from neurotrends.config import re
from neurotrends.tagger import rex_compile, rex_flex, rex_ctx, rex_named
from neurotrends.tagger import CustomTagger
from ..misc import delimiter, float_ptn
mm_ptn = r'(mm|milli{dlm}met(er|re)s?)'.format(dlm=delimiter)
fw_ptn = r'(fwhm|full{dlm}width)'.format(dlm=delimiter)
hm_ptn = r'(fwhm|half{dlm}max(imum)?)'.format(dlm=delimiter)
smooth_spatial_ptn = [
r'{num}{dlm}{mm}{dlm}{fw}'.format(
num=rex_named(float_ptn, 'kernel'),
mm=mm_ptn,
fw=fw_ptn,
dlm=delimiter,
), r'''
{halfmax}{dlm}
(of|at|(set{dlm}to)|(equal{dlm}to))?{dlm}
({num}){dlm}{mm}
'''.format(
dlm=delimiter,
halfmax=hm_ptn,
num=rex_named(float_ptn, 'kernel'),
mm=mm_ptn,
)
]
smooth_spatial_ptn = [rex_compile(ptn) for ptn in smooth_spatial_ptn]
MAX_FWHM = 30
r'mastoid',
r'amplifi',
r'electrode',
r'alpha',
r'beta',
r'delta',
r'gamma',
r'vocal',
r'word',
]
]
highpass_filter_values_fraction = rex_compile(
ur'(?<![\d\-\u2212]\s){num1}{dlm}[/\u2044]{dlm}{num2}{dlm}{unit}'.format(
dlm=delimiter,
num1=rex_named(float_ptn, 'num'),
num2=rex_named(float_ptn, 'dnm'),
unit=rex_named(hpf_unit_ptn, 'units'),
)
)
highpass_filter_values = rex_compile(
ur'(?<![\d\-\u2212]\s){num}{dlm}{unit}'.format(
dlm=delimiter,
num=rex_named(float_ptn, 'cutoff'),
unit=rex_named(hpf_unit_ptn, 'units'),
)
)
highpass_filter_bool_ptn = [
rex_compile(ptn)
for ptn in highpass_filter_bool_ptn
from neurotrends.tagger import CustomTagger
from ..misc import delimiter
MIN_FIELD_STRENGTH = 0.5
MAX_FIELD_STRENGTH = 12
# Magnet patterns
vend_ptn = r'siemens|philips|general{dlm}electric|\Wge\W'.format(dlm=delimiter)
scan_ptn = r'magnet|scan(ner)?|mri|field|system'
mag_ptn = r'({vend}|{scan})'.format(vend=vend_ptn, scan=scan_ptn)
tesla_ptn = r'(tesla|t(?!\w|{dlm}=|{dlm}\d+|\())'.format(dlm=delimiter)
num_ptn = r'[\s\(](\d{1,2}\.?\d{,2})(?!=\d)'
field_ptn = [
rex_compile(rex_named(num_ptn, 'field') + delimiter + tesla_ptn),
]
sig_ptn = 'p{dlm}[<=>]+{dlm}\d?\.\d+'.format(dlm=delimiter)
sig_ptn = rex_compile(sig_ptn)
def est_field_strength(txt):
fields = []
for ptn in field_ptn:
matches = rex_flex(ptn, txt, fun=re.finditer)
for match in matches:
from neurotrends.config import re
from neurotrends.tagger import rex_compile, rex_flex, rex_ctx, rex_named
from neurotrends.tagger import CustomTagger
from ..misc import delimiter, float_ptn
mm_ptn = r'(mm|milli{dlm}met(er|re)s?)'.format(dlm=delimiter)
fw_ptn = r'(fwhm|full{dlm}width)'.format(dlm=delimiter)
hm_ptn = r'(fwhm|half{dlm}max(imum)?)'.format(dlm=delimiter)
smooth_spatial_ptn = [
r'{num}{dlm}{mm}{dlm}{fw}'.format(
num=rex_named(float_ptn, 'kernel'),
mm=mm_ptn,
fw=fw_ptn,
dlm=delimiter,
),
r'''
{halfmax}{dlm}
(of|at|(set{dlm}to)|(equal{dlm}to))?{dlm}
({num}){dlm}{mm}
'''.format(
dlm=delimiter,
halfmax=hm_ptn,
num=rex_named(float_ptn, 'kernel'),
mm=mm_ptn,
)
]
smooth_spatial_ptn = [
rex_compile(ptn) for ptn in smooth_spatial_ptn
]
from neurotrends.tagger import CustomTagger
from ..misc import delimiter
MIN_FIELD_STRENGTH = 0.5
MAX_FIELD_STRENGTH = 12
# Magnet patterns
vend_ptn = r'siemens|philips|general{dlm}electric|\Wge\W'.format(dlm=delimiter)
scan_ptn = r'magnet|scan(ner)?|mri|field|system'
mag_ptn = r'({vend}|{scan})'.format(vend=vend_ptn, scan=scan_ptn)
tesla_ptn = r'(tesla|t(?!\w|{dlm}=|{dlm}\d+|\())'.format(dlm=delimiter)
num_ptn = r'[\s\(](\d{1,2}\.?\d{,2})(?!=\d)'
field_ptn = [
rex_compile(rex_named(num_ptn, 'field') + delimiter + tesla_ptn),
]
sig_ptn = 'p{dlm}[<=>]+{dlm}\d?\.\d+'.format(dlm=delimiter)
sig_ptn = rex_compile(sig_ptn)
def est_field_strength(txt):
fields = []
for ptn in field_ptn:
matches = rex_flex(ptn, txt, fun=re.finditer)
for match in matches:
r"mastoid",
r"amplifi",
r"electrode",
r"alpha",
r"beta",
r"delta",
r"gamma",
r"vocal",
r"word",
]
]
highpass_filter_values_fraction = rex_compile(
ur"(?<![\d\-\u2212]\s){num1}{dlm}[/\u2044]{dlm}{num2}{dlm}{unit}".format(
dlm=delimiter,
num1=rex_named(float_ptn, "num"),
num2=rex_named(float_ptn, "dnm"),
unit=rex_named(hpf_unit_ptn, "units"),
)
)
highpass_filter_values = rex_compile(
ur"(?<![\d\-\u2212]\s){num}{dlm}{unit}".format(
dlm=delimiter, num=rex_named(float_ptn, "cutoff"), unit=rex_named(hpf_unit_ptn, "units")
)
)
highpass_filter_bool_ptn = [rex_compile(ptn) for ptn in highpass_filter_bool_ptn]
def est_highpass_cutoff(txt):
"""
r'mastoid',
r'amplifi',
r'electrode',
r'alpha',
r'beta',
r'delta',
r'gamma',
r'vocal',
r'word',
]
]
highpass_filter_values_fraction = rex_compile(
ur'(?<![\d\-\u2212]\s){num1}{dlm}[/\u2044]{dlm}{num2}{dlm}{unit}'.format(
dlm=delimiter,
num1=rex_named(float_ptn, 'num'),
num2=rex_named(float_ptn, 'dnm'),
unit=rex_named(hpf_unit_ptn, 'units'),
))
highpass_filter_values = rex_compile(
ur'(?<![\d\-\u2212]\s){num}{dlm}{unit}'.format(
dlm=delimiter,
num=rex_named(float_ptn, 'cutoff'),
unit=rex_named(hpf_unit_ptn, 'units'),
))
highpass_filter_bool_ptn = [
rex_compile(ptn) for ptn in highpass_filter_bool_ptn
]