def relationGraphCouples(lysis_attribut: str):
"""
| Draw a relation graph between phages and bacteria according
| to the lysis attribute.
:param lysis_attribut: lysis
:type lysis_attribut: str
"""
# Choose what type of lysis we want
if lysis_attribut == 'CLEAR_LYSIS':
lysis_type = constants.CLEAR_LYSIS
elif lysis_attribut == 'SEMI_CLEAR_LYSIS':
lysis_type = constants.SEMI_CLEAR_LYSIS
elif lysis_attribut == 'OPAQUE_LYSIS':
lysis_type = constants.OPAQUE_LYSIS
elif lysis_attribut == 'CLEAR_LYSIS_1E7PLUS':
lysis_type = constants.CLEAR_LYSIS_1E7PLUS
elif lysis_attribut == 'SEMI_CLEAR_LYSIS_1E7PLUS':
lysis_type = constants.SEMI_CLEAR_LYSIS_1E7PLUS
elif lysis_attribut == 'CLEAR_LYSIS_1E7MINUS':
lysis_type = constants.CLEAR_LYSIS_1E7MINUS
elif lysis_attribut == 'SEMI_CLEAR_LYSIS_1E7MINUS':
lysis_type = constants.SEMI_CLEAR_LYSIS_1E7MINUS
elif lysis_attribut == 'ALL_CLEAR_LYSIS':
lysis_type = constants.ALL_CLEAR_LYSIS
elif lysis_attribut == 'ALL_SEMI_CLEAR_LYSIS':
lysis_type = constants.ALL_SEMI_CLEAR_LYSIS
# Couples to analyse will be in list_couples_lysis_type
list_couples_lysis_type = []
list_couples_lysis_type = functions.getCouplesLysis(lysis_type)
# Defining two correlation tables between phages and bacteria
phages = []
bacterium = []
for couple in list_couples_lysis_type:
phages.append(
BacteriophageJson.getByID(couple.bacteriophage).designation)
# Get the name of bacteria (strain designation + species designation)
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,
list_couples_lysis_type,
graph_name='graph',
is_png=False)
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 create_strain_json(strainOBJ, idSpecie):
"""
insert a strain into a REST API
:param strainOBJ: strain that you want to insert
:param idGenus: FK of the specie strain
:type strainOBJ: strain
:type idGenus: int
"""
print(strainOBJ)
strainObjREST = StrainJson(designation=strainOBJ.designation, specie=idSpecie)
strainREST = strainObjREST.setStrain()
createCSVCorrespondence(strainOBJ.id_strain, strainREST.id)
def getBacteriumListIdsByStrainId(strain_id: int):
list_bacterium_ids_treated = []
strain_obj = StrainJson.getByID(strain_id)
list_bacterium_ids = strain_obj.bacteria
for bacterium in list_bacterium_ids:
bacterium = bacterium.replace(
'http://trex.lan.iict.ch:8080/api/bacterium/', '')[:-1]
list_bacterium_ids_treated.append(bacterium)
return list_bacterium_ids_treated
def getAllOfStrain():
"""
| Get all Strains from DB Inphinity
:return: all strains from DB Inphinity
:rtype: list
"""
list_strain = StrainJson.getAllAPI()
return list_strain
def getBacteriumDesignationNewByID(id_new_bacterium: int):
bacterium_obj = BacteriumJson.getByID(id_new_bacterium)
strain_id = bacterium_obj.strain
strain_obj = StrainJson.getByID(strain_id)
strain_designation = strain_obj.designation
specie_id = strain_obj.specie
specie_obj = SpecieJson.getByID(specie_id)
specie_designation = specie_obj.designation
taxonomy_bacterium = 'Specie: ' + specie_designation + ' Strain: ' + strain_designation
return taxonomy_bacterium
def getBacteriumStrainSpecieDesignationById(id_bacterium):
bacterium_json_obj = BacteriumJson.getByID(id_bacterium)
strain_id = bacterium_json_obj.strain
strain_obj = StrainJson.getByID(strain_id)
strain_designation = strain_obj.designation
specie_id = strain_obj.specie
specie_obj = SpecieJson.getByID(specie_id)
specie_designation = specie_obj.designation
taxonomy_bacterium = 'Specie: ' + specie_designation + ' Strain: ' + strain_designation
return taxonomy_bacterium
def createStrain(designation, fk_specie):
#Information for the Strain
strain_obj = StrainJson(designation=designation, specie=fk_specie)
id_strain = strain_obj.setStrain()
return id_strain
from objects_API.DomainSourceInformationJ import DomainSourceInformationJson from objects_API.DomainInteractionSourceJ import DomainInteractionSourceJson 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))
def draw_graph(phages: list,
bacteria: list,
list_couples_lysis_type: list,
is_png=False,
node_size=300,
node_alpha=0.5,
node_text_size=8,
edge_alpha=0.5,
edge_tickness=0.5,
edge_text_pos=1.0,
text_font='sans-serif',
graph_name='network_graphic'):
"""
| Make a graph to bind phages with bacteria according to their lysis attribute
:param phages: list of phages
:param bacteria: list of bacteria
:param list_couple_lysis_type: list of couples
:param is_png: if true, save the graph as a png image
:param node_size: size of node
:param node_alpha: clearness of node_alpha
:param node_text_size: size of text in node
:param edge_alpha: clearness of node_alpha
:param edge_tickness: tichness of edge,
:param edge_text_pos: position of text
:param text_font: text font
:param graph_name: name of graph
:type phages: list
:type bacteria: list
:type list_couple_lysis_type: list
:type is_png: boolean
:type node_size: int
:type node_size: int
:type node_alpha: int
:type node_text_size: int
:type edge_alpha: int
:type edge_tickness: int
:type edge_text_pos: int
:type text_font: string
:type graph_name: string
"""
# Plot declaration
fig, ax = plt.subplots(figsize=(20, 10))
ax.set_title('Network between phages and bacteria', fontsize=16)
margin = 0.1
fig.subplots_adjust(margin, margin, 1. - margin, 1. - margin)
ax.axis('equal')
nodes_phages = [] # All different phages
nodes_bacteria = [] # All different bacteria
# Different couples in function of their taxonomy
nodes_couples_strain_level = []
nodes_couples_species_level = []
# All species of the current research
all_species = []
# Get the name of each bacteria (strain + species)
for couple in list_couples_lysis_type:
strain_id = BacteriumJson.getByID(couple.bacterium).strain
strain_designation = StrainJson.getByID(strain_id).designation
specie_designation = SpecieJson.getByID(
StrainJson.getByID(strain_id).specie).designation
bacteria_designation = specie_designation + '-' + strain_designation + '\n' + str(
couple.bacterium)
# Get bacteria designation
if not bacteria_designation in nodes_bacteria:
nodes_bacteria.append(bacteria_designation)
# Get phages' designation
phages_designation = BacteriophageJson.getByID(
couple.bacteriophage).designation
if not phages_designation in nodes_phages:
nodes_phages.append(phages_designation)
if couple.level == constants.STRAIN_ID:
if not phages_designation in nodes_couples_strain_level:
nodes_couples_strain_level.append(phages_designation)
elif couple.level == constants.SPECIES_ID:
if not phages_designation in nodes_couples_species_level:
nodes_couples_species_level.append(phages_designation)
all_species.append(specie_designation)
designation_of_species, number_of_species = np.unique(all_species,
return_counts=True)
list_of_list = [[] for i in range(len(number_of_species))]
i = 0
while (i < len(number_of_species)):
for bact in nodes_bacteria:
if bact.split('-')[0] == designation_of_species[i]:
list_of_list[i].append(bact)
i += 1
nodes = set(nodes_phages + nodes_bacteria) # All the nodes in our graph
G = nx.Graph() # Create networkx graph
# Add nodes
for node in nodes:
G.add_node(node)
# Add edges
i = 0
while (i < len(phages)):
G.add_edge(phages[i], bacteria[i])
i += 1
graph_pos = nx.spring_layout(G) # Draw graph
# Defining nodes features for couples level strain
nx.draw_networkx_nodes(G,
graph_pos,
nodelist=nodes_couples_strain_level,
node_size=node_size,
alpha=node_alpha,
node_color='g')
# Defining nodes features for couples level sepcies
nx.draw_networkx_nodes(G,
graph_pos,
nodelist=nodes_couples_species_level,
node_size=node_size,
alpha=node_alpha,
node_color='black')
# Different colors for different strains
color = ['red', 'purple', 'blue', 'orange', 'grey']
i = 0
for el in list_of_list:
# Defining nodes features for bacteria
nx.draw_networkx_nodes(G,
graph_pos,
nodelist=el,
node_size=node_size,
alpha=node_alpha,
node_color=color[i])
i = (i + 1) % 5
nx.draw_networkx_edges(G,
graph_pos,
width=edge_tickness,
alpha=edge_alpha,
edge_color='b')
#display ID of bacteria and phages
nx.draw_networkx_labels(G,
graph_pos,
font_size=node_text_size,
font_family=text_font)
#show graph
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.set_xlabel('Rouge/Violet/Bleu/Orange/Gris = Bactéries' +
' ----- Vert = Phages - Couple niveau souche' +
' ----- Noir = Phages - Couple niveau espèce' +
'\nNombre de phages différents : ' + str(len(nodes_phages)) +
' ----- Nombre de bactéries différentes : ' +
str(len(nodes_bacteria)) +
'\nNombre d\'espèces différentes : ' +
str(len(number_of_species)) + '\n' +
str(designation_of_species))
# Save graph in png or display it
if is_png:
plt.savefig('./' + graph_name + '.png')
else:
plt.show()
def createSimilarityMatrix(list_organism_to_compare: list,
file_name: str,
path: str,
is_phage=True):
"""
| Create a similarity matrix with a list of organisms
:param list_organism_to_compare: list of organisms
:param file_name: name of file where data will be stored
:param path: where the matrix will be stored
:type phage: list
:type file_name: str
:type path: str
"""
matrice_similarity = []
similarity = []
matrix_size = len(list_organism_to_compare)
i = 0
for i in range(matrix_size):
similarity = []
for j in range(matrix_size):
# If this is the same phage, rating max -> 1.0
if list_organism_to_compare[i] == list_organism_to_compare[j]:
similarity.append(1.0)
continue
# Add similarity score in the list similarity
similarity.append(
getSimilarityScoreTwoPhages(list_organism_to_compare[i],
list_organism_to_compare[j]))
# Add the score in the matrix
matrice_similarity.append(similarity)
i += 1
# print(str(i) + "/" + str(len(list_organism_to_compare)) + " organism compared\n")
# Get organisms names
organism_name = []
if is_phage == True:
for organism in list_organism_to_compare:
organism_name.append(
BacteriophageJson.getByID(organism).designation)
else:
for organism in list_organism_to_compare:
strain = StrainJson.getByID(BacteriumJson.getByID(organism).strain)
organism_name.append(
SpecieJson.getByID(strain.specie).designation + " " +
strain.designation)
# Save file
df1 = pd.DataFrame(data=matrice_similarity,
columns=organism_name,
index=organism_name)
if is_phage == True:
df1 = df1.rename_axis('Phages designation', axis='columns')
df1.to_csv(os.path.join(path, file_name),
index_label='Phages designation')
else:
df1 = df1.rename_axis('Bacterium designation', axis='columns')
df1.to_csv(os.path.join(path, file_name),
index_label='Bacterium designation')
ending_message = "file " + file_name + " saved in " + path
print(ending_message)