7.5.5.4.2. pymodaq_gui.plotting.utils.filter module

class pymodaq_gui.plotting.utils.filter.Filter[source]

Bases: object

Methods

filter_data
register_activation_signal
register_target_slot
set_active

filter_data(data: DataRaw)[source]

register_activation_signal(activation_signal)[source]

register_target_slot(slot)[source]

set_active(activate=True)[source]

class pymodaq_gui.plotting.utils.filter.Filter1DFromCrosshair(crosshair: Crosshair)[source]

Bases: Filter

Methods

update_axis

update_axis(axis: Axis)[source]

class pymodaq_gui.plotting.utils.filter.Filter1DFromRois(roi_manager: ROIManager)[source]

Bases: Filter

Parameters:

roi_manager (ROIManager) –
graph_item (PlotItems) –

Methods

get_data_from_roi
get_slice_from_roi
update_axis

get_data_from_roi(roi: LinearROI, roi_param: Parameter, data: DataWithAxes) → DataToExport[source]

get_slice_from_roi(roi: RectROI, data: DataWithAxes) → slice[source]

update_axis(axis: Axis)[source]

class pymodaq_gui.plotting.utils.filter.Filter2DFromCrosshair(crosshair: Crosshair, graph_items, image_keys)[source]

Bases: Filter

Methods

mapfromview(x, y[, item_key])

get item coordinates from view coordinates :param x: :type x: (float) x coordinate in the view reference frame :param y: :type y: (float) y coordinate in the view refernece frame

get_data_from_spread
get_data_from_uniform
set_active
set_graph_items

get_data_from_spread(dwa: DataWithAxes) → DataToExport[source]

get_data_from_uniform(dwa: DataWithAxes) → DataToExport[source]

mapfromview(x, y, item_key='red')[source]

get item coordinates from view coordinates :param x: :type x: (float) x coordinate in the view reference frame :param y: :type y: (float) y coordinate in the view refernece frame

Returns:

x ((float) coordinate in the item reference frame)
y ((float) coordinate in the item reference frame)

set_active(activate=True)[source]

set_graph_items(graph_items)[source]

class pymodaq_gui.plotting.utils.filter.Filter2DFromRois(roi_manager: ROIManager, graph_item: UniformImageItem, image_keys)[source]

Bases: Filter

Filters 2D data using 2D ROIs

Parameters:

roi_manager (ROIManager) –
graph_item (UniformImageItem or SpreadImageItem) – The graphical item where data and ROIs are plotted
image_keys ((list) list of string identifier to link datas to their graph_items. This means that in) – _filter_data, datas.data[key] is plotted on graph_items[key] for key in image_keys

Methods

get_slices_from_roi
get_xydata_from_roi
get_xydata_spread

get_slices_from_roi(roi: RectROI, data_shape: tuple) → Tuple[slice, slice][source]

get_xydata_from_roi(roi: RectROI, dwa: DataWithAxes, math_function: str) → DataToExport[source]

get_xydata_spread(data, roi)[source]

class pymodaq_gui.plotting.utils.filter.FourierFilterer(parent=None)[source]

Bases: QObject

Methods

show_data(data)

show data and fft :param data: :type data: (dict) with keys 'data', optionally 'xaxis' and 'yaxis'

calculate_fft
filter_changed
setUI
set_data
update_filter
update_plot

calculate_fft()[source]

setUI()[source]

set_data()[source]

show_data(data)[source]: show data and fft :param data: :type data: (dict) with keys ‘data’, optionally ‘xaxis’ and ‘yaxis’

update_filter()[source]

update_plot()[source]

filter_changed

int = …, arguments: Sequence = …) -> PYQT_SIGNAL

types is normally a sequence of individual types. Each type is either a type object or a string that is the name of a C++ type. Alternatively each type could itself be a sequence of types each describing a different overloaded signal. name is the optional C++ name of the signal. If it is not specified then the name of the class attribute that is bound to the signal is used. revision is the optional revision of the signal that is exported to QML. If it is not specified then 0 is used. arguments is the optional sequence of the names of the signal’s arguments.

Type:: pyqtSignal(*types, name
Type:: str = …, revision