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Partial port of mpmath hyp1f1 function
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""" mpmath hyp1f1 algorithm crudely ported """ | |
import math | |
import cmath | |
import operator | |
import numpy as np | |
import scipy.special as sps | |
eps = np.finfo(float).eps | |
H_FACTOR = np.ldexp(1.0, -int(53 * 0.3)) | |
class NoConvergence(Exception): | |
pass | |
def hypsum(p, q, coeffs, z, maxterms=6000): | |
coeffs = list(coeffs) | |
num = range(p) | |
den = range(p,p+q) | |
tol = eps | |
s = t = 1.0 | |
k = 0 | |
while True: | |
for i in num: t *= (coeffs[i]+k) | |
for i in den: t /= (coeffs[i]+k) | |
k += 1; t /= k; t *= z; s += t | |
if abs(t) < tol: | |
return s | |
if k > maxterms: | |
raise NoConvergence | |
def convert(x): | |
try: | |
return float(x) | |
except: | |
return complex(x) | |
def mag(z): | |
if z: | |
return np.frexp(abs(z))[1] | |
return -np.inf | |
def isint(z): | |
if z.imag: | |
return False | |
z = z.real | |
try: | |
return z == int(z) | |
except: | |
return False | |
def expjpi(x): | |
return exp(1j * np.pi * x) | |
def exp(x): | |
if type(x) is float: | |
return math.exp(x) | |
if type(x) is complex: | |
return cmath.exp(x) | |
try: | |
x = float(x) | |
return math.exp(x) | |
except (TypeError, ValueError): | |
x = complex(x) | |
return cmath.exp(x) | |
def power(*args): | |
try: | |
return operator.pow(*(float(x) for x in args)) | |
except (TypeError, ValueError): | |
return operator.pow(*(complex(x) for x in args)) | |
def fneg(x): | |
return -convert(x) | |
def isnpint(x): | |
if type(x) is complex: | |
if x.imag: | |
return False | |
x = x.real | |
return x <= 0.0 and round(x) == x | |
def nint_distance(z): | |
n = round(z.real) | |
if n == z: | |
return n, -np.inf | |
return n, mag(abs(z-n)) | |
def _check_need_perturb(terms, discard_known_zeros): | |
perturb = False | |
discard = [] | |
for term_index, term in enumerate(terms): | |
w_s, c_s, alpha_s, beta_s, a_s, b_s, z = term | |
have_singular_nongamma_weight = False | |
# Avoid division by zero in leading factors (TODO: | |
# also check for near division by zero?) | |
for k, w in enumerate(w_s): | |
if not w: | |
if np.real(c_s[k]) <= 0 and c_s[k]: | |
perturb = True | |
have_singular_nongamma_weight = True | |
pole_count = [0, 0, 0] | |
# Check for gamma and series poles and near-poles | |
for data_index, data in enumerate([alpha_s, beta_s, b_s]): | |
for i, x in enumerate(data): | |
n, d = nint_distance(x) | |
# Poles | |
if n > 0: | |
continue | |
if d == -np.inf: | |
# OK if we have a polynomial | |
# ------------------------------ | |
if data_index == 2: | |
for u in a_s: | |
if isnpint(u) and u >= int(n): | |
break | |
else: | |
pole_count[data_index] += 1 | |
if (discard_known_zeros and | |
pole_count[1] > pole_count[0] + pole_count[2] and | |
not have_singular_nongamma_weight): | |
discard.append(term_index) | |
elif sum(pole_count): | |
perturb = True | |
return perturb, discard | |
def hypercomb(function, params=[], discard_known_zeros=True): | |
params = params[:] | |
terms = function(*params) | |
perturb, discard = _check_need_perturb(terms, discard_known_zeros) | |
if perturb: | |
h = H_FACTOR | |
for k in range(len(params)): | |
params[k] += h | |
# Heuristically ensure that the perturbations | |
# are "independent" so that two perturbations | |
# don't accidentally cancel each other out | |
# in a subtraction. | |
h += h/(k+1) | |
terms = function(*params) | |
if discard_known_zeros: | |
terms = [term for (i, term) in enumerate(terms) if i not in discard] | |
if not terms: | |
return 0. | |
evaluated_terms = [] | |
for term_index, term_data in enumerate(terms): | |
w_s, c_s, alpha_s, beta_s, a_s, b_s, z = term_data | |
# Always hyp2f0 | |
assert len(a_s) == 2 | |
assert len(b_s) == 0 | |
v = np.prod([hypsum(2, 0, a_s, z)] + \ | |
[sps.gamma(a) for a in alpha_s] + \ | |
[sps.rgamma(b) for b in beta_s] + \ | |
[power(w, c) for (w,c) in zip(w_s,c_s)]) | |
evaluated_terms.append(v) | |
if len(terms) == 1 and (not perturb): | |
return evaluated_terms[0] | |
sumvalue = sum(evaluated_terms) | |
return sumvalue | |
def hyp1f1(a, b, z): | |
z = convert(z) | |
if not z: | |
return 1.0 + z | |
magz = mag(z) | |
if magz >= 7 and not (isint(a) and np.real(a) <= 0): | |
if np.isinf(z): | |
if (np.sign(a) == np.sign(b) == np.sign(z) == 1): | |
return np.inf | |
return np.nan * z | |
try: | |
sector = np.imag(z) < 0 | |
def h(a,b): | |
if sector: | |
E = expjpi(fneg(a)) | |
else: | |
E = expjpi(a) | |
rz = 1/z | |
T1 = ([E,z], [1,-a], [b], [b-a], [a, 1+a-b], [], -rz) | |
T2 = ([exp(z),z], [1,a-b], [b], [a], [b-a, 1-a], [], rz) | |
return T1, T2 | |
v = hypercomb(h, [a,b]) | |
if np.isrealobj(a) and np.isrealobj(b) and np.isrealobj(z): | |
v = np.real(v) | |
return v | |
except NoConvergence: | |
pass | |
v = hypsum(1, 1, [a, b], z) | |
return v |
The code still has issues (as pointed in the mpmath blog http://fredrikj.net/blog/2009/09/python-floats-and-other-unusual-things-spotted-in-mpmath/), this is inherently due to floating point precision sadly.
mpmath:
mp.hyp1f1(2.5, 1.2, -30.5)
6.62762709628679e-5
fp.hyp1f1(2.5, 1.2, -30.5)
-0.012819333651375751
This version :
In [9]: hyp1f1(2.5,1.2,-30.5)
Out[9]: -0.01281933365137575
scipy :
In [2]: hyp1f1(2.5,1.2,-30.5)
Out[2]: 6.6276270962867717e-05
So... it might no happen in our restricted usecase (first argument is always 0.5 or -1.5 I think, something close to that, but who knows), but giving that to scipy might be harder to sell, since both versions exhibit complimentary issues.
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Equivalently crude cython port, so much python stuff that we can't change though.