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
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()
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
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()
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
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
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
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
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