- Timestamp:
- Jan 17, 2017 12:18:58 PM (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:
- aad41bb
- Parents:
- ef0e644
- Location:
- src/sas
- Files:
-
- 8 edited
-
sascalc/data_util/qsmearing.py (modified) (5 diffs)
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sascalc/dataloader/data_info.py (modified) (6 diffs)
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sascalc/dataloader/readers/sesans_reader.py (modified) (7 diffs)
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sascalc/fit/AbstractFitEngine.py (modified) (2 diffs)
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sasgui/guiframe/dataFitting.py (modified) (7 diffs)
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sasgui/guiframe/data_manager.py (modified) (1 diff)
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sasgui/perspectives/fitting/basepage.py (modified) (1 diff)
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sasgui/plottools/plottables.py (modified) (2 diffs)
Legend:
- Unmodified
- Added
- Removed
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src/sas/sascalc/data_util/qsmearing.py
rd3911e3 ra9f579c 13 13 import logging 14 14 import sys 15 15 from sasmodels import sesans 16 import numpy as np # type: ignore 17 from numpy import pi, exp # type:ignore 16 18 from sasmodels.resolution import Slit1D, Pinhole1D 19 from sasmodels.sesans import SESANS1D 17 20 from sasmodels.resolution2d import Pinhole2D 21 from src.sas.sascalc.data_util.nxsunit import Converter 18 22 19 23 def smear_selection(data, model = None): … … 36 40 # Sanity check. If we are not dealing with a SAS Data1D 37 41 # object, just return None 42 # This checks for 2D data (does not throw exception because fail is common) 38 43 if data.__class__.__name__ not in ['Data1D', 'Theory1D']: 39 44 if data == None: … … 41 46 elif data.dqx_data == None or data.dqy_data == None: 42 47 return None 43 return P ySmear2D(data, model)44 48 return Pinhole2D(data) 49 # This checks for 1D data with smearing info in the data itself (again, fail is likely; no exceptions) 45 50 if not hasattr(data, "dx") and not hasattr(data, "dxl")\ 46 51 and not hasattr(data, "dxw"): … … 48 53 49 54 # Look for resolution smearing data 55 # This is the code that checks for SESANS data; it looks for the file loader 56 # TODO: change other sanity checks to check for file loader instead of data structure? 57 _found_sesans = False 58 #if data.dx is not None and data.meta_data['loader']=='SESANS': 59 if data.dx is not None and data.isSesans: 60 #if data.dx[0] > 0.0: 61 if numpy.size(data.dx[data.dx <= 0]) == 0: 62 _found_sesans = True 63 # if data.dx[0] <= 0.0: 64 if numpy.size(data.dx[data.dx <= 0]) > 0: 65 raise ValueError('one or more of your dx values are negative, please check the data file!') 66 67 if _found_sesans == True: 68 #Pre-compute the Hankel matrix (H) 69 qmax, qunits = data.sample.zacceptance 70 hankel = sesans.SesansTransform() 71 sesans.SesansTransform.set_transform(hankel, 72 SE = Converter(data._xunit)(data.x, "A"), 73 zaccept = Converter(qunits)(qmax, "1/A"), 74 Rmax = 10000000) 75 # Then return the actual transform, as if it were a smearing function 76 return PySmear(SESANS1D(data, hankel._H0, hankel._H, hankel.q), model) 77 50 78 _found_resolution = False 51 79 if data.dx is not None and len(data.dx) == len(data.x): … … 92 120 self.model = model 93 121 self.resolution = resolution 94 self.offset = numpy.searchsorted(self.resolution.q_calc, self.resolution.q[0]) 122 123 if hasattr(self.resolution, 'data'): 124 if self.resolution.data.meta_data['loader'] == 'SESANS': # Always True if file extension is '.ses'! 125 self.offset = 0 126 # This is default behaviour, for future resolution/transform functions this needs to be revisited. 127 else: 128 self.offset = numpy.searchsorted(self.resolution.q_calc, self.resolution.q[0]) 129 else: 130 self.offset = numpy.searchsorted(self.resolution.q_calc, self.resolution.q[0]) 131 132 # self.offset = numpy.searchsorted(self.resolution.q_calc, self.resolution.q[0]) 95 133 96 134 def apply(self, iq_in, first_bin=0, last_bin=None): -
src/sas/sascalc/dataloader/data_info.py
r345e7e4 ra9f579c 93 93 ## Slit smearing width 94 94 dxw = None 95 ## SESANS specific params (wavelengths for spin echo length calculation) 96 lam = None 97 dlam = None 95 98 96 99 # Units … … 100 103 _yunit = '' 101 104 102 def __init__(self, x, y, dx=None, dy=None, dxl=None, dxw=None ):105 def __init__(self, x, y, dx=None, dy=None, dxl=None, dxw=None, lam=None, dlam=None): 103 106 self.x = numpy.asarray(x) 104 107 self.y = numpy.asarray(y) … … 111 114 if dxw is not None: 112 115 self.dxw = numpy.asarray(dxw) 116 if lam is not None: 117 self.lam = numpy.asarray(lam) 118 if dlam is not None: 119 self.dlam = numpy.asarray(dlam) 113 120 114 121 def xaxis(self, label, unit): … … 736 743 return self._perform_union(other) 737 744 738 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): 745 class Data1D(plottable_1D, DataInfo): 746 """ 747 1D data class 748 """ 749 def __init__(self, x=None, y=None, dx=None, dy=None, lam=None, dlam=None, isSesans=False): 750 self.isSesans = isSesans 746 751 DataInfo.__init__(self) 747 plottable_sesans1D.__init__(self, x, y, lam, dx, dy, dlam) 752 plottable_1D.__init__(self, x, y, dx, dy,None, None, lam, dlam) 753 if self.isSesans: 754 x_unit = 'A' 755 y_unit = 'pol' 756 elif not self.isSesans: # it's SANS data! (Could also be simple else statement, but i prefer exhaustive conditionals...-JHB) 757 x_unit = '1/A' 758 y_unit = '1/cm' 759 else: # and if it's neither, you get punished! 760 raise(TypeError,'This is neither SANS nor SESANS data, what the hell are you doing??') 748 761 749 762 def __str__(self): … … 759 772 return _str 760 773 761 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 817 774 def is_slit_smeared(self): 818 775 """ … … 843 800 y = numpy.zeros(length) 844 801 dy = numpy.zeros(length) 845 clone = Data1D(x, y, dx=dx, dy=dy) 802 lam = numpy.zeros(length) 803 dlam = numpy.zeros(length) 804 clone = Data1D(x, y, lam=lam, dx=dx, dy=dy, dlam=dlam) 846 805 847 806 clone.title = self.title -
src/sas/sascalc/dataloader/readers/sesans_reader.py
r345e7e4 ra9f579c 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 x 114 # print zvals 87 115 88 for line in lines: 116 89 # Initial try for CSV (split on ,) … … 122 95 if len(toks)>5: 123 96 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])97 dzvals.append(toks[3]) 98 lamvals.append(toks[4]) 99 dlamvals.append(toks[5]) 100 Pvals.append(toks[1]) 101 dPvals.append(toks[2]) 129 102 else: 130 103 continue … … 140 113 default_z_unit = "A" 141 114 data_conv_P = None 142 default_p_unit = " " 115 default_p_unit = " " # Adjust unit for axis (L^-3) 143 116 lam_unit = lam_header[1].replace("[","").replace("]","") 117 if lam_unit == 'AA': 118 lam_unit = 'A' 144 119 varheader=[zvals[0],dzvals[0],lamvals[0],dlamvals[0],Pvals[0],dPvals[0]] 145 120 valrange=range(1, len(zvals)) … … 161 136 output.x, output.x_unit = self._unit_conversion(x, lam_unit, default_z_unit) 162 137 output.y = y 138 output.y_unit = '\AA^{-2} cm^{-1}' # output y_unit added 163 139 output.dx, output.dx_unit = self._unit_conversion(dx, lam_unit, default_z_unit) 164 140 output.dy = dy … … 166 142 output.dlam, output.dlam_unit = self._unit_conversion(dlam, lam_unit, default_z_unit) 167 143 168 output.xaxis("\ rm{z}", output.x_unit)169 output.yaxis("\\rm{ P/P0}", output.y_unit)144 output.xaxis("\\rm{z}", output.x_unit) 145 output.yaxis("\\rm{ln(P)/(t \lambda^2)}", output.y_unit) # Adjust label to ln P/(lam^2 t), remove lam column refs 170 146 # Store loading process information 171 147 output.meta_data['loader'] = self.type_name 172 output.sample.thickness = float(paramvals[6])148 #output.sample.thickness = float(paramvals[6]) 173 149 output.sample.name = paramvals[1] 174 150 output.sample.ID = paramvals[0] 175 151 zaccept_unit_split = paramnames[7].split("[") 176 152 zaccept_unit = zaccept_unit_split[1].replace("]","") 177 if zaccept_unit.strip() == '\AA^-1' :153 if zaccept_unit.strip() == '\AA^-1' or zaccept_unit.strip() == '\A^-1': 178 154 zaccept_unit = "1/A" 179 155 output.sample.zacceptance=(float(paramvals[7]),zaccept_unit) 180 output.vars =varheader156 output.vars = varheader 181 157 182 158 if len(output.x) < 1: -
src/sas/sascalc/fit/AbstractFitEngine.py
rd3911e3 ra9f579c 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/sasgui/guiframe/dataFitting.py
r345e7e4 ra9f579c 17 17 """ 18 18 """ 19 def __init__(self, x=None, y=None, dx=None, dy=None): 19 20 def __init__(self, x=None, y=None, dx=None, dy=None, lam=None, dlam=None, isSesans=False): 20 21 """ 21 22 """ … … 24 25 if y is None: 25 26 y = [] 26 PlotData1D.__init__(self, x, y, dx, dy) 27 LoadData1D.__init__(self, x, y, dx, dy) 27 self.isSesans = isSesans 28 PlotData1D.__init__(self, x, y, dx, dy, lam, dlam) 29 LoadData1D.__init__(self, x, y, dx, dy, lam, dlam, isSesans) 30 28 31 self.id = None 29 32 self.list_group_id = [] … … 68 71 # First, check the data compatibility 69 72 dy, dy_other = self._validity_check(other) 70 result = Data1D(x=[], y=[], dx=None, dy=None)73 result = Data1D(x=[], y=[], lam=[], dx=None, dy=None, dlam=None) 71 74 result.clone_without_data(length=len(self.x), clone=self) 72 75 result.copy_from_datainfo(data1d=self) … … 115 118 # First, check the data compatibility 116 119 self._validity_check_union(other) 117 result = Data1D(x=[], y=[], dx=None, dy=None)120 result = Data1D(x=[], y=[], lam=[], dx=None, dy=None, dlam=None) 118 121 tot_length = len(self.x) + len(other.x) 119 122 result = self.clone_without_data(length=tot_length, clone=result) 123 if self.dlam == None or other.dlam is None: 124 result.dlam = None 125 else: 126 result.dlam = numpy.zeros(tot_length) 120 127 if self.dy == None or other.dy is None: 121 128 result.dy = None … … 141 148 result.y = numpy.append(self.y, other.y) 142 149 result.y = result.y[ind] 150 result.lam = numpy.append(self.lam, other.lam) 151 result.lam = result.lam[ind] 152 if result.dlam != None: 153 result.dlam = numpy.append(self.dlam, other.dlam) ^ M 154 result.dlam = result.dlam[ind] 143 155 if result.dy != None: 144 156 result.dy = numpy.append(self.dy, other.dy) … … 260 272 # First, check the data compatibility 261 273 self._validity_check_union(other) 262 result = Data1D(x=[], y=[], dx=None, dy=None)274 result = Data1D(x=[], y=[], lam=[], dx=None, dy=None, dlam=[]) 263 275 tot_length = len(self.x)+len(other.x) 264 276 result.clone_without_data(length=tot_length, clone=self) 277 if self.dlam == None or other.dlam is None: 278 result.dlam = None 279 else: 280 result.dlam = numpy.zeros(tot_length) 265 281 if self.dy == None or other.dy is None: 266 282 result.dy = None … … 285 301 result.y = numpy.append(self.y, other.y) 286 302 result.y = result.y[ind] 303 result.lam = numpy.append(self.lam, other.lam) 304 result.lam = result.lam[ind] 287 305 if result.dy != None: 288 306 result.dy = numpy.append(self.dy, other.dy) -
src/sas/sasgui/guiframe/data_manager.py
r345e7e4 ra9f579c 62 62 if issubclass(Data2D, data.__class__): 63 63 new_plot = Data2D(image=None, err_image=None) 64 else: 65 new_plot = Data1D(x=[], y=[], dx=None, dy=None) 66 64 elif data.meta_data['loader'] == 'SESANS': 65 new_plot = Data1D(x=[], y=[], dx=None, dy=None, lam=None, dlam=None, isSesans=True) 66 else: 67 new_plot = Data1D(x=[], y=[], dx=None, dy=None, lam=None, dlam=None) #SESANS check??? 68 67 69 new_plot.copy_from_datainfo(data) 68 70 data.clone_without_data(clone=new_plot) -
src/sas/sasgui/perspectives/fitting/basepage.py
r505706a ra9f579c 142 142 self.theory_qmin_x = None 143 143 self.theory_qmax_x = None 144 self.cb1 = None # TODO: remove? 144 145 self.btEditMask = None 145 146 self.btFit = None -
src/sas/sasgui/plottools/plottables.py
r345e7e4 ra9f579c 1023 1023 """ 1024 1024 1025 def __init__(self, x, y, dx=None, dy=None ):1025 def __init__(self, x, y, dx=None, dy=None, lam=None, dlam=None): 1026 1026 """ 1027 1027 Draw points specified by x[i],y[i] in the current color/symbol. … … 1037 1037 self.x = x 1038 1038 self.y = y 1039 self.lam = lam 1039 1040 self.dx = dx 1040 1041 self.dy = dy 1042 self.dlam = dlam 1041 1043 self.source = None 1042 1044 self.detector = None
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