def setUp(self):
window_selector_model = realigner_pb2.WindowSelectorModel(
model_type=realigner_pb2.WindowSelectorModel.VARIANT_READS,
variant_reads_model=realigner_pb2.WindowSelectorModel.
VariantReadsThresholdModel(min_num_supporting_reads=1,
max_num_supporting_reads=10))
self.config = realigner_pb2.WindowSelectorOptions(
min_mapq=20,
min_base_quality=20,
min_windows_distance=4,
region_expansion_in_bp=20,
window_selector_model=window_selector_model)
def setUp(self):
window_selector_model = realigner_pb2.WindowSelectorModel(
model_type=realigner_pb2.WindowSelectorModel.ALLELE_COUNT_LINEAR,
allele_count_linear_model=realigner_pb2.WindowSelectorModel.
AlleleCountLinearModel(bias=0,
coeff_soft_clip=0,
coeff_substitution=-0.5,
coeff_insertion=1,
coeff_deletion=1,
coeff_reference=-0.5,
decision_boundary=0))
self.config = realigner_pb2.WindowSelectorOptions(
min_mapq=20,
min_base_quality=20,
min_windows_distance=4,
region_expansion_in_bp=20,
window_selector_model=window_selector_model)
def window_selector_config(flags_obj):
"""Creates a WindowSelectorOptions proto based on input and default settings.
Args:
flags_obj: configuration FLAGS.
Returns:
realigner_pb2.WindowSelector protobuf.
Raises:
ValueError: If either ws_{min,max}_supporting_reads are set and
ws_use_window_selector_model is True.
Or if ws_window_selector_model > ws_max_num_supporting_reads.
Or if ws_use_window_selector_model is False and
ws_window_selector_model is not None.
"""
if not flags_obj.ws_use_window_selector_model:
if flags_obj.ws_window_selector_model is not None:
raise ValueError('Cannot specify a ws_window_selector_model '
'if ws_use_window_selector_model is False.')
min_num_supporting_reads = (
_DEFAULT_MIN_SUPPORTING_READS
if flags_obj.ws_min_num_supporting_reads == _UNSET_WS_INT_FLAG else
flags_obj.ws_min_num_supporting_reads)
max_num_supporting_reads = (
_DEFAULT_MAX_SUPPORTING_READS
if flags_obj.ws_max_num_supporting_reads == _UNSET_WS_INT_FLAG else
flags_obj.ws_max_num_supporting_reads)
window_selector_model = realigner_pb2.WindowSelectorModel(
model_type=realigner_pb2.WindowSelectorModel.VARIANT_READS,
variant_reads_model=realigner_pb2.WindowSelectorModel.
VariantReadsThresholdModel(
min_num_supporting_reads=min_num_supporting_reads,
max_num_supporting_reads=max_num_supporting_reads))
else:
if flags_obj.ws_min_num_supporting_reads != _UNSET_WS_INT_FLAG:
raise ValueError('Cannot use both ws_min_num_supporting_reads and '
'ws_use_window_selector_model flags.')
if flags_obj.ws_max_num_supporting_reads != _UNSET_WS_INT_FLAG:
raise ValueError('Cannot use both ws_max_num_supporting_reads and '
'ws_use_window_selector_model flags.')
if flags_obj.ws_window_selector_model is None:
window_selector_model = _ALLELE_COUNT_LINEAR_MODEL_DEFAULT
else:
with tf.gfile.GFile(flags_obj.ws_window_selector_model) as f:
window_selector_model = text_format.Parse(
f.read(), realigner_pb2.WindowSelectorModel())
if (window_selector_model.model_type ==
realigner_pb2.WindowSelectorModel.VARIANT_READS):
model = window_selector_model.variant_reads_model
if model.max_num_supporting_reads < model.min_num_supporting_reads:
raise ValueError('ws_min_supporting_reads should be smaller than '
'ws_max_supporting_reads.')
ws_config = realigner_pb2.WindowSelectorOptions(
min_mapq=flags_obj.ws_min_mapq,
min_base_quality=flags_obj.ws_min_base_quality,
min_windows_distance=flags_obj.ws_min_windows_distance,
max_window_size=flags_obj.ws_max_window_size,
region_expansion_in_bp=flags_obj.ws_region_expansion_in_bp,
window_selector_model=window_selector_model)
return ws_config