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Viewing changes to PyMca/SimpleMath.py

  • Committer: Package Import Robot
  • Author(s): Picca Frédéric-Emmanuel
  • Date: 2014-10-01 21:38:53 UTC
  • mfrom: (1.1.7)
  • Revision ID: package-import@ubuntu.com-20141001213853-b6b199r0ty8smcxd
Tags: 4.7.4+dfsg-1
* Imported Upstream version 4.7.4+dfsg
* debian/patches
  - 0003-forwaded-upstream-allow-to-build-with-the-system-qhu.patch
    (an equivalent patch was applyed by upstream)

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PyMca/SimpleMath.py
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                              right=yInterPrime[-1])
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        return x, result
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69
 
70
 
    def average(self,xdata0,ydata0):
71
 
        #check if all the x axis are identical (no interpolation needed)
72
 
        allthesamex=1
73
 
        x0=xdata0[0]
74
 
        for xaxis in xdata0:
75
 
            if len(x0) == len(xaxis):
76
 
                if numpy.alltrue(x0==xaxis):
 
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    def average(self, xarr, yarr, x=None):
 
71
        """
 
72
        :param xarr : List containing x values in 1-D numpy arrays
 
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        :param yarr : List containing y Values in 1-D numpy arrays
 
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        :param x: x values of the final average spectrum (or None)
 
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        :return: Average spectrum. In case of invalid input (None, None) tuple is returned.
 
76
 
 
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        From the spectra given in xarr & yarr, the method determines the overlap in
 
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        the x-range. For spectra with unequal x-ranges, the method interpolates all
 
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        spectra on the values given in x if provided or the first curve and averages them.
 
80
        """
 
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        if (len(xarr) != len(yarr)) or\
 
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           (len(xarr) == 0) or (len(yarr) == 0):
 
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            if DEBUG:
 
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                print('specAverage -- invalid input!')
 
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                print('Array lengths do not match or are 0')
 
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            return None, None 
 
87
 
 
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        same = True
 
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        if x == None:
 
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            SUPPLIED = False
 
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            x0 = xarr[0]
 
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        else:
 
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            SUPPLIED = True
 
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            x0 = x
 
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        for x in xarr:
 
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            if len(x0) == len(x):
 
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                if numpy.all(x0 == x):
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                    pass
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                else:
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                    allthesamex=0
 
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                    same = False
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                    break
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            else:
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                allthesamex=0
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                break
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        if allthesamex:
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            xdata=[]
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            ydata=[]
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            i=0
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            for x0 in xdata0:
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                x=numpy.array(x0)
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                xdata.append(x)
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                ydata.append(numpy.array(ydata0[i]))
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                i=i+1
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95
 
            finalx=numpy.array(x0)
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            finalx=xdata0[0]
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            finaly=numpy.zeros(finalx.shape ,numpy.float)
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            i = 0
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            for x0 in xdata0:
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                finaly += ydata[i]
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                i=i+1
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        else:
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            #sort the data
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            xdata=[]
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            ydata=[]
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            i=0
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            for x0 in xdata0:
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                x=numpy.array(x0)
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                i1=numpy.argsort(x)
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                xdata.append(numpy.take(x,i1))
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                ydata.append(numpy.take(numpy.array(ydata0[i]),i1))
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                i=i+1         
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            #get the max and the min x axis
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            xmin=xdata[0][0]
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            xmax=xdata[0][-1]
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            for x in xdata:
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                if xmin < x[0]:
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                    xmin=x[0]
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                if xmax > x[-1]:
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                    xmax=x[-1]
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            #take the data in between
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            x=[]
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            y=[]
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            i=0
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            minimumLength = len(xdata[0])
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            for x0 in xdata:
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                i1=numpy.nonzero((x0>=xmin) & (x0<=xmax))[0]
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                x.append(numpy.take(x0,i1))
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                y.append(numpy.take(numpy.array(ydata[i]),i1))
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                if len(x0) < minimumLength:
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                    minimumLength = len(x0)
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                i=i+1
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135
 
            if minimumLength < 2:
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                raise ValueError("Not enough points to take a meaningfull average")
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            #take as x axis the first
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            finalx=x[0]
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            for i in range(len(x)):
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                if x[i][0] > finalx[0]:
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                    finalx = x[i] 
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            finaly=numpy.zeros(finalx.shape, numpy.float)
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            j=-1
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            allthesamex=0
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            for p in range(len(finalx)):
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              point=finalx[p] 
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              i=0
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              j=j+1
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              try:            
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                for x0 in x:
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                    if allthesamex:
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                        finaly[p]+=y[i][p]
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                    else:
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                        i1=max(numpy.nonzero(x0<=point)[0])
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                        i2=min(numpy.nonzero(x0>=point)[0])
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                        if i1 >= i2:
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                            #take the point as it is
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                            finaly[p]+=y[i][i1]
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                        else:
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                            #interpolation
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                            A=(x0[i2]-point)/(x0[i2]-x0[i1])
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                            B=1.-A
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                            finaly[p]+=A*y[i][i1]+B*y[i][i2]
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                    i=i+1
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              except:
166
 
                break
167
 
        if allthesamex:
168
 
              finalx=finalx[0:]
169
 
              finaly=finaly[0:]/len(xdata0)      
170
 
        else:
171
 
              finalx=finalx[0:j]
172
 
              finaly=finaly[0:j]/len(xdata0)
173
 
     
174
 
        return finalx,finaly
 
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                same = False
 
104
                break
 
105
 
 
106
        xsort = []
 
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        ysort = []
 
108
        for (x,y) in zip(xarr, yarr):
 
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            if numpy.all(numpy.diff(x) > 0.):
 
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                # All values sorted
 
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                xsort.append(x)
 
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                ysort.append(y)
 
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            else:
 
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                # Sort values
 
115
                mask = numpy.argsort(x)
 
116
                xsort.append(x.take(mask))
 
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                ysort.append(y.take(mask))
 
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119
        if SUPPLIED:
 
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            xmin0 = x0.min()
 
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            xmax0 = x0.max()
 
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        else:
 
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            xmin0 = xsort[0][0]
 
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            xmax0 = xsort[0][-1]
 
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        if (not same) or (not SUPPLIED):
 
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            # Determine global xmin0 & xmax0
 
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            for x in xsort:
 
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                xmin = x.min()
 
129
                xmax = x.max()
 
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                if xmin > xmin0:
 
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                    xmin0 = xmin
 
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                if xmax < xmax0:
 
133
                    xmax0 = xmax
 
134
            if xmax <= xmin:
 
135
                if DEBUG:
 
136
                    print('specAverage -- ')
 
137
                    print('No overlap between spectra!')
 
138
                return numpy.array([]), numpy.array([])
 
139
 
 
140
        # Clip xRange to maximal overlap in spectra
 
141
        mask = numpy.nonzero((x0 >= xmin0) & 
 
142
                             (x0 <= xmax0))[0]
 
143
        xnew = numpy.take(x0, mask)
 
144
        ynew = numpy.zeros(len(xnew))
 
145
 
 
146
        # Perform average
 
147
        for (x, y) in zip(xsort, ysort):
 
148
            if same:
 
149
                ynew += y  
 
150
            else:
 
151
                yinter = numpy.interp(xnew, x, y)
 
152
                ynew   += numpy.asarray(yinter)
 
153
        num = len(yarr)
 
154
        ynew /= num
 
155
        return xnew, ynew
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156
 
176
157
    def smooth(self, *var, **kw):
177
158
        """