Completed
Pull Request — master (#170)
by Jasper
01:27
created

FifFile.inspect()   C

Complexity

Conditions 9

Size

Total Lines 55

Duplication

Lines 0
Ratio 0 %

Importance

Changes 1
Bugs 0 Features 0
Metric Value
cc 9
c 1
b 0
f 0
dl 0
loc 55
rs 5.4159

How to fix   Long Method   

Long Method

Small methods make your code easier to understand, in particular if combined with a good name. Besides, if your method is small, finding a good name is usually much easier.

For example, if you find yourself adding comments to a method's body, this is usually a good sign to extract the commented part to a new method, and use the comment as a starting point when coming up with a good name for this new method.

Commonly applied refactorings include:

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from __future__ import division
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import logging
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from datetime import datetime
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from functools import partial
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from niprov.basefile import BaseFile
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from niprov.libraries import Libraries
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class FifFile(BaseFile):
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    def __init__(self, location, **kwargs):
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        super(FifFile, self).__init__(location, **kwargs)
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        self.libs = self.dependencies.getLibraries()
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    def inspect(self):
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        provenance = super(FifFile, self).inspect()
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        """ try:
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                img = self.libs.mne.io.Raw(self.path, allow_maxshield=True)
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                except ValueError:
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                    pass
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                else:
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                    inspect file
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                    Return
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        """
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        ftypes = {
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            'cov': self.libs.mne.read_cov,
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            'epo': self.libs.mne.read_epochs,
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            'ave': self.libs.mne.read_evokeds,
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            'raw': partial(self.libs.mne.io.read_raw_fif, allow_maxshield=True),
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        }
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        oldLevel = logging.getLogger('mne').getEffectiveLevel()
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        logging.getLogger('mne').setLevel(logging.ERROR)
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        for ftype, readfif in ftypes.items():
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            try:
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                img = readfif(self.path)
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                if img == []:
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                    continue
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                break
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            except ValueError:
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                continue
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        else:
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            ftype = 'other'
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        logging.getLogger('mne').setLevel(oldLevel)
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        if ftype == 'raw':
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            sub = img.info['subject_info']
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            if sub is not None:
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                provenance['subject'] = sub['first_name']+' '+sub['last_name']
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            provenance['project'] = img.info['proj_name']
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            acqTS = img.info['meas_date'][0]
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            provenance['acquired'] = datetime.fromtimestamp(acqTS)
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            T = img.last_samp - img.first_samp + 1
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            provenance['dimensions'] = [img.info['nchan'], T]
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            provenance['sampling-frequency'] = img.info['sfreq']
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            provenance['duration'] = T/img.info['sfreq']
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        if ftype == 'epo':
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            provenance['lowpass'] = img.info['lowpass']
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            provenance['highpass'] = img.info['highpass']
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            provenance['bad-channels'] = img.info['bads']
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            provenance['dimensions'] = [img.events.shape[0], img.times.shape[0]]
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        if ftype == 'ave':
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            nEvokeds = len(img)
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            provenance['dimensions'] = [nEvokeds] + list(img[0].data.shape)
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        provenance['fif-type'] = ftype
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        provenance['modality'] = 'MEG'
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        return provenance
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    def attach(self, form='json'):
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        """
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        Attach the current provenance to the file by appending it as a
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        json-encoded string to the 'description' header field.
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        Args:
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            form (str): Data format in which to serialize provenance. Defaults 
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                to 'json'.
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        """
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        info = self.libs.mne.io.read_info(self.path)
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        provstr = self.getProvenance(form)
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        info['description'] = info['description']+' NIPROV:'+provstr
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        self.libs.mne.io.write_info(self.path, info)
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