nickynicolson

Peter investigates the taxonomy of Diplazium tomentosum.

//console

He starts with one of the types from the Leiden herbarium (http://plants.jstor.org/specimen/l0051073):

[source,cypher]
----
CREATE (s:Specimen{id:"L0051073"
    ,jstorUrl:'http://plants.jstor.org/specimen/l0051073'

nickynicolson

= The taxonomic mind-mapper
Nicky Nicolson, Peter Hovenkamp 
:neo4j-version: 2.1.0
:author: Nicky Nicolson
:twitter: nickynicolson
 
== Domain
We investigate the use of the scheme in: https://docs.google.com/document/d/1FIxNrrGrIZs0l4QJEdGfctXbYVL4cQhKspmMEHmKAGg/edit with a use case in the taxonomy of Diplazium tomentosum (https://docs.google.com/document/d/1vni44RBwGNZ7iRCFf243NtcD-7xwjHrDeAPehato7KY/edit?usp=sharing)

== Data model

nickynicolson

// Create meta-graph with orphan counts
MATCH (n)
/* ugly string replace to convert collection of labels to colon delimited string */
WITH replace(replace(replace(replace(str(labels(n)),'[',''),']',''),'"',''),',',':') AS l, count(distinct n) AS c
MERGE (mn:Meta_Node {name:l,count:c})
WITH mn
MATCH (a)-[r]->(b)   
WITH replace(replace(replace(replace(str(labels(a)),'[',''),']',''),'"',''),',',':') AS a_labels
	, count(distinct a) AS from_count
	, type(r) AS rel_type

nickynicolson

// Use Gists to store code you would like to remember later on
console.log(window); // log the "window" object to the console

nickynicolson

This graph gist demonstrates use of Jaccard calculation to determine similarity between two sets of nodes

nickynicolson

nickynicolson

import urllib
import urllib2

try:
  # Base url for the TNRS match_names API
  url = 'http://api.opentreeoflife.org/v2/tnrs/match_names'
  # Encode data value to be looked up as an array of names:
  data = '{"names": ["'+value+'"]}'
  print "Looking up: " + data
  # Set HTTP headers:

nickynicolson

<?xml version="1.0" encoding="UTF-8"?>
<xsl:stylesheet version="1.0" xmlns:xsl="http://www.w3.org/1999/XSL/Transform">
<xsl:output method="text" indent="yes" encoding="UTF-8"/>
<xsl:variable name="delimiter" select="'&#09;'"/>
<xsl:variable name="newline" select="'&#10;'"/>

<xsl:template match="/">
	<!-- header line -->
	<xsl:value-of select="concat('primary_accession',$delimiter,'date_created',$delimiter,'date_last_amended', $delimiter, 'definition', $delimiter, 'title', $delimiter, 'reference', $delimiter, 'doi', $delimiter, 'specimen_voucher', $delimiter, 'bio_material', $delimiter, 'organism', $newline)"/>
	<!-- data -->

nickynicolson

from sklearn.metrics import confusion_matrix
import pandas as pd

def cm2df(cm, labels):
    df = pd.DataFrame()
    # rows
    for i, row_label in enumerate(labels):
        rowdata={}
        # columns
        for j, col_label in enumerate(labels): 

nickynicolson

import networkx as nx
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import mplleaflet
import sys

def main():
    inputfile=sys.argv[1]
    outputfile_base=sys.argv[2]