Module: external.tifffile¶

Bases: object

Read image and metadata from TIFF, STK, LSM, and FluoView files.

TiffFile instances must be closed using the close method, which is automatically called when using the ‘with’ statement.

Examples

>>> with TiffFile('test.tif') as tif:  
...     data = tif.asarray()
...     data.shape
(256, 256, 4)

Attributes

__init__(arg, name=None, offset=None, size=None, multifile=True, multifile_close=True)[source]¶

Initialize instance from file.

Parameters:

arg : str or open file Name of file or open file object. The file objects are closed in TiffFile.close(). name : str Optional name of file in case ‘arg’ is a file handle. offset : int Optional start position of embedded file. By default this is the current file position. size : int Optional size of embedded file. By default this is the number of bytes from the ‘offset’ to the end of the file. multifile : bool If True (default), series may include pages from multiple files. Currently applies to OME-TIFF only. multifile_close : bool If True (default), keep the handles of other files in multifile series closed. This is inefficient when few files refer to many pages. If False, the C runtime may run out of resources.

asarray(key=None, series=None, memmap=False)[source]¶

Return image data from multiple TIFF pages as numpy array.

By default the first image series is returned.

Parameters:	key : int, slice, or sequence of page indices Defines which pages to return as array. series : int Defines which series of pages to return as array. memmap : bool If True, return an array stored in a binary file on disk if possible.

close()[source]¶

Close open file handle(s).

filehandle¶

Return file handle.

filename¶

Return name of file handle.

fstat¶

Lazy object attribute whose value is computed on first access.

is_bigtiff¶

Lazy object attribute whose value is computed on first access.

is_fluoview¶

Lazy object attribute whose value is computed on first access.

is_imagej¶

Lazy object attribute whose value is computed on first access.

is_lsm¶

Lazy object attribute whose value is computed on first access.

is_mdgel¶

Lazy object attribute whose value is computed on first access.

is_mediacy¶

Lazy object attribute whose value is computed on first access.

is_micromanager¶

Lazy object attribute whose value is computed on first access.

is_nih¶

Lazy object attribute whose value is computed on first access.

is_ome¶

Lazy object attribute whose value is computed on first access.

is_palette¶

Lazy object attribute whose value is computed on first access.

is_rgb¶

Lazy object attribute whose value is computed on first access.

is_stk¶

Lazy object attribute whose value is computed on first access.

series¶

Lazy object attribute whose value is computed on first access.

Bases: object

Sequence of image files.

The data shape and dtype of all files must match.

Examples

>>> tifs = TiffSequence("test.oif.files/*.tif")  
>>> tifs.shape, tifs.axes  
((2, 100), 'CT')
>>> data = tifs.asarray()  
>>> data.shape  
(2, 100, 256, 256)

Attributes

__init__(files, imread=<class 'skimage.external.tifffile.tifffile.TiffFile'>, pattern='axes', *args, **kwargs)[source]¶

Initialize instance from multiple files.

Parameters:	files : str, or sequence of str Glob pattern or sequence of file names. imread : function or class Image read function or class with asarray function returning numpy array from single file. pattern : str Regular expression pattern that matches axes names and sequence indices in file names. By default this matches Olympus OIF and Leica TIFF series.

exception ParseError[source]¶

Bases: exceptions.Exception

TiffSequence.asarray(memmap=False, *args, **kwargs)[source]¶

Read image data from all files and return as single numpy array.

If memmap is True, return an array stored in a binary file on disk. The args and kwargs parameters are passed to the imread function.

Raise IndexError or ValueError if image shapes don’t match.

TiffSequence.close()[source]¶

Bases: object

Write image data to TIFF file.

TiffWriter instances must be closed using the close method, which is automatically called when using the ‘with’ statement.

Examples

>>> data = numpy.random.rand(2, 5, 3, 301, 219)
>>> with TiffWriter('temp.tif', bigtiff=True) as tif:
...     for i in range(data.shape[0]):
...         tif.save(data[i], compress=6)

__init__(filename, bigtiff=False, byteorder=None, software='tifffile.py')[source]¶

Create a new TIFF file for writing.

Use bigtiff=True when creating files greater than 2 GB.

Parameters:	filename : str Name of file to write. bigtiff : bool If True, the BigTIFF format is used. byteorder : {‘<’, ‘>’} The endianness of the data in the file. By default this is the system’s native byte order. software : str Name of the software used to create the image. Saved with the first page only.

TAGS = {'strip_byte_counts': 279, 'strip_offsets': 273, 'resolution_unit': 296, 'x_resolution': 282, 'photometric': 262, 'y_resolution': 283, 'subfile_type': 255, 'tile_byte_counts': 325, 'tile_offsets': 324, 'tile_width': 322, 'image_depth': 32997, 'bits_per_sample': 258, 'tile_depth': 32998, 'image_length': 257, 'datetime': 306, 'document_name': 269, 'orientation': 274, 'planar_configuration': 284, 'sample_format': 339, 'compression': 259, 'image_description': 270, 'fill_order': 266, 'image_width': 256, 'rows_per_strip': 278, 'color_map': 320, 'page_name': 285, 'samples_per_pixel': 277, 'new_subfile_type': 254, 'tile_length': 323, 'extra_samples': 338, 'predictor': 317, 'software': 305}¶

TYPES = {'B': 1, 'I': 4, 'H': 3, 'Q': 16, '2I': 5, 'b': 6, 'd': 12, 'f': 11, 'i': 9, 'h': 8, 'q': 17, 's': 2}¶

close()[source]¶

save(data, photometric=None, planarconfig=None, resolution=None, description=None, volume=False, writeshape=False, compress=0, extratags=())[source]¶

Write image data to TIFF file.

Image data are written in one stripe per plane. Dimensions larger than 2 to 4 (depending on photometric mode, planar configuration, and SGI mode) are flattened and saved as separate pages. The ‘sample_format’ and ‘bits_per_sample’ TIFF tags are derived from the data type.

Parameters:

data : array_like Input image. The last dimensions are assumed to be image depth, height, width, and samples. photometric : {‘minisblack’, ‘miniswhite’, ‘rgb’} The color space of the image data. By default this setting is inferred from the data shape. planarconfig : {‘contig’, ‘planar’} Specifies if samples are stored contiguous or in separate planes. By default this setting is inferred from the data shape. ‘contig’: last dimension contains samples. ‘planar’: third last dimension contains samples. resolution : (float, float) or ((int, int), (int, int)) X and Y resolution in dots per inch as float or rational numbers. description : str The subject of the image. Saved with the first page only. compress : int Values from 0 to 9 controlling the level of zlib compression. If 0, data are written uncompressed (default). volume : bool If True, volume data are stored in one tile (if applicable) using the SGI image_depth and tile_depth tags. Image width and depth must be multiple of 16. Few software can read this format, e.g. MeVisLab. writeshape : bool If True, write the data shape to the image_description tag if necessary and no other description is given. extratags: sequence of tuples Additional tags as [(code, dtype, count, value, writeonce)]. code : int The TIFF tag Id. dtype : str Data type of items in ‘value’ in Python struct format. One of B, s, H, I, 2I, b, h, i, f, d, Q, or q. count : int Number of data values. Not used for string values. value : sequence ‘Count’ values compatible with ‘dtype’. writeonce : bool If True, the tag is written to the first page only.