def __init__(self, args, unknown_args):
self.args = args
self.unknown_args = unknown_args
self.option = checkInput(args)
#
env.logger = getLogger(max(min(args.verbosity - 1, 2), 0),
fn=os.path.splitext(args.output[0])[0],
fv=2 if args.verbosity is not 0 else 0)
env.logger.debug('\n{0}\n{1}\n{0}'.format(
"=" * min(len(args.cmd), 100), args.cmd))
self.logger = env.logger.info if args.verbosity != 1 else printinfo
#
self.logger('Loading data from [{}] ...'.format(args.data))
if self.option == 1:
self.file = SFSFile(args.data)
else:
self.file = GFile(args.data)
self.groups = self.file.getnames()
self.logger('{:,d} units found'.format(len(self.groups)))
# load non-missing data
# to annotate to each variant position wether or not it is missing from assocation analysis
# name it chip_file because it mimics the behavior of exome chip design
if args.missing_unlisted:
self.chip_file = SFSFile(args.missing_unlisted)
else:
self.chip_file = None
# set limit
if self.args.limit:
self.limit = min(max(1, args.limit), len(self.groups))
self.logger('{:,d} units will be analyzed'.format(self.limit))
else:
self.limit = len(self.groups)
self.result = ResultManager(args.output,
action='w' if not args.append else 'a')
if self.args.verbosity == 1:
# widgets = [FormatLabel('scanning: unit %(value)d - '), BouncingBar(marker=RotatingMarker())]
widgets = [
FormatLabel('scanning: unit %(value)d - '),
Percentage(), ' ',
Bar('>'), ' ',
ETA()
]
self.pbar = ProgressBar(widgets=widgets,
maxval=self.limit,
term_width=get_terminal_size()[0] -
5).start()
else:
# use each group's progress bar or not progress bar at all
self.pbar = ProgressBarNull()
# this is buffer object to hold all input dict to a list
self.data_buffer = [] if self.args.replicates < 0 else None
def __init__(self, args, unknown_args):
self.args = args
self.unknown_args = unknown_args
self.option = checkInput(args)
#
env.logger = getLogger(
max(min(args.verbosity - 1, 2), 0),
fn=os.path.splitext(args.output[0])[0],
fv=2 if args.verbosity is not 0 else 0,
)
env.logger.debug("\n{0}\n{1}\n{0}".format("=" * min(len(args.cmd), 100), args.cmd))
self.logger = env.logger.info if args.verbosity != 1 else printinfo
#
self.logger("Loading data from [{}] ...".format(args.data))
if self.option == 1:
self.file = SFSFile(args.data)
else:
self.file = GFile(args.data)
self.groups = self.file.getnames()
self.logger("{:,d} units found".format(len(self.groups)))
# load non-missing data
# to annotate to each variant position wether or not it is missing from assocation analysis
# name it chip_file because it mimics the behavior of exome chip design
if args.missing_unlisted:
self.chip_file = SFSFile(args.missing_unlisted)
else:
self.chip_file = None
# set limit
if self.args.limit:
self.limit = min(max(1, args.limit), len(self.groups))
self.logger("{:,d} units will be analyzed".format(self.limit))
else:
self.limit = len(self.groups)
self.result = ResultManager(args.output, action="w" if not args.append else "a")
if self.args.verbosity == 1:
# widgets = [FormatLabel('scanning: unit %(value)d - '), BouncingBar(marker=RotatingMarker())]
widgets = [FormatLabel("scanning: unit %(value)d - "), Percentage(), " ", Bar(">"), " ", ETA()]
self.pbar = ProgressBar(widgets=widgets, maxval=self.limit, term_width=get_terminal_size()[0] - 5).start()
else:
# use each group's progress bar or not progress bar at all
self.pbar = ProgressBarNull()
# this is buffer object to hold all input dict to a list
self.data_buffer = [] if self.args.replicates < 0 else None
class Executor:
def __init__(self, args, unknown_args):
self.args = args
self.unknown_args = unknown_args
self.option = checkInput(args)
#
env.logger = getLogger(max(min(args.verbosity - 1, 2), 0), fn = os.path.splitext(args.output[0])[0],
fv = 2 if args.verbosity is not 0 else 0)
env.logger.debug('\n{0}\n{1}\n{0}'.format("="*min(len(args.cmd), 100), args.cmd))
self.logger = env.logger.info if args.verbosity != 1 else printinfo
#
self.logger('Loading data from [{}] ...'.format(args.data))
if self.option == 1:
self.file = SFSFile(args.data)
else:
self.file = GFile(args.data)
self.groups = self.file.getnames()
self.logger('{:,d} units found'.format(len(self.groups)))
# load non-missing data
# to annotate to each variant position wether or not it is missing from assocation analysis
# name it chip_file because it mimics the behavior of exome chip design
if args.missing_unlisted:
self.chip_file = SFSFile(args.missing_unlisted)
else:
self.chip_file = None
# set limit
if self.args.limit:
self.limit = min(max(1, args.limit), len(self.groups))
self.logger('{:,d} units will be analyzed'.format(self.limit))
else:
self.limit = len(self.groups)
self.result = ResultManager(args.output, action = 'w' if not args.append else 'a')
if self.args.verbosity == 1:
# widgets = [FormatLabel('scanning: unit %(value)d - '), BouncingBar(marker=RotatingMarker())]
widgets = [FormatLabel('scanning: unit %(value)d - '), Percentage(), ' ',
Bar('>'), ' ', ETA()]
self.pbar = ProgressBar(widgets=widgets, maxval = self.limit,
term_width=get_terminal_size()[0] - 5).start()
else:
# use each group's progress bar or not progress bar at all
self.pbar = ProgressBarNull()
# this is buffer object to hold all input dict to a list
self.data_buffer = [] if self.args.replicates < 0 else None
def run(self):
if self.data_buffer is not None and self.option == 0:
if self.args.resampling:
self.logger('[WARNING] Loading all genotype data to memory. May fail if there is not enough memory!')
else:
self.logger('Converting data attributes ...')
try:
if self.option == 1:
self.__scan_sfs()
else:
self.__scan_gdat()
except:
self.result.close(quiet = True)
raise
self.file.close()
if self.chip_file is not None:
self.chip_file.close()
if self.data_buffer is not None:
self.result.append(Calculator(self.args, self.unknown_args, self.data_buffer).run())
self.result.close()
self.pbar.finish()
def __scan_gdat(self):
'''scan gdat file'''
maf = 'maf'
pos = 'position'
function_score = 'annotation'
# Allow for customized key names in gdat file
try:
for x, y in zip(getColumn(self.args.data[:-5] + '.key', 1),
getColumn(self.args.data[:-5] + '.key', 2)):
if x == 'maf':
maf = y
if x == 'position':
pos = y
if x == 'annotation':
function_score = y
except:
pass
#
for group, item in enumerate(self.groups):
if group >= self.limit:
break
data = self.file.getdata(item)
if self.args.resampling:
data.decompress()
else:
data['haplotype'] = [[]]
try:
loci_input = {'pool':data['haplotype'], 'name':item,
'maf':list(data[maf]), 'pos':list(data[pos]),
'function_score':list(data[function_score])}
except KeyError as e:
env.logger.error('Column name {} not found. Please provide [{}.key] file to overwrite column naming conventions.'.\
format(e, self.args.data[:-5]))
continue
loci_input['num_variants'] = len(loci_input['maf'])
if self.chip_file:
cdata = self.chip_file.getdata(item)
if cdata is None or (not is_within(cdata['num_variants'], self.args.def_valid_locus)):
continue
loci_input['missing'] = [False if x in cdata['pos'] else True for x in loci_input['pos']]
else:
loci_input['missing'] = None
if is_within(loci_input['num_variants'], self.args.def_valid_locus):
if self.data_buffer is None:
self.result.append(Calculator(self.args, self.unknown_args,loci_input).run())
else:
self.data_buffer.append(loci_input)
self.pbar.update(group + 1)
def __scan_sfs(self):
for group, loci_input in enumerate(self.file.data):
if group >= self.limit:
break
# text sfs file does not have any haplotype pools
loci_input['pool'] = [[]]
if self.chip_file:
cdata = self.chip_file.getdata(loci_input['name'])
if cdata is None or (not is_within(cdata['num_variants'], self.args.def_valid_locus)):
continue
loci_input['missing'] = [False if x in cdata['pos'] else True for x in loci_input['pos']]
assert len(loci_input['missing']) == len(loci_input['maf'])
else:
loci_input['missing'] = None
if is_within(loci_input['num_variants'], self.args.def_valid_locus):
if self.data_buffer is None:
self.result.append(Calculator(self.args, self.unknown_args,loci_input).run())
else:
self.data_buffer.append(loci_input)
self.pbar.update(group + 1)
class Executor:
def __init__(self, args, unknown_args):
self.args = args
self.unknown_args = unknown_args
self.option = checkInput(args)
#
env.logger = getLogger(max(min(args.verbosity - 1, 2), 0),
fn=os.path.splitext(args.output[0])[0],
fv=2 if args.verbosity is not 0 else 0)
env.logger.debug('\n{0}\n{1}\n{0}'.format(
"=" * min(len(args.cmd), 100), args.cmd))
self.logger = env.logger.info if args.verbosity != 1 else printinfo
#
self.logger('Loading data from [{}] ...'.format(args.data))
if self.option == 1:
self.file = SFSFile(args.data)
else:
self.file = GFile(args.data)
self.groups = self.file.getnames()
self.logger('{:,d} units found'.format(len(self.groups)))
# load non-missing data
# to annotate to each variant position wether or not it is missing from assocation analysis
# name it chip_file because it mimics the behavior of exome chip design
if args.missing_unlisted:
self.chip_file = SFSFile(args.missing_unlisted)
else:
self.chip_file = None
# set limit
if self.args.limit:
self.limit = min(max(1, args.limit), len(self.groups))
self.logger('{:,d} units will be analyzed'.format(self.limit))
else:
self.limit = len(self.groups)
self.result = ResultManager(args.output,
action='w' if not args.append else 'a')
if self.args.verbosity == 1:
# widgets = [FormatLabel('scanning: unit %(value)d - '), BouncingBar(marker=RotatingMarker())]
widgets = [
FormatLabel('scanning: unit %(value)d - '),
Percentage(), ' ',
Bar('>'), ' ',
ETA()
]
self.pbar = ProgressBar(widgets=widgets,
maxval=self.limit,
term_width=get_terminal_size()[0] -
5).start()
else:
# use each group's progress bar or not progress bar at all
self.pbar = ProgressBarNull()
# this is buffer object to hold all input dict to a list
self.data_buffer = [] if self.args.replicates < 0 else None
def run(self):
if self.data_buffer is not None and self.option == 0:
if self.args.resampling:
self.logger(
'[WARNING] Loading all genotype data to memory. May fail if there is not enough memory!'
)
else:
self.logger('Converting data attributes ...')
try:
if self.option == 1:
self.__scan_sfs()
else:
self.__scan_gdat()
except:
self.result.close(quiet=True)
raise
self.file.close()
if self.chip_file is not None:
self.chip_file.close()
if self.data_buffer is not None:
self.result.append(
Calculator(self.args, self.unknown_args,
self.data_buffer).run())
self.result.close()
self.pbar.finish()
def __scan_gdat(self):
'''scan gdat file'''
maf = 'maf'
pos = 'position'
function_score = 'annotation'
# Allow for customized key names in gdat file
try:
for x, y in zip(getColumn(self.args.data[:-5] + '.key', 1),
getColumn(self.args.data[:-5] + '.key', 2)):
if x == 'maf':
maf = y
if x == 'position':
pos = y
if x == 'annotation':
function_score = y
except:
pass
#
for group, item in enumerate(self.groups):
if group >= self.limit:
break
data = self.file.getdata(item)
if self.args.resampling:
data.decompress()
else:
data['haplotype'] = [[]]
try:
loci_input = {
'pool': data['haplotype'],
'name': item,
'maf': list(data[maf]),
'pos': list(data[pos]),
'function_score': list(data[function_score])
}
except KeyError as e:
env.logger.error('Column name {} not found. Please provide [{}.key] file to overwrite column naming conventions.'.\
format(e, self.args.data[:-5]))
continue
loci_input['num_variants'] = len(loci_input['maf'])
if self.chip_file:
cdata = self.chip_file.getdata(item)
if cdata is None or (not is_within(cdata['num_variants'],
self.args.def_valid_locus)):
continue
loci_input['missing'] = [
False if x in cdata['pos'] else True
for x in loci_input['pos']
]
else:
loci_input['missing'] = None
if is_within(loci_input['num_variants'],
self.args.def_valid_locus):
if self.data_buffer is None:
self.result.append(
Calculator(self.args, self.unknown_args,
loci_input).run())
else:
self.data_buffer.append(loci_input)
self.pbar.update(group + 1)
def __scan_sfs(self):
for group, loci_input in enumerate(self.file.data):
if group >= self.limit:
break
# text sfs file does not have any haplotype pools
loci_input['pool'] = [[]]
if self.chip_file:
cdata = self.chip_file.getdata(loci_input['name'])
if cdata is None or (not is_within(cdata['num_variants'],
self.args.def_valid_locus)):
continue
loci_input['missing'] = [
False if x in cdata['pos'] else True
for x in loci_input['pos']
]
assert len(loci_input['missing']) == len(loci_input['maf'])
else:
loci_input['missing'] = None
if is_within(loci_input['num_variants'],
self.args.def_valid_locus):
if self.data_buffer is None:
self.result.append(
Calculator(self.args, self.unknown_args,
loci_input).run())
else:
self.data_buffer.append(loci_input)
self.pbar.update(group + 1)