def filtered(self, freq_range, filt_type='stop', order=4):
"""
Filter the data using a Butterworth filter and return a new
TimeSeries instance.
Parameters
----------
freq_range : array-like
The range of frequencies to filter.
filt_type : str
Filter type (default: ``'stop'``).
order : int
The order of the filter (default: 4).
Returns
-------
ts : TimeSeriesX
A TimeSeriesX instance with the filtered data.
"""
warnings.warn("The filtered method is not very flexible. "
"Consider using filters in ptsa.data.filters instead.")
time_axis_index = get_axis_index(self, axis_name='time')
filtered_array = buttfilt(self.values, freq_range, float(self['samplerate']), filt_type,
order, axis=time_axis_index)
new_ts = self.copy()
new_ts.data = filtered_array
return new_ts
def filter(self):
"""
Applies Butterwoth filter to input time series and returns filtered TimeSeriesX object
Returns
-------
filtered: TimeSeriesX
The filtered time series
"""
time_axis_index = get_axis_index(self.time_series, axis_name='time')
filtered_array = buttfilt(self.time_series,
self.freq_range,
float(self.time_series['samplerate']),
self.filt_type,
self.order,
axis=time_axis_index)
coords_dict = {
coord_name: DataArray(coord.copy())
for coord_name, coord in list(self.time_series.coords.items())
}
coords_dict['samplerate'] = self.time_series['samplerate']
dims = [dim_name for dim_name in self.time_series.dims]
filtered_time_series = TimeSeriesX(filtered_array,
dims=dims,
coords=coords_dict)
# filtered_time_series = TimeSeriesX(filtered_time_series)
filtered_time_series.attrs = self.time_series.attrs.copy()
return filtered_time_series
def filter(self):
"""
Applies Butterwoth filter to input time series and returns filtered TimeSeriesX object
Returns
-------
filtered: TimeSeriesX
The filtered time series
"""
time_axis_index = get_axis_index(self.time_series, axis_name='time')
filtered_array = buttfilt(self.time_series,
self.freq_range, float(self.time_series['samplerate']), self.filt_type,
self.order, axis=time_axis_index)
coords_dict = {coord_name: DataArray(coord.copy()) for coord_name, coord in list(self.time_series.coords.items())}
coords_dict['samplerate'] = self.time_series['samplerate']
dims = [dim_name for dim_name in self.time_series.dims]
filtered_time_series = TimeSeriesX(
filtered_array,
dims=dims,
coords=coords_dict
)
# filtered_time_series = TimeSeriesX(filtered_time_series)
filtered_time_series.attrs = self.time_series.attrs.copy()
return filtered_time_series
def filtered(self, freq_range, filt_type='stop', order=4):
"""
Filter the data using a Butterworth filter and return a new
TimeSeries instance.
Parameters
----------
freq_range : {array_like}
The range of frequencies to filter.
filt_type = {scipy.signal.band_dict.keys()},optional
Filter type.
order = {int}
The order of the filter.
Returns
-------
ts : {TimeSeries}
A TimeSeries instance with the filtered data.
"""
from ptsa.filt import buttfilt
time_axis_index = get_axis_index(self, axis_name='time')
filtered_array = buttfilt(self.values,
freq_range,
float(self['samplerate']),
filt_type,
order,
axis=time_axis_index)
coords = {}
for coord_name, coord in self.coords.items():
if len(coord.shape):
coords[coord_name] = coord
filtered_time_series = TimeSeriesX(
filtered_array,
dims=[dim_name for dim_name in self.dims],
coords=coords)
filtered_time_series.attrs = self.attrs.copy()
return filtered_time_series
def filtered(self, freq_range, filt_type='stop', order=4):
"""
Filter the data using a Butterworth filter and return a new
TimeSeries instance.
Parameters
----------
freq_range : {array_like}
The range of frequencies to filter.
filt_type = {scipy.signal.band_dict.keys()},optional
Filter type.
order = {int}
The order of the filter.
Returns
-------
ts : {TimeSeries}
A TimeSeries instance with the filtered data.
"""
from ptsa.filt import buttfilt
time_axis_index = get_axis_index(self, axis_name='time')
filtered_array = buttfilt(self.values, freq_range, float(self['samplerate']), filt_type,
order, axis=time_axis_index)
coords={}
for coord_name, coord in self.coords.items():
if len(coord.shape):
coords[coord_name] = coord
filtered_time_series = TimeSeriesX(
filtered_array,
dims=[dim_name for dim_name in self.dims],
coords=coords
)
filtered_time_series.attrs = self.attrs.copy()
return filtered_time_series
def __init__(self, data, **kwds):
xr.DataArray.__init__(self, data, **kwds)
self.a = 10
self.time_axis_index = get_axis_index(self, axis_name='time')
def __init__(self,data,**kwds):
xr.DataArray.__init__(self, data, **kwds)
self.a=10
self.time_axis_index=get_axis_index(self,axis_name='time')
