| 1 | import usans |
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| 2 | |
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| 3 | class BT5DataSet: |
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| 4 | |
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| 5 | def __init__(self, fn=None): |
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| 6 | |
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| 7 | self.fileName = fn |
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| 8 | self.plot = None |
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| 9 | self.detdata = {} |
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| 10 | self.metadata = {} |
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| 11 | self.alignvals = {} |
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| 12 | self.alignvalstring = '' |
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| 13 | |
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| 14 | if (self.fileName != None): |
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| 15 | self.getBT5DataFromFile(self.fileName) |
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| 16 | |
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| 17 | |
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| 18 | def getBT5DataFromFile(self,fileName): |
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| 19 | ''' |
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| 20 | Takes a filename and returns a dictionary of the detector values |
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| 21 | keyed by varying value (ususally A2 or A5) |
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| 22 | ''' |
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| 23 | |
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| 24 | if usans.isBT5Data(fileName): |
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| 25 | |
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| 26 | motlist = [] |
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| 27 | |
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| 28 | #print "File: ",fileName |
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| 29 | inputfile = open(fileName, "r") |
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| 30 | |
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| 31 | inputdata = inputfile.readlines() |
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| 32 | |
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| 33 | mdtmp = inputdata[0].replace("'", "") |
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| 34 | mdtmp = mdtmp.split() |
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| 35 | |
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| 36 | #Sundry metadata about run settings |
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| 37 | (self.metadata['filename'], self.metadata['datetime'], |
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| 38 | self.metadata['mon'], self.metadata['prefactor'], |
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| 39 | self.metadata['base'], self.metadata['numpnts'], |
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| 40 | self.metadata['type']) = (mdtmp[0], ' '.join(mdtmp[1:5]), float(mdtmp[6]), int(mdtmp[7]), mdtmp[8], int(mdtmp[9]), mdtmp[10]) |
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| 41 | |
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| 42 | #Comment string |
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| 43 | self.metadata['title'] = inputdata[2].strip() |
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| 44 | |
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| 45 | #Start, step and end values for motors 1-6 |
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| 46 | motlist.append(inputdata[5].split()[1:]) |
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| 47 | motlist.append(inputdata[6].split()[1:]) |
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| 48 | motlist.append(inputdata[7].split()[1:]) |
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| 49 | motlist.append(inputdata[8].split()[1:]) |
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| 50 | motlist.append(inputdata[9].split()[1:]) |
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| 51 | motlist.append(inputdata[10].split()[1:]) |
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| 52 | self.metadata['motorvals'] = motlist |
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| 53 | |
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| 54 | for index in range(13, len(inputdata), 2): |
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| 55 | self.detdata[float(inputdata[index].split()[0])] = inputdata[index + 1].split(',') |
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| 56 | |
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| 57 | for key in self.detdata.keys(): |
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| 58 | for val in range(0, len(self.detdata[key])): |
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| 59 | self.detdata[key][val] = int(self.detdata[key][val]) |
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| 60 | |
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| 61 | inputfile.close() |
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| 62 | |
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| 63 | |
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| 64 | |
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| 65 | |
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| 66 | def printDetectorData(self): |
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| 67 | ''' |
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| 68 | Print the contents of the file in a formatted fashion |
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| 69 | |
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| 70 | Takes a dictionary of data as provided by getBT5DataFromFile() and prints out the contents |
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| 71 | in a formatted fashion |
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| 72 | ''' |
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| 73 | motorvals = self.detdata.keys() |
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| 74 | motorvals.sort(cmp=numeric_compare) |
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| 75 | |
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| 76 | for motorval in motorvals: |
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| 77 | str = repr(motorval) + ":" |
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| 78 | str += "\tMon: " + repr(detdata[motorval][0]) |
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| 79 | str += "\tDet 1-5: " + repr(detdata[motorval][2]) |
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| 80 | str += "\t" + repr(detdata[motorval][1]) |
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| 81 | str += "\t" + repr(detdata[motorval][4]) |
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| 82 | str += "\t" + repr(detdata[motorval][5]) |
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| 83 | str += "\t" + repr(detdata[motorval][6]) |
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| 84 | str += "\tTrans: " + repr(detdata[motorval][3]) |
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| 85 | print str |
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| 86 | |
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| 87 | return 0 |
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| 88 | |
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| 89 | def calcAlignVals(self,mv): |
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| 90 | ''' |
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| 91 | Return the values we record in the logbook for a given motor position |
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| 92 | |
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| 93 | Takes a dictionary as provided by getBT5DataFromFile and returns a dictionary with |
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| 94 | keys Central, Trans and Sum |
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| 95 | ''' |
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| 96 | motorval = float(mv) |
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| 97 | |
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| 98 | self.alignvals['Central'] = self.detdata[motorval][1] |
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| 99 | self.alignvals['Trans'] = self.detdata[motorval][3] |
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| 100 | self.alignvals['Sum'] = self.detdata[motorval][1] + self.detdata[motorval][2] + self.detdata[motorval][4] + self.detdata[motorval][5] + self.detdata[motorval][6] |
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| 101 | self.alignvals['Monitor'] = self.detdata[motorval][0] |
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| 102 | self.alignvals['Sum/Monitor'] = float(self.alignvals['Sum'])/float(self.alignvals['Monitor']) |
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| 103 | |
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| 104 | self.alignvalstring = "#4: "+repr(self.alignvals['Central']) |
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| 105 | self.alignvalstring += " Trans: "+repr(self.alignvals['Trans']) |
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| 106 | self.alignvalstring += " Sum: "+repr(self.alignvals['Sum']) |
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| 107 | self.alignvalstring += " MCR: "+repr(self.alignvals['Monitor']) |
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| 108 | self.alignvalstring += " Sum/MCR: %5.3f" % self.alignvals['Sum/Monitor'] |
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| 109 | |
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| 110 | def maxDetCount(self, detector): |
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| 111 | ''' |
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| 112 | Return the maximum value and corresponding motor position for a given detector |
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| 113 | |
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| 114 | Takes a dictionary as provided by getBT5DataFromFile() and returns a dictionary with |
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| 115 | keys Position and Value |
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| 116 | ''' |
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| 117 | maxpos = '' |
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| 118 | maxval = 0 |
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| 119 | result = {} |
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| 120 | |
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| 121 | mvals = self.detdata.keys() |
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| 122 | det = {'1':2, '2':1, '3':4, '4':5, '5':6}[repr(detector)] |
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| 123 | |
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| 124 | for mval in mvals: |
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| 125 | if self.detdata[mval][det] > maxval: |
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| 126 | maxval = data[mval][det] |
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| 127 | maxpos = mval |
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| 128 | |
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| 129 | result['Position'] = maxpos |
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| 130 | result['Value'] = maxval |
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| 131 | |
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| 132 | return result |
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| 133 | |
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| 134 | def plot_dataset(self,axes,plottype=None): |
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| 135 | ''' |
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| 136 | Takes a matplotlib axes object and plots bt5 dataset on it. |
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| 137 | ''' |
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| 138 | data = self.detdata |
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| 139 | metadata = self.metadata |
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| 140 | |
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| 141 | if type is None: |
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| 142 | plottype = 'rate' |
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| 143 | |
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| 144 | if plottype == 'total': |
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| 145 | #generate totals |
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| 146 | xdata = [] |
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| 147 | ydata = [] |
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| 148 | |
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| 149 | mvals = data.keys() |
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| 150 | mvals.sort(usans.numeric_compare) |
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| 151 | for mval in mvals: |
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| 152 | xdata.append(mval) |
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| 153 | ydata.append(data[mval][1] + data[mval][2] + data[mval][4] + data[mval][5] + data[mval][6]) |
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| 154 | |
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| 155 | self.plot = axes.plot(xdata,ydata, 'bo', picker=5) |
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| 156 | |
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| 157 | elif plottype == 'rate': |
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| 158 | # generate countrate |
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| 159 | xdata = [] |
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| 160 | ydata = [] |
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| 161 | |
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| 162 | mvals = data.keys() |
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| 163 | mvals.sort(usans.numeric_compare) |
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| 164 | for mval in mvals: |
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| 165 | xdata.append(mval) |
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| 166 | |
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| 167 | if metadata['base'] == 'TIME': |
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| 168 | #Counting in TIME base, so normalize by seconds |
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| 169 | cnttime = metadata['mon'] |
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| 170 | for mval in mvals: |
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| 171 | ydata.append((data[mval][1] + data[mval][2] + data[mval][4] + data[mval][5] + data[mval][6]) / cnttime) |
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| 172 | else: |
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| 173 | #Must be counting in monitor base so normalize by monitor |
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| 174 | moncts = metadata['mon'] |
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| 175 | for mval in mvals: |
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| 176 | ydata.append((data[mval][1] + data[mval][2] + data[mval][4] + data[mval][5] + data[mval][6]) / cnttime) |
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| 177 | |
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| 178 | self.plot = axes.plot(xdata,ydata, 'bo', picker=5) |
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| 179 | |
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| 180 | |
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| 181 | elif plottype == 'trans': |
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| 182 | xdata = [] |
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| 183 | ydata = [] |
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| 184 | |
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| 185 | mvals = data.keys() |
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| 186 | mvals.sort(usans.numeric_compare) |
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| 187 | for mval in mvals: |
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| 188 | xdata.append(mval) |
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| 189 | ydata.append(data[mval][3]) |
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| 190 | |
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| 191 | self.plot = axes.plot(xdata,ydata, 'bo', picker=5) |
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| 192 | |
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| 193 | |
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| 194 | |
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| 195 | elif plottype == 'mon': |
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| 196 | xdata = [] |
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| 197 | ydata = [] |
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| 198 | |
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| 199 | mvals = data.keys() |
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| 200 | mvals.sort(usans.numeric_compare) |
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| 201 | for mval in mvals: |
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| 202 | xdata.append(mval) |
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| 203 | ydata.append(data[mval][0]) |
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| 204 | |
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| 205 | self.plot = axes.plot(xdata,ydata, 'bo', picker=5) |
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| 206 | |
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| 207 | |
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| 208 | elif plottype == 'split': |
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| 209 | xdata = [] |
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| 210 | ydata1 = [] |
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| 211 | ydata2 = [] |
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| 212 | ydata3 = [] |
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| 213 | ydata4 = [] |
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| 214 | ydata5 = [] |
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| 215 | |
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| 216 | mvals = data.keys() |
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| 217 | mvals.sort(usans.numeric_compare) |
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| 218 | for mval in mvals: |
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| 219 | xdata.append(mval) |
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| 220 | ydata1.append(data[mval][1]) |
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| 221 | ydata2.append(data[mval][2]) |
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| 222 | ydata3.append(data[mval][4]) |
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| 223 | ydata4.append(data[mval][5]) |
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| 224 | ydata5.append(data[mval][6]) |
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| 225 | |
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| 226 | self.plot = axes.plot(xdata,ydata1, 'o', |
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| 227 | xdata,ydata2, 'o', |
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| 228 | xdata,ydata3, 'o', |
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| 229 | xdata,ydata4, 'o', |
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| 230 | xdata,ydata5, 'o') |
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| 231 | |
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| 232 | def remove_plot(self): |
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| 233 | |
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| 234 | for line in self.plot: |
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| 235 | axes = line.get_axes() |
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| 236 | axes.lines.remove(line) |
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