# Changeset bea7acb in sasmodels

Ignore:
Timestamp:
Mar 10, 2016 8:56:46 AM (9 years ago)
Branches:
master, core_shell_microgels, costrafo411, magnetic_model, release_v0.94, release_v0.95, ticket-1257-vesicle-product, ticket_1156, ticket_1265_superball, ticket_822_more_unit_tests
Children:
fc0fcd0, 3a45c2c
Parents:
0d0aee1 (diff), b15849c (diff)
Note: this is a merge changeset, the changes displayed below correspond to the merge itself.
Use the (diff) links above to see all the changes relative to each parent.
Message:

Merge remote-tracking branch 'origin/master'

Files:
5 edited

Unmodified
Removed
• ## explore/J1c.py

 re6f1410 import pylab mp.dps = 150 # number of digits to use in estimating true value SHOW_DIFF = True  # True if show diff rather than function value LINEAR_X = False  # True if q is linearly spaced instead of log spaced def mp_J1c(vec): def mp_J1c(vec, bits=500): """ Direct calculation using sympy multiprecision library. """ return [_mp_J1c(mp.mpf(x)) for x in vec] with mp.workprec(bits): return [_mp_J1c(mp.mpf(x)) for x in vec] def _mp_J1c(x): return mp.mpf(2)*mp.j1(x)/x def np_j1c(x, dtype): def np_J1c(x, dtype): """ Direct calculation using scipy. """ from scipy.special import j1 from scipy.special import j1 as J1 x = np.asarray(x, dtype) return np.asarray(2, dtype)*j1(x)/x return np.asarray(2, dtype)*J1(x)/x def cephes_j1c(x, dtype, n): def cephes_J1c(x, dtype, n): """ Calculation using pade approximant. """ f = np.float64 if np.dtype(dtype) == np.float64 else np.float32 x = np.asarray(x, dtype) ans = np.empty_like(x) # Branch a a_idx = ax < 8.0 a_idx = ax < f(8.0) a_xsq = x[a_idx]**2 a_coeff1 = list(reversed((72362614232.0, -7895059235.0, 242396853.1, -2972611.439, 15704.48260, -30.16036606))) a_coeff2 = list(reversed((144725228442.0, 2300535178.0, 18583304.74, 99447.43394, 376.9991397, 1.0))) a_ans1 = np.polyval(a_coeff1[n:], a_xsq) a_ans2 = np.polyval(a_coeff2[n:], a_xsq) ans[a_idx] = 2*a_ans1/a_ans2 a_ans1 = np.polyval(np.asarray(a_coeff1[n:], dtype), a_xsq) a_ans2 = np.polyval(np.asarray(a_coeff2[n:], dtype), a_xsq) ans[a_idx] = f(2.0)*a_ans1/a_ans2 # Branch b b_x = x[b_idx] b_y = 64.0/(b_ax**2) b_xx = b_ax - 2.356194491 b_y = f(64.0)/(b_ax**2) b_xx = b_ax - f(2.356194491) b_coeff1 = list(reversed((1.0, 0.183105e-2, -0.3516396496e-4, 0.2457520174e-5, -0.240337019e-6))) b_coeff2 = list(reversed((0.04687499995, -0.2002690873e-3, 0.8449199096e-5, -0.88228987e-6, 0.105787412e-6))) b_ans1 = np.polyval(b_coeff1[n:], b_y) b_ans2 = np.polyval(b_coeff2[n:], b_y) b_ans1 = np.polyval(np.asarray(b_coeff1[n:], dtype),b_y) b_ans2 = np.polyval(np.asarray(b_coeff2[n:], dtype), b_y) b_sn, b_cn = np.sin(b_xx), np.cos(b_xx) ans[b_idx] = np.sign(b_x)*np.sqrt(0.636619772/b_ax) * (b_cn*b_ans1 - (8.0/b_ax)*b_sn*b_ans2)*2.0/b_x ans[b_idx] = np.sign(b_x)*np.sqrt(f(0.636619772)/b_ax) * (b_cn*b_ans1 - (f(8.0)/b_ax)*b_sn*b_ans2)*f(2.0)/b_x return ans def div_J1c(x, dtype): f = np.float64 if np.dtype(dtype) == np.float64 else np.float32 x = np.asarray(x, dtype) return f(2.0)*np.asarray([_J1(xi, f)/xi for xi in x], dtype) def _J1(x, f): ax = abs(x) if ax < f(8.0): y = x*x ans1 = x*(f(72362614232.0) + y*(f(-7895059235.0) + y*(f(242396853.1) + y*(f(-2972611.439) + y*(f(15704.48260) + y*(f(-30.16036606))))))) ans2 = (f(144725228442.0) + y*(f(2300535178.0) + y*(f(18583304.74) + y*(f(99447.43394) + y*(f(376.9991397) + y))))) return ans1/ans2 else: y = f(64.0)/(ax*ax) xx = ax - f(2.356194491) ans1 = (f(1.0) + y*(f(0.183105e-2) + y*(f(-0.3516396496e-4) + y*(f(0.2457520174e-5) + y*f(-0.240337019e-6))))) ans2 = (f(0.04687499995) + y*(f(-0.2002690873e-3) + y*(f(0.8449199096e-5) + y*(f(-0.88228987e-6) + y*f(0.105787412e-6))))) sn, cn = np.sin(xx), np.cos(xx) ans = np.sqrt(f(0.636619772)/ax) * (cn*ans1 - (f(8.0)/ax)*sn*ans2) return -ans if (x < f(0.0)) else ans def plotdiff(x, target, actual, label): """ target = np.asarray(mp_J1c(x), 'double') direct = np_j1c(x, precision) approx0 = cephes_j1c(x, precision, 0) approx1 = cephes_j1c(x, precision, 1) plotdiff(x, target, direct, 'direct '+precision) plotdiff(x, target, approx0, 'cephes '+precision) #plotdiff(x, target, approx1, 'reduced '+precision) #plotdiff(x, target, mp_J1c(x, 11), 'mp 11 bits') plotdiff(x, target, np_J1c(x, precision), 'direct '+precision) plotdiff(x, target, cephes_J1c(x, precision, 0), 'cephes '+precision) #plotdiff(x, target, cephes_J1c(x, precision, 1), 'cephes '+precision) #plotdiff(x, target, div_J1c(x, precision), 'cephes 2 J1(x)/x '+precision) pylab.xlabel("qr (1/Ang)") if SHOW_DIFF: if __name__ == "__main__": print "\n".join(str(x) for x in mp_J1c([1e-6,1e-5,1e-4,1e-3])) #print "\n".join(str(x) for x in mp_J1c([1e-6,1e-5,1e-4,1e-3])) main() pylab.show()
• ## sasmodels/models/power_law.py

 r841753c #power_law model #conversion of PowerLawAbsModel.py #converted by Steve King, Dec 2015 r"""
• ## doc/rst_prolog

 r0a4628d .. |cm^-2| replace:: cm\ :sup:`-2` .. |cm^3| replace:: cm\ :sup:`3` .. |1e15cm^3| replace:: 10\ :sup:`15`\ cm\ :sup:`3` .. |cm^-3| replace:: cm\ :sup:`-3` .. |sr^-1| replace:: sr\ :sup:`-1`
• ## sasmodels/convert.py

 r7d4b2ae new model definition end with sld. """ return dict((p, (v*1e6 if p.endswith('sld') else v)) return dict((p, (v*1e6 if p.endswith('sld') else v*1e-15 if 'ndensity' in p else v)) for p, v in pars.items()) new model definition end with sld. """ return dict((p, (v*1e-6 if p.endswith('sld') else v)) return dict((p, (v*1e-6 if p.endswith('sld') else v*1e15 if 'ndensity' in p else v)) for p, v in pars.items())
• ## sasmodels/generate.py

 rc437dbb "1/Ang^2": "|Ang^-2|", "1e-6/Ang^2": "|1e-6Ang^-2|", "1e15/cm^3": "|1e15cm^3|", "degrees": "degree", "1/cm": "|cm^-1|", "1/cm^3": "|cm^-3|", "Ang/cm": "|Ang*cm^-1|", "Ang^3": "|Ang^3|", "": "None", }
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