| 1 | import sys, time |
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| 2 | from calcthread import CalcThread |
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| 3 | from sans.pr.invertor import Invertor |
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| 4 | import numpy |
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| 5 | from config import printEVT |
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| 6 | |
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| 7 | class CalcPr(CalcThread): |
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| 8 | """ |
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| 9 | Compute 2D model |
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| 10 | This calculation assumes a 2-fold symmetry of the model |
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| 11 | where points are computed for one half of the detector |
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| 12 | and I(qx, qy) = I(-qx, -qy) is assumed. |
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| 13 | """ |
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| 14 | |
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| 15 | def __init__(self, pr, nfunc=5, error_func=None, |
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| 16 | completefn = None, |
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| 17 | updatefn = None, |
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| 18 | yieldtime = 0.01, |
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| 19 | worktime = 0.01 |
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| 20 | ): |
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| 21 | CalcThread.__init__(self,completefn, |
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| 22 | updatefn, |
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| 23 | yieldtime, |
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| 24 | worktime) |
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| 25 | self.pr = pr |
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| 26 | self.nfunc = nfunc |
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| 27 | self.error_func = error_func |
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| 28 | self.starttime = 0 |
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| 29 | |
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| 30 | def isquit(self): |
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| 31 | try: |
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| 32 | CalcThread.isquit(self) |
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| 33 | except KeyboardInterrupt: |
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| 34 | printEVT("P(r) calc interrupted") |
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| 35 | raise KeyboardInterrupt |
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| 36 | |
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| 37 | def compute(self): |
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| 38 | import time |
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| 39 | try: |
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| 40 | self.starttime = time.time() |
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| 41 | #out, cov = self.pr.invert(self.nfunc) |
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| 42 | out, cov = self.pr.lstsq(self.nfunc) |
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| 43 | elapsed = time.time()-self.starttime |
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| 44 | self.complete(out=out, cov=cov, pr=self.pr, elapsed=elapsed) |
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| 45 | except: |
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| 46 | if not self.error_func==None: |
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| 47 | self.error_func("CalcPr.compute: %s" % sys.exc_value) |
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| 48 | |
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| 49 | class EstimatePr(CalcThread): |
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| 50 | """ |
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| 51 | Compute 2D model |
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| 52 | This calculation assumes a 2-fold symmetry of the model |
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| 53 | where points are computed for one half of the detector |
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| 54 | and I(qx, qy) = I(-qx, -qy) is assumed. |
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| 55 | """ |
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| 56 | |
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| 57 | def __init__(self, pr, nfunc=5, error_func=None, |
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| 58 | completefn = None, |
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| 59 | updatefn = None, |
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| 60 | yieldtime = 0.01, |
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| 61 | worktime = 0.01 |
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| 62 | ): |
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| 63 | CalcThread.__init__(self,completefn, |
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| 64 | updatefn, |
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| 65 | yieldtime, |
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| 66 | worktime) |
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| 67 | self.pr = pr |
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| 68 | self.nfunc = nfunc |
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| 69 | self.error_func = error_func |
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| 70 | self.starttime = 0 |
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| 71 | |
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| 72 | def isquit(self): |
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| 73 | try: |
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| 74 | CalcThread.isquit(self) |
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| 75 | except KeyboardInterrupt: |
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| 76 | printEVT("P(r) calc interrupted") |
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| 77 | raise KeyboardInterrupt |
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| 78 | |
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| 79 | def compute(self): |
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| 80 | import time |
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| 81 | try: |
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| 82 | self.starttime = time.time() |
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| 83 | # If the current alpha is zero, try |
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| 84 | # another value |
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| 85 | if self.pr.alpha<=0: |
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| 86 | self.pr.alpha = 0.0001 |
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| 87 | |
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| 88 | # Perform inversion to find the largest alpha |
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| 89 | out, cov = self.pr.lstsq(self.nfunc) |
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| 90 | elapsed = time.time()-self.starttime |
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| 91 | initial_alpha = self.pr.alpha |
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| 92 | initial_peaks = self.pr.get_peaks(out) |
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| 93 | |
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| 94 | # Try the inversion with the estimated alpha |
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| 95 | self.pr.alpha = self.pr.suggested_alpha |
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| 96 | out, cov = self.pr.lstsq(self.nfunc) |
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| 97 | |
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| 98 | npeaks = self.pr.get_peaks(out) |
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| 99 | # if more than one peak to start with |
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| 100 | # just return the estimate |
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| 101 | if npeaks>1: |
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| 102 | message = "Your P(r) is not smooth, please check your inversion parameters" |
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| 103 | self.complete(alpha=self.pr.suggested_alpha, message=message, elapsed=elapsed) |
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| 104 | else: |
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| 105 | |
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| 106 | # Look at smaller values |
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| 107 | # We assume that for the suggested alpha, we have 1 peak |
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| 108 | # if not, send a message to change parameters |
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| 109 | alpha = self.pr.suggested_alpha |
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| 110 | best_alpha = self.pr.suggested_alpha |
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| 111 | found = False |
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| 112 | for i in range(10): |
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| 113 | self.pr.alpha = (0.33)**(i+1)*alpha |
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| 114 | out, cov = self.pr.lstsq(self.nfunc) |
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| 115 | #osc = self.pr.oscillations(out) |
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| 116 | #print self.pr.alpha, osc |
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| 117 | |
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| 118 | peaks = self.pr.get_peaks(out) |
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| 119 | print self.pr.alpha, peaks |
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| 120 | if peaks>1: |
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| 121 | found = True |
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| 122 | break |
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| 123 | best_alpha = self.pr.alpha |
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| 124 | |
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| 125 | # If we didn't find a turning point for alpha and |
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| 126 | # the initial alpha already had only one peak, |
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| 127 | # just return that |
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| 128 | if not found and initial_peaks==1 and initial_alpha<best_alpha: |
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| 129 | best_alpha = initial_alpha |
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| 130 | |
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| 131 | # Check whether the size makes sense |
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| 132 | message=None |
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| 133 | |
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| 134 | if not found: |
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| 135 | message = "None" |
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| 136 | elif best_alpha>=0.5*self.pr.suggested_alpha: |
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| 137 | # best alpha is too big, return a |
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| 138 | # reasonable value |
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| 139 | message = "The estimated alpha for your system is too large. " |
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| 140 | message += "Try increasing your maximum distance." |
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| 141 | |
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| 142 | self.complete(alpha=best_alpha, message=None, elapsed=elapsed) |
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| 143 | |
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| 144 | except: |
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| 145 | if not self.error_func==None: |
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| 146 | printEVT("EstimatePr.compute: %s" % sys.exc_value) |
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| 147 | |
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| 148 | |
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