Package topo :: Package command :: Module analysis :: Class measure_rfs

Class measure_rfs

Map receptive fields by reverse correlation.

Presents a large collection of input patterns, typically pixel by pixel on and off, keeping track of which units in the specified input_sheet were active when each unit in other Sheets in the simulation was active. This data can then be used to plot receptive fields for each unit. Note that the results are true receptive fields, not the connection fields usually presented in lieu of receptive fields, because they take all circuitry in between the input and the target unit into account.

Note also that it is crucial to set the scale parameter properly when using units with a hard activation threshold (as opposed to a smooth sigmoid), because the input pattern used here may not be a very effective way to drive the unit to activate. The value should be set high enough that the target units activate at least some of the time there is a pattern on the input.

Nested Classes

[hide private]

Inherited from param.parameterized.Parameterized: __metaclass__

Instance Methods

[hide private]

__call__(self, **params)
Measure the response to the specified pattern and store the data in each sheet.

source code

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

source code

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

[hide private]

Inherited from param.parameterized.ParameterizedFunction: __new__

Class Variables

[hide private]

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

__abstract = True
bool(x) -> bool

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

name = <param.parameterized.String object at 0xb31516c>
String identifier for this object.

Inherited from analysis.featureresponses.SingleInputResponseCommand: input_sheet, offset, pattern_presenter, scale, weighted_average

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

Inherited from param.parameterized.Parameterized: print_level

Properties

[hide private]

Inherited from object: __class__

Method Details

[hide private]

call(self, **params)
(Call operator)

source code

Measure the response to the specified pattern and store the data in each sheet.

Overrides: param.parameterized.ParameterizedFunction.__call__

_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]

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= ["offset", "size"])

__abstract

bool(x) -> bool

Returns True when the argument x is true, False otherwise. The builtins True and False are the only two instances of the class bool. The class bool is a subclass of the class int, and cannot be subclassed.

Value:

True

__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>,
 'duration': <param.Number object at 0xb30ff5c>,
 'generator_sheets': <param.List object at 0xb20d2ec>,
 'input_sheet': <param.ObjectSelector object at 0xb32014c>,
 'name': <param.parameterized.String object at 0xb31516c>,
 'offset': <param.Number object at 0xb3201dc>,
 'pattern_presenter': <param.Callable object at 0xb32309c>,
...

Class measure_rfs

__call__(self, **params) (Call operator)

_feature_list(self, p)

static_parameters

__abstract

__params

call(self, **params)
(Call operator)