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)