Package topo :: Package command :: Module analysis :: Class measure_corner_or_pref

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Class measure_corner_or_pref

source code

Measure a corner preference map by collating the response to patterns.

Nested Classes

[hide private]

Inherited from param.parameterized.Parameterized: __metaclass__

Instance Methods

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_feature_list(self, p)
Return the list of features to vary; must be implemented by each subclass.

source code

Inherited from analysis.featureresponses.MeasureResponseCommand: __call__

Inherited from param.parameterized.ParameterizedFunction: __reduce__, __str__, script_repr

Inherited from param.parameterized.Parameterized: __getstate__, __init__, __repr__, __setstate__, debug, defaults, force_new_dynamic_value, get_param_values, get_value_generator, inspect_value, message, print_param_values, set_default, set_dynamic_time_fn, set_param, state_pop, state_push, verbose, warning

Inherited from param.parameterized.Parameterized (private): _add_parameter, _instantiate_param, _set_name, _setup_params

Inherited from object: __delattr__, __format__, __getattribute__, __hash__, __reduce_ex__, __setattr__, __sizeof__, __subclasshook__

Class Methods

[hide private]

Inherited from param.parameterized.ParameterizedFunction: instance

Inherited from param.parameterized.Parameterized: params, print_param_defaults

Static Methods

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Inherited from param.parameterized.ParameterizedFunction: __new__

Class Variables

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scale = param.Number(default= 1.0)
Multiplicative strength of input pattern.

divisions = param.Integer(default= 10)
The number of different positions to measure in X and in Y.

pattern_presenter = param.Callable(PatternPresenter(gaussian_c...
Callable object that will present a parameter-controlled pattern to a set of Sheets.

x_range = param.NumericTuple((-1.2, 1.2))
The range of X values to test.

y_range = param.NumericTuple((-1.2, 1.2))
The range of Y values to test.

num_orientation = param.Integer(default= 4, bounds= (1, None),...
Number of orientations to test.

static_parameters = param.List(default= ["scale", "offset"])
List of names of parameters of this class to pass to the pattern_presenter as static parameters, i.e.

__params = {'apply_output_fns': <param.Boolean object at 0xb20...
dict() -> new empty dictionary.

name = <param.parameterized.String object at 0xb3158ac>
String identifier for this object.

Inherited from analysis.featureresponses.PositionMeasurementCommand: size

Inherited from analysis.featureresponses.MeasureResponseCommand: apply_output_fns, display, duration, generator_sheets, offset, sheet_views_prefix, subplot, weighted_average

Inherited from param.parameterized.Parameterized: print_level

Properties

[hide private]

Inherited from object: __class__

Method Details

[hide private]

_feature_list(self, p)

source code

Return the list of features to vary; must be implemented by each subclass.

Overrides: analysis.featureresponses.MeasureResponseCommand._feature_list: (inherited documentation)

Class Variable Details

[hide private]

pattern_presenter

Callable object that will present a parameter-controlled pattern to a set of Sheets. For measuring position, the pattern_presenter should be spatially localized, yet also able to activate the appropriate neurons reliably.

Value:

param.Callable(PatternPresenter(gaussian_corner, apply_output_fns= False, duration
= 1.0))

num_orientation

Number of orientations to test.

Value:

param.Integer(default= 4, bounds= (1, None), softbounds= (1, 24), doc= "Number of 
orientations to test.")

static_parameters

List of names of parameters of this class to pass to the pattern_presenter as static parameters, i.e. values that will be fixed to a single value during measurement.

Value:

param.List(default= ["scale", "offset"])

__params

dict() -> new empty dictionary.
dict(mapping) -> new dictionary initialized from a mapping object's
    (key, value) pairs.
dict(seq) -> new dictionary initialized as if via:
    d = {}
    for k, v in seq:
        d[k] = v
dict(**kwargs) -> new dictionary initialized with the name=value pairs
    in the keyword argument list.  For example:  dict(one=1, two=2)

Value:

{'apply_output_fns': <param.Boolean object at 0xb20d06c>,
 'display': <param.Boolean object at 0xb20df2c>,
 'divisions': <param.Integer object at 0xb3203d4>,
 'duration': <param.Number object at 0xb30ff5c>,
 'generator_sheets': <param.List object at 0xb20d2ec>,
 'name': <param.parameterized.String object at 0xb3158ac>,
 'num_orientation': <param.Integer object at 0xb32041c>,
 'offset': <param.Number object at 0xb30ff14>,
...