def func(band_data):
log_root = np.log10(0.0223)
denom = (1.0 - log_root) * 0.75
band_data *= 0.01
band_data = xu.log10(band_data)
band_data -= log_root
band_data /= denom
return band_data
def func(band_data):
log_root = np.log10(0.0223)
denom = (1.0 - log_root) * 0.75
band_data *= 0.01
band_data = xu.log10(band_data)
band_data -= log_root
band_data /= denom
return band_data
def func(band_data):
log_root = np.log10(0.0223)
denom = (1.0 - log_root) * 0.75
band_data *= 0.01
band_data = band_data.clip(np.finfo(float).eps)
band_data = xu.log10(band_data)
band_data -= log_root
band_data /= denom
return band_data
def ds_arithmetics(ds: DatasetLike.TYPE,
op: str,
monitor: Monitor = Monitor.NONE) -> xr.Dataset:
"""
Do arithmetic operations on the given dataset by providing a list of
arithmetic operations and the corresponding constant. The operations will
be applied to the dataset in the order in which they appear in the list.
For example:
'log,+5,-2,/3,*2'
Currently supported arithmetic operations:
log,log10,log2,log1p,exp,+,-,/,*
where:
log - natural logarithm
log10 - base 10 logarithm
log2 - base 2 logarithm
log1p - log(1+x)
exp - the exponential
The operations will be applied element-wise to all arrays of the dataset.
:param ds: The dataset to which to apply arithmetic operations
:param op: A comma separated list of arithmetic operations to apply
:param monitor: a progress monitor.
:return: The dataset with given arithmetic operations applied
"""
ds = DatasetLike.convert(ds)
retset = ds
with monitor.starting('Calculate result', total_work=len(op.split(','))):
for item in op.split(','):
with monitor.child(1).observing("Calculate"):
item = item.strip()
if item[0] == '+':
retset = retset + float(item[1:])
elif item[0] == '-':
retset = retset - float(item[1:])
elif item[0] == '*':
retset = retset * float(item[1:])
elif item[0] == '/':
retset = retset / float(item[1:])
elif item[:] == 'log':
retset = xu.log(retset)
elif item[:] == 'log10':
retset = xu.log10(retset)
elif item[:] == 'log2':
retset = xu.log2(retset)
elif item[:] == 'log1p':
retset = xu.log1p(retset)
elif item[:] == 'exp':
retset = xu.exp(retset)
else:
raise ValueError('Arithmetic operation {} not'
' implemented.'.format(item[0]))
return retset
def ds_arithmetics(ds: xr.Dataset, op: str) -> xr.Dataset:
"""
Do arithmetic operations on the given dataset by providing a list of
arithmetic operations and the corresponding constant. The operations will
be applied to the dataset in the order in which they appear in the list.
For example:
'log,+5,-2,/3,*2'
Currently supported arithmetic operations:
log,log10,log2,log1p,exp,+,-,/,*
where:
log - natural logarithm
log10 - base 10 logarithm
log2 - base 2 logarithm
log1p - log(1+x)
exp - the exponential
The operations will be applied element-wise to all arrays of the dataset.
:param ds: The dataset to which to apply arithmetic operations
:param op: A comma separated list of arithmetic operations to apply
:return: The dataset with given arithmetic operations applied
"""
retset = ds
for item in op.split(','):
item = item.strip()
if item[0] == '+':
retset = retset + float(item[1:])
elif item[0] == '-':
retset = retset - float(item[1:])
elif item[0] == '*':
retset = retset * float(item[1:])
elif item[0] == '/':
retset = retset / float(item[1:])
elif item[:] == 'log':
retset = xu.log(retset)
elif item[:] == 'log10':
retset = xu.log10(retset)
elif item[:] == 'log2':
retset = xu.log2(retset)
elif item[:] == 'log1p':
retset = xu.log1p(retset)
elif item[:] == 'exp':
retset = xu.exp(retset)
else:
raise ValueError('Arithmetic operation {} not'
' implemented.'.format(item[0]))
return retset
def plot(self):
"""
Plot the weights distribution of the window and the associated
spectrum (work only for 1D and 2D windows).
"""
win_array = xr.DataArray(self.coefficients.squeeze(),
dims=self.dims).squeeze()
win_spectrum = psd(
fft(win_array, nfft=1024, dim=self.dims, dx=self.dx, sym=True))
win_spectrum_norm = 20 * log10(win_spectrum / abs(win_spectrum).max())
self.win_spectrum_norm = win_spectrum_norm
if self.ndim == 1:
_plot1d_window(win_array, win_spectrum_norm)
elif self.ndim == 2:
_plot2d_window(win_array, win_spectrum_norm)
else:
raise ValueError(
"This number of dimension is not supported by the "
"plot function")
