<commit_before># emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
"""
The rapidart module provides routines for artifact detection and region of
interest analysis.

These functions include:

  * SpecifyModel: allows specification of sparse and non-sparse models
"""

import os
from copy import deepcopy

import numpy as np
from scipy.signal import convolve
from scipy.special import gammaln
#from scipy.stats.distributions import gamma

from nipype.externals.pynifti import load
from nipype.interfaces.base import BaseInterface, TraitedSpec,\
 InputMultiPath, traits, File
from nipype.utils.misc import isdefined
from nipype.utils.filemanip import filename_to_list, loadflat
from nipype.interfaces.spm import scans_for_fnames

class SpecifyModelInputSpec(TraitedSpec):
    subject_id = traits.Either(traits.Str(),traits.Int(),mandatory=True,
        desc ="Subject identifier used as a parameter to the subject_info_func.")
    subject_info = traits.List(mandatory=True,
                          desc= "List subject specific condition information")
    """    . If all
            subjects had the same stimulus presentation schedule,
            then this function can return the same structure
            independent of the subject. This function must return a
            list of dicts with the list length equal to the number of
            sessions. The dicts should contain the following
            information.

            conditions : list of names
<commit_msg>make subject_id in modelspec depracated<commit_after># emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
"""
The rapidart module provides routines for artifact detection and region of
interest analysis.

These functions include:

  * SpecifyModel: allows specification of sparse and non-sparse models
"""

import os
from copy import deepcopy

import numpy as np
from scipy.signal import convolve
from scipy.special import gammaln
#from scipy.stats.distributions import gamma

from nipype.externals.pynifti import load
from nipype.interfaces.base import BaseInterface, TraitedSpec,\
 InputMultiPath, traits, File
from nipype.utils.misc import isdefined
from nipype.utils.filemanip import filename_to_list, loadflat
from nipype.interfaces.spm import scans_for_fnames

class SpecifyModelInputSpec(TraitedSpec):
    subject_id = traits.Either(traits.Str(),traits.Int(),
        desc ="This input is depracated and will be removed in the future releases. Update your code.")
    subject_info = traits.List(mandatory=True,
                          desc= "List subject specific condition information")
    """    . If all
            subjects had the same stimulus presentation schedule,
            then this function can return the same structure
            independent of the subject. This function must return a
            list of dicts with the list length equal to the number of
            sessions. The dicts should contain the following
            information.

            conditions : list of names

{'fraction_non_alphanumeric': 0.06280193236714976, 'fraction_numerical': 0.0025764895330112722, 'mean_word_length': 3.4119318181818183, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 3, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '1336735', 'n_tokens_mistral': 842, 'n_tokens_neox': 813, 'n_words': 326}