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Fix PyAPI multipole indentation, add more comments
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Sterling Harper
parent
1bc72660de
commit
9649d112ea
1 changed files with 70 additions and 56 deletions
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@ -116,8 +116,10 @@ def _broaden_wmp_polynomials(En, dopp, n):
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factors[2] = (factors[0] * (half_inv_dopp2 + En)
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+ exp_m_beta2 / (beta * np.sqrt(np.pi)))
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# Perform recursive broadening of high order components.
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for i in range(1, n-2):
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# Perform recursive broadening of high order components. range(1, n-4)
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# replaces a do i = 1, n=3. All indices are reduced by one due to the
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# 1-based vs. 0-based indexing.
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for i in range(1, n-4):
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if i != 1:
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factors[i+2] = (-factors[i-2] * (i - 1.0) * i * quarter_inv_dopp4
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+ factors[i] * (En + (1.0 + 2.0 * i) * half_inv_dopp2))
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@ -268,13 +270,17 @@ class WindowedMultipole(EqualityMixin):
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if num_l is not None:
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cv.check_type('num_l', num_l, Integral)
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cv.check_greater_than('num_l', num_l, 1, equality=True)
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cv.check_less_than('num_l', num_l, 4, equality=True)
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# There is an if block in _evaluate that assumes num_l <= 4.
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self._num_l = num_l
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@fit_order.setter
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def fit_order(self, fit_order):
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if fit_order is not None:
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cv.check_type('fit_order', fit_order, Integral)
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cv.check_greater_than('fit_order', fit_order, 1, equality=True)
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cv.check_greater_than('fit_order', fit_order, 2, equality=True)
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# _broaden_wmp_polynomials assumes the curve fit has at least 3
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# terms.
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self._fit_order = fit_order
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@fissionable.setter
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@ -486,6 +492,9 @@ class WindowedMultipole(EqualityMixin):
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"""
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if E < self.start_E: return (0, 0, 0)
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if E >= self.end_E: return (0, 0, 0)
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# ======================================================================
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# Bookkeeping
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@ -495,30 +504,35 @@ class WindowedMultipole(EqualityMixin):
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invE = 1.0 / E
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dopp = self.sqrtAWR / sqrtkT
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# Locate us.
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# Locate us. The i_window calc omits a + 1 present in F90 because of
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# the 1-based vs. 0-based indexing. Similarly startw needs to be
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# decreased by 1. endw does not need to be decreased because
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# range(startw, endw) does not include endw.
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i_window = int(np.floor((sqrtE - np.sqrt(self.start_E)) / self.spacing))
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startw = self.w_start[i_window] - 1
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endw = self.w_end[i_window]
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# Fill in factors.
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# Fill in factors. Because of the unique interference dips in scatering
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# resonances, the total cross section has a special "factor" that does
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# not appear in the absorption and fission equations.
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if startw <= endw:
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twophi = np.zeros(self.num_l, dtype=np.float)
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sigT_factor = np.zeros(self.num_l, dtype=np.cfloat)
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twophi = np.zeros(self.num_l, dtype=np.float)
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sigT_factor = np.zeros(self.num_l, dtype=np.cfloat)
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for iL in range(1, self.num_l+1):
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twophi[iL-1] = self.pseudo_k0RS[iL-1] * sqrtE
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if iL == 2:
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twophi[iL-1] = twophi[iL-1] - np.arctan(twophi[iL-1])
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elif iL == 3:
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arg = 3.0 * twophi[iL-1] / (3.0 - twophi[iL-1]**2)
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twophi[iL-1] = twophi[iL-1] - np.arctan(arg)
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elif iL == 4:
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arg = (twophi[iL-1] * (15.0 - twophi[iL-1]**2)
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/ (15.0 - 6.0 * twophi[iL-1]**2))
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twophi[iL-1] = twophi[iL-1] - np.arctan(arg)
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for iL in range(self.num_l):
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twophi[iL] = self.pseudo_k0RS[iL] * sqrtE
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if iL == 1:
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twophi[iL] = twophi[iL] - np.arctan(twophi[iL])
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elif iL == 2:
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arg = 3.0 * twophi[iL] / (3.0 - twophi[iL]**2)
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twophi[iL] = twophi[iL] - np.arctan(arg)
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elif iL == 3:
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arg = (twophi[iL] * (15.0 - twophi[iL]**2)
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/ (15.0 - 6.0 * twophi[iL]**2))
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twophi[iL] = twophi[iL] - np.arctan(arg)
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twophi = 2.0 * twophi
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sigT_factor = np.cos(twophi) - 1j*np.sin(twophi)
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twophi = 2.0 * twophi
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sigT_factor = np.cos(twophi) - 1j*np.sin(twophi)
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# Initialize the ouptut cross sections.
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sigT = 0.0
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@ -551,44 +565,44 @@ class WindowedMultipole(EqualityMixin):
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# Add the contribution from the poles in this window.
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if sqrtkT == 0.0:
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# If at 0K, use asymptotic form.
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for i_pole in range(startw, endw):
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psi_chi = -1j / (self.data[i_pole, MP_EA] - sqrtE)
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c_temp = psi_chi / E
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if self.formalism == 'MLBW':
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sigT += ((self.data[i_pole, MLBW_RT] * c_temp *
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sigT_factor[self.l_value[i_pole]-1]).real
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+ (self.data[i_pole, MLBW_RX] * c_temp).real)
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sigA += (self.data[i_pole, MLBW_RA] * c_temp).real
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sigF += (self.data[i_pole, MLBW_RF] * c_temp).real
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elif self.formalism == 'RM':
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sigT += (self.data[i_pole, RM_RT] * c_temp *
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sigT_factor[self.l_value[i_pole]-1]).real
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sigA += (self.data[i_pole, RM_RA] * c_temp).real
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sigF += (self.data[i_pole, RM_RF] * c_temp).real
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else:
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raise ValueError('Unrecognized/Unsupported R-matrix'
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' formalism')
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# If at 0K, use asymptotic form.
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for i_pole in range(startw, endw):
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psi_chi = -1j / (self.data[i_pole, MP_EA] - sqrtE)
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c_temp = psi_chi / E
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if self.formalism == 'MLBW':
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sigT += ((self.data[i_pole, MLBW_RT] * c_temp *
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sigT_factor[self.l_value[i_pole]-1]).real
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+ (self.data[i_pole, MLBW_RX] * c_temp).real)
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sigA += (self.data[i_pole, MLBW_RA] * c_temp).real
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sigF += (self.data[i_pole, MLBW_RF] * c_temp).real
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elif self.formalism == 'RM':
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sigT += (self.data[i_pole, RM_RT] * c_temp *
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sigT_factor[self.l_value[i_pole]-1]).real
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sigA += (self.data[i_pole, RM_RA] * c_temp).real
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sigF += (self.data[i_pole, RM_RF] * c_temp).real
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else:
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raise ValueError('Unrecognized/Unsupported R-matrix'
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' formalism')
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else:
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# At temperature, use Faddeeva function-based form.
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for i_pole in range(startw, endw):
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Z = (sqrtE - self.data[i_pole, MP_EA]) * dopp
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w_val = _faddeeva(Z) * dopp * invE * np.sqrt(np.pi)
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if self.formalism == 'MLBW':
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sigT += ((self.data[i_pole, MLBW_RT] *
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sigT_factor[self.l_value[i_pole]-1] +
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self.data[i_pole, MLBW_RX]) * w_val).real
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sigA += (self.data[i_pole, MLBW_RA] * w_val).real
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sigF += (self.data[i_pole, MLBW_RF] * w_val).real
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elif self.formalism == 'RM':
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sigT += (self.data[i_pole, RM_RT] * w_val *
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sigT_factor[self.l_value[i_pole]-1]).real
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sigA += (self.data[i_pole, RM_RA] * w_val).real
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sigF += (self.data[i_pole, RM_RF] * w_val).real
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else:
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raise ValueError('Unrecognized/Unsupported R-matrix'
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' formalism')
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# At temperature, use Faddeeva function-based form.
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for i_pole in range(startw, endw):
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Z = (sqrtE - self.data[i_pole, MP_EA]) * dopp
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w_val = _faddeeva(Z) * dopp * invE * np.sqrt(np.pi)
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if self.formalism == 'MLBW':
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sigT += ((self.data[i_pole, MLBW_RT] *
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sigT_factor[self.l_value[i_pole]-1] +
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self.data[i_pole, MLBW_RX]) * w_val).real
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sigA += (self.data[i_pole, MLBW_RA] * w_val).real
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sigF += (self.data[i_pole, MLBW_RF] * w_val).real
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elif self.formalism == 'RM':
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sigT += (self.data[i_pole, RM_RT] * w_val *
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sigT_factor[self.l_value[i_pole]-1]).real
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sigA += (self.data[i_pole, RM_RA] * w_val).real
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sigF += (self.data[i_pole, RM_RF] * w_val).real
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else:
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raise ValueError('Unrecognized/Unsupported R-matrix'
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' formalism')
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return sigT, sigA, sigF
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