class="py-op">.</tt><tt id="link-59" class="py-name"><a title="Bio.Nexus.Trees.Tree.split
Bio.Restriction.Restriction.RestrictionBatch.split" class="py-name" href="#" onclick="return doclink('link-59', 'split', 'link-23');">split</a></tt><tt class="py-op">(</tt><tt class="py-op">)</tt><tt class="py-op">[</tt><tt class="py-number">1</tt><tt class="py-op">:</tt><tt class="py-op">]</tt><tt class="py-op">)</tt> </tt>
<a name="L89"></a><tt class="py-lineno"> 89</tt> <tt class="py-line"> </tt>
<a name="L90"></a><tt class="py-lineno"> 90</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt class="py-name">mm</tt> </tt>
</div><a name="L91"></a><tt class="py-lineno"> 91</tt> <tt class="py-line"> </tt>
<a name="save"></a><div id="save-def"><a name="L92"></a><tt class="py-lineno"> 92</tt> <a class="py-toggle" href="#" id="save-toggle" onclick="return toggle('save');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#save">save</a><tt class="py-op">(</tt><tt class="py-param">mm</tt><tt class="py-op">,</tt> <tt class="py-param">handle</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="save-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="save-expanded"><a name="L93"></a><tt class="py-lineno"> 93</tt> <tt class="py-line"> <tt class="py-docstring">"""save(mm, handle)"""</tt> </tt>
<a name="L94"></a><tt class="py-lineno"> 94</tt> <tt class="py-line"> <tt class="py-comment"># This will fail if there are spaces in the states or alphabet.</tt> </tt>
<a name="L95"></a><tt class="py-lineno"> 95</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">w</tt> <tt class="py-op">=</tt> <tt id="link-60" class="py-name"><a title="Bio.LocusLink.web_parse.handle
Bio.Ndb.handle" class="py-name" href="#" onclick="return doclink('link-60', 'handle', 'link-10');">handle</a></tt><tt class="py-op">.</tt><tt id="link-61" class="py-name" targets="Method Bio.AlignAce.Motif.Motif.write()=Bio.AlignAce.Motif.Motif-class.html#write,Function Bio.AlignIO.write()=Bio.AlignIO-module.html#write,Method Bio.EUtils.sourcegen.SourceFile.write()=Bio.EUtils.sourcegen.SourceFile-class.html#write,Method Bio.EUtils.sourcegen.SourceGen.write()=Bio.EUtils.sourcegen.SourceGen-class.html#write,Method Bio.NeuralNetwork.Gene.Pattern.PatternIO.write()=Bio.NeuralNetwork.Gene.Pattern.PatternIO-class.html#write,Function Bio.SeqIO.write()=Bio.SeqIO-module.html#write,Method Bio.Writer.Writer.write()=Bio.Writer.Writer-class.html#write,Method Bio.writers.SeqRecord.embl.WriteEmbl.write()=Bio.writers.SeqRecord.embl.WriteEmbl-class.html#write,Method Bio.writers.SeqRecord.fasta.WriteFasta.write()=Bio.writers.SeqRecord.fasta.WriteFasta-class.html#write"><a title="Bio.AlignAce.Motif.Motif.write
Bio.AlignIO.write
Bio.EUtils.sourcegen.SourceFile.write
Bio.EUtils.sourcegen.SourceGen.write
Bio.NeuralNetwork.Gene.Pattern.PatternIO.write
Bio.SeqIO.write
Bio.Writer.Writer.write
Bio.writers.SeqRecord.embl.WriteEmbl.write
Bio.writers.SeqRecord.fasta.WriteFasta.write" class="py-name" href="#" onclick="return doclink('link-61', 'write', 'link-61');">write</a></tt> </tt>
<a name="L96"></a><tt class="py-lineno"> 96</tt> <tt class="py-line"> <tt class="py-name">w</tt><tt class="py-op">(</tt><tt class="py-string">"STATES: %s\n"</tt> <tt class="py-op">%</tt> <tt class="py-string">' '</tt><tt class="py-op">.</tt><tt class="py-name">join</tt><tt class="py-op">(</tt><tt class="py-name">mm</tt><tt class="py-op">.</tt><tt class="py-name">states</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
<a name="L97"></a><tt class="py-lineno"> 97</tt> <tt class="py-line"> <tt class="py-name">w</tt><tt class="py-op">(</tt><tt class="py-string">"ALPHABET: %s\n"</tt> <tt class="py-op">%</tt> <tt class="py-string">' '</tt><tt class="py-op">.</tt><tt class="py-name">join</tt><tt class="py-op">(</tt><tt class="py-name">mm</tt><tt class="py-op">.</tt><tt id="link-62" class="py-name"><a title="Bio.Prosite.Pattern.Prosite.alphabet
Bio.Std.alphabet" class="py-name" href="#" onclick="return doclink('link-62', 'alphabet', 'link-8');">alphabet</a></tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
<a name="L98"></a><tt class="py-lineno"> 98</tt> <tt class="py-line"> <tt class="py-name">w</tt><tt class="py-op">(</tt><tt class="py-string">"INITIAL:\n"</tt><tt class="py-op">)</tt> </tt>
<a name="L99"></a><tt class="py-lineno"> 99</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt id="link-63" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-63', 'i', 'link-34');">i</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">mm</tt><tt class="py-op">.</tt><tt class="py-name">p_initial</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L100"></a><tt class="py-lineno">100</tt> <tt class="py-line"> <tt class="py-name">w</tt><tt class="py-op">(</tt><tt class="py-string">" %s: %g\n"</tt> <tt class="py-op">%</tt> <tt class="py-op">(</tt><tt class="py-name">mm</tt><tt class="py-op">.</tt><tt class="py-name">states</tt><tt class="py-op">[</tt><tt id="link-64" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-64', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">,</tt> <tt class="py-name">mm</tt><tt class="py-op">.</tt><tt class="py-name">p_initial</tt><tt class="py-op">[</tt><tt id="link-65" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-65', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
<a name="L101"></a><tt class="py-lineno">101</tt> <tt class="py-line"> <tt class="py-name">w</tt><tt class="py-op">(</tt><tt class="py-string">"TRANSITION:\n"</tt><tt class="py-op">)</tt> </tt>
<a name="L102"></a><tt class="py-lineno">102</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt id="link-66" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-66', 'i', 'link-34');">i</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">mm</tt><tt class="py-op">.</tt><tt class="py-name">p_transition</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L103"></a><tt class="py-lineno">103</tt> <tt class="py-line"> <tt id="link-67" class="py-name" targets="Variable Bio.MarkovModel.x=Bio.MarkovModel-module.html#x,Variable Bio.Statistics.lowess.x=Bio.Statistics.lowess-module.html#x"><a title="Bio.MarkovModel.x
Bio.Statistics.lowess.x" class="py-name" href="#" onclick="return doclink('link-67', 'x', 'link-67');">x</a></tt> <tt class="py-op">=</tt> <tt id="link-68" class="py-name"><a title="Bio.GFF.FeatureAggregate.map" class="py-name" href="#" onclick="return doclink('link-68', 'map', 'link-48');">map</a></tt><tt class="py-op">(</tt><tt class="py-name">str</tt><tt class="py-op">,</tt> <tt class="py-name">mm</tt><tt class="py-op">.</tt><tt class="py-name">p_transition</tt><tt class="py-op">[</tt><tt id="link-69" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-69', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">)</tt> </tt>
<a name="L104"></a><tt class="py-lineno">104</tt> <tt class="py-line"> <tt class="py-name">w</tt><tt class="py-op">(</tt><tt class="py-string">" %s: %s\n"</tt> <tt class="py-op">%</tt> <tt class="py-op">(</tt><tt class="py-name">mm</tt><tt class="py-op">.</tt><tt class="py-name">states</tt><tt class="py-op">[</tt><tt id="link-70" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-70', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">,</tt> <tt class="py-string">' '</tt><tt class="py-op">.</tt><tt class="py-name">join</tt><tt class="py-op">(</tt><tt id="link-71" class="py-name"><a title="Bio.MarkovModel.x
Bio.Statistics.lowess.x" class="py-name" href="#" onclick="return doclink('link-71', 'x', 'link-67');">x</a></tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
<a name="L105"></a><tt class="py-lineno">105</tt> <tt class="py-line"> <tt class="py-name">w</tt><tt class="py-op">(</tt><tt class="py-string">"EMISSION:\n"</tt><tt class="py-op">)</tt> </tt>
<a name="L106"></a><tt class="py-lineno">106</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt id="link-72" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-72', 'i', 'link-34');">i</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">mm</tt><tt class="py-op">.</tt><tt class="py-name">p_emission</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L107"></a><tt class="py-lineno">107</tt> <tt class="py-line"> <tt id="link-73" class="py-name"><a title="Bio.MarkovModel.x
Bio.Statistics.lowess.x" class="py-name" href="#" onclick="return doclink('link-73', 'x', 'link-67');">x</a></tt> <tt class="py-op">=</tt> <tt id="link-74" class="py-name"><a title="Bio.GFF.FeatureAggregate.map" class="py-name" href="#" onclick="return doclink('link-74', 'map', 'link-48');">map</a></tt><tt class="py-op">(</tt><tt class="py-name">str</tt><tt class="py-op">,</tt> <tt class="py-name">mm</tt><tt class="py-op">.</tt><tt class="py-name">p_emission</tt><tt class="py-op">[</tt><tt id="link-75" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-75', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">)</tt> </tt>
<a name="L108"></a><tt class="py-lineno">108</tt> <tt class="py-line"> <tt class="py-name">w</tt><tt class="py-op">(</tt><tt class="py-string">" %s: %s\n"</tt> <tt class="py-op">%</tt> <tt class="py-op">(</tt><tt class="py-name">mm</tt><tt class="py-op">.</tt><tt class="py-name">states</tt><tt class="py-op">[</tt><tt id="link-76" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-76', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">,</tt> <tt class="py-string">' '</tt><tt class="py-op">.</tt><tt class="py-name">join</tt><tt class="py-op">(</tt><tt id="link-77" class="py-name"><a title="Bio.MarkovModel.x
Bio.Statistics.lowess.x" class="py-name" href="#" onclick="return doclink('link-77', 'x', 'link-67');">x</a></tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
</div><a name="L109"></a><tt class="py-lineno">109</tt> <tt class="py-line"> </tt>
<a name="L110"></a><tt class="py-lineno">110</tt> <tt class="py-line"><tt class="py-comment"># XXX allow them to specify starting points</tt> </tt>
<a name="train_bw"></a><div id="train_bw-def"><a name="L111"></a><tt class="py-lineno">111</tt> <a class="py-toggle" href="#" id="train_bw-toggle" onclick="return toggle('train_bw');">-</a><tt class="py-line"><tt class="py-comment"></tt><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#train_bw">train_bw</a><tt class="py-op">(</tt><tt class="py-param">states</tt><tt class="py-op">,</tt> <tt class="py-param">alphabet</tt><tt class="py-op">,</tt> <tt class="py-param">training_data</tt><tt class="py-op">,</tt> </tt>
<a name="L112"></a><tt class="py-lineno">112</tt> <tt class="py-line"> <tt class="py-param">pseudo_initial</tt><tt class="py-op">=</tt><tt class="py-name">None</tt><tt class="py-op">,</tt> <tt class="py-param">pseudo_transition</tt><tt class="py-op">=</tt><tt class="py-name">None</tt><tt class="py-op">,</tt> <tt class="py-param">pseudo_emission</tt><tt class="py-op">=</tt><tt class="py-name">None</tt><tt class="py-op">,</tt> </tt>
<a name="L113"></a><tt class="py-lineno">113</tt> <tt class="py-line"> <tt class="py-param">update_fn</tt><tt class="py-op">=</tt><tt class="py-name">None</tt><tt class="py-op">,</tt> </tt>
<a name="L114"></a><tt class="py-lineno">114</tt> <tt class="py-line"> <tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="train_bw-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="train_bw-expanded"><a name="L115"></a><tt class="py-lineno">115</tt> <tt class="py-line"> <tt class="py-docstring">"""train_bw(states, alphabet, training_data[, pseudo_initial]</tt> </tt>
<a name="L116"></a><tt class="py-lineno">116</tt> <tt class="py-line"><tt class="py-docstring"> [, pseudo_transition][, pseudo_emission][, update_fn]) -> MarkovModel</tt> </tt>
<a name="L117"></a><tt class="py-lineno">117</tt> <tt class="py-line"><tt class="py-docstring"></tt> </tt>
<a name="L118"></a><tt class="py-lineno">118</tt> <tt class="py-line"><tt class="py-docstring"> Train a MarkovModel using the Baum-Welch algorithm. states is a list</tt> </tt>
<a name="L119"></a><tt class="py-lineno">119</tt> <tt class="py-line"><tt class="py-docstring"> of strings that describe the names of each state. alphabet is a</tt> </tt>
<a name="L120"></a><tt class="py-lineno">120</tt> <tt class="py-line"><tt class="py-docstring"> list of objects that indicate the allowed outputs. training_data</tt> </tt>
<a name="L121"></a><tt class="py-lineno">121</tt> <tt class="py-line"><tt class="py-docstring"> is a list of observations. Each observation is a list of objects</tt> </tt>
<a name="L122"></a><tt class="py-lineno">122</tt> <tt class="py-line"><tt class="py-docstring"> from the alphabet.</tt> </tt>
<a name="L123"></a><tt class="py-lineno">123</tt> <tt class="py-line"><tt class="py-docstring"></tt> </tt>
<a name="L124"></a><tt class="py-lineno">124</tt> <tt class="py-line"><tt class="py-docstring"> pseudo_initial, pseudo_transition, and pseudo_emission are</tt> </tt>
<a name="L125"></a><tt class="py-lineno">125</tt> <tt class="py-line"><tt class="py-docstring"> optional parameters that you can use to assign pseudo-counts to</tt> </tt>
<a name="L126"></a><tt class="py-lineno">126</tt> <tt class="py-line"><tt class="py-docstring"> different matrices. They should be matrices of the appropriate</tt> </tt>
<a name="L127"></a><tt class="py-lineno">127</tt> <tt class="py-line"><tt class="py-docstring"> size that contain numbers to add to each parameter matrix, before</tt> </tt>
<a name="L128"></a><tt class="py-lineno">128</tt> <tt class="py-line"><tt class="py-docstring"> normalization.</tt> </tt>
<a name="L129"></a><tt class="py-lineno">129</tt> <tt class="py-line"><tt class="py-docstring"></tt> </tt>
<a name="L130"></a><tt class="py-lineno">130</tt> <tt class="py-line"><tt class="py-docstring"> update_fn is an optional callback that takes parameters</tt> </tt>
<a name="L131"></a><tt class="py-lineno">131</tt> <tt class="py-line"><tt class="py-docstring"> (iteration, log_likelihood). It is called once per iteration.</tt> </tt>
<a name="L132"></a><tt class="py-lineno">132</tt> <tt class="py-line"><tt class="py-docstring"></tt> </tt>
<a name="L133"></a><tt class="py-lineno">133</tt> <tt class="py-line"><tt class="py-docstring"> """</tt> </tt>
<a name="L134"></a><tt class="py-lineno">134</tt> <tt class="py-line"> <tt class="py-name">N</tt><tt class="py-op">,</tt> <tt class="py-name">M</tt> <tt class="py-op">=</tt> <tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">states</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> <tt class="py-name">len</tt><tt class="py-op">(</tt><tt id="link-78" class="py-name"><a title="Bio.Prosite.Pattern.Prosite.alphabet
Bio.Std.alphabet" class="py-name" href="#" onclick="return doclink('link-78', 'alphabet', 'link-8');">alphabet</a></tt><tt class="py-op">)</tt> </tt>
<a name="L135"></a><tt class="py-lineno">135</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-keyword">not</tt> <tt class="py-name">training_data</tt><tt class="py-op">:</tt> </tt>
<a name="L136"></a><tt class="py-lineno">136</tt> <tt class="py-line"> <tt class="py-keyword">raise</tt> <tt class="py-name">ValueError</tt><tt class="py-op">,</tt> <tt class="py-string">"No training data given."</tt> </tt>
<a name="L137"></a><tt class="py-lineno">137</tt> <tt class="py-line"> <tt class="py-name">pseudo_initial</tt><tt class="py-op">,</tt> <tt class="py-name">pseudo_emission</tt><tt class="py-op">,</tt> <tt class="py-name">pseudo_transition</tt> <tt class="py-op">=</tt> <tt id="link-79" class="py-name"><a title="Bio.GFF.FeatureAggregate.map" class="py-name" href="#" onclick="return doclink('link-79', 'map', 'link-48');">map</a></tt><tt class="py-op">(</tt> </tt>
<a name="L138"></a><tt class="py-lineno">138</tt> <tt class="py-line"> <tt id="link-80" class="py-name" targets="Function Bio.MarkovModel._safe_asarray()=Bio.MarkovModel-module.html#_safe_asarray"><a title="Bio.MarkovModel._safe_asarray" class="py-name" href="#" onclick="return doclink('link-80', '_safe_asarray', 'link-80');">_safe_asarray</a></tt><tt class="py-op">,</tt> <tt class="py-op">(</tt><tt class="py-name">pseudo_initial</tt><tt class="py-op">,</tt> <tt class="py-name">pseudo_emission</tt><tt class="py-op">,</tt> <tt class="py-name">pseudo_transition</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
<a name="L139"></a><tt class="py-lineno">139</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-name">pseudo_initial</tt> <tt class="py-keyword">and</tt> <tt class="py-name">shape</tt><tt class="py-op">(</tt><tt class="py-name">pseudo_initial</tt><tt class="py-op">)</tt> <tt class="py-op">!=</tt> <tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L140"></a><tt class="py-lineno">140</tt> <tt class="py-line"> <tt class="py-keyword">raise</tt> <tt class="py-name">ValueError</tt><tt class="py-op">,</tt> <tt class="py-string">"pseudo_initial not shape len(states)"</tt> </tt>
<a name="L141"></a><tt class="py-lineno">141</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-name">pseudo_transition</tt> <tt class="py-keyword">and</tt> <tt class="py-name">shape</tt><tt class="py-op">(</tt><tt class="py-name">pseudo_transition</tt><tt class="py-op">)</tt> <tt class="py-op">!=</tt> <tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt><tt class="py-name">N</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L142"></a><tt class="py-lineno">142</tt> <tt class="py-line"> <tt class="py-keyword">raise</tt> <tt class="py-name">ValueError</tt><tt class="py-op">,</tt> <tt class="py-string">"pseudo_transition not shape "</tt> <tt class="py-op">+</tt> \ </tt>
<a name="L143"></a><tt class="py-lineno">143</tt> <tt class="py-line"> <tt class="py-string">"len(states) X len(states)"</tt> </tt>
<a name="L144"></a><tt class="py-lineno">144</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-name">pseudo_emission</tt> <tt class="py-keyword">and</tt> <tt class="py-name">shape</tt><tt class="py-op">(</tt><tt class="py-name">pseudo_emission</tt><tt class="py-op">)</tt> <tt class="py-op">!=</tt> <tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt><tt class="py-name">M</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L145"></a><tt class="py-lineno">145</tt> <tt class="py-line"> <tt class="py-keyword">raise</tt> <tt class="py-name">ValueError</tt><tt class="py-op">,</tt> <tt class="py-string">"pseudo_emission not shape "</tt> <tt class="py-op">+</tt> \ </tt>
<a name="L146"></a><tt class="py-lineno">146</tt> <tt class="py-line"> <tt class="py-string">"len(states) X len(alphabet)"</tt> </tt>
<a name="L147"></a><tt class="py-lineno">147</tt> <tt class="py-line"> </tt>
<a name="L148"></a><tt class="py-lineno">148</tt> <tt class="py-line"> <tt class="py-comment"># Training data is given as a list of members of the alphabet.</tt> </tt>
<a name="L149"></a><tt class="py-lineno">149</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># Replace those with indexes into the alphabet list for easier</tt> </tt>
<a name="L150"></a><tt class="py-lineno">150</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># computation.</tt> </tt>
<a name="L151"></a><tt class="py-lineno">151</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">training_outputs</tt> <tt class="py-op">=</tt> <tt class="py-op">[</tt><tt class="py-op">]</tt> </tt>
<a name="L152"></a><tt class="py-lineno">152</tt> <tt class="py-line"> <tt class="py-name">indexes</tt> <tt class="py-op">=</tt> <tt id="link-81" class="py-name"><a title="Bio.listfns" class="py-name" href="#" onclick="return doclink('link-81', 'listfns', 'link-1');">listfns</a></tt><tt class="py-op">.</tt><tt id="link-82" class="py-name" targets="Function Bio.listfns.itemindex()=Bio.listfns-module.html#itemindex"><a title="Bio.listfns.itemindex" class="py-name" href="#" onclick="return doclink('link-82', 'itemindex', 'link-82');">itemindex</a></tt><tt class="py-op">(</tt><tt id="link-83" class="py-name"><a title="Bio.Prosite.Pattern.Prosite.alphabet
Bio.Std.alphabet" class="py-name" href="#" onclick="return doclink('link-83', 'alphabet', 'link-8');">alphabet</a></tt><tt class="py-op">)</tt> </tt>
<a name="L153"></a><tt class="py-lineno">153</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt class="py-name">outputs</tt> <tt class="py-keyword">in</tt> <tt class="py-name">training_data</tt><tt class="py-op">:</tt> </tt>
<a name="L154"></a><tt class="py-lineno">154</tt> <tt class="py-line"> <tt class="py-name">training_outputs</tt><tt class="py-op">.</tt><tt id="link-84" class="py-name" targets="Method Bio.Crystal.Chain.append()=Bio.Crystal.Chain-class.html#append,Method Bio.EUtils.POM.ElementNode.append()=Bio.EUtils.POM.ElementNode-class.html#append,Method Bio.EUtils.sourcegen.SourceFile.append()=Bio.EUtils.sourcegen.SourceFile-class.html#append,Method Bio.SCOP.Raf.SeqMap.append()=Bio.SCOP.Raf.SeqMap-class.html#append,Method Bio.Seq.MutableSeq.append()=Bio.Seq.MutableSeq-class.html#append,Method Bio.Wise.psw.Alignment.append()=Bio.Wise.psw.Alignment-class.html#append,Method Bio.Wise.psw.AlignmentColumn.append()=Bio.Wise.psw.AlignmentColumn-class.html#append,Method Martel.msre_parse.SubPattern.append()=Martel.msre_parse.SubPattern-class.html#append"><a title="Bio.Crystal.Chain.append
Bio.EUtils.POM.ElementNode.append
Bio.EUtils.sourcegen.SourceFile.append
Bio.SCOP.Raf.SeqMap.append
Bio.Seq.MutableSeq.append
Bio.Wise.psw.Alignment.append
Bio.Wise.psw.AlignmentColumn.append
Martel.msre_parse.SubPattern.append" class="py-name" href="#" onclick="return doclink('link-84', 'append', 'link-84');">append</a></tt><tt class="py-op">(</tt><tt class="py-op">[</tt><tt class="py-name">indexes</tt><tt class="py-op">[</tt><tt id="link-85" class="py-name"><a title="Bio.MarkovModel.x
Bio.Statistics.lowess.x" class="py-name" href="#" onclick="return doclink('link-85', 'x', 'link-67');">x</a></tt><tt class="py-op">]</tt> <tt class="py-keyword">for</tt> <tt id="link-86" class="py-name"><a title="Bio.MarkovModel.x
Bio.Statistics.lowess.x" class="py-name" href="#" onclick="return doclink('link-86', 'x', 'link-67');">x</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">outputs</tt><tt class="py-op">]</tt><tt class="py-op">)</tt> </tt>
<a name="L155"></a><tt class="py-lineno">155</tt> <tt class="py-line"> </tt>
<a name="L156"></a><tt class="py-lineno">156</tt> <tt class="py-line"> <tt class="py-comment"># Do some sanity checking on the outputs.</tt> </tt>
<a name="L157"></a><tt class="py-lineno">157</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt id="link-87" class="py-name" targets="Method Bio.Compass._Consumer.lengths()=Bio.Compass._Consumer-class.html#lengths"><a title="Bio.Compass._Consumer.lengths" class="py-name" href="#" onclick="return doclink('link-87', 'lengths', 'link-87');">lengths</a></tt> <tt class="py-op">=</tt> <tt id="link-88" class="py-name"><a title="Bio.GFF.FeatureAggregate.map" class="py-name" href="#" onclick="return doclink('link-88', 'map', 'link-48');">map</a></tt><tt class="py-op">(</tt><tt class="py-name">len</tt><tt class="py-op">,</tt> <tt class="py-name">training_outputs</tt><tt class="py-op">)</tt> </tt>
<a name="L158"></a><tt class="py-lineno">158</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-name">min</tt><tt class="py-op">(</tt><tt id="link-89" class="py-name"><a title="Bio.Compass._Consumer.lengths" class="py-name" href="#" onclick="return doclink('link-89', 'lengths', 'link-87');">lengths</a></tt><tt class="py-op">)</tt> <tt class="py-op">==</tt> <tt class="py-number">0</tt><tt class="py-op">:</tt> </tt>
<a name="L159"></a><tt class="py-lineno">159</tt> <tt class="py-line"> <tt class="py-keyword">raise</tt> <tt class="py-name">ValueError</tt><tt class="py-op">,</tt> <tt class="py-string">"I got training data with outputs of length 0"</tt> </tt>
<a name="L160"></a><tt class="py-lineno">160</tt> <tt class="py-line"> </tt>
<a name="L161"></a><tt class="py-lineno">161</tt> <tt class="py-line"> <tt class="py-comment"># Do the training with baum welch.</tt> </tt>
<a name="L162"></a><tt class="py-lineno">162</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt id="link-90" class="py-name"><a title="Bio.MarkovModel.x
Bio.Statistics.lowess.x" class="py-name" href="#" onclick="return doclink('link-90', 'x', 'link-67');">x</a></tt> <tt class="py-op">=</tt> <tt id="link-91" class="py-name" targets="Function Bio.MarkovModel._baum_welch()=Bio.MarkovModel-module.html#_baum_welch"><a title="Bio.MarkovModel._baum_welch" class="py-name" href="#" onclick="return doclink('link-91', '_baum_welch', 'link-91');">_baum_welch</a></tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt> <tt class="py-name">M</tt><tt class="py-op">,</tt> <tt class="py-name">training_outputs</tt><tt class="py-op">,</tt> </tt>
<a name="L163"></a><tt class="py-lineno">163</tt> <tt class="py-line"> <tt class="py-name">pseudo_initial</tt><tt class="py-op">=</tt><tt class="py-name">pseudo_initial</tt><tt class="py-op">,</tt> </tt>
<a name="L164"></a><tt class="py-lineno">164</tt> <tt class="py-line"> <tt class="py-name">pseudo_transition</tt><tt class="py-op">=</tt><tt class="py-name">pseudo_transition</tt><tt class="py-op">,</tt> </tt>
<a name="L165"></a><tt class="py-lineno">165</tt> <tt class="py-line"> <tt class="py-name">pseudo_emission</tt><tt class="py-op">=</tt><tt class="py-name">pseudo_emission</tt><tt class="py-op">,</tt> </tt>
<a name="L166"></a><tt class="py-lineno">166</tt> <tt class="py-line"> <tt class="py-name">update_fn</tt><tt class="py-op">=</tt><tt class="py-name">update_fn</tt><tt class="py-op">)</tt> </tt>
<a name="L167"></a><tt class="py-lineno">167</tt> <tt class="py-line"> <tt class="py-name">p_initial</tt><tt class="py-op">,</tt> <tt class="py-name">p_transition</tt><tt class="py-op">,</tt> <tt class="py-name">p_emission</tt> <tt class="py-op">=</tt> <tt id="link-92" class="py-name"><a title="Bio.MarkovModel.x
Bio.Statistics.lowess.x" class="py-name" href="#" onclick="return doclink('link-92', 'x', 'link-67');">x</a></tt> </tt>
<a name="L168"></a><tt class="py-lineno">168</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt id="link-93" class="py-name"><a title="Bio.HMM.MarkovModel
Bio.MarkovModel
Bio.MarkovModel.MarkovModel" class="py-name" href="#" onclick="return doclink('link-93', 'MarkovModel', 'link-28');">MarkovModel</a></tt><tt class="py-op">(</tt><tt class="py-name">states</tt><tt class="py-op">,</tt> <tt id="link-94" class="py-name"><a title="Bio.Prosite.Pattern.Prosite.alphabet
Bio.Std.alphabet" class="py-name" href="#" onclick="return doclink('link-94', 'alphabet', 'link-8');">alphabet</a></tt><tt class="py-op">,</tt> <tt class="py-name">p_initial</tt><tt class="py-op">,</tt> <tt class="py-name">p_transition</tt><tt class="py-op">,</tt> <tt class="py-name">p_emission</tt><tt class="py-op">)</tt> </tt>
</div><a name="L169"></a><tt class="py-lineno">169</tt> <tt class="py-line"> </tt>
<a name="L170"></a><tt class="py-lineno">170</tt> <tt class="py-line"><tt id="link-95" class="py-name" targets="Variable Bio.MarkovModel.MAX_ITERATIONS=Bio.MarkovModel-module.html#MAX_ITERATIONS"><a title="Bio.MarkovModel.MAX_ITERATIONS" class="py-name" href="#" onclick="return doclink('link-95', 'MAX_ITERATIONS', 'link-95');">MAX_ITERATIONS</a></tt> <tt class="py-op">=</tt> <tt class="py-number">1000</tt> </tt>
<a name="_baum_welch"></a><div id="_baum_welch-def"><a name="L171"></a><tt class="py-lineno">171</tt> <a class="py-toggle" href="#" id="_baum_welch-toggle" onclick="return toggle('_baum_welch');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#_baum_welch">_baum_welch</a><tt class="py-op">(</tt><tt class="py-param">N</tt><tt class="py-op">,</tt> <tt class="py-param">M</tt><tt class="py-op">,</tt> <tt class="py-param">training_outputs</tt><tt class="py-op">,</tt> </tt>
<a name="L172"></a><tt class="py-lineno">172</tt> <tt class="py-line"> <tt class="py-param">p_initial</tt><tt class="py-op">=</tt><tt class="py-name">None</tt><tt class="py-op">,</tt> <tt class="py-param">p_transition</tt><tt class="py-op">=</tt><tt class="py-name">None</tt><tt class="py-op">,</tt> <tt class="py-param">p_emission</tt><tt class="py-op">=</tt><tt class="py-name">None</tt><tt class="py-op">,</tt> </tt>
<a name="L173"></a><tt class="py-lineno">173</tt> <tt class="py-line"> <tt class="py-param">pseudo_initial</tt><tt class="py-op">=</tt><tt class="py-name">None</tt><tt class="py-op">,</tt> <tt class="py-param">pseudo_transition</tt><tt class="py-op">=</tt><tt class="py-name">None</tt><tt class="py-op">,</tt> </tt>
<a name="L174"></a><tt class="py-lineno">174</tt> <tt class="py-line"> <tt class="py-param">pseudo_emission</tt><tt class="py-op">=</tt><tt class="py-name">None</tt><tt class="py-op">,</tt> <tt class="py-param">update_fn</tt><tt class="py-op">=</tt><tt class="py-name">None</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="_baum_welch-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="_baum_welch-expanded"><a name="L175"></a><tt class="py-lineno">175</tt> <tt class="py-line"> <tt class="py-comment"># Returns (p_initial, p_transition, p_emission)</tt> </tt>
<a name="L176"></a><tt class="py-lineno">176</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">p_initial</tt> <tt class="py-op">=</tt> <tt id="link-96" class="py-name" targets="Function Bio.MarkovModel._safe_copy_and_check()=Bio.MarkovModel-module.html#_safe_copy_and_check"><a title="Bio.MarkovModel._safe_copy_and_check" class="py-name" href="#" onclick="return doclink('link-96', '_safe_copy_and_check', 'link-96');">_safe_copy_and_check</a></tt><tt class="py-op">(</tt><tt class="py-name">p_initial</tt><tt class="py-op">,</tt> <tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> <tt class="py-keyword">or</tt> \ </tt>
<a name="L177"></a><tt class="py-lineno">177</tt> <tt class="py-line"> <tt id="link-97" class="py-name" targets="Function Bio.MarkovModel._random_norm()=Bio.MarkovModel-module.html#_random_norm"><a title="Bio.MarkovModel._random_norm" class="py-name" href="#" onclick="return doclink('link-97', '_random_norm', 'link-97');">_random_norm</a></tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">)</tt> </tt>
<a name="L178"></a><tt class="py-lineno">178</tt> <tt class="py-line"> <tt class="py-name">p_transition</tt> <tt class="py-op">=</tt> <tt id="link-98" class="py-name"><a title="Bio.MarkovModel._safe_copy_and_check" class="py-name" href="#" onclick="return doclink('link-98', '_safe_copy_and_check', 'link-96');">_safe_copy_and_check</a></tt><tt class="py-op">(</tt><tt class="py-name">p_transition</tt><tt class="py-op">,</tt> <tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt><tt class="py-name">N</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> <tt class="py-keyword">or</tt> \ </tt>
<a name="L179"></a><tt class="py-lineno">179</tt> <tt class="py-line"> <tt id="link-99" class="py-name"><a title="Bio.MarkovModel._random_norm" class="py-name" href="#" onclick="return doclink('link-99', '_random_norm', 'link-97');">_random_norm</a></tt><tt class="py-op">(</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt><tt class="py-name">N</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
<a name="L180"></a><tt class="py-lineno">180</tt> <tt class="py-line"> <tt class="py-name">p_emission</tt> <tt class="py-op">=</tt> <tt id="link-100" class="py-name"><a title="Bio.MarkovModel._safe_copy_and_check" class="py-name" href="#" onclick="return doclink('link-100', '_safe_copy_and_check', 'link-96');">_safe_copy_and_check</a></tt><tt class="py-op">(</tt><tt class="py-name">p_emission</tt><tt class="py-op">,</tt> <tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt><tt class="py-name">M</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> <tt class="py-keyword">or</tt> \ </tt>
<a name="L181"></a><tt class="py-lineno">181</tt> <tt class="py-line"> <tt id="link-101" class="py-name"><a title="Bio.MarkovModel._random_norm" class="py-name" href="#" onclick="return doclink('link-101', '_random_norm', 'link-97');">_random_norm</a></tt><tt class="py-op">(</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt><tt class="py-name">M</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
<a name="L182"></a><tt class="py-lineno">182</tt> <tt class="py-line"> </tt>
<a name="L183"></a><tt class="py-lineno">183</tt> <tt class="py-line"> <tt class="py-comment"># Do all the calculations in log space to avoid underflows.</tt> </tt>
<a name="L184"></a><tt class="py-lineno">184</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">lp_initial</tt><tt class="py-op">,</tt> <tt class="py-name">lp_transition</tt><tt class="py-op">,</tt> <tt class="py-name">lp_emission</tt> <tt class="py-op">=</tt> <tt id="link-102" class="py-name"><a title="Bio.GFF.FeatureAggregate.map" class="py-name" href="#" onclick="return doclink('link-102', 'map', 'link-48');">map</a></tt><tt class="py-op">(</tt> </tt>
<a name="L185"></a><tt class="py-lineno">185</tt> <tt class="py-line"> <tt id="link-103" class="py-name"><a title="Bio.Affy.CelFile.log
Bio.LogisticRegression.log
Bio.MarkovModel.log
Bio.MaxEntropy.log
Bio.NaiveBayes.log
Bio.Statistics.lowess.log
Bio.distance.log
Bio.kNN.log" class="py-name" href="#" onclick="return doclink('link-103', 'log', 'link-4');">log</a></tt><tt class="py-op">,</tt> <tt class="py-op">(</tt><tt class="py-name">p_initial</tt><tt class="py-op">,</tt> <tt class="py-name">p_transition</tt><tt class="py-op">,</tt> <tt class="py-name">p_emission</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
<a name="L186"></a><tt class="py-lineno">186</tt> <tt class="py-line"> <tt class="py-name">lpseudo_initial</tt><tt class="py-op">,</tt> <tt class="py-name">lpseudo_transition</tt><tt class="py-op">,</tt> <tt class="py-name">lpseudo_emission</tt> <tt class="py-op">=</tt> <tt id="link-104" class="py-name"><a title="Bio.GFF.FeatureAggregate.map" class="py-name" href="#" onclick="return doclink('link-104', 'map', 'link-48');">map</a></tt><tt class="py-op">(</tt> </tt>
<a name="L187"></a><tt class="py-lineno">187</tt> <tt class="py-line"> <tt id="link-105" class="py-name" targets="Function Bio.MarkovModel._safe_log()=Bio.MarkovModel-module.html#_safe_log"><a title="Bio.MarkovModel._safe_log" class="py-name" href="#" onclick="return doclink('link-105', '_safe_log', 'link-105');">_safe_log</a></tt><tt class="py-op">,</tt> <tt class="py-op">(</tt><tt class="py-name">pseudo_initial</tt><tt class="py-op">,</tt> <tt class="py-name">pseudo_transition</tt><tt class="py-op">,</tt> <tt class="py-name">pseudo_emission</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
<a name="L188"></a><tt class="py-lineno">188</tt> <tt class="py-line"> </tt>
<a name="L189"></a><tt class="py-lineno">189</tt> <tt class="py-line"> <tt class="py-comment"># Iterate through each sequence of output, updating the parameters</tt> </tt>
<a name="L190"></a><tt class="py-lineno">190</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># to the HMM. Stop when the log likelihoods of the sequences</tt> </tt>
<a name="L191"></a><tt class="py-lineno">191</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># stops varying.</tt> </tt>
<a name="L192"></a><tt class="py-lineno">192</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">prev_llik</tt> <tt class="py-op">=</tt> <tt class="py-name">None</tt> </tt>
<a name="L193"></a><tt class="py-lineno">193</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt id="link-106" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-106', 'i', 'link-34');">i</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt id="link-107" class="py-name"><a title="Bio.MarkovModel.MAX_ITERATIONS" class="py-name" href="#" onclick="return doclink('link-107', 'MAX_ITERATIONS', 'link-95');">MAX_ITERATIONS</a></tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L194"></a><tt class="py-lineno">194</tt> <tt class="py-line"> <tt class="py-name">llik</tt> <tt class="py-op">=</tt> <tt id="link-108" class="py-name"><a title="Bio.MarkovModel.LOG0" class="py-name" href="#" onclick="return doclink('link-108', 'LOG0', 'link-3');">LOG0</a></tt> </tt>
<a name="L195"></a><tt class="py-lineno">195</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt class="py-name">outputs</tt> <tt class="py-keyword">in</tt> <tt class="py-name">training_outputs</tt><tt class="py-op">:</tt> </tt>
<a name="L196"></a><tt class="py-lineno">196</tt> <tt class="py-line"> <tt id="link-109" class="py-name"><a title="Bio.MarkovModel.x
Bio.Statistics.lowess.x" class="py-name" href="#" onclick="return doclink('link-109', 'x', 'link-67');">x</a></tt> <tt class="py-op">=</tt> <tt id="link-110" class="py-name" targets="Function Bio.MarkovModel._baum_welch_one()=Bio.MarkovModel-module.html#_baum_welch_one"><a title="Bio.MarkovModel._baum_welch_one" class="py-name" href="#" onclick="return doclink('link-110', '_baum_welch_one', 'link-110');">_baum_welch_one</a></tt><tt class="py-op">(</tt> </tt>
<a name="L197"></a><tt class="py-lineno">197</tt> <tt class="py-line"> <tt class="py-name">N</tt><tt class="py-op">,</tt> <tt class="py-name">M</tt><tt class="py-op">,</tt> <tt class="py-name">outputs</tt><tt class="py-op">,</tt> </tt>
<a name="L198"></a><tt class="py-lineno">198</tt> <tt class="py-line"> <tt class="py-name">lp_initial</tt><tt class="py-op">,</tt> <tt class="py-name">lp_transition</tt><tt class="py-op">,</tt> <tt class="py-name">lp_emission</tt><tt class="py-op">,</tt> </tt>
<a name="L199"></a><tt class="py-lineno">199</tt> <tt class="py-line"> <tt class="py-name">lpseudo_initial</tt><tt class="py-op">,</tt> <tt class="py-name">lpseudo_transition</tt><tt class="py-op">,</tt> <tt class="py-name">lpseudo_emission</tt><tt class="py-op">,</tt><tt class="py-op">)</tt> </tt>
<a name="L200"></a><tt class="py-lineno">200</tt> <tt class="py-line"> <tt class="py-name">llik</tt> <tt class="py-op">+=</tt> <tt id="link-111" class="py-name"><a title="Bio.MarkovModel.x
Bio.Statistics.lowess.x" class="py-name" href="#" onclick="return doclink('link-111', 'x', 'link-67');">x</a></tt> </tt>
<a name="L201"></a><tt class="py-lineno">201</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-name">update_fn</tt> <tt class="py-keyword">is</tt> <tt class="py-keyword">not</tt> <tt class="py-name">None</tt><tt class="py-op">:</tt> </tt>
<a name="L202"></a><tt class="py-lineno">202</tt> <tt class="py-line"> <tt class="py-name">update_fn</tt><tt class="py-op">(</tt><tt id="link-112" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-112', 'i', 'link-34');">i</a></tt><tt class="py-op">,</tt> <tt class="py-name">llik</tt><tt class="py-op">)</tt> </tt>
<a name="L203"></a><tt class="py-lineno">203</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-name">prev_llik</tt> <tt class="py-keyword">is</tt> <tt class="py-keyword">not</tt> <tt class="py-name">None</tt> <tt class="py-keyword">and</tt> <tt id="link-113" class="py-name" targets="Variable Bio.Affy.CelFile.fabs=Bio.Affy.CelFile-module.html#fabs,Variable Bio.LogisticRegression.fabs=Bio.LogisticRegression-module.html#fabs,Variable Bio.MarkovModel.fabs=Bio.MarkovModel-module.html#fabs,Variable Bio.MaxEntropy.fabs=Bio.MaxEntropy-module.html#fabs,Variable Bio.NaiveBayes.fabs=Bio.NaiveBayes-module.html#fabs,Variable Bio.Statistics.lowess.fabs=Bio.Statistics.lowess-module.html#fabs,Variable Bio.distance.fabs=Bio.distance-module.html#fabs,Variable Bio.kNN.fabs=Bio.kNN-module.html#fabs"><a title="Bio.Affy.CelFile.fabs
Bio.LogisticRegression.fabs
Bio.MarkovModel.fabs
Bio.MaxEntropy.fabs
Bio.NaiveBayes.fabs
Bio.Statistics.lowess.fabs
Bio.distance.fabs
Bio.kNN.fabs" class="py-name" href="#" onclick="return doclink('link-113', 'fabs', 'link-113');">fabs</a></tt><tt class="py-op">(</tt><tt class="py-name">prev_llik</tt><tt class="py-op">-</tt><tt class="py-name">llik</tt><tt class="py-op">)</tt> <tt class="py-op"><</tt> <tt class="py-number">0.1</tt><tt class="py-op">:</tt> </tt>
<a name="L204"></a><tt class="py-lineno">204</tt> <tt class="py-line"> <tt class="py-keyword">break</tt> </tt>
<a name="L205"></a><tt class="py-lineno">205</tt> <tt class="py-line"> <tt class="py-name">prev_llik</tt> <tt class="py-op">=</tt> <tt class="py-name">llik</tt> </tt>
<a name="L206"></a><tt class="py-lineno">206</tt> <tt class="py-line"> <tt class="py-keyword">else</tt><tt class="py-op">:</tt> </tt>
<a name="L207"></a><tt class="py-lineno">207</tt> <tt class="py-line"> <tt class="py-keyword">raise</tt> <tt class="py-string">"HMM did not converge in %d iterations"</tt> <tt class="py-op">%</tt> <tt id="link-114" class="py-name"><a title="Bio.MarkovModel.MAX_ITERATIONS" class="py-name" href="#" onclick="return doclink('link-114', 'MAX_ITERATIONS', 'link-95');">MAX_ITERATIONS</a></tt> </tt>
<a name="L208"></a><tt class="py-lineno">208</tt> <tt class="py-line"> </tt>
<a name="L209"></a><tt class="py-lineno">209</tt> <tt class="py-line"> <tt class="py-comment"># Return everything back in normal space.</tt> </tt>
<a name="L210"></a><tt class="py-lineno">210</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-keyword">return</tt> <tt id="link-115" class="py-name"><a title="Bio.GFF.FeatureAggregate.map" class="py-name" href="#" onclick="return doclink('link-115', 'map', 'link-48');">map</a></tt><tt class="py-op">(</tt><tt id="link-116" class="py-name" targets="Variable Bio.Affy.CelFile.exp=Bio.Affy.CelFile-module.html#exp,Variable Bio.LogisticRegression.exp=Bio.LogisticRegression-module.html#exp,Variable Bio.MarkovModel.exp=Bio.MarkovModel-module.html#exp,Variable Bio.MaxEntropy.exp=Bio.MaxEntropy-module.html#exp,Variable Bio.NaiveBayes.exp=Bio.NaiveBayes-module.html#exp,Variable Bio.Statistics.lowess.exp=Bio.Statistics.lowess-module.html#exp,Variable Bio.distance.exp=Bio.distance-module.html#exp,Variable Bio.kNN.exp=Bio.kNN-module.html#exp"><a title="Bio.Affy.CelFile.exp
Bio.LogisticRegression.exp
Bio.MarkovModel.exp
Bio.MaxEntropy.exp
Bio.NaiveBayes.exp
Bio.Statistics.lowess.exp
Bio.distance.exp
Bio.kNN.exp" class="py-name" href="#" onclick="return doclink('link-116', 'exp', 'link-116');">exp</a></tt><tt class="py-op">,</tt> <tt class="py-op">(</tt><tt class="py-name">lp_initial</tt><tt class="py-op">,</tt> <tt class="py-name">lp_transition</tt><tt class="py-op">,</tt> <tt class="py-name">lp_emission</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
</div><a name="L211"></a><tt class="py-lineno">211</tt> <tt class="py-line"> </tt>
<a name="_baum_welch_one"></a><div id="_baum_welch_one-def"><a name="L212"></a><tt class="py-lineno">212</tt> <a class="py-toggle" href="#" id="_baum_welch_one-toggle" onclick="return toggle('_baum_welch_one');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#_baum_welch_one">_baum_welch_one</a><tt class="py-op">(</tt><tt class="py-param">N</tt><tt class="py-op">,</tt> <tt class="py-param">M</tt><tt class="py-op">,</tt> <tt class="py-param">outputs</tt><tt class="py-op">,</tt> </tt>
<a name="L213"></a><tt class="py-lineno">213</tt> <tt class="py-line"> <tt class="py-param">lp_initial</tt><tt class="py-op">,</tt> <tt class="py-param">lp_transition</tt><tt class="py-op">,</tt> <tt class="py-param">lp_emission</tt><tt class="py-op">,</tt> </tt>
<a name="L214"></a><tt class="py-lineno">214</tt> <tt class="py-line"> <tt class="py-param">lpseudo_initial</tt><tt class="py-op">,</tt> <tt class="py-param">lpseudo_transition</tt><tt class="py-op">,</tt> <tt class="py-param">lpseudo_emission</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="_baum_welch_one-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="_baum_welch_one-expanded"><a name="L215"></a><tt class="py-lineno">215</tt> <tt class="py-line"> <tt class="py-comment"># Do one iteration of Baum-Welch based on a sequence of output.</tt> </tt>
<a name="L216"></a><tt class="py-lineno">216</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># NOTE: This will change the values of lp_initial, lp_transition,</tt> </tt>
<a name="L217"></a><tt class="py-lineno">217</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># and lp_emission in place.</tt> </tt>
<a name="L218"></a><tt class="py-lineno">218</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">T</tt> <tt class="py-op">=</tt> <tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">outputs</tt><tt class="py-op">)</tt> </tt>
<a name="L219"></a><tt class="py-lineno">219</tt> <tt class="py-line"> <tt class="py-name">fmat</tt> <tt class="py-op">=</tt> <tt id="link-117" class="py-name" targets="Function Bio.MarkovModel._forward()=Bio.MarkovModel-module.html#_forward"><a title="Bio.MarkovModel._forward" class="py-name" href="#" onclick="return doclink('link-117', '_forward', 'link-117');">_forward</a></tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt> <tt class="py-name">T</tt><tt class="py-op">,</tt> <tt class="py-name">lp_initial</tt><tt class="py-op">,</tt> <tt class="py-name">lp_transition</tt><tt class="py-op">,</tt> <tt class="py-name">lp_emission</tt><tt class="py-op">,</tt> <tt class="py-name">outputs</tt><tt class="py-op">)</tt> </tt>
<a name="L220"></a><tt class="py-lineno">220</tt> <tt class="py-line"> <tt class="py-name">bmat</tt> <tt class="py-op">=</tt> <tt id="link-118" class="py-name" targets="Function Bio.MarkovModel._backward()=Bio.MarkovModel-module.html#_backward"><a title="Bio.MarkovModel._backward" class="py-name" href="#" onclick="return doclink('link-118', '_backward', 'link-118');">_backward</a></tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt> <tt class="py-name">T</tt><tt class="py-op">,</tt> <tt class="py-name">lp_transition</tt><tt class="py-op">,</tt> <tt class="py-name">lp_emission</tt><tt class="py-op">,</tt> <tt class="py-name">outputs</tt><tt class="py-op">)</tt> </tt>
<a name="L221"></a><tt class="py-lineno">221</tt> <tt class="py-line"> </tt>
<a name="L222"></a><tt class="py-lineno">222</tt> <tt class="py-line"> <tt class="py-comment"># Calculate the probability of traversing each arc for any given</tt> </tt>
<a name="L223"></a><tt class="py-lineno">223</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># transition.</tt> </tt>
<a name="L224"></a><tt class="py-lineno">224</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">lp_arc</tt> <tt class="py-op">=</tt> <tt class="py-name">zeros</tt><tt class="py-op">(</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt> <tt class="py-name">N</tt><tt class="py-op">,</tt> <tt class="py-name">T</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> <tt id="link-119" class="py-name"><a title="Bio.MarkovModel.MATCODE" class="py-name" href="#" onclick="return doclink('link-119', 'MATCODE', 'link-6');">MATCODE</a></tt><tt class="py-op">)</tt> </tt>
<a name="L225"></a><tt class="py-lineno">225</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt class="py-name">t</tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">T</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L226"></a><tt class="py-lineno">226</tt> <tt class="py-line"> <tt class="py-name">k</tt> <tt class="py-op">=</tt> <tt class="py-name">outputs</tt><tt class="py-op">[</tt><tt class="py-name">t</tt><tt class="py-op">]</tt> </tt>
<a name="L227"></a><tt class="py-lineno">227</tt> <tt class="py-line"> <tt class="py-name">lp_traverse</tt> <tt class="py-op">=</tt> <tt class="py-name">zeros</tt><tt class="py-op">(</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt> <tt class="py-name">N</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> <tt id="link-120" class="py-name"><a title="Bio.MarkovModel.MATCODE" class="py-name" href="#" onclick="return doclink('link-120', 'MATCODE', 'link-6');">MATCODE</a></tt><tt class="py-op">)</tt> <tt class="py-comment"># P going over one arc.</tt> </tt>
<a name="L228"></a><tt class="py-lineno">228</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt id="link-121" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-121', 'i', 'link-34');">i</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L229"></a><tt class="py-lineno">229</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt class="py-name">j</tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L230"></a><tt class="py-lineno">230</tt> <tt class="py-line"> <tt class="py-comment"># P(getting to this arc)</tt> </tt>
<a name="L231"></a><tt class="py-lineno">231</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># P(making this transition)</tt> </tt>
<a name="L232"></a><tt class="py-lineno">232</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># P(emitting this character)</tt> </tt>
<a name="L233"></a><tt class="py-lineno">233</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># P(going to the end)</tt> </tt>
<a name="L234"></a><tt class="py-lineno">234</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">lp</tt> <tt class="py-op">=</tt> <tt class="py-name">fmat</tt><tt class="py-op">[</tt><tt id="link-122" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-122', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">[</tt><tt class="py-name">t</tt><tt class="py-op">]</tt> <tt class="py-op">+</tt> \ </tt>
<a name="L235"></a><tt class="py-lineno">235</tt> <tt class="py-line"> <tt class="py-name">lp_transition</tt><tt class="py-op">[</tt><tt id="link-123" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-123', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">[</tt><tt class="py-name">j</tt><tt class="py-op">]</tt> <tt class="py-op">+</tt> \ </tt>
<a name="L236"></a><tt class="py-lineno">236</tt> <tt class="py-line"> <tt class="py-name">lp_emission</tt><tt class="py-op">[</tt><tt id="link-124" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-124', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">[</tt><tt class="py-name">k</tt><tt class="py-op">]</tt> <tt class="py-op">+</tt> \ </tt>
<a name="L237"></a><tt class="py-lineno">237</tt> <tt class="py-line"> <tt class="py-name">bmat</tt><tt class="py-op">[</tt><tt class="py-name">j</tt><tt class="py-op">]</tt><tt class="py-op">[</tt><tt class="py-name">t</tt><tt class="py-op">+</tt><tt class="py-number">1</tt><tt class="py-op">]</tt> </tt>
<a name="L238"></a><tt class="py-lineno">238</tt> <tt class="py-line"> <tt class="py-name">lp_traverse</tt><tt class="py-op">[</tt><tt id="link-125" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-125', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">[</tt><tt class="py-name">j</tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt class="py-name">lp</tt> </tt>
<a name="L239"></a><tt class="py-lineno">239</tt> <tt class="py-line"> <tt class="py-comment"># Normalize the probability for this time step.</tt> </tt>
<a name="L240"></a><tt class="py-lineno">240</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">lp_arc</tt><tt class="py-op">[</tt><tt class="py-op">:</tt><tt class="py-op">,</tt><tt class="py-op">:</tt><tt class="py-op">,</tt><tt class="py-name">t</tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt class="py-name">lp_traverse</tt> <tt class="py-op">-</tt> <tt id="link-126" class="py-name" targets="Function Bio.MarkovModel._logsum()=Bio.MarkovModel-module.html#_logsum"><a title="Bio.MarkovModel._logsum" class="py-name" href="#" onclick="return doclink('link-126', '_logsum', 'link-126');">_logsum</a></tt><tt class="py-op">(</tt><tt class="py-name">lp_traverse</tt><tt class="py-op">)</tt> </tt>
<a name="L241"></a><tt class="py-lineno">241</tt> <tt class="py-line"> </tt>
<a name="L242"></a><tt class="py-lineno">242</tt> <tt class="py-line"> </tt>
<a name="L243"></a><tt class="py-lineno">243</tt> <tt class="py-line"> <tt class="py-comment"># Sum of all the transitions out of state i at time t.</tt> </tt>
<a name="L244"></a><tt class="py-lineno">244</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">lp_arcout_t</tt> <tt class="py-op">=</tt> <tt class="py-name">zeros</tt><tt class="py-op">(</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt> <tt class="py-name">T</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> <tt id="link-127" class="py-name"><a title="Bio.MarkovModel.MATCODE" class="py-name" href="#" onclick="return doclink('link-127', 'MATCODE', 'link-6');">MATCODE</a></tt><tt class="py-op">)</tt> </tt>
<a name="L245"></a><tt class="py-lineno">245</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt class="py-name">t</tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">T</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L246"></a><tt class="py-lineno">246</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt id="link-128" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-128', 'i', 'link-34');">i</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L247"></a><tt class="py-lineno">247</tt> <tt class="py-line"> <tt class="py-name">lp_arcout_t</tt><tt class="py-op">[</tt><tt id="link-129" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-129', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">[</tt><tt class="py-name">t</tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt id="link-130" class="py-name"><a title="Bio.MarkovModel._logsum" class="py-name" href="#" onclick="return doclink('link-130', '_logsum', 'link-126');">_logsum</a></tt><tt class="py-op">(</tt><tt class="py-name">lp_arc</tt><tt class="py-op">[</tt><tt id="link-131" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-131', 'i', 'link-34');">i</a></tt><tt class="py-op">,</tt><tt class="py-op">:</tt><tt class="py-op">,</tt><tt class="py-name">t</tt><tt class="py-op">]</tt><tt class="py-op">)</tt> </tt>
<a name="L248"></a><tt class="py-lineno">248</tt> <tt class="py-line"> </tt>
<a name="L249"></a><tt class="py-lineno">249</tt> <tt class="py-line"> <tt class="py-comment"># Sum of all the transitions out of state i.</tt> </tt>
<a name="L250"></a><tt class="py-lineno">250</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">lp_arcout</tt> <tt class="py-op">=</tt> <tt class="py-name">zeros</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt> <tt id="link-132" class="py-name"><a title="Bio.MarkovModel.MATCODE" class="py-name" href="#" onclick="return doclink('link-132', 'MATCODE', 'link-6');">MATCODE</a></tt><tt class="py-op">)</tt> </tt>
<a name="L251"></a><tt class="py-lineno">251</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt id="link-133" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-133', 'i', 'link-34');">i</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L252"></a><tt class="py-lineno">252</tt> <tt class="py-line"> <tt class="py-name">lp_arcout</tt><tt class="py-op">[</tt><tt id="link-134" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-134', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt id="link-135" class="py-name"><a title="Bio.MarkovModel._logsum" class="py-name" href="#" onclick="return doclink('link-135', '_logsum', 'link-126');">_logsum</a></tt><tt class="py-op">(</tt><tt class="py-name">lp_arcout_t</tt><tt class="py-op">[</tt><tt id="link-136" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-136', 'i', 'link-34');">i</a></tt><tt class="py-op">,</tt><tt class="py-op">:</tt><tt class="py-op">]</tt><tt class="py-op">)</tt> </tt>
<a name="L253"></a><tt class="py-lineno">253</tt> <tt class="py-line"> </tt>
<a name="L254"></a><tt class="py-lineno">254</tt> <tt class="py-line"> <tt class="py-comment"># UPDATE P_INITIAL.</tt> </tt>
<a name="L255"></a><tt class="py-lineno">255</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">lp_initial</tt><tt class="py-op">[</tt><tt class="py-op">:</tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt class="py-name">lp_arcout_t</tt><tt class="py-op">[</tt><tt class="py-op">:</tt><tt class="py-op">,</tt><tt class="py-number">0</tt><tt class="py-op">]</tt> </tt>
<a name="L256"></a><tt class="py-lineno">256</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-name">lpseudo_initial</tt><tt class="py-op">:</tt> </tt>
<a name="L257"></a><tt class="py-lineno">257</tt> <tt class="py-line"> <tt class="py-name">lp_initial</tt> <tt class="py-op">=</tt> <tt id="link-137" class="py-name" targets="Function Bio.MarkovModel._logvecadd()=Bio.MarkovModel-module.html#_logvecadd"><a title="Bio.MarkovModel._logvecadd" class="py-name" href="#" onclick="return doclink('link-137', '_logvecadd', 'link-137');">_logvecadd</a></tt><tt class="py-op">(</tt><tt class="py-name">lp_initial</tt><tt class="py-op">,</tt> <tt class="py-name">lpseudo_initial</tt><tt class="py-op">)</tt> </tt>
<a name="L258"></a><tt class="py-lineno">258</tt> <tt class="py-line"> <tt class="py-name">lp_initial</tt> <tt class="py-op">=</tt> <tt class="py-name">lp_initial</tt> <tt class="py-op">-</tt> <tt id="link-138" class="py-name"><a title="Bio.MarkovModel._logsum" class="py-name" href="#" onclick="return doclink('link-138', '_logsum', 'link-126');">_logsum</a></tt><tt class="py-op">(</tt><tt class="py-name">lp_initial</tt><tt class="py-op">)</tt> </tt>
<a name="L259"></a><tt class="py-lineno">259</tt> <tt class="py-line"> </tt>
<a name="L260"></a><tt class="py-lineno">260</tt> <tt class="py-line"> <tt class="py-comment"># UPDATE P_TRANSITION. p_transition[i][j] is the sum of all the</tt> </tt>
<a name="L261"></a><tt class="py-lineno">261</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># transitions from i to j, normalized by the sum of the</tt> </tt>
<a name="L262"></a><tt class="py-lineno">262</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># transitions out of i.</tt> </tt>
<a name="L263"></a><tt class="py-lineno">263</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-keyword">for</tt> <tt id="link-139" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-139', 'i', 'link-34');">i</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L264"></a><tt class="py-lineno">264</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt class="py-name">j</tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L265"></a><tt class="py-lineno">265</tt> <tt class="py-line"> <tt class="py-name">lp_transition</tt><tt class="py-op">[</tt><tt id="link-140" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-140', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">[</tt><tt class="py-name">j</tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt id="link-141" class="py-name"><a title="Bio.MarkovModel._logsum" class="py-name" href="#" onclick="return doclink('link-141', '_logsum', 'link-126');">_logsum</a></tt><tt class="py-op">(</tt><tt class="py-name">lp_arc</tt><tt class="py-op">[</tt><tt id="link-142" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-142', 'i', 'link-34');">i</a></tt><tt class="py-op">,</tt><tt class="py-name">j</tt><tt class="py-op">,</tt><tt class="py-op">:</tt><tt class="py-op">]</tt><tt class="py-op">)</tt> <tt class="py-op">-</tt> <tt class="py-name">lp_arcout</tt><tt class="py-op">[</tt><tt id="link-143" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-143', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt> </tt>
<a name="L266"></a><tt class="py-lineno">266</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-name">lpseudo_transition</tt><tt class="py-op">:</tt> </tt>
<a name="L267"></a><tt class="py-lineno">267</tt> <tt class="py-line"> <tt class="py-name">lp_transition</tt><tt class="py-op">[</tt><tt id="link-144" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-144', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt id="link-145" class="py-name"><a title="Bio.MarkovModel._logvecadd" class="py-name" href="#" onclick="return doclink('link-145', '_logvecadd', 'link-137');">_logvecadd</a></tt><tt class="py-op">(</tt><tt class="py-name">lp_transition</tt><tt class="py-op">[</tt><tt id="link-146" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-146', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">,</tt> <tt class="py-name">lpseudo_transition</tt><tt class="py-op">)</tt> </tt>
<a name="L268"></a><tt class="py-lineno">268</tt> <tt class="py-line"> <tt class="py-name">lp_transition</tt><tt class="py-op">[</tt><tt id="link-147" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-147', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt class="py-name">lp_transition</tt><tt class="py-op">[</tt><tt id="link-148" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-148', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt> <tt class="py-op">-</tt> <tt id="link-149" class="py-name"><a title="Bio.MarkovModel._logsum" class="py-name" href="#" onclick="return doclink('link-149', '_logsum', 'link-126');">_logsum</a></tt><tt class="py-op">(</tt><tt class="py-name">lp_transition</tt><tt class="py-op">[</tt><tt id="link-150" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-150', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">)</tt> </tt>
<a name="L269"></a><tt class="py-lineno">269</tt> <tt class="py-line"> </tt>
<a name="L270"></a><tt class="py-lineno">270</tt> <tt class="py-line"> <tt class="py-comment"># UPDATE P_EMISSION. lp_emission[i][k] is the sum of all the</tt> </tt>
<a name="L271"></a><tt class="py-lineno">271</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># transitions out of i when k is observed, divided by the sum of</tt> </tt>
<a name="L272"></a><tt class="py-lineno">272</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># the transitions out of i.</tt> </tt>
<a name="L273"></a><tt class="py-lineno">273</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-keyword">for</tt> <tt id="link-151" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-151', 'i', 'link-34');">i</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L274"></a><tt class="py-lineno">274</tt> <tt class="py-line"> <tt class="py-name">ksum</tt> <tt class="py-op">=</tt> <tt class="py-name">zeros</tt><tt class="py-op">(</tt><tt class="py-name">M</tt><tt class="py-op">,</tt> <tt id="link-152" class="py-name"><a title="Bio.MarkovModel.MATCODE" class="py-name" href="#" onclick="return doclink('link-152', 'MATCODE', 'link-6');">MATCODE</a></tt><tt class="py-op">)</tt><tt class="py-op">+</tt><tt id="link-153" class="py-name"><a title="Bio.MarkovModel.LOG0" class="py-name" href="#" onclick="return doclink('link-153', 'LOG0', 'link-3');">LOG0</a></tt> <tt class="py-comment"># ksum[k] is the sum of all i with k.</tt> </tt>
<a name="L275"></a><tt class="py-lineno">275</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt class="py-name">t</tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">T</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L276"></a><tt class="py-lineno">276</tt> <tt class="py-line"> <tt class="py-name">k</tt> <tt class="py-op">=</tt> <tt class="py-name">outputs</tt><tt class="py-op">[</tt><tt class="py-name">t</tt><tt class="py-op">]</tt> </tt>
<a name="L277"></a><tt class="py-lineno">277</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt class="py-name">j</tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L278"></a><tt class="py-lineno">278</tt> <tt class="py-line"> <tt class="py-name">ksum</tt><tt class="py-op">[</tt><tt class="py-name">k</tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt id="link-154" class="py-name" targets="Function Bio.MarkovModel._logadd()=Bio.MarkovModel-module.html#_logadd"><a title="Bio.MarkovModel._logadd" class="py-name" href="#" onclick="return doclink('link-154', '_logadd', 'link-154');">_logadd</a></tt><tt class="py-op">(</tt><tt class="py-name">ksum</tt><tt class="py-op">[</tt><tt class="py-name">k</tt><tt class="py-op">]</tt><tt class="py-op">,</tt> <tt class="py-name">lp_arc</tt><tt class="py-op">[</tt><tt id="link-155" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-155', 'i', 'link-34');">i</a></tt><tt class="py-op">,</tt><tt class="py-name">j</tt><tt class="py-op">,</tt><tt class="py-name">t</tt><tt class="py-op">]</tt><tt class="py-op">)</tt> </tt>
<a name="L279"></a><tt class="py-lineno">279</tt> <tt class="py-line"> <tt class="py-name">ksum</tt> <tt class="py-op">=</tt> <tt class="py-name">ksum</tt> <tt class="py-op">-</tt> <tt id="link-156" class="py-name"><a title="Bio.MarkovModel._logsum" class="py-name" href="#" onclick="return doclink('link-156', '_logsum', 'link-126');">_logsum</a></tt><tt class="py-op">(</tt><tt class="py-name">ksum</tt><tt class="py-op">)</tt> <tt class="py-comment"># Normalize</tt> </tt>
<a name="L280"></a><tt class="py-lineno">280</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-name">lpseudo_emission</tt><tt class="py-op">:</tt> </tt>
<a name="L281"></a><tt class="py-lineno">281</tt> <tt class="py-line"> <tt class="py-name">ksum</tt> <tt class="py-op">=</tt> <tt id="link-157" class="py-name"><a title="Bio.MarkovModel._logvecadd" class="py-name" href="#" onclick="return doclink('link-157', '_logvecadd', 'link-137');">_logvecadd</a></tt><tt class="py-op">(</tt><tt class="py-name">ksum</tt><tt class="py-op">,</tt> <tt class="py-name">lpseudo_emission</tt><tt class="py-op">[</tt><tt id="link-158" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-158', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">)</tt> </tt>
<a name="L282"></a><tt class="py-lineno">282</tt> <tt class="py-line"> <tt class="py-name">ksum</tt> <tt class="py-op">=</tt> <tt class="py-name">ksum</tt> <tt class="py-op">-</tt> <tt id="link-159" class="py-name"><a title="Bio.MarkovModel._logsum" class="py-name" href="#" onclick="return doclink('link-159', '_logsum', 'link-126');">_logsum</a></tt><tt class="py-op">(</tt><tt class="py-name">ksum</tt><tt class="py-op">)</tt> <tt class="py-comment"># Renormalize</tt> </tt>
<a name="L283"></a><tt class="py-lineno">283</tt> <tt class="py-line"> <tt class="py-name">lp_emission</tt><tt class="py-op">[</tt><tt id="link-160" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-160', 'i', 'link-34');">i</a></tt><tt class="py-op">,</tt><tt class="py-op">:</tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt class="py-name">ksum</tt> </tt>
<a name="L284"></a><tt class="py-lineno">284</tt> <tt class="py-line"> </tt>
<a name="L285"></a><tt class="py-lineno">285</tt> <tt class="py-line"> <tt class="py-comment"># Calculate the log likelihood of the output based on the forward</tt> </tt>
<a name="L286"></a><tt class="py-lineno">286</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># matrix. Since the parameters of the HMM has changed, the log</tt> </tt>
<a name="L287"></a><tt class="py-lineno">287</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># likelihoods are going to be a step behind, and we might be doing</tt> </tt>
<a name="L288"></a><tt class="py-lineno">288</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># one extra iteration of training. The alternative is to rerun</tt> </tt>
<a name="L289"></a><tt class="py-lineno">289</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># the _forward algorithm and calculate from the clean one, but</tt> </tt>
<a name="L290"></a><tt class="py-lineno">290</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># that may be more expensive than overshooting the training by one</tt> </tt>
<a name="L291"></a><tt class="py-lineno">291</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># step.</tt> </tt>
<a name="L292"></a><tt class="py-lineno">292</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-keyword">return</tt> <tt id="link-161" class="py-name"><a title="Bio.MarkovModel._logsum" class="py-name" href="#" onclick="return doclink('link-161', '_logsum', 'link-126');">_logsum</a></tt><tt class="py-op">(</tt><tt class="py-name">fmat</tt><tt class="py-op">[</tt><tt class="py-op">:</tt><tt class="py-op">,</tt><tt class="py-name">T</tt><tt class="py-op">]</tt><tt class="py-op">)</tt> </tt>
</div><a name="L293"></a><tt class="py-lineno">293</tt> <tt class="py-line"> </tt>
<a name="_forward"></a><div id="_forward-def"><a name="L294"></a><tt class="py-lineno">294</tt> <a class="py-toggle" href="#" id="_forward-toggle" onclick="return toggle('_forward');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#_forward">_forward</a><tt class="py-op">(</tt><tt class="py-param">N</tt><tt class="py-op">,</tt> <tt class="py-param">T</tt><tt class="py-op">,</tt> <tt class="py-param">lp_initial</tt><tt class="py-op">,</tt> <tt class="py-param">lp_transition</tt><tt class="py-op">,</tt> <tt class="py-param">lp_emission</tt><tt class="py-op">,</tt> <tt class="py-param">outputs</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="_forward-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="_forward-expanded"><a name="L295"></a><tt class="py-lineno">295</tt> <tt class="py-line"> <tt class="py-comment"># Implement the forward algorithm. This actually calculates a</tt> </tt>
<a name="L296"></a><tt class="py-lineno">296</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># Nx(T+1) matrix, where the last column is the total probability</tt> </tt>
<a name="L297"></a><tt class="py-lineno">297</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># of the output.</tt> </tt>
<a name="L298"></a><tt class="py-lineno">298</tt> <tt class="py-line"><tt class="py-comment"></tt> </tt>
<a name="L299"></a><tt class="py-lineno">299</tt> <tt class="py-line"> <tt id="link-162" class="py-name" targets="Method Bio.Blast.NCBIStandalone._ParametersConsumer.matrix()=Bio.Blast.NCBIStandalone._ParametersConsumer-class.html#matrix,Variable Bio.MetaTool.metatool_format.matrix=Bio.MetaTool.metatool_format-module.html#matrix,Method Bio.Prosite._RecordConsumer.matrix()=Bio.Prosite._RecordConsumer-class.html#matrix"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-162', 'matrix', 'link-162');">matrix</a></tt> <tt class="py-op">=</tt> <tt class="py-name">zeros</tt><tt class="py-op">(</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt> <tt class="py-name">T</tt><tt class="py-op">+</tt><tt class="py-number">1</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> <tt id="link-163" class="py-name"><a title="Bio.MarkovModel.MATCODE" class="py-name" href="#" onclick="return doclink('link-163', 'MATCODE', 'link-6');">MATCODE</a></tt><tt class="py-op">)</tt> </tt>
<a name="L300"></a><tt class="py-lineno">300</tt> <tt class="py-line"> </tt>
<a name="L301"></a><tt class="py-lineno">301</tt> <tt class="py-line"> <tt class="py-comment"># Initialize the first column to be the initial values.</tt> </tt>
<a name="L302"></a><tt class="py-lineno">302</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt id="link-164" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-164', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">[</tt><tt class="py-op">:</tt><tt class="py-op">,</tt><tt class="py-number">0</tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt class="py-name">lp_initial</tt> </tt>
<a name="L303"></a><tt class="py-lineno">303</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt class="py-name">t</tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-number">1</tt><tt class="py-op">,</tt> <tt class="py-name">T</tt><tt class="py-op">+</tt><tt class="py-number">1</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L304"></a><tt class="py-lineno">304</tt> <tt class="py-line"> <tt class="py-name">k</tt> <tt class="py-op">=</tt> <tt class="py-name">outputs</tt><tt class="py-op">[</tt><tt class="py-name">t</tt><tt class="py-op">-</tt><tt class="py-number">1</tt><tt class="py-op">]</tt> </tt>
<a name="L305"></a><tt class="py-lineno">305</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt class="py-name">j</tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L306"></a><tt class="py-lineno">306</tt> <tt class="py-line"> <tt class="py-comment"># The probability of the state is the sum of the</tt> </tt>
<a name="L307"></a><tt class="py-lineno">307</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># transitions from all the states from time t-1.</tt> </tt>
<a name="L308"></a><tt class="py-lineno">308</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">lprob</tt> <tt class="py-op">=</tt> <tt id="link-165" class="py-name"><a title="Bio.MarkovModel.LOG0" class="py-name" href="#" onclick="return doclink('link-165', 'LOG0', 'link-3');">LOG0</a></tt> </tt>
<a name="L309"></a><tt class="py-lineno">309</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt id="link-166" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-166', 'i', 'link-34');">i</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L310"></a><tt class="py-lineno">310</tt> <tt class="py-line"> <tt class="py-name">lp</tt> <tt class="py-op">=</tt> <tt id="link-167" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-167', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">[</tt><tt id="link-168" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-168', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">[</tt><tt class="py-name">t</tt><tt class="py-op">-</tt><tt class="py-number">1</tt><tt class="py-op">]</tt> <tt class="py-op">+</tt> \ </tt>
<a name="L311"></a><tt class="py-lineno">311</tt> <tt class="py-line"> <tt class="py-name">lp_transition</tt><tt class="py-op">[</tt><tt id="link-169" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-169', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">[</tt><tt class="py-name">j</tt><tt class="py-op">]</tt> <tt class="py-op">+</tt> \ </tt>
<a name="L312"></a><tt class="py-lineno">312</tt> <tt class="py-line"> <tt class="py-name">lp_emission</tt><tt class="py-op">[</tt><tt id="link-170" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-170', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">[</tt><tt class="py-name">k</tt><tt class="py-op">]</tt> </tt>
<a name="L313"></a><tt class="py-lineno">313</tt> <tt class="py-line"> <tt class="py-name">lprob</tt> <tt class="py-op">=</tt> <tt id="link-171" class="py-name"><a title="Bio.MarkovModel._logadd" class="py-name" href="#" onclick="return doclink('link-171', '_logadd', 'link-154');">_logadd</a></tt><tt class="py-op">(</tt><tt class="py-name">lprob</tt><tt class="py-op">,</tt> <tt class="py-name">lp</tt><tt class="py-op">)</tt> </tt>
<a name="L314"></a><tt class="py-lineno">314</tt> <tt class="py-line"> <tt id="link-172" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-172', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">[</tt><tt class="py-name">j</tt><tt class="py-op">]</tt><tt class="py-op">[</tt><tt class="py-name">t</tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt class="py-name">lprob</tt> </tt>
<a name="L315"></a><tt class="py-lineno">315</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt id="link-173" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-173', 'matrix', 'link-162');">matrix</a></tt> </tt>
</div><a name="L316"></a><tt class="py-lineno">316</tt> <tt class="py-line"> </tt>
<a name="_backward"></a><div id="_backward-def"><a name="L317"></a><tt class="py-lineno">317</tt> <a class="py-toggle" href="#" id="_backward-toggle" onclick="return toggle('_backward');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#_backward">_backward</a><tt class="py-op">(</tt><tt class="py-param">N</tt><tt class="py-op">,</tt> <tt class="py-param">T</tt><tt class="py-op">,</tt> <tt class="py-param">lp_transition</tt><tt class="py-op">,</tt> <tt class="py-param">lp_emission</tt><tt class="py-op">,</tt> <tt class="py-param">outputs</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="_backward-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="_backward-expanded"><a name="L318"></a><tt class="py-lineno">318</tt> <tt class="py-line"> <tt id="link-174" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-174', 'matrix', 'link-162');">matrix</a></tt> <tt class="py-op">=</tt> <tt class="py-name">zeros</tt><tt class="py-op">(</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt> <tt class="py-name">T</tt><tt class="py-op">+</tt><tt class="py-number">1</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> <tt id="link-175" class="py-name"><a title="Bio.MarkovModel.MATCODE" class="py-name" href="#" onclick="return doclink('link-175', 'MATCODE', 'link-6');">MATCODE</a></tt><tt class="py-op">)</tt> </tt>
<a name="L319"></a><tt class="py-lineno">319</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt class="py-name">t</tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">T</tt><tt class="py-op">-</tt><tt class="py-number">1</tt><tt class="py-op">,</tt> <tt class="py-op">-</tt><tt class="py-number">1</tt><tt class="py-op">,</tt> <tt class="py-op">-</tt><tt class="py-number">1</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L320"></a><tt class="py-lineno">320</tt> <tt class="py-line"> <tt class="py-name">k</tt> <tt class="py-op">=</tt> <tt class="py-name">outputs</tt><tt class="py-op">[</tt><tt class="py-name">t</tt><tt class="py-op">]</tt> </tt>
<a name="L321"></a><tt class="py-lineno">321</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt id="link-176" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-176', 'i', 'link-34');">i</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L322"></a><tt class="py-lineno">322</tt> <tt class="py-line"> <tt class="py-comment"># The probability of the state is the sum of the</tt> </tt>
<a name="L323"></a><tt class="py-lineno">323</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># transitions from all the states from time t+1.</tt> </tt>
<a name="L324"></a><tt class="py-lineno">324</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">lprob</tt> <tt class="py-op">=</tt> <tt id="link-177" class="py-name"><a title="Bio.MarkovModel.LOG0" class="py-name" href="#" onclick="return doclink('link-177', 'LOG0', 'link-3');">LOG0</a></tt> </tt>
<a name="L325"></a><tt class="py-lineno">325</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt class="py-name">j</tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L326"></a><tt class="py-lineno">326</tt> <tt class="py-line"> <tt class="py-name">lp</tt> <tt class="py-op">=</tt> <tt id="link-178" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-178', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">[</tt><tt class="py-name">j</tt><tt class="py-op">]</tt><tt class="py-op">[</tt><tt class="py-name">t</tt><tt class="py-op">+</tt><tt class="py-number">1</tt><tt class="py-op">]</tt> <tt class="py-op">+</tt> \ </tt>
<a name="L327"></a><tt class="py-lineno">327</tt> <tt class="py-line"> <tt class="py-name">lp_transition</tt><tt class="py-op">[</tt><tt id="link-179" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-179', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">[</tt><tt class="py-name">j</tt><tt class="py-op">]</tt> <tt class="py-op">+</tt> \ </tt>
<a name="L328"></a><tt class="py-lineno">328</tt> <tt class="py-line"> <tt class="py-name">lp_emission</tt><tt class="py-op">[</tt><tt id="link-180" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-180', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">[</tt><tt class="py-name">k</tt><tt class="py-op">]</tt> </tt>
<a name="L329"></a><tt class="py-lineno">329</tt> <tt class="py-line"> <tt class="py-name">lprob</tt> <tt class="py-op">=</tt> <tt id="link-181" class="py-name"><a title="Bio.MarkovModel._logadd" class="py-name" href="#" onclick="return doclink('link-181', '_logadd', 'link-154');">_logadd</a></tt><tt class="py-op">(</tt><tt class="py-name">lprob</tt><tt class="py-op">,</tt> <tt class="py-name">lp</tt><tt class="py-op">)</tt> </tt>
<a name="L330"></a><tt class="py-lineno">330</tt> <tt class="py-line"> <tt id="link-182" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-182', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">[</tt><tt id="link-183" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-183', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">[</tt><tt class="py-name">t</tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt class="py-name">lprob</tt> </tt>
<a name="L331"></a><tt class="py-lineno">331</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt id="link-184" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-184', 'matrix', 'link-162');">matrix</a></tt> </tt>
</div><a name="L332"></a><tt class="py-lineno">332</tt> <tt class="py-line"> </tt>
<a name="train_visible"></a><div id="train_visible-def"><a name="L333"></a><tt class="py-lineno">333</tt> <a class="py-toggle" href="#" id="train_visible-toggle" onclick="return toggle('train_visible');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#train_visible">train_visible</a><tt class="py-op">(</tt><tt class="py-param">states</tt><tt class="py-op">,</tt> <tt class="py-param">alphabet</tt><tt class="py-op">,</tt> <tt class="py-param">training_data</tt><tt class="py-op">,</tt> </tt>
<a name="L334"></a><tt class="py-lineno">334</tt> <tt class="py-line"> <tt class="py-param">pseudo_initial</tt><tt class="py-op">=</tt><tt class="py-name">None</tt><tt class="py-op">,</tt> <tt class="py-param">pseudo_transition</tt><tt class="py-op">=</tt><tt class="py-name">None</tt><tt class="py-op">,</tt> </tt>
<a name="L335"></a><tt class="py-lineno">335</tt> <tt class="py-line"> <tt class="py-param">pseudo_emission</tt><tt class="py-op">=</tt><tt class="py-name">None</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="train_visible-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="train_visible-expanded"><a name="L336"></a><tt class="py-lineno">336</tt> <tt class="py-line"> <tt class="py-docstring">"""train_visible(states, alphabet, training_data[, pseudo_initial]</tt> </tt>
<a name="L337"></a><tt class="py-lineno">337</tt> <tt class="py-line"><tt class="py-docstring"> [, pseudo_transition][, pseudo_emission]) -> MarkovModel</tt> </tt>
<a name="L338"></a><tt class="py-lineno">338</tt> <tt class="py-line"><tt class="py-docstring"></tt> </tt>
<a name="L339"></a><tt class="py-lineno">339</tt> <tt class="py-line"><tt class="py-docstring"> Train a visible MarkovModel using maximum likelihoood estimates</tt> </tt>
<a name="L340"></a><tt class="py-lineno">340</tt> <tt class="py-line"><tt class="py-docstring"> for each of the parameters. states is a list of strings that</tt> </tt>
<a name="L341"></a><tt class="py-lineno">341</tt> <tt class="py-line"><tt class="py-docstring"> describe the names of each state. alphabet is a list of objects</tt> </tt>
<a name="L342"></a><tt class="py-lineno">342</tt> <tt class="py-line"><tt class="py-docstring"> that indicate the allowed outputs. training_data is a list of</tt> </tt>
<a name="L343"></a><tt class="py-lineno">343</tt> <tt class="py-line"><tt class="py-docstring"> (outputs, observed states) where outputs is a list of the emission</tt> </tt>
<a name="L344"></a><tt class="py-lineno">344</tt> <tt class="py-line"><tt class="py-docstring"> from the alphabet, and observed states is a list of states from</tt> </tt>
<a name="L345"></a><tt class="py-lineno">345</tt> <tt class="py-line"><tt class="py-docstring"> states.</tt> </tt>
<a name="L346"></a><tt class="py-lineno">346</tt> <tt class="py-line"><tt class="py-docstring"></tt> </tt>
<a name="L347"></a><tt class="py-lineno">347</tt> <tt class="py-line"><tt class="py-docstring"> pseudo_initial, pseudo_transition, and pseudo_emission are</tt> </tt>
<a name="L348"></a><tt class="py-lineno">348</tt> <tt class="py-line"><tt class="py-docstring"> optional parameters that you can use to assign pseudo-counts to</tt> </tt>
<a name="L349"></a><tt class="py-lineno">349</tt> <tt class="py-line"><tt class="py-docstring"> different matrices. They should be matrices of the appropriate</tt> </tt>
<a name="L350"></a><tt class="py-lineno">350</tt> <tt class="py-line"><tt class="py-docstring"> size that contain numbers to add to each parameter matrix</tt> </tt>
<a name="L351"></a><tt class="py-lineno">351</tt> <tt class="py-line"><tt class="py-docstring"></tt> </tt>
<a name="L352"></a><tt class="py-lineno">352</tt> <tt class="py-line"><tt class="py-docstring"> """</tt> </tt>
<a name="L353"></a><tt class="py-lineno">353</tt> <tt class="py-line"> <tt class="py-name">N</tt><tt class="py-op">,</tt> <tt class="py-name">M</tt> <tt class="py-op">=</tt> <tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">states</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> <tt class="py-name">len</tt><tt class="py-op">(</tt><tt id="link-185" class="py-name"><a title="Bio.Prosite.Pattern.Prosite.alphabet
Bio.Std.alphabet" class="py-name" href="#" onclick="return doclink('link-185', 'alphabet', 'link-8');">alphabet</a></tt><tt class="py-op">)</tt> </tt>
<a name="L354"></a><tt class="py-lineno">354</tt> <tt class="py-line"> <tt class="py-name">pseudo_initial</tt><tt class="py-op">,</tt> <tt class="py-name">pseudo_emission</tt><tt class="py-op">,</tt> <tt class="py-name">pseudo_transition</tt> <tt class="py-op">=</tt> <tt id="link-186" class="py-name"><a title="Bio.GFF.FeatureAggregate.map" class="py-name" href="#" onclick="return doclink('link-186', 'map', 'link-48');">map</a></tt><tt class="py-op">(</tt> </tt>
<a name="L355"></a><tt class="py-lineno">355</tt> <tt class="py-line"> <tt id="link-187" class="py-name"><a title="Bio.MarkovModel._safe_asarray" class="py-name" href="#" onclick="return doclink('link-187', '_safe_asarray', 'link-80');">_safe_asarray</a></tt><tt class="py-op">,</tt> <tt class="py-op">(</tt><tt class="py-name">pseudo_initial</tt><tt class="py-op">,</tt> <tt class="py-name">pseudo_emission</tt><tt class="py-op">,</tt> <tt class="py-name">pseudo_transition</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
<a name="L356"></a><tt class="py-lineno">356</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-name">pseudo_initial</tt> <tt class="py-keyword">and</tt> <tt class="py-name">shape</tt><tt class="py-op">(</tt><tt class="py-name">pseudo_initial</tt><tt class="py-op">)</tt> <tt class="py-op">!=</tt> <tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L357"></a><tt class="py-lineno">357</tt> <tt class="py-line"> <tt class="py-keyword">raise</tt> <tt class="py-name">ValueError</tt><tt class="py-op">,</tt> <tt class="py-string">"pseudo_initial not shape len(states)"</tt> </tt>
<a name="L358"></a><tt class="py-lineno">358</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-name">pseudo_transition</tt> <tt class="py-keyword">and</tt> <tt class="py-name">shape</tt><tt class="py-op">(</tt><tt class="py-name">pseudo_transition</tt><tt class="py-op">)</tt> <tt class="py-op">!=</tt> <tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt><tt class="py-name">N</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L359"></a><tt class="py-lineno">359</tt> <tt class="py-line"> <tt class="py-keyword">raise</tt> <tt class="py-name">ValueError</tt><tt class="py-op">,</tt> <tt class="py-string">"pseudo_transition not shape "</tt> <tt class="py-op">+</tt> \ </tt>
<a name="L360"></a><tt class="py-lineno">360</tt> <tt class="py-line"> <tt class="py-string">"len(states) X len(states)"</tt> </tt>
<a name="L361"></a><tt class="py-lineno">361</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-name">pseudo_emission</tt> <tt class="py-keyword">and</tt> <tt class="py-name">shape</tt><tt class="py-op">(</tt><tt class="py-name">pseudo_emission</tt><tt class="py-op">)</tt> <tt class="py-op">!=</tt> <tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt><tt class="py-name">M</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L362"></a><tt class="py-lineno">362</tt> <tt class="py-line"> <tt class="py-keyword">raise</tt> <tt class="py-name">ValueError</tt><tt class="py-op">,</tt> <tt class="py-string">"pseudo_emission not shape "</tt> <tt class="py-op">+</tt> \ </tt>
<a name="L363"></a><tt class="py-lineno">363</tt> <tt class="py-line"> <tt class="py-string">"len(states) X len(alphabet)"</tt> </tt>
<a name="L364"></a><tt class="py-lineno">364</tt> <tt class="py-line"> </tt>
<a name="L365"></a><tt class="py-lineno">365</tt> <tt class="py-line"> <tt class="py-comment"># Training data is given as a list of members of the alphabet.</tt> </tt>
<a name="L366"></a><tt class="py-lineno">366</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># Replace those with indexes into the alphabet list for easier</tt> </tt>
<a name="L367"></a><tt class="py-lineno">367</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># computation.</tt> </tt>
<a name="L368"></a><tt class="py-lineno">368</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">training_states</tt><tt class="py-op">,</tt> <tt class="py-name">training_outputs</tt> <tt class="py-op">=</tt> <tt class="py-op">[</tt><tt class="py-op">]</tt><tt class="py-op">,</tt> <tt class="py-op">[</tt><tt class="py-op">]</tt> </tt>
<a name="L369"></a><tt class="py-lineno">369</tt> <tt class="py-line"> <tt class="py-name">states_indexes</tt> <tt class="py-op">=</tt> <tt id="link-188" class="py-name"><a title="Bio.listfns" class="py-name" href="#" onclick="return doclink('link-188', 'listfns', 'link-1');">listfns</a></tt><tt class="py-op">.</tt><tt id="link-189" class="py-name"><a title="Bio.listfns.itemindex" class="py-name" href="#" onclick="return doclink('link-189', 'itemindex', 'link-82');">itemindex</a></tt><tt class="py-op">(</tt><tt class="py-name">states</tt><tt class="py-op">)</tt> </tt>
<a name="L370"></a><tt class="py-lineno">370</tt> <tt class="py-line"> <tt class="py-name">outputs_indexes</tt> <tt class="py-op">=</tt> <tt id="link-190" class="py-name"><a title="Bio.listfns" class="py-name" href="#" onclick="return doclink('link-190', 'listfns', 'link-1');">listfns</a></tt><tt class="py-op">.</tt><tt id="link-191" class="py-name"><a title="Bio.listfns.itemindex" class="py-name" href="#" onclick="return doclink('link-191', 'itemindex', 'link-82');">itemindex</a></tt><tt class="py-op">(</tt><tt id="link-192" class="py-name"><a title="Bio.Prosite.Pattern.Prosite.alphabet
Bio.Std.alphabet" class="py-name" href="#" onclick="return doclink('link-192', 'alphabet', 'link-8');">alphabet</a></tt><tt class="py-op">)</tt> </tt>
<a name="L371"></a><tt class="py-lineno">371</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt class="py-name">toutputs</tt><tt class="py-op">,</tt> <tt class="py-name">tstates</tt> <tt class="py-keyword">in</tt> <tt class="py-name">training_data</tt><tt class="py-op">:</tt> </tt>
<a name="L372"></a><tt class="py-lineno">372</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">tstates</tt><tt class="py-op">)</tt> <tt class="py-op">!=</tt> <tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">toutputs</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L373"></a><tt class="py-lineno">373</tt> <tt class="py-line"> <tt class="py-keyword">raise</tt> <tt class="py-name">ValueError</tt><tt class="py-op">,</tt> <tt class="py-string">"states and outputs not aligned"</tt> </tt>
<a name="L374"></a><tt class="py-lineno">374</tt> <tt class="py-line"> <tt class="py-name">training_states</tt><tt class="py-op">.</tt><tt id="link-193" class="py-name"><a title="Bio.Crystal.Chain.append
Bio.EUtils.POM.ElementNode.append
Bio.EUtils.sourcegen.SourceFile.append
Bio.SCOP.Raf.SeqMap.append
Bio.Seq.MutableSeq.append
Bio.Wise.psw.Alignment.append
Bio.Wise.psw.AlignmentColumn.append
Martel.msre_parse.SubPattern.append" class="py-name" href="#" onclick="return doclink('link-193', 'append', 'link-84');">append</a></tt><tt class="py-op">(</tt><tt class="py-op">[</tt><tt class="py-name">states_indexes</tt><tt class="py-op">[</tt><tt id="link-194" class="py-name"><a title="Bio.MarkovModel.x
Bio.Statistics.lowess.x" class="py-name" href="#" onclick="return doclink('link-194', 'x', 'link-67');">x</a></tt><tt class="py-op">]</tt> <tt class="py-keyword">for</tt> <tt id="link-195" class="py-name"><a title="Bio.MarkovModel.x
Bio.Statistics.lowess.x" class="py-name" href="#" onclick="return doclink('link-195', 'x', 'link-67');">x</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">tstates</tt><tt class="py-op">]</tt><tt class="py-op">)</tt> </tt>
<a name="L375"></a><tt class="py-lineno">375</tt> <tt class="py-line"> <tt class="py-name">training_outputs</tt><tt class="py-op">.</tt><tt id="link-196" class="py-name"><a title="Bio.Crystal.Chain.append
Bio.EUtils.POM.ElementNode.append
Bio.EUtils.sourcegen.SourceFile.append
Bio.SCOP.Raf.SeqMap.append
Bio.Seq.MutableSeq.append
Bio.Wise.psw.Alignment.append
Bio.Wise.psw.AlignmentColumn.append
Martel.msre_parse.SubPattern.append" class="py-name" href="#" onclick="return doclink('link-196', 'append', 'link-84');">append</a></tt><tt class="py-op">(</tt><tt class="py-op">[</tt><tt class="py-name">outputs_indexes</tt><tt class="py-op">[</tt><tt id="link-197" class="py-name"><a title="Bio.MarkovModel.x
Bio.Statistics.lowess.x" class="py-name" href="#" onclick="return doclink('link-197', 'x', 'link-67');">x</a></tt><tt class="py-op">]</tt> <tt class="py-keyword">for</tt> <tt id="link-198" class="py-name"><a title="Bio.MarkovModel.x
Bio.Statistics.lowess.x" class="py-name" href="#" onclick="return doclink('link-198', 'x', 'link-67');">x</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">toutputs</tt><tt class="py-op">]</tt><tt class="py-op">)</tt> </tt>
<a name="L376"></a><tt class="py-lineno">376</tt> <tt class="py-line"> </tt>
<a name="L377"></a><tt class="py-lineno">377</tt> <tt class="py-line"> <tt id="link-199" class="py-name"><a title="Bio.MarkovModel.x
Bio.Statistics.lowess.x" class="py-name" href="#" onclick="return doclink('link-199', 'x', 'link-67');">x</a></tt> <tt class="py-op">=</tt> <tt id="link-200" class="py-name" targets="Function Bio.MarkovModel._mle()=Bio.MarkovModel-module.html#_mle"><a title="Bio.MarkovModel._mle" class="py-name" href="#" onclick="return doclink('link-200', '_mle', 'link-200');">_mle</a></tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt> <tt class="py-name">M</tt><tt class="py-op">,</tt> <tt class="py-name">training_outputs</tt><tt class="py-op">,</tt> <tt class="py-name">training_states</tt><tt class="py-op">,</tt> </tt>
<a name="L378"></a><tt class="py-lineno">378</tt> <tt class="py-line"> <tt class="py-name">pseudo_initial</tt><tt class="py-op">,</tt> <tt class="py-name">pseudo_transition</tt><tt class="py-op">,</tt> <tt class="py-name">pseudo_emission</tt><tt class="py-op">)</tt> </tt>
<a name="L379"></a><tt class="py-lineno">379</tt> <tt class="py-line"> <tt class="py-name">p_initial</tt><tt class="py-op">,</tt> <tt class="py-name">p_transition</tt><tt class="py-op">,</tt> <tt class="py-name">p_emission</tt> <tt class="py-op">=</tt> <tt id="link-201" class="py-name"><a title="Bio.MarkovModel.x
Bio.Statistics.lowess.x" class="py-name" href="#" onclick="return doclink('link-201', 'x', 'link-67');">x</a></tt> </tt>
<a name="L380"></a><tt class="py-lineno">380</tt> <tt class="py-line"> </tt>
<a name="L381"></a><tt class="py-lineno">381</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt id="link-202" class="py-name"><a title="Bio.HMM.MarkovModel
Bio.MarkovModel
Bio.MarkovModel.MarkovModel" class="py-name" href="#" onclick="return doclink('link-202', 'MarkovModel', 'link-28');">MarkovModel</a></tt><tt class="py-op">(</tt><tt class="py-name">states</tt><tt class="py-op">,</tt> <tt id="link-203" class="py-name"><a title="Bio.Prosite.Pattern.Prosite.alphabet
Bio.Std.alphabet" class="py-name" href="#" onclick="return doclink('link-203', 'alphabet', 'link-8');">alphabet</a></tt><tt class="py-op">,</tt> <tt class="py-name">p_initial</tt><tt class="py-op">,</tt> <tt class="py-name">p_transition</tt><tt class="py-op">,</tt> <tt class="py-name">p_emission</tt><tt class="py-op">)</tt> </tt>
</div><a name="L382"></a><tt class="py-lineno">382</tt> <tt class="py-line"> </tt>
<a name="_mle"></a><div id="_mle-def"><a name="L383"></a><tt class="py-lineno">383</tt> <a class="py-toggle" href="#" id="_mle-toggle" onclick="return toggle('_mle');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#_mle">_mle</a><tt class="py-op">(</tt><tt class="py-param">N</tt><tt class="py-op">,</tt> <tt class="py-param">M</tt><tt class="py-op">,</tt> <tt class="py-param">training_outputs</tt><tt class="py-op">,</tt> <tt class="py-param">training_states</tt><tt class="py-op">,</tt> <tt class="py-param">pseudo_initial</tt><tt class="py-op">,</tt> </tt>
<a name="L384"></a><tt class="py-lineno">384</tt> <tt class="py-line"> <tt class="py-param">pseudo_transition</tt><tt class="py-op">,</tt> <tt class="py-param">pseudo_emission</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="_mle-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="_mle-expanded"><a name="L385"></a><tt class="py-lineno">385</tt> <tt class="py-line"> <tt class="py-comment"># p_initial is the probability that a sequence of states starts</tt> </tt>
<a name="L386"></a><tt class="py-lineno">386</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># off with a particular one.</tt> </tt>
<a name="L387"></a><tt class="py-lineno">387</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">p_initial</tt> <tt class="py-op">=</tt> <tt class="py-name">zeros</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt> <tt id="link-204" class="py-name"><a title="Bio.MarkovModel.MATCODE" class="py-name" href="#" onclick="return doclink('link-204', 'MATCODE', 'link-6');">MATCODE</a></tt><tt class="py-op">)</tt> </tt>
<a name="L388"></a><tt class="py-lineno">388</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-name">pseudo_initial</tt><tt class="py-op">:</tt> </tt>
<a name="L389"></a><tt class="py-lineno">389</tt> <tt class="py-line"> <tt class="py-name">p_initial</tt> <tt class="py-op">=</tt> <tt class="py-name">p_initial</tt> <tt class="py-op">+</tt> <tt class="py-name">pseudo_initial</tt> </tt>
<a name="L390"></a><tt class="py-lineno">390</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt class="py-name">states</tt> <tt class="py-keyword">in</tt> <tt class="py-name">training_states</tt><tt class="py-op">:</tt> </tt>
<a name="L391"></a><tt class="py-lineno">391</tt> <tt class="py-line"> <tt class="py-name">p_initial</tt><tt class="py-op">[</tt><tt class="py-name">states</tt><tt class="py-op">[</tt><tt class="py-number">0</tt><tt class="py-op">]</tt><tt class="py-op">]</tt> <tt class="py-op">+=</tt> <tt class="py-number">1</tt> </tt>
<a name="L392"></a><tt class="py-lineno">392</tt> <tt class="py-line"> <tt class="py-name">p_initial</tt> <tt class="py-op">=</tt> <tt id="link-205" class="py-name" targets="Function Bio.MarkovModel._normalize()=Bio.MarkovModel-module.html#_normalize"><a title="Bio.MarkovModel._normalize" class="py-name" href="#" onclick="return doclink('link-205', '_normalize', 'link-205');">_normalize</a></tt><tt class="py-op">(</tt><tt class="py-name">p_initial</tt><tt class="py-op">)</tt> </tt>
<a name="L393"></a><tt class="py-lineno">393</tt> <tt class="py-line"> </tt>
<a name="L394"></a><tt class="py-lineno">394</tt> <tt class="py-line"> <tt class="py-comment"># p_transition is the probability that a state leads to the next</tt> </tt>
<a name="L395"></a><tt class="py-lineno">395</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># one. C(i,j)/C(i) where i and j are states.</tt> </tt>
<a name="L396"></a><tt class="py-lineno">396</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">p_transition</tt> <tt class="py-op">=</tt> <tt class="py-name">zeros</tt><tt class="py-op">(</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt><tt class="py-name">N</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> <tt id="link-206" class="py-name"><a title="Bio.MarkovModel.MATCODE" class="py-name" href="#" onclick="return doclink('link-206', 'MATCODE', 'link-6');">MATCODE</a></tt><tt class="py-op">)</tt> </tt>
<a name="L397"></a><tt class="py-lineno">397</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-name">pseudo_transition</tt><tt class="py-op">:</tt> </tt>
<a name="L398"></a><tt class="py-lineno">398</tt> <tt class="py-line"> <tt class="py-name">p_transition</tt> <tt class="py-op">=</tt> <tt class="py-name">p_transition</tt> <tt class="py-op">+</tt> <tt class="py-name">pseudo_transition</tt> </tt>
<a name="L399"></a><tt class="py-lineno">399</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt class="py-name">states</tt> <tt class="py-keyword">in</tt> <tt class="py-name">training_states</tt><tt class="py-op">:</tt> </tt>
<a name="L400"></a><tt class="py-lineno">400</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt class="py-name">n</tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">states</tt><tt class="py-op">)</tt><tt class="py-op">-</tt><tt class="py-number">1</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L401"></a><tt class="py-lineno">401</tt> <tt class="py-line"> <tt id="link-207" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-207', 'i', 'link-34');">i</a></tt><tt class="py-op">,</tt> <tt class="py-name">j</tt> <tt class="py-op">=</tt> <tt class="py-name">states</tt><tt class="py-op">[</tt><tt class="py-name">n</tt><tt class="py-op">]</tt><tt class="py-op">,</tt> <tt class="py-name">states</tt><tt class="py-op">[</tt><tt class="py-name">n</tt><tt class="py-op">+</tt><tt class="py-number">1</tt><tt class="py-op">]</tt> </tt>
<a name="L402"></a><tt class="py-lineno">402</tt> <tt class="py-line"> <tt class="py-name">p_transition</tt><tt class="py-op">[</tt><tt id="link-208" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-208', 'i', 'link-34');">i</a></tt><tt class="py-op">,</tt> <tt class="py-name">j</tt><tt class="py-op">]</tt> <tt class="py-op">+=</tt> <tt class="py-number">1</tt> </tt>
<a name="L403"></a><tt class="py-lineno">403</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt id="link-209" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-209', 'i', 'link-34');">i</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">p_transition</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L404"></a><tt class="py-lineno">404</tt> <tt class="py-line"> <tt class="py-name">p_transition</tt><tt class="py-op">[</tt><tt id="link-210" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-210', 'i', 'link-34');">i</a></tt><tt class="py-op">,</tt><tt class="py-op">:</tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt class="py-name">p_transition</tt><tt class="py-op">[</tt><tt id="link-211" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-211', 'i', 'link-34');">i</a></tt><tt class="py-op">,</tt><tt class="py-op">:</tt><tt class="py-op">]</tt> <tt class="py-op">/</tt> <tt id="link-212" class="py-name" targets="Method Bio.Nexus.Nexus.StepMatrix.sum()=Bio.Nexus.Nexus.StepMatrix-class.html#sum,Function Bio.utils.sum()=Bio.utils-module.html#sum"><a title="Bio.Nexus.Nexus.StepMatrix.sum
Bio.utils.sum" class="py-name" href="#" onclick="return doclink('link-212', 'sum', 'link-212');">sum</a></tt><tt class="py-op">(</tt><tt class="py-name">p_transition</tt><tt class="py-op">[</tt><tt id="link-213" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-213', 'i', 'link-34');">i</a></tt><tt class="py-op">,</tt><tt class="py-op">:</tt><tt class="py-op">]</tt><tt class="py-op">)</tt> </tt>
<a name="L405"></a><tt class="py-lineno">405</tt> <tt class="py-line"> </tt>
<a name="L406"></a><tt class="py-lineno">406</tt> <tt class="py-line"> <tt class="py-comment"># p_emission is the probability of an output given a state.</tt> </tt>
<a name="L407"></a><tt class="py-lineno">407</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># C(s,o)|C(s) where o is an output and s is a state.</tt> </tt>
<a name="L408"></a><tt class="py-lineno">408</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">p_emission</tt> <tt class="py-op">=</tt> <tt class="py-name">zeros</tt><tt class="py-op">(</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt><tt class="py-name">M</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> <tt id="link-214" class="py-name"><a title="Bio.MarkovModel.MATCODE" class="py-name" href="#" onclick="return doclink('link-214', 'MATCODE', 'link-6');">MATCODE</a></tt><tt class="py-op">)</tt> </tt>
<a name="L409"></a><tt class="py-lineno">409</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-name">pseudo_emission</tt><tt class="py-op">:</tt> </tt>
<a name="L410"></a><tt class="py-lineno">410</tt> <tt class="py-line"> <tt class="py-name">p_emission</tt> <tt class="py-op">=</tt> <tt class="py-name">p_emission</tt> <tt class="py-op">+</tt> <tt class="py-name">pseudo_emission</tt> </tt>
<a name="L411"></a><tt class="py-lineno">411</tt> <tt class="py-line"> <tt class="py-name">p_emission</tt> <tt class="py-op">=</tt> <tt class="py-name">ones</tt><tt class="py-op">(</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt><tt class="py-name">M</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> <tt id="link-215" class="py-name"><a title="Bio.MarkovModel.MATCODE" class="py-name" href="#" onclick="return doclink('link-215', 'MATCODE', 'link-6');">MATCODE</a></tt><tt class="py-op">)</tt> </tt>
<a name="L412"></a><tt class="py-lineno">412</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt class="py-name">outputs</tt><tt class="py-op">,</tt> <tt class="py-name">states</tt> <tt class="py-keyword">in</tt> <tt class="py-name">zip</tt><tt class="py-op">(</tt><tt class="py-name">training_outputs</tt><tt class="py-op">,</tt> <tt class="py-name">training_states</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L413"></a><tt class="py-lineno">413</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt class="py-name">o</tt><tt class="py-op">,</tt> <tt id="link-216" class="py-name" targets="Variable Martel.test.test_swissprot38.s=Martel.test.test_swissprot38-module.html#s"><a title="Martel.test.test_swissprot38.s" class="py-name" href="#" onclick="return doclink('link-216', 's', 'link-216');">s</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">zip</tt><tt class="py-op">(</tt><tt class="py-name">outputs</tt><tt class="py-op">,</tt> <tt class="py-name">states</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L414"></a><tt class="py-lineno">414</tt> <tt class="py-line"> <tt class="py-name">p_emission</tt><tt class="py-op">[</tt><tt id="link-217" class="py-name"><a title="Martel.test.test_swissprot38.s" class="py-name" href="#" onclick="return doclink('link-217', 's', 'link-216');">s</a></tt><tt class="py-op">,</tt> <tt class="py-name">o</tt><tt class="py-op">]</tt> <tt class="py-op">+=</tt> <tt class="py-number">1</tt> </tt>
<a name="L415"></a><tt class="py-lineno">415</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt id="link-218" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-218', 'i', 'link-34');">i</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">p_emission</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L416"></a><tt class="py-lineno">416</tt> <tt class="py-line"> <tt class="py-name">p_emission</tt><tt class="py-op">[</tt><tt id="link-219" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-219', 'i', 'link-34');">i</a></tt><tt class="py-op">,</tt><tt class="py-op">:</tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt class="py-name">p_emission</tt><tt class="py-op">[</tt><tt id="link-220" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-220', 'i', 'link-34');">i</a></tt><tt class="py-op">,</tt><tt class="py-op">:</tt><tt class="py-op">]</tt> <tt class="py-op">/</tt> <tt id="link-221" class="py-name"><a title="Bio.Nexus.Nexus.StepMatrix.sum
Bio.utils.sum" class="py-name" href="#" onclick="return doclink('link-221', 'sum', 'link-212');">sum</a></tt><tt class="py-op">(</tt><tt class="py-name">p_emission</tt><tt class="py-op">[</tt><tt id="link-222" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-222', 'i', 'link-34');">i</a></tt><tt class="py-op">,</tt><tt class="py-op">:</tt><tt class="py-op">]</tt><tt class="py-op">)</tt> </tt>
<a name="L417"></a><tt class="py-lineno">417</tt> <tt class="py-line"> </tt>
<a name="L418"></a><tt class="py-lineno">418</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt class="py-name">p_initial</tt><tt class="py-op">,</tt> <tt class="py-name">p_transition</tt><tt class="py-op">,</tt> <tt class="py-name">p_emission</tt> </tt>
</div><a name="L419"></a><tt class="py-lineno">419</tt> <tt class="py-line"> </tt>
<a name="_argmaxes"></a><div id="_argmaxes-def"><a name="L420"></a><tt class="py-lineno">420</tt> <a class="py-toggle" href="#" id="_argmaxes-toggle" onclick="return toggle('_argmaxes');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#_argmaxes">_argmaxes</a><tt class="py-op">(</tt><tt class="py-param">vector</tt><tt class="py-op">,</tt> <tt class="py-param">allowance</tt><tt class="py-op">=</tt><tt class="py-name">None</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="_argmaxes-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="_argmaxes-expanded"><a name="L421"></a><tt class="py-lineno">421</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt class="py-op">[</tt><tt class="py-name">argmax</tt><tt class="py-op">(</tt><tt class="py-name">vector</tt><tt class="py-op">)</tt><tt class="py-op">]</tt> </tt>
</div><a name="L422"></a><tt class="py-lineno">422</tt> <tt class="py-line"> </tt>
<a name="find_states"></a><div id="find_states-def"><a name="L423"></a><tt class="py-lineno">423</tt> <a class="py-toggle" href="#" id="find_states-toggle" onclick="return toggle('find_states');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#find_states">find_states</a><tt class="py-op">(</tt><tt class="py-param">markov_model</tt><tt class="py-op">,</tt> <tt class="py-param">output</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="find_states-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="find_states-expanded"><a name="L424"></a><tt class="py-lineno">424</tt> <tt class="py-line"> <tt class="py-docstring">"""find_states(markov_model, output) -> list of (states, score)"""</tt> </tt>
<a name="L425"></a><tt class="py-lineno">425</tt> <tt class="py-line"> <tt class="py-name">mm</tt> <tt class="py-op">=</tt> <tt class="py-name">markov_model</tt> </tt>
<a name="L426"></a><tt class="py-lineno">426</tt> <tt class="py-line"> <tt class="py-name">N</tt> <tt class="py-op">=</tt> <tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">mm</tt><tt class="py-op">.</tt><tt class="py-name">states</tt><tt class="py-op">)</tt> </tt>
<a name="L427"></a><tt class="py-lineno">427</tt> <tt class="py-line"> </tt>
<a name="L428"></a><tt class="py-lineno">428</tt> <tt class="py-line"> <tt class="py-comment"># _viterbi does calculations in log space. Add a tiny bit to the</tt> </tt>
<a name="L429"></a><tt class="py-lineno">429</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># matrices so that the logs will not break.</tt> </tt>
<a name="L430"></a><tt class="py-lineno">430</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt id="link-223" class="py-name"><a title="Bio.MarkovModel.x
Bio.Statistics.lowess.x" class="py-name" href="#" onclick="return doclink('link-223', 'x', 'link-67');">x</a></tt> <tt class="py-op">=</tt> <tt class="py-name">mm</tt><tt class="py-op">.</tt><tt class="py-name">p_initial</tt> <tt class="py-op">+</tt> <tt id="link-224" class="py-name"><a title="Bio.MarkovModel.VERY_SMALL_NUMBER" class="py-name" href="#" onclick="return doclink('link-224', 'VERY_SMALL_NUMBER', 'link-2');">VERY_SMALL_NUMBER</a></tt> </tt>
<a name="L431"></a><tt class="py-lineno">431</tt> <tt class="py-line"> <tt class="py-name">y</tt> <tt class="py-op">=</tt> <tt class="py-name">mm</tt><tt class="py-op">.</tt><tt class="py-name">p_transition</tt> <tt class="py-op">+</tt> <tt id="link-225" class="py-name"><a title="Bio.MarkovModel.VERY_SMALL_NUMBER" class="py-name" href="#" onclick="return doclink('link-225', 'VERY_SMALL_NUMBER', 'link-2');">VERY_SMALL_NUMBER</a></tt> </tt>
<a name="L432"></a><tt class="py-lineno">432</tt> <tt class="py-line"> <tt class="py-name">z</tt> <tt class="py-op">=</tt> <tt class="py-name">mm</tt><tt class="py-op">.</tt><tt class="py-name">p_emission</tt> <tt class="py-op">+</tt> <tt id="link-226" class="py-name"><a title="Bio.MarkovModel.VERY_SMALL_NUMBER" class="py-name" href="#" onclick="return doclink('link-226', 'VERY_SMALL_NUMBER', 'link-2');">VERY_SMALL_NUMBER</a></tt> </tt>
<a name="L433"></a><tt class="py-lineno">433</tt> <tt class="py-line"> <tt class="py-name">lp_initial</tt><tt class="py-op">,</tt> <tt class="py-name">lp_transition</tt><tt class="py-op">,</tt> <tt class="py-name">lp_emission</tt> <tt class="py-op">=</tt> <tt id="link-227" class="py-name"><a title="Bio.GFF.FeatureAggregate.map" class="py-name" href="#" onclick="return doclink('link-227', 'map', 'link-48');">map</a></tt><tt class="py-op">(</tt><tt id="link-228" class="py-name"><a title="Bio.Affy.CelFile.log
Bio.LogisticRegression.log
Bio.MarkovModel.log
Bio.MaxEntropy.log
Bio.NaiveBayes.log
Bio.Statistics.lowess.log
Bio.distance.log
Bio.kNN.log" class="py-name" href="#" onclick="return doclink('link-228', 'log', 'link-4');">log</a></tt><tt class="py-op">,</tt> <tt class="py-op">(</tt><tt id="link-229" class="py-name"><a title="Bio.MarkovModel.x
Bio.Statistics.lowess.x" class="py-name" href="#" onclick="return doclink('link-229', 'x', 'link-67');">x</a></tt><tt class="py-op">,</tt> <tt class="py-name">y</tt><tt class="py-op">,</tt> <tt class="py-name">z</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
<a name="L434"></a><tt class="py-lineno">434</tt> <tt class="py-line"> <tt class="py-comment"># Change output into a list of indexes into the alphabet.</tt> </tt>
<a name="L435"></a><tt class="py-lineno">435</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">indexes</tt> <tt class="py-op">=</tt> <tt id="link-230" class="py-name"><a title="Bio.listfns" class="py-name" href="#" onclick="return doclink('link-230', 'listfns', 'link-1');">listfns</a></tt><tt class="py-op">.</tt><tt id="link-231" class="py-name"><a title="Bio.listfns.itemindex" class="py-name" href="#" onclick="return doclink('link-231', 'itemindex', 'link-82');">itemindex</a></tt><tt class="py-op">(</tt><tt class="py-name">mm</tt><tt class="py-op">.</tt><tt id="link-232" class="py-name"><a title="Bio.Prosite.Pattern.Prosite.alphabet
Bio.Std.alphabet" class="py-name" href="#" onclick="return doclink('link-232', 'alphabet', 'link-8');">alphabet</a></tt><tt class="py-op">)</tt> </tt>
<a name="L436"></a><tt class="py-lineno">436</tt> <tt class="py-line"> <tt class="py-name">output</tt> <tt class="py-op">=</tt> <tt class="py-op">[</tt><tt class="py-name">indexes</tt><tt class="py-op">[</tt><tt id="link-233" class="py-name"><a title="Bio.MarkovModel.x
Bio.Statistics.lowess.x" class="py-name" href="#" onclick="return doclink('link-233', 'x', 'link-67');">x</a></tt><tt class="py-op">]</tt> <tt class="py-keyword">for</tt> <tt id="link-234" class="py-name"><a title="Bio.MarkovModel.x
Bio.Statistics.lowess.x" class="py-name" href="#" onclick="return doclink('link-234', 'x', 'link-67');">x</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">output</tt><tt class="py-op">]</tt> </tt>
<a name="L437"></a><tt class="py-lineno">437</tt> <tt class="py-line"> </tt>
<a name="L438"></a><tt class="py-lineno">438</tt> <tt class="py-line"> <tt class="py-comment"># Run the viterbi algorithm.</tt> </tt>
<a name="L439"></a><tt class="py-lineno">439</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">results</tt> <tt class="py-op">=</tt> <tt id="link-235" class="py-name" targets="Function Bio.MarkovModel._viterbi()=Bio.MarkovModel-module.html#_viterbi"><a title="Bio.MarkovModel._viterbi" class="py-name" href="#" onclick="return doclink('link-235', '_viterbi', 'link-235');">_viterbi</a></tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt> <tt class="py-name">lp_initial</tt><tt class="py-op">,</tt> <tt class="py-name">lp_transition</tt><tt class="py-op">,</tt> <tt class="py-name">lp_emission</tt><tt class="py-op">,</tt> <tt class="py-name">output</tt><tt class="py-op">)</tt> </tt>
<a name="L440"></a><tt class="py-lineno">440</tt> <tt class="py-line"> </tt>
<a name="L441"></a><tt class="py-lineno">441</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt id="link-236" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-236', 'i', 'link-34');">i</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">results</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L442"></a><tt class="py-lineno">442</tt> <tt class="py-line"> <tt class="py-name">states</tt><tt class="py-op">,</tt> <tt id="link-237" class="py-name" targets="Method Bio.Blast.NCBIStandalone._HSPConsumer.score()=Bio.Blast.NCBIStandalone._HSPConsumer-class.html#score,Variable Bio.expressions.blast.ncbiblast.score=Bio.expressions.blast.ncbiblast-module.html#score"><a title="Bio.Blast.NCBIStandalone._HSPConsumer.score
Bio.expressions.blast.ncbiblast.score" class="py-name" href="#" onclick="return doclink('link-237', 'score', 'link-237');">score</a></tt> <tt class="py-op">=</tt> <tt class="py-name">results</tt><tt class="py-op">[</tt><tt id="link-238" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-238', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt> </tt>
<a name="L443"></a><tt class="py-lineno">443</tt> <tt class="py-line"> <tt class="py-name">results</tt><tt class="py-op">[</tt><tt id="link-239" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-239', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt class="py-op">[</tt><tt class="py-name">mm</tt><tt class="py-op">.</tt><tt class="py-name">states</tt><tt class="py-op">[</tt><tt id="link-240" class="py-name"><a title="Bio.MarkovModel.x
Bio.Statistics.lowess.x" class="py-name" href="#" onclick="return doclink('link-240', 'x', 'link-67');">x</a></tt><tt class="py-op">]</tt> <tt class="py-keyword">for</tt> <tt id="link-241" class="py-name"><a title="Bio.MarkovModel.x
Bio.Statistics.lowess.x" class="py-name" href="#" onclick="return doclink('link-241', 'x', 'link-67');">x</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">states</tt><tt class="py-op">]</tt><tt class="py-op">,</tt> <tt id="link-242" class="py-name"><a title="Bio.Affy.CelFile.exp
Bio.LogisticRegression.exp
Bio.MarkovModel.exp
Bio.MaxEntropy.exp
Bio.NaiveBayes.exp
Bio.Statistics.lowess.exp
Bio.distance.exp
Bio.kNN.exp" class="py-name" href="#" onclick="return doclink('link-242', 'exp', 'link-116');">exp</a></tt><tt class="py-op">(</tt><tt id="link-243" class="py-name"><a title="Bio.Blast.NCBIStandalone._HSPConsumer.score
Bio.expressions.blast.ncbiblast.score" class="py-name" href="#" onclick="return doclink('link-243', 'score', 'link-237');">score</a></tt><tt class="py-op">)</tt> </tt>
<a name="L444"></a><tt class="py-lineno">444</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt class="py-name">results</tt> </tt>
</div><a name="L445"></a><tt class="py-lineno">445</tt> <tt class="py-line"> </tt>
<a name="_viterbi"></a><div id="_viterbi-def"><a name="L446"></a><tt class="py-lineno">446</tt> <a class="py-toggle" href="#" id="_viterbi-toggle" onclick="return toggle('_viterbi');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#_viterbi">_viterbi</a><tt class="py-op">(</tt><tt class="py-param">N</tt><tt class="py-op">,</tt> <tt class="py-param">lp_initial</tt><tt class="py-op">,</tt> <tt class="py-param">lp_transition</tt><tt class="py-op">,</tt> <tt class="py-param">lp_emission</tt><tt class="py-op">,</tt> <tt class="py-param">output</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="_viterbi-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="_viterbi-expanded"><a name="L447"></a><tt class="py-lineno">447</tt> <tt class="py-line"> <tt class="py-comment"># The Viterbi algorithm finds the most likely set of states for a</tt> </tt>
<a name="L448"></a><tt class="py-lineno">448</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># given output. Returns a list of states.</tt> </tt>
<a name="L449"></a><tt class="py-lineno">449</tt> <tt class="py-line"><tt class="py-comment"></tt> </tt>
<a name="L450"></a><tt class="py-lineno">450</tt> <tt class="py-line"> <tt class="py-name">T</tt> <tt class="py-op">=</tt> <tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">output</tt><tt class="py-op">)</tt> </tt>
<a name="L451"></a><tt class="py-lineno">451</tt> <tt class="py-line"> <tt class="py-comment"># Store the backtrace in a NxT matrix.</tt> </tt>
<a name="L452"></a><tt class="py-lineno">452</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">backtrace</tt> <tt class="py-op">=</tt> <tt class="py-op">[</tt><tt class="py-op">]</tt> <tt class="py-comment"># list of indexes of states in previous timestep.</tt> </tt>
<a name="L453"></a><tt class="py-lineno">453</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt id="link-244" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-244', 'i', 'link-34');">i</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L454"></a><tt class="py-lineno">454</tt> <tt class="py-line"> <tt class="py-name">backtrace</tt><tt class="py-op">.</tt><tt id="link-245" class="py-name"><a title="Bio.Crystal.Chain.append
Bio.EUtils.POM.ElementNode.append
Bio.EUtils.sourcegen.SourceFile.append
Bio.SCOP.Raf.SeqMap.append
Bio.Seq.MutableSeq.append
Bio.Wise.psw.Alignment.append
Bio.Wise.psw.AlignmentColumn.append
Martel.msre_parse.SubPattern.append" class="py-name" href="#" onclick="return doclink('link-245', 'append', 'link-84');">append</a></tt><tt class="py-op">(</tt><tt class="py-op">[</tt><tt class="py-name">None</tt><tt class="py-op">]</tt> <tt class="py-op">*</tt> <tt class="py-name">T</tt><tt class="py-op">)</tt> </tt>
<a name="L455"></a><tt class="py-lineno">455</tt> <tt class="py-line"> </tt>
<a name="L456"></a><tt class="py-lineno">456</tt> <tt class="py-line"> <tt class="py-comment"># Store the best scores.</tt> </tt>
<a name="L457"></a><tt class="py-lineno">457</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt id="link-246" class="py-name" targets="Method Bio.Compass._Consumer.scores()=Bio.Compass._Consumer-class.html#scores"><a title="Bio.Compass._Consumer.scores" class="py-name" href="#" onclick="return doclink('link-246', 'scores', 'link-246');">scores</a></tt> <tt class="py-op">=</tt> <tt class="py-name">zeros</tt><tt class="py-op">(</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">,</tt> <tt class="py-name">T</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> <tt id="link-247" class="py-name"><a title="Bio.MarkovModel.MATCODE" class="py-name" href="#" onclick="return doclink('link-247', 'MATCODE', 'link-6');">MATCODE</a></tt><tt class="py-op">)</tt> </tt>
<a name="L458"></a><tt class="py-lineno">458</tt> <tt class="py-line"> <tt id="link-248" class="py-name"><a title="Bio.Compass._Consumer.scores" class="py-name" href="#" onclick="return doclink('link-248', 'scores', 'link-246');">scores</a></tt><tt class="py-op">[</tt><tt class="py-op">:</tt><tt class="py-op">,</tt><tt class="py-number">0</tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt class="py-name">lp_initial</tt> <tt class="py-op">+</tt> <tt class="py-name">lp_emission</tt><tt class="py-op">[</tt><tt class="py-op">:</tt><tt class="py-op">,</tt><tt class="py-name">output</tt><tt class="py-op">[</tt><tt class="py-number">0</tt><tt class="py-op">]</tt><tt class="py-op">]</tt> </tt>
<a name="L459"></a><tt class="py-lineno">459</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt class="py-name">t</tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-number">1</tt><tt class="py-op">,</tt> <tt class="py-name">T</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L460"></a><tt class="py-lineno">460</tt> <tt class="py-line"> <tt class="py-name">k</tt> <tt class="py-op">=</tt> <tt class="py-name">output</tt><tt class="py-op">[</tt><tt class="py-name">t</tt><tt class="py-op">]</tt> </tt>
<a name="L461"></a><tt class="py-lineno">461</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt class="py-name">j</tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">N</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L462"></a><tt class="py-lineno">462</tt> <tt class="py-line"> <tt class="py-comment"># Find the most likely place it came from.</tt> </tt>
<a name="L463"></a><tt class="py-lineno">463</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">i_scores</tt> <tt class="py-op">=</tt> <tt id="link-249" class="py-name"><a title="Bio.Compass._Consumer.scores" class="py-name" href="#" onclick="return doclink('link-249', 'scores', 'link-246');">scores</a></tt><tt class="py-op">[</tt><tt class="py-op">:</tt><tt class="py-op">,</tt><tt class="py-name">t</tt><tt class="py-op">-</tt><tt class="py-number">1</tt><tt class="py-op">]</tt> <tt class="py-op">+</tt> \ </tt>
<a name="L464"></a><tt class="py-lineno">464</tt> <tt class="py-line"> <tt class="py-name">lp_transition</tt><tt class="py-op">[</tt><tt class="py-op">:</tt><tt class="py-op">,</tt><tt class="py-name">j</tt><tt class="py-op">]</tt> <tt class="py-op">+</tt> \ </tt>
<a name="L465"></a><tt class="py-lineno">465</tt> <tt class="py-line"> <tt class="py-name">lp_emission</tt><tt class="py-op">[</tt><tt class="py-name">j</tt><tt class="py-op">,</tt><tt class="py-name">k</tt><tt class="py-op">]</tt> </tt>
<a name="L466"></a><tt class="py-lineno">466</tt> <tt class="py-line"> <tt class="py-name">indexes</tt> <tt class="py-op">=</tt> <tt id="link-250" class="py-name" targets="Function Bio.MarkovModel._argmaxes()=Bio.MarkovModel-module.html#_argmaxes"><a title="Bio.MarkovModel._argmaxes" class="py-name" href="#" onclick="return doclink('link-250', '_argmaxes', 'link-250');">_argmaxes</a></tt><tt class="py-op">(</tt><tt class="py-name">i_scores</tt><tt class="py-op">)</tt> </tt>
<a name="L467"></a><tt class="py-lineno">467</tt> <tt class="py-line"> <tt id="link-251" class="py-name"><a title="Bio.Compass._Consumer.scores" class="py-name" href="#" onclick="return doclink('link-251', 'scores', 'link-246');">scores</a></tt><tt class="py-op">[</tt><tt class="py-name">j</tt><tt class="py-op">,</tt><tt class="py-name">t</tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt class="py-name">i_scores</tt><tt class="py-op">[</tt><tt class="py-name">indexes</tt><tt class="py-op">[</tt><tt class="py-number">0</tt><tt class="py-op">]</tt><tt class="py-op">]</tt> </tt>
<a name="L468"></a><tt class="py-lineno">468</tt> <tt class="py-line"> <tt class="py-name">backtrace</tt><tt class="py-op">[</tt><tt class="py-name">j</tt><tt class="py-op">]</tt><tt class="py-op">[</tt><tt class="py-name">t</tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt class="py-name">indexes</tt> </tt>
<a name="L469"></a><tt class="py-lineno">469</tt> <tt class="py-line"> </tt>
<a name="L470"></a><tt class="py-lineno">470</tt> <tt class="py-line"> <tt class="py-comment"># Do the backtrace. First, find a good place to start. Then,</tt> </tt>
<a name="L471"></a><tt class="py-lineno">471</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># we'll follow the backtrace matrix to find the list of states.</tt> </tt>
<a name="L472"></a><tt class="py-lineno">472</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># In the event of ties, there may be multiple paths back through</tt> </tt>
<a name="L473"></a><tt class="py-lineno">473</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># the matrix, which implies a recursive solution. We'll simulate</tt> </tt>
<a name="L474"></a><tt class="py-lineno">474</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-comment"># it by keeping our own stack.</tt> </tt>
<a name="L475"></a><tt class="py-lineno">475</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-name">in_process</tt> <tt class="py-op">=</tt> <tt class="py-op">[</tt><tt class="py-op">]</tt> <tt class="py-comment"># list of (t, states, score)</tt> </tt>
<a name="L476"></a><tt class="py-lineno">476</tt> <tt class="py-line"> <tt class="py-name">results</tt> <tt class="py-op">=</tt> <tt class="py-op">[</tt><tt class="py-op">]</tt> <tt class="py-comment"># return values. list of (states, score)</tt> </tt>
<a name="L477"></a><tt class="py-lineno">477</tt> <tt class="py-line"> <tt class="py-name">indexes</tt> <tt class="py-op">=</tt> <tt id="link-252" class="py-name"><a title="Bio.MarkovModel._argmaxes" class="py-name" href="#" onclick="return doclink('link-252', '_argmaxes', 'link-250');">_argmaxes</a></tt><tt class="py-op">(</tt><tt id="link-253" class="py-name"><a title="Bio.Compass._Consumer.scores" class="py-name" href="#" onclick="return doclink('link-253', 'scores', 'link-246');">scores</a></tt><tt class="py-op">[</tt><tt class="py-op">:</tt><tt class="py-op">,</tt><tt class="py-name">T</tt><tt class="py-op">-</tt><tt class="py-number">1</tt><tt class="py-op">]</tt><tt class="py-op">)</tt> <tt class="py-comment"># pick the first place</tt> </tt>
<a name="L478"></a><tt class="py-lineno">478</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt id="link-254" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-254', 'i', 'link-34');">i</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">indexes</tt><tt class="py-op">:</tt> </tt>
<a name="L479"></a><tt class="py-lineno">479</tt> <tt class="py-line"> <tt class="py-name">in_process</tt><tt class="py-op">.</tt><tt id="link-255" class="py-name"><a title="Bio.Crystal.Chain.append
Bio.EUtils.POM.ElementNode.append
Bio.EUtils.sourcegen.SourceFile.append
Bio.SCOP.Raf.SeqMap.append
Bio.Seq.MutableSeq.append
Bio.Wise.psw.Alignment.append
Bio.Wise.psw.AlignmentColumn.append
Martel.msre_parse.SubPattern.append" class="py-name" href="#" onclick="return doclink('link-255', 'append', 'link-84');">append</a></tt><tt class="py-op">(</tt><tt class="py-op">(</tt><tt class="py-name">T</tt><tt class="py-op">-</tt><tt class="py-number">1</tt><tt class="py-op">,</tt> <tt class="py-op">[</tt><tt id="link-256" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-256', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">,</tt> <tt id="link-257" class="py-name"><a title="Bio.Compass._Consumer.scores" class="py-name" href="#" onclick="return doclink('link-257', 'scores', 'link-246');">scores</a></tt><tt class="py-op">[</tt><tt id="link-258" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-258', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">[</tt><tt class="py-name">T</tt><tt class="py-op">-</tt><tt class="py-number">1</tt><tt class="py-op">]</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
<a name="L480"></a><tt class="py-lineno">480</tt> <tt class="py-line"> <tt class="py-keyword">while</tt> <tt class="py-name">in_process</tt><tt class="py-op">:</tt> </tt>
<a name="L481"></a><tt class="py-lineno">481</tt> <tt class="py-line"> <tt class="py-name">t</tt><tt class="py-op">,</tt> <tt class="py-name">states</tt><tt class="py-op">,</tt> <tt id="link-259" class="py-name"><a title="Bio.Blast.NCBIStandalone._HSPConsumer.score
Bio.expressions.blast.ncbiblast.score" class="py-name" href="#" onclick="return doclink('link-259', 'score', 'link-237');">score</a></tt> <tt class="py-op">=</tt> <tt class="py-name">in_process</tt><tt class="py-op">.</tt><tt id="link-260" class="py-name" targets="Method Bio.Seq.MutableSeq.pop()=Bio.Seq.MutableSeq-class.html#pop"><a title="Bio.Seq.MutableSeq.pop" class="py-name" href="#" onclick="return doclink('link-260', 'pop', 'link-260');">pop</a></tt><tt class="py-op">(</tt><tt class="py-op">)</tt> </tt>
<a name="L482"></a><tt class="py-lineno">482</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-name">t</tt> <tt class="py-op">==</tt> <tt class="py-number">0</tt><tt class="py-op">:</tt> </tt>
<a name="L483"></a><tt class="py-lineno">483</tt> <tt class="py-line"> <tt class="py-name">results</tt><tt class="py-op">.</tt><tt id="link-261" class="py-name"><a title="Bio.Crystal.Chain.append
Bio.EUtils.POM.ElementNode.append
Bio.EUtils.sourcegen.SourceFile.append
Bio.SCOP.Raf.SeqMap.append
Bio.Seq.MutableSeq.append
Bio.Wise.psw.Alignment.append
Bio.Wise.psw.AlignmentColumn.append
Martel.msre_parse.SubPattern.append" class="py-name" href="#" onclick="return doclink('link-261', 'append', 'link-84');">append</a></tt><tt class="py-op">(</tt><tt class="py-op">(</tt><tt class="py-name">states</tt><tt class="py-op">,</tt> <tt id="link-262" class="py-name"><a title="Bio.Blast.NCBIStandalone._HSPConsumer.score
Bio.expressions.blast.ncbiblast.score" class="py-name" href="#" onclick="return doclink('link-262', 'score', 'link-237');">score</a></tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
<a name="L484"></a><tt class="py-lineno">484</tt> <tt class="py-line"> <tt class="py-keyword">else</tt><tt class="py-op">:</tt> </tt>
<a name="L485"></a><tt class="py-lineno">485</tt> <tt class="py-line"> <tt class="py-name">indexes</tt> <tt class="py-op">=</tt> <tt class="py-name">backtrace</tt><tt class="py-op">[</tt><tt class="py-name">states</tt><tt class="py-op">[</tt><tt class="py-number">0</tt><tt class="py-op">]</tt><tt class="py-op">]</tt><tt class="py-op">[</tt><tt class="py-name">t</tt><tt class="py-op">]</tt> </tt>
<a name="L486"></a><tt class="py-lineno">486</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt id="link-263" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-263', 'i', 'link-34');">i</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">indexes</tt><tt class="py-op">:</tt> </tt>
<a name="L487"></a><tt class="py-lineno">487</tt> <tt class="py-line"> <tt class="py-name">in_process</tt><tt class="py-op">.</tt><tt id="link-264" class="py-name"><a title="Bio.Crystal.Chain.append
Bio.EUtils.POM.ElementNode.append
Bio.EUtils.sourcegen.SourceFile.append
Bio.SCOP.Raf.SeqMap.append
Bio.Seq.MutableSeq.append
Bio.Wise.psw.Alignment.append
Bio.Wise.psw.AlignmentColumn.append
Martel.msre_parse.SubPattern.append" class="py-name" href="#" onclick="return doclink('link-264', 'append', 'link-84');">append</a></tt><tt class="py-op">(</tt><tt class="py-op">(</tt><tt class="py-name">t</tt><tt class="py-op">-</tt><tt class="py-number">1</tt><tt class="py-op">,</tt> <tt class="py-op">[</tt><tt id="link-265" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-265', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">+</tt><tt class="py-name">states</tt><tt class="py-op">,</tt> <tt id="link-266" class="py-name"><a title="Bio.Blast.NCBIStandalone._HSPConsumer.score
Bio.expressions.blast.ncbiblast.score" class="py-name" href="#" onclick="return doclink('link-266', 'score', 'link-237');">score</a></tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
<a name="L488"></a><tt class="py-lineno">488</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt class="py-name">results</tt> </tt>
</div><a name="L489"></a><tt class="py-lineno">489</tt> <tt class="py-line"> </tt>
<a name="_normalize"></a><div id="_normalize-def"><a name="L490"></a><tt class="py-lineno">490</tt> <a class="py-toggle" href="#" id="_normalize-toggle" onclick="return toggle('_normalize');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#_normalize">_normalize</a><tt class="py-op">(</tt><tt class="py-param">matrix</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="_normalize-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="_normalize-expanded"><a name="L491"></a><tt class="py-lineno">491</tt> <tt class="py-line"> <tt class="py-comment"># Make sure numbers add up to 1.0</tt> </tt>
<a name="L492"></a><tt class="py-lineno">492</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-keyword">if</tt> <tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">shape</tt><tt class="py-op">(</tt><tt id="link-267" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-267', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">)</tt><tt class="py-op">)</tt> <tt class="py-op">==</tt> <tt class="py-number">1</tt><tt class="py-op">:</tt> </tt>
<a name="L493"></a><tt class="py-lineno">493</tt> <tt class="py-line"> <tt id="link-268" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-268', 'matrix', 'link-162');">matrix</a></tt> <tt class="py-op">=</tt> <tt id="link-269" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-269', 'matrix', 'link-162');">matrix</a></tt> <tt class="py-op">/</tt> <tt class="py-name">float</tt><tt class="py-op">(</tt><tt id="link-270" class="py-name"><a title="Bio.Nexus.Nexus.StepMatrix.sum
Bio.utils.sum" class="py-name" href="#" onclick="return doclink('link-270', 'sum', 'link-212');">sum</a></tt><tt class="py-op">(</tt><tt id="link-271" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-271', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
<a name="L494"></a><tt class="py-lineno">494</tt> <tt class="py-line"> <tt class="py-keyword">elif</tt> <tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">shape</tt><tt class="py-op">(</tt><tt id="link-272" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-272', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">)</tt><tt class="py-op">)</tt> <tt class="py-op">==</tt> <tt class="py-number">2</tt><tt class="py-op">:</tt> </tt>
<a name="L495"></a><tt class="py-lineno">495</tt> <tt class="py-line"> <tt class="py-comment"># Normalize by rows.</tt> </tt>
<a name="L496"></a><tt class="py-lineno">496</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-keyword">for</tt> <tt id="link-273" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-273', 'i', 'link-34');">i</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">len</tt><tt class="py-op">(</tt><tt id="link-274" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-274', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L497"></a><tt class="py-lineno">497</tt> <tt class="py-line"> <tt id="link-275" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-275', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">[</tt><tt id="link-276" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-276', 'i', 'link-34');">i</a></tt><tt class="py-op">,</tt><tt class="py-op">:</tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt id="link-277" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-277', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">[</tt><tt id="link-278" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-278', 'i', 'link-34');">i</a></tt><tt class="py-op">,</tt><tt class="py-op">:</tt><tt class="py-op">]</tt> <tt class="py-op">/</tt> <tt id="link-279" class="py-name"><a title="Bio.Nexus.Nexus.StepMatrix.sum
Bio.utils.sum" class="py-name" href="#" onclick="return doclink('link-279', 'sum', 'link-212');">sum</a></tt><tt class="py-op">(</tt><tt id="link-280" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-280', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">[</tt><tt id="link-281" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-281', 'i', 'link-34');">i</a></tt><tt class="py-op">,</tt><tt class="py-op">:</tt><tt class="py-op">]</tt><tt class="py-op">)</tt> </tt>
<a name="L498"></a><tt class="py-lineno">498</tt> <tt class="py-line"> <tt class="py-keyword">else</tt><tt class="py-op">:</tt> </tt>
<a name="L499"></a><tt class="py-lineno">499</tt> <tt class="py-line"> <tt class="py-keyword">raise</tt> <tt class="py-name">ValueError</tt><tt class="py-op">,</tt> <tt class="py-string">"I cannot handle matrixes of that shape"</tt> </tt>
<a name="L500"></a><tt class="py-lineno">500</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt id="link-282" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-282', 'matrix', 'link-162');">matrix</a></tt> </tt>
</div><a name="L501"></a><tt class="py-lineno">501</tt> <tt class="py-line"> </tt>
<a name="_uniform_norm"></a><div id="_uniform_norm-def"><a name="L502"></a><tt class="py-lineno">502</tt> <a class="py-toggle" href="#" id="_uniform_norm-toggle" onclick="return toggle('_uniform_norm');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#_uniform_norm">_uniform_norm</a><tt class="py-op">(</tt><tt class="py-param">shape</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="_uniform_norm-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="_uniform_norm-expanded"><a name="L503"></a><tt class="py-lineno">503</tt> <tt class="py-line"> <tt id="link-283" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-283', 'matrix', 'link-162');">matrix</a></tt> <tt class="py-op">=</tt> <tt class="py-name">ones</tt><tt class="py-op">(</tt><tt class="py-name">shape</tt><tt class="py-op">,</tt> <tt id="link-284" class="py-name"><a title="Bio.MarkovModel.MATCODE" class="py-name" href="#" onclick="return doclink('link-284', 'MATCODE', 'link-6');">MATCODE</a></tt><tt class="py-op">)</tt> </tt>
<a name="L504"></a><tt class="py-lineno">504</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt id="link-285" class="py-name"><a title="Bio.MarkovModel._normalize" class="py-name" href="#" onclick="return doclink('link-285', '_normalize', 'link-205');">_normalize</a></tt><tt class="py-op">(</tt><tt id="link-286" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-286', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">)</tt> </tt>
</div><a name="L505"></a><tt class="py-lineno">505</tt> <tt class="py-line"> </tt>
<a name="_random_norm"></a><div id="_random_norm-def"><a name="L506"></a><tt class="py-lineno">506</tt> <a class="py-toggle" href="#" id="_random_norm-toggle" onclick="return toggle('_random_norm');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#_random_norm">_random_norm</a><tt class="py-op">(</tt><tt class="py-param">shape</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="_random_norm-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="_random_norm-expanded"><a name="L507"></a><tt class="py-lineno">507</tt> <tt class="py-line"> <tt id="link-287" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-287', 'matrix', 'link-162');">matrix</a></tt> <tt class="py-op">=</tt> <tt class="py-name">asarray</tt><tt class="py-op">(</tt><tt class="py-name">RandomArray</tt><tt class="py-op">.</tt><tt class="py-name">random</tt><tt class="py-op">(</tt><tt class="py-name">shape</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> <tt id="link-288" class="py-name"><a title="Bio.MarkovModel.MATCODE" class="py-name" href="#" onclick="return doclink('link-288', 'MATCODE', 'link-6');">MATCODE</a></tt><tt class="py-op">)</tt> </tt>
<a name="L508"></a><tt class="py-lineno">508</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt id="link-289" class="py-name"><a title="Bio.MarkovModel._normalize" class="py-name" href="#" onclick="return doclink('link-289', '_normalize', 'link-205');">_normalize</a></tt><tt class="py-op">(</tt><tt id="link-290" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-290', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">)</tt> </tt>
</div><a name="L509"></a><tt class="py-lineno">509</tt> <tt class="py-line"> </tt>
<a name="_copy_and_check"></a><div id="_copy_and_check-def"><a name="L510"></a><tt class="py-lineno">510</tt> <a class="py-toggle" href="#" id="_copy_and_check-toggle" onclick="return toggle('_copy_and_check');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#_copy_and_check">_copy_and_check</a><tt class="py-op">(</tt><tt class="py-param">matrix</tt><tt class="py-op">,</tt> <tt class="py-param">desired_shape</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="_copy_and_check-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="_copy_and_check-expanded"><a name="L511"></a><tt class="py-lineno">511</tt> <tt class="py-line"> <tt class="py-comment"># Copy the matrix.</tt> </tt>
<a name="L512"></a><tt class="py-lineno">512</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt id="link-291" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-291', 'matrix', 'link-162');">matrix</a></tt> <tt class="py-op">=</tt> <tt class="py-name">array</tt><tt class="py-op">(</tt><tt id="link-292" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-292', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">,</tt> <tt id="link-293" class="py-name"><a title="Bio.MarkovModel.MATCODE" class="py-name" href="#" onclick="return doclink('link-293', 'MATCODE', 'link-6');">MATCODE</a></tt><tt class="py-op">,</tt> <tt id="link-294" class="py-name" targets="Method Bio.Crystal.Crystal.copy()=Bio.Crystal.Crystal-class.html#copy,Method Bio.GA.Organism.Organism.copy()=Bio.GA.Organism.Organism-class.html#copy,Method Bio.GenBank.NCBIDictionary.copy()=Bio.GenBank.NCBIDictionary-class.html#copy,Method Bio.PDB.Vector'.Vector.copy()=Bio.PDB.Vector%27.Vector-class.html#copy,Method Bio.Prosite.ExPASyDictionary.copy()=Bio.Prosite.ExPASyDictionary-class.html#copy,Method Bio.Prosite.Pattern.PrositeTerm.copy()=Bio.Prosite.Pattern.PrositeTerm-class.html#copy,Method Bio.Prosite.Prodoc.ExPASyDictionary.copy()=Bio.Prosite.Prodoc.ExPASyDictionary-class.html#copy,Method Bio.PubMed.Dictionary.copy()=Bio.PubMed.Dictionary-class.html#copy,Method Bio.SwissProt.SProt.ExPASyDictionary.copy()=Bio.SwissProt.SProt.ExPASyDictionary-class.html#copy,Method Martel.Expression.Any.copy()=Martel.Expression.Any-class.html#copy,Method Martel.Expression.AnyEol.copy()=Martel.Expression.AnyEol-class.html#copy,Method Martel.Expression.Assert.copy()=Martel.Expression.Assert-class.html#copy,Method Martel.Expression.AtBeginning.copy()=Martel.Expression.AtBeginning-class.html#copy,Method Martel.Expression.AtEnd.copy()=Martel.Expression.AtEnd-class.html#copy,Method Martel.Expression.Debug.copy()=Martel.Expression.Debug-class.html#copy,Method Martel.Expression.Dot.copy()=Martel.Expression.Dot-class.html#copy,Method Martel.Expression.Expression.copy()=Martel.Expression.Expression-class.html#copy,Method Martel.Expression.ExpressionList.copy()=Martel.Expression.ExpressionList-class.html#copy,Method Martel.Expression.FastFeature.copy()=Martel.Expression.FastFeature-class.html#copy,Method Martel.Expression.Group.copy()=Martel.Expression.Group-class.html#copy,Method Martel.Expression.GroupRef.copy()=Martel.Expression.GroupRef-class.html#copy,Method Martel.Expression.HeaderFooter.copy()=Martel.Expression.HeaderFooter-class.html#copy,Method Martel.Expression.Literal.copy()=Martel.Expression.Literal-class.html#copy,Method Martel.Expression.MaxRepeat.copy()=Martel.Expression.MaxRepeat-class.html#copy,Method Martel.Expression.NullOp.copy()=Martel.Expression.NullOp-class.html#copy,Method Martel.Expression.ParseRecords.copy()=Martel.Expression.ParseRecords-class.html#copy,Method Martel.Expression.PassThrough.copy()=Martel.Expression.PassThrough-class.html#copy,Method Martel.Expression.Str.copy()=Martel.Expression.Str-class.html#copy,Method Martel.IterParser.IterHeaderFooter.copy()=Martel.IterParser.IterHeaderFooter-class.html#copy,Method Martel.IterParser.IterRecords.copy()=Martel.IterParser.IterRecords-class.html#copy,Method Martel.Iterator.IteratorRecords.copy()=Martel.Iterator.IteratorRecords-class.html#copy,Method Martel.Parser.HeaderFooterParser.copy()=Martel.Parser.HeaderFooterParser-class.html#copy,Method Martel.Parser.Parser.copy()=Martel.Parser.Parser-class.html#copy,Method Martel.Parser.RecordParser.copy()=Martel.Parser.RecordParser-class.html#copy"><a title="Bio.Crystal.Crystal.copy
Bio.GA.Organism.Organism.copy
Bio.GenBank.NCBIDictionary.copy
Bio.PDB.Vector'.Vector.copy
Bio.Prosite.ExPASyDictionary.copy
Bio.Prosite.Pattern.PrositeTerm.copy
Bio.Prosite.Prodoc.ExPASyDictionary.copy
Bio.PubMed.Dictionary.copy
Bio.SwissProt.SProt.ExPASyDictionary.copy
Martel.Expression.Any.copy
Martel.Expression.AnyEol.copy
Martel.Expression.Assert.copy
Martel.Expression.AtBeginning.copy
Martel.Expression.AtEnd.copy
Martel.Expression.Debug.copy
Martel.Expression.Dot.copy
Martel.Expression.Expression.copy
Martel.Expression.ExpressionList.copy
Martel.Expression.FastFeature.copy
Martel.Expression.Group.copy
Martel.Expression.GroupRef.copy
Martel.Expression.HeaderFooter.copy
Martel.Expression.Literal.copy
Martel.Expression.MaxRepeat.copy
Martel.Expression.NullOp.copy
Martel.Expression.ParseRecords.copy
Martel.Expression.PassThrough.copy
Martel.Expression.Str.copy
Martel.IterParser.IterHeaderFooter.copy
Martel.IterParser.IterRecords.copy
Martel.Iterator.IteratorRecords.copy
Martel.Parser.HeaderFooterParser.copy
Martel.Parser.Parser.copy
Martel.Parser.RecordParser.copy" class="py-name" href="#" onclick="return doclink('link-294', 'copy', 'link-294');">copy</a></tt><tt class="py-op">=</tt><tt class="py-number">1</tt><tt class="py-op">)</tt> </tt>
<a name="L513"></a><tt class="py-lineno">513</tt> <tt class="py-line"> <tt class="py-comment"># Check the dimensions.</tt> </tt>
<a name="L514"></a><tt class="py-lineno">514</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-keyword">if</tt> <tt class="py-name">shape</tt><tt class="py-op">(</tt><tt id="link-295" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-295', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">)</tt> <tt class="py-op">!=</tt> <tt class="py-name">desired_shape</tt><tt class="py-op">:</tt> </tt>
<a name="L515"></a><tt class="py-lineno">515</tt> <tt class="py-line"> <tt class="py-keyword">raise</tt> <tt class="py-name">ValuError</tt><tt class="py-op">,</tt> <tt class="py-string">"Incorrect dimension"</tt> </tt>
<a name="L516"></a><tt class="py-lineno">516</tt> <tt class="py-line"> <tt class="py-comment"># Make sure it's normalized.</tt> </tt>
<a name="L517"></a><tt class="py-lineno">517</tt> <tt class="py-line"><tt class="py-comment"></tt> <tt class="py-keyword">if</tt> <tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">shape</tt><tt class="py-op">(</tt><tt id="link-296" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-296', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">)</tt><tt class="py-op">)</tt> <tt class="py-op">==</tt> <tt class="py-number">1</tt><tt class="py-op">:</tt> </tt>
<a name="L518"></a><tt class="py-lineno">518</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt id="link-297" class="py-name"><a title="Bio.Affy.CelFile.fabs
Bio.LogisticRegression.fabs
Bio.MarkovModel.fabs
Bio.MaxEntropy.fabs
Bio.NaiveBayes.fabs
Bio.Statistics.lowess.fabs
Bio.distance.fabs
Bio.kNN.fabs" class="py-name" href="#" onclick="return doclink('link-297', 'fabs', 'link-113');">fabs</a></tt><tt class="py-op">(</tt><tt id="link-298" class="py-name"><a title="Bio.Nexus.Nexus.StepMatrix.sum
Bio.utils.sum" class="py-name" href="#" onclick="return doclink('link-298', 'sum', 'link-212');">sum</a></tt><tt class="py-op">(</tt><tt id="link-299" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-299', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">)</tt><tt class="py-op">-</tt><tt class="py-number">1.0</tt><tt class="py-op">)</tt> <tt class="py-op">></tt> <tt class="py-number">0.01</tt><tt class="py-op">:</tt> </tt>
<a name="L519"></a><tt class="py-lineno">519</tt> <tt class="py-line"> <tt class="py-keyword">raise</tt> <tt class="py-name">ValueError</tt><tt class="py-op">,</tt> <tt class="py-string">"matrix not normalized to 1.0"</tt> </tt>
<a name="L520"></a><tt class="py-lineno">520</tt> <tt class="py-line"> <tt class="py-keyword">elif</tt> <tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">shape</tt><tt class="py-op">(</tt><tt id="link-300" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-300', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">)</tt><tt class="py-op">)</tt> <tt class="py-op">==</tt> <tt class="py-number">2</tt><tt class="py-op">:</tt> </tt>
<a name="L521"></a><tt class="py-lineno">521</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt id="link-301" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-301', 'i', 'link-34');">i</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">len</tt><tt class="py-op">(</tt><tt id="link-302" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-302', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L522"></a><tt class="py-lineno">522</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt id="link-303" class="py-name"><a title="Bio.Affy.CelFile.fabs
Bio.LogisticRegression.fabs
Bio.MarkovModel.fabs
Bio.MaxEntropy.fabs
Bio.NaiveBayes.fabs
Bio.Statistics.lowess.fabs
Bio.distance.fabs
Bio.kNN.fabs" class="py-name" href="#" onclick="return doclink('link-303', 'fabs', 'link-113');">fabs</a></tt><tt class="py-op">(</tt><tt id="link-304" class="py-name"><a title="Bio.Nexus.Nexus.StepMatrix.sum
Bio.utils.sum" class="py-name" href="#" onclick="return doclink('link-304', 'sum', 'link-212');">sum</a></tt><tt class="py-op">(</tt><tt id="link-305" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-305', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">[</tt><tt id="link-306" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-306', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">)</tt><tt class="py-op">-</tt><tt class="py-number">1.0</tt><tt class="py-op">)</tt> <tt class="py-op">></tt> <tt class="py-number">0.01</tt><tt class="py-op">:</tt> </tt>
<a name="L523"></a><tt class="py-lineno">523</tt> <tt class="py-line"> <tt class="py-keyword">raise</tt> <tt class="py-name">ValueError</tt><tt class="py-op">,</tt> <tt class="py-string">"matrix %d not normalized to 1.0"</tt> <tt class="py-op">%</tt> <tt id="link-307" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-307', 'i', 'link-34');">i</a></tt> </tt>
<a name="L524"></a><tt class="py-lineno">524</tt> <tt class="py-line"> <tt class="py-keyword">else</tt><tt class="py-op">:</tt> </tt>
<a name="L525"></a><tt class="py-lineno">525</tt> <tt class="py-line"> <tt class="py-keyword">raise</tt> <tt class="py-name">ValueError</tt><tt class="py-op">,</tt> <tt class="py-string">"I don't handle matrices > 2 dimensions"</tt> </tt>
<a name="L526"></a><tt class="py-lineno">526</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt id="link-308" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-308', 'matrix', 'link-162');">matrix</a></tt> </tt>
</div><a name="L527"></a><tt class="py-lineno">527</tt> <tt class="py-line"> </tt>
<a name="_safe_copy_and_check"></a><div id="_safe_copy_and_check-def"><a name="L528"></a><tt class="py-lineno">528</tt> <a class="py-toggle" href="#" id="_safe_copy_and_check-toggle" onclick="return toggle('_safe_copy_and_check');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#_safe_copy_and_check">_safe_copy_and_check</a><tt class="py-op">(</tt><tt class="py-param">matrix</tt><tt class="py-op">,</tt> <tt class="py-param">desired_shape</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="_safe_copy_and_check-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="_safe_copy_and_check-expanded"><a name="L529"></a><tt class="py-lineno">529</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt id="link-309" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-309', 'matrix', 'link-162');">matrix</a></tt> <tt class="py-keyword">is</tt> <tt class="py-name">None</tt><tt class="py-op">:</tt> </tt>
<a name="L530"></a><tt class="py-lineno">530</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt class="py-name">None</tt> </tt>
<a name="L531"></a><tt class="py-lineno">531</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt id="link-310" class="py-name" targets="Function Bio.MarkovModel._copy_and_check()=Bio.MarkovModel-module.html#_copy_and_check"><a title="Bio.MarkovModel._copy_and_check" class="py-name" href="#" onclick="return doclink('link-310', '_copy_and_check', 'link-310');">_copy_and_check</a></tt><tt class="py-op">(</tt><tt id="link-311" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-311', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">,</tt> <tt class="py-name">desired_shape</tt><tt class="py-op">)</tt> </tt>
</div><a name="L532"></a><tt class="py-lineno">532</tt> <tt class="py-line"> </tt>
<a name="_safe_log"></a><div id="_safe_log-def"><a name="L533"></a><tt class="py-lineno">533</tt> <a class="py-toggle" href="#" id="_safe_log-toggle" onclick="return toggle('_safe_log');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#_safe_log">_safe_log</a><tt class="py-op">(</tt><tt class="py-param">n</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="_safe_log-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="_safe_log-expanded"><a name="L534"></a><tt class="py-lineno">534</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-name">n</tt> <tt class="py-keyword">is</tt> <tt class="py-name">None</tt><tt class="py-op">:</tt> </tt>
<a name="L535"></a><tt class="py-lineno">535</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt class="py-name">None</tt> </tt>
<a name="L536"></a><tt class="py-lineno">536</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt id="link-312" class="py-name"><a title="Bio.Affy.CelFile.log
Bio.LogisticRegression.log
Bio.MarkovModel.log
Bio.MaxEntropy.log
Bio.NaiveBayes.log
Bio.Statistics.lowess.log
Bio.distance.log
Bio.kNN.log" class="py-name" href="#" onclick="return doclink('link-312', 'log', 'link-4');">log</a></tt><tt class="py-op">(</tt><tt class="py-name">n</tt><tt class="py-op">)</tt> </tt>
</div><a name="L537"></a><tt class="py-lineno">537</tt> <tt class="py-line"> </tt>
<a name="_safe_asarray"></a><div id="_safe_asarray-def"><a name="L538"></a><tt class="py-lineno">538</tt> <a class="py-toggle" href="#" id="_safe_asarray-toggle" onclick="return toggle('_safe_asarray');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#_safe_asarray">_safe_asarray</a><tt class="py-op">(</tt><tt class="py-param">a</tt><tt class="py-op">,</tt> <tt class="py-param">typecode</tt><tt class="py-op">=</tt><tt class="py-name">None</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="_safe_asarray-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="_safe_asarray-expanded"><a name="L539"></a><tt class="py-lineno">539</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-name">a</tt> <tt class="py-keyword">is</tt> <tt class="py-name">None</tt><tt class="py-op">:</tt> </tt>
<a name="L540"></a><tt class="py-lineno">540</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt class="py-name">None</tt> </tt>
<a name="L541"></a><tt class="py-lineno">541</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt class="py-name">asarray</tt><tt class="py-op">(</tt><tt class="py-name">a</tt><tt class="py-op">,</tt> <tt class="py-name">typecode</tt><tt class="py-op">=</tt><tt class="py-name">typecode</tt><tt class="py-op">)</tt> </tt>
</div><a name="L542"></a><tt class="py-lineno">542</tt> <tt class="py-line"> </tt>
<a name="_logadd"></a><div id="_logadd-def"><a name="L543"></a><tt class="py-lineno">543</tt> <a class="py-toggle" href="#" id="_logadd-toggle" onclick="return toggle('_logadd');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#_logadd">_logadd</a><tt class="py-op">(</tt><tt class="py-param">logx</tt><tt class="py-op">,</tt> <tt class="py-param">logy</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="_logadd-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="_logadd-expanded"><a name="L544"></a><tt class="py-lineno">544</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-name">logy</tt> <tt class="py-op">-</tt> <tt class="py-name">logx</tt> <tt class="py-op">></tt> <tt class="py-number">100</tt><tt class="py-op">:</tt> </tt>
<a name="L545"></a><tt class="py-lineno">545</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt class="py-name">logy</tt> </tt>
<a name="L546"></a><tt class="py-lineno">546</tt> <tt class="py-line"> <tt class="py-keyword">elif</tt> <tt class="py-name">logx</tt> <tt class="py-op">-</tt> <tt class="py-name">logy</tt> <tt class="py-op">></tt> <tt class="py-number">100</tt><tt class="py-op">:</tt> </tt>
<a name="L547"></a><tt class="py-lineno">547</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt class="py-name">logx</tt> </tt>
<a name="L548"></a><tt class="py-lineno">548</tt> <tt class="py-line"> <tt class="py-name">minxy</tt> <tt class="py-op">=</tt> <tt class="py-name">min</tt><tt class="py-op">(</tt><tt class="py-name">logx</tt><tt class="py-op">,</tt> <tt class="py-name">logy</tt><tt class="py-op">)</tt> </tt>
<a name="L549"></a><tt class="py-lineno">549</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt class="py-name">minxy</tt> <tt class="py-op">+</tt> <tt id="link-313" class="py-name"><a title="Bio.Affy.CelFile.log
Bio.LogisticRegression.log
Bio.MarkovModel.log
Bio.MaxEntropy.log
Bio.NaiveBayes.log
Bio.Statistics.lowess.log
Bio.distance.log
Bio.kNN.log" class="py-name" href="#" onclick="return doclink('link-313', 'log', 'link-4');">log</a></tt><tt class="py-op">(</tt><tt id="link-314" class="py-name"><a title="Bio.Affy.CelFile.exp
Bio.LogisticRegression.exp
Bio.MarkovModel.exp
Bio.MaxEntropy.exp
Bio.NaiveBayes.exp
Bio.Statistics.lowess.exp
Bio.distance.exp
Bio.kNN.exp" class="py-name" href="#" onclick="return doclink('link-314', 'exp', 'link-116');">exp</a></tt><tt class="py-op">(</tt><tt class="py-name">logx</tt><tt class="py-op">-</tt><tt class="py-name">minxy</tt><tt class="py-op">)</tt> <tt class="py-op">+</tt> <tt id="link-315" class="py-name"><a title="Bio.Affy.CelFile.exp
Bio.LogisticRegression.exp
Bio.MarkovModel.exp
Bio.MaxEntropy.exp
Bio.NaiveBayes.exp
Bio.Statistics.lowess.exp
Bio.distance.exp
Bio.kNN.exp" class="py-name" href="#" onclick="return doclink('link-315', 'exp', 'link-116');">exp</a></tt><tt class="py-op">(</tt><tt class="py-name">logy</tt><tt class="py-op">-</tt><tt class="py-name">minxy</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
</div><a name="L550"></a><tt class="py-lineno">550</tt> <tt class="py-line"> </tt>
<a name="_logsum"></a><div id="_logsum-def"><a name="L551"></a><tt class="py-lineno">551</tt> <a class="py-toggle" href="#" id="_logsum-toggle" onclick="return toggle('_logsum');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#_logsum">_logsum</a><tt class="py-op">(</tt><tt class="py-param">matrix</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="_logsum-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="_logsum-expanded"><a name="L552"></a><tt class="py-lineno">552</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">shape</tt><tt class="py-op">(</tt><tt id="link-316" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-316', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">)</tt><tt class="py-op">)</tt> <tt class="py-op">></tt> <tt class="py-number">1</tt><tt class="py-op">:</tt> </tt>
<a name="L553"></a><tt class="py-lineno">553</tt> <tt class="py-line"> <tt class="py-name">vec</tt> <tt class="py-op">=</tt> <tt class="py-name">reshape</tt><tt class="py-op">(</tt><tt id="link-317" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-317', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">,</tt> <tt class="py-op">(</tt><tt class="py-name">product</tt><tt class="py-op">(</tt><tt class="py-name">shape</tt><tt class="py-op">(</tt><tt id="link-318" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-318', 'matrix', 'link-162');">matrix</a></tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">,</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
<a name="L554"></a><tt class="py-lineno">554</tt> <tt class="py-line"> <tt class="py-keyword">else</tt><tt class="py-op">:</tt> </tt>
<a name="L555"></a><tt class="py-lineno">555</tt> <tt class="py-line"> <tt class="py-name">vec</tt> <tt class="py-op">=</tt> <tt id="link-319" class="py-name"><a title="Bio.Blast.NCBIStandalone._ParametersConsumer.matrix
Bio.MetaTool.metatool_format.matrix
Bio.Prosite._RecordConsumer.matrix" class="py-name" href="#" onclick="return doclink('link-319', 'matrix', 'link-162');">matrix</a></tt> </tt>
<a name="L556"></a><tt class="py-lineno">556</tt> <tt class="py-line"> <tt id="link-320" class="py-name"><a title="Bio.Nexus.Nexus.StepMatrix.sum
Bio.utils.sum" class="py-name" href="#" onclick="return doclink('link-320', 'sum', 'link-212');">sum</a></tt> <tt class="py-op">=</tt> <tt id="link-321" class="py-name"><a title="Bio.MarkovModel.LOG0" class="py-name" href="#" onclick="return doclink('link-321', 'LOG0', 'link-3');">LOG0</a></tt> </tt>
<a name="L557"></a><tt class="py-lineno">557</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt class="py-name">num</tt> <tt class="py-keyword">in</tt> <tt class="py-name">vec</tt><tt class="py-op">:</tt> </tt>
<a name="L558"></a><tt class="py-lineno">558</tt> <tt class="py-line"> <tt id="link-322" class="py-name"><a title="Bio.Nexus.Nexus.StepMatrix.sum
Bio.utils.sum" class="py-name" href="#" onclick="return doclink('link-322', 'sum', 'link-212');">sum</a></tt> <tt class="py-op">=</tt> <tt id="link-323" class="py-name"><a title="Bio.MarkovModel._logadd" class="py-name" href="#" onclick="return doclink('link-323', '_logadd', 'link-154');">_logadd</a></tt><tt class="py-op">(</tt><tt id="link-324" class="py-name"><a title="Bio.Nexus.Nexus.StepMatrix.sum
Bio.utils.sum" class="py-name" href="#" onclick="return doclink('link-324', 'sum', 'link-212');">sum</a></tt><tt class="py-op">,</tt> <tt class="py-name">num</tt><tt class="py-op">)</tt> </tt>
<a name="L559"></a><tt class="py-lineno">559</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt id="link-325" class="py-name"><a title="Bio.Nexus.Nexus.StepMatrix.sum
Bio.utils.sum" class="py-name" href="#" onclick="return doclink('link-325', 'sum', 'link-212');">sum</a></tt> </tt>
</div><a name="L560"></a><tt class="py-lineno">560</tt> <tt class="py-line"> </tt>
<a name="_logvecadd"></a><div id="_logvecadd-def"><a name="L561"></a><tt class="py-lineno">561</tt> <a class="py-toggle" href="#" id="_logvecadd-toggle" onclick="return toggle('_logvecadd');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#_logvecadd">_logvecadd</a><tt class="py-op">(</tt><tt class="py-param">logvec1</tt><tt class="py-op">,</tt> <tt class="py-param">logvec2</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="_logvecadd-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="_logvecadd-expanded"><a name="L562"></a><tt class="py-lineno">562</tt> <tt class="py-line"> <tt class="py-keyword">assert</tt> <tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">logvec1</tt><tt class="py-op">)</tt> <tt class="py-op">==</tt> <tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">logvec2</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> <tt class="py-string">"vectors aren't the same length"</tt> </tt>
<a name="L563"></a><tt class="py-lineno">563</tt> <tt class="py-line"> <tt class="py-name">sumvec</tt> <tt class="py-op">=</tt> <tt class="py-name">zeros</tt><tt class="py-op">(</tt><tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">logvec1</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> <tt id="link-326" class="py-name"><a title="Bio.MarkovModel.MATCODE" class="py-name" href="#" onclick="return doclink('link-326', 'MATCODE', 'link-6');">MATCODE</a></tt><tt class="py-op">)</tt> </tt>
<a name="L564"></a><tt class="py-lineno">564</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt id="link-327" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-327', 'i', 'link-34');">i</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">range</tt><tt class="py-op">(</tt><tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">logvec1</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L565"></a><tt class="py-lineno">565</tt> <tt class="py-line"> <tt class="py-name">sumvec</tt><tt class="py-op">[</tt><tt id="link-328" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-328', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt id="link-329" class="py-name"><a title="Bio.MarkovModel._logadd" class="py-name" href="#" onclick="return doclink('link-329', '_logadd', 'link-154');">_logadd</a></tt><tt class="py-op">(</tt><tt class="py-name">logvec1</tt><tt class="py-op">[</tt><tt id="link-330" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-330', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">,</tt> <tt class="py-name">logvec2</tt><tt class="py-op">[</tt><tt id="link-331" class="py-name"><a title="Bio.PDB.Polypeptide.i" class="py-name" href="#" onclick="return doclink('link-331', 'i', 'link-34');">i</a></tt><tt class="py-op">]</tt><tt class="py-op">)</tt> </tt>
<a name="L566"></a><tt class="py-lineno">566</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt class="py-name">sumvec</tt> </tt>
</div><a name="L567"></a><tt class="py-lineno">567</tt> <tt class="py-line"> </tt>
<a name="_exp_logsum"></a><div id="_exp_logsum-def"><a name="L568"></a><tt class="py-lineno">568</tt> <a class="py-toggle" href="#" id="_exp_logsum-toggle" onclick="return toggle('_exp_logsum');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="Bio.MarkovModel-module.html#_exp_logsum">_exp_logsum</a><tt class="py-op">(</tt><tt class="py-param">numbers</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="_exp_logsum-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="_exp_logsum-expanded"><a name="L569"></a><tt class="py-lineno">569</tt> <tt class="py-line"> <tt id="link-332" class="py-name"><a title="Bio.Nexus.Nexus.StepMatrix.sum
Bio.utils.sum" class="py-name" href="#" onclick="return doclink('link-332', 'sum', 'link-212');">sum</a></tt> <tt class="py-op">=</tt> <tt id="link-333" class="py-name"><a title="Bio.MarkovModel._logsum" class="py-name" href="#" onclick="return doclink('link-333', '_logsum', 'link-126');">_logsum</a></tt><tt class="py-op">(</tt><tt class="py-name">numbers</tt><tt class="py-op">)</tt> </tt>
<a name="L570"></a><tt class="py-lineno">570</tt> <tt class="py-line"> <tt class="py-keyword">return</tt> <tt class="py-name">math</tt><tt class="py-op">.</tt><tt id="link-334" class="py-name"><a title="Bio.Affy.CelFile.exp
Bio.LogisticRegression.exp
Bio.MarkovModel.exp
Bio.MaxEntropy.exp
Bio.NaiveBayes.exp
Bio.Statistics.lowess.exp
Bio.distance.exp
Bio.kNN.exp" class="py-name" href="#" onclick="return doclink('link-334', 'exp', 'link-116');">exp</a></tt><tt class="py-op">(</tt><tt id="link-335" class="py-name"><a title="Bio.Nexus.Nexus.StepMatrix.sum
Bio.utils.sum" class="py-name" href="#" onclick="return doclink('link-335', 'sum', 'link-212');">sum</a></tt><tt class="py-op">)</tt> </tt>
</div><a name="L571"></a><tt class="py-lineno">571</tt> <tt class="py-line"> </tt>
<a name="L572"></a><tt class="py-lineno">572</tt> <tt class="py-line"><tt class="py-keyword">try</tt><tt class="py-op">:</tt> </tt>
<a name="L573"></a><tt class="py-lineno">573</tt> <tt class="py-line"> <tt class="py-keyword">import</tt> <tt class="py-name">cMarkovModel</tt> </tt>
<a name="L574"></a><tt class="py-lineno">574</tt> <tt class="py-line"><tt class="py-keyword">except</tt> <tt class="py-name">ImportError</tt><tt class="py-op">,</tt> <tt id="link-336" class="py-name"><a title="Bio.MarkovModel.x
Bio.Statistics.lowess.x" class="py-name" href="#" onclick="return doclink('link-336', 'x', 'link-67');">x</a></tt><tt class="py-op">:</tt> </tt>
<a name="L575"></a><tt class="py-lineno">575</tt> <tt class="py-line"> <tt class="py-keyword">pass</tt> </tt>
<a name="L576"></a><tt class="py-lineno">576</tt> <tt class="py-line"><tt class="py-keyword">else</tt><tt class="py-op">:</tt> </tt>
<a name="L577"></a><tt class="py-lineno">577</tt> <tt class="py-line"> <tt class="py-keyword">import</tt> <tt class="py-name">sys</tt> </tt>
<a name="L578"></a><tt class="py-lineno">578</tt> <tt class="py-line"> <tt id="link-337" class="py-name" targets="Variable Bio.MarkovModel.this_module=Bio.MarkovModel-module.html#this_module,Variable Bio.pairwise2.this_module=Bio.pairwise2-module.html#this_module"><a title="Bio.MarkovModel.this_module
Bio.pairwise2.this_module" class="py-name" href="#" onclick="return doclink('link-337', 'this_module', 'link-337');">this_module</a></tt> <tt class="py-op">=</tt> <tt class="py-name">sys</tt><tt class="py-op">.</tt><tt class="py-name">modules</tt><tt class="py-op">[</tt><tt class="py-name">__name__</tt><tt class="py-op">]</tt> </tt>
<a name="L579"></a><tt class="py-lineno">579</tt> <tt class="py-line"> <tt class="py-keyword">for</tt> <tt id="link-338" class="py-name" targets="Variable Bio.Encodings.IUPACEncoding.name=Bio.Encodings.IUPACEncoding-module.html#name"><a title="Bio.Encodings.IUPACEncoding.name" class="py-name" href="#" onclick="return doclink('link-338', 'name', 'link-338');">name</a></tt> <tt class="py-keyword">in</tt> <tt class="py-name">cMarkovModel</tt><tt class="py-op">.</tt><tt class="py-name">__dict__</tt><tt class="py-op">.</tt><tt id="link-339" class="py-name" targets="Method Bio.Crystal.Crystal.keys()=Bio.Crystal.Crystal-class.html#keys,Method Bio.EUtils.MultiDict._BaseMultiDict.keys()=Bio.EUtils.MultiDict._BaseMultiDict-class.html#keys,Method Bio.GenBank.NCBIDictionary.keys()=Bio.GenBank.NCBIDictionary-class.html#keys,Method Bio.Mindy.BaseDB.DictLookup.keys()=Bio.Mindy.BaseDB.DictLookup-class.html#keys,Method Bio.Mindy.BaseDB.OpenDB.keys()=Bio.Mindy.BaseDB.OpenDB-class.html#keys,Method Bio.Mindy.BerkeleyDB.PrimaryNamespace.keys()=Bio.Mindy.BerkeleyDB.PrimaryNamespace-class.html#keys,Method Bio.Mindy.BerkeleyDB.SecondaryNamespace.keys()=Bio.Mindy.BerkeleyDB.SecondaryNamespace-class.html#keys,Method Bio.Mindy.FlatDB.PrimaryNamespace.keys()=Bio.Mindy.FlatDB.PrimaryNamespace-class.html#keys,Method Bio.Mindy.FlatDB.PrimaryTable.keys()=Bio.Mindy.FlatDB.PrimaryTable-class.html#keys,Method Bio.Mindy.FlatDB.SecondaryNamespace.keys()=Bio.Mindy.FlatDB.SecondaryNamespace-class.html#keys,Method Bio.Mindy.FlatDB.SecondaryTable.keys()=Bio.Mindy.FlatDB.SecondaryTable-class.html#keys,Method Bio.PDB.AbstractPropertyMap.AbstractPropertyMap.keys()=Bio.PDB.AbstractPropertyMap.AbstractPropertyMap-class.html#keys,Method Bio.Prosite.ExPASyDictionary.keys()=Bio.Prosite.ExPASyDictionary-class.html#keys,Method Bio.Prosite.Prodoc.ExPASyDictionary.keys()=Bio.Prosite.Prodoc.ExPASyDictionary-class.html#keys,Method Bio.PubMed.Dictionary.keys()=Bio.PubMed.Dictionary-class.html#keys,Method Bio.SwissProt.SProt.Dictionary.keys()=Bio.SwissProt.SProt.Dictionary-class.html#keys,Method Bio.SwissProt.SProt.ExPASyDictionary.keys()=Bio.SwissProt.SProt.ExPASyDictionary-class.html#keys,Method Bio.config.Registry.Registry.keys()=Bio.config.Registry.Registry-class.html#keys,Method BioSQL.BioSeqDatabase.BioSeqDatabase.keys()=BioSQL.BioSeqDatabase.BioSeqDatabase-class.html#keys,Method BioSQL.BioSeqDatabase.DBServer.keys()=BioSQL.BioSeqDatabase.DBServer-class.html#keys,Method Martel.Parser.MartelAttributeList.keys()=Martel.Parser.MartelAttributeList-class.html#keys"><a title="Bio.Crystal.Crystal.keys
Bio.EUtils.MultiDict._BaseMultiDict.keys
Bio.GenBank.NCBIDictionary.keys
Bio.Mindy.BaseDB.DictLookup.keys
Bio.Mindy.BaseDB.OpenDB.keys
Bio.Mindy.BerkeleyDB.PrimaryNamespace.keys
Bio.Mindy.BerkeleyDB.SecondaryNamespace.keys
Bio.Mindy.FlatDB.PrimaryNamespace.keys
Bio.Mindy.FlatDB.PrimaryTable.keys
Bio.Mindy.FlatDB.SecondaryNamespace.keys
Bio.Mindy.FlatDB.SecondaryTable.keys
Bio.PDB.AbstractPropertyMap.AbstractPropertyMap.keys
Bio.Prosite.ExPASyDictionary.keys
Bio.Prosite.Prodoc.ExPASyDictionary.keys
Bio.PubMed.Dictionary.keys
Bio.SwissProt.SProt.Dictionary.keys
Bio.SwissProt.SProt.ExPASyDictionary.keys
Bio.config.Registry.Registry.keys
BioSQL.BioSeqDatabase.BioSeqDatabase.keys
BioSQL.BioSeqDatabase.DBServer.keys
Martel.Parser.MartelAttributeList.keys" class="py-name" href="#" onclick="return doclink('link-339', 'keys', 'link-339');">keys</a></tt><tt class="py-op">(</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L580"></a><tt class="py-lineno">580</tt> <tt class="py-line"> <tt class="py-keyword">if</tt> <tt class="py-keyword">not</tt> <tt id="link-340" class="py-name"><a title="Bio.Encodings.IUPACEncoding.name" class="py-name" href="#" onclick="return doclink('link-340', 'name', 'link-338');">name</a></tt><tt class="py-op">.</tt><tt class="py-name">startswith</tt><tt class="py-op">(</tt><tt class="py-string">"__"</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
<a name="L581"></a><tt class="py-lineno">581</tt> <tt class="py-line"> <tt id="link-341" class="py-name"><a title="Bio.MarkovModel.this_module
Bio.pairwise2.this_module" class="py-name" href="#" onclick="return doclink('link-341', 'this_module', 'link-337');">this_module</a></tt><tt class="py-op">.</tt><tt class="py-name">__dict__</tt><tt class="py-op">[</tt><tt id="link-342" class="py-name"><a title="Bio.Encodings.IUPACEncoding.name" class="py-name" href="#" onclick="return doclink('link-342', 'name', 'link-338');">name</a></tt><tt class="py-op">]</tt> <tt class="py-op">=</tt> <tt class="py-name">cMarkovModel</tt><tt class="py-op">.</tt><tt class="py-name">__dict__</tt><tt class="py-op">[</tt><tt id="link-343" class="py-name"><a title="Bio.Encodings.IUPACEncoding.name" class="py-name" href="#" onclick="return doclink('link-343', 'name', 'link-338');">name</a></tt><tt class="py-op">]</tt> </tt>
<a name="L582"></a><tt class="py-lineno">582</tt> <tt class="py-line"> </tt><script type="text/javascript">
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