VariedFilter

class sofia_redux.scan.filters.varied_filter.VariedFilter(integration=None, data=None)

Bases: Filter

Initialize an integration varied filter.

The filter is designed to filter integration data using an FFT. The varied filter also contains a source profile, point response, and dp or delta dependents for channels. This is an abstract class used to model a varying filter response across frequencies.

Parameters:

integrationIntegration, optional

datanumpy.ndarray (float), optional

An array of shape (nt, n_channels) where nt is the nearest power of 2 integer above the number of integration frames. i.e., if n_frames=5, nt=8, or if n_frames=13, nt=16. If not provided will be set to frame_data * frame_relative_weight.

Attributes Summary

channel_dependent_attributes

Return attributes that are dependent on the parent channels.

Methods Summary

calc_point_response([channels])	Return the point response of the source profile.
dft_filter([channels])	Return the filter rejection using a discrete FFT.
get_config_name()	Return the configuration name.
get_id()	Return the filter ID.
get_mean_point_response()	Return the mean point response of the filter.
get_point_response([channels])	Return the point response for the filter.
get_source_profile()	Return the source profile of the varied filter.
post_filter_channels([channels])	Performs the post-filtering channels steps.
pre_filter_channels([channels])	Performs the pre-filtering channels steps.
remove_from_frames(rejected_signal, frames, ...)	Remove the rejected signal from frame data.
response_at(fch)	Return the response at a given frequency channel(s).
set_integration(integration)	Set the varied filter integration.
update_source_profile()	Create the source profile based on integration crossing time.

Attributes Documentation

channel_dependent_attributes

Return attributes that are dependent on the parent channels.

This is required during a slim operation (reducing number of channels).

Returns:

set (str)

Methods Documentation

calc_point_response(channels=None)

Return the point response of the source profile.

channelsChannelGroup, optional

The channel group for which to calculate the point response. The default is all filtering channels.

The point response is given as:

sum(profile <below hi-pass>) + sum(profile * response <above hi-pass>) divided by the source_norm attribute.

Returns:

responsenumpy.ndarray (float)

The point response for each channel of shape (n_channels,).

dft_filter(channels=None)

Return the filter rejection using a discrete FFT.

UNSUPPORTED FOR THE VARIED FILTER.

Parameters:

channelsChannelGroup, optional

The channel group for which the filtering applied. By default, set to the filtering channels.

Returns:

None

abstract get_config_name()

Return the configuration name.

Returns:

config_namestr

abstract get_id()

Return the filter ID.

Returns:

filter_idstr

get_mean_point_response()

Return the mean point response of the filter.

Returns:

responsefloat

get_point_response(channels=None)

Return the point response for the filter.

Parameters:

channelsChannelGroup, optional

The channels for which to extract the point response. The default is the filtering channels.

Returns:

point_responsenumpy.ndarray (float)

The point response for the given channels.

get_source_profile()

Return the source profile of the varied filter.

Returns:

source_profilenumpy.ndarray (float)

The source profile of shape (nf + 1) where nf = nt // 2 and nt = pow2ceil(integration.size).

post_filter_channels(channels=None)

Performs the post-filtering channels steps.

Parameters:

channelsChannelGroup, optional

The channel group for which to perform the post-filtering step. If not supplied, defaults to the filtering channels.

Returns:

None

pre_filter_channels(channels=None)

Performs the pre-filtering channels steps.

Parameters:

channelsChannelGroup, optional

The channel group for which to perform the pre-filtering step. If not supplied, defaults to the filtering channels.

Returns:

None

remove_from_frames(rejected_signal, frames, channels)

Remove the rejected signal from frame data.

Parameters:

rejected_signalnumpy.ndarray (float)

The rejected signal of shape (filtering_channels.size, n_frames).

framesFrames

The frames for which to remove the rejected signal.

channelsChannelGroup

The channel for which to subtract the signal.

Returns:

None

abstract response_at(fch)

Return the response at a given frequency channel(s).

Parameters:

fchint or numpy.ndarray (int or bool) or slice

The frequency channel or channels in question.

Returns:

responsenumpy.ndarray (float)

set_integration(integration)

Set the varied filter integration.

Sets the padding of the FFT filter, the number of frequencies, the frequency spacing, and retrieves the channels from the integration if necessary.

Parameters:

integrationIntegration

Returns:

None

update_source_profile()

Create the source profile based on integration crossing time.

The source is assumed to be Gaussian. Updates the source_profile and source_norm attributes.

Returns:

None