def load_traits(self):
hdf_store = fsutils.create_h5file_path(path=self.hdf_path,
file_name="phen_meta",
dir_name=self.trait_dir)
dftrait = pd.read_csv(self.trait_file, sep="\t")
self.write_traitfile_to_hdf(hdf_store,
os.path.basename(self.trait_file))
def _get_traversed_size(self, retrieved_index, trait):
if retrieved_index == 0:
h5file = fsutils.create_h5file_path(self.search_path, dir_name=self.trait_dir, file_name=trait)
service = trait_service.TraitService(h5file)
trait_size = service.get_trait_size(trait)
service.close_file()
return trait_size
return retrieved_index
def get_list_of_studies_for_trait(self, trait):
h5file = fsutils.create_h5file_path(self.search_path, self.trait_dir,
trait)
if not isfile(h5file):
raise NotFoundError("Trait " + trait)
service = study_service.StudyService(h5file=h5file)
studies = service.list_studies()
service.close_file()
return sorted(studies)
def __init__(self, chromosome, start, size, config_properties=None):
self.chromosome = chromosome
self.start = start
self.size = size
self.properties = properties_handler.get_properties(config_properties)
self.search_path = properties_handler.get_search_path(self.properties)
self.chr_dir = self.properties.chr_dir
self.datasets = utils.create_dictionary_of_empty_dsets(TO_QUERY_DSETS)
self.index_marker = 0
self.h5file = fsutils.create_h5file_path(path=self.search_path, dir_name=self.chr_dir, file_name=chromosome)
if not os.path.isfile(self.h5file):
raise NotFoundError("Chromosome " + str(chromosome))
self.service = chromosome_service.ChromosomeService(self.h5file)
def __init__(self, trait, start, size, config_properties=None):
self.trait = trait
self.start = start
self.size = size
self.properties = properties_handler.get_properties(config_properties)
self.search_path = properties_handler.get_search_path(self.properties)
self.trait_dir = self.properties.trait_dir
self.datasets = utils.create_dictionary_of_empty_dsets(TO_QUERY_DSETS)
# index marker will be returned along with the datasets
# it is the number that when added to the 'start' value that we started the query with
# will pinpoint where the next search needs to continue from
self.index_marker = 0
self.h5file = fsutils.create_h5file_path(self.search_path,
dir_name=self.trait_dir,
file_name=trait)
if not os.path.isfile(self.h5file):
raise NotFoundError("Trait " + trait)
self.service = study_service.StudyService(self.h5file)