FittingResultList¶
- class menpo.fit.fittingresult.FittingResultList(fitting_results, error_type='me_norm')[source]¶
Bases: list, Viewable
Enhanced list of FittingResults objects. It implements a series of methods that facilitate the generation of global fitting results.
Parameters: fitting_results: :class:`menpo.fitter.fitting.FittingResults` :
A list of FittingResult objects.
error_type: ‘me_norm’, ‘me’ or ‘rmse’, optional. :
Specifies the way in which the error between the fitted and ground truth shapes is to be computed.
Default: ‘me_norm’
- append()¶
L.append(object) – append object to end
- count(value) → integer -- return number of occurrences of value¶
- extend()¶
L.extend(iterable) – extend list by appending elements from the iterable
- index(value[, start[, stop]]) → integer -- return first index of value.¶
Raises ValueError if the value is not present.
- insert()¶
L.insert(index, object) – insert object before index
- plot_cumulative_error_dist(figure_id=None, new_figure=False, **kwargs)[source]¶
Plots the final and initial cumulative error distributions.
- plot_error_dist(figure_id=None, new_figure=False, **kwargs)[source]¶
Plots the final and initial error distributions.
- pop([index]) → item -- remove and return item at index (default last).¶
Raises IndexError if list is empty or index is out of range.
- remove()¶
L.remove(value) – remove first occurrence of value. Raises ValueError if the value is not present.
- reverse()¶
L.reverse() – reverse IN PLACE
- sort()¶
L.sort(cmp=None, key=None, reverse=False) – stable sort IN PLACE; cmp(x, y) -> -1, 0, 1
- view(**kwargs)¶
View the object using the default rendering engine figure handling. For example, the default behaviour for Matplotlib is that all draw commands are applied to the same figure object.
Parameters: kwargs : dict
Passed through to specific rendering engine.
Returns: viewer : Renderer
The renderer instantiated.
- view_final_fitting(figure_id=None, new_figure=False, **kwargs)[source]¶
Displays the final fitting result obtained by each fitting object.
- view_initialization(figure_id=None, new_figure=False, **kwargs)[source]¶
Displays the initialization used by each fitting object.
- view_new(**kwargs)¶
View the object on a new figure.
Parameters: kwargs : dict
Passed through to specific rendering engine.
Returns: viewer : Renderer
The renderer instantiated.
- view_on(figure_id, **kwargs)¶
View the object on a a specific figure specified by the given id.
Parameters: figure_id : object
A unique identifier for a figure.
kwargs : dict
Passed through to specific rendering engine.
Returns: viewer : Renderer
The renderer instantiated.
- algorithm[source]¶
Returns the name of the fitting algorithm used by the fitter object associated to the fitting objects.
- convergence[source]¶
Returns the percentage of fitting objects that converged. A fitting object is considered to have converged if the final fitting error is smaller than the initial one.
- final_cumulative_error_dist[source]¶
Computes the final cumulative error distribution among all fitting objects.
Returns: ced: ndarray :
The final cumulative error distribution among all fitting objects within the interval [0, self._error_stop]
x_axis: ndarray :
The interval [0, self._error_stop]
- final_error_dist[source]¶
Computes the final error distribution among all fitting objects.
Returns: ed: ndarray :
The final error distribution among all fitting objects within the interval [0, self._error_stop]
x_axis: ndarray :
The interval [0, self._error_stop]
- initial_cumulative_error_dist[source]¶
Computes the initial cumulative error distribution among all fitting objects.
Returns: ced: ndarray :
The initial cumulative error distribution among all fitting objects within the interval [0, self._error_stop]
x_axis: ndarray :
The interval [0, self._error_stop]