Psychometric functions

csf	The spatio-temporal contrast sensitivity function.
norm_cdf	The cumulate normal distribution.
norm_cdf_2	The cumulative normal distribution with lapse rate equal to lower asymptote.
weibull	A Weibull psychometric function.

questplus.psychometric_function.csf(*, contrast, spatial_freq, temporal_freq, c0, cf, cw, min_thresh, slope=3.5, lower_asymptote=0.01, lapse_rate=0.01, scale='log10')

The spatio-temporal contrast sensitivity function.

Parameters

• contrast (Union[float, Iterable[float]]) –

• spatial_freq (Union[float, Iterable[float]]) –

• temporal_freq (Union[float, Iterable[float]]) –

• c0 (Union[float, Iterable[float]]) –

• cf (Union[float, Iterable[float]]) –

• cw (Union[float, Iterable[float]]) –

• min_thresh (Union[float, Iterable[float]]) –

• slope (Union[float, Iterable[float]]) –

• lower_asymptote (Union[float, Iterable[float]]) –

• lapse_rate (Union[float, Iterable[float]]) –

• scale (str) –

Return type

ndarray

questplus.psychometric_function.norm_cdf(*, intensity, mean, sd, lower_asymptote=0.01, lapse_rate=0.01, scale='linear')

The cumulate normal distribution.

Parameters

• intensity (Union[float, Iterable[float]]) –

• mean (Union[float, Iterable[float]]) –

• sd (Union[float, Iterable[float]]) –

• lower_asymptote (Union[float, Iterable[float]]) –

• lapse_rate (Union[float, Iterable[float]]) –

• scale (str) –

questplus.psychometric_function.norm_cdf_2(*, intensity, mean, sd, lapse_rate=0.01, scale='linear')

The cumulative normal distribution with lapse rate equal to lower asymptote.

Parameters

• intensity (Union[float, Iterable[float]]) –

• mean (Union[float, Iterable[float]]) –

• sd (Union[float, Iterable[float]]) –

• lapse_rate (Union[float, Iterable[float]]) –

• scale (str) –

questplus.psychometric_function.weibull(*, intensity, threshold, slope=3.5, lower_asymptote=0.01, lapse_rate=0.01, scale='log10')

A Weibull psychometric function.

Parameters

• intensity (Union[float, Iterable[float]]) – Stimulus values on the abscissa, \(x\).

• threshold (Union[float, Iterable[float]]) – The threshold parameter, \(\alpha\).

• slope (Union[float, Iterable[float]]) – The slope parameter, \(\beta\).

• lower_asymptote (Union[float, Iterable[float]]) – The lower asymptote, \(\gamma\), which is equivalent to the false-alarm rate in a yes-no task, or \(\frac{1}{n}\) in an \(n\)-AFC task.

• lapse_rate (Union[float, Iterable[float]]) – The lapse rate, \(\delta\). The upper asymptote of the psychometric function will be \(1-\delta\).

• scale (str) – The scale of the stimulus parameters. Possible values are log10, dB, and linear.

Returns

The psychometric function evaluated at the specified intensities for all parameters combinations.

Return type

p

Notes

An appropriate parametrization of the function is chosen based on the scale keyword argument. Specifically, the following parametrizations are used:

scale=’linear’

\(p = 1 - \delta - (1 - \gamma - \delta)\, e^{-\left (\frac{x}{t} \right )^\beta}\)

scale=’log10’

\(p = 1 - \delta - (1 - \gamma - \delta)\, e^{-10^{\beta (x - t)}}\)

scale=’dB’:

\(p = 1 - \delta - (1 - \gamma - \delta)\, e^{-10^{\frac{\beta}{20} (x - t)}}\)