loadsave

Utilities to load and save image objects

guessed_image_type(filename)

Guess image type from file filename

load(filename, **kwargs)

Load file given filename, guessing at file type

read_img_data(img[, prefer])

Read data from image associated with files

save(img, filename, **kwargs)

Save an image to file adapting format to filename

guessed_image_type

nibabel.loadsave.guessed_image_type(filename)

Guess image type from file filename

guessed_image_type deprecated.

  • deprecated from version: 3.2

  • Will raise <class ‘nibabel.deprecator.ExpiredDeprecationError’> as of version: 5.0

Parameters:
filenamestr

File name containing an image

Returns:
image_classclass

Class corresponding to guessed image type

load

nibabel.loadsave.load(filename, **kwargs)

Load file given filename, guessing at file type

Parameters:
filenamestr or os.PathLike

specification of file to load

**kwargskeyword arguments

Keyword arguments to format-specific load

Returns:
imgSpatialImage

Image of guessed type

read_img_data

nibabel.loadsave.read_img_data(img, prefer='scaled')

Read data from image associated with files

read_img_data deprecated. Please use img.dataobj.get_unscaled() instead.

  • deprecated from version: 3.2

  • Will raise <class ‘nibabel.deprecator.ExpiredDeprecationError’> as of version: 5.0

If you want unscaled data, please use img.dataobj.get_unscaled() instead. If you want scaled data, use img.get_fdata() (which will cache the loaded array) or np.array(img.dataobj) (which won’t cache the array). If you want to load the data as for a modified header, save the image with the modified header, and reload.

Parameters:
imgSpatialImage

Image with valid image file in img.file_map. Unlike the img.get_fdata() method, this function returns the data read from the image file, as specified by the current image header and current image files.

preferstr, optional

Can be ‘scaled’ - in which case we return the data with the scaling suggested by the format, or ‘unscaled’, in which case we return, if we can, the raw data from the image file, without the scaling applied.

Returns:
arrndarray

array as read from file, given parameters in header

Notes

Summary: please use the get_data method of img instead of this function unless you are sure what you are doing.

In general, you will probably prefer prefer='scaled', because this gives the data as the image format expects to return it.

Use prefer == ‘unscaled’ with care; the modified Analyze-type formats such as SPM formats, and nifti1, specify that the image data array is given by the raw data on disk, multiplied by a scalefactor and maybe with the addition of a constant. This function, with unscaled returns the data on the disk, without these format-specific scalings applied. Please use this function only if you absolutely need the unscaled data, and the magnitude of the data, as given by the scalefactor, is not relevant to your application. The Analyze-type formats have a single scalefactor +/- offset per image on disk. If you do not care about the absolute values, and will be removing the mean from the data, then the unscaled values will have preserved intensity ratios compared to the mean-centered scaled data. However, this is not necessarily true of other formats with more complicated scaling - such as MINC.

save

nibabel.loadsave.save(img, filename, **kwargs)

Save an image to file adapting format to filename

Parameters:
imgSpatialImage

image to save

filenamestr or os.PathLike

filename (often implying filenames) to which to save img.

**kwargskeyword arguments

Keyword arguments to format-specific save

Returns:
None