diff --git a/count_journal.py b/count_journal.py
deleted file mode 100755
index 13886a2e7badf339bdd23475f7d3de713329f472..0000000000000000000000000000000000000000
--- a/count_journal.py
+++ /dev/null
@@ -1,40 +0,0 @@
-#!/usr/bin/env python3
-
-from input.interface import InputInterface as Input
-
-def count_journals(url: str):
- inter = Input()
- pub = inter.get_publication(url)
-
- if pub.citations:
- for citation in pub.citations:
- journal = citation.journal
- if journal in cit:
- cit[journal] += 1
- else:
- cit[journal] = 1
-
- if pub.references:
- for reference in pub.references:
- journal = reference.journal
- if journal in cit:
- cit[journal] += 1
- else:
- cit[journal] = 1
-
-if __name__ == "__main__":
- cit = {}
-
- count_journals("https://doi.org/10.1021/acs.jcim.1c00203")
- count_journals("https://doi.org/10.1021/acs.jcim.6b00561")
- count_journals("https://doi.org/10.1021/acs.jcim.6b00613")
- count_journals("https://doi.org/10.1021/acs.jcim.1c00917")
- count_journals("https://doi.org/10.1021/acs.jmedchem.0c01332")
- #count_journals("https://pubs.acs.org/doi/10.1021/acs.biochem.1c00290")
- #count_journals("https://pubs.acs.org/doi/10.1021/acsenvironau.1c00007")
- #count_journals("https://pubs.acs.org/doi/10.1021/acs.biochem.7b01162")
-
- cit = dict(sorted(cit.items(), key=lambda item: item[1]))
- for journal in cit:
- if journal != "":
- print(f'{journal}: {cit[journal]}')
diff --git a/example_input.py b/example_input.py
deleted file mode 100755
index c9bca4189fce4c1fd0a0dfc42ef4e517baa5f406..0000000000000000000000000000000000000000
--- a/example_input.py
+++ /dev/null
@@ -1,13 +0,0 @@
-#!/usr/bin/env python3
-
-from input.interface import InputInterface as Input
-
-def main(url: str):
- i = Input()
- #print(i.get_publication(url))
- print(i.get_pub_light(url))
- # print(i.get_supported_fetchers()) Useless because all classes are called the same
-
-if __name__ == "__main__":
- #main("https://doi.org/10.1021/acs.jcim.1c0023")
- main("https://doi.org/10.1021/acs.jcim.5b00332")
diff --git a/input/README.md b/input/README.md
deleted file mode 100644
index 110ce69136a8935b83d070113130222f243e924f..0000000000000000000000000000000000000000
--- a/input/README.md
+++ /dev/null
@@ -1,50 +0,0 @@
-# Projekt CiS-Projekt 2021/22
-
-Input-Package to fetch publication information with a given url.
-
-## Usage/Examples
-
-```python
-from input.interface import InputInterface as Input
-from input.publication import Publication
-
-def main(url):
- inter = Input()
- try:
- pub = inter.get_publication(url)
- except Exception as error:
- raise error
-
- print(pub)
- pub.title = "Cool new Title"
- print(pub)
-
-if __name__ == "__main__":
- main("https://doi.org/10.1021/acs.chemrev.8b00728")
-```
-
-The expected results of calling this methode are:
-| Input-Url | Result |
-|-----------|-----------|
-| supported & correct| A publication Instance |
-| supported & uncorrect| ValueError|
-| not supported | ValueError|
-
-Supported Url are urls, which comply with the url-pattern of supported Journals.
-
-### Supported Journals:
-
-- ACS-Journals
-- (Nature-Journals)
-
-## Testing
-
-``` c
-python -m unittest input/test/<file.py> -v
-# for all tests in directory
-python -m unittest discover input/test -v
-```
-## Authors
-- Florian Jochens
-- Sam Ockenden
-- Julius Schenk
\ No newline at end of file
diff --git a/input/__init__.py b/input/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/input/get/__init__.py b/input/get/__init__.py
deleted file mode 100755
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/input/get/acs.py b/input/get/acs.py
deleted file mode 100755
index 9691845b27ae694a8213a0f0fe5f827c75890eee..0000000000000000000000000000000000000000
--- a/input/get/acs.py
+++ /dev/null
@@ -1,192 +0,0 @@
-#!/usr/bin/env python3
-
-"""
-Child class of JournalFetcher
-Usage: Check if Url can be used with 'can_use_url'
- and then fetch publication with 'get_publication'
-"""
-
-import re
-
-from input.get.journal_fetcher import JournalFetcher
-from input.publication import Publication, Citation
-
-
-class Fetcher(JournalFetcher):
- """
- Specific Fetcher for the ACS journals.
- """
-
- # Constant for the abbreviations of the supported Journals
- SUPPORTED_JOURNALS = ['1021']
-
- @staticmethod
- def can_use_url(url: str) -> str:
- """
- Uses Regex to extract journal specific substrings in Doi.
- TODO: Support non Doi-urls
- """
- matched_url = re.match(r'^(https?://)?(doi.org/|pubs.acs.org/doi/)?(10.(\d{4})/\w+.\S+)', url.strip(". \t\r\n"))
-
- #Checks if match exists
- if matched_url is not None:
- return matched_url[4] in Fetcher.SUPPORTED_JOURNALS
- else:
- return False
-
- @staticmethod
-
-
- def get_pub_light(url: str) -> Publication:
- """
- Fetches html and creates Beatifulsoup-instance in parent class.
- Specific css-searches for ACS-Journals and creates Publication-instance.
- """
-
- # Creation of Soup
- try:
- soup = JournalFetcher.get_soup(url)
- except Exception as error:
- raise error
-
- # Raise Error if re recognizes Pattern, but url isnt correct:
- # For other Urls
- if soup.text.strip(" \t\n")=="Missing resource null":
- raise ValueError("'{}' matches Pattern for 'ACS', but doesnt link to Paper.".format(url))
-
- # For Dois
- if soup.title is not None:
- if soup.title.text == "Error: DOI Not Found":
- raise ValueError("'{}' matches Pattern for 'ACS', but doesnt link to Paper.".format(url))
-
-
- soup_header = soup.select('.article_header')[0]
-
- # Creates Publication
- doi_url = soup_header.select('a[title="DOI URL"]')[0].string
- title = soup_header.select(".hlFld-Title")[0].text
-
- contributors = []
- for author in soup_header.select(".hlFld-ContribAuthor"):
- contributors.append(author.text)
-
- journal = soup_header.select(".cit-title")[0].text
-
- # Replaces abbreviation with whole name
- if journal in JournalFetcher.abbrev_dict:
- journal = JournalFetcher.abbrev_dict[journal]
-
-
- published = soup_header.select(".pub-date-value")[0].text
-
- subjects = []
- subject_soup = soup_header.select('.article_header-taxonomy')[0]
- for subject in subject_soup.select('a'):
- subjects.append(subject.text)
-
- return Publication(doi_url, title, contributors, journal, published,
- subjects)
-
- def get_publication(url: str) -> Publication:
- """
- Fetches html and creates Beatifulsoup-instance in parent class.
- Specific css-searches for ACS-Journals and creates Publication-instance.
- """
-
- # Creation of Soup
- try:
- soup = JournalFetcher.get_soup(url)
- except Exception as error:
- raise error
-
- # Raise Error if re recognizes Pattern, but url isnt correct:
- # For other Urls
- if soup.text.strip(" \t\n")=="Missing resource null":
- raise ValueError("'{}' matches Pattern for 'ACS', but doesnt link to Paper.".format(url))
-
- # For Dois
- if soup.title is not None:
- if soup.title.text == "Error: DOI Not Found":
- raise ValueError("'{}' matches Pattern for 'ACS', but doesnt link to Paper.".format(url))
-
-
- soup_header = soup.select('.article_header')[0]
-
- #Could be used for more specific search
- ref_cit_soup = soup
-
- # Creates Publication
- doi_url = soup_header.select('a[title="DOI URL"]')[0].string
- title = soup_header.select(".hlFld-Title")[0].text
-
- contributors = []
- for author in soup_header.select(".hlFld-ContribAuthor"):
- contributors.append(author.text)
-
- journal = soup_header.select(".cit-title")[0].text
-
- # Replaces abbreviation with whole name
- if journal in JournalFetcher.abbrev_dict:
- journal = JournalFetcher.abbrev_dict[journal]
-
-
- published = soup_header.select(".pub-date-value")[0].text
-
- subjects = []
- subject_soup = soup_header.select('.article_header-taxonomy')[0]
- for subject in subject_soup.select('a'):
- subjects.append(subject.text)
-
-
- references = []
- references_soup = ref_cit_soup.select('ol#references')
- if references_soup != []:
- for reference in references_soup[0].select('li'):
- if reference.select('.refDoi') != []:
- ref_doi = "https://doi.org/{}".format(reference.select('.refDoi')[0].text.strip()[5:])
- else:
- # No Doi -> No Paper
- continue
- ref_title = reference.select('.NLM_article-title')[0].text\
- if reference.select('.NLM_article-title') != [] else None
- ref_journal = reference.select('i')[0].text\
- if reference.select('i') != [] else None
-
- # Replaces abbreviation with whole name
- if ref_journal in JournalFetcher.abbrev_dict:
- ref_journal = JournalFetcher.abbrev_dict[ref_journal]
-
- ref_contributors=[]
- for author in reference.select('.NLM_contrib-group'):
- ref_contributors.append(author.text.replace("\n", " ").replace("\r", ""))
-
- references.append(Citation(ref_doi, ref_title, ref_journal, ref_contributors, cit_type="Reference"))
-
- citations = []
- citation_soup = ref_cit_soup.select('.cited-content_cbyCitation')
- if citation_soup != []:
- for citation in citation_soup[0].select('li'):
- if citation.select('a[title="DOI URL"]') != []:
- cit_doi = citation.select('a[title="DOI URL"]')[0].text
- else:
- # No Doi -> No Paper
- continue
- cit_title = citation.select('.cited-content_cbyCitation_article-title')[0].text\
- if citation.select('.cited-content_cbyCitation_article-title')!= [] else None
- cit_journal = citation.select('.cited-content_cbyCitation_journal-name')[0].text\
- if citation.select('.cited-content_cbyCitation_journal-name') != [] else None
-
- # Replaces abbreviation with whole name
- if cit_journal in JournalFetcher.abbrev_dict:
- cit_journal = JournalFetcher.abbrev_dict[cit_journal]
- cit_contributors =[]
- cit_contributors = citation.select('.cited-content_cbyCitation_article-contributors')[0]\
- .text.replace("\n", " ").replace("\r", "").split(', ')
- # clean up of the last Entry
- cit_contributors_last = cit_contributors.pop().strip(". ")
- if cit_contributors_last != '':
- cit_contributors.append(cit_contributors_last)
- citations.append(Citation(cit_doi, cit_title, cit_journal, cit_contributors, cit_type = "Citation"))
-
- return Publication(doi_url, title, contributors, journal, published
- , subjects, references, citations)
diff --git a/input/get/journal_fetcher.py b/input/get/journal_fetcher.py
deleted file mode 100755
index 514af1f80f5c7d442b790aebf5fe3954d50f8f5d..0000000000000000000000000000000000000000
--- a/input/get/journal_fetcher.py
+++ /dev/null
@@ -1,96 +0,0 @@
-#!/usr/bin/env python3
-
-"""
-Parent class for specific Journal
-"""
-
-from abc import ABCMeta, abstractmethod
-from bs4 import BeautifulSoup
-import requests
-from input.publication import Publication
-
-
-class JournalFetcher(metaclass=ABCMeta):
- """
- This is a abstract-class for fetcher modules
- """
-
- @staticmethod
- def get_soup(url: str) -> BeautifulSoup:
- """
- Retrieves webside-html and returns a BeautifulSoup-instance
-
- Parameters:
- -----------
- :type url: str
- :param url: doi-url to a publication
- :return: BeatifulSoup-instance
- """
- try:
- req = requests.get(url)
- except requests.exceptions.HTTPError as err:
- raise SystemExit(err)
-
- return BeautifulSoup(req.content, 'html.parser')
-
-
- @staticmethod
- @abstractmethod
- def can_use_url(url: str) -> bool:
- """
- Abstract-function to be implemented in subclass.
- Checks if given url links to a supported journal
- """
- raise AttributeError("JournalFetcher for '{}' hasnt implemented 'can_use_url()'".format(url))
-
-
- @staticmethod
- @abstractmethod
- def get_publication(url: str) -> Publication:
- """
- Abstract-function to be implemented in subclass.
- Creates a Publication-instance.
- """
- raise AttributeError("JournalFetcher for '{}' hasnt implemented 'get_publication()'".format(url))
-
-
- # A Dictionary, which connects abbreviation to whole journal-name
- abbrev_dict = {
- "Nat. Protoc.":"Journal of Natural Products"
- ,"PLoS Comput. Biol.":"PLoS Computational Biology"
- ,"PLoS One":"PLoS One"
- ,"Protein Sci.":"Protein Science"
- ,"J. Am. Chem. Soc.":"Journal of the American Chemical Society"
- ,"J. Chem. Phys.":"Journal of Chemical Physics"
- ,"Appl. Sci.":"Applied Science"
- ,"Comput. Sci. Eng.":"Computing in Science & Engineering"
- ,"Beilstein J. Org. Chem.":"Beilstein Journal of Organic Chemistry"
- ,"Biol. Chem.":"Biological Chemistry"
- ,"Isr. J. Chem.":"Israel Journal of Chemistry"
- ,"Nat. Methods":"Nature Methods"
- ,"Proc. Natl. Acad. Sci. U. S. A.":"Proceedings of the National Academy of Sciences of the United States of America"
- ,"J. Phys. Chem. B":"Journal of Physical Chemistry B"
- ,"Carbohydr. Res.":"Carbohydrate Research"
- ,"J. Chem. Theory Comput.":"Journal of Chemical Theory and Computation"
- ,"J. Mol. Biol.":"Journal of Molecular Biology"
- ,"Nucleic Acids Res.":"Nucleic Acids Research"
- ,"J. Comput. Chem.":"Journal of Computational Chemistry"
- ,"J. Cheminf.":"Journal of Cheminformatics"
- ,"J. Med. Chem.":"Journal of Medicinal Chemistry"
- ,"J. Comput.-Aided Mol. Des.":"Journal of Computer-Aided Molecular Design"
- ,"J. Chem. Inf. Model.":"Journal of Chemical Information and Modeling"
- ,"Mol. Cell":"Molecular Cell"
- ,"J. Cell Biolog.":"Journal of Cell Biology"
- ,"Mol. Cell Biol.":"Molecular and Cellular Biology"
- ,"J. Cell Sci.":"Journal of Cell Science"
- ,"Nat. Cell Biol.":"Nature Cell Biology"
- ,"J. Aerosol Sci. Technol.":"Aerosol Science and Technology"
- ,"Mol. Biol. Cell":"Molecular Biology of the Cell"
- ,"Build. Environ.":"Building and Environment"
- ,"Sci. Rep.":"Scientific Reports"
- ,"Nat. Chem.":"Nature Chemistry"
- ,"Nat. Med.":"Nature Medicine"
- ,"Nat. Commun.":"Nature Communications"
- ,"Exp. Cell Res.":"Experimental Cell Research"
- ,"Nat. Chem. Biol.":"Nature Chemical Biology"
- }
\ No newline at end of file
diff --git a/input/get/nature.py b/input/get/nature.py
deleted file mode 100644
index c50ea0ef9d1d4a9a386730e31cc72372cbf698c0..0000000000000000000000000000000000000000
--- a/input/get/nature.py
+++ /dev/null
@@ -1,59 +0,0 @@
-#!/usr/bin/env python3
-
-"""
-Child class of JournalFetcher
-Usage: Check if Url can be used with 'can_use_url'
- and then fetch publication with 'get_publication'
-"""
-
-# import re
-from input.get.journal_fetcher import JournalFetcher
-from input.publication import Publication
-
-
-class Fetcher(JournalFetcher):
-
- """
- scrapes publication metadata from a provided url
- """
-
- # TODO: List of Compatable Journals
- # NOTE: nature does not use journal names in doi links, must match by 10.xxxx identifier instead
- SUPPORTED_JOURNALS = []
-
- @staticmethod
- def can_use_url(url: str) -> bool:
- """
- Checks if given url links to a supported journal.
- """
-
- # TODO: Check the URL for compatability
- # re.match in SUPPORTED_JOURNALS
- return False
-
- @staticmethod
- def get_publication(url: str) -> Publication:
- """
- Creates a Publication-instance.
- """
-
- soup = JournalFetcher.get_soup(url)
-
- _doi_url = "https://doi.org/" + soup.head.find(attrs={"name": "DOI"}).get("content")
- _title = soup.head.find(attrs={"name": "citation_title"}).get("content")
- _journal = soup.head.find(attrs={"name": "citation_journal_title"}).get("content")
- _published = soup.head.find(attrs={"name": "prism.publicationDate"}).get("content")
- _contributors = []
- _subjects = []
-
- for creator in soup.head.findAll(attrs={"name": "dc.creator"}):
- _contributors.append(creator.get("content"))
-
- for subject in soup.head.findAll(attrs={"name": "dc.subject"}):
- _subjects.append(subject.get("content"))
-
- return Publication(_doi_url, _title, _contributors, _journal, _published, _subjects)
-
- # TODO: Exceptions-handling
- # raise ValueException("Cant Fetch: '{}'".format(error))
- # return None
diff --git a/input/get/template_.py b/input/get/template_.py
deleted file mode 100755
index 58de0237bd514f7dd1b5b25f251b740d33e3589e..0000000000000000000000000000000000000000
--- a/input/get/template_.py
+++ /dev/null
@@ -1,51 +0,0 @@
-#!/usr/bin/env python3
-
-"""
-Child class of JournalFetcher
-Usage: None, this is just a template and should be ignored
-"""
-
-# import re
-from input.get.journal_fetcher import JournalFetcher
-from input.publication import Publication
-
-
-class Fetcher(JournalFetcher):
-
- """
- This is only a template and therefore has no functionality
- """
-
- # TODO: Naming-Convention:
- # Class: 'Fetcher'
- # file: [journal-/organisation-name]
- # format = "[a-z]*.py" allowed
- # TODO: List of Compatable Journals
- SUPPORTED_JOURNALS = []
-
- @staticmethod
- def can_use_url(url: str) -> bool:
- """
- Checks if given url links to a supported journal.
- """
-
- # TODO: Check the URL for compatability
- # url_re = re.match(r'(https?://)?(doi.org/)?(10.(\d{4})/\w+.\S+)', url)
- # if url_re is not None:
- # return url_re[4] in SUPPORTED_JOURNALS
- # else:
- return False
-
- @staticmethod
- def get_publication(url: str) -> Publication:
- """
- Creates a Publication-instance.
- """
-
- # TODO: Fetch data from the HTML
- # soup = JournalFetcher.get_soup(url)
- # doi,title,contributors[],journal,publication_date,subjects[],references[],citations[]
- # TODO: Create new Publication-instance
- # return Publication(doi_url, title, contributors = [], journal
- # , publication_date, subjects = [], references = [], citations = [])
- return None
\ No newline at end of file
diff --git a/input/interface.py b/input/interface.py
deleted file mode 100755
index 59515b3a3a2a5361222b8e55d3a7314ab3907132..0000000000000000000000000000000000000000
--- a/input/interface.py
+++ /dev/null
@@ -1,113 +0,0 @@
-#!/usr/bin/env python3
-
-"""
-Interface for the Input-Package only this should be accessed from outside this Package.
-
-"""
-from os import walk
-import importlib
-import pathlib
-import re
-from input.publication import Publication
-
-class InputInterface:
- """
- Singleton which dynamically imports and manages fetchers
- """
-
- instance = None
- get_path = None
- fetcher_classes=[]
-
- # '__new__' is called before '__init__' and gives us an instance
- def __new__(cls, *args, **kwargs):
-
- # checks if an instance exists and if it doesnt creates one
- if cls.instance == None:
- cls.instance = super(InputInterface, cls).__new__(cls,*args, **kwargs)
-
- return cls.instance
-
- def __init__(self):
- # imports all modules
-
- if self.fetcher_classes ==[]:
- self.import_fetcher_classes()
- if self.fetcher_classes ==[]:
- raise AttributeError("No specific Fetchers where found at: '{}'"
- .format(self.get_path))
-
-
- def get_publication(self, url: str) -> Publication:
- """
- The interface-method to get a Publication-instance
- (including it's citations and references)
-
- Parameters
- ----------
- :param url: url to a Publication
- :type url: str
- :return: Publication instance or None if not supported
- """
-
- # Checks if module supports the 'url' and
- # returns a Publication if it does.
- for fetcher_class in InputInterface.fetcher_classes:
- if fetcher_class.can_use_url(url):
- return fetcher_class.get_publication(url)
-
- # No Module for given url was found
- raise ValueError("'{}' is not supported".format(url))
-
- def get_pub_light(self, url: str) -> Publication:
- """
- The interface-method to get a Publication-instance
- (only for main article)
-
- Parameters
- ----------
- :param url: url to a Publication
- :type url: str
- :return: Publication instance or None if not supported
- """
-
- # Checks if module supports the 'url' and
- # returns a Publication if it does.
- for fetcher_class in InputInterface.fetcher_classes:
- if fetcher_class.can_use_url(url):
- return fetcher_class.get_pub_light(url)
-
- # No Module for given url was found
- raise ValueError("'{}' is not supported".format(url))
-
- def get_supported_fetchers(self):
- # print(self.fetcher_classes[0].__name__) Useless right now,
- # because all classes are called the same
- return [a.__name__ for a in self.fetcher_classes]
-
- def import_fetcher_classes(self):
- """
- Searches in 'get', if there are [a-z]*.py modules (specific Fetchers)
- and tries to import them.
- Saves found modules in 'fetcher_files'.
- """
-
- # Path to 'get'-package
- self.get_path = '{}/get'.format(pathlib.Path(__file__).parent.resolve())
-
- # Searches for modules with given Pattern
- fetcher_file_names=[]
- for file in next(walk(self.get_path), (None, None, []))[2]:
- if re.match(r'[a-z]+.py', file) is not None:
- fetcher_file_names.append(file)
-
- # Tries to import those modules and saves their 'Fetcher'-class
- for file in fetcher_file_names:
- try:
- fetcher_class = importlib.import_module("input.get.{}".format(file[:-3]))
- try:
- self.fetcher_classes.append(fetcher_class.__getattribute__('Fetcher'))
- except Exception as error:
- ImportError("Module '{}' does not have a 'Fetcher'-class".format(file[:-3]))
- except Exception:
- raise ImportError("Module '{}' can not be imported".format(file[:-3]))
diff --git a/input/publication.py b/input/publication.py
deleted file mode 100755
index fc512e7173a84695ea566706784c565a7b5ebb8f..0000000000000000000000000000000000000000
--- a/input/publication.py
+++ /dev/null
@@ -1,143 +0,0 @@
-#!/usr/bin/env python3
-
-# this is needed for typing pre python 3.9, this maybe as an large Overhead
-from typing import Any, List
-
-
-class Publication:
- """
- Represents a Publications
- """
- def __init__(self, doi_url: str, title: str \
- , contributors: List[str], journal: str \
- , publication_date: str, subjects: List[str]\
- , references: List[Any] = None, citations: List[Any] = None ):
- """
- Parameters
- ----------
- :param doi_url: doi_url of the publication
- :type doi_url: str
- :param title: title of the publication
- :type title: str
- :param contributors:list of all contributors
- :type contributors: list[]
- :param published: date of release
- :type published: str
- :param subjects: the subject of the Publication
- :type subjects: List[str]
- :param references: the Citation which is been referenced by this Publication
- :type references: List[Any]
- :param citations: the Citation which references this Publication
- :type citations: List[Any]
- :return: None
- """
- self.doi_url = doi_url
- self.title = title
- self.contributors = contributors
- self.journal = journal
- self.publication_date = publication_date
- self.subjects = subjects
- if references is None:
- self.references = []
- else:
- self.references = references
- if citations is None:
- self.citations = []
- else:
- self.citations = citations
-
- # For the 'Verarbeitungsgruppe'
- self.group = None
-
- def __str__(self) -> str:
- return ("Title: {}\n"
- "Doi-url: {}\n"
- "Authors: {}\n"
- "Journal: {}\n"
- "Published on: {}\n"
- "Subjects: {}\n"
- "References: \n{}\n"
- "Citations: \n{}")\
- .format(self.title, self.doi_url, ", ".join(self.contributors)
- , self.journal, self.publication_date
- , ", ".join(self.subjects)
- , "\n".join(self.get_citation_string(self.references))
- , "\n".join(self.get_citation_string(self.citations)))
-
- @staticmethod
- def get_citation_string(citations):
- if citations == []:
- return ["None"]
- else:
- citation_string = []
- for citation in citations:
- citation_string.append(citation.__str__())
- return citation_string
-
- def add_citations(self, citation) -> None:
- """
- Appends a list of Citations or Citation to self.citations.
-
- Parameter
- ---------
- :param citation: Citation or Reference of the Publication
- :type citation: Citation or list[Citation]
- :return: self.citations
- """
- if type(citation) is Citation:
- self.citations.append(citation)
-
- # Checks if 'citation' is a list of Citations
- elif type(citation) is list:
- for _cit in citation:
- if type(_cit) is Citation:
- self.citations.append(_cit)
- else:
- raise TypeError("_set_citation expects Citations or List of Citations, not: '{}'"
- .format(type(_cit)))
- else:
- raise TypeError("_set_citation expects Citations or List of Citations, not: '{}'"
- .format(type(citation)))
-
- return self.citations
-
- def __eq__(self, other) -> bool:
- """ Compares the unique doi_url of two Publications"""
- if type(self)==type(other):
- return self.doi_url == other.doi_url
- return False
-
-
-class Citation:
- def __init__(self, doi_url: str, title: str \
- , journal: str, contributors: List[str] \
- , cit_type: str = "Citation"):
- """
- Parameters
- ----------
- :param doi_url: doi_url of the publication
- :type doi_url: str
- :param title: title of the publication
- :type title: str
- :param contributors: list of all contributors
- :type contributors: List[str]
- :param cit_type: Specifies if Reference or Citation
- :type cit_type: str
- :return: None
- """
-
- self.title = title
- self.doi_url = doi_url
- self.journal = journal
- self.contributors = contributors
- self.cit_type = cit_type
-
- def __str__(self) -> str:
- return ("\t{}-Title: {}\n"
- "\t{}-Doi: {}\n"
- "\t{}-Journal: {}\n"
- "\t{}-Contributors: {}\n")\
- .format(self.cit_type, self.title
- , self.cit_type, self.doi_url
- , self.cit_type, self.journal
- , self.cit_type, ", ".join(self.contributors))
diff --git a/input/requirements.txt b/input/requirements.txt
deleted file mode 100644
index a151126691e7f0a9f1c824e9cbac243a96b32e71..0000000000000000000000000000000000000000
--- a/input/requirements.txt
+++ /dev/null
@@ -1,2 +0,0 @@
-beautifulsoup4
-requests
\ No newline at end of file
diff --git a/input/test/__init__.py b/input/test/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/input/test/test_acs.py b/input/test/test_acs.py
deleted file mode 100644
index e3dfe84a09d3599de32efbab0dd60655b5414152..0000000000000000000000000000000000000000
--- a/input/test/test_acs.py
+++ /dev/null
@@ -1,303 +0,0 @@
-#!/usr/bin/env python
-
-from input.get.acs import Fetcher as Acs
-from input.publication import Publication, Citation
-from input.test.test_input import FetcherTestCase
-
-
-class AcsTestCase(FetcherTestCase):
- """
- Methods with test_* will be detected by unittest and run.
- """
-
- def test_acs_url(self):
- # Positive Testing
- self.can_use_url_test(Acs, "https://doi.org/10.1021/acs.jcim.1c00203" , True)
- self.can_use_url_test(Acs, "doi.org/10.1021/acs.jcim.1c00203" , True)
- self.can_use_url_test(Acs, "10.1021/acs.jcim.1c00203" , True)
- self.can_use_url_test(Acs, " 10.1021/acs.jcim.1c00203" , True)
- self.can_use_url_test(Acs, "10.1021/acs.jcim.1c00203 " , True)
- self.can_use_url_test(Acs, "\t 10.1021/acs.jcim.1c00203 \t\n" , True)
- self.can_use_url_test(Acs, "https://pubs.acs.org/doi/10.1021/acs.jcim.1c00203" , True)
-
- # Negative Testing
- self.can_use_url_test(Acs, "" , False)
- self.can_use_url_test(Acs, "https://doi.org/10.1038/219021a0" , False)
- self.can_use_url_test(Acs, "https://www.nature.com/articles/219021a0" , False)
- self.can_use_url_test(Acs, "https://pubs.acs.org/doi/doi.org/10.1021/acs.jcim.1c00203", False)
-
-
-
- def test_acs_publication(self):
- url = "https://doi.org/10.1021/acs.jcim.1c00203"
- self.get_publication_test(Acs, url, self.expectedPubs[url])
-
- def test_acs_exceptions(self):
- test_url= "https://doi.org/10.1021/acs.jcim.1c002"
- self.get_publication_exception_test(Acs, test_url)
-
- # Dictionary of Expected Results, with url
- expectedPubs = {
- "https://doi.org/10.1021/acs.jcim.1c00203":
- Publication(
- doi_url = "https://doi.org/10.1021/acs.jcim.1c00203",
- title = "AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings",
- contributors = ["Jerome Eberhardt", "Diogo Santos-Martins", "Andreas F. Tillack", "Stefano Forli"],
- journal="Journal of Chemical Information and Modeling",
- publication_date = "July 19, 2021",
- subjects = ["Algorithms","Ligands","Molecules","Receptors","Macrocycles"],
- references = [
- Citation(doi_url = "https://doi.org/10.1002/jcc.21334"
- , title ="AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading"
- , journal="Journal of Computational Chemistry"
- , contributors=["Trott, O.", "Olson, A. J."]
- , cit_type="Reference")
- , Citation(doi_url = "https://doi.org/10.1038/nprot.2016.051"
- , title ="Computational protein-ligand docking and virtual drug screening with the AutoDock suite"
- , journal="Journal of Natural Products"
- , contributors=["Forli, S.","Huey, R.","Pique, M. E.","Sanner, M. F.","Goodsell, D. S.","Olson, A. J."]
- , cit_type="Reference")
- , Citation(title = "A semiempirical free energy force field with charge-based desolvation"
- , doi_url = "https://doi.org/10.1002/jcc.20634"
- , journal="Journal of Computational Chemistry"
- , contributors=["Huey, R.","Morris, G. M.","Olson, A. J.","Goodsell, D. S."]
- , cit_type="Reference")
- , Citation(title="Accelerating autodock4 with gpus and gradient-based local search"
- , doi_url="https://doi.org/10.1021/acs.jctc.0c01006"
- , journal="Journal of Chemical Theory and Computation"
- , contributors=["Santos-Martins, D.","Solis-Vasquez, L.","Tillack, A. F.","Sanner, M. F.","Koch, A.","Forli, S."]
- , cit_type="Reference")
- , Citation(title="AutoDockFR: Advances in Protein-Ligand Docking with Explicitly Specified Binding Site Flexibility"
- , doi_url="https://doi.org/10.1371/journal.pcbi.1004586"
- , journal="PLoS Computational Biology"
- , contributors=["Ravindranath, P. A.","Forli, S.","Goodsell, D. S.","Olson, A. J.","Sanner, M. F."]
- , cit_type="Reference")
- , Citation(title="Docking flexible cyclic peptides with AutoDock CrankPep"
- , doi_url="https://doi.org/10.1021/acs.jctc.9b00557"
- , journal="Journal of Chemical Theory and Computation"
- , contributors=["Zhang, Y.","Sanner, M. F."]
- , cit_type="Reference")
- , Citation(title="Fast, accurate, and reliable molecular docking with QuickVina 2"
- , doi_url="https://doi.org/10.1093/bioinformatics/btv082"
- , journal="Bioinformatics"
- , contributors=["Alhossary, A.","Handoko, S. D.","Mu, Y.","Kwoh, C.-K."]
- , cit_type="Reference")
- , Citation(title="Lessons learned in empirical scoring with smina from the CSAR 2011 benchmarking exercise"
- , doi_url="https://doi.org/10.1021/ci300604z"
- , journal="Journal of Chemical Information and Modeling"
- , contributors=["Koes, D. R.","Baumgartner, M. P.","Camacho, C. J."]
- , cit_type="Reference")
- , Citation(title="Vina-Carb: Improving Glycosidic Angles during Carbohydrate Docking"
- , doi_url="https://doi.org/10.1021/acs.jctc.5b00834"
- , journal="Journal of Chemical Theory and Computation"
- , contributors=["Nivedha, A. K.","Thieker, D. F.","Makeneni, S.","Hu, H.","Woods, R. J."]
- , cit_type="Reference")
- , Citation(title="AutoDock VinaXB: implementation of XBSF, new empirical halogen bond scoring function, into AutoDock Vina"
- , doi_url="https://doi.org/10.1186/s13321-016-0139-1"
- , journal="Journal of Cheminformatics"
- , contributors=["Koebel, M. R.","Schmadeke, G.","Posner, R. G.","Sirimulla, S."]
- , cit_type="Reference")
- , Citation(title="Vinardo: A Scoring Function Based on Autodock Vina Improves Scoring, Docking, and Virtual Screening"
- , doi_url="https://doi.org/10.1371/journal.pone.0155183"
- , journal="PLoS One"
- , contributors=["Quiroga, R.","Villarreal, M. A."]
- , cit_type="Reference")
- , Citation(title="Lennard-Jones potential and dummy atom settings to overcome the AUTODOCK limitation in treating flexible ring systems"
- , doi_url="https://doi.org/10.1021/ci700036j"
- , journal="Journal of Chemical Information and Modeling"
- , contributors=["Forli, S.","Botta, M."]
- , cit_type="Reference")
- , Citation(title="AutoDock4Zn: an improved AutoDock force field for small-molecule docking to zinc metalloproteins"
- , doi_url="https://doi.org/10.1021/ci500209e"
- , journal="Journal of Chemical Information and Modeling"
- , contributors=["Santos-Martins, D.","Forli, S.","Ramos, M. J.","Olson, A. J."]
- , cit_type="Reference")
- , Citation(title="A force field with discrete displaceable waters and desolvation entropy for hydrated ligand docking"
- , doi_url="https://doi.org/10.1021/jm2005145"
- , journal="Journal of Medicinal Chemistry"
- , contributors=["Forli, S.","Olson, A. J."]
- , cit_type="Reference")
- , Citation(title="Directional phosphorylation and nuclear transport of the splicing factor SRSF1 is regulated by an RNA recognition motif"
- , doi_url="https://doi.org/10.1016/j.jmb.2016.04.009"
- , journal="Journal of Molecular Biology"
- , contributors=["Serrano, P.","Aubol, B. E.","Keshwani, M. M.","Forli, S.","Ma, C.-T.","Dutta, S. K.","Geralt, M.","Wüthrich, K.","Adams, J. A."]
- , cit_type="Reference")
- , Citation(title="Covalent docking using autodock: Two-point attractor and flexible side chain methods"
- , doi_url="https://doi.org/10.1002/pro.2733"
- , journal="Protein Science"
- , contributors=["Bianco, G.","Forli, S.","Goodsell, D. S.","Olson, A. J."]
- , cit_type="Reference")
- , Citation(title="Consensus docking: improving the reliability of docking in a virtual screening context"
- , doi_url="https://doi.org/10.1021/ci300399w"
- , journal="Journal of Chemical Information and Modeling"
- , contributors=["Houston, D. R.","Walkinshaw, M. D."]
- , cit_type="Reference")
- , Citation(title="DockBench: an integrated informatic platform bridging the gap between the robust validation of docking protocols and virtual screening simulations"
- , doi_url="https://doi.org/10.3390/molecules20069977"
- , journal="Molecules"
- , contributors=["Cuzzolin, A.","Sturlese, M.","Malvacio, I.","Ciancetta, A.","Moro, S."]
- , cit_type="Reference")
- , Citation(title="A new force field for molecular mechanical simulation of nucleic acids and proteins"
- , doi_url="https://doi.org/10.1021/ja00315a051"
- , journal="Journal of the American Chemical Society"
- , contributors=["Weiner, S. J.","Kollman, P. A.","Case, D. A.","Singh, U. C.","Ghio, C.","Alagona, G.","Profeta, S.","Weiner, P."]
- , cit_type="Reference")
- , Citation(title="AutoDock Bias: improving binding mode prediction and virtual screening using known protein-ligand interactions"
- , doi_url="https://doi.org/10.1093/bioinformatics/btz152"
- , journal="Bioinformatics"
- , contributors=["Arcon, J. P.","Modenutti, C. P.","Avendaño, D.","Lopez, E. D.","Defelipe, L. A.","Ambrosio, F. A.","Turjanski, A. G.","Forli, S.","Marti, M. A."]
- , cit_type="Reference")
- , Citation(title="Inhomogeneous Fluid Approach to Solvation Thermodynamics. 1. Theory"
- , doi_url="https://doi.org/10.1021/jp9723574"
- , journal="Journal of Physical Chemistry B"
- , contributors=["Lazaridis, T."]
- , cit_type="Reference")
- , Citation(title="Inhomogeneous fluid approach to solvation thermodynamics. 2. Applications to simple fluids"
- , doi_url="https://doi.org/10.1021/jp972358w"
- , journal="Journal of Physical Chemistry B"
- , contributors=["Lazaridis, T."]
- , cit_type="Reference")
- , Citation(title="Grid inhomogeneous solvation theory: Hydration structure and thermodynamics of the miniature receptor cucurbit[7]uril"
- , doi_url="https://doi.org/10.1063/1.4733951"
- , journal="Journal of Chemical Physics"
- , contributors=["Nguyen, C. N.","Young, T. K.","Gilson, M. K."]
- , cit_type="Reference")
- , Citation(title="AutoDock-GIST: Incorporating Thermodynamics of Active-Site Water into Scoring Function for Accurate Protein-Ligand Docking"
- , doi_url="https://doi.org/10.3390/molecules21111604"
- , journal="Molecules"
- , contributors=["Uehara, S.","Tanaka, S."]
- , cit_type="Reference")
- , Citation(title="ZINC20—A Free Ultralarge-Scale Chemical Database for Ligand Discovery"
- , doi_url="https://doi.org/10.1021/acs.jcim.0c00675"
- , journal="Journal of Chemical Information and Modeling"
- , contributors=["Irwin, J. J.","Tang, K. G.","Young, J.","Dandarchuluun, C.","Wong, B. R.","Khurelbaatar, M.","Moroz, Y. S.","Mayfield, J.","Sayle, R. A."]
- , cit_type="Reference")
- , Citation(title="Structural biology-inspired discovery of novel KRAS–PDEδ inhibitors"
- , doi_url="https://doi.org/10.1021/acs.jmedchem.7b01243"
- , journal="Journal of Medicinal Chemistry"
- , contributors=["Jiang, Y.","Zhuang, C.","Chen, L.","Lu, J.","Dong, G.","Miao, Z.","Zhang, W.","Li, J.","Sheng, C."]
- , cit_type="Reference")
- , Citation(title="D3R grand challenge 2015: evaluation of protein–ligand pose and affinity predictions"
- , doi_url="https://doi.org/10.1007/s10822-016-9946-8"
- , journal="Journal of Computer-Aided Molecular Design"
- , contributors=["Gathiaka, S.","Liu, S.","Chiu, M.","Yang, H.","Stuckey, J. A.","Kang, Y. N.","Delproposto, J.","Kubish, G.","Dunbar, J. B.","Carlson, H. A.","Burley, S. K.","Walters, W. P.","Amaro, R. E.","Feher, V. A.","Gilson, M. K."]
- , cit_type="Reference")
- , Citation(title="D3R grand challenge 4: blind prediction of protein–ligand poses, affinity rankings, and relative binding free energies"
- , doi_url="https://doi.org/10.1007/s10822-020-00289-y"
- , journal="Journal of Computer-Aided Molecular Design"
- , contributors=["Parks, C. D.","Gaieb, Z.","Chiu, M.","Yang, H.","Shao, C.","Walters, W. P.","Jansen, J. M.","McGaughey, G.","Lewis, R. A.","Bembenek, S. D.","Ameriks, M. K.","Mirzadegan, T.","Burley, S. K.","Amaro, R. E.","Gilson, M. K."]
- , cit_type="Reference")
- , Citation(title="D3R Grand Challenge 4: prospective pose prediction of BACE1 ligands with AutoDock-GPU"
- , doi_url="https://doi.org/10.1007/s10822-019-00241-9"
- , journal="Journal of Computer-Aided Molecular Design"
- , contributors=["Santos-Martins, D.","Eberhardt, J.","Bianco, G.","Solis-Vasquez, L.","Ambrosio, F. A.","Koch, A.","Forli, S."]
- , cit_type="Reference")
- , Citation(title="Comparison of affinity ranking using AutoDock-GPU and MM-GBSA scores for BACE-1 inhibitors in the D3R Grand Challenge 4"
- , doi_url="https://doi.org/10.1007/s10822-019-00240-w"
- , journal="Journal of Computer-Aided Molecular Design"
- , contributors=["El Khoury, L.","Santos-Martins, D.","Sasmal, S.","Eberhardt, J.","Bianco, G.","Ambrosio, F. A.","Solis-Vasquez, L.","Koch, A.","Forli, S.","Mobley, D. L."]
- , cit_type="Reference")
- , Citation(title="Macrocycle modeling in ICM: benchmarking and evaluation in D3R Grand Challenge 4"
- , doi_url="https://doi.org/10.1007/s10822-019-00225-9"
- , journal="Journal of Computer-Aided Molecular Design"
- , contributors=["Lam, P. C.-H.","Abagyan, R.","Totrov, M."]
- , cit_type="Reference")
- , Citation(title="Directory of useful decoys, enhanced (DUD-E): better ligands and decoys for better benchmarking"
- , doi_url="https://doi.org/10.1021/jm300687e"
- , journal="Journal of Medicinal Chemistry"
- , contributors=["Mysinger, M. M.","Carchia, M.","Irwin, J. J.","Shoichet, B. K."]
- , cit_type="Reference")
- , Citation(title="Evaluation of AutoDock and AutoDock Vina on the CASF-2013 benchmark"
- , doi_url="https://doi.org/10.1021/acs.jcim.8b00312"
- , journal="Journal of Chemical Information and Modeling"
- , contributors=["Gaillard, T."]
- , cit_type="Reference")
- , Citation(title="Autodock vina adopts more accurate binding poses but autodock4 forms better binding affinity"
- , doi_url="https://doi.org/10.1021/acs.jcim.9b00778"
- , journal="Journal of Chemical Information and Modeling"
- , contributors=["Nguyen, N. T.","Nguyen, T. H.","Pham, T. N. H.","Huy, N. T.","Bay, M. V.","Pham, M. Q.","Nam, P. C.","Vu, V. V.","Ngo, S. T."]
- , cit_type="Reference")
- , Citation(title="Development and validation of a genetic algorithm for flexible docking"
- , doi_url="https://doi.org/10.1006/jmbi.1996.0897"
- , journal="Journal of Molecular Biology"
- , contributors=["Jones, G.","Willett, P.","Glen, R. C.","Leach, A. R.","Taylor, R."]
- , cit_type="Reference")
- , Citation(title="Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy"
- , doi_url="https://doi.org/10.1021/jm0306430"
- , journal="Journal of Medicinal Chemistry"
- , contributors=["Friesner, R. A.","Banks, J. L.","Murphy, R. B.","Halgren, T. A.","Klicic, J. J.","Mainz, D. T.","Repasky, M. P.","Knoll, E. H.","Shelley, M.","Perry, J. K."]
- , cit_type="Reference")
- , Citation(title="Surflex: fully automatic flexible molecular docking using a molecular similarity-based search engine"
- , doi_url="https://doi.org/10.1021/jm020406h"
- , journal="Journal of Medicinal Chemistry"
- , contributors=["Jain, A. N."]
- , cit_type="Reference")
- , Citation(title="A fast flexible docking method using an incremental construction algorithm"
- , doi_url="https://doi.org/10.1006/jmbi.1996.0477"
- , journal="Journal of Molecular Biology"
- , contributors=["Rarey, M.","Kramer, B.","Lengauer, T.","Klebe, G."]
- , cit_type="Reference")
- , Citation(title="EDock: blind protein–ligand docking by replica-exchange monte carlo simulation"
- , doi_url="https://doi.org/10.1186/s13321-020-00440-9"
- , journal="Journal of Cheminformatics"
- , contributors=["Zhang, W.","Bell, E. W.","Yin, M.","Zhang, Y."]
- , cit_type="Reference")
- , Citation(title="DOCK 6: Impact of new features and current docking performance"
- , doi_url="https://doi.org/10.1002/jcc.23905"
- , journal="Journal of Computational Chemistry"
- , contributors=["Allen, W. J.","Balius, T. E.","Mukherjee, S.","Brozell, S. R.","Moustakas, D. T.","Lang, P. T.","Case, D. A.","Kuntz, I. D.","Rizzo, R. C."]
- , cit_type="Reference")
- , Citation(title="Improving scoring-docking-screening powers of protein–ligand scoring functions using random forest"
- , doi_url="https://doi.org/10.1002/jcc.24667"
- , journal="Journal of Computational Chemistry"
- , contributors=["Wang, C.","Zhang, Y."]
- , cit_type="Reference")
- , Citation(title="ID-Score: a new empirical scoring function based on a comprehensive set of descriptors related to protein–ligand interactions"
- , doi_url="https://doi.org/10.1021/ci300493w"
- , journal="Journal of Chemical Information and Modeling"
- , contributors=["Li, G.-B.","Yang, L.-L.","Wang, W.-J.","Li, L.-L.","Yang, S.-Y."]
- , cit_type="Reference")
- , Citation(title="Further development and validation of empirical scoring functions for structure-based binding affinity prediction"
- , doi_url="https://doi.org/10.1023/a:1016357811882"
- , journal="Journal of Computer-Aided Molecular Design"
- , contributors=["Wang, R.","Lai, L.","Wang, S."]
- , cit_type="Reference")
- , Citation(title="A knowledge-based energy function for protein- ligand, protein- protein, and protein- DNA complexes"
- , doi_url="https://doi.org/10.1021/jm049314d"
- , journal="Journal of Medicinal Chemistry"
- , contributors=["Zhang, C.","Liu, S.","Zhu, Q.","Zhou, Y."]
- , cit_type="Reference")
- , Citation(title="DLIGAND2: an improved knowledge-based energy function for protein–ligand interactions using the distance-scaled, finite, ideal-gas reference state"
- , doi_url="https://doi.org/10.1186/s13321-019-0373-4"
- , journal="Journal of Cheminformatics"
- , contributors=["Chen, P.","Ke, Y.","Lu, Y.","Du, Y.","Li, J.","Yan, H.","Zhao, H.","Zhou, Y.","Yang, Y."]
- , cit_type="Reference")
- , Citation(title="Comparing AutoDock and Vina in ligand/decoy discrimination for virtual screening"
- , doi_url="https://doi.org/10.3390/app9214538"
- , journal="Applied Science"
- , contributors=["Vieira, T. F.","Sousa, S. F."]
- , cit_type="Reference")
- , Citation(title="Benchmark of four popular virtual screening programs: construction of the active/decoy dataset remains a major determinant of measured performance"
- , doi_url="https://doi.org/10.1186/s13321-016-0167-x"
- , journal="Journal of Cheminformatics"
- , contributors=["Chaput, L.","Martinez-Sanz, J.","Quiniou, E.","Rigolet, P.","Saettel, N.","Mouawad, L."]
- , cit_type="Reference")
- , Citation(title="Array programming with NumPy"
- , doi_url="https://doi.org/10.1038/s41586-020-2649-2"
- , journal="Nature"
- , contributors=["Harris, C. R."]
- , cit_type="Reference")
- , Citation(title="Matplotlib: A 2D graphics environment"
- , doi_url="https://doi.org/10.1109/mcse.2007.55"
- , journal="Computing in Science & Engineering"
- , contributors=["Hunter, J. D."]
- , cit_type="Reference")
- ], citations = [
- Citation(doi_url = "https://doi.org/10.1021/acsomega.1c04320"
- , title ="Novel Anti-Hepatitis B Virus Activity of Euphorbia schimperi and Its Quercetin and Kaempferol Derivatives"
- , journal="ACS Omega"
- , contributors=["Mohammad K. Parvez","Sarfaraz Ahmed","Mohammed S. Al-Dosari","Mazin A. S. Abdelwahid","Ahmed H. Arbab","Adnan J. Al-Rehaily","Mai M. Al-Oqail"],cit_type="Citation"),
-
- ]
- )
- }
\ No newline at end of file
diff --git a/input/test/test_input.py b/input/test/test_input.py
deleted file mode 100755
index b2ca55f961565fd1192b72ce992c9ff95bd23020..0000000000000000000000000000000000000000
--- a/input/test/test_input.py
+++ /dev/null
@@ -1,82 +0,0 @@
-import unittest
-from input.get.journal_fetcher import JournalFetcher
-from input.interface import InputInterface
-from input.publication import Publication
-
-"""
-Testing the Publication fetcher
-
-Publication 1: 'https://doi.org/10.1021/acs.jcim.1c00203'
-Publication 2: 'doi.org/10.1021/acs.jcim.1c00917'
-Publication 3: '10.1038/nchem.1781'
-Publication 4: '11.12/jaj'
-Publication 5: '11.12/'
-Publication 6: 'https://doi.org/10.1021/acs.jmedchem.0c01332' # Paper is a PDF
-"""
-# TODO: Testcases for:
-# - Specific Journals: Inherit from FetcherTestCase
-# - interface module-importer (test case)
-# - Error detection
-# - wrong/no Journal_fetchers
-# - wrong urls
-# - correct Types in publication
-# - Edgecases (i.e. paper as pdf, no connection, etc)
-
-
-class InterfaceTestCase(unittest.TestCase):
- def setUp(self):
- self.assertEqual(InputInterface.instance, None)
- self.interface = InputInterface()
-
- def test_singleton(self):
- # interface should already be made in setUp()
- self.assertNotEqual(self.interface.instance, None)
- new_interface = InputInterface()
- self.assertEqual(self.interface, new_interface)
-
- # def test_imported_modules(self):
- # fetchers = self.interface.get_supported_fetchers
-
-class FetcherTestCase(unittest.TestCase):
-
-
- def can_use_url_test(self, fetcher : JournalFetcher, test_url: str, expected_res: bool):
- # Tests the 'can_use_url'-method
- self.assertEqual(fetcher.can_use_url(test_url), expected_res)
-
-
- def get_publication_test(self, fetcher : JournalFetcher, test_url: str, expected_res: Publication):
- """
- this test asserts that every variable is equals to the expected result
- """
- actual_res = fetcher.get_publication(test_url)
- self.assertEqual(actual_res.doi_url, expected_res.doi_url)
- self.assertEqual(actual_res.title, expected_res.title)
- self.assertEqual(actual_res.contributors, expected_res.contributors)
- self.assertEqual(actual_res.journal, expected_res.journal)
- self.assertEqual(actual_res.publication_date, expected_res.publication_date)
- self.assertEqual(actual_res.subjects, expected_res.subjects)
-
- # Checking for all references
- self.assertEqual(len(actual_res.references), len(expected_res.references))
- num_references = len(expected_res.references)
- for i in range(num_references):
- self.assertEqual(actual_res.references[i].doi_url, expected_res.references[i].doi_url)
- self.assertEqual(actual_res.references[i].journal, expected_res.references[i].journal)
- self.assertEqual(actual_res.references[i].contributors, expected_res.references[i].contributors)
- self.assertEqual(actual_res.references[i].cit_type, expected_res.references[i].cit_type)
-
- # Checking for all citations
- self.assertEqual(len(actual_res.citations), len(expected_res.citations))
- num_citations = len(expected_res.citations)
- for i in range(num_citations):
- self.assertEqual(actual_res.citations[i].doi_url, expected_res.citations[i].doi_url)
- self.assertEqual(actual_res.citations[i].journal, expected_res.citations[i].journal)
- self.assertEqual(actual_res.citations[i].contributors, expected_res.citations[i].contributors)
- self.assertEqual(actual_res.citations[i].cit_type, expected_res.citations[i].cit_type)
-
-
- def get_publication_exception_test(self, fetcher: JournalFetcher, test_url: str):
- # Ckecks
- with self.assertRaises(ValueError):
- fetcher.get_publication(test_url)
\ No newline at end of file
diff --git a/input_old/README.md b/input_old/README.md
deleted file mode 100644
index 76bd11d5d70daac13e190f4d52269eb381413c69..0000000000000000000000000000000000000000
--- a/input_old/README.md
+++ /dev/null
@@ -1,3 +0,0 @@
-# Projekt CiS-Projekt 2021/22
-Input-Skripts
-
diff --git a/input_old/__pycache__/input_fj.cpython-39.pyc b/input_old/__pycache__/input_fj.cpython-39.pyc
deleted file mode 100644
index a3e6099f4ab4c56400b2698c812d4b5fc9a9a7aa..0000000000000000000000000000000000000000
Binary files a/input_old/__pycache__/input_fj.cpython-39.pyc and /dev/null differ
diff --git a/input_old/example_urls b/input_old/example_urls
deleted file mode 100644
index 96ac680c65edddcb495312000157edea1ab94884..0000000000000000000000000000000000000000
--- a/input_old/example_urls
+++ /dev/null
@@ -1,2 +0,0 @@
-https://pubs.acs.org/doi/10.1021/acs.jcim.5b00332
-https://pubs.acs.org/doi/10.1021/acs.jcim.6b00709
diff --git a/input_old/input_fj.py b/input_old/input_fj.py
deleted file mode 100644
index ecc8e68fc5a84a446ae3f09dcb5ed56e8d262766..0000000000000000000000000000000000000000
--- a/input_old/input_fj.py
+++ /dev/null
@@ -1,154 +0,0 @@
-#!/usr/bin/env python3
-"""
-Functions for information retrieval of articles from the ACS journal JCIM
-
-"""
-
-__author__ = "Florian Jochens"
-__email__ = "fj@andaco.de"
-__status__ = "Production"
-#__copyright__ = ""
-#__credits__ = ["", "", "", ""]
-#__license__ = ""
-#__version__ = ""
-#__maintainer__ = ""
-
-from bs4 import BeautifulSoup as bs
-import requests as req
-import sys
-from pathlib import Path
-
-class Publication:
- #_registry = []
- _citations = []
- _references = []
-
- def __init__(self, title, publication_date, contributors, doi_url,
- subjects = None, num_citations = None):
- #self._registry.append(self)
- self.title = title
- self.publication_date = publication_date
- self.contributors = contributors
- self.doi_url = doi_url
- self.subjects = subjects
- self.num_citations = num_citations
- #self._citations = []
- #self._references = []
-
-class Citation:
- def __init__(self, title, journal, contributors, doi_url):
- self.title = title
- self.journal = journal
- self.contributors = contributors
- self.doi_url = doi_url
-
-class References:
- def __init__(self, title, journal, contributors, doi_url):
- self.title = title
- self.journal = journal
- self.contributors = contributors
- self.doi_url = doi_url
-
-def get_article_info(soup):
- header = soup.find('div', class_ = 'article_header-left pull-left')
- article_title = header.find('span', class_ = 'hlFld-Title').text
- publication_date = header.find('span', class_ = 'pub-date-value').text
- for link in header.find('div', class_ = 'article_header-doiurl'):
- doi_url = link.get('href')
- subs = header.find('div', class_ = 'article_header-taxonomy')
- subjects = []
- for sub in subs.find_all('a'):
- subjects.append(sub.get('title'))
- cons = header.find('ul', class_ = 'loa')
- contributors = []
- for con in cons.find_all('span', class_ = 'hlFld-ContribAuthor'):
- contributors.append(con.text)
- numc = header.find('div', class_ = 'articleMetrics_count')
- if not numc.a:
- num_citations = 0
- else:
- num_citations = numc.a.text
-
- pub = Publication(article_title, publication_date, contributors, doi_url,
- subjects, num_citations)
- return pub
-
-def get_download_url():
- export = soup.find('div', class_ = 'cit-download-dropdown_content')
- url = 'https://pubs.acs.org'
- for link in export.find_all('a'):
- if link.get('title') == 'Citation and references':
- url += link.get('href')
- print(url)
- return url
-
-def download(url): # Download citation and references file
- if url.find('='):
- filename = url.rsplit('=', 1)[1]
- path = Path(('./files/' + filename))
- if path.is_file():
- print("File already exists")
- else:
- print("File does not exist")
-
-def get_citation_info(pub, num_citations, soup):
- pub._citations = []
- details = soup.find('ol', class_ = 'cited-content_cbyCitation')
- titles = []
- for title in details.find_all('span',
- class_ = 'cited-content_cbyCitation_article-title'):
- titles.append(title.text.replace('.', ''))
- journal_names = []
- for name in details.find_all('span',
- class_ = 'cited-content_cbyCitation_journal-name'):
- journal_names.append(name.text)
- doi_urls = []
- for url in details.find_all('a'):
- doi_urls.append(url.get('href'))
- contributors = []
- for contrib in details.find_all('span',
- class_ = 'cited-content_cbyCitation_article-contributors'):
- contributors.append(contrib.text)
- for i in range(0, int(num_citations)):
- pub._citations.append(Citation(titles[i], journal_names[i],
- contributors[i], doi_urls[i]))
-def print_pub_info(pub):
- print(f'''Article title: {pub.title}
-Publication date: {pub.publication_date}
-DOI-URL: {pub.doi_url}
-
-Subjects:''')
- print(*(pub.subjects), sep = ", ")
- print('\nContributors:')
- print(*(pub.contributors), sep = ", ")
-
- if int(pub.num_citations) > 0:
- if int(pub.num_citations) == 1:
- print(f'\nThis publication is cited by the following publication:\n')
- else:
- print(f'\nThis publication is cited by the following {pub.num_citations} publications:\n')
- for citation in pub._citations:
- print(f'''
- Title: {citation.title}
- Journal: {citation.journal}
- Contributors: {citation.contributors}
- DOI-URL: {citation.doi_url}
- ''')
- else:
- print('\nThis publication is not cited by any other publication.')
-
-def input(url):
- html_text = req.get(url).text
- soup = bs(html_text, 'html.parser')
-
- pub = get_article_info(soup)
- if int(pub.num_citations) > 0:
- get_citation_info(pub, int(pub.num_citations), soup)
- return pub
-
-#if len(sys.argv) != 2:
-# sys.stderr.write('Usage: {} <url>\n'.format(sys.argv[0]))
-# exit(1)
-#url = sys.argv[1]
-#pub = input(url)
-#print_pub_info(pub)
diff --git a/input_old/pub.py b/input_old/pub.py
deleted file mode 100644
index 13b90e804cd485813b731385b319b3077a017dd2..0000000000000000000000000000000000000000
--- a/input_old/pub.py
+++ /dev/null
@@ -1,32 +0,0 @@
-class Publication:
- #_registry = []
- #_citations = []
- #_references = []
-
- def __init__(self, title, publication_date, contributors, doi_url,
- subjects, num_citations):
- #self._registry.append(self)
- self.title = title
- self.publication_date = publication_date
- self.contributors = contributors
- self.doi_url = doi_url
- self.subjects = subjects
- self.num_citations = num_citations
- self.num_references = num_references
- self._citations = []
- self._references = []
-
-class Citation:
- def __init__(self, title, journal, contributors, doi_url):
- self.title = title
- self.journal = journal
- self.contributors = contributors
- self.doi_url = doi_url
-
-class References:
- def __init__(self, title, journal, contributors, doi_url):
- self.title = title
- self.journal = journal
- self.contributors = contributors
- self.doi_url = doi_url
-
diff --git a/input_old/test.py b/input_old/test.py
deleted file mode 100755
index dc623ca182691e9e06a6713a4d3d5dcf0bbf23c2..0000000000000000000000000000000000000000
--- a/input_old/test.py
+++ /dev/null
@@ -1,15 +0,0 @@
-#!/usr/bin/env python3
-
-from input_fj import input, print_pub_info
-import sys
-
-if len(sys.argv) != 3:
- sys.stderr.write('Usage: {} <url> <url>\n'.format(sys.argv[0]))
- exit(1)
-url = sys.argv[1]
-url2 = sys.argv[2]
-pub = input(url)
-print_pub_info(pub)
-pub2 = input(url2)
-print_pub_info(pub2)
-
diff --git a/input_old/x b/input_old/x
deleted file mode 100644
index c8ade9d56a520a3ac57e5eadce8b81bb3e63c0dd..0000000000000000000000000000000000000000
--- a/input_old/x
+++ /dev/null
@@ -1,234 +0,0 @@
-Article title: Feasibility of Active Machine Learning for Multiclass Compound Classification
-Publication date: January 7, 2016
-DOI-URL: https://doi.org/10.1021/acs.jcim.5b00332
-
-Subjects:
-Algorithms, Molecules, Drug discovery, Screening assays, Receptors
-
-Contributors:
-Tobias Lang, Florian Flachsenberg, Ulrike von Luxburg, Matthias Rarey
-
-This publication is cited by the following 30 publications:
-
-
- Title: Concepts of Artificial Intelligence for Computer-Assisted Drug Discovery
- Journal: Chemical Reviews
- Contributors: Xin Yang, Yifei Wang, Ryan Byrne, Gisbert Schneider, Shengyong Yang.
- DOI-URL: https://doi.org/10.1021/acs.chemrev.8b00728
-
-
- Title: De Novo Molecule Design by Translating from Reduced Graphs to SMILES
- Journal: Journal of Chemical Information and Modeling
- Contributors: Peter Pogány, Navot Arad, Sam Genway, Stephen D. Pickett.
- DOI-URL: https://doi.org/10.1021/acs.jcim.8b00626
-
-
- Title: Designing Algorithms To Aid Discovery by Chemical Robots
- Journal: ACS Central Science
- Contributors: Alon B. Henson, Piotr S. Gromski, Leroy Cronin.
- DOI-URL: https://doi.org/10.1021/acscentsci.8b00176
-
-
- Title: Modeling Kinase Inhibition Using Highly Confident Data Sets
- Journal: Journal of Chemical Information and Modeling
- Contributors: Sorin Avram, Alina Bora, Liliana Halip, Ramona Curpăn.
- DOI-URL: https://doi.org/10.1021/acs.jcim.7b00729
-
-
- Title: Predictive Models for Fast and Effective Profiling of Kinase Inhibitors
- Journal: Journal of Chemical Information and Modeling
- Contributors: Alina Bora, Sorin Avram, Ionel Ciucanu, Marius Raica, and Stefana Avram .
- DOI-URL: https://doi.org/10.1021/acs.jcim.5b00646
-
-
- Title: Evaluation of categorical matrix completion algorithms: toward improved active learning for drug discovery
- Journal: Bioinformatics
- Contributors: Huangqingbo Sun, Robert F Murphy, .
- DOI-URL: https://doi.org/10.1093/bioinformatics/btab322
-
-
- Title: An Artificial Intelligence Approach Based on Hybrid CNN-XGB Model to Achieve High Prediction Accuracy through Feature Extraction, Classification and Regression for Enhancing Drug Discovery in Biomedicine
- Journal: International Journal of Biology and Biomedical Engineering
- Contributors: Mukesh Madanan, Biju T. Sayed, Nurul Akhmal Mohd Zulkefli, Nitha C. Velayudhan.
- DOI-URL: https://doi.org/10.46300/91011.2021.15.22
-
-
- Title: Artificial Intelligence in Medicinal Chemistry
- Journal:
- Contributors: Edward Griffen, Alexander Dossetter, Andrew Leach, Shane Montague.
- DOI-URL: https://doi.org/10.1002/0471266949.bmc267
-
-
- Title: Practical Chemogenomic Modeling and Molecule Discovery Strategies Unveiled by Active Learning
- Journal:
- Contributors: J.B. Brown.
- DOI-URL: https://doi.org/10.1016/B978-0-12-801238-3.11533-8
-
-
- Title: Machine learning phases and criticalities without using real data for training
- Journal: Physical Review B
- Contributors: D.-R. Tan, F.-J. Jiang.
- DOI-URL: https://doi.org/10.1103/PhysRevB.102.224434
-
-
- Title: Active learning effectively identifies a minimal set of maximally informative and asymptotically performant cytotoxic structure–activity patterns in NCI-60 cell lines
- Journal: RSC Medicinal Chemistry
- Contributors: Takumi Nakano, Shunichi Takeda, J.B. Brown.
- DOI-URL: https://doi.org/10.1039/D0MD00110D
-
-
- Title: Active learning efficiently converges on rational limits of toxicity prediction and identifies patterns for molecule design
- Journal: Computational Toxicology
- Contributors: Ahsan Habib Polash, Takumi Nakano, Christin Rakers, Shunichi Takeda, J.B. Brown.
- DOI-URL: https://doi.org/10.1016/j.comtox.2020.100129
-
-
- Title: Practical considerations for active machine learning in drug discovery
- Journal: Drug Discovery Today: Technologies
- Contributors: Daniel Reker.
- DOI-URL: https://doi.org/10.1016/j.ddtec.2020.06.001
-
-
- Title: Designing compact training sets for data-driven molecular property prediction through optimal exploitation and exploration
- Journal: Molecular Systems Design & Engineering
- Contributors: Bowen Li, Srinivas Rangarajan.
- DOI-URL: https://doi.org/10.1039/C9ME00078J
-
-
- Title: Applicability Domain of Active Learning in Chemical Probe Identification: Convergence in Learning from Non-Specific Compounds and Decision Rule Clarification
- Journal: Molecules
- Contributors: Ahsan Habib Polash, Takumi Nakano, Shunichi Takeda, J.B. Brown.
- DOI-URL: https://doi.org/10.3390/molecules24152716
-
-
- Title: Capturing and applying knowledge to guide compound optimisation
- Journal: Drug Discovery Today
- Contributors: Matthew Segall, Tamsin Mansley, Peter Hunt, Edmund Champness.
- DOI-URL: https://doi.org/10.1016/j.drudis.2019.02.004
-
-
- Title: A novel graph kernel on chemical compound classification
- Journal: Journal of Bioinformatics and Computational Biology
- Contributors: Qiangrong Jiang, Jiajia Ma.
- DOI-URL: https://doi.org/10.1142/S0219720018500269
-
-
- Title: Accelerating Drug Discovery Using Convolution Neural Network Based Active Learning
- Journal:
- Contributors: Pengfei Liu, Kwong-Sak Leung.
- DOI-URL: https://doi.org/10.1109/TENCON.2018.8650298
-
-
- Title: An Adaptive Lightweight Security Framework Suited for IoT
- Journal:
- Contributors: Menachem Domb.
- DOI-URL: https://doi.org/10.5772/intechopen.73712
-
-
- Title: Adaptive mining and model building of medicinal chemistry data with a multi-metric perspective
- Journal: Future Medicinal Chemistry
- Contributors: JB Brown.
- DOI-URL: https://doi.org/10.4155/fmc-2018-0188
-
-
- Title: Chemogenomic Active Learning's Domain of Applicability on Small, Sparse qHTS Matrices: A Study Using Cytochrome P450 and Nuclear Hormone Receptor Families
- Journal: ChemMedChem
- Contributors: Christin Rakers, Rifat Ara Najnin, Ahsan Habib Polash, Shunichi Takeda, J.B. Brown.
- DOI-URL: https://doi.org/10.1002/cmdc.201700677
-
-
- Title: Automating drug discovery
- Journal: Nature Reviews Drug Discovery
- Contributors: Gisbert Schneider.
- DOI-URL: https://doi.org/10.1038/nrd.2017.232
-
-
- Title: Classifiers and their Metrics Quantified
- Journal: Molecular Informatics
- Contributors: J. B. Brown.
- DOI-URL: https://doi.org/10.1002/minf.201700127
-
-
- Title: Active Search for Computer-aided Drug Design
- Journal: Molecular Informatics
- Contributors: Dino Oglic, Steven A. Oatley, Simon J. F. Macdonald, Thomas Mcinally, Roman Garnett, Jonathan D. Hirst, Thomas Gärtner.
- DOI-URL: https://doi.org/10.1002/minf.201700130
-
-
- Title: Selection of Informative Examples in Chemogenomic Datasets
- Journal:
- Contributors: Daniel Reker, J. B. Brown.
- DOI-URL: https://doi.org/10.1007/978-1-4939-8639-2_13
-
-
- Title: The value of prior knowledge in machine learning of complex network systems
- Journal: Bioinformatics
- Contributors: Dana Ferranti, David Krane, David Craft, .
- DOI-URL: https://doi.org/10.1093/bioinformatics/btx438
-
-
- Title: Lightweight adaptive Random-Forest for IoT rule generation and execution
- Journal: Journal of Information Security and Applications
- Contributors: Menachem Domb, Elisheva Bonchek-Dokow, Guy Leshem.
- DOI-URL: https://doi.org/10.1016/j.jisa.2017.03.001
-
-
- Title: Active learning for computational chemogenomics
- Journal: Future Medicinal Chemistry
- Contributors: Daniel Reker, Petra Schneider, Gisbert Schneider, JB Brown.
- DOI-URL: https://doi.org/10.4155/fmc-2016-0197
-
-
- Title: Small Random Forest Models for Effective Chemogenomic Active Learning
- Journal: Journal of Computer Aided Chemistry
- Contributors: Christin Rakers, Daniel Reker, J.B. Brown.
- DOI-URL: https://doi.org/10.2751/jcac.18.124
-
-
- Title: Large-Scale Off-Target Identification Using Fast and Accurate Dual Regularized One-Class Collaborative Filtering and Its Application to Drug Repurposing
- Journal: PLOS Computational Biology
- Contributors: Hansaim Lim, Aleksandar Poleksic, Yuan Yao, Hanghang Tong, Di He, Luke Zhuang, Patrick Meng, Lei Xie, .
- DOI-URL: https://doi.org/10.1371/journal.pcbi.1005135
-
-Article title: Matched Molecular Series: Measuring SAR Similarity
-Publication date: May 1, 2017
-DOI-URL: https://doi.org/10.1021/acs.jcim.6b00709
-
-Subjects:
-Substituents, Mathematical methods, Structure activity relationship, Biological databases
-
-Contributors:
-Emanuel S. R. Ehmki, Christian Kramer
-
-This publication is cited by the following 5 publications:
-
-
- Title: Matched Molecular Series Analysis for ADME Property Prediction
- Journal: Journal of Chemical Information and Modeling
- Contributors: Mahendra Awale, Sereina Riniker, Christian Kramer.
- DOI-URL: https://doi.org/10.1021/acs.jcim.0c00269
-
-
- Title: Approaches using AI in medicinal chemistry
- Journal:
- Contributors: Christian Tyrchan, Eva Nittinger, Dea Gogishvili, Atanas Patronov, Thierry Kogej.
- DOI-URL: https://doi.org/10.1016/B978-0-12-822249-2.00002-5
-
-
- Title: Bioactivity Prediction Based on Matched Molecular Pair and Matched Molecular Series Methods
- Journal: Current Pharmaceutical Design
- Contributors: Xiaoyu Ding, Chen Cui, Dingyan Wang, Jihui Zhao, Mingyue Zheng, Xiaomin Luo, Hualiang Jiang, Kaixian Chen.
- DOI-URL: https://doi.org/10.2174/1381612826666200427111309
-
-
- Title: BRADSHAW: a system for automated molecular design
- Journal: Journal of Computer-Aided Molecular Design
- Contributors: Darren V. S. Green, Stephen Pickett, Chris Luscombe, Stefan Senger, David Marcus, Jamel Meslamani, David Brett, Adam Powell, Jonathan Masson.
- DOI-URL: https://doi.org/10.1007/s10822-019-00234-8
-
-
- Title: The use of matched molecular series networks for cross target structure activity relationship translation and potency prediction
- Journal: MedChemComm
- Contributors: Christopher E. Keefer, George Chang.
- DOI-URL: https://doi.org/10.1039/C7MD00465F
-
diff --git a/verarbeitung/Processing.py b/verarbeitung/Processing.py
deleted file mode 100644
index 0dcc7391bd5a633a86841f6097f486017ae94dfa..0000000000000000000000000000000000000000
--- a/verarbeitung/Processing.py
+++ /dev/null
@@ -1,247 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-Functions 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__ = ""
-
-from bs4 import BeautifulSoup as bs
-import requests as req
-import sys
-from pathlib import Path
-from input_fj import input
-from input_test import input_test_func
-from json_demo import output_to_json
-
-# adds every publication from input list to graph structure
-# doi_input_list: list of publication dois from user
-def initialize_nodes_list(doi_input_list, search_depth_max, search_height_max, test_var):
- references_pub_obj_list = []
- citations_pub_obj_list = []
-
- for pub_doi in doi_input_list:
-
- #checks if its a test and chooses input function accordingly
- if(test_var):
- pub = input_test_func(pub_doi)
- else:
- pub = input(pub_doi)
-
- # checks if publication already exists in nodes
- not_in_nodes = True
- for node in nodes: # checks if a pub is already in nodes
- if (pub.doi_url == node.doi_url):
- not_in_nodes = False
- break
- if (not_in_nodes):
- nodes.append(pub)
- pub.group = "input"
- else:
- doi_input_list.remove(pub_doi)
-
- # inserts references as publication objects into list and
- # inserts first depth references into nodes/edges if maximum search depth > 0
- for reference in create_graph_structure_references(pub, 0, search_depth_max, test_var):
- references_pub_obj_list.append(reference)
-
- # inserts citations as publication objects into list and
- # inserts first height citations into nodes if maximum search height > 0
- for citation in create_graph_structure_citations(pub, 0, search_height_max, test_var):
- citations_pub_obj_list.append(citation)
-
- return(references_pub_obj_list, citations_pub_obj_list)
-
-
-# adds edges between citation and reference group
-def complete_inner_edges(test_var):
- for node in nodes:
- if (node.group == "depth"):
- for citation in node.citations:
- for cit in nodes:
- if (citation.doi_url == cit.doi_url and [citation.doi_url, node.doi_url] not in edges):
- edges.append([citation.doi_url, node.doi_url])
- if (node.group == "height"):
- for reference in node.references:
- for ref in nodes:
- if (reference.doi_url == ref.doi_url and [node.doi_url, reference.doi_url] not in edges):
- edges.append([node.doi_url,reference.doi_url])
-
-
-
-# adds a node for every publication unknown
-# adds edges for references between publications
-def create_graph_structure_references(pub, search_depth, search_depth_max, test_var):
- references_pub_obj_list = []
- for reference in pub.references:
- not_in_nodes = True
- for node in nodes:
- # checks every reference for duplication
- if (reference.doi_url == node.doi_url):
- not_in_nodes = False
- break
- if (not_in_nodes):
- if (search_depth < search_depth_max):
-
- #checks if its a test and chooses input function accordingly
- if (test_var):
- reference_pub_obj = input_test_func(reference.doi_url)
- else:
- reference_pub_obj = input(reference.doi_url)
-
- reference_pub_obj.group = "depth"
- nodes.append(reference_pub_obj)
- edges.append([pub.doi_url,reference_pub_obj.doi_url])
- references_pub_obj_list.append(reference_pub_obj)
-
- # adds edge only if citation already exists
- elif [pub.doi_url,reference.doi_url] not in edges:
- edges.append([pub.doi_url,reference.doi_url])
- return references_pub_obj_list
-
-
-# recursive function to implement height-first-search on references
-# references_pub_obj_list: input list of references as publication objects
-# search_depth: current search_depth of height-first-search
-# search_depth_max: maximal search_depth for dfs
-def process_references_rec(references_pub_obj_list, search_depth, search_depth_max, test_var):
- # adds next level to nodes/edges
- for pub in references_pub_obj_list:
- new_reference_pub_obj_list = create_graph_structure_references(pub, search_depth, search_depth_max, test_var)
-
- # If the maximum height has not yet been reached, calls function recursivly with increased height
- if (search_depth < search_depth_max):
- process_references_rec(new_reference_pub_obj_list, search_depth+1, search_depth_max, test_var)
-
-
-
-
-# adds a node for every publication unknown
-# adds edges for citations between publications
-def create_graph_structure_citations(pub, search_height, search_height_max, test_var):
- citations_pub_obj_list = []
- for citation in pub.citations:
- not_in_nodes = True
- for node in nodes:
- # checks every citation for duplication
- if (citation.doi_url == node.doi_url):
- not_in_nodes = False
- break
- if (not_in_nodes):
- if (search_height < search_height_max):
-
- #checks if its a test and chooses input function accordingly
- if (test_var):
- citation_pub_obj = input_test_func(citation.doi_url)
- else:
- citation_pub_obj = input(citation.doi_url)
-
- citation_pub_obj.group = "height"
- nodes.append(citation_pub_obj)
- edges.append([citation_pub_obj.doi_url,pub.doi_url])
- citations_pub_obj_list.append(citation_pub_obj)
-
- # adds only edge if citation already exists
- elif [citation.doi_url,pub.doi_url] not in edges:
- edges.append([citation.doi_url,pub.doi_url])
- return citations_pub_obj_list
-
-
-
-# recursive function to implement height-first-search on citations
-# citations_pub_obj_list: input list of citations as publication objects
-# search_height: current search_height of height-first-search
-# search_height_max: maximal search_height for dfs
-def process_citations_rec(citations_pub_obj_list, search_height, search_height_max, test_var):
- # adds next level to nodes/edges
- for pub in citations_pub_obj_list:
- new_citation_pub_obj_list = create_graph_structure_citations(pub, search_height, search_height_max, test_var)
-
- # If the maximum height has not yet been reached, calls function recursivly with increased height
- if (search_height < search_height_max):
- process_citations_rec(new_citation_pub_obj_list, search_height+1, search_height_max, test_var)
-
-
-
-
-# main function to call. Needs as input:
-# doi_input_list: input list of dois
-# search_height: max search height to process to
-# search_depth: max search depth to process to
-# test_var: only needed for unit test as True, default is False
-def process_main(doi_input_list, search_height, search_depth, test_var = False):
- # ERROR-Handling doi_array = NULL
- if (len(doi_input_list) == 0):
- print("Error, no input data")
-
- # ERROR- if a negative number is entered for height
- if (search_height < 0):
- print("Error, search_height of search must be positive")
-
- # ERROR- if a negative number is entered for depth
- if (search_depth < 0):
- print("Error, search_depth of search must be positive")
-
- # create empty array for the nodes
- # create empty array for the edges
- global nodes, edges
- nodes = []
- edges = []
-
- # 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(doi_input_list,search_depth, search_height, test_var)
-
- # function calls to begin recursive processing up to max depth/height
- process_citations_rec(citations_obj_list, 1, search_height, test_var)
- process_references_rec(references_obj_list, 1, search_depth, 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)
-
- # only for unit tests
- if (test_var == True):
- doi_nodes_list = []
- for node in nodes:
- doi_nodes_list.append(node.doi_url)
- return(doi_nodes_list, edges)
-
-
-
-
-# a function to print nodes and edges from a graph
-def print_graph(nodes, edges):
- print("Knoten:\n")
- for node in nodes:
- print(node.title, "\n")
- print("\nKanten:\n")
- for edge in edges:
- print(edge,"\n")
-
-
-# program test, because there is no connection to UI yet.
-def try_known_publications():
- doi_list = []
- doi_list.append('https://pubs.acs.org/doi/10.1021/acs.jcim.9b00249')
- #arr.append('https://pubs.acs.org/doi/10.1021/acs.jcim.9b00249')
- doi_list.append('https://doi.org/10.1021/acs.jmedchem.0c01332')
- #arr.append('https://doi.org/10.1021/acs.jcim.0c00741')
-
- #arr.append('https://doi.org/10.1021/ci700007b')
- #arr.append('https://doi.org/10.1021/acs.jcim.5b00292')
- #url = sys.argv[1]
- #arr.append[url]
-
-
- nodes,edges = process_main(doi_list,2,2)
-
- print_graph(nodes, edges)
\ No newline at end of file
diff --git a/verarbeitung/Processing_unittest.py b/verarbeitung/Processing_unittest.py
deleted file mode 100644
index 772d57204ce3374211d1d1fd3d08d279f085aac3..0000000000000000000000000000000000000000
--- a/verarbeitung/Processing_unittest.py
+++ /dev/null
@@ -1,66 +0,0 @@
-import unittest
-from Processing import process_main
-
-class ProcessingTest(unittest.TestCase):
- def testCycle(self):
- nodes, edges = process_main(['doiz1'],1,1,True)
- self.assertCountEqual(nodes, ['doiz1', 'doiz2'])
- self.assertCountEqual(edges, [['doiz1', 'doiz2'], ['doiz2', 'doiz1']])
-
- nodes, edges = process_main(['doiz1'],2,2,True)
- self.assertCountEqual(nodes, ['doiz1', 'doiz2'])
- self.assertCountEqual(edges, [['doiz2', 'doiz1'], ['doiz1', 'doiz2']])
-
- #def testBigCycle(self):
-
- #def testEmptyHeight(self):
-
- #def testEmptyDepth(self):
-
- def testEmptyDepthHeight(self):
- nodes, edges = process_main(['doi1'],0,0,True)
- self.assertCountEqual(nodes,['doi1'])
- self.assertCountEqual(edges, [])
-
- nodes, edges = process_main(['doi1', 'doi2'],0,0,True)
- self.assertCountEqual(nodes, ['doi1','doi2'])
- self.assertCountEqual(edges, [['doi1', 'doi2']])
-
- nodes, edges = process_main(['doi1', 'doi2', 'doi3'],0,0,True)
- self.assertCountEqual(nodes, ['doi1','doi2', 'doi3'])
- self.assertCountEqual(edges, [['doi3', 'doi1'], ['doi1', 'doi2']])
-
-
- def testInnerEdges(self):
- nodes, edges = process_main(['doi_ie1'],1,1,True)
- self.assertCountEqual(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 = process_main(['doi_h01'],1,0,True)
- self.assertCountEqual(nodes,['doi_h01'])
- self.assertCountEqual(edges, [])
-
- nodes, edges = process_main(['doi_h02'],1,0,True)
- self.assertCountEqual(nodes,['doi_h02','doi_h1'])
- self.assertCountEqual(edges, [['doi_h1','doi_h02']])
-
- nodes, edges = process_main(['doi_h02'],2,0,True)
- self.assertCountEqual(nodes,['doi_h02','doi_h1','doi_h2'])
- self.assertCountEqual(edges, [['doi_h1','doi_h02'], ['doi_h2','doi_h1']])
-
- def testRightDepth(self):
- nodes, edges = process_main(['doi_d01'],0,1,True)
- self.assertCountEqual(nodes,['doi_d01'])
- self.assertCountEqual(edges, [])
-
- nodes, edges = process_main(['doi_d02'],0,1,True)
- self.assertCountEqual(nodes,['doi_d02','doi_d1'])
- self.assertCountEqual(edges, [['doi_d02','doi_d1']])
-
- nodes, edges = process_main(['doi_d02'],0,2,True)
- self.assertCountEqual(nodes,['doi_d02','doi_d1','doi_d2'])
- self.assertCountEqual(edges, [['doi_d02','doi_d1'], ['doi_d1','doi_d2']])
-
-if __name__ == "__main__":
- unittest.main()
\ No newline at end of file
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diff --git a/verarbeitung/__pycache__/unittest.cpython-36.pyc b/verarbeitung/__pycache__/unittest.cpython-36.pyc
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diff --git a/verarbeitung/input_test.py b/verarbeitung/input_test.py
deleted file mode 100644
index 44361c4b095f1c4fb0fce1868498d0e9da32f551..0000000000000000000000000000000000000000
--- a/verarbeitung/input_test.py
+++ /dev/null
@@ -1,82 +0,0 @@
-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]
diff --git a/verarbeitung/json_demo.py b/verarbeitung/json_demo.py
deleted file mode 100644
index b9f618d1a2dcac13ca51a530f365d40aa226bc11..0000000000000000000000000000000000000000
--- a/verarbeitung/json_demo.py
+++ /dev/null
@@ -1,49 +0,0 @@
-#!/usr/bin/env python3
-import json
-from input_fj import input
-
-"""
-Functions that format the computed graph to match the interface to the output-part
-
-"""
-
-# creates a list that contains a dictionary for each node
-# the dictionaries store the values for the attributes
-def format_nodes(V):
- list_of_node_dicts = list()
- for node in V:
- new_dict = dict()
- new_dict["name"] = node.title
- new_dict["author"] = node.contributors
- new_dict["year"] = node.publication_date
- new_dict["journal"] = node.journal
- new_dict["doi"] = node.doi_url
- new_dict["group"] = node.group
- list_of_node_dicts.append(new_dict)
- return list_of_node_dicts
-
-# creates a list that contains a disctionary for each edge
-# the dictionaries contain the source as keys and the target as values
-def format_edges(E):
- list_of_edge_dicts = list()
- for edge in E:
- new_dict_2 = dict()
- new_dict_2["source"] = edge[0]
- new_dict_2["target"] = edge[1]
- list_of_edge_dicts.append(new_dict_2)
- return list_of_edge_dicts
-
-# combine the lists of nodes and edges to a dictionary and saves it to a json file
-def output_to_json(V,E):
- dict_of_all = dict()
- list_of_node_dicts = format_nodes(V)
- list_of_edge_dicts = format_edges(E)
- dict_of_all["nodes"] = list_of_node_dicts
- dict_of_all["links"] = list_of_edge_dicts
- with open('json_text.json','w') as outfile:
- json.dump(dict_of_all, outfile)
-
-#knoten = ["doi1", "doi2", "doi3"]
-#kanten = [[1,2],[3,4],[5,6]]
-#output_to_json(knoten,kanten)
-
diff --git "a/verarbeitung/n\303\266tige Tests.txt" "b/verarbeitung/n\303\266tige Tests.txt"
deleted file mode 100644
index 95563280436fbf6b9b8702dffef6f32e213f5a16..0000000000000000000000000000000000000000
--- "a/verarbeitung/n\303\266tige Tests.txt"
+++ /dev/null
@@ -1,4 +0,0 @@
-Zyklus
-großer Zyklus
-Innere Kanten vervollständigen
-