def runworker(self, molecular_search_settings):
classes_list, class_to_create, existing_classes_objs = self.check_database_get_class_list(molecular_search_settings)
settings = MolecularLookupDictSettings()
settings.usedAtoms = deepcopy(molecular_search_settings.usedAtoms)
settings.url_database = molecular_search_settings.url_database
settings.db_jobs = molecular_search_settings.db_jobs
self.add_carbonsHydrogens(settings, existing_classes_objs)
if class_to_create:
settings = MolecularLookupDictSettings()
settings.usedAtoms = deepcopy(molecular_search_settings.usedAtoms)
settings.url_database = molecular_search_settings.url_database
settings.db_jobs = molecular_search_settings.db_jobs
self.sql_db.session.commit()
odd_ch_obj = self.get_carbonsHydrogens(settings,'odd')
self.odd_ch_id = [obj.id for obj in odd_ch_obj]
self.odd_ch_dict = [{'C':obj.C, 'H':obj.H} for obj in odd_ch_obj]
self.odd_ch_mass = [obj.mass for obj in odd_ch_obj]
self.odd_ch_dbe = [obj.dbe for obj in odd_ch_obj]
even_ch_obj = self.get_carbonsHydrogens(settings, 'even')
self.even_ch_id = [obj.id for obj in even_ch_obj]
self.even_ch_dict = [{'C':obj.C, 'H':obj.H} for obj in even_ch_obj]
self.even_ch_mass = [obj.mass for obj in even_ch_obj]
self.even_ch_dbe = [obj.dbe for obj in even_ch_obj]
all_results= list()
for class_tuple in tqdm(class_to_create):
results = self.populate_combinations(class_tuple, settings)
all_results.extend(results)
if settings.db_jobs == 1:
#if len(all_results) >= self.sql_db.chunks_count:
list_insert_chunks = list(chunks(results, self.sql_db.chunks_count))
for chunk in list_insert_chunks:
insert_query = MolecularFormulaLink.__table__.insert().values(chunk)
self.sql_db.session.execute(insert_query)
#all_results = list()
self.sql_db.session.commit()
# each chunk takes ~600Mb of memory, so if using 8 processes the total free memory needs to be 5GB
if settings.db_jobs > 1:
list_insert_chunks = list(chunks(all_results, self.sql_db.chunks_count))
print( "Started database insert using {} iterations for a total of {} rows".format(len(list_insert_chunks), len(all_results)))
worker_args = [(chunk, settings.url_database) for chunk in list_insert_chunks]
p = multiprocessing.Pool(settings.db_jobs)
for class_list in tqdm(p.imap_unordered(insert_database_worker, worker_args)):
pass
p.close()
p.join()
return classes_list
def run_noise_threshold_calc(self, auto, bayes=False):
if self.is_centroid:
# calculates noise_baseline and noise_std
# needed to run auto noise threshold mode
# it is not used for signal to noise nor
# relative abudance methods
abundances_chunks = chunks(self.abundance, 50)
each_min_abund = [min(x) for x in abundances_chunks]
return average(each_min_abund), std(each_min_abund)
else:
mz_cut, abundance_cut = self.cut_mz_domain_noise(auto)
if auto:
yminima = self.get_abundance_minima_centroid(
mz_cut, abundance_cut)
return self.get_noise_average(yminima, auto=auto, bayes=bayes)
else:
# pyplot.show()
return self.get_noise_average(abundance_cut,
auto=auto,
bayes=bayes)
def run():
for classe_chunk in chunks(classes, 300):
classes_str_list = [class_tuple[0] for class_tuple in classe_chunk]
# load the molecular formula objs binned by ion type and heteroatoms classes, {ion type:{classe:[list_formula]}}
# for adduct ion type a third key is added {atoms:{ion type:{classe:[list_formula]}}}
dict_res = self.database_to_dict(classes_str_list, nominal_mzs, self.mass_spectrum_obj.molecular_search_settings, ion_charge)
pbar = tqdm.tqdm(classe_chunk)
for classe_tuple in pbar:
# class string is a json serialized dict
classe_str = classe_tuple[0]
classe_dict = classe_tuple[1]
if self.mass_spectrum_obj.molecular_search_settings.isProtonated:
ion_type = Labels.protonated_de_ion
pbar.set_description_str(desc="Started molecular formula search for class %s, (de)protonated " % classe_str, refresh=True)
candidate_formulas = dict_res.get(ion_type).get(classe_str)
if candidate_formulas:
self.run_search(ms_peaks, candidate_formulas,
min_abundance, ion_type, ion_charge)
if self.mass_spectrum_obj.molecular_search_settings.isRadical:
pbar.set_description_str(desc="Started molecular formula search for class %s, radical " % classe_str, refresh=True)
ion_type = Labels.radical_ion
candidate_formulas = dict_res.get(ion_type).get(classe_str)
if candidate_formulas:
self.run_search(ms_peaks, candidate_formulas,
min_abundance, ion_type, ion_charge)
# looks for adduct, used_atom_valences should be 0
# this code does not support H exchance by halogen atoms
if self.mass_spectrum_obj.molecular_search_settings.isAdduct:
pbar.set_description_str(desc="Started molecular formula search for class %s, adduct " % classe_str, refresh=True)
ion_type = Labels.adduct_ion
dict_atoms_formulas = dict_res.get(ion_type)
for adduct_atom, dict_by_class in dict_atoms_formulas.items():
candidate_formulas = dict_by_class.get(classe_str)
if candidate_formulas:
self.run_search(ms_peaks, candidate_formulas,
min_abundance, ion_type, ion_charge, adduct_atom=adduct_atom)
def check_database_get_class_list(self, molecular_search_settings):
all_class_to_create = []
classes_dict = self.get_classes_in_order(molecular_search_settings)
class_str_set = set(classes_dict.keys())
existing_classes_objs = self.sql_db.session.query(
HeteroAtoms).distinct().all()
existing_classes_str = set(
[classe.name for classe in existing_classes_objs])
self.len_existing_classes = len(existing_classes_str)
class_to_create = class_str_set - existing_classes_str
class_count = len(existing_classes_objs)
data_classes = list()
for index, class_str in enumerate(class_to_create):
class_dict = classes_dict.get(class_str)
halogen_count = self.get_total_halogen_atoms(class_dict)
data_classes.append({
"name": class_str,
"id": class_count + index + 1,
"halogensCount": halogen_count
})
#data_classes = [{"name":class_str, "id":class_count+ index + 1} for index, class_str in enumerate(class_to_create)]
if data_classes:
list_insert_chunks = chunks(data_classes, self.sql_db.chunks_count)
for insert_chunk in list_insert_chunks:
insert_query = HeteroAtoms.__table__.insert().values(
insert_chunk)
self.sql_db.session.execute(insert_query)
for index, class_str in enumerate(class_to_create):
class_tuple = (class_str, classes_dict.get(class_str),
class_count + index + 1)
all_class_to_create.append(class_tuple)
return [(c_s, c_d) for c_s, c_d in classes_dict.items()
], all_class_to_create, existing_classes_objs
def add_carbonsHydrogens(self, settings, existing_classes_objs):
usedAtoms = settings.usedAtoms
user_min_c, user_max_c = usedAtoms.get('C')
user_min_h, user_max_h = usedAtoms.get('H')
query_obj = self.sql_db.session.query(func.max(CarbonHydrogen.C).label("max_c"),
func.min(CarbonHydrogen.C).label("min_c"),
func.max(CarbonHydrogen.H).label("max_h"),
func.min(CarbonHydrogen.H).label("min_h"),
)
database = query_obj.first()
if database.max_c == user_max_c and database.min_c == user_min_c and database.max_h == user_max_h and database.min_h == user_min_h:
#all data is already available at the database
pass
else:
current_count = self.sql_db.session.query(CarbonHydrogen.C).count()
databaseCarbonHydrogen = self.sql_db.session.query(CarbonHydrogen).all()
userCarbon = set(range(user_min_c, user_max_c + 1))
userHydrogen = set(range(user_min_h, user_max_h + 1))
carbon_hydrogen_objs_database = {}
for obj in databaseCarbonHydrogen:
str_data = "C:{},H:{}".format(obj.C, obj.H)
carbon_hydrogen_objs_database[str_data] = str_data
carbon_hydrogen_objs_to_create = {'even': {}, 'odd': {}}
list_ch_obj_to_add = list()
i = 0
for comb in itertools.product(userCarbon, userHydrogen):
C = comb[0]
H = comb[1]
data = {"C":C,
"H":H,
}
data_insert = {"C":C,
"H":H,
}
str_data = "C:{},H:{}".format(C,H)
if not str_data in carbon_hydrogen_objs_database.keys():
label = 'even' if comb[1]%2 == 0 else 'odd'
data["mass"] = (C * Atoms.atomic_masses.get('C')) + (H * Atoms.atomic_masses.get('H'))
data["dbe"] = C - (H/2) + 1
data["id"] = i + current_count + 1
data_insert["id"] = i + current_count + 1
i = i + 1
carbon_hydrogen_objs_to_create[label][str_data] = data
list_ch_obj_to_add.append(data_insert)
if list_ch_obj_to_add:
# insert carbon hydrogen objs
list_insert_chunks = chunks(list_ch_obj_to_add, self.sql_db.chunks_count)
for insert_chunk in list_insert_chunks:
insert_query = CarbonHydrogen.__table__.insert().values(insert_chunk)
self.sql_db.session.execute(insert_query)
self.sql_db.session.commit()
list_molecular_form= list()
for classe_obj in existing_classes_objs:
classe_dict = classe_obj.to_dict()
classe_mass = self.calc_mz(classe_dict)
classe_dbe = self.calc_dbe_class(classe_dict)
odd_even_label = self.get_h_odd_or_even(classe_dict)
ch_datalist = carbon_hydrogen_objs_to_create.get(odd_even_label).values()
for ch_dict in ch_datalist:
mass = ch_dict.get('mass') + classe_mass
dbe = ch_dict.get('dbe') + classe_dbe
if settings.min_mz <= mass <= settings.max_mz:
if settings.min_dbe <= dbe <= settings.max_dbe:
list_molecular_form.append( {"heteroAtoms_id":classe_obj.id,
"carbonHydrogen_id":ch_dict.get('id'),
"mass":mass, "DBE":dbe})
list_insert_chunks = chunks(list_molecular_form, self.sql_db.chunks_count)
for insert_chunk in list_insert_chunks:
insert_query = MolecularFormulaLink.__table__.insert().values(insert_chunk)
self.sql_db.session.execute(insert_query)
self.sql_db.session.commit()
