class Directories(DefaultSchema):
ecephys_directory = InputDir(
help=
'Location of the ecephys_spike_sorting directory containing modules directory'
)
npx_directory = InputDir(help='Location of raw neuropixels binary files')
kilosort_output_directory = OutputDir(
help='Location of Kilosort output files')
extracted_data_directory = OutputDir(
help='Location for NPX/CatGT processed files')
kilosort_output_tmp = OutputDir(help='Location for temporary KS output')
class ExperimentPlane(DefaultSchema):
experiment_id = Int(
required=True,
description="Ophys experiment id.")
storage_directory = OutputDir(
required=True,
description="Folder for output files.")
roi_index = Int(
required=True,
description="Index of ROI in the scanimage metadata.")
scanfield_z = Float(
required=True,
description="Z value of the scanfield for this experiment plane.")
resolution = Float(
required=True,
description="Pixel size in microns.")
offset_x = Int(
required=True,
description="X offset of image from gold reticle.")
offset_y = Int(
required=True,
description="Y offset of image from gold reticle.")
rotation = Float(
required=True,
description="Rotation of image relative to gold reticle.")
class PiaWmStreamlineSchema(ArgSchema):
"""Arg Schema for run_pia_wm_streamlines"""
pia_path_str = String(
required=True,
description='string alternating x, y coordinates outlining the pia')
wm_path_str = String(
required=True,
description='string alternating x, y coordinates outlining the wm')
soma_path_str = String(
required=False,
description='string alternating x, y coordinates outlining the soma. '
'If provided, streamlines will be translated so that '
'the origin is at the soma')
resolution = Float(required=False,
default=1,
description='Resolution of pixels in microns')
pia_fixed_value = Float(required=False,
default=1,
description='Fixed value pia boundary condition')
wm_fixed_value = Float(required=False,
default=0,
description='Fixed value wm boundary condition')
mesh_res = Int(required=False,
default=20,
description='Resolution for mesh for laplace solver')
output_dir = OutputDir(required=True,
description='Directory to write xarray results')
class PointMatchOptimizationParameters(RenderParameters):
stack = Str(
required=True,
description='Name of the stack containing the tile pair')
tile_stack = Str(
required=False,
default=None,
missing=None,
description='Name of the stack that will hold these two tiles')
tileId1 = Str(
required=True,
description='tileId of the first tile in the tile pair')
tileId2 = Str(
required=True,
description='tileId of the second tile in the tile pair')
pool_size = Int(
required=False,
default=10,
missing=10,
description='Pool size for parallel processing')
SIFT_options = Nested(SIFT_options, required=True)
outputDirectory = OutputDir(
required=True,
description='Parent directory in which subdirectories will be created to store images and point-match results from SIFT')
url_options = Nested(url_options, required=True)
class PointMatchClientParametersQsub(
RenderParameters, SIFTPointMatchParameters, SparkOptions):
sparkhome = InputDir(
required=False,
default="/allen/aibs/pipeline/image_processing/"
"volume_assembly/utils/spark",
missing="/allen/aibs/pipeline/image_processing/"
"volume_assembly/utils/spark",
description="Path to the spark home directory")
pbs_template = InputFile(
required=True,
description="pbs template to wrap spark job")
no_nodes = Int(
required=False,
default=30,
missing=10,
description='Number of nodes to run the pbs job')
ppn = Int(
required=False,
default=30,
missing=30,
description='Number of processors per node (default = 30)')
queue_name = Str(
required=False,
default='connectome',
missing='connectome',
description='Name of the queue to submit the job')
logdir = OutputDir(
required=True,
description="location to set logging for qsub command"
)
class MultIntensityCorrParams(StackTransitionParameters):
correction_stack = Str(
required=True,
description='Correction stack (usually median stack for AT data)')
output_directory = OutputDir(
required=True,
description='Directory for storing Images')
# TODO add create_stack metadata
cycle_number = Int(
required=False, default=2,
description="what cycleNumber to upload for output_stack on render")
cycle_step_number = Int(
required=False, default=1,
description=("what cycleStepNumber to upload "
"for output_stack on render"))
clip = Bool(
required=False, default=True,
description="whether to clip values")
scale_factor = Float(
required=False, default=1.0,
description="scaling value")
clip_min = Int(
required=False, default=0,
description='Min Clip value')
clip_max = Int(
required=False, default=65535,
description='Max Clip value')
class MontageSolverSchema(ArgSchema):
data_dir = InputDir(
required=False,
description="directory containing metafile, images, and matches")
metafile = InputFile(
required=False,
description=("fullpath to metafile. Helps in the case of multiple"
" metafiles in one directory. data_dir will take "
" os.path.dirname(metafile)"))
output_dir = OutputDir(required=False,
missing=None,
default=None,
description="directory for output files")
read_transform_from = Str(
required=False,
missing='metafile',
default='metafile',
validator=mm.validate.OneOf(['metafile', 'reffile', 'dict']),
description="3 possible ways to read in the reference transform")
ref_transform = InputFile(required=False,
missing=None,
default=None,
description="transform json")
ref_transform_dict = Dict(require=False,
missing=None,
description="transform in from memory")
ransacReprojThreshold = Float(
required=False,
missing=10.0,
default=10.0,
description=("passed into cv2.estimateAffinePartial2D()"
"for RANSAC filtering of montage template matches"))
compress_output = Boolean(
required=False,
missing=True,
default=True,
description=("tilespecs will be .json or .json.gz"))
solver_templates = List(
Str,
required=True,
description="input json basenames for the solver args")
solver_template_dir = InputDir(
required=True, description="location of the templates for the solver")
@mm.post_load
def check_solver_inputs(self, data):
for args in data['solver_templates']:
argpath = os.path.join(data['solver_template_dir'], args)
if not os.path.isfile(argpath):
raise mm.ValidationError("solver arg file doesn't exist: %s" %
argpath)
@mm.post_load
def check_metafile(self, data):
if ('data_dir' not in data) & ('metafile' not in data):
raise mm.ValidationError(" must specify either data_dir"
" or metafile")
class PairwiseMatchingSchema(ArgSchema, CommonMatchingParameters):
output_directory = OutputDir(
required=True,
description="destination for output files.")
save_registered_image = fields.Bool(
required=False,
default=False,
description='Whether to save registered image.')
fixed = fields.Nested(PairwiseExperimentSchema)
moving = fields.Nested(PairwiseExperimentSchema)
class MaterializedBoxParameters(argschema.schemas.DefaultSchema):
stack = Str(required=True,
description=("stack fromw which boxes will be materialized"))
rootDirectory = OutputDir(
required=True,
description=
("directory in which materialization directory structure will be "
"created (structure is "
"<rootDirectory>/<project>/<stack>/<width>x<height>/<mipMapLevel>/<z>/<row>/<col>.<fmt>)"
))
width = Int(required=True,
description=("width of flat rectangular tiles to generate"))
height = Int(required=True,
description=("height of flat rectangular tiles to generate"))
maxLevel = Int(required=False,
default=0,
description=("maximum mipMapLevel to generate."))
fmt = Str(required=False,
validator=validate.OneOf(['PNG', 'TIF', 'JPG']),
description=("image format to generate mipmaps -- "
"PNG if not specified"))
maxOverviewWidthAndHeight = Int(
required=False,
description=(
"maximum pixel size for width or height of overview image. "
"If excluded or 0, no overview generated."))
skipInterpolation = Boolean(
required=False,
description=("whether to skip interpolation (e.g. DMG data)"))
binaryMask = Boolean(
required=False,
description=("whether to use binary mask (e.g. DMG data)"))
label = Boolean(
required=False,
description=("whether to generate single color tile labels rather "
"than actual images"))
createIGrid = Boolean(required=False,
description=("whther to create an IGrid file"))
forceGeneration = Boolean(
required=False, description=("whether to regenerate existing tiles"))
renderGroup = Int(
required=False,
description=(
"index (1-n) identifying coarse portion of layer to render"))
numberOfRenderGroups = Int(
required=False,
description=(
"used in conjunction with renderGroup, total number of groups "
"being used"))
filterListName = Str(
required=False,
description=("Apply specified filter list to all renderings"))
class RenderSectionAtScaleParameters(RenderParameters):
input_stack = Str(
required=True,
description='Input stack to make the downsample version of')
image_directory = OutputDir(
required=True,
description='Directory to save the downsampled sections')
imgformat = Str(required=False,
default="png",
missing="png",
description='Image format (default - png)')
doFilter = Boolean(required=False,
default=True,
missing=True,
description='Apply filtering before rendering')
fillWithNoise = Boolean(
required=False,
default=False,
missing=False,
description='Fill image with noise (default - False)')
scale = Float(required=True,
description='scale of the downsampled sections')
minZ = Int(required=False,
default=-1,
missing=-1,
description='min Z to create the downsample section from')
maxZ = Int(required=False,
default=-1,
missing=-1,
description='max Z to create the downsample section from')
filterListName = Str(
required=False,
description=("Apply specified filter list to all renderings"))
bounds = Nested(Bounds, required=False, default=None, missing=None)
use_stack_bounds = Boolean(
required=False,
default=False,
missing=False,
description=
'Do you want to use stack bounds while downsampling?. Default=False')
pool_size = Int(required=False,
default=20,
missing=20,
description='number of parallel threads to use')
@post_load
def validate_data(self, data):
# FIXME will be able to remove with render-python tweak
if data.get('filterListName') is not None:
warnings.warn(
"filterListName not implemented -- will use default behavior",
UserWarning)
class SolverSchema(ArgSchema):
data = Nested(DataLoaderSchema)
transform = Dict(required=True,
description="dict containing transform specification")
leave_out_index = Int(required=False,
missing=None,
default=None,
description="index to leave out of data")
output_dir = OutputDir(
required=False,
missing=None,
default=None,
description="path for writing output json of transform")
class PtMatchOptimizationParameters(RenderParameters):
stack = Str(
required=True,
description=(
'Name of the stack containing the tile pair (not the base stack)'))
tile_stack = Str(
required=False,
default=None,
missing=None,
description='Name of the stack that will hold these two tiles')
tilepair_file = InputFile(required=True, description='Tile pair file')
no_tilepairs_to_test = Int(
required=False,
default=10,
missing=10,
description=('Number of tilepairs to be tested for '
'optimization - default = 10'))
filter_tilepairs = Bool(
required=False,
default=False,
missing=False,
description=("Do you want filter the tilpair file for pairs "
"that overlap? - default = False"))
max_tilepairs_with_matches = Int(
required=False,
default=0,
missing=0,
description=('How many tilepairs with matches required for '
'selection of optimized parameter set'))
numberOfThreads = Int(
required=False,
default=5,
missing=5,
description='Number of threads to run point matching job')
SIFT_options = Nested(SIFT_options, required=True)
outputDirectory = OutputDir(
required=True,
description=(
'Parent directory in which subdirectories will be '
'created to store images and point-match results from SIFT'))
url_options = Nested(url_options, required=True)
pool_size = Int(required=False,
default=10,
missing=10,
description='Pool size for parallel processing')
@post_load
def validate_data(self, data):
if data['max_tilepairs_with_matches'] == 0:
data['max_tilepairs_with_matches'] = data['no_tilepairs_to_test']
class StagedSolveSchema(ArgSchema):
data = Nested(DataLoaderSchema)
transforms = List(Dict,
required=True,
description="list of transform arg dicts")
leave_out_index = Int(required=False,
missing=None,
default=None,
description="index to leave out of data")
output_dir = OutputDir(
required=False,
missing=None,
default=None,
description="path for writing output json of transform")
class MakeDownsampleSectionStackParameters(RenderParameters):
input_stack = Str(
required=True,
metadata={'description': 'stack to make a downsample version of'})
scale = Float(required=False,
default=.01,
metadata={'description': 'scale to make images'})
image_directory = OutputDir(
required=True, metadata={'decription', 'path to save section images'})
output_stack = Str(required=True,
metadata={'description': 'output stack to name'})
pool_size = Int(
required=False,
default=20,
metadata={'description': 'number of parallel threads to use'})
class InputSchema(ArgSchema):
log_level = Str(required=False, default="INFO")
depths_tif = InputFile(required=True,
description="Full path to depth 2p tiff file.")
surface_tif = InputFile(required=True,
description="Full path to surface 2p tiff file.")
timeseries_tif = InputFile(
required=True, description="Full path to timeseries tiff file.")
storage_directory = OutputDir(
required=True, description="Folder for column stack outputs.")
plane_groups = Nested(PlaneGroup, many=True)
test_mode = Int(
default=0,
description=("Flag to run without actually splitting data. For testing"
" runner mechanism and metadata. Testing of splitting "
"is handled in testing for the mesoscope_2p package."))
class InputParameters(ArgSchema):
output_dir = OutputDir(
default="./",
description="Directory in which to store data output files")
input_source = InputFile(description="Path to input movie", required=True)
pupil_bounding_box = NumpyArray(dtype="int", default=[])
cr_bounding_box = NumpyArray(dtype="int", default=[])
start_frame = Int(description="Frame of movie to start processing at")
stop_frame = Int(description="Frame of movie to end processing at")
frame_step = Int(description=(
"Interval of frames to process. Used for skipping frames,"
"if 1 it will process every frame between start and stop"))
ransac = Nested(RansacParameters)
annotation = Nested(AnnotationParameters)
starburst = Nested(StarburstParameters)
eye_params = Nested(EyeParameters)
qc = Nested(QCParameters)
class TraceExtractionInputSchema(ArgSchema):
log_level = LogLevel(default='INFO',
description="set the logging level of the module")
motion_border = Nested(
MotionBorder,
required=True,
description=("border widths - pixels outside the border are "
"considered invalid"))
storage_directory = OutputDir(required=True,
description="used to set output directory")
motion_corrected_stack = H5InputFile(
required=True,
description="path to h5 file containing motion corrected image stack")
rois = Nested(
ExtractROISchema,
many=True,
description="specifications of individual regions of interest")
log_0 = InputFile(
required=False,
description=("path to motion correction output csv. "
"NOTE: not used, but provided by LIMS schema."))
class SolverSchema(ArgSchema):
data = Nested(DataLoaderSchema)
regularization = Nested(regularization)
leave_out_index = Int(required=False,
missing=None,
default=None,
description="index to leave out of data")
model = Str(required=False,
default='TPS',
missing='TPS',
description=("LIN, POLY, or TPS for linear, polynomial, "
"thin plate spline"))
npts = Int(required=False,
missing=None,
default=None,
description="number of pts per axis for TPS controls")
output_dir = OutputDir(
required=False,
missing=None,
default=None,
description="path for writing output json of transform")
class RoughQCSchema(RenderParameters):
input_downsampled_stack = Str(
required=True, description="Pre rough aligned downsampled stack")
output_downsampled_stack = Str(required=True,
description="Rough aligned stack name")
minZ = Int(required=True, description="min z")
maxZ = Int(required=True, description="max z")
pool_size = Int(required=False,
default=10,
missing=10,
description="Pool size")
output_dir = OutputDir(required=False,
default=None,
missing=None,
description="temp filename to save fig")
out_file_format = Str(
validator=mm.validate.OneOf(['html', 'pdf']),
required=False,
default="pdf",
description=
"Do you want the output to be bokeh plots in html (option = 'html') or pdf files for plots (option = 'pdf', default)"
)
class NwayMatchSummarySchema(ArgSchema):
input_file = InputFile(
required=False,
desc="Input *.json file path to nway matching."
)
output_file = InputFile(
required=False,
desc="Output *.json file from nway matching."
)
# TODO: eliminate this non-specific Dict
nway_input = fields.Dict(
required=True,
desc="Input to nway matching in Python dictionary form."
)
nway_output = fields.Nested(NwayMatchingOutputNoPlotsSchema)
output_directory = OutputDir(
required=True,
description="Destination for summary plot output file(s).")
@mm.pre_load
def fill_dict_inputs(self, data: dict, **kwargs) -> dict:
if not data['nway_input']:
with open(data['input_file'], 'r') as f:
input_dict = json.load(f)
data['nway_input'] = input_dict
elif data.get('input_file'):
logger.warning("Both --nway_input and --input_file were provided "
"so --input_file will be ignored.")
if not data['nway_output']:
with open(data['output_file'], 'r') as f:
output_dict = json.load(f)
data['nway_output'] = output_dict
elif data.get('output_file'):
logger.warning("Both --nway_output and --output_file were "
"provided so --output_file will be ignored.")
return data
class MeshLensCorrectionSchema(ArgSchema):
nvertex = Int(required=False,
default=1000,
missinf=1000,
description="maximum number of vertices to attempt")
tilespec_file = InputFile(required=False,
description="path to json of tilespecs")
tilespecs = List(Dict,
required=False,
description="list of dict of tilespecs")
match_file = InputFile(required=False,
description="path to json of matches")
matches = List(Dict, required=False, description="list of dict of matches")
regularization = Nested(regularization, missing={})
good_solve = Nested(good_solve_criteria, missing={})
output_dir = OutputDir(required=False,
description="directory for output files")
outfile = Str(required=False,
description=("Basename to which resolved json output of "
"lens correction is written"))
compress_output = Boolean(
required=False,
missing=True,
default=True,
description=("tilespecs will be .json or .json.gz"))
timestamp = Boolean(required=False,
missing=False,
default=False,
description="add a timestamp to basename output")
@mm.post_load
def one_of_two(self, data):
for a, b in [['tilespecs', 'tilespec_file'], ['matches',
'match_file']]:
if (a in data) == (b in data): # xor
raise mm.ValidationError(
'must specify one and only one of %s or %s' % (a, b))
class LensCorrectionSchema(ArgSchema):
data_dir = InputDir(
required=True,
description="directory containing metafile, images, and matches")
output_dir = OutputDir(required=False,
description="directory for output files")
mask_file = InputFile(required=False,
default=None,
missing=None,
description="mask to apply to each tile")
nvertex = Int(required=False,
default=1000,
missinf=1000,
description="maximum number of vertices to attempt")
ransac_thresh = Float(required=False,
default=5.0,
missing=5.0,
description="ransac outlier threshold")
regularization = Nested(regularization, missing={})
good_solve = Nested(good_solve_criteria, missing={})
ignore_match_indices = List(
Int,
required=False,
default=None,
missing=None,
description=("debug feature for ignoring certain indices"
" of the match collection"))
compress_output = Boolean(
required=False,
missing=True,
default=True,
description=("tilespecs will be .json or .json.gz"))
timestamp = Boolean(required=False,
missing=False,
default=False,
description="add a timestamp to basename output")
class BasicOutputDir(ArgSchema):
output_dir = OutputDir(required=True, description="basic output dir")
class QCParameters(DefaultSchema):
generate_plots = Bool(
default=EyeTracker.DEFAULT_GENERATE_QC_OUTPUT,
description="Flag for whether or not to output QC plots")
output_dir = OutputDir(default="./qc",
description="Folder to store QC outputs")
class SolverOptionsParameters(DefaultSchema):
degree = Int(
required=False,
default=1,
missing=1,
description=
"Degree of rquired transformation (0 - Rigid, 1 - Affine(default), 2 - Polynomial)"
)
solver = Str(
required=False,
default="backslash",
missing="backslash",
description="type of solver to solve the system (default - backslash)")
close_stack = Bool(
required=False,
default=False,
description=
"whether the solver should close the stack after uploading results")
transfac = Float(required=False,
default=0.00001,
missing=0.00001,
description="translation factor")
lambda_value = Float(required=False,
default=1000,
missing=1000,
description="lambda for the solver")
edge_lambda = Float(required=False,
default=0.005,
missing=0.005,
description="edge lambda for solver regularization")
nbrs = Int(
required=False,
default=2,
missing=2,
description=
"number of neighboring sections to consider (applies for cross section point matches)"
)
nbrs_step = Int(required=False,
default=1,
missing=1,
description="neighbors step")
xs_weight = Float(required=True,
description="Cross section point match weights")
min_points = Int(
required=False,
default=5,
missing=5,
description=
"Minimum number of points correspondences required per tile pair")
max_points = Int(
required=False,
default=200,
missing=200,
description=
"Maximum number of point correspondences required per tile pair")
filter_point_matches = Int(
required=False,
default=1,
missing=1,
description="Filter point matches from collection (default = 1)")
outlier_lambda = Int(required=False,
default=1000,
missing=1000,
description="lambda value for outliers")
min_tiles = Int(required=False,
default=3,
missing=3,
description="Minimum number of tiles in section")
Width = Int(required=True, description="Width of the tiles")
Height = Int(required=True, description="Height of the tiles")
outside_group = Int(required=False,
default=0,
missing=0,
description="Outside group")
matrix_only = Int(required=False,
default=0,
missing=0,
description="matrix only")
distribute_A = Int(required=False,
default=16,
missing=16,
description="Distribute A matrix")
dir_scratch = OutputDir(required=True, description="Scratch directory")
distributed = Int(required=False,
default=0,
missing=0,
description="Distributed parameter of solver")
use_peg = Int(required=False,
default=0,
missing=0,
description="Use pegs? (default = 0)")
verbose = Int(required=False,
default=0,
missing=0,
description="Verbose output from solver needed?")
debug = Int(required=False,
default=0,
missing=0,
description="turn on debug mode (default = 0 - off)")
constrain_by_z = Int(required=False,
default=0,
missing=0,
description="Constrain solution by z (default = 0)")
sandwich = Int(required=False,
default=0,
missing=0,
description="sandwich factor of solver")
constraint_fac = Int(required=False,
default=1e15,
missing=1e15,
description="Contraint factor")
pmopts = Nested(PointMatchFilteringOptions,
required=True,
description="Point match filtering options for solver")
pastix = Nested(PastixOptions,
required=True,
description="Pastix solver options")
class PointMatchClientParametersSlurmSpark(SlurmSparkParameters,
SIFTPointMatchParameters):
logdir = OutputDir(
required=False,
description="location to set logging for slurm-spark command"
)
class TilePairClientParameters(RenderParameters):
stack = Str(
required=True,
description="input stack to which tilepairs need to be generated")
baseStack = Str(
required=False,
default=None,
missing=None,
description="Base stack")
minZ = Int(
required=False,
default=None,
missing=None,
description="z min for generating tilepairs")
maxZ = Int(
required=False,
default=None,
missing=None,
description="z max for generating tilepairs")
xyNeighborFactor = Float(
required=False,
default=0.9,
description="Multiply this by max(width, height) of "
"each tile to determine radius for locating neighbor tiles")
zNeighborDistance = Int(
required=False,
default=2,
missing=2,
description="Look for neighbor tiles with z values less than "
"or equal to this distance from the current tile's z value")
excludeCornerNeighbors = Bool(
required=False,
default=True,
missing=True,
description="Exclude neighbor tiles whose center x and y is "
"outside the source tile's x and y range respectively")
excludeSameLayerNeighbors = Bool(
required=False,
default=False,
missing=False,
description="Exclude neighbor tiles in the "
"same layer (z) as the source tile")
excludeCompletelyObscuredTiles = Bool(
required=False,
default=True,
missing=True,
description="Exclude tiles that are completely "
"obscured by reacquired tiles")
output_dir = OutputDir(
required=True,
description="Output directory path to save the tilepair json file")
memGB = Str(
required=False,
default='6G',
missing='6G',
description="Memory for the java client to run")
@post_load
def validate_data(self, data):
if data['baseStack'] is None:
data['baseStack'] = data['stack']
class Directories(DefaultSchema):
kilosort_output_directory = OutputDir(
help='Location of Kilosort output files')
extracted_data_directory = OutputDir(
help='Location for NPX file extraction')
class MeshLensCorrectionSchema(PointMatchOpenCVParameters):
input_stack = Str(required=True,
description="Name of raw input lens data stack")
output_stack = Str(required=True,
description="Name of lens corrected output stack")
overwrite_zlayer = Bool(required=False,
default=True,
missing=True,
description="Overwrite z layer (default = True)")
rerun_pointmatch = Bool(required=False,
default=True,
missing=True,
description="delete pointmatch values and rerun")
close_stack = Bool(required=False,
default=True,
missing=True,
description="Close input stack")
do_montage_QC = Bool(required=False,
default=True,
missing=True,
description="perform montage QC on stack result")
match_collection = Str(required=True,
description="name of point match collection")
metafile = Str(required=False, description="fullpath of metadata file")
metafile_uri = Str(required=True,
description="uri_handler uri of metafile object")
z_index = Int(required=True,
description="z value for the lens correction data in stack")
ncpus = Int(required=False,
default=-1,
description="max number of cpus to use")
nvertex = Int(required=False,
default=1000,
missing=1000,
description="maximum number of vertices to attempt")
output_dir = OutputDir(
required=False,
default=None,
missing=None,
description="output dir to save tile pair file and qc json")
outfile = Str(required=True,
description=("File to which json output of lens correction "
"(leaf TransformSpec) is written"))
regularization = Nested(regularization, missing={})
good_solve = Nested(good_solve_criteria, missing={})
sectionId = Str(required=True, default="xxx", description="section Id")
mask_coords = List(List(Int),
required=False,
default=None,
missing=None,
cli_as_single_argument=True,
description="Nx2 list of in-order bound coordinates")
mask_dir = OutputDir(required=False,
default=None,
missing=None,
description="directory for saving masks")
mask_file = InputFile(required=False,
default=None,
missing=None,
description="explicit mask setting from file")
@marshmallow.pre_load
def metafile_to_uri(self, data):
asap.utilities.schema_utils.posix_to_uri(data, "metafile",
"metafile_uri")
class ModeOutputDirSchema(ArgSchema):
output_dir = OutputDir(required=True,
description="775 output directory",
mode=0o775)