`hyperspy.api.samfire.local_strategies`#

`hyperspy.api.samfire.local_strategies.LocalStrategy`(name)	A SAMFire strategy that operates in "pixel space" - i.e calculates the starting point estimates based on the local averages of the pixels.
`hyperspy.api.samfire.local_strategies.ReducedChiSquaredStrategy`()	Reduced chi-squared Local strategy of the SAMFire.

class hyperspy.api.samfire.local_strategies.LocalStrategy(name)#

Bases: SamfireStrategy

A SAMFire strategy that operates in “pixel space” - i.e calculates the starting point estimates based on the local averages of the pixels. Requires some weighting method (e.g. reduced chi-squared).

clean()#: Purges the currently saved values.

plot(fig=None)#

Plots the current marker in a flat image

Parameters:

fighyperspy.api.signals.Signal2D or numpy.ndarray: if an already plotted image, then updates. Otherwise creates a new one.

Returns:

hyperspy.api.signals.Signal2D: The resulting 2D signal. If passed again, will be updated (computationally cheaper operation).

property radii#: A tuple of >=0 floats that show the “radii of relevance”

refresh(overwrite, given_pixels=None)#

Refreshes the marker - recalculates with the current values from scratch.

Parameters:

overwritebool: If True, all but the given_pixels will be recalculated. Used when part of already calculated results has to be refreshed. If False, only use pixels with marker == -scale (by default -1) to propagate to pixels with marker >= 0. This allows “ignoring” pixels with marker < -scale (e.g. -2).
given_pixelsnumpy.ndarray of bool: Pixels with True value are assumed as correctly calculated.

remove()#: Removes this strategy from its SAMFire

property samf#: The SAMFire that owns this strategy.

update(ind, isgood)#

Updates the database and marker with the given pixel results

Parameters:

indtuple: the index with new results
isgoodbool: if the fit was successful.

values(ind)#

Returns the current starting value estimates for the given pixel. Calculated as the weighted local average. Only returns components that are active, and parameters that are free.

Parameters:

indtuple: the index of the pixel of interest.

Returns:

valuesdict: A dictionary of estimates, structured as {component_name: {parameter_name: value, …}, …} for active components and free parameters.

property weight#: A Weight object, able to assign significance weights to separate pixels or maps, given the model.

class hyperspy.api.samfire.local_strategies.ReducedChiSquaredStrategy#

Bases: LocalStrategy

Reduced chi-squared Local strategy of the SAMFire. Uses reduced chi-squared as the weight, and exponential decay as the decay function.

clean()#: Purges the currently saved values.

plot(fig=None)#

Plots the current marker in a flat image

Parameters:

fighyperspy.api.signals.Signal2D or numpy.ndarray: if an already plotted image, then updates. Otherwise creates a new one.

Returns:

hyperspy.api.signals.Signal2D: The resulting 2D signal. If passed again, will be updated (computationally cheaper operation).

property radii#: A tuple of >=0 floats that show the “radii of relevance”

refresh(overwrite, given_pixels=None)#

Refreshes the marker - recalculates with the current values from scratch.

Parameters:

overwritebool: If True, all but the given_pixels will be recalculated. Used when part of already calculated results has to be refreshed. If False, only use pixels with marker == -scale (by default -1) to propagate to pixels with marker >= 0. This allows “ignoring” pixels with marker < -scale (e.g. -2).
given_pixelsnumpy.ndarray of bool: Pixels with True value are assumed as correctly calculated.

remove()#: Removes this strategy from its SAMFire

property samf#: The SAMFire that owns this strategy.

update(ind, isgood)#

Updates the database and marker with the given pixel results

Parameters:

indtuple: the index with new results
isgoodbool: if the fit was successful.

values(ind)#

Returns the current starting value estimates for the given pixel. Calculated as the weighted local average. Only returns components that are active, and parameters that are free.

Parameters:

indtuple: the index of the pixel of interest.

Returns:

valuesdict: A dictionary of estimates, structured as {component_name: {parameter_name: value, …}, …} for active components and free parameters.

property weight#: A Weight object, able to assign significance weights to separate pixels or maps, given the model.

hyperspy.api.samfire.local_strategies#

`hyperspy.api.samfire.local_strategies`#