def download_outputs(path_prefix, creds_path, bucket_name, qap_type, \
download_to):
import pickle
from CPAC.AWS import fetch_creds
from CPAC.AWS.aws_utils import s3_download
src_list = []
bucket = fetch_creds.return_bucket(creds_path, bucket_name)
if qap_type == "anat_spatial":
search_for = "anatomical_spatial"
elif qap_type == "func_spatial":
search_for = "functional_spatial"
elif qap_type == "func_temporal":
search_for = "functional_temporal"
for k in bucket.list(prefix=path_prefix):
k_name = str(k.name)
if (search_for in k_name) and (".csv" in k_name):
src_list.append(k_name)
s3_download(bucket, src_list, download_to)
def download_outputs(path_prefix, creds_path, bucket_name, qap_type, \
download_to):
import pickle
from CPAC.AWS import fetch_creds
from CPAC.AWS.aws_utils import s3_download
src_list = []
bucket = fetch_creds.return_bucket(creds_path, bucket_name)
if qap_type == "anat_spatial":
search_for = "anatomical_spatial"
elif qap_type == "func_spatial":
search_for = "functional_spatial"
elif qap_type == "func_temporal":
search_for = "functional_temporal"
for k in bucket.list(prefix=path_prefix):
k_name = str(k.name)
if (search_for in k_name) and (".csv" in k_name):
src_list.append(k_name)
s3_download(bucket, src_list, download_to)
def dl_subj_from_s3(subj_idx, cfg_file, s3_dict_yaml):
'''
'''
# Import packages
from CPAC.AWS import fetch_creds, aws_utils
import yaml
# Load config file
with open(cfg_file,'r') as f:
cfg_dict = yaml.load(f)
# Init variables
bucket_prefix = cfg_dict["bucket_prefix"]
local_prefix = cfg_dict["local_prefix"]
bucket_name = cfg_dict["bucket_name"]
creds_path = cfg_dict["creds_path"]
bucket = fetch_creds.return_bucket(creds_path, bucket_name)
s3_list = []
s3_dict = {}
# pull in S3 dict yaml
with open(s3_dict_yaml,'r') as f:
s3_dict = yaml.load(f)
if len(s3_dict) == 0:
err = "\n[!] Filepaths have not been successfully gathered from " \
"the filepath YAML dictionary!\n"
raise Exception(err)
# Get list of subject keys for indexing
sd_keys = s3_dict.keys()
sd_keys.sort()
# Grab subject dictionary of interest
subj_key = sd_keys[subj_idx-1]
sub_dict = s3_dict[subj_key]
# Download subject data to local prefix
s3_dl = []
for s3_key, s3_path in sub_dict.items():
s3_dl.append(s3_path)
sub_dict[s3_key] = s3_path.replace(bucket_prefix, local_prefix)
aws_utils.s3_download(bucket, s3_dl, local_prefix=local_prefix, \
bucket_prefix=bucket_prefix)
sub_dict = {subj_key : sub_dict}
# Return single subject dictionary
return sub_dict
def dl_subj_from_s3(subj_idx, cfg_file, s3_dict_yaml):
'''
'''
# Import packages
from CPAC.AWS import fetch_creds, aws_utils
import yaml
# Load config file
with open(cfg_file, 'r') as f:
cfg_dict = yaml.load(f)
# Init variables
bucket_prefix = cfg_dict["bucket_prefix"]
local_prefix = cfg_dict["local_prefix"]
bucket_name = cfg_dict["bucket_name"]
creds_path = cfg_dict["creds_path"]
bucket = fetch_creds.return_bucket(creds_path, bucket_name)
s3_list = []
s3_dict = {}
# pull in S3 dict yaml
with open(s3_dict_yaml, 'r') as f:
s3_dict = yaml.load(f)
if len(s3_dict) == 0:
err = "\n[!] Filepaths have not been successfully gathered from " \
"the filepath YAML dictionary!\n"
raise Exception(err)
# Get list of subject keys for indexing
sd_keys = s3_dict.keys()
sd_keys.sort()
# Grab subject dictionary of interest
subj_key = sd_keys[subj_idx - 1]
sub_dict = s3_dict[subj_key]
# Download subject data to local prefix
s3_dl = []
for s3_key, s3_path in sub_dict.items():
s3_dl.append(s3_path)
sub_dict[s3_key] = s3_path.replace(bucket_prefix, local_prefix)
aws_utils.s3_download(bucket, s3_dl, local_prefix=local_prefix, \
bucket_prefix=bucket_prefix)
sub_dict = {subj_key: sub_dict}
# Return single subject dictionary
return sub_dict
key_list = []
for i, k in enumerate(bucket.list(prefix=s3_prefix)):
key_list.append(str(k.name).replace(s3_prefix, ''))
# Fetch all unique participant codes.
participants = [k.split('/')[0] for k in key_list if 'sub-' in k]
participants = sorted(list(set(participants)))
participants = participants[0:4]
downloads_list = [
os.path.join(s3_prefix, k) for k in key_list
if ('sub-' in k and k.split('/')[0] in participants) or ('sub-' not in k)
]
# Download the files.
aws_utils.s3_download(bucket, downloads_list, tmp, bucket_prefix=s3_prefix)
# Run the BIDS validator- save the output to a file that is based off the last 'subdirectory'
# in the prefix.
validator_output = commands.getoutput('bids-validator %s' % tmp)
shutil.rmtree(tmp)
# E-mail the output to me and Dave.
email_list = ['*****@*****.**', '*****@*****.**']
msg = MIMEText(validator_output)
msg['Subject'] = 'BIDS validation results for %s' % (s3_prefix)
msg['From'] = '*****@*****.**'
msg['To'] = '; '.join(email_list)
s = smtplib.SMTP('localhost')
s.sendmail('*****@*****.**', email_list, msg.as_string())
fixed = os.path.join(tmp, 'fixed', s3_prefix.split('/')[-2])
orig = os.path.join(tmp, 'orig', s3_prefix.split('/')[-2])
if not os.path.exists(fixed):
os.makedirs(fixed)
if not os.path.exists(orig):
os.makedirs(orig)
# Fetch 4 participants from the BIDS dataset and download to a temporary directory.
# Start by fetching all keys.
bucket = fetch_creds.return_bucket(creds, 'fcp-indi')
key_list = []
for i, k in enumerate(bucket.list(prefix=s3_prefix)):
if 'participants.tsv' in str(k.name):
key_list.append(str(k.name))
# Download the files.
aws_utils.s3_download(bucket, key_list, orig, bucket_prefix=s3_prefix)
# Change NaNs to 'n/a'.
df = pd.read_csv(os.path.join(orig, 'participants.tsv'), sep='\t')
df.to_csv(os.path.join(fixed, 'participants.tsv'),
sep='\t',
na_rep='n/a',
header=True,
index=False)
aws_utils.s3_upload(bucket, [os.path.join(fixed, 'participants.tsv')],
['/'.join([s3_prefix, 'participants.tsv'])],
make_public=True,
overwrite=True)
stratdict[strat][subtar][f]['size']
for f in stratdict[strat][subtar].keys()
]) / (1024.**3)
print subsize_gb
if (subsize_gb >= 2.5) and (subsize_gb <= 3.2):
filestopull = [
stratdict[strat][sub][f]['name'] for sub in tarlist
for f in stratdict[strat][sub].keys()
]
while not os.path.isfile('./' + filestopull[-1].replace(
'data/Projects/ACPI/Outputs/', './')):
try:
aws_utils.s3_download(
bucket,
filestopull,
'./',
bucket_prefix='data/Projects/ACPI/Outputs/')
except:
print "DL Falied, Trying Again"
tarname = strat + '_' + tarlist[0] + '_' + tarlist[-1]
print 'Tarring', tarlist, tarname
fo.write(tarname + '\n')
tar = tarfile.open(tarname + '.tar.gz', 'w:gz')
tar.add(strat + '/')
tar.close()
shutil.rmtree(strat)
aws_utils.s3_upload(
bucket, [tarname + '.tar.gz'],
['data/Projects/ACPI/OutputTars/' + tarname + '.tar.gz'])
os.remove(tarname + '.tar.gz')
def main(sub_idx):
# Init variables
bucket_name = 'fcp-indi'
bucket_prefix = 'data/Projects/ABIDE_Initiative/Outputs/cpac/raw_outputs_rerun'
config_file = '/home/ubuntu/abide_run/settings/pipeline_config_abide_rerun.yml'
creds_path = '/home/ubuntu/secure-creds/aws-keys/fcp-indi-keys2.csv'
local_prefix = '/mnt/eigen_run'
sublist_file = '/home/ubuntu/abide_run/eig-subs1.yml'
# Pull in bucket, config, and subject
sublist = yaml.load(open(sublist_file, 'r'))
subject = sublist[sub_idx]
sub_id = subject.split('_')[-1]
bucket = fetch_creds.return_bucket(creds_path, bucket_name)
c = Configuration(yaml.load(open(config_file, 'r')))
# Test to see if theyre already upload
to_do = True
if to_do:
## Collect functional_mni list from S3 bucket
filt_global = 'pipeline_abide_rerun__freq-filter/%s_session_1/functional_mni/_scan_rest_1_rest/_csf_threshold_0.96/_gm_threshold_0.7/_wm_threshold_0.96/_compcor_ncomponents_5_selector_pc10.linear1.wm0.global1.motion1.quadratic1.gm0.compcor1.csf0/_bandpass_freqs_0.01.0.1/bandpassed_demeaned_filtered_antswarp.nii.gz' % sub_id
filt_noglobal = filt_global.replace('global1', 'global0')
nofilt_global = 'pipeline_abide_rerun/%s_session_1/functional_mni/_scan_rest_1_rest/_csf_threshold_0.96/_gm_threshold_0.7/_wm_threshold_0.96/_compcor_ncomponents_5_selector_pc10.linear1.wm0.global1.motion1.quadratic1.gm0.compcor1.csf0/residual_antswarp.nii.gz' % sub_id
nofilt_noglobal = nofilt_global.replace('global1', 'global0')
s3_functional_mni_list = [
filt_global, filt_noglobal, nofilt_global, nofilt_noglobal
]
s3_functional_mni_list = [
os.path.join(bucket_prefix, s) for s in s3_functional_mni_list
]
# Download contents to local inputs directory
try:
aws_utils.s3_download(bucket,
s3_functional_mni_list,
local_prefix=os.path.join(
local_prefix, 'centrality_inputs'),
bucket_prefix=bucket_prefix)
except Exception as e:
print 'Unable to find eigenvector centrality inputs for subject %s, skipping...' % sub_id
print 'Error: %s' % e
return
# Build strat dict (dictionary of strategies and local input paths)
strat_dict = {
'filt_global':
os.path.join(local_prefix, 'centrality_inputs', filt_global),
'filt_noglobal':
os.path.join(local_prefix, 'centrality_inputs', filt_noglobal),
'nofilt_noglobal':
os.path.join(local_prefix, 'centrality_inputs', nofilt_noglobal),
'nofilt_global':
os.path.join(local_prefix, 'centrality_inputs', nofilt_global)
}
# Create list of processes
proc_list = [
Process(target=make_workflow,
args=(in_name, strat, sub_id, c, local_prefix))
for strat, in_name in strat_dict.items()
]
# Iterate through processes and fire off
for p in proc_list:
p.start()
for p in proc_list:
if p.is_alive():
p.join()
# Gather outputs
wfs = glob.glob(os.path.join(local_prefix, 'eigen_wf_%s_*' % sub_id))
local_list = []
for wf in wfs:
for root, dirs, files in os.walk(wf):
if files:
local_list.extend([os.path.join(root, f) for f in files])
s3_list = [
loc.replace(
local_prefix,
'data/Projects/ABIDE_Initiative/Outputs/cpac/raw_outputs_eigen'
) for loc in local_list
]
aws_utils.s3_upload(bucket, local_list, s3_list)
# And delete working directories
try:
for input_file in strat_dict.values():
print 'removing input file %s...' % input_file
os.remove(input_file % sub_id)
except Exception as e:
print 'Unable to remove input files'
print 'Error: %s' % e
work_dirs = glob.glob(
os.path.join(local_prefix, 'eigen_wf_%s_*' % sub_id))
for work_dir in work_dirs:
print 'removing %s...' % work_dir
shutil.rmtree(work_dir)
else:
print 'subject %s already processed and uploaded, skipping...' % sub_id
def main(sub_idx):
# Init variables
bucket_name = 'fcp-indi'
bucket_prefix = 'data/Projects/ABIDE_Initiative/Outputs/cpac/raw_outputs_rerun'
config_file = '/home/ubuntu/abide_run/settings/pipeline_config_abide_rerun.yml'
creds_path = '/home/ubuntu/secure-creds/aws-keys/fcp-indi-keys2.csv'
local_prefix = '/mnt/eigen_run'
sublist_file = '/home/ubuntu/abide_run/eig-subs1.yml'
# Pull in bucket, config, and subject
sublist = yaml.load(open(sublist_file, 'r'))
subject = sublist[sub_idx]
sub_id = subject.split('_')[-1]
bucket = fetch_creds.return_bucket(creds_path, bucket_name)
c = Configuration(yaml.load(open(config_file, 'r')))
# Test to see if theyre already upload
to_do = True
if to_do:
## Collect functional_mni list from S3 bucket
filt_global = 'pipeline_abide_rerun__freq-filter/%s_session_1/functional_mni/_scan_rest_1_rest/_csf_threshold_0.96/_gm_threshold_0.7/_wm_threshold_0.96/_compcor_ncomponents_5_selector_pc10.linear1.wm0.global1.motion1.quadratic1.gm0.compcor1.csf0/_bandpass_freqs_0.01.0.1/bandpassed_demeaned_filtered_antswarp.nii.gz' % sub_id
filt_noglobal = filt_global.replace('global1','global0')
nofilt_global = 'pipeline_abide_rerun/%s_session_1/functional_mni/_scan_rest_1_rest/_csf_threshold_0.96/_gm_threshold_0.7/_wm_threshold_0.96/_compcor_ncomponents_5_selector_pc10.linear1.wm0.global1.motion1.quadratic1.gm0.compcor1.csf0/residual_antswarp.nii.gz' % sub_id
nofilt_noglobal = nofilt_global.replace('global1','global0')
s3_functional_mni_list = [filt_global, filt_noglobal, nofilt_global, nofilt_noglobal]
s3_functional_mni_list = [os.path.join(bucket_prefix, s) for s in s3_functional_mni_list]
# Download contents to local inputs directory
try:
aws_utils.s3_download(bucket, s3_functional_mni_list, local_prefix=os.path.join(local_prefix, 'centrality_inputs'), bucket_prefix=bucket_prefix)
except Exception as e:
print 'Unable to find eigenvector centrality inputs for subject %s, skipping...' % sub_id
print 'Error: %s' % e
return
# Build strat dict (dictionary of strategies and local input paths)
strat_dict = {'filt_global' : os.path.join(local_prefix, 'centrality_inputs', filt_global),
'filt_noglobal' : os.path.join(local_prefix, 'centrality_inputs', filt_noglobal),
'nofilt_noglobal' : os.path.join(local_prefix, 'centrality_inputs', nofilt_noglobal),
'nofilt_global' : os.path.join(local_prefix, 'centrality_inputs', nofilt_global)}
# Create list of processes
proc_list = [Process(target=make_workflow, args=(in_name, strat, sub_id, c, local_prefix)) for strat, in_name in strat_dict.items()]
# Iterate through processes and fire off
for p in proc_list:
p.start()
for p in proc_list:
if p.is_alive():
p.join()
# Gather outputs
wfs = glob.glob(os.path.join(local_prefix, 'eigen_wf_%s_*' % sub_id))
local_list = []
for wf in wfs:
for root, dirs, files in os.walk(wf):
if files:
local_list.extend([os.path.join(root, f) for f in files])
s3_list = [loc.replace(local_prefix, 'data/Projects/ABIDE_Initiative/Outputs/cpac/raw_outputs_eigen') for loc in local_list]
aws_utils.s3_upload(bucket, local_list, s3_list)
# And delete working directories
try:
for input_file in strat_dict.values():
print 'removing input file %s...' % input_file
os.remove(input_file % sub_id)
except Exception as e:
print 'Unable to remove input files'
print 'Error: %s' %e
work_dirs = glob.glob(os.path.join(local_prefix, 'eigen_wf_%s_*' % sub_id))
for work_dir in work_dirs:
print 'removing %s...' % work_dir
shutil.rmtree(work_dir)
else:
print 'subject %s already processed and uploaded, skipping...' % sub_id
