Memory errors

Node: _autorecon31
Working directory: /scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC05_wf/anat_preproc_wf/surface_recon_wf/autorecon_resume_wf/autorecon3/mapflow/
_autorecon31

Node inputs:

T1_files = <undefined>
T2_file = <undefined>
args = <undefined>
big_ventricles = <undefined>
brainstem = <undefined>
directive = autorecon3
environ = {}
expert = <undefined>
flags = <undefined>
hemi = rh
hippocampal_subfields_T1 = <undefined>
hippocampal_subfields_T2 = <undefined>
hires = <undefined>
ignore_exception = False
mprage = <undefined>
mri_aparc2aseg = <undefined>
mri_ca_label = <undefined>
mri_ca_normalize = <undefined>
mri_ca_register = <undefined>
mri_edit_wm_with_aseg = <undefined>
mri_em_register = <undefined>
mri_fill = <undefined>
mri_mask = <undefined>
mri_normalize = <undefined>
mri_pretess = <undefined>
mri_remove_neck = <undefined>
mri_segment = <undefined>
mri_segstats = <undefined>
mri_tessellate = <undefined>
mri_watershed = <undefined>
mris_anatomical_stats = <undefined>
mris_ca_label = <undefined>
mris_fix_topology = <undefined>
mris_inflate = <undefined>
mris_make_surfaces = <undefined>
mris_register = <undefined>
mris_smooth = <undefined>
mris_sphere = <undefined>
mris_surf2vol = <undefined>
mrisp_paint = <undefined>
openmp = 8
parallel = <undefined>
subject_id = sub-MSC05
subjects_dir = /scratch/03763/oesteban/fmriprep-phase1/out/ds000224/freesurfer
talairach = <undefined>
terminal_output = <undefined>
use_T2 = True
xopts = <undefined>

Traceback (most recent call last):
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/plugins/multiproc.py", line 51, in run_node
    result['result'] = node.run(updatehash=updatehash)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 407, in run
    self._run_interface()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 517, in _run_interface
    self._result = self._run_command(execute)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 650, in _run_command
    result = self._interface.run()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/base.py", line 1088, in run
    runtime = self._run_interface(runtime)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/base.py", line 1653, in _run_interface
    runtime.dependencies = get_dependencies(executable_name, runtime.environ)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/base.py", line 1467, in get_dependencies
    env=environ)
  File "/usr/local/miniconda/lib/python3.6/subprocess.py", line 707, in __init__
    restore_signals, start_new_session)
  File "/usr/local/miniconda/lib/python3.6/subprocess.py", line 1260, in _execute_child
    restore_signals, start_new_session, preexec_fn)
OSError: [Errno 12] Cannot allocate memory

Node: fmriprep_wf.single_subject_MSC08_wf.func_preproc_ses_func01_task_motor_run_02_wf.bold_reg_wf.bbreg_wf.mri_coreg
Working directory: /scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC08_wf/func_preproc_ses_func01_task_motor_run_02_wf/bold_reg_wf/bbreg_wf/mri_co
reg

Node inputs:

args = <undefined>
brute_force_limit = <undefined>
brute_force_samples = <undefined>
compress_report = auto
conform_reference = <undefined>
dof = 9
environ = {'SUBJECTS_DIR': '/opt/freesurfer/subjects'}
ftol = 0.0001
generate_report = True
ignore_exception = False
initial_rotation = <undefined>
initial_scale = <undefined>
initial_shear = <undefined>
initial_translation = <undefined>
linmintol = 0.01
max_iters = <undefined>
no_brute_force = <undefined>
no_coord_dithering = <undefined>
...skipping...
Traceback (most recent call last):
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/plugins/multiproc.py", line 51, in run_node
    result['result'] = node.run(updatehash=updatehash)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 407, in run
    self._run_interface()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 517, in _run_interface
    self._result = self._run_command(execute)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 650, in _run_command
    result = self._interface.run()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/freesurfer/base.py", line 162, in run
    return super(FSCommand, self).run(**inputs)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/base.py", line 1088, in run
    runtime = self._run_interface(runtime)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/common/report.py", line 53, in _run_interface
    ReportCapableInterface, self)._run_interface(runtime)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/base.py", line 1653, in _run_interface
    runtime.dependencies = get_dependencies(executable_name, runtime.environ)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/base.py", line 1467, in get_dependencies
    env=environ)
  File "/usr/local/miniconda/lib/python3.6/subprocess.py", line 707, in __init__
    restore_signals, start_new_session)
  File "/usr/local/miniconda/lib/python3.6/subprocess.py", line 1260, in _execute_child
    restore_signals, start_new_session, preexec_fn)
OSError: [Errno 12] Cannot allocate memory

Working directory: /scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_03_task_localizer_run_02_wf/bold_mni_trans_wf/bold_to_mni_
transform

Node inputs:

args = <undefined>
default_value = 0.0
dimension = <undefined>
environ = {}
float = True
ignore_exception = False
input_image = ['/scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_03_task_localizer_run_02_wf/bold_hmc_wf/split/vol0000.nii.gz'
, '/scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_03_task_localizer_run_02_wf/bold_hmc_wf/split/vol0001.nii.gz', '/scratch/0
3763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_03_task_localizer_run_02_wf/bold_hmc_wf/split/vol0002.nii.gz', '/scratch/03763/oesteban
/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_03_task_localizer_run_02_wf/bold_hmc_wf/split/vol0003.nii.gz', '/scratch/03763/oesteban/fmriprep-pha
se1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_03_task_localizer_run_02_wf/bold_hmc_wf/split/vol0004.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds00
0232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_03_task_localizer_run_02_wf/bold_hmc_wf/split/vol0005.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep
_wf/single_subject_09_wf/func_preproc_ses_03_task_localizer_run_02_wf/bold_hmc_wf/split/vol0006.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_su
bject_09_wf/func_preproc_ses_03_task_localizer_run_02_wf/bold_hmc_wf/split/vol0007.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/f
unc_preproc_ses_03_task_localizer_run_02_wf/bold_hmc_wf/split/vol0008.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_s
es_03_task_localizer_run_02_wf/bold_hmc_wf/split/vol0009.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_03_task_lo
calizer_run_02_wf/bold_hmc_wf/split/vol0010.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_03_task_localizer_run_0
2_wf/bold_hmc_wf/split/vol0011.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_03_task_localizer_run_02_wf/bold_hmc
...skipping...
    self._run_interface()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 517, in _run_interface
    self._result = self._run_command(execute)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 650, in _run_command
    result = self._interface.run()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/base.py", line 1088, in run
    runtime = self._run_interface(runtime)
  File "/usr/local/miniconda/lib/python3.6/site-packages/fmriprep/interfaces/itk.py", line 140, in _run_interface
    pool = Pool(processes=num_threads, maxtasksperchild=100)
  File "/usr/local/miniconda/lib/python3.6/multiprocessing/context.py", line 119, in Pool
    context=self.get_context())
  File "/usr/local/miniconda/lib/python3.6/multiprocessing/pool.py", line 168, in __init__
    self._repopulate_pool()
  File "/usr/local/miniconda/lib/python3.6/multiprocessing/pool.py", line 233, in _repopulate_pool
    w.start()
  File "/usr/local/miniconda/lib/python3.6/multiprocessing/process.py", line 105, in start
    self._popen = self._Popen(self)
  File "/usr/local/miniconda/lib/python3.6/multiprocessing/context.py", line 277, in _Popen
    return Popen(process_obj)
  File "/usr/local/miniconda/lib/python3.6/multiprocessing/popen_fork.py", line 20, in __init__
    self._launch(process_obj)
  File "/usr/local/miniconda/lib/python3.6/multiprocessing/popen_fork.py", line 67, in _launch
    self.pid = os.fork()
OSError: [Errno 12] Cannot allocate memory

Node: fmriprep_wf.single_subject_MSC08_wf.anat_preproc_wf.surface_recon_wf.autorecon_resume_wf.recon_report
Working directory: /scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC08_wf/anat_preproc_wf/surface_recon_wf/autorecon_resume_wf/recon_report

Node inputs:

T1_files = <undefined>
T2_file = <undefined>
args = <undefined>
big_ventricles = <undefined>
brainstem = <undefined>
compress_report = auto
directive = autorecon3
environ = {}
expert = <undefined>
flags = <undefined>
generate_report = True
hemi = <undefined>
hippocampal_subfields_T1 = <undefined>
hippocampal_subfields_T2 = <undefined>
hires = <undefined>
ignore_exception = False
mprage = <undefined>
mri_aparc2aseg = <undefined>
mri_ca_label = <undefined>
mri_ca_normalize = <undefined>
mri_ca_register = <undefined>
mri_edit_wm_with_aseg = <undefined>
mri_em_register = <undefined>
mri_fill = <undefined>
mri_mask = <undefined>
mri_normalize = <undefined>
mri_pretess = <undefined>
mri_remove_neck = <undefined>
mri_segment = <undefined>
mri_segstats = <undefined>
mri_tessellate = <undefined>
mri_watershed = <undefined>
mris_anatomical_stats = <undefined>
mris_ca_label = <undefined>
mris_fix_topology = <undefined>
mris_inflate = <undefined>
mris_make_surfaces = <undefined>
mris_register = <undefined>
mris_smooth = <undefined>
mris_sphere = <undefined>
mris_surf2vol = <undefined>
mrisp_paint = <undefined>
openmp = <undefined>
out_report = report.html
parallel = <undefined>
subject_id = sub-MSC08
subjects_dir = /scratch/03763/oesteban/fmriprep-phase1/out/ds000224/freesurfer
talairach = <undefined>
terminal_output = <undefined>
use_T2 = <undefined>
Node: fmriprep_wf.single_subject_MSC08_wf.anat_preproc_wf.surface_recon_wf.autorecon_resume_wf.recon_report
Working directory: /scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC08_wf/anat_preproc_wf/surface_recon_wf/autorecon_resume_wf/recon_report

Node inputs:

T1_files = <undefined>
T2_file = <undefined>
args = <undefined>
big_ventricles = <undefined>
brainstem = <undefined>
compress_report = auto
directive = autorecon3
environ = {}
expert = <undefined>
flags = <undefined>
generate_report = True
hemi = <undefined>
hippocampal_subfields_T1 = <undefined>
hippocampal_subfields_T2 = <undefined>
hires = <undefined>
ignore_exception = False
mprage = <undefined>
mri_aparc2aseg = <undefined>
mri_ca_label = <undefined>
mri_ca_normalize = <undefined>
mri_ca_register = <undefined>
mri_edit_wm_with_aseg = <undefined>
mri_em_register = <undefined>
mri_fill = <undefined>
mri_mask = <undefined>
mri_normalize = <undefined>
mri_pretess = <undefined>
mri_remove_neck = <undefined>
mri_segment = <undefined>
mri_segstats = <undefined>
mri_tessellate = <undefined>
mri_watershed = <undefined>
mris_anatomical_stats = <undefined>
mris_ca_label = <undefined>
mris_fix_topology = <undefined>
mris_inflate = <undefined>
mris_make_surfaces = <undefined>
mris_register = <undefined>
mris_smooth = <undefined>
mris_sphere = <undefined>
mris_surf2vol = <undefined>
mrisp_paint = <undefined>
openmp = <undefined>
out_report = report.html
parallel = <undefined>
subject_id = sub-MSC08
subjects_dir = /scratch/03763/oesteban/fmriprep-phase1/out/ds000224/freesurfer
talairach = <undefined>
terminal_output = <undefined>
use_T2 = <undefined>
xopts = <undefined>

Traceback (most recent call last):
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/plugins/multiproc.py", line 51, in run_node
    result['result'] = node.run(updatehash=updatehash)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 407, in run
    self._run_interface()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 517, in _run_interface
    self._result = self._run_command(execute)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 650, in _run_command
    result = self._interface.run()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/base.py", line 1088, in run
    runtime = self._run_interface(runtime)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/common/report.py", line 53, in _run_interface
    ReportCapableInterface, self)._run_interface(runtime)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/base.py", line 1653, in _run_interface
    runtime.dependencies = get_dependencies(executable_name, runtime.environ)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/base.py", line 1467, in get_dependencies
    env=environ)
  File "/usr/local/miniconda/lib/python3.6/subprocess.py", line 707, in __init__
    restore_signals, start_new_session)
  File "/usr/local/miniconda/lib/python3.6/subprocess.py", line 1260, in _execute_child
    restore_signals, start_new_session, preexec_fn)
OSError: [Errno 12] Cannot allocate memory

Node: fmriprep_wf.single_subject_MSC09_wf.func_preproc_ses_func09_task_motor_run_02_wf.bold_reg_wf.bold_to_t1w_transform
Working directory: /scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_reg_wf/bold_to_t1w_tra
nsform

Node inputs:

args = <undefined>
default_value = 0.0
dimension = <undefined>
environ = {}
float = True
ignore_exception = False
input_image = ['/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0000.nii.
gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0001.nii.gz', '/scr
atch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0002.nii.gz', '/scratch/03763
/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0003.nii.gz', '/scratch/03763/oesteban/
fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0004.nii.gz', '/scratch/03763/oesteban/fmriprep-p
hase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0005.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work
/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0006.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/
fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0007.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_w
f/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0008.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_s
ubject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0009.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC
09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0010.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func
_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0011.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_s
es_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0012.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_
task_motor_run_02_wf/bold_hmc_wf/split/vol0013.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor
_run_02_wf/bold_hmc_wf/split/vol0014.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf
/bold_hmc_wf/split/vol0015.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_
wf/split/vol0016.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/v
ol0017.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0018.nii
.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0019.nii.gz', '/sc
ratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0020.nii.gz', '/scratch/0376
3/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0021.nii.gz', '/scratch/03763/oesteban
/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0022.nii.gz', '/scratch/03763/oesteban/fmriprep-
phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0023.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/wor
k/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0024.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224
/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0025.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_
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cratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0038.nii.gz', '/scratch/037
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/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0074.nii.gz', '/scratch/0
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func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0083.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_prepr
oc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0084.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_fun
c09_task_motor_run_02_wf/bold_hmc_wf/split/vol0085.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_m
otor_run_02_wf/bold_hmc_wf/split/vol0086.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_0
2_wf/bold_hmc_wf/split/vol0087.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_
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it/vol0089.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0090
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'/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0092.nii.gz', '/scratch/
03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0093.nii.gz', '/scratch/03763/oest
eban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0094.nii.gz', '/scratch/03763/oesteban/fmrip
rep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0095.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1
/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0096.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds00
0224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0097.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmrip
rep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0098.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/sin
gle_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0099.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subjec
t_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0100.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf
/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0101.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_prep
roc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/split/vol0102.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_fu
nc09_task_motor_run_02_wf/bold_hmc_wf/split/vol0103.nii.gz']
input_image_type = <undefined>
interpolation = LanczosWindowedSinc
interpolation_parameters = <undefined>
invert_transform_flags = <undefined>
num_threads = 8
out_postfix = _trans
output_image = <undefined>
print_out_composite_warp_file = <undefined>
reference_image = /scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_reg_wf/gen_ref/highres0
01_BrainExtractionBrain_reference.nii.gz
save_cmd = True
terminal_output = <undefined>
transforms = ['/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_reg_wf/bbreg_wf/fsl2itk_fw
d/affine.txt', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/nonlinear_sdc_wf/syn/ants_susc
eptibility0Warp.nii.gz', '/scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_motor_run_02_wf/bold_hmc_wf/fsl2itk/
mat2itk.txt']

Traceback (most recent call last):
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/plugins/multiproc.py", line 51, in run_node
    result['result'] = node.run(updatehash=updatehash)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 407, in run
    self._run_interface()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 517, in _run_interface
    self._result = self._run_command(execute)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 650, in _run_command
    result = self._interface.run()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/base.py", line 1088, in run
    runtime = self._run_interface(runtime)
  File "/usr/local/miniconda/lib/python3.6/site-packages/fmriprep/interfaces/itk.py", line 140, in _run_interface
    pool = Pool(processes=num_threads, maxtasksperchild=100)
  File "/usr/local/miniconda/lib/python3.6/multiprocessing/context.py", line 119, in Pool
    context=self.get_context())
  File "/usr/local/miniconda/lib/python3.6/multiprocessing/pool.py", line 168, in __init__
    self._repopulate_pool()
  File "/usr/local/miniconda/lib/python3.6/multiprocessing/pool.py", line 233, in _repopulate_pool
    w.start()
  File "/usr/local/miniconda/lib/python3.6/multiprocessing/process.py", line 105, in start
    self._popen = self._Popen(self)
  File "/usr/local/miniconda/lib/python3.6/multiprocessing/context.py", line 277, in _Popen
    return Popen(process_obj)
  File "/usr/local/miniconda/lib/python3.6/multiprocessing/popen_fork.py", line 20, in __init__
    self._launch(process_obj)
  File "/usr/local/miniconda/lib/python3.6/multiprocessing/popen_fork.py", line 67, in _launch
    self.pid = os.fork()
OSError: [Errno 12] Cannot allocate memory

Node: fmriprep_wf.single_subject_MSC09_wf.func_preproc_ses_func09_task_memoryfaces_wf.bold_reg_wf.bbreg_wf.bbregister
Working directory: /scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_memoryfaces_wf/bold_reg_wf/bbreg_wf/bbregis
ter

Node inputs:

args = <undefined>
compress_report = auto
contrast_type = t2
dof = 9
environ = {'SUBJECTS_DIR': '/opt/freesurfer/subjects'}
epi_mask = <undefined>
fsldof = <undefined>
generate_report = True
ignore_exception = False
init = <undefined>
init_cost_file = <undefined>
init_reg_file = /scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_memoryfaces_wf/bold_reg_wf/bbreg_wf/mri_coreg/
registration.lta
intermediate_file = <undefined>
out_fsl_file = <undefined>
out_lta_file = True
out_reg_file = <undefined>
out_report = report.svg
reg_frame = <undefined>
reg_middle_frame = <undefined>
registered_file = True
source_file = /scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_memoryfaces_wf/nonlinear_sdc_wf/skullstrip_bold_
wf/apply_mask/ants_susceptibility_Warped_masked.nii.gz
spm_nifti = <undefined>
subject_id = sub-MSC09
subjects_dir = /scratch/03763/oesteban/fmriprep-phase1/out/ds000224/freesurfer
terminal_output = <undefined>

Traceback (most recent call last):
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/plugins/multiproc.py", line 51, in run_node
    result['result'] = node.run(updatehash=updatehash)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 407, in run
    self._run_interface()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 517, in _run_interface
    self._result = self._run_command(execute)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 650, in _run_command
    result = self._interface.run()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/freesurfer/base.py", line 162, in run
    return super(FSCommand, self).run(**inputs)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/base.py", line 1088, in run
    runtime = self._run_interface(runtime)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/common/report.py", line 73, in _run_interface
    self._generate_report()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/common/report.py", line 176, in _generate_report
    compress=self.inputs.compress_report),
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/viz/utils.py", line 379, in plot_registration
    svg = extract_svg(display, compress=compress)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/viz/utils.py", line 206, in extract_svg
    image_svg = svg_compress(image_svg, compress)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/viz/utils.py", line 171, in svg_compress
    stdout=subprocess.PIPE, check=True).stdout
  File "/usr/local/miniconda/lib/python3.6/subprocess.py", line 403, in run
    with Popen(*popenargs, **kwargs) as process:
  File "/usr/local/miniconda/lib/python3.6/subprocess.py", line 707, in __init__
    restore_signals, start_new_session)
  File "/usr/local/miniconda/lib/python3.6/subprocess.py", line 1260, in _execute_child
    restore_signals, start_new_session, preexec_fn)
OSError: [Errno 12] Cannot allocate memory

Node: _lta_ras2ras0
Working directory: /scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_memorywords_wf/bold_reg_wf/bbreg_wf/lta_ras
2ras/mapflow/_lta_ras2ras0

Node inputs:

args = <undefined>
environ = {}
ignore_exception = False
in_fsl = <undefined>
in_itk = <undefined>
in_lta = /scratch/03763/oesteban/fmriprep-phase1/work/ds000224/fmriprep_wf/single_subject_MSC09_wf/func_preproc_ses_func09_task_memorywords_wf/bold_reg_wf/bbreg_wf/bbregister/ants_s
usceptibility_Warped_masked_bbreg_sub-MSC09.lta
in_mni = <undefined>
in_niftyreg = <undefined>
in_reg = <undefined>
invert = <undefined>
ltavox2vox = <undefined>
out_fsl = <undefined>
out_itk = <undefined>
out_lta = True
out_mni = <undefined>
out_reg = <undefined>
source_file = <undefined>
target_conform = <undefined>
target_file = <undefined>
terminal_output = <undefined>

Traceback (most recent call last):
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/plugins/multiproc.py", line 51, in run_node
    result['result'] = node.run(updatehash=updatehash)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 407, in run
    self._run_interface()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 517, in _run_interface
    self._result = self._run_command(execute)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 650, in _run_command
    result = self._interface.run()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/base.py", line 1088, in run
    runtime = self._run_interface(runtime)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/base.py", line 1653, in _run_interface
    runtime.dependencies = get_dependencies(executable_name, runtime.environ)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/base.py", line 1467, in get_dependencies
    env=environ)
  File "/usr/local/miniconda/lib/python3.6/subprocess.py", line 707, in __init__
    restore_signals, start_new_session)
  File "/usr/local/miniconda/lib/python3.6/subprocess.py", line 1260, in _execute_child
    restore_signals, start_new_session, preexec_fn)
OSError: [Errno 12] Cannot allocate memory

Node: fmriprep_wf.single_subject_09_wf.func_preproc_ses_04_task_localizer_run_01_wf.bold_confounds_wf.dvars
Working directory: /scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_04_task_localizer_run_01_wf/bold_confounds_wf/dvars

Node inputs:

figdpi = 100
figformat = png
figsize = (11.7, 2.3)
ignore_exception = False
in_file = /scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_04_task_localizer_run_01_wf/bold_reg_wf/merge/vol0000_xform-00000_m
erged.nii.gz
in_mask = /scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_04_task_localizer_run_01_wf/bold_reg_wf/mask_t1w_tfm/ants_susceptib
ility_Warped_brain_mask_maths_trans.nii.gz
intensity_normalization = 1000.0
remove_zerovariance = True
save_all = True
save_nstd = False
save_plot = False
save_std = True
save_vxstd = False
series_tr = <undefined>

Traceback (most recent call last):
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/plugins/multiproc.py", line 51, in run_node
    result['result'] = node.run(updatehash=updatehash)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 407, in run
    self._run_interface()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 517, in _run_interface
    self._result = self._run_command(execute)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 650, in _run_command
    result = self._interface.run()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/base.py", line 1088, in run
    runtime = self._run_interface(runtime)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/algorithms/confounds.py", line 143, in _run_interface
    intensity_normalization=self.inputs.intensity_normalization)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/algorithms/confounds.py", line 771, in compute_dvars
    mfunc = (mfunc / np.median(mfunc)) * intensity_normalization
MemoryError

Node: fmriprep_wf.single_subject_09_wf.func_preproc_ses_04_task_localizer_run_02_wf.bold_confounds_wf.tcompcor
Working directory: /scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_04_task_localizer_run_02_wf/bold_confounds_wf/tcompcor

Node inputs:

components_file = tcompcor.tsv
compress_report = auto
generate_report = True
header_prefix = <undefined>
high_pass_cutoff = 128.0
ignore_exception = False
ignore_initial_volumes = 0
mask_files = ['/scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_04_task_localizer_run_02_wf/bold_confounds_wf/csf_roi/eroded_m
ask.nii.gz']
mask_index = <undefined>
merge_method = <undefined>
num_components = 6
out_report = report.html
percentile_threshold = 0.05
pre_filter = cosine
realigned_file = /scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_04_task_localizer_run_02_wf/bold_reg_wf/merge/vol0000_xform-
00000_merged.nii.gz
regress_poly_degree = 1
repetition_time = 1.06
save_pre_filter = True
use_regress_poly = <undefined>

Traceback (most recent call last):
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/plugins/multiproc.py", line 51, in run_node
    result['result'] = node.run(updatehash=updatehash)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 407, in run
    self._run_interface()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 517, in _run_interface
    self._result = self._run_command(execute)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 650, in _run_command
    result = self._interface.run()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/base.py", line 1088, in run
    runtime = self._run_interface(runtime)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/common/report.py", line 53, in _run_interface
    ReportCapableInterface, self)._run_interface(runtime)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/algorithms/confounds.py", line 449, in _run_interface
    mask_images = self._process_masks(mask_images, imgseries.get_data())
  File "/home1/03763/oesteban/.local/lib/python3.6/site-packages/nibabel/spatialimages.py", line 572, in get_data
    data = np.asanyarray(self._dataobj)
  File "/usr/local/miniconda/lib/python3.6/site-packages/numpy/core/numeric.py", line 583, in asanyarray
    return array(a, dtype, copy=False, order=order, subok=True)
  File "/home1/03763/oesteban/.local/lib/python3.6/site-packages/nibabel/arrayproxy.py", line 145, in __array__
    raw_data = self.get_unscaled()
  File "/home1/03763/oesteban/.local/lib/python3.6/site-packages/nibabel/arrayproxy.py", line 140, in get_unscaled
    mmap=self._mmap)
  File "/home1/03763/oesteban/.local/lib/python3.6/site-packages/nibabel/volumeutils.py", line 524, in array_from_file
    n_read = infile.readinto(data_bytes)
  File "/usr/local/miniconda/lib/python3.6/gzip.py", line 276, in read
    return self._buffer.read(size)
MemoryError

Node: fmriprep_wf.single_subject_09_wf.func_preproc_ses_04_task_localizer_run_01_wf.bold_confounds_wf.signals
Working directory: /scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_04_task_localizer_run_01_wf/bold_confounds_wf/signals

Node inputs:

class_labels = ['WhiteMatter', 'GlobalSignal']
detrend = True
ignore_exception = False
in_file = /scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_04_task_localizer_run_01_wf/bold_reg_wf/merge/vol0000_xform-00000_m
erged.nii.gz
incl_shared_variance = True
include_global = False
label_files = ['/scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_04_task_localizer_run_01_wf/bold_confounds_wf/concat_rois/con
cat.nii.gz']
out_file = signals.tsv

Traceback (most recent call last):
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/plugins/multiproc.py", line 51, in run_node
    result['result'] = node.run(updatehash=updatehash)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 407, in run
    self._run_interface()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 517, in _run_interface
    self._result = self._run_command(execute)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 650, in _run_command
    result = self._interface.run()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/base.py", line 1088, in run
    runtime = self._run_interface(runtime)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/nilearn.py", line 83, in _run_interface
    signals.append(masker.fit_transform(self.inputs.in_file))
  File "/usr/local/miniconda/lib/python3.6/site-packages/nilearn/input_data/nifti_maps_masker.py", line 214, in fit_transform
    return self.fit().transform(imgs, confounds=confounds)
  File "/usr/local/miniconda/lib/python3.6/site-packages/nilearn/input_data/base_masker.py", line 176, in transform
    return self.transform_single_imgs(imgs, confounds)
  File "/usr/local/miniconda/lib/python3.6/site-packages/nilearn/input_data/nifti_maps_masker.py", line 320, in transform_single_imgs
    verbose=self.verbose)
  File "/usr/local/miniconda/lib/python3.6/site-packages/sklearn/externals/joblib/memory.py", line 283, in __call__
    return self.func(*args, **kwargs)
  File "/usr/local/miniconda/lib/python3.6/site-packages/nilearn/input_data/base_masker.py", line 66, in filter_and_extract
    imgs = _utils.check_niimg(imgs, atleast_4d=True, ensure_ndim=4)
  File "/usr/local/miniconda/lib/python3.6/site-packages/nilearn/_utils/niimg_conversions.py", line 271, in check_niimg
    niimg = load_niimg(niimg, dtype=dtype)
  File "/usr/local/miniconda/lib/python3.6/site-packages/nilearn/_utils/niimg.py", line 116, in load_niimg
    dtype = _get_target_dtype(niimg.get_data().dtype, dtype)
  File "/home1/03763/oesteban/.local/lib/python3.6/site-packages/nibabel/spatialimages.py", line 572, in get_data
    data = np.asanyarray(self._dataobj)
  File "/usr/local/miniconda/lib/python3.6/site-packages/numpy/core/numeric.py", line 583, in asanyarray
    return array(a, dtype, copy=False, order=order, subok=True)
  File "/home1/03763/oesteban/.local/lib/python3.6/site-packages/nibabel/arrayproxy.py", line 145, in __array__
    raw_data = self.get_unscaled()
  File "/home1/03763/oesteban/.local/lib/python3.6/site-packages/nibabel/arrayproxy.py", line 140, in get_unscaled
    mmap=self._mmap)
  File "/home1/03763/oesteban/.local/lib/python3.6/site-packages/nibabel/volumeutils.py", line 524, in array_from_file
    n_read = infile.readinto(data_bytes)
  File "/usr/local/miniconda/lib/python3.6/gzip.py", line 276, in read
    return self._buffer.read(size)
MemoryError

Node: fmriprep_wf.single_subject_09_wf.func_preproc_ses_03_task_localizer_run_02_wf.bold_mni_trans_wf.mask_mni_tfm
Working directory: /scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_03_task_localizer_run_02_wf/bold_mni_trans_wf/mask_mni_tfm

Node inputs:

args = <undefined>
default_value = 0.0
dimension = <undefined>
environ = {'NSLOTS': '1'}
float = True
ignore_exception = False
input_image = /scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_03_task_localizer_run_02_wf/nonlinear_sdc_wf/skullstrip_bold_wf
/combine_masks/ants_susceptibility_Warped_brain_mask_maths.nii.gz
input_image_type = <undefined>
interpolation = NearestNeighbor
interpolation_parameters = <undefined>
invert_transform_flags = <undefined>
num_threads = 1
out_postfix = _trans
output_image = <undefined>
print_out_composite_warp_file = <undefined>
reference_image = /scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_03_task_localizer_run_02_wf/bold_mni_trans_wf/gen_ref/1mm_T
1_reference.nii.gz
terminal_output = <undefined>
transforms = ['/scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/anat_preproc_wf/t1_2_mni/ants_t1_to_mniComposite.h5', '/scratch/03763/oesteban/
fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_03_task_localizer_run_02_wf/bold_reg_wf/bbreg_wf/fsl2itk_fwd/affine.txt']

Traceback (most recent call last):
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/plugins/multiproc.py", line 51, in run_node
    result['result'] = node.run(updatehash=updatehash)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 407, in run
    self._run_interface()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 517, in _run_interface
    self._result = self._run_command(execute)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 650, in _run_command
    result = self._interface.run()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/base.py", line 1088, in run
    runtime = self._run_interface(runtime)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/interfaces/fixes.py", line 24, in _run_interface
    runtime, correct_return_codes)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/base.py", line 1653, in _run_interface
    runtime.dependencies = get_dependencies(executable_name, runtime.environ)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/base.py", line 1467, in get_dependencies
    env=environ)
  File "/usr/local/miniconda/lib/python3.6/subprocess.py", line 707, in __init__
    restore_signals, start_new_session)
  File "/usr/local/miniconda/lib/python3.6/subprocess.py", line 1260, in _execute_child
    restore_signals, start_new_session, preexec_fn)
OSError: [Errno 12] Cannot allocate memory

Node: fmriprep_wf.single_subject_09_wf.func_preproc_ses_04_task_localizer_run_01_wf.bold_surf_wf.sampler
Working directory: /scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_04_task_localizer_run_01_wf/bold_surf_wf/_hemi_lh/sampler

Node inputs:

apply_rot = <undefined>
apply_trans = <undefined>
args = <undefined>
cortex_mask = True
environ = {'SUBJECTS_DIR': '/opt/freesurfer/subjects'}
fix_tk_reg = <undefined>
float2int_method = <undefined>
frame = <undefined>
hemi = <undefined>
hits_file = <undefined>
hits_type = <undefined>
ico_order = <undefined>
ignore_exception = False
interp_method = trilinear
mask_label = <undefined>
mni152reg = <undefined>
no_reshape = <undefined>
out_file = <undefined>
out_type = gii
override_reg_subj = <undefined>
projection_stem = <undefined>
reference_file = <undefined>
reg_file = <undefined>
reg_header = True
reshape = <undefined>
reshape_slices = <undefined>
sampling_method = average
sampling_range = (0.0, 1.0, 0.2)
sampling_units = frac
scale_input = <undefined>
smooth_surf = <undefined>
smooth_vol = <undefined>
source_file = ['/scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_04_task_localizer_run_01_wf/bold_surf_wf/rename_src/mapflow/_
rename_src0/fsaverage5.nii.gz']
subject_id = <undefined>
subjects_dir = /opt/freesurfer/subjects
surf_reg = <undefined>
surface = <undefined>
target_subject = ['fsaverage5']
terminal_output = <undefined>
vox_file = <undefined>

Traceback (most recent call last):
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/plugins/multiproc.py", line 51, in run_node
    result['result'] = node.run(updatehash=updatehash)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 407, in run
    self._run_interface()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 1326, in _run_interface
    updatehash=updatehash))
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 1232, in _collate_results
    (self.name, '\n'.join(msg)))
Exception: Subnodes of node: sampler failed:
Subnode 0 failed
Error:
Command:
mri_vol2surf --cortex --hemi lh --interp trilinear --o /scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_04_task_localizer_run_
01_wf/bold_surf_wf/_hemi_lh/sampler/mapflow/_sampler0/lh.fsaverage5.gii  --regheader sub-09 --projfrac-avg 0.000 1.000 0.200 --mov /scratch/03763/oesteban/fmriprep-phase1/work/ds000
232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_04_task_localizer_run_01_wf/bold_surf_wf/rename_src/mapflow/_rename_src0/fsaverage5.nii.gz --trgsubject fsaverage5
Standard output:
srcvol = /scratch/03763/oesteban/fmriprep-phase1/work/ds000232/fmriprep_wf/single_subject_09_wf/func_preproc_ses_04_task_localizer_run_01_wf/bold_surf_wf/rename_src/mapflow/_rename_
src0/fsaverage5.nii.gz
srcreg unspecified
srcregold = 0
srcwarp unspecified
surf = white
hemi = lh
trgsubject = fsaverage5
surfreg = sphere.reg
ProjFrac = 0.5
thickness = thickness
reshape = 0
interp = trilinear
float2int = round
GetProjMax = 0
INFO: float2int code = 0
niiRead(): NIFTI_UNITS_UNKNOWN, assuming mm

Standard error:
MRIallocSequence(128, 101, 132,380): could not allocate 51712 bytes for 31378th slice

Cannot allocate memory

Return code: 254

Some memory issues still persist:
171018-06:05:51,88 workflow ERROR:
         Node signals failed to run on host nid00625.
171018-06:05:51,89 workflow ERROR:
         Saving crash info to /scratch/03763/oesteban/fmriprep-phase1/out/ds000232/fmriprep/sub-09/log/20171018-043323_44a30a1d-c637-474d-9cd2-d372b1b12107/crash-20171018-060551-oesteban-signals-da27074e-2003-
4a55-901e-3454753dbae3.txt
Traceback (most recent call last):
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/plugins/multiproc.py", line 51, in run_node
    result['result'] = node.run(updatehash=updatehash)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 407, in run
    self._run_interface()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 517, in _run_interface
    self._result = self._run_command(execute)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/pipeline/engine/nodes.py", line 650, in _run_command
    result = self._interface.run()
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/base.py", line 1088, in run
    runtime = self._run_interface(runtime)
  File "/usr/local/miniconda/lib/python3.6/site-packages/niworkflows/nipype/interfaces/nilearn.py", line 83, in _run_interface
    signals.append(masker.fit_transform(self.inputs.in_file))
  File "/usr/local/miniconda/lib/python3.6/site-packages/nilearn/input_data/nifti_maps_masker.py", line 214, in fit_transform
    return self.fit().transform(imgs, confounds=confounds)
  File "/usr/local/miniconda/lib/python3.6/site-packages/nilearn/input_data/base_masker.py", line 176, in transform
    return self.transform_single_imgs(imgs, confounds)
  File "/usr/local/miniconda/lib/python3.6/site-packages/nilearn/input_data/nifti_maps_masker.py", line 254, in transform_single_imgs
    imgs_ = _utils.check_niimg_4d(imgs)
  File "/usr/local/miniconda/lib/python3.6/site-packages/nilearn/_utils/niimg_conversions.py", line 361, in check_niimg_4d
    dtype=dtype)
  File "/usr/local/miniconda/lib/python3.6/site-packages/nilearn/_utils/niimg_conversions.py", line 271, in check_niimg
    niimg = load_niimg(niimg, dtype=dtype)
  File "/usr/local/miniconda/lib/python3.6/site-packages/nilearn/_utils/niimg.py", line 116, in load_niimg
    dtype = _get_target_dtype(niimg.get_data().dtype, dtype)
  File "/home1/03763/oesteban/.local/lib/python3.6/site-packages/nibabel/spatialimages.py", line 572, in get_data
    data = np.asanyarray(self._dataobj)
  File "/usr/local/miniconda/lib/python3.6/site-packages/numpy/core/numeric.py", line 583, in asanyarray
    return array(a, dtype, copy=False, order=order, subok=True)
  File "/home1/03763/oesteban/.local/lib/python3.6/site-packages/nibabel/arrayproxy.py", line 145, in __array__
    raw_data = self.get_unscaled()
  File "/home1/03763/oesteban/.local/lib/python3.6/site-packages/nibabel/arrayproxy.py", line 140, in get_unscaled
  File "/home1/03763/oesteban/.local/lib/python3.6/site-packages/nibabel/arrayproxy.py", line 140, in get_unscaled
    mmap=self._mmap)
  File "/home1/03763/oesteban/.local/lib/python3.6/site-packages/nibabel/volumeutils.py", line 524, in array_from_file
    n_read = infile.readinto(data_bytes)
  File "/usr/local/miniconda/lib/python3.6/gzip.py", line 276, in read
    return self._buffer.read(size)
MemoryError

This memory error seems totally related to one on sampler (since they are executed close together and both were using the same compute node).

Worth considering packaging indexed_gzip, which should help reduce the memory footprint of these reads on large BOLD series. See nipy/nibabel#552.

Would it be just plug and play? Or we need to revise nibabel's loads?

Unfortunately, it had to be kept from being fully plug and play, because it clashed with an existing behavior of closing and releasing filehandles, to keep the OS from exhausting them, which apparently Gael ran into some years back.
To enable it (if available) nibabel.arrayproxy.KEEP_FILE_OPEN_DEFAULT needs to be set to 'auto'.
I would at to the top of run.py:
import nibabel
nibabel.arrayproxy.KEEP_FILE_OPEN_DEFAULT = 'auto'

I'm not sure how well that context will be passed when running function nodes, but it should work fine for anything that doesn't have to be pickled. We may want to do some tests.

Thanks a lot. Before going down that road, I think I've found the biggest issue here.
For ds000232/ sub-05_ses-04_task-main_run-01 we have the following:

Original file: 250MB, int16, grid of 102x102x30x940
Merged (bold_reg_wf) file: 5GB (uncompressed), float32, grid of 128x129x97x940.

I think we should calculate confounds (dvars, signals) on the original matrix size and possibly try float16?
The aftermath is related to https://neurostars.org/t/why-are-functional-data-files-output-by-fmriprep-in-t1w-space-so-much-larger/796/4?u=oesteban . We should definitely keep the original pixel resolution in T1w space.
I would unfold this memory issue in two:

[ ] Calculate confounds on the original space
[ ] When the T1w is selected as target space, keep the original resolution of the BOLD signal (do not conform to 2mm x 2mm x 2mm).

WDYT @chrisfilo, @effigies ?

@oesteban we are never conforming to 2x2x2 resolution - the original BOLD resolution is always used. See my comments here. I believe this is a field of view issue - I proposed a solution here.

Maybe a sensible approach for cropping BOLD series is to inflate the mask (1-2cm in all directions?), and crop that. fslroi would probably be the best tool for that in the short term. (Cropping should be in nibabel in the next release, but that's not always the fastest process.)

Ok, yes, I see that the resolution is the same. Only the extent of the volume is extended to that of the reference (T1w) image.
Well, that answers to the second question, when writing output files. I'm opening an issue to address that.
I'll first address that one, because we probably don't need to worry about the first one (calculate confounds on the original space) since we are applying all transforms at once. It should be equivalent.

@effigies  FYI cropping is implemented in nilearn. One downside of this approach is that each output file might have different field of view (dimensions in voxels) - across participants that is. Not sure if it matters for T1w space outputs though.


iOS mobile browsers Safari and Chrome don't detect the language

The expected implemented behaviour should be to set English as the default fallback language.

Source: https://www.hejto.pl/wpis/od-jakiegos-czasu-diffle-w-chrome-czy-safari-w-wersji-mobilnej-na-ios-wyglada-ja

The language is not a problem. There is something wrong with rendering icons in the header.

Settings have icons, buto details has a broken caret:


Feature Request: UI Change Dice Number input

Subject: Change UI for dice number input to make it way faster and the control less complicated.
Suggestion: Use the joystick (UP=1, RIGHT=2, DOWN=3, LEFT=4) and the UPPER two buttons on the right (TOP=5, MIDDLE=6) to let the user enter the dice numbers without having to extra confirm each number. Assign the 3rd button on the right (BOTTOM=BACKSPACE) to let the user delete the last entry. Show graphically on screen all numbers and how they are assigned to the joystick and the buttons, similar to the I/O Testscreen.
Once the entropy is completely put in, move to the usual "Caution / "I understand" screen.

This is a creative solution to make inputing dice rolls to go much more quickly. We would also probably need to add a notification screen before the input process began to explain to users which controls correlated with which dice rolls. I would be curious to get opinions on this approach from Nick or Keith.

We would also probably need to add a notification screen before the input process began to explain to users which controls correlated with which dice rolls.

Not necessary if it's done like I said above: While in "dice roll input mode" show a graphic exactly like the I/O-test-screen. Similar to the graphic I attached. No further explanation needed this way.

Another thought I have is to utilize the center press for 5, which frees up a button on the right, that could be used for an "abort" option to allow a user to back out without having to finish the entire entry process.

I thought about it as well. But I came to a different conclusion: Pressing the joystick button is the least comfortable button push and if you slide to the side by not pressing straight down you end up with a different key input. But the 5 will be demanded to be pushed way more often than "ABORTing" the process. So I'd assign the "ABORT-feature" to the joystick button push and remain the buttons to the right as suggested. On top if you press the joystick button, instead of instantly aborting the dice rolling process, the user could be requested to either "ABORT" the process, "CONTINUE" the dice rolling. Maybe even "CREATE SEED NOW (insecure)".


Register package

@JuliaRegistrator register

Registration pull request created: JuliaRegistries/General/64360
After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.
This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:
git tag -a v0.1.0 -m "<description of version>" bec3e4524477f0ba950dd9602e08bd0e2280fdf4
git push origin v0.1.0

After fixing [compat] requirements preventing AutoMerge in JuliaRegistries/General#64360, ready to try again.

@JuliaRegistrator register

Registration pull request updated: JuliaRegistries/General/64360
After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.
This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:
git tag -a v0.1.0 -m "<description of version>" ca1faaf698ed66aecc2a5e5bf6cc84ddb0680b43
git push origin v0.1.0

New package passes all checks, waiting 3 days for package to be merged into General.


how to use runCommand of mongodb

hi,
monk is really cool but there is a problem that im working on a little search engine with mongodb and m doing text search so i have to run
db.col.runCommand("text",{search:"gun", project: {"_id":0}});
but i did not find any way to use it with monk
please help me that how to use it with monk
thanks

Old issue but in case someone else has this same issue.
To do a full text search using monk, pass the $text operand into the find query.  Doing a full text search requires a text index on the field you want to search and there is only one text index allowed per collection.
Example finding string 'foo' in collection 'posts'.
db.get('posts').find({'$text': {'$search' : 'foo'}}, function(err, docs){
    // do something
});


Building with Ninja

I tried building several packages with Ninja as generator and everything seems to work great. Packaging is noticeably faster.
Since plans to support it popped up already in several discussions and mentions of Ninja are in scripts since initial commit, it seems like this approach has been invetigated before. Are there any hidden issues that need to be solved before vcpkg can use it by default? The way I see it, it's just a matter of tweaking few lines in vcpkg_*_cmake functions and adding Ninja to vcpkg_find_acquire_program.
The benefits would also include guarantee that user-wide integration does not affect packaging in any way. Additionally, adding Ninja as an available tool would make it easier to support third party buildsystems like Meson.

It shouldn't be used by default because not all libraries CMake scripts support it. But we can use it for some libraries after testing with Ninja.

I find that suprising because one of the main points of CMake is to abstract away differences beetween generators. One thing that comes to mind is that buildscript assumes specific layout of build directory, but I'm not sure what benefit it could bring.  Could you point me to an example of such problematic library?

I noticed that most often doesn't work libraries that call other tools (like code generation). I remember that aws-cpp-sdk with install also produce wrong result (I did not check why).
OpenCV for example cannot be compiled with Ninja https://github.com/opencv/opencv/issues/6372

I see, thanks. Nonetheless, since vast majority of libraries builds corrently, we may still consider using Ninja by default and simply make problematic ports pass "I don't like ninjas" flag to vcpkg_configure_cmake.
I've tried a few more packages and in addition to ports you mentioned SDL2 also fails due to some Resource Compiler error. On the other hand, bumping version of OpenCV to 3.2.0 may help, as the problematic line was changed there, see https://github.com/opencv/opencv/commit/33ab236ed3d34284374e8b2741ceedf19664edbf

I'd love to move to Ninja -- in addition to being faster, it also has fewer moving parts (and therefore less to debug when things go wrong). Most CMake scripts are designed with a single-configuration generator in mind, so that's another point in Ninja's favor. It might enable building the Release and Debug flavors in parallel. You can even see evidence of some previous attempts to use Ninja that we rolled back approximately around the time of the release to increase stability [1].
However, there are a few kinks that need to be worked out. If a project uses Precompile Headers, MSBuild will automatically insert the correct dependency tracking whereas Ninja needs special handling [2]. When building for UWP via Ninja, a lot of things aren't added by default, such as /APPCONTAINER and references to the core .winmd files. Inside vcpkg_build_cmake and vcpkg_install_cmake, we pass some MSBuild-specific flags that will also require additional communication between the configure step and the build step.
I would like to get to a point where we can use Ninja by default, however I think the right path for now is to enable it off-by-default, then try to apply it individually to each portfile. We can add it to the built-in template for the create command to encourage adoption by new ports (for desktop triplets).
[1] https://github.com/Microsoft/vcpkg/blob/ce9927f7327bc71ade246108a7d984deda6293fd/scripts/cmake/vcpkg_configure_cmake.cmake#L1
[2] https://github.com/Microsoft/cpprestsdk/blob/c1c673d/Release/src/CMakeLists.txt#L105-L108

@ras0219-msft Maybe report this issues to Ninja project? https://github.com/ninja-build/ninja/issues

@KindDragon I think that these issues are all in the CMake generator (Ninja is just running the commands requested with the dependency information given).
On the CMake side, I don't know if these would be considered bugs or not. The PCH issue appears to be quite well known for the last decade [1], for example, and it is simply considered a not-yet-implemented feature afaict. Digging through their bug database for the other issues I've mentioned, I think progress may have been made since I last attempted to use CMake for a WinRT project (a couple years ago). I don't have any good repro's sitting in front of me, so I can't really confirm/deny/file a useful bug.
The point I'd like to make with my past experiences is that it is unfortunately likely that a project currently building with MSBuild may not just work when switched to Ninja. Thus, I believe the prudent course is to switch portfiles over to using Ninja only when they can be tested to still work instead of all at once.
[1] https://cmake.org/Bug/view.php?id=1260

Ok, thanks

BTW vote for this issue https://gitlab.kitware.com/cmake/cmake/issues/1260

Packaging is noticeably faster.

Why is it (significantly) faster?
I understand Ninja is faster in a edit/compile/debug cycle but if a package is only build once it doesn't really matter does it?
And would this allow vcpkg to do it's thing without cmake at all?

Ninja can be faster than MSBuild because

it has a more fine-grained model for C++ compilation (MSBuild can't simultaneously see inside two different projects) which allows better parallelism.
it is lighter-weight, so the engine/scheduler consumes less CPU/memory/disk, which leaves more resources for the actual compiler/linker.

It has far fewer features than MSBuild as well, but that's fine for us because CMake provides the higher level features and "compiles" down to the lower-level Ninja.
As for Vcpkg working without CMake -- unfortunately that really can't happen in the near future, because a huge chunk of great libraries support windows using CMake. While we could do a bunch of work to remove our internal dependency on CMake (using it for the portfile language, using it for downloads, etc), we would still need it to build the actual library.
As an aside, it is the incredible prevalence of CMake in libraries that support Windows that caused us to take such a large dependency on it in the first place.

I'm going to close this issue with the merging of #628 since the primary task (add ninja support) has completed, however please feel free to continue asking questions/discussing Ninja here.

Since PREFER_NINJA was added to some packages, I had some trouble building those packages.
Apparently PREFER_NINJA has caused CMake to choose the wrong compiler for those packages on my machine. In my case I have MinGW-w64's gcc.exe and g++.exe in my PATH, which resulted in CMake to choose those over MSVC's cl.exe. That's because in CMakeDetermineCCompiler.cmake and CMakeDetermineCXXCompiler.cmake it is defined that way. The order is g++ aCC cl bcc xlC clang++ for CXX and gcc cl bcc xlc clang for C.
I could have solve it by removing MinGW-w64 out of my PATH or by changing the order in those two CMakeDetermine*Compiler.cmake files. But a better solution for me was to instead append a fix path to list(APPEND _csc_OPTIONS ... ) in scripts/cmake/vcpkg_configure_cmake.cmake, like:
list(APPEND _csc_OPTIONS
"-DCMAKE_CXX_COMPILER=C:/Program\ Files\ (x86)/Microsoft\ Visual\ Studio\ 14.0/VC/bin/amd64/cl.exe"
"-DCMAKE_C_COMPILER=C:/Program\ Files\ (x86)/Microsoft\ Visual\ Studio\ 14.0/VC/bin/amd64/cl.exe"
...)
Not sure if that's a good solution or not, but it works for me. Maybe there's a better way for PREFER_NINJA to not trigger another compiler.


Update to 0.20.7, update recipe, add more platforms

Checklist

[ ] Used a personal fork of the feedstock to propose changes
[ ] Bumped the build number (if the version is unchanged)
[ ] Reset the build number to 0 (if the version changed)
[ ] Re-rendered with the latest conda-smithy (Use the phrase @conda-forge-admin, please rerender in a comment in this PR for automated rerendering)
[ ] Ensured the license file is being packaged.

Hi! This is the friendly automated conda-forge-linting service.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe/meta.yaml) and found it was in an excellent condition.

@conda-forge-admin, please rerender

@synapticarbors Ready for review / merge :)

Real solution in https://github.com/conda-forge/eza-feedstock/pull/35 ... will submit that to upstream

done via https://github.com/conda-forge/eza-feedstock/pull/35


Test failure: ThrowsWhenNotOptionalAndDirectoryDoesntExist

This test fails occasionally with the following error:
Assert.Contains() Failure
Not found: The directory name
In value:  The path must be absolute.
Parameter name: root
   at Microsoft.Extensions.Configuration.KeyPerFile.Test.KeyPerFileTests.ThrowsWhenNotOptionalAndDirectoryDoesntExist() in /_/test/Config.KeyPerFile.Test/KeyPerFileTests.cs:line 31

Other tests within that build may have failed with a similar message, but they are not listed here. Check the link above for more info.
This test failed on master.
CC @Eilon (because the bot doesn't know who else to pick)
This issue was made automatically. If there is a problem contact ryanbrandenburg.

Please use this workflow to address this flaky test issue, including checking applicable checkboxes and filling in the applicable "TODO" entries:

Is this actually a flaky test?

No, this is a regular test failure, fix the test/product (TODO: Link to commit/PR)
Yes, proceed below...

Is this test failure caused by product code flakiness? (Either this product, or another product this test depends on.)

[ ] File a bug against the product (TODO: Link to other bug)
Is it possible to change the test to avoid the flakiness?

Yes? Go to the "Change the test!" section.
No?

[ ] Disable the test (TODO: Link to PR/commit)
[ ] Wait for other bug to be resolved
[ ] Wait for us to get build that has the fix
[ ] Re-enable our test (TODO: Link to PR/commit)
[ ] Close this bug

Is it that the test itself is flaky? This includes external transient problems (e.g. remote server problems, file system race condition, etc.)

Is there is a way to change our test to avoid this flakiness?

Yes? Change the test!

[ ] Change the test to avoid the flakiness, for example by using a different test strategy, or by adding retries w/ timeouts (TODO: Link to PR/commit)
[ ] Run the test 100 times locally as a sanity check.
[ ] Close this bug

No?

Is there any logging or extra information that we could add to make this more diagnosable when it happens again?

Yes?

[ ] Add the logging (TODO: Link to PR/commit)

No?

[ ] Delete the test because flaky tests are not useful (TODO: Link to PR/commit)

This comment was made automatically. If there is a problem contact ryanbrandenburg.

ThrowsWhenNotOptionalAndDirectoryDoesntExist failed with about the same error on master.
This comment was made automatically. If there is a problem contact ryanbrandenburg.

@HaoK can you take a look? Doesn't look like there have been a lot of changes to this repo in a while...  The last real change I could find is from 3+ months ago: https://github.com/aspnet/Configuration/commit/3e2d00cdf5602f8afcde53558654dee80c7083fc

Hrm this is a weird one, the test is pretty much just testing what happens when you feed in a bogus file.  So this means we are getting different errors when a file doesn't exist now, I'll see if something else changed lower in the stack...
        [Fact]
        public void ThrowsWhenNotOptionalAndDirectoryDoesntExist()
        {
            var e = Assert.Throws<ArgumentException>(() => new ConfigurationBuilder().AddKeyPerFile("nonexistent", false).Build());
            Assert.Contains("The directory name", e.Message);
        }

Ah looks like @pranavkm made some changes to PhysicalFileWatcher to lazily create the file watcher, so we are getting a different exception now, I can just update the test to look for the absolute error message, before we were getting the directory not existing from CreateFileWatcher which is no longer invoked in the ctor.
https://github.com/aspnet/FileSystem/commit/b9986fc364ec439606f998d44e02be71a922aec7#diff-f6ace54f687eecc90df2427e721b8f65

Fixed via https://github.com/aspnet/Configuration/pull/870


added verticalDown feature

added verticalDown option. default is set to false.
the allows carousel to scroll downward instead of upward. the only catch to this is you have to set the slidesToShow to all of your slides minus the slidesToScroll you want. In your styles, you can overflow:hidden a desired height as to not show ALL the slides at once.
Best I could do with the time at hand.


Export the styles as CSS instead of less

The npm package ships with a .less styles file.
This is not very usable for projects not running .less. Exporting a .css file would greatly enhance usability.

thanks for your feedback. style.css was added in 0.1.1


Point to New Jersey's REST address layer

Could not retrieve this chunk of objects from ESRI source: HTTP 502

Maybe try restarting this one? Looks like their server hiccuped

Looks like we are considered abuse. Might make sense to cache this dataset using a much slower download process.

It might be worth adding a retry mechanism with backoff?

Yeah good idea, I’ll put that on the list.

Pulling in the GDB is easier on us and their server, so I'm going to close this.


Vite Storybook Integration

Add storybook support for new react components. Included the experimental Vite core for Storybook so expect inconsistencies!
Changes proposed in this pull request:

add storybook dependencies and base configuration
add addons to handle setting the kitsu theme
add sample story for button component

/cc @hummingbird-me/staff

Closing since we eventually merged this in some form 🙏


Add v3.0-preview APIs for LUIS

Latest improvements:
MSFT employees can try out our new experience at OpenAPI Hub  - one location for using our validation tools and finding your workflow.

Contribution checklist:

[x] I have reviewed the documentation for the workflow.
[x] Validation tools were run on swagger spec(s) and have all been fixed in this PR.
[x] The OpenAPI Hub was used for checking validation status and next steps.

ARM API Review Checklist

[ ] Service team MUST add the "WaitForARMFeedback" label if the management plane API changes fall into one of the below categories.
adding/removing APIs.
adding/removing properties.
adding/removing API-version.
adding a new service in Azure.

Failure to comply may result in delays for manifest application. Note this does not apply to data plane APIs.

[ ] If you are blocked on ARM review and want to get the PR merged urgently, please get the ARM oncall for reviews (RP Manifest Approvers team under Azure Resource Manager service) from IcM and reach out to them.
Please follow the link to find more details on API review process.

Automation for azure-sdk-for-python

Automation for azure-sdk-for-ruby

Automation for azure-sdk-for-js

Automation for azure-sdk-for-java

Automation for azure-sdk-for-go

Can one of the admins verify this patch?

Since this is introducing a new version, we need to get approval from ARM team

I am fine with these changes. But, before merge ARM Team has to approve this PR (since this is a new version). So, I added appropriate label and wait for them.

Since this is introducing a new version, we need to get approval from ARM team

We already got an approval from the Azure review board, is that enough?

Besides, the default PR description template says that this doesn't apply for date-plane APIs. Which I assume is our case because "data-plane" is in the path of our service swagger files.

ARM won't review data plane apis.. so removing the tag WaitForARMFeedback.


[ERROR] Could not resolve "framer-motion"

node_modules/@zener/nepali-datepicker-react/dist/index.mjs:1:131:
1 │ ...e as kt,motion as It}from"framer-motion";import{useEffect as Te,...
You can mark the path "framer-motion" as external to exclude it from the bundle, which will remove this error.

hi @dipbazz, I have updated the package with commit a22c8f9dc7e5ffebf4fa72aa7d85fae8d7e550e7.
Please try clean installing the updated package v1.1.1.

Hi @tulsiojha, Thank you for the fix.

Since the issue is resolved. This issue is closed now.


"one, two, three" example on website is missing FROM clause

The query below at the https://postgresml.org/ front page is missing the FROM and doesn't work.
SELECT pgml.predict(
  'Sales Forecasting',
  ARRAY[
    last_week_sales,
    week_of_year
  ]
) AS prediction
ORDER BY prediction DESC

I think it should be:
SELECT pgml.predict(
  'Sales Forecasting',
  ARRAY[
    last_week_sales,
    week_of_year
  ]
) AS prediction
FROM hist_sales
ORDER BY prediction DESC

...since hist_sales is the relation_name in the pgml.train command, or maybe some other like current_sales, but no table at all seems confusing.

Good catch. We'll get this fixed.


[SPARK-50109][PYTHON][DOCS] Refine the docstring for more date functions

What changes were proposed in this pull request?
Refine the docstring for more date functions
Why are the changes needed?
1, make example copy-pasteable;
2, clarify str is a column name or literal string;
3, show both the input columns and output columns, to make the projection more clear;
4, improve the test coverage by adding more doctests;
Does this PR introduce any user-facing change?
doc change
How was this patch tested?
ci
Was this patch authored or co-authored using generative AI tooling?
no

LGTM, thank you!

Merged to master for Apache Spark 4.0.0 on February 2025.
Thank you, @zhengruifeng and @xinrong-meng .

thank you @dongjoon-hyun and @xinrong-meng so much!


⚠ GitLab Server has degraded performance

In 05411a6, GitLab Server (https://gitlab01.its-telekom.eu) experienced degraded performance:

HTTP code: 200
Response time: 7100 ms

Resolved: GitLab Server performance has improved in b8a4e65.


Books review/tags functionality

reviews are done.  for book tags.. currently it's just whatever category googleApi gives us.  Does that work or are you thinking something else?


Support Zero-3?

I used accelerate launch with ZERO-3 to run train.llama.infini.noclm.1Mseq.sh.
But I got this:
RuntimeError: Function 'LinearFunctionForZeroStage3Backward' returned nan values in its 0th output

I have this question too


Create custom role APIs

resolves #2493

Hi @mohaldu - please don't use force-push in this repo... we always squash-and-merge anyway, so it is not necessary. See CONTRIBUTING.md for more details.

Hi @gmlewis  thanks for the review, all changes made

@mohaldu - please run go generate ./... at the top of the repo then push the resulting changes.
See CONTRIBUTING.md for more details.

Thank you, @valbeat !
Merging.