def addInteractionsNewDB(interaction_type: bool, bacterium_id: int,
phage_id: int, level_id: int, lysis_id: int,
persone_responsible: int, source_data_id: int,
validity_id: bool):
couple_obj = CoupleJson(interaction_type=interaction_type,
bacteriophage=phage_id,
bacterium=bacterium_id,
level=level_id,
lysis=lysis_id,
person_responsible=persone_responsible,
source_data=source_data_id,
validity=validity_id)
couple_obj_json = couple_obj.setCouple()
return couple_obj_json
def matrixSimilarityScript(file_name: str,
path: str,
organism_id: int,
is_phage=False):
"""
| Create a matrix of similarity with many organisms.
| In this version, get all the couples with organism id (according with a
| specific level of lysis).
| Calculates the similarity between all the different organisms in the couples
:Remark: To compare other organisms, modifie the content of list_organism_to_compare
:param file_name: name of the similarity matrix
:param path: where save the matrix
:param organism_id: id of the organism to find couples
:param is_phage: to differenciate bacterium and phages
:type file_name: str
:type path: str
:type organism_id: int
:type is_phage: boolean
"""
lysis_type = constants.ALL_CLEAR_LYSIS
file_name = file_name
path = path
organism_dict = {} # Get couple from specific bacterie
if is_phage == False:
organism_dict['bacterium'] = organism_id
else:
organism_dict['bacteriophage'] = organism_id
# Get all the couples with the organism gave in parameter
liste_couple = (CoupleJson.getCouplesByFilterParameter(organism_dict))
# Select couple according with the lysis attribute
liste_couple_final = []
for couple in liste_couple:
if couple.lysis in lysis_type:
liste_couple_final.append(couple)
list_organism_to_compare = []
for couple in liste_couple_final:
if is_phage == False:
# check if there is no duplicate phage in the list
if couple.bacteriophage not in list_organism_to_compare:
list_organism_to_compare.append(couple.bacteriophage)
else:
# check if there is no duplicate phage in the list
if couple.bacterium not in list_organism_to_compare:
list_organism_to_compare.append(couple.bacterium)
# Change the contents of list_organism_to_compare to compare other organisms
# list_organism_to_compare = general_functions.getCouplesLysis(lysis_type)
createSimilarityMatrix(list_organism_to_compare, file_name, path,
not is_phage)
def getAllOfCouples():
"""
| Get all couples from DB Inphinity
:return: all couples from DB Inphinity
:rtype: list
"""
list_couples = CoupleJson.getAllAPI()
return list_couples
def relationGraphOrganism(organism_id: int, is_phage=False):
"""
| Draw a relation graph between phages and bacteria according
| to the organism_id and clear lysis attribute.
:Remark: Change the list_couple_final for other comparisons
:param organism_id: lysis
:param is_phage: if the organism is a phage
:type organism_id: int
:type is_phage: boolean
"""
# Choose what type of lysis we want
lysis_type = constants.ALL_CLEAR_LYSIS
# Get couple from specific bacterie
organism_dict = {}
# Research bact or phage by ID
if is_phage == False:
organism_dict['bacterium'] = organism_id
else:
organism_dict['bacteriophage'] = organism_id
liste_couple = (CoupleJson.getCouplesByFilterParameter(organism_dict))
# Select couple in function of the lysis
liste_couple_final = []
for couple in liste_couple:
if couple.lysis in lysis_type:
liste_couple_final.append(couple)
# Defining two correlation tables between phages and bacteriums
phages = []
bacterium = []
for couple in liste_couple_final:
phages.append(
BacteriophageJson.getByID(couple.bacteriophage).designation
) # Get designation and phage id
# Get the name of bacterium (strain designation + species designation) and his id
strain_id = BacteriumJson.getByID(couple.bacterium).strain
strain_designation = StrainJson.getByID(strain_id).designation
specie_designation = SpecieJson.getByID(
StrainJson.getByID(strain_id).specie).designation
bacterium.append(specie_designation + '-' + strain_designation + '\n' +
str(couple.bacterium))
# Draw network graph
draw_graph(phages,
bacterium,
liste_couple_final,
graph_name='graph',
is_png=False)
def getCouplesLevelOne():
"""
Return all the couples with an interaction of level 1
:return: list of couples
:rtype: list(CoupleJson)
"""
dict_parameters_couple = {}
dict_parameters_couple['level'] = 1
list_couples = CoupleJson.getCouplesByFilterParameter(
dict_parameters_couple)
return list_couples
def getCoupleTyById(id_couple: int):
"""
return a interaction type of a given couple ID
:param id_couple: id of the couple
:type id_couple: int
:return: type of the couple
:rtype: int
"""
dict_parameters_couple = {}
dict_parameters_couple['id'] = id_couple
couple_obj = CoupleJson.getCouplesByFilterParameter(dict_parameters_couple)
type_interaction = couple_obj.interaction_type
return type_interaction
from objects_API.FamilyJ import FamilyJson
from objects_API.GenusJ import GenusJson
from objects_API.StrainJ import StrainJson
from objects_API.CoupleJ import CoupleJson
conf_obj = ConfigurationAPI()
conf_obj.load_data_from_ini()
AuthenticationAPI().createAutenthicationToken()
family_obj = FamilyJson.getByID(147)
genus_obj = GenusJson.getByID(98)
strain_obj = StrainJson.getByID(17144)
print(family_obj)
print(genus_obj)
print(strain_obj)
list_couple = CoupleJson.getAllAPI()
list_family = FamilyJson.getAllAPI()
list_gesy = GenusJson.getAllAPI()
list_strain = StrainJson.getAllAPI()
list_couple_ddi = DomainInteractionPairJson.getAllAPI()
list_db_names = DomainSourceInformationJson.getAllAPI()
list_locationsDDI_source = DomainInteractionSourceJson.getAllAPI()
print(len(list_couple_ddi))
#list_couples = getAllCouples()
print('hello')
def getAllCouples():
list_couple = CoupleJson.getAllAPI()
return list_couple
def createFeaturesFile(file_name: str,
path: str,
organism_id: int = None,
is_phage: bool = False):
"""
| Create a csv file with organisms features.
| The organisms to compare are choosen according to the organism_id param.
| Takes all couples with organism_id and select only the couples Clear Lysis.
| Then extracts features from the remaining organisms.
| If no organism_id referenced take the organisms in list_couple
The features are :
- mean of all amino acids
- mean of all chemical elements
- weight of the organism
- iso eletrical point
- aromaticity
:param file_name: name of csv file
:param path: path to save the file
:param organism_id: id of organism
:param is_phage: if true, compare bacteria. If false, compare bacteriophages
:type file_name: str
:type path: str
:type organism_id: int
:type is_phage: boolean
"""
# Choose what type of lysis we want
lysis_type = constants.ALL_CLEAR_LYSIS
file_name = file_name
path = path
# Get the phages of all the couples with an interaction type
# list_couple = network.getCouplesInteraction(CoupleJson.getAllAPI(), interaction_type=True)
# Get the phages of specific couples
liste_couple = general_functions.getCouplesLysis(lysis_type)
# Get couple from specific bacterie
organism_dict = {}
# Research bact or phage by ID
if is_phage == False and organism_id != None:
organism_dict['bacterium'] = organism_id
liste_couple = (CoupleJson.getCouplesByFilterParameter(organism_dict))
elif organism_id != None:
organism_dict['bacteriophage'] = organism_id
liste_couple = (CoupleJson.getCouplesByFilterParameter(organism_dict))
if organism_id != None:
# Select couple in function of the lysis
liste_couple_final = []
for couple in liste_couple:
if couple.lysis in lysis_type:
liste_couple_final.append(couple)
else:
liste_couple_final = liste_couple
# phages to extract features will be here
list_phages = []
for couple in liste_couple_final:
if not couple.bacteriophage in list_phages:
list_phages.append(couple.bacteriophage)
phages_amino_acids = OrderedDict()
for couple in liste_couple_final:
if not couple.bacteriophage in phages_amino_acids.keys():
phage_amino_acid_dict = getFeaturesForAPhage(
BacteriophageJson.getByID(couple.bacteriophage),
active_percentage=False,
get_features=True)
phages_amino_acids[BacteriophageJson.getByID(
couple.bacteriophage).designation] = phage_amino_acid_dict
# Source :
# ADAM SMITH [Pseudonyme], 2015. This is beyond simple if you can use pandas.
# Stackoverflow [en ligne]. 16 Juillet 2015 à 16h38.
# [Consulté le 3 Avril 2019]. Disponible à l'adresse : https://stackoverflow.com/questions/31436783/writing-dictionary-of-dictionaries-to-csv-file-in-a-particular-format
df1 = pd.DataFrame.from_dict(data=phages_amino_acids, orient="index")
df1.to_csv(os.path.join(path, file_name))
df1 = df1.rename_axis('Phages designation', axis='columns')
df1.to_csv(os.path.join(path, file_name), index_label='Phages designation')
ending_message = "file " + file_name + " saved in " + path
print(ending_message)
#
id_phage = couple_element.fk_phage
acc_bacteriophage = obtainphageACCnumberFromOldDBId(id_phage)
id_new_phage_db = -1
if id_phage in dict_convert_phages_id:
id_new_phage_db = dict_convert_phages_id[id_phage]
else:
try:
id_new_phage_db = getBacteriophageByACCNEWDB(acc_bacteriophage)
except:
id_new_phage_db = -1
if id_new_phage_db != -1 and id_new_bacterium_db != -1:
try:
couple_obj = CoupleJson.getByBacteriumPhageIds(
id_new_bacterium_db, id_new_phage_db)
except:
count_error += 1
interaction_type_cp = couple_element.interact_pn
id_bacterium_cp = id_new_bacterium_db
id_phage_cp = id_new_phage_db
validity_id_cp = 4 #not validate
level_interaction_cp = 2
source_data_cp = 1
person_responsible_cp = 3
couple_obj_json = CoupleJson(
interaction_type=interaction_type_cp,
bacteriophage=id_phage_cp,
bacterium=id_bacterium_cp,
level=level_interaction_cp,
def getAllCouplesByParameters(parameter_dic: dict):
list_couples = CoupleJson.getCouplesByFilterParameter(parameter_dic)
return list_couples