circlemodel

CircleModel

class skimage.measure.CircleModel [source]

Bases: skimage.measure.fit.BaseModel

Total least squares estimator for 2D circles.

The functional model of the circle is:

1	r**2 = (x - xc)**2 + (y - yc)**2

This estimator minimizes the squared distances from all points to the circle:

1	min{ sum((r - sqrt((x_i - xc)**2 + (y_i - yc)**2))**2) }

A minimum number of 3 points is required to solve for the parameters.

Attributes

params

(tuple) Circle model parameters in the following order xc, yc, r.

__init__() [source]

estimate(data) [source]

Estimate circle model from data using total least squares.

Parameters:	data : (N, 2) array N points with (x, y) coordinates, respectively.
Returns:	success : bool True, if model estimation succeeds.

predict_xy(t, params=None) [source]

Predict x- and y-coordinates using the estimated model.

Parameters:	t : array Angles in circle in radians. Angles start to count from positive x-axis to positive y-axis in a right-handed system. params : (3, ) array, optional Optional custom parameter set.
Returns:	xy : (..., 2) array Predicted x- and y-coordinates.

residuals(data) [source]

Determine residuals of data to model.

For each point the shortest distance to the circle is returned.

Parameters:	data : (N, 2) array N points with (x, y) coordinates, respectively.
Returns:	residuals : (N, ) array Residual for each data point.