removed duplication of lsq-ellipse package and call it instead

CHANGELOG.rst

@@ -6,6 +6,12 @@ All notable changes to this project will be documented in this file.
 The format is based on `Keep a Changelog`_,
 and this project adheres to `Semantic Versioning`_.
 
+`Unreleased`_ - 2020-05-11
+--------------------------
+Changed
+'''''''
+- Ellipse of best fit method calls the `lsq-ellipse`_ package.
+
 `1.1.2`_ - 2019-11-07
 ---------------------
 Fixed
@@ -65,4 +71,5 @@ Added
 .. _`1.0.0`: https://github.com/kip-hart/MicroStructPy/releases/tag/v1.0.0
 
 .. _`Keep a Changelog`: https://keepachangelog.com/en/1.0.0/
-.. _`Semantic Versioning`: https://semver.org/spec/v2.0.0.html
+.. _`lsq-ellipse`: https://pypi.org/project/lsq-ellipse
+.. _`Semantic Versioning`: https://semver.org/spec/v2.0.0.html

requirements.txt

@@ -8,3 +8,4 @@ pyvoro-mmalahe==1.3.3
 scipy==1.3.1
 xmltodict==0.12.0
 tox==3.14.0
+lsq-ellipse==2.0.1

setup.py

@@ -86,6 +86,7 @@ def find_version(*fname):
         'aabbtree',
         'matplotlib>=2.2.0,<3.1.0',
         'pybind11',  # must come before meshpy for successful install
+        'lsq-ellipse',
         'meshpy>=2018.2.1',
         'numpy>=1.13.0',
         'pyquaternion',

src/microstructpy/geometry/ellipse.py

@@ -5,6 +5,7 @@
 # --------------------------------------------------------------------------- #
 from __future__ import division
 
+import ellipses as lsqel
 import matplotlib.pyplot as plt
 import numpy as np
 from matplotlib import patches
@@ -169,9 +170,8 @@ def best_fit(self, points):
         r"""Find ellipse of best fit for points
 
         This function computes the ellipse of best fit for a set of points.
-        It is heavily adapted from the `least-squares-ellipse-fitting`_
-        repository on GitHub. This repository implements a published fitting
-        algorithm in Python. [#halir]_
+        It calls the `least-squares-ellipse-fitting`_ package, which implements
+        a published fitting algorithm in Python. [#halir]_
 
         The current instance of the class is used as an initial guess for
         the ellipse of best fit. Since an ellipse can be expressed multiple
@@ -197,7 +197,10 @@ def best_fit(self, points):
         pt_cen = pts.mean(axis=0)
         pts -= pt_cen.reshape(1, -1)
 
-        width, height, phi, xc, yc = _best_fit(pts, self)
+        reg = lsqel.LsqEllipse().fit(pts)
+        center, width, height, phi = reg.as_parameters()
+        xc, yc = center
+
         xc += pt_cen[0]
         yc += pt_cen[1]