Changeset 55bc5a7f in sasview for src/sas/sascalc
- Timestamp:
- Dec 19, 2016 4:40:37 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:
- b61bd57
- Parents:
- e1e41de (diff), 67b0a99 (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. - Location:
- src/sas/sascalc
- Files:
-
- 6 edited
-
dataloader/readers/cansas_reader_HDF5.py (modified) (1 diff)
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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
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src/sas/sascalc/dataloader/readers/cansas_reader_HDF5.py
r5e906207 rbbd0f37 162 162 else: 163 163 self.current_dataset.x = data_set.flatten() 164 continue 165 elif key == u'Qdev': 166 self.current_dataset.dx = data_set.flatten() 164 167 continue 165 168 elif key == u'Qy': -
src/sas/sascalc/data_util/qsmearing.py
rf8aa738 rc6728e1 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 sesans 16 import numpy as np # type: ignore 17 from numpy import pi, exp # type: ignore 15 18 16 19 from sasmodels.resolution import Slit1D, Pinhole1D 20 from sasmodels.sesans import SESANS1D 17 21 from sasmodels.resolution2d import Pinhole2D 22 from src.sas.sascalc.data_util.nxsunit import Converter 23 18 24 19 25 def smear_selection(data, model = None): … … 36 42 # Sanity check. If we are not dealing with a SAS Data1D 37 43 # object, just return None 44 45 # This checks for 2D data (does not throw exception because fail is common) 38 46 if data.__class__.__name__ not in ['Data1D', 'Theory1D']: 39 47 if data == None: … … 42 50 return None 43 51 return Pinhole2D(data) 44 52 # This checks for 1D data with smearing info in the data itself (again, fail is likely; no exceptions) 45 53 if not hasattr(data, "dx") and not hasattr(data, "dxl")\ 46 54 and not hasattr(data, "dxw"): … … 48 56 49 57 # Look for resolution smearing data 58 # This is the code that checks for SESANS data; it looks for the file loader 59 # TODO: change other sanity checks to check for file loader instead of data structure? 60 _found_sesans = False 61 #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 = True 66 #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.zacceptance 72 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 function 78 return PySmear(SESANS1D(data, hankel._H0, hankel._H, hankel.q), model) 79 50 80 _found_resolution = False 51 81 if data.dx is not None and len(data.dx) == len(data.x): … … 92 122 self.model = model 93 123 self.resolution = resolution 94 self.offset = numpy.searchsorted(self.resolution.q_calc, self.resolution.q[0]) 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]) 95 134 96 135 def apply(self, iq_in, first_bin=0, last_bin=None): … … 126 165 q[first:last+1]. 127 166 """ 167 128 168 q = self.resolution.q 129 169 first = numpy.searchsorted(q, q_min) -
src/sas/sascalc/dataloader/data_info.py
r1b1a1c1 r1fac6c0 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 mutually36 # exclusive with the presence of Qdev (dx)37 x = None38 y = None39 lam = None40 dx = None41 dy = None42 dlam = None43 ## Slit smearing length44 dxl = None45 ## Slit smearing width46 dxw = None47 48 # Units49 _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 unit69 """70 self._xaxis = label71 self._xunit = unit72 73 def yaxis(self, label, unit):74 """75 set the y axis label and unit76 """77 self._yaxis = label78 self._yunit = unit79 80 81 27 class plottable_1D(object): 82 28 """ … … 94 40 dxw = None 95 41 42 ## SESANS specific params (wavelengths for spin echo length calculation) 43 44 lam = None 45 dlam = None 46 96 47 # Units 97 48 _xaxis = '' … … 100 51 _yunit = '' 101 52 102 def __init__(self, x, y, dx=None, dy=None, dxl=None, dxw=None ):53 def __init__(self, x, y, dx=None, dy=None, dxl=None, dxw=None, lam=None, dlam=None): 103 54 self.x = numpy.asarray(x) 104 55 self.y = numpy.asarray(y) … … 111 62 if dxw is not None: 112 63 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) 113 68 114 69 def xaxis(self, label, unit): … … 736 691 return self._perform_union(other) 737 692 738 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): 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 746 708 DataInfo.__init__(self) 747 plottable_sesans1D.__init__(self, x, y, lam, dx, dy, dlam) 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??') 748 718 749 719 def __str__(self): … … 759 729 return _str 760 730 761 def clone_without_data(self, length=0, clone=None):762 """763 Clone the current object, without copying the data (which764 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 initialized768 :param clone: if provided, the data will be copied to clone769 """770 from copy import deepcopy771 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.title779 clone.run = self.run780 clone.filename = self.filename781 clone.instrument = self.instrument782 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 clone793 794 class Data1D(plottable_1D, DataInfo):795 """796 1D data class797 """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 printout808 """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 _str816 817 731 def is_slit_smeared(self): 818 732 """ … … 843 757 y = numpy.zeros(length) 844 758 dy = numpy.zeros(length) 845 clone = Data1D(x, y, dx=dx, dy=dy) 759 lam = numpy.zeros(length) 760 dlam = numpy.zeros(length) 761 clone = Data1D(x, y, lam=lam, dx=dx, dy=dy, dlam=dlam ) 846 762 847 763 clone.title = self.title -
src/sas/sascalc/dataloader/readers/sesans_reader.py
r1c0e3b0 ra01af35 8 8 import numpy 9 9 import os 10 from sas.sascalc.dataloader.data_info import SESANSData1D10 from sas.sascalc.dataloader.data_info import Data1D 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 buff62 61 lines = buff.splitlines() 63 # print lines64 #Jae could not find python universal line spliter:65 #keep the below for now66 # some ascii data has \r line separator,67 # try it when the data is on only one long line68 # if len(lines) < 2 :69 # lines = buff.split('\r')70 71 62 x = numpy.zeros(0) 72 63 y = numpy.zeros(0) … … 83 74 tdlam = numpy.zeros(0) 84 75 tdx = numpy.zeros(0) 85 # print "all good" 86 output = SESANSData1D(x=x, y=y, lam=lam, dy=dy, dx=dx, dlam=dlam) 87 # print output 76 output = Data1D(x=x, y=y, lam=lam, dy=dy, dx=dx, dlam=dlam, isSesans=True ) 88 77 self.filename = output.filename = basename 89 78 90 # #Initialize counters for data lines and header lines.91 # is_data = False # Has more than 5 lines92 # # More than "5" lines of data is considered as actual93 # # data unless that is the only data94 # mum_data_lines = 595 # # To count # of current data candidate lines96 # i = -197 # # To count total # of previous data candidate lines98 # i1 = -199 # # To count # of header lines100 # j = -1101 # # Helps to count # of header lines102 # j1 = -1103 # #minimum required number of columns of data; ( <= 4).104 # lentoks = 2105 79 paramnames=[] 106 80 paramvals=[] … … 111 85 Pvals=[] 112 86 dPvals=[] 113 # print x114 # print zvals115 87 for line in lines: 116 88 # Initial try for CSV (split on ,) … … 122 94 if len(toks)>5: 123 95 zvals.append(toks[0]) 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])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]) 129 101 else: 130 102 continue … … 140 112 default_z_unit = "A" 141 113 data_conv_P = None 142 default_p_unit = " " 114 default_p_unit = " " # Adjust unit for axis (L^-3) 143 115 lam_unit = lam_header[1].replace("[","").replace("]","") 116 if lam_unit == 'AA': 117 lam_unit = 'A' 144 118 varheader=[zvals[0],dzvals[0],lamvals[0],dlamvals[0],Pvals[0],dPvals[0]] 145 119 valrange=range(1, len(zvals)) … … 161 135 output.x, output.x_unit = self._unit_conversion(x, lam_unit, default_z_unit) 162 136 output.y = y 137 output.y_unit = '\AA^{-2} cm^{-1}' # output y_unit erbij 163 138 output.dx, output.dx_unit = self._unit_conversion(dx, lam_unit, default_z_unit) 164 139 output.dy = dy … … 166 141 output.dlam, output.dlam_unit = self._unit_conversion(dlam, lam_unit, default_z_unit) 167 142 168 output.xaxis("\ rm{z}", output.x_unit)169 output.yaxis("\\rm{ P/P0}", output.y_unit)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 refs 170 145 # Store loading process information 171 146 output.meta_data['loader'] = self.type_name 172 output.sample.thickness = float(paramvals[6])147 #output.sample.thickness = float(paramvals[6]) 173 148 output.sample.name = paramvals[1] 174 149 output.sample.ID = paramvals[0] 175 150 zaccept_unit_split = paramnames[7].split("[") 176 151 zaccept_unit = zaccept_unit_split[1].replace("]","") 177 if zaccept_unit.strip() == '\AA^-1' :152 if zaccept_unit.strip() == '\AA^-1' or zaccept_unit.strip() == '\A^-1': 178 153 zaccept_unit = "1/A" 179 154 output.sample.zacceptance=(float(paramvals[7]),zaccept_unit) -
src/sas/sascalc/fit/AbstractFitEngine.py
rfc18690 r7988501 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 ):133 def __init__(self, x, y, dx=None, dy=None, smearer=None, data=None, lam=None, dlam=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 )154 Data1D.__init__(self, x=x, y=y, dx=dx, dy=dy, lam=lam,dlam=dlam) 155 155 self.num_points = len(x) 156 156 self.sas_data = data -
src/sas/sascalc/fit/BumpsFitting.py
r1a5d5f2 rf668101 27 27 from bumps import parameter 28 28 from bumps.fitproblem import FitProblem 29 30 29 31 30 from sas.sascalc.fit.AbstractFitEngine import FitEngine
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