spatialdata._io.format.CurrentRasterFormat#

spatialdata._io.format.CurrentRasterFormat#

alias of RasterFormatV01

Attributes table#

Methods table#

generate_coordinate_transformations(shapes)

generate_well_dict(well, rows, columns)

init_channels()

init_store(path[, mode])

Not ideal.

matches(metadata)

validate_coordinate_transformations(ndim, ...)

Validate that a list of dicts contains a 'scale' transformation.

validate_well_dict(well, rows, columns)

Attributes#

CurrentRasterFormat.REQUIRED_PLATE_WELL_KEYS: Dict[str, type] = {'columnIndex': <class 'int'>, 'path': <class 'str'>, 'rowIndex': <class 'int'>}#
CurrentRasterFormat.spatialdata_format_version#
CurrentRasterFormat.version#

Methods#

CurrentRasterFormat.generate_coordinate_transformations(shapes)#
Return type:

None | list[list[dict[str, Any]]]

CurrentRasterFormat.generate_well_dict(well, rows, columns)#
Return type:

dict

CurrentRasterFormat.init_channels()#
Return type:

None

CurrentRasterFormat.init_store(path, mode='r')#

Not ideal. Stores should remain hidden TODO: could also check dimension_separator

Return type:

FSStore

CurrentRasterFormat.matches(metadata)#
Return type:

bool

CurrentRasterFormat.validate_coordinate_transformations(ndim, nlevels, coordinate_transformations=None)#

Validate that a list of dicts contains a ‘scale’ transformation.

Raises ValueError if no ‘scale’ found or doesn’t match ndim :type ndim: int :param ndim:Number of image dimensions.

Return type:

None

CurrentRasterFormat.validate_well_dict(well, rows, columns)#
Return type:

None