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              "value": "The estimation is carried out using a 2D version of the spherical estimation given in "
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        "value": "t = np.linspace(0, 2 * np.pi, 25)\nxy = CircleModel((2, 3), 4).predict_xy(t)\n",
        "execution_status": "success"
      },
      {
        "__type": "Code",
        "__tag": 4050,
        "value": "model = CircleModel.from_estimate(xy)\nmodel.center\nmodel.radius\nres = model.residuals(xy)\nnp.abs(np.round(res, 9))\n",
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      },
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        "value": "\nThe estimation can fail when — for example — all the input or output\npoints are the same.  If this happens, you will get a transform that is not\n\"truthy\" - meaning that ``bool(tform)`` is ``False``:\n\n"
      },
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        "value": "if model:\n    print(\"Estimation succeeded.\")\n",
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        "value": "bad_data = np.ones((4, 2))\nbad_model = CircleModel.from_estimate(bad_data)\nif not bad_model:\n    print(\"Estimation failed.\")\n",
        "execution_status": "success"
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        "value": "\nTrying to use this failed estimation transform result will give a suitable\nerror:\n\n"
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        "value": "bad_model.residuals(xy)  # doctest: +IGNORE_EXCEPTION_DETAIL\n",
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    "target_name": "CircleModel"
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  "references": [
    ".. [1] Jekel, Charles F. Obtaining non-linear orthotropic material models",
    "       for pvc-coated polyester via inverse bubble inflation.",
    "       Thesis (MEng), Stellenbosch University, 2016. Appendix A, pp. 83-87.",
    "       https://hdl.handle.net/10019.1/98627"
  ],
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