io.files¶

Module: `io.files`¶

The io.files module provides basic functions for working with file-based images in nipy.

load : load an image from a file
save : save an image to a file

Examples¶

See documentation for load and save functions for worked examples.

Functions¶

nipy.io.files.as_image(image_input)¶

Load image from filename or pass through image instance

Parameters:

image_inputstr or Image instance: image or string filename of image. If a string, load image and return. If an image, pass through without modification

Returns:

imgImage or Image-like instance: Input object if image_input seemed to be an image, loaded Image object if image_input was a string.

Raises:

TypeErrorif neither string nor image-like passed

Examples

>>> from nipy.testing import anatfile
>>> from nipy.io.api import load_image
>>> img = as_image(anatfile)
>>> img2 = as_image(img)
>>> img2 is img
True

nipy.io.files.load(filename)¶

Load an image from the given filename.

Parameters:

filenamestring: Should resolve to a complete filename path.

Returns:

imageAn Image object: If successful, a new Image object is returned.

See also

save_image: function for saving images
Image: image object

Examples

>>> from nipy.io.api import load_image
>>> from nipy.testing import anatfile
>>> img = load_image(anatfile)
>>> img.shape
(33, 41, 25)

nipy.io.files.save(img, filename, dtype_from='data')¶

Write the image to a file.

Parameters:

imgAn Image object
filenamestring: Should be a valid filename.
dtype_from{‘data’, ‘header’} or dtype specifier, optional: Method of setting dtype to save data to disk. Value of ‘data’ (default), means use data dtype to save. ‘header’ means use data dtype specified in header, if available, otherwise use data dtype. Can also be any valid specifier for a numpy dtype, e.g. ‘i4’, np.float32. Not every format supports every dtype, so some values of this parameter or data dtypes will raise errors.

Returns:

imageAn Image object: Possibly modified by saving.

See also

load_image: function for loading images
Image: image object

Notes

Filetype is determined by the file extension in ‘filename’. Currently the following filetypes are supported:

Nifti single file : [‘.nii’, ‘.nii.gz’]
Nifti file pair : [‘.hdr’, ‘.hdr.gz’]
SPM Analyze : [‘.img’, ‘.img.gz’]

Examples

Make a temporary directory to store files

>>> import os
>>> from tempfile import mkdtemp
>>> tmpdir = mkdtemp()

Make some some files and save them

>>> import numpy as np
>>> from nipy.core.api import Image, AffineTransform
>>> from nipy.io.api import save_image
>>> data = np.zeros((91,109,91), dtype=np.uint8)
>>> cmap = AffineTransform('kji', 'zxy', np.eye(4))
>>> img = Image(data, cmap)
>>> fname1 = os.path.join(tmpdir, 'img1.nii.gz')
>>> saved_img1 = save_image(img, fname1)
>>> saved_img1.shape
(91, 109, 91)
>>> fname2 = os.path.join(tmpdir, 'img2.img.gz')
>>> saved_img2 = save_image(img, fname2)
>>> saved_img2.shape
(91, 109, 91)
>>> fname = 'test.mnc'
>>> saved_image3 = save_image(img, fname)
Traceback (most recent call last):
   ...
ValueError: Sorry, we cannot yet save as format "minc"

Finally, we clear up our temporary files:

>>> import shutil
>>> shutil.rmtree(tmpdir)