Changeset 50f1477 in sasview for src/sas/sascalc
- Timestamp:
- Dec 19, 2016 7:25:08 AM (8 years ago)
- Branches:
- master, ESS_GUI, ESS_GUI_Docs, ESS_GUI_batch_fitting, ESS_GUI_bumps_abstraction, ESS_GUI_iss1116, ESS_GUI_iss879, ESS_GUI_iss959, ESS_GUI_opencl, ESS_GUI_ordering, ESS_GUI_sync_sascalc, costrafo411, magnetic_scatt, release-4.1.1, release-4.1.2, release-4.2.2, ticket-1009, ticket-1094-headless, ticket-1242-2d-resolution, ticket-1243, ticket-1249, ticket885, unittest-saveload
- Children:
- 09fdc89, b61bd57
- Parents:
- f2724b6 (diff), 345e7e4 (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. - git-author:
- jhbakker <j.h.bakker@…> (12/19/16 07:25:08)
- git-committer:
- GitHub <noreply@…> (12/19/16 07:25:08)
- Location:
- src/sas/sascalc
- Files:
-
- 5 edited
-
data_util/qsmearing.py (modified) (7 diffs)
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dataloader/data_info.py (modified) (7 diffs)
-
dataloader/readers/sesans_reader.py (modified) (8 diffs)
-
fit/AbstractFitEngine.py (modified) (2 diffs)
-
fit/BumpsFitting.py (modified) (1 diff)
Legend:
- Unmodified
- Added
- Removed
-
src/sas/sascalc/data_util/qsmearing.py
rc6728e1 r345e7e4 5 5 #This software was developed by the University of Tennessee as part of the 6 6 #Distributed Data Analysis of Neutron Scattering Experiments (DANSE) 7 #project funded by the US National Science Foundation. 7 #project funded by the US National Science Foundation. 8 8 #See the license text in license.txt 9 9 #copyright 2008, University of Tennessee … … 13 13 import logging 14 14 import sys 15 from sasmodels import sesans16 import numpy as np # type: ignore17 from numpy import pi, exp # type: ignore18 15 19 16 from sasmodels.resolution import Slit1D, Pinhole1D 20 from sasmodels.sesans import SESANS1D21 17 from sasmodels.resolution2d import Pinhole2D 22 from src.sas.sascalc.data_util.nxsunit import Converter23 24 18 25 19 def smear_selection(data, model = None): … … 42 36 # Sanity check. If we are not dealing with a SAS Data1D 43 37 # object, just return None 44 45 # This checks for 2D data (does not throw exception because fail is common)46 38 if data.__class__.__name__ not in ['Data1D', 'Theory1D']: 47 39 if data == None: … … 50 42 return None 51 43 return Pinhole2D(data) 52 # This checks for 1D data with smearing info in the data itself (again, fail is likely; no exceptions) 44 53 45 if not hasattr(data, "dx") and not hasattr(data, "dxl")\ 54 46 and not hasattr(data, "dxw"): … … 56 48 57 49 # Look for resolution smearing data 58 # This is the code that checks for SESANS data; it looks for the file loader59 # TODO: change other sanity checks to check for file loader instead of data structure?60 _found_sesans = False61 #if data.dx is not None and data.meta_data['loader']=='SESANS':62 if data.dx is not None and data.isSesans:63 #if data.dx[0] > 0.0:64 if numpy.size(data.dx[data.dx <= 0]) == 0:65 _found_sesans = True66 #if data.dx[0] <= 0.0:67 if numpy.size(data.dx[data.dx <= 0]) > 0:68 raise ValueError('one or more of your dx values are negative, please check the data file!')69 if _found_sesans == True:70 #Pre-compute the Hankel matrix (H)71 qmax, qunits = data.sample.zacceptance72 hankel=sesans.SesansTransform()73 sesans.SesansTransform.set_transform(hankel,74 SE = Converter(data._xunit)(data.x, "A"),75 zaccept = Converter(qunits)(qmax, "1/A"),76 Rmax = 10000000)77 # Then return the actual transform, as if it were a smearing function78 return PySmear(SESANS1D(data, hankel._H0, hankel._H, hankel.q), model)79 80 50 _found_resolution = False 81 51 if data.dx is not None and len(data.dx) == len(data.x): … … 122 92 self.model = model 123 93 self.resolution = resolution 124 if hasattr(self.resolution, 'data'): 125 if self.resolution.data.meta_data['loader'] == 'SESANS': # Always True if file extension is '.ses'! 126 self.offset = 0 127 # This is default behaviour, for future resolution/transform functions this needs to be revisited. 128 else: 129 self.offset = numpy.searchsorted(self.resolution.q_calc, self.resolution.q[0]) 130 else: 131 self.offset = numpy.searchsorted(self.resolution.q_calc, self.resolution.q[0]) 132 133 #self.offset = numpy.searchsorted(self.resolution.q_calc, self.resolution.q[0]) 94 self.offset = numpy.searchsorted(self.resolution.q_calc, self.resolution.q[0]) 134 95 135 96 def apply(self, iq_in, first_bin=0, last_bin=None): … … 165 126 q[first:last+1]. 166 127 """ 167 168 128 q = self.resolution.q 169 129 first = numpy.searchsorted(q, q_min) -
src/sas/sascalc/dataloader/data_info.py
r1fac6c0 r345e7e4 25 25 import numpy 26 26 import math 27 28 class plottable_sesans1D(object): 29 """ 30 SESANS is a place holder for 1D SESANS plottables. 31 32 #TODO: This was directly copied from the plottables_1D. Modified Somewhat. 33 #Class has been updated. 34 """ 35 # The presence of these should be mutually 36 # exclusive with the presence of Qdev (dx) 37 x = None 38 y = None 39 lam = None 40 dx = None 41 dy = None 42 dlam = None 43 ## Slit smearing length 44 dxl = None 45 ## Slit smearing width 46 dxw = None 47 48 # Units 49 _xaxis = '' 50 _xunit = '' 51 _yaxis = '' 52 _yunit = '' 53 54 def __init__(self, x, y, lam, dx=None, dy=None, dlam=None): 55 # print "SESANS plottable working" 56 self.x = numpy.asarray(x) 57 self.y = numpy.asarray(y) 58 self.lam = numpy.asarray(lam) 59 if dx is not None: 60 self.dx = numpy.asarray(dx) 61 if dy is not None: 62 self.dy = numpy.asarray(dy) 63 if dlam is not None: 64 self.dlam = numpy.asarray(dlam) 65 66 def xaxis(self, label, unit): 67 """ 68 set the x axis label and unit 69 """ 70 self._xaxis = label 71 self._xunit = unit 72 73 def yaxis(self, label, unit): 74 """ 75 set the y axis label and unit 76 """ 77 self._yaxis = label 78 self._yunit = unit 79 80 27 81 class plottable_1D(object): 28 82 """ … … 40 94 dxw = None 41 95 42 ## SESANS specific params (wavelengths for spin echo length calculation)43 44 lam = None45 dlam = None46 47 96 # Units 48 97 _xaxis = '' … … 51 100 _yunit = '' 52 101 53 def __init__(self, x, y, dx=None, dy=None, dxl=None, dxw=None , lam=None, dlam=None):102 def __init__(self, x, y, dx=None, dy=None, dxl=None, dxw=None): 54 103 self.x = numpy.asarray(x) 55 104 self.y = numpy.asarray(y) … … 62 111 if dxw is not None: 63 112 self.dxw = numpy.asarray(dxw) 64 if lam is not None:65 self.lam = numpy.asarray(lam)66 if dlam is not None:67 self.dlam = numpy.asarray(dlam)68 113 69 114 def xaxis(self, label, unit): … … 691 736 return self._perform_union(other) 692 737 693 class Data1D(plottable_1D, DataInfo): 694 """ 695 1D data class 696 """ 697 #if plottable_1D.lam is None: # This means it's SANS data! 698 # x_unit = '1/A' 699 # y_unit = '1/cm' 700 #elif plottable_1D.lam is not None: # This means it's SESANS data! 701 # x_unit = 'A' 702 # y_unit = 'pol' 703 #else: # and if it's neither, you get punished! 704 # raise(TypeError,'This is neither SANS nor SESANS data, what the hell are you doing??') 705 706 def __init__(self, x=None, y=None, dx=None, dy=None, lam=None, dlam=None, isSesans=False): 707 self.isSesans = isSesans 738 class SESANSData1D(plottable_sesans1D, DataInfo): 739 """ 740 SESANS 1D data class 741 """ 742 x_unit = 'nm' 743 y_unit = 'pol' 744 745 def __init__(self, x=None, y=None, lam=None, dx=None, dy=None, dlam=None): 708 746 DataInfo.__init__(self) 709 plottable_1D.__init__(self, x, y, dx, dy,None, None, lam, dlam) 710 if self.isSesans: 711 x_unit = 'A' 712 y_unit = 'pol' 713 elif not self.isSesans: # it's SANS data! (Could also be simple else statement, but i prefer exhaustive conditionals...-JHB) 714 x_unit = '1/A' 715 y_unit = '1/cm' 716 else: # and if it's neither, you get punished! 717 raise(TypeError,'This is neither SANS nor SESANS data, what the hell are you doing??') 747 plottable_sesans1D.__init__(self, x, y, lam, dx, dy, dlam) 718 748 719 749 def __str__(self): … … 729 759 return _str 730 760 761 def clone_without_data(self, length=0, clone=None): 762 """ 763 Clone the current object, without copying the data (which 764 will be filled out by a subsequent operation). 765 The data arrays will be initialized to zero. 766 767 :param length: length of the data array to be initialized 768 :param clone: if provided, the data will be copied to clone 769 """ 770 from copy import deepcopy 771 if clone is None or not issubclass(clone.__class__, Data1D): 772 x = numpy.zeros(length) 773 dx = numpy.zeros(length) 774 y = numpy.zeros(length) 775 dy = numpy.zeros(length) 776 clone = Data1D(x, y, dx=dx, dy=dy) 777 778 clone.title = self.title 779 clone.run = self.run 780 clone.filename = self.filename 781 clone.instrument = self.instrument 782 clone.notes = deepcopy(self.notes) 783 clone.process = deepcopy(self.process) 784 clone.detector = deepcopy(self.detector) 785 clone.sample = deepcopy(self.sample) 786 clone.source = deepcopy(self.source) 787 clone.collimation = deepcopy(self.collimation) 788 clone.trans_spectrum = deepcopy(self.trans_spectrum) 789 clone.meta_data = deepcopy(self.meta_data) 790 clone.errors = deepcopy(self.errors) 791 792 return clone 793 794 class Data1D(plottable_1D, DataInfo): 795 """ 796 1D data class 797 """ 798 x_unit = '1/A' 799 y_unit = '1/cm' 800 801 def __init__(self, x, y, dx=None, dy=None): 802 DataInfo.__init__(self) 803 plottable_1D.__init__(self, x, y, dx, dy) 804 805 def __str__(self): 806 """ 807 Nice printout 808 """ 809 _str = "%s\n" % DataInfo.__str__(self) 810 _str += "Data:\n" 811 _str += " Type: %s\n" % self.__class__.__name__ 812 _str += " X-axis: %s\t[%s]\n" % (self._xaxis, self._xunit) 813 _str += " Y-axis: %s\t[%s]\n" % (self._yaxis, self._yunit) 814 _str += " Length: %g\n" % len(self.x) 815 return _str 816 731 817 def is_slit_smeared(self): 732 818 """ … … 757 843 y = numpy.zeros(length) 758 844 dy = numpy.zeros(length) 759 lam = numpy.zeros(length) 760 dlam = numpy.zeros(length) 761 clone = Data1D(x, y, lam=lam, dx=dx, dy=dy, dlam=dlam ) 845 clone = Data1D(x, y, dx=dx, dy=dy) 762 846 763 847 clone.title = self.title -
src/sas/sascalc/dataloader/readers/sesans_reader.py
ra01af35 r345e7e4 8 8 import numpy 9 9 import os 10 from sas.sascalc.dataloader.data_info import Data1D10 from sas.sascalc.dataloader.data_info import SESANSData1D 11 11 12 12 # Check whether we have a converter available … … 59 59 raise RuntimeError, "sesans_reader: cannot open %s" % path 60 60 buff = input_f.read() 61 # print buff 61 62 lines = buff.splitlines() 63 # print lines 64 #Jae could not find python universal line spliter: 65 #keep the below for now 66 # some ascii data has \r line separator, 67 # try it when the data is on only one long line 68 # if len(lines) < 2 : 69 # lines = buff.split('\r') 70 62 71 x = numpy.zeros(0) 63 72 y = numpy.zeros(0) … … 74 83 tdlam = numpy.zeros(0) 75 84 tdx = numpy.zeros(0) 76 output = Data1D(x=x, y=y, lam=lam, dy=dy, dx=dx, dlam=dlam, isSesans=True ) 85 # print "all good" 86 output = SESANSData1D(x=x, y=y, lam=lam, dy=dy, dx=dx, dlam=dlam) 87 # print output 77 88 self.filename = output.filename = basename 78 89 90 # #Initialize counters for data lines and header lines. 91 # is_data = False # Has more than 5 lines 92 # # More than "5" lines of data is considered as actual 93 # # data unless that is the only data 94 # mum_data_lines = 5 95 # # To count # of current data candidate lines 96 # i = -1 97 # # To count total # of previous data candidate lines 98 # i1 = -1 99 # # To count # of header lines 100 # j = -1 101 # # Helps to count # of header lines 102 # j1 = -1 103 # #minimum required number of columns of data; ( <= 4). 104 # lentoks = 2 79 105 paramnames=[] 80 106 paramvals=[] … … 85 111 Pvals=[] 86 112 dPvals=[] 113 # print x 114 # print zvals 87 115 for line in lines: 88 116 # Initial try for CSV (split on ,) … … 94 122 if len(toks)>5: 95 123 zvals.append(toks[0]) 96 dzvals.append(toks[ 3])97 lamvals.append(toks[ 4])98 dlamvals.append(toks[ 5])99 Pvals.append(toks[ 1])100 dPvals.append(toks[ 2])124 dzvals.append(toks[1]) 125 lamvals.append(toks[2]) 126 dlamvals.append(toks[3]) 127 Pvals.append(toks[4]) 128 dPvals.append(toks[5]) 101 129 else: 102 130 continue … … 112 140 default_z_unit = "A" 113 141 data_conv_P = None 114 default_p_unit = " " # Adjust unit for axis (L^-3)142 default_p_unit = " " 115 143 lam_unit = lam_header[1].replace("[","").replace("]","") 116 if lam_unit == 'AA':117 lam_unit = 'A'118 144 varheader=[zvals[0],dzvals[0],lamvals[0],dlamvals[0],Pvals[0],dPvals[0]] 119 145 valrange=range(1, len(zvals)) … … 135 161 output.x, output.x_unit = self._unit_conversion(x, lam_unit, default_z_unit) 136 162 output.y = y 137 output.y_unit = '\AA^{-2} cm^{-1}' # output y_unit erbij138 163 output.dx, output.dx_unit = self._unit_conversion(dx, lam_unit, default_z_unit) 139 164 output.dy = dy … … 141 166 output.dlam, output.dlam_unit = self._unit_conversion(dlam, lam_unit, default_z_unit) 142 167 143 output.xaxis("\ \rm{z}", output.x_unit)144 output.yaxis("\\rm{ ln(P)/(t \lambda^2)}", output.y_unit) # Adjust label to ln P/(lam^2 t), remove lam column refs168 output.xaxis("\rm{z}", output.x_unit) 169 output.yaxis("\\rm{P/P0}", output.y_unit) 145 170 # Store loading process information 146 171 output.meta_data['loader'] = self.type_name 147 #output.sample.thickness = float(paramvals[6])172 output.sample.thickness = float(paramvals[6]) 148 173 output.sample.name = paramvals[1] 149 174 output.sample.ID = paramvals[0] 150 175 zaccept_unit_split = paramnames[7].split("[") 151 176 zaccept_unit = zaccept_unit_split[1].replace("]","") 152 if zaccept_unit.strip() == '\AA^-1' or zaccept_unit.strip() == '\A^-1':177 if zaccept_unit.strip() == '\AA^-1': 153 178 zaccept_unit = "1/A" 154 179 output.sample.zacceptance=(float(paramvals[7]),zaccept_unit) -
src/sas/sascalc/fit/AbstractFitEngine.py
r7988501 r345e7e4 131 131 a way to get residuals from data. 132 132 """ 133 def __init__(self, x, y, dx=None, dy=None, smearer=None, data=None , lam=None, dlam=None):133 def __init__(self, x, y, dx=None, dy=None, smearer=None, data=None): 134 134 """ 135 135 :param smearer: is an object of class QSmearer or SlitSmearer … … 152 152 153 153 """ 154 Data1D.__init__(self, x=x, y=y, dx=dx, dy=dy , lam=lam,dlam=dlam)154 Data1D.__init__(self, x=x, y=y, dx=dx, dy=dy) 155 155 self.num_points = len(x) 156 156 self.sas_data = data -
src/sas/sascalc/fit/BumpsFitting.py
rf668101 r345e7e4 27 27 from bumps import parameter 28 28 from bumps.fitproblem import FitProblem 29 29 30 30 31 from sas.sascalc.fit.AbstractFitEngine import FitEngine
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