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stringlengths 75
19.8k
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stringclasses 1
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stringlengths 75
19.8k
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17.3k
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stringlengths 40
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242
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|---|---|---|---|---|---|---|---|---|---|---|---|
237,200
|
ANTsX/ANTsPy
|
ants/core/ants_image.py
|
ANTsImage.to_file
|
def to_file(self, filename):
"""
Write the ANTsImage to file
Args
----
filename : string
filepath to which the image will be written
"""
filename = os.path.expanduser(filename)
libfn = utils.get_lib_fn('toFile%s'%self._libsuffix)
libfn(self.pointer, filename)
|
python
|
def to_file(self, filename):
"""
Write the ANTsImage to file
Args
----
filename : string
filepath to which the image will be written
"""
filename = os.path.expanduser(filename)
libfn = utils.get_lib_fn('toFile%s'%self._libsuffix)
libfn(self.pointer, filename)
|
[
"def",
"to_file",
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"_libsuffix",
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"libfn",
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] |
Write the ANTsImage to file
Args
----
filename : string
filepath to which the image will be written
|
[
"Write",
"the",
"ANTsImage",
"to",
"file"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_image.py#L347-L358
|
237,201
|
ANTsX/ANTsPy
|
ants/core/ants_image.py
|
ANTsImage.apply
|
def apply(self, fn):
"""
Apply an arbitrary function to ANTsImage.
Args
----
fn : python function or lambda
function to apply to ENTIRE image at once
Returns
-------
ANTsImage
image with function applied to it
"""
this_array = self.numpy()
new_array = fn(this_array)
return self.new_image_like(new_array)
|
python
|
def apply(self, fn):
"""
Apply an arbitrary function to ANTsImage.
Args
----
fn : python function or lambda
function to apply to ENTIRE image at once
Returns
-------
ANTsImage
image with function applied to it
"""
this_array = self.numpy()
new_array = fn(this_array)
return self.new_image_like(new_array)
|
[
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"this_array",
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"return",
"self",
".",
"new_image_like",
"(",
"new_array",
")"
] |
Apply an arbitrary function to ANTsImage.
Args
----
fn : python function or lambda
function to apply to ENTIRE image at once
Returns
-------
ANTsImage
image with function applied to it
|
[
"Apply",
"an",
"arbitrary",
"function",
"to",
"ANTsImage",
"."
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_image.py#L361-L377
|
237,202
|
ANTsX/ANTsPy
|
ants/core/ants_image.py
|
ANTsImage.sum
|
def sum(self, axis=None, keepdims=False):
""" Return sum along specified axis """
return self.numpy().sum(axis=axis, keepdims=keepdims)
|
python
|
def sum(self, axis=None, keepdims=False):
""" Return sum along specified axis """
return self.numpy().sum(axis=axis, keepdims=keepdims)
|
[
"def",
"sum",
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"(",
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")"
] |
Return sum along specified axis
|
[
"Return",
"sum",
"along",
"specified",
"axis"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_image.py#L395-L397
|
237,203
|
ANTsX/ANTsPy
|
ants/core/ants_image.py
|
ANTsImage.range
|
def range(self, axis=None):
""" Return range tuple along specified axis """
return (self.min(axis=axis), self.max(axis=axis))
|
python
|
def range(self, axis=None):
""" Return range tuple along specified axis """
return (self.min(axis=axis), self.max(axis=axis))
|
[
"def",
"range",
"(",
"self",
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")",
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".",
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")",
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] |
Return range tuple along specified axis
|
[
"Return",
"range",
"tuple",
"along",
"specified",
"axis"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_image.py#L404-L406
|
237,204
|
ANTsX/ANTsPy
|
ants/core/ants_image.py
|
ANTsImage.argrange
|
def argrange(self, axis=None):
""" Return argrange along specified axis """
amin = self.argmin(axis=axis)
amax = self.argmax(axis=axis)
if axis is None:
return (amin, amax)
else:
return np.stack([amin, amax]).T
|
python
|
def argrange(self, axis=None):
""" Return argrange along specified axis """
amin = self.argmin(axis=axis)
amax = self.argmax(axis=axis)
if axis is None:
return (amin, amax)
else:
return np.stack([amin, amax]).T
|
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Return argrange along specified axis
|
[
"Return",
"argrange",
"along",
"specified",
"axis"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_image.py#L413-L420
|
237,205
|
ANTsX/ANTsPy
|
ants/core/ants_image.py
|
ANTsImage.unique
|
def unique(self, sort=False):
""" Return unique set of values in image """
unique_vals = np.unique(self.numpy())
if sort:
unique_vals = np.sort(unique_vals)
return unique_vals
|
python
|
def unique(self, sort=False):
""" Return unique set of values in image """
unique_vals = np.unique(self.numpy())
if sort:
unique_vals = np.sort(unique_vals)
return unique_vals
|
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"=",
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"unique_vals"
] |
Return unique set of values in image
|
[
"Return",
"unique",
"set",
"of",
"values",
"in",
"image"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_image.py#L427-L432
|
237,206
|
ANTsX/ANTsPy
|
ants/core/ants_image.py
|
LabelImage.uniquekeys
|
def uniquekeys(self, metakey=None):
"""
Get keys for a given metakey
"""
if metakey is None:
return self._uniquekeys
else:
if metakey not in self.metakeys():
raise ValueError('metakey %s does not exist' % metakey)
return self._uniquekeys[metakey]
|
python
|
def uniquekeys(self, metakey=None):
"""
Get keys for a given metakey
"""
if metakey is None:
return self._uniquekeys
else:
if metakey not in self.metakeys():
raise ValueError('metakey %s does not exist' % metakey)
return self._uniquekeys[metakey]
|
[
"def",
"uniquekeys",
"(",
"self",
",",
"metakey",
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"None",
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"_uniquekeys",
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] |
Get keys for a given metakey
|
[
"Get",
"keys",
"for",
"a",
"given",
"metakey"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_image.py#L731-L740
|
237,207
|
ANTsX/ANTsPy
|
ants/utils/label_clusters.py
|
label_clusters
|
def label_clusters(image, min_cluster_size=50, min_thresh=1e-6, max_thresh=1, fully_connected=False):
"""
This will give a unique ID to each connected
component 1 through N of size > min_cluster_size
ANTsR function: `labelClusters`
Arguments
---------
image : ANTsImage
input image e.g. a statistical map
min_cluster_size : integer
throw away clusters smaller than this value
min_thresh : scalar
threshold to a statistical map
max_thresh : scalar
threshold to a statistical map
fully_connected : boolean
boolean sets neighborhood connectivity pattern
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> image = ants.image_read( ants.get_ants_data('r16') )
>>> timageFully = ants.label_clusters( image, 10, 128, 150, True )
>>> timageFace = ants.label_clusters( image, 10, 128, 150, False )
"""
dim = image.dimension
clust = threshold_image(image, min_thresh, max_thresh)
temp = int(fully_connected)
args = [dim, clust, clust, min_cluster_size, temp]
processed_args = _int_antsProcessArguments(args)
libfn = utils.get_lib_fn('LabelClustersUniquely')
libfn(processed_args)
return clust
|
python
|
def label_clusters(image, min_cluster_size=50, min_thresh=1e-6, max_thresh=1, fully_connected=False):
"""
This will give a unique ID to each connected
component 1 through N of size > min_cluster_size
ANTsR function: `labelClusters`
Arguments
---------
image : ANTsImage
input image e.g. a statistical map
min_cluster_size : integer
throw away clusters smaller than this value
min_thresh : scalar
threshold to a statistical map
max_thresh : scalar
threshold to a statistical map
fully_connected : boolean
boolean sets neighborhood connectivity pattern
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> image = ants.image_read( ants.get_ants_data('r16') )
>>> timageFully = ants.label_clusters( image, 10, 128, 150, True )
>>> timageFace = ants.label_clusters( image, 10, 128, 150, False )
"""
dim = image.dimension
clust = threshold_image(image, min_thresh, max_thresh)
temp = int(fully_connected)
args = [dim, clust, clust, min_cluster_size, temp]
processed_args = _int_antsProcessArguments(args)
libfn = utils.get_lib_fn('LabelClustersUniquely')
libfn(processed_args)
return clust
|
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"'LabelClustersUniquely'",
")",
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"return",
"clust"
] |
This will give a unique ID to each connected
component 1 through N of size > min_cluster_size
ANTsR function: `labelClusters`
Arguments
---------
image : ANTsImage
input image e.g. a statistical map
min_cluster_size : integer
throw away clusters smaller than this value
min_thresh : scalar
threshold to a statistical map
max_thresh : scalar
threshold to a statistical map
fully_connected : boolean
boolean sets neighborhood connectivity pattern
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> image = ants.image_read( ants.get_ants_data('r16') )
>>> timageFully = ants.label_clusters( image, 10, 128, 150, True )
>>> timageFace = ants.label_clusters( image, 10, 128, 150, False )
|
[
"This",
"will",
"give",
"a",
"unique",
"ID",
"to",
"each",
"connected",
"component",
"1",
"through",
"N",
"of",
"size",
">",
"min_cluster_size"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/utils/label_clusters.py#L11-L53
|
237,208
|
ANTsX/ANTsPy
|
ants/registration/make_points_image.py
|
make_points_image
|
def make_points_image(pts, mask, radius=5):
"""
Create label image from physical space points
Creates spherical points in the coordinate space of the target image based
on the n-dimensional matrix of points that the user supplies. The image
defines the dimensionality of the data so if the input image is 3D then
the input points should be 2D or 3D.
ANTsR function: `makePointsImage`
Arguments
---------
pts : numpy.ndarray
input powers points
mask : ANTsImage
mask defining target space
radius : integer
radius for the points
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> import pandas as pd
>>> mni = ants.image_read(ants.get_data('mni')).get_mask()
>>> powers_pts = pd.read_csv(ants.get_data('powers_mni_itk'))
>>> powers_labels = ants.make_points_image(powers_pts.iloc[:,:3].values, mni, radius=3)
"""
powers_lblimg = mask * 0
npts = len(pts)
dim = mask.dimension
if pts.shape[1] != dim:
raise ValueError('points dimensionality should match that of images')
for r in range(npts):
pt = pts[r,:]
idx = tio.transform_physical_point_to_index(mask, pt.tolist() ).astype(int)
in_image = (np.prod(idx <= mask.shape)==1) and (len(np.where(idx<0)[0])==0)
if ( in_image == True ):
if (dim == 3):
powers_lblimg[idx[0],idx[1],idx[2]] = r + 1
elif (dim == 2):
powers_lblimg[idx[0],idx[1]] = r + 1
return utils.morphology( powers_lblimg, 'dilate', radius, 'grayscale' )
|
python
|
def make_points_image(pts, mask, radius=5):
"""
Create label image from physical space points
Creates spherical points in the coordinate space of the target image based
on the n-dimensional matrix of points that the user supplies. The image
defines the dimensionality of the data so if the input image is 3D then
the input points should be 2D or 3D.
ANTsR function: `makePointsImage`
Arguments
---------
pts : numpy.ndarray
input powers points
mask : ANTsImage
mask defining target space
radius : integer
radius for the points
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> import pandas as pd
>>> mni = ants.image_read(ants.get_data('mni')).get_mask()
>>> powers_pts = pd.read_csv(ants.get_data('powers_mni_itk'))
>>> powers_labels = ants.make_points_image(powers_pts.iloc[:,:3].values, mni, radius=3)
"""
powers_lblimg = mask * 0
npts = len(pts)
dim = mask.dimension
if pts.shape[1] != dim:
raise ValueError('points dimensionality should match that of images')
for r in range(npts):
pt = pts[r,:]
idx = tio.transform_physical_point_to_index(mask, pt.tolist() ).astype(int)
in_image = (np.prod(idx <= mask.shape)==1) and (len(np.where(idx<0)[0])==0)
if ( in_image == True ):
if (dim == 3):
powers_lblimg[idx[0],idx[1],idx[2]] = r + 1
elif (dim == 2):
powers_lblimg[idx[0],idx[1]] = r + 1
return utils.morphology( powers_lblimg, 'dilate', radius, 'grayscale' )
|
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"(",
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",",
"'dilate'",
",",
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",",
"'grayscale'",
")"
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Create label image from physical space points
Creates spherical points in the coordinate space of the target image based
on the n-dimensional matrix of points that the user supplies. The image
defines the dimensionality of the data so if the input image is 3D then
the input points should be 2D or 3D.
ANTsR function: `makePointsImage`
Arguments
---------
pts : numpy.ndarray
input powers points
mask : ANTsImage
mask defining target space
radius : integer
radius for the points
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> import pandas as pd
>>> mni = ants.image_read(ants.get_data('mni')).get_mask()
>>> powers_pts = pd.read_csv(ants.get_data('powers_mni_itk'))
>>> powers_labels = ants.make_points_image(powers_pts.iloc[:,:3].values, mni, radius=3)
|
[
"Create",
"label",
"image",
"from",
"physical",
"space",
"points"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/registration/make_points_image.py#L11-L60
|
237,209
|
ANTsX/ANTsPy
|
ants/utils/weingarten_image_curvature.py
|
weingarten_image_curvature
|
def weingarten_image_curvature(image, sigma=1.0, opt='mean'):
"""
Uses the weingarten map to estimate image mean or gaussian curvature
ANTsR function: `weingartenImageCurvature`
Arguments
---------
image : ANTsImage
image from which curvature is calculated
sigma : scalar
smoothing parameter
opt : string
mean by default, otherwise `gaussian` or `characterize`
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> image = ants.image_read(ants.get_ants_data('mni')).resample_image((3,3,3))
>>> imagecurv = ants.weingarten_image_curvature(image)
"""
if image.dimension not in {2,3}:
raise ValueError('image must be 2D or 3D')
if image.dimension == 2:
d = image.shape
temp = np.zeros(list(d)+[10])
for k in range(1,7):
voxvals = image[:d[0],:d[1]]
temp[:d[0],:d[1],k] = voxvals
temp = core.from_numpy(temp)
myspc = image.spacing
myspc = list(myspc) + [min(myspc)]
temp.set_spacing(myspc)
temp = temp.clone('float')
else:
temp = image.clone('float')
optnum = 0
if opt == 'gaussian':
optnum = 6
if opt == 'characterize':
optnum = 5
libfn = utils.get_lib_fn('weingartenImageCurvature')
mykout = libfn(temp.pointer, sigma, optnum)
mykout = iio.ANTsImage(pixeltype=image.pixeltype, dimension=3,
components=image.components, pointer=mykout)
if image.dimension == 3:
return mykout
elif image.dimension == 2:
subarr = core.from_numpy(mykout.numpy()[:,:,4])
return core.copy_image_info(image, subarr)
|
python
|
def weingarten_image_curvature(image, sigma=1.0, opt='mean'):
"""
Uses the weingarten map to estimate image mean or gaussian curvature
ANTsR function: `weingartenImageCurvature`
Arguments
---------
image : ANTsImage
image from which curvature is calculated
sigma : scalar
smoothing parameter
opt : string
mean by default, otherwise `gaussian` or `characterize`
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> image = ants.image_read(ants.get_ants_data('mni')).resample_image((3,3,3))
>>> imagecurv = ants.weingarten_image_curvature(image)
"""
if image.dimension not in {2,3}:
raise ValueError('image must be 2D or 3D')
if image.dimension == 2:
d = image.shape
temp = np.zeros(list(d)+[10])
for k in range(1,7):
voxvals = image[:d[0],:d[1]]
temp[:d[0],:d[1],k] = voxvals
temp = core.from_numpy(temp)
myspc = image.spacing
myspc = list(myspc) + [min(myspc)]
temp.set_spacing(myspc)
temp = temp.clone('float')
else:
temp = image.clone('float')
optnum = 0
if opt == 'gaussian':
optnum = 6
if opt == 'characterize':
optnum = 5
libfn = utils.get_lib_fn('weingartenImageCurvature')
mykout = libfn(temp.pointer, sigma, optnum)
mykout = iio.ANTsImage(pixeltype=image.pixeltype, dimension=3,
components=image.components, pointer=mykout)
if image.dimension == 3:
return mykout
elif image.dimension == 2:
subarr = core.from_numpy(mykout.numpy()[:,:,4])
return core.copy_image_info(image, subarr)
|
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".",
"copy_image_info",
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",",
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")"
] |
Uses the weingarten map to estimate image mean or gaussian curvature
ANTsR function: `weingartenImageCurvature`
Arguments
---------
image : ANTsImage
image from which curvature is calculated
sigma : scalar
smoothing parameter
opt : string
mean by default, otherwise `gaussian` or `characterize`
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> image = ants.image_read(ants.get_ants_data('mni')).resample_image((3,3,3))
>>> imagecurv = ants.weingarten_image_curvature(image)
|
[
"Uses",
"the",
"weingarten",
"map",
"to",
"estimate",
"image",
"mean",
"or",
"gaussian",
"curvature"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/utils/weingarten_image_curvature.py#L11-L69
|
237,210
|
ANTsX/ANTsPy
|
ants/core/ants_image_io.py
|
from_numpy
|
def from_numpy(data, origin=None, spacing=None, direction=None, has_components=False, is_rgb=False):
"""
Create an ANTsImage object from a numpy array
ANTsR function: `as.antsImage`
Arguments
---------
data : ndarray
image data array
origin : tuple/list
image origin
spacing : tuple/list
image spacing
direction : list/ndarray
image direction
has_components : boolean
whether the image has components
Returns
-------
ANTsImage
image with given data and any given information
"""
data = data.astype('float32') if data.dtype.name == 'float64' else data
img = _from_numpy(data.T.copy(), origin, spacing, direction, has_components, is_rgb)
return img
|
python
|
def from_numpy(data, origin=None, spacing=None, direction=None, has_components=False, is_rgb=False):
"""
Create an ANTsImage object from a numpy array
ANTsR function: `as.antsImage`
Arguments
---------
data : ndarray
image data array
origin : tuple/list
image origin
spacing : tuple/list
image spacing
direction : list/ndarray
image direction
has_components : boolean
whether the image has components
Returns
-------
ANTsImage
image with given data and any given information
"""
data = data.astype('float32') if data.dtype.name == 'float64' else data
img = _from_numpy(data.T.copy(), origin, spacing, direction, has_components, is_rgb)
return img
|
[
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"(",
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"=",
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",",
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",",
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",",
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",",
"has_components",
",",
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] |
Create an ANTsImage object from a numpy array
ANTsR function: `as.antsImage`
Arguments
---------
data : ndarray
image data array
origin : tuple/list
image origin
spacing : tuple/list
image spacing
direction : list/ndarray
image direction
has_components : boolean
whether the image has components
Returns
-------
ANTsImage
image with given data and any given information
|
[
"Create",
"an",
"ANTsImage",
"object",
"from",
"a",
"numpy",
"array"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_image_io.py#L76-L106
|
237,211
|
ANTsX/ANTsPy
|
ants/core/ants_image_io.py
|
_from_numpy
|
def _from_numpy(data, origin=None, spacing=None, direction=None, has_components=False, is_rgb=False):
"""
Internal function for creating an ANTsImage
"""
if is_rgb: has_components = True
ndim = data.ndim
if has_components:
ndim -= 1
dtype = data.dtype.name
ptype = _npy_to_itk_map[dtype]
data = np.array(data)
if origin is None: origin = tuple([0.]*ndim)
if spacing is None: spacing = tuple([1.]*ndim)
if direction is None: direction = np.eye(ndim)
libfn = utils.get_lib_fn('fromNumpy%s%i' % (_ntype_type_map[dtype], ndim))
if not has_components:
itk_image = libfn(data, data.shape[::-1])
ants_image = iio.ANTsImage(pixeltype=ptype, dimension=ndim, components=1, pointer=itk_image)
ants_image.set_origin(origin)
ants_image.set_spacing(spacing)
ants_image.set_direction(direction)
ants_image._ndarr = data
else:
arrays = [data[i,...].copy() for i in range(data.shape[0])]
data_shape = arrays[0].shape
ants_images = []
for i in range(len(arrays)):
tmp_ptr = libfn(arrays[i], data_shape[::-1])
tmp_img = iio.ANTsImage(pixeltype=ptype,
dimension=ndim,
components=1,
pointer=tmp_ptr)
tmp_img.set_origin(origin)
tmp_img.set_spacing(spacing)
tmp_img.set_direction(direction)
tmp_img._ndarr = arrays[i]
ants_images.append(tmp_img)
ants_image = utils.merge_channels(ants_images)
if is_rgb: ants_image = ants_image.vector_to_rgb()
return ants_image
|
python
|
def _from_numpy(data, origin=None, spacing=None, direction=None, has_components=False, is_rgb=False):
"""
Internal function for creating an ANTsImage
"""
if is_rgb: has_components = True
ndim = data.ndim
if has_components:
ndim -= 1
dtype = data.dtype.name
ptype = _npy_to_itk_map[dtype]
data = np.array(data)
if origin is None: origin = tuple([0.]*ndim)
if spacing is None: spacing = tuple([1.]*ndim)
if direction is None: direction = np.eye(ndim)
libfn = utils.get_lib_fn('fromNumpy%s%i' % (_ntype_type_map[dtype], ndim))
if not has_components:
itk_image = libfn(data, data.shape[::-1])
ants_image = iio.ANTsImage(pixeltype=ptype, dimension=ndim, components=1, pointer=itk_image)
ants_image.set_origin(origin)
ants_image.set_spacing(spacing)
ants_image.set_direction(direction)
ants_image._ndarr = data
else:
arrays = [data[i,...].copy() for i in range(data.shape[0])]
data_shape = arrays[0].shape
ants_images = []
for i in range(len(arrays)):
tmp_ptr = libfn(arrays[i], data_shape[::-1])
tmp_img = iio.ANTsImage(pixeltype=ptype,
dimension=ndim,
components=1,
pointer=tmp_ptr)
tmp_img.set_origin(origin)
tmp_img.set_spacing(spacing)
tmp_img.set_direction(direction)
tmp_img._ndarr = arrays[i]
ants_images.append(tmp_img)
ants_image = utils.merge_channels(ants_images)
if is_rgb: ants_image = ants_image.vector_to_rgb()
return ants_image
|
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] |
Internal function for creating an ANTsImage
|
[
"Internal",
"function",
"for",
"creating",
"an",
"ANTsImage"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_image_io.py#L109-L152
|
237,212
|
ANTsX/ANTsPy
|
ants/core/ants_image_io.py
|
make_image
|
def make_image(imagesize, voxval=0, spacing=None, origin=None, direction=None, has_components=False, pixeltype='float'):
"""
Make an image with given size and voxel value or given a mask and vector
ANTsR function: `makeImage`
Arguments
---------
shape : tuple/ANTsImage
input image size or mask
voxval : scalar
input image value or vector, size of mask
spacing : tuple/list
image spatial resolution
origin : tuple/list
image spatial origin
direction : list/ndarray
direction matrix to convert from index to physical space
components : boolean
whether there are components per pixel or not
pixeltype : float
data type of image values
Returns
-------
ANTsImage
"""
if isinstance(imagesize, iio.ANTsImage):
img = imagesize.clone()
sel = imagesize > 0
if voxval.ndim > 1:
voxval = voxval.flatten()
if (len(voxval) == int((sel>0).sum())) or (len(voxval) == 0):
img[sel] = voxval
else:
raise ValueError('Num given voxels %i not same as num positive values %i in `imagesize`' % (len(voxval), int((sel>0).sum())))
return img
else:
if isinstance(voxval, (tuple,list,np.ndarray)):
array = np.asarray(voxval).astype('float32').reshape(imagesize)
else:
array = np.full(imagesize,voxval,dtype='float32')
image = from_numpy(array, origin=origin, spacing=spacing,
direction=direction, has_components=has_components)
return image.clone(pixeltype)
|
python
|
def make_image(imagesize, voxval=0, spacing=None, origin=None, direction=None, has_components=False, pixeltype='float'):
"""
Make an image with given size and voxel value or given a mask and vector
ANTsR function: `makeImage`
Arguments
---------
shape : tuple/ANTsImage
input image size or mask
voxval : scalar
input image value or vector, size of mask
spacing : tuple/list
image spatial resolution
origin : tuple/list
image spatial origin
direction : list/ndarray
direction matrix to convert from index to physical space
components : boolean
whether there are components per pixel or not
pixeltype : float
data type of image values
Returns
-------
ANTsImage
"""
if isinstance(imagesize, iio.ANTsImage):
img = imagesize.clone()
sel = imagesize > 0
if voxval.ndim > 1:
voxval = voxval.flatten()
if (len(voxval) == int((sel>0).sum())) or (len(voxval) == 0):
img[sel] = voxval
else:
raise ValueError('Num given voxels %i not same as num positive values %i in `imagesize`' % (len(voxval), int((sel>0).sum())))
return img
else:
if isinstance(voxval, (tuple,list,np.ndarray)):
array = np.asarray(voxval).astype('float32').reshape(imagesize)
else:
array = np.full(imagesize,voxval,dtype='float32')
image = from_numpy(array, origin=origin, spacing=spacing,
direction=direction, has_components=has_components)
return image.clone(pixeltype)
|
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"full",
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"imagesize",
",",
"voxval",
",",
"dtype",
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",",
"has_components",
"=",
"has_components",
")",
"return",
"image",
".",
"clone",
"(",
"pixeltype",
")"
] |
Make an image with given size and voxel value or given a mask and vector
ANTsR function: `makeImage`
Arguments
---------
shape : tuple/ANTsImage
input image size or mask
voxval : scalar
input image value or vector, size of mask
spacing : tuple/list
image spatial resolution
origin : tuple/list
image spatial origin
direction : list/ndarray
direction matrix to convert from index to physical space
components : boolean
whether there are components per pixel or not
pixeltype : float
data type of image values
Returns
-------
ANTsImage
|
[
"Make",
"an",
"image",
"with",
"given",
"size",
"and",
"voxel",
"value",
"or",
"given",
"a",
"mask",
"and",
"vector"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_image_io.py#L155-L205
|
237,213
|
ANTsX/ANTsPy
|
ants/core/ants_image_io.py
|
matrix_to_images
|
def matrix_to_images(data_matrix, mask):
"""
Unmasks rows of a matrix and writes as images
ANTsR function: `matrixToImages`
Arguments
---------
data_matrix : numpy.ndarray
each row corresponds to an image
array should have number of columns equal to non-zero voxels in the mask
mask : ANTsImage
image containing a binary mask. Rows of the matrix are
unmasked and written as images. The mask defines the output image space
Returns
-------
list of ANTsImage types
"""
if data_matrix.ndim > 2:
data_matrix = data_matrix.reshape(data_matrix.shape[0], -1)
numimages = len(data_matrix)
numVoxelsInMatrix = data_matrix.shape[1]
numVoxelsInMask = (mask >= 0.5).sum()
if numVoxelsInMask != numVoxelsInMatrix:
raise ValueError('Num masked voxels %i must match data matrix %i' % (numVoxelsInMask, numVoxelsInMatrix))
imagelist = []
for i in range(numimages):
img = mask.clone()
img[mask >= 0.5] = data_matrix[i,:]
imagelist.append(img)
return imagelist
|
python
|
def matrix_to_images(data_matrix, mask):
"""
Unmasks rows of a matrix and writes as images
ANTsR function: `matrixToImages`
Arguments
---------
data_matrix : numpy.ndarray
each row corresponds to an image
array should have number of columns equal to non-zero voxels in the mask
mask : ANTsImage
image containing a binary mask. Rows of the matrix are
unmasked and written as images. The mask defines the output image space
Returns
-------
list of ANTsImage types
"""
if data_matrix.ndim > 2:
data_matrix = data_matrix.reshape(data_matrix.shape[0], -1)
numimages = len(data_matrix)
numVoxelsInMatrix = data_matrix.shape[1]
numVoxelsInMask = (mask >= 0.5).sum()
if numVoxelsInMask != numVoxelsInMatrix:
raise ValueError('Num masked voxels %i must match data matrix %i' % (numVoxelsInMask, numVoxelsInMatrix))
imagelist = []
for i in range(numimages):
img = mask.clone()
img[mask >= 0.5] = data_matrix[i,:]
imagelist.append(img)
return imagelist
|
[
"def",
"matrix_to_images",
"(",
"data_matrix",
",",
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")",
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".",
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"data_matrix",
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",",
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"imagelist",
".",
"append",
"(",
"img",
")",
"return",
"imagelist"
] |
Unmasks rows of a matrix and writes as images
ANTsR function: `matrixToImages`
Arguments
---------
data_matrix : numpy.ndarray
each row corresponds to an image
array should have number of columns equal to non-zero voxels in the mask
mask : ANTsImage
image containing a binary mask. Rows of the matrix are
unmasked and written as images. The mask defines the output image space
Returns
-------
list of ANTsImage types
|
[
"Unmasks",
"rows",
"of",
"a",
"matrix",
"and",
"writes",
"as",
"images"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_image_io.py#L208-L243
|
237,214
|
ANTsX/ANTsPy
|
ants/core/ants_image_io.py
|
images_to_matrix
|
def images_to_matrix(image_list, mask=None, sigma=None, epsilon=0.5 ):
"""
Read images into rows of a matrix, given a mask - much faster for
large datasets as it is based on C++ implementations.
ANTsR function: `imagesToMatrix`
Arguments
---------
image_list : list of ANTsImage types
images to convert to ndarray
mask : ANTsImage (optional)
image containing binary mask. voxels in the mask are placed in the matrix
sigma : scaler (optional)
smoothing factor
epsilon : scalar
threshold for mask
Returns
-------
ndarray
array with a row for each image
shape = (N_IMAGES, N_VOXELS)
Example
-------
>>> import ants
>>> img = ants.image_read(ants.get_ants_data('r16'))
>>> img2 = ants.image_read(ants.get_ants_data('r16'))
>>> img3 = ants.image_read(ants.get_ants_data('r16'))
>>> mat = ants.image_list_to_matrix([img,img2,img3])
"""
def listfunc(x):
if np.sum(np.array(x.shape) - np.array(mask.shape)) != 0:
x = reg.resample_image_to_target(x, mask, 2)
return x[mask]
if mask is None:
mask = utils.get_mask(image_list[0])
num_images = len(image_list)
mask_arr = mask.numpy() >= epsilon
num_voxels = np.sum(mask_arr)
data_matrix = np.empty((num_images, num_voxels))
do_smooth = sigma is not None
for i,img in enumerate(image_list):
if do_smooth:
data_matrix[i, :] = listfunc(utils.smooth_image(img, sigma, sigma_in_physical_coordinates=True))
else:
data_matrix[i,:] = listfunc(img)
return data_matrix
|
python
|
def images_to_matrix(image_list, mask=None, sigma=None, epsilon=0.5 ):
"""
Read images into rows of a matrix, given a mask - much faster for
large datasets as it is based on C++ implementations.
ANTsR function: `imagesToMatrix`
Arguments
---------
image_list : list of ANTsImage types
images to convert to ndarray
mask : ANTsImage (optional)
image containing binary mask. voxels in the mask are placed in the matrix
sigma : scaler (optional)
smoothing factor
epsilon : scalar
threshold for mask
Returns
-------
ndarray
array with a row for each image
shape = (N_IMAGES, N_VOXELS)
Example
-------
>>> import ants
>>> img = ants.image_read(ants.get_ants_data('r16'))
>>> img2 = ants.image_read(ants.get_ants_data('r16'))
>>> img3 = ants.image_read(ants.get_ants_data('r16'))
>>> mat = ants.image_list_to_matrix([img,img2,img3])
"""
def listfunc(x):
if np.sum(np.array(x.shape) - np.array(mask.shape)) != 0:
x = reg.resample_image_to_target(x, mask, 2)
return x[mask]
if mask is None:
mask = utils.get_mask(image_list[0])
num_images = len(image_list)
mask_arr = mask.numpy() >= epsilon
num_voxels = np.sum(mask_arr)
data_matrix = np.empty((num_images, num_voxels))
do_smooth = sigma is not None
for i,img in enumerate(image_list):
if do_smooth:
data_matrix[i, :] = listfunc(utils.smooth_image(img, sigma, sigma_in_physical_coordinates=True))
else:
data_matrix[i,:] = listfunc(img)
return data_matrix
|
[
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"=",
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",",
"sigma",
"=",
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",",
"epsilon",
"=",
"0.5",
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"def",
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")",
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"if",
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"=",
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"(",
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",",
"num_voxels",
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"=",
"sigma",
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"i",
",",
"img",
"in",
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"(",
"image_list",
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":",
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"do_smooth",
":",
"data_matrix",
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",",
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"=",
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"smooth_image",
"(",
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",",
"sigma_in_physical_coordinates",
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"True",
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")",
"else",
":",
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"[",
"i",
",",
":",
"]",
"=",
"listfunc",
"(",
"img",
")",
"return",
"data_matrix"
] |
Read images into rows of a matrix, given a mask - much faster for
large datasets as it is based on C++ implementations.
ANTsR function: `imagesToMatrix`
Arguments
---------
image_list : list of ANTsImage types
images to convert to ndarray
mask : ANTsImage (optional)
image containing binary mask. voxels in the mask are placed in the matrix
sigma : scaler (optional)
smoothing factor
epsilon : scalar
threshold for mask
Returns
-------
ndarray
array with a row for each image
shape = (N_IMAGES, N_VOXELS)
Example
-------
>>> import ants
>>> img = ants.image_read(ants.get_ants_data('r16'))
>>> img2 = ants.image_read(ants.get_ants_data('r16'))
>>> img3 = ants.image_read(ants.get_ants_data('r16'))
>>> mat = ants.image_list_to_matrix([img,img2,img3])
|
[
"Read",
"images",
"into",
"rows",
"of",
"a",
"matrix",
"given",
"a",
"mask",
"-",
"much",
"faster",
"for",
"large",
"datasets",
"as",
"it",
"is",
"based",
"on",
"C",
"++",
"implementations",
"."
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_image_io.py#L247-L301
|
237,215
|
ANTsX/ANTsPy
|
ants/core/ants_image_io.py
|
timeseries_to_matrix
|
def timeseries_to_matrix( image, mask=None ):
"""
Convert a timeseries image into a matrix.
ANTsR function: `timeseries2matrix`
Arguments
---------
image : image whose slices we convert to a matrix. E.g. a 3D image of size
x by y by z will convert to a z by x*y sized matrix
mask : ANTsImage (optional)
image containing binary mask. voxels in the mask are placed in the matrix
Returns
-------
ndarray
array with a row for each image
shape = (N_IMAGES, N_VOXELS)
Example
-------
>>> import ants
>>> img = ants.make_image( (10,10,10,5 ) )
>>> mat = ants.timeseries_to_matrix( img )
"""
temp = utils.ndimage_to_list( image )
if mask is None:
mask = temp[0]*0 + 1
return image_list_to_matrix( temp, mask )
|
python
|
def timeseries_to_matrix( image, mask=None ):
"""
Convert a timeseries image into a matrix.
ANTsR function: `timeseries2matrix`
Arguments
---------
image : image whose slices we convert to a matrix. E.g. a 3D image of size
x by y by z will convert to a z by x*y sized matrix
mask : ANTsImage (optional)
image containing binary mask. voxels in the mask are placed in the matrix
Returns
-------
ndarray
array with a row for each image
shape = (N_IMAGES, N_VOXELS)
Example
-------
>>> import ants
>>> img = ants.make_image( (10,10,10,5 ) )
>>> mat = ants.timeseries_to_matrix( img )
"""
temp = utils.ndimage_to_list( image )
if mask is None:
mask = temp[0]*0 + 1
return image_list_to_matrix( temp, mask )
|
[
"def",
"timeseries_to_matrix",
"(",
"image",
",",
"mask",
"=",
"None",
")",
":",
"temp",
"=",
"utils",
".",
"ndimage_to_list",
"(",
"image",
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":",
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"[",
"0",
"]",
"*",
"0",
"+",
"1",
"return",
"image_list_to_matrix",
"(",
"temp",
",",
"mask",
")"
] |
Convert a timeseries image into a matrix.
ANTsR function: `timeseries2matrix`
Arguments
---------
image : image whose slices we convert to a matrix. E.g. a 3D image of size
x by y by z will convert to a z by x*y sized matrix
mask : ANTsImage (optional)
image containing binary mask. voxels in the mask are placed in the matrix
Returns
-------
ndarray
array with a row for each image
shape = (N_IMAGES, N_VOXELS)
Example
-------
>>> import ants
>>> img = ants.make_image( (10,10,10,5 ) )
>>> mat = ants.timeseries_to_matrix( img )
|
[
"Convert",
"a",
"timeseries",
"image",
"into",
"a",
"matrix",
"."
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_image_io.py#L307-L336
|
237,216
|
ANTsX/ANTsPy
|
ants/core/ants_image_io.py
|
matrix_to_timeseries
|
def matrix_to_timeseries( image, matrix, mask=None ):
"""
converts a matrix to a ND image.
ANTsR function: `matrix2timeseries`
Arguments
---------
image: reference ND image
matrix: matrix to convert to image
mask: mask image defining voxels of interest
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> img = ants.make_image( (10,10,10,5 ) )
>>> mask = ants.ndimage_to_list( img )[0] * 0
>>> mask[ 4:8, 4:8, 4:8 ] = 1
>>> mat = ants.timeseries_to_matrix( img, mask = mask )
>>> img2 = ants.matrix_to_timeseries( img, mat, mask)
"""
if mask is None:
mask = temp[0]*0 + 1
temp = matrix_to_images( matrix, mask )
newImage = utils.list_to_ndimage( image, temp)
iio.copy_image_info( image, newImage)
return(newImage)
|
python
|
def matrix_to_timeseries( image, matrix, mask=None ):
"""
converts a matrix to a ND image.
ANTsR function: `matrix2timeseries`
Arguments
---------
image: reference ND image
matrix: matrix to convert to image
mask: mask image defining voxels of interest
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> img = ants.make_image( (10,10,10,5 ) )
>>> mask = ants.ndimage_to_list( img )[0] * 0
>>> mask[ 4:8, 4:8, 4:8 ] = 1
>>> mat = ants.timeseries_to_matrix( img, mask = mask )
>>> img2 = ants.matrix_to_timeseries( img, mat, mask)
"""
if mask is None:
mask = temp[0]*0 + 1
temp = matrix_to_images( matrix, mask )
newImage = utils.list_to_ndimage( image, temp)
iio.copy_image_info( image, newImage)
return(newImage)
|
[
"def",
"matrix_to_timeseries",
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",",
"matrix",
",",
"mask",
"=",
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"copy_image_info",
"(",
"image",
",",
"newImage",
")",
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"(",
"newImage",
")"
] |
converts a matrix to a ND image.
ANTsR function: `matrix2timeseries`
Arguments
---------
image: reference ND image
matrix: matrix to convert to image
mask: mask image defining voxels of interest
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> img = ants.make_image( (10,10,10,5 ) )
>>> mask = ants.ndimage_to_list( img )[0] * 0
>>> mask[ 4:8, 4:8, 4:8 ] = 1
>>> mat = ants.timeseries_to_matrix( img, mask = mask )
>>> img2 = ants.matrix_to_timeseries( img, mat, mask)
|
[
"converts",
"a",
"matrix",
"to",
"a",
"ND",
"image",
"."
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_image_io.py#L339-L374
|
237,217
|
ANTsX/ANTsPy
|
ants/core/ants_image_io.py
|
image_header_info
|
def image_header_info(filename):
"""
Read file info from image header
ANTsR function: `antsImageHeaderInfo`
Arguments
---------
filename : string
name of image file from which info will be read
Returns
-------
dict
"""
if not os.path.exists(filename):
raise Exception('filename does not exist')
libfn = utils.get_lib_fn('antsImageHeaderInfo')
retval = libfn(filename)
retval['dimensions'] = tuple(retval['dimensions'])
retval['origin'] = tuple([round(o,4) for o in retval['origin']])
retval['spacing'] = tuple([round(s,4) for s in retval['spacing']])
retval['direction'] = np.round(retval['direction'],4)
return retval
|
python
|
def image_header_info(filename):
"""
Read file info from image header
ANTsR function: `antsImageHeaderInfo`
Arguments
---------
filename : string
name of image file from which info will be read
Returns
-------
dict
"""
if not os.path.exists(filename):
raise Exception('filename does not exist')
libfn = utils.get_lib_fn('antsImageHeaderInfo')
retval = libfn(filename)
retval['dimensions'] = tuple(retval['dimensions'])
retval['origin'] = tuple([round(o,4) for o in retval['origin']])
retval['spacing'] = tuple([round(s,4) for s in retval['spacing']])
retval['direction'] = np.round(retval['direction'],4)
return retval
|
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")",
"return",
"retval"
] |
Read file info from image header
ANTsR function: `antsImageHeaderInfo`
Arguments
---------
filename : string
name of image file from which info will be read
Returns
-------
dict
|
[
"Read",
"file",
"info",
"from",
"image",
"header"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_image_io.py#L377-L401
|
237,218
|
ANTsX/ANTsPy
|
ants/core/ants_image_io.py
|
image_read
|
def image_read(filename, dimension=None, pixeltype='float', reorient=False):
"""
Read an ANTsImage from file
ANTsR function: `antsImageRead`
Arguments
---------
filename : string
Name of the file to read the image from.
dimension : int
Number of dimensions of the image read. This need not be the same as
the dimensions of the image in the file. Allowed values: 2, 3, 4.
If not provided, the dimension is obtained from the image file
pixeltype : string
C++ datatype to be used to represent the pixels read. This datatype
need not be the same as the datatype used in the file.
Options: unsigned char, unsigned int, float, double
reorient : boolean | string
if True, the image will be reoriented to RPI if it is 3D
if False, nothing will happen
if string, this should be the 3-letter orientation to which the
input image will reoriented if 3D.
if the image is 2D, this argument is ignored
Returns
-------
ANTsImage
"""
if filename.endswith('.npy'):
filename = os.path.expanduser(filename)
img_array = np.load(filename)
if os.path.exists(filename.replace('.npy', '.json')):
with open(filename.replace('.npy', '.json')) as json_data:
img_header = json.load(json_data)
ants_image = from_numpy(img_array,
origin=img_header.get('origin', None),
spacing=img_header.get('spacing', None),
direction=np.asarray(img_header.get('direction',None)),
has_components=img_header.get('components',1)>1)
else:
img_header = {}
ants_image = from_numpy(img_array)
else:
filename = os.path.expanduser(filename)
if not os.path.exists(filename):
raise ValueError('File %s does not exist!' % filename)
hinfo = image_header_info(filename)
ptype = hinfo['pixeltype']
pclass = hinfo['pixelclass']
ndim = hinfo['nDimensions']
ncomp = hinfo['nComponents']
is_rgb = True if pclass == 'rgb' else False
if dimension is not None:
ndim = dimension
# error handling on pixelclass
if pclass not in _supported_pclasses:
raise ValueError('Pixel class %s not supported!' % pclass)
# error handling on pixeltype
if ptype in _unsupported_ptypes:
ptype = _unsupported_ptype_map.get(ptype, 'unsupported')
if ptype == 'unsupported':
raise ValueError('Pixeltype %s not supported' % ptype)
# error handling on dimension
if (ndim < 2) or (ndim > 4):
raise ValueError('Found %i-dimensional image - not supported!' % ndim)
libfn = utils.get_lib_fn(_image_read_dict[pclass][ptype][ndim])
itk_pointer = libfn(filename)
ants_image = iio.ANTsImage(pixeltype=ptype, dimension=ndim, components=ncomp,
pointer=itk_pointer, is_rgb=is_rgb)
if pixeltype is not None:
ants_image = ants_image.clone(pixeltype)
if (reorient != False) and (ants_image.dimension == 3):
if reorient == True:
ants_image = ants_image.reorient_image2('RPI')
elif isinstance(reorient, str):
ants_image = ants_image.reorient_image2(reorient)
return ants_image
|
python
|
def image_read(filename, dimension=None, pixeltype='float', reorient=False):
"""
Read an ANTsImage from file
ANTsR function: `antsImageRead`
Arguments
---------
filename : string
Name of the file to read the image from.
dimension : int
Number of dimensions of the image read. This need not be the same as
the dimensions of the image in the file. Allowed values: 2, 3, 4.
If not provided, the dimension is obtained from the image file
pixeltype : string
C++ datatype to be used to represent the pixels read. This datatype
need not be the same as the datatype used in the file.
Options: unsigned char, unsigned int, float, double
reorient : boolean | string
if True, the image will be reoriented to RPI if it is 3D
if False, nothing will happen
if string, this should be the 3-letter orientation to which the
input image will reoriented if 3D.
if the image is 2D, this argument is ignored
Returns
-------
ANTsImage
"""
if filename.endswith('.npy'):
filename = os.path.expanduser(filename)
img_array = np.load(filename)
if os.path.exists(filename.replace('.npy', '.json')):
with open(filename.replace('.npy', '.json')) as json_data:
img_header = json.load(json_data)
ants_image = from_numpy(img_array,
origin=img_header.get('origin', None),
spacing=img_header.get('spacing', None),
direction=np.asarray(img_header.get('direction',None)),
has_components=img_header.get('components',1)>1)
else:
img_header = {}
ants_image = from_numpy(img_array)
else:
filename = os.path.expanduser(filename)
if not os.path.exists(filename):
raise ValueError('File %s does not exist!' % filename)
hinfo = image_header_info(filename)
ptype = hinfo['pixeltype']
pclass = hinfo['pixelclass']
ndim = hinfo['nDimensions']
ncomp = hinfo['nComponents']
is_rgb = True if pclass == 'rgb' else False
if dimension is not None:
ndim = dimension
# error handling on pixelclass
if pclass not in _supported_pclasses:
raise ValueError('Pixel class %s not supported!' % pclass)
# error handling on pixeltype
if ptype in _unsupported_ptypes:
ptype = _unsupported_ptype_map.get(ptype, 'unsupported')
if ptype == 'unsupported':
raise ValueError('Pixeltype %s not supported' % ptype)
# error handling on dimension
if (ndim < 2) or (ndim > 4):
raise ValueError('Found %i-dimensional image - not supported!' % ndim)
libfn = utils.get_lib_fn(_image_read_dict[pclass][ptype][ndim])
itk_pointer = libfn(filename)
ants_image = iio.ANTsImage(pixeltype=ptype, dimension=ndim, components=ncomp,
pointer=itk_pointer, is_rgb=is_rgb)
if pixeltype is not None:
ants_image = ants_image.clone(pixeltype)
if (reorient != False) and (ants_image.dimension == 3):
if reorient == True:
ants_image = ants_image.reorient_image2('RPI')
elif isinstance(reorient, str):
ants_image = ants_image.reorient_image2(reorient)
return ants_image
|
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"False",
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"(",
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"dimension",
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":",
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",",
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":",
"ants_image",
"=",
"ants_image",
".",
"reorient_image2",
"(",
"reorient",
")",
"return",
"ants_image"
] |
Read an ANTsImage from file
ANTsR function: `antsImageRead`
Arguments
---------
filename : string
Name of the file to read the image from.
dimension : int
Number of dimensions of the image read. This need not be the same as
the dimensions of the image in the file. Allowed values: 2, 3, 4.
If not provided, the dimension is obtained from the image file
pixeltype : string
C++ datatype to be used to represent the pixels read. This datatype
need not be the same as the datatype used in the file.
Options: unsigned char, unsigned int, float, double
reorient : boolean | string
if True, the image will be reoriented to RPI if it is 3D
if False, nothing will happen
if string, this should be the 3-letter orientation to which the
input image will reoriented if 3D.
if the image is 2D, this argument is ignored
Returns
-------
ANTsImage
|
[
"Read",
"an",
"ANTsImage",
"from",
"file"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_image_io.py#L425-L515
|
237,219
|
ANTsX/ANTsPy
|
ants/core/ants_image_io.py
|
dicom_read
|
def dicom_read(directory, pixeltype='float'):
"""
Read a set of dicom files in a directory into a single ANTsImage.
The origin of the resulting 3D image will be the origin of the
first dicom image read.
Arguments
---------
directory : string
folder in which all the dicom images exist
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> img = ants.dicom_read('~/desktop/dicom-subject/')
"""
slices = []
imgidx = 0
for imgpath in os.listdir(directory):
if imgpath.endswith('.dcm'):
if imgidx == 0:
tmp = image_read(os.path.join(directory,imgpath), dimension=3, pixeltype=pixeltype)
origin = tmp.origin
spacing = tmp.spacing
direction = tmp.direction
tmp = tmp.numpy()[:,:,0]
else:
tmp = image_read(os.path.join(directory,imgpath), dimension=2, pixeltype=pixeltype).numpy()
slices.append(tmp)
imgidx += 1
slices = np.stack(slices, axis=-1)
return from_numpy(slices, origin=origin, spacing=spacing, direction=direction)
|
python
|
def dicom_read(directory, pixeltype='float'):
"""
Read a set of dicom files in a directory into a single ANTsImage.
The origin of the resulting 3D image will be the origin of the
first dicom image read.
Arguments
---------
directory : string
folder in which all the dicom images exist
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> img = ants.dicom_read('~/desktop/dicom-subject/')
"""
slices = []
imgidx = 0
for imgpath in os.listdir(directory):
if imgpath.endswith('.dcm'):
if imgidx == 0:
tmp = image_read(os.path.join(directory,imgpath), dimension=3, pixeltype=pixeltype)
origin = tmp.origin
spacing = tmp.spacing
direction = tmp.direction
tmp = tmp.numpy()[:,:,0]
else:
tmp = image_read(os.path.join(directory,imgpath), dimension=2, pixeltype=pixeltype).numpy()
slices.append(tmp)
imgidx += 1
slices = np.stack(slices, axis=-1)
return from_numpy(slices, origin=origin, spacing=spacing, direction=direction)
|
[
"def",
"dicom_read",
"(",
"directory",
",",
"pixeltype",
"=",
"'float'",
")",
":",
"slices",
"=",
"[",
"]",
"imgidx",
"=",
"0",
"for",
"imgpath",
"in",
"os",
".",
"listdir",
"(",
"directory",
")",
":",
"if",
"imgpath",
".",
"endswith",
"(",
"'.dcm'",
")",
":",
"if",
"imgidx",
"==",
"0",
":",
"tmp",
"=",
"image_read",
"(",
"os",
".",
"path",
".",
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"(",
"directory",
",",
"imgpath",
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"=",
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"(",
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",",
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"tmp",
"=",
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"path",
".",
"join",
"(",
"directory",
",",
"imgpath",
")",
",",
"dimension",
"=",
"2",
",",
"pixeltype",
"=",
"pixeltype",
")",
".",
"numpy",
"(",
")",
"slices",
".",
"append",
"(",
"tmp",
")",
"imgidx",
"+=",
"1",
"slices",
"=",
"np",
".",
"stack",
"(",
"slices",
",",
"axis",
"=",
"-",
"1",
")",
"return",
"from_numpy",
"(",
"slices",
",",
"origin",
"=",
"origin",
",",
"spacing",
"=",
"spacing",
",",
"direction",
"=",
"direction",
")"
] |
Read a set of dicom files in a directory into a single ANTsImage.
The origin of the resulting 3D image will be the origin of the
first dicom image read.
Arguments
---------
directory : string
folder in which all the dicom images exist
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> img = ants.dicom_read('~/desktop/dicom-subject/')
|
[
"Read",
"a",
"set",
"of",
"dicom",
"files",
"in",
"a",
"directory",
"into",
"a",
"single",
"ANTsImage",
".",
"The",
"origin",
"of",
"the",
"resulting",
"3D",
"image",
"will",
"be",
"the",
"origin",
"of",
"the",
"first",
"dicom",
"image",
"read",
"."
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_image_io.py#L518-L555
|
237,220
|
ANTsX/ANTsPy
|
ants/core/ants_image_io.py
|
image_write
|
def image_write(image, filename, ri=False):
"""
Write an ANTsImage to file
ANTsR function: `antsImageWrite`
Arguments
---------
image : ANTsImage
image to save to file
filename : string
name of file to which image will be saved
ri : boolean
if True, return image. This allows for using this function in a pipeline:
>>> img2 = img.smooth_image(2.).image_write(file1, ri=True).threshold_image(0,20).image_write(file2, ri=True)
if False, do not return image
"""
if filename.endswith('.npy'):
img_array = image.numpy()
img_header = {'origin': image.origin,'spacing': image.spacing,
'direction': image.direction.tolist(), 'components': image.components}
np.save(filename, img_array)
with open(filename.replace('.npy','.json'), 'w') as outfile:
json.dump(img_header, outfile)
else:
image.to_file(filename)
if ri:
return image
|
python
|
def image_write(image, filename, ri=False):
"""
Write an ANTsImage to file
ANTsR function: `antsImageWrite`
Arguments
---------
image : ANTsImage
image to save to file
filename : string
name of file to which image will be saved
ri : boolean
if True, return image. This allows for using this function in a pipeline:
>>> img2 = img.smooth_image(2.).image_write(file1, ri=True).threshold_image(0,20).image_write(file2, ri=True)
if False, do not return image
"""
if filename.endswith('.npy'):
img_array = image.numpy()
img_header = {'origin': image.origin,'spacing': image.spacing,
'direction': image.direction.tolist(), 'components': image.components}
np.save(filename, img_array)
with open(filename.replace('.npy','.json'), 'w') as outfile:
json.dump(img_header, outfile)
else:
image.to_file(filename)
if ri:
return image
|
[
"def",
"image_write",
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"image",
",",
"filename",
",",
"ri",
"=",
"False",
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"endswith",
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"'.npy'",
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"else",
":",
"image",
".",
"to_file",
"(",
"filename",
")",
"if",
"ri",
":",
"return",
"image"
] |
Write an ANTsImage to file
ANTsR function: `antsImageWrite`
Arguments
---------
image : ANTsImage
image to save to file
filename : string
name of file to which image will be saved
ri : boolean
if True, return image. This allows for using this function in a pipeline:
>>> img2 = img.smooth_image(2.).image_write(file1, ri=True).threshold_image(0,20).image_write(file2, ri=True)
if False, do not return image
|
[
"Write",
"an",
"ANTsImage",
"to",
"file"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_image_io.py#L558-L589
|
237,221
|
ANTsX/ANTsPy
|
ants/segmentation/otsu.py
|
otsu_segmentation
|
def otsu_segmentation(image, k, mask=None):
"""
Otsu image segmentation
This is a very fast segmentation algorithm good for quick explortation,
but does not return probability maps.
ANTsR function: `thresholdImage(image, 'Otsu', k)`
Arguments
---------
image : ANTsImage
input image
k : integer
integer number of classes. Note that a background class will
be added to this, so the resulting segmentation will
have k+1 unique values.
mask : ANTsImage
segment inside this mask
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> mni = ants.image_read(ants.get_data('mni'))
>>> seg = mni.otsu_segmentation(k=3) #0=bg,1=csf,2=gm,3=wm
"""
if mask is not None:
image = image.mask_image(mask)
seg = image.threshold_image('Otsu', k)
return seg
|
python
|
def otsu_segmentation(image, k, mask=None):
"""
Otsu image segmentation
This is a very fast segmentation algorithm good for quick explortation,
but does not return probability maps.
ANTsR function: `thresholdImage(image, 'Otsu', k)`
Arguments
---------
image : ANTsImage
input image
k : integer
integer number of classes. Note that a background class will
be added to this, so the resulting segmentation will
have k+1 unique values.
mask : ANTsImage
segment inside this mask
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> mni = ants.image_read(ants.get_data('mni'))
>>> seg = mni.otsu_segmentation(k=3) #0=bg,1=csf,2=gm,3=wm
"""
if mask is not None:
image = image.mask_image(mask)
seg = image.threshold_image('Otsu', k)
return seg
|
[
"def",
"otsu_segmentation",
"(",
"image",
",",
"k",
",",
"mask",
"=",
"None",
")",
":",
"if",
"mask",
"is",
"not",
"None",
":",
"image",
"=",
"image",
".",
"mask_image",
"(",
"mask",
")",
"seg",
"=",
"image",
".",
"threshold_image",
"(",
"'Otsu'",
",",
"k",
")",
"return",
"seg"
] |
Otsu image segmentation
This is a very fast segmentation algorithm good for quick explortation,
but does not return probability maps.
ANTsR function: `thresholdImage(image, 'Otsu', k)`
Arguments
---------
image : ANTsImage
input image
k : integer
integer number of classes. Note that a background class will
be added to this, so the resulting segmentation will
have k+1 unique values.
mask : ANTsImage
segment inside this mask
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> mni = ants.image_read(ants.get_data('mni'))
>>> seg = mni.otsu_segmentation(k=3) #0=bg,1=csf,2=gm,3=wm
|
[
"Otsu",
"image",
"segmentation"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/segmentation/otsu.py#L7-L43
|
237,222
|
ANTsX/ANTsPy
|
ants/utils/crop_image.py
|
crop_image
|
def crop_image(image, label_image=None, label=1):
"""
Use a label image to crop a smaller ANTsImage from within a larger ANTsImage
ANTsR function: `cropImage`
Arguments
---------
image : ANTsImage
image to crop
label_image : ANTsImage
image with label values. If not supplied, estimated from data.
label : integer
the label value to use
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> fi = ants.image_read( ants.get_ants_data('r16') )
>>> cropped = ants.crop_image(fi)
>>> cropped = ants.crop_image(fi, fi, 100 )
"""
inpixeltype = image.pixeltype
ndim = image.dimension
if image.pixeltype != 'float':
image = image.clone('float')
if label_image is None:
label_image = get_mask(image)
if label_image.pixeltype != 'float':
label_image = label_image.clone('float')
libfn = utils.get_lib_fn('cropImageF%i' % ndim)
itkimage = libfn(image.pointer, label_image.pointer, label, 0, [], [])
return iio.ANTsImage(pixeltype='float', dimension=ndim,
components=image.components, pointer=itkimage).clone(inpixeltype)
|
python
|
def crop_image(image, label_image=None, label=1):
"""
Use a label image to crop a smaller ANTsImage from within a larger ANTsImage
ANTsR function: `cropImage`
Arguments
---------
image : ANTsImage
image to crop
label_image : ANTsImage
image with label values. If not supplied, estimated from data.
label : integer
the label value to use
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> fi = ants.image_read( ants.get_ants_data('r16') )
>>> cropped = ants.crop_image(fi)
>>> cropped = ants.crop_image(fi, fi, 100 )
"""
inpixeltype = image.pixeltype
ndim = image.dimension
if image.pixeltype != 'float':
image = image.clone('float')
if label_image is None:
label_image = get_mask(image)
if label_image.pixeltype != 'float':
label_image = label_image.clone('float')
libfn = utils.get_lib_fn('cropImageF%i' % ndim)
itkimage = libfn(image.pointer, label_image.pointer, label, 0, [], [])
return iio.ANTsImage(pixeltype='float', dimension=ndim,
components=image.components, pointer=itkimage).clone(inpixeltype)
|
[
"def",
"crop_image",
"(",
"image",
",",
"label_image",
"=",
"None",
",",
"label",
"=",
"1",
")",
":",
"inpixeltype",
"=",
"image",
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"(",
"image",
".",
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",",
"label_image",
".",
"pointer",
",",
"label",
",",
"0",
",",
"[",
"]",
",",
"[",
"]",
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"return",
"iio",
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"ANTsImage",
"(",
"pixeltype",
"=",
"'float'",
",",
"dimension",
"=",
"ndim",
",",
"components",
"=",
"image",
".",
"components",
",",
"pointer",
"=",
"itkimage",
")",
".",
"clone",
"(",
"inpixeltype",
")"
] |
Use a label image to crop a smaller ANTsImage from within a larger ANTsImage
ANTsR function: `cropImage`
Arguments
---------
image : ANTsImage
image to crop
label_image : ANTsImage
image with label values. If not supplied, estimated from data.
label : integer
the label value to use
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> fi = ants.image_read( ants.get_ants_data('r16') )
>>> cropped = ants.crop_image(fi)
>>> cropped = ants.crop_image(fi, fi, 100 )
|
[
"Use",
"a",
"label",
"image",
"to",
"crop",
"a",
"smaller",
"ANTsImage",
"from",
"within",
"a",
"larger",
"ANTsImage"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/utils/crop_image.py#L14-L56
|
237,223
|
ANTsX/ANTsPy
|
ants/utils/crop_image.py
|
decrop_image
|
def decrop_image(cropped_image, full_image):
"""
The inverse function for `ants.crop_image`
ANTsR function: `decropImage`
Arguments
---------
cropped_image : ANTsImage
cropped image
full_image : ANTsImage
image in which the cropped image will be put back
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> fi = ants.image_read(ants.get_ants_data('r16'))
>>> mask = ants.get_mask(fi)
>>> cropped = ants.crop_image(fi, mask, 1)
>>> cropped = ants.smooth_image(cropped, 1)
>>> decropped = ants.decrop_image(cropped, fi)
"""
inpixeltype = 'float'
if cropped_image.pixeltype != 'float':
inpixeltype= cropped_image.pixeltype
cropped_image = cropped_image.clone('float')
if full_image.pixeltype != 'float':
full_image = full_image.clone('float')
libfn = utils.get_lib_fn('cropImageF%i' % cropped_image.dimension)
itkimage = libfn(cropped_image.pointer, full_image.pointer, 1, 1, [], [])
ants_image = iio.ANTsImage(pixeltype='float', dimension=cropped_image.dimension,
components=cropped_image.components, pointer=itkimage)
if inpixeltype != 'float':
ants_image = ants_image.clone(inpixeltype)
return ants_image
|
python
|
def decrop_image(cropped_image, full_image):
"""
The inverse function for `ants.crop_image`
ANTsR function: `decropImage`
Arguments
---------
cropped_image : ANTsImage
cropped image
full_image : ANTsImage
image in which the cropped image will be put back
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> fi = ants.image_read(ants.get_ants_data('r16'))
>>> mask = ants.get_mask(fi)
>>> cropped = ants.crop_image(fi, mask, 1)
>>> cropped = ants.smooth_image(cropped, 1)
>>> decropped = ants.decrop_image(cropped, fi)
"""
inpixeltype = 'float'
if cropped_image.pixeltype != 'float':
inpixeltype= cropped_image.pixeltype
cropped_image = cropped_image.clone('float')
if full_image.pixeltype != 'float':
full_image = full_image.clone('float')
libfn = utils.get_lib_fn('cropImageF%i' % cropped_image.dimension)
itkimage = libfn(cropped_image.pointer, full_image.pointer, 1, 1, [], [])
ants_image = iio.ANTsImage(pixeltype='float', dimension=cropped_image.dimension,
components=cropped_image.components, pointer=itkimage)
if inpixeltype != 'float':
ants_image = ants_image.clone(inpixeltype)
return ants_image
|
[
"def",
"decrop_image",
"(",
"cropped_image",
",",
"full_image",
")",
":",
"inpixeltype",
"=",
"'float'",
"if",
"cropped_image",
".",
"pixeltype",
"!=",
"'float'",
":",
"inpixeltype",
"=",
"cropped_image",
".",
"pixeltype",
"cropped_image",
"=",
"cropped_image",
".",
"clone",
"(",
"'float'",
")",
"if",
"full_image",
".",
"pixeltype",
"!=",
"'float'",
":",
"full_image",
"=",
"full_image",
".",
"clone",
"(",
"'float'",
")",
"libfn",
"=",
"utils",
".",
"get_lib_fn",
"(",
"'cropImageF%i'",
"%",
"cropped_image",
".",
"dimension",
")",
"itkimage",
"=",
"libfn",
"(",
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".",
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",",
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".",
"pointer",
",",
"1",
",",
"1",
",",
"[",
"]",
",",
"[",
"]",
")",
"ants_image",
"=",
"iio",
".",
"ANTsImage",
"(",
"pixeltype",
"=",
"'float'",
",",
"dimension",
"=",
"cropped_image",
".",
"dimension",
",",
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"=",
"cropped_image",
".",
"components",
",",
"pointer",
"=",
"itkimage",
")",
"if",
"inpixeltype",
"!=",
"'float'",
":",
"ants_image",
"=",
"ants_image",
".",
"clone",
"(",
"inpixeltype",
")",
"return",
"ants_image"
] |
The inverse function for `ants.crop_image`
ANTsR function: `decropImage`
Arguments
---------
cropped_image : ANTsImage
cropped image
full_image : ANTsImage
image in which the cropped image will be put back
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> fi = ants.image_read(ants.get_ants_data('r16'))
>>> mask = ants.get_mask(fi)
>>> cropped = ants.crop_image(fi, mask, 1)
>>> cropped = ants.smooth_image(cropped, 1)
>>> decropped = ants.decrop_image(cropped, fi)
|
[
"The",
"inverse",
"function",
"for",
"ants",
".",
"crop_image"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/utils/crop_image.py#L108-L149
|
237,224
|
ANTsX/ANTsPy
|
ants/segmentation/kmeans.py
|
kmeans_segmentation
|
def kmeans_segmentation(image, k, kmask=None, mrf=0.1):
"""
K-means image segmentation that is a wrapper around `ants.atropos`
ANTsR function: `kmeansSegmentation`
Arguments
---------
image : ANTsImage
input image
k : integer
integer number of classes
kmask : ANTsImage (optional)
segment inside this mask
mrf : scalar
smoothness, higher is smoother
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> fi = ants.image_read(ants.get_ants_data('r16'), 'float')
>>> fi = ants.n3_bias_field_correction(fi, 2)
>>> seg = ants.kmeans_segmentation(fi, 3)
"""
dim = image.dimension
kmimage = utils.iMath(image, 'Normalize')
if kmask is None:
kmask = utils.get_mask(kmimage, 0.01, 1, cleanup=2)
kmask = utils.iMath(kmask, 'FillHoles').threshold_image(1,2)
nhood = 'x'.join(['1']*dim)
mrf = '[%s,%s]' % (str(mrf), nhood)
kmimage = atropos(a = kmimage, m = mrf, c = '[5,0]', i = 'kmeans[%s]'%(str(k)), x = kmask)
kmimage['segmentation'] = kmimage['segmentation'].clone(image.pixeltype)
return kmimage
|
python
|
def kmeans_segmentation(image, k, kmask=None, mrf=0.1):
"""
K-means image segmentation that is a wrapper around `ants.atropos`
ANTsR function: `kmeansSegmentation`
Arguments
---------
image : ANTsImage
input image
k : integer
integer number of classes
kmask : ANTsImage (optional)
segment inside this mask
mrf : scalar
smoothness, higher is smoother
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> fi = ants.image_read(ants.get_ants_data('r16'), 'float')
>>> fi = ants.n3_bias_field_correction(fi, 2)
>>> seg = ants.kmeans_segmentation(fi, 3)
"""
dim = image.dimension
kmimage = utils.iMath(image, 'Normalize')
if kmask is None:
kmask = utils.get_mask(kmimage, 0.01, 1, cleanup=2)
kmask = utils.iMath(kmask, 'FillHoles').threshold_image(1,2)
nhood = 'x'.join(['1']*dim)
mrf = '[%s,%s]' % (str(mrf), nhood)
kmimage = atropos(a = kmimage, m = mrf, c = '[5,0]', i = 'kmeans[%s]'%(str(k)), x = kmask)
kmimage['segmentation'] = kmimage['segmentation'].clone(image.pixeltype)
return kmimage
|
[
"def",
"kmeans_segmentation",
"(",
"image",
",",
"k",
",",
"kmask",
"=",
"None",
",",
"mrf",
"=",
"0.1",
")",
":",
"dim",
"=",
"image",
".",
"dimension",
"kmimage",
"=",
"utils",
".",
"iMath",
"(",
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",",
"'Normalize'",
")",
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":",
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"(",
"kmimage",
",",
"0.01",
",",
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",",
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")",
"kmask",
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",",
"'FillHoles'",
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"threshold_image",
"(",
"1",
",",
"2",
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"=",
"'x'",
".",
"join",
"(",
"[",
"'1'",
"]",
"*",
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")",
"mrf",
"=",
"'[%s,%s]'",
"%",
"(",
"str",
"(",
"mrf",
")",
",",
"nhood",
")",
"kmimage",
"=",
"atropos",
"(",
"a",
"=",
"kmimage",
",",
"m",
"=",
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",",
"c",
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",",
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"=",
"'kmeans[%s]'",
"%",
"(",
"str",
"(",
"k",
")",
")",
",",
"x",
"=",
"kmask",
")",
"kmimage",
"[",
"'segmentation'",
"]",
"=",
"kmimage",
"[",
"'segmentation'",
"]",
".",
"clone",
"(",
"image",
".",
"pixeltype",
")",
"return",
"kmimage"
] |
K-means image segmentation that is a wrapper around `ants.atropos`
ANTsR function: `kmeansSegmentation`
Arguments
---------
image : ANTsImage
input image
k : integer
integer number of classes
kmask : ANTsImage (optional)
segment inside this mask
mrf : scalar
smoothness, higher is smoother
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> fi = ants.image_read(ants.get_ants_data('r16'), 'float')
>>> fi = ants.n3_bias_field_correction(fi, 2)
>>> seg = ants.kmeans_segmentation(fi, 3)
|
[
"K",
"-",
"means",
"image",
"segmentation",
"that",
"is",
"a",
"wrapper",
"around",
"ants",
".",
"atropos"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/segmentation/kmeans.py#L9-L49
|
237,225
|
ANTsX/ANTsPy
|
ants/registration/reorient_image.py
|
reorient_image2
|
def reorient_image2(image, orientation='RAS'):
"""
Reorient an image.
Example
-------
>>> import ants
>>> mni = ants.image_read(ants.get_data('mni'))
>>> mni2 = mni.reorient_image2()
"""
if image.dimension != 3:
raise ValueError('image must have 3 dimensions')
inpixeltype = image.pixeltype
ndim = image.dimension
if image.pixeltype != 'float':
image = image.clone('float')
libfn = utils.get_lib_fn('reorientImage2')
itkimage = libfn(image.pointer, orientation)
new_img = iio.ANTsImage(pixeltype='float', dimension=ndim,
components=image.components, pointer=itkimage)#.clone(inpixeltype)
if inpixeltype != 'float':
new_img = new_img.clone(inpixeltype)
return new_img
|
python
|
def reorient_image2(image, orientation='RAS'):
"""
Reorient an image.
Example
-------
>>> import ants
>>> mni = ants.image_read(ants.get_data('mni'))
>>> mni2 = mni.reorient_image2()
"""
if image.dimension != 3:
raise ValueError('image must have 3 dimensions')
inpixeltype = image.pixeltype
ndim = image.dimension
if image.pixeltype != 'float':
image = image.clone('float')
libfn = utils.get_lib_fn('reorientImage2')
itkimage = libfn(image.pointer, orientation)
new_img = iio.ANTsImage(pixeltype='float', dimension=ndim,
components=image.components, pointer=itkimage)#.clone(inpixeltype)
if inpixeltype != 'float':
new_img = new_img.clone(inpixeltype)
return new_img
|
[
"def",
"reorient_image2",
"(",
"image",
",",
"orientation",
"=",
"'RAS'",
")",
":",
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"image",
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"!=",
"3",
":",
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"ValueError",
"(",
"'image must have 3 dimensions'",
")",
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",",
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":",
"new_img",
"=",
"new_img",
".",
"clone",
"(",
"inpixeltype",
")",
"return",
"new_img"
] |
Reorient an image.
Example
-------
>>> import ants
>>> mni = ants.image_read(ants.get_data('mni'))
>>> mni2 = mni.reorient_image2()
|
[
"Reorient",
"an",
"image",
"."
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/registration/reorient_image.py#L56-L82
|
237,226
|
ANTsX/ANTsPy
|
ants/registration/reorient_image.py
|
reorient_image
|
def reorient_image(image, axis1, axis2=None, doreflection=False, doscale=0, txfn=None):
"""
Align image along a specified axis
ANTsR function: `reorientImage`
Arguments
---------
image : ANTsImage
image to reorient
axis1 : list/tuple of integers
vector of size dim, might need to play w/axis sign
axis2 : list/tuple of integers
vector of size dim for 3D
doreflection : boolean
whether to reflect
doscale : scalar value
1 allows automated estimate of scaling
txfn : string
file name for transformation
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> image = ants.image_read(ants.get_ants_data('r16'))
>>> ants.reorient_image(image, (1,0))
"""
inpixeltype = image.pixeltype
if image.pixeltype != 'float':
image = image.clone('float')
axis_was_none = False
if axis2 is None:
axis_was_none = True
axis2 = [0]*image.dimension
axis1 = np.array(axis1)
axis2 = np.array(axis2)
axis1 = axis1 / np.sqrt(np.sum(axis1*axis1)) * (-1)
axis1 = axis1.astype('int')
if not axis_was_none:
axis2 = axis2 / np.sqrt(np.sum(axis2*axis2)) * (-1)
axis2 = axis2.astype('int')
else:
axis2 = np.array([0]*image.dimension).astype('int')
if txfn is None:
txfn = mktemp(suffix='.mat')
if isinstance(doreflection, tuple):
doreflection = list(doreflection)
if not isinstance(doreflection, list):
doreflection = [doreflection]
if isinstance(doscale, tuple):
doscale = list(doscale)
if not isinstance(doscale, list):
doscale = [doscale]
if len(doreflection) == 1:
doreflection = [doreflection[0]]*image.dimension
if len(doscale) == 1:
doscale = [doscale[0]]*image.dimension
libfn = utils.get_lib_fn('reorientImage%s' % image._libsuffix)
libfn(image.pointer, txfn, axis1.tolist(), axis2.tolist(), doreflection, doscale)
image2 = apply_transforms(image, image, transformlist=[txfn])
if image.pixeltype != inpixeltype:
image2 = image2.clone(inpixeltype)
return {'reoimage':image2,
'txfn':txfn}
|
python
|
def reorient_image(image, axis1, axis2=None, doreflection=False, doscale=0, txfn=None):
"""
Align image along a specified axis
ANTsR function: `reorientImage`
Arguments
---------
image : ANTsImage
image to reorient
axis1 : list/tuple of integers
vector of size dim, might need to play w/axis sign
axis2 : list/tuple of integers
vector of size dim for 3D
doreflection : boolean
whether to reflect
doscale : scalar value
1 allows automated estimate of scaling
txfn : string
file name for transformation
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> image = ants.image_read(ants.get_ants_data('r16'))
>>> ants.reorient_image(image, (1,0))
"""
inpixeltype = image.pixeltype
if image.pixeltype != 'float':
image = image.clone('float')
axis_was_none = False
if axis2 is None:
axis_was_none = True
axis2 = [0]*image.dimension
axis1 = np.array(axis1)
axis2 = np.array(axis2)
axis1 = axis1 / np.sqrt(np.sum(axis1*axis1)) * (-1)
axis1 = axis1.astype('int')
if not axis_was_none:
axis2 = axis2 / np.sqrt(np.sum(axis2*axis2)) * (-1)
axis2 = axis2.astype('int')
else:
axis2 = np.array([0]*image.dimension).astype('int')
if txfn is None:
txfn = mktemp(suffix='.mat')
if isinstance(doreflection, tuple):
doreflection = list(doreflection)
if not isinstance(doreflection, list):
doreflection = [doreflection]
if isinstance(doscale, tuple):
doscale = list(doscale)
if not isinstance(doscale, list):
doscale = [doscale]
if len(doreflection) == 1:
doreflection = [doreflection[0]]*image.dimension
if len(doscale) == 1:
doscale = [doscale[0]]*image.dimension
libfn = utils.get_lib_fn('reorientImage%s' % image._libsuffix)
libfn(image.pointer, txfn, axis1.tolist(), axis2.tolist(), doreflection, doscale)
image2 = apply_transforms(image, image, transformlist=[txfn])
if image.pixeltype != inpixeltype:
image2 = image2.clone(inpixeltype)
return {'reoimage':image2,
'txfn':txfn}
|
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"return",
"{",
"'reoimage'",
":",
"image2",
",",
"'txfn'",
":",
"txfn",
"}"
] |
Align image along a specified axis
ANTsR function: `reorientImage`
Arguments
---------
image : ANTsImage
image to reorient
axis1 : list/tuple of integers
vector of size dim, might need to play w/axis sign
axis2 : list/tuple of integers
vector of size dim for 3D
doreflection : boolean
whether to reflect
doscale : scalar value
1 allows automated estimate of scaling
txfn : string
file name for transformation
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> image = ants.image_read(ants.get_ants_data('r16'))
>>> ants.reorient_image(image, (1,0))
|
[
"Align",
"image",
"along",
"a",
"specified",
"axis"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/registration/reorient_image.py#L85-L168
|
237,227
|
ANTsX/ANTsPy
|
ants/registration/reorient_image.py
|
get_center_of_mass
|
def get_center_of_mass(image):
"""
Compute an image center of mass in physical space which is defined
as the mean of the intensity weighted voxel coordinate system.
ANTsR function: `getCenterOfMass`
Arguments
---------
image : ANTsImage
image from which center of mass will be computed
Returns
-------
scalar
Example
-------
>>> fi = ants.image_read( ants.get_ants_data("r16"))
>>> com1 = ants.get_center_of_mass( fi )
>>> fi = ants.image_read( ants.get_ants_data("r64"))
>>> com2 = ants.get_center_of_mass( fi )
"""
if image.pixeltype != 'float':
image = image.clone('float')
libfn = utils.get_lib_fn('centerOfMass%s' % image._libsuffix)
com = libfn(image.pointer)
return tuple(com)
|
python
|
def get_center_of_mass(image):
"""
Compute an image center of mass in physical space which is defined
as the mean of the intensity weighted voxel coordinate system.
ANTsR function: `getCenterOfMass`
Arguments
---------
image : ANTsImage
image from which center of mass will be computed
Returns
-------
scalar
Example
-------
>>> fi = ants.image_read( ants.get_ants_data("r16"))
>>> com1 = ants.get_center_of_mass( fi )
>>> fi = ants.image_read( ants.get_ants_data("r64"))
>>> com2 = ants.get_center_of_mass( fi )
"""
if image.pixeltype != 'float':
image = image.clone('float')
libfn = utils.get_lib_fn('centerOfMass%s' % image._libsuffix)
com = libfn(image.pointer)
return tuple(com)
|
[
"def",
"get_center_of_mass",
"(",
"image",
")",
":",
"if",
"image",
".",
"pixeltype",
"!=",
"'float'",
":",
"image",
"=",
"image",
".",
"clone",
"(",
"'float'",
")",
"libfn",
"=",
"utils",
".",
"get_lib_fn",
"(",
"'centerOfMass%s'",
"%",
"image",
".",
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"com",
"=",
"libfn",
"(",
"image",
".",
"pointer",
")",
"return",
"tuple",
"(",
"com",
")"
] |
Compute an image center of mass in physical space which is defined
as the mean of the intensity weighted voxel coordinate system.
ANTsR function: `getCenterOfMass`
Arguments
---------
image : ANTsImage
image from which center of mass will be computed
Returns
-------
scalar
Example
-------
>>> fi = ants.image_read( ants.get_ants_data("r16"))
>>> com1 = ants.get_center_of_mass( fi )
>>> fi = ants.image_read( ants.get_ants_data("r64"))
>>> com2 = ants.get_center_of_mass( fi )
|
[
"Compute",
"an",
"image",
"center",
"of",
"mass",
"in",
"physical",
"space",
"which",
"is",
"defined",
"as",
"the",
"mean",
"of",
"the",
"intensity",
"weighted",
"voxel",
"coordinate",
"system",
"."
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/registration/reorient_image.py#L171-L200
|
237,228
|
ANTsX/ANTsPy
|
ants/utils/convert_nibabel.py
|
to_nibabel
|
def to_nibabel(image):
"""
Convert an ANTsImage to a Nibabel image
"""
if image.dimension != 3:
raise ValueError('Only 3D images currently supported')
import nibabel as nib
array_data = image.numpy()
affine = np.hstack([image.direction*np.diag(image.spacing),np.array(image.origin).reshape(3,1)])
affine = np.vstack([affine, np.array([0,0,0,1.])])
affine[:2,:] *= -1
new_img = nib.Nifti1Image(array_data, affine)
return new_img
|
python
|
def to_nibabel(image):
"""
Convert an ANTsImage to a Nibabel image
"""
if image.dimension != 3:
raise ValueError('Only 3D images currently supported')
import nibabel as nib
array_data = image.numpy()
affine = np.hstack([image.direction*np.diag(image.spacing),np.array(image.origin).reshape(3,1)])
affine = np.vstack([affine, np.array([0,0,0,1.])])
affine[:2,:] *= -1
new_img = nib.Nifti1Image(array_data, affine)
return new_img
|
[
"def",
"to_nibabel",
"(",
"image",
")",
":",
"if",
"image",
".",
"dimension",
"!=",
"3",
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"raise",
"ValueError",
"(",
"'Only 3D images currently supported'",
")",
"import",
"nibabel",
"as",
"nib",
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"=",
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".",
"numpy",
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".",
"Nifti1Image",
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"array_data",
",",
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"new_img"
] |
Convert an ANTsImage to a Nibabel image
|
[
"Convert",
"an",
"ANTsImage",
"to",
"a",
"Nibabel",
"image"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/utils/convert_nibabel.py#L10-L23
|
237,229
|
ANTsX/ANTsPy
|
ants/utils/convert_nibabel.py
|
from_nibabel
|
def from_nibabel(nib_image):
"""
Convert a nibabel image to an ANTsImage
"""
tmpfile = mktemp(suffix='.nii.gz')
nib_image.to_filename(tmpfile)
new_img = iio2.image_read(tmpfile)
os.remove(tmpfile)
return new_img
|
python
|
def from_nibabel(nib_image):
"""
Convert a nibabel image to an ANTsImage
"""
tmpfile = mktemp(suffix='.nii.gz')
nib_image.to_filename(tmpfile)
new_img = iio2.image_read(tmpfile)
os.remove(tmpfile)
return new_img
|
[
"def",
"from_nibabel",
"(",
"nib_image",
")",
":",
"tmpfile",
"=",
"mktemp",
"(",
"suffix",
"=",
"'.nii.gz'",
")",
"nib_image",
".",
"to_filename",
"(",
"tmpfile",
")",
"new_img",
"=",
"iio2",
".",
"image_read",
"(",
"tmpfile",
")",
"os",
".",
"remove",
"(",
"tmpfile",
")",
"return",
"new_img"
] |
Convert a nibabel image to an ANTsImage
|
[
"Convert",
"a",
"nibabel",
"image",
"to",
"an",
"ANTsImage"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/utils/convert_nibabel.py#L26-L34
|
237,230
|
ANTsX/ANTsPy
|
ants/contrib/sampling/affine3d.py
|
RandomShear3D.transform
|
def transform(self, X=None, y=None):
"""
Transform an image using an Affine transform with
shear parameters randomly generated from the user-specified
range. Return the transform if X=None.
Arguments
---------
X : ANTsImage
Image to transform
y : ANTsImage (optional)
Another image to transform
Returns
-------
ANTsImage if y is None, else a tuple of ANTsImage types
Examples
--------
>>> import ants
>>> img = ants.image_read(ants.get_data('ch2'))
>>> tx = ants.contrib.RandomShear3D(shear_range=(-10,10))
>>> img2 = tx.transform(img)
"""
# random draw in shear range
shear_x = random.gauss(self.shear_range[0], self.shear_range[1])
shear_y = random.gauss(self.shear_range[0], self.shear_range[1])
shear_z = random.gauss(self.shear_range[0], self.shear_range[1])
self.params = (shear_x, shear_y, shear_z)
tx = Shear3D((shear_x, shear_y, shear_z),
reference=self.reference,
lazy=self.lazy)
return tx.transform(X,y)
|
python
|
def transform(self, X=None, y=None):
"""
Transform an image using an Affine transform with
shear parameters randomly generated from the user-specified
range. Return the transform if X=None.
Arguments
---------
X : ANTsImage
Image to transform
y : ANTsImage (optional)
Another image to transform
Returns
-------
ANTsImage if y is None, else a tuple of ANTsImage types
Examples
--------
>>> import ants
>>> img = ants.image_read(ants.get_data('ch2'))
>>> tx = ants.contrib.RandomShear3D(shear_range=(-10,10))
>>> img2 = tx.transform(img)
"""
# random draw in shear range
shear_x = random.gauss(self.shear_range[0], self.shear_range[1])
shear_y = random.gauss(self.shear_range[0], self.shear_range[1])
shear_z = random.gauss(self.shear_range[0], self.shear_range[1])
self.params = (shear_x, shear_y, shear_z)
tx = Shear3D((shear_x, shear_y, shear_z),
reference=self.reference,
lazy=self.lazy)
return tx.transform(X,y)
|
[
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"self",
",",
"X",
"=",
"None",
",",
"y",
"=",
"None",
")",
":",
"# random draw in shear range",
"shear_x",
"=",
"random",
".",
"gauss",
"(",
"self",
".",
"shear_range",
"[",
"0",
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",",
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"shear_range",
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"1",
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".",
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"shear_range",
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",",
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"shear_range",
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"1",
"]",
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"self",
".",
"params",
"=",
"(",
"shear_x",
",",
"shear_y",
",",
"shear_z",
")",
"tx",
"=",
"Shear3D",
"(",
"(",
"shear_x",
",",
"shear_y",
",",
"shear_z",
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",",
"reference",
"=",
"self",
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"reference",
",",
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"self",
".",
"lazy",
")",
"return",
"tx",
".",
"transform",
"(",
"X",
",",
"y",
")"
] |
Transform an image using an Affine transform with
shear parameters randomly generated from the user-specified
range. Return the transform if X=None.
Arguments
---------
X : ANTsImage
Image to transform
y : ANTsImage (optional)
Another image to transform
Returns
-------
ANTsImage if y is None, else a tuple of ANTsImage types
Examples
--------
>>> import ants
>>> img = ants.image_read(ants.get_data('ch2'))
>>> tx = ants.contrib.RandomShear3D(shear_range=(-10,10))
>>> img2 = tx.transform(img)
|
[
"Transform",
"an",
"image",
"using",
"an",
"Affine",
"transform",
"with",
"shear",
"parameters",
"randomly",
"generated",
"from",
"the",
"user",
"-",
"specified",
"range",
".",
"Return",
"the",
"transform",
"if",
"X",
"=",
"None",
"."
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/contrib/sampling/affine3d.py#L304-L339
|
237,231
|
ANTsX/ANTsPy
|
ants/contrib/sampling/affine3d.py
|
RandomZoom3D.transform
|
def transform(self, X=None, y=None):
"""
Transform an image using an Affine transform with
zoom parameters randomly generated from the user-specified
range. Return the transform if X=None.
Arguments
---------
X : ANTsImage
Image to transform
y : ANTsImage (optional)
Another image to transform
Returns
-------
ANTsImage if y is None, else a tuple of ANTsImage types
Examples
--------
>>> import ants
>>> img = ants.image_read(ants.get_data('ch2'))
>>> tx = ants.contrib.RandomZoom3D(zoom_range=(0.8,0.9))
>>> img2 = tx.transform(img)
"""
# random draw in zoom range
zoom_x = np.exp( random.gauss(
np.log( self.zoom_range[0] ),
np.log( self.zoom_range[1] ) ) )
zoom_y = np.exp( random.gauss(
np.log( self.zoom_range[0] ),
np.log( self.zoom_range[1] ) ) )
zoom_z = np.exp( random.gauss(
np.log( self.zoom_range[0] ),
np.log( self.zoom_range[1] ) ) )
self.params = (zoom_x, zoom_y, zoom_z)
tx = Zoom3D((zoom_x,zoom_y,zoom_z),
reference=self.reference,
lazy=self.lazy)
return tx.transform(X,y)
|
python
|
def transform(self, X=None, y=None):
"""
Transform an image using an Affine transform with
zoom parameters randomly generated from the user-specified
range. Return the transform if X=None.
Arguments
---------
X : ANTsImage
Image to transform
y : ANTsImage (optional)
Another image to transform
Returns
-------
ANTsImage if y is None, else a tuple of ANTsImage types
Examples
--------
>>> import ants
>>> img = ants.image_read(ants.get_data('ch2'))
>>> tx = ants.contrib.RandomZoom3D(zoom_range=(0.8,0.9))
>>> img2 = tx.transform(img)
"""
# random draw in zoom range
zoom_x = np.exp( random.gauss(
np.log( self.zoom_range[0] ),
np.log( self.zoom_range[1] ) ) )
zoom_y = np.exp( random.gauss(
np.log( self.zoom_range[0] ),
np.log( self.zoom_range[1] ) ) )
zoom_z = np.exp( random.gauss(
np.log( self.zoom_range[0] ),
np.log( self.zoom_range[1] ) ) )
self.params = (zoom_x, zoom_y, zoom_z)
tx = Zoom3D((zoom_x,zoom_y,zoom_z),
reference=self.reference,
lazy=self.lazy)
return tx.transform(X,y)
|
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"tx",
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] |
Transform an image using an Affine transform with
zoom parameters randomly generated from the user-specified
range. Return the transform if X=None.
Arguments
---------
X : ANTsImage
Image to transform
y : ANTsImage (optional)
Another image to transform
Returns
-------
ANTsImage if y is None, else a tuple of ANTsImage types
Examples
--------
>>> import ants
>>> img = ants.image_read(ants.get_data('ch2'))
>>> tx = ants.contrib.RandomZoom3D(zoom_range=(0.8,0.9))
>>> img2 = tx.transform(img)
|
[
"Transform",
"an",
"image",
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"Affine",
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"X",
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"None",
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] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/contrib/sampling/affine3d.py#L629-L670
|
237,232
|
ANTsX/ANTsPy
|
ants/contrib/sampling/affine2d.py
|
Translate2D.transform
|
def transform(self, X=None, y=None):
"""
Transform an image using an Affine transform with the given
translation parameters. Return the transform if X=None.
Arguments
---------
X : ANTsImage
Image to transform
y : ANTsImage (optional)
Another image to transform
Returns
-------
ANTsImage if y is None, else a tuple of ANTsImage types
Examples
--------
>>> import ants
>>> img = ants.image_read(ants.get_data('r16'))
>>> tx = ants.contrib.Translate2D(translation=(10,0))
>>> img2_x = tx.transform(img)
>>> tx = ants.contrib.Translate2D(translation=(-10,0)) # other direction
>>> img2_x = tx.transform(img)
>>> tx = ants.contrib.Translate2D(translation=(0,10))
>>> img2_z = tx.transform(img)
>>> tx = ants.contrib.Translate2D(translation=(10,10))
>>> img2 = tx.transform(img)
"""
# convert to radians and unpack
translation_x, translation_y = self.translation
translation_matrix = np.array([[1, 0, translation_x],
[0, 1, translation_y]])
self.tx.set_parameters(translation_matrix)
if self.lazy or X is None:
return self.tx
else:
return self.tx.apply_to_image(X, reference=self.reference)
|
python
|
def transform(self, X=None, y=None):
"""
Transform an image using an Affine transform with the given
translation parameters. Return the transform if X=None.
Arguments
---------
X : ANTsImage
Image to transform
y : ANTsImage (optional)
Another image to transform
Returns
-------
ANTsImage if y is None, else a tuple of ANTsImage types
Examples
--------
>>> import ants
>>> img = ants.image_read(ants.get_data('r16'))
>>> tx = ants.contrib.Translate2D(translation=(10,0))
>>> img2_x = tx.transform(img)
>>> tx = ants.contrib.Translate2D(translation=(-10,0)) # other direction
>>> img2_x = tx.transform(img)
>>> tx = ants.contrib.Translate2D(translation=(0,10))
>>> img2_z = tx.transform(img)
>>> tx = ants.contrib.Translate2D(translation=(10,10))
>>> img2 = tx.transform(img)
"""
# convert to radians and unpack
translation_x, translation_y = self.translation
translation_matrix = np.array([[1, 0, translation_x],
[0, 1, translation_y]])
self.tx.set_parameters(translation_matrix)
if self.lazy or X is None:
return self.tx
else:
return self.tx.apply_to_image(X, reference=self.reference)
|
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"X",
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] |
Transform an image using an Affine transform with the given
translation parameters. Return the transform if X=None.
Arguments
---------
X : ANTsImage
Image to transform
y : ANTsImage (optional)
Another image to transform
Returns
-------
ANTsImage if y is None, else a tuple of ANTsImage types
Examples
--------
>>> import ants
>>> img = ants.image_read(ants.get_data('r16'))
>>> tx = ants.contrib.Translate2D(translation=(10,0))
>>> img2_x = tx.transform(img)
>>> tx = ants.contrib.Translate2D(translation=(-10,0)) # other direction
>>> img2_x = tx.transform(img)
>>> tx = ants.contrib.Translate2D(translation=(0,10))
>>> img2_z = tx.transform(img)
>>> tx = ants.contrib.Translate2D(translation=(10,10))
>>> img2 = tx.transform(img)
|
[
"Transform",
"an",
"image",
"using",
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"Affine",
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"transform",
"if",
"X",
"=",
"None",
"."
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/contrib/sampling/affine2d.py#L62-L101
|
237,233
|
ANTsX/ANTsPy
|
ants/contrib/sampling/affine2d.py
|
RandomTranslate2D.transform
|
def transform(self, X=None, y=None):
"""
Transform an image using an Affine transform with
translation parameters randomly generated from the user-specified
range. Return the transform if X=None.
Arguments
---------
X : ANTsImage
Image to transform
y : ANTsImage (optional)
Another image to transform
Returns
-------
ANTsImage if y is None, else a tuple of ANTsImage types
Examples
--------
>>> import ants
>>> img = ants.image_read(ants.get_data('r16'))
>>> tx = ants.contrib.RandomShear2D(translation_range=(-10,10))
>>> img2 = tx.transform(img)
"""
# random draw in translation range
translation_x = random.gauss(self.translation_range[0], self.translation_range[1])
translation_y = random.gauss(self.translation_range[0], self.translation_range[1])
self.params = (translation_x, translation_y)
tx = Translate2D((translation_x, translation_y),
reference=self.reference,
lazy=self.lazy)
return tx.transform(X,y)
|
python
|
def transform(self, X=None, y=None):
"""
Transform an image using an Affine transform with
translation parameters randomly generated from the user-specified
range. Return the transform if X=None.
Arguments
---------
X : ANTsImage
Image to transform
y : ANTsImage (optional)
Another image to transform
Returns
-------
ANTsImage if y is None, else a tuple of ANTsImage types
Examples
--------
>>> import ants
>>> img = ants.image_read(ants.get_data('r16'))
>>> tx = ants.contrib.RandomShear2D(translation_range=(-10,10))
>>> img2 = tx.transform(img)
"""
# random draw in translation range
translation_x = random.gauss(self.translation_range[0], self.translation_range[1])
translation_y = random.gauss(self.translation_range[0], self.translation_range[1])
self.params = (translation_x, translation_y)
tx = Translate2D((translation_x, translation_y),
reference=self.reference,
lazy=self.lazy)
return tx.transform(X,y)
|
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Transform an image using an Affine transform with
translation parameters randomly generated from the user-specified
range. Return the transform if X=None.
Arguments
---------
X : ANTsImage
Image to transform
y : ANTsImage (optional)
Another image to transform
Returns
-------
ANTsImage if y is None, else a tuple of ANTsImage types
Examples
--------
>>> import ants
>>> img = ants.image_read(ants.get_data('r16'))
>>> tx = ants.contrib.RandomShear2D(translation_range=(-10,10))
>>> img2 = tx.transform(img)
|
[
"Transform",
"an",
"image",
"using",
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"Affine",
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"with",
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"parameters",
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"transform",
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"X",
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"None",
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] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/contrib/sampling/affine2d.py#L141-L175
|
237,234
|
ANTsX/ANTsPy
|
ants/contrib/sampling/affine2d.py
|
Shear2D.transform
|
def transform(self, X=None, y=None):
"""
Transform an image using an Affine transform with the given
shear parameters. Return the transform if X=None.
Arguments
---------
X : ANTsImage
Image to transform
y : ANTsImage (optional)
Another image to transform
Returns
-------
ANTsImage if y is None, else a tuple of ANTsImage types
Examples
--------
>>> import ants
>>> img = ants.image_read(ants.get_data('r16'))
>>> tx = ants.contrib.Shear2D(shear=(10,0,0))
>>> img2_x = tx.transform(img)# x axis stays same
>>> tx = ants.contrib.Shear2D(shear=(-10,0,0)) # other direction
>>> img2_x = tx.transform(img)# x axis stays same
>>> tx = ants.contrib.Shear2D(shear=(0,10,0))
>>> img2_y = tx.transform(img) # y axis stays same
>>> tx = ants.contrib.Shear2D(shear=(0,0,10))
>>> img2_z = tx.transform(img) # z axis stays same
>>> tx = ants.contrib.Shear2D(shear=(10,10,10))
>>> img2 = tx.transform(img)
"""
# convert to radians and unpack
shear = [math.pi / 180 * s for s in self.shear]
shear_x, shear_y = shear
shear_matrix = np.array([[1, shear_x, 0],
[shear_y, 1, 0]])
self.tx.set_parameters(shear_matrix)
if self.lazy or X is None:
return self.tx
else:
return self.tx.apply_to_image(X, reference=self.reference)
|
python
|
def transform(self, X=None, y=None):
"""
Transform an image using an Affine transform with the given
shear parameters. Return the transform if X=None.
Arguments
---------
X : ANTsImage
Image to transform
y : ANTsImage (optional)
Another image to transform
Returns
-------
ANTsImage if y is None, else a tuple of ANTsImage types
Examples
--------
>>> import ants
>>> img = ants.image_read(ants.get_data('r16'))
>>> tx = ants.contrib.Shear2D(shear=(10,0,0))
>>> img2_x = tx.transform(img)# x axis stays same
>>> tx = ants.contrib.Shear2D(shear=(-10,0,0)) # other direction
>>> img2_x = tx.transform(img)# x axis stays same
>>> tx = ants.contrib.Shear2D(shear=(0,10,0))
>>> img2_y = tx.transform(img) # y axis stays same
>>> tx = ants.contrib.Shear2D(shear=(0,0,10))
>>> img2_z = tx.transform(img) # z axis stays same
>>> tx = ants.contrib.Shear2D(shear=(10,10,10))
>>> img2 = tx.transform(img)
"""
# convert to radians and unpack
shear = [math.pi / 180 * s for s in self.shear]
shear_x, shear_y = shear
shear_matrix = np.array([[1, shear_x, 0],
[shear_y, 1, 0]])
self.tx.set_parameters(shear_matrix)
if self.lazy or X is None:
return self.tx
else:
return self.tx.apply_to_image(X, reference=self.reference)
|
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Transform an image using an Affine transform with the given
shear parameters. Return the transform if X=None.
Arguments
---------
X : ANTsImage
Image to transform
y : ANTsImage (optional)
Another image to transform
Returns
-------
ANTsImage if y is None, else a tuple of ANTsImage types
Examples
--------
>>> import ants
>>> img = ants.image_read(ants.get_data('r16'))
>>> tx = ants.contrib.Shear2D(shear=(10,0,0))
>>> img2_x = tx.transform(img)# x axis stays same
>>> tx = ants.contrib.Shear2D(shear=(-10,0,0)) # other direction
>>> img2_x = tx.transform(img)# x axis stays same
>>> tx = ants.contrib.Shear2D(shear=(0,10,0))
>>> img2_y = tx.transform(img) # y axis stays same
>>> tx = ants.contrib.Shear2D(shear=(0,0,10))
>>> img2_z = tx.transform(img) # z axis stays same
>>> tx = ants.contrib.Shear2D(shear=(10,10,10))
>>> img2 = tx.transform(img)
|
[
"Transform",
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"image",
"using",
"an",
"Affine",
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"transform",
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] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/contrib/sampling/affine2d.py#L217-L259
|
237,235
|
ANTsX/ANTsPy
|
ants/contrib/sampling/affine2d.py
|
Zoom2D.transform
|
def transform(self, X=None, y=None):
"""
Transform an image using an Affine transform with the given
zoom parameters. Return the transform if X=None.
Arguments
---------
X : ANTsImage
Image to transform
y : ANTsImage (optional)
Another image to transform
Returns
-------
ANTsImage if y is None, else a tuple of ANTsImage types
Examples
--------
>>> import ants
>>> img = ants.image_read(ants.get_data('r16'))
>>> tx = ants.contrib.Zoom2D(zoom=(0.8,0.8,0.8))
>>> img2 = tx.transform(img)
"""
# unpack zoom range
zoom_x, zoom_y= self.zoom
self.params = (zoom_x, zoom_y)
zoom_matrix = np.array([[zoom_x, 0, 0],
[0, zoom_y, 0]])
self.tx.set_parameters(zoom_matrix)
if self.lazy or X is None:
return self.tx
else:
return self.tx.apply_to_image(X, reference=self.reference)
|
python
|
def transform(self, X=None, y=None):
"""
Transform an image using an Affine transform with the given
zoom parameters. Return the transform if X=None.
Arguments
---------
X : ANTsImage
Image to transform
y : ANTsImage (optional)
Another image to transform
Returns
-------
ANTsImage if y is None, else a tuple of ANTsImage types
Examples
--------
>>> import ants
>>> img = ants.image_read(ants.get_data('r16'))
>>> tx = ants.contrib.Zoom2D(zoom=(0.8,0.8,0.8))
>>> img2 = tx.transform(img)
"""
# unpack zoom range
zoom_x, zoom_y= self.zoom
self.params = (zoom_x, zoom_y)
zoom_matrix = np.array([[zoom_x, 0, 0],
[0, zoom_y, 0]])
self.tx.set_parameters(zoom_matrix)
if self.lazy or X is None:
return self.tx
else:
return self.tx.apply_to_image(X, reference=self.reference)
|
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Transform an image using an Affine transform with the given
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Arguments
---------
X : ANTsImage
Image to transform
y : ANTsImage (optional)
Another image to transform
Returns
-------
ANTsImage if y is None, else a tuple of ANTsImage types
Examples
--------
>>> import ants
>>> img = ants.image_read(ants.get_data('r16'))
>>> tx = ants.contrib.Zoom2D(zoom=(0.8,0.8,0.8))
>>> img2 = tx.transform(img)
|
[
"Transform",
"an",
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"using",
"an",
"Affine",
"transform",
"with",
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"given",
"zoom",
"parameters",
".",
"Return",
"the",
"transform",
"if",
"X",
"=",
"None",
"."
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/contrib/sampling/affine2d.py#L526-L560
|
237,236
|
ANTsX/ANTsPy
|
ants/segmentation/kelly_kapowski.py
|
kelly_kapowski
|
def kelly_kapowski(s, g, w, its=50, r=0.025, m=1.5, **kwargs):
"""
Compute cortical thickness using the DiReCT algorithm.
Diffeomorphic registration-based cortical thickness based on probabilistic
segmentation of an image. This is an optimization algorithm.
Arguments
---------
s : ANTsimage
segmentation image
g : ANTsImage
gray matter probability image
w : ANTsImage
white matter probability image
its : integer
convergence params - controls iterations
r : scalar
gradient descent update parameter
m : scalar
gradient field smoothing parameter
kwargs : keyword arguments
anything else, see KellyKapowski help in ANTs
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> img = ants.image_read( ants.get_ants_data('r16') ,2)
>>> img = ants.resample_image(img, (64,64),1,0)
>>> mask = ants.get_mask( img )
>>> segs = ants.kmeans_segmentation( img, k=3, kmask = mask)
>>> thick = ants.kelly_kapowski(s=segs['segmentation'], g=segs['probabilityimages'][1],
w=segs['probabilityimages'][2], its=45,
r=0.5, m=1)
"""
if isinstance(s, iio.ANTsImage):
s = s.clone('unsigned int')
d = s.dimension
outimg = g.clone()
kellargs = {'d': d,
's': s,
'g': g,
'w': w,
'c': its,
'r': r,
'm': m,
'o': outimg}
for k, v in kwargs.items():
kellargs[k] = v
processed_kellargs = utils._int_antsProcessArguments(kellargs)
libfn = utils.get_lib_fn('KellyKapowski')
libfn(processed_kellargs)
return outimg
|
python
|
def kelly_kapowski(s, g, w, its=50, r=0.025, m=1.5, **kwargs):
"""
Compute cortical thickness using the DiReCT algorithm.
Diffeomorphic registration-based cortical thickness based on probabilistic
segmentation of an image. This is an optimization algorithm.
Arguments
---------
s : ANTsimage
segmentation image
g : ANTsImage
gray matter probability image
w : ANTsImage
white matter probability image
its : integer
convergence params - controls iterations
r : scalar
gradient descent update parameter
m : scalar
gradient field smoothing parameter
kwargs : keyword arguments
anything else, see KellyKapowski help in ANTs
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> img = ants.image_read( ants.get_ants_data('r16') ,2)
>>> img = ants.resample_image(img, (64,64),1,0)
>>> mask = ants.get_mask( img )
>>> segs = ants.kmeans_segmentation( img, k=3, kmask = mask)
>>> thick = ants.kelly_kapowski(s=segs['segmentation'], g=segs['probabilityimages'][1],
w=segs['probabilityimages'][2], its=45,
r=0.5, m=1)
"""
if isinstance(s, iio.ANTsImage):
s = s.clone('unsigned int')
d = s.dimension
outimg = g.clone()
kellargs = {'d': d,
's': s,
'g': g,
'w': w,
'c': its,
'r': r,
'm': m,
'o': outimg}
for k, v in kwargs.items():
kellargs[k] = v
processed_kellargs = utils._int_antsProcessArguments(kellargs)
libfn = utils.get_lib_fn('KellyKapowski')
libfn(processed_kellargs)
return outimg
|
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"(",
"'KellyKapowski'",
")",
"libfn",
"(",
"processed_kellargs",
")",
"return",
"outimg"
] |
Compute cortical thickness using the DiReCT algorithm.
Diffeomorphic registration-based cortical thickness based on probabilistic
segmentation of an image. This is an optimization algorithm.
Arguments
---------
s : ANTsimage
segmentation image
g : ANTsImage
gray matter probability image
w : ANTsImage
white matter probability image
its : integer
convergence params - controls iterations
r : scalar
gradient descent update parameter
m : scalar
gradient field smoothing parameter
kwargs : keyword arguments
anything else, see KellyKapowski help in ANTs
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> img = ants.image_read( ants.get_ants_data('r16') ,2)
>>> img = ants.resample_image(img, (64,64),1,0)
>>> mask = ants.get_mask( img )
>>> segs = ants.kmeans_segmentation( img, k=3, kmask = mask)
>>> thick = ants.kelly_kapowski(s=segs['segmentation'], g=segs['probabilityimages'][1],
w=segs['probabilityimages'][2], its=45,
r=0.5, m=1)
|
[
"Compute",
"cortical",
"thickness",
"using",
"the",
"DiReCT",
"algorithm",
"."
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/segmentation/kelly_kapowski.py#L11-L77
|
237,237
|
ANTsX/ANTsPy
|
ants/core/ants_transform_io.py
|
new_ants_transform
|
def new_ants_transform(precision='float', dimension=3, transform_type='AffineTransform', parameters=None):
"""
Create a new ANTsTransform
ANTsR function: None
Example
-------
>>> import ants
>>> tx = ants.new_ants_transform()
"""
libfn = utils.get_lib_fn('newAntsTransform%s%i' % (utils.short_ptype(precision), dimension))
itk_tx = libfn(precision, dimension, transform_type)
ants_tx = tio.ANTsTransform(precision=precision, dimension=dimension,
transform_type=transform_type, pointer=itk_tx)
if parameters is not None:
ants_tx.set_parameters(parameters)
return ants_tx
|
python
|
def new_ants_transform(precision='float', dimension=3, transform_type='AffineTransform', parameters=None):
"""
Create a new ANTsTransform
ANTsR function: None
Example
-------
>>> import ants
>>> tx = ants.new_ants_transform()
"""
libfn = utils.get_lib_fn('newAntsTransform%s%i' % (utils.short_ptype(precision), dimension))
itk_tx = libfn(precision, dimension, transform_type)
ants_tx = tio.ANTsTransform(precision=precision, dimension=dimension,
transform_type=transform_type, pointer=itk_tx)
if parameters is not None:
ants_tx.set_parameters(parameters)
return ants_tx
|
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".",
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] |
Create a new ANTsTransform
ANTsR function: None
Example
-------
>>> import ants
>>> tx = ants.new_ants_transform()
|
[
"Create",
"a",
"new",
"ANTsTransform"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_transform_io.py#L16-L35
|
237,238
|
ANTsX/ANTsPy
|
ants/core/ants_transform_io.py
|
create_ants_transform
|
def create_ants_transform(transform_type='AffineTransform',
precision='float',
dimension=3,
matrix=None,
offset=None,
center=None,
translation=None,
parameters=None,
fixed_parameters=None,
displacement_field=None,
supported_types=False):
"""
Create and initialize an ANTsTransform
ANTsR function: `createAntsrTransform`
Arguments
---------
transform_type : string
type of transform(s)
precision : string
numerical precision
dimension : integer
spatial dimension of transform
matrix : ndarray
matrix for linear transforms
offset : tuple/list
offset for linear transforms
center : tuple/list
center for linear transforms
translation : tuple/list
translation for linear transforms
parameters : ndarray/list
array of parameters
fixed_parameters : ndarray/list
array of fixed parameters
displacement_field : ANTsImage
multichannel ANTsImage for non-linear transform
supported_types : boolean
flag that returns array of possible transforms types
Returns
-------
ANTsTransform or list of ANTsTransform types
Example
-------
>>> import ants
>>> translation = (3,4,5)
>>> tx = ants.create_ants_transform( type='Euler3DTransform', translation=translation )
"""
def _check_arg(arg, dim=1):
if arg is None:
if dim == 1:
return []
elif dim == 2:
return [[]]
elif isinstance(arg, np.ndarray):
return arg.tolist()
elif isinstance(arg, (tuple, list)):
return list(arg)
else:
raise ValueError('Incompatible input argument')
matrix = _check_arg(matrix, dim=2)
offset = _check_arg(offset)
center = _check_arg(center)
translation = _check_arg(translation)
parameters = _check_arg(parameters)
fixed_parameters = _check_arg(fixed_parameters)
matrix_offset_types = {'AffineTransform', 'CenteredAffineTransform',
'Euler2DTransform', 'Euler3DTransform', 'Rigid3DTransform',
'Rigid2DTransform', 'QuaternionRigidTransform',
'Similarity2DTransform', 'CenteredSimilarity2DTransform',
'Similarity3DTransform', 'CenteredRigid2DTransform',
'CenteredEuler3DTransform'}
#user_matrix_types = {'Affine','CenteredAffine',
# 'Euler', 'CenteredEuler',
# 'Rigid', 'CenteredRigid', 'QuaternionRigid',
# 'Similarity', 'CenteredSimilarity'}
if supported_types:
return set(list(matrix_offset_types) + ['DisplacementFieldTransform'])
# Check for valid dimension
if (dimension < 2) or (dimension > 4):
raise ValueError('Unsupported dimension: %i' % dimension)
# Check for valid precision
precision_types = ('float', 'double')
if precision not in precision_types:
raise ValueError('Unsupported Precision %s' % str(precision))
# Check for supported transform type
if (transform_type not in matrix_offset_types) and (transform_type != 'DisplacementFieldTransform'):
raise ValueError('Unsupported type %s' % str(transform_type))
# Check parameters with type
if (transform_type=='Euler3DTransform'):
dimension = 3
elif (transform_type=='Euler2DTransform'):
dimension = 2
elif (transform_type=='Rigid3DTransform'):
dimension = 3
elif (transform_type=='QuaternionRigidTransform'):
dimension = 3
elif (transform_type=='Rigid2DTransform'):
dimension = 2
elif (transform_type=='CenteredRigid2DTransform'):
dimension = 2
elif (transform_type=='CenteredEuler3DTransform'):
dimension = 3
elif (transform_type=='Similarity3DTransform'):
dimension = 3
elif (transform_type=='Similarity2DTransform'):
dimension = 2
elif (transform_type=='CenteredSimilarity2DTransform'):
dimension = 2
# If displacement field
if displacement_field is not None:
raise ValueError('Displacement field transform not currently supported')
# itk_tx = transform_from_displacement_field(displacement_field)
# return tio.ants_transform(itk_tx)
# Transforms that derive from itk::MatrixOffsetTransformBase
libfn = utils.get_lib_fn('matrixOffset%s%i' % (utils.short_ptype(precision), dimension))
itk_tx = libfn(transform_type,
precision,
dimension,
matrix,
offset,
center,
translation,
parameters,
fixed_parameters)
return tio.ANTsTransform(precision=precision, dimension=dimension,
transform_type=transform_type, pointer=itk_tx)
|
python
|
def create_ants_transform(transform_type='AffineTransform',
precision='float',
dimension=3,
matrix=None,
offset=None,
center=None,
translation=None,
parameters=None,
fixed_parameters=None,
displacement_field=None,
supported_types=False):
"""
Create and initialize an ANTsTransform
ANTsR function: `createAntsrTransform`
Arguments
---------
transform_type : string
type of transform(s)
precision : string
numerical precision
dimension : integer
spatial dimension of transform
matrix : ndarray
matrix for linear transforms
offset : tuple/list
offset for linear transforms
center : tuple/list
center for linear transforms
translation : tuple/list
translation for linear transforms
parameters : ndarray/list
array of parameters
fixed_parameters : ndarray/list
array of fixed parameters
displacement_field : ANTsImage
multichannel ANTsImage for non-linear transform
supported_types : boolean
flag that returns array of possible transforms types
Returns
-------
ANTsTransform or list of ANTsTransform types
Example
-------
>>> import ants
>>> translation = (3,4,5)
>>> tx = ants.create_ants_transform( type='Euler3DTransform', translation=translation )
"""
def _check_arg(arg, dim=1):
if arg is None:
if dim == 1:
return []
elif dim == 2:
return [[]]
elif isinstance(arg, np.ndarray):
return arg.tolist()
elif isinstance(arg, (tuple, list)):
return list(arg)
else:
raise ValueError('Incompatible input argument')
matrix = _check_arg(matrix, dim=2)
offset = _check_arg(offset)
center = _check_arg(center)
translation = _check_arg(translation)
parameters = _check_arg(parameters)
fixed_parameters = _check_arg(fixed_parameters)
matrix_offset_types = {'AffineTransform', 'CenteredAffineTransform',
'Euler2DTransform', 'Euler3DTransform', 'Rigid3DTransform',
'Rigid2DTransform', 'QuaternionRigidTransform',
'Similarity2DTransform', 'CenteredSimilarity2DTransform',
'Similarity3DTransform', 'CenteredRigid2DTransform',
'CenteredEuler3DTransform'}
#user_matrix_types = {'Affine','CenteredAffine',
# 'Euler', 'CenteredEuler',
# 'Rigid', 'CenteredRigid', 'QuaternionRigid',
# 'Similarity', 'CenteredSimilarity'}
if supported_types:
return set(list(matrix_offset_types) + ['DisplacementFieldTransform'])
# Check for valid dimension
if (dimension < 2) or (dimension > 4):
raise ValueError('Unsupported dimension: %i' % dimension)
# Check for valid precision
precision_types = ('float', 'double')
if precision not in precision_types:
raise ValueError('Unsupported Precision %s' % str(precision))
# Check for supported transform type
if (transform_type not in matrix_offset_types) and (transform_type != 'DisplacementFieldTransform'):
raise ValueError('Unsupported type %s' % str(transform_type))
# Check parameters with type
if (transform_type=='Euler3DTransform'):
dimension = 3
elif (transform_type=='Euler2DTransform'):
dimension = 2
elif (transform_type=='Rigid3DTransform'):
dimension = 3
elif (transform_type=='QuaternionRigidTransform'):
dimension = 3
elif (transform_type=='Rigid2DTransform'):
dimension = 2
elif (transform_type=='CenteredRigid2DTransform'):
dimension = 2
elif (transform_type=='CenteredEuler3DTransform'):
dimension = 3
elif (transform_type=='Similarity3DTransform'):
dimension = 3
elif (transform_type=='Similarity2DTransform'):
dimension = 2
elif (transform_type=='CenteredSimilarity2DTransform'):
dimension = 2
# If displacement field
if displacement_field is not None:
raise ValueError('Displacement field transform not currently supported')
# itk_tx = transform_from_displacement_field(displacement_field)
# return tio.ants_transform(itk_tx)
# Transforms that derive from itk::MatrixOffsetTransformBase
libfn = utils.get_lib_fn('matrixOffset%s%i' % (utils.short_ptype(precision), dimension))
itk_tx = libfn(transform_type,
precision,
dimension,
matrix,
offset,
center,
translation,
parameters,
fixed_parameters)
return tio.ANTsTransform(precision=precision, dimension=dimension,
transform_type=transform_type, pointer=itk_tx)
|
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"None",
":",
"raise",
"ValueError",
"(",
"'Displacement field transform not currently supported'",
")",
"# itk_tx = transform_from_displacement_field(displacement_field)",
"# return tio.ants_transform(itk_tx)",
"# Transforms that derive from itk::MatrixOffsetTransformBase",
"libfn",
"=",
"utils",
".",
"get_lib_fn",
"(",
"'matrixOffset%s%i'",
"%",
"(",
"utils",
".",
"short_ptype",
"(",
"precision",
")",
",",
"dimension",
")",
")",
"itk_tx",
"=",
"libfn",
"(",
"transform_type",
",",
"precision",
",",
"dimension",
",",
"matrix",
",",
"offset",
",",
"center",
",",
"translation",
",",
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",",
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"(",
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"precision",
",",
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"=",
"dimension",
",",
"transform_type",
"=",
"transform_type",
",",
"pointer",
"=",
"itk_tx",
")"
] |
Create and initialize an ANTsTransform
ANTsR function: `createAntsrTransform`
Arguments
---------
transform_type : string
type of transform(s)
precision : string
numerical precision
dimension : integer
spatial dimension of transform
matrix : ndarray
matrix for linear transforms
offset : tuple/list
offset for linear transforms
center : tuple/list
center for linear transforms
translation : tuple/list
translation for linear transforms
parameters : ndarray/list
array of parameters
fixed_parameters : ndarray/list
array of fixed parameters
displacement_field : ANTsImage
multichannel ANTsImage for non-linear transform
supported_types : boolean
flag that returns array of possible transforms types
Returns
-------
ANTsTransform or list of ANTsTransform types
Example
-------
>>> import ants
>>> translation = (3,4,5)
>>> tx = ants.create_ants_transform( type='Euler3DTransform', translation=translation )
|
[
"Create",
"and",
"initialize",
"an",
"ANTsTransform"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_transform_io.py#L38-L187
|
237,239
|
ANTsX/ANTsPy
|
ants/core/ants_transform_io.py
|
read_transform
|
def read_transform(filename, dimension=2, precision='float'):
"""
Read a transform from file
ANTsR function: `readAntsrTransform`
Arguments
---------
filename : string
filename of transform
dimension : integer
spatial dimension of transform
precision : string
numerical precision of transform
Returns
-------
ANTsTransform
Example
-------
>>> import ants
>>> tx = ants.new_ants_transform(dimension=2)
>>> tx.set_parameters((0.9,0,0,1.1,10,11))
>>> ants.write_transform(tx, '~/desktop/tx.mat')
>>> tx2 = ants.read_transform('~/desktop/tx.mat')
"""
filename = os.path.expanduser(filename)
if not os.path.exists(filename):
raise ValueError('filename does not exist!')
libfn1 = utils.get_lib_fn('getTransformDimensionFromFile')
dimension = libfn1(filename)
libfn2 = utils.get_lib_fn('getTransformNameFromFile')
transform_type = libfn2(filename)
libfn3 = utils.get_lib_fn('readTransform%s%i' % (utils.short_ptype(precision), dimension))
itk_tx = libfn3(filename, dimension, precision)
return tio.ANTsTransform(precision=precision, dimension=dimension,
transform_type=transform_type, pointer=itk_tx)
|
python
|
def read_transform(filename, dimension=2, precision='float'):
"""
Read a transform from file
ANTsR function: `readAntsrTransform`
Arguments
---------
filename : string
filename of transform
dimension : integer
spatial dimension of transform
precision : string
numerical precision of transform
Returns
-------
ANTsTransform
Example
-------
>>> import ants
>>> tx = ants.new_ants_transform(dimension=2)
>>> tx.set_parameters((0.9,0,0,1.1,10,11))
>>> ants.write_transform(tx, '~/desktop/tx.mat')
>>> tx2 = ants.read_transform('~/desktop/tx.mat')
"""
filename = os.path.expanduser(filename)
if not os.path.exists(filename):
raise ValueError('filename does not exist!')
libfn1 = utils.get_lib_fn('getTransformDimensionFromFile')
dimension = libfn1(filename)
libfn2 = utils.get_lib_fn('getTransformNameFromFile')
transform_type = libfn2(filename)
libfn3 = utils.get_lib_fn('readTransform%s%i' % (utils.short_ptype(precision), dimension))
itk_tx = libfn3(filename, dimension, precision)
return tio.ANTsTransform(precision=precision, dimension=dimension,
transform_type=transform_type, pointer=itk_tx)
|
[
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"=",
"dimension",
",",
"transform_type",
"=",
"transform_type",
",",
"pointer",
"=",
"itk_tx",
")"
] |
Read a transform from file
ANTsR function: `readAntsrTransform`
Arguments
---------
filename : string
filename of transform
dimension : integer
spatial dimension of transform
precision : string
numerical precision of transform
Returns
-------
ANTsTransform
Example
-------
>>> import ants
>>> tx = ants.new_ants_transform(dimension=2)
>>> tx.set_parameters((0.9,0,0,1.1,10,11))
>>> ants.write_transform(tx, '~/desktop/tx.mat')
>>> tx2 = ants.read_transform('~/desktop/tx.mat')
|
[
"Read",
"a",
"transform",
"from",
"file"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_transform_io.py#L223-L266
|
237,240
|
ANTsX/ANTsPy
|
ants/core/ants_transform_io.py
|
write_transform
|
def write_transform(transform, filename):
"""
Write ANTsTransform to file
ANTsR function: `writeAntsrTransform`
Arguments
---------
transform : ANTsTransform
transform to save
filename : string
filename of transform (file extension is ".mat" for affine transforms)
Returns
-------
N/A
Example
-------
>>> import ants
>>> tx = ants.new_ants_transform(dimension=2)
>>> tx.set_parameters((0.9,0,0,1.1,10,11))
>>> ants.write_transform(tx, '~/desktop/tx.mat')
>>> tx2 = ants.read_transform('~/desktop/tx.mat')
"""
filename = os.path.expanduser(filename)
libfn = utils.get_lib_fn('writeTransform%s' % (transform._libsuffix))
libfn(transform.pointer, filename)
|
python
|
def write_transform(transform, filename):
"""
Write ANTsTransform to file
ANTsR function: `writeAntsrTransform`
Arguments
---------
transform : ANTsTransform
transform to save
filename : string
filename of transform (file extension is ".mat" for affine transforms)
Returns
-------
N/A
Example
-------
>>> import ants
>>> tx = ants.new_ants_transform(dimension=2)
>>> tx.set_parameters((0.9,0,0,1.1,10,11))
>>> ants.write_transform(tx, '~/desktop/tx.mat')
>>> tx2 = ants.read_transform('~/desktop/tx.mat')
"""
filename = os.path.expanduser(filename)
libfn = utils.get_lib_fn('writeTransform%s' % (transform._libsuffix))
libfn(transform.pointer, filename)
|
[
"def",
"write_transform",
"(",
"transform",
",",
"filename",
")",
":",
"filename",
"=",
"os",
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"(",
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")",
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"utils",
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"transform",
".",
"_libsuffix",
")",
")",
"libfn",
"(",
"transform",
".",
"pointer",
",",
"filename",
")"
] |
Write ANTsTransform to file
ANTsR function: `writeAntsrTransform`
Arguments
---------
transform : ANTsTransform
transform to save
filename : string
filename of transform (file extension is ".mat" for affine transforms)
Returns
-------
N/A
Example
-------
>>> import ants
>>> tx = ants.new_ants_transform(dimension=2)
>>> tx.set_parameters((0.9,0,0,1.1,10,11))
>>> ants.write_transform(tx, '~/desktop/tx.mat')
>>> tx2 = ants.read_transform('~/desktop/tx.mat')
|
[
"Write",
"ANTsTransform",
"to",
"file"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_transform_io.py#L269-L297
|
237,241
|
ANTsX/ANTsPy
|
ants/registration/reflect_image.py
|
reflect_image
|
def reflect_image(image, axis=None, tx=None, metric='mattes'):
"""
Reflect an image along an axis
ANTsR function: `reflectImage`
Arguments
---------
image : ANTsImage
image to reflect
axis : integer (optional)
which dimension to reflect across, numbered from 0 to imageDimension-1
tx : string (optional)
transformation type to estimate after reflection
metric : string
similarity metric for image registration. see antsRegistration.
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> fi = ants.image_read( ants.get_ants_data('r16'), 'float' )
>>> axis = 2
>>> asym = ants.reflect_image(fi, axis, 'Affine')['warpedmovout']
>>> asym = asym - fi
"""
if axis is None:
axis = image.dimension - 1
if (axis > image.dimension) or (axis < 0):
axis = image.dimension - 1
rflct = mktemp(suffix='.mat')
libfn = utils.get_lib_fn('reflectionMatrix%s'%image._libsuffix)
libfn(image.pointer, axis, rflct)
if tx is not None:
rfi = registration(image, image, type_of_transform=tx,
syn_metric=metric, outprefix=mktemp(),
initial_transform=rflct)
return rfi
else:
return apply_transforms(image, image, rflct)
|
python
|
def reflect_image(image, axis=None, tx=None, metric='mattes'):
"""
Reflect an image along an axis
ANTsR function: `reflectImage`
Arguments
---------
image : ANTsImage
image to reflect
axis : integer (optional)
which dimension to reflect across, numbered from 0 to imageDimension-1
tx : string (optional)
transformation type to estimate after reflection
metric : string
similarity metric for image registration. see antsRegistration.
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> fi = ants.image_read( ants.get_ants_data('r16'), 'float' )
>>> axis = 2
>>> asym = ants.reflect_image(fi, axis, 'Affine')['warpedmovout']
>>> asym = asym - fi
"""
if axis is None:
axis = image.dimension - 1
if (axis > image.dimension) or (axis < 0):
axis = image.dimension - 1
rflct = mktemp(suffix='.mat')
libfn = utils.get_lib_fn('reflectionMatrix%s'%image._libsuffix)
libfn(image.pointer, axis, rflct)
if tx is not None:
rfi = registration(image, image, type_of_transform=tx,
syn_metric=metric, outprefix=mktemp(),
initial_transform=rflct)
return rfi
else:
return apply_transforms(image, image, rflct)
|
[
"def",
"reflect_image",
"(",
"image",
",",
"axis",
"=",
"None",
",",
"tx",
"=",
"None",
",",
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"=",
"'mattes'",
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",",
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"rfi",
"else",
":",
"return",
"apply_transforms",
"(",
"image",
",",
"image",
",",
"rflct",
")"
] |
Reflect an image along an axis
ANTsR function: `reflectImage`
Arguments
---------
image : ANTsImage
image to reflect
axis : integer (optional)
which dimension to reflect across, numbered from 0 to imageDimension-1
tx : string (optional)
transformation type to estimate after reflection
metric : string
similarity metric for image registration. see antsRegistration.
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> fi = ants.image_read( ants.get_ants_data('r16'), 'float' )
>>> axis = 2
>>> asym = ants.reflect_image(fi, axis, 'Affine')['warpedmovout']
>>> asym = asym - fi
|
[
"Reflect",
"an",
"image",
"along",
"an",
"axis"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/registration/reflect_image.py#L12-L61
|
237,242
|
ANTsX/ANTsPy
|
ants/contrib/bids/cohort.py
|
BIDSCohort.create_sampler
|
def create_sampler(self, inputs, targets, input_reader=None, target_reader=None,
input_transform=None, target_transform=None, co_transform=None,
input_return_processor=None, target_return_processor=None, co_return_processor=None):
"""
Create a BIDSSampler that can be used to generate infinite augmented samples
"""
pass
|
python
|
def create_sampler(self, inputs, targets, input_reader=None, target_reader=None,
input_transform=None, target_transform=None, co_transform=None,
input_return_processor=None, target_return_processor=None, co_return_processor=None):
"""
Create a BIDSSampler that can be used to generate infinite augmented samples
"""
pass
|
[
"def",
"create_sampler",
"(",
"self",
",",
"inputs",
",",
"targets",
",",
"input_reader",
"=",
"None",
",",
"target_reader",
"=",
"None",
",",
"input_transform",
"=",
"None",
",",
"target_transform",
"=",
"None",
",",
"co_transform",
"=",
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",",
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",",
"target_return_processor",
"=",
"None",
",",
"co_return_processor",
"=",
"None",
")",
":",
"pass"
] |
Create a BIDSSampler that can be used to generate infinite augmented samples
|
[
"Create",
"a",
"BIDSSampler",
"that",
"can",
"be",
"used",
"to",
"generate",
"infinite",
"augmented",
"samples"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/contrib/bids/cohort.py#L88-L94
|
237,243
|
ANTsX/ANTsPy
|
ants/utils/slice_image.py
|
slice_image
|
def slice_image(image, axis=None, idx=None):
"""
Slice an image.
Example
-------
>>> import ants
>>> mni = ants.image_read(ants.get_data('mni'))
>>> mni2 = ants.slice_image(mni, axis=1, idx=100)
"""
if image.dimension < 3:
raise ValueError('image must have at least 3 dimensions')
inpixeltype = image.pixeltype
ndim = image.dimension
if image.pixeltype != 'float':
image = image.clone('float')
libfn = utils.get_lib_fn('sliceImageF%i' % ndim)
itkimage = libfn(image.pointer, axis, idx)
return iio.ANTsImage(pixeltype='float', dimension=ndim-1,
components=image.components, pointer=itkimage).clone(inpixeltype)
|
python
|
def slice_image(image, axis=None, idx=None):
"""
Slice an image.
Example
-------
>>> import ants
>>> mni = ants.image_read(ants.get_data('mni'))
>>> mni2 = ants.slice_image(mni, axis=1, idx=100)
"""
if image.dimension < 3:
raise ValueError('image must have at least 3 dimensions')
inpixeltype = image.pixeltype
ndim = image.dimension
if image.pixeltype != 'float':
image = image.clone('float')
libfn = utils.get_lib_fn('sliceImageF%i' % ndim)
itkimage = libfn(image.pointer, axis, idx)
return iio.ANTsImage(pixeltype='float', dimension=ndim-1,
components=image.components, pointer=itkimage).clone(inpixeltype)
|
[
"def",
"slice_image",
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",",
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"=",
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")",
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"image",
".",
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".",
"components",
",",
"pointer",
"=",
"itkimage",
")",
".",
"clone",
"(",
"inpixeltype",
")"
] |
Slice an image.
Example
-------
>>> import ants
>>> mni = ants.image_read(ants.get_data('mni'))
>>> mni2 = ants.slice_image(mni, axis=1, idx=100)
|
[
"Slice",
"an",
"image",
"."
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/utils/slice_image.py#L10-L32
|
237,244
|
ANTsX/ANTsPy
|
ants/utils/pad_image.py
|
pad_image
|
def pad_image(image, shape=None, pad_width=None, value=0.0, return_padvals=False):
"""
Pad an image to have the given shape or to be isotropic.
Arguments
---------
image : ANTsImage
image to pad
shape : tuple
- if shape is given, the image will be padded in each dimension
until it has this shape
- if shape is not given, the image will be padded along each
dimension to match the largest existing dimension so that it
has isotropic dimension
pad_width : list of
pad_value : scalar
value with which image will be padded
Example
-------
>>> import ants
>>> img = ants.image_read(ants.get_data('r16'))
>>> img2 = ants.pad_image(img, shape=(300,300))
>>> mni = ants.image_read(ants.get_data('mni'))
>>> mni2 = ants.pad_image(mni)
>>> mni3 = ants.pad_image(mni, pad_width=[(0,4),(0,4),(0,4)])
>>> mni4 = ants.pad_image(mni, pad_width=(4,4,4))
"""
inpixeltype = image.pixeltype
ndim = image.dimension
if image.pixeltype != 'float':
image = image.clone('float')
if pad_width is None:
if shape is None:
shape = [max(image.shape)] * image.dimension
lower_pad_vals = [math.floor(max(ns-os,0)/2) for os,ns in zip(image.shape, shape)]
upper_pad_vals = [math.ceil(max(ns-os,0)/2) for os,ns in zip(image.shape, shape)]
else:
if shape is not None:
raise ValueError('Cannot give both `shape` and `pad_width`. Pick one!')
if len(pad_width) != image.dimension:
raise ValueError('Must give pad width for each image dimension')
lower_pad_vals = []
upper_pad_vals = []
for p in pad_width:
if isinstance(p, (list, tuple)):
lower_pad_vals.append(p[0])
upper_pad_vals.append(p[1])
else:
lower_pad_vals.append(math.floor(p/2))
upper_pad_vals.append(math.ceil(p/2))
libfn = utils.get_lib_fn('padImageF%i' % ndim)
itkimage = libfn(image.pointer, lower_pad_vals, upper_pad_vals, value)
new_image = iio.ANTsImage(pixeltype='float', dimension=ndim,
components=image.components, pointer=itkimage).clone(inpixeltype)
if return_padvals:
return new_image, lower_pad_vals, upper_pad_vals
else:
return new_image
|
python
|
def pad_image(image, shape=None, pad_width=None, value=0.0, return_padvals=False):
"""
Pad an image to have the given shape or to be isotropic.
Arguments
---------
image : ANTsImage
image to pad
shape : tuple
- if shape is given, the image will be padded in each dimension
until it has this shape
- if shape is not given, the image will be padded along each
dimension to match the largest existing dimension so that it
has isotropic dimension
pad_width : list of
pad_value : scalar
value with which image will be padded
Example
-------
>>> import ants
>>> img = ants.image_read(ants.get_data('r16'))
>>> img2 = ants.pad_image(img, shape=(300,300))
>>> mni = ants.image_read(ants.get_data('mni'))
>>> mni2 = ants.pad_image(mni)
>>> mni3 = ants.pad_image(mni, pad_width=[(0,4),(0,4),(0,4)])
>>> mni4 = ants.pad_image(mni, pad_width=(4,4,4))
"""
inpixeltype = image.pixeltype
ndim = image.dimension
if image.pixeltype != 'float':
image = image.clone('float')
if pad_width is None:
if shape is None:
shape = [max(image.shape)] * image.dimension
lower_pad_vals = [math.floor(max(ns-os,0)/2) for os,ns in zip(image.shape, shape)]
upper_pad_vals = [math.ceil(max(ns-os,0)/2) for os,ns in zip(image.shape, shape)]
else:
if shape is not None:
raise ValueError('Cannot give both `shape` and `pad_width`. Pick one!')
if len(pad_width) != image.dimension:
raise ValueError('Must give pad width for each image dimension')
lower_pad_vals = []
upper_pad_vals = []
for p in pad_width:
if isinstance(p, (list, tuple)):
lower_pad_vals.append(p[0])
upper_pad_vals.append(p[1])
else:
lower_pad_vals.append(math.floor(p/2))
upper_pad_vals.append(math.ceil(p/2))
libfn = utils.get_lib_fn('padImageF%i' % ndim)
itkimage = libfn(image.pointer, lower_pad_vals, upper_pad_vals, value)
new_image = iio.ANTsImage(pixeltype='float', dimension=ndim,
components=image.components, pointer=itkimage).clone(inpixeltype)
if return_padvals:
return new_image, lower_pad_vals, upper_pad_vals
else:
return new_image
|
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"def",
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"ceil",
"(",
"p",
"/",
"2",
")",
")",
"libfn",
"=",
"utils",
".",
"get_lib_fn",
"(",
"'padImageF%i'",
"%",
"ndim",
")",
"itkimage",
"=",
"libfn",
"(",
"image",
".",
"pointer",
",",
"lower_pad_vals",
",",
"upper_pad_vals",
",",
"value",
")",
"new_image",
"=",
"iio",
".",
"ANTsImage",
"(",
"pixeltype",
"=",
"'float'",
",",
"dimension",
"=",
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",",
"components",
"=",
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"components",
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"return",
"new_image",
",",
"lower_pad_vals",
",",
"upper_pad_vals",
"else",
":",
"return",
"new_image"
] |
Pad an image to have the given shape or to be isotropic.
Arguments
---------
image : ANTsImage
image to pad
shape : tuple
- if shape is given, the image will be padded in each dimension
until it has this shape
- if shape is not given, the image will be padded along each
dimension to match the largest existing dimension so that it
has isotropic dimension
pad_width : list of
pad_value : scalar
value with which image will be padded
Example
-------
>>> import ants
>>> img = ants.image_read(ants.get_data('r16'))
>>> img2 = ants.pad_image(img, shape=(300,300))
>>> mni = ants.image_read(ants.get_data('mni'))
>>> mni2 = ants.pad_image(mni)
>>> mni3 = ants.pad_image(mni, pad_width=[(0,4),(0,4),(0,4)])
>>> mni4 = ants.pad_image(mni, pad_width=(4,4,4))
|
[
"Pad",
"an",
"image",
"to",
"have",
"the",
"given",
"shape",
"or",
"to",
"be",
"isotropic",
"."
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/utils/pad_image.py#L10-L75
|
237,245
|
ANTsX/ANTsPy
|
ants/core/ants_metric.py
|
ANTsImageToImageMetric.set_fixed_image
|
def set_fixed_image(self, image):
"""
Set Fixed ANTsImage for metric
"""
if not isinstance(image, iio.ANTsImage):
raise ValueError('image must be ANTsImage type')
if image.dimension != self.dimension:
raise ValueError('image dim (%i) does not match metric dim (%i)' % (image.dimension, self.dimension))
self._metric.setFixedImage(image.pointer, False)
self.fixed_image = image
|
python
|
def set_fixed_image(self, image):
"""
Set Fixed ANTsImage for metric
"""
if not isinstance(image, iio.ANTsImage):
raise ValueError('image must be ANTsImage type')
if image.dimension != self.dimension:
raise ValueError('image dim (%i) does not match metric dim (%i)' % (image.dimension, self.dimension))
self._metric.setFixedImage(image.pointer, False)
self.fixed_image = image
|
[
"def",
"set_fixed_image",
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"(",
"image",
".",
"pointer",
",",
"False",
")",
"self",
".",
"fixed_image",
"=",
"image"
] |
Set Fixed ANTsImage for metric
|
[
"Set",
"Fixed",
"ANTsImage",
"for",
"metric"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_metric.py#L48-L59
|
237,246
|
ANTsX/ANTsPy
|
ants/core/ants_metric.py
|
ANTsImageToImageMetric.set_moving_image
|
def set_moving_image(self, image):
"""
Set Moving ANTsImage for metric
"""
if not isinstance(image, iio.ANTsImage):
raise ValueError('image must be ANTsImage type')
if image.dimension != self.dimension:
raise ValueError('image dim (%i) does not match metric dim (%i)' % (image.dimension, self.dimension))
self._metric.setMovingImage(image.pointer, False)
self.moving_image = image
|
python
|
def set_moving_image(self, image):
"""
Set Moving ANTsImage for metric
"""
if not isinstance(image, iio.ANTsImage):
raise ValueError('image must be ANTsImage type')
if image.dimension != self.dimension:
raise ValueError('image dim (%i) does not match metric dim (%i)' % (image.dimension, self.dimension))
self._metric.setMovingImage(image.pointer, False)
self.moving_image = image
|
[
"def",
"set_moving_image",
"(",
"self",
",",
"image",
")",
":",
"if",
"not",
"isinstance",
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"(",
"image",
".",
"pointer",
",",
"False",
")",
"self",
".",
"moving_image",
"=",
"image"
] |
Set Moving ANTsImage for metric
|
[
"Set",
"Moving",
"ANTsImage",
"for",
"metric"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/core/ants_metric.py#L74-L85
|
237,247
|
ANTsX/ANTsPy
|
ants/utils/image_to_cluster_images.py
|
image_to_cluster_images
|
def image_to_cluster_images(image, min_cluster_size=50, min_thresh=1e-06, max_thresh=1):
"""
Converts an image to several independent images.
Produces a unique image for each connected
component 1 through N of size > min_cluster_size
ANTsR function: `image2ClusterImages`
Arguments
---------
image : ANTsImage
input image
min_cluster_size : integer
throw away clusters smaller than this value
min_thresh : scalar
threshold to a statistical map
max_thresh : scalar
threshold to a statistical map
Returns
-------
list of ANTsImage types
Example
-------
>>> import ants
>>> image = ants.image_read(ants.get_ants_data('r16'))
>>> image = ants.threshold_image(image, 1, 1e15)
>>> image_cluster_list = ants.image_to_cluster_images(image)
"""
if not isinstance(image, iio.ANTsImage):
raise ValueError('image must be ANTsImage type')
clust = label_clusters(image, min_cluster_size, min_thresh, max_thresh)
labs = np.unique(clust[clust > 0])
clustlist = []
for i in range(len(labs)):
labimage = image.clone()
labimage[clust != labs[i]] = 0
clustlist.append(labimage)
return clustlist
|
python
|
def image_to_cluster_images(image, min_cluster_size=50, min_thresh=1e-06, max_thresh=1):
"""
Converts an image to several independent images.
Produces a unique image for each connected
component 1 through N of size > min_cluster_size
ANTsR function: `image2ClusterImages`
Arguments
---------
image : ANTsImage
input image
min_cluster_size : integer
throw away clusters smaller than this value
min_thresh : scalar
threshold to a statistical map
max_thresh : scalar
threshold to a statistical map
Returns
-------
list of ANTsImage types
Example
-------
>>> import ants
>>> image = ants.image_read(ants.get_ants_data('r16'))
>>> image = ants.threshold_image(image, 1, 1e15)
>>> image_cluster_list = ants.image_to_cluster_images(image)
"""
if not isinstance(image, iio.ANTsImage):
raise ValueError('image must be ANTsImage type')
clust = label_clusters(image, min_cluster_size, min_thresh, max_thresh)
labs = np.unique(clust[clust > 0])
clustlist = []
for i in range(len(labs)):
labimage = image.clone()
labimage[clust != labs[i]] = 0
clustlist.append(labimage)
return clustlist
|
[
"def",
"image_to_cluster_images",
"(",
"image",
",",
"min_cluster_size",
"=",
"50",
",",
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",",
"max_thresh",
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"image",
",",
"min_cluster_size",
",",
"min_thresh",
",",
"max_thresh",
")",
"labs",
"=",
"np",
".",
"unique",
"(",
"clust",
"[",
"clust",
">",
"0",
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"clustlist",
"=",
"[",
"]",
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"in",
"range",
"(",
"len",
"(",
"labs",
")",
")",
":",
"labimage",
"=",
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"labimage",
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"clust",
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"labs",
"[",
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"]",
"]",
"=",
"0",
"clustlist",
".",
"append",
"(",
"labimage",
")",
"return",
"clustlist"
] |
Converts an image to several independent images.
Produces a unique image for each connected
component 1 through N of size > min_cluster_size
ANTsR function: `image2ClusterImages`
Arguments
---------
image : ANTsImage
input image
min_cluster_size : integer
throw away clusters smaller than this value
min_thresh : scalar
threshold to a statistical map
max_thresh : scalar
threshold to a statistical map
Returns
-------
list of ANTsImage types
Example
-------
>>> import ants
>>> image = ants.image_read(ants.get_ants_data('r16'))
>>> image = ants.threshold_image(image, 1, 1e15)
>>> image_cluster_list = ants.image_to_cluster_images(image)
|
[
"Converts",
"an",
"image",
"to",
"several",
"independent",
"images",
"."
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/utils/image_to_cluster_images.py#L9-L51
|
237,248
|
ANTsX/ANTsPy
|
ants/utils/threshold_image.py
|
threshold_image
|
def threshold_image(image, low_thresh=None, high_thresh=None, inval=1, outval=0, binary=True):
"""
Converts a scalar image into a binary image by thresholding operations
ANTsR function: `thresholdImage`
Arguments
---------
image : ANTsImage
Input image to operate on
low_thresh : scalar (optional)
Lower edge of threshold window
hight_thresh : scalar (optional)
Higher edge of threshold window
inval : scalar
Output value for image voxels in between lothresh and hithresh
outval : scalar
Output value for image voxels lower than lothresh or higher than hithresh
binary : boolean
if true, returns binary thresholded image
if false, return binary thresholded image multiplied by original image
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> image = ants.image_read( ants.get_ants_data('r16') )
>>> timage = ants.threshold_image(image, 0.5, 1e15)
"""
if high_thresh is None:
high_thresh = image.max() + 0.01
if low_thresh is None:
low_thresh = image.min() - 0.01
dim = image.dimension
outimage = image.clone()
args = [dim, image, outimage, low_thresh, high_thresh, inval, outval]
processed_args = _int_antsProcessArguments(args)
libfn = utils.get_lib_fn('ThresholdImage')
libfn(processed_args)
if binary:
return outimage
else:
return outimage*image
|
python
|
def threshold_image(image, low_thresh=None, high_thresh=None, inval=1, outval=0, binary=True):
"""
Converts a scalar image into a binary image by thresholding operations
ANTsR function: `thresholdImage`
Arguments
---------
image : ANTsImage
Input image to operate on
low_thresh : scalar (optional)
Lower edge of threshold window
hight_thresh : scalar (optional)
Higher edge of threshold window
inval : scalar
Output value for image voxels in between lothresh and hithresh
outval : scalar
Output value for image voxels lower than lothresh or higher than hithresh
binary : boolean
if true, returns binary thresholded image
if false, return binary thresholded image multiplied by original image
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> image = ants.image_read( ants.get_ants_data('r16') )
>>> timage = ants.threshold_image(image, 0.5, 1e15)
"""
if high_thresh is None:
high_thresh = image.max() + 0.01
if low_thresh is None:
low_thresh = image.min() - 0.01
dim = image.dimension
outimage = image.clone()
args = [dim, image, outimage, low_thresh, high_thresh, inval, outval]
processed_args = _int_antsProcessArguments(args)
libfn = utils.get_lib_fn('ThresholdImage')
libfn(processed_args)
if binary:
return outimage
else:
return outimage*image
|
[
"def",
"threshold_image",
"(",
"image",
",",
"low_thresh",
"=",
"None",
",",
"high_thresh",
"=",
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",",
"inval",
"=",
"1",
",",
"outval",
"=",
"0",
",",
"binary",
"=",
"True",
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",",
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",",
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",",
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"]",
"processed_args",
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"get_lib_fn",
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"'ThresholdImage'",
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"libfn",
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"processed_args",
")",
"if",
"binary",
":",
"return",
"outimage",
"else",
":",
"return",
"outimage",
"*",
"image"
] |
Converts a scalar image into a binary image by thresholding operations
ANTsR function: `thresholdImage`
Arguments
---------
image : ANTsImage
Input image to operate on
low_thresh : scalar (optional)
Lower edge of threshold window
hight_thresh : scalar (optional)
Higher edge of threshold window
inval : scalar
Output value for image voxels in between lothresh and hithresh
outval : scalar
Output value for image voxels lower than lothresh or higher than hithresh
binary : boolean
if true, returns binary thresholded image
if false, return binary thresholded image multiplied by original image
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> image = ants.image_read( ants.get_ants_data('r16') )
>>> timage = ants.threshold_image(image, 0.5, 1e15)
|
[
"Converts",
"a",
"scalar",
"image",
"into",
"a",
"binary",
"image",
"by",
"thresholding",
"operations"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/utils/threshold_image.py#L10-L60
|
237,249
|
ANTsX/ANTsPy
|
ants/registration/symmetrize_image.py
|
symmetrize_image
|
def symmetrize_image(image):
"""
Use registration and reflection to make an image symmetric
ANTsR function: N/A
Arguments
---------
image : ANTsImage
image to make symmetric
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> image = ants.image_read( ants.get_ants_data('r16') , 'float')
>>> simage = ants.symimage(image)
"""
imager = reflect_image(image, axis=0)
imageavg = imager * 0.5 + image
for i in range(5):
w1 = registration(imageavg, image, type_of_transform='SyN')
w2 = registration(imageavg, imager, type_of_transform='SyN')
xavg = w1['warpedmovout']*0.5 + w2['warpedmovout']*0.5
nada1 = apply_transforms(image, image, w1['fwdtransforms'], compose=w1['fwdtransforms'][0])
nada2 = apply_transforms(image, image, w2['fwdtransforms'], compose=w2['fwdtransforms'][0])
wavg = (iio.image_read(nada1) + iio.image_read(nada2)) * (-0.5)
wavgfn = mktemp(suffix='.nii.gz')
iio.image_write(wavg, wavgfn)
xavg = apply_transforms(image, imageavg, wavgfn)
return xavg
|
python
|
def symmetrize_image(image):
"""
Use registration and reflection to make an image symmetric
ANTsR function: N/A
Arguments
---------
image : ANTsImage
image to make symmetric
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> image = ants.image_read( ants.get_ants_data('r16') , 'float')
>>> simage = ants.symimage(image)
"""
imager = reflect_image(image, axis=0)
imageavg = imager * 0.5 + image
for i in range(5):
w1 = registration(imageavg, image, type_of_transform='SyN')
w2 = registration(imageavg, imager, type_of_transform='SyN')
xavg = w1['warpedmovout']*0.5 + w2['warpedmovout']*0.5
nada1 = apply_transforms(image, image, w1['fwdtransforms'], compose=w1['fwdtransforms'][0])
nada2 = apply_transforms(image, image, w2['fwdtransforms'], compose=w2['fwdtransforms'][0])
wavg = (iio.image_read(nada1) + iio.image_read(nada2)) * (-0.5)
wavgfn = mktemp(suffix='.nii.gz')
iio.image_write(wavg, wavgfn)
xavg = apply_transforms(image, imageavg, wavgfn)
return xavg
|
[
"def",
"symmetrize_image",
"(",
"image",
")",
":",
"imager",
"=",
"reflect_image",
"(",
"image",
",",
"axis",
"=",
"0",
")",
"imageavg",
"=",
"imager",
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"+",
"image",
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"range",
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"5",
")",
":",
"w1",
"=",
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"imageavg",
",",
"image",
",",
"type_of_transform",
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"'SyN'",
")",
"w2",
"=",
"registration",
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"imageavg",
",",
"imager",
",",
"type_of_transform",
"=",
"'SyN'",
")",
"xavg",
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"w1",
"[",
"'warpedmovout'",
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"*",
"0.5",
"+",
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"'warpedmovout'",
"]",
"*",
"0.5",
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"apply_transforms",
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",",
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",",
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",",
"compose",
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"apply_transforms",
"(",
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",",
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",",
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"]",
",",
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"'fwdtransforms'",
"]",
"[",
"0",
"]",
")",
"wavg",
"=",
"(",
"iio",
".",
"image_read",
"(",
"nada1",
")",
"+",
"iio",
".",
"image_read",
"(",
"nada2",
")",
")",
"*",
"(",
"-",
"0.5",
")",
"wavgfn",
"=",
"mktemp",
"(",
"suffix",
"=",
"'.nii.gz'",
")",
"iio",
".",
"image_write",
"(",
"wavg",
",",
"wavgfn",
")",
"xavg",
"=",
"apply_transforms",
"(",
"image",
",",
"imageavg",
",",
"wavgfn",
")",
"return",
"xavg"
] |
Use registration and reflection to make an image symmetric
ANTsR function: N/A
Arguments
---------
image : ANTsImage
image to make symmetric
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> image = ants.image_read( ants.get_ants_data('r16') , 'float')
>>> simage = ants.symimage(image)
|
[
"Use",
"registration",
"and",
"reflection",
"to",
"make",
"an",
"image",
"symmetric"
] |
638020af2cdfc5ff4bdb9809ffe67aa505727a3b
|
https://github.com/ANTsX/ANTsPy/blob/638020af2cdfc5ff4bdb9809ffe67aa505727a3b/ants/registration/symmetrize_image.py#L13-L49
|
237,250
|
freakboy3742/pyxero
|
xero/basemanager.py
|
BaseManager._get_attachments
|
def _get_attachments(self, id):
"""Retrieve a list of attachments associated with this Xero object."""
uri = '/'.join([self.base_url, self.name, id, 'Attachments']) + '/'
return uri, {}, 'get', None, None, False
|
python
|
def _get_attachments(self, id):
"""Retrieve a list of attachments associated with this Xero object."""
uri = '/'.join([self.base_url, self.name, id, 'Attachments']) + '/'
return uri, {}, 'get', None, None, False
|
[
"def",
"_get_attachments",
"(",
"self",
",",
"id",
")",
":",
"uri",
"=",
"'/'",
".",
"join",
"(",
"[",
"self",
".",
"base_url",
",",
"self",
".",
"name",
",",
"id",
",",
"'Attachments'",
"]",
")",
"+",
"'/'",
"return",
"uri",
",",
"{",
"}",
",",
"'get'",
",",
"None",
",",
"None",
",",
"False"
] |
Retrieve a list of attachments associated with this Xero object.
|
[
"Retrieve",
"a",
"list",
"of",
"attachments",
"associated",
"with",
"this",
"Xero",
"object",
"."
] |
5566f17fa06ed1f2fb9426c112951a72276b0f9a
|
https://github.com/freakboy3742/pyxero/blob/5566f17fa06ed1f2fb9426c112951a72276b0f9a/xero/basemanager.py#L240-L243
|
237,251
|
freakboy3742/pyxero
|
xero/basemanager.py
|
BaseManager._put_attachment_data
|
def _put_attachment_data(self, id, filename, data, content_type, include_online=False):
"""Upload an attachment to the Xero object."""
uri = '/'.join([self.base_url, self.name, id, 'Attachments', filename])
params = {'IncludeOnline': 'true'} if include_online else {}
headers = {'Content-Type': content_type, 'Content-Length': str(len(data))}
return uri, params, 'put', data, headers, False
|
python
|
def _put_attachment_data(self, id, filename, data, content_type, include_online=False):
"""Upload an attachment to the Xero object."""
uri = '/'.join([self.base_url, self.name, id, 'Attachments', filename])
params = {'IncludeOnline': 'true'} if include_online else {}
headers = {'Content-Type': content_type, 'Content-Length': str(len(data))}
return uri, params, 'put', data, headers, False
|
[
"def",
"_put_attachment_data",
"(",
"self",
",",
"id",
",",
"filename",
",",
"data",
",",
"content_type",
",",
"include_online",
"=",
"False",
")",
":",
"uri",
"=",
"'/'",
".",
"join",
"(",
"[",
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",",
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",",
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"}",
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"}",
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"'Content-Length'",
":",
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"data",
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")",
"}",
"return",
"uri",
",",
"params",
",",
"'put'",
",",
"data",
",",
"headers",
",",
"False"
] |
Upload an attachment to the Xero object.
|
[
"Upload",
"an",
"attachment",
"to",
"the",
"Xero",
"object",
"."
] |
5566f17fa06ed1f2fb9426c112951a72276b0f9a
|
https://github.com/freakboy3742/pyxero/blob/5566f17fa06ed1f2fb9426c112951a72276b0f9a/xero/basemanager.py#L280-L285
|
237,252
|
freakboy3742/pyxero
|
examples/partner_oauth_flow/runserver.py
|
PartnerCredentialsHandler.page_response
|
def page_response(self, title='', body=''):
"""
Helper to render an html page with dynamic content
"""
f = StringIO()
f.write('<!DOCTYPE html>\n')
f.write('<html>\n')
f.write('<head><title>{}</title><head>\n'.format(title))
f.write('<body>\n<h2>{}</h2>\n'.format(title))
f.write('<div class="content">{}</div>\n'.format(body))
f.write('</body>\n</html>\n')
length = f.tell()
f.seek(0)
self.send_response(200)
encoding = sys.getfilesystemencoding()
self.send_header("Content-type", "text/html; charset=%s" % encoding)
self.send_header("Content-Length", str(length))
self.end_headers()
self.copyfile(f, self.wfile)
f.close()
|
python
|
def page_response(self, title='', body=''):
"""
Helper to render an html page with dynamic content
"""
f = StringIO()
f.write('<!DOCTYPE html>\n')
f.write('<html>\n')
f.write('<head><title>{}</title><head>\n'.format(title))
f.write('<body>\n<h2>{}</h2>\n'.format(title))
f.write('<div class="content">{}</div>\n'.format(body))
f.write('</body>\n</html>\n')
length = f.tell()
f.seek(0)
self.send_response(200)
encoding = sys.getfilesystemencoding()
self.send_header("Content-type", "text/html; charset=%s" % encoding)
self.send_header("Content-Length", str(length))
self.end_headers()
self.copyfile(f, self.wfile)
f.close()
|
[
"def",
"page_response",
"(",
"self",
",",
"title",
"=",
"''",
",",
"body",
"=",
"''",
")",
":",
"f",
"=",
"StringIO",
"(",
")",
"f",
".",
"write",
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"'<!DOCTYPE html>\\n'",
")",
"f",
".",
"write",
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"200",
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".",
"getfilesystemencoding",
"(",
")",
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"send_header",
"(",
"\"Content-type\"",
",",
"\"text/html; charset=%s\"",
"%",
"encoding",
")",
"self",
".",
"send_header",
"(",
"\"Content-Length\"",
",",
"str",
"(",
"length",
")",
")",
"self",
".",
"end_headers",
"(",
")",
"self",
".",
"copyfile",
"(",
"f",
",",
"self",
".",
"wfile",
")",
"f",
".",
"close",
"(",
")"
] |
Helper to render an html page with dynamic content
|
[
"Helper",
"to",
"render",
"an",
"html",
"page",
"with",
"dynamic",
"content"
] |
5566f17fa06ed1f2fb9426c112951a72276b0f9a
|
https://github.com/freakboy3742/pyxero/blob/5566f17fa06ed1f2fb9426c112951a72276b0f9a/examples/partner_oauth_flow/runserver.py#L22-L41
|
237,253
|
freakboy3742/pyxero
|
examples/partner_oauth_flow/runserver.py
|
PartnerCredentialsHandler.redirect_response
|
def redirect_response(self, url, permanent=False):
"""
Generate redirect response
"""
if permanent:
self.send_response(301)
else:
self.send_response(302)
self.send_header("Location", url)
self.end_headers()
|
python
|
def redirect_response(self, url, permanent=False):
"""
Generate redirect response
"""
if permanent:
self.send_response(301)
else:
self.send_response(302)
self.send_header("Location", url)
self.end_headers()
|
[
"def",
"redirect_response",
"(",
"self",
",",
"url",
",",
"permanent",
"=",
"False",
")",
":",
"if",
"permanent",
":",
"self",
".",
"send_response",
"(",
"301",
")",
"else",
":",
"self",
".",
"send_response",
"(",
"302",
")",
"self",
".",
"send_header",
"(",
"\"Location\"",
",",
"url",
")",
"self",
".",
"end_headers",
"(",
")"
] |
Generate redirect response
|
[
"Generate",
"redirect",
"response"
] |
5566f17fa06ed1f2fb9426c112951a72276b0f9a
|
https://github.com/freakboy3742/pyxero/blob/5566f17fa06ed1f2fb9426c112951a72276b0f9a/examples/partner_oauth_flow/runserver.py#L43-L52
|
237,254
|
freakboy3742/pyxero
|
xero/auth.py
|
PublicCredentials._init_credentials
|
def _init_credentials(self, oauth_token, oauth_token_secret):
"Depending on the state passed in, get self._oauth up and running"
if oauth_token and oauth_token_secret:
if self.verified:
# If provided, this is a fully verified set of
# credentials. Store the oauth_token and secret
# and initialize OAuth around those
self._init_oauth(oauth_token, oauth_token_secret)
else:
# If provided, we are reconstructing an initalized
# (but non-verified) set of public credentials.
self.oauth_token = oauth_token
self.oauth_token_secret = oauth_token_secret
else:
# This is a brand new set of credentials - we need to generate
# an oauth token so it's available for the url property.
oauth = OAuth1(
self.consumer_key,
client_secret=self.consumer_secret,
callback_uri=self.callback_uri,
rsa_key=self.rsa_key,
signature_method=self._signature_method
)
url = self.base_url + REQUEST_TOKEN_URL
headers = {'User-Agent': self.user_agent}
response = requests.post(url=url, headers=headers, auth=oauth)
self._process_oauth_response(response)
|
python
|
def _init_credentials(self, oauth_token, oauth_token_secret):
"Depending on the state passed in, get self._oauth up and running"
if oauth_token and oauth_token_secret:
if self.verified:
# If provided, this is a fully verified set of
# credentials. Store the oauth_token and secret
# and initialize OAuth around those
self._init_oauth(oauth_token, oauth_token_secret)
else:
# If provided, we are reconstructing an initalized
# (but non-verified) set of public credentials.
self.oauth_token = oauth_token
self.oauth_token_secret = oauth_token_secret
else:
# This is a brand new set of credentials - we need to generate
# an oauth token so it's available for the url property.
oauth = OAuth1(
self.consumer_key,
client_secret=self.consumer_secret,
callback_uri=self.callback_uri,
rsa_key=self.rsa_key,
signature_method=self._signature_method
)
url = self.base_url + REQUEST_TOKEN_URL
headers = {'User-Agent': self.user_agent}
response = requests.post(url=url, headers=headers, auth=oauth)
self._process_oauth_response(response)
|
[
"def",
"_init_credentials",
"(",
"self",
",",
"oauth_token",
",",
"oauth_token_secret",
")",
":",
"if",
"oauth_token",
"and",
"oauth_token_secret",
":",
"if",
"self",
".",
"verified",
":",
"# If provided, this is a fully verified set of",
"# credentials. Store the oauth_token and secret",
"# and initialize OAuth around those",
"self",
".",
"_init_oauth",
"(",
"oauth_token",
",",
"oauth_token_secret",
")",
"else",
":",
"# If provided, we are reconstructing an initalized",
"# (but non-verified) set of public credentials.",
"self",
".",
"oauth_token",
"=",
"oauth_token",
"self",
".",
"oauth_token_secret",
"=",
"oauth_token_secret",
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"# This is a brand new set of credentials - we need to generate",
"# an oauth token so it's available for the url property.",
"oauth",
"=",
"OAuth1",
"(",
"self",
".",
"consumer_key",
",",
"client_secret",
"=",
"self",
".",
"consumer_secret",
",",
"callback_uri",
"=",
"self",
".",
"callback_uri",
",",
"rsa_key",
"=",
"self",
".",
"rsa_key",
",",
"signature_method",
"=",
"self",
".",
"_signature_method",
")",
"url",
"=",
"self",
".",
"base_url",
"+",
"REQUEST_TOKEN_URL",
"headers",
"=",
"{",
"'User-Agent'",
":",
"self",
".",
"user_agent",
"}",
"response",
"=",
"requests",
".",
"post",
"(",
"url",
"=",
"url",
",",
"headers",
"=",
"headers",
",",
"auth",
"=",
"oauth",
")",
"self",
".",
"_process_oauth_response",
"(",
"response",
")"
] |
Depending on the state passed in, get self._oauth up and running
|
[
"Depending",
"on",
"the",
"state",
"passed",
"in",
"get",
"self",
".",
"_oauth",
"up",
"and",
"running"
] |
5566f17fa06ed1f2fb9426c112951a72276b0f9a
|
https://github.com/freakboy3742/pyxero/blob/5566f17fa06ed1f2fb9426c112951a72276b0f9a/xero/auth.py#L134-L163
|
237,255
|
freakboy3742/pyxero
|
xero/auth.py
|
PublicCredentials._init_oauth
|
def _init_oauth(self, oauth_token, oauth_token_secret):
"Store and initialize a verified set of OAuth credentials"
self.oauth_token = oauth_token
self.oauth_token_secret = oauth_token_secret
self._oauth = OAuth1(
self.consumer_key,
client_secret=self.consumer_secret,
resource_owner_key=self.oauth_token,
resource_owner_secret=self.oauth_token_secret,
rsa_key=self.rsa_key,
signature_method=self._signature_method
)
|
python
|
def _init_oauth(self, oauth_token, oauth_token_secret):
"Store and initialize a verified set of OAuth credentials"
self.oauth_token = oauth_token
self.oauth_token_secret = oauth_token_secret
self._oauth = OAuth1(
self.consumer_key,
client_secret=self.consumer_secret,
resource_owner_key=self.oauth_token,
resource_owner_secret=self.oauth_token_secret,
rsa_key=self.rsa_key,
signature_method=self._signature_method
)
|
[
"def",
"_init_oauth",
"(",
"self",
",",
"oauth_token",
",",
"oauth_token_secret",
")",
":",
"self",
".",
"oauth_token",
"=",
"oauth_token",
"self",
".",
"oauth_token_secret",
"=",
"oauth_token_secret",
"self",
".",
"_oauth",
"=",
"OAuth1",
"(",
"self",
".",
"consumer_key",
",",
"client_secret",
"=",
"self",
".",
"consumer_secret",
",",
"resource_owner_key",
"=",
"self",
".",
"oauth_token",
",",
"resource_owner_secret",
"=",
"self",
".",
"oauth_token_secret",
",",
"rsa_key",
"=",
"self",
".",
"rsa_key",
",",
"signature_method",
"=",
"self",
".",
"_signature_method",
")"
] |
Store and initialize a verified set of OAuth credentials
|
[
"Store",
"and",
"initialize",
"a",
"verified",
"set",
"of",
"OAuth",
"credentials"
] |
5566f17fa06ed1f2fb9426c112951a72276b0f9a
|
https://github.com/freakboy3742/pyxero/blob/5566f17fa06ed1f2fb9426c112951a72276b0f9a/xero/auth.py#L165-L177
|
237,256
|
freakboy3742/pyxero
|
xero/auth.py
|
PublicCredentials._process_oauth_response
|
def _process_oauth_response(self, response):
"Extracts the fields from an oauth response"
if response.status_code == 200:
credentials = parse_qs(response.text)
# Initialize the oauth credentials
self._init_oauth(
credentials.get('oauth_token')[0],
credentials.get('oauth_token_secret')[0]
)
# If tokens are refreshable, we'll get a session handle
self.oauth_session_handle = credentials.get(
'oauth_session_handle', [None])[0]
# Calculate token/auth expiry
oauth_expires_in = credentials.get(
'oauth_expires_in',
[OAUTH_EXPIRY_SECONDS])[0]
oauth_authorisation_expires_in = credentials.get(
'oauth_authorization_expires_in',
[OAUTH_EXPIRY_SECONDS])[0]
self.oauth_expires_at = datetime.datetime.now() + \
datetime.timedelta(seconds=int(
oauth_expires_in))
self.oauth_authorization_expires_at = \
datetime.datetime.now() + \
datetime.timedelta(seconds=int(
oauth_authorisation_expires_in))
else:
self._handle_error_response(response)
|
python
|
def _process_oauth_response(self, response):
"Extracts the fields from an oauth response"
if response.status_code == 200:
credentials = parse_qs(response.text)
# Initialize the oauth credentials
self._init_oauth(
credentials.get('oauth_token')[0],
credentials.get('oauth_token_secret')[0]
)
# If tokens are refreshable, we'll get a session handle
self.oauth_session_handle = credentials.get(
'oauth_session_handle', [None])[0]
# Calculate token/auth expiry
oauth_expires_in = credentials.get(
'oauth_expires_in',
[OAUTH_EXPIRY_SECONDS])[0]
oauth_authorisation_expires_in = credentials.get(
'oauth_authorization_expires_in',
[OAUTH_EXPIRY_SECONDS])[0]
self.oauth_expires_at = datetime.datetime.now() + \
datetime.timedelta(seconds=int(
oauth_expires_in))
self.oauth_authorization_expires_at = \
datetime.datetime.now() + \
datetime.timedelta(seconds=int(
oauth_authorisation_expires_in))
else:
self._handle_error_response(response)
|
[
"def",
"_process_oauth_response",
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"self",
",",
"response",
")",
":",
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"response",
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"status_code",
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"credentials",
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"parse_qs",
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"text",
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"# Initialize the oauth credentials",
"self",
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"get",
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"get",
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"0",
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"# If tokens are refreshable, we'll get a session handle",
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"+",
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")",
")",
"else",
":",
"self",
".",
"_handle_error_response",
"(",
"response",
")"
] |
Extracts the fields from an oauth response
|
[
"Extracts",
"the",
"fields",
"from",
"an",
"oauth",
"response"
] |
5566f17fa06ed1f2fb9426c112951a72276b0f9a
|
https://github.com/freakboy3742/pyxero/blob/5566f17fa06ed1f2fb9426c112951a72276b0f9a/xero/auth.py#L179-L210
|
237,257
|
freakboy3742/pyxero
|
xero/auth.py
|
PublicCredentials.state
|
def state(self):
"""Obtain the useful state of this credentials object so that
we can reconstruct it independently.
"""
return dict(
(attr, getattr(self, attr))
for attr in (
'consumer_key', 'consumer_secret', 'callback_uri',
'verified', 'oauth_token', 'oauth_token_secret',
'oauth_session_handle', 'oauth_expires_at',
'oauth_authorization_expires_at', 'scope'
)
if getattr(self, attr) is not None
)
|
python
|
def state(self):
"""Obtain the useful state of this credentials object so that
we can reconstruct it independently.
"""
return dict(
(attr, getattr(self, attr))
for attr in (
'consumer_key', 'consumer_secret', 'callback_uri',
'verified', 'oauth_token', 'oauth_token_secret',
'oauth_session_handle', 'oauth_expires_at',
'oauth_authorization_expires_at', 'scope'
)
if getattr(self, attr) is not None
)
|
[
"def",
"state",
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"self",
")",
":",
"return",
"dict",
"(",
"(",
"attr",
",",
"getattr",
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"'callback_uri'",
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"'oauth_token'",
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",",
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"if",
"getattr",
"(",
"self",
",",
"attr",
")",
"is",
"not",
"None",
")"
] |
Obtain the useful state of this credentials object so that
we can reconstruct it independently.
|
[
"Obtain",
"the",
"useful",
"state",
"of",
"this",
"credentials",
"object",
"so",
"that",
"we",
"can",
"reconstruct",
"it",
"independently",
"."
] |
5566f17fa06ed1f2fb9426c112951a72276b0f9a
|
https://github.com/freakboy3742/pyxero/blob/5566f17fa06ed1f2fb9426c112951a72276b0f9a/xero/auth.py#L245-L258
|
237,258
|
freakboy3742/pyxero
|
xero/auth.py
|
PublicCredentials.verify
|
def verify(self, verifier):
"Verify an OAuth token"
# Construct the credentials for the verification request
oauth = OAuth1(
self.consumer_key,
client_secret=self.consumer_secret,
resource_owner_key=self.oauth_token,
resource_owner_secret=self.oauth_token_secret,
verifier=verifier,
rsa_key=self.rsa_key,
signature_method=self._signature_method
)
# Make the verification request, gettiung back an access token
url = self.base_url + ACCESS_TOKEN_URL
headers = {'User-Agent': self.user_agent}
response = requests.post(url=url, headers=headers, auth=oauth)
self._process_oauth_response(response)
self.verified = True
|
python
|
def verify(self, verifier):
"Verify an OAuth token"
# Construct the credentials for the verification request
oauth = OAuth1(
self.consumer_key,
client_secret=self.consumer_secret,
resource_owner_key=self.oauth_token,
resource_owner_secret=self.oauth_token_secret,
verifier=verifier,
rsa_key=self.rsa_key,
signature_method=self._signature_method
)
# Make the verification request, gettiung back an access token
url = self.base_url + ACCESS_TOKEN_URL
headers = {'User-Agent': self.user_agent}
response = requests.post(url=url, headers=headers, auth=oauth)
self._process_oauth_response(response)
self.verified = True
|
[
"def",
"verify",
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"self",
",",
"verifier",
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":",
"# Construct the credentials for the verification request",
"oauth",
"=",
"OAuth1",
"(",
"self",
".",
"consumer_key",
",",
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"consumer_secret",
",",
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"resource_owner_secret",
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"oauth_token_secret",
",",
"verifier",
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"verifier",
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"url",
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"self",
".",
"base_url",
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"ACCESS_TOKEN_URL",
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"=",
"{",
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"user_agent",
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"response",
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"post",
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"url",
"=",
"url",
",",
"headers",
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"headers",
",",
"auth",
"=",
"oauth",
")",
"self",
".",
"_process_oauth_response",
"(",
"response",
")",
"self",
".",
"verified",
"=",
"True"
] |
Verify an OAuth token
|
[
"Verify",
"an",
"OAuth",
"token"
] |
5566f17fa06ed1f2fb9426c112951a72276b0f9a
|
https://github.com/freakboy3742/pyxero/blob/5566f17fa06ed1f2fb9426c112951a72276b0f9a/xero/auth.py#L260-L279
|
237,259
|
freakboy3742/pyxero
|
xero/auth.py
|
PublicCredentials.url
|
def url(self):
"Returns the URL that can be visited to obtain a verifier code"
# The authorize url is always api.xero.com
query_string = {'oauth_token': self.oauth_token}
if self.scope:
query_string['scope'] = self.scope
url = XERO_BASE_URL + AUTHORIZE_URL + '?' + \
urlencode(query_string)
return url
|
python
|
def url(self):
"Returns the URL that can be visited to obtain a verifier code"
# The authorize url is always api.xero.com
query_string = {'oauth_token': self.oauth_token}
if self.scope:
query_string['scope'] = self.scope
url = XERO_BASE_URL + AUTHORIZE_URL + '?' + \
urlencode(query_string)
return url
|
[
"def",
"url",
"(",
"self",
")",
":",
"# The authorize url is always api.xero.com",
"query_string",
"=",
"{",
"'oauth_token'",
":",
"self",
".",
"oauth_token",
"}",
"if",
"self",
".",
"scope",
":",
"query_string",
"[",
"'scope'",
"]",
"=",
"self",
".",
"scope",
"url",
"=",
"XERO_BASE_URL",
"+",
"AUTHORIZE_URL",
"+",
"'?'",
"+",
"urlencode",
"(",
"query_string",
")",
"return",
"url"
] |
Returns the URL that can be visited to obtain a verifier code
|
[
"Returns",
"the",
"URL",
"that",
"can",
"be",
"visited",
"to",
"obtain",
"a",
"verifier",
"code"
] |
5566f17fa06ed1f2fb9426c112951a72276b0f9a
|
https://github.com/freakboy3742/pyxero/blob/5566f17fa06ed1f2fb9426c112951a72276b0f9a/xero/auth.py#L282-L292
|
237,260
|
freakboy3742/pyxero
|
xero/auth.py
|
PartnerCredentials.refresh
|
def refresh(self):
"Refresh an expired token"
# Construct the credentials for the verification request
oauth = OAuth1(
self.consumer_key,
client_secret=self.consumer_secret,
resource_owner_key=self.oauth_token,
resource_owner_secret=self.oauth_token_secret,
rsa_key=self.rsa_key,
signature_method=self._signature_method
)
# Make the verification request, getting back an access token
headers = {'User-Agent': self.user_agent}
params = {'oauth_session_handle': self.oauth_session_handle}
response = requests.post(url=self.base_url + ACCESS_TOKEN_URL,
params=params, headers=headers, auth=oauth)
self._process_oauth_response(response)
|
python
|
def refresh(self):
"Refresh an expired token"
# Construct the credentials for the verification request
oauth = OAuth1(
self.consumer_key,
client_secret=self.consumer_secret,
resource_owner_key=self.oauth_token,
resource_owner_secret=self.oauth_token_secret,
rsa_key=self.rsa_key,
signature_method=self._signature_method
)
# Make the verification request, getting back an access token
headers = {'User-Agent': self.user_agent}
params = {'oauth_session_handle': self.oauth_session_handle}
response = requests.post(url=self.base_url + ACCESS_TOKEN_URL,
params=params, headers=headers, auth=oauth)
self._process_oauth_response(response)
|
[
"def",
"refresh",
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"self",
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":",
"# Construct the credentials for the verification request",
"oauth",
"=",
"OAuth1",
"(",
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".",
"consumer_key",
",",
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"resource_owner_key",
"=",
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"oauth_token",
",",
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"=",
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"oauth_token_secret",
",",
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"=",
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"headers",
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"user_agent",
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"params",
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"}",
"response",
"=",
"requests",
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"post",
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"url",
"=",
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"base_url",
"+",
"ACCESS_TOKEN_URL",
",",
"params",
"=",
"params",
",",
"headers",
"=",
"headers",
",",
"auth",
"=",
"oauth",
")",
"self",
".",
"_process_oauth_response",
"(",
"response",
")"
] |
Refresh an expired token
|
[
"Refresh",
"an",
"expired",
"token"
] |
5566f17fa06ed1f2fb9426c112951a72276b0f9a
|
https://github.com/freakboy3742/pyxero/blob/5566f17fa06ed1f2fb9426c112951a72276b0f9a/xero/auth.py#L375-L393
|
237,261
|
freakboy3742/pyxero
|
xero/filesmanager.py
|
FilesManager._get_files
|
def _get_files(self, folderId):
"""Retrieve the list of files contained in a folder"""
uri = '/'.join([self.base_url, self.name, folderId, 'Files'])
return uri, {}, 'get', None, None, False, None
|
python
|
def _get_files(self, folderId):
"""Retrieve the list of files contained in a folder"""
uri = '/'.join([self.base_url, self.name, folderId, 'Files'])
return uri, {}, 'get', None, None, False, None
|
[
"def",
"_get_files",
"(",
"self",
",",
"folderId",
")",
":",
"uri",
"=",
"'/'",
".",
"join",
"(",
"[",
"self",
".",
"base_url",
",",
"self",
".",
"name",
",",
"folderId",
",",
"'Files'",
"]",
")",
"return",
"uri",
",",
"{",
"}",
",",
"'get'",
",",
"None",
",",
"None",
",",
"False",
",",
"None"
] |
Retrieve the list of files contained in a folder
|
[
"Retrieve",
"the",
"list",
"of",
"files",
"contained",
"in",
"a",
"folder"
] |
5566f17fa06ed1f2fb9426c112951a72276b0f9a
|
https://github.com/freakboy3742/pyxero/blob/5566f17fa06ed1f2fb9426c112951a72276b0f9a/xero/filesmanager.py#L118-L121
|
237,262
|
dmulcahey/zha-device-handlers
|
zhaquirks/hivehome/__init__.py
|
MotionCluster.handle_cluster_request
|
def handle_cluster_request(self, tsn, command_id, args):
"""Handle the cluster command."""
if command_id == 0:
if self._timer_handle:
self._timer_handle.cancel()
loop = asyncio.get_event_loop()
self._timer_handle = loop.call_later(30, self._turn_off)
|
python
|
def handle_cluster_request(self, tsn, command_id, args):
"""Handle the cluster command."""
if command_id == 0:
if self._timer_handle:
self._timer_handle.cancel()
loop = asyncio.get_event_loop()
self._timer_handle = loop.call_later(30, self._turn_off)
|
[
"def",
"handle_cluster_request",
"(",
"self",
",",
"tsn",
",",
"command_id",
",",
"args",
")",
":",
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"command_id",
"==",
"0",
":",
"if",
"self",
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"_timer_handle",
":",
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"_timer_handle",
".",
"cancel",
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"loop",
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"asyncio",
".",
"get_event_loop",
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")",
"self",
".",
"_timer_handle",
"=",
"loop",
".",
"call_later",
"(",
"30",
",",
"self",
".",
"_turn_off",
")"
] |
Handle the cluster command.
|
[
"Handle",
"the",
"cluster",
"command",
"."
] |
bab2a53724c6fb5caee2e796dd46ebcb45400f93
|
https://github.com/dmulcahey/zha-device-handlers/blob/bab2a53724c6fb5caee2e796dd46ebcb45400f93/zhaquirks/hivehome/__init__.py#L21-L27
|
237,263
|
dmulcahey/zha-device-handlers
|
zhaquirks/xiaomi/__init__.py
|
BasicCluster._parse_attributes
|
def _parse_attributes(self, value):
"""Parse non standard atrributes."""
from zigpy.zcl import foundation as f
attributes = {}
attribute_names = {
1: BATTERY_VOLTAGE_MV,
3: TEMPERATURE,
4: XIAOMI_ATTR_4,
5: XIAOMI_ATTR_5,
6: XIAOMI_ATTR_6,
10: PATH
}
result = {}
while value:
skey = int(value[0])
svalue, value = f.TypeValue.deserialize(value[1:])
result[skey] = svalue.value
for item, value in result.items():
key = attribute_names[item] \
if item in attribute_names else "0xff01-" + str(item)
attributes[key] = value
if BATTERY_VOLTAGE_MV in attributes:
attributes[BATTERY_LEVEL] = int(
self._calculate_remaining_battery_percentage(
attributes[BATTERY_VOLTAGE_MV]
)
)
return attributes
|
python
|
def _parse_attributes(self, value):
"""Parse non standard atrributes."""
from zigpy.zcl import foundation as f
attributes = {}
attribute_names = {
1: BATTERY_VOLTAGE_MV,
3: TEMPERATURE,
4: XIAOMI_ATTR_4,
5: XIAOMI_ATTR_5,
6: XIAOMI_ATTR_6,
10: PATH
}
result = {}
while value:
skey = int(value[0])
svalue, value = f.TypeValue.deserialize(value[1:])
result[skey] = svalue.value
for item, value in result.items():
key = attribute_names[item] \
if item in attribute_names else "0xff01-" + str(item)
attributes[key] = value
if BATTERY_VOLTAGE_MV in attributes:
attributes[BATTERY_LEVEL] = int(
self._calculate_remaining_battery_percentage(
attributes[BATTERY_VOLTAGE_MV]
)
)
return attributes
|
[
"def",
"_parse_attributes",
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"self",
",",
"value",
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"from",
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".",
"zcl",
"import",
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":",
"attributes",
"[",
"BATTERY_LEVEL",
"]",
"=",
"int",
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"self",
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"_calculate_remaining_battery_percentage",
"(",
"attributes",
"[",
"BATTERY_VOLTAGE_MV",
"]",
")",
")",
"return",
"attributes"
] |
Parse non standard atrributes.
|
[
"Parse",
"non",
"standard",
"atrributes",
"."
] |
bab2a53724c6fb5caee2e796dd46ebcb45400f93
|
https://github.com/dmulcahey/zha-device-handlers/blob/bab2a53724c6fb5caee2e796dd46ebcb45400f93/zhaquirks/xiaomi/__init__.py#L64-L91
|
237,264
|
dmulcahey/zha-device-handlers
|
zhaquirks/xiaomi/__init__.py
|
BasicCluster._calculate_remaining_battery_percentage
|
def _calculate_remaining_battery_percentage(self, voltage):
"""Calculate percentage."""
min_voltage = 2500
max_voltage = 3000
percent = (voltage - min_voltage) / (max_voltage - min_voltage) * 200
return min(200, percent)
|
python
|
def _calculate_remaining_battery_percentage(self, voltage):
"""Calculate percentage."""
min_voltage = 2500
max_voltage = 3000
percent = (voltage - min_voltage) / (max_voltage - min_voltage) * 200
return min(200, percent)
|
[
"def",
"_calculate_remaining_battery_percentage",
"(",
"self",
",",
"voltage",
")",
":",
"min_voltage",
"=",
"2500",
"max_voltage",
"=",
"3000",
"percent",
"=",
"(",
"voltage",
"-",
"min_voltage",
")",
"/",
"(",
"max_voltage",
"-",
"min_voltage",
")",
"*",
"200",
"return",
"min",
"(",
"200",
",",
"percent",
")"
] |
Calculate percentage.
|
[
"Calculate",
"percentage",
"."
] |
bab2a53724c6fb5caee2e796dd46ebcb45400f93
|
https://github.com/dmulcahey/zha-device-handlers/blob/bab2a53724c6fb5caee2e796dd46ebcb45400f93/zhaquirks/xiaomi/__init__.py#L93-L98
|
237,265
|
dmulcahey/zha-device-handlers
|
zhaquirks/xiaomi/__init__.py
|
PowerConfigurationCluster.battery_reported
|
def battery_reported(self, voltage, rawVoltage):
"""Battery reported."""
self._update_attribute(BATTERY_PERCENTAGE_REMAINING, voltage)
self._update_attribute(self.BATTERY_VOLTAGE_ATTR,
int(rawVoltage / 100))
|
python
|
def battery_reported(self, voltage, rawVoltage):
"""Battery reported."""
self._update_attribute(BATTERY_PERCENTAGE_REMAINING, voltage)
self._update_attribute(self.BATTERY_VOLTAGE_ATTR,
int(rawVoltage / 100))
|
[
"def",
"battery_reported",
"(",
"self",
",",
"voltage",
",",
"rawVoltage",
")",
":",
"self",
".",
"_update_attribute",
"(",
"BATTERY_PERCENTAGE_REMAINING",
",",
"voltage",
")",
"self",
".",
"_update_attribute",
"(",
"self",
".",
"BATTERY_VOLTAGE_ATTR",
",",
"int",
"(",
"rawVoltage",
"/",
"100",
")",
")"
] |
Battery reported.
|
[
"Battery",
"reported",
"."
] |
bab2a53724c6fb5caee2e796dd46ebcb45400f93
|
https://github.com/dmulcahey/zha-device-handlers/blob/bab2a53724c6fb5caee2e796dd46ebcb45400f93/zhaquirks/xiaomi/__init__.py#L122-L126
|
237,266
|
dmulcahey/zha-device-handlers
|
zhaquirks/smartthings/tag_v4.py
|
FastPollingPowerConfigurationCluster.configure_reporting
|
async def configure_reporting(self, attribute, min_interval,
max_interval, reportable_change):
"""Configure reporting."""
result = await super().configure_reporting(
PowerConfigurationCluster.BATTERY_VOLTAGE_ATTR,
self.FREQUENCY,
self.FREQUENCY,
self.MINIMUM_CHANGE
)
return result
|
python
|
async def configure_reporting(self, attribute, min_interval,
max_interval, reportable_change):
"""Configure reporting."""
result = await super().configure_reporting(
PowerConfigurationCluster.BATTERY_VOLTAGE_ATTR,
self.FREQUENCY,
self.FREQUENCY,
self.MINIMUM_CHANGE
)
return result
|
[
"async",
"def",
"configure_reporting",
"(",
"self",
",",
"attribute",
",",
"min_interval",
",",
"max_interval",
",",
"reportable_change",
")",
":",
"result",
"=",
"await",
"super",
"(",
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".",
"configure_reporting",
"(",
"PowerConfigurationCluster",
".",
"BATTERY_VOLTAGE_ATTR",
",",
"self",
".",
"FREQUENCY",
",",
"self",
".",
"FREQUENCY",
",",
"self",
".",
"MINIMUM_CHANGE",
")",
"return",
"result"
] |
Configure reporting.
|
[
"Configure",
"reporting",
"."
] |
bab2a53724c6fb5caee2e796dd46ebcb45400f93
|
https://github.com/dmulcahey/zha-device-handlers/blob/bab2a53724c6fb5caee2e796dd46ebcb45400f93/zhaquirks/smartthings/tag_v4.py#L23-L32
|
237,267
|
F5Networks/f5-common-python
|
f5/bigip/tm/sys/folder.py
|
Folder.update
|
def update(self, **kwargs):
'''Update the object, removing device group if inherited
If inheritedDevicegroup is the string "true" we need to remove
deviceGroup from the args before we update or we get the
following error:
The floating traffic-group: /Common/traffic-group-1 can only be set on
/testfolder if its device-group is inherited from the root folder
'''
inherit_device_group = self.__dict__.get('inheritedDevicegroup', False)
if inherit_device_group == 'true':
self.__dict__.pop('deviceGroup')
return self._update(**kwargs)
|
python
|
def update(self, **kwargs):
'''Update the object, removing device group if inherited
If inheritedDevicegroup is the string "true" we need to remove
deviceGroup from the args before we update or we get the
following error:
The floating traffic-group: /Common/traffic-group-1 can only be set on
/testfolder if its device-group is inherited from the root folder
'''
inherit_device_group = self.__dict__.get('inheritedDevicegroup', False)
if inherit_device_group == 'true':
self.__dict__.pop('deviceGroup')
return self._update(**kwargs)
|
[
"def",
"update",
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"self",
",",
"*",
"*",
"kwargs",
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":",
"inherit_device_group",
"=",
"self",
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"__dict__",
".",
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"'inheritedDevicegroup'",
",",
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"pop",
"(",
"'deviceGroup'",
")",
"return",
"self",
".",
"_update",
"(",
"*",
"*",
"kwargs",
")"
] |
Update the object, removing device group if inherited
If inheritedDevicegroup is the string "true" we need to remove
deviceGroup from the args before we update or we get the
following error:
The floating traffic-group: /Common/traffic-group-1 can only be set on
/testfolder if its device-group is inherited from the root folder
|
[
"Update",
"the",
"object",
"removing",
"device",
"group",
"if",
"inherited"
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/bigip/tm/sys/folder.py#L90-L103
|
237,268
|
F5Networks/f5-common-python
|
f5/bigip/tm/cm/device_group.py
|
Device_Group.sync_to
|
def sync_to(self):
"""Wrapper method that synchronizes configuration to DG.
Executes the containing object's cm :meth:`~f5.bigip.cm.Cm.exec_cmd`
method to sync the configuration TO the device-group.
:note:: Both sync_to, and sync_from methods are convenience
methods which usually are not what this SDK offers.
It is best to execute config-sync with the use of
exec_cmd() method on the cm endpoint.
"""
device_group_collection = self._meta_data['container']
cm = device_group_collection._meta_data['container']
sync_cmd = 'config-sync to-group %s' % self.name
cm.exec_cmd('run', utilCmdArgs=sync_cmd)
|
python
|
def sync_to(self):
"""Wrapper method that synchronizes configuration to DG.
Executes the containing object's cm :meth:`~f5.bigip.cm.Cm.exec_cmd`
method to sync the configuration TO the device-group.
:note:: Both sync_to, and sync_from methods are convenience
methods which usually are not what this SDK offers.
It is best to execute config-sync with the use of
exec_cmd() method on the cm endpoint.
"""
device_group_collection = self._meta_data['container']
cm = device_group_collection._meta_data['container']
sync_cmd = 'config-sync to-group %s' % self.name
cm.exec_cmd('run', utilCmdArgs=sync_cmd)
|
[
"def",
"sync_to",
"(",
"self",
")",
":",
"device_group_collection",
"=",
"self",
".",
"_meta_data",
"[",
"'container'",
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"cm",
"=",
"device_group_collection",
".",
"_meta_data",
"[",
"'container'",
"]",
"sync_cmd",
"=",
"'config-sync to-group %s'",
"%",
"self",
".",
"name",
"cm",
".",
"exec_cmd",
"(",
"'run'",
",",
"utilCmdArgs",
"=",
"sync_cmd",
")"
] |
Wrapper method that synchronizes configuration to DG.
Executes the containing object's cm :meth:`~f5.bigip.cm.Cm.exec_cmd`
method to sync the configuration TO the device-group.
:note:: Both sync_to, and sync_from methods are convenience
methods which usually are not what this SDK offers.
It is best to execute config-sync with the use of
exec_cmd() method on the cm endpoint.
|
[
"Wrapper",
"method",
"that",
"synchronizes",
"configuration",
"to",
"DG",
"."
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/bigip/tm/cm/device_group.py#L62-L77
|
237,269
|
F5Networks/f5-common-python
|
f5/bigip/tm/sys/application.py
|
Service._create
|
def _create(self, **kwargs):
'''Create service on device and create accompanying Python object.
:params kwargs: keyword arguments passed in from create call
:raises: HTTPError
:returns: Python Service object
'''
try:
return super(Service, self)._create(**kwargs)
except HTTPError as ex:
if "The configuration was updated successfully but could not be " \
"retrieved" not in ex.response.text:
raise
# BIG-IP® will create in Common partition if none is given.
# In order to create the uri properly in this class's load,
# drop in Common as the partition in kwargs.
if 'partition' not in kwargs:
kwargs['partition'] = 'Common'
# Pop all but the necessary load kwargs from the kwargs given to
# create. Otherwise, load may fail.
kwargs_copy = kwargs.copy()
for key in kwargs_copy:
if key not in self._meta_data['required_load_parameters']:
kwargs.pop(key)
# If response was created successfully, do a local_update.
# If not, call to overridden _load method via load
return self.load(**kwargs)
|
python
|
def _create(self, **kwargs):
'''Create service on device and create accompanying Python object.
:params kwargs: keyword arguments passed in from create call
:raises: HTTPError
:returns: Python Service object
'''
try:
return super(Service, self)._create(**kwargs)
except HTTPError as ex:
if "The configuration was updated successfully but could not be " \
"retrieved" not in ex.response.text:
raise
# BIG-IP® will create in Common partition if none is given.
# In order to create the uri properly in this class's load,
# drop in Common as the partition in kwargs.
if 'partition' not in kwargs:
kwargs['partition'] = 'Common'
# Pop all but the necessary load kwargs from the kwargs given to
# create. Otherwise, load may fail.
kwargs_copy = kwargs.copy()
for key in kwargs_copy:
if key not in self._meta_data['required_load_parameters']:
kwargs.pop(key)
# If response was created successfully, do a local_update.
# If not, call to overridden _load method via load
return self.load(**kwargs)
|
[
"def",
"_create",
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"self",
",",
"*",
"*",
"kwargs",
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"try",
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"return",
"super",
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",",
"self",
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".",
"_create",
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"\"retrieved\"",
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"raise",
"# BIG-IP® will create in Common partition if none is given.",
"# In order to create the uri properly in this class's load,",
"# drop in Common as the partition in kwargs.",
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"key",
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"# If response was created successfully, do a local_update.",
"# If not, call to overridden _load method via load",
"return",
"self",
".",
"load",
"(",
"*",
"*",
"kwargs",
")"
] |
Create service on device and create accompanying Python object.
:params kwargs: keyword arguments passed in from create call
:raises: HTTPError
:returns: Python Service object
|
[
"Create",
"service",
"on",
"device",
"and",
"create",
"accompanying",
"Python",
"object",
"."
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/bigip/tm/sys/application.py#L105-L133
|
237,270
|
F5Networks/f5-common-python
|
f5/bigip/tm/sys/application.py
|
Service._build_service_uri
|
def _build_service_uri(self, base_uri, partition, name):
'''Build the proper uri for a service resource.
This follows the scheme:
<base_uri>/~<partition>~<<name>.app>~<name>
:param base_uri: str -- base uri for container
:param partition: str -- partition for this service
:param name: str -- name of the service
:returns: str -- uri to access this service
'''
name = name.replace('/', '~')
return '%s~%s~%s.app~%s' % (base_uri, partition, name, name)
|
python
|
def _build_service_uri(self, base_uri, partition, name):
'''Build the proper uri for a service resource.
This follows the scheme:
<base_uri>/~<partition>~<<name>.app>~<name>
:param base_uri: str -- base uri for container
:param partition: str -- partition for this service
:param name: str -- name of the service
:returns: str -- uri to access this service
'''
name = name.replace('/', '~')
return '%s~%s~%s.app~%s' % (base_uri, partition, name, name)
|
[
"def",
"_build_service_uri",
"(",
"self",
",",
"base_uri",
",",
"partition",
",",
"name",
")",
":",
"name",
"=",
"name",
".",
"replace",
"(",
"'/'",
",",
"'~'",
")",
"return",
"'%s~%s~%s.app~%s'",
"%",
"(",
"base_uri",
",",
"partition",
",",
"name",
",",
"name",
")"
] |
Build the proper uri for a service resource.
This follows the scheme:
<base_uri>/~<partition>~<<name>.app>~<name>
:param base_uri: str -- base uri for container
:param partition: str -- partition for this service
:param name: str -- name of the service
:returns: str -- uri to access this service
|
[
"Build",
"the",
"proper",
"uri",
"for",
"a",
"service",
"resource",
"."
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/bigip/tm/sys/application.py#L168-L180
|
237,271
|
F5Networks/f5-common-python
|
f5/bigiq/cm/device/licensing/pool/utility.py
|
Members.delete
|
def delete(self, **kwargs):
"""Deletes a member from a license pool
You need to be careful with this method. When you use it, and it
succeeds on the remote BIG-IP, the configuration of the BIG-IP
will be reloaded. During this process, you will not be able to
access the REST interface.
This method overrides the Resource class's method because it requires
that extra json kwargs be supplied. This is not a behavior that is
part of the normal Resource class's delete method.
:param kwargs:
:return:
"""
if 'id' not in kwargs:
# BIG-IQ requires that you provide the ID of the members to revoke
# a license from. This ID is already part of the deletion URL though.
# Therefore, if you do not provide it, we enumerate it for you.
delete_uri = self._meta_data['uri']
if delete_uri.endswith('/'):
delete_uri = delete_uri[0:-1]
kwargs['id'] = os.path.basename(delete_uri)
uid = uuid.UUID(kwargs['id'], version=4)
if uid.hex != kwargs['id'].replace('-', ''):
raise F5SDKError(
"The specified ID is invalid"
)
requests_params = self._handle_requests_params(kwargs)
kwargs = self._check_for_python_keywords(kwargs)
kwargs = self._prepare_request_json(kwargs)
delete_uri = self._meta_data['uri']
session = self._meta_data['bigip']._meta_data['icr_session']
# Check the generation for match before delete
force = self._check_force_arg(kwargs.pop('force', True))
if not force:
self._check_generation()
response = session.delete(delete_uri, json=kwargs, **requests_params)
if response.status_code == 200:
self.__dict__ = {'deleted': True}
# This sleep is necessary to prevent BIG-IQ from being able to remove
# a license. It happens in certain cases that assignments can be revoked
# (and license deletion started) too quickly. Therefore, we must introduce
# an artificial delay here to prevent revoking from returning before
# BIG-IQ would be ready to remove the license.
time.sleep(1)
|
python
|
def delete(self, **kwargs):
"""Deletes a member from a license pool
You need to be careful with this method. When you use it, and it
succeeds on the remote BIG-IP, the configuration of the BIG-IP
will be reloaded. During this process, you will not be able to
access the REST interface.
This method overrides the Resource class's method because it requires
that extra json kwargs be supplied. This is not a behavior that is
part of the normal Resource class's delete method.
:param kwargs:
:return:
"""
if 'id' not in kwargs:
# BIG-IQ requires that you provide the ID of the members to revoke
# a license from. This ID is already part of the deletion URL though.
# Therefore, if you do not provide it, we enumerate it for you.
delete_uri = self._meta_data['uri']
if delete_uri.endswith('/'):
delete_uri = delete_uri[0:-1]
kwargs['id'] = os.path.basename(delete_uri)
uid = uuid.UUID(kwargs['id'], version=4)
if uid.hex != kwargs['id'].replace('-', ''):
raise F5SDKError(
"The specified ID is invalid"
)
requests_params = self._handle_requests_params(kwargs)
kwargs = self._check_for_python_keywords(kwargs)
kwargs = self._prepare_request_json(kwargs)
delete_uri = self._meta_data['uri']
session = self._meta_data['bigip']._meta_data['icr_session']
# Check the generation for match before delete
force = self._check_force_arg(kwargs.pop('force', True))
if not force:
self._check_generation()
response = session.delete(delete_uri, json=kwargs, **requests_params)
if response.status_code == 200:
self.__dict__ = {'deleted': True}
# This sleep is necessary to prevent BIG-IQ from being able to remove
# a license. It happens in certain cases that assignments can be revoked
# (and license deletion started) too quickly. Therefore, we must introduce
# an artificial delay here to prevent revoking from returning before
# BIG-IQ would be ready to remove the license.
time.sleep(1)
|
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"# an artificial delay here to prevent revoking from returning before",
"# BIG-IQ would be ready to remove the license.",
"time",
".",
"sleep",
"(",
"1",
")"
] |
Deletes a member from a license pool
You need to be careful with this method. When you use it, and it
succeeds on the remote BIG-IP, the configuration of the BIG-IP
will be reloaded. During this process, you will not be able to
access the REST interface.
This method overrides the Resource class's method because it requires
that extra json kwargs be supplied. This is not a behavior that is
part of the normal Resource class's delete method.
:param kwargs:
:return:
|
[
"Deletes",
"a",
"member",
"from",
"a",
"license",
"pool"
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/bigiq/cm/device/licensing/pool/utility.py#L137-L187
|
237,272
|
F5Networks/f5-common-python
|
f5/multi_device/trust_domain.py
|
TrustDomain._set_attributes
|
def _set_attributes(self, **kwargs):
'''Set attributes for instance in one place
:param kwargs: dict -- dictionary of keyword arguments
'''
self.devices = kwargs['devices'][:]
self.partition = kwargs['partition']
self.device_group_name = 'device_trust_group'
self.device_group_type = 'sync-only'
|
python
|
def _set_attributes(self, **kwargs):
'''Set attributes for instance in one place
:param kwargs: dict -- dictionary of keyword arguments
'''
self.devices = kwargs['devices'][:]
self.partition = kwargs['partition']
self.device_group_name = 'device_trust_group'
self.device_group_type = 'sync-only'
|
[
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"device_group_name",
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"'device_trust_group'",
"self",
".",
"device_group_type",
"=",
"'sync-only'"
] |
Set attributes for instance in one place
:param kwargs: dict -- dictionary of keyword arguments
|
[
"Set",
"attributes",
"for",
"instance",
"in",
"one",
"place"
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/multi_device/trust_domain.py#L76-L85
|
237,273
|
F5Networks/f5-common-python
|
f5/multi_device/trust_domain.py
|
TrustDomain.validate
|
def validate(self):
'''Validate that devices are each trusted by one another
:param kwargs: dict -- keyword args for devices and partition
:raises: DeviceNotTrusted
'''
self._populate_domain()
missing = []
for domain_device in self.domain:
for truster, trustees in iteritems(self.domain):
if domain_device not in trustees:
missing.append((domain_device, truster, trustees))
if missing:
msg = ''
for item in missing:
msg += '\n%r is not trusted by %r, which trusts: %r' % \
(item[0], item[1], item[2])
raise DeviceNotTrusted(msg)
self.device_group = DeviceGroup(
devices=self.devices,
device_group_name=self.device_group_name,
device_group_type=self.device_group_type,
device_group_partition=self.partition
)
|
python
|
def validate(self):
'''Validate that devices are each trusted by one another
:param kwargs: dict -- keyword args for devices and partition
:raises: DeviceNotTrusted
'''
self._populate_domain()
missing = []
for domain_device in self.domain:
for truster, trustees in iteritems(self.domain):
if domain_device not in trustees:
missing.append((domain_device, truster, trustees))
if missing:
msg = ''
for item in missing:
msg += '\n%r is not trusted by %r, which trusts: %r' % \
(item[0], item[1], item[2])
raise DeviceNotTrusted(msg)
self.device_group = DeviceGroup(
devices=self.devices,
device_group_name=self.device_group_name,
device_group_type=self.device_group_type,
device_group_partition=self.partition
)
|
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",",
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Validate that devices are each trusted by one another
:param kwargs: dict -- keyword args for devices and partition
:raises: DeviceNotTrusted
|
[
"Validate",
"that",
"devices",
"are",
"each",
"trusted",
"by",
"one",
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] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/multi_device/trust_domain.py#L87-L112
|
237,274
|
F5Networks/f5-common-python
|
f5/multi_device/trust_domain.py
|
TrustDomain._populate_domain
|
def _populate_domain(self):
'''Populate TrustDomain's domain attribute.
This entails an inspection of each device's certificate-authority
devices in its trust domain and recording them. After which, we
get a dictionary of who trusts who in the domain.
'''
self.domain = {}
for device in self.devices:
device_name = get_device_info(device).name
ca_devices = \
device.tm.cm.trust_domains.trust_domain.load(
name='Root'
).caDevices
self.domain[device_name] = [
d.replace('/%s/' % self.partition, '') for d in ca_devices
]
|
python
|
def _populate_domain(self):
'''Populate TrustDomain's domain attribute.
This entails an inspection of each device's certificate-authority
devices in its trust domain and recording them. After which, we
get a dictionary of who trusts who in the domain.
'''
self.domain = {}
for device in self.devices:
device_name = get_device_info(device).name
ca_devices = \
device.tm.cm.trust_domains.trust_domain.load(
name='Root'
).caDevices
self.domain[device_name] = [
d.replace('/%s/' % self.partition, '') for d in ca_devices
]
|
[
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] |
Populate TrustDomain's domain attribute.
This entails an inspection of each device's certificate-authority
devices in its trust domain and recording them. After which, we
get a dictionary of who trusts who in the domain.
|
[
"Populate",
"TrustDomain",
"s",
"domain",
"attribute",
"."
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/multi_device/trust_domain.py#L114-L131
|
237,275
|
F5Networks/f5-common-python
|
f5/multi_device/trust_domain.py
|
TrustDomain.create
|
def create(self, **kwargs):
'''Add trusted peers to the root bigip device.
When adding a trusted device to a device, the trust is reflexive. That
is, the truster trusts the trustee and the trustee trusts the truster.
So we only need to add the trusted devices to one device.
:param kwargs: dict -- devices and partition
'''
self._set_attributes(**kwargs)
for device in self.devices[1:]:
self._add_trustee(device)
pollster(self.validate)()
|
python
|
def create(self, **kwargs):
'''Add trusted peers to the root bigip device.
When adding a trusted device to a device, the trust is reflexive. That
is, the truster trusts the trustee and the trustee trusts the truster.
So we only need to add the trusted devices to one device.
:param kwargs: dict -- devices and partition
'''
self._set_attributes(**kwargs)
for device in self.devices[1:]:
self._add_trustee(device)
pollster(self.validate)()
|
[
"def",
"create",
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"(",
"device",
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"pollster",
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"validate",
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"(",
")"
] |
Add trusted peers to the root bigip device.
When adding a trusted device to a device, the trust is reflexive. That
is, the truster trusts the trustee and the trustee trusts the truster.
So we only need to add the trusted devices to one device.
:param kwargs: dict -- devices and partition
|
[
"Add",
"trusted",
"peers",
"to",
"the",
"root",
"bigip",
"device",
"."
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/multi_device/trust_domain.py#L133-L146
|
237,276
|
F5Networks/f5-common-python
|
f5/multi_device/trust_domain.py
|
TrustDomain.teardown
|
def teardown(self):
'''Teardown trust domain by removing trusted devices.'''
for device in self.devices:
self._remove_trustee(device)
self._populate_domain()
self.domain = {}
|
python
|
def teardown(self):
'''Teardown trust domain by removing trusted devices.'''
for device in self.devices:
self._remove_trustee(device)
self._populate_domain()
self.domain = {}
|
[
"def",
"teardown",
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"self",
")",
":",
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")",
"self",
".",
"_populate_domain",
"(",
")",
"self",
".",
"domain",
"=",
"{",
"}"
] |
Teardown trust domain by removing trusted devices.
|
[
"Teardown",
"trust",
"domain",
"by",
"removing",
"trusted",
"devices",
"."
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/multi_device/trust_domain.py#L148-L154
|
237,277
|
F5Networks/f5-common-python
|
f5/multi_device/trust_domain.py
|
TrustDomain._add_trustee
|
def _add_trustee(self, device):
'''Add a single trusted device to the trust domain.
:param device: ManagementRoot object -- device to add to trust domain
'''
device_name = get_device_info(device).name
if device_name in self.domain:
msg = 'Device: %r is already in this trust domain.' % device_name
raise DeviceAlreadyInTrustDomain(msg)
self._modify_trust(self.devices[0], self._get_add_trustee_cmd, device)
|
python
|
def _add_trustee(self, device):
'''Add a single trusted device to the trust domain.
:param device: ManagementRoot object -- device to add to trust domain
'''
device_name = get_device_info(device).name
if device_name in self.domain:
msg = 'Device: %r is already in this trust domain.' % device_name
raise DeviceAlreadyInTrustDomain(msg)
self._modify_trust(self.devices[0], self._get_add_trustee_cmd, device)
|
[
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Add a single trusted device to the trust domain.
:param device: ManagementRoot object -- device to add to trust domain
|
[
"Add",
"a",
"single",
"trusted",
"device",
"to",
"the",
"trust",
"domain",
"."
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/multi_device/trust_domain.py#L156-L166
|
237,278
|
F5Networks/f5-common-python
|
f5/multi_device/trust_domain.py
|
TrustDomain._remove_trustee
|
def _remove_trustee(self, device):
'''Remove a trustee from the trust domain.
:param device: MangementRoot object -- device to remove
'''
trustee_name = get_device_info(device).name
name_object_map = get_device_names_to_objects(self.devices)
delete_func = self._get_delete_trustee_cmd
for truster in self.domain:
if trustee_name in self.domain[truster] and \
truster != trustee_name:
truster_obj = name_object_map[truster]
self._modify_trust(truster_obj, delete_func, trustee_name)
self._populate_domain()
for trustee in self.domain[trustee_name]:
if trustee_name != trustee:
self._modify_trust(device, delete_func, trustee)
self.devices.remove(name_object_map[trustee_name])
|
python
|
def _remove_trustee(self, device):
'''Remove a trustee from the trust domain.
:param device: MangementRoot object -- device to remove
'''
trustee_name = get_device_info(device).name
name_object_map = get_device_names_to_objects(self.devices)
delete_func = self._get_delete_trustee_cmd
for truster in self.domain:
if trustee_name in self.domain[truster] and \
truster != trustee_name:
truster_obj = name_object_map[truster]
self._modify_trust(truster_obj, delete_func, trustee_name)
self._populate_domain()
for trustee in self.domain[trustee_name]:
if trustee_name != trustee:
self._modify_trust(device, delete_func, trustee)
self.devices.remove(name_object_map[trustee_name])
|
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Remove a trustee from the trust domain.
:param device: MangementRoot object -- device to remove
|
[
"Remove",
"a",
"trustee",
"from",
"the",
"trust",
"domain",
"."
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/multi_device/trust_domain.py#L168-L189
|
237,279
|
F5Networks/f5-common-python
|
f5/multi_device/trust_domain.py
|
TrustDomain._modify_trust
|
def _modify_trust(self, truster, mod_peer_func, trustee):
'''Modify a trusted peer device by deploying an iapp.
:param truster: ManagementRoot object -- device on which to perform
commands
:param mod_peer_func: function -- function to call to modify peer
:param trustee: ManagementRoot object or str -- device to modify
'''
iapp_name = 'trusted_device'
mod_peer_cmd = mod_peer_func(trustee)
iapp_actions = self.iapp_actions.copy()
iapp_actions['definition']['implementation'] = mod_peer_cmd
self._deploy_iapp(iapp_name, iapp_actions, truster)
self._delete_iapp(iapp_name, truster)
|
python
|
def _modify_trust(self, truster, mod_peer_func, trustee):
'''Modify a trusted peer device by deploying an iapp.
:param truster: ManagementRoot object -- device on which to perform
commands
:param mod_peer_func: function -- function to call to modify peer
:param trustee: ManagementRoot object or str -- device to modify
'''
iapp_name = 'trusted_device'
mod_peer_cmd = mod_peer_func(trustee)
iapp_actions = self.iapp_actions.copy()
iapp_actions['definition']['implementation'] = mod_peer_cmd
self._deploy_iapp(iapp_name, iapp_actions, truster)
self._delete_iapp(iapp_name, truster)
|
[
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] |
Modify a trusted peer device by deploying an iapp.
:param truster: ManagementRoot object -- device on which to perform
commands
:param mod_peer_func: function -- function to call to modify peer
:param trustee: ManagementRoot object or str -- device to modify
|
[
"Modify",
"a",
"trusted",
"peer",
"device",
"by",
"deploying",
"an",
"iapp",
"."
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/multi_device/trust_domain.py#L191-L206
|
237,280
|
F5Networks/f5-common-python
|
f5/multi_device/trust_domain.py
|
TrustDomain._delete_iapp
|
def _delete_iapp(self, iapp_name, deploying_device):
'''Delete an iapp service and template on the root device.
:param iapp_name: str -- name of iapp
:param deploying_device: ManagementRoot object -- device where the
iapp will be deleted
'''
iapp = deploying_device.tm.sys.application
iapp_serv = iapp.services.service.load(
name=iapp_name, partition=self.partition
)
iapp_serv.delete()
iapp_tmpl = iapp.templates.template.load(
name=iapp_name, partition=self.partition
)
iapp_tmpl.delete()
|
python
|
def _delete_iapp(self, iapp_name, deploying_device):
'''Delete an iapp service and template on the root device.
:param iapp_name: str -- name of iapp
:param deploying_device: ManagementRoot object -- device where the
iapp will be deleted
'''
iapp = deploying_device.tm.sys.application
iapp_serv = iapp.services.service.load(
name=iapp_name, partition=self.partition
)
iapp_serv.delete()
iapp_tmpl = iapp.templates.template.load(
name=iapp_name, partition=self.partition
)
iapp_tmpl.delete()
|
[
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"partition",
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"delete",
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] |
Delete an iapp service and template on the root device.
:param iapp_name: str -- name of iapp
:param deploying_device: ManagementRoot object -- device where the
iapp will be deleted
|
[
"Delete",
"an",
"iapp",
"service",
"and",
"template",
"on",
"the",
"root",
"device",
"."
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/multi_device/trust_domain.py#L208-L224
|
237,281
|
F5Networks/f5-common-python
|
f5/multi_device/trust_domain.py
|
TrustDomain._deploy_iapp
|
def _deploy_iapp(self, iapp_name, actions, deploying_device):
'''Deploy iapp to add trusted device
:param iapp_name: str -- name of iapp
:param actions: dict -- actions definition of iapp sections
:param deploying_device: ManagementRoot object -- device where the
iapp will be created
'''
tmpl = deploying_device.tm.sys.application.templates.template
serv = deploying_device.tm.sys.application.services.service
tmpl.create(name=iapp_name, partition=self.partition, actions=actions)
pollster(deploying_device.tm.sys.application.templates.template.load)(
name=iapp_name, partition=self.partition
)
serv.create(
name=iapp_name,
partition=self.partition,
template='/%s/%s' % (self.partition, iapp_name)
)
|
python
|
def _deploy_iapp(self, iapp_name, actions, deploying_device):
'''Deploy iapp to add trusted device
:param iapp_name: str -- name of iapp
:param actions: dict -- actions definition of iapp sections
:param deploying_device: ManagementRoot object -- device where the
iapp will be created
'''
tmpl = deploying_device.tm.sys.application.templates.template
serv = deploying_device.tm.sys.application.services.service
tmpl.create(name=iapp_name, partition=self.partition, actions=actions)
pollster(deploying_device.tm.sys.application.templates.template.load)(
name=iapp_name, partition=self.partition
)
serv.create(
name=iapp_name,
partition=self.partition,
template='/%s/%s' % (self.partition, iapp_name)
)
|
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"'/%s/%s'",
"%",
"(",
"self",
".",
"partition",
",",
"iapp_name",
")",
")"
] |
Deploy iapp to add trusted device
:param iapp_name: str -- name of iapp
:param actions: dict -- actions definition of iapp sections
:param deploying_device: ManagementRoot object -- device where the
iapp will be created
|
[
"Deploy",
"iapp",
"to",
"add",
"trusted",
"device"
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/multi_device/trust_domain.py#L226-L245
|
237,282
|
F5Networks/f5-common-python
|
f5/multi_device/trust_domain.py
|
TrustDomain._get_add_trustee_cmd
|
def _get_add_trustee_cmd(self, trustee):
'''Get tmsh command to add a trusted device.
:param trustee: ManagementRoot object -- device to add as trusted
:returns: str -- tmsh command to add trustee
'''
trustee_info = pollster(get_device_info)(trustee)
username = trustee._meta_data['username']
password = trustee._meta_data['password']
return 'tmsh::modify cm trust-domain Root ca-devices add ' \
'\\{ %s \\} name %s username %s password %s' % \
(trustee_info.managementIp, trustee_info.name, username, password)
|
python
|
def _get_add_trustee_cmd(self, trustee):
'''Get tmsh command to add a trusted device.
:param trustee: ManagementRoot object -- device to add as trusted
:returns: str -- tmsh command to add trustee
'''
trustee_info = pollster(get_device_info)(trustee)
username = trustee._meta_data['username']
password = trustee._meta_data['password']
return 'tmsh::modify cm trust-domain Root ca-devices add ' \
'\\{ %s \\} name %s username %s password %s' % \
(trustee_info.managementIp, trustee_info.name, username, password)
|
[
"def",
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"'tmsh::modify cm trust-domain Root ca-devices add '",
"'\\\\{ %s \\\\} name %s username %s password %s'",
"%",
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"trustee_info",
".",
"managementIp",
",",
"trustee_info",
".",
"name",
",",
"username",
",",
"password",
")"
] |
Get tmsh command to add a trusted device.
:param trustee: ManagementRoot object -- device to add as trusted
:returns: str -- tmsh command to add trustee
|
[
"Get",
"tmsh",
"command",
"to",
"add",
"a",
"trusted",
"device",
"."
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/multi_device/trust_domain.py#L247-L259
|
237,283
|
F5Networks/f5-common-python
|
f5/bigip/tm/vcmp/virtual_disk.py
|
Virtual_Disk.load
|
def load(self, **kwargs):
"""Loads a given resource
Loads a given resource provided a 'name' and an optional 'slot'
parameter. The 'slot' parameter is not a required load parameter
because it is provided as an optional way of constructing the
correct 'name' of the vCMP resource.
:param kwargs:
:return:
"""
kwargs['transform_name'] = True
kwargs = self._mutate_name(kwargs)
return self._load(**kwargs)
|
python
|
def load(self, **kwargs):
"""Loads a given resource
Loads a given resource provided a 'name' and an optional 'slot'
parameter. The 'slot' parameter is not a required load parameter
because it is provided as an optional way of constructing the
correct 'name' of the vCMP resource.
:param kwargs:
:return:
"""
kwargs['transform_name'] = True
kwargs = self._mutate_name(kwargs)
return self._load(**kwargs)
|
[
"def",
"load",
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",",
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"kwargs",
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"(",
"kwargs",
")",
"return",
"self",
".",
"_load",
"(",
"*",
"*",
"kwargs",
")"
] |
Loads a given resource
Loads a given resource provided a 'name' and an optional 'slot'
parameter. The 'slot' parameter is not a required load parameter
because it is provided as an optional way of constructing the
correct 'name' of the vCMP resource.
:param kwargs:
:return:
|
[
"Loads",
"a",
"given",
"resource"
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/bigip/tm/vcmp/virtual_disk.py#L53-L66
|
237,284
|
F5Networks/f5-common-python
|
f5/utils/iapp_parser.py
|
IappParser._get_section_end_index
|
def _get_section_end_index(self, section, section_start):
'''Get end of section's content.
In the loop to match braces, we must not count curly braces that are
within a doubly quoted string.
:param section: string name of section
:param section_start: integer index of section's beginning
:return: integer index of section's end
:raises: CurlyBraceMismatchException
'''
brace_count = 0
in_quote = False
in_escape = False
for index, char in enumerate(self.template_str[section_start:]):
# This check is to look for items inside of an escape sequence.
#
# For example, in the iApp team's iApps, there is a proc called
# "iapp_get_items" which has a line that looks like this.
#
# set val [string map {\" ""} $val]
#
# This will cause this parser to fail because of the unbalanced
# quotes. Therefore, this conditional takes this into consideration
#
if char == '\\' and not in_escape:
in_escape = True
elif char == '\\' and in_escape:
in_escape = False
if not in_escape:
if char == '"' and not in_quote:
in_quote = True
elif char == '"' and in_quote:
in_quote = False
if char == '{' and not in_quote:
brace_count += 1
elif char == '}' and not in_quote:
brace_count -= 1
if brace_count is 0:
return index + section_start
if brace_count is not 0:
raise CurlyBraceMismatchException(
'Curly braces mismatch in section %s.' % section
)
|
python
|
def _get_section_end_index(self, section, section_start):
'''Get end of section's content.
In the loop to match braces, we must not count curly braces that are
within a doubly quoted string.
:param section: string name of section
:param section_start: integer index of section's beginning
:return: integer index of section's end
:raises: CurlyBraceMismatchException
'''
brace_count = 0
in_quote = False
in_escape = False
for index, char in enumerate(self.template_str[section_start:]):
# This check is to look for items inside of an escape sequence.
#
# For example, in the iApp team's iApps, there is a proc called
# "iapp_get_items" which has a line that looks like this.
#
# set val [string map {\" ""} $val]
#
# This will cause this parser to fail because of the unbalanced
# quotes. Therefore, this conditional takes this into consideration
#
if char == '\\' and not in_escape:
in_escape = True
elif char == '\\' and in_escape:
in_escape = False
if not in_escape:
if char == '"' and not in_quote:
in_quote = True
elif char == '"' and in_quote:
in_quote = False
if char == '{' and not in_quote:
brace_count += 1
elif char == '}' and not in_quote:
brace_count -= 1
if brace_count is 0:
return index + section_start
if brace_count is not 0:
raise CurlyBraceMismatchException(
'Curly braces mismatch in section %s.' % section
)
|
[
"def",
"_get_section_end_index",
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"self",
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"section_start",
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"# This check is to look for items inside of an escape sequence.",
"#",
"# For example, in the iApp team's iApps, there is a proc called",
"# \"iapp_get_items\" which has a line that looks like this.",
"#",
"# set val [string map {\\\" \"\"} $val]",
"#",
"# This will cause this parser to fail because of the unbalanced",
"# quotes. Therefore, this conditional takes this into consideration",
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"0",
":",
"raise",
"CurlyBraceMismatchException",
"(",
"'Curly braces mismatch in section %s.'",
"%",
"section",
")"
] |
Get end of section's content.
In the loop to match braces, we must not count curly braces that are
within a doubly quoted string.
:param section: string name of section
:param section_start: integer index of section's beginning
:return: integer index of section's end
:raises: CurlyBraceMismatchException
|
[
"Get",
"end",
"of",
"section",
"s",
"content",
"."
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/utils/iapp_parser.py#L80-L129
|
237,285
|
F5Networks/f5-common-python
|
f5/utils/iapp_parser.py
|
IappParser._get_section_start_index
|
def _get_section_start_index(self, section):
'''Get start of a section's content.
:param section: string name of section
:return: integer index of section's beginning
:raises: NonextantSectionException
'''
sec_start_re = r'%s\s*\{' % section
found = re.search(sec_start_re, self.template_str)
if found:
return found.end() - 1
raise NonextantSectionException(
'Section %s not found in template' % section
)
|
python
|
def _get_section_start_index(self, section):
'''Get start of a section's content.
:param section: string name of section
:return: integer index of section's beginning
:raises: NonextantSectionException
'''
sec_start_re = r'%s\s*\{' % section
found = re.search(sec_start_re, self.template_str)
if found:
return found.end() - 1
raise NonextantSectionException(
'Section %s not found in template' % section
)
|
[
"def",
"_get_section_start_index",
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"self",
",",
"section",
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":",
"sec_start_re",
"=",
"r'%s\\s*\\{'",
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")",
"-",
"1",
"raise",
"NonextantSectionException",
"(",
"'Section %s not found in template'",
"%",
"section",
")"
] |
Get start of a section's content.
:param section: string name of section
:return: integer index of section's beginning
:raises: NonextantSectionException
|
[
"Get",
"start",
"of",
"a",
"section",
"s",
"content",
"."
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/utils/iapp_parser.py#L131-L147
|
237,286
|
F5Networks/f5-common-python
|
f5/utils/iapp_parser.py
|
IappParser._get_template_name
|
def _get_template_name(self):
'''Find template name.
:returns: string of template name
:raises: NonextantTemplateNameException
'''
start_pattern = r"sys application template\s+" \
r"(\/[\w\.\-]+\/)?" \
r"(?P<name>[\w\.\-]+)\s*\{"
template_start = re.search(start_pattern, self.template_str)
if template_start:
return template_start.group('name')
raise NonextantTemplateNameException('Template name not found.')
|
python
|
def _get_template_name(self):
'''Find template name.
:returns: string of template name
:raises: NonextantTemplateNameException
'''
start_pattern = r"sys application template\s+" \
r"(\/[\w\.\-]+\/)?" \
r"(?P<name>[\w\.\-]+)\s*\{"
template_start = re.search(start_pattern, self.template_str)
if template_start:
return template_start.group('name')
raise NonextantTemplateNameException('Template name not found.')
|
[
"def",
"_get_template_name",
"(",
"self",
")",
":",
"start_pattern",
"=",
"r\"sys application template\\s+\"",
"r\"(\\/[\\w\\.\\-]+\\/)?\"",
"r\"(?P<name>[\\w\\.\\-]+)\\s*\\{\"",
"template_start",
"=",
"re",
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",",
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"template_start",
".",
"group",
"(",
"'name'",
")",
"raise",
"NonextantTemplateNameException",
"(",
"'Template name not found.'",
")"
] |
Find template name.
:returns: string of template name
:raises: NonextantTemplateNameException
|
[
"Find",
"template",
"name",
"."
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/utils/iapp_parser.py#L149-L164
|
237,287
|
F5Networks/f5-common-python
|
f5/utils/iapp_parser.py
|
IappParser._get_template_attr
|
def _get_template_attr(self, attr):
'''Find the attribute value for a specific attribute.
:param attr: string of attribute name
:returns: string of attribute value
'''
attr_re = r'{0}\s+.*'.format(attr)
attr_found = re.search(attr_re, self.template_str)
if attr_found:
attr_value = attr_found.group(0).replace(attr, '', 1)
return attr_value.strip()
|
python
|
def _get_template_attr(self, attr):
'''Find the attribute value for a specific attribute.
:param attr: string of attribute name
:returns: string of attribute value
'''
attr_re = r'{0}\s+.*'.format(attr)
attr_found = re.search(attr_re, self.template_str)
if attr_found:
attr_value = attr_found.group(0).replace(attr, '', 1)
return attr_value.strip()
|
[
"def",
"_get_template_attr",
"(",
"self",
",",
"attr",
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":",
"attr_re",
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",",
"''",
",",
"1",
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".",
"strip",
"(",
")"
] |
Find the attribute value for a specific attribute.
:param attr: string of attribute name
:returns: string of attribute value
|
[
"Find",
"the",
"attribute",
"value",
"for",
"a",
"specific",
"attribute",
"."
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/utils/iapp_parser.py#L166-L178
|
237,288
|
F5Networks/f5-common-python
|
f5/utils/iapp_parser.py
|
IappParser._add_sections
|
def _add_sections(self):
'''Add the found and required sections to the templ_dict.'''
for section in self.template_sections:
try:
sec_start = self._get_section_start_index(section)
except NonextantSectionException:
if section in self.sections_not_required:
continue
raise
sec_end = self._get_section_end_index(section, sec_start)
section_value = self.template_str[sec_start+1:sec_end].strip()
section, section_value = self._transform_key_value(
section,
section_value,
self.section_map
)
self.templ_dict['actions']['definition'][section] = section_value
self.template_str = self.template_str[:sec_start+1] + \
self.template_str[sec_end:]
|
python
|
def _add_sections(self):
'''Add the found and required sections to the templ_dict.'''
for section in self.template_sections:
try:
sec_start = self._get_section_start_index(section)
except NonextantSectionException:
if section in self.sections_not_required:
continue
raise
sec_end = self._get_section_end_index(section, sec_start)
section_value = self.template_str[sec_start+1:sec_end].strip()
section, section_value = self._transform_key_value(
section,
section_value,
self.section_map
)
self.templ_dict['actions']['definition'][section] = section_value
self.template_str = self.template_str[:sec_start+1] + \
self.template_str[sec_end:]
|
[
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"+",
"1",
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"+",
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"[",
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":",
"]"
] |
Add the found and required sections to the templ_dict.
|
[
"Add",
"the",
"found",
"and",
"required",
"sections",
"to",
"the",
"templ_dict",
"."
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/utils/iapp_parser.py#L180-L198
|
237,289
|
F5Networks/f5-common-python
|
f5/utils/iapp_parser.py
|
IappParser._add_cli_scripts
|
def _add_cli_scripts(self):
'''Add the found external sections to the templ_dict.'''
pattern = r"cli script\s+" \
r"(\/[\w\.\-]+\/)?" \
r"(?P<name>[\w\.\-]+)\s*\{"
sections = re.finditer(pattern, self.template_str)
for section in sections:
if 'scripts' not in self.templ_dict:
self.templ_dict['scripts'] = []
try:
sec_start = self._get_section_start_index(
section.group('name')
)
except NonextantSectionException:
continue
sec_end = self._get_section_end_index(
section.group('name'), sec_start
)
section_value = self.template_str[sec_start+1:sec_end].strip()
self.templ_dict['scripts'].append(dict(
name=section.group('name'),
script=section_value
))
self.template_str = self.template_str[:sec_start+1] + \
self.template_str[sec_end:]
|
python
|
def _add_cli_scripts(self):
'''Add the found external sections to the templ_dict.'''
pattern = r"cli script\s+" \
r"(\/[\w\.\-]+\/)?" \
r"(?P<name>[\w\.\-]+)\s*\{"
sections = re.finditer(pattern, self.template_str)
for section in sections:
if 'scripts' not in self.templ_dict:
self.templ_dict['scripts'] = []
try:
sec_start = self._get_section_start_index(
section.group('name')
)
except NonextantSectionException:
continue
sec_end = self._get_section_end_index(
section.group('name'), sec_start
)
section_value = self.template_str[sec_start+1:sec_end].strip()
self.templ_dict['scripts'].append(dict(
name=section.group('name'),
script=section_value
))
self.template_str = self.template_str[:sec_start+1] + \
self.template_str[sec_end:]
|
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|
[
"Add",
"the",
"found",
"external",
"sections",
"to",
"the",
"templ_dict",
"."
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/utils/iapp_parser.py#L200-L230
|
237,290
|
F5Networks/f5-common-python
|
f5/utils/iapp_parser.py
|
IappParser._add_attrs
|
def _add_attrs(self):
'''Add the found and required attrs to the templ_dict.'''
for attr in self.template_attrs:
attr_value = self._get_template_attr(attr)
if not attr_value:
continue
attr, attr_value = self._transform_key_value(
attr,
attr_value,
self.attr_map
)
self.templ_dict[attr] = attr_value
|
python
|
def _add_attrs(self):
'''Add the found and required attrs to the templ_dict.'''
for attr in self.template_attrs:
attr_value = self._get_template_attr(attr)
if not attr_value:
continue
attr, attr_value = self._transform_key_value(
attr,
attr_value,
self.attr_map
)
self.templ_dict[attr] = attr_value
|
[
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Add the found and required attrs to the templ_dict.
|
[
"Add",
"the",
"found",
"and",
"required",
"attrs",
"to",
"the",
"templ_dict",
"."
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/utils/iapp_parser.py#L232-L245
|
237,291
|
F5Networks/f5-common-python
|
f5/utils/iapp_parser.py
|
IappParser._parse_tcl_list
|
def _parse_tcl_list(self, attr, list_str):
'''Turns a string representation of a TCL list into a Python list.
:param attr: string name of attribute
:param list_str: string representation of a list
:returns: Python list
'''
list_str = list_str.strip()
if not list_str:
return []
if list_str[0] != '{' and list_str[-1] != '}':
if list_str.find('none') >= 0:
return list_str
if not re.search(self.tcl_list_patterns[attr], list_str):
raise MalformedTCLListException(
'TCL list for "%s" is malformed. ' % attr
)
list_str = list_str.strip('{').strip('}')
list_str = list_str.strip()
return list_str.split()
|
python
|
def _parse_tcl_list(self, attr, list_str):
'''Turns a string representation of a TCL list into a Python list.
:param attr: string name of attribute
:param list_str: string representation of a list
:returns: Python list
'''
list_str = list_str.strip()
if not list_str:
return []
if list_str[0] != '{' and list_str[-1] != '}':
if list_str.find('none') >= 0:
return list_str
if not re.search(self.tcl_list_patterns[attr], list_str):
raise MalformedTCLListException(
'TCL list for "%s" is malformed. ' % attr
)
list_str = list_str.strip('{').strip('}')
list_str = list_str.strip()
return list_str.split()
|
[
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"_parse_tcl_list",
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",",
"list_str",
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":",
"list_str",
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"list_str",
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"strip",
"(",
")",
"return",
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"(",
")"
] |
Turns a string representation of a TCL list into a Python list.
:param attr: string name of attribute
:param list_str: string representation of a list
:returns: Python list
|
[
"Turns",
"a",
"string",
"representation",
"of",
"a",
"TCL",
"list",
"into",
"a",
"Python",
"list",
"."
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/utils/iapp_parser.py#L247-L271
|
237,292
|
F5Networks/f5-common-python
|
f5/utils/iapp_parser.py
|
IappParser._transform_key_value
|
def _transform_key_value(self, key, value, map_dict):
'''Massage keys and values for iapp dict to look like JSON.
:param key: string dictionary key
:param value: string dictionary value
:param map_dict: dictionary to map key names
'''
if key in self.tcl_list_patterns:
value = self._parse_tcl_list(key, value)
if key in map_dict:
key = map_dict[key]
return key, value
|
python
|
def _transform_key_value(self, key, value, map_dict):
'''Massage keys and values for iapp dict to look like JSON.
:param key: string dictionary key
:param value: string dictionary value
:param map_dict: dictionary to map key names
'''
if key in self.tcl_list_patterns:
value = self._parse_tcl_list(key, value)
if key in map_dict:
key = map_dict[key]
return key, value
|
[
"def",
"_transform_key_value",
"(",
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",",
"key",
",",
"value",
",",
"map_dict",
")",
":",
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"map_dict",
":",
"key",
"=",
"map_dict",
"[",
"key",
"]",
"return",
"key",
",",
"value"
] |
Massage keys and values for iapp dict to look like JSON.
:param key: string dictionary key
:param value: string dictionary value
:param map_dict: dictionary to map key names
|
[
"Massage",
"keys",
"and",
"values",
"for",
"iapp",
"dict",
"to",
"look",
"like",
"JSON",
"."
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/utils/iapp_parser.py#L273-L287
|
237,293
|
F5Networks/f5-common-python
|
f5/utils/iapp_parser.py
|
IappParser.parse_template
|
def parse_template(self):
'''Parse the template string into a dict.
Find the (large) inner sections first, save them, and remove them from
a modified string. Then find the template attributes in the modified
string.
:returns: dictionary of parsed template
'''
self.templ_dict = {'actions': {'definition': {}}}
self.templ_dict['name'] = self._get_template_name()
self._add_cli_scripts()
self._add_sections()
self._add_attrs()
return self.templ_dict
|
python
|
def parse_template(self):
'''Parse the template string into a dict.
Find the (large) inner sections first, save them, and remove them from
a modified string. Then find the template attributes in the modified
string.
:returns: dictionary of parsed template
'''
self.templ_dict = {'actions': {'definition': {}}}
self.templ_dict['name'] = self._get_template_name()
self._add_cli_scripts()
self._add_sections()
self._add_attrs()
return self.templ_dict
|
[
"def",
"parse_template",
"(",
"self",
")",
":",
"self",
".",
"templ_dict",
"=",
"{",
"'actions'",
":",
"{",
"'definition'",
":",
"{",
"}",
"}",
"}",
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"[",
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"_get_template_name",
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"_add_sections",
"(",
")",
"self",
".",
"_add_attrs",
"(",
")",
"return",
"self",
".",
"templ_dict"
] |
Parse the template string into a dict.
Find the (large) inner sections first, save them, and remove them from
a modified string. Then find the template attributes in the modified
string.
:returns: dictionary of parsed template
|
[
"Parse",
"the",
"template",
"string",
"into",
"a",
"dict",
"."
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/utils/iapp_parser.py#L289-L307
|
237,294
|
F5Networks/f5-common-python
|
f5/bigip/shared/authn.py
|
Root._create
|
def _create(self, **kwargs):
"""wrapped by `create` override that in subclasses to customize"""
if 'uri' in self._meta_data:
error = "There was an attempt to assign a new uri to this "\
"resource, the _meta_data['uri'] is %s and it should"\
" not be changed." % (self._meta_data['uri'])
raise URICreationCollision(error)
self._check_exclusive_parameters(**kwargs)
requests_params = self._handle_requests_params(kwargs)
self._minimum_one_is_missing(**kwargs)
self._check_create_parameters(**kwargs)
kwargs = self._check_for_python_keywords(kwargs)
# Reduce boolean pairs as specified by the meta_data entry below
for key1, key2 in self._meta_data['reduction_forcing_pairs']:
kwargs = self._reduce_boolean_pair(kwargs, key1, key2)
# Make convenience variable with short names for this method.
_create_uri = self._meta_data['container']._meta_data['uri']
session = self._meta_data['bigip']._meta_data['icr_session']
kwargs = self._prepare_request_json(kwargs)
# Invoke the REST operation on the device.
response = session.post(_create_uri, json=kwargs, **requests_params)
# Make new instance of self
result = self._produce_instance(response)
return result
|
python
|
def _create(self, **kwargs):
"""wrapped by `create` override that in subclasses to customize"""
if 'uri' in self._meta_data:
error = "There was an attempt to assign a new uri to this "\
"resource, the _meta_data['uri'] is %s and it should"\
" not be changed." % (self._meta_data['uri'])
raise URICreationCollision(error)
self._check_exclusive_parameters(**kwargs)
requests_params = self._handle_requests_params(kwargs)
self._minimum_one_is_missing(**kwargs)
self._check_create_parameters(**kwargs)
kwargs = self._check_for_python_keywords(kwargs)
# Reduce boolean pairs as specified by the meta_data entry below
for key1, key2 in self._meta_data['reduction_forcing_pairs']:
kwargs = self._reduce_boolean_pair(kwargs, key1, key2)
# Make convenience variable with short names for this method.
_create_uri = self._meta_data['container']._meta_data['uri']
session = self._meta_data['bigip']._meta_data['icr_session']
kwargs = self._prepare_request_json(kwargs)
# Invoke the REST operation on the device.
response = session.post(_create_uri, json=kwargs, **requests_params)
# Make new instance of self
result = self._produce_instance(response)
return result
|
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"_meta_data",
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"error",
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"\"resource, the _meta_data['uri'] is %s and it should\"",
"\" not be changed.\"",
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"(",
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"_meta_data",
"[",
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"kwargs",
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] |
wrapped by `create` override that in subclasses to customize
|
[
"wrapped",
"by",
"create",
"override",
"that",
"in",
"subclasses",
"to",
"customize"
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/bigip/shared/authn.py#L55-L83
|
237,295
|
F5Networks/f5-common-python
|
f5sdk_plugins/fixtures.py
|
peer
|
def peer(opt_peer, opt_username, opt_password, scope="module"):
'''peer bigip fixture'''
p = BigIP(opt_peer, opt_username, opt_password)
return p
|
python
|
def peer(opt_peer, opt_username, opt_password, scope="module"):
'''peer bigip fixture'''
p = BigIP(opt_peer, opt_username, opt_password)
return p
|
[
"def",
"peer",
"(",
"opt_peer",
",",
"opt_username",
",",
"opt_password",
",",
"scope",
"=",
"\"module\"",
")",
":",
"p",
"=",
"BigIP",
"(",
"opt_peer",
",",
"opt_username",
",",
"opt_password",
")",
"return",
"p"
] |
peer bigip fixture
|
[
"peer",
"bigip",
"fixture"
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5sdk_plugins/fixtures.py#L116-L119
|
237,296
|
F5Networks/f5-common-python
|
f5/bigip/tm/gtm/topology.py
|
Topology.exists
|
def exists(self, **kwargs):
"""Providing a partition is not necessary on topology; causes errors"""
kwargs.pop('partition', None)
kwargs['transform_name'] = True
return self._exists(**kwargs)
|
python
|
def exists(self, **kwargs):
"""Providing a partition is not necessary on topology; causes errors"""
kwargs.pop('partition', None)
kwargs['transform_name'] = True
return self._exists(**kwargs)
|
[
"def",
"exists",
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",",
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")",
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",",
"None",
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"[",
"'transform_name'",
"]",
"=",
"True",
"return",
"self",
".",
"_exists",
"(",
"*",
"*",
"kwargs",
")"
] |
Providing a partition is not necessary on topology; causes errors
|
[
"Providing",
"a",
"partition",
"is",
"not",
"necessary",
"on",
"topology",
";",
"causes",
"errors"
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/bigip/tm/gtm/topology.py#L149-L153
|
237,297
|
F5Networks/f5-common-python
|
f5/utils/responses/handlers.py
|
Stats._key_dot_replace
|
def _key_dot_replace(self, rdict):
"""Replace fullstops in returned keynames"""
temp_dict = {}
for key, value in iteritems(rdict):
if isinstance(value, dict):
value = self._key_dot_replace(value)
temp_dict[key.replace('.', '_')] = value
return temp_dict
|
python
|
def _key_dot_replace(self, rdict):
"""Replace fullstops in returned keynames"""
temp_dict = {}
for key, value in iteritems(rdict):
if isinstance(value, dict):
value = self._key_dot_replace(value)
temp_dict[key.replace('.', '_')] = value
return temp_dict
|
[
"def",
"_key_dot_replace",
"(",
"self",
",",
"rdict",
")",
":",
"temp_dict",
"=",
"{",
"}",
"for",
"key",
",",
"value",
"in",
"iteritems",
"(",
"rdict",
")",
":",
"if",
"isinstance",
"(",
"value",
",",
"dict",
")",
":",
"value",
"=",
"self",
".",
"_key_dot_replace",
"(",
"value",
")",
"temp_dict",
"[",
"key",
".",
"replace",
"(",
"'.'",
",",
"'_'",
")",
"]",
"=",
"value",
"return",
"temp_dict"
] |
Replace fullstops in returned keynames
|
[
"Replace",
"fullstops",
"in",
"returned",
"keynames"
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/utils/responses/handlers.py#L43-L50
|
237,298
|
F5Networks/f5-common-python
|
f5/utils/responses/handlers.py
|
Stats._get_nest_stats
|
def _get_nest_stats(self):
"""Helper method to deal with nestedStats
as json format changed in v12.x
"""
for x in self.rdict:
check = urlparse(x)
if check.scheme:
nested_dict = self.rdict[x]['nestedStats']
tmp_dict = nested_dict['entries']
return self._key_dot_replace(tmp_dict)
return self._key_dot_replace(self.rdict)
|
python
|
def _get_nest_stats(self):
"""Helper method to deal with nestedStats
as json format changed in v12.x
"""
for x in self.rdict:
check = urlparse(x)
if check.scheme:
nested_dict = self.rdict[x]['nestedStats']
tmp_dict = nested_dict['entries']
return self._key_dot_replace(tmp_dict)
return self._key_dot_replace(self.rdict)
|
[
"def",
"_get_nest_stats",
"(",
"self",
")",
":",
"for",
"x",
"in",
"self",
".",
"rdict",
":",
"check",
"=",
"urlparse",
"(",
"x",
")",
"if",
"check",
".",
"scheme",
":",
"nested_dict",
"=",
"self",
".",
"rdict",
"[",
"x",
"]",
"[",
"'nestedStats'",
"]",
"tmp_dict",
"=",
"nested_dict",
"[",
"'entries'",
"]",
"return",
"self",
".",
"_key_dot_replace",
"(",
"tmp_dict",
")",
"return",
"self",
".",
"_key_dot_replace",
"(",
"self",
".",
"rdict",
")"
] |
Helper method to deal with nestedStats
as json format changed in v12.x
|
[
"Helper",
"method",
"to",
"deal",
"with",
"nestedStats"
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/utils/responses/handlers.py#L52-L64
|
237,299
|
F5Networks/f5-common-python
|
f5/utils/responses/handlers.py
|
Stats.refresh
|
def refresh(self, **kwargs):
"""Refreshes stats attached to an object"""
self.resource.refresh(**kwargs)
self.rdict = self.resource.entries
self._update_stats()
|
python
|
def refresh(self, **kwargs):
"""Refreshes stats attached to an object"""
self.resource.refresh(**kwargs)
self.rdict = self.resource.entries
self._update_stats()
|
[
"def",
"refresh",
"(",
"self",
",",
"*",
"*",
"kwargs",
")",
":",
"self",
".",
"resource",
".",
"refresh",
"(",
"*",
"*",
"kwargs",
")",
"self",
".",
"rdict",
"=",
"self",
".",
"resource",
".",
"entries",
"self",
".",
"_update_stats",
"(",
")"
] |
Refreshes stats attached to an object
|
[
"Refreshes",
"stats",
"attached",
"to",
"an",
"object"
] |
7e67d5acd757a60e3d5f8c88c534bd72208f5494
|
https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/utils/responses/handlers.py#L71-L75
|
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