def _mk_stats_parser():
p = ArgParser(add_help=False)
# p.add_argument_group("Statistics options",
# "Options for calculating statistics.")
default_fwhms = "0.2"
p.set_defaults(stats_kernels=default_fwhms)
p.set_defaults(calc_stats=True)
p.add_argument(
"--calc-stats",
dest="calc_stats",
action="store_true",
help=
"Calculate statistics at the end of the registration. [Default = %(default)s]"
)
p.add_argument(
"--no-calc-stats",
dest="calc_stats",
action="store_false",
help=
"If specified, statistics are not calculated. Opposite of --calc-stats."
)
p.add_argument(
"--stats-kernels",
dest="stats_kernels",
type=str,
help=
"comma separated list of blurring kernels for analysis. [Default = %(default)s]."
)
return p
def _mk_thickness_parser(parser: ArgParser):
group = parser.add_argument_group("Thickness",
"Thickness calculation options.")
group.add_argument("--run-thickness",
action='store_true',
dest="run_thickness",
help="Run thickness computation.")
group.add_argument("--no-run-thickness",
action='store_false',
dest="run_thickness",
help="Don't run thickness computation.")
parser.set_defaults(run_thickness=True)
group.add_argument(
"--label-mapping",
type=str,
dest="label_mapping",
help="path to CSV file mapping; see minclaplace/wiki/LaplaceGrid")
group.add_argument(
"--atlas-fwhm",
dest="atlas_fwhm",
type=float, # default ?!
help="Blurring kernel (mm) for atlas")
group.add_argument(
"--thickness-fwhm",
dest="thickness_fwhm",
type=float, # default??
help="Blurring kernel (mm) for cortical surfaces")
return parser
def _mk_lsq12_parser():
p = ArgParser(add_help=False)
# group = parser.add_argument_group("LSQ12 registration options",
# "Options for performing a pairwise, affine registration")
p.set_defaults(run_lsq12=True)
p.add_argument("--run-lsq12", dest="run_lsq12",
action="store_true",
help="Actually run the 12 parameter alignment [default = %(default)s]")
p.add_argument("--no-run-lsq12", dest="run_lsq12",
action="store_false",
help="Opposite of --run-lsq12")
p.add_argument("--lsq12-max-pairs", dest="max_pairs",
type=parse_nullable_int, default=25,
help="Maximum number of pairs to register together ('None' implies all pairs). "
"[Default = %(default)s]")
p.add_argument("--lsq12-likefile", dest="like_file",
type=str, default=None,
help="Can optionally specify a 'like'-file for resampling at the end of pairwise "
"alignment. Default is None, which means that the input file will be used. "
"[Default = %(default)s]")
p.add_argument("--lsq12-protocol", dest="protocol",
type=str,
help="Can optionally specify a registration protocol that is different from defaults. "
"Parameters must be specified as in the following example: \n"
"applications_testing/test_data/minctracc_example_linear_protocol.csv \n"
"[Default = %(default)s].")
return p
def _mk_maget_parser(parser : ArgParser):
group = parser.add_argument_group("MAGeT options", "Options for running MAGeT.")
group.add_argument("--atlas-library", dest="atlas_lib", # can't make required=True since may not be using MAGeT :|
type=str, # TODO: check existence of this dir?
help="Directory of existing atlas/label pairs")
group.add_argument("--pairwise", dest="pairwise",
action="store_true",
help="""If specified, register inputs to each other pairwise. [Default]""")
group.add_argument("--no-pairwise", dest="pairwise",
action="store_false",
help="""If specified, only register inputs to atlases in library.""")
parser.set_defaults(pairwise=True)
group.add_argument("--mask", dest="mask",
action="store_true", default=False,
help="Create a mask for all images prior to handling labels. [Default = %(default)s]")
group.add_argument("--mask-only", dest="mask_only",
action="store_true", default=False,
help="Create a mask for all images only, do not run full algorithm. [Default = %(default)s]")
group.add_argument("--max-templates", dest="max_templates",
default=25, type=int,
help="Maximum number of templates to generate. [Default = %(default)s]")
group.add_argument("--masking-method", dest="mask_method",
default="minctracc", type=str,
help="Specify whether to use minctracc or mincANTS for masking. [Default = %(default)s].")
group.add_argument("--masking-nlin-protocol", dest="masking_nlin_protocol",
# TODO basically copied from nlin parser
type=str, default=None,
help="Can optionally specify a registration protocol that is different from nlin protocol. "
"Parameters must be specified as in either or the following examples: \n"
"applications_testing/test_data/minctracc_example_nlin_protocol.csv \n"
"applications_testing/test_data/mincANTS_example_nlin_protocol.csv \n"
"[Default = %(default)s]")
return parser
def _mk_segmentation_parser(parser : ArgParser, default : bool):
group = parser.add_argument_group("Segmentation", "Segmentation options.")
group.add_argument("--run-maget", action='store_true', dest="run_maget",
help="Run MAGeT segmentation. [default = %(default)s]")
group.add_argument("--no-run-maget", dest="run_maget",
action='store_false', help="Don't run MAGeT segmentation")
parser.set_defaults(run_maget=True)
return parser
def _mk_segmentation_parser(parser: ArgParser, default: bool):
group = parser.add_argument_group("Segmentation", "Segmentation options.")
group.add_argument("--run-maget",
action='store_true',
dest="run_maget",
help="Run MAGeT segmentation. [default = %(default)s]")
group.add_argument("--no-run-maget",
dest="run_maget",
action='store_false',
help="Don't run MAGeT segmentation")
parser.set_defaults(run_maget=True)
return parser
def _mk_lsq12_parser():
p = ArgParser(add_help=False)
# group = parser.add_argument_group("LSQ12 registration options",
# "Options for performing a pairwise, affine registration")
p.set_defaults(run_lsq12=True)
p.set_defaults(generate_tournament_style_lsq12_avg=False)
p.add_argument(
"--run-lsq12",
dest="run_lsq12",
action="store_true",
help="Actually run the 12 parameter alignment [default = %(default)s]")
p.add_argument("--no-run-lsq12",
dest="run_lsq12",
action="store_false",
help="Opposite of --run-lsq12")
p.add_argument(
"--lsq12-max-pairs",
dest="max_pairs",
type=parse_nullable_int,
default=25,
help=
"Maximum number of pairs to register together ('None' implies all pairs). "
"[Default = %(default)s]")
p.add_argument(
"--lsq12-likefile",
dest="like_file",
type=str,
default=None,
help=
"Can optionally specify a 'like'-file for resampling at the end of pairwise "
"alignment. Default is None, which means that the input file will be used. "
"[Default = %(default)s]")
p.add_argument(
"--lsq12-protocol",
dest="protocol",
type=str,
help=
"Can optionally specify a registration protocol that is different from defaults. "
"Parameters must be specified as in the following example: \n"
"applications_testing/test_data/minctracc_example_linear_protocol.csv \n"
"[Default = %(default)s].")
#p.add_argument("--generate-tournament-style-lsq12-avg", dest="generate_tournament_style_lsq12_avg",
# action="store_true",
# help="Instead of creating the average of the lsq12 resampled files "
# "by simply averaging them directly, create an iterative average "
# "as follows. Perform a non linear registration between pairs "
# "of files. Resample each file halfway along that transformation "
# "in order for them to end up in the middle. Average those two files. "
# "Then continue on to the next level as in a tournament. [default = %(default)s]")
#p.add_argument("--no-generate-tournament-style-lsq12-avg", dest="generate_tournament_style_lsq12_avg",
# action="store_false",
# help="Opposite of --generate-tournament-style-lsq12-avg")
return p
def get_settings_parser() -> ArgParser:
"""Returns the single global argument parser for adding parameters.
Parameters can be added in all modules by add_argument.
After calling parse() once in the main program, all settings
are available in the global settings dictionary.
"""
global _parser # pylint: disable=global-statement
if not _parser:
_parser = ArgParser( # default_config_files=["default.cfg"],
formatter_class=ArgumentDefaultsRawHelpFormatter)
_parser.set_defaults(seed=0)
return _parser
def _mk_thickness_parser(parser : ArgParser):
group = parser.add_argument_group("Thickness", "Thickness calculation options.")
group.add_argument("--run-thickness", action='store_true', dest="run_thickness",
help="Run thickness computation.")
group.add_argument("--no-run-thickness", action='store_false', dest="run_thickness",
help="Don't run thickness computation.")
parser.set_defaults(run_thickness=True)
group.add_argument("--label-mapping", type=str, dest="label_mapping",
help="path to CSV file mapping; see minclaplace/wiki/LaplaceGrid")
group.add_argument("--atlas-fwhm", dest="atlas_fwhm", type=float, # default ?!
help="Blurring kernel (mm) for atlas")
group.add_argument("--thickness-fwhm", dest="thickness_fwhm", type=float, # default??
help="Blurring kernel (mm) for cortical surfaces")
return parser
def _mk_stats_parser():
p = ArgParser(add_help=False)
# p.add_argument_group("Statistics options",
# "Options for calculating statistics.")
default_fwhms = "0.2"
p.set_defaults(stats_kernels=default_fwhms)
p.set_defaults(calc_stats=True)
p.add_argument("--calc-stats", dest="calc_stats",
action="store_true",
help="Calculate statistics at the end of the registration. [Default = %(default)s]")
p.add_argument("--no-calc-stats", dest="calc_stats",
action="store_false",
help="If specified, statistics are not calculated. Opposite of --calc-stats.")
p.add_argument("--stats-kernels", dest="stats_kernels",
type=str,
help="comma separated list of blurring kernels for analysis. [Default = %(default)s].")
return p
def _mk_lsq12_parser():
p = ArgParser(add_help=False)
# group = parser.add_argument_group("LSQ12 registration options",
# "Options for performing a pairwise, affine registration")
p.set_defaults(run_lsq12=True)
p.set_defaults(generate_tournament_style_lsq12_avg=False)
p.add_argument("--run-lsq12", dest="run_lsq12",
action="store_true",
help="Actually run the 12 parameter alignment [default = %(default)s]")
p.add_argument("--no-run-lsq12", dest="run_lsq12",
action="store_false",
help="Opposite of --run-lsq12")
p.add_argument("--lsq12-max-pairs", dest="max_pairs",
type=parse_nullable_int, default=25,
help="Maximum number of pairs to register together ('None' implies all pairs). "
"[Default = %(default)s]")
p.add_argument("--lsq12-likefile", dest="like_file",
type=str, default=None,
help="Can optionally specify a 'like'-file for resampling at the end of pairwise "
"alignment. Default is None, which means that the input file will be used. "
"[Default = %(default)s]")
p.add_argument("--lsq12-protocol", dest="protocol",
type=str,
help="Can optionally specify a registration protocol that is different from defaults. "
"Parameters must be specified as in the following example: \n"
"applications_testing/test_data/minctracc_example_linear_protocol.csv \n"
"[Default = %(default)s].")
#p.add_argument("--generate-tournament-style-lsq12-avg", dest="generate_tournament_style_lsq12_avg",
# action="store_true",
# help="Instead of creating the average of the lsq12 resampled files "
# "by simply averaging them directly, create an iterative average "
# "as follows. Perform a non linear registration between pairs "
# "of files. Resample each file halfway along that transformation "
# "in order for them to end up in the middle. Average those two files. "
# "Then continue on to the next level as in a tournament. [default = %(default)s]")
#p.add_argument("--no-generate-tournament-style-lsq12-avg", dest="generate_tournament_style_lsq12_avg",
# action="store_false",
# help="Opposite of --generate-tournament-style-lsq12-avg")
return p
def _mk_nlin_parser(p: ArgParser):
group = p.add_argument_group(
"Nonlinear registration options",
"Options for performing a non-linear registration")
group.add_argument(
"--registration-method",
dest="reg_method",
default="ANTS",
choices=["ANTS", "antsRegistration", "minctracc"],
help="Specify algorithm used for non-linear registrations. "
"[Default = %(default)s]")
# TODO wire up the choices here in reg_method and reg_strategy to the actual ones ...
group.add_argument(
"--registration-strategy",
dest="reg_strategy",
default="build_model",
choices=[
'build_model', 'pairwise', 'tournament',
'tournament_and_build_model', 'pairwise_and_build_model'
],
help="Process used for model construction [Default = %(default)s")
group.add_argument(
"--nlin-protocol",
dest="nlin_protocol",
type=str,
default=None,
help=
"Can optionally specify a registration protocol that is different from defaults. "
"Parameters must be specified as in either or the following examples: \n"
"applications_testing/test_data/minctracc_example_nlin_protocol.csv \n"
"applications_testing/test_data/mincANTS_example_nlin_protocol.csv \n"
"[Default = %(default)s]")
group.add_argument("--use-robust-averaging",
dest="use_robust_averaging",
action='store_true',
help="use robust intensity averaging if possible")
p.set_defaults(use_robust_averaging=False)
return p
def _mk_lsq6_parser(with_nuc : bool = True,
with_inormalize : bool = True):
p = ArgParser(add_help=False)
p.set_defaults(lsq6_method="lsq6_large_rotations")
p.set_defaults(nuc = True if with_nuc else False)
p.set_defaults(inormalize = True if with_inormalize else False)
p.set_defaults(copy_header_info=False)
# TODO: should this actually be part of the LSQ6 component? What would it return in this case?
p.set_defaults(run_lsq6=True)
p.add_argument("--run-lsq6", dest="run_lsq6",
action="store_true",
help="Actually run the 6 parameter alignment [default = %(default)s]")
p.add_argument("--no-run-lsq6", dest="run_lsq6",
action="store_false",
help="Opposite of --run-lsq6")
# TODO should be part of some mutually exclusive group ...
p.add_argument("--init-model", dest="init_model",
type=str, default=None,
help="File in standard space in the initial model. The initial model "
"can also have a file in native space and potentially a transformation "
"file. See our wiki (https://wiki.mouseimaging.ca/) for detailed "
"information on initial models. [Default = %(default)s]")
p.add_argument("--lsq6-target", dest="lsq6_target",
type=str, default=None,
help="File to be used as the target for the initial (often 6-parameter) alignment. "
"[Default = %(default)s]")
p.add_argument("--bootstrap", dest="bootstrap",
action="store_true", default=False,
help="Use the first input file to the pipeline as the target for the "
"initial (often 6-parameter) alignment. [Default = %(default)s]")
# TODO: add information about the pride of models to the code in such a way that it
# is reflected on GitHub
p.add_argument("--pride-of-models", dest="pride_of_models",
type=str, default=None,
help="(selected longitudinal pipelines only!) Specify a csv file that contains the mapping of "
"all your initial models at different time points. The idea is that you might "
"want to use different initial models for the time points in your data. "
"The csv file should have one column called \"model_file\", and one column "
"called \"time_point\". The time points can be given in either integer values "
"or float values. Each model file should point to the file in standard space "
"for that particular model. [Default = %(default)s]")
# TODO: do we need to implement this option? This was for Kieran Short, but the procedure
# he will be using in the future most likely will not involve this option.
# group.add_argument("--lsq6-alternate-data-prefix", dest="lsq6_alternate_prefix",
# type=str, default=None,
# help="Specify a prefix for an augmented data set to use for the 6 parameter "
# "alignment. Assumptions: there is a matching alternate file for each regular input "
# "file, e.g. input files are: input_1.mnc input_2.mnc ... input_n.mnc. If the "
# "string provided for this flag is \"aug_\", then the following files should exist: "
# "aug_input_1.mnc aug_input_2.mnc ... aug_input_n.mnc. These files are assumed to be "
# "in the same orientation/location as the regular input files. They will be used for "
# "for the 6 parameter alignment. The transformations will then be used to transform "
# "the regular input files, with which the pipeline will continue.")
p.add_argument("--lsq6-simple", dest="lsq6_method",
action="store_const", const="lsq6_simple",
help="Run a 6 parameter alignment assuming that the input files are roughly "
"aligned: same space, similar orientation. Keep in mind that if you use an "
"initial model with both a standard and a native space, the assumption is "
"that the input files are already roughly aligned to the native space. "
"Three iterations are run: 1st is 17 times stepsize blur, 2nd is 9 times "
"stepsize gradient, 3rd is 4 times stepsize blur. [Default = %(default)s]")
p.add_argument("--lsq6-centre-estimation", dest="lsq6_method",
action="store_const", const="lsq6_centre_estimation",
help="Run a 6 parameter alignment assuming that the input files have a "
"similar orientation, but are scanned in different coils/spaces. [Default = %(default)s]")
p.add_argument("--lsq6-large-rotations", dest="lsq6_method",
action="store_const", const="lsq6_large_rotations",
help="Run a 6 parameter alignment assuming that the input files have a random "
"orientation and are scanned in different coils/spaces. A brute force search over "
"the x,y,z rotation space is performed to find the best 6 parameter alignment. "
"[Default = %(default)s]")
p.add_argument("--lsq6-large-rotations-tmp-dir", dest="rotation_tmp_dir",
type=str, default="/dev/shm/",
help="Specify the directory that rotational_minctracc.py uses for temporary files. "
"By default we use /dev/shm/, because this program involves a lot of I/O, and "
"this is probably one of the fastest way to provide this. [Default = %(default)s]")
p.add_argument("--lsq6-large-rotations-parameters", dest="rotation_params",
type=str, default="5,4,10,8",
help="Settings for the large rotation alignment. factor=factor based on smallest file "
"resolution: 1) blur factor, 2) resample step size factor, 3) registration step size "
"factor, 4) w_translations factor ***** if you are working with mouse brain data "
" the defaults do not have to be based on the file resolution; a default set of "
" settings works for all mouse brain. In order to use those setting, specify: "
"\"mousebrain\" as the argument for this option. ***** [default = %(default)s]")
p.add_argument("--lsq6-rotational-range", dest="rotation_range",
type=int, default=50,
help="Settings for the rotational range in degrees when running the large rotation "
"alignment. [Default = %(default)s]")
p.add_argument("--lsq6-rotational-interval", dest="rotation_interval",
type=int, default=10,
help="Settings for the rotational interval in degrees when running the large rotation "
"alignment. [Default = %(default)s]")
p.add_argument("--nuc", dest="nuc",
action="store_true",
help="Perform non-uniformity correction. [Default = %(default)s]")
p.add_argument("--no-nuc", dest="nuc",
action="store_false",
help="If specified, do not perform non-uniformity correction. Opposite of --nuc.")
p.add_argument("--inormalize", dest="inormalize",
action="store_true",
help="Normalize the intensities after lsq6 alignment and nuc, if done. "
"[Default = %(default)s] ")
p.add_argument("--no-inormalize", dest="inormalize",
action="store_false",
help="If specified, do not perform intensity normalization. Opposite of --inormalize.")
p.add_argument("--copy-header-info-to-average", dest="copy_header_info",
action="store_true",
help="Copy the MINC header information of the first input file into the "
"average that is created. [Default = %(default)s] ")
p.add_argument("--no-copy-header-info-to-average", dest="copy_header_info",
action="store_false",
help="Opposite of --copy-header-info-to-average.")
p.add_argument("--lsq6-protocol", dest="protocol_file",
type=str, default=None,
help="Specify an lsq6 protocol that overrides the default setting for stages in "
"the 6 parameter minctracc call. Parameters must be specified as in the following \n"
"example: applications_testing/test_data/minctracc_example_linear_protocol.csv \n"
"[Default = %(default)s].")
return p
def _mk_maget_parser(parser: ArgParser):
group = parser.add_argument_group("MAGeT options",
"Options for running MAGeT.")
group.add_argument(
"--atlas-library",
dest=
"atlas_lib", # can't make required=True since may not be using MAGeT :|
type=str, # TODO: check existence of this dir?
help=
"Directory of existing atlas/label pairs (alternative to --atlas-csv)")
group.add_argument(
"--atlas-csv",
dest="atlas_csv",
type=str,
help=
"CSV containing (at least) `file`, `mask_file`, `label_file` columns "
"(alternative to --atlas-library)")
group.add_argument(
"--pairwise",
dest="pairwise",
action="store_true",
help=
"""If specified, register inputs to each other pairwise. [Default]""")
group.add_argument(
"--no-pairwise",
dest="pairwise",
action="store_false",
help="""If specified, only register inputs to atlases in library.""")
parser.set_defaults(pairwise=True)
group.add_argument(
"--mask",
dest="mask",
action="store_true",
default=True,
help=
"Create a mask for all images prior to handling labels. [Default = %(default)s]"
)
group.add_argument("--no-mask",
dest="mask",
action="store_false",
default=True,
help="Opposite of --mask.")
group.add_argument(
"--mask-only",
dest="mask_only",
action="store_true",
default=False,
help=
"Create a mask for all images only, do not run full algorithm. [Default = %(default)s]"
)
group.add_argument(
"--max-templates",
dest="max_templates",
default=25,
type=int,
help="Maximum number of templates to generate. [Default = %(default)s]"
)
group.add_argument(
"--masking-method",
dest="mask_method",
default="minctracc",
type=str,
help=
"Specify whether to use minctracc or ANTS for masking. [Default = %(default)s]."
)
group.add_argument(
"--masking-nlin-protocol",
dest="masking_nlin_protocol",
# TODO basically copied from nlin parser
type=str,
default=None,
help=
"Can optionally specify a registration protocol that is different from nlin protocol. "
"Parameters must be specified as in either or the following examples: \n"
"applications_testing/test_data/minctracc_example_nlin_protocol.csv \n"
"applications_testing/test_data/mincANTS_example_nlin_protocol.csv \n"
"[Default = %(default)s]")
return parser
def _mk_lsq6_parser(with_nuc: bool = True, with_inormalize: bool = True):
p = ArgParser(add_help=False)
p.set_defaults(lsq6_method="lsq6_large_rotations")
p.set_defaults(nuc=True if with_nuc else False)
p.set_defaults(inormalize=True if with_inormalize else False)
p.set_defaults(copy_header_info=False)
# TODO: should this actually be part of the LSQ6 component? What would it return in this case?
p.set_defaults(run_lsq6=True)
p.add_argument(
"--run-lsq6",
dest="run_lsq6",
action="store_true",
help="Actually run the 6 parameter alignment [default = %(default)s]")
p.add_argument("--no-run-lsq6",
dest="run_lsq6",
action="store_false",
help="Opposite of --run-lsq6")
# TODO should be part of some mutually exclusive group ...
p.add_argument(
"--init-model",
dest="init_model",
type=str,
default=None,
help="File in standard space in the initial model. The initial model "
"can also have a file in native space and potentially a transformation "
"file. See our wiki (https://wiki.mouseimaging.ca/) for detailed "
"information on initial models. [Default = %(default)s]")
p.add_argument(
"--lsq6-target",
dest="lsq6_target",
type=str,
default=None,
help=
"File to be used as the target for the initial (often 6-parameter) alignment. "
"[Default = %(default)s]")
p.add_argument(
"--bootstrap",
dest="bootstrap",
action="store_true",
default=False,
help="Use the first input file to the pipeline as the target for the "
"initial (often 6-parameter) alignment. [Default = %(default)s]")
# TODO: add information about the pride of models to the code in such a way that it
# is reflected on GitHub
p.add_argument(
"--pride-of-models",
dest="pride_of_models",
type=str,
default=None,
help=
"(selected longitudinal pipelines only!) Specify a csv file that contains the mapping of "
"all your initial models at different time points. The idea is that you might "
"want to use different initial models for the time points in your data. "
"The csv file should have one column called \"model_file\", and one column "
"called \"time_point\". The time points can be given in either integer values "
"or float values. Each model file should point to the file in standard space "
"for that particular model. [Default = %(default)s]")
# TODO: do we need to implement this option? This was for Kieran Short, but the procedure
# he will be using in the future most likely will not involve this option.
# group.add_argument("--lsq6-alternate-data-prefix", dest="lsq6_alternate_prefix",
# type=str, default=None,
# help="Specify a prefix for an augmented data set to use for the 6 parameter "
# "alignment. Assumptions: there is a matching alternate file for each regular input "
# "file, e.g. input files are: input_1.mnc input_2.mnc ... input_n.mnc. If the "
# "string provided for this flag is \"aug_\", then the following files should exist: "
# "aug_input_1.mnc aug_input_2.mnc ... aug_input_n.mnc. These files are assumed to be "
# "in the same orientation/location as the regular input files. They will be used for "
# "for the 6 parameter alignment. The transformations will then be used to transform "
# "the regular input files, with which the pipeline will continue.")
p.add_argument(
"--lsq6-simple",
dest="lsq6_method",
action="store_const",
const="lsq6_simple",
help=
"Run a 6 parameter alignment assuming that the input files are roughly "
"aligned: same space, similar orientation. Keep in mind that if you use an "
"initial model with both a standard and a native space, the assumption is "
"that the input files are already roughly aligned to the native space. "
"Three iterations are run: 1st is 17 times stepsize blur, 2nd is 9 times "
"stepsize gradient, 3rd is 4 times stepsize blur. [Default = %(default)s]"
)
p.add_argument(
"--lsq6-centre-estimation",
dest="lsq6_method",
action="store_const",
const="lsq6_centre_estimation",
help="Run a 6 parameter alignment assuming that the input files have a "
"similar orientation, but are scanned in different coils/spaces. [Default = %(default)s]"
)
p.add_argument(
"--lsq6-large-rotations",
dest="lsq6_method",
action="store_const",
const="lsq6_large_rotations",
help=
"Run a 6 parameter alignment assuming that the input files have a random "
"orientation and are scanned in different coils/spaces. A brute force search over "
"the x,y,z rotation space is performed to find the best 6 parameter alignment. "
"[Default = %(default)s]")
p.add_argument(
"--lsq6-large-rotations-tmp-dir",
dest="rotation_tmp_dir",
type=str,
default="/dev/shm/",
help=
"Specify the directory that rotational_minctracc.py uses for temporary files. "
"By default we use /dev/shm/, because this program involves a lot of I/O, and "
"this is probably one of the fastest way to provide this. [Default = %(default)s]"
)
p.add_argument(
"--lsq6-large-rotations-parameters",
dest="rotation_params",
type=str,
default="5,4,10,8",
help=
"Settings for the large rotation alignment. factor=factor based on smallest file "
"resolution: 1) blur factor, 2) resample step size factor, 3) registration step size "
"factor, 4) w_translations factor ***** if you are working with mouse brain data "
" the defaults do not have to be based on the file resolution; a default set of "
" settings works for all mouse brain. In order to use those setting, specify: "
"\"mousebrain\" as the argument for this option. ***** [default = %(default)s]"
)
p.add_argument(
"--lsq6-rotational-range",
dest="rotation_range",
type=int,
default=50,
help=
"Settings for the rotational range in degrees when running the large rotation "
"alignment. [Default = %(default)s]")
p.add_argument(
"--lsq6-rotational-interval",
dest="rotation_interval",
type=int,
default=10,
help=
"Settings for the rotational interval in degrees when running the large rotation "
"alignment. [Default = %(default)s]")
p.add_argument(
"--nuc",
dest="nuc",
action="store_true",
help="Perform non-uniformity correction. [Default = %(default)s]")
p.add_argument(
"--no-nuc",
dest="nuc",
action="store_false",
help=
"If specified, do not perform non-uniformity correction. Opposite of --nuc."
)
p.add_argument(
"--inormalize",
dest="inormalize",
action="store_true",
help="Normalize the intensities after lsq6 alignment and nuc, if done. "
"[Default = %(default)s] ")
p.add_argument(
"--no-inormalize",
dest="inormalize",
action="store_false",
help=
"If specified, do not perform intensity normalization. Opposite of --inormalize."
)
p.add_argument(
"--copy-header-info-to-average",
dest="copy_header_info",
action="store_true",
help="Copy the MINC header information of the first input file into the "
"average that is created. [Default = %(default)s] ")
p.add_argument("--no-copy-header-info-to-average",
dest="copy_header_info",
action="store_false",
help="Opposite of --copy-header-info-to-average.")
p.add_argument(
"--lsq6-protocol",
dest="protocol_file",
type=str,
default=None,
help=
"Specify an lsq6 protocol that overrides the default setting for stages in "
"the 6 parameter minctracc call. Parameters must be specified as in the following \n"
"example: applications_testing/test_data/minctracc_example_linear_protocol.csv \n"
"[Default = %(default)s].")
return p
def _create_parser():
parser = ArgParser(prog='releaser',
default_config_files=['.releaser'],
auto_env_var_prefix='releaser_')
parser.add_argument('--config', is_config_file=True)
parser.add_argument('--repository',
dest='repo',
type=Repo,
default=Repo(Path.cwd()))
parser.add_argument('--preprod-url', dest='preprod_url', default=None)
parser.add_argument('--release-branch', default='master')
parser.add_argument('--app-name')
parser.add_argument('--release-date', default='today')
parser.add_argument('--issue-tracker-url')
next_version_group = parser.add_mutually_exclusive_group()
next_version_group.add_argument('--build',
action='store_const',
const='BUILD',
env_var='RELEASER_NEXT_VERSION',
dest='next_version')
next_version_group.add_argument('--patch',
action='store_const',
const='PATCH',
env_var='RELEASER_NEXT_VERSION',
dest='next_version')
next_version_group.add_argument('--minor',
action='store_const',
const='MINOR',
env_var='RELEASER_NEXT_VERSION',
dest='next_version')
next_version_group.add_argument('--major',
action='store_const',
const='MAJOR',
env_var='RELEASER_NEXT_VERSION',
dest='next_version')
next_version_group.set_defaults(next_version='MINOR')
subparsers = parser.add_subparsers(dest='command')
versions_subparser = subparsers.add_parser('versions')
subparsers.add_parser('changes')
subparsers.add_parser('draft')
subparsers.add_parser('tag')
parser.add_argument('--template-mail',
type=Path,
dest='template_mail_path',
default=ROOT / 'releaser/templates/mail.md.j2')
parser.add_argument('--template-tag',
type=Path,
dest='template_tag_path',
default=ROOT / 'releaser/templates/tag.md.j2')
parser.add_argument('--template-changes',
type=Path,
dest='template_changes_path',
default=ROOT / 'releaser/templates/changes.md.j2')
parser.add_argument('--start', default='today @ 21:45')
parser.add_argument('--end', default='today @ 22:15')
parser.set_defaults(command='changes')
versions_subparser.add_argument('n',
nargs='?',
type=int,
default=999999999)
return parser
# General settings
p.add_argument(
'--verbose',
type=int,
default=0,
help='Verbosity level. '
'Default: 0',
)
p.add_argument(
'--wasserstein',
dest='wasserstein',
action='store_true',
help='If given, use wasserstein GAN.',
)
p.set_defaults(wasserstein=False)
p.add_argument(
'--GPU',
type=int,
default=0,
help='Which GPU. '
'Default: 0',
)
p.add_argument(
'--load_model',
dest='load_model',
action='store_true',
help='If given, load model.',
)
p.set_defaults(load_model=False)
default=[-90, 90],
help='Latitude range. Default = [-90, 90]')
p.add_argument('--target_factor',
type=float,
default=1.,
help='Factor to multiply targets with. For TF comparison '
'set to 1e-3. Default = 1.')
p.add_argument('--random_seed',
type=int,
default=42,
help='Random seed for shuffling of data.')
p.add_argument('--shuffle',
dest='shuffle',
action='store_true',
help='If given, shuffle data along sample dimension.')
p.set_defaults(shuffle=False)
p.add_argument('--only_norm',
dest='only_norm',
action='store_true',
help='If given, only compute and save normalization file.')
p.set_defaults(only_norm=False)
p.add_argument('--flx_same_dt',
dest='flx_same_dt',
action='store_true',
help='If given, take surface fluxes from same time step.')
p.set_defaults(flx_same_dt=False)
p.add_argument('--norm_features',
type=str,
default=None,
help='by_var or by_lev')
p.add_argument('--norm_targets',
)
p.add_argument(
'--test_dates',
type=str,
nargs='+',
default=['2016-01-01', '2017-01-01'],
help='Test start (inc) and stop (exc) dates in format '
'yyyy-mm-dd. Default: 2016-01-01 2017-01-01',
)
p.add_argument(
'--use_aux',
dest='use_aux',
action='store_true',
help='If given, use auxiliary variables.',
)
p.set_defaults(use_aux=False)
p.add_argument(
'--add_current_error',
dest='add_current_error',
action='store_true',
help='If given, use current error.',
)
p.set_defaults(add_current_error=False)
p.add_argument(
'--current_error_len',
type=int,
default=1,
help='Length of current error. Default: 1',
)
p.set_defaults(current_error=False)
p.add_argument(