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Commit 7ed27902 authored by Ehlers, Katja's avatar Ehlers, Katja
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Merge branch 'main' into 'output' 

please

See merge request bax9187/projekt-cis-biochemie-2021-22!6
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verarbeitung/get_pub_from_input.py 0 → 100644
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# -*- coding: utf-8 -*-
"""
A function to return an object of Type Publication for a given doi
"""
__authors__ = "Donna Löding, Alina Molkentin, Xinyi Tang, Judith Große, Malte Schokolowski"
__email__ = "cis-project2021@zbh.uni-hamburg.de"
__status__ = "Production"
#__copyright__ = ""
#__credits__ = ["", "", "", ""]
#__license__ = ""
#__version__ = ""
#__maintainer__ = ""
import sys
from pathlib import Path
sys.path.append("../")
from input.interface import InputInterface as Input
from verarbeitung.test.input_test import input_test_func
def get_pub(pub_doi, test_var):
'''
:param pub_doi: input doi to get Publication object for
:type pub_doi: String
:param test_var: variable to differenciate between test and url call
:type test_var: boolean
function to return an object of type Publication for given input doi depending on whether its a test or url doi
'''
#checks if it's a test and chooses appropiate function
if(test_var):
pub = input_test_func(pub_doi)
#checks that it isnt a test and chooses standart-input function
else:
inter = Input()
try:
pub = inter.get_publication(pub_doi) #creates an object of class Publication
except AttributeError:
pub = inter.get_publication(pub_doi)
except ValueError:
return(ValueError)
except IndexError:
return(IndexError)
return(pub)
\ No newline at end of file
verarbeitung/input_test.py deleted 100644 → 0
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class Publication:
def __init__(self, doi_url, title, contributors, journal, publication_date, references, citations, group):
self.doi_url = doi_url
self.title = title
self.contributors = contributors
self.journal = journal
self.publication_date = publication_date
if references is None:
self.references = []
else:
self.references = ref(references)
if citations is None:
self.citations = []
else:
self.citations = cit(citations)
self.group = group
class Citation:
def __init__(self,doi_url, title, contributors, journal, publication_date):
self.doi_url = doi_url
self.title = title
self.contributors = contributors
self.journal = journal
self.publication_date = publication_date
class Reference:
def __init__(self,doi_url, title, contributors, journal, publication_date):
self.doi_url = doi_url
self.title = title
self.contributors = contributors
self.journal = journal
self.publication_date = publication_date
def input_test_func(pub_doi):
for array in list_of_arrays:
if pub_doi == array[0]:
pub = Publication(array[0], array[1], array[2], array[3], array[4], array[5], array[6], array[7])
return pub
def cit(list_doi):
cits = []
for doi_url in list_doi:
for array in list_of_arrays:
if doi_url == array[0]:
cits.append(Citation(array[0], array[1], array[2], array[3], array[4]))
return cits
def ref(list_doi):
refs = []
for doi_url in list_doi:
for array in list_of_arrays:
if doi_url == array[0]:
refs.append(Citation(array[0], array[1], array[2], array[3], array[4]))
return refs
beispiel1 = ['doi1', 'title1', ['contributor1'], 'journal1', 'date1', ['doi2'], ['doi3'], '']
beispiel2 = ['doi2', 'title2', ['contributor2'], 'journal2', 'date2', [], ['doi1'], '']
beispiel3 = ['doi3', 'title3', ['contributor3'], 'journal3', 'date3', ['doi1'], [], '']
zyklus1 = ['doiz1', 'titlez1', ['contributorz1.1', 'contributorz1.2'], 'journalz1', 'datez1', ['doiz2'], ['doiz2'], '']
zyklus2 = ['doiz2', 'titlez2', ['contributorz2.1', 'contributorz2.2'], 'journalz2', 'datez2', ['doiz1'], ['doiz1'], '']
inner_edge1 = ['doi_ie1', 'title_ie1', ['contributor_ie1.1', 'contributor_ie1.2'], 'journal_ie1', 'date_ie1', ['doi_ie2'], ['doi_ie3'], '']
inner_edge2 = ['doi_ie2', 'title_ie2', ['contributor_ie2.1', 'contributor_ie2.2'], 'journal_ie2', 'date_ie2', [], ['doi_ie1','doi_ie3'], '']
inner_edge3 = ['doi_ie3', 'titlez_ie3', ['contributor_ie3.1', 'contributor_ie3.2'], 'journal_ie3', 'date_ie3', ['doi_ie1','doi_ie2'], [], '']
right_height01 = ['doi_h01', 'title_h01', ['contributor_h01'], 'journal_h01', 'date_h01', [], [], '']
right_height02 = ['doi_h02', 'title_h02', ['contributor_h02'], 'journal_h02', 'date_h02', [], ['doi_h1'], '']
right_height1 = ['doi_h1', 'title_h1', ['contributor_h1'], 'journal_h1', 'date_h1', [], ['doi_h2'], '']
right_height2 = ['doi_h2', 'title_h2', ['contributor_h2'], 'journal_h2', 'date_h2', [], ['doi_h3'], '']
right_height3 = ['doi_h3', 'title_h3', ['contributor_h3'], 'journal_h3', 'date_h3', [], [], '']
right_depth01 = ['doi_d01', 'title_d01', ['contributor_d01'], 'journal_d01', 'date_d01', [], [], '']
right_depth02 = ['doi_d02', 'title_d02', ['contributor_d02'], 'journal_d02', 'date_d02', ['doi_d1'], [], '']
right_depth1 = ['doi_d1', 'title_d1', ['contributor_d1'], 'journal_d1', 'date_d1', ['doi_d2'], [], '']
right_depth2 = ['doi_d2', 'title_d2', ['contributor_d2'], 'journal_d2', 'date_d2', ['doi_d3'], [], '']
right_depth3 = ['doi_d3', 'title_d3', ['contributor_d3'], 'journal_d3', 'date_d3', [], [], '']
list_of_arrays = [beispiel1, beispiel2, beispiel3, zyklus1, zyklus2, inner_edge1, inner_edge2, inner_edge3, right_height01, right_height02, right_height1, right_height2, right_height3, right_depth01, right_depth02, right_depth1, right_depth2, right_depth3]
verarbeitung/json_text.json 0 → 100644
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\ No newline at end of file
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{"nodes": [{"doi": "doi_lg_1_i", "name": "title_lg_1_i", "author": ["contributor_lg_1_i"], "year": "date_lg_1_i", "journal": "journal_lg_1_i", "group": "Input", "depth": 0, "citations": 2}, {"doi": "doi_lg_1_d11", "name": "title_lg_1_d11", "author": ["contributor_lg_1_d11"], "year": "date_lg_1_d11", "journal": "journal_lg_1_d11", "group": "Reference", "depth": -1, "citations": 1}, {"doi": "doi_lg_1_d12", "name": "title_lg_1_d12", "author": ["contributor_lg_1_d12"], "year": "date_lg_1_d12", "journal": "journal_lg_1_d12", "group": "Reference", "depth": -1, "citations": 2}, {"doi": "doi_lg_1_h11", "name": "title_lg_1_h11", "author": ["contributor_lg_1_h11"], "year": "date_lg_1_h11", "journal": "journal_lg_1_h11", "group": "Citedby", "depth": 1, "citations": 2}, {"doi": "doi_lg_1_h12", "name": "title_lg_1_h12", "author": ["contributor_lg_1_h12"], "year": "date_lg_1_h12", "journal": "journal_lg_1_h12", "group": "Citedby", "depth": 1, "citations": 2}, {"doi": "doi_lg_1_h21", "name": "title_lg_1_h21", "author": ["contributor_lg_1_h21"], "year": "date_lg_1_h21", "journal": "journal_lg_1_h21", "group": "Citedby", "depth": 2, "citations": 0}, {"doi": "doi_lg_1_h22", "name": "title_lg_1_h22", "author": ["contributor_lg_1_h22"], "year": "date_lg_1_h22", "journal": "journal_lg_1_h22", "group": "Citedby", "depth": 2, "citations": 0}, {"doi": "doi_lg_1_h23", "name": "title_lg_1_h23", "author": ["contributor_lg_1_h23"], "year": "date_lg_1_h23", "journal": "journal_lg_1_h23", "group": "Citedby", "depth": 2, "citations": 0}, {"doi": "doi_lg_1_d21", "name": "title_lg_1_d21", "author": ["contributor_lg_1_d21"], "year": "date_lg_1_d21", "journal": "journal_lg_1_d21", "group": "Reference", "depth": -2, "citations": 2}, {"doi": "doi_lg_1_d22", "name": "title_lg_1_d22", "author": ["contributor_lg_1_d22"], "year": "date_lg_1_d22", "journal": "journal_lg_1_d22", "group": "Reference", "depth": -2, "citations": 2}, {"doi": "doi_lg_1_d23", "name": "title_lg_1_d23", "author": ["contributor_lg_1_d23"], "year": "date_lg_1_d23", "journal": "journal_lg_1_d23", "group": "Reference", "depth": -2, "citations": 2}], "links": [{"source": "doi_lg_1_i", "target": "doi_lg_1_d11"}, {"source": "doi_lg_1_i", "target": "doi_lg_1_d12"}, {"source": "doi_lg_1_h11", "target": "doi_lg_1_i"}, {"source": "doi_lg_1_h12", "target": "doi_lg_1_i"}, {"source": "doi_lg_1_h21", "target": "doi_lg_1_h11"}, {"source": "doi_lg_1_h22", "target": "doi_lg_1_h11"}, {"source": "doi_lg_1_h22", "target": "doi_lg_1_h12"}, {"source": "doi_lg_1_h23", "target": "doi_lg_1_h12"}, {"source": "doi_lg_1_d11", "target": "doi_lg_1_d21"}, {"source": "doi_lg_1_d11", "target": "doi_lg_1_d22"}, {"source": "doi_lg_1_d21", "target": "doi_lg_1_d22"}, {"source": "doi_lg_1_d22", "target": "doi_lg_1_d21"}, {"source": "doi_lg_1_d12", "target": "doi_lg_1_d23"}, {"source": "doi_lg_1_h12", "target": "doi_lg_1_d12"}]}
\ No newline at end of file
verarbeitung/process_main.py 0 → 100644
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# -*- coding: utf-8 -*-
"""
main function to call to generate a graph representing citations between multiple ACS/Nature journals
"""
__authors__ = "Donna Löding, Alina Molkentin, Xinyi Tang, Judith Große, Malte Schokolowski"
__email__ = "cis-project2021@zbh.uni-hamburg.de"
__status__ = "Production"
#__copyright__ = ""
#__credits__ = ["", "", "", ""]
#__license__ = ""
#__version__ = ""
#__maintainer__ = ""
import sys
from pathlib import Path
from os import error
sys.path.append("../")
from verarbeitung.construct_new_graph.export_to_json import output_to_json
from verarbeitung.construct_new_graph.initialize_graph import init_graph_construction
from verarbeitung.update_graph.update_graph import update_graph
def Processing(url_list, search_depth, search_height, json_file = 'json_text.json'):
'''
:param url_list: list of urls to construct publication graph for
:type url_list: List[String]
:param search_depth: maximum depth to search for references
:type search_depth: int
:param search_height: maximum height to search for citations
:type search_height: int
:param json_file: file to export graph to
:type json_file: String
main function to construct new or updated publication graphs
'''
# updates graph if json file is known in directory otherwise starts new graph construction
try:
with open(json_file) as f:
nodes, edges = update_graph(url_list, json_file, search_depth, search_height)
except IOError:
nodes, edges = init_graph_construction(url_list, search_depth, search_height)
# exports graph to given json file name
output_to_json(nodes, edges, json_file)
\ No newline at end of file
verarbeitung/start_script.py 0 → 100644
+ 11
− 0
View file @ 7ed27902
import sys
from pathlib import Path
from verarbeitung.process_main import Processing
from verarbeitung.dev_files.print_graph_test import try_known_publications, try_delete_nodes
doi_list = []
doi_list.append('https://pubs.acs.org/doi/10.1021/acs.jcim.9b00249')
#doi_list.append('https://doi.org/10.1021/acs.jcim.9b00249')
doi_list.append('https://pubs.acs.org/doi/10.1021/acs.jcim.1c00203')
Processing(doi_list, 2, 2, 'test.json')
\ No newline at end of file
verarbeitung/test.json 0 → 100644
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− 0
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{"nodes": [{"doi": "https://doi.org/10.1021/acs.jcim.9b00249", "name": "Comparing Molecular Patterns Using the Example of SMARTS: Applications and Filter Collection Analysis", "author": ["Emanuel S. R. Ehmki", "Robert Schmidt", "Farina Ohm", "Matthias Rarey"], "year": "May 24, 2019", "journal": "Journal of Chemical Information and Modeling", "group": "Input", "depth": 0, "citations": 5}, {"doi": "https://doi.org/10.1021/acs.chemrev.1c00107", "name": "Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems", "author": ["John A. Keith", "Valentin Vassilev-Galindo", "Bingqing Cheng", "Stefan Chmiela", "Michael Gastegger", "Klaus-Robert M\u00fcller", "Alexandre Tkatchenko"], "year": "July 7, 2021", "journal": "Chem. Rev.", "group": "Citedby", "depth": 1, "citations": 2}, {"doi": "https://doi.org/10.1021/acs.jcim.0c00741", "name": "Disconnected Maximum Common Substructures under Constraints", "author": ["Robert Schmidt", "Florian Krull", "Anna Lina Heinzke", "Matthias Rarey"], "year": "December 16, 2020", "journal": "Journal of Chemical Information and Modeling", "group": "Citedby", "depth": 1, "citations": 0}, {"doi": "https://doi.org/10.1021/acs.jmedchem.0c01332", "name": "Evolution of Novartis\u2019 Small Molecule Screening Deck Design", "author": ["Ansgar Schuffenhauer", "Nadine Schneider", "Samuel Hintermann", "Douglas Auld", "Jutta Blank", "Simona Cotesta", "Caroline Engeloch", "Nikolas Fechner", "Christoph Gaul", "Jerome Giovannoni", "Johanna Jansen", "John Joslin", "Philipp Krastel", "Eugen Lounkine", "John Manchester", "Lauren G. Monovich", "Anna Paola Pelliccioli", "Manuel Schwarze", "Michael D. Shultz", "Nikolaus Stiefl", "Daniel K. Baeschlin"], "year": "November 3, 2020", "journal": "Journal of Medicinal Chemistry", "group": "Citedby", "depth": 1, "citations": 8}, {"doi": "https://doi.org/10.1021/acs.jcim.9b00250", "name": "Comparing Molecular Patterns Using the Example of SMARTS: Theory and Algorithms", "author": ["Robert Schmidt", "Emanuel S. R. Ehmki", "Farina Ohm", "Hans-Christian Ehrlich", "Andriy Mashychev", "Matthias Rarey"], "year": "May 23, 2019", "journal": "Journal of Chemical Information and Modeling", "group": "Citedby", "depth": 1, "citations": 12}, {"doi": "https://doi.org/10.1021/acs.jcim.1c00203", "name": "AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings", "author": ["Jerome Eberhardt", "Diogo Santos-Martins", "Andreas F. Tillack", "Stefano Forli"], "year": "July 19, 2021", "journal": "Journal of Chemical Information and Modeling", "group": "Input", "depth": 0, "citations": 1}, {"doi": "https://doi.org/10.1021/acs.jctc.0c01006", "name": "Accelerating AutoDock4 with GPUs and Gradient-Based Local Search", "author": ["Diogo Santos-Martins", "Leonardo Solis-Vasquez", "Andreas F Tillack", "Michel F Sanner", "Andreas Koch", "Stefano Forli"], "year": "January 6, 2021", "journal": "Journal of Chemical Theory and Computation", "group": "Reference", "depth": -1, "citations": 14}, {"doi": "https://doi.org/10.1021/acs.jctc.9b00557", "name": "Docking Flexible Cyclic Peptides with AutoDock CrankPep", "author": ["Yuqi Zhang", "Michel F. Sanner"], "year": "September 11, 2019", "journal": "Journal of Chemical Theory and Computation", "group": "Reference", "depth": -1, "citations": 9}, {"doi": "https://doi.org/10.1021/ci300604z", "name": "Lessons Learned in Empirical Scoring with smina from the CSAR 2011 Benchmarking Exercise", "author": ["David Ryan Koes", "Matthew P. Baumgartner", "Carlos J. Camacho"], "year": "February 4, 2013", "journal": "Journal of Chemical Information and Modeling", "group": "Reference", "depth": -1, "citations": 100}, {"doi": "https://doi.org/10.1021/acs.jctc.5b00834", "name": "Vina-Carb: Improving Glycosidic Angles during Carbohydrate Docking", "author": ["Anita K. Nivedha", "David F. Thieker", "Spandana Makeneni", "Huimin Hu", "Robert J. 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Olson"], "year": "June 15, 2014", "journal": "Journal of Chemical Information and Modeling", "group": "Reference", "depth": -1, "citations": 100}, {"doi": "https://doi.org/10.1021/jm2005145", "name": "A Force Field with Discrete Displaceable Waters and Desolvation Entropy for Hydrated Ligand Docking", "author": ["Stefano Forli", "Arthur J. Olson"], "year": "December 9, 2011", "journal": "Journal of Medicinal Chemistry", "group": "Reference", "depth": -1, "citations": 100}, {"doi": "https://doi.org/10.1021/ci300399w", "name": "Consensus Docking: Improving the Reliability of Docking in a Virtual Screening Context", "author": ["Douglas R. Houston", "Malcolm D. Walkinshaw"], "year": "January 27, 2013", "journal": "Journal of Chemical Information and Modeling", "group": "Reference", "depth": -1, "citations": 100}, {"doi": "https://doi.org/10.1021/jp9723574", "name": "Inhomogeneous Fluid Approach to Solvation Thermodynamics. 1. 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# Projekt CiS-Projekt 2021/22
Directory to contain unittests for construction and update of publication graph
## Files in directory
input_test.py
- Immitiert die Arbeit der Input Gruppe auf eine sehr einfache Weise.
Beispielhafte Informationen werden aus Strings herausgelesen und als Klassenobjekt gespeichert.
construct_graph_unittest.py
- Führt diverse Tests zur Konstruktion des Graphen ohne Vorkenntnisse mit eigenen Beispielen und
unserer Input_test Funktion aus.
update_graph_unittest.py
- Führt diverse Tests zum Updaten eines alten Graphs mit aktualisierter Input Liste mit eigenen
Beispielen und unserer Input_test Funktion aus.
## Authors
- Donna Löding
- Alina Molkentin
- Xinyi Tang
- Judith Große
- Malte Schokolowski
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verarbeitung/test/__init__.py 0 → 100644
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verarbeitung/test/construct_graph_unittest.py 0 → 100644
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import unittest
import sys
from pathlib import Path
sys.path.append("../")
from verarbeitung.construct_new_graph.initialize_graph import init_graph_construction
class ConstructionTest(unittest.TestCase):
maxDiff = None
def testCycle(self):
nodes, edges = init_graph_construction(['doiz1'],1,1,True)
doi_nodes = keep_only_dois(nodes)
self.assertCountEqual(doi_nodes, ['doiz1', 'doiz2'])
self.assertCountEqual(edges, [['doiz1', 'doiz2'], ['doiz2', 'doiz1']])
nodes, edges = init_graph_construction(['doiz1'],2,2,True)
doi_nodes = keep_only_dois(nodes)
self.assertCountEqual(doi_nodes, ['doiz1', 'doiz2'])
self.assertCountEqual(edges, [['doiz2', 'doiz1'], ['doiz1', 'doiz2']])
#def testBigCycle(self):
#def testEmptyHeight(self):
#def testEmptyDepth(self):
def testEmptyDepthHeight(self):
nodes, edges = init_graph_construction(['doi1'],0,0,True)
doi_nodes = keep_only_dois(nodes)
self.assertCountEqual(doi_nodes,['doi1'])
self.assertCountEqual(edges, [])
nodes, edges = init_graph_construction(['doi1', 'doi2'],0,0,True)
doi_nodes = keep_only_dois(nodes)
self.assertCountEqual(doi_nodes, ['doi1','doi2'])
self.assertCountEqual(edges, [['doi1', 'doi2']])
nodes, edges = init_graph_construction(['doi1', 'doi2', 'doi3'],0,0,True)
doi_nodes = keep_only_dois(nodes)
self.assertCountEqual(doi_nodes, ['doi1','doi2', 'doi3'])
self.assertCountEqual(edges, [['doi3', 'doi1'], ['doi1', 'doi2']])
def testInnerEdges(self):
nodes, edges = init_graph_construction(['doi_ie1'],1,1,True)
doi_nodes = keep_only_dois(nodes)
self.assertCountEqual(doi_nodes,['doi_ie1','doi_ie2','doi_ie3'])
self.assertCountEqual(edges,[['doi_ie1','doi_ie2'],['doi_ie3','doi_ie1'],['doi_ie3','doi_ie2']])
def testRightHeight(self):
nodes, edges = init_graph_construction(['doi_h01'],1,0,True)
doi_nodes = keep_only_dois(nodes)
self.assertCountEqual(doi_nodes,['doi_h01'])
self.assertCountEqual(edges, [])
nodes, edges = init_graph_construction(['doi_h02'],1,0,True)
doi_nodes = keep_only_dois(nodes)
self.assertCountEqual(doi_nodes,['doi_h02','doi_h1'])
self.assertCountEqual(edges, [['doi_h1','doi_h02']])
nodes, edges = init_graph_construction(['doi_h02'],2,0,True)
doi_nodes = keep_only_dois(nodes)
self.assertCountEqual(doi_nodes,['doi_h02','doi_h1','doi_h2'])
self.assertCountEqual(edges, [['doi_h1','doi_h02'], ['doi_h2','doi_h1']])
def testRightDepth(self):
nodes, edges = init_graph_construction(['doi_d01'],0,1,True)
doi_nodes = keep_only_dois(nodes)
self.assertCountEqual(doi_nodes,['doi_d01'])
self.assertCountEqual(edges, [])
nodes, edges = init_graph_construction(['doi_d02'],0,1,True)
doi_nodes = keep_only_dois(nodes)
self.assertCountEqual(doi_nodes,['doi_d02','doi_d1'])
self.assertCountEqual(edges, [['doi_d02','doi_d1']])
nodes, edges = init_graph_construction(['doi_d02'],0,2,True)
doi_nodes = keep_only_dois(nodes)
self.assertCountEqual(doi_nodes,['doi_d02','doi_d1','doi_d2'])
self.assertCountEqual(edges, [['doi_d02','doi_d1'], ['doi_d1','doi_d2']])
def keep_only_dois(nodes):
'''
:param nodes: input list of nodes of type Publication
:type nodes: List[Publication]
gets nodes of type pub and return only their doi
'''
doi_list = []
for node in nodes:
doi_list.append(node.doi_url)
return doi_list
if __name__ == "__main__":
unittest.main()
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verarbeitung/test/input_test.py 0 → 100644
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import sys
sys.path.append("../")
from input.publication import Publication, Citation
def input_test_func(pub_doi):
'''
:param pub_doi: pub doi to find publication in list_of_arrays
:type pub_doi: String
returns the publication class for given doi
'''
for array in list_of_arrays:
if pub_doi == array[0]:
pub = Publication(array[0], array[1], array[2], array[3], array[4], array[5], [], [])
pub.citations = cit(array[7], "Citation")
pub.references = cit(array[6], "Reference")
return pub
def cit(list_doi, cit_type):
'''
:param list_doi list of citation dois to get their Citation Class
:type list_doi: List[String]
returns a list of citations objects for given doi list
'''
cits = []
for doi_url in list_doi:
for array in list_of_arrays:
if doi_url == array[0]:
cits.append(Citation(array[0], array[1], array[2], array[3], cit_type))
return cits
beispiel1 = ['doi1', 'title1', ['contributor1'], 'journal1', 'date1', ['subject1'], ['doi2'], ['doi3']]
beispiel2 = ['doi2', 'title2', ['contributor2'], 'journal2', 'date2', ['subject2'], [], ['doi1']]
beispiel3 = ['doi3', 'title3', ['contributor3'], 'journal3', 'date3', ['subject3'], ['doi1'], []]
zyklus1 = ['doiz1', 'titlez1', ['contributorz1.1', 'contributorz1.2'], 'journalz1', 'datez1', ['subjectz1'], ['doiz2'], ['doiz2']]
zyklus2 = ['doiz2', 'titlez2', ['contributorz2.1', 'contributorz2.2'], 'journalz2', 'datez2', ['subjectz1'], ['doiz1'], ['doiz1']]
inner_edge1 = ['doi_ie1', 'title_ie1', ['contributor_ie1.1', 'contributor_ie1.2'], 'journal_ie1', 'date_ie1', ['subject_ie1'], ['doi_ie2'], ['doi_ie3']]
inner_edge2 = ['doi_ie2', 'title_ie2', ['contributor_ie2.1', 'contributor_ie2.2'], 'journal_ie2', 'date_ie2', ['subject_ie2'], [], ['doi_ie1','doi_ie3']]
inner_edge3 = ['doi_ie3', 'titlez_ie3', ['contributor_ie3.1', 'contributor_ie3.2'], 'journal_ie3', 'date_ie3', ['subject_ie3'], ['doi_ie1','doi_ie2'], []]
right_height01 = ['doi_h01', 'title_h01', ['contributor_h01'], 'journal_h01', 'date_h01', ['subject_h01'], [], []]
right_height02 = ['doi_h02', 'title_h02', ['contributor_h02'], 'journal_h02', 'date_h02', ['subject_h02'], [], ['doi_h1']]
right_height1 = ['doi_h1', 'title_h1', ['contributor_h1'], 'journal_h1', 'date_h1', ['subject_h1'], [], ['doi_h2']]
right_height2 = ['doi_h2', 'title_h2', ['contributor_h2'], 'journal_h2', 'date_h2', ['subject_h2'], [], ['doi_h3']]
right_height3 = ['doi_h3', 'title_h3', ['contributor_h3'], 'journal_h3', 'date_h3', ['subject_h3'], [], []]
right_depth01 = ['doi_d01', 'title_d01', ['contributor_d01'], 'journal_d01', 'date_d01', ['subject_d01'], [], []]
right_depth02 = ['doi_d02', 'title_d02', ['contributor_d02'], 'journal_d02', 'date_d02', ['subject_d01'], ['doi_d1'], []]
right_depth1 = ['doi_d1', 'title_d1', ['contributor_d1'], 'journal_d1', 'date_d1', ['subject_d1'], ['doi_d2'], []]
right_depth2 = ['doi_d2', 'title_d2', ['contributor_d2'], 'journal_d2', 'date_d2', ['subject_d2'], ['doi_d3'], []]
right_depth3 = ['doi_d3', 'title_d3', ['contributor_d3'], 'journal_d3', 'date_d3', ['subject_d3'], [], []]
large_graph_1_h21 = ['doi_lg_1_h21', 'title_lg_1_h21', ['contributor_lg_1_h21'], 'journal_lg_1_h21', 'date_lg_1_h21', ['subject_lg_1_h21'], ['doi_lg_1_h11'], []]
large_graph_1_h22 = ['doi_lg_1_h22', 'title_lg_1_h22', ['contributor_lg_1_h22'], 'journal_lg_1_h22', 'date_lg_1_h22', ['subject_lg_1_h22'], ['doi_lg_1_h11','doi_lg_1_h12'], []]
large_graph_1_h23 = ['doi_lg_1_h23', 'title_lg_1_h23', ['contributor_lg_1_h23'], 'journal_lg_1_h23', 'date_lg_1_h23', ['subject_lg_1_h23'], ['doi_lg_1_h12','doi_cg_i'], []]
large_graph_1_h11 = ['doi_lg_1_h11', 'title_lg_1_h11', ['contributor_lg_1_h11'], 'journal_lg_1_h11', 'date_lg_1_h11', ['subject_lg_1_h11'], ['doi_lg_1_i'], ['doi_lg_1_h21','doi_lg_1_h22']]
large_graph_1_h12 = ['doi_lg_1_h12', 'title_lg_1_h12', ['contributor_lg_1_h12'], 'journal_lg_1_h12', 'date_lg_1_h12', ['subject_lg_1_h12'], ['doi_lg_1_i','doi_lg_1_d12'], ['doi_lg_1_h22','doi_lg_1_h23']]
large_graph_1_i = ['doi_lg_1_i' , 'title_lg_1_i' , ['contributor_lg_1_i'] , 'journal_lg_1_i' , 'date_lg_1_i' , ['subject_lg_1_i'] , ['doi_lg_1_d11','doi_lg_1_d12'], ['doi_lg_1_h11','doi_lg_1_h12']]
large_graph_1_d11 = ['doi_lg_1_d11', 'title_lg_1_d11', ['contributor_lg_1_d11'], 'journal_lg_1_d11', 'date_lg_1_d11', ['subject_lg_1_d11'], ['doi_lg_1_d21','doi_lg_1_d22'], ['doi_lg_1_i']]
large_graph_1_d12 = ['doi_lg_1_d12', 'title_lg_1_d12', ['contributor_lg_1_d12'], 'journal_lg_1_d12', 'date_lg_1_d12', ['subject_lg_1_d12'], ['doi_lg_1_d23'], ['doi_lg_1_h12','doi_lg_1_i']]
large_graph_1_d21 = ['doi_lg_1_d21', 'title_lg_1_d21', ['contributor_lg_1_d21'], 'journal_lg_1_d21', 'date_lg_1_d21', ['subject_lg_1_d21'], ['doi_lg_1_d22'], ['doi_lg_1_d11','doi_lg_1_d22']]
large_graph_1_d22 = ['doi_lg_1_d22', 'title_lg_1_d22', ['contributor_lg_1_d22'], 'journal_lg_1_d22', 'date_lg_1_d22', ['subject_lg_1_d22'], ['doi_lg_1_d21'], ['doi_lg_1_d11','doi_lg_1_d21']]
large_graph_1_d23 = ['doi_lg_1_d23', 'title_lg_1_d23', ['contributor_lg_1_d23'], 'journal_lg_1_d23', 'date_lg_1_d23', ['subject_lg_1_d23'], [], ['doi_lg_1_d12','doi_cg_d11']]
large_graph_2_h21 = ['doi_lg_2_h21', 'title_lg_2_h21', ['contributor_lg_2_h21'], 'journal_lg_2_h21', 'date_lg_2_h21', ['subject_lg_2_h21'], ['doi_lg_2_h11'], []]
large_graph_2_h22 = ['doi_lg_2_h22', 'title_lg_2_h22', ['contributor_lg_2_h22'], 'journal_lg_2_h22', 'date_lg_2_h22', ['subject_lg_2_h22'], ['doi_lg_2_h11'], []]
large_graph_2_h23 = ['doi_lg_2_h23', 'title_lg_2_h23', ['contributor_lg_2_h23'], 'journal_lg_2_h23', 'date_lg_2_h23', ['subject_lg_2_h23'], ['doi_lg_2_h12','doi_lg_2_h24'], ['doi_lg_2_h24']]
large_graph_2_h24 = ['doi_lg_2_h24', 'title_lg_2_h24', ['contributor_lg_2_h24'], 'journal_lg_2_h24', 'date_lg_2_h24', ['subject_lg_2_h24'], ['doi_lg_2_h12','doi_lg_2_h23','doi_lg_2_d12'], ['doi_lg_2_h23']]
large_graph_2_h11 = ['doi_lg_2_h11', 'title_lg_2_h11', ['contributor_lg_2_h11'], 'journal_lg_2_h11', 'date_lg_2_h11', ['subject_lg_2_h11'], ['doi_lg_2_i','doi_cg_i'], ['doi_lg_2_h21','doi_lg_2_h22']]
large_graph_2_h12 = ['doi_lg_2_h12', 'title_lg_2_h12', ['contributor_lg_2_h12'], 'journal_lg_2_h12', 'date_lg_2_h12', ['subject_lg_2_h12'], ['doi_lg_2_i'], ['doi_lg_2_h23','doi_lg_2_h24']]
large_graph_2_i = ['doi_lg_2_i' , 'title_lg_2_i' , ['contributor_lg_2_i'] , 'journal_lg_2_i' , 'date_lg_2_i' , ['subject_lg_2_i'] , ['doi_lg_2_d11','doi_lg_2_d12'], ['doi_lg_2_h11','doi_lg_2_h12','doi_cg_i','doi_lg_2_h11']]
large_graph_2_d11 = ['doi_lg_2_d11', 'title_lg_2_d11', ['contributor_lg_2_d11'], 'journal_lg_2_d11', 'date_lg_2_d11', ['subject_lg_2_d11'], ['doi_lg_2_i','doi_lg_2_d21'], ['doi_lg_2_i']]
large_graph_2_d12 = ['doi_lg_2_d12', 'title_lg_2_d12', ['contributor_lg_2_d12'], 'journal_lg_2_d12', 'date_lg_2_d12', ['subject_lg_2_d12'], ['doi_lg_2_d22','doi_lg_2_d23','doi_lg_2_d24'], ['doi_lg_2_h24','doi_lg_2_i']]
large_graph_2_d21 = ['doi_lg_2_d21', 'title_lg_2_d21', ['contributor_lg_2_d21'], 'journal_lg_2_d21', 'date_lg_2_d21', ['subject_lg_2_d21'], [], ['doi_lg_2_d11']]
large_graph_2_d22 = ['doi_lg_2_d22', 'title_lg_2_d22', ['contributor_lg_2_d22'], 'journal_lg_2_d22', 'date_lg_2_d22', ['subject_lg_2_d22'], [], ['doi_lg_2_d12']]
large_graph_2_d23 = ['doi_lg_2_d23', 'title_lg_2_d23', ['contributor_lg_2_d23'], 'journal_lg_2_d23', 'date_lg_2_d23', ['subject_lg_2_d23'], [], ['doi_lg_2_d12']]
large_graph_2_d24 = ['doi_lg_2_d24', 'title_lg_2_d24', ['contributor_lg_2_d24'], 'journal_lg_2_d24', 'date_lg_2_d24', ['subject_lg_2_d24'], [], ['doi_lg_2_d12']]
crossed_graph_h21 = ['doi_cg_h21', 'title_cg_h21', ['contributor_cg_h21'], 'journal_cg_h21', 'date_cg_h21', ['subject_cg_h21'], ['doi_cg_h11'], []]
crossed_graph_h22 = ['doi_cg_h22', 'title_cg_h22', ['contributor_cg_h22'], 'journal_cg_h22', 'date_cg_h22', ['subject_cg_h22'], ['doi_cg_h11'], []]
crossed_graph_h11 = ['doi_cg_h11', 'title_cg_h11', ['contributor_cg_h11'], 'journal_cg_h11', 'date_cg_h11', ['subject_cg_h11'], ['doi_cg_i'], ['doi_cg_h21','doi_cg_h22']]
crossed_graph_i = ['doi_cg_i', 'title_cg_i', ['contributor_cg_i'], 'journal_cg_i', 'date_cg_i', ['subject_cg_i'], ['doi_lg_2_i','doi_cg_d11','doi_cg_d12'], ['doi_lg_1_h23','doi_cg_h11','doi_lg_2_h11']]
crossed_graph_d11 = ['doi_cg_d11', 'title_cg_d11', ['contributor_cg_d11'], 'journal_cg_d11', 'date_cg_d11', ['subject_cg_d11'], ['doi_lg_1_d23','doi_cg_d21'], ['doi_cg_i']]
crossed_graph_d12 = ['doi_cg_d12', 'title_cg_d12', ['contributor_cg_d12'], 'journal_cg_d12', 'date_cg_d12', ['subject_cg_d12'], ['doi_cg_d22'], ['doi_cg_i']]
crossed_graph_d21 = ['doi_cg_d21', 'title_cg_d21', ['contributor_cg_d21'], 'journal_cg_d21', 'date_cg_d21', ['subject_cg_d21'], [], ['doi_cg_d11']]
crossed_graph_d22 = ['doi_cg_d22', 'title_cg_d22', ['contributor_cg_d22'], 'journal_cg_d22', 'date_cg_d22', ['subject_cg_d22'], [], ['doi_cg_d12']]
list_of_arrays = [beispiel1, beispiel2, beispiel3, zyklus1, zyklus2, inner_edge1, inner_edge2, inner_edge3,
right_height01, right_height02, right_height1, right_height2, right_height3, right_depth01, right_depth02, right_depth1, right_depth2, right_depth3,
large_graph_1_h21, large_graph_1_h22, large_graph_1_h23, large_graph_1_h11, large_graph_1_h12, large_graph_1_i, large_graph_1_d11, large_graph_1_d12,
large_graph_1_d21, large_graph_1_d22, large_graph_1_d23, large_graph_2_h21, large_graph_2_h22, large_graph_2_h23, large_graph_2_h24, large_graph_2_h11, large_graph_2_h12,
large_graph_2_i, large_graph_2_d11, large_graph_2_d12, large_graph_2_d21, large_graph_2_d22, large_graph_2_d23, crossed_graph_h21, crossed_graph_h22, crossed_graph_h11,
crossed_graph_i, crossed_graph_d11, crossed_graph_d12, crossed_graph_d21, crossed_graph_d22]
verarbeitung/test/test_graphs_plan.pdf 0 → 100644
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verarbeitung/test/update_graph_unittest.py 0 → 100644
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import unittest
import sys
from pathlib import Path
sys.path.append("../")
from verarbeitung.construct_new_graph.initialize_graph import init_graph_construction
from verarbeitung.construct_new_graph.export_to_json import output_to_json
from verarbeitung.update_graph.import_from_json import input_from_json
from verarbeitung.update_graph.update_graph import update_graph
class UpdatingTest(unittest.TestCase):
maxDiff = None
# def test_import_from_json(self):
# nodes_old, edges_old = init_graph_construction(['doi_lg_1_i'],2,2,True)
# output_to_json(nodes_old, edges_old, test_var = True)
# nodes_new, edges_new = input_from_json('test_output.json')
# self.assertCountEqual(nodes_old,nodes_new)
# self.assertCountEqual(edges_old, edges_new)
# def test_deleted_input_dois(self):
# nodes_old_single, edges_old_single = init_graph_construction(['doi_lg_1_i'],2,2,True)
# nodes_old_both, edges_old_both = init_graph_construction(['doi_lg_1_i','doi_lg_2_i'],2,2,True)
# output_to_json(nodes_old_both, edges_old_both, test_var=True)
# nodes_new_single, edges_new_single = update_graph(['doi_lg_1_i'], 'test_output.json', 2, 2, True)
# self.assertCountEqual(nodes_old_single,nodes_new_single)
# self.assertCountEqual(edges_old_single, edges_new_single)
# nodes_old_single, edges_old_single = init_graph_construction(['doi_cg_i'],3,3,True)
# nodes_old_two, edges_old_two = init_graph_construction(['doi_lg_1_i','doi_cg_i'],3,3,True)
# nodes_old_three, edges_old_three = init_graph_construction(['doi_lg_1_i','doi_lg_2_i','doi_cg_i'],3,3,True)
def test_new_height(self):
nodes_height_0, edges_height_0 = init_graph_construction(['doi_lg_1_i'],2,0,True)
nodes_height_1, edges_height_1 = init_graph_construction(['doi_lg_1_i'],2,1,True)
nodes_height_2, edges_height_2 = init_graph_construction(['doi_lg_1_i'],2,2,True)
output_to_json(nodes_height_2, edges_height_2, 'new_height.json', True)
nodes_new_height_1, edges_new_height_1 = update_graph(['doi_lg_1_i'], 'new_height.json', 2, 1, True)
self.assertCountEqual(nodes_height_1, nodes_new_height_1)
self.assertCountEqual(edges_height_1, edges_new_height_1)
nodes_height_2, edges_height_2 = init_graph_construction(['doi_lg_1_i'],2,2,True)
output_to_json(nodes_height_2, edges_height_2, 'new_height.json', True)
nodes_new_height_0, edges_new_height_0 = update_graph(['doi_lg_1_i'], 'new_height.json', 2, 0, True)
self.assertCountEqual(nodes_height_0, nodes_new_height_0)
self.assertCountEqual(edges_height_0, edges_new_height_0)
def keep_only_dois(nodes):
'''
:param nodes: input list of nodes of type Publication
:type nodes: List[Publication]
gets nodes of type pub and return only their doi
'''
doi_list = []
for node in nodes:
doi_list.append(node.doi_url)
return doi_list
if __name__ == "__main__":
unittest.main()
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verarbeitung/test_output.json 0 → 100644
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{"nodes": [{"doi": "doi_lg_1_i", "name": "title_lg_1_i", "author": ["contributor_lg_1_i"], "year": "date_lg_1_i", "journal": "journal_lg_1_i", "group": "Input", "depth": 0, "citations": 2}, {"doi": "doi_lg_1_d11", "name": "title_lg_1_d11", "author": ["contributor_lg_1_d11"], "year": "date_lg_1_d11", "journal": "journal_lg_1_d11", "group": "Reference", "depth": -1, "citations": 1}, {"doi": "doi_lg_1_d12", "name": "title_lg_1_d12", "author": ["contributor_lg_1_d12"], "year": "date_lg_1_d12", "journal": "journal_lg_1_d12", "group": "Reference", "depth": -1, "citations": 2}, {"doi": "doi_lg_1_h11", "name": "title_lg_1_h11", "author": ["contributor_lg_1_h11"], "year": "date_lg_1_h11", "journal": "journal_lg_1_h11", "group": "Citedby", "depth": 1, "citations": 2}, {"doi": "doi_lg_1_h12", "name": "title_lg_1_h12", "author": ["contributor_lg_1_h12"], "year": "date_lg_1_h12", "journal": "journal_lg_1_h12", "group": "Citedby", "depth": 1, "citations": 2}, {"doi": "doi_lg_2_i", "name": "title_lg_2_i", "author": ["contributor_lg_2_i"], "year": "date_lg_2_i", "journal": "journal_lg_2_i", "group": "Input", "depth": 0, "citations": 4}, {"doi": "doi_lg_2_d11", "name": "title_lg_2_d11", "author": ["contributor_lg_2_d11"], "year": "date_lg_2_d11", "journal": "journal_lg_2_d11", "group": "Reference", "depth": -1, "citations": 1}, {"doi": "doi_lg_2_d12", "name": "title_lg_2_d12", "author": ["contributor_lg_2_d12"], "year": "date_lg_2_d12", "journal": "journal_lg_2_d12", "group": "Reference", "depth": -1, "citations": 2}, {"doi": "doi_lg_2_h11", "name": "title_lg_2_h11", "author": ["contributor_lg_2_h11"], "year": "date_lg_2_h11", "journal": "journal_lg_2_h11", "group": "Citedby", "depth": 1, "citations": 2}, {"doi": "doi_lg_2_h12", "name": "title_lg_2_h12", "author": ["contributor_lg_2_h12"], "year": "date_lg_2_h12", "journal": "journal_lg_2_h12", "group": "Citedby", "depth": 1, "citations": 2}, {"doi": "doi_cg_i", "name": "title_cg_i", "author": ["contributor_cg_i"], "year": "date_cg_i", "journal": "journal_cg_i", "group": "Citedby", "depth": 1, "citations": 3}, {"doi": "doi_lg_1_h21", "name": "title_lg_1_h21", "author": ["contributor_lg_1_h21"], "year": "date_lg_1_h21", "journal": "journal_lg_1_h21", "group": "Citedby", "depth": 2, "citations": 0}, {"doi": "doi_lg_1_h22", "name": "title_lg_1_h22", "author": ["contributor_lg_1_h22"], "year": "date_lg_1_h22", "journal": "journal_lg_1_h22", "group": "Citedby", "depth": 2, "citations": 0}, {"doi": "doi_lg_1_h23", "name": "title_lg_1_h23", "author": ["contributor_lg_1_h23"], "year": "date_lg_1_h23", "journal": "journal_lg_1_h23", "group": "Citedby", "depth": 2, "citations": 0}, {"doi": "doi_lg_2_h21", "name": "title_lg_2_h21", "author": ["contributor_lg_2_h21"], "year": "date_lg_2_h21", "journal": "journal_lg_2_h21", "group": "Citedby", "depth": 2, "citations": 0}, {"doi": "doi_lg_2_h22", "name": "title_lg_2_h22", "author": ["contributor_lg_2_h22"], "year": "date_lg_2_h22", "journal": "journal_lg_2_h22", "group": "Citedby", "depth": 2, "citations": 0}, {"doi": "doi_lg_2_h23", "name": "title_lg_2_h23", "author": ["contributor_lg_2_h23"], "year": "date_lg_2_h23", "journal": "journal_lg_2_h23", "group": "Citedby", "depth": 2, "citations": 1}, {"doi": "doi_lg_2_h24", "name": "title_lg_2_h24", "author": ["contributor_lg_2_h24"], "year": "date_lg_2_h24", "journal": "journal_lg_2_h24", "group": "Citedby", "depth": 2, "citations": 1}, {"doi": "doi_cg_h11", "name": "title_cg_h11", "author": ["contributor_cg_h11"], "year": "date_cg_h11", "journal": "journal_cg_h11", "group": "Citedby", "depth": 2, "citations": 2}, {"doi": "doi_lg_1_d21", "name": "title_lg_1_d21", "author": ["contributor_lg_1_d21"], "year": "date_lg_1_d21", "journal": "journal_lg_1_d21", "group": "Reference", "depth": -2, "citations": 2}, {"doi": "doi_lg_1_d22", "name": "title_lg_1_d22", "author": ["contributor_lg_1_d22"], "year": "date_lg_1_d22", "journal": "journal_lg_1_d22", "group": "Reference", "depth": -2, "citations": 2}, {"doi": "doi_lg_1_d23", "name": "title_lg_1_d23", "author": ["contributor_lg_1_d23"], "year": "date_lg_1_d23", "journal": "journal_lg_1_d23", "group": "Reference", "depth": -2, "citations": 2}, {"doi": "doi_lg_2_d21", "name": "title_lg_2_d21", "author": ["contributor_lg_2_d21"], "year": "date_lg_2_d21", "journal": "journal_lg_2_d21", "group": "Reference", "depth": -2, "citations": 1}, {"doi": "doi_lg_2_d22", "name": "title_lg_2_d22", "author": ["contributor_lg_2_d22"], "year": "date_lg_2_d22", "journal": "journal_lg_2_d22", "group": "Reference", "depth": -2, "citations": 1}, {"doi": "doi_lg_2_d23", "name": "title_lg_2_d23", "author": ["contributor_lg_2_d23"], "year": "date_lg_2_d23", "journal": "journal_lg_2_d23", "group": "Reference", "depth": -2, "citations": 1}], "links": [{"source": "doi_lg_1_i", "target": "doi_lg_1_d11"}, {"source": "doi_lg_1_i", "target": "doi_lg_1_d12"}, {"source": "doi_lg_1_h11", "target": "doi_lg_1_i"}, {"source": "doi_lg_1_h12", "target": "doi_lg_1_i"}, {"source": "doi_lg_2_i", "target": "doi_lg_2_d11"}, {"source": "doi_lg_2_i", "target": "doi_lg_2_d12"}, {"source": "doi_lg_2_h11", "target": "doi_lg_2_i"}, {"source": "doi_lg_2_h12", "target": "doi_lg_2_i"}, {"source": "doi_cg_i", "target": "doi_lg_2_i"}, {"source": "doi_lg_1_h21", "target": "doi_lg_1_h11"}, {"source": "doi_lg_1_h22", "target": "doi_lg_1_h11"}, {"source": "doi_lg_1_h22", "target": "doi_lg_1_h12"}, {"source": "doi_lg_1_h23", "target": "doi_lg_1_h12"}, {"source": "doi_lg_2_h21", "target": "doi_lg_2_h11"}, {"source": "doi_lg_2_h22", "target": "doi_lg_2_h11"}, {"source": "doi_lg_2_h23", "target": "doi_lg_2_h12"}, {"source": "doi_lg_2_h24", "target": "doi_lg_2_h12"}, {"source": "doi_lg_2_h24", "target": "doi_lg_2_h23"}, {"source": "doi_lg_2_h23", "target": "doi_lg_2_h24"}, {"source": "doi_lg_1_h23", "target": "doi_cg_i"}, {"source": "doi_cg_h11", "target": "doi_cg_i"}, {"source": "doi_lg_2_h11", "target": "doi_cg_i"}, {"source": "doi_lg_1_d11", "target": "doi_lg_1_d21"}, {"source": "doi_lg_1_d11", "target": "doi_lg_1_d22"}, {"source": "doi_lg_1_d21", "target": "doi_lg_1_d22"}, {"source": "doi_lg_1_d22", "target": "doi_lg_1_d21"}, {"source": "doi_lg_1_d12", "target": "doi_lg_1_d23"}, {"source": "doi_lg_2_d11", "target": "doi_lg_2_i"}, {"source": "doi_lg_2_d11", "target": "doi_lg_2_d21"}, {"source": "doi_lg_2_d12", "target": "doi_lg_2_d22"}, {"source": "doi_lg_2_d12", "target": "doi_lg_2_d23"}, {"source": "doi_lg_1_h12", "target": "doi_lg_1_d12"}, {"source": "doi_lg_1_h11", "target": "doi_lg_1_h12"}, {"source": "doi_lg_2_h24", "target": "doi_lg_2_d12"}]}
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verarbeitung/update_graph/Kanten_Vergleich.py 0 → 100644
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#!/usr/bin/env python3
def back_to_valid_edges(links_from_json, processed_input_list):
'''
:param links_from_json: list of edges from the old graph
:type links_from_json: list
:param processed_input_list: list pubs still in graph
:type processed_input_list: list
function that deletes edges, if one ore two including nodes are deleted nodes
'''
list_of_valid_edges = links_from_json.copy()
#iterates over all edges from old graph
for edge in list_of_valid_edges:
# counter for adjacent nodes
found_adj_nodes = 0
for pub in processed_input_list:
# checks for both adjacent nodes of edge if pub is source/target node
for adj_node in edge:
# increases counter if adjacent node was found
if (adj_node == pub.doi_url):
found_adj_nodes += 1
if (found_adj_nodes == 2):
break
#removes the edge if less than 2 adjacent nodes found
if (found_adj_nodes < 2):
links_from_json.remove(edge)
#Kanten_Menge_Ganz = [["doi_1","doi_2"],["doi_3","doi_4"],["doi_5","doi_6"]]
#Geloeschte = ["doi_2","doi_1","doi_4"]
#print(back_to_valid_edges(Kanten_Menge_Ganz,Geloeschte))
#Im Anschluss muss mit den Hinzugefügten Knoten Processing aufgerufen werden
verarbeitung/update_graph/Knoten_Vergleich.py 0 → 100644
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#!/usr/bin/env python3
from collections import Counter
def doi_listen_vergleichen(alte,neue):
'''
:param alte: list of dois from old graph
:type alte: list
:param neue: list of dois from new graph
:type neue: list
function to calculate, which nodes from the old graph are deleted and which are added
'''
dois_from_old_graph = alte #WICHTIG: Keine doppelten DOIs
dois_from_new_graph = neue
deleted_nodes = []
common_nodes = []
inserted_nodes = []
all_dois = dois_from_old_graph + dois_from_new_graph
for doi in all_dois: # iterates over the merged list of new and old dois
if ((all_dois.count(doi) == 2) & (doi not in common_nodes)): # If the doi occurs twice the node is in the old and the new graph
common_nodes.append(doi) #appends the doi to common ones, if its not alredy in it
elif ((doi in dois_from_old_graph) & (doi not in dois_from_new_graph)): #If the doi occurs once and it is from old graph it is a deleted node
deleted_nodes.append(doi) #appends the doi to deleted ones
elif ((doi in dois_from_new_graph) & (doi not in dois_from_old_graph)): #if the doi occurs ince and it is from new graph it is a inserted node
inserted_nodes.append(doi) #appends the doi to the inserted ones
return(common_nodes, inserted_nodes, deleted_nodes)
#Test Prints
#liste_1 = ["doi_1","doi_2","doi_3","doi_4","doi_5"]
#liste_2 = ["doi_1","doi_2","doi_3","doi_6","doi_7"]
#print("gemeinsame Elemente: ",doi_listen_vergleichen(liste_1,liste_2)[0])
#print("hinzugefügte Elemente: ",doi_listen_vergleichen(liste_1,liste_2)[1])
#print("gelöschte Elemente: ",doi_listen_vergleichen(liste_1,liste_2)[2])
verarbeitung/update_graph/README.md 0 → 100644
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# Projekt CiS-Projekt 2021/22
Directory for functions to adjust a publication graph to updated input lists and changed citation/reference depths. For minimal use of the time consuming Input function, a reinterpretation of the exported json file is implemented.
## Files in directory
import_from_json.py
- Stellt die alte Knoten-und Kantenmenge aus der Json Datei wieder her.
Knoten_Vergleich.py
- Überprüft welche Knoten neu hinzugekommen sind und welche enfternt wurden.
Kanten_Vergleich.py
- Stellt nach der Löschung eines Knotens wieder eine valide Kantenmenge her.
update_graph_del.py
- Führt die Löschung eines Knotens durch
connect_new_input.py
- Verbindet den alten Graphen aus der Json Datei mit den neuen DOIs zu dem neuen Graphen.
update_graph.py
- Überprüft welche Änderungen der Benutzer vorgenommen hat (Löschen oder hinzufügen von DOIs)
und führt diese aus.
## Authors
- Donna Löding
- Alina Molkentin
- Xinyi Tang
- Judith Große
- Malte Schokolowski
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verarbeitung/update_graph/__init__.py 0 → 100644
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verarbeitung/update_graph/connect_new_input.py 0 → 100644
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# -*- coding: utf-8 -*-
"""
Functions to update a graph representing citations between multiple ACS/Nature journals
"""
__authors__ = "Donna Löding, Alina Molkentin, Xinyi Tang, Judith Große, Malte Schokolowski"
__email__ = "cis-project2021@zbh.uni-hamburg.de"
__status__ = "Production"
#__copyright__ = ""
#__credits__ = ["", "", "", ""]
#__license__ = ""
#__version__ = ""
#__maintainer__ = ""
import sys
from pathlib import Path
from os import error
sys.path.append("../")
from .import_from_json import input_from_json
from verarbeitung.construct_new_graph.initialize_graph import initialize_nodes_list, complete_inner_edges
from verarbeitung.construct_new_graph.add_citations_rec import add_citations
from verarbeitung.construct_new_graph.export_to_json import output_to_json
def connect_old_and_new_input(json_file, new_doi_list, search_depth, search_height, test_var = False):
'''
:param json_file: json file with old graph
:type json_file: json file
:param new_doi_list: additional dois which has to be connected to the old graph
:type new_doi_list: list of strings
:param search_depth: depth to search for references
:type search_depth: int
:param search_height: height to search for citations
:type search_height: int
:param test_var: variable to differenciate between test and url call
:type test_var: boolean
connetcs the old graph and the new input dois to a complete new graph
'''
global nodes, edges
nodes = []
edges = []
nodes, edges = input_from_json(json_file)
complete_changed_group_nodes(new_doi_list, search_depth, search_height, test_var)
# initializes nodes/edges from input and gets a list with publication objects for citations and references returned
references_obj_list, citations_obj_list = initialize_nodes_list(new_doi_list,search_depth, search_height, test_var)
# function calls to begin recursive processing up to max depth/height
add_citations(nodes, edges, citations_obj_list, 1, search_height, "Citation", test_var)
add_citations(nodes, edges, references_obj_list, 1, search_depth, "Reference", test_var)
# adds edges between reference group and citation group of known publications
complete_inner_edges(test_var)
# calls a skript to save nodes and edges of graph in .json file
output_to_json(nodes,edges, test_var)
return(nodes, edges)
def complete_changed_group_nodes(new_doi_list, search_depth_max, search_height_max, test_var):
'''
work in progress
'''
changed_group_node_citations = []
changed_group_node_references = []
for node in nodes:
if (node.group < 0) and (node.doi in new_doi_list):
node.group = "input"
elif (node.group > 0) and (node.doi in new_doi_list):
node.group = "input"
verarbeitung/update_graph/delete_nodes_edges.py 0 → 100644
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# -*- coding: utf-8 -*-
"""
Functions to remove publications/links from nodes/edges list, if they can no longer be reached
"""
__authors__ = "Donna Löding, Alina Molkentin, Xinyi Tang, Judith Große, Malte Schokolowski"
__email__ = "cis-project2021@zbh.uni-hamburg.de"
__status__ = "Production"
#__copyright__ = ""
#__credits__ = ["", "", "", ""]
#__license__ = ""
#__version__ = ""
#__maintainer__ = ""
import sys
from pathlib import Path
sys.path.append("../../")
from .Kanten_Vergleich import back_to_valid_edges
def search_ref_graph_rec(pub):
'''
:param pub: pub go get appended to usable_nodes
:type pub: Publication
function that appends nodes of group "reference" to list usable_nodes, if they are reachable from input nodes
'''
for reference in pub.references:
for ref_pub in input_obj_list:
if ((reference.doi_url == ref_pub.doi_url) and (ref_pub not in usable_nodes)):
usable_nodes.append(ref_pub)
# to find a cyclus and avoid recursion error
not_in_citations = True
for citation in pub.citations:
if (reference.doi_url == citation.doi_url):
not_in_citations = False
break
if (not_in_citations):
search_ref_graph_rec(ref_pub)
def search_cit_graph_rec(pub):
'''
:param pub: pub go get appended to usable_nodes
:type pub: Publication
function that appends nodes of group "citation" to list usable_nodes, if they are reachable from input nodes
'''
for citation in pub.citations:
for cit_pub in input_obj_list:
if ((citation.doi_url == cit_pub.doi_url) and (cit_pub not in usable_nodes)):
usable_nodes.append(cit_pub)
# to find a cyclus and avoid recursion error
not_in_references = True
for reference in pub.references:
if (citation.doi_url == reference.doi_url):
not_in_references = False
break
if (not_in_references):
search_cit_graph_rec(cit_pub)
def delete_nodes_and_edges(input_list, common_nodes, old_edges_list):
'''
:param input_list: list of publications to get reduced
:type input_list: List[Publication]
:param common_nodes: list of input dois which are in old and new input call
:type common_nodes: List[String]
:param old_edges_list: list of links between publications from old call
:type old_edges_list: List[List[String,String]]
function to start recursive node removal for references and citations and to change edge list to valid state
'''
global usable_nodes, input_obj_list
usable_nodes = []
input_obj_list = input_list
# starts for every common input node a tree-search and adds found nodes to usable_nodes
for common in common_nodes:
for pub in input_obj_list:
if (common == pub.doi_url):
usable_nodes.append(pub)
search_ref_graph_rec(pub)
search_cit_graph_rec(pub)
valid_edges = back_to_valid_edges(old_edges_list, usable_nodes)
return(usable_nodes, valid_edges)
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