def _createDatabase(self, destDir, ds_file):
tabixIndexedFile = TabixIndexer.index(destDir=destDir,
inputFilename=ds_file,
preset="vcf")
baseDSFile = os.path.basename(tabixIndexedFile)
return baseDSFile
def _createDatabase(
self, destDir, ds_file, ds_match_mode, index_column_names, annotation_column_names, column_names
):
index_columns = []
for index_column_name in index_column_names: # ensures that all index columns are in the column names list
index_columns += [column_names.index(index_column_name)]
if len(index_columns) != 3 and len(index_columns) != 5:
raise ValueError("Wrong number of index columns. Must be a comma separated list of length 3 or 5.")
column_names = set(column_names)
annotation_column_names = set(annotation_column_names)
# Read the column names and determine whether they exist or not in the file
data = pandas.read_csv(filepath_or_buffer=ds_file, delimiter="\t", iterator=True, chunksize=1)
for chunk in data:
index = chunk.columns
fieldNames = set(index)
missingColumns = fieldNames.difference(column_names)
if len(missingColumns) != 0:
msg = "The input tsv, %s, is missing the following columns: %s." % (
ds_file,
string.join(missingColumns, ", "),
)
raise InputMismatchException(msg)
missingColumns = annotation_column_names.difference(fieldNames)
if len(missingColumns) != 0:
msg = "The input tsv, %s, is missing the following annotation columns: %s." % (
ds_file,
string.join(missingColumns),
)
raise InputMismatchException(msg)
break
# Iterate through the file and determine column's data type
data = pandas.read_csv(
filepath_or_buffer=ds_file,
delimiter="\t",
iterator=True,
chunksize=10000,
usecols=annotation_column_names,
na_values=["", ".", "-"],
)
for chunk in data:
index = chunk.columns
# Missing values default to float data type
for idx in index:
if ds_match_mode != "exact" or len(index_column_names) != 3:
if numpy.issubdtype(chunk[idx].dtype, numpy.inexact):
if idx not in self.columnDataTypes or self.columnDataTypes[idx] not in ("String",):
self.columnDataTypes[idx] = "Float"
elif numpy.issubdtype(chunk[idx].dtype, numpy.integer):
if idx not in self.columnDataTypes or self.columnDataTypes[idx] not in ("Float", "String"):
self.columnDataTypes[idx] = "Integer"
elif numpy.issubdtype(chunk[idx].dtype, numpy.bool_):
self.columnDataTypes[idx] = "Flag"
else:
self.columnDataTypes[idx] = "String"
else:
self.columnDataTypes[idx] = "String"
if ds_match_mode != "exact" or len(index_column_names) != 3:
break
tabixIndexedFile = TabixIndexer.index(
destDir=destDir, inputFilename=ds_file, fileColumnNumList=index_columns, preset="tsv"
)
baseDSFile = os.path.basename(tabixIndexedFile)
logging.getLogger(__name__).info("%s file was created." % tabixIndexedFile)
return baseDSFile
def _createDatabase(self, destDir, ds_file):
tabixIndexedFile = TabixIndexer.index(destDir=destDir, inputFilename=ds_file, preset="vcf")
baseDSFile = os.path.basename(tabixIndexedFile)
return baseDSFile
