mantidimaging.core.operations.monitor_normalisation.monitor_normalisation module

class mantidimaging.core.operations.monitor_normalisation.monitor_normalisation.MonitorNormalisation[source]

Bases: mantidimaging.core.operations.base_filter.BaseFilter

Normalises the image data using the average count of a beam monitor from the experiment log file. This scaling operation is an alternative to ROI normalisation and allows to account for beam fluctuations and different exposure times of projections.

Intended to be used on: Projections

When: As a pre-processing step to normalise the grey value ranges of the data.

static execute_wrapper(*args) functools.partial[source]

Should construct a partial call to _filter_func using values taken from the widgets passed to this function as kwargs. :param kwargs: widgets which contain values required for _filter_func. :return: a partial call to _filter_func using parameters taken from the input widgets.

static filter_func(images:, cores=None, chunksize=None, progress=None)[source]

Executes the filter algorithm on a given set of image data with the given parameters.

  • data – the image data to apply the filter to

  • kwargs – any additional arguments which the specific filter uses


the image data after applying the filter

filter_name = 'Monitor Normalisation'
static register_gui(form: PyQt5.QtWidgets.QFormLayout, on_change: Callable, view: mantidimaging.gui.mvp_base.view.BaseMainWindowView) Dict[str, PyQt5.QtWidgets.QWidget][source]

Adds any required input widgets to the given form and returns references to them.

The return values should be in a dict which can be unpacked as kwargs for a call to the operations execute_wrapper.

  • view

  • form – the layout to create input widgets in

  • on_change – the filter view action to be bound to all created inputs


the widgets bound as kwargs which are needed to call execute_wrapper

static validate_execute_kwargs(kwargs: Dict[str, Any]) bool[source]