pcntoolkit.dataio.fileio#

Attributes#

`CIFTI_MAPPINGS`
`CIFTI_VOL_ATLAS`
`path`
`path`

Functions#

`create_incremental_backup`(filepath)	Create an incremental backup of a file using the .bak{n} naming scheme.
`create_mask`(data_array, mask[, verbose])	Create a mask from a data array or a nifti file
`file_extension`(filename)	Determine the file extension of a file (e.g. .nii.gz)
`file_stem`(filename)	Determine the file stem of a file (e.g. /path/to/file.nii.gz -> file)
`file_type`(filename)	Determine the file type of a file
`load`(filename[, mask, text, vol])	Load array from a file.
`load_ascii`(filename)	Load an ascii file into a numpy array
`load_cifti`(filename[, vol, mask, rmtmp])	Load a cifti file into a numpy array
`load_nifti`(datafile[, mask, vol])	Load a nifti file into a numpy array
`load_pd`(filename)	Load a csv file into a pandas dataframe
`save`(data, filename[, example, mask, text, dtype])	Save a numpy array to a file
`save_ascii`(data, filename)	Save a numpy array to an ascii file
`save_cifti`(data, filename, example[, mask, vol, volatlas])	Save a cifti file from a numpy array
`save_nifti`(data, filename, examplenii, mask[, dtype])	Write output to nifti
`save_pd`(data, filename)	Save a pandas dataframe to a csv file
`vol2vec`(dat, mask[, verbose])	Vectorise a 3d image

Module Contents#

create_incremental_backup(filepath)#

Create an incremental backup of a file using the .bak{n} naming scheme.

If the file exists, a backup is created in the same directory with the following format:: original_name.bak{n}.original_extension

where {n} is incremented based on existing backups. If the file does not exist, None is returned.

create_mask(data_array, mask, verbose=False)#

Create a mask from a data array or a nifti file

Basic usage:

create_mask(data_array, mask, verbose)

Parameters:

data_array – numpy array containing the data to write out
mask – nifti image containing a mask for the image
verbose – verbose output

file_extension(filename)#

Determine the file extension of a file (e.g. .nii.gz)

Basic usage:

file_extension(filename)

Parameters:: filename – name of the file to check

file_stem(filename)#

Determine the file stem of a file (e.g. /path/to/file.nii.gz -> file)

Basic usage:

file_stem(filename)

Parameters:: filename – name of the file to check

file_type(filename)#

Determine the file type of a file

Basic usage:

file_type(filename)

Parameters:: filename – name of the file to check
Returns:: str: The file type (‘cifti’, ‘nifti’, ‘text’, or ‘binary’)
Raises:: ValueError if file type is unknown

load(filename, mask=None, text=False, vol=True)#

Load array from a file.

A beautiful waterfall of errors.

Basic usage:

load(filename, mask, text, vol)

Parameters:

filename – name of the file to load
mask – nifti image containing a mask for the image
text – whether to write out a text file
vol – whether to load the image as a volume

load_ascii(filename)#

Load an ascii file into a numpy array

Basic usage:

load_ascii(filename)

Parameters:: filename – name of the file to load

load_cifti(filename, vol=False, mask=None, rmtmp=True)#

Load a cifti file into a numpy array

Basic usage:

load_cifti(filename, vol, mask, rmtmp)

Parameters:

filename – name of the file to load
vol – whether to load the image as a volume
mask – nifti image containing a mask for the image
rmtmp – whether to remove temporary files

load_nifti(datafile, mask=None, vol=False)#

Load a nifti file into a numpy array

Basic usage:

load_nifti(datafile, mask, vol, verbose)

Parameters:

datafile – name of the file to load
mask – nifti image containing a mask for the image
vol – whether to load the image as a volume
verbose – verbose output

load_pd(filename)#

Load a csv file into a pandas dataframe

Basic usage:

load_pd(filename)

Parameters:: filename – name of the file to load

save(data, filename, example=None, mask=None, text=False, dtype=None)#

Save a numpy array to a file

Basic usage:

save(data, filename, example, mask, text, dtype)

Parameters:

data – numpy array containing the data to write out
filename – where to store it
example – example file to copy the geometry from
mask – nifti image containing a mask for the image
text – whether to write out a text file
dtype – data type for the output image (if different from the image)

save_ascii(data, filename)#

Save a numpy array to an ascii file

Basic usage:

save_ascii(data, filename)

Parameters:

data – numpy array containing the data to write out
filename – where to store it

save_cifti(data, filename, example, mask=None, vol=True, volatlas=None)#

Save a cifti file from a numpy array

Basic usage:

save_cifti(data, filename, example, mask, vol, volatlas)

Parameters:

data – numpy array containing the data to write out
filename – where to store it
example – example file to copy the geometry from
mask – nifti image containing a mask for the image
vol – whether to load the image as a volume
volatlas – atlas to use for the volume

save_nifti(data, filename, examplenii, mask, dtype=None)#

Write output to nifti

Basic usage:

save_nifti(data, filename mask, dtype)

Parameters:

data – numpy array containing the data to write out
filename – where to store it
examplenii – nifti to copy the geometry and data type from
dtype – data type for the output image (if different from the image)

Mask:

nifti image containing a mask for the image

save_pd(data, filename)#

Save a pandas dataframe to a csv file

Basic usage:

save_pd(data, filename)

Parameters:

data – pandas dataframe containing the data to write out
filename – where to store it

vol2vec(dat, mask, verbose=False)#

Vectorise a 3d image

Basic usage:

vol2vec(dat, mask, verbose)

Parameters:

dat – numpy array containing the data to write out
mask – nifti image containing a mask for the image
verbose – verbose output

CIFTI_MAPPINGS = ('dconn', 'dtseries', 'pconn', 'ptseries', 'dscalar', 'dlabel', 'pscalar', 'pdconn', 'dpconn',...#

CIFTI_VOL_ATLAS = 'Atlas_ROIs.2.nii.gz'#

path = b'.'#

path#