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Prototype Quaternion dtype support for Numpy - see https://github.com/moble/quaternion for maintained version
martinling/numpy_quaternion
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This Python module adds a quaternion dtype to NumPy. To build: $ python setup.py build To install (may require administrator rights): # python setup.py install Example: >>> import numpy as np >>> import quaternion >>> np.quaternion(1,0,0,0) quaternion(1, 0, 0, 0) >>> q1 = np.quaternion(1,2,3,4) >>> q2 = np.quaternion(5,6,7,8) >>> q1 * q2 quaternion(-60, 12, 30, 24) >>> a = np.array([q1, q2]) >>> a array([quaternion(1, 2, 3, 4), quaternion(5, 6, 7, 8)], dtype=quaternion) >>> exp(a) array([quaternion(1.69392, -0.78956, -1.18434, -1.57912), quaternion(138.909, -25.6861, -29.9671, -34.2481)], dtype=quaternion) The following ufuncs are implemented: add, subtract, multiply, divide, log, exp, power, negative, conjugate, copysign, equal, not_equal, less, less_equal, isnan, isinf, isfinite, absolute Quaternion components are stored as doubles. Comparison operations follow the same lexicographic ordering as tuples. The unary tests isnan and isinf return true if they would return true for any individual component; isfinite returns true if it would return true for all components. Real types may be cast to quaternions, giving quaternions with zero for all three imaginary components. Complex types may also be cast to quaternions, with their single imaginary component becoming the first imaginary component of the quaternion. Quaternions may not be cast to real or complex types. Written at the SciPy 2011 sprints, with help from Mark Weibe. The basic structure of this package is copied from Mark's half-precision floating point package: https://github.com/m-paradox/numpy_half - without this and Mark's help I would have had little chance of figuring out how to do this!
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Prototype Quaternion dtype support for Numpy - see https://github.com/moble/quaternion for maintained version
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