The functional model of the circle is:
r**2 = (x - xc)**2 + (y - yc)**2
This estimator minimizes the squared distances from all points to the circle:
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.
Total least squares estimator for 2D circles.
>>> t = np.linspace(0, 2 * np.pi, 25)This example is valid syntax, but we were not able to check execution
... xy = CircleModel().predict_xy(t, params=(2, 3, 4))
... model = CircleModel()
... model.estimate(xy) True
>>> tuple(np.round(model.params, 5)) (2.0, 3.0, 4.0)This example is valid syntax, but we were not able to check execution
>>> res = model.residuals(xy)See :
... np.abs(np.round(res, 9)) array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])
The following pages refer to to this document either explicitly or contain code examples using this.
skimage.measure.fit.CircleModel
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