1 | """ |
---|
2 | This module is responsible to compute invariant related computation. |
---|
3 | @author: Gervaise B. Alina/UTK |
---|
4 | """ |
---|
5 | import numpy |
---|
6 | class InvariantCalculator(object): |
---|
7 | """ |
---|
8 | Compute invariant |
---|
9 | """ |
---|
10 | def __init__(self): |
---|
11 | """ |
---|
12 | Initialize variables |
---|
13 | """ |
---|
14 | self.x =[] |
---|
15 | self.y =[] |
---|
16 | self.dxl = None |
---|
17 | |
---|
18 | def setData(self, x=[], y=[], dxl=None): |
---|
19 | """ |
---|
20 | set the data |
---|
21 | """ |
---|
22 | tempx = numpy.array(x) |
---|
23 | tempy = numpy.array(y) |
---|
24 | #Make sure data is order before computing |
---|
25 | ind = numpy.lexsort((tempy,tempx)) |
---|
26 | self.x = tempx[ind] |
---|
27 | self.y = tempy[ind] |
---|
28 | if dxl !=None: |
---|
29 | tempdxl= numpy.array(dxl) |
---|
30 | self.dxl= tempdxl[ind] |
---|
31 | else: |
---|
32 | self.dxl=dxl |
---|
33 | |
---|
34 | |
---|
35 | def computeInvariant(self): |
---|
36 | """ |
---|
37 | Compute invariant |
---|
38 | """ |
---|
39 | if len(self.x)<=1 or len(self.y)<=1 or len(self.x)!=len(self.y): |
---|
40 | msg= "Length x and y must be equal" |
---|
41 | msg +=" and greater than 1; got x=%s, y=%s"%(len(self.x),len(self.y)) |
---|
42 | raise ValueError,msg |
---|
43 | elif len(self.x)==1 and len(self.y)==1: |
---|
44 | return 0 |
---|
45 | |
---|
46 | else: |
---|
47 | n= len(self.x)-1 |
---|
48 | #compute the first delta |
---|
49 | dx0= self.x[1]- self.x[0] |
---|
50 | #compute the last delta |
---|
51 | dxn= self.x[n]- self.x[n-1] |
---|
52 | sum = 0 |
---|
53 | sum += self.x[0]* self.x[0]* self.y[0]*dx0 |
---|
54 | sum += self.x[n]* self.x[n]* self.y[n]*dxn |
---|
55 | if len(self.x)==2: |
---|
56 | return sum |
---|
57 | else: |
---|
58 | #iterate between for element different from the first and the last |
---|
59 | for i in xrange(1, n-1): |
---|
60 | dxi = (self.x[i+1] - self.x[i-1])/2 |
---|
61 | sum += self.x[i]*self.x[i]* self.y[i]* dxi |
---|
62 | return sum |
---|
63 | |
---|
64 | |
---|
65 | def computeSmearInvariant(self): |
---|
66 | """ |
---|
67 | Compute invariant with smearing info |
---|
68 | """ |
---|
69 | if self.dxl ==None: |
---|
70 | msg = "Cannot compute Smear invariant dxl " |
---|
71 | msg +="must be a list, got dx= %s"%str(self.dxl) |
---|
72 | raise ValueError,msg |
---|
73 | |
---|
74 | if len(self.x)<=1 or len(self.y)<=1 or len(self.x)!=len(self.y)\ |
---|
75 | or len(self.x)!= len(self.dxl): |
---|
76 | msg= "Length x and y must be equal" |
---|
77 | msg +=" and greater than 1; got x=%s, y=%s"%(len(self.x),len(self.y)) |
---|
78 | raise ValueError,msg |
---|
79 | else: |
---|
80 | n= len(self.x)-1 |
---|
81 | #compute the first delta |
---|
82 | dx0= self.x[1]- self.x[0] |
---|
83 | #compute the last delta |
---|
84 | dxn= self.x[n]- self.x[n-1] |
---|
85 | sum = 0 |
---|
86 | sum += self.x[0]* self.dxl[0]* self.y[0]*dx0 |
---|
87 | sum += self.x[n]* self.dxl[n]* self.y[n]*dxn |
---|
88 | if len(self.x)==2: |
---|
89 | return sum |
---|
90 | else: |
---|
91 | #iterate between for element different from the first and the last |
---|
92 | for i in xrange(1, n-1): |
---|
93 | dxi = (self.x[i+1] - self.x[i-1])/2 |
---|
94 | sum += self.x[i]*self.dxl[i]* self.y[i]* dxi |
---|
95 | return sum |
---|
96 | |
---|
97 | if __name__=="__main__": |
---|
98 | # test the module |
---|
99 | x=[1,2,3,4,10] |
---|
100 | y=[2,3,4,5,6] |
---|
101 | |
---|
102 | I= InvariantCalculator() |
---|
103 | I.setData(x=x, y=y) |
---|
104 | invariant = I.computeInvariant() |
---|
105 | print "1-Invariant : ", invariant |
---|
106 | |
---|
107 | x=[0,1] |
---|
108 | y=[0,2] |
---|
109 | I.setData(x=x, y=y) |
---|
110 | invariant = I.computeInvariant() |
---|
111 | print "2-Invariant : ", invariant |
---|
112 | |
---|
113 | x=[1,3,4,10,2] |
---|
114 | y=[2,4,5,6,3] |
---|
115 | I.setData(x=x, y=y) |
---|
116 | invariant = I.computeInvariant() |
---|
117 | print "3-Invariant : ", invariant |
---|
118 | |
---|
119 | # compute invariant with smear information |
---|
120 | from sans.guiframe.dataFitting import Data1D |
---|
121 | data1= Data1D(x=x,y=y ) |
---|
122 | data1.dxl =[0.1,0.1,0.1,0.1,0.1] |
---|
123 | |
---|
124 | I.setData(x= data1.x, y= data1.y, dxl=data1.dxl) |
---|
125 | invariant = I.computeSmearInvariant() |
---|
126 | print "4-Smear Invariant:", invariant |
---|
127 | I.setData(x= data1.x, y= data1.y) |
---|
128 | try: |
---|
129 | invariant = I.computeSmearInvariant() |
---|
130 | except: |
---|
131 | print "5-Smear Invariant error for dxl=None" |
---|