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@ -1136,7 +1136,7 @@ def richardson(Q, k):
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R = Q[k] + (Q[k] - Q[k - 1]) / c
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return R
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def quadgr(fun, a, b, abseps=1e-5):
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def quadgr(fun, a, b, abseps=1e-5, maxiter=17):
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'''
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Gauss-Legendre quadrature with Richardson extrapolation.
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@ -1218,7 +1218,7 @@ def quadgr(fun, a, b, abseps=1e-5):
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Q = -Q
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return Q, err
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#% Gauss-Legendre quadrature (12-point)
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# Gauss-Legendre quadrature (12-point)
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xq = np.asarray([0.12523340851146894, 0.36783149899818018, 0.58731795428661748,
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0.76990267419430469, 0.9041172563704748, 0.98156063424671924])
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wq = np.asarray([0.24914704581340288, 0.23349253653835478, 0.20316742672306584,
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@ -1232,8 +1232,8 @@ def quadgr(fun, a, b, abseps=1e-5):
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# else:
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dtype = np.float64
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#% Initiate vectors
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max_iter = 17 # Max number of iterations
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# Initiate vectors
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# max_iter = 17 # Max number of iterations
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Q0 = zeros(max_iter, dtype=dtype) # Quadrature
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Q1 = zeros(max_iter, dtype=dtype) # First Richardson extrapolation
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Q2 = zeros(max_iter, dtype=dtype) # Second Richardson extrapolation
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@ -1480,10 +1480,12 @@ def main():
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q0 = np.trapz(humps(x), x)
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[q, err] = romberg(humps, 0, np.pi / 2, 1e-4)
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print q, err
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def test_docstrings():
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np.set_printoptions(precision=7)
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import doctest
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doctest.testmod()
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if __name__ == '__main__':
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test_docstrings()
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#main()
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