class DonorInfoSchema(BaseSchema):
_MANY = True
id = Int(required=True, description="Donor ID")
name = Str(required=True, description="Donor Name")
external_donor_name = Str(
description="External donor name (expected to be labtracks ID)")
specimens = Nested(SpecimenSchema, many=True)
class PairwiseRigidSchema(StackTransitionParameters):
match_collection = Str(required=True,
description="Point match collection name")
gap_file = InputFile(
required=False,
default=None,
missing=None,
description="json file {k: v} where int(k) is a z value to skip"
"entries in here that are not already missing will"
"be omitted from the output stack"
"i.e. this is a place one can skip sections")
translate_to_positive = Bool(
required=False,
default=True,
missing=True,
description="translate output stack to positive space")
translation_buffer = List(Float,
required=False,
default=[0, 0],
missing=[0, 0],
description=("minimum (x, y) of output stack if "
"translate_to_positive=True"))
anchor_stack = Str(
require=False,
default=None,
missing=None,
description=("fix transforms using tiles in this stack"))
class FlipStackParameters(RenderParameters):
input_stack = Str(required=True,description='stack to apply affine to')
output_stack = Str(required=False,description='stack to save answer into (defaults to overwriting input_stack)')
minZ = Int(required=True,description='minimum Z to flip')
maxZ = Int(required=True,description='maximum Z to flip')
pool_size = Int(required=False,default=20,description='size of pool for parallel processing (default=20)')
delete_after = Boolean(required=False,default=False,description='whether to delete the old image files or not after flipping')
class PointMatchTransferParameters(RenderTransferParameters):
collection_source = Str(required=True,
description='point match collection to move from source_render')
collection_target = Str(required=False,
description='point match colleciton to move to target_render (default to the same)')
pool_size = Int(required=False,default=20,
description='point match colleciton to move to target_render (default to the same)')
class BaseStackParameters(DefaultSchema):
stack = Str(required=True, description="Stack name")
owner = Str(
required=False,
default=None,
missing=None,
description="Owner of the stack (defaults to render clients' owner)")
project = Str(required=False,
default=None,
missing=None,
description="Project of the stack")
service_host = Str(
required=False,
default=None,
missing=None,
description="url of render service host (without http://)")
baseURL = Str(required=False,
default=None,
missing=None,
description="Base Render URL")
renderbinPath = InputDir(required=False,
default=None,
missing=None,
description="Path to render's client scripts")
verbose = Int(required=False,
default=0,
missing=0,
description="Verbose output from solver needed?")
class LensCorrectionParameters(ArgSchema):
manifest_path = InputFile(required=True,
description='path to manifest file')
project_path = Str(required=True, description='path to project directory')
fiji_path = InputFile(required=True, description='path to FIJI')
grid_size = Int(
required=True,
description=('maximum row and column to form square '
'subset of tiles starting from zero (based on filenames '
'which end in "\{row\}_\{column\}.tif")'))
heap_size = Int(required=False,
default=20,
description="memory in GB to allocate to Java heap")
outfile = Str(required=False,
description=("File to which json output of lens correction "
"(leaf TransformSpec) is written"))
processing_directory = Str(
required=False,
allow_none=True,
description=("directory to which trakem2 processing "
"directory will be written "
"(will place in project_path directory if "
"unspecified or create temporary directory if None)"))
SIFT_params = Nested(SIFTParameters)
align_params = Nested(AlignmentParameters)
max_threads_SIFT = Int(required=False,
default=3,
description=("Threads specified for SIFT"))
class MakeMedianParams(StackTransitionParameters):
file_prefix = Str(required=False, default="Median",
description='File prefix for median image file that is saved')
output_directory = Str(required=True,
description='Output Directory for saving median image')
num_images = Int (required=False,default=-1,
description="Number of images to randomly subsample to generate median")
class DetectAndDropStitchingMistakesParameters(RenderParameters):
prestitchedStack = Str(
required=True,
description='name of render stack of tiles before stitching')
poststitchedStack = Str(
required=True,
description='name of render stack of tiles after stitching')
outputStack = Str(
required=True,
description='name of render stack to output with stitching fixed')
jsonDirectory = Str(required=True,
description='directory to save json files')
edge_threshold = Int(
required=False,
default=1843,
description=
'distance between tilespecs to consider as edges(default=1843)')
pool_size = Int(required=False,
default=20,
description='degree of parallelism (default=20)')
distance_threshold = Int(
required=False,
default=50,
description=
'amplitude difference between pre and post stitching results,\
that causes edge to be tossed (units of render)(default=50)')
class ConsolidateTransformsParameters(RenderParameters):
stack = Str(required=True, description='stack to consolidate')
postfix = Str(required=False,
default="_CONS",
description=('postfix to add to stack name on saving if no '
'output defined (default _CONS)'))
transforms_slice = Slice(
required=True,
description=("a string representing a slice describing "
"the set of transforms to be consolidated (i.e. 1:)"))
output_stack = Str(required=False,
description=('name of output stack (default to adding '
'postfix to input)'))
pool_size = Int(
required=False,
default=10,
description=(
'name of output stack (default to adding postfix to input)'))
minZ = Float(
required=False,
description=(
"minimum z to consolidate in read in from stack and write "
"to output_stack. Default to minimum z in stack"))
maxZ = Float(
required=False,
description=(
"maximum z to consolidate in read in from stack and write "
"to output_stack. Default to maximum z in stack"))
overwrite_zlayer = Boolean(
required=False,
default=False,
description=("whether to remove the existing layer from the "
"target stack before uploading."))
close_stack = Boolean(required=False, default=False)
class RenderStackParameters(RenderParameters):
stack = Str(required=True,
description='stack to render')
channel = Str(required=False,
description='name to use instead of stack to name files/directories')
minX = Int(required=False,
description='minimum X of box (else default to stack bounds)')
minY = Int(required=False,
description='minimum Y of box (else default to stack bounds)')
width = Int(required=False,
description='width of box (else default to stack bounds)')
height = Int(required=False,
description='height of box (else default to stack bounds)')
scale = Float(required=False,default=1.0,
description='scale to render (default is 1.0)')
minZ = Int(required=False,
description='minimum Z to use to render (default to stack bounds)')
maxZ = Int(required=False,
description='maximum Z to use to render (default to stack bounds)')
minIntensity = Int(required=False,default=0,
description='minimum Intensity used to render tiles(default to 0)')
maxIntensity = Int(required=False,default=65535,
description='maximum Intensity used to render tiles(default to 65535)')
volume_dir = Str(required=True,
description='root folder to save images.. volume_dir/channel/channel_XXXXXX.tif')
pool_size = Int(required=False,default=5,
description='degree of parallelism to use (default to 5)')
class ApplyAlignmentFromRegisteredStackParametersBase(RenderParameters):
prealigned_stack = Str(
required=True,
description=
'stack has same tiles as aligned stack but is registered with source_stack(s) example'
)
postaligned_stack = Str(
required=True,
description=
'stack has same tiles as prealignedstack stack but is in the desired aligned space'
)
pool_size = Int(required=False,
default=20,
description='degree of parallelism (default 20)')
stackResolutionX = Int(
required=False,
default=1,
description=
'X stack resolution (nm) to save in output stack (default use source stack)'
)
stackResolutionY = Int(
required=False,
default=1,
description=
'Y stack resolution (nm) to save in output stack (default use source stack)'
)
stackResolutionZ = Int(
required=False,
default=1,
description=
'Z stack resolution (nm) to save in output stack (default use source stack)'
)
class ApplyLensCorrectionParameters(StackTransitionParameters):
transform = Nested(TransformParameters)
refId = Str(allow_none=True,
required=True,
description=('Reference ID to use when uploading transform to '
'render database (Not Implemented)'))
labels = List(Str,
required=False,
missing=['lens'],
default=['lens'],
description="labels for the lens correction transform")
maskUrl = InputFile(
required=False,
default=None,
missing=None,
description='path to level 0 maskUrl to apply to stack')
maskUrl_uri = Str(required=False,
default=None,
missing=None,
description="uri for level 0 mask image to apply")
@marshmallow.pre_load
def maskUrl_to_uri(self, data):
rendermodules.utilities.schema_utils.posix_to_uri(
data, "maskUrl", "maskUrl_uri")
class FilterEMParameters(RenderParameters):
input_stack = Str(required=True, description='stack to apply affine to')
output_stack = Str(
required=False,
description=
'stack to save answer into (defaults to overwriting input_stack)')
pool_size = Int(
required=False,
default=20,
description='size of pool for parallel processing (default=20)')
sat_pix = Float(
required=False,
default=.2,
description=
'percent of pixels to saturate when normalizing contrast (default .2%)'
)
contrast_adjust = Float(
required=False,
default=.85,
description='constrast fraction to adjust before CLAHE (default .85)')
clahe_size = Int(
required=False,
default=90,
description=
'CLAHE parameter for grid size.. smaller is less strong, larger is stronger (default 90)'
)
clahe_clip_limit = Float(
required=False,
default=1.5,
description='clip limit for CLAHE normalization (default 1.5)')
vert_flip = Boolean(required=False,
default=True,
description='vertically flip the image (default True)')
class FilterSchema(RenderParameters, ZValueParameters, ProcessPoolParameters):
input_stack = Str(
required=True,
description='stack with stage-aligned coordinates')
input_match_collection = Str(
required=True,
description='Name of the montage point match collection')
output_match_collection = Str(
required=True,
default=None,
missing=None,
description='Name of the montage point match collection to write to')
resmax = Float(
required=True,
description=("maximum value in "
"pixels for average residual in tile pair"))
transmax = Float(
required=True,
description=("maximum value in "
"pixels for translation relative to stage coords"))
filter_output_file = OutputFile(
required=True,
description="location of json file with filter output")
inverse_weighting = Bool(
required=True,
default=False,
missing=False,
description='new weights weighted inverse to counts per tile-pair')
class QCPointMatchResultsParameters(RenderParameters):
matchcollections = List(
Str,
required=True,
metadata={'description': 'list of match collections to analyze'})
input_tilepairfile = InputFile(
required=True,
metadata={'description': 'file path of tile pair file to qc'})
output_tilepairfile = Str(
required=True,
metadata={
'description':
'file path of where to save the tile pair file to qc'
})
figdir = Str(required=True,
metadata={'description': 'directory to save images'})
min_matches = Int(
required=False,
default=5,
metadata={
'description':
'number of matches between tiles to be considered a valid match'
})
pool_size = Int(
required=False,
default=20,
metadata={'description': 'number of parallel threads to use'})
class UploadChannelTileSpecParameters(RenderParameters):
inputDir = Str(required=True,
metadata={'description': 'directory to upload'})
outputStack = Str(required=True,
metadata={'description': 'directory to upload'})
channel = Str(required=True,
metadata={'description': 'directory to upload'})
class TransformLocalAnnotationParameters(RenderParameters):
stack = Str(required=True,
description='stack to look for transform annotations into')
input_annotation_file = InputFile(required=True,
description='path to annotation file')
output_annotation_file = Str(
required=True, description='path to save transformed annotation')
class LensCorrectionParameters(ArgSchema):
manifest_path = Str(required=True,
metadata={'description': 'path to manifest file'})
project_path = Str(required=True,
metadata={'description': 'path to project directory'})
SIFT_params = Nested(SIFTParameters)
other_params = Nested(OtherParameters)
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 PostProcessROIsInputSchema(ArgSchema):
suite2p_stat_path = Str(
required=True,
validate=lambda x: Path(x).exists(),
description=("Path to s2p output stat file containing ROIs generated "
"during source extraction"))
motion_corrected_video = Str(
required=True,
validate=lambda x: Path(x).exists(),
description=("Path to motion corrected video file *.h5"))
motion_correction_values = InputFile(
required=True,
description=("Path to motion correction values for each frame "
"stored in .csv format. This .csv file is expected to"
"have a header row of either:\n"
"['framenumber','x','y','correlation','kalman_x',"
"'kalman_y']\n['framenumber','x','y','correlation',"
"'input_x','input_y','kalman_x',"
"'kalman_y','algorithm','type']"))
output_json = OutputFile(
required=True, description=("Path to a file to write output data."))
maximum_motion_shift = Float(
missing=30.0,
required=False,
allow_none=False,
description=("The maximum allowable motion shift for a frame in pixels"
" before it is considered an anomaly and thrown out of "
"processing"))
abs_threshold = Float(
missing=None,
required=False,
allow_none=True,
description=("The absolute threshold to binarize ROI masks against. "
"If not provided will use quantile to generate "
"threshold."))
binary_quantile = Float(
missing=0.1,
validate=Range(min=0, max=1),
description=("The quantile against which an ROI is binarized. If not "
"provided will use default function value of 0.1."))
npixel_threshold = Int(
default=50,
required=False,
description=("ROIs with fewer pixels than this will be labeled as "
"invalid and small size."))
aspect_ratio_threshold = Float(
default=0.2,
required=False,
description=("ROIs whose aspect ratio is <= this value are "
"not recorded. This captures a large majority of "
"Suite2P-created artifacts from motion border"))
morphological_ops = Bool(
default=True,
required=False,
description=("whether to perform morphological operations after "
"binarization. ROIs that are washed away to empty "
"after this operation are eliminated from the record. "
"This can apply to ROIs that were previously labeled "
"as small size, for example."))
class NeuroglancerLayerOptions(DefaultSchema):
opacity = Float(validate=mm.validate.Range(0, 1),
description="default opacity of layers")
blend = Str(default="default",
validate=mm.validate.OneOf(['default', 'additive']),
description="Blend mode for this each layer created",
required=False)
shader = Str(description="shader to use")
class SplitTileParameters(RenderParameters):
stack = Str(required=True,
metadata={'description': 'stack from tile to split'})
tileId = Str(required=True,
metadata={'description': 'tileId of tile to split'})
matchCollection = Str(
required=True,
metadata={'description': 'matchCollection to base splitting on'})
class GenerateMipMapsParameters(InputStackParameters):
output_dir = mm.fields.Str(
required=False,
description='directory to which the mipmaps will be stored')
output_prefix = mm.fields.Str(
required=True, description=("uri prefix for generated mipmaps"))
method = mm.fields.Str(
required=True,
default="block_reduce",
validator=mm.validate.OneOf(["PIL", "block_reduce"]),
description=(
"method to downsample mipmapLevels, "
"'PIL' for PIL Image (currently NEAREST) filtered resize, "
"can be 'block_reduce' for skimage based area downsampling"))
# "'render' for render-ws based rendering. "
convert_to_8bit = mm.fields.Boolean(
required=False,
default=True,
description='convert the data from 16 to 8 bit (default True)')
pool_size = mm.fields.Int(required=False,
default=20,
description='number of cores to be used')
imgformat = mm.fields.Str(
required=False,
default='tiff',
description='image format for mipmaps (default tiff)')
levels = mm.fields.Int(
required=False,
default=6,
description='number of levels of mipmaps, default is 6')
force_redo = mm.fields.Boolean(
required=False,
default=True,
description='force re-generation of existing mipmaps')
PIL_filter = Str(required=False,
default='NEAREST',
validator=mm.validate.OneOf([
'NEAREST', 'BOX', 'BILINEAR', 'HAMMING', 'BICUBIC',
'LANCZOS'
]),
description=('filter to be used in PIL resize'))
block_func = Str(required=False,
default='mean',
validator=mm.validate.OneOf(['mean', 'median']),
description=("function to represent blocks in "
"area downsampling with block_reduce"))
@classmethod
def validationOptions(cls, options):
excluded_fields = {'PIL': [''], 'block_reduce': [''], 'render': ['']}
exc_fields = excluded_fields[options['method']]
return cls(exclude=exc_fields).dump(options)
# TODO test this
@pre_load
def directory_to_prefix(self, data):
rendermodules.utilities.schema_utils.posix_to_uri(
data, "output_dir", "output_prefix")
class AddDownSampleParameters(RenderParameters):
input_stack = Str(required=True,
description='stack to input')
output_stack = Str(required=True,
description='stack to output (deletes before upload)')
convert_to_8bit = Boolean(required=False,default=True,
description='convert the data from 16 to 8 bit (default True)')
pool_size = Int(required=False, default=20,
description='size of parallelism')
class src_dst(DefaultSchema):
src = Str(required=False,
missing='opt',
default='opt',
description=("is optical data src or dst"))
dst = Str(required=False,
missing='em',
default='em',
description=("is em data src or dst"))
class common_schema(ArgSchema):
client_mount_or_map = Str(
required=True,
default="/data/em-131fs3",
missing="/data/em-131fs3",
description=("where the client sees the robocopied destination"
" windows example 'Q:'"))
fdir = Str(required=True,
description="appended to client_mount to find files")
class ApplyTransformParameters(RenderParameters):
alignedStack = Str(required=True,
metadata={'description':'stack whose transforms you want to copy'})
inputStack = Str(required=True,
metadata={'description':'stack you want to apply transforms to'})
outputStack = Str(required=True,
metadata={'description':'stack name to save result'})
pool_size = Int(required=True,default=20,
metadata={'description':'number of parallel threads'})
class GenerateEMTileSpecsParameters(OutputStackParameters):
metafile = InputFile(
required=False,
description="metadata file containing TEMCA acquisition data")
metafile_uri = Str(
required=True,
description=("uri of metadata containing TEMCA acquisition data"))
# FIXME maskUrl and image_directory are not required -- posix_to_uri should support this
maskUrl = InputFile(required=False,
default=None,
missing=None,
description="absolute path to image mask to apply")
maskUrl_uri = Str(required=False,
default=None,
missing=None,
description=("uri of image mask to apply"))
image_directory = InputDir(
required=False,
description=("directory used in determining absolute paths to images. "
"Defaults to parent directory containing metafile "
"if omitted."))
image_prefix = Str(
required=False,
description=(
"prefix used in determining full uris of images in metadata. "
"Defaults to using the / delimited prefix to "
"the metadata_uri if omitted"))
maximum_intensity = Int(
required=False,
default=255,
description=("intensity value to interpret as white"))
minimum_intensity = Int(
required=False,
default=0,
description=("intensity value to interpret as black"))
sectionId = Str(
required=False,
description=("sectionId to apply to tiles during ingest. "
"If unspecified will default to a string "
"representation of the float value of z_index."))
@pre_load
def metafile_to_uri(self, data):
rendermodules.utilities.schema_utils.posix_to_uri(
data, "metafile", "metafile_uri")
# FIXME not required -- does this work
@pre_load
def maskUrl_to_uri(self, data):
rendermodules.utilities.schema_utils.posix_to_uri(
data, "storage_directory", "storage_prefix")
@pre_load
def image_directory_to_prefix(self, data):
rendermodules.utilities.schema_utils.posix_to_uri(
data, "image_directory", "image_prefix")
class RegisterSubvolumeOutputParameters(argschema.schemas.DefaultSchema):
stack_a = Str(required=True,
description=("'parent' stack remaining fixed for this "
"transform to register"))
stack_b = Str(required=True,
description=("'child' stack which moves with this "
"transformation in order to register"))
transform = Nested(
Transform, required=False, default=None, allow_none=True,
description="")
class ApplyMaskParameters(RenderParameters):
mask_file = Str(required=True, description='Mask file')
input_stack = Str(required=True, description='Input Stack')
output_stack = Str(required=True, description='Output Stack')
pool_size = Int(
required=False,
default=20,
description='size of pool for parallel processing (default=20)')
minz = Int(required=False, default=-1, description='minz')
maxz = Int(required=False, default=-1, description='maxz')
