pyXenium.multimodal.HistoSegLazySlideConfig#

class HistoSegLazySlideConfig(output_dir=None, contour_key='histoseg_structures', contour_geojson=None, contour_id_key='polygon_id', contour_coordinate_space='xenium_pixel', contour_pixel_size_um=None, he_image_key='he', he_source_path=None, wsi_reader=None, slide_mpp=None, model='plip', text_model=None, text_terms=<factory>, prompt_set_name='breast_histology_v1', prompt_source='manual exploratory prompt set', prompt_review_status='not pathologist-confirmed', relative_prompt_axes=<factory>, tile_px=224, mpp=0.5, device='cuda', amp=True, batch_size=64, max_tiles=None, table_format='csv', include_rna=True, include_wta_programs=True, include_boundary_programs=True, include_prediction_benchmark=True, wta_program_library='breast_tme_wta_v1', program_library='tumor_boundary_v1', rna_markers=<factory>)#

Bases: object

Configuration for HistoSeg-anchored LazySlide image feature analysis.

Parameters:

output_dir (str | Path | None)
contour_key (str)
contour_geojson (str | Path | None)
contour_id_key (str)
contour_coordinate_space (str)
contour_pixel_size_um (float | None)
he_image_key (str)
he_source_path (str | Path | None)
wsi_reader (str | None)
slide_mpp (float | None)
model (str)
text_model (str | None)
text_terms (tuple[str, ...])
prompt_set_name (str)
prompt_source (str)
prompt_review_status (str)
relative_prompt_axes (tuple[tuple[str, str, str], ...])
tile_px (int)
mpp (float)
device (str)
amp (bool)
batch_size (int)
max_tiles (int | None)
table_format (Literal['csv', 'parquet'])
include_rna (bool)
include_wta_programs (bool)
include_boundary_programs (bool)
include_prediction_benchmark (bool)
wta_program_library (str)
program_library (str)
rna_markers (tuple[str, ...])

__init__(output_dir=None, contour_key='histoseg_structures', contour_geojson=None, contour_id_key='polygon_id', contour_coordinate_space='xenium_pixel', contour_pixel_size_um=None, he_image_key='he', he_source_path=None, wsi_reader=None, slide_mpp=None, model='plip', text_model=None, text_terms=<factory>, prompt_set_name='breast_histology_v1', prompt_source='manual exploratory prompt set', prompt_review_status='not pathologist-confirmed', relative_prompt_axes=<factory>, tile_px=224, mpp=0.5, device='cuda', amp=True, batch_size=64, max_tiles=None, table_format='csv', include_rna=True, include_wta_programs=True, include_boundary_programs=True, include_prediction_benchmark=True, wta_program_library='breast_tme_wta_v1', program_library='tumor_boundary_v1', rna_markers=<factory>)#

Parameters:

output_dir (str | Path | None)
contour_key (str)
contour_geojson (str | Path | None)
contour_id_key (str)
contour_coordinate_space (str)
contour_pixel_size_um (float | None)
he_image_key (str)
he_source_path (str | Path | None)
wsi_reader (str | None)
slide_mpp (float | None)
model (str)
text_model (str | None)
text_terms (tuple[str, ...])
prompt_set_name (str)
prompt_source (str)
prompt_review_status (str)
relative_prompt_axes (tuple[tuple[str, str, str], ...])
tile_px (int)
mpp (float)
device (str)
amp (bool)
batch_size (int)
max_tiles (int | None)
table_format (Literal['csv', 'parquet'])
include_rna (bool)
include_wta_programs (bool)
include_boundary_programs (bool)
include_prediction_benchmark (bool)
wta_program_library (str)
program_library (str)
rna_markers (tuple[str, ...])

Return type:

None

Methods

`__init__`([output_dir, contour_key, ...])
`to_dict`()

Attributes

output_dir: str | Path | None = None#

contour_key: str = 'histoseg_structures'#

contour_geojson: str | Path | None = None#

contour_id_key: str = 'polygon_id'#

contour_coordinate_space: str = 'xenium_pixel'#

contour_pixel_size_um: float | None = None#

he_image_key: str = 'he'#

he_source_path: str | Path | None = None#

wsi_reader: str | None = None#

slide_mpp: float | None = None#

model: str = 'plip'#

text_model: str | None = None#

text_terms: tuple[str, ...]#

prompt_set_name: str = 'breast_histology_v1'#

prompt_source: str = 'manual exploratory prompt set'#

prompt_review_status: str = 'not pathologist-confirmed'#

relative_prompt_axes: tuple[tuple[str, str, str], ...]#

tile_px: int = 224#

mpp: float = 0.5#

device: str = 'cuda'#

amp: bool = True#

batch_size: int = 64#

max_tiles: int | None = None#

table_format: Literal['csv', 'parquet'] = 'csv'#

include_rna: bool = True#

include_wta_programs: bool = True#

include_boundary_programs: bool = True#

include_prediction_benchmark: bool = True#

wta_program_library: str = 'breast_tme_wta_v1'#

program_library: str = 'tumor_boundary_v1'#

rna_markers: tuple[str, ...]#

to_dict()#

Return type:: dict[str, Any]

`amp`
`batch_size`
`contour_coordinate_space`
`contour_geojson`
`contour_id_key`
`contour_key`
`contour_pixel_size_um`
`device`
`he_image_key`
`he_source_path`
`include_boundary_programs`
`include_prediction_benchmark`
`include_rna`
`include_wta_programs`
`max_tiles`
`model`
`mpp`
`output_dir`
`program_library`
`prompt_review_status`
`prompt_set_name`
`prompt_source`
`slide_mpp`
`table_format`
`text_model`
`tile_px`
`wsi_reader`
`wta_program_library`
`text_terms`
`relative_prompt_axes`
`rna_markers`