Accuracy warnings in scipy.special - python-2.7

Question

I am running an MCMC sampler which requires the calculation of the hypergeometric function at each step using scipy.special.hyp2f1().
At certain points on my grid (which I do not care about) the solutions to the hypergeometric function are quite unstable and SciPy prints the warning:
Warning! You should check the accuracy
This is rather annoying, and over 1000s of samples may well slow down my routine.
I have tried using special.errprint(0) with no luck, as well as disabling all warnings in Python using both the warnings module and the -W ignore flag.
The offending function (called from another file) is below
from numpy import pi, hypot, real, imag
import scipy.special as special
def deflection_angle(p, (x1, x2)):
# Find the normalisation constant
norm = (p.f * p.m * (p.r0 ** (t - 2.0)) / pi) ** (1.0 / t)
# Define the complex plane
z = x1 + 1j * x2
# Define the radial coordinates
r = hypot(x1, x2)
# Truncate the radial coordinates
r_ = r * (r < p.r0).astype('float') + p.r0 * (r >= p.r0).astype('float')
# Calculate the radial part
radial = (norm ** 2 / (p.f * z)) * ((norm / r_) ** (t - 2))
# Calculate the angular part
h1, h2, h3 = 0.5, 1.0 - t / 2.0, 2.0 - t / 2.0
h4 = ((1 - p.f ** 2) / p.f ** 2) * (r_ / z) ** 2
special.errprint(0)
angular = special.hyp2f1(h1, h2, h3, h4)
# Assemble the deflection angle
alpha = (- radial * angular).conjugate()
# Separate real and imaginary parts
return real(alpha), imag(alpha)`

Answer 1

Unfortunately, hyp2f1 is notoriously hard to compute over some non-trivial areas of the parameter space. Many implementations would dilently produce inaccurate or wildly wrong results. Scipy.special tries hard to at least monitor convergence. An alternative could be to usr arbitrary precision implementations, e.g. mpmath. But these would certainly be quite a bit slower, so MCMC users beware.
EDIT: Ok, this seems to be scipy version dependent. I tried #wrwrwr's example on scipy 0.13.3, and it reproduces what you see: "Warning! You should check the accuracy" is printed regardless of the errprint status. However, doing the same with the dev version, I get
In [12]: errprint(True)
Out[12]: 0
In [13]: hyp2f1(0.5, 2/3., 1.5, 0.09j+0.75j)
/home/br/virtualenvs/scipy_py27/bin/ipython:1: SpecialFunctionWarning: scipy.special/chyp2f1: loss of precision
#!/home/br/virtualenvs/scipy_py27/bin/python
Out[13]: (0.93934867949609357+0.15593972567482395j)
In [14]: errprint(False)
Out[14]: 1
In [15]: hyp2f1(0.5, 2/3., 1.5, 0.09j+0.75j)
Out[15]: (0.93934867949609357+0.15593972567482395j)
So, apparently it got fixed at some point between 2013 and now. You might want to upgrade your scipy version.