Remove dead code

africanus/averaging/bda_mapping.py

@@ -20,72 +20,6 @@ class RowMapperError(Exception):
     pass
 
 
-# @njit(nogil=True, cache=True)
-# def erf26(x):
-#     """Implements 7.1.26 erf approximation from Abramowitz and
-#        Stegun (1972), pg. 299. Accurate for abs(eps(x)) <= 1.5e-7."""
-
-#     # Constants
-#     p = 0.3275911
-#     a1 = 0.254829592
-#     a2 = -0.284496736
-#     a3 = 1.421413741
-#     a4 = -1.453152027
-#     a5 = 1.061405429
-#     e = 2.718281828
-
-#     # t
-#     t = 1.0/(1.0 + (p * x))
-
-#     # Erf calculation
-#     erf = 1.0 - (((((a5 * t + a4) * t + a3) * t + a2) * t + a1) * t)
-#     erf *= e ** -(x ** 2)
-
-#     return -round(erf, 9) if x < 0 else round(erf, 0)
-
-
-# @njit(nogil=True, cache=True)
-# def time_decorrelation(u, v, w, max_lm, time_bin_secs, min_wavelength):
-#     sidereal_rotation_rate = 7.292118516e-5
-#     diffraction_limit = min_wavelength / np.sqrt(u**2 + v**2 + w**2)
-#     term = max_lm * time_bin_secs * sidereal_rotation_rate / diffraction_limit
-#     return 1.0 - 1.0645 * erf26(0.8326*term) / term
-
-
-# _SERIES_COEFFS = (1./40, 107./67200, 3197./24192000, 49513./3973939200)
-
-
-# @njit(nogil=True, cache=True, inline='always')
-# def inv_sinc(sinc_x, tol=1e-12):
-#     # Invalid input
-#     if sinc_x > 1.0:
-#         raise ValueError("sinc_x > 1.0")
-
-#     # Initial guess from reversion of Taylor series
-#     # https://math.stackexchange.com/questions/3189307/inverse-of-frac-sinxx
-#     x = t_pow = np.sqrt(6*np.abs((1 - sinc_x)))
-#     t_squared = t_pow*t_pow
-
-#     for coeff in numba.literal_unroll(_SERIES_COEFFS):
-#         t_pow *= t_squared
-#         x += coeff * t_pow
-
-#     # Use Newton Raphson to go the rest of the way
-#     # https://www.wolframalpha.com/input/?i=simplify+%28sinc%5Bx%5D+-+c%29+%2F+D%5Bsinc%5Bx%5D%2Cx%5D
-#     while True:
-#         # evaluate delta between this iteration sinc(x) and original
-#         sinx = np.sin(x)
-#         𝞓sinc_x = (1.0 if x == 0.0 else sinx/x) - sinc_x
-
-#         # Stop if converged
-#         if np.abs(𝞓sinc_x) < tol:
-#             break
-
-#         # Next iteration
-#         x -= (x*x * 𝞓sinc_x) / (x*np.cos(x) - sinx)
-
-#     return x
-
 
 @njit(nogil=True, cache=True, inline='always')
 def factors(n):