def test_current_inverse(rq_rand):
"""
randomly generates an (r,theta) and applies the transform to
convert to (u,v), then back to (r,theta).
It checks the result is accurate to within 10-10 tolerance
"""
rq_out = uv_to_r_theta_current(r_theta_to_uv_current(rq_rand['rq']))
print 'actual (r,theta): '
print rq_rand['rq']
print 'computed (r,theta): '
print rq_out
assert np.allclose(rq_out, rq_rand['rq'], inv_atol, rtol)
def test_r_theta_to_uv_current(rq_curr):
uv_out = r_theta_to_uv_current(rq_curr['rq'])
assert np.allclose(uv_out, rq_curr['uv'], atol, rtol)
