CircleModel
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class skimage.measure.CircleModel
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Bases:
skimage.measure.fit.BaseModel
Total least squares estimator for 2D circles.
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.
Attributes
params (tuple) Circle model parameters in the following order xc
,yc
,r
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__init__()
[source]
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estimate(data)
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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.
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predict_xy(t, params=None)
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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.
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residuals(data)
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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.
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