- Timestamp:
- Feb 28, 2017 1:17:19 PM (8 years ago)
- Children:
- 13043af
- Parents:
- 46f798f
- git-author:
- Jeff Krzywon <krzywon@…> (02/28/17 13:17:19)
- git-committer:
- GitHub <noreply@…> (02/28/17 13:17:19)
- Location:
- src/sas
- Files:
-
- 9 edited
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sascalc/data_util/qsmearing.py (modified) (5 diffs)
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sascalc/dataloader/data_info.py (modified) (13 diffs)
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sascalc/dataloader/readers/cansas_constants.py (modified) (1 diff)
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sascalc/dataloader/readers/cansas_reader.py (modified) (3 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) (8 diffs)
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sasgui/guiframe/data_manager.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
r2ffe241 r0d64713 13 13 import logging 14 14 import sys 15 import numpy as np # type: ignore 16 from numpy import pi, exp # type:ignore 15 17 16 from sasmodels.resolution import Slit1D, Pinhole1D 18 from sasmodels.sesans import SesansTransform19 17 from sasmodels.resolution2d import Pinhole2D 20 from src.sas.sascalc.data_util.nxsunit import Converter21 18 22 19 def smear_selection(data, model = None): … … 39 36 # Sanity check. If we are not dealing with a SAS Data1D 40 37 # object, just return None 41 # This checks for 2D data (does not throw exception because fail is common)42 38 if data.__class__.__name__ not in ['Data1D', 'Theory1D']: 43 39 if data == None: … … 45 41 elif data.dqx_data == None or data.dqy_data == None: 46 42 return None 47 return PySmear2D(data )48 # This checks for 1D data with smearing info in the data itself (again, fail is likely; no exceptions) 43 return PySmear2D(data, model) 44 49 45 if not hasattr(data, "dx") and not hasattr(data, "dxl")\ 50 46 and not hasattr(data, "dxw"): … … 52 48 53 49 # Look for resolution smearing data 54 # This is the code that checks for SESANS data; it looks for the file loader55 # TODO: change other sanity checks to check for file loader instead of data structure?56 _found_sesans = False57 #if data.dx is not None and data.meta_data['loader']=='SESANS':58 if data.dx is not None and data.isSesans:59 #if data.dx[0] > 0.0:60 if numpy.size(data.dx[data.dx <= 0]) == 0:61 _found_sesans = True62 # if data.dx[0] <= 0.0:63 if numpy.size(data.dx[data.dx <= 0]) > 0:64 raise ValueError('one or more of your dx values are negative, please check the data file!')65 66 if _found_sesans == True:67 #Pre-compute the Hankel matrix (H)68 qmax, qunits = data.sample.zacceptance69 SElength = Converter(data._xunit)(data.x, "A")70 zaccept = Converter(qunits)(qmax, "1/A"),71 Rmax = 1000000072 hankel = SesansTransform(data.x, SElength, zaccept, Rmax)73 # Then return the actual transform, as if it were a smearing function74 return PySmear(hankel, model, offset=0)75 76 50 _found_resolution = False 77 51 if data.dx is not None and len(data.dx) == len(data.x): … … 115 89 Wrapper for pure python sasmodels resolution functions. 116 90 """ 117 def __init__(self, resolution, model , offset=None):91 def __init__(self, resolution, model): 118 92 self.model = model 119 93 self.resolution = resolution 120 if offset is None: 121 offset = numpy.searchsorted(self.resolution.q_calc, self.resolution.q[0]) 122 self.offset = offset 94 self.offset = numpy.searchsorted(self.resolution.q_calc, self.resolution.q[0]) 123 95 124 96 def apply(self, iq_in, first_bin=0, last_bin=None): -
src/sas/sascalc/dataloader/data_info.py
r2ffe241 r0d64713 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 27 80 28 81 class plottable_1D(object): … … 40 93 ## Slit smearing width 41 94 dxw = None 42 ## SESANS specific params (wavelengths for spin echo length calculation)43 lam = None44 dlam = None45 95 46 96 # Units … … 50 100 _yunit = '' 51 101 52 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): 53 103 self.x = numpy.asarray(x) 54 104 self.y = numpy.asarray(y) … … 61 111 if dxw is not None: 62 112 self.dxw = numpy.asarray(dxw) 63 if lam is not None:64 self.lam = numpy.asarray(lam)65 if dlam is not None:66 self.dlam = numpy.asarray(dlam)67 113 68 114 def xaxis(self, label, unit): … … 352 398 ## Details 353 399 details = None 354 ## SESANS zacceptance355 zacceptance = None356 400 357 401 def __init__(self): … … 491 535 ## Loading errors 492 536 errors = None 493 ## SESANS data check494 isSesans = None495 496 537 497 538 def __init__(self): … … 526 567 ## Loading errors 527 568 self.errors = [] 528 ## SESANS data check529 self.isSesans = False530 569 531 570 def append_empty_process(self): … … 547 586 _str += "Title: %s\n" % self.title 548 587 _str += "Run: %s\n" % str(self.run) 549 _str += "SESANS: %s\n" % str(self.isSesans)550 588 _str += "Instrument: %s\n" % str(self.instrument) 551 589 _str += "%s\n" % str(self.sample) … … 698 736 return self._perform_union(other) 699 737 700 class Data1D(plottable_1D, DataInfo): 701 """ 702 1D data class 703 """ 704 def __init__(self, x=None, y=None, dx=None, dy=None, lam=None, dlam=None, isSesans=None): 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): 705 746 DataInfo.__init__(self) 706 plottable_1D.__init__(self, x, y, dx, dy,None, None, lam, dlam) 707 self.isSesans = isSesans 708 try: 709 if self.isSesans: # the data is SESANS 710 self.x_unit = 'A' 711 self.y_unit = 'pol' 712 elif not self.isSesans: # the data is SANS 713 self.x_unit = '1/A' 714 self.y_unit = '1/cm' 715 except: # the data is not recognized/supported, and the user is notified 716 raise(TypeError, 'data not recognized, check documentation for supported 1D data formats') 747 plottable_sesans1D.__init__(self, x, y, lam, dx, dy, dlam) 717 748 718 749 def __str__(self): … … 728 759 return _str 729 760 761 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 816 730 817 def is_slit_smeared(self): 731 818 """ … … 756 843 y = numpy.zeros(length) 757 844 dy = numpy.zeros(length) 758 lam = numpy.zeros(length) 759 dlam = numpy.zeros(length) 760 clone = Data1D(x, y, lam=lam, dx=dx, dy=dy, dlam=dlam) 845 clone = Data1D(x, y, dx=dx, dy=dy) 761 846 762 847 clone.title = self.title … … 933 1018 ## Vector of Q-values at the center of each bin in y 934 1019 y_bins = None 935 ## No 2D SESANS data as of yet. Always set it to False936 isSesans = False937 1020 938 1021 def __init__(self, data=None, err_data=None, qx_data=None, 939 1022 qy_data=None, q_data=None, mask=None, 940 1023 dqx_data=None, dqy_data=None): 1024 self.y_bins = [] 1025 self.x_bins = [] 941 1026 DataInfo.__init__(self) 942 1027 plottable_2D.__init__(self, data, err_data, qx_data, 943 1028 qy_data, q_data, mask, dqx_data, dqy_data) 944 self.y_bins = []945 self.x_bins = []946 947 1029 if len(self.detector) > 0: 948 1030 raise RuntimeError, "Data2D: Detector bank already filled at init" … … 1183 1265 final_dataset.xmin = data.xmin 1184 1266 final_dataset.ymin = data.ymin 1185 final_dataset.isSesans = datainfo.isSesans1186 1267 final_dataset.title = datainfo.title 1187 1268 final_dataset.run = datainfo.run -
src/sas/sascalc/dataloader/readers/cansas_constants.py
rad4632c r0d64713 133 133 "variable" : None, 134 134 "children" : {"Idata" : SASDATA_IDATA, 135 "Sesans": {"storeas": "content"},136 "zacceptance": {"storeas": "float"},137 135 "<any>" : ANY 138 136 } -
src/sas/sascalc/dataloader/readers/cansas_reader.py
rc221349 r0d64713 261 261 # I and Q - 1D data 262 262 elif tagname == 'I' and isinstance(self.current_dataset, plottable_1D): 263 unit_list = unit.split("|") 264 if len(unit_list) > 1: 265 self.current_dataset.yaxis(unit_list[0].strip(), 266 unit_list[1].strip()) 267 else: 268 self.current_dataset.yaxis("Intensity", unit) 263 self.current_dataset.yaxis("Intensity", unit) 269 264 self.current_dataset.y = np.append(self.current_dataset.y, data_point) 270 265 elif tagname == 'Idev' and isinstance(self.current_dataset, plottable_1D): 271 266 self.current_dataset.dy = np.append(self.current_dataset.dy, data_point) 272 267 elif tagname == 'Q': 273 unit_list = unit.split("|") 274 if len(unit_list) > 1: 275 self.current_dataset.xaxis(unit_list[0].strip(), 276 unit_list[1].strip()) 277 else: 278 self.current_dataset.xaxis("Q", unit) 268 self.current_dataset.xaxis("Q", unit) 279 269 self.current_dataset.x = np.append(self.current_dataset.x, data_point) 280 270 elif tagname == 'Qdev': … … 288 278 elif tagname == 'Shadowfactor': 289 279 pass 290 elif tagname == 'Sesans':291 self.current_datainfo.isSesans = bool(data_point)292 elif tagname == 'zacceptance':293 self.current_datainfo.sample.zacceptance = (data_point, unit)294 280 295 281 # I and Qx, Qy - 2D data … … 1034 1020 node.append(point) 1035 1021 self.write_node(point, "Q", datainfo.x[i], 1036 {'unit': datainfo. _xaxis + " | " + datainfo._xunit})1022 {'unit': datainfo.x_unit}) 1037 1023 if len(datainfo.y) >= i: 1038 1024 self.write_node(point, "I", datainfo.y[i], 1039 {'unit': datainfo. _yaxis + " | " + datainfo._yunit})1025 {'unit': datainfo.y_unit}) 1040 1026 if datainfo.dy is not None and len(datainfo.dy) > i: 1041 1027 self.write_node(point, "Idev", datainfo.dy[i], 1042 {'unit': datainfo. _yaxis + " | " + datainfo._yunit})1028 {'unit': datainfo.y_unit}) 1043 1029 if datainfo.dx is not None and len(datainfo.dx) > i: 1044 1030 self.write_node(point, "Qdev", datainfo.dx[i], 1045 {'unit': datainfo. _xaxis + " | " + datainfo._xunit})1031 {'unit': datainfo.x_unit}) 1046 1032 if datainfo.dxw is not None and len(datainfo.dxw) > i: 1047 1033 self.write_node(point, "dQw", datainfo.dxw[i], 1048 {'unit': datainfo. _xaxis + " | " + datainfo._xunit})1034 {'unit': datainfo.x_unit}) 1049 1035 if datainfo.dxl is not None and len(datainfo.dxl) > i: 1050 1036 self.write_node(point, "dQl", datainfo.dxl[i], 1051 {'unit': datainfo._xaxis + " | " + datainfo._xunit}) 1052 if datainfo.isSesans: 1053 sesans = self.create_element("Sesans") 1054 sesans.text = str(datainfo.isSesans) 1055 node.append(sesans) 1056 self.write_node(node, "zacceptance", datainfo.sample.zacceptance[0], 1057 {'unit': datainfo.sample.zacceptance[1]}) 1058 1037 {'unit': datainfo.x_unit}) 1059 1038 1060 1039 def _write_data_2d(self, datainfo, entry_node): -
src/sas/sascalc/dataloader/readers/sesans_reader.py
r7caf3e5 r0d64713 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=[] 87 113 # print x 114 # print zvals 88 115 for line in lines: 89 116 # Initial try for CSV (split on ,) … … 95 122 if len(toks)>5: 96 123 zvals.append(toks[0]) 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])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]) 102 129 else: 103 130 continue … … 113 140 default_z_unit = "A" 114 141 data_conv_P = None 115 default_p_unit = " " # Adjust unit for axis (L^-3)142 default_p_unit = " " 116 143 lam_unit = lam_header[1].replace("[","").replace("]","") 117 if lam_unit == 'AA':118 lam_unit = 'A'119 144 varheader=[zvals[0],dzvals[0],lamvals[0],dlamvals[0],Pvals[0],dPvals[0]] 120 145 valrange=range(1, len(zvals)) … … 136 161 output.x, output.x_unit = self._unit_conversion(x, lam_unit, default_z_unit) 137 162 output.y = y 138 output.y_unit = r'\AA^{-2} cm^{-1}' # output y_unit added139 163 output.dx, output.dx_unit = self._unit_conversion(dx, lam_unit, default_z_unit) 140 164 output.dy = dy 141 165 output.lam, output.lam_unit = self._unit_conversion(lam, lam_unit, default_z_unit) 142 166 output.dlam, output.dlam_unit = self._unit_conversion(dlam, lam_unit, default_z_unit) 143 167 144 168 output.xaxis(r"\rm{z}", output.x_unit) 145 output.yaxis(r"\rm{ln(P)/(t \lambda^2)}", output.y_unit) # Adjust label to ln P/(lam^2 t), remove lam column refs 146 169 output.yaxis(r"\rm{P/P0}", output.y_unit) 147 170 # Store loading process information 148 171 output.meta_data['loader'] = self.type_name 149 #output.sample.thickness = float(paramvals[6])172 output.sample.thickness = float(paramvals[6]) 150 173 output.sample.name = paramvals[1] 151 174 output.sample.ID = paramvals[0] 152 175 zaccept_unit_split = paramnames[7].split("[") 153 176 zaccept_unit = zaccept_unit_split[1].replace("]","") 154 if zaccept_unit.strip() == r'\AA^-1' or zaccept_unit.strip() == r'\A^-1':177 if zaccept_unit.strip() == r'\AA^-1': 155 178 zaccept_unit = "1/A" 156 179 output.sample.zacceptance=(float(paramvals[7]),zaccept_unit) 157 output.vars =varheader180 output.vars=varheader 158 181 159 182 if len(output.x) < 1: -
src/sas/sascalc/fit/AbstractFitEngine.py
ra9f579c r0d64713 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/sasgui/guiframe/dataFitting.py
r68adf86 r0d64713 17 17 """ 18 18 """ 19 20 def __init__(self, x=None, y=None, dx=None, dy=None, lam=None, dlam=None, isSesans=False): 19 def __init__(self, x=None, y=None, dx=None, dy=None): 21 20 """ 22 21 """ … … 25 24 if y is None: 26 25 y = [] 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 26 PlotData1D.__init__(self, x, y, dx, dy) 27 LoadData1D.__init__(self, x, y, dx, dy) 31 28 self.id = None 32 29 self.list_group_id = [] … … 35 32 self.path = None 36 33 self.xtransform = None 37 if self.isSesans:38 self.xtransform = "x"39 34 self.ytransform = None 40 if self.isSesans:41 self.ytransform = "y"42 35 self.title = "" 43 36 self.scale = None … … 75 68 # First, check the data compatibility 76 69 dy, dy_other = self._validity_check(other) 77 result = Data1D(x=[], y=[], lam=[], dx=None, dy=None, dlam=None)70 result = Data1D(x=[], y=[], dx=None, dy=None) 78 71 result.clone_without_data(length=len(self.x), clone=self) 79 72 result.copy_from_datainfo(data1d=self) … … 122 115 # First, check the data compatibility 123 116 self._validity_check_union(other) 124 result = Data1D(x=[], y=[], lam=[], dx=None, dy=None, dlam=None)117 result = Data1D(x=[], y=[], dx=None, dy=None) 125 118 tot_length = len(self.x) + len(other.x) 126 119 result = self.clone_without_data(length=tot_length, clone=result) 127 if self.dlam == None or other.dlam is None:128 result.dlam = None129 else:130 result.dlam = numpy.zeros(tot_length)131 120 if self.dy == None or other.dy is None: 132 121 result.dy = None … … 152 141 result.y = numpy.append(self.y, other.y) 153 142 result.y = result.y[ind] 154 result.lam = numpy.append(self.lam, other.lam)155 result.lam = result.lam[ind]156 if result.dlam != None:157 result.dlam = numpy.append(self.dlam, other.dlam)158 result.dlam = result.dlam[ind]159 143 if result.dy != None: 160 144 result.dy = numpy.append(self.dy, other.dy) … … 276 260 # First, check the data compatibility 277 261 self._validity_check_union(other) 278 result = Data1D(x=[], y=[], lam=[], dx=None, dy=None, dlam=[])262 result = Data1D(x=[], y=[], dx=None, dy=None) 279 263 tot_length = len(self.x)+len(other.x) 280 264 result.clone_without_data(length=tot_length, clone=self) 281 if self.dlam == None or other.dlam is None:282 result.dlam = None283 else:284 result.dlam = numpy.zeros(tot_length)285 265 if self.dy == None or other.dy is None: 286 266 result.dy = None … … 305 285 result.y = numpy.append(self.y, other.y) 306 286 result.y = result.y[ind] 307 result.lam = numpy.append(self.lam, other.lam)308 result.lam = result.lam[ind]309 287 if result.dy != None: 310 288 result.dy = numpy.append(self.dy, other.dy) -
src/sas/sasgui/guiframe/data_manager.py
r2ffe241 r0d64713 61 61 62 62 if issubclass(Data2D, data.__class__): 63 new_plot = Data2D(image=None, err_image=None) # For now, isSesans for 2D data is always false 64 else: 65 new_plot = Data1D(x=[], y=[], dx=None, dy=None, lam=None, dlam=None, isSesans=data.isSesans) 66 67 68 #elif data.meta_data['loader'] == 'SESANS': 69 # new_plot = Data1D(x=[], y=[], dx=None, dy=None, lam=None, dlam=None, isSesans=True) 70 #else: 71 # new_plot = Data1D(x=[], y=[], dx=None, dy=None, lam=None, dlam=None) #SESANS check??? 72 63 new_plot = Data2D(image=None, err_image=None) 64 else: 65 new_plot = Data1D(x=[], y=[], dx=None, dy=None) 66 73 67 new_plot.copy_from_datainfo(data) 74 68 data.clone_without_data(clone=new_plot) -
src/sas/sasgui/plottools/plottables.py
ra9f579c r0d64713 1023 1023 """ 1024 1024 1025 def __init__(self, x, y, dx=None, dy=None , lam=None, dlam=None):1025 def __init__(self, x, y, dx=None, dy=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 = lam1040 1039 self.dx = dx 1041 1040 self.dy = dy 1042 self.dlam = dlam1043 1041 self.source = None 1044 1042 self.detector = None
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