navigate.model.data_sources.tiff_data_source.TiffDataSource

class navigate.model.data_sources.tiff_data_source.TiffDataSource(file_name: str = '', mode: str = 'w', is_bigtiff: bool = False)

Bases: DataSource

Data source for TIFF files.

__init__(file_name: str = '', mode: str = 'w', is_bigtiff: bool = False) → None

Initialize a TIFF data source.

Parameters:

• file_name (str) – Path to file.

• mode (str) – File mode. “r” for read, “w” for write.

• is_bigtiff (bool) – Is this a bigtiff file?

Methods

__init__([file_name, mode, is_bigtiff])	Initialize a TIFF data source.
close([internal])	Close the file.
generate_image_name(current_channel, ...)	Generates a string for the filename, e.g., CH00_000000.tif
get_data([timepoint, position, channel, z, ...])	Get data according to timepoint, position, channel and z-axis id
get_shape_from_metadata()	Get the shape of the data source from the metadata.
read()	Read a tiff file.
set_bigtiff(is_bigtiff)	Set whether this is a bigtiff file.
set_metadata(metadata_config)	Sets the metadata
set_metadata_from_configuration_experiment(...)	Sets the metadata from according to the microscope configuration.
setup()	Additional steps for establishing the initial file setup.
write(data, **kw)	Writes 2D image to the data source.

Attributes

data	Return the image data as a numpy array.
is_bigtiff	Is this a bigtiff file?
is_ome	Is this an OME-TIFF file?
mode	Getter for the mode of the data source.
nbytes	Getter for the size of this data source in bytes.
shape	Getter for the shape as XYCZT.
voxel_size	Getter for the voxel size
image	Image data
save_directory	Directory to save the data to.
metadata	Metadata object

close(internal=False) → None

Close the file.

Parameters:

internal (bool) – Internal flag. Do not close if True.

generate_image_name(current_channel, current_time_point)

Generates a string for the filename, e.g., CH00_000000.tif

Parameters:

• current_channel (int) – Current channel index.

• current_time_point (int) – Current time point index.

Returns:

Image name.

Return type:

str

get_data(timepoint: int = 0, position: int = 0, channel: int = 0, z: int = -1, resolution: int = 1) → Union[_SupportsArray[dtype], _NestedSequence[_SupportsArray[dtype]], bool, int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]

Get data according to timepoint, position, channel and z-axis id

Parameters:

• timepoint (int) – The timepoint value

• position (int) – The position id in multi-position table

• channel (int) – The channel id

• z (int) – The index of Z in a Z-stack. Return all z if -1.

• resolution (int) – values from 1, 2, 4, 8 Not supported for now.

Returns:

data – Image data

Return type:

npt.ArrayLike

get_shape_from_metadata()

Get the shape of the data source from the metadata.

read() → None

Read a tiff file.

set_bigtiff(is_bigtiff: bool) → None

Set whether this is a bigtiff file.

Parameters:

is_bigtiff (bool) – Is this a bigtiff file?

set_metadata(metadata_config: dict) → None

Sets the metadata

Parameters:

metadata_config (dict) – shape configuration: “c”, “z”, “t”, “p”, “is_dynamic”, “per_stack”

set_metadata_from_configuration_experiment(configuration: Dict[str, Any], microscope_name: Optional[str] = None) → None

Sets the metadata from according to the microscope configuration.

Parameters:

• configuration (Dict[str, Any]) – Configuration experiment.

• microscope_name (str) – The microscope name

setup()

Additional steps for establishing the initial file setup.

write(data: Union[_SupportsArray[dtype], _NestedSequence[_SupportsArray[dtype]], bool, int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]], **kw) → None

Writes 2D image to the data source.

One channel, all z-position, one timepoint = one stack. N channels are opened simultaneously for writing. At each time point, a new file is opened for each channel.

Parameters:

• data (npt.ArrayLike) – Data to write to file.

• kw (dict) – Keyword arguments to pass to tifffile.imsave.

bits

Number of bits per pixel.

Type:

int

property data: Union[_SupportsArray[dtype], _NestedSequence[_SupportsArray[dtype]], bool, int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]

Return the image data as a numpy array.

Returns:

Image data.

Return type:

npt.ArrayLike

dc

Step size between channels (always 1)

Type:

float

dt

The time interval between frames (seconds).

Type:

float

dx

Pixel size in x dimension (microns). float: Pixel size in y dimension (microns). float: Pixel size in z dimension (microns).

Type:

float

dy

Pixel size in x dimension (microns). float: Pixel size in y dimension (microns). float: Pixel size in z dimension (microns).

Type:

float

dz

Pixel size in x dimension (microns). float: Pixel size in y dimension (microns). float: Pixel size in z dimension (microns).

Type:

float

file_name

Name of the file to read/write from.

Type:

str

image

Image data

Type:

np.ndarray

property is_bigtiff: bool

Is this a bigtiff file?

Returns:

Is this a bigtiff file?

Return type:

bool

property is_ome: bool

Is this an OME-TIFF file?

Returns:

Is this an OME-TIFF file?

Return type:

bool

logger

Logger for this class.

Type:

logging.Logger

metadata

Metadata object

Type:

Metadata

property mode: str

Getter for the mode of the data source.

Returns:

Mode of the data source.

Return type:

str

property nbytes: int

Getter for the size of this data source in bytes.

Does not account for pyramidal data sources. That process is handled by the bdv_data_source class, which is a child of this class.

Returns:

total_bytes – Size of this data source in bytes.

Return type:

int

positions

Number of positions in the data source.

Type:

int

save_directory

Directory to save the data to.

Type:

str

property shape: tuple

Getter for the shape as XYCZT.

Returns:

Shape of the data source in XYCZT format.

Return type:

tuple

shape_c

Size of the data source in c dimension.

Type:

int

shape_t

Size of the data source in t dimension.

Type:

int

shape_x

Size of the data source in x dimension.

Type:

int

shape_y

Size of the data source in y dimension.

Type:

int

shape_z

Size of the data source in z dimension.

Type:

int

property voxel_size: tuple

Getter for the voxel size

Returns:

Voxel size in x, y, z dimensions.

Return type:

tuple