Changeset 9e7837a in sasmodels


Ignore:
Timestamp:
Jul 27, 2018 7:33:49 PM (6 years ago)
Author:
Paul Kienzle <pkienzle@…>
Branches:
master, core_shell_microgels, magnetic_model, ticket-1257-vesicle-product, ticket_1156, ticket_1265_superball, ticket_822_more_unit_tests
Children:
c11d09f
Parents:
581661f
Message:

use asymmetric integration window for resolution, (-2.5,+3.0) sigma

File:
1 edited

Legend:

Unmodified
Added
Removed
  • sasmodels/resolution.py

    r0b9c6df r9e7837a  
    2020MINIMUM_RESOLUTION = 1e-8 
    2121MINIMUM_ABSOLUTE_Q = 0.02  # relative to the minimum q in the data 
    22 PINHOLE_N_SIGMA = 2.5 # From: Barker & Pedersen 1995 JAC 
     22# According to (Barker & Pedersen 1995 JAC), 2.5 sigma is a good limit. 
     23# According to simulations with github.com:scattering/sansresolution.git 
     24# it is better to use asymmetric bounds (2.5, 3.0) 
     25PINHOLE_N_SIGMA = (2.5, 3.0) 
    2326 
    2427class Resolution(object): 
     
    9093        # from the geometry, they may appear since we are using a truncated 
    9194        # gaussian to represent resolution rather than a skew distribution. 
    92         cutoff = MINIMUM_ABSOLUTE_Q*np.min(self.q) 
    93         self.q_calc = self.q_calc[self.q_calc >= cutoff] 
     95        #cutoff = MINIMUM_ABSOLUTE_Q*np.min(self.q) 
     96        #self.q_calc = self.q_calc[self.q_calc >= cutoff] 
    9497 
    9598        # Build weight matrix from calculated q values 
     
    188191    cdf = erf((edges[:, None] - q[None, :]) / (sqrt(2.0)*q_width)[None, :]) 
    189192    weights = cdf[1:] - cdf[:-1] 
    190     # Limit q range to +/- 2.5 sigma 
    191     qhigh = q + nsigma*q_width 
    192     #qlow = q - nsigma*q_width  # linear limits 
    193     qlow = q*q/qhigh  # log limits 
     193    # Limit q range to (-2.5,+3) sigma 
     194    try: 
     195        nsigma_low, nsigma_high = nsigma 
     196    except TypeError: 
     197        nsigma_low = nsigma_high = nsigma 
     198    qhigh = q + nsigma_high*q_width 
     199    qlow = q - nsigma_low*q_width  # linear limits 
     200    ##qlow = q*q/qhigh  # log limits 
    194201    weights[q_calc[:, None] < qlow[None, :]] = 0. 
    195202    weights[q_calc[:, None] > qhigh[None, :]] = 0. 
     
    365372 
    366373 
    367 def pinhole_extend_q(q, q_width, nsigma=3): 
     374def pinhole_extend_q(q, q_width, nsigma=PINHOLE_N_SIGMA): 
    368375    """ 
    369376    Given *q* and *q_width*, find a set of sampling points *q_calc* so 
     
    371378    function. 
    372379    """ 
    373     q_min, q_max = np.min(q - nsigma*q_width), np.max(q + nsigma*q_width) 
     380    try: 
     381        nsigma_low, nsigma_high = nsigma 
     382    except TypeError: 
     383        nsigma_low = nsigma_high = nsigma 
     384    q_min, q_max = np.min(q - nsigma_low*q_width), np.max(q + nsigma_high*q_width) 
    374385    return linear_extrapolation(q, q_min, q_max) 
    375386 
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