r.raise_for_status() # in case the abort URL is effed
sys.exit(1)
# now that we have our params, let's do cool stuff with them
command = params['command']
args = params.get('args', [])
kwargs = params.get('kwargs', {})
if command not in GDAL_COMMANDS:
requests.post(abort_url, data={
'error_text': "{command} is not a valid GDAL or OGR command".format(command=command)
})
# okay, we have a valid command and some params. we're sure we're going to run this thing
# so let's get the data
tmpd = tempfile.mkdtmp()
os.chroot(tmpd)
source_data_filename = os.path.split(source_data_filename)[-1]
try:
r = requests.get(source_data_url)
with open(source_data_filename, 'wb') as f:
for chunk in r.iter_content(chunk_size):
fd.write(chunk)
except requests.ConnectionError as e:
requests.post(abort_url, data={
'error_text': str(e)
})
r.raise_for_status() # in case the abort URL is effed
sys.exit(1)
#
# Arguments:
# * channel_group: the channel group index to process
# * filename: the filename of the KWIK file
# * params: a dictionary with all KK parameters
import os
import shutil
import tempfile
from spikedetekt2.dataio import Experiment
# get the basename (filename without the extension)
basename = os.path.splitext(filename)[0]
# Create a temporary working folder where we're going to run KK.
tmpdir = tempfile.mkdtmp()
curdir = os.getpwd()
os.chdir(tmpdir)
# Create the filenames of the .fet and .fmask files to create.
filename_fet = os.path.join(tmpdir, basename + '.fet')
filename_fmask = os.path.join(tmpdir, basename + '.fmask')
filename_clu = os.path.join(tmpdir, basename + '.clu')
with Experiment(filename) as exp: # Open in read-only, close the file at the end of the block
# Load all features and masks in memory.
# WARNING: this might consume to much Ram ==> need to do it by chunks.
fm = exp.channel_groups[channel_group].spikes.features_masks[:]
# fm is a Nspikes x Nfeatures x 2 array (features AND masks)
fet = fm[:,:,0]
fmask = fm[:,:,1]
#
# Arguments:
# * channel_group: the channel group index to process
# * filename: the filename of the KWIK file
# * params: a dictionary with all KK parameters
import os
import shutil
import tempfile
from spikedetekt2.dataio import Experiment
# get the basename (filename without the extension)
basename = os.path.splitext(filename)[0]
# Create a temporary working folder where we're going to run KK.
tmpdir = tempfile.mkdtmp()
curdir = os.getpwd()
os.chdir(tmpdir)
# Create the filenames of the .fet and .fmask files to create.
filename_fet = os.path.join(tmpdir, basename + '.fet')
filename_fmask = os.path.join(tmpdir, basename + '.fmask')
filename_clu = os.path.join(tmpdir, basename + '.clu')
with Experiment(
filename
) as exp: # Open in read-only, close the file at the end of the block
# Load all features and masks in memory.
# WARNING: this might consume to much Ram ==> need to do it by chunks.
fm = exp.channel_groups[channel_group].spikes.features_masks[:]
# fm is a Nspikes x Nfeatures x 2 array (features AND masks)
