source: sasview/src/sas/sascalc/dataloader/data_info.py @ 685e0e3

ESS_GUIESS_GUI_batch_fittingESS_GUI_bumps_abstractionESS_GUI_iss1116ESS_GUI_iss879ESS_GUI_openclESS_GUI_orderingESS_GUI_sync_sascalc
Last change on this file since 685e0e3 was 749b715, checked in by Piotr Rozyczko <piotr.rozyczko@…>, 7 years ago

Ess sesans plots (#113)

  • Fix line endings
  • Keep the isSesans parameter when making copies.
  • Draw Sesans data in linear coordinates
  • Add unit test for Sesans Plotting
  • Remove lint
  • Property mode set to 100644
File size: 39.8 KB
Line 
1"""
2    Module that contains classes to hold information read from
3    reduced data files.
4
5    A good description of the data members can be found in
6    the CanSAS 1D XML data format:
7
8    http://www.smallangles.net/wgwiki/index.php/cansas1d_documentation
9"""
10#####################################################################
11#This software was developed by the University of Tennessee as part of the
12#Distributed Data Analysis of Neutron Scattering Experiments (DANSE)
13#project funded by the US National Science Foundation.
14#See the license text in license.txt
15#copyright 2008, University of Tennessee
16######################################################################
17
18from __future__ import print_function
19
20#TODO: Keep track of data manipulation in the 'process' data structure.
21#TODO: This module should be independent of plottables. We should write
22#        an adapter class for plottables when needed.
23
24#from sas.guitools.plottables import Data1D as plottable_1D
25from sas.sascalc.data_util.uncertainty import Uncertainty
26import numpy as np
27import math
28
29class plottable_1D(object):
30    """
31    Data1D is a place holder for 1D plottables.
32    """
33    # The presence of these should be mutually
34    # exclusive with the presence of Qdev (dx)
35    x = None
36    y = None
37    dx = None
38    dy = None
39    ## Slit smearing length
40    dxl = None
41    ## Slit smearing width
42    dxw = None
43    ## SESANS specific params (wavelengths for spin echo length calculation)
44    lam = None
45    dlam = None
46
47    # Units
48    _xaxis = ''
49    _xunit = ''
50    _yaxis = ''
51    _yunit = ''
52
53    def __init__(self, x, y, dx=None, dy=None, dxl=None, dxw=None, lam=None, dlam=None):
54        self.x = np.asarray(x)
55        self.y = np.asarray(y)
56        if dx is not None:
57            self.dx = np.asarray(dx)
58        if dy is not None:
59            self.dy = np.asarray(dy)
60        if dxl is not None:
61            self.dxl = np.asarray(dxl)
62        if dxw is not None:
63            self.dxw = np.asarray(dxw)
64        if lam is not None:
65            self.lam = np.asarray(lam)
66        if dlam is not None:
67            self.dlam = np.asarray(dlam)
68
69    def xaxis(self, label, unit):
70        """
71        set the x axis label and unit
72        """
73        self._xaxis = label
74        self._xunit = unit
75
76    def yaxis(self, label, unit):
77        """
78        set the y axis label and unit
79        """
80        self._yaxis = label
81        self._yunit = unit
82
83
84class plottable_2D(object):
85    """
86    Data2D is a place holder for 2D plottables.
87    """
88    xmin = None
89    xmax = None
90    ymin = None
91    ymax = None
92    data = None
93    qx_data = None
94    qy_data = None
95    q_data = None
96    err_data = None
97    dqx_data = None
98    dqy_data = None
99    mask = None
100
101    # Units
102    _xaxis = ''
103    _xunit = ''
104    _yaxis = ''
105    _yunit = ''
106    _zaxis = ''
107    _zunit = ''
108
109    def __init__(self, data=None, err_data=None, qx_data=None,
110                 qy_data=None, q_data=None, mask=None,
111                 dqx_data=None, dqy_data=None):
112        self.data = np.asarray(data)
113        self.qx_data = np.asarray(qx_data)
114        self.qy_data = np.asarray(qy_data)
115        self.q_data = np.asarray(q_data)
116        self.mask = np.asarray(mask)
117        self.err_data = np.asarray(err_data)
118        if dqx_data is not None:
119            self.dqx_data = np.asarray(dqx_data)
120        if dqy_data is not None:
121            self.dqy_data = np.asarray(dqy_data)
122
123    def xaxis(self, label, unit):
124        """
125        set the x axis label and unit
126        """
127        self._xaxis = label
128        self._xunit = unit
129
130    def yaxis(self, label, unit):
131        """
132        set the y axis label and unit
133        """
134        self._yaxis = label
135        self._yunit = unit
136
137    def zaxis(self, label, unit):
138        """
139        set the z axis label and unit
140        """
141        self._zaxis = label
142        self._zunit = unit
143
144
145class Vector(object):
146    """
147    Vector class to hold multi-dimensional objects
148    """
149    ## x component
150    x = None
151    ## y component
152    y = None
153    ## z component
154    z = None
155
156    def __init__(self, x=None, y=None, z=None):
157        """
158        Initialization. Components that are not
159        set a set to None by default.
160
161        :param x: x component
162        :param y: y component
163        :param z: z component
164        """
165        self.x = x
166        self.y = y
167        self.z = z
168
169    def __str__(self):
170        msg = "x = %s\ty = %s\tz = %s" % (str(self.x), str(self.y), str(self.z))
171        return msg
172
173
174class Detector(object):
175    """
176    Class to hold detector information
177    """
178    ## Name of the instrument [string]
179    name = None
180    ## Sample to detector distance [float] [mm]
181    distance = None
182    distance_unit = 'mm'
183    ## Offset of this detector position in X, Y,
184    #(and Z if necessary) [Vector] [mm]
185    offset = None
186    offset_unit = 'm'
187    ## Orientation (rotation) of this detector in roll,
188    # pitch, and yaw [Vector] [degrees]
189    orientation = None
190    orientation_unit = 'degree'
191    ## Center of the beam on the detector in X and Y
192    #(and Z if necessary) [Vector] [mm]
193    beam_center = None
194    beam_center_unit = 'mm'
195    ## Pixel size in X, Y, (and Z if necessary) [Vector] [mm]
196    pixel_size = None
197    pixel_size_unit = 'mm'
198    ## Slit length of the instrument for this detector.[float] [mm]
199    slit_length = None
200    slit_length_unit = 'mm'
201
202    def __init__(self):
203        """
204        Initialize class attribute that are objects...
205        """
206        self.offset = Vector()
207        self.orientation = Vector()
208        self.beam_center = Vector()
209        self.pixel_size = Vector()
210
211    def __str__(self):
212        _str = "Detector:\n"
213        _str += "   Name:         %s\n" % self.name
214        _str += "   Distance:     %s [%s]\n" % \
215            (str(self.distance), str(self.distance_unit))
216        _str += "   Offset:       %s [%s]\n" % \
217            (str(self.offset), str(self.offset_unit))
218        _str += "   Orientation:  %s [%s]\n" % \
219            (str(self.orientation), str(self.orientation_unit))
220        _str += "   Beam center:  %s [%s]\n" % \
221            (str(self.beam_center), str(self.beam_center_unit))
222        _str += "   Pixel size:   %s [%s]\n" % \
223            (str(self.pixel_size), str(self.pixel_size_unit))
224        _str += "   Slit length:  %s [%s]\n" % \
225            (str(self.slit_length), str(self.slit_length_unit))
226        return _str
227
228
229class Aperture(object):
230    ## Name
231    name = None
232    ## Type
233    type = None
234    ## Size name
235    size_name = None
236    ## Aperture size [Vector]
237    size = None
238    size_unit = 'mm'
239    ## Aperture distance [float]
240    distance = None
241    distance_unit = 'mm'
242
243    def __init__(self):
244        self.size = Vector()
245
246
247class Collimation(object):
248    """
249    Class to hold collimation information
250    """
251    ## Name
252    name = None
253    ## Length [float] [mm]
254    length = None
255    length_unit = 'mm'
256    ## Aperture
257    aperture = None
258
259    def __init__(self):
260        self.aperture = []
261
262    def __str__(self):
263        _str = "Collimation:\n"
264        _str += "   Length:       %s [%s]\n" % \
265            (str(self.length), str(self.length_unit))
266        for item in self.aperture:
267            _str += "   Aperture size:%s [%s]\n" % \
268                (str(item.size), str(item.size_unit))
269            _str += "   Aperture_dist:%s [%s]\n" % \
270                (str(item.distance), str(item.distance_unit))
271        return _str
272
273
274class Source(object):
275    """
276    Class to hold source information
277    """
278    ## Name
279    name = None
280    ## Radiation type [string]
281    radiation = None
282    ## Beam size name
283    beam_size_name = None
284    ## Beam size [Vector] [mm]
285    beam_size = None
286    beam_size_unit = 'mm'
287    ## Beam shape [string]
288    beam_shape = None
289    ## Wavelength [float] [Angstrom]
290    wavelength = None
291    wavelength_unit = 'A'
292    ## Minimum wavelength [float] [Angstrom]
293    wavelength_min = None
294    wavelength_min_unit = 'nm'
295    ## Maximum wavelength [float] [Angstrom]
296    wavelength_max = None
297    wavelength_max_unit = 'nm'
298    ## Wavelength spread [float] [Angstrom]
299    wavelength_spread = None
300    wavelength_spread_unit = 'percent'
301
302    def __init__(self):
303        self.beam_size = Vector()
304
305    def __str__(self):
306        _str = "Source:\n"
307        _str += "   Radiation:    %s\n" % str(self.radiation)
308        _str += "   Shape:        %s\n" % str(self.beam_shape)
309        _str += "   Wavelength:   %s [%s]\n" % \
310            (str(self.wavelength), str(self.wavelength_unit))
311        _str += "   Waveln_min:   %s [%s]\n" % \
312            (str(self.wavelength_min), str(self.wavelength_min_unit))
313        _str += "   Waveln_max:   %s [%s]\n" % \
314            (str(self.wavelength_max), str(self.wavelength_max_unit))
315        _str += "   Waveln_spread:%s [%s]\n" % \
316            (str(self.wavelength_spread), str(self.wavelength_spread_unit))
317        _str += "   Beam_size:    %s [%s]\n" % \
318            (str(self.beam_size), str(self.beam_size_unit))
319        return _str
320
321
322"""
323Definitions of radiation types
324"""
325NEUTRON = 'neutron'
326XRAY = 'x-ray'
327MUON = 'muon'
328ELECTRON = 'electron'
329
330
331class Sample(object):
332    """
333    Class to hold the sample description
334    """
335    ## Short name for sample
336    name = ''
337    ## ID
338    ID = ''
339    ## Thickness [float] [mm]
340    thickness = None
341    thickness_unit = 'mm'
342    ## Transmission [float] [fraction]
343    transmission = None
344    ## Temperature [float] [No Default]
345    temperature = None
346    temperature_unit = None
347    ## Position [Vector] [mm]
348    position = None
349    position_unit = 'mm'
350    ## Orientation [Vector] [degrees]
351    orientation = None
352    orientation_unit = 'degree'
353    ## Details
354    details = None
355    ## SESANS zacceptance
356    zacceptance = (0,"")
357    yacceptance = (0,"")
358
359    def __init__(self):
360        self.position = Vector()
361        self.orientation = Vector()
362        self.details = []
363
364    def __str__(self):
365        _str = "Sample:\n"
366        _str += "   ID:           %s\n" % str(self.ID)
367        _str += "   Transmission: %s\n" % str(self.transmission)
368        _str += "   Thickness:    %s [%s]\n" % \
369            (str(self.thickness), str(self.thickness_unit))
370        _str += "   Temperature:  %s [%s]\n" % \
371            (str(self.temperature), str(self.temperature_unit))
372        _str += "   Position:     %s [%s]\n" % \
373            (str(self.position), str(self.position_unit))
374        _str += "   Orientation:  %s [%s]\n" % \
375            (str(self.orientation), str(self.orientation_unit))
376
377        _str += "   Details:\n"
378        for item in self.details:
379            _str += "      %s\n" % item
380
381        return _str
382
383
384class Process(object):
385    """
386    Class that holds information about the processes
387    performed on the data.
388    """
389    name = ''
390    date = ''
391    description = ''
392    term = None
393    notes = None
394
395    def __init__(self):
396        self.term = []
397        self.notes = []
398
399    def is_empty(self):
400        """
401            Return True if the object is empty
402        """
403        return len(self.name) == 0 and len(self.date) == 0 and len(self.description) == 0 \
404            and len(self.term) == 0 and len(self.notes) == 0
405
406    def single_line_desc(self):
407        """
408            Return a single line string representing the process
409        """
410        return "%s %s %s" % (self.name, self.date, self.description)
411
412    def __str__(self):
413        _str = "Process:\n"
414        _str += "   Name:         %s\n" % self.name
415        _str += "   Date:         %s\n" % self.date
416        _str += "   Description:  %s\n" % self.description
417        for item in self.term:
418            _str += "   Term:         %s\n" % item
419        for item in self.notes:
420            _str += "   Note:         %s\n" % item
421        return _str
422
423
424class TransmissionSpectrum(object):
425    """
426    Class that holds information about transmission spectrum
427    for white beams and spallation sources.
428    """
429    name = ''
430    timestamp = ''
431    ## Wavelength (float) [A]
432    wavelength = None
433    wavelength_unit = 'A'
434    ## Transmission (float) [unit less]
435    transmission = None
436    transmission_unit = ''
437    ## Transmission Deviation (float) [unit less]
438    transmission_deviation = None
439    transmission_deviation_unit = ''
440
441    def __init__(self):
442        self.wavelength = []
443        self.transmission = []
444        self.transmission_deviation = []
445
446    def __str__(self):
447        _str = "Transmission Spectrum:\n"
448        _str += "   Name:             \t{0}\n".format(self.name)
449        _str += "   Timestamp:        \t{0}\n".format(self.timestamp)
450        _str += "   Wavelength unit:  \t{0}\n".format(self.wavelength_unit)
451        _str += "   Transmission unit:\t{0}\n".format(self.transmission_unit)
452        _str += "   Trans. Dev. unit:  \t{0}\n".format(\
453                                            self.transmission_deviation_unit)
454        length_list = [len(self.wavelength), len(self.transmission), \
455                len(self.transmission_deviation)]
456        _str += "   Number of Pts:    \t{0}\n".format(max(length_list))
457        return _str
458
459
460class DataInfo(object):
461    """
462    Class to hold the data read from a file.
463    It includes four blocks of data for the
464    instrument description, the sample description,
465    the data itself and any other meta data.
466    """
467    ## Title
468    title = ''
469    ## Run number
470    run = None
471    ## Run name
472    run_name = None
473    ## File name
474    filename = ''
475    ## Notes
476    notes = None
477    ## Processes (Action on the data)
478    process = None
479    ## Instrument name
480    instrument = ''
481    ## Detector information
482    detector = None
483    ## Sample information
484    sample = None
485    ## Source information
486    source = None
487    ## Collimation information
488    collimation = None
489    ## Transmission Spectrum INfo
490    trans_spectrum = None
491    ## Additional meta-data
492    meta_data = None
493    ## Loading errors
494    errors = None
495    ## SESANS data check
496    isSesans = None
497
498
499    def __init__(self):
500        """
501        Initialization
502        """
503        ## Title
504        self.title = ''
505        ## Run number
506        self.run = []
507        self.run_name = {}
508        ## File name
509        self.filename = ''
510        ## Notes
511        self.notes = []
512        ## Processes (Action on the data)
513        self.process = []
514        ## Instrument name
515        self.instrument = ''
516        ## Detector information
517        self.detector = []
518        ## Sample information
519        self.sample = Sample()
520        ## Source information
521        self.source = Source()
522        ## Collimation information
523        self.collimation = []
524        ## Transmission Spectrum
525        self.trans_spectrum = []
526        ## Additional meta-data
527        self.meta_data = {}
528        ## Loading errors
529        self.errors = []
530        ## SESANS data check
531        self.isSesans = False
532
533    def append_empty_process(self):
534        """
535        """
536        self.process.append(Process())
537
538    def add_notes(self, message=""):
539        """
540        Add notes to datainfo
541        """
542        self.notes.append(message)
543
544    def __str__(self):
545        """
546        Nice printout
547        """
548        _str = "File:            %s\n" % self.filename
549        _str += "Title:           %s\n" % self.title
550        _str += "Run:             %s\n" % str(self.run)
551        _str += "SESANS:          %s\n" % str(self.isSesans)
552        _str += "Instrument:      %s\n" % str(self.instrument)
553        _str += "%s\n" % str(self.sample)
554        _str += "%s\n" % str(self.source)
555        for item in self.detector:
556            _str += "%s\n" % str(item)
557        for item in self.collimation:
558            _str += "%s\n" % str(item)
559        for item in self.process:
560            _str += "%s\n" % str(item)
561        for item in self.notes:
562            _str += "%s\n" % str(item)
563        for item in self.trans_spectrum:
564            _str += "%s\n" % str(item)
565        return _str
566
567    # Private method to perform operation. Not implemented for DataInfo,
568    # but should be implemented for each data class inherited from DataInfo
569    # that holds actual data (ex.: Data1D)
570    def _perform_operation(self, other, operation):
571        """
572        Private method to perform operation. Not implemented for DataInfo,
573        but should be implemented for each data class inherited from DataInfo
574        that holds actual data (ex.: Data1D)
575        """
576        return NotImplemented
577
578    def _perform_union(self, other):
579        """
580        Private method to perform union operation. Not implemented for DataInfo,
581        but should be implemented for each data class inherited from DataInfo
582        that holds actual data (ex.: Data1D)
583        """
584        return NotImplemented
585
586    def __add__(self, other):
587        """
588        Add two data sets
589
590        :param other: data set to add to the current one
591        :return: new data set
592        :raise ValueError: raised when two data sets are incompatible
593        """
594        def operation(a, b):
595            return a + b
596        return self._perform_operation(other, operation)
597
598    def __radd__(self, other):
599        """
600        Add two data sets
601
602        :param other: data set to add to the current one
603        :return: new data set
604        :raise ValueError: raised when two data sets are incompatible
605        """
606        def operation(a, b):
607            return b + a
608        return self._perform_operation(other, operation)
609
610    def __sub__(self, other):
611        """
612        Subtract two data sets
613
614        :param other: data set to subtract from the current one
615        :return: new data set
616        :raise ValueError: raised when two data sets are incompatible
617        """
618        def operation(a, b):
619            return a - b
620        return self._perform_operation(other, operation)
621
622    def __rsub__(self, other):
623        """
624        Subtract two data sets
625
626        :param other: data set to subtract from the current one
627        :return: new data set
628        :raise ValueError: raised when two data sets are incompatible
629        """
630        def operation(a, b):
631            return b - a
632        return self._perform_operation(other, operation)
633
634    def __mul__(self, other):
635        """
636        Multiply two data sets
637
638        :param other: data set to subtract from the current one
639        :return: new data set
640        :raise ValueError: raised when two data sets are incompatible
641        """
642        def operation(a, b):
643            return a * b
644        return self._perform_operation(other, operation)
645
646    def __rmul__(self, other):
647        """
648        Multiply two data sets
649
650        :param other: data set to subtract from the current one
651        :return: new data set
652        :raise ValueError: raised when two data sets are incompatible
653        """
654        def operation(a, b):
655            return b * a
656        return self._perform_operation(other, operation)
657
658    def __div__(self, other):
659        """
660        Divided a data set by another
661
662        :param other: data set that the current one is divided by
663        :return: new data set
664        :raise ValueError: raised when two data sets are incompatible
665        """
666        def operation(a, b):
667            return a/b
668        return self._perform_operation(other, operation)
669
670    def __rdiv__(self, other):
671        """
672        Divided a data set by another
673
674        :param other: data set that the current one is divided by
675        :return: new data set
676        :raise ValueError: raised when two data sets are incompatible
677        """
678        def operation(a, b):
679            return b/a
680        return self._perform_operation(other, operation)
681
682    def __or__(self, other):
683        """
684        Union a data set with another
685
686        :param other: data set to be unified
687        :return: new data set
688        :raise ValueError: raised when two data sets are incompatible
689        """
690        return self._perform_union(other)
691
692    def __ror__(self, other):
693        """
694        Union a data set with another
695
696        :param other: data set to be unified
697        :return: new data set
698        :raise ValueError: raised when two data sets are incompatible
699        """
700        return self._perform_union(other)
701
702class Data1D(plottable_1D, DataInfo):
703    """
704    1D data class
705    """
706    def __init__(self, x=None, y=None, dx=None, dy=None, lam=None, dlam=None, isSesans=None):
707        DataInfo.__init__(self)
708        plottable_1D.__init__(self, x, y, dx, dy,None, None, lam, dlam)
709        self.isSesans = isSesans
710        try:
711            if self.isSesans: # the data is SESANS
712                self.x_unit = 'A'
713                self.y_unit = 'pol'
714            elif not self.isSesans: # the data is SANS
715                self.x_unit = '1/A'
716                self.y_unit = '1/cm'
717        except: # the data is not recognized/supported, and the user is notified
718            raise TypeError('data not recognized, check documentation for supported 1D data formats')
719
720    def __str__(self):
721        """
722        Nice printout
723        """
724        _str = "%s\n" % DataInfo.__str__(self)
725        _str += "Data:\n"
726        _str += "   Type:         %s\n" % self.__class__.__name__
727        _str += "   X-axis:       %s\t[%s]\n" % (self._xaxis, self._xunit)
728        _str += "   Y-axis:       %s\t[%s]\n" % (self._yaxis, self._yunit)
729        _str += "   Length:       %g\n" % len(self.x)
730        return _str
731
732    def is_slit_smeared(self):
733        """
734        Check whether the data has slit smearing information
735        :return: True is slit smearing info is present, False otherwise
736        """
737        def _check(v):
738            if (v.__class__ == list or v.__class__ == np.ndarray) \
739                and len(v) > 0 and min(v) > 0:
740                return True
741            return False
742        return _check(self.dxl) or _check(self.dxw)
743
744    def clone_without_data(self, length=0, clone=None):
745        """
746        Clone the current object, without copying the data (which
747        will be filled out by a subsequent operation).
748        The data arrays will be initialized to zero.
749
750        :param length: length of the data array to be initialized
751        :param clone: if provided, the data will be copied to clone
752        """
753        from copy import deepcopy
754
755        if clone is None or not issubclass(clone.__class__, Data1D):
756            x = np.zeros(length)
757            dx = np.zeros(length)
758            y = np.zeros(length)
759            dy = np.zeros(length)
760            lam = np.zeros(length)
761            dlam = np.zeros(length)
762            clone = Data1D(x, y, lam=lam, dx=dx, dy=dy, dlam=dlam)
763
764        clone.title = self.title
765        clone.run = self.run
766        clone.filename = self.filename
767        clone.instrument = self.instrument
768        clone.notes = deepcopy(self.notes)
769        clone.process = deepcopy(self.process)
770        clone.detector = deepcopy(self.detector)
771        clone.sample = deepcopy(self.sample)
772        clone.source = deepcopy(self.source)
773        clone.collimation = deepcopy(self.collimation)
774        clone.trans_spectrum = deepcopy(self.trans_spectrum)
775        clone.meta_data = deepcopy(self.meta_data)
776        clone.errors = deepcopy(self.errors)
777        clone.isSesans = self.isSesans
778
779        return clone
780
781    def _validity_check(self, other):
782        """
783        Checks that the data lengths are compatible.
784        Checks that the x vectors are compatible.
785        Returns errors vectors equal to original
786        errors vectors if they were present or vectors
787        of zeros when none was found.
788
789        :param other: other data set for operation
790        :return: dy for self, dy for other [numpy arrays]
791        :raise ValueError: when lengths are not compatible
792        """
793        dy_other = None
794        if isinstance(other, Data1D):
795            # Check that data lengths are the same
796            if len(self.x) != len(other.x) or \
797                len(self.y) != len(other.y):
798                msg = "Unable to perform operation: data length are not equal"
799                raise ValueError(msg)
800            # Here we could also extrapolate between data points
801            TOLERANCE = 0.01
802            for i in range(len(self.x)):
803                if math.fabs((self.x[i] - other.x[i])/self.x[i]) > TOLERANCE:
804                    msg = "Incompatible data sets: x-values do not match"
805                    raise ValueError(msg)
806
807            # Check that the other data set has errors, otherwise
808            # create zero vector
809            dy_other = other.dy
810            if other.dy is None or (len(other.dy) != len(other.y)):
811                dy_other = np.zeros(len(other.y))
812
813        # Check that we have errors, otherwise create zero vector
814        dy = self.dy
815        if self.dy is None or (len(self.dy) != len(self.y)):
816            dy = np.zeros(len(self.y))
817
818        return dy, dy_other
819
820    def _perform_operation(self, other, operation):
821        """
822        """
823        # First, check the data compatibility
824        dy, dy_other = self._validity_check(other)
825        result = self.clone_without_data(len(self.x))
826        if self.dxw is None:
827            result.dxw = None
828        else:
829            result.dxw = np.zeros(len(self.x))
830        if self.dxl is None:
831            result.dxl = None
832        else:
833            result.dxl = np.zeros(len(self.x))
834
835        for i in range(len(self.x)):
836            result.x[i] = self.x[i]
837            if self.dx is not None and len(self.x) == len(self.dx):
838                result.dx[i] = self.dx[i]
839            if self.dxw is not None and len(self.x) == len(self.dxw):
840                result.dxw[i] = self.dxw[i]
841            if self.dxl is not None and len(self.x) == len(self.dxl):
842                result.dxl[i] = self.dxl[i]
843
844            a = Uncertainty(self.y[i], dy[i]**2)
845            if isinstance(other, Data1D):
846                b = Uncertainty(other.y[i], dy_other[i]**2)
847                if other.dx is not None:
848                    result.dx[i] *= self.dx[i]
849                    result.dx[i] += (other.dx[i]**2)
850                    result.dx[i] /= 2
851                    result.dx[i] = math.sqrt(result.dx[i])
852                if result.dxl is not None and other.dxl is not None:
853                    result.dxl[i] *= self.dxl[i]
854                    result.dxl[i] += (other.dxl[i]**2)
855                    result.dxl[i] /= 2
856                    result.dxl[i] = math.sqrt(result.dxl[i])
857            else:
858                b = other
859
860            output = operation(a, b)
861            result.y[i] = output.x
862            result.dy[i] = math.sqrt(math.fabs(output.variance))
863        return result
864
865    def _validity_check_union(self, other):
866        """
867        Checks that the data lengths are compatible.
868        Checks that the x vectors are compatible.
869        Returns errors vectors equal to original
870        errors vectors if they were present or vectors
871        of zeros when none was found.
872
873        :param other: other data set for operation
874        :return: bool
875        :raise ValueError: when data types are not compatible
876        """
877        if not isinstance(other, Data1D):
878            msg = "Unable to perform operation: different types of data set"
879            raise ValueError(msg)
880        return True
881
882    def _perform_union(self, other):
883        """
884        """
885        # First, check the data compatibility
886        self._validity_check_union(other)
887        result = self.clone_without_data(len(self.x) + len(other.x))
888        if self.dy is None or other.dy is None:
889            result.dy = None
890        else:
891            result.dy = np.zeros(len(self.x) + len(other.x))
892        if self.dx is None or other.dx is None:
893            result.dx = None
894        else:
895            result.dx = np.zeros(len(self.x) + len(other.x))
896        if self.dxw is None or other.dxw is None:
897            result.dxw = None
898        else:
899            result.dxw = np.zeros(len(self.x) + len(other.x))
900        if self.dxl is None or other.dxl is None:
901            result.dxl = None
902        else:
903            result.dxl = np.zeros(len(self.x) + len(other.x))
904
905        result.x = np.append(self.x, other.x)
906        #argsorting
907        ind = np.argsort(result.x)
908        result.x = result.x[ind]
909        result.y = np.append(self.y, other.y)
910        result.y = result.y[ind]
911        if result.dy is not None:
912            result.dy = np.append(self.dy, other.dy)
913            result.dy = result.dy[ind]
914        if result.dx is not None:
915            result.dx = np.append(self.dx, other.dx)
916            result.dx = result.dx[ind]
917        if result.dxw is not None:
918            result.dxw = np.append(self.dxw, other.dxw)
919            result.dxw = result.dxw[ind]
920        if result.dxl is not None:
921            result.dxl = np.append(self.dxl, other.dxl)
922            result.dxl = result.dxl[ind]
923        return result
924
925
926class Data2D(plottable_2D, DataInfo):
927    """
928    2D data class
929    """
930    ## Units for Q-values
931    Q_unit = '1/A'
932    ## Units for I(Q) values
933    I_unit = '1/cm'
934    ## Vector of Q-values at the center of each bin in x
935    x_bins = None
936    ## Vector of Q-values at the center of each bin in y
937    y_bins = None
938    ## No 2D SESANS data as of yet. Always set it to False
939    isSesans = False
940
941    def __init__(self, data=None, err_data=None, qx_data=None,
942                 qy_data=None, q_data=None, mask=None,
943                 dqx_data=None, dqy_data=None):
944        DataInfo.__init__(self)
945        plottable_2D.__init__(self, data, err_data, qx_data,
946                              qy_data, q_data, mask, dqx_data, dqy_data)
947        self.y_bins = []
948        self.x_bins = []
949
950        if len(self.detector) > 0:
951            raise RuntimeError("Data2D: Detector bank already filled at init")
952
953    def __str__(self):
954        _str = "%s\n" % DataInfo.__str__(self)
955        _str += "Data:\n"
956        _str += "   Type:         %s\n" % self.__class__.__name__
957        _str += "   X- & Y-axis:  %s\t[%s]\n" % (self._yaxis, self._yunit)
958        _str += "   Z-axis:       %s\t[%s]\n" % (self._zaxis, self._zunit)
959        _str += "   Length:       %g \n" % (len(self.data))
960        _str += "   Shape:        (%d, %d)\n" % (len(self.y_bins), len(self.x_bins))
961        return _str
962
963    def clone_without_data(self, length=0, clone=None):
964        """
965        Clone the current object, without copying the data (which
966        will be filled out by a subsequent operation).
967        The data arrays will be initialized to zero.
968
969        :param length: length of the data array to be initialized
970        :param clone: if provided, the data will be copied to clone
971        """
972        from copy import deepcopy
973
974        if clone is None or not issubclass(clone.__class__, Data2D):
975            data = np.zeros(length)
976            err_data = np.zeros(length)
977            qx_data = np.zeros(length)
978            qy_data = np.zeros(length)
979            q_data = np.zeros(length)
980            mask = np.zeros(length)
981            dqx_data = None
982            dqy_data = None
983            clone = Data2D(data=data, err_data=err_data,
984                           qx_data=qx_data, qy_data=qy_data,
985                           q_data=q_data, mask=mask)
986
987        clone.title = self.title
988        clone.run = self.run
989        clone.filename = self.filename
990        clone.instrument = self.instrument
991        clone.notes = deepcopy(self.notes)
992        clone.process = deepcopy(self.process)
993        clone.detector = deepcopy(self.detector)
994        clone.sample = deepcopy(self.sample)
995        clone.source = deepcopy(self.source)
996        clone.collimation = deepcopy(self.collimation)
997        clone.trans_spectrum = deepcopy(self.trans_spectrum)
998        clone.meta_data = deepcopy(self.meta_data)
999        clone.errors = deepcopy(self.errors)
1000
1001        return clone
1002
1003    def _validity_check(self, other):
1004        """
1005        Checks that the data lengths are compatible.
1006        Checks that the x vectors are compatible.
1007        Returns errors vectors equal to original
1008        errors vectors if they were present or vectors
1009        of zeros when none was found.
1010
1011        :param other: other data set for operation
1012        :return: dy for self, dy for other [numpy arrays]
1013        :raise ValueError: when lengths are not compatible
1014        """
1015        err_other = None
1016        TOLERANCE = 0.01
1017        if isinstance(other, Data2D):
1018            # Check that data lengths are the same
1019            if len(self.data) != len(other.data) or \
1020                len(self.qx_data) != len(other.qx_data) or \
1021                len(self.qy_data) != len(other.qy_data):
1022                msg = "Unable to perform operation: data length are not equal"
1023                raise ValueError(msg)
1024            for ind in range(len(self.data)):
1025                if math.fabs((self.qx_data[ind] - other.qx_data[ind])/self.qx_data[ind]) > TOLERANCE:
1026                    msg = "Incompatible data sets: qx-values do not match: %s %s" % (self.qx_data[ind], other.qx_data[ind])
1027                    raise ValueError(msg)
1028                if math.fabs((self.qy_data[ind] - other.qy_data[ind])/self.qy_data[ind]) > TOLERANCE:
1029                    msg = "Incompatible data sets: qy-values do not match: %s %s" % (self.qy_data[ind], other.qy_data[ind])
1030                    raise ValueError(msg)
1031
1032            # Check that the scales match
1033            err_other = other.err_data
1034            if other.err_data is None or \
1035                (len(other.err_data) != len(other.data)):
1036                err_other = np.zeros(len(other.data))
1037
1038        # Check that we have errors, otherwise create zero vector
1039        err = self.err_data
1040        if self.err_data is None or \
1041            (len(self.err_data) != len(self.data)):
1042            err = np.zeros(len(other.data))
1043        return err, err_other
1044
1045    def _perform_operation(self, other, operation):
1046        """
1047        Perform 2D operations between data sets
1048
1049        :param other: other data set
1050        :param operation: function defining the operation
1051        """
1052        # First, check the data compatibility
1053        dy, dy_other = self._validity_check(other)
1054        result = self.clone_without_data(np.size(self.data))
1055        if self.dqx_data is None or self.dqy_data is None:
1056            result.dqx_data = None
1057            result.dqy_data = None
1058        else:
1059            result.dqx_data = np.zeros(len(self.data))
1060            result.dqy_data = np.zeros(len(self.data))
1061        for i in range(np.size(self.data)):
1062            result.data[i] = self.data[i]
1063            if self.err_data is not None and \
1064                            np.size(self.data) == np.size(self.err_data):
1065                result.err_data[i] = self.err_data[i]
1066            if self.dqx_data is not None:
1067                result.dqx_data[i] = self.dqx_data[i]
1068            if self.dqy_data is not None:
1069                result.dqy_data[i] = self.dqy_data[i]
1070            result.qx_data[i] = self.qx_data[i]
1071            result.qy_data[i] = self.qy_data[i]
1072            result.q_data[i] = self.q_data[i]
1073            result.mask[i] = self.mask[i]
1074
1075            a = Uncertainty(self.data[i], dy[i]**2)
1076            if isinstance(other, Data2D):
1077                b = Uncertainty(other.data[i], dy_other[i]**2)
1078                if other.dqx_data is not None and \
1079                        result.dqx_data is not None:
1080                    result.dqx_data[i] *= self.dqx_data[i]
1081                    result.dqx_data[i] += (other.dqx_data[i]**2)
1082                    result.dqx_data[i] /= 2
1083                    result.dqx_data[i] = math.sqrt(result.dqx_data[i])
1084                if other.dqy_data is not None and \
1085                        result.dqy_data is not None:
1086                    result.dqy_data[i] *= self.dqy_data[i]
1087                    result.dqy_data[i] += (other.dqy_data[i]**2)
1088                    result.dqy_data[i] /= 2
1089                    result.dqy_data[i] = math.sqrt(result.dqy_data[i])
1090            else:
1091                b = other
1092            output = operation(a, b)
1093            result.data[i] = output.x
1094            result.err_data[i] = math.sqrt(math.fabs(output.variance))
1095        return result
1096
1097    def _validity_check_union(self, other):
1098        """
1099        Checks that the data lengths are compatible.
1100        Checks that the x vectors are compatible.
1101        Returns errors vectors equal to original
1102        errors vectors if they were present or vectors
1103        of zeros when none was found.
1104
1105        :param other: other data set for operation
1106        :return: bool
1107        :raise ValueError: when data types are not compatible
1108        """
1109        if not isinstance(other, Data2D):
1110            msg = "Unable to perform operation: different types of data set"
1111            raise ValueError(msg)
1112        return True
1113
1114    def _perform_union(self, other):
1115        """
1116        Perform 2D operations between data sets
1117
1118        :param other: other data set
1119        :param operation: function defining the operation
1120        """
1121        # First, check the data compatibility
1122        self._validity_check_union(other)
1123        result = self.clone_without_data(np.size(self.data) + \
1124                                         np.size(other.data))
1125        result.xmin = self.xmin
1126        result.xmax = self.xmax
1127        result.ymin = self.ymin
1128        result.ymax = self.ymax
1129        if self.dqx_data is None or self.dqy_data is None or \
1130                other.dqx_data is None or other.dqy_data is None:
1131            result.dqx_data = None
1132            result.dqy_data = None
1133        else:
1134            result.dqx_data = np.zeros(len(self.data) + \
1135                                       np.size(other.data))
1136            result.dqy_data = np.zeros(len(self.data) + \
1137                                       np.size(other.data))
1138
1139        result.data = np.append(self.data, other.data)
1140        result.qx_data = np.append(self.qx_data, other.qx_data)
1141        result.qy_data = np.append(self.qy_data, other.qy_data)
1142        result.q_data = np.append(self.q_data, other.q_data)
1143        result.mask = np.append(self.mask, other.mask)
1144        if result.err_data is not None:
1145            result.err_data = np.append(self.err_data, other.err_data)
1146        if self.dqx_data is not None:
1147            result.dqx_data = np.append(self.dqx_data, other.dqx_data)
1148        if self.dqy_data is not None:
1149            result.dqy_data = np.append(self.dqy_data, other.dqy_data)
1150
1151        return result
1152
1153
1154def combine_data_info_with_plottable(data, datainfo):
1155    """
1156    A function that combines the DataInfo data in self.current_datainto with a plottable_1D or 2D data object.
1157
1158    :param data: A plottable_1D or plottable_2D data object
1159    :return: A fully specified Data1D or Data2D object
1160    """
1161
1162    final_dataset = None
1163    if isinstance(data, plottable_1D):
1164        final_dataset = Data1D(data.x, data.y, isSesans=datainfo.isSesans)
1165        final_dataset.dx = data.dx
1166        final_dataset.dy = data.dy
1167        final_dataset.dxl = data.dxl
1168        final_dataset.dxw = data.dxw
1169        final_dataset.x_unit = data._xunit
1170        final_dataset.y_unit = data._yunit
1171        final_dataset.xaxis(data._xaxis, data._xunit)
1172        final_dataset.yaxis(data._yaxis, data._yunit)
1173    elif isinstance(data, plottable_2D):
1174        final_dataset = Data2D(data.data, data.err_data, data.qx_data, data.qy_data, data.q_data,
1175                               data.mask, data.dqx_data, data.dqy_data)
1176        final_dataset.xaxis(data._xaxis, data._xunit)
1177        final_dataset.yaxis(data._yaxis, data._yunit)
1178        final_dataset.zaxis(data._zaxis, data._zunit)
1179        if len(data.data.shape) == 2:
1180            n_rows, n_cols = data.data.shape
1181            final_dataset.y_bins = data.qy_data[0::int(n_cols)]
1182            final_dataset.x_bins = data.qx_data[:int(n_cols)]
1183    else:
1184        return_string = "Should Never Happen: _combine_data_info_with_plottable input is not a plottable1d or " + \
1185                        "plottable2d data object"
1186        return return_string
1187
1188    if hasattr(data, "xmax"):
1189        final_dataset.xmax = data.xmax
1190    if hasattr(data, "ymax"):
1191        final_dataset.ymax = data.ymax
1192    if hasattr(data, "xmin"):
1193        final_dataset.xmin = data.xmin
1194    if hasattr(data, "ymin"):
1195        final_dataset.ymin = data.ymin
1196    final_dataset.isSesans = datainfo.isSesans
1197    final_dataset.title = datainfo.title
1198    final_dataset.run = datainfo.run
1199    final_dataset.run_name = datainfo.run_name
1200    final_dataset.filename = datainfo.filename
1201    final_dataset.notes = datainfo.notes
1202    final_dataset.process = datainfo.process
1203    final_dataset.instrument = datainfo.instrument
1204    final_dataset.detector = datainfo.detector
1205    final_dataset.sample = datainfo.sample
1206    final_dataset.source = datainfo.source
1207    final_dataset.collimation = datainfo.collimation
1208    final_dataset.trans_spectrum = datainfo.trans_spectrum
1209    final_dataset.meta_data = datainfo.meta_data
1210    final_dataset.errors = datainfo.errors
1211    return final_dataset
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