removed the 3d-specific run_baker method
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@ -39,6 +39,7 @@ def get_phis(X, R):
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# baker: eq 7
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# TODO: perhaps also test len(R[0]) .. ?
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if len(X) == 2:
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log.debug("running 2D")
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A = np.array([
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[ 1, 1, 1],
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[R[0][0], R[1][0], R[2][0]],
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@ -49,6 +50,7 @@ def get_phis(X, R):
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X[1]
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])
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elif len(X) == 3:
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log.debug("running 3D")
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A = np.array([
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[ 1, 1, 1, 1 ],
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[R[0][0], R[1][0], R[2][0], R[3][0]],
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@ -176,89 +178,6 @@ def run_baker(X, R, S, order=2):
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return answer
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def run_baker_3D(X, R, S):
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"""
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This is the main function to call to get an interpolation to X from the input meshes
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X -- the destination point (3D)
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X = [0,0,0]
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R = Simplex (4 points, contains X)
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S = extra points (surrounding, in some manner, R and X, but not in R)
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"""
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# calculate values only for the triangle
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phi, qlin = qlinear_3D(X, R)
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if len(S.verts) == 0:
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answer = {
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'a': None,
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'b': None,
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'c': None,
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'd': None,
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'e': None,
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'f': None,
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'qlin': qlin,
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'error': None,
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'final': None,
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}
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return answer
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B = [] # baker eq 9
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w = [] # baker eq 11
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for (s, q) in zip(S.verts, S.q):
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cur_phi, cur_qlin = qlinear_3D(s, R)
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(phi1, phi2, phi3, phi4) = cur_phi
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B.append(
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[
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phi1 * phi2,
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phi1 * phi3,
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phi1 * phi4,
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phi2 * phi3,
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phi2 * phi4,
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phi3 * phi4,
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]
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)
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w.append(q - cur_qlin)
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B = np.array(B)
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w = np.array(w)
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A = np.dot(B.T, B)
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b = np.dot(B.T, w)
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# baker solve eq 10
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try:
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(a, b, c, d, e, f) = np.linalg.solve(A,b)
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except np.linalg.LinAlgError as e:
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log.error("linear calculation went bad, resorting to np.linalg.pinv: %s", e)
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(a, b, c, d, e, f) = np.dot(np.linalg.pinv(A), b)
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error_term = a * phi[0] * phi[1]\
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+ b * phi[0] * phi[2]\
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+ c * phi[0] * phi[3]\
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+ d * phi[1] * phi[2]\
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+ e * phi[1] * phi[3]\
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+ f * phi[2] * phi[3]
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q_final = qlin + error_term
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answer = {
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'a': a,
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'b': b,
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'c': c,
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'd': d,
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'e': e,
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'f': f,
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'qlin': qlin,
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'error': error_term,
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'final': q_final,
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}
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return answer
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def _boxings(n, k):
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"""\
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