[2613] | 1 | from asap.scantable import scantable |
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| 2 | from asap._asap import _edgemarker |
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[2635] | 3 | import numpy |
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| 4 | import math |
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| 5 | |
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[2613] | 6 | class edgemarker: |
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| 7 | """ |
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| 8 | The edgemarker is a helper tool to calibrate OTF observation |
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| 9 | without explicit OFF scans. According to a few user-specified |
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| 10 | options, the class automatically detects an edge region of the |
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| 11 | map and mark integrations within this region as OFF. |
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| 12 | |
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| 13 | The edgemarker supports raster pattern as well as other generic |
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| 14 | ones (e.g. lissajous, double circle). The constructor takes |
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| 15 | one boolean parameter to specify whether scan pattern is raster |
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| 16 | or not. This is because that edge detection algorithms for raster |
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| 17 | and others are different. |
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| 18 | |
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| 19 | Current limitation of this class is that it cannot handle some |
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| 20 | complicated observed area. Typical case is that the area has |
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| 21 | clear 'dent' (e.g. a composite area consisting of two diamond- |
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[2616] | 22 | shaped areas that slightly overlap). In such case, the class |
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[2613] | 23 | will fail to detect such feature. |
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| 24 | |
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| 25 | Note that the class takes a copy of input data so that input |
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| 26 | data will not be overwritten. Result will be provided as a |
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| 27 | separate data whose contents are essentially the same as input |
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| 28 | except for that some integrations are marked as OFF. |
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| 29 | |
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| 30 | Here is typical usage: |
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| 31 | |
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| 32 | s = scantable( 'otf.asap', average=False ) |
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| 33 | marker = edgemarker( israster=False ) |
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| 34 | marker.setdata( s ) |
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| 35 | marker.setoption( fraction='15%', width=0.5 ) |
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| 36 | marker.mark() |
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| 37 | |
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| 38 | # get result as scantable instance |
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| 39 | s2 = marker.getresult() |
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| 40 | |
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| 41 | # save result on disk |
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| 42 | marker.save( 'otfwithoff.asap', overwrite=True ) |
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| 43 | """ |
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| 44 | def __init__( self, israster=False ): |
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| 45 | """ |
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| 46 | Constructor. |
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| 47 | |
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| 48 | israster -- Whether scan pattern is raster or not. Set True |
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| 49 | if scan pattern is raster. Default is False. |
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| 50 | """ |
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| 51 | self.israster = israster |
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| 52 | self.marker = _edgemarker( self.israster ) |
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| 53 | self.st = None |
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| 54 | |
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| 55 | def setdata( self, st ): |
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| 56 | """ |
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| 57 | Set data to be processed. |
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| 58 | |
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| 59 | st -- Data as scantable instance. |
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| 60 | """ |
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| 61 | self.st = st |
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| 62 | self.marker._setdata( self.st, False ) |
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| 63 | self.marker._examine() |
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| 64 | |
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| 65 | def setoption( self, *args, **kwargs ): |
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| 66 | """ |
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| 67 | Set options for edge detection. Valid options depend on |
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[2616] | 68 | whether scan pattern is raster or not (i.e. constructor |
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| 69 | is called with israster=True or False). |
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[2613] | 70 | |
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[2616] | 71 | === for raster (israster=True) === |
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[2613] | 72 | fraction -- Fraction of OFF integration in each raster |
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| 73 | row. Either numerical value (<1.0) or string |
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| 74 | is accepted. For string, its value should be |
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| 75 | 'auto' or format 'xx%'. For example, '10%' |
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| 76 | is same as 0.1. The 'auto' option estimates |
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| 77 | number of OFFs based on t_OFF = sqrt(N) t_ON. |
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| 78 | Default is 0.1. |
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| 79 | npts -- Number of OFF integration in each raster row. |
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| 80 | Default is -1 (use fraction). |
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| 81 | |
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| 82 | Note that number of integrations specified by the above |
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| 83 | parameters will be marked as OFF from both ends. So, twice |
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| 84 | of specified number/fraction will be marked as OFF. For |
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| 85 | example, if you specify fraction='10%', resultant fraction |
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| 86 | of OFF integrations will be 20%. |
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| 87 | |
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| 88 | Note also that, if both fraction and npts are specified, |
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| 89 | specification by npts will come before. |
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| 90 | |
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[2616] | 91 | === for non-raster (israster=False) === |
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[2613] | 92 | fraction -- Fraction of edge area with respect to whole |
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| 93 | observed area. Either numerical value (<1.0) |
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| 94 | or string is accepted. For string, its value |
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| 95 | should be in 'xx%' format. For example, '10%' |
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| 96 | is same as 0.1. Default is 0.1. |
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| 97 | width -- Pixel width for edge detection. It should be given |
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[2616] | 98 | as a fraction of the median spatial separation |
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| 99 | between neighboring integrations in time. Default |
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| 100 | is 0.5. In the most case, default value will be fine. |
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| 101 | Larger value will cause worse result. Smaller value |
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| 102 | may improve result. However, if too small value is |
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| 103 | set (e.g. 1.0e-5), the algorithm may not work. |
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[2613] | 104 | elongated -- Set True only if observed area is extremely |
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| 105 | elongated in one direction. Default is False. |
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| 106 | In most cases, default value will be fine. |
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| 107 | """ |
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| 108 | option = {} |
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| 109 | if self.israster: |
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| 110 | keys = [ 'fraction', 'npts' ] |
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| 111 | else: |
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| 112 | keys = [ 'fraction', 'width', 'elongated' ] |
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| 113 | for key in keys: |
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| 114 | if kwargs.has_key( key ): |
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| 115 | option[key] = kwargs[key] |
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| 116 | |
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| 117 | if len(option) > 0: |
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| 118 | self.marker._setoption( option ) |
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| 119 | |
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| 120 | def mark( self ): |
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| 121 | """ |
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| 122 | Process data. Edge region is detected according to detection |
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| 123 | parameters given by setoption(). Then, integrations within |
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| 124 | edge region will be marked as OFF. |
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| 125 | """ |
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| 126 | self.marker._detect() |
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| 127 | self.marker._mark() |
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| 128 | |
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| 129 | def getresult( self ): |
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| 130 | """ |
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| 131 | Get result as scantable instance. Returned scantable is |
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| 132 | copy of input scantable except for that some data are |
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| 133 | marked as OFF as a result of edge detection and marking. |
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| 134 | """ |
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| 135 | return scantable( self.marker._get() ) |
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| 136 | |
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| 137 | def save( self, name, overwrite=False ): |
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| 138 | """ |
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| 139 | Save result as scantable. |
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| 140 | |
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| 141 | name -- Name of the scantable. |
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| 142 | overwrite -- Overwrite existing data if True. Default is |
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| 143 | False. |
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| 144 | """ |
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| 145 | s = self.getresult() |
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| 146 | s.save( name, overwrite=overwrite ) |
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[2635] | 147 | |
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| 148 | def plot( self ): |
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| 149 | """ |
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| 150 | """ |
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| 151 | from matplotlib import pylab as pl |
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| 152 | from asap import selector |
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| 153 | from asap._asap import srctype as st |
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| 154 | pl.clf() |
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| 155 | |
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| 156 | # result as a scantable |
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| 157 | s = self.getresult() |
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| 158 | |
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| 159 | # ON scan |
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| 160 | sel = selector() |
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| 161 | sel.set_types( int(st.pson) ) |
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| 162 | s.set_selection( sel ) |
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| 163 | diron = numpy.array( s.get_directionval() ).transpose() |
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| 164 | diron[0] = rotate( diron[0] ) |
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| 165 | s.set_selection() |
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| 166 | sel.reset() |
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| 167 | |
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| 168 | # OFF scan |
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| 169 | sel.set_types( int(st.psoff) ) |
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| 170 | s.set_selection( sel ) |
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| 171 | diroff = numpy.array( s.get_directionval() ).transpose() |
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| 172 | diroff[0] = rotate( diroff[0] ) |
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| 173 | s.set_selection() |
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| 174 | sel.reset() |
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| 175 | del s |
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| 176 | del sel |
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| 177 | |
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| 178 | # plot |
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| 179 | pl.ioff() |
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| 180 | ax=pl.axes() |
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| 181 | ax.set_aspect(1.0) |
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| 182 | pl.plot( diron[0], diron[1], '.', color='blue', label='ON' ) |
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| 183 | pl.plot( diroff[0], diroff[1], '.', color='green', label='OFF' ) |
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| 184 | [xmin,xmax,ymin,ymax] = pl.axis() |
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| 185 | pl.axis([xmax,xmin,ymin,ymax]) |
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| 186 | pl.legend(loc='best',prop={'size':'small'},numpoints=1) |
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| 187 | pl.xlabel( 'R.A. [rad]' ) |
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| 188 | pl.ylabel( 'Declination [rad]' ) |
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| 189 | pl.title( 'edgemarker result' ) |
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| 190 | pl.ion() |
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| 191 | pl.draw() |
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| 192 | |
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| 193 | def _0to2pi( v ): |
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| 194 | return v % (2.0*math.pi) |
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| 195 | |
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| 196 | def quadrant( v ): |
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| 197 | vl = _0to2pi( v ) |
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| 198 | base = 0.5 * math.pi |
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| 199 | return int( vl / base ) |
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| 200 | |
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| 201 | def quadrantList( a ): |
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| 202 | n = len(a) |
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| 203 | nquad = numpy.zeros( 4, dtype=int ) |
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| 204 | for i in xrange(n): |
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| 205 | v = quadrant( a[i] ) |
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| 206 | nquad[v] += 1 |
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| 207 | #print nquad |
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| 208 | return nquad |
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| 209 | |
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| 210 | def rotate( v ): |
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| 211 | a = numpy.zeros( len(v), dtype=float ) |
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| 212 | for i in xrange(len(v)): |
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| 213 | a[i] = _0to2pi( v[i] ) |
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| 214 | nquad = quadrantList( a ) |
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| 215 | quadList = [[],[],[],[]] |
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| 216 | rot = numpy.zeros( 4, dtype=bool ) |
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| 217 | if all( nquad==0 ): |
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| 218 | print 'no data' |
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| 219 | elif all( nquad>0 ): |
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| 220 | #print 'extends in all quadrants' |
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| 221 | pass |
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| 222 | elif nquad[0]>0 and nquad[3]>0: |
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| 223 | #print 'need rotation' |
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| 224 | rot[3] = True |
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| 225 | rot[2] = nquad[1]==0 and nquad[2]>0 |
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| 226 | #print rot |
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| 227 | |
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| 228 | for i in xrange(len(a)): |
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| 229 | if rot[quadrant(a[i])]: |
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| 230 | a[i] -= 2*math.pi |
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| 231 | return a |
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