fixing prospector complaints
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@ -829,8 +829,8 @@ class DADF5():
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for i,q in enumerate(q['data']):
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o = Rotation(np.array([q['w'],q['x'],q['y'],q['z']]))
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rotatedPole = o*pole # rotate pole according to crystal orientation
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(x,y) = rotatedPole[0:2]/(1.+abs(pole[2])) # stereographic projection
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rotatedPole = o*unit_pole # rotate pole according to crystal orientation
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(x,y) = rotatedPole[0:2]/(1.+abs(unit_pole[2])) # stereographic projection
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coords[i] = [np.sqrt(x*x+y*y),np.arctan2(y,x)] if polar else [x,y]
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return {
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@ -839,8 +839,8 @@ class DADF5():
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'meta' : {
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'Unit': '1',
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'Description': '{} coordinates of stereographic projection of pole (direction/plane) in crystal frame'\
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.format('Polar' if polar else 'Cartesian'),
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'Creator' : 'dadf5.py:addPole v{}'.format(version)
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.format('Polar' if polar else 'Cartesian'),
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'Creator' : 'dadf5.py:add_pole v{}'.format(version)
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}
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}
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@ -980,7 +980,8 @@ class DADF5():
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args['results'].put({**args['func'](**args['in']),'group':args['group']})
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env = Environment()
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N_threads = 1#int(env.options['DAMASK_NUM_THREADS'])
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N_threads = int(env.options['DAMASK_NUM_THREADS'])
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N_threads //=N_threads # disable for the moment
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results = Queue(N_threads)
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pool = util.ThreadPool(N_threads)
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@ -299,6 +299,7 @@ def __Mises(x,s):
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Symmetric tensor of which the von Mises equivalent is computed.
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s : float
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Scaling factor (2/3 for strain, 3/2 for stress).
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"""
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d = deviatoric_part(x)
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return np.sqrt(s*(np.sum(d**2.0))) if np.shape(x) == (3,3) else \
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@ -167,11 +167,10 @@ def progressBar(iteration, total, prefix='', bar_length=50):
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def scale_to_coprime(v):
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"""Scale vector to co-prime (relatively prime) integers."""
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MAX_DENOMINATOR = 1000
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def get_square_denominator(x):
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"""returns the denominator of the square of a number."""
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"""Denominator of the square of a number."""
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return Fraction(x ** 2).limit_denominator(MAX_DENOMINATOR).denominator
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def lcm(a, b):
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@ -217,7 +217,6 @@ class TestMechanics:
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A = mechanics.symmetric(np.random.random((self.n,3,3)))
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LRHS = np.linalg.det(mechanics.eigenvectors(A,RHS=False))
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RHS = np.linalg.det(mechanics.eigenvectors(A,RHS=True))
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s = np.random.randint(self.n)
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assert np.allclose(np.abs(LRHS),RHS)
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def test_spherical_no_shear(self):
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