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def add_summary(self, summary, global_step=None):
"""Adds a `Summary` protocol buffer to the event file. This method wraps the provided summary in an `Event` pro... |
if isinstance(summary, bytes):
summ = summary_pb2.Summary()
summ.ParseFromString(summary)
summary = summ
# We strip metadata from values with tags that we have seen before in order
# to save space - we just store the metadata on the first value with a
... |
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def add_graph(self, graph):
"""Adds a `Graph` protocol buffer to the event file.""" |
event = event_pb2.Event(graph_def=graph.SerializeToString())
self._add_event(event, None) |
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def add_scalar(self, tag, value, global_step=None):
"""Adds scalar data to the event file. Parameters tag : str Name for the scalar plot. value : float, tuple, l... |
if isinstance(value, (tuple, list, dict)):
if isinstance(value, (tuple, list)):
if len(value) != 2:
raise ValueError('expected two elements in value, while received %d'
% len(value))
value = {value[0]: value[1]... |
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def _add_scalars(self, tag, scalar_dict, global_step=None):
"""Adds multiple scalars to summary. This enables drawing multiple curves in one plot. Parameters tag... |
timestamp = time.time()
fw_logdir = self._file_writer.get_logdir()
for scalar_name, scalar_value in scalar_dict.items():
fw_tag = fw_logdir + '/' + tag + '/' + scalar_name
if fw_tag in self._all_writers.keys():
fw = self._all_writers[fw_tag]
e... |
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def add_histogram(self, tag, values, global_step=None, bins='default'):
"""Add histogram data to the event file. Note: This function internally calls `asnumpy()`... |
if bins == 'default':
bins = self._get_default_bins()
self._file_writer.add_summary(histogram_summary(tag, values, bins), global_step) |
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def add_image(self, tag, image, global_step=None):
"""Add image data to the event file. This function supports input as a 2D, 3D, or 4D image. If the input image... |
self._file_writer.add_summary(image_summary(tag, image), global_step) |
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def add_audio(self, tag, audio, sample_rate=44100, global_step=None):
"""Add audio data to the event file. Note: This function internally calls `asnumpy()` for M... |
self._file_writer.add_summary(audio_summary(tag, audio, sample_rate=sample_rate),
global_step) |
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def add_text(self, tag, text, global_step=None):
"""Add text data to the event file. Parameters tag : str Name for the `text`. text : str Text to be saved to the... |
self._file_writer.add_summary(text_summary(tag, text), global_step)
if tag not in self._text_tags:
self._text_tags.append(tag)
extension_dir = self.get_logdir() + '/plugins/tensorboard_text/'
if not os.path.exists(extension_dir):
os.makedirs(extension... |
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def add_pr_curve(self, tag, labels, predictions, num_thresholds, global_step=None, weights=None):
"""Adds precision-recall curve. Note: This function internally ... |
if num_thresholds < 2:
raise ValueError('num_thresholds must be >= 2')
labels = _make_numpy_array(labels)
predictions = _make_numpy_array(predictions)
self._file_writer.add_summary(pr_curve_summary(tag, labels, predictions,
... |
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def _rectangular(n):
"""Checks to see if a 2D list is a valid 2D matrix""" |
for i in n:
if len(i) != len(n[0]):
return False
return True |
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def _is_2D_matrix(matrix):
"""Checks to see if a ndarray is 2D or a list of lists is 2D""" |
return ((isinstance(matrix[0], list) and _rectangular(matrix) and
not isinstance(matrix[0][0], list)) or
(not isinstance(matrix, list) and matrix.shape == 2)) |
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def _save_image(image, filename, nrow=8, padding=2, square_image=True):
"""Saves a given Tensor into an image file. If the input tensor contains multiple images,... |
if not isinstance(image, NDArray):
raise TypeError('MXNet NDArray expected, received {}'.format(str(type(image))))
image = _prepare_image(image, nrow=nrow, padding=padding, square_image=square_image)
if Image is None:
raise ImportError('saving image failed because PIL is not found')
im ... |
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def _save_embedding_tsv(data, file_path):
"""Given a 2D `NDarray` or a `numpy.ndarray` as embeding, save it in tensors.tsv under the path provided by the user.""... |
if isinstance(data, np.ndarray):
data_list = data.tolist()
elif isinstance(data, NDArray):
data_list = data.asnumpy().tolist()
else:
raise TypeError('expected NDArray of np.ndarray, while received type {}'.format(
str(type(data))))
with open(os.path.join(file_path, '... |
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def _make_image(tensor):
"""Converts an NDArray type image to Image protobuf""" |
assert isinstance(tensor, NDArray)
if Image is None:
raise ImportError('need to install PIL for visualizing images')
height, width, channel = tensor.shape
tensor = _make_numpy_array(tensor)
image = Image.fromarray(tensor)
output = io.BytesIO()
image.save(output, format='PNG')
im... |
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def pr_curve_summary(tag, labels, predictions, num_thresholds, weights=None):
"""Outputs a precision-recall curve `Summary` protocol buffer. Parameters tag : str... |
# num_thresholds > 127 results in failure of creating protobuf,
# probably a bug of protobuf
if num_thresholds > 127:
logging.warning('num_thresholds>127 would result in failure of creating pr_curve protobuf,'
' clipping it at 127')
num_thresholds = 127
labels = ... |
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def _get_nodes_from_symbol(sym):
"""Given a symbol and shapes, return a list of `NodeDef`s for visualizing the the graph in TensorBoard.""" |
if not isinstance(sym, Symbol):
raise TypeError('sym must be an `mxnet.symbol.Symbol`,'
' received type {}'.format(str(type(sym))))
conf = json.loads(sym.tojson())
nodes = conf['nodes']
data2op = {} # key: data id, value: list of ops to whom data is an input
for i, ... |
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def temporal_derivatives(order, variables, data):
""" Compute temporal derivative terms by the method of backwards differences. Parameters order: range or list(i... |
variables_deriv = OrderedDict()
data_deriv = OrderedDict()
if 0 in order:
data_deriv[0] = data[variables]
variables_deriv[0] = variables
order = set(order) - set([0])
for o in order:
variables_deriv[o] = ['{}_derivative{}'.format(v, o)
for v... |
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def exponential_terms(order, variables, data):
""" Compute exponential expansions. Parameters order: range or list(int) A list of exponential terms to include. F... |
variables_exp = OrderedDict()
data_exp = OrderedDict()
if 1 in order:
data_exp[1] = data[variables]
variables_exp[1] = variables
order = set(order) - set([1])
for o in order:
variables_exp[o] = ['{}_power{}'.format(v, o) for v in variables]
data_exp[o] = data[var... |
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def _order_as_range(order):
"""Convert a hyphenated string representing order for derivative or exponential terms into a range object that can be passed as input... |
order = order.split('-')
order = [int(o) for o in order]
if len(order) > 1:
order = range(order[0], (order[-1] + 1))
return order |
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def _check_and_expand_exponential(expr, variables, data):
"""Check if the current operation specifies exponential expansion. ^^6 specifies all powers up to the 6... |
if re.search(r'\^\^[0-9]+$', expr):
order = re.compile(r'\^\^([0-9]+)$').findall(expr)
order = range(1, int(*order) + 1)
variables, data = exponential_terms(order, variables, data)
elif re.search(r'\^[0-9]+[\-]?[0-9]*$', expr):
order = re.compile(r'\^([0-9]+[\-]?[0-9]*)').findal... |
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def _check_and_expand_derivative(expr, variables, data):
"""Check if the current operation specifies a temporal derivative. dd6x specifies all derivatives up to ... |
if re.search(r'^dd[0-9]+', expr):
order = re.compile(r'^dd([0-9]+)').findall(expr)
order = range(0, int(*order) + 1)
(variables, data) = temporal_derivatives(order, variables, data)
elif re.search(r'^d[0-9]+[\-]?[0-9]*', expr):
order = re.compile(r'^d([0-9]+[\-]?[0-9]*)').findal... |
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def _check_and_expand_subformula(expression, parent_data, variables, data):
"""Check if the current operation contains a suboperation, and parse it where appropr... |
grouping_depth = 0
for i, char in enumerate(expression):
if char == '(':
if grouping_depth == 0:
formula_delimiter = i + 1
grouping_depth += 1
elif char == ')':
grouping_depth -= 1
if grouping_depth == 0:
expr = exp... |
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def parse_expression(expression, parent_data):
""" Parse an expression in a model formula. Parameters expression: str Formula expression: either a single variabl... |
variables = None
data = None
variables, data = _check_and_expand_subformula(expression,
parent_data,
variables,
data)
variables, data = _check_and_exp... |
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def _expand_shorthand(model_formula, variables):
"""Expand shorthand terms in the model formula. """ |
wm = 'white_matter'
gsr = 'global_signal'
rps = 'trans_x + trans_y + trans_z + rot_x + rot_y + rot_z'
fd = 'framewise_displacement'
acc = _get_matches_from_data('a_comp_cor_[0-9]+', variables)
tcc = _get_matches_from_data('t_comp_cor_[0-9]+', variables)
dv = _get_matches_from_data('^std_dva... |
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def _unscramble_regressor_columns(parent_data, data):
"""Reorder the columns of a confound matrix such that the columns are in the same order as the input data w... |
matches = ['_power[0-9]+', '_derivative[0-9]+']
var = OrderedDict((c, deque()) for c in parent_data.columns)
for c in data.columns:
col = c
for m in matches:
col = re.sub(m, '', col)
if col == c:
var[col].appendleft(c)
else:
var[col].appen... |
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def parse_formula(model_formula, parent_data, unscramble=False):
""" Recursively parse a model formula by breaking it into additive atoms and tracking grouping s... |
variables = {}
data = {}
expr_delimiter = 0
grouping_depth = 0
model_formula = _expand_shorthand(model_formula, parent_data.columns)
for i, char in enumerate(model_formula):
if char == '(':
grouping_depth += 1
elif char == ')':
grouping_depth -= 1
... |
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def mask(in_file, mask_file, new_name):
""" Apply a binary mask to an image. Parameters in_file : str Path to a NIfTI file to mask mask_file : str Path to a bina... |
import nibabel as nb
import os
# Load the input image
in_nii = nb.load(in_file)
# Load the mask image
mask_nii = nb.load(mask_file)
# Set all non-mask voxels in the input file to zero.
data = in_nii.get_data()
data[mask_nii.get_data() == 0] = 0
# Save the new masked image.
n... |
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def create_cfm(in_file, lesion_mask=None, global_mask=True, out_path=None):
""" Create a mask to constrain registration. Parameters in_file : str Path to an exis... |
import os
import numpy as np
import nibabel as nb
from nipype.utils.filemanip import fname_presuffix
if out_path is None:
out_path = fname_presuffix(in_file, suffix='_cfm', newpath=os.getcwd())
else:
out_path = os.path.abspath(out_path)
if not global_mask and not lesion_ma... |
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def _get_settings(self):
""" Return any settings defined by the user, as well as any pre-defined settings files that exist for the image modalities to be registe... |
# If user-defined settings exist...
if isdefined(self.inputs.settings):
# Note this in the log and return those settings.
NIWORKFLOWS_LOG.info('User-defined settings, overriding defaults')
return self.inputs.settings
# Define a prefix for output files based ... |
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def _get_ants_args(self):
args = {'moving_image': self.inputs.moving_image, 'num_threads': self.inputs.num_threads, 'float': self.inputs.float, 'terminal_output'... |
# If a moving mask is provided...
if isdefined(self.inputs.moving_mask):
# If explicit masking is enabled...
if self.inputs.explicit_masking:
# Mask the moving image.
# Do not use a moving mask during registration.
args['moving_ima... |
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def dollars_to_math(source):
r""" Replace dollar signs with backticks. More precisely, do a regular expression search. Replace a plain dollar sign ($) by a backt... |
s = "\n".join(source)
if s.find("$") == -1:
return
# This searches for "$blah$" inside a pair of curly braces --
# don't change these, since they're probably coming from a nested
# math environment. So for each match, we replace it with a temporary
# string, and later on we substitute ... |
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def _post_run_hook(self, runtime):
""" there is not inner interface to run """ |
self._fixed_image = self.inputs.after
self._moving_image = self.inputs.before
self._contour = self.inputs.wm_seg if isdefined(self.inputs.wm_seg) else None
NIWORKFLOWS_LOG.info(
'Report - setting before (%s) and after (%s) images',
self._fixed_image, self._moving... |
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def _get_data_path(data_dir=None):
""" Get data storage directory data_dir: str Path of the data directory. Used to force data storage in a specified location. :... |
data_dir = data_dir or ''
default_dirs = [Path(d).expanduser().resolve()
for d in os.getenv('CRN_SHARED_DATA', '').split(os.pathsep)
if d.strip()]
default_dirs += [Path(d).expanduser().resolve()
for d in os.getenv('CRN_DATA', '').split(os.pathse... |
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def _get_dataset(dataset_name, dataset_prefix=None, data_dir=None, default_paths=None, verbose=1):
""" Create if necessary and returns data directory of given da... |
dataset_folder = dataset_name if not dataset_prefix \
else '%s%s' % (dataset_prefix, dataset_name)
default_paths = default_paths or ''
paths = [p / dataset_folder for p in _get_data_path(data_dir)]
all_paths = [Path(p) / dataset_folder
for p in default_paths.split(os.pathsep)]... |
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def _md5_sum_file(path):
""" Calculates the MD5 sum of a file. """ |
with Path(path).open('rb') as fhandle:
md5sum = hashlib.md5()
while True:
data = fhandle.read(8192)
if not data:
break
md5sum.update(data)
return md5sum.hexdigest() |
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def _chunk_report_(bytes_so_far, total_size, initial_size, t_0):
"""Show downloading percentage. :param int bytes_so_far: number of downloaded bytes :param int t... |
if not total_size:
sys.stderr.write("\rDownloaded {0:d} of ? bytes.".format(bytes_so_far))
else:
# Estimate remaining download time
total_percent = float(bytes_so_far) / total_size
current_download_size = bytes_so_far - initial_size
bytes_remaining = total_size - byte... |
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def refine_aseg(aseg, ball_size=4):
""" First step to reconcile ANTs' and FreeSurfer's brain masks. Here, the ``aseg.mgz`` mask from FreeSurfer is refined in two... |
# Read aseg data
bmask = aseg.copy()
bmask[bmask > 0] = 1
bmask = bmask.astype(np.uint8)
# Morphological operations
selem = sim.ball(ball_size)
newmask = sim.binary_closing(bmask, selem)
newmask = binary_fill_holes(newmask.astype(np.uint8), selem).astype(np.uint8)
return newmask.a... |
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def grow_mask(anat, aseg, ants_segs=None, ww=7, zval=2.0, bw=4):
""" Grow mask including pixels that have a high likelihood. GM tissue parameters are sampled in ... |
selem = sim.ball(bw)
if ants_segs is None:
ants_segs = np.zeros_like(aseg, dtype=np.uint8)
aseg[aseg == 42] = 3 # Collapse both hemispheres
gm = anat.copy()
gm[aseg != 3] = 0
refined = refine_aseg(aseg)
newrefmask = sim.binary_dilation(refined, selem) - refined
indices = np.... |
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def medial_wall_to_nan(in_file, subjects_dir, target_subject, newpath=None):
""" Convert values on medial wall to NaNs """ |
import nibabel as nb
import numpy as np
import os
fn = os.path.basename(in_file)
if not target_subject.startswith('fs'):
return in_file
cortex = nb.freesurfer.read_label(os.path.join(
subjects_dir, target_subject, 'label', '{}.cortex.label'.format(fn[:2])))
func = nb.load(... |
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def make_link_node(rawtext, app, type, slug, options):
"""Create a link to a github resource. :param rawtext: Text being replaced with link node. :param app: Sph... |
try:
base = app.config.github_project_url
if not base:
raise AttributeError
if not base.endswith('/'):
base += '/'
except AttributeError as err:
raise ValueError('github_project_url configuration value is not set (%s)' % str(err))
ref = base + type ... |
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def ghissue_role(name, rawtext, text, lineno, inliner, options={}, content=[]):
"""Link to a GitHub issue. Returns 2 part tuple containing list of nodes to inser... |
try:
issue_num = int(text)
if issue_num <= 0:
raise ValueError
except ValueError:
msg = inliner.reporter.error(
'GitHub issue number must be a number greater than or equal to 1; '
'"%s" is invalid.' % text, line=lineno)
prb = inliner.problema... |
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def ghuser_role(name, rawtext, text, lineno, inliner, options={}, content=[]):
"""Link to a GitHub user. Returns 2 part tuple containing list of nodes to insert ... |
app = inliner.document.settings.env.app
#app.info('user link %r' % text)
ref = 'https://www.github.com/' + text
node = nodes.reference(rawtext, text, refuri=ref, **options)
return [node], [] |
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def ghcommit_role(name, rawtext, text, lineno, inliner, options={}, content=[]):
"""Link to a GitHub commit. Returns 2 part tuple containing list of nodes to ins... |
app = inliner.document.settings.env.app
#app.info('user link %r' % text)
try:
base = app.config.github_project_url
if not base:
raise AttributeError
if not base.endswith('/'):
base += '/'
except AttributeError as err:
raise ValueError('github_proj... |
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| def _import(self, name):
''' Import namespace package '''
mod = __import__(name)
components = name.split('.')
for comp in components[1:]:
mod = getattr(mod, comp)
return mod |
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| def discover_modules(self):
''' Return module sequence discovered from ``self.package_name``
Parameters
----------
None
Returns
-------
mods : sequence
Sequence of module names within ``self.package_name``
Examples
--------
... |
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def get_metadata_for_nifti(in_file, bids_dir=None, validate=True):
"""Fetch metadata for a given nifti file 'SIEMENS' """ |
return _init_layout(in_file, bids_dir, validate).get_metadata(
str(in_file)) |
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def group_multiecho(bold_sess):
""" Multiplexes multi-echo EPIs into arrays. Dual-echo is a special case of multi-echo, which is treated as single-echo data. ['s... |
from itertools import groupby
def _grp_echos(x):
if '_echo-' not in x:
return x
echo = re.search("_echo-\\d*", x).group(0)
return x.replace(echo, "_echo-?")
ses_uids = []
for _, bold in groupby(bold_sess, key=_grp_echos):
bold = list(bold)
# If sing... |
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def _define_variant(self):
"""Assign arbitrary label to combination of CIFTI spaces""" |
space = None
variants = {
# to be expanded once addtional spaces are supported
'space1': ['fsaverage5', 'MNI152NLin2009cAsym'],
'space2': ['fsaverage6', 'MNI152NLin2009cAsym'],
}
for sp, targets in variants.items():
if all(target in target... |
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def _fetch_data(self):
"""Converts inputspec to files""" |
if (self.inputs.surface_target == "fsnative" or
self.inputs.volume_target != "MNI152NLin2009cAsym"):
# subject space is not support yet
raise NotImplementedError
annotation_files = sorted(glob(os.path.join(self.inputs.subjects_dir,
... |
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def reorient(in_file, newpath=None):
"""Reorient Nifti files to RAS""" |
out_file = fname_presuffix(in_file, suffix='_ras', newpath=newpath)
nb.as_closest_canonical(nb.load(in_file)).to_filename(out_file)
return out_file |
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def normalize_xform(img):
""" Set identical, valid qform and sform matrices in an image Selects the best available affine (sform > qform > shape-based), and coer... |
# Let nibabel convert from affine to quaternions, and recover xform
tmp_header = img.header.copy()
tmp_header.set_qform(img.affine)
xform = tmp_header.get_qform()
xform_code = 2
# Check desired codes
qform, qform_code = img.get_qform(coded=True)
sform, sform_code = img.get_sform(coded=... |
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def demean(in_file, in_mask, only_mask=False, newpath=None):
"""Demean ``in_file`` within the mask defined by ``in_mask``""" |
import os
import numpy as np
import nibabel as nb
from nipype.utils.filemanip import fname_presuffix
out_file = fname_presuffix(in_file, suffix='_demeaned',
newpath=os.getcwd())
nii = nb.load(in_file)
msk = nb.load(in_mask).get_data()
data = nii.get_data(... |
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def nii_ones_like(in_file, value, dtype, newpath=None):
"""Create a NIfTI file filled with ``value``, matching properties of ``in_file``""" |
import os
import numpy as np
import nibabel as nb
nii = nb.load(in_file)
data = np.ones(nii.shape, dtype=float) * value
out_file = os.path.join(newpath or os.getcwd(), "filled.nii.gz")
nii = nb.Nifti1Image(data, nii.affine, nii.header)
nii.set_data_dtype(dtype)
nii.to_filename(out... |
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def reorient_wf(name='ReorientWorkflow'):
"""A workflow to reorient images to 'RPI' orientation""" |
workflow = pe.Workflow(name=name)
inputnode = pe.Node(niu.IdentityInterface(fields=['in_file']),
name='inputnode')
outputnode = pe.Node(niu.IdentityInterface(
fields=['out_file']), name='outputnode')
deoblique = pe.Node(afni.Refit(deoblique=True), name='deoblique')
... |
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def _tsv2json(in_tsv, out_json, index_column, additional_metadata=None, drop_columns=None, enforce_case=True):
""" Convert metadata from TSV format to JSON forma... |
import pandas as pd
# Adapted from https://dev.to/rrampage/snake-case-to-camel-case-and- ...
# back-using-regular-expressions-and-python-m9j
re_to_camel = r'(.*?)_([a-zA-Z0-9])'
re_to_snake = r'(^.+?|.*?)((?<![_A-Z])[A-Z]|(?<![_0-9])[0-9]+)'
def snake(match):
return '{}_{}'.format(matc... |
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def _tpm2roi(in_tpm, in_mask, mask_erosion_mm=None, erosion_mm=None, mask_erosion_prop=None, erosion_prop=None, pthres=0.95, newpath=None):
""" Generate a mask f... |
tpm_img = nb.load(in_tpm)
roi_mask = (tpm_img.get_data() >= pthres).astype(np.uint8)
eroded_mask_file = None
erode_in = (mask_erosion_mm is not None and mask_erosion_mm > 0 or
mask_erosion_prop is not None and mask_erosion_prop < 1)
if erode_in:
eroded_mask_file = fname_pre... |
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def run_reports(reportlets_dir, out_dir, subject_label, run_uuid, config=None, packagename=None):
""" Runs the reports .. testsetup:: .. doctest:: 0 .. testclean... |
report = Report(Path(reportlets_dir), out_dir, run_uuid, config=config,
subject_id=subject_label, packagename=packagename)
return report.generate_report() |
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def generate_reports(subject_list, output_dir, work_dir, run_uuid, config=None, packagename=None):
""" A wrapper to run_reports on a given ``subject_list`` """ |
reports_dir = str(Path(work_dir) / 'reportlets')
report_errors = [
run_reports(reports_dir, output_dir, subject_label, run_uuid,
config, packagename=packagename)
for subject_label in subject_list
]
errno = sum(report_errors)
if errno:
import logging
... |
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def index(self, config):
""" Traverse the reports config definition and instantiate reportlets. This method also places figures in their final location. """ |
for subrep_cfg in config:
# First determine whether we need to split by some ordering
# (ie. sessions / tasks / runs), which are separated by commas.
orderings = [s for s in subrep_cfg.get('ordering', '').strip().split(',') if s]
queries = []
for key ... |
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def generate_report(self):
"""Once the Report has been indexed, the final HTML can be generated""" |
logs_path = self.out_dir / 'logs'
boilerplate = []
boiler_idx = 0
if (logs_path / 'CITATION.html').exists():
text = (logs_path / 'CITATION.html').read_text(encoding='UTF-8')
text = '<div class="boiler-html">%s</div>' % re.compile(
'<body>(.*?)</... |
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def _applytfms(args):
""" Applies ANTs' antsApplyTransforms to the input image. All inputs are zipped in one tuple to make it digestible by multiprocessing's map... |
import nibabel as nb
from nipype.utils.filemanip import fname_presuffix
from niworkflows.interfaces.fixes import FixHeaderApplyTransforms as ApplyTransforms
in_file, in_xform, ifargs, index, newpath = args
out_file = fname_presuffix(in_file, suffix='_xform-%05d' % index,
... |
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def _arrange_xfms(transforms, num_files, tmp_folder):
""" Convenience method to arrange the list of transforms that should be applied to each input file """ |
base_xform = ['#Insight Transform File V1.0', '#Transform 0']
# Initialize the transforms matrix
xfms_T = []
for i, tf_file in enumerate(transforms):
# If it is a deformation field, copy to the tfs_matrix directly
if guess_type(tf_file)[0] != 'text/plain':
xfms_T.append([tf_... |
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def load_transform(fname):
"""Load affine transform from file Parameters fname : str or None Filename of an LTA or FSL-style MAT transform file. If ``None``, ret... |
if fname is None:
return np.eye(4)
if fname.endswith('.mat'):
return np.loadtxt(fname)
elif fname.endswith('.lta'):
with open(fname, 'rb') as fobj:
for line in fobj:
if line.startswith(b'1 4 4'):
break
lines = fobj.readlin... |
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def vertex_normals(vertices, faces):
"""Calculates the normals of a triangular mesh""" |
def normalize_v3(arr):
''' Normalize a numpy array of 3 component vectors shape=(n,3) '''
lens = np.sqrt(arr[:, 0]**2 + arr[:, 1]**2 + arr[:, 2]**2)
arr /= lens[:, np.newaxis]
tris = vertices[faces]
facenorms = np.cross(tris[::, 1] - tris[::, 0], tris[::, 2] - tris[::, 0])
nor... |
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def pointcloud2ply(vertices, normals, out_file=None):
"""Converts the file to PLY format""" |
from pathlib import Path
import pandas as pd
from pyntcloud import PyntCloud
df = pd.DataFrame(np.hstack((vertices, normals)))
df.columns = ['x', 'y', 'z', 'nx', 'ny', 'nz']
cloud = PyntCloud(df)
if out_file is None:
out_file = Path('pointcloud.ply').resolve()
cloud.to_file(st... |
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def ply2gii(in_file, metadata, out_file=None):
"""Convert from ply to GIfTI""" |
from pathlib import Path
from numpy import eye
from nibabel.gifti import (
GiftiMetaData, GiftiCoordSystem, GiftiImage, GiftiDataArray,
)
from pyntcloud import PyntCloud
in_file = Path(in_file)
surf = PyntCloud.from_file(str(in_file))
# Update centroid metadata
metadata.up... |
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def fix_multi_T1w_source_name(in_files):
""" Make up a generic source name when there are multiple T1s '/path/to/sub-045_T1w.nii.gz' """ |
import os
from nipype.utils.filemanip import filename_to_list
base, in_file = os.path.split(filename_to_list(in_files)[0])
subject_label = in_file.split("_", 1)[0].split("-")[1]
return os.path.join(base, "sub-%s_T1w.nii.gz" % subject_label) |
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def add_suffix(in_files, suffix):
""" Wrap nipype's fname_presuffix to conveniently just add a prefix 'sub-045_ses-test_T1w_test.nii.gz' """ |
import os.path as op
from nipype.utils.filemanip import fname_presuffix, filename_to_list
return op.basename(fname_presuffix(filename_to_list(in_files)[0],
suffix=suffix)) |
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def _read_txt(path):
"""Read a txt crashfile """ |
from pathlib import Path
lines = Path(path).read_text().splitlines()
data = {'file': str(path)}
traceback_start = 0
if lines[0].startswith('Node'):
data['node'] = lines[0].split(': ', 1)[1].strip()
data['node_dir'] = lines[1].split(': ', 1)[1].strip()
inputs = []
cur... |
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def _conform_mask(in_mask, in_reference):
"""Ensures the mask headers make sense and match those of the T1w""" |
from pathlib import Path
import nibabel as nb
from nipype.utils.filemanip import fname_presuffix
ref = nb.load(in_reference)
nii = nb.load(in_mask)
hdr = nii.header.copy()
hdr.set_data_dtype('int16')
hdr.set_slope_inter(1, 0)
qform, qcode = ref.header.get_qform(coded=True)
if ... |
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def get_template(template_name, data_dir=None, url=None, resume=True, verbose=1):
"""Download and load a template""" |
warn(DEPRECATION_MSG)
if template_name.startswith('tpl-'):
template_name = template_name[4:]
# An aliasing mechanism. Please avoid
template_name = TEMPLATE_ALIASES.get(template_name, template_name)
return get_dataset(template_name, dataset_prefix='tpl-', data_dir=data_dir,
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def get_bids_examples(data_dir=None, url=None, resume=True, verbose=1, variant='BIDS-examples-1-1.0.0-rc3u5'):
"""Download BIDS-examples-1""" |
warn(DEPRECATION_MSG)
variant = 'BIDS-examples-1-1.0.0-rc3u5' if variant not in BIDS_EXAMPLES else variant
if url is None:
url = BIDS_EXAMPLES[variant][0]
md5 = BIDS_EXAMPLES[variant][1]
return fetch_file(variant, url, data_dir, resume=resume, verbose=verbose,
md5sum=m... |
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def svg2str(display_object, dpi=300):
""" Serializes a nilearn display object as a string """ |
from io import StringIO
image_buf = StringIO()
display_object.frame_axes.figure.savefig(
image_buf, dpi=dpi, format='svg',
facecolor='k', edgecolor='k')
return image_buf.getvalue() |
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def extract_svg(display_object, dpi=300, compress='auto'):
""" Removes the preamble of the svg files generated with nilearn """ |
image_svg = svg2str(display_object, dpi)
if compress is True or compress == 'auto':
image_svg = svg_compress(image_svg, compress)
image_svg = re.sub(' height="[0-9]+[a-z]*"', '', image_svg, count=1)
image_svg = re.sub(' width="[0-9]+[a-z]*"', '', image_svg, count=1)
image_svg = re.sub(' vie... |
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def cuts_from_bbox(mask_nii, cuts=3):
"""Finds equi-spaced cuts for presenting images""" |
from nibabel.affines import apply_affine
mask_data = mask_nii.get_data() > 0.0
# First, project the number of masked voxels on each axes
ijk_counts = [
mask_data.sum(2).sum(1), # project sagittal planes to transverse (i) axis
mask_data.sum(2).sum(0), # project coronal planes to to l... |
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| def _3d_in_file(in_file):
''' if self.inputs.in_file is 3d, return it.
if 4d, pick an arbitrary volume and return that.
if in_file is a list of files, return an arbitrary file from
the list, and an arbitrary volume from that file
'''
in_file = filemanip.filename_to_list(in_file)[0]
try:
... |
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def transform_to_2d(data, max_axis):
""" Projects 3d data cube along one axis using maximum intensity with preservation of the signs. Adapted from nilearn. """ |
import numpy as np
# get the shape of the array we are projecting to
new_shape = list(data.shape)
del new_shape[max_axis]
# generate a 3D indexing array that points to max abs value in the
# current projection
a1, a2 = np.indices(new_shape)
inds = [a1, a2]
inds.insert(max_axis, np.... |
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def main():
""" Install entry-point """ |
from os import path as op
from inspect import getfile, currentframe
from setuptools import setup, find_packages
from niworkflows.__about__ import (
__packagename__,
__author__,
__email__,
__maintainer__,
__license__,
__description__,
__longdesc__,... |
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def afni_wf(name='AFNISkullStripWorkflow', unifize=False, n4_nthreads=1):
""" Skull-stripping workflow Originally derived from the `codebase of the QAP <https://... |
workflow = pe.Workflow(name=name)
inputnode = pe.Node(niu.IdentityInterface(fields=['in_file']),
name='inputnode')
outputnode = pe.Node(niu.IdentityInterface(
fields=['bias_corrected', 'out_file', 'out_mask', 'bias_image']), name='outputnode')
inu_n4 = pe.Node(
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def _get(url, headers={}, params=None):
"""Tries to GET data from an endpoint using retries""" |
param_string = _foursquare_urlencode(params)
for i in xrange(NUM_REQUEST_RETRIES):
try:
try:
response = requests.get(url, headers=headers, params=param_string, verify=VERIFY_SSL)
return _process_response(response)
except requests.exceptions.Reques... |
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def _post(url, headers={}, data=None, files=None):
"""Tries to POST data to an endpoint""" |
try:
response = requests.post(url, headers=headers, data=data, files=files, verify=VERIFY_SSL)
return _process_response(response)
except requests.exceptions.RequestException as e:
_log_and_raise_exception('Error connecting with foursquare API', e) |
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def _process_response(response):
"""Make the request and handle exception processing""" |
# Read the response as JSON
try:
data = response.json()
except ValueError:
_log_and_raise_exception('Invalid response', response.text)
# Default case, Got proper response
if response.status_code == 200:
return { 'headers': response.headers, 'data': data }
return _raise_... |
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def _raise_error_from_response(data):
"""Processes the response data""" |
# Check the meta-data for why this request failed
meta = data.get('meta')
if meta:
# Account for foursquare conflicts
# see: https://developer.foursquare.com/overview/responses
if meta.get('code') in (200, 409): return data
exc = error_types.get(meta.get('errorType'))
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def _foursquare_urlencode(query, doseq=0, safe_chars="&/,+"):
"""Gnarly hack because Foursquare doesn't properly handle standard url encoding""" |
# Original doc: http://docs.python.org/2/library/urllib.html#urllib.urlencode
# Works the same way as urllib.urlencode except two differences -
# 1. it uses `quote()` instead of `quote_plus()`
# 2. it takes an extra parameter called `safe_chars` which is a string
# having the characters which sh... |
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def _attach_endpoints(self):
"""Dynamically attach endpoint callables to this client""" |
for name, endpoint in inspect.getmembers(self):
if inspect.isclass(endpoint) and issubclass(endpoint, self._Endpoint) and (endpoint is not self._Endpoint):
endpoint_instance = endpoint(self.base_requester)
setattr(self, endpoint_instance.endpoint, endpoint_instance) |
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def register(self, widget, basename, **parameters):
""" Register a widget, URL basename and any optional URL parameters. Parameters are passed as keyword argumen... |
self.registry.append((widget, basename, parameters)) |
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def iterator(self):
""" Execute the API request and return an iterator over the objects. This method does not use the query cache. """ |
for obj in (self.execute().json().get("items") or []):
yield self.api_obj_class(self.api, obj) |
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def version(self):
""" Get Kubernetes API version """ |
response = self.get(version="", base="/version")
response.raise_for_status()
data = response.json()
return (data["major"], data["minor"]) |
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def get_kwargs(self, **kwargs):
""" Creates a full URL to request based on arguments. :Parametes: - `kwargs`: All keyword arguments to build a kubernetes API end... |
version = kwargs.pop("version", "v1")
if version == "v1":
base = kwargs.pop("base", "/api")
elif "/" in version:
base = kwargs.pop("base", "/apis")
else:
if "base" not in kwargs:
raise TypeError("unknown API version; base kwarg must be... |
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def request(self, *args, **kwargs):
""" Makes an API request based on arguments. :Parameters: - `args`: Non-keyword arguments - `kwargs`: Keyword arguments """ |
return self.session.request(*args, **self.get_kwargs(**kwargs)) |
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def get(self, *args, **kwargs):
""" Executes an HTTP GET. :Parameters: - `args`: Non-keyword arguments - `kwargs`: Keyword arguments """ |
return self.session.get(*args, **self.get_kwargs(**kwargs)) |
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def options(self, *args, **kwargs):
""" Executes an HTTP OPTIONS. :Parameters: - `args`: Non-keyword arguments - `kwargs`: Keyword arguments """ |
return self.session.options(*args, **self.get_kwargs(**kwargs)) |
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def head(self, *args, **kwargs):
""" Executes an HTTP HEAD. :Parameters: - `args`: Non-keyword arguments - `kwargs`: Keyword arguments """ |
return self.session.head(*args, **self.get_kwargs(**kwargs)) |
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def post(self, *args, **kwargs):
""" Executes an HTTP POST. :Parameters: - `args`: Non-keyword arguments - `kwargs`: Keyword arguments """ |
return self.session.post(*args, **self.get_kwargs(**kwargs)) |
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def put(self, *args, **kwargs):
""" Executes an HTTP PUT. :Parameters: - `args`: Non-keyword arguments - `kwargs`: Keyword arguments """ |
return self.session.put(*args, **self.get_kwargs(**kwargs)) |
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def patch(self, *args, **kwargs):
""" Executes an HTTP PATCH. :Parameters: - `args`: Non-keyword arguments - `kwargs`: Keyword arguments """ |
return self.session.patch(*args, **self.get_kwargs(**kwargs)) |
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def delete(self, *args, **kwargs):
""" Executes an HTTP DELETE. :Parameters: - `args`: Non-keyword arguments - `kwargs`: Keyword arguments """ |
return self.session.delete(*args, **self.get_kwargs(**kwargs)) |
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def from_file(cls, filename, **kwargs):
""" Creates an instance of the KubeConfig class from a kubeconfig file. :Parameters: - `filename`: The full path to the c... |
filename = os.path.expanduser(filename)
if not os.path.isfile(filename):
raise exceptions.PyKubeError("Configuration file {} not found".format(filename))
with open(filename) as f:
doc = yaml.safe_load(f.read())
self = cls(doc, **kwargs)
self.filename = fi... |
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def clusters(self):
""" Returns known clusters by exposing as a read-only property. """ |
if not hasattr(self, "_clusters"):
cs = {}
for cr in self.doc["clusters"]:
cs[cr["name"]] = c = copy.deepcopy(cr["cluster"])
if "server" not in c:
c["server"] = "http://localhost"
BytesOrFile.maybe_set(c, "certificate-a... |
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def users(self):
""" Returns known users by exposing as a read-only property. """ |
if not hasattr(self, "_users"):
us = {}
if "users" in self.doc:
for ur in self.doc["users"]:
us[ur["name"]] = u = copy.deepcopy(ur["user"])
BytesOrFile.maybe_set(u, "client-certificate")
BytesOrFile.maybe_set(u,... |
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