How to extract patristic distances from dendropy phylogenetic_distance_matrix












0















I have created a cophenetic distance matrix in dendropy using:



from dendropy.simulate import treesim
tree = treesim.birth_death_tree(birth_rate=1.0, death_rate=0.5, ntax=10)
pdm = tree.phylogenetic_distance_matrix()


However, having read the documentation and trying many things I cannot extract the actual matrix in a usable manner from the object "pdm"



NB there is a method as_data_table with this class that I am also unable to fathom










share|improve this question



























    0















    I have created a cophenetic distance matrix in dendropy using:



    from dendropy.simulate import treesim
    tree = treesim.birth_death_tree(birth_rate=1.0, death_rate=0.5, ntax=10)
    pdm = tree.phylogenetic_distance_matrix()


    However, having read the documentation and trying many things I cannot extract the actual matrix in a usable manner from the object "pdm"



    NB there is a method as_data_table with this class that I am also unable to fathom










    share|improve this question

























      0












      0








      0








      I have created a cophenetic distance matrix in dendropy using:



      from dendropy.simulate import treesim
      tree = treesim.birth_death_tree(birth_rate=1.0, death_rate=0.5, ntax=10)
      pdm = tree.phylogenetic_distance_matrix()


      However, having read the documentation and trying many things I cannot extract the actual matrix in a usable manner from the object "pdm"



      NB there is a method as_data_table with this class that I am also unable to fathom










      share|improve this question














      I have created a cophenetic distance matrix in dendropy using:



      from dendropy.simulate import treesim
      tree = treesim.birth_death_tree(birth_rate=1.0, death_rate=0.5, ntax=10)
      pdm = tree.phylogenetic_distance_matrix()


      However, having read the documentation and trying many things I cannot extract the actual matrix in a usable manner from the object "pdm"



      NB there is a method as_data_table with this class that I am also unable to fathom







      python dendropy






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked Nov 28 '18 at 15:25









      user3329732user3329732

      405




      405
























          1 Answer
          1






          active

          oldest

          votes


















          1














          as_data_table() returns an object of type dendropy.utility.container.DataTable. This DataTable is a custom container class, which implements lots of useful methods you can use to get at your data. You can read the source here to understand it:



          https://dendropy.org/_modules/dendropy/utility/container.html



          You can very quickly see the data in a format you can understand by looking at its _data variable:



          from dendropy.simulate import treesim
          import pprint


          tree = treesim.birth_death_tree(birth_rate=1.0, death_rate=0.5, ntax=10)
          pdm = tree.phylogenetic_distance_matrix()

          pp = pprint.PrettyPrinter(depth=2)
          pp.pprint(pdm.as_data_table()._data)


          Outputs:



          {'T1': {'T1': 0.0,
          'T10': 1.832709865628535,
          'T2': 2.2418431376329204,
          'T3': 1.8146189808922477,
          'T4': 1.832709865628535,
          'T5': 1.832709865628535,
          'T6': 0.5848837844916799,
          'T7': 0,
          'T8': 1.6307174196094565,
          'T9': 1.8146189808922477},
          'T10': {'T1': 1.832709865628535,
          'T10': 0.0,
          'T2': 2.2418431376329204,
          'T3': 1.832709865628535,
          'T4': 0.8434862029618123,
          'T5': 1.215095937098336,
          'T6': 1.832709865628535,
          'T7': 1.832709865628535,
          'T8': 1.832709865628535,
          'T9': 1.832709865628535},
          'T2': {'T1': 2.2418431376329204,
          'T10': 2.2418431376329204,
          'T2': 0.0,
          'T3': 2.2418431376329204,
          'T4': 2.2418431376329204,
          'T5': 2.2418431376329204,
          'T6': 2.2418431376329204,
          'T7': 2.2418431376329204,
          'T8': 2.2418431376329204,
          'T9': 2.2418431376329204},
          'T3': {'T1': 1.8146189808922477,
          'T10': 1.832709865628535,
          'T2': 2.2418431376329204,
          'T3': 0.0,
          'T4': 1.832709865628535,
          'T5': 1.832709865628535,
          'T6': 1.8146189808922477,
          'T7': 1.8146189808922477,
          'T8': 1.8146189808922477,
          'T9': 1.4811625503429378},
          'T4': {'T1': 1.832709865628535,
          'T10': 0.8434862029618123,
          'T2': 2.2418431376329204,
          'T3': 1.832709865628535,
          'T4': 0.0,
          'T5': 1.215095937098336,
          'T6': 1.832709865628535,
          'T7': 1.832709865628535,
          'T8': 1.832709865628535,
          'T9': 1.832709865628535},
          'T5': {'T1': 1.832709865628535,
          'T10': 1.215095937098336,
          'T2': 2.2418431376329204,
          'T3': 1.832709865628535,
          'T4': 1.215095937098336,
          'T5': 0.0,
          'T6': 1.832709865628535,
          'T7': 1.832709865628535,
          'T8': 1.832709865628535,
          'T9': 1.832709865628535},
          'T6': {'T1': 0.5848837844916799,
          'T10': 1.832709865628535,
          'T2': 2.2418431376329204,
          'T3': 1.8146189808922477,
          'T4': 1.832709865628535,
          'T5': 1.832709865628535,
          'T6': 0.0,
          'T7': 0.5848837844916799,
          'T8': 1.6307174196094565,
          'T9': 1.8146189808922477},
          'T7': {'T1': 0,
          'T10': 1.832709865628535,
          'T2': 2.2418431376329204,
          'T3': 1.8146189808922477,
          'T4': 1.832709865628535,
          'T5': 1.832709865628535,
          'T6': 0.5848837844916799,
          'T7': 0.0,
          'T8': 1.6307174196094565,
          'T9': 1.8146189808922477},
          'T8': {'T1': 1.6307174196094565,
          'T10': 1.832709865628535,
          'T2': 2.2418431376329204,
          'T3': 1.8146189808922477,
          'T4': 1.832709865628535,
          'T5': 1.832709865628535,
          'T6': 1.6307174196094565,
          'T7': 1.6307174196094565,
          'T8': 0.0,
          'T9': 1.8146189808922477},
          'T9': {'T1': 1.8146189808922477,
          'T10': 1.832709865628535,
          'T2': 2.2418431376329204,
          'T3': 1.4811625503429378,
          'T4': 1.832709865628535,
          'T5': 1.832709865628535,
          'T6': 1.8146189808922477,
          'T7': 1.8146189808922477,
          'T8': 1.8146189808922477,
          'T9': 0.0}}





          share|improve this answer























            Your Answer






            StackExchange.ifUsing("editor", function () {
            StackExchange.using("externalEditor", function () {
            StackExchange.using("snippets", function () {
            StackExchange.snippets.init();
            });
            });
            }, "code-snippets");

            StackExchange.ready(function() {
            var channelOptions = {
            tags: "".split(" "),
            id: "1"
            };
            initTagRenderer("".split(" "), "".split(" "), channelOptions);

            StackExchange.using("externalEditor", function() {
            // Have to fire editor after snippets, if snippets enabled
            if (StackExchange.settings.snippets.snippetsEnabled) {
            StackExchange.using("snippets", function() {
            createEditor();
            });
            }
            else {
            createEditor();
            }
            });

            function createEditor() {
            StackExchange.prepareEditor({
            heartbeatType: 'answer',
            autoActivateHeartbeat: false,
            convertImagesToLinks: true,
            noModals: true,
            showLowRepImageUploadWarning: true,
            reputationToPostImages: 10,
            bindNavPrevention: true,
            postfix: "",
            imageUploader: {
            brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
            contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
            allowUrls: true
            },
            onDemand: true,
            discardSelector: ".discard-answer"
            ,immediatelyShowMarkdownHelp:true
            });


            }
            });














            draft saved

            draft discarded


















            StackExchange.ready(
            function () {
            StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53522836%2fhow-to-extract-patristic-distances-from-dendropy-phylogenetic-distance-matrix%23new-answer', 'question_page');
            }
            );

            Post as a guest















            Required, but never shown

























            1 Answer
            1






            active

            oldest

            votes








            1 Answer
            1






            active

            oldest

            votes









            active

            oldest

            votes






            active

            oldest

            votes









            1














            as_data_table() returns an object of type dendropy.utility.container.DataTable. This DataTable is a custom container class, which implements lots of useful methods you can use to get at your data. You can read the source here to understand it:



            https://dendropy.org/_modules/dendropy/utility/container.html



            You can very quickly see the data in a format you can understand by looking at its _data variable:



            from dendropy.simulate import treesim
            import pprint


            tree = treesim.birth_death_tree(birth_rate=1.0, death_rate=0.5, ntax=10)
            pdm = tree.phylogenetic_distance_matrix()

            pp = pprint.PrettyPrinter(depth=2)
            pp.pprint(pdm.as_data_table()._data)


            Outputs:



            {'T1': {'T1': 0.0,
            'T10': 1.832709865628535,
            'T2': 2.2418431376329204,
            'T3': 1.8146189808922477,
            'T4': 1.832709865628535,
            'T5': 1.832709865628535,
            'T6': 0.5848837844916799,
            'T7': 0,
            'T8': 1.6307174196094565,
            'T9': 1.8146189808922477},
            'T10': {'T1': 1.832709865628535,
            'T10': 0.0,
            'T2': 2.2418431376329204,
            'T3': 1.832709865628535,
            'T4': 0.8434862029618123,
            'T5': 1.215095937098336,
            'T6': 1.832709865628535,
            'T7': 1.832709865628535,
            'T8': 1.832709865628535,
            'T9': 1.832709865628535},
            'T2': {'T1': 2.2418431376329204,
            'T10': 2.2418431376329204,
            'T2': 0.0,
            'T3': 2.2418431376329204,
            'T4': 2.2418431376329204,
            'T5': 2.2418431376329204,
            'T6': 2.2418431376329204,
            'T7': 2.2418431376329204,
            'T8': 2.2418431376329204,
            'T9': 2.2418431376329204},
            'T3': {'T1': 1.8146189808922477,
            'T10': 1.832709865628535,
            'T2': 2.2418431376329204,
            'T3': 0.0,
            'T4': 1.832709865628535,
            'T5': 1.832709865628535,
            'T6': 1.8146189808922477,
            'T7': 1.8146189808922477,
            'T8': 1.8146189808922477,
            'T9': 1.4811625503429378},
            'T4': {'T1': 1.832709865628535,
            'T10': 0.8434862029618123,
            'T2': 2.2418431376329204,
            'T3': 1.832709865628535,
            'T4': 0.0,
            'T5': 1.215095937098336,
            'T6': 1.832709865628535,
            'T7': 1.832709865628535,
            'T8': 1.832709865628535,
            'T9': 1.832709865628535},
            'T5': {'T1': 1.832709865628535,
            'T10': 1.215095937098336,
            'T2': 2.2418431376329204,
            'T3': 1.832709865628535,
            'T4': 1.215095937098336,
            'T5': 0.0,
            'T6': 1.832709865628535,
            'T7': 1.832709865628535,
            'T8': 1.832709865628535,
            'T9': 1.832709865628535},
            'T6': {'T1': 0.5848837844916799,
            'T10': 1.832709865628535,
            'T2': 2.2418431376329204,
            'T3': 1.8146189808922477,
            'T4': 1.832709865628535,
            'T5': 1.832709865628535,
            'T6': 0.0,
            'T7': 0.5848837844916799,
            'T8': 1.6307174196094565,
            'T9': 1.8146189808922477},
            'T7': {'T1': 0,
            'T10': 1.832709865628535,
            'T2': 2.2418431376329204,
            'T3': 1.8146189808922477,
            'T4': 1.832709865628535,
            'T5': 1.832709865628535,
            'T6': 0.5848837844916799,
            'T7': 0.0,
            'T8': 1.6307174196094565,
            'T9': 1.8146189808922477},
            'T8': {'T1': 1.6307174196094565,
            'T10': 1.832709865628535,
            'T2': 2.2418431376329204,
            'T3': 1.8146189808922477,
            'T4': 1.832709865628535,
            'T5': 1.832709865628535,
            'T6': 1.6307174196094565,
            'T7': 1.6307174196094565,
            'T8': 0.0,
            'T9': 1.8146189808922477},
            'T9': {'T1': 1.8146189808922477,
            'T10': 1.832709865628535,
            'T2': 2.2418431376329204,
            'T3': 1.4811625503429378,
            'T4': 1.832709865628535,
            'T5': 1.832709865628535,
            'T6': 1.8146189808922477,
            'T7': 1.8146189808922477,
            'T8': 1.8146189808922477,
            'T9': 0.0}}





            share|improve this answer




























              1














              as_data_table() returns an object of type dendropy.utility.container.DataTable. This DataTable is a custom container class, which implements lots of useful methods you can use to get at your data. You can read the source here to understand it:



              https://dendropy.org/_modules/dendropy/utility/container.html



              You can very quickly see the data in a format you can understand by looking at its _data variable:



              from dendropy.simulate import treesim
              import pprint


              tree = treesim.birth_death_tree(birth_rate=1.0, death_rate=0.5, ntax=10)
              pdm = tree.phylogenetic_distance_matrix()

              pp = pprint.PrettyPrinter(depth=2)
              pp.pprint(pdm.as_data_table()._data)


              Outputs:



              {'T1': {'T1': 0.0,
              'T10': 1.832709865628535,
              'T2': 2.2418431376329204,
              'T3': 1.8146189808922477,
              'T4': 1.832709865628535,
              'T5': 1.832709865628535,
              'T6': 0.5848837844916799,
              'T7': 0,
              'T8': 1.6307174196094565,
              'T9': 1.8146189808922477},
              'T10': {'T1': 1.832709865628535,
              'T10': 0.0,
              'T2': 2.2418431376329204,
              'T3': 1.832709865628535,
              'T4': 0.8434862029618123,
              'T5': 1.215095937098336,
              'T6': 1.832709865628535,
              'T7': 1.832709865628535,
              'T8': 1.832709865628535,
              'T9': 1.832709865628535},
              'T2': {'T1': 2.2418431376329204,
              'T10': 2.2418431376329204,
              'T2': 0.0,
              'T3': 2.2418431376329204,
              'T4': 2.2418431376329204,
              'T5': 2.2418431376329204,
              'T6': 2.2418431376329204,
              'T7': 2.2418431376329204,
              'T8': 2.2418431376329204,
              'T9': 2.2418431376329204},
              'T3': {'T1': 1.8146189808922477,
              'T10': 1.832709865628535,
              'T2': 2.2418431376329204,
              'T3': 0.0,
              'T4': 1.832709865628535,
              'T5': 1.832709865628535,
              'T6': 1.8146189808922477,
              'T7': 1.8146189808922477,
              'T8': 1.8146189808922477,
              'T9': 1.4811625503429378},
              'T4': {'T1': 1.832709865628535,
              'T10': 0.8434862029618123,
              'T2': 2.2418431376329204,
              'T3': 1.832709865628535,
              'T4': 0.0,
              'T5': 1.215095937098336,
              'T6': 1.832709865628535,
              'T7': 1.832709865628535,
              'T8': 1.832709865628535,
              'T9': 1.832709865628535},
              'T5': {'T1': 1.832709865628535,
              'T10': 1.215095937098336,
              'T2': 2.2418431376329204,
              'T3': 1.832709865628535,
              'T4': 1.215095937098336,
              'T5': 0.0,
              'T6': 1.832709865628535,
              'T7': 1.832709865628535,
              'T8': 1.832709865628535,
              'T9': 1.832709865628535},
              'T6': {'T1': 0.5848837844916799,
              'T10': 1.832709865628535,
              'T2': 2.2418431376329204,
              'T3': 1.8146189808922477,
              'T4': 1.832709865628535,
              'T5': 1.832709865628535,
              'T6': 0.0,
              'T7': 0.5848837844916799,
              'T8': 1.6307174196094565,
              'T9': 1.8146189808922477},
              'T7': {'T1': 0,
              'T10': 1.832709865628535,
              'T2': 2.2418431376329204,
              'T3': 1.8146189808922477,
              'T4': 1.832709865628535,
              'T5': 1.832709865628535,
              'T6': 0.5848837844916799,
              'T7': 0.0,
              'T8': 1.6307174196094565,
              'T9': 1.8146189808922477},
              'T8': {'T1': 1.6307174196094565,
              'T10': 1.832709865628535,
              'T2': 2.2418431376329204,
              'T3': 1.8146189808922477,
              'T4': 1.832709865628535,
              'T5': 1.832709865628535,
              'T6': 1.6307174196094565,
              'T7': 1.6307174196094565,
              'T8': 0.0,
              'T9': 1.8146189808922477},
              'T9': {'T1': 1.8146189808922477,
              'T10': 1.832709865628535,
              'T2': 2.2418431376329204,
              'T3': 1.4811625503429378,
              'T4': 1.832709865628535,
              'T5': 1.832709865628535,
              'T6': 1.8146189808922477,
              'T7': 1.8146189808922477,
              'T8': 1.8146189808922477,
              'T9': 0.0}}





              share|improve this answer


























                1












                1








                1







                as_data_table() returns an object of type dendropy.utility.container.DataTable. This DataTable is a custom container class, which implements lots of useful methods you can use to get at your data. You can read the source here to understand it:



                https://dendropy.org/_modules/dendropy/utility/container.html



                You can very quickly see the data in a format you can understand by looking at its _data variable:



                from dendropy.simulate import treesim
                import pprint


                tree = treesim.birth_death_tree(birth_rate=1.0, death_rate=0.5, ntax=10)
                pdm = tree.phylogenetic_distance_matrix()

                pp = pprint.PrettyPrinter(depth=2)
                pp.pprint(pdm.as_data_table()._data)


                Outputs:



                {'T1': {'T1': 0.0,
                'T10': 1.832709865628535,
                'T2': 2.2418431376329204,
                'T3': 1.8146189808922477,
                'T4': 1.832709865628535,
                'T5': 1.832709865628535,
                'T6': 0.5848837844916799,
                'T7': 0,
                'T8': 1.6307174196094565,
                'T9': 1.8146189808922477},
                'T10': {'T1': 1.832709865628535,
                'T10': 0.0,
                'T2': 2.2418431376329204,
                'T3': 1.832709865628535,
                'T4': 0.8434862029618123,
                'T5': 1.215095937098336,
                'T6': 1.832709865628535,
                'T7': 1.832709865628535,
                'T8': 1.832709865628535,
                'T9': 1.832709865628535},
                'T2': {'T1': 2.2418431376329204,
                'T10': 2.2418431376329204,
                'T2': 0.0,
                'T3': 2.2418431376329204,
                'T4': 2.2418431376329204,
                'T5': 2.2418431376329204,
                'T6': 2.2418431376329204,
                'T7': 2.2418431376329204,
                'T8': 2.2418431376329204,
                'T9': 2.2418431376329204},
                'T3': {'T1': 1.8146189808922477,
                'T10': 1.832709865628535,
                'T2': 2.2418431376329204,
                'T3': 0.0,
                'T4': 1.832709865628535,
                'T5': 1.832709865628535,
                'T6': 1.8146189808922477,
                'T7': 1.8146189808922477,
                'T8': 1.8146189808922477,
                'T9': 1.4811625503429378},
                'T4': {'T1': 1.832709865628535,
                'T10': 0.8434862029618123,
                'T2': 2.2418431376329204,
                'T3': 1.832709865628535,
                'T4': 0.0,
                'T5': 1.215095937098336,
                'T6': 1.832709865628535,
                'T7': 1.832709865628535,
                'T8': 1.832709865628535,
                'T9': 1.832709865628535},
                'T5': {'T1': 1.832709865628535,
                'T10': 1.215095937098336,
                'T2': 2.2418431376329204,
                'T3': 1.832709865628535,
                'T4': 1.215095937098336,
                'T5': 0.0,
                'T6': 1.832709865628535,
                'T7': 1.832709865628535,
                'T8': 1.832709865628535,
                'T9': 1.832709865628535},
                'T6': {'T1': 0.5848837844916799,
                'T10': 1.832709865628535,
                'T2': 2.2418431376329204,
                'T3': 1.8146189808922477,
                'T4': 1.832709865628535,
                'T5': 1.832709865628535,
                'T6': 0.0,
                'T7': 0.5848837844916799,
                'T8': 1.6307174196094565,
                'T9': 1.8146189808922477},
                'T7': {'T1': 0,
                'T10': 1.832709865628535,
                'T2': 2.2418431376329204,
                'T3': 1.8146189808922477,
                'T4': 1.832709865628535,
                'T5': 1.832709865628535,
                'T6': 0.5848837844916799,
                'T7': 0.0,
                'T8': 1.6307174196094565,
                'T9': 1.8146189808922477},
                'T8': {'T1': 1.6307174196094565,
                'T10': 1.832709865628535,
                'T2': 2.2418431376329204,
                'T3': 1.8146189808922477,
                'T4': 1.832709865628535,
                'T5': 1.832709865628535,
                'T6': 1.6307174196094565,
                'T7': 1.6307174196094565,
                'T8': 0.0,
                'T9': 1.8146189808922477},
                'T9': {'T1': 1.8146189808922477,
                'T10': 1.832709865628535,
                'T2': 2.2418431376329204,
                'T3': 1.4811625503429378,
                'T4': 1.832709865628535,
                'T5': 1.832709865628535,
                'T6': 1.8146189808922477,
                'T7': 1.8146189808922477,
                'T8': 1.8146189808922477,
                'T9': 0.0}}





                share|improve this answer













                as_data_table() returns an object of type dendropy.utility.container.DataTable. This DataTable is a custom container class, which implements lots of useful methods you can use to get at your data. You can read the source here to understand it:



                https://dendropy.org/_modules/dendropy/utility/container.html



                You can very quickly see the data in a format you can understand by looking at its _data variable:



                from dendropy.simulate import treesim
                import pprint


                tree = treesim.birth_death_tree(birth_rate=1.0, death_rate=0.5, ntax=10)
                pdm = tree.phylogenetic_distance_matrix()

                pp = pprint.PrettyPrinter(depth=2)
                pp.pprint(pdm.as_data_table()._data)


                Outputs:



                {'T1': {'T1': 0.0,
                'T10': 1.832709865628535,
                'T2': 2.2418431376329204,
                'T3': 1.8146189808922477,
                'T4': 1.832709865628535,
                'T5': 1.832709865628535,
                'T6': 0.5848837844916799,
                'T7': 0,
                'T8': 1.6307174196094565,
                'T9': 1.8146189808922477},
                'T10': {'T1': 1.832709865628535,
                'T10': 0.0,
                'T2': 2.2418431376329204,
                'T3': 1.832709865628535,
                'T4': 0.8434862029618123,
                'T5': 1.215095937098336,
                'T6': 1.832709865628535,
                'T7': 1.832709865628535,
                'T8': 1.832709865628535,
                'T9': 1.832709865628535},
                'T2': {'T1': 2.2418431376329204,
                'T10': 2.2418431376329204,
                'T2': 0.0,
                'T3': 2.2418431376329204,
                'T4': 2.2418431376329204,
                'T5': 2.2418431376329204,
                'T6': 2.2418431376329204,
                'T7': 2.2418431376329204,
                'T8': 2.2418431376329204,
                'T9': 2.2418431376329204},
                'T3': {'T1': 1.8146189808922477,
                'T10': 1.832709865628535,
                'T2': 2.2418431376329204,
                'T3': 0.0,
                'T4': 1.832709865628535,
                'T5': 1.832709865628535,
                'T6': 1.8146189808922477,
                'T7': 1.8146189808922477,
                'T8': 1.8146189808922477,
                'T9': 1.4811625503429378},
                'T4': {'T1': 1.832709865628535,
                'T10': 0.8434862029618123,
                'T2': 2.2418431376329204,
                'T3': 1.832709865628535,
                'T4': 0.0,
                'T5': 1.215095937098336,
                'T6': 1.832709865628535,
                'T7': 1.832709865628535,
                'T8': 1.832709865628535,
                'T9': 1.832709865628535},
                'T5': {'T1': 1.832709865628535,
                'T10': 1.215095937098336,
                'T2': 2.2418431376329204,
                'T3': 1.832709865628535,
                'T4': 1.215095937098336,
                'T5': 0.0,
                'T6': 1.832709865628535,
                'T7': 1.832709865628535,
                'T8': 1.832709865628535,
                'T9': 1.832709865628535},
                'T6': {'T1': 0.5848837844916799,
                'T10': 1.832709865628535,
                'T2': 2.2418431376329204,
                'T3': 1.8146189808922477,
                'T4': 1.832709865628535,
                'T5': 1.832709865628535,
                'T6': 0.0,
                'T7': 0.5848837844916799,
                'T8': 1.6307174196094565,
                'T9': 1.8146189808922477},
                'T7': {'T1': 0,
                'T10': 1.832709865628535,
                'T2': 2.2418431376329204,
                'T3': 1.8146189808922477,
                'T4': 1.832709865628535,
                'T5': 1.832709865628535,
                'T6': 0.5848837844916799,
                'T7': 0.0,
                'T8': 1.6307174196094565,
                'T9': 1.8146189808922477},
                'T8': {'T1': 1.6307174196094565,
                'T10': 1.832709865628535,
                'T2': 2.2418431376329204,
                'T3': 1.8146189808922477,
                'T4': 1.832709865628535,
                'T5': 1.832709865628535,
                'T6': 1.6307174196094565,
                'T7': 1.6307174196094565,
                'T8': 0.0,
                'T9': 1.8146189808922477},
                'T9': {'T1': 1.8146189808922477,
                'T10': 1.832709865628535,
                'T2': 2.2418431376329204,
                'T3': 1.4811625503429378,
                'T4': 1.832709865628535,
                'T5': 1.832709865628535,
                'T6': 1.8146189808922477,
                'T7': 1.8146189808922477,
                'T8': 1.8146189808922477,
                'T9': 0.0}}






                share|improve this answer












                share|improve this answer



                share|improve this answer










                answered Nov 28 '18 at 15:42









                Rob BrichenoRob Bricheno

                2,450420




                2,450420
































                    draft saved

                    draft discarded




















































                    Thanks for contributing an answer to Stack Overflow!


                    • Please be sure to answer the question. Provide details and share your research!

                    But avoid



                    • Asking for help, clarification, or responding to other answers.

                    • Making statements based on opinion; back them up with references or personal experience.


                    To learn more, see our tips on writing great answers.




                    draft saved


                    draft discarded














                    StackExchange.ready(
                    function () {
                    StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53522836%2fhow-to-extract-patristic-distances-from-dendropy-phylogenetic-distance-matrix%23new-answer', 'question_page');
                    }
                    );

                    Post as a guest















                    Required, but never shown





















































                    Required, but never shown














                    Required, but never shown












                    Required, but never shown







                    Required, but never shown

































                    Required, but never shown














                    Required, but never shown












                    Required, but never shown







                    Required, but never shown







                    Popular posts from this blog

                    Contact image not getting when fetch all contact list from iPhone by CNContact

                    count number of partitions of a set with n elements into k subsets

                    A CLEAN and SIMPLE way to add appendices to Table of Contents and bookmarks