Exemplo n.º 1
0
def h5load(filename, verbose):
    ''' h5load(filename, verbose)
    input:
        - filename (as string)
        - names of variables and values to be loaded (as string)
    return:
        - dictionary of saved data
    notice:
        use with files saved with accpy.dataio.save
    '''
    if filename[-5:] != '.hdf5':
        filename = ''.join([filename, '.hdf5'])
    fid = h5pyFile(filename, 'r')
    data = {}
    if verbose:
        print('\n==========================================================')
        print('Beginning to load from %s ...' % filename)
        print('\n----------------------------------------------------------')
        for key in fid:
            data[key] = fid[key].value
            print('Loading values from {0:} {1:} ... '.format(
                key, type(data[key])))
        print('\n----------------------------------------------------------')
        print('... finished loading from %s !' % filename)
        print('\n==========================================================')
    else:
        for key in fid:
            data[key] = fid[key].value
    fid.close()
    return data
Exemplo n.º 2
0
def confsave(filename, listofvars, listofvals):
    # working with two lists as dictionarys do not accept numpy arrays
    hdf5_fid = h5pyFile(filename, 'w')
    hdf5_fid.create_dataset('listofvars', data=listofvars)
    for var, val in zip(listofvars, listofvals):
        hdf5_fid.create_dataset(var, data=val)
    hdf5_fid.close()
Exemplo n.º 3
0
def save(filename, showinfo, **namesandvariables):
    ''' save(filename,variables(e.g. a=a, b=b, ...))
    input:
        - desired filename as string
        - names = values of variables to be saved
    return:
        - saves data to "datetime_filename.hdf5 in working directory"
    notice:
        accepted datatypes:
            -
    '''
    timstamp = strftime('%Y%m%d%H%M%S')
    filename = ''.join([timstamp, '_', filename, '.hdf5'])
    hdf5_fid = h5pyFile(filename, 'w')
    if showinfo:
        print('\n==========================================================')
        print('Beginning to save to %s ...' % filename)
        print('\n----------------------------------------------------------')
        for key, value in namesandvariables.iteritems():
            print('Saving values in %s ... ' % key)
            hdf5_fid.create_dataset(key, data=value)
        print('\n----------------------------------------------------------')
        print('... finished saving to %s !' % filename)
        print('\n==========================================================')
    else:
        for key, value in namesandvariables.iteritems():
            hdf5_fid.create_dataset(key, data=value)
    hdf5_fid.close()
    return filename
Exemplo n.º 4
0
def confsave(filename, listofvars, listofvals):
    # working with two lists as dictionarys do not accept numpy arrays
    hdf5_fid = h5pyFile(filename, 'w')
    hdf5_fid.create_dataset('listofvars', data=listofvars)
    for var, val in zip(listofvars, listofvals):
        hdf5_fid.create_dataset(var, data=val)
    hdf5_fid.close()
Exemplo n.º 5
0
def load(filename, showinfo, *varnames):
    ''' load(filename,variables(e.g. 'a', 'b', ...))
    input:
        - desired filename (as string)
        - names of variables and values to be loaded (as string)
    return:
        - wanted variables are loaded from filename
    notice:
        use with files saved with mypy.save
        -
    '''
    if filename[-5:] != '.hdf5':
        filename = ''.join([filename, '.hdf5'])
    fid = h5pyFile(filename, 'r')
    data = []
    if showinfo:
        print('\n==========================================================')
        print('Beginning to load from %s ...' % filename)
        print('\n----------------------------------------------------------')
        for arg in varnames:
            print('Loading values from %s ...' % arg)
            data.append(fid[arg].value)
        print('\n----------------------------------------------------------')
        print('... finished loading from %s !' % filename)
        print('\n==========================================================')
    else:
        for arg in varnames:
            data.append(fid[arg].value)
    fid.close()
    return data
Exemplo n.º 6
0
    def get_fcx2(
        self,
        sessions = 'all',
        path = 'fcx-2/'
    ):
        
        if sessions == 'all':
            sessions = [f's{no}' for no in range(1, 11)]
            
        sessions = [f'{self.root}{path}{s}' for s in sessions]
        tmp = []
        for s in sessions:
            for p in os.listdir(s):
                if 'data_primary' in p:
                    tmp.append(f'{s}/{p}')
        sessions = tmp
        del tmp
            
        out = {}
        for s in sessions:
            with h5pyFile(s, 'r') as fp:
                data = np.array(fp['gdat_clean_filt'])
                # Errors 1: empty channels
                data = data[:, (data == 0).all(0) == False]
                # Errors 2: Sessions that are padded with zeroes to extreme lengths
                #   (Note: == 0 comparisson works, since no non-trash-value is close enough to 0 to return true)
                data = data[data != 0].reshape((-1, data.shape[1]))
                
                sess = s.split('/')[-2]
                out[sess] = {
                    'data': data,
                    'fs': 500 if ('8' in sess or '9' in sess) else 1000
                }
                
#         Construct spectrogram functions
        for sess, obj in out.items():
            def spect_for_sess(
                channel,
                nperseg   = 100,
                noverlap  = 75,
                nfft      = 2 ** 12,
                f_lo      = 10,
                f_hi      = 100,
                window    = 'boxcar',
                normalize = True
            ):
                return self.spectrogram_base(
                    obj['data'].T[channel].flatten(),
                    obj['fs'],
                    nperseg,
                    noverlap,
                    nfft,
                    f_lo,
                    f_hi,
                    window = 'boxcar',
                    normalize = True
                )
            obj['spectrogram'] = spect_for_sess
                
        return out
Exemplo n.º 7
0
def confload(filename):
    fid = h5pyFile(filename, 'r')
    listofvars = list(fid['listofvars'].value)
    listofvals = []
    for var in listofvars:
        listofvals.append(fid[var].value)
    fid.close()
    return listofvars, listofvals
Exemplo n.º 8
0
def confload(filename):
    fid = h5pyFile(filename, 'r')
    listofvars = list(fid['listofvars'].value)
    listofvals = []
    for var in listofvars:
        listofvals.append(fid[var].value)
    fid.close()
    return listofvars, listofvals
Exemplo n.º 9
0
def h5save(filename, verbose, **namesandvariables):
    ''' save dataset to hdf5 format
    input:
        - desired filename as string
        - names = values of variables to be saved
    return:
        - saves data to "timestamp_filename.hdf5 in working directory"
        - complete filename is returned
    usage:
        1.  recommended
                datadict = {'a' : 2,
                            'b' : 'foo',
                            'c' : 1.337,
                            'd' : [1, 2, 'c']}
                h5save(filename, True. **datadict)
        2.  alternative 
                a=2, b='foo', c=1.337, d=[1, 2, 'c']
                h5save(filename, True. a=a, b=b, c=c, d=d)
                accepted datatypes:
                    - int   -> numpy.int64
                    - str   -> str
                    - float -> numpy.float64
                    - list  -> numpy.ndarray of:
                                - np.string__   if >0 string
                                - np.float64    if >0 float
                                - np.int64      if only ints
        
    '''
    timstamp = strftime('%Y%m%d%H%M%S')
    filename = ''.join([timstamp, '_', filename, '.hdf5'])
    hdf5_fid = h5pyFile(filename, 'w')
    if verbose:
        print('\n==========================================================')
        print('Beginning to save to %s ...' % filename)
        print('\n----------------------------------------------------------')
    for key, value in namesandvariables.iteritems():
        if verbose:
            print('Saving values in %s ... ' % key)
        hdf5_fid.create_dataset(key, data=value)
    if verbose:
        print('\n----------------------------------------------------------')
        print('... finished saving to %s !' % filename)
        print('\n==========================================================')
    hdf5_fid.close()
    return filename