duplicate-code.out

************* Module pygsti.objects.labeldicts
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==pygsti.objects.gate:331
==pygsti.objects.spamvec:208
    def num_params(self):
        """
        Get the number of independent parameters which specify this SPAM vector.
        Zero in the case of StaticSPAMVec.

        Returns
        -------
        int
           the number of independent parameters.
        """
        return 0 #no parameters


    def to_vector(self):
        """
        Get the SPAM vector parameters as an array of values.  An empty
        array in the case of StaticSPAMVec.

        Returns
        -------
        numpy array
            The parameters as a 1D array with length num_params().
        """
        return _np.array([], 'd') #no parameters


    def from_vector(self, v):
        """
        Initialize the SPAM vector using a 1D array of parameters.

        Parameters
        ----------
        v : numpy array
            The 1D vector of gate parameters.  Length
            must == num_params()

        Returns
        -------
        None
        """
        assert(len(v) == 0) #should be no parameters, and nothing to do

 (duplicate-code)
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==pygsti.objects.protectedarray:39
==pygsti.objects.spamvec:104
    def __pos__(self):        return self.base
    def __neg__(self):        return -self.base
    def __abs__(self):        return abs(self.base)
    def __add__(self,x):      return self.base + x
    def __radd__(self,x):     return x + self.base
    def __sub__(self,x):      return self.base - x
    def __rsub__(self,x):     return x - self.base
    def __mul__(self,x):      return self.base * x
    def __rmul__(self,x):     return x * self.base
    def __truediv__(self, x):  return self.base / x
    def __rtruediv__(self, x): return x / self.base
    def __floordiv__(self,x):  return self.base // x
    def __rfloordiv__(self,x): return x // self.base
    def __pow__(self,x):      return self.base ** x
    def __eq__(self,x):       return self.base == x
    def __len__(self):        return len(self.base)
    def __int__(self):        return int(self.base)
    def __long__(self):       return int(self.base)
    def __float__(self):      return float(self.base)
    def __complex__(self):    return complex(self.base)

 (duplicate-code)
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==pygsti.report.latex:202
==pygsti.report.ppt:194
                    s = "%se^{%s}" % (render(r),ex)
                else:
                    s = "%s%s%si" % (render(el.real),'+' if el.imag > 0 else '-', render(abs(el.imag)))
            else:
                s = "%s" % render(el.real)
        else:
            if abs(el.imag) > TOL:
                s = "%si" % render(el.imag)
            else:
                s = "0"
    except:
        #try:
        #    if abs(el) > TOL: #throws error if el is not a number
        #        s = "%s" % render(el.real)
        #    else:
        #        s = "0"
        #except:
        s = str(el)

    return s

 (duplicate-code)
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==pygsti.report.html:212
==pygsti.report.latex:203
==pygsti.report.ppt:195
                else:
                    s = "%s%s%si" % (render(el.real),'+' if el.imag > 0 else '-', render(abs(el.imag)))
            else:
                s = "%s" % render(el.real)
        else:
            if abs(el.imag) > TOL:
                s = "%si" % render(el.imag)
            else:
                s = "0"
    except:
        #try:
        #    if abs(el) > TOL: #throw exception if el is not a number
        #        s = "%s" % render(el.real)
        #    else:
        #        s = "0"
        #except:
        s = str(el)

    return s

 (duplicate-code)
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==pygsti.report.html:174
==pygsti.report.ppt:158
    TOL = 1e-9  #tolerance for printing zero values

    def render(x):
        if abs(x) < 5*10**(-(ROUND+1)):
            s = "%.0e" % x # one significant figure
        elif abs(x) < 1:
            s = "%.*f" % (ROUND,x)
        elif abs(x) <= 10**ROUND:
            s = "%.*f" % (ROUND-int(_np.log10(abs(x))),x)  #round to get ROUND digits when x is < 1
            #str(round(x,ROUND))  #OLD
        else:
            s = "%.0e" % x # one significant figure

        #Fix scientific notition
        p = s.split('e')
        if len(p) == 2:
            ex = str(int(p[1])) #exponent without extras (e.g. +04 => 4) (duplicate-code)
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==pygsti.report.latex:185
==pygsti.report.ppt:178
        if "." in s:
            while s.endswith("0"): s = s[:-1]
            if s.endswith("."): s = s[:-1]
        return s

    if type(el) == str: return el
    if type(el) in (int,_np.int64):
        return "%d" % el
    if el is None or _np.isnan(el): return "--"

    try:
        if abs(el.real) > TOL:
            if abs(el.imag) > TOL:
                if complexAsPolar:
                    r,phi = cmath.polar(el) (duplicate-code)
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==pygsti.report.html:176
==pygsti.report.latex:167
==pygsti.report.ppt:160
    def render(x):
        if abs(x) < 5*10**(-(ROUND+1)):
            s = "%.0e" % x # one significant figure
        elif abs(x) < 1:
            s = "%.*f" % (ROUND,x)
        elif abs(x) <= 10**ROUND:
            s = "%.*f" % (ROUND-int(_np.log10(abs(x))),x)  #round to get ROUND digits when x is > 1
            #str(round(x,ROUND))  #OLD
        else:
            s = "%.0e" % x # one significant figure

        #Fix scientific notition
        p = s.split('e')
        if len(p) == 2:
            ex = str(int(p[1])) #exponent without extras (e.g. +04 => 4) (duplicate-code)
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==pygsti.algorithms.fiducialselection:514
==pygsti.algorithms.germselection:405
          bFoundBetterNeighbor = False
          for neighborNum, neighbor in enumerate(get_neighbors(weights)):
              if tuple(neighbor) not in scoreD_keys:
                  neighborL1 = sum(neighbor)
                  neighborScore = compute_score(neighbor)
              else:
                  neighborL1 = sum(neighbor)
                  neighborScore = scoreD[tuple(neighbor)]

              #Move if we've found better position; if we've relaxed, we only move when L1 is improved.
              if neighborScore <= score and (neighborL1 < L1 or lessWeightOnly == False):
                  weights, score, L1 = neighbor, neighborScore, neighborL1
                  bFoundBetterNeighbor = True (duplicate-code)
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==pygsti.objects.gate:205
==pygsti.objects.spamvec:86
    def __getitem__( self, key ):
        return self.base.__getitem__(key)

    def __getslice__(self, i,j):
        return self.__getitem__(slice(i,j)) #Called for A[:]

    def __setitem__(self, key, val):
        return self.base.__setitem__(key,val)

    def __getattr__(self, attr):
        #use __dict__ so no chance for recursive __getattr__
        ret = getattr(self.__dict__['base'],attr) (duplicate-code)
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==pygsti.objects.dataset:600
==pygsti.objects.multidataset:348
        bOpen = not (hasattr(fileOrFilename, 'write'))
        if bOpen:
            if fileOrFilename.endswith(".gz"):
                import gzip as _gzip
                f = _gzip.open(fileOrFilename,"rb")
            else:
                f = open(fileOrFilename,"rb")
        else:
            f = fileOrFilename

        state_dict = _pickle.load(f)
        def expand(x): #to be backward compatible (duplicate-code)
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==pygsti.objects.dataset:567
==pygsti.objects.multidataset:321
        bOpen = not (hasattr(fileOrFilename, 'write'))
        if bOpen:
            if fileOrFilename.endswith(".gz"):
                import gzip as _gzip
                f = _gzip.open(fileOrFilename,"wb")
            else:
                f = open(fileOrFilename,"wb")
        else:
            f = fileOrFilename

        _pickle.dump(toPickle,f) (duplicate-code)
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==pygsti.report.html:200
==pygsti.report.ppt:183
    if type(el) == str: return el
    if type(el) in (int,_np.int64):
        return "%d" % el
    if el is None or _np.isnan(el): return "--"

    try:
        if abs(el.real) > TOL:
            if abs(el.imag) > TOL:
                if complexAsPolar:
                    r,phi = cmath.polar(el)
                    ex = ("i%.1f" % phi) if phi >= 0 else ("-i%.1f" % -phi) (duplicate-code)
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==pygsti.objects.dataset:179
==pygsti.objects.multidataset:101
            self.load(fileToLoadFrom)
            return

        # self.gsIndex  :  Ordered dictionary where keys = gate strings (tuples), values = integer indices into counts
        if gateStringIndices is not None:
            self.gsIndex = gateStringIndices
        elif gateStrings is not None:
            dictData = [ (gs if isinstance(gs,_gs.GateString) else _gs.GateString(gs),i) \
                           for (i,gs) in enumerate(gateStrings) ] #convert to GateStrings if necessary
            self.gsIndex = _OrderedDict( dictData ) (duplicate-code)
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==pygsti.report.html:200
==pygsti.report.latex:190
    if type(el) == str: return el
    if type(el) in (int,_np.int64):
        return "%d" % el
    if el is None or _np.isnan(el): return "--"

    try:
        if abs(el.real) > TOL:
            if abs(el.imag) > TOL:
                if complexAsPolar:
                    r,phi = cmath.polar(el) (duplicate-code)
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==pygsti.algorithms.fiducialselection:537
==pygsti.algorithms.germselection:428
              assert(slack > 0)

              printer.log("No better neighbor. Relaxing score w/slack: %g => %g" % (score, score+slack), 2)
              score += slack #artificially increase score and see if any neighbor is better now...

              for neighborNum, neighbor in enumerate(get_neighbors(weights)):
                  if sum(neighbor) < L1 and scoreD[tuple(neighbor)] < score:
                      weights, score, L1 = neighbor, scoreD[tuple(neighbor)], sum(neighbor)
                      bFoundBetterNeighbor = True (duplicate-code)
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==pygsti.construction.rpeconstruction:403
==pygsti.tools.rpetools:341
                                                  returnPhiFunList=True)
    for alphaTemp1 in alphaHatList:
        alphaErrorList.append(abs(alphaTrue - alphaTemp1))
    for epsilonTemp1 in epsilonHatList:
        epsilonErrorList.append(abs(epsilonTrue - epsilonTemp1))
#        print abs(_np.pi/2-abs(alphaTemp1))
    for thetaTemp1 in thetaHatList:
        thetaErrorList.append(abs(thetaTrue - thetaTemp1)) (duplicate-code)
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==pygsti.algorithms.fiducialselection:548
==pygsti.algorithms.germselection:439
              if not bFoundBetterNeighbor: #Relaxing didn't help!
                  printer.log("Stationary point found!");
                  break #end main for loop

          printer.log("Moving to better neighbor")
      else:
          printer.log("Hit max. iterations")
 (duplicate-code)
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==pygsti.optimize.customcg:127
==pygsti.optimize.optimize:222
        solution.success = True
    else:
        solution.success = False
        solution.message = "Maximum iterations exceeded"
    return solution


# Minimize g(s), given (s1,g1=g(s1)) as a starting point and guess, s2 for minimum (duplicate-code)
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==pygsti.algorithms.fiducialselection:494
==pygsti.algorithms.germselection:386
            v = boolVec.copy()
            v[i] = (v[i] + 1) % 2 #toggle v[i] btwn 0 and 1
            yield v

    if initialWeights is not None:
        weights = _np.array( [1 if x else 0 for x in initialWeights ] )
    else: (duplicate-code)
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==pygsti.report.html:33
==pygsti.report.latex:32
==pygsti.report.ppt:31
    if isinstance(x,_np.ndarray) or \
       isinstance(x,_objs.Gate) or \
       isinstance(x,_objs.SPAMVec):
        d = 0
        for l in x.shape:
            if l > 1: d += 1
        x = _np.squeeze(x) (duplicate-code)
R:  1, 0: Similar lines in 2 files
==pygsti.objects.gscalc:978
==pygsti.tools.likelihoodfns:682
        if comm is None:
            nprocs, rank = 1, 0
        else:
            nprocs = comm.Get_size()
            rank = comm.Get_rank()
 (duplicate-code)
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==pygsti.algorithms.core:1001
==pygsti.algorithms.core:1966
==pygsti.tools.chi2fns:121
    if memLimit is not None and memLimit < intermedMem:
        reductionFactor = float(intermedMem) / float(memLimit)
        maxEvalSubTreeSize = int(ng / reductionFactor)
    else:
        maxEvalSubTreeSize = None
 (duplicate-code)
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==pygsti.optimize.customcg:127
==pygsti.optimize.optimize:292
                solution.success = True
            else:
                solution.success = False
                solution.message = "Maximum iterations exceeded"
            return solution
 (duplicate-code)
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==pygsti.report.html:133
==pygsti.report.ppt:123
    ROUND = 4
    lines = [ ]; prefix = ""
    if fontsize is not None:
        prefix += "" #unsupported currently

    for r in range(m.shape[0]): (duplicate-code)