| @@ -1,1728 +1,1736 | |||||
| 1 | ''' |
|
1 | ''' | |
| 2 | Created on Jul 9, 2014 |
|
2 | Created on Jul 9, 2014 | |
| 3 |
|
3 | |||
| 4 | @author: roj-idl71 |
|
4 | @author: roj-idl71 | |
| 5 | ''' |
|
5 | ''' | |
| 6 | import os |
|
6 | import os | |
| 7 | import datetime |
|
7 | import datetime | |
| 8 | import numpy |
|
8 | import numpy | |
| 9 |
|
9 | |||
| 10 | from figure import Figure, isRealtime, isTimeInHourRange |
|
10 | from figure import Figure, isRealtime, isTimeInHourRange | |
| 11 | from plotting_codes import * |
|
11 | from plotting_codes import * | |
| 12 |
|
12 | |||
| 13 |
|
13 | |||
| 14 | class SpectraPlot(Figure): |
|
14 | class SpectraPlot(Figure): | |
| 15 |
|
15 | |||
| 16 | isConfig = None |
|
16 | isConfig = None | |
| 17 | __nsubplots = None |
|
17 | __nsubplots = None | |
| 18 |
|
18 | |||
| 19 | WIDTHPROF = None |
|
19 | WIDTHPROF = None | |
| 20 | HEIGHTPROF = None |
|
20 | HEIGHTPROF = None | |
| 21 | PREFIX = 'spc' |
|
21 | PREFIX = 'spc' | |
| 22 |
|
22 | |||
| 23 | def __init__(self, **kwargs): |
|
23 | def __init__(self, **kwargs): | |
| 24 | Figure.__init__(self, **kwargs) |
|
24 | Figure.__init__(self, **kwargs) | |
| 25 | self.isConfig = False |
|
25 | self.isConfig = False | |
| 26 | self.__nsubplots = 1 |
|
26 | self.__nsubplots = 1 | |
| 27 |
|
27 | |||
| 28 | self.WIDTH = 250 |
|
28 | self.WIDTH = 250 | |
| 29 | self.HEIGHT = 250 |
|
29 | self.HEIGHT = 250 | |
| 30 | self.WIDTHPROF = 120 |
|
30 | self.WIDTHPROF = 120 | |
| 31 | self.HEIGHTPROF = 0 |
|
31 | self.HEIGHTPROF = 0 | |
| 32 | self.counter_imagwr = 0 |
|
32 | self.counter_imagwr = 0 | |
| 33 |
|
33 | |||
| 34 | self.PLOT_CODE = SPEC_CODE |
|
34 | self.PLOT_CODE = SPEC_CODE | |
| 35 |
|
35 | |||
| 36 | self.FTP_WEI = None |
|
36 | self.FTP_WEI = None | |
| 37 | self.EXP_CODE = None |
|
37 | self.EXP_CODE = None | |
| 38 | self.SUB_EXP_CODE = None |
|
38 | self.SUB_EXP_CODE = None | |
| 39 | self.PLOT_POS = None |
|
39 | self.PLOT_POS = None | |
| 40 |
|
40 | |||
| 41 | self.__xfilter_ena = False |
|
41 | self.__xfilter_ena = False | |
| 42 | self.__yfilter_ena = False |
|
42 | self.__yfilter_ena = False | |
| 43 |
|
43 | |||
| 44 | def getSubplots(self): |
|
44 | def getSubplots(self): | |
| 45 |
|
45 | |||
| 46 | ncol = int(numpy.sqrt(self.nplots)+0.9) |
|
46 | ncol = int(numpy.sqrt(self.nplots)+0.9) | |
| 47 | nrow = int(self.nplots*1./ncol + 0.9) |
|
47 | nrow = int(self.nplots*1./ncol + 0.9) | |
| 48 |
|
48 | |||
| 49 | return nrow, ncol |
|
49 | return nrow, ncol | |
| 50 |
|
50 | |||
| 51 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
51 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): | |
| 52 |
|
52 | |||
| 53 | self.__showprofile = showprofile |
|
53 | self.__showprofile = showprofile | |
| 54 | self.nplots = nplots |
|
54 | self.nplots = nplots | |
| 55 |
|
55 | |||
| 56 | ncolspan = 1 |
|
56 | ncolspan = 1 | |
| 57 | colspan = 1 |
|
57 | colspan = 1 | |
| 58 | if showprofile: |
|
58 | if showprofile: | |
| 59 | ncolspan = 3 |
|
59 | ncolspan = 3 | |
| 60 | colspan = 2 |
|
60 | colspan = 2 | |
| 61 | self.__nsubplots = 2 |
|
61 | self.__nsubplots = 2 | |
| 62 |
|
62 | |||
| 63 | self.createFigure(id = id, |
|
63 | self.createFigure(id = id, | |
| 64 | wintitle = wintitle, |
|
64 | wintitle = wintitle, | |
| 65 | widthplot = self.WIDTH + self.WIDTHPROF, |
|
65 | widthplot = self.WIDTH + self.WIDTHPROF, | |
| 66 | heightplot = self.HEIGHT + self.HEIGHTPROF, |
|
66 | heightplot = self.HEIGHT + self.HEIGHTPROF, | |
| 67 | show=show) |
|
67 | show=show) | |
| 68 |
|
68 | |||
| 69 | nrow, ncol = self.getSubplots() |
|
69 | nrow, ncol = self.getSubplots() | |
| 70 |
|
70 | |||
| 71 | counter = 0 |
|
71 | counter = 0 | |
| 72 | for y in range(nrow): |
|
72 | for y in range(nrow): | |
| 73 | for x in range(ncol): |
|
73 | for x in range(ncol): | |
| 74 |
|
74 | |||
| 75 | if counter >= self.nplots: |
|
75 | if counter >= self.nplots: | |
| 76 | break |
|
76 | break | |
| 77 |
|
77 | |||
| 78 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
78 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) | |
| 79 |
|
79 | |||
| 80 | if showprofile: |
|
80 | if showprofile: | |
| 81 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) |
|
81 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) | |
| 82 |
|
82 | |||
| 83 | counter += 1 |
|
83 | counter += 1 | |
| 84 |
|
84 | |||
| 85 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile=True, |
|
85 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile=True, | |
| 86 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, |
|
86 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, | |
| 87 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, |
|
87 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, | |
| 88 | server=None, folder=None, username=None, password=None, |
|
88 | server=None, folder=None, username=None, password=None, | |
| 89 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, realtime=False, |
|
89 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, realtime=False, | |
| 90 | xaxis="frequency", colormap='jet', normFactor=None): |
|
90 | xaxis="frequency", colormap='jet', normFactor=None): | |
| 91 |
|
91 | |||
| 92 | """ |
|
92 | """ | |
| 93 |
|
93 | |||
| 94 | Input: |
|
94 | Input: | |
| 95 | dataOut : |
|
95 | dataOut : | |
| 96 | id : |
|
96 | id : | |
| 97 | wintitle : |
|
97 | wintitle : | |
| 98 | channelList : |
|
98 | channelList : | |
| 99 | showProfile : |
|
99 | showProfile : | |
| 100 | xmin : None, |
|
100 | xmin : None, | |
| 101 | xmax : None, |
|
101 | xmax : None, | |
| 102 | ymin : None, |
|
102 | ymin : None, | |
| 103 | ymax : None, |
|
103 | ymax : None, | |
| 104 | zmin : None, |
|
104 | zmin : None, | |
| 105 | zmax : None |
|
105 | zmax : None | |
| 106 | """ |
|
106 | """ | |
| 107 | if realtime: |
|
107 | if realtime: | |
| 108 | if not(isRealtime(utcdatatime = dataOut.utctime)): |
|
108 | if not(isRealtime(utcdatatime = dataOut.utctime)): | |
| 109 | print 'Skipping this plot function' |
|
109 | print 'Skipping this plot function' | |
| 110 | return |
|
110 | return | |
| 111 |
|
111 | |||
| 112 | if channelList == None: |
|
112 | if channelList == None: | |
| 113 | channelIndexList = dataOut.channelIndexList |
|
113 | channelIndexList = dataOut.channelIndexList | |
| 114 | else: |
|
114 | else: | |
| 115 | channelIndexList = [] |
|
115 | channelIndexList = [] | |
| 116 | for channel in channelList: |
|
116 | for channel in channelList: | |
| 117 | if channel not in dataOut.channelList: |
|
117 | if channel not in dataOut.channelList: | |
| 118 | raise ValueError, "Channel %d is not in dataOut.channelList" %channel |
|
118 | raise ValueError, "Channel %d is not in dataOut.channelList" %channel | |
| 119 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
119 | channelIndexList.append(dataOut.channelList.index(channel)) | |
| 120 |
|
120 | |||
| 121 | if normFactor is None: |
|
121 | if normFactor is None: | |
| 122 | factor = dataOut.normFactor |
|
122 | factor = dataOut.normFactor | |
| 123 | else: |
|
123 | else: | |
| 124 | factor = normFactor |
|
124 | factor = normFactor | |
| 125 | if xaxis == "frequency": |
|
125 | if xaxis == "frequency": | |
| 126 | x = dataOut.getFreqRange(1)/1000. |
|
126 | x = dataOut.getFreqRange(1)/1000. | |
| 127 | xlabel = "Frequency (kHz)" |
|
127 | xlabel = "Frequency (kHz)" | |
| 128 |
|
128 | |||
| 129 | elif xaxis == "time": |
|
129 | elif xaxis == "time": | |
| 130 | x = dataOut.getAcfRange(1) |
|
130 | x = dataOut.getAcfRange(1) | |
| 131 | xlabel = "Time (ms)" |
|
131 | xlabel = "Time (ms)" | |
| 132 |
|
132 | |||
| 133 | else: |
|
133 | else: | |
| 134 | x = dataOut.getVelRange(1) |
|
134 | x = dataOut.getVelRange(1) | |
| 135 | xlabel = "Velocity (m/s)" |
|
135 | xlabel = "Velocity (m/s)" | |
| 136 |
|
136 | |||
| 137 | ylabel = "Range (Km)" |
|
137 | ylabel = "Range (Km)" | |
| 138 |
|
138 | |||
| 139 | y = dataOut.getHeiRange() |
|
139 | y = dataOut.getHeiRange() | |
| 140 |
|
140 | |||
| 141 | z = dataOut.data_spc/factor |
|
141 | z = dataOut.data_spc/factor | |
| 142 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
142 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | |
| 143 | zdB = 10*numpy.log10(z) |
|
143 | zdB = 10*numpy.log10(z) | |
| 144 |
|
144 | |||
| 145 | #print "a000",dataOut.data_spc.dtype |
|
145 | #print "a000",dataOut.data_spc.dtype | |
| 146 | avg = numpy.average(z, axis=1) |
|
146 | avg = numpy.average(z, axis=1) | |
| 147 | avgdB = 10*numpy.log10(avg) |
|
147 | avgdB = 10*numpy.log10(avg) | |
| 148 | #print "before plot" |
|
148 | #print "before plot" | |
| 149 | noise = dataOut.getNoise()/factor |
|
149 | noise = dataOut.getNoise()/factor | |
| 150 | noisedB = 10*numpy.log10(noise) |
|
150 | noisedB = 10*numpy.log10(noise) | |
| 151 |
|
151 | |||
| 152 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) |
|
152 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) | |
| 153 | title = wintitle + " Spectra" |
|
153 | title = wintitle + " Spectra" | |
| 154 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): |
|
154 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): | |
| 155 | title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith) |
|
155 | title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith) | |
| 156 |
|
156 | |||
| 157 | if not self.isConfig: |
|
157 | if not self.isConfig: | |
| 158 |
|
158 | |||
| 159 | nplots = len(channelIndexList) |
|
159 | nplots = len(channelIndexList) | |
| 160 |
|
160 | |||
| 161 | self.setup(id=id, |
|
161 | self.setup(id=id, | |
| 162 | nplots=nplots, |
|
162 | nplots=nplots, | |
| 163 | wintitle=wintitle, |
|
163 | wintitle=wintitle, | |
| 164 | showprofile=showprofile, |
|
164 | showprofile=showprofile, | |
| 165 | show=show) |
|
165 | show=show) | |
| 166 |
|
166 | |||
| 167 | if xmin == None: xmin = numpy.nanmin(x) |
|
167 | if xmin == None: xmin = numpy.nanmin(x) | |
| 168 | if xmax == None: xmax = numpy.nanmax(x) |
|
168 | if xmax == None: xmax = numpy.nanmax(x) | |
| 169 | if ymin == None: ymin = numpy.nanmin(y) |
|
169 | if ymin == None: ymin = numpy.nanmin(y) | |
| 170 | if ymax == None: ymax = numpy.nanmax(y) |
|
170 | if ymax == None: ymax = numpy.nanmax(y) | |
| 171 | if zmin == None: zmin = numpy.floor(numpy.nanmin(noisedB)) - 3 |
|
171 | if zmin == None: zmin = numpy.floor(numpy.nanmin(noisedB)) - 3 | |
| 172 | if zmax == None: zmax = numpy.ceil(numpy.nanmax(avgdB)) + 3 |
|
172 | if zmax == None: zmax = numpy.ceil(numpy.nanmax(avgdB)) + 3 | |
| 173 |
|
173 | |||
| 174 | self.FTP_WEI = ftp_wei |
|
174 | self.FTP_WEI = ftp_wei | |
| 175 | self.EXP_CODE = exp_code |
|
175 | self.EXP_CODE = exp_code | |
| 176 | self.SUB_EXP_CODE = sub_exp_code |
|
176 | self.SUB_EXP_CODE = sub_exp_code | |
| 177 | self.PLOT_POS = plot_pos |
|
177 | self.PLOT_POS = plot_pos | |
| 178 |
|
178 | |||
| 179 | self.isConfig = True |
|
179 | self.isConfig = True | |
| 180 |
|
180 | |||
| 181 | self.setWinTitle(title) |
|
181 | self.setWinTitle(title) | |
| 182 |
|
182 | |||
| 183 | for i in range(self.nplots): |
|
183 | for i in range(self.nplots): | |
| 184 | index = channelIndexList[i] |
|
184 | index = channelIndexList[i] | |
| 185 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) |
|
185 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) | |
| 186 | title = "Channel %d: %4.2fdB: %s" %(dataOut.channelList[index], noisedB[index], str_datetime) |
|
186 | title = "Channel %d: %4.2fdB: %s" %(dataOut.channelList[index], noisedB[index], str_datetime) | |
| 187 | if len(dataOut.beam.codeList) != 0: |
|
187 | if len(dataOut.beam.codeList) != 0: | |
| 188 | title = "Ch%d:%4.2fdB,%2.2f,%2.2f:%s" %(dataOut.channelList[index], noisedB[index], dataOut.beam.azimuthList[index], dataOut.beam.zenithList[index], str_datetime) |
|
188 | title = "Ch%d:%4.2fdB,%2.2f,%2.2f:%s" %(dataOut.channelList[index], noisedB[index], dataOut.beam.azimuthList[index], dataOut.beam.zenithList[index], str_datetime) | |
| 189 |
|
189 | |||
| 190 | axes = self.axesList[i*self.__nsubplots] |
|
190 | axes = self.axesList[i*self.__nsubplots] | |
| 191 | axes.pcolor(x, y, zdB[index,:,:], |
|
191 | axes.pcolor(x, y, zdB[index,:,:], | |
| 192 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, |
|
192 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, | |
| 193 | xlabel=xlabel, ylabel=ylabel, title=title, colormap=colormap, |
|
193 | xlabel=xlabel, ylabel=ylabel, title=title, colormap=colormap, | |
| 194 | ticksize=9, cblabel='') |
|
194 | ticksize=9, cblabel='') | |
| 195 |
|
195 | |||
| 196 | if self.__showprofile: |
|
196 | if self.__showprofile: | |
| 197 | axes = self.axesList[i*self.__nsubplots +1] |
|
197 | axes = self.axesList[i*self.__nsubplots +1] | |
| 198 | axes.pline(avgdB[index,:], y, |
|
198 | axes.pline(avgdB[index,:], y, | |
| 199 | xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax, |
|
199 | xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax, | |
| 200 | xlabel='dB', ylabel='', title='', |
|
200 | xlabel='dB', ylabel='', title='', | |
| 201 | ytick_visible=False, |
|
201 | ytick_visible=False, | |
| 202 | grid='x') |
|
202 | grid='x') | |
| 203 |
|
203 | |||
| 204 | noiseline = numpy.repeat(noisedB[index], len(y)) |
|
204 | noiseline = numpy.repeat(noisedB[index], len(y)) | |
| 205 | axes.addpline(noiseline, y, idline=1, color="black", linestyle="dashed", lw=2) |
|
205 | axes.addpline(noiseline, y, idline=1, color="black", linestyle="dashed", lw=2) | |
| 206 |
|
206 | |||
| 207 | self.draw() |
|
207 | self.draw() | |
| 208 |
|
208 | |||
| 209 | if figfile == None: |
|
209 | if figfile == None: | |
| 210 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
210 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 211 | name = str_datetime |
|
211 | name = str_datetime | |
| 212 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): |
|
212 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): | |
| 213 | name = name + '_az' + '_%2.2f'%(dataOut.azimuth) + '_zn' + '_%2.2f'%(dataOut.zenith) |
|
213 | name = name + '_az' + '_%2.2f'%(dataOut.azimuth) + '_zn' + '_%2.2f'%(dataOut.zenith) | |
| 214 | figfile = self.getFilename(name) |
|
214 | figfile = self.getFilename(name) | |
| 215 |
|
215 | |||
| 216 | self.save(figpath=figpath, |
|
216 | self.save(figpath=figpath, | |
| 217 | figfile=figfile, |
|
217 | figfile=figfile, | |
| 218 | save=save, |
|
218 | save=save, | |
| 219 | ftp=ftp, |
|
219 | ftp=ftp, | |
| 220 | wr_period=wr_period, |
|
220 | wr_period=wr_period, | |
| 221 | thisDatetime=thisDatetime) |
|
221 | thisDatetime=thisDatetime) | |
| 222 |
|
222 | |||
| 223 | class ACFPlot(Figure): |
|
223 | class ACFPlot(Figure): | |
| 224 |
|
224 | |||
| 225 | isConfig = None |
|
225 | isConfig = None | |
| 226 | __nsubplots = None |
|
226 | __nsubplots = None | |
| 227 |
|
227 | |||
| 228 | WIDTHPROF = None |
|
228 | WIDTHPROF = None | |
| 229 | HEIGHTPROF = None |
|
229 | HEIGHTPROF = None | |
| 230 | PREFIX = 'acf' |
|
230 | PREFIX = 'acf' | |
| 231 |
|
231 | |||
| 232 | def __init__(self, **kwargs): |
|
232 | def __init__(self, **kwargs): | |
| 233 | Figure.__init__(self, **kwargs) |
|
233 | Figure.__init__(self, **kwargs) | |
| 234 | self.isConfig = False |
|
234 | self.isConfig = False | |
| 235 | self.__nsubplots = 1 |
|
235 | self.__nsubplots = 1 | |
| 236 |
|
236 | |||
| 237 | self.PLOT_CODE = ACF_CODE |
|
237 | self.PLOT_CODE = ACF_CODE | |
| 238 |
|
238 | |||
| 239 | self.WIDTH = 900 |
|
239 | self.WIDTH = 900 | |
| 240 | self.HEIGHT = 700 |
|
240 | self.HEIGHT = 700 | |
| 241 | self.counter_imagwr = 0 |
|
241 | self.counter_imagwr = 0 | |
| 242 |
|
242 | |||
| 243 | def getSubplots(self): |
|
243 | def getSubplots(self): | |
| 244 | ncol = 1 |
|
244 | ncol = 1 | |
| 245 | nrow = 1 |
|
245 | nrow = 1 | |
| 246 |
|
246 | |||
| 247 | return nrow, ncol |
|
247 | return nrow, ncol | |
| 248 |
|
248 | |||
| 249 | def setup(self, id, nplots, wintitle, show): |
|
249 | def setup(self, id, nplots, wintitle, show): | |
| 250 |
|
250 | |||
| 251 | self.nplots = nplots |
|
251 | self.nplots = nplots | |
| 252 |
|
252 | |||
| 253 | ncolspan = 1 |
|
253 | ncolspan = 1 | |
| 254 | colspan = 1 |
|
254 | colspan = 1 | |
| 255 |
|
255 | |||
| 256 | self.createFigure(id = id, |
|
256 | self.createFigure(id = id, | |
| 257 | wintitle = wintitle, |
|
257 | wintitle = wintitle, | |
| 258 | widthplot = self.WIDTH, |
|
258 | widthplot = self.WIDTH, | |
| 259 | heightplot = self.HEIGHT, |
|
259 | heightplot = self.HEIGHT, | |
| 260 | show=show) |
|
260 | show=show) | |
| 261 |
|
261 | |||
| 262 | nrow, ncol = self.getSubplots() |
|
262 | nrow, ncol = self.getSubplots() | |
| 263 |
|
263 | |||
| 264 | counter = 0 |
|
264 | counter = 0 | |
| 265 | for y in range(nrow): |
|
265 | for y in range(nrow): | |
| 266 | for x in range(ncol): |
|
266 | for x in range(ncol): | |
| 267 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
267 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) | |
| 268 |
|
268 | |||
| 269 | def run(self, dataOut, id, wintitle="", channelList=None,channel=None,nSamples=None, |
|
269 | def run(self, dataOut, id, wintitle="", channelList=None,channel=None,nSamples=None, | |
| 270 | nSampleList= None,resolutionFactor=None, |
|
270 | nSampleList= None,resolutionFactor=None, | |
| 271 | xmin=None, xmax=None, ymin=None, ymax=None, |
|
271 | xmin=None, xmax=None, ymin=None, ymax=None, | |
| 272 | save=False, figpath='./', figfile=None, show=True, |
|
272 | save=False, figpath='./', figfile=None, show=True, | |
| 273 | ftp=False, wr_period=1, server=None, |
|
273 | ftp=False, wr_period=1, server=None, | |
| 274 | folder=None, username=None, password=None, |
|
274 | folder=None, username=None, password=None, | |
| 275 | xaxis="frequency"): |
|
275 | xaxis="frequency"): | |
| 276 |
|
276 | |||
| 277 | channel0 = channel |
|
277 | channel0 = channel | |
| 278 | nSamples = nSamples |
|
278 | nSamples = nSamples | |
| 279 | resFactor = resolutionFactor |
|
279 | resFactor = resolutionFactor | |
| 280 |
|
280 | |||
| 281 | if nSamples == None: |
|
281 | if nSamples == None: | |
| 282 | nSamples = 20 |
|
282 | nSamples = 20 | |
| 283 |
|
283 | |||
| 284 | if resFactor == None: |
|
284 | if resFactor == None: | |
| 285 | resFactor = 5 |
|
285 | resFactor = 5 | |
| 286 | #else: |
|
286 | #else: | |
| 287 | # if nSamples not in dataOut.channelList: |
|
287 | # if nSamples not in dataOut.channelList: | |
| 288 | # raise ValueError, "Channel %d is not in %s dataOut.channelList"%(channel0, dataOut.channelList) |
|
288 | # raise ValueError, "Channel %d is not in %s dataOut.channelList"%(channel0, dataOut.channelList) | |
| 289 |
|
289 | |||
| 290 | if channel0 == None: |
|
290 | if channel0 == None: | |
| 291 | channel0 = 0 |
|
291 | channel0 = 0 | |
| 292 | else: |
|
292 | else: | |
| 293 | if channel0 not in dataOut.channelList: |
|
293 | if channel0 not in dataOut.channelList: | |
| 294 | raise ValueError, "Channel %d is not in %s dataOut.channelList"%(channel0, dataOut.channelList) |
|
294 | raise ValueError, "Channel %d is not in %s dataOut.channelList"%(channel0, dataOut.channelList) | |
| 295 |
|
295 | |||
| 296 | if channelList == None: |
|
296 | if channelList == None: | |
| 297 | channelIndexList = dataOut.channelIndexList |
|
297 | channelIndexList = dataOut.channelIndexList | |
| 298 | channelList = dataOut.channelList |
|
298 | channelList = dataOut.channelList | |
| 299 | else: |
|
299 | else: | |
| 300 | channelIndexList = [] |
|
300 | channelIndexList = [] | |
| 301 | for channel in channelList: |
|
301 | for channel in channelList: | |
| 302 | if channel not in dataOut.channelList: |
|
302 | if channel not in dataOut.channelList: | |
| 303 | raise ValueError, "Channel %d is not in dataOut.channelList" |
|
303 | raise ValueError, "Channel %d is not in dataOut.channelList" | |
| 304 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
304 | channelIndexList.append(dataOut.channelList.index(channel)) | |
| 305 |
|
305 | |||
| 306 | #z = dataOut.data_spc/factor |
|
306 | #z = dataOut.data_spc/factor | |
| 307 | factor = dataOut.normFactor |
|
307 | factor = dataOut.normFactor | |
| 308 | y = dataOut.getHeiRange() |
|
308 | y = dataOut.getHeiRange() | |
| 309 | deltaHeight = dataOut.heightList[1]-dataOut.heightList[0] |
|
309 | deltaHeight = dataOut.heightList[1]-dataOut.heightList[0] | |
| 310 | z = dataOut.data_acf |
|
310 | z = dataOut.data_acf | |
|
|
311 | ||||
|
|
312 | #import matplotlib.pyplot as plt | |||
|
|
313 | #plt.plot(z[0,:,85]) | |||
|
|
314 | #plt.show() | |||
|
|
315 | #import time | |||
|
|
316 | #time.sleep(20) | |||
|
|
317 | ||||
|
|
318 | ||||
| 311 | #z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
319 | #z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | |
| 312 | shape = dataOut.data_acf.shape |
|
320 | shape = dataOut.data_acf.shape | |
| 313 | hei_index = numpy.arange(shape[2]) |
|
321 | hei_index = numpy.arange(shape[2]) | |
| 314 | hei_plot = numpy.arange(nSamples)*resFactor |
|
322 | hei_plot = numpy.arange(nSamples)*resFactor | |
| 315 |
|
323 | |||
| 316 | if nSampleList is not None: |
|
324 | if nSampleList is not None: | |
| 317 | for nsample in nSampleList: |
|
325 | for nsample in nSampleList: | |
| 318 | if nsample not in dataOut.heightList/deltaHeight: |
|
326 | if nsample not in dataOut.heightList/deltaHeight: | |
| 319 | raise ValueError, "nsample %d is not in %s dataOut.heightList"%(nsample,dataOut.heightList) |
|
327 | raise ValueError, "nsample %d is not in %s dataOut.heightList"%(nsample,dataOut.heightList) | |
| 320 |
|
328 | |||
| 321 | if nSampleList is not None: |
|
329 | if nSampleList is not None: | |
| 322 | hei_plot = numpy.array(nSampleList)*resFactor |
|
330 | hei_plot = numpy.array(nSampleList)*resFactor | |
| 323 |
|
331 | |||
| 324 | if hei_plot[-1] >= hei_index[-1]: |
|
332 | if hei_plot[-1] >= hei_index[-1]: | |
| 325 | print ("La cantidad de puntos en altura es %d y la resolucion es %d Km"%(hei_plot.shape[0],deltaHeight*resFactor )) |
|
333 | print ("La cantidad de puntos en altura es %d y la resolucion es %d Km"%(hei_plot.shape[0],deltaHeight*resFactor )) | |
| 326 | raise ValueError, "resFactor %d multiplicado por el valor de %d nSamples es mayor a %d cantidad total de puntos"%(resFactor,nSamples,hei_index[-1]) |
|
334 | raise ValueError, "resFactor %d multiplicado por el valor de %d nSamples es mayor a %d cantidad total de puntos"%(resFactor,nSamples,hei_index[-1]) | |
| 327 |
|
335 | |||
| 328 | #escalamiento -1 a 1 a resolucion (factor de resolucion en altura)* deltaHeight |
|
336 | #escalamiento -1 a 1 a resolucion (factor de resolucion en altura)* deltaHeight | |
| 329 | min = numpy.min(z[0,:,0]) |
|
337 | min = numpy.min(z[0,:,0]) | |
| 330 | max =numpy.max(z[0,:,0]) |
|
338 | max =numpy.max(z[0,:,0]) | |
| 331 | for i in range(shape[0]): |
|
339 | for i in range(shape[0]): | |
| 332 | for j in range(shape[2]): |
|
340 | for j in range(shape[2]): | |
| 333 | z[i,:,j]= (((z[i,:,j]-min)/(max-min))*deltaHeight*resFactor + j*deltaHeight) |
|
341 | z[i,:,j]= (((z[i,:,j]-min)/(max-min))*deltaHeight*resFactor + j*deltaHeight) | |
| 334 |
|
342 | |||
| 335 | if xaxis == "frequency": |
|
343 | if xaxis == "frequency": | |
| 336 | x = dataOut.getFreqRange()/1000. |
|
344 | x = dataOut.getFreqRange()/1000. | |
| 337 | zdB = 10*numpy.log10(z[channel0,:,hei_plot]) |
|
345 | zdB = 10*numpy.log10(z[channel0,:,hei_plot]) | |
| 338 | xlabel = "Frequency (kHz)" |
|
346 | xlabel = "Frequency (kHz)" | |
| 339 | ylabel = "Power (dB)" |
|
347 | ylabel = "Power (dB)" | |
| 340 |
|
348 | |||
| 341 | elif xaxis == "time": |
|
349 | elif xaxis == "time": | |
| 342 | delta= dataOut.getAcfRange()[1]-dataOut.getAcfRange()[0] |
|
350 | delta= dataOut.getAcfRange()[1]-dataOut.getAcfRange()[0] | |
| 343 | x = dataOut.getAcfRange()+delta/2.0 |
|
351 | x = dataOut.getAcfRange()+delta/2.0 | |
| 344 | zdB = z[channel0,:,hei_plot] |
|
352 | zdB = z[channel0,:,hei_plot] | |
| 345 | xlabel = "Time (ms)" |
|
353 | xlabel = "Time (ms)" | |
| 346 | ylabel = "ACF" |
|
354 | ylabel = "ACF" | |
| 347 |
|
355 | |||
| 348 | else: |
|
356 | else: | |
| 349 | x = dataOut.getVelRange() |
|
357 | x = dataOut.getVelRange() | |
| 350 | zdB = 10*numpy.log10(z[channel0,:,hei_plot]) |
|
358 | zdB = 10*numpy.log10(z[channel0,:,hei_plot]) | |
| 351 | xlabel = "Velocity (m/s)" |
|
359 | xlabel = "Velocity (m/s)" | |
| 352 | ylabel = "Power (dB)" |
|
360 | ylabel = "Power (dB)" | |
| 353 |
|
361 | |||
| 354 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) |
|
362 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) | |
| 355 | title = wintitle + " ACF Plot Ch %s %s" %(channel0,thisDatetime.strftime("%d-%b-%Y")) |
|
363 | title = wintitle + " ACF Plot Ch %s %s" %(channel0,thisDatetime.strftime("%d-%b-%Y")) | |
| 356 |
|
364 | |||
| 357 | if not self.isConfig: |
|
365 | if not self.isConfig: | |
| 358 |
|
366 | |||
| 359 | nplots = 1 |
|
367 | nplots = 1 | |
| 360 |
|
368 | |||
| 361 | self.setup(id=id, |
|
369 | self.setup(id=id, | |
| 362 | nplots=nplots, |
|
370 | nplots=nplots, | |
| 363 | wintitle=wintitle, |
|
371 | wintitle=wintitle, | |
| 364 | show=show) |
|
372 | show=show) | |
| 365 |
|
373 | |||
| 366 | if xmin == None: xmin = numpy.nanmin(x)*0.9 |
|
374 | if xmin == None: xmin = numpy.nanmin(x)*0.9 | |
| 367 | if xmax == None: xmax = numpy.nanmax(x)*1.1 |
|
375 | if xmax == None: xmax = numpy.nanmax(x)*1.1 | |
| 368 | if ymin == None: ymin = numpy.nanmin(zdB) |
|
376 | if ymin == None: ymin = numpy.nanmin(zdB) | |
| 369 | if ymax == None: ymax = numpy.nanmax(zdB) |
|
377 | if ymax == None: ymax = numpy.nanmax(zdB) | |
| 370 |
|
378 | |||
| 371 | print ("El parametro resFactor es %d y la resolucion en altura es %d"%(resFactor,deltaHeight )) |
|
379 | print ("El parametro resFactor es %d y la resolucion en altura es %d"%(resFactor,deltaHeight )) | |
| 372 | print ("La cantidad de puntos en altura es %d y la nueva resolucion es %d Km"%(hei_plot.shape[0],deltaHeight*resFactor )) |
|
380 | print ("La cantidad de puntos en altura es %d y la nueva resolucion es %d Km"%(hei_plot.shape[0],deltaHeight*resFactor )) | |
| 373 | print ("La altura maxima es %d Km"%(hei_plot[-1]*deltaHeight )) |
|
381 | print ("La altura maxima es %d Km"%(hei_plot[-1]*deltaHeight )) | |
| 374 |
|
382 | |||
| 375 | self.isConfig = True |
|
383 | self.isConfig = True | |
| 376 |
|
384 | |||
| 377 | self.setWinTitle(title) |
|
385 | self.setWinTitle(title) | |
| 378 |
|
386 | |||
| 379 | title = "ACF Plot: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
387 | title = "ACF Plot: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
| 380 | axes = self.axesList[0] |
|
388 | axes = self.axesList[0] | |
| 381 |
|
389 | |||
| 382 | legendlabels = ["Range = %dKm" %y[i] for i in hei_plot] |
|
390 | legendlabels = ["Range = %dKm" %y[i] for i in hei_plot] | |
| 383 |
|
391 | |||
| 384 | axes.pmultilineyaxis( x, zdB, |
|
392 | axes.pmultilineyaxis( x, zdB, | |
| 385 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, |
|
393 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, | |
| 386 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, |
|
394 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, | |
| 387 | ytick_visible=True, nxticks=5, |
|
395 | ytick_visible=True, nxticks=5, | |
| 388 | grid='x') |
|
396 | grid='x') | |
| 389 |
|
397 | |||
| 390 | self.draw() |
|
398 | self.draw() | |
| 391 |
|
399 | |||
| 392 | if figfile == None: |
|
400 | if figfile == None: | |
| 393 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
401 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 394 | name = str_datetime |
|
402 | name = str_datetime | |
| 395 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): |
|
403 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): | |
| 396 | name = name + '_az' + '_%2.2f'%(dataOut.azimuth) + '_zn' + '_%2.2f'%(dataOut.zenith) |
|
404 | name = name + '_az' + '_%2.2f'%(dataOut.azimuth) + '_zn' + '_%2.2f'%(dataOut.zenith) | |
| 397 | figfile = self.getFilename(name) |
|
405 | figfile = self.getFilename(name) | |
| 398 |
|
406 | |||
| 399 | self.save(figpath=figpath, |
|
407 | self.save(figpath=figpath, | |
| 400 | figfile=figfile, |
|
408 | figfile=figfile, | |
| 401 | save=save, |
|
409 | save=save, | |
| 402 | ftp=ftp, |
|
410 | ftp=ftp, | |
| 403 | wr_period=wr_period, |
|
411 | wr_period=wr_period, | |
| 404 | thisDatetime=thisDatetime) |
|
412 | thisDatetime=thisDatetime) | |
| 405 |
|
413 | |||
| 406 |
|
414 | |||
| 407 |
|
415 | |||
| 408 | class CrossSpectraPlot(Figure): |
|
416 | class CrossSpectraPlot(Figure): | |
| 409 |
|
417 | |||
| 410 | isConfig = None |
|
418 | isConfig = None | |
| 411 | __nsubplots = None |
|
419 | __nsubplots = None | |
| 412 |
|
420 | |||
| 413 | WIDTH = None |
|
421 | WIDTH = None | |
| 414 | HEIGHT = None |
|
422 | HEIGHT = None | |
| 415 | WIDTHPROF = None |
|
423 | WIDTHPROF = None | |
| 416 | HEIGHTPROF = None |
|
424 | HEIGHTPROF = None | |
| 417 | PREFIX = 'cspc' |
|
425 | PREFIX = 'cspc' | |
| 418 |
|
426 | |||
| 419 | def __init__(self, **kwargs): |
|
427 | def __init__(self, **kwargs): | |
| 420 | Figure.__init__(self, **kwargs) |
|
428 | Figure.__init__(self, **kwargs) | |
| 421 | self.isConfig = False |
|
429 | self.isConfig = False | |
| 422 | self.__nsubplots = 4 |
|
430 | self.__nsubplots = 4 | |
| 423 | self.counter_imagwr = 0 |
|
431 | self.counter_imagwr = 0 | |
| 424 | self.WIDTH = 250 |
|
432 | self.WIDTH = 250 | |
| 425 | self.HEIGHT = 250 |
|
433 | self.HEIGHT = 250 | |
| 426 | self.WIDTHPROF = 0 |
|
434 | self.WIDTHPROF = 0 | |
| 427 | self.HEIGHTPROF = 0 |
|
435 | self.HEIGHTPROF = 0 | |
| 428 |
|
436 | |||
| 429 | self.PLOT_CODE = CROSS_CODE |
|
437 | self.PLOT_CODE = CROSS_CODE | |
| 430 | self.FTP_WEI = None |
|
438 | self.FTP_WEI = None | |
| 431 | self.EXP_CODE = None |
|
439 | self.EXP_CODE = None | |
| 432 | self.SUB_EXP_CODE = None |
|
440 | self.SUB_EXP_CODE = None | |
| 433 | self.PLOT_POS = None |
|
441 | self.PLOT_POS = None | |
| 434 |
|
442 | |||
| 435 | def getSubplots(self): |
|
443 | def getSubplots(self): | |
| 436 |
|
444 | |||
| 437 | ncol = 4 |
|
445 | ncol = 4 | |
| 438 | nrow = self.nplots |
|
446 | nrow = self.nplots | |
| 439 |
|
447 | |||
| 440 | return nrow, ncol |
|
448 | return nrow, ncol | |
| 441 |
|
449 | |||
| 442 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
450 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): | |
| 443 |
|
451 | |||
| 444 | self.__showprofile = showprofile |
|
452 | self.__showprofile = showprofile | |
| 445 | self.nplots = nplots |
|
453 | self.nplots = nplots | |
| 446 |
|
454 | |||
| 447 | ncolspan = 1 |
|
455 | ncolspan = 1 | |
| 448 | colspan = 1 |
|
456 | colspan = 1 | |
| 449 |
|
457 | |||
| 450 | self.createFigure(id = id, |
|
458 | self.createFigure(id = id, | |
| 451 | wintitle = wintitle, |
|
459 | wintitle = wintitle, | |
| 452 | widthplot = self.WIDTH + self.WIDTHPROF, |
|
460 | widthplot = self.WIDTH + self.WIDTHPROF, | |
| 453 | heightplot = self.HEIGHT + self.HEIGHTPROF, |
|
461 | heightplot = self.HEIGHT + self.HEIGHTPROF, | |
| 454 | show=True) |
|
462 | show=True) | |
| 455 |
|
463 | |||
| 456 | nrow, ncol = self.getSubplots() |
|
464 | nrow, ncol = self.getSubplots() | |
| 457 |
|
465 | |||
| 458 | counter = 0 |
|
466 | counter = 0 | |
| 459 | for y in range(nrow): |
|
467 | for y in range(nrow): | |
| 460 | for x in range(ncol): |
|
468 | for x in range(ncol): | |
| 461 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
469 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) | |
| 462 |
|
470 | |||
| 463 | counter += 1 |
|
471 | counter += 1 | |
| 464 |
|
472 | |||
| 465 | def run(self, dataOut, id, wintitle="", pairsList=None, |
|
473 | def run(self, dataOut, id, wintitle="", pairsList=None, | |
| 466 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, |
|
474 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, | |
| 467 | coh_min=None, coh_max=None, phase_min=None, phase_max=None, |
|
475 | coh_min=None, coh_max=None, phase_min=None, phase_max=None, | |
| 468 | save=False, figpath='./', figfile=None, ftp=False, wr_period=1, |
|
476 | save=False, figpath='./', figfile=None, ftp=False, wr_period=1, | |
| 469 | power_cmap='jet', coherence_cmap='jet', phase_cmap='RdBu_r', show=True, |
|
477 | power_cmap='jet', coherence_cmap='jet', phase_cmap='RdBu_r', show=True, | |
| 470 | server=None, folder=None, username=None, password=None, |
|
478 | server=None, folder=None, username=None, password=None, | |
| 471 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, normFactor=None, |
|
479 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, normFactor=None, | |
| 472 | xaxis='frequency'): |
|
480 | xaxis='frequency'): | |
| 473 |
|
481 | |||
| 474 | """ |
|
482 | """ | |
| 475 |
|
483 | |||
| 476 | Input: |
|
484 | Input: | |
| 477 | dataOut : |
|
485 | dataOut : | |
| 478 | id : |
|
486 | id : | |
| 479 | wintitle : |
|
487 | wintitle : | |
| 480 | channelList : |
|
488 | channelList : | |
| 481 | showProfile : |
|
489 | showProfile : | |
| 482 | xmin : None, |
|
490 | xmin : None, | |
| 483 | xmax : None, |
|
491 | xmax : None, | |
| 484 | ymin : None, |
|
492 | ymin : None, | |
| 485 | ymax : None, |
|
493 | ymax : None, | |
| 486 | zmin : None, |
|
494 | zmin : None, | |
| 487 | zmax : None |
|
495 | zmax : None | |
| 488 | """ |
|
496 | """ | |
| 489 |
|
497 | |||
| 490 | if pairsList == None: |
|
498 | if pairsList == None: | |
| 491 | pairsIndexList = dataOut.pairsIndexList |
|
499 | pairsIndexList = dataOut.pairsIndexList | |
| 492 | else: |
|
500 | else: | |
| 493 | pairsIndexList = [] |
|
501 | pairsIndexList = [] | |
| 494 | for pair in pairsList: |
|
502 | for pair in pairsList: | |
| 495 | if pair not in dataOut.pairsList: |
|
503 | if pair not in dataOut.pairsList: | |
| 496 | raise ValueError, "Pair %s is not in dataOut.pairsList" %str(pair) |
|
504 | raise ValueError, "Pair %s is not in dataOut.pairsList" %str(pair) | |
| 497 | pairsIndexList.append(dataOut.pairsList.index(pair)) |
|
505 | pairsIndexList.append(dataOut.pairsList.index(pair)) | |
| 498 |
|
506 | |||
| 499 | if not pairsIndexList: |
|
507 | if not pairsIndexList: | |
| 500 | return |
|
508 | return | |
| 501 |
|
509 | |||
| 502 | if len(pairsIndexList) > 4: |
|
510 | if len(pairsIndexList) > 4: | |
| 503 | pairsIndexList = pairsIndexList[0:4] |
|
511 | pairsIndexList = pairsIndexList[0:4] | |
| 504 |
|
512 | |||
| 505 | if normFactor is None: |
|
513 | if normFactor is None: | |
| 506 | factor = dataOut.normFactor |
|
514 | factor = dataOut.normFactor | |
| 507 | else: |
|
515 | else: | |
| 508 | factor = normFactor |
|
516 | factor = normFactor | |
| 509 | x = dataOut.getVelRange(1) |
|
517 | x = dataOut.getVelRange(1) | |
| 510 | y = dataOut.getHeiRange() |
|
518 | y = dataOut.getHeiRange() | |
| 511 | z = dataOut.data_spc[:,:,:]/factor |
|
519 | z = dataOut.data_spc[:,:,:]/factor | |
| 512 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
520 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | |
| 513 |
|
521 | |||
| 514 | noise = dataOut.noise/factor |
|
522 | noise = dataOut.noise/factor | |
| 515 |
|
523 | |||
| 516 | zdB = 10*numpy.log10(z) |
|
524 | zdB = 10*numpy.log10(z) | |
| 517 | noisedB = 10*numpy.log10(noise) |
|
525 | noisedB = 10*numpy.log10(noise) | |
| 518 |
|
526 | |||
| 519 | if coh_min == None: |
|
527 | if coh_min == None: | |
| 520 | coh_min = 0.0 |
|
528 | coh_min = 0.0 | |
| 521 | if coh_max == None: |
|
529 | if coh_max == None: | |
| 522 | coh_max = 1.0 |
|
530 | coh_max = 1.0 | |
| 523 |
|
531 | |||
| 524 | if phase_min == None: |
|
532 | if phase_min == None: | |
| 525 | phase_min = -180 |
|
533 | phase_min = -180 | |
| 526 | if phase_max == None: |
|
534 | if phase_max == None: | |
| 527 | phase_max = 180 |
|
535 | phase_max = 180 | |
| 528 |
|
536 | |||
| 529 | #thisDatetime = dataOut.datatime |
|
537 | #thisDatetime = dataOut.datatime | |
| 530 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) |
|
538 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) | |
| 531 | title = wintitle + " Cross-Spectra: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
539 | title = wintitle + " Cross-Spectra: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
| 532 | # xlabel = "Velocity (m/s)" |
|
540 | # xlabel = "Velocity (m/s)" | |
| 533 | ylabel = "Range (Km)" |
|
541 | ylabel = "Range (Km)" | |
| 534 |
|
542 | |||
| 535 | if xaxis == "frequency": |
|
543 | if xaxis == "frequency": | |
| 536 | x = dataOut.getFreqRange(1)/1000. |
|
544 | x = dataOut.getFreqRange(1)/1000. | |
| 537 | xlabel = "Frequency (kHz)" |
|
545 | xlabel = "Frequency (kHz)" | |
| 538 |
|
546 | |||
| 539 | elif xaxis == "time": |
|
547 | elif xaxis == "time": | |
| 540 | x = dataOut.getAcfRange(1) |
|
548 | x = dataOut.getAcfRange(1) | |
| 541 | xlabel = "Time (ms)" |
|
549 | xlabel = "Time (ms)" | |
| 542 |
|
550 | |||
| 543 | else: |
|
551 | else: | |
| 544 | x = dataOut.getVelRange(1) |
|
552 | x = dataOut.getVelRange(1) | |
| 545 | xlabel = "Velocity (m/s)" |
|
553 | xlabel = "Velocity (m/s)" | |
| 546 |
|
554 | |||
| 547 | if not self.isConfig: |
|
555 | if not self.isConfig: | |
| 548 |
|
556 | |||
| 549 | nplots = len(pairsIndexList) |
|
557 | nplots = len(pairsIndexList) | |
| 550 |
|
558 | |||
| 551 | self.setup(id=id, |
|
559 | self.setup(id=id, | |
| 552 | nplots=nplots, |
|
560 | nplots=nplots, | |
| 553 | wintitle=wintitle, |
|
561 | wintitle=wintitle, | |
| 554 | showprofile=False, |
|
562 | showprofile=False, | |
| 555 | show=show) |
|
563 | show=show) | |
| 556 |
|
564 | |||
| 557 | avg = numpy.abs(numpy.average(z, axis=1)) |
|
565 | avg = numpy.abs(numpy.average(z, axis=1)) | |
| 558 | avgdB = 10*numpy.log10(avg) |
|
566 | avgdB = 10*numpy.log10(avg) | |
| 559 |
|
567 | |||
| 560 | if xmin == None: xmin = numpy.nanmin(x) |
|
568 | if xmin == None: xmin = numpy.nanmin(x) | |
| 561 | if xmax == None: xmax = numpy.nanmax(x) |
|
569 | if xmax == None: xmax = numpy.nanmax(x) | |
| 562 | if ymin == None: ymin = numpy.nanmin(y) |
|
570 | if ymin == None: ymin = numpy.nanmin(y) | |
| 563 | if ymax == None: ymax = numpy.nanmax(y) |
|
571 | if ymax == None: ymax = numpy.nanmax(y) | |
| 564 | if zmin == None: zmin = numpy.floor(numpy.nanmin(noisedB)) - 3 |
|
572 | if zmin == None: zmin = numpy.floor(numpy.nanmin(noisedB)) - 3 | |
| 565 | if zmax == None: zmax = numpy.ceil(numpy.nanmax(avgdB)) + 3 |
|
573 | if zmax == None: zmax = numpy.ceil(numpy.nanmax(avgdB)) + 3 | |
| 566 |
|
574 | |||
| 567 | self.FTP_WEI = ftp_wei |
|
575 | self.FTP_WEI = ftp_wei | |
| 568 | self.EXP_CODE = exp_code |
|
576 | self.EXP_CODE = exp_code | |
| 569 | self.SUB_EXP_CODE = sub_exp_code |
|
577 | self.SUB_EXP_CODE = sub_exp_code | |
| 570 | self.PLOT_POS = plot_pos |
|
578 | self.PLOT_POS = plot_pos | |
| 571 |
|
579 | |||
| 572 | self.isConfig = True |
|
580 | self.isConfig = True | |
| 573 |
|
581 | |||
| 574 | self.setWinTitle(title) |
|
582 | self.setWinTitle(title) | |
| 575 |
|
583 | |||
| 576 | for i in range(self.nplots): |
|
584 | for i in range(self.nplots): | |
| 577 | pair = dataOut.pairsList[pairsIndexList[i]] |
|
585 | pair = dataOut.pairsList[pairsIndexList[i]] | |
| 578 |
|
586 | |||
| 579 | chan_index0 = dataOut.channelList.index(pair[0]) |
|
587 | chan_index0 = dataOut.channelList.index(pair[0]) | |
| 580 | chan_index1 = dataOut.channelList.index(pair[1]) |
|
588 | chan_index1 = dataOut.channelList.index(pair[1]) | |
| 581 |
|
589 | |||
| 582 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) |
|
590 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) | |
| 583 | title = "Ch%d: %4.2fdB: %s" %(pair[0], noisedB[chan_index0], str_datetime) |
|
591 | title = "Ch%d: %4.2fdB: %s" %(pair[0], noisedB[chan_index0], str_datetime) | |
| 584 | zdB = 10.*numpy.log10(dataOut.data_spc[chan_index0,:,:]/factor) |
|
592 | zdB = 10.*numpy.log10(dataOut.data_spc[chan_index0,:,:]/factor) | |
| 585 | axes0 = self.axesList[i*self.__nsubplots] |
|
593 | axes0 = self.axesList[i*self.__nsubplots] | |
| 586 | axes0.pcolor(x, y, zdB, |
|
594 | axes0.pcolor(x, y, zdB, | |
| 587 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, |
|
595 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, | |
| 588 | xlabel=xlabel, ylabel=ylabel, title=title, |
|
596 | xlabel=xlabel, ylabel=ylabel, title=title, | |
| 589 | ticksize=9, colormap=power_cmap, cblabel='') |
|
597 | ticksize=9, colormap=power_cmap, cblabel='') | |
| 590 |
|
598 | |||
| 591 | title = "Ch%d: %4.2fdB: %s" %(pair[1], noisedB[chan_index1], str_datetime) |
|
599 | title = "Ch%d: %4.2fdB: %s" %(pair[1], noisedB[chan_index1], str_datetime) | |
| 592 | zdB = 10.*numpy.log10(dataOut.data_spc[chan_index1,:,:]/factor) |
|
600 | zdB = 10.*numpy.log10(dataOut.data_spc[chan_index1,:,:]/factor) | |
| 593 | axes0 = self.axesList[i*self.__nsubplots+1] |
|
601 | axes0 = self.axesList[i*self.__nsubplots+1] | |
| 594 | axes0.pcolor(x, y, zdB, |
|
602 | axes0.pcolor(x, y, zdB, | |
| 595 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, |
|
603 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, | |
| 596 | xlabel=xlabel, ylabel=ylabel, title=title, |
|
604 | xlabel=xlabel, ylabel=ylabel, title=title, | |
| 597 | ticksize=9, colormap=power_cmap, cblabel='') |
|
605 | ticksize=9, colormap=power_cmap, cblabel='') | |
| 598 |
|
606 | |||
| 599 | coherenceComplex = dataOut.data_cspc[pairsIndexList[i],:,:]/numpy.sqrt(dataOut.data_spc[chan_index0,:,:]*dataOut.data_spc[chan_index1,:,:]) |
|
607 | coherenceComplex = dataOut.data_cspc[pairsIndexList[i],:,:]/numpy.sqrt(dataOut.data_spc[chan_index0,:,:]*dataOut.data_spc[chan_index1,:,:]) | |
| 600 | coherence = numpy.abs(coherenceComplex) |
|
608 | coherence = numpy.abs(coherenceComplex) | |
| 601 | # phase = numpy.arctan(-1*coherenceComplex.imag/coherenceComplex.real)*180/numpy.pi |
|
609 | # phase = numpy.arctan(-1*coherenceComplex.imag/coherenceComplex.real)*180/numpy.pi | |
| 602 | phase = numpy.arctan2(coherenceComplex.imag, coherenceComplex.real)*180/numpy.pi |
|
610 | phase = numpy.arctan2(coherenceComplex.imag, coherenceComplex.real)*180/numpy.pi | |
| 603 |
|
611 | |||
| 604 | title = "Coherence Ch%d * Ch%d" %(pair[0], pair[1]) |
|
612 | title = "Coherence Ch%d * Ch%d" %(pair[0], pair[1]) | |
| 605 | axes0 = self.axesList[i*self.__nsubplots+2] |
|
613 | axes0 = self.axesList[i*self.__nsubplots+2] | |
| 606 | axes0.pcolor(x, y, coherence, |
|
614 | axes0.pcolor(x, y, coherence, | |
| 607 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=coh_min, zmax=coh_max, |
|
615 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=coh_min, zmax=coh_max, | |
| 608 | xlabel=xlabel, ylabel=ylabel, title=title, |
|
616 | xlabel=xlabel, ylabel=ylabel, title=title, | |
| 609 | ticksize=9, colormap=coherence_cmap, cblabel='') |
|
617 | ticksize=9, colormap=coherence_cmap, cblabel='') | |
| 610 |
|
618 | |||
| 611 | title = "Phase Ch%d * Ch%d" %(pair[0], pair[1]) |
|
619 | title = "Phase Ch%d * Ch%d" %(pair[0], pair[1]) | |
| 612 | axes0 = self.axesList[i*self.__nsubplots+3] |
|
620 | axes0 = self.axesList[i*self.__nsubplots+3] | |
| 613 | axes0.pcolor(x, y, phase, |
|
621 | axes0.pcolor(x, y, phase, | |
| 614 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=phase_min, zmax=phase_max, |
|
622 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=phase_min, zmax=phase_max, | |
| 615 | xlabel=xlabel, ylabel=ylabel, title=title, |
|
623 | xlabel=xlabel, ylabel=ylabel, title=title, | |
| 616 | ticksize=9, colormap=phase_cmap, cblabel='') |
|
624 | ticksize=9, colormap=phase_cmap, cblabel='') | |
| 617 |
|
625 | |||
| 618 |
|
626 | |||
| 619 |
|
627 | |||
| 620 | self.draw() |
|
628 | self.draw() | |
| 621 |
|
629 | |||
| 622 | self.save(figpath=figpath, |
|
630 | self.save(figpath=figpath, | |
| 623 | figfile=figfile, |
|
631 | figfile=figfile, | |
| 624 | save=save, |
|
632 | save=save, | |
| 625 | ftp=ftp, |
|
633 | ftp=ftp, | |
| 626 | wr_period=wr_period, |
|
634 | wr_period=wr_period, | |
| 627 | thisDatetime=thisDatetime) |
|
635 | thisDatetime=thisDatetime) | |
| 628 |
|
636 | |||
| 629 |
|
637 | |||
| 630 | class RTIPlot(Figure): |
|
638 | class RTIPlot(Figure): | |
| 631 |
|
639 | |||
| 632 | __isConfig = None |
|
640 | __isConfig = None | |
| 633 | __nsubplots = None |
|
641 | __nsubplots = None | |
| 634 |
|
642 | |||
| 635 | WIDTHPROF = None |
|
643 | WIDTHPROF = None | |
| 636 | HEIGHTPROF = None |
|
644 | HEIGHTPROF = None | |
| 637 | PREFIX = 'rti' |
|
645 | PREFIX = 'rti' | |
| 638 |
|
646 | |||
| 639 | def __init__(self, **kwargs): |
|
647 | def __init__(self, **kwargs): | |
| 640 |
|
648 | |||
| 641 | Figure.__init__(self, **kwargs) |
|
649 | Figure.__init__(self, **kwargs) | |
| 642 | self.timerange = None |
|
650 | self.timerange = None | |
| 643 | self.isConfig = False |
|
651 | self.isConfig = False | |
| 644 | self.__nsubplots = 1 |
|
652 | self.__nsubplots = 1 | |
| 645 |
|
653 | |||
| 646 | self.WIDTH = 800 |
|
654 | self.WIDTH = 800 | |
| 647 | self.HEIGHT = 180 |
|
655 | self.HEIGHT = 180 | |
| 648 | self.WIDTHPROF = 120 |
|
656 | self.WIDTHPROF = 120 | |
| 649 | self.HEIGHTPROF = 0 |
|
657 | self.HEIGHTPROF = 0 | |
| 650 | self.counter_imagwr = 0 |
|
658 | self.counter_imagwr = 0 | |
| 651 |
|
659 | |||
| 652 | self.PLOT_CODE = RTI_CODE |
|
660 | self.PLOT_CODE = RTI_CODE | |
| 653 |
|
661 | |||
| 654 | self.FTP_WEI = None |
|
662 | self.FTP_WEI = None | |
| 655 | self.EXP_CODE = None |
|
663 | self.EXP_CODE = None | |
| 656 | self.SUB_EXP_CODE = None |
|
664 | self.SUB_EXP_CODE = None | |
| 657 | self.PLOT_POS = None |
|
665 | self.PLOT_POS = None | |
| 658 | self.tmin = None |
|
666 | self.tmin = None | |
| 659 | self.tmax = None |
|
667 | self.tmax = None | |
| 660 |
|
668 | |||
| 661 | self.xmin = None |
|
669 | self.xmin = None | |
| 662 | self.xmax = None |
|
670 | self.xmax = None | |
| 663 |
|
671 | |||
| 664 | self.figfile = None |
|
672 | self.figfile = None | |
| 665 |
|
673 | |||
| 666 | def getSubplots(self): |
|
674 | def getSubplots(self): | |
| 667 |
|
675 | |||
| 668 | ncol = 1 |
|
676 | ncol = 1 | |
| 669 | nrow = self.nplots |
|
677 | nrow = self.nplots | |
| 670 |
|
678 | |||
| 671 | return nrow, ncol |
|
679 | return nrow, ncol | |
| 672 |
|
680 | |||
| 673 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
681 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): | |
| 674 |
|
682 | |||
| 675 | self.__showprofile = showprofile |
|
683 | self.__showprofile = showprofile | |
| 676 | self.nplots = nplots |
|
684 | self.nplots = nplots | |
| 677 |
|
685 | |||
| 678 | ncolspan = 1 |
|
686 | ncolspan = 1 | |
| 679 | colspan = 1 |
|
687 | colspan = 1 | |
| 680 | if showprofile: |
|
688 | if showprofile: | |
| 681 | ncolspan = 7 |
|
689 | ncolspan = 7 | |
| 682 | colspan = 6 |
|
690 | colspan = 6 | |
| 683 | self.__nsubplots = 2 |
|
691 | self.__nsubplots = 2 | |
| 684 |
|
692 | |||
| 685 | self.createFigure(id = id, |
|
693 | self.createFigure(id = id, | |
| 686 | wintitle = wintitle, |
|
694 | wintitle = wintitle, | |
| 687 | widthplot = self.WIDTH + self.WIDTHPROF, |
|
695 | widthplot = self.WIDTH + self.WIDTHPROF, | |
| 688 | heightplot = self.HEIGHT + self.HEIGHTPROF, |
|
696 | heightplot = self.HEIGHT + self.HEIGHTPROF, | |
| 689 | show=show) |
|
697 | show=show) | |
| 690 |
|
698 | |||
| 691 | nrow, ncol = self.getSubplots() |
|
699 | nrow, ncol = self.getSubplots() | |
| 692 |
|
700 | |||
| 693 | counter = 0 |
|
701 | counter = 0 | |
| 694 | for y in range(nrow): |
|
702 | for y in range(nrow): | |
| 695 | for x in range(ncol): |
|
703 | for x in range(ncol): | |
| 696 |
|
704 | |||
| 697 | if counter >= self.nplots: |
|
705 | if counter >= self.nplots: | |
| 698 | break |
|
706 | break | |
| 699 |
|
707 | |||
| 700 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
708 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) | |
| 701 |
|
709 | |||
| 702 | if showprofile: |
|
710 | if showprofile: | |
| 703 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) |
|
711 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) | |
| 704 |
|
712 | |||
| 705 | counter += 1 |
|
713 | counter += 1 | |
| 706 |
|
714 | |||
| 707 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile='True', |
|
715 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile='True', | |
| 708 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, |
|
716 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, | |
| 709 | timerange=None, colormap='jet', |
|
717 | timerange=None, colormap='jet', | |
| 710 | save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True, |
|
718 | save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True, | |
| 711 | server=None, folder=None, username=None, password=None, |
|
719 | server=None, folder=None, username=None, password=None, | |
| 712 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, normFactor=None, HEIGHT=None): |
|
720 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, normFactor=None, HEIGHT=None): | |
| 713 |
|
721 | |||
| 714 | """ |
|
722 | """ | |
| 715 |
|
723 | |||
| 716 | Input: |
|
724 | Input: | |
| 717 | dataOut : |
|
725 | dataOut : | |
| 718 | id : |
|
726 | id : | |
| 719 | wintitle : |
|
727 | wintitle : | |
| 720 | channelList : |
|
728 | channelList : | |
| 721 | showProfile : |
|
729 | showProfile : | |
| 722 | xmin : None, |
|
730 | xmin : None, | |
| 723 | xmax : None, |
|
731 | xmax : None, | |
| 724 | ymin : None, |
|
732 | ymin : None, | |
| 725 | ymax : None, |
|
733 | ymax : None, | |
| 726 | zmin : None, |
|
734 | zmin : None, | |
| 727 | zmax : None |
|
735 | zmax : None | |
| 728 | """ |
|
736 | """ | |
| 729 |
|
737 | |||
| 730 | #colormap = kwargs.get('colormap', 'jet') |
|
738 | #colormap = kwargs.get('colormap', 'jet') | |
| 731 | if HEIGHT is not None: |
|
739 | if HEIGHT is not None: | |
| 732 | self.HEIGHT = HEIGHT |
|
740 | self.HEIGHT = HEIGHT | |
| 733 |
|
741 | |||
| 734 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): |
|
742 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): | |
| 735 | return |
|
743 | return | |
| 736 |
|
744 | |||
| 737 | if channelList == None: |
|
745 | if channelList == None: | |
| 738 | channelIndexList = dataOut.channelIndexList |
|
746 | channelIndexList = dataOut.channelIndexList | |
| 739 | else: |
|
747 | else: | |
| 740 | channelIndexList = [] |
|
748 | channelIndexList = [] | |
| 741 | for channel in channelList: |
|
749 | for channel in channelList: | |
| 742 | if channel not in dataOut.channelList: |
|
750 | if channel not in dataOut.channelList: | |
| 743 | raise ValueError, "Channel %d is not in dataOut.channelList" |
|
751 | raise ValueError, "Channel %d is not in dataOut.channelList" | |
| 744 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
752 | channelIndexList.append(dataOut.channelList.index(channel)) | |
| 745 |
|
753 | |||
| 746 | if normFactor is None: |
|
754 | if normFactor is None: | |
| 747 | factor = dataOut.normFactor |
|
755 | factor = dataOut.normFactor | |
| 748 | else: |
|
756 | else: | |
| 749 | factor = normFactor |
|
757 | factor = normFactor | |
| 750 |
|
758 | |||
| 751 | # factor = dataOut.normFactor |
|
759 | # factor = dataOut.normFactor | |
| 752 | x = dataOut.getTimeRange() |
|
760 | x = dataOut.getTimeRange() | |
| 753 | y = dataOut.getHeiRange() |
|
761 | y = dataOut.getHeiRange() | |
| 754 |
|
762 | |||
| 755 | z = dataOut.data_spc/factor |
|
763 | z = dataOut.data_spc/factor | |
| 756 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
764 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | |
| 757 | avg = numpy.average(z, axis=1) |
|
765 | avg = numpy.average(z, axis=1) | |
| 758 | avgdB = 10.*numpy.log10(avg) |
|
766 | avgdB = 10.*numpy.log10(avg) | |
| 759 | # avgdB = dataOut.getPower() |
|
767 | # avgdB = dataOut.getPower() | |
| 760 |
|
768 | |||
| 761 |
|
769 | |||
| 762 | thisDatetime = dataOut.datatime |
|
770 | thisDatetime = dataOut.datatime | |
| 763 | # thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) |
|
771 | # thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) | |
| 764 | title = wintitle + " RTI" #: %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
772 | title = wintitle + " RTI" #: %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
| 765 | xlabel = "" |
|
773 | xlabel = "" | |
| 766 | ylabel = "Range (Km)" |
|
774 | ylabel = "Range (Km)" | |
| 767 |
|
775 | |||
| 768 | update_figfile = False |
|
776 | update_figfile = False | |
| 769 |
|
777 | |||
| 770 | if dataOut.ltctime >= self.xmax: |
|
778 | if dataOut.ltctime >= self.xmax: | |
| 771 | self.counter_imagwr = wr_period |
|
779 | self.counter_imagwr = wr_period | |
| 772 | self.isConfig = False |
|
780 | self.isConfig = False | |
| 773 | update_figfile = True |
|
781 | update_figfile = True | |
| 774 |
|
782 | |||
| 775 | if not self.isConfig: |
|
783 | if not self.isConfig: | |
| 776 |
|
784 | |||
| 777 | nplots = len(channelIndexList) |
|
785 | nplots = len(channelIndexList) | |
| 778 |
|
786 | |||
| 779 | self.setup(id=id, |
|
787 | self.setup(id=id, | |
| 780 | nplots=nplots, |
|
788 | nplots=nplots, | |
| 781 | wintitle=wintitle, |
|
789 | wintitle=wintitle, | |
| 782 | showprofile=showprofile, |
|
790 | showprofile=showprofile, | |
| 783 | show=show) |
|
791 | show=show) | |
| 784 |
|
792 | |||
| 785 | if timerange != None: |
|
793 | if timerange != None: | |
| 786 | self.timerange = timerange |
|
794 | self.timerange = timerange | |
| 787 |
|
795 | |||
| 788 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) |
|
796 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) | |
| 789 |
|
797 | |||
| 790 | noise = dataOut.noise/factor |
|
798 | noise = dataOut.noise/factor | |
| 791 | noisedB = 10*numpy.log10(noise) |
|
799 | noisedB = 10*numpy.log10(noise) | |
| 792 |
|
800 | |||
| 793 | if ymin == None: ymin = numpy.nanmin(y) |
|
801 | if ymin == None: ymin = numpy.nanmin(y) | |
| 794 | if ymax == None: ymax = numpy.nanmax(y) |
|
802 | if ymax == None: ymax = numpy.nanmax(y) | |
| 795 | if zmin == None: zmin = numpy.floor(numpy.nanmin(noisedB)) - 3 |
|
803 | if zmin == None: zmin = numpy.floor(numpy.nanmin(noisedB)) - 3 | |
| 796 | if zmax == None: zmax = numpy.ceil(numpy.nanmax(avgdB)) + 3 |
|
804 | if zmax == None: zmax = numpy.ceil(numpy.nanmax(avgdB)) + 3 | |
| 797 |
|
805 | |||
| 798 | self.FTP_WEI = ftp_wei |
|
806 | self.FTP_WEI = ftp_wei | |
| 799 | self.EXP_CODE = exp_code |
|
807 | self.EXP_CODE = exp_code | |
| 800 | self.SUB_EXP_CODE = sub_exp_code |
|
808 | self.SUB_EXP_CODE = sub_exp_code | |
| 801 | self.PLOT_POS = plot_pos |
|
809 | self.PLOT_POS = plot_pos | |
| 802 |
|
810 | |||
| 803 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
811 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 804 | self.isConfig = True |
|
812 | self.isConfig = True | |
| 805 | self.figfile = figfile |
|
813 | self.figfile = figfile | |
| 806 | update_figfile = True |
|
814 | update_figfile = True | |
| 807 |
|
815 | |||
| 808 | self.setWinTitle(title) |
|
816 | self.setWinTitle(title) | |
| 809 |
|
817 | |||
| 810 | for i in range(self.nplots): |
|
818 | for i in range(self.nplots): | |
| 811 | index = channelIndexList[i] |
|
819 | index = channelIndexList[i] | |
| 812 | title = "Channel %d: %s" %(dataOut.channelList[index], thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) |
|
820 | title = "Channel %d: %s" %(dataOut.channelList[index], thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) | |
| 813 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): |
|
821 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): | |
| 814 | title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith) |
|
822 | title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith) | |
| 815 | axes = self.axesList[i*self.__nsubplots] |
|
823 | axes = self.axesList[i*self.__nsubplots] | |
| 816 | zdB = avgdB[index].reshape((1,-1)) |
|
824 | zdB = avgdB[index].reshape((1,-1)) | |
| 817 | axes.pcolorbuffer(x, y, zdB, |
|
825 | axes.pcolorbuffer(x, y, zdB, | |
| 818 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, |
|
826 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, | |
| 819 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, |
|
827 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, | |
| 820 | ticksize=9, cblabel='', cbsize="1%", colormap=colormap) |
|
828 | ticksize=9, cblabel='', cbsize="1%", colormap=colormap) | |
| 821 |
|
829 | |||
| 822 | if self.__showprofile: |
|
830 | if self.__showprofile: | |
| 823 | axes = self.axesList[i*self.__nsubplots +1] |
|
831 | axes = self.axesList[i*self.__nsubplots +1] | |
| 824 | axes.pline(avgdB[index], y, |
|
832 | axes.pline(avgdB[index], y, | |
| 825 | xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax, |
|
833 | xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax, | |
| 826 | xlabel='dB', ylabel='', title='', |
|
834 | xlabel='dB', ylabel='', title='', | |
| 827 | ytick_visible=False, |
|
835 | ytick_visible=False, | |
| 828 | grid='x') |
|
836 | grid='x') | |
| 829 |
|
837 | |||
| 830 | self.draw() |
|
838 | self.draw() | |
| 831 |
|
839 | |||
| 832 | self.save(figpath=figpath, |
|
840 | self.save(figpath=figpath, | |
| 833 | figfile=figfile, |
|
841 | figfile=figfile, | |
| 834 | save=save, |
|
842 | save=save, | |
| 835 | ftp=ftp, |
|
843 | ftp=ftp, | |
| 836 | wr_period=wr_period, |
|
844 | wr_period=wr_period, | |
| 837 | thisDatetime=thisDatetime, |
|
845 | thisDatetime=thisDatetime, | |
| 838 | update_figfile=update_figfile) |
|
846 | update_figfile=update_figfile) | |
| 839 |
|
847 | |||
| 840 | class CoherenceMap(Figure): |
|
848 | class CoherenceMap(Figure): | |
| 841 | isConfig = None |
|
849 | isConfig = None | |
| 842 | __nsubplots = None |
|
850 | __nsubplots = None | |
| 843 |
|
851 | |||
| 844 | WIDTHPROF = None |
|
852 | WIDTHPROF = None | |
| 845 | HEIGHTPROF = None |
|
853 | HEIGHTPROF = None | |
| 846 | PREFIX = 'cmap' |
|
854 | PREFIX = 'cmap' | |
| 847 |
|
855 | |||
| 848 | def __init__(self, **kwargs): |
|
856 | def __init__(self, **kwargs): | |
| 849 | Figure.__init__(self, **kwargs) |
|
857 | Figure.__init__(self, **kwargs) | |
| 850 | self.timerange = 2*60*60 |
|
858 | self.timerange = 2*60*60 | |
| 851 | self.isConfig = False |
|
859 | self.isConfig = False | |
| 852 | self.__nsubplots = 1 |
|
860 | self.__nsubplots = 1 | |
| 853 |
|
861 | |||
| 854 | self.WIDTH = 800 |
|
862 | self.WIDTH = 800 | |
| 855 | self.HEIGHT = 180 |
|
863 | self.HEIGHT = 180 | |
| 856 | self.WIDTHPROF = 120 |
|
864 | self.WIDTHPROF = 120 | |
| 857 | self.HEIGHTPROF = 0 |
|
865 | self.HEIGHTPROF = 0 | |
| 858 | self.counter_imagwr = 0 |
|
866 | self.counter_imagwr = 0 | |
| 859 |
|
867 | |||
| 860 | self.PLOT_CODE = COH_CODE |
|
868 | self.PLOT_CODE = COH_CODE | |
| 861 |
|
869 | |||
| 862 | self.FTP_WEI = None |
|
870 | self.FTP_WEI = None | |
| 863 | self.EXP_CODE = None |
|
871 | self.EXP_CODE = None | |
| 864 | self.SUB_EXP_CODE = None |
|
872 | self.SUB_EXP_CODE = None | |
| 865 | self.PLOT_POS = None |
|
873 | self.PLOT_POS = None | |
| 866 | self.counter_imagwr = 0 |
|
874 | self.counter_imagwr = 0 | |
| 867 |
|
875 | |||
| 868 | self.xmin = None |
|
876 | self.xmin = None | |
| 869 | self.xmax = None |
|
877 | self.xmax = None | |
| 870 |
|
878 | |||
| 871 | def getSubplots(self): |
|
879 | def getSubplots(self): | |
| 872 | ncol = 1 |
|
880 | ncol = 1 | |
| 873 | nrow = self.nplots*2 |
|
881 | nrow = self.nplots*2 | |
| 874 |
|
882 | |||
| 875 | return nrow, ncol |
|
883 | return nrow, ncol | |
| 876 |
|
884 | |||
| 877 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
885 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): | |
| 878 | self.__showprofile = showprofile |
|
886 | self.__showprofile = showprofile | |
| 879 | self.nplots = nplots |
|
887 | self.nplots = nplots | |
| 880 |
|
888 | |||
| 881 | ncolspan = 1 |
|
889 | ncolspan = 1 | |
| 882 | colspan = 1 |
|
890 | colspan = 1 | |
| 883 | if showprofile: |
|
891 | if showprofile: | |
| 884 | ncolspan = 7 |
|
892 | ncolspan = 7 | |
| 885 | colspan = 6 |
|
893 | colspan = 6 | |
| 886 | self.__nsubplots = 2 |
|
894 | self.__nsubplots = 2 | |
| 887 |
|
895 | |||
| 888 | self.createFigure(id = id, |
|
896 | self.createFigure(id = id, | |
| 889 | wintitle = wintitle, |
|
897 | wintitle = wintitle, | |
| 890 | widthplot = self.WIDTH + self.WIDTHPROF, |
|
898 | widthplot = self.WIDTH + self.WIDTHPROF, | |
| 891 | heightplot = self.HEIGHT + self.HEIGHTPROF, |
|
899 | heightplot = self.HEIGHT + self.HEIGHTPROF, | |
| 892 | show=True) |
|
900 | show=True) | |
| 893 |
|
901 | |||
| 894 | nrow, ncol = self.getSubplots() |
|
902 | nrow, ncol = self.getSubplots() | |
| 895 |
|
903 | |||
| 896 | for y in range(nrow): |
|
904 | for y in range(nrow): | |
| 897 | for x in range(ncol): |
|
905 | for x in range(ncol): | |
| 898 |
|
906 | |||
| 899 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
907 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) | |
| 900 |
|
908 | |||
| 901 | if showprofile: |
|
909 | if showprofile: | |
| 902 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) |
|
910 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) | |
| 903 |
|
911 | |||
| 904 | def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True', |
|
912 | def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True', | |
| 905 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, |
|
913 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, | |
| 906 | timerange=None, phase_min=None, phase_max=None, |
|
914 | timerange=None, phase_min=None, phase_max=None, | |
| 907 | save=False, figpath='./', figfile=None, ftp=False, wr_period=1, |
|
915 | save=False, figpath='./', figfile=None, ftp=False, wr_period=1, | |
| 908 | coherence_cmap='jet', phase_cmap='RdBu_r', show=True, |
|
916 | coherence_cmap='jet', phase_cmap='RdBu_r', show=True, | |
| 909 | server=None, folder=None, username=None, password=None, |
|
917 | server=None, folder=None, username=None, password=None, | |
| 910 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): |
|
918 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): | |
| 911 |
|
919 | |||
| 912 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): |
|
920 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): | |
| 913 | return |
|
921 | return | |
| 914 |
|
922 | |||
| 915 | if pairsList == None: |
|
923 | if pairsList == None: | |
| 916 | pairsIndexList = dataOut.pairsIndexList |
|
924 | pairsIndexList = dataOut.pairsIndexList | |
| 917 | else: |
|
925 | else: | |
| 918 | pairsIndexList = [] |
|
926 | pairsIndexList = [] | |
| 919 | for pair in pairsList: |
|
927 | for pair in pairsList: | |
| 920 | if pair not in dataOut.pairsList: |
|
928 | if pair not in dataOut.pairsList: | |
| 921 | raise ValueError, "Pair %s is not in dataOut.pairsList" %(pair) |
|
929 | raise ValueError, "Pair %s is not in dataOut.pairsList" %(pair) | |
| 922 | pairsIndexList.append(dataOut.pairsList.index(pair)) |
|
930 | pairsIndexList.append(dataOut.pairsList.index(pair)) | |
| 923 |
|
931 | |||
| 924 | if pairsIndexList == []: |
|
932 | if pairsIndexList == []: | |
| 925 | return |
|
933 | return | |
| 926 |
|
934 | |||
| 927 | if len(pairsIndexList) > 4: |
|
935 | if len(pairsIndexList) > 4: | |
| 928 | pairsIndexList = pairsIndexList[0:4] |
|
936 | pairsIndexList = pairsIndexList[0:4] | |
| 929 |
|
937 | |||
| 930 | if phase_min == None: |
|
938 | if phase_min == None: | |
| 931 | phase_min = -180 |
|
939 | phase_min = -180 | |
| 932 | if phase_max == None: |
|
940 | if phase_max == None: | |
| 933 | phase_max = 180 |
|
941 | phase_max = 180 | |
| 934 |
|
942 | |||
| 935 | x = dataOut.getTimeRange() |
|
943 | x = dataOut.getTimeRange() | |
| 936 | y = dataOut.getHeiRange() |
|
944 | y = dataOut.getHeiRange() | |
| 937 |
|
945 | |||
| 938 | thisDatetime = dataOut.datatime |
|
946 | thisDatetime = dataOut.datatime | |
| 939 |
|
947 | |||
| 940 | title = wintitle + " CoherenceMap" #: %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
948 | title = wintitle + " CoherenceMap" #: %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
| 941 | xlabel = "" |
|
949 | xlabel = "" | |
| 942 | ylabel = "Range (Km)" |
|
950 | ylabel = "Range (Km)" | |
| 943 | update_figfile = False |
|
951 | update_figfile = False | |
| 944 |
|
952 | |||
| 945 | if not self.isConfig: |
|
953 | if not self.isConfig: | |
| 946 | nplots = len(pairsIndexList) |
|
954 | nplots = len(pairsIndexList) | |
| 947 | self.setup(id=id, |
|
955 | self.setup(id=id, | |
| 948 | nplots=nplots, |
|
956 | nplots=nplots, | |
| 949 | wintitle=wintitle, |
|
957 | wintitle=wintitle, | |
| 950 | showprofile=showprofile, |
|
958 | showprofile=showprofile, | |
| 951 | show=show) |
|
959 | show=show) | |
| 952 |
|
960 | |||
| 953 | if timerange != None: |
|
961 | if timerange != None: | |
| 954 | self.timerange = timerange |
|
962 | self.timerange = timerange | |
| 955 |
|
963 | |||
| 956 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) |
|
964 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) | |
| 957 |
|
965 | |||
| 958 | if ymin == None: ymin = numpy.nanmin(y) |
|
966 | if ymin == None: ymin = numpy.nanmin(y) | |
| 959 | if ymax == None: ymax = numpy.nanmax(y) |
|
967 | if ymax == None: ymax = numpy.nanmax(y) | |
| 960 | if zmin == None: zmin = 0. |
|
968 | if zmin == None: zmin = 0. | |
| 961 | if zmax == None: zmax = 1. |
|
969 | if zmax == None: zmax = 1. | |
| 962 |
|
970 | |||
| 963 | self.FTP_WEI = ftp_wei |
|
971 | self.FTP_WEI = ftp_wei | |
| 964 | self.EXP_CODE = exp_code |
|
972 | self.EXP_CODE = exp_code | |
| 965 | self.SUB_EXP_CODE = sub_exp_code |
|
973 | self.SUB_EXP_CODE = sub_exp_code | |
| 966 | self.PLOT_POS = plot_pos |
|
974 | self.PLOT_POS = plot_pos | |
| 967 |
|
975 | |||
| 968 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
976 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 969 |
|
977 | |||
| 970 | self.isConfig = True |
|
978 | self.isConfig = True | |
| 971 | update_figfile = True |
|
979 | update_figfile = True | |
| 972 |
|
980 | |||
| 973 | self.setWinTitle(title) |
|
981 | self.setWinTitle(title) | |
| 974 |
|
982 | |||
| 975 | for i in range(self.nplots): |
|
983 | for i in range(self.nplots): | |
| 976 |
|
984 | |||
| 977 | pair = dataOut.pairsList[pairsIndexList[i]] |
|
985 | pair = dataOut.pairsList[pairsIndexList[i]] | |
| 978 |
|
986 | |||
| 979 | ccf = numpy.average(dataOut.data_cspc[pairsIndexList[i],:,:],axis=0) |
|
987 | ccf = numpy.average(dataOut.data_cspc[pairsIndexList[i],:,:],axis=0) | |
| 980 | powa = numpy.average(dataOut.data_spc[pair[0],:,:],axis=0) |
|
988 | powa = numpy.average(dataOut.data_spc[pair[0],:,:],axis=0) | |
| 981 | powb = numpy.average(dataOut.data_spc[pair[1],:,:],axis=0) |
|
989 | powb = numpy.average(dataOut.data_spc[pair[1],:,:],axis=0) | |
| 982 |
|
990 | |||
| 983 |
|
991 | |||
| 984 | avgcoherenceComplex = ccf/numpy.sqrt(powa*powb) |
|
992 | avgcoherenceComplex = ccf/numpy.sqrt(powa*powb) | |
| 985 | coherence = numpy.abs(avgcoherenceComplex) |
|
993 | coherence = numpy.abs(avgcoherenceComplex) | |
| 986 |
|
994 | |||
| 987 | z = coherence.reshape((1,-1)) |
|
995 | z = coherence.reshape((1,-1)) | |
| 988 |
|
996 | |||
| 989 | counter = 0 |
|
997 | counter = 0 | |
| 990 |
|
998 | |||
| 991 | title = "Coherence Ch%d * Ch%d: %s" %(pair[0], pair[1], thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
999 | title = "Coherence Ch%d * Ch%d: %s" %(pair[0], pair[1], thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
| 992 | axes = self.axesList[i*self.__nsubplots*2] |
|
1000 | axes = self.axesList[i*self.__nsubplots*2] | |
| 993 | axes.pcolorbuffer(x, y, z, |
|
1001 | axes.pcolorbuffer(x, y, z, | |
| 994 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, |
|
1002 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, | |
| 995 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, |
|
1003 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, | |
| 996 | ticksize=9, cblabel='', colormap=coherence_cmap, cbsize="1%") |
|
1004 | ticksize=9, cblabel='', colormap=coherence_cmap, cbsize="1%") | |
| 997 |
|
1005 | |||
| 998 | if self.__showprofile: |
|
1006 | if self.__showprofile: | |
| 999 | counter += 1 |
|
1007 | counter += 1 | |
| 1000 | axes = self.axesList[i*self.__nsubplots*2 + counter] |
|
1008 | axes = self.axesList[i*self.__nsubplots*2 + counter] | |
| 1001 | axes.pline(coherence, y, |
|
1009 | axes.pline(coherence, y, | |
| 1002 | xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax, |
|
1010 | xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax, | |
| 1003 | xlabel='', ylabel='', title='', ticksize=7, |
|
1011 | xlabel='', ylabel='', title='', ticksize=7, | |
| 1004 | ytick_visible=False, nxticks=5, |
|
1012 | ytick_visible=False, nxticks=5, | |
| 1005 | grid='x') |
|
1013 | grid='x') | |
| 1006 |
|
1014 | |||
| 1007 | counter += 1 |
|
1015 | counter += 1 | |
| 1008 |
|
1016 | |||
| 1009 | phase = numpy.arctan2(avgcoherenceComplex.imag, avgcoherenceComplex.real)*180/numpy.pi |
|
1017 | phase = numpy.arctan2(avgcoherenceComplex.imag, avgcoherenceComplex.real)*180/numpy.pi | |
| 1010 |
|
1018 | |||
| 1011 | z = phase.reshape((1,-1)) |
|
1019 | z = phase.reshape((1,-1)) | |
| 1012 |
|
1020 | |||
| 1013 | title = "Phase Ch%d * Ch%d: %s" %(pair[0], pair[1], thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
1021 | title = "Phase Ch%d * Ch%d: %s" %(pair[0], pair[1], thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
| 1014 | axes = self.axesList[i*self.__nsubplots*2 + counter] |
|
1022 | axes = self.axesList[i*self.__nsubplots*2 + counter] | |
| 1015 | axes.pcolorbuffer(x, y, z, |
|
1023 | axes.pcolorbuffer(x, y, z, | |
| 1016 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=phase_min, zmax=phase_max, |
|
1024 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=phase_min, zmax=phase_max, | |
| 1017 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, |
|
1025 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, | |
| 1018 | ticksize=9, cblabel='', colormap=phase_cmap, cbsize="1%") |
|
1026 | ticksize=9, cblabel='', colormap=phase_cmap, cbsize="1%") | |
| 1019 |
|
1027 | |||
| 1020 | if self.__showprofile: |
|
1028 | if self.__showprofile: | |
| 1021 | counter += 1 |
|
1029 | counter += 1 | |
| 1022 | axes = self.axesList[i*self.__nsubplots*2 + counter] |
|
1030 | axes = self.axesList[i*self.__nsubplots*2 + counter] | |
| 1023 | axes.pline(phase, y, |
|
1031 | axes.pline(phase, y, | |
| 1024 | xmin=phase_min, xmax=phase_max, ymin=ymin, ymax=ymax, |
|
1032 | xmin=phase_min, xmax=phase_max, ymin=ymin, ymax=ymax, | |
| 1025 | xlabel='', ylabel='', title='', ticksize=7, |
|
1033 | xlabel='', ylabel='', title='', ticksize=7, | |
| 1026 | ytick_visible=False, nxticks=4, |
|
1034 | ytick_visible=False, nxticks=4, | |
| 1027 | grid='x') |
|
1035 | grid='x') | |
| 1028 |
|
1036 | |||
| 1029 | self.draw() |
|
1037 | self.draw() | |
| 1030 |
|
1038 | |||
| 1031 | if dataOut.ltctime >= self.xmax: |
|
1039 | if dataOut.ltctime >= self.xmax: | |
| 1032 | self.counter_imagwr = wr_period |
|
1040 | self.counter_imagwr = wr_period | |
| 1033 | self.isConfig = False |
|
1041 | self.isConfig = False | |
| 1034 | update_figfile = True |
|
1042 | update_figfile = True | |
| 1035 |
|
1043 | |||
| 1036 | self.save(figpath=figpath, |
|
1044 | self.save(figpath=figpath, | |
| 1037 | figfile=figfile, |
|
1045 | figfile=figfile, | |
| 1038 | save=save, |
|
1046 | save=save, | |
| 1039 | ftp=ftp, |
|
1047 | ftp=ftp, | |
| 1040 | wr_period=wr_period, |
|
1048 | wr_period=wr_period, | |
| 1041 | thisDatetime=thisDatetime, |
|
1049 | thisDatetime=thisDatetime, | |
| 1042 | update_figfile=update_figfile) |
|
1050 | update_figfile=update_figfile) | |
| 1043 |
|
1051 | |||
| 1044 | class PowerProfilePlot(Figure): |
|
1052 | class PowerProfilePlot(Figure): | |
| 1045 |
|
1053 | |||
| 1046 | isConfig = None |
|
1054 | isConfig = None | |
| 1047 | __nsubplots = None |
|
1055 | __nsubplots = None | |
| 1048 |
|
1056 | |||
| 1049 | WIDTHPROF = None |
|
1057 | WIDTHPROF = None | |
| 1050 | HEIGHTPROF = None |
|
1058 | HEIGHTPROF = None | |
| 1051 | PREFIX = 'spcprofile' |
|
1059 | PREFIX = 'spcprofile' | |
| 1052 |
|
1060 | |||
| 1053 | def __init__(self, **kwargs): |
|
1061 | def __init__(self, **kwargs): | |
| 1054 | Figure.__init__(self, **kwargs) |
|
1062 | Figure.__init__(self, **kwargs) | |
| 1055 | self.isConfig = False |
|
1063 | self.isConfig = False | |
| 1056 | self.__nsubplots = 1 |
|
1064 | self.__nsubplots = 1 | |
| 1057 |
|
1065 | |||
| 1058 | self.PLOT_CODE = POWER_CODE |
|
1066 | self.PLOT_CODE = POWER_CODE | |
| 1059 |
|
1067 | |||
| 1060 | self.WIDTH = 300 |
|
1068 | self.WIDTH = 300 | |
| 1061 | self.HEIGHT = 500 |
|
1069 | self.HEIGHT = 500 | |
| 1062 | self.counter_imagwr = 0 |
|
1070 | self.counter_imagwr = 0 | |
| 1063 |
|
1071 | |||
| 1064 | def getSubplots(self): |
|
1072 | def getSubplots(self): | |
| 1065 | ncol = 1 |
|
1073 | ncol = 1 | |
| 1066 | nrow = 1 |
|
1074 | nrow = 1 | |
| 1067 |
|
1075 | |||
| 1068 | return nrow, ncol |
|
1076 | return nrow, ncol | |
| 1069 |
|
1077 | |||
| 1070 | def setup(self, id, nplots, wintitle, show): |
|
1078 | def setup(self, id, nplots, wintitle, show): | |
| 1071 |
|
1079 | |||
| 1072 | self.nplots = nplots |
|
1080 | self.nplots = nplots | |
| 1073 |
|
1081 | |||
| 1074 | ncolspan = 1 |
|
1082 | ncolspan = 1 | |
| 1075 | colspan = 1 |
|
1083 | colspan = 1 | |
| 1076 |
|
1084 | |||
| 1077 | self.createFigure(id = id, |
|
1085 | self.createFigure(id = id, | |
| 1078 | wintitle = wintitle, |
|
1086 | wintitle = wintitle, | |
| 1079 | widthplot = self.WIDTH, |
|
1087 | widthplot = self.WIDTH, | |
| 1080 | heightplot = self.HEIGHT, |
|
1088 | heightplot = self.HEIGHT, | |
| 1081 | show=show) |
|
1089 | show=show) | |
| 1082 |
|
1090 | |||
| 1083 | nrow, ncol = self.getSubplots() |
|
1091 | nrow, ncol = self.getSubplots() | |
| 1084 |
|
1092 | |||
| 1085 | counter = 0 |
|
1093 | counter = 0 | |
| 1086 | for y in range(nrow): |
|
1094 | for y in range(nrow): | |
| 1087 | for x in range(ncol): |
|
1095 | for x in range(ncol): | |
| 1088 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
1096 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) | |
| 1089 |
|
1097 | |||
| 1090 | def run(self, dataOut, id, wintitle="", channelList=None, |
|
1098 | def run(self, dataOut, id, wintitle="", channelList=None, | |
| 1091 | xmin=None, xmax=None, ymin=None, ymax=None, |
|
1099 | xmin=None, xmax=None, ymin=None, ymax=None, | |
| 1092 | save=False, figpath='./', figfile=None, show=True, |
|
1100 | save=False, figpath='./', figfile=None, show=True, | |
| 1093 | ftp=False, wr_period=1, server=None, |
|
1101 | ftp=False, wr_period=1, server=None, | |
| 1094 | folder=None, username=None, password=None): |
|
1102 | folder=None, username=None, password=None): | |
| 1095 |
|
1103 | |||
| 1096 |
|
1104 | |||
| 1097 | if channelList == None: |
|
1105 | if channelList == None: | |
| 1098 | channelIndexList = dataOut.channelIndexList |
|
1106 | channelIndexList = dataOut.channelIndexList | |
| 1099 | channelList = dataOut.channelList |
|
1107 | channelList = dataOut.channelList | |
| 1100 | else: |
|
1108 | else: | |
| 1101 | channelIndexList = [] |
|
1109 | channelIndexList = [] | |
| 1102 | for channel in channelList: |
|
1110 | for channel in channelList: | |
| 1103 | if channel not in dataOut.channelList: |
|
1111 | if channel not in dataOut.channelList: | |
| 1104 | raise ValueError, "Channel %d is not in dataOut.channelList" |
|
1112 | raise ValueError, "Channel %d is not in dataOut.channelList" | |
| 1105 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
1113 | channelIndexList.append(dataOut.channelList.index(channel)) | |
| 1106 |
|
1114 | |||
| 1107 | factor = dataOut.normFactor |
|
1115 | factor = dataOut.normFactor | |
| 1108 |
|
1116 | |||
| 1109 | y = dataOut.getHeiRange() |
|
1117 | y = dataOut.getHeiRange() | |
| 1110 |
|
1118 | |||
| 1111 | #for voltage |
|
1119 | #for voltage | |
| 1112 | if dataOut.type == 'Voltage': |
|
1120 | if dataOut.type == 'Voltage': | |
| 1113 | x = dataOut.data[channelIndexList,:] * numpy.conjugate(dataOut.data[channelIndexList,:]) |
|
1121 | x = dataOut.data[channelIndexList,:] * numpy.conjugate(dataOut.data[channelIndexList,:]) | |
| 1114 | x = x.real |
|
1122 | x = x.real | |
| 1115 | x = numpy.where(numpy.isfinite(x), x, numpy.NAN) |
|
1123 | x = numpy.where(numpy.isfinite(x), x, numpy.NAN) | |
| 1116 |
|
1124 | |||
| 1117 | #for spectra |
|
1125 | #for spectra | |
| 1118 | if dataOut.type == 'Spectra': |
|
1126 | if dataOut.type == 'Spectra': | |
| 1119 | x = dataOut.data_spc[channelIndexList,:,:]/factor |
|
1127 | x = dataOut.data_spc[channelIndexList,:,:]/factor | |
| 1120 | x = numpy.where(numpy.isfinite(x), x, numpy.NAN) |
|
1128 | x = numpy.where(numpy.isfinite(x), x, numpy.NAN) | |
| 1121 | x = numpy.average(x, axis=1) |
|
1129 | x = numpy.average(x, axis=1) | |
| 1122 |
|
1130 | |||
| 1123 |
|
1131 | |||
| 1124 | xdB = 10*numpy.log10(x) |
|
1132 | xdB = 10*numpy.log10(x) | |
| 1125 |
|
1133 | |||
| 1126 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) |
|
1134 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) | |
| 1127 | title = wintitle + " Power Profile %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
1135 | title = wintitle + " Power Profile %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
| 1128 | xlabel = "dB" |
|
1136 | xlabel = "dB" | |
| 1129 | ylabel = "Range (Km)" |
|
1137 | ylabel = "Range (Km)" | |
| 1130 |
|
1138 | |||
| 1131 | if not self.isConfig: |
|
1139 | if not self.isConfig: | |
| 1132 |
|
1140 | |||
| 1133 | nplots = 1 |
|
1141 | nplots = 1 | |
| 1134 |
|
1142 | |||
| 1135 | self.setup(id=id, |
|
1143 | self.setup(id=id, | |
| 1136 | nplots=nplots, |
|
1144 | nplots=nplots, | |
| 1137 | wintitle=wintitle, |
|
1145 | wintitle=wintitle, | |
| 1138 | show=show) |
|
1146 | show=show) | |
| 1139 |
|
1147 | |||
| 1140 | if ymin == None: ymin = numpy.nanmin(y) |
|
1148 | if ymin == None: ymin = numpy.nanmin(y) | |
| 1141 | if ymax == None: ymax = numpy.nanmax(y) |
|
1149 | if ymax == None: ymax = numpy.nanmax(y) | |
| 1142 | if xmin == None: xmin = numpy.nanmin(xdB)*0.9 |
|
1150 | if xmin == None: xmin = numpy.nanmin(xdB)*0.9 | |
| 1143 | if xmax == None: xmax = numpy.nanmax(xdB)*1.1 |
|
1151 | if xmax == None: xmax = numpy.nanmax(xdB)*1.1 | |
| 1144 |
|
1152 | |||
| 1145 | self.isConfig = True |
|
1153 | self.isConfig = True | |
| 1146 |
|
1154 | |||
| 1147 | self.setWinTitle(title) |
|
1155 | self.setWinTitle(title) | |
| 1148 |
|
1156 | |||
| 1149 | title = "Power Profile: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
1157 | title = "Power Profile: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
| 1150 | axes = self.axesList[0] |
|
1158 | axes = self.axesList[0] | |
| 1151 |
|
1159 | |||
| 1152 | legendlabels = ["channel %d"%x for x in channelList] |
|
1160 | legendlabels = ["channel %d"%x for x in channelList] | |
| 1153 | axes.pmultiline(xdB, y, |
|
1161 | axes.pmultiline(xdB, y, | |
| 1154 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, |
|
1162 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, | |
| 1155 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, |
|
1163 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, | |
| 1156 | ytick_visible=True, nxticks=5, |
|
1164 | ytick_visible=True, nxticks=5, | |
| 1157 | grid='x') |
|
1165 | grid='x') | |
| 1158 |
|
1166 | |||
| 1159 | self.draw() |
|
1167 | self.draw() | |
| 1160 |
|
1168 | |||
| 1161 | self.save(figpath=figpath, |
|
1169 | self.save(figpath=figpath, | |
| 1162 | figfile=figfile, |
|
1170 | figfile=figfile, | |
| 1163 | save=save, |
|
1171 | save=save, | |
| 1164 | ftp=ftp, |
|
1172 | ftp=ftp, | |
| 1165 | wr_period=wr_period, |
|
1173 | wr_period=wr_period, | |
| 1166 | thisDatetime=thisDatetime) |
|
1174 | thisDatetime=thisDatetime) | |
| 1167 |
|
1175 | |||
| 1168 | class SpectraCutPlot(Figure): |
|
1176 | class SpectraCutPlot(Figure): | |
| 1169 |
|
1177 | |||
| 1170 | isConfig = None |
|
1178 | isConfig = None | |
| 1171 | __nsubplots = None |
|
1179 | __nsubplots = None | |
| 1172 |
|
1180 | |||
| 1173 | WIDTHPROF = None |
|
1181 | WIDTHPROF = None | |
| 1174 | HEIGHTPROF = None |
|
1182 | HEIGHTPROF = None | |
| 1175 | PREFIX = 'spc_cut' |
|
1183 | PREFIX = 'spc_cut' | |
| 1176 |
|
1184 | |||
| 1177 | def __init__(self, **kwargs): |
|
1185 | def __init__(self, **kwargs): | |
| 1178 | Figure.__init__(self, **kwargs) |
|
1186 | Figure.__init__(self, **kwargs) | |
| 1179 | self.isConfig = False |
|
1187 | self.isConfig = False | |
| 1180 | self.__nsubplots = 1 |
|
1188 | self.__nsubplots = 1 | |
| 1181 |
|
1189 | |||
| 1182 | self.PLOT_CODE = POWER_CODE |
|
1190 | self.PLOT_CODE = POWER_CODE | |
| 1183 |
|
1191 | |||
| 1184 | self.WIDTH = 700 |
|
1192 | self.WIDTH = 700 | |
| 1185 | self.HEIGHT = 500 |
|
1193 | self.HEIGHT = 500 | |
| 1186 | self.counter_imagwr = 0 |
|
1194 | self.counter_imagwr = 0 | |
| 1187 |
|
1195 | |||
| 1188 | def getSubplots(self): |
|
1196 | def getSubplots(self): | |
| 1189 | ncol = 1 |
|
1197 | ncol = 1 | |
| 1190 | nrow = 1 |
|
1198 | nrow = 1 | |
| 1191 |
|
1199 | |||
| 1192 | return nrow, ncol |
|
1200 | return nrow, ncol | |
| 1193 |
|
1201 | |||
| 1194 | def setup(self, id, nplots, wintitle, show): |
|
1202 | def setup(self, id, nplots, wintitle, show): | |
| 1195 |
|
1203 | |||
| 1196 | self.nplots = nplots |
|
1204 | self.nplots = nplots | |
| 1197 |
|
1205 | |||
| 1198 | ncolspan = 1 |
|
1206 | ncolspan = 1 | |
| 1199 | colspan = 1 |
|
1207 | colspan = 1 | |
| 1200 |
|
1208 | |||
| 1201 | self.createFigure(id = id, |
|
1209 | self.createFigure(id = id, | |
| 1202 | wintitle = wintitle, |
|
1210 | wintitle = wintitle, | |
| 1203 | widthplot = self.WIDTH, |
|
1211 | widthplot = self.WIDTH, | |
| 1204 | heightplot = self.HEIGHT, |
|
1212 | heightplot = self.HEIGHT, | |
| 1205 | show=show) |
|
1213 | show=show) | |
| 1206 |
|
1214 | |||
| 1207 | nrow, ncol = self.getSubplots() |
|
1215 | nrow, ncol = self.getSubplots() | |
| 1208 |
|
1216 | |||
| 1209 | counter = 0 |
|
1217 | counter = 0 | |
| 1210 | for y in range(nrow): |
|
1218 | for y in range(nrow): | |
| 1211 | for x in range(ncol): |
|
1219 | for x in range(ncol): | |
| 1212 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
1220 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) | |
| 1213 |
|
1221 | |||
| 1214 | def run(self, dataOut, id, wintitle="", channelList=None, |
|
1222 | def run(self, dataOut, id, wintitle="", channelList=None, | |
| 1215 | xmin=None, xmax=None, ymin=None, ymax=None, |
|
1223 | xmin=None, xmax=None, ymin=None, ymax=None, | |
| 1216 | save=False, figpath='./', figfile=None, show=True, |
|
1224 | save=False, figpath='./', figfile=None, show=True, | |
| 1217 | ftp=False, wr_period=1, server=None, |
|
1225 | ftp=False, wr_period=1, server=None, | |
| 1218 | folder=None, username=None, password=None, |
|
1226 | folder=None, username=None, password=None, | |
| 1219 | xaxis="frequency"): |
|
1227 | xaxis="frequency"): | |
| 1220 |
|
1228 | |||
| 1221 |
|
1229 | |||
| 1222 | if channelList == None: |
|
1230 | if channelList == None: | |
| 1223 | channelIndexList = dataOut.channelIndexList |
|
1231 | channelIndexList = dataOut.channelIndexList | |
| 1224 | channelList = dataOut.channelList |
|
1232 | channelList = dataOut.channelList | |
| 1225 | else: |
|
1233 | else: | |
| 1226 | channelIndexList = [] |
|
1234 | channelIndexList = [] | |
| 1227 | for channel in channelList: |
|
1235 | for channel in channelList: | |
| 1228 | if channel not in dataOut.channelList: |
|
1236 | if channel not in dataOut.channelList: | |
| 1229 | raise ValueError, "Channel %d is not in dataOut.channelList" |
|
1237 | raise ValueError, "Channel %d is not in dataOut.channelList" | |
| 1230 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
1238 | channelIndexList.append(dataOut.channelList.index(channel)) | |
| 1231 |
|
1239 | |||
| 1232 | factor = dataOut.normFactor |
|
1240 | factor = dataOut.normFactor | |
| 1233 |
|
1241 | |||
| 1234 | y = dataOut.getHeiRange() |
|
1242 | y = dataOut.getHeiRange() | |
| 1235 |
|
1243 | |||
| 1236 | z = dataOut.data_spc/factor |
|
1244 | z = dataOut.data_spc/factor | |
| 1237 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
1245 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | |
| 1238 |
|
1246 | |||
| 1239 | hei_index = numpy.arange(25)*3 + 20 |
|
1247 | hei_index = numpy.arange(25)*3 + 20 | |
| 1240 |
|
1248 | |||
| 1241 | if xaxis == "frequency": |
|
1249 | if xaxis == "frequency": | |
| 1242 | x = dataOut.getFreqRange()/1000. |
|
1250 | x = dataOut.getFreqRange()/1000. | |
| 1243 | zdB = 10*numpy.log10(z[0,:,hei_index]) |
|
1251 | zdB = 10*numpy.log10(z[0,:,hei_index]) | |
| 1244 | xlabel = "Frequency (kHz)" |
|
1252 | xlabel = "Frequency (kHz)" | |
| 1245 | ylabel = "Power (dB)" |
|
1253 | ylabel = "Power (dB)" | |
| 1246 |
|
1254 | |||
| 1247 | elif xaxis == "time": |
|
1255 | elif xaxis == "time": | |
| 1248 | x = dataOut.getAcfRange() |
|
1256 | x = dataOut.getAcfRange() | |
| 1249 | zdB = z[0,:,hei_index] |
|
1257 | zdB = z[0,:,hei_index] | |
| 1250 | xlabel = "Time (ms)" |
|
1258 | xlabel = "Time (ms)" | |
| 1251 | ylabel = "ACF" |
|
1259 | ylabel = "ACF" | |
| 1252 |
|
1260 | |||
| 1253 | else: |
|
1261 | else: | |
| 1254 | x = dataOut.getVelRange() |
|
1262 | x = dataOut.getVelRange() | |
| 1255 | zdB = 10*numpy.log10(z[0,:,hei_index]) |
|
1263 | zdB = 10*numpy.log10(z[0,:,hei_index]) | |
| 1256 | xlabel = "Velocity (m/s)" |
|
1264 | xlabel = "Velocity (m/s)" | |
| 1257 | ylabel = "Power (dB)" |
|
1265 | ylabel = "Power (dB)" | |
| 1258 |
|
1266 | |||
| 1259 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) |
|
1267 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) | |
| 1260 | title = wintitle + " Range Cuts %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
1268 | title = wintitle + " Range Cuts %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
| 1261 |
|
1269 | |||
| 1262 | if not self.isConfig: |
|
1270 | if not self.isConfig: | |
| 1263 |
|
1271 | |||
| 1264 | nplots = 1 |
|
1272 | nplots = 1 | |
| 1265 |
|
1273 | |||
| 1266 | self.setup(id=id, |
|
1274 | self.setup(id=id, | |
| 1267 | nplots=nplots, |
|
1275 | nplots=nplots, | |
| 1268 | wintitle=wintitle, |
|
1276 | wintitle=wintitle, | |
| 1269 | show=show) |
|
1277 | show=show) | |
| 1270 |
|
1278 | |||
| 1271 | if xmin == None: xmin = numpy.nanmin(x)*0.9 |
|
1279 | if xmin == None: xmin = numpy.nanmin(x)*0.9 | |
| 1272 | if xmax == None: xmax = numpy.nanmax(x)*1.1 |
|
1280 | if xmax == None: xmax = numpy.nanmax(x)*1.1 | |
| 1273 | if ymin == None: ymin = numpy.nanmin(zdB) |
|
1281 | if ymin == None: ymin = numpy.nanmin(zdB) | |
| 1274 | if ymax == None: ymax = numpy.nanmax(zdB) |
|
1282 | if ymax == None: ymax = numpy.nanmax(zdB) | |
| 1275 |
|
1283 | |||
| 1276 | self.isConfig = True |
|
1284 | self.isConfig = True | |
| 1277 |
|
1285 | |||
| 1278 | self.setWinTitle(title) |
|
1286 | self.setWinTitle(title) | |
| 1279 |
|
1287 | |||
| 1280 | title = "Spectra Cuts: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
1288 | title = "Spectra Cuts: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
| 1281 | axes = self.axesList[0] |
|
1289 | axes = self.axesList[0] | |
| 1282 |
|
1290 | |||
| 1283 | legendlabels = ["Range = %dKm" %y[i] for i in hei_index] |
|
1291 | legendlabels = ["Range = %dKm" %y[i] for i in hei_index] | |
| 1284 |
|
1292 | |||
| 1285 | axes.pmultilineyaxis( x, zdB, |
|
1293 | axes.pmultilineyaxis( x, zdB, | |
| 1286 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, |
|
1294 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, | |
| 1287 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, |
|
1295 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, | |
| 1288 | ytick_visible=True, nxticks=5, |
|
1296 | ytick_visible=True, nxticks=5, | |
| 1289 | grid='x') |
|
1297 | grid='x') | |
| 1290 |
|
1298 | |||
| 1291 | self.draw() |
|
1299 | self.draw() | |
| 1292 |
|
1300 | |||
| 1293 | self.save(figpath=figpath, |
|
1301 | self.save(figpath=figpath, | |
| 1294 | figfile=figfile, |
|
1302 | figfile=figfile, | |
| 1295 | save=save, |
|
1303 | save=save, | |
| 1296 | ftp=ftp, |
|
1304 | ftp=ftp, | |
| 1297 | wr_period=wr_period, |
|
1305 | wr_period=wr_period, | |
| 1298 | thisDatetime=thisDatetime) |
|
1306 | thisDatetime=thisDatetime) | |
| 1299 |
|
1307 | |||
| 1300 | class Noise(Figure): |
|
1308 | class Noise(Figure): | |
| 1301 |
|
1309 | |||
| 1302 | isConfig = None |
|
1310 | isConfig = None | |
| 1303 | __nsubplots = None |
|
1311 | __nsubplots = None | |
| 1304 |
|
1312 | |||
| 1305 | PREFIX = 'noise' |
|
1313 | PREFIX = 'noise' | |
| 1306 |
|
1314 | |||
| 1307 |
|
1315 | |||
| 1308 | def __init__(self, **kwargs): |
|
1316 | def __init__(self, **kwargs): | |
| 1309 | Figure.__init__(self, **kwargs) |
|
1317 | Figure.__init__(self, **kwargs) | |
| 1310 | self.timerange = 24*60*60 |
|
1318 | self.timerange = 24*60*60 | |
| 1311 | self.isConfig = False |
|
1319 | self.isConfig = False | |
| 1312 | self.__nsubplots = 1 |
|
1320 | self.__nsubplots = 1 | |
| 1313 | self.counter_imagwr = 0 |
|
1321 | self.counter_imagwr = 0 | |
| 1314 | self.WIDTH = 800 |
|
1322 | self.WIDTH = 800 | |
| 1315 | self.HEIGHT = 400 |
|
1323 | self.HEIGHT = 400 | |
| 1316 | self.WIDTHPROF = 120 |
|
1324 | self.WIDTHPROF = 120 | |
| 1317 | self.HEIGHTPROF = 0 |
|
1325 | self.HEIGHTPROF = 0 | |
| 1318 | self.xdata = None |
|
1326 | self.xdata = None | |
| 1319 | self.ydata = None |
|
1327 | self.ydata = None | |
| 1320 |
|
1328 | |||
| 1321 | self.PLOT_CODE = NOISE_CODE |
|
1329 | self.PLOT_CODE = NOISE_CODE | |
| 1322 |
|
1330 | |||
| 1323 | self.FTP_WEI = None |
|
1331 | self.FTP_WEI = None | |
| 1324 | self.EXP_CODE = None |
|
1332 | self.EXP_CODE = None | |
| 1325 | self.SUB_EXP_CODE = None |
|
1333 | self.SUB_EXP_CODE = None | |
| 1326 | self.PLOT_POS = None |
|
1334 | self.PLOT_POS = None | |
| 1327 | self.figfile = None |
|
1335 | self.figfile = None | |
| 1328 |
|
1336 | |||
| 1329 | self.xmin = None |
|
1337 | self.xmin = None | |
| 1330 | self.xmax = None |
|
1338 | self.xmax = None | |
| 1331 |
|
1339 | |||
| 1332 | def getSubplots(self): |
|
1340 | def getSubplots(self): | |
| 1333 |
|
1341 | |||
| 1334 | ncol = 1 |
|
1342 | ncol = 1 | |
| 1335 | nrow = 1 |
|
1343 | nrow = 1 | |
| 1336 |
|
1344 | |||
| 1337 | return nrow, ncol |
|
1345 | return nrow, ncol | |
| 1338 |
|
1346 | |||
| 1339 | def openfile(self, filename): |
|
1347 | def openfile(self, filename): | |
| 1340 | dirname = os.path.dirname(filename) |
|
1348 | dirname = os.path.dirname(filename) | |
| 1341 |
|
1349 | |||
| 1342 | if not os.path.exists(dirname): |
|
1350 | if not os.path.exists(dirname): | |
| 1343 | os.mkdir(dirname) |
|
1351 | os.mkdir(dirname) | |
| 1344 |
|
1352 | |||
| 1345 | f = open(filename,'w+') |
|
1353 | f = open(filename,'w+') | |
| 1346 | f.write('\n\n') |
|
1354 | f.write('\n\n') | |
| 1347 | f.write('JICAMARCA RADIO OBSERVATORY - Noise \n') |
|
1355 | f.write('JICAMARCA RADIO OBSERVATORY - Noise \n') | |
| 1348 | f.write('DD MM YYYY HH MM SS Channel0 Channel1 Channel2 Channel3\n\n' ) |
|
1356 | f.write('DD MM YYYY HH MM SS Channel0 Channel1 Channel2 Channel3\n\n' ) | |
| 1349 | f.close() |
|
1357 | f.close() | |
| 1350 |
|
1358 | |||
| 1351 | def save_data(self, filename_phase, data, data_datetime): |
|
1359 | def save_data(self, filename_phase, data, data_datetime): | |
| 1352 |
|
1360 | |||
| 1353 | f=open(filename_phase,'a') |
|
1361 | f=open(filename_phase,'a') | |
| 1354 |
|
1362 | |||
| 1355 | timetuple_data = data_datetime.timetuple() |
|
1363 | timetuple_data = data_datetime.timetuple() | |
| 1356 | day = str(timetuple_data.tm_mday) |
|
1364 | day = str(timetuple_data.tm_mday) | |
| 1357 | month = str(timetuple_data.tm_mon) |
|
1365 | month = str(timetuple_data.tm_mon) | |
| 1358 | year = str(timetuple_data.tm_year) |
|
1366 | year = str(timetuple_data.tm_year) | |
| 1359 | hour = str(timetuple_data.tm_hour) |
|
1367 | hour = str(timetuple_data.tm_hour) | |
| 1360 | minute = str(timetuple_data.tm_min) |
|
1368 | minute = str(timetuple_data.tm_min) | |
| 1361 | second = str(timetuple_data.tm_sec) |
|
1369 | second = str(timetuple_data.tm_sec) | |
| 1362 |
|
1370 | |||
| 1363 | data_msg = '' |
|
1371 | data_msg = '' | |
| 1364 | for i in range(len(data)): |
|
1372 | for i in range(len(data)): | |
| 1365 | data_msg += str(data[i]) + ' ' |
|
1373 | data_msg += str(data[i]) + ' ' | |
| 1366 |
|
1374 | |||
| 1367 | f.write(day+' '+month+' '+year+' '+hour+' '+minute+' '+second+' ' + data_msg + '\n') |
|
1375 | f.write(day+' '+month+' '+year+' '+hour+' '+minute+' '+second+' ' + data_msg + '\n') | |
| 1368 | f.close() |
|
1376 | f.close() | |
| 1369 |
|
1377 | |||
| 1370 |
|
1378 | |||
| 1371 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
1379 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): | |
| 1372 |
|
1380 | |||
| 1373 | self.__showprofile = showprofile |
|
1381 | self.__showprofile = showprofile | |
| 1374 | self.nplots = nplots |
|
1382 | self.nplots = nplots | |
| 1375 |
|
1383 | |||
| 1376 | ncolspan = 7 |
|
1384 | ncolspan = 7 | |
| 1377 | colspan = 6 |
|
1385 | colspan = 6 | |
| 1378 | self.__nsubplots = 2 |
|
1386 | self.__nsubplots = 2 | |
| 1379 |
|
1387 | |||
| 1380 | self.createFigure(id = id, |
|
1388 | self.createFigure(id = id, | |
| 1381 | wintitle = wintitle, |
|
1389 | wintitle = wintitle, | |
| 1382 | widthplot = self.WIDTH+self.WIDTHPROF, |
|
1390 | widthplot = self.WIDTH+self.WIDTHPROF, | |
| 1383 | heightplot = self.HEIGHT+self.HEIGHTPROF, |
|
1391 | heightplot = self.HEIGHT+self.HEIGHTPROF, | |
| 1384 | show=show) |
|
1392 | show=show) | |
| 1385 |
|
1393 | |||
| 1386 | nrow, ncol = self.getSubplots() |
|
1394 | nrow, ncol = self.getSubplots() | |
| 1387 |
|
1395 | |||
| 1388 | self.addAxes(nrow, ncol*ncolspan, 0, 0, colspan, 1) |
|
1396 | self.addAxes(nrow, ncol*ncolspan, 0, 0, colspan, 1) | |
| 1389 |
|
1397 | |||
| 1390 |
|
1398 | |||
| 1391 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile='True', |
|
1399 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile='True', | |
| 1392 | xmin=None, xmax=None, ymin=None, ymax=None, |
|
1400 | xmin=None, xmax=None, ymin=None, ymax=None, | |
| 1393 | timerange=None, |
|
1401 | timerange=None, | |
| 1394 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, |
|
1402 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, | |
| 1395 | server=None, folder=None, username=None, password=None, |
|
1403 | server=None, folder=None, username=None, password=None, | |
| 1396 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): |
|
1404 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): | |
| 1397 |
|
1405 | |||
| 1398 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): |
|
1406 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): | |
| 1399 | return |
|
1407 | return | |
| 1400 |
|
1408 | |||
| 1401 | if channelList == None: |
|
1409 | if channelList == None: | |
| 1402 | channelIndexList = dataOut.channelIndexList |
|
1410 | channelIndexList = dataOut.channelIndexList | |
| 1403 | channelList = dataOut.channelList |
|
1411 | channelList = dataOut.channelList | |
| 1404 | else: |
|
1412 | else: | |
| 1405 | channelIndexList = [] |
|
1413 | channelIndexList = [] | |
| 1406 | for channel in channelList: |
|
1414 | for channel in channelList: | |
| 1407 | if channel not in dataOut.channelList: |
|
1415 | if channel not in dataOut.channelList: | |
| 1408 | raise ValueError, "Channel %d is not in dataOut.channelList" |
|
1416 | raise ValueError, "Channel %d is not in dataOut.channelList" | |
| 1409 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
1417 | channelIndexList.append(dataOut.channelList.index(channel)) | |
| 1410 |
|
1418 | |||
| 1411 | x = dataOut.getTimeRange() |
|
1419 | x = dataOut.getTimeRange() | |
| 1412 | #y = dataOut.getHeiRange() |
|
1420 | #y = dataOut.getHeiRange() | |
| 1413 | factor = dataOut.normFactor |
|
1421 | factor = dataOut.normFactor | |
| 1414 | noise = dataOut.noise[channelIndexList]/factor |
|
1422 | noise = dataOut.noise[channelIndexList]/factor | |
| 1415 | noisedB = 10*numpy.log10(noise) |
|
1423 | noisedB = 10*numpy.log10(noise) | |
| 1416 |
|
1424 | |||
| 1417 | thisDatetime = dataOut.datatime |
|
1425 | thisDatetime = dataOut.datatime | |
| 1418 |
|
1426 | |||
| 1419 | title = wintitle + " Noise" # : %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
1427 | title = wintitle + " Noise" # : %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
| 1420 | xlabel = "" |
|
1428 | xlabel = "" | |
| 1421 | ylabel = "Intensity (dB)" |
|
1429 | ylabel = "Intensity (dB)" | |
| 1422 | update_figfile = False |
|
1430 | update_figfile = False | |
| 1423 |
|
1431 | |||
| 1424 | if not self.isConfig: |
|
1432 | if not self.isConfig: | |
| 1425 |
|
1433 | |||
| 1426 | nplots = 1 |
|
1434 | nplots = 1 | |
| 1427 |
|
1435 | |||
| 1428 | self.setup(id=id, |
|
1436 | self.setup(id=id, | |
| 1429 | nplots=nplots, |
|
1437 | nplots=nplots, | |
| 1430 | wintitle=wintitle, |
|
1438 | wintitle=wintitle, | |
| 1431 | showprofile=showprofile, |
|
1439 | showprofile=showprofile, | |
| 1432 | show=show) |
|
1440 | show=show) | |
| 1433 |
|
1441 | |||
| 1434 | if timerange != None: |
|
1442 | if timerange != None: | |
| 1435 | self.timerange = timerange |
|
1443 | self.timerange = timerange | |
| 1436 |
|
1444 | |||
| 1437 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) |
|
1445 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) | |
| 1438 |
|
1446 | |||
| 1439 | if ymin == None: ymin = numpy.floor(numpy.nanmin(noisedB)) - 10.0 |
|
1447 | if ymin == None: ymin = numpy.floor(numpy.nanmin(noisedB)) - 10.0 | |
| 1440 | if ymax == None: ymax = numpy.nanmax(noisedB) + 10.0 |
|
1448 | if ymax == None: ymax = numpy.nanmax(noisedB) + 10.0 | |
| 1441 |
|
1449 | |||
| 1442 | self.FTP_WEI = ftp_wei |
|
1450 | self.FTP_WEI = ftp_wei | |
| 1443 | self.EXP_CODE = exp_code |
|
1451 | self.EXP_CODE = exp_code | |
| 1444 | self.SUB_EXP_CODE = sub_exp_code |
|
1452 | self.SUB_EXP_CODE = sub_exp_code | |
| 1445 | self.PLOT_POS = plot_pos |
|
1453 | self.PLOT_POS = plot_pos | |
| 1446 |
|
1454 | |||
| 1447 |
|
1455 | |||
| 1448 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
1456 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 1449 | self.isConfig = True |
|
1457 | self.isConfig = True | |
| 1450 | self.figfile = figfile |
|
1458 | self.figfile = figfile | |
| 1451 | self.xdata = numpy.array([]) |
|
1459 | self.xdata = numpy.array([]) | |
| 1452 | self.ydata = numpy.array([]) |
|
1460 | self.ydata = numpy.array([]) | |
| 1453 |
|
1461 | |||
| 1454 | update_figfile = True |
|
1462 | update_figfile = True | |
| 1455 |
|
1463 | |||
| 1456 | #open file beacon phase |
|
1464 | #open file beacon phase | |
| 1457 | path = '%s%03d' %(self.PREFIX, self.id) |
|
1465 | path = '%s%03d' %(self.PREFIX, self.id) | |
| 1458 | noise_file = os.path.join(path,'%s.txt'%self.name) |
|
1466 | noise_file = os.path.join(path,'%s.txt'%self.name) | |
| 1459 | self.filename_noise = os.path.join(figpath,noise_file) |
|
1467 | self.filename_noise = os.path.join(figpath,noise_file) | |
| 1460 |
|
1468 | |||
| 1461 | self.setWinTitle(title) |
|
1469 | self.setWinTitle(title) | |
| 1462 |
|
1470 | |||
| 1463 | title = "Noise %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) |
|
1471 | title = "Noise %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) | |
| 1464 |
|
1472 | |||
| 1465 | legendlabels = ["channel %d"%(idchannel) for idchannel in channelList] |
|
1473 | legendlabels = ["channel %d"%(idchannel) for idchannel in channelList] | |
| 1466 | axes = self.axesList[0] |
|
1474 | axes = self.axesList[0] | |
| 1467 |
|
1475 | |||
| 1468 | self.xdata = numpy.hstack((self.xdata, x[0:1])) |
|
1476 | self.xdata = numpy.hstack((self.xdata, x[0:1])) | |
| 1469 |
|
1477 | |||
| 1470 | if len(self.ydata)==0: |
|
1478 | if len(self.ydata)==0: | |
| 1471 | self.ydata = noisedB.reshape(-1,1) |
|
1479 | self.ydata = noisedB.reshape(-1,1) | |
| 1472 | else: |
|
1480 | else: | |
| 1473 | self.ydata = numpy.hstack((self.ydata, noisedB.reshape(-1,1))) |
|
1481 | self.ydata = numpy.hstack((self.ydata, noisedB.reshape(-1,1))) | |
| 1474 |
|
1482 | |||
| 1475 |
|
1483 | |||
| 1476 | axes.pmultilineyaxis(x=self.xdata, y=self.ydata, |
|
1484 | axes.pmultilineyaxis(x=self.xdata, y=self.ydata, | |
| 1477 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, |
|
1485 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, | |
| 1478 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid", |
|
1486 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid", | |
| 1479 | XAxisAsTime=True, grid='both' |
|
1487 | XAxisAsTime=True, grid='both' | |
| 1480 | ) |
|
1488 | ) | |
| 1481 |
|
1489 | |||
| 1482 | self.draw() |
|
1490 | self.draw() | |
| 1483 |
|
1491 | |||
| 1484 | if dataOut.ltctime >= self.xmax: |
|
1492 | if dataOut.ltctime >= self.xmax: | |
| 1485 | self.counter_imagwr = wr_period |
|
1493 | self.counter_imagwr = wr_period | |
| 1486 | self.isConfig = False |
|
1494 | self.isConfig = False | |
| 1487 | update_figfile = True |
|
1495 | update_figfile = True | |
| 1488 |
|
1496 | |||
| 1489 | self.save(figpath=figpath, |
|
1497 | self.save(figpath=figpath, | |
| 1490 | figfile=figfile, |
|
1498 | figfile=figfile, | |
| 1491 | save=save, |
|
1499 | save=save, | |
| 1492 | ftp=ftp, |
|
1500 | ftp=ftp, | |
| 1493 | wr_period=wr_period, |
|
1501 | wr_period=wr_period, | |
| 1494 | thisDatetime=thisDatetime, |
|
1502 | thisDatetime=thisDatetime, | |
| 1495 | update_figfile=update_figfile) |
|
1503 | update_figfile=update_figfile) | |
| 1496 |
|
1504 | |||
| 1497 | #store data beacon phase |
|
1505 | #store data beacon phase | |
| 1498 | if save: |
|
1506 | if save: | |
| 1499 | self.save_data(self.filename_noise, noisedB, thisDatetime) |
|
1507 | self.save_data(self.filename_noise, noisedB, thisDatetime) | |
| 1500 |
|
1508 | |||
| 1501 | class BeaconPhase(Figure): |
|
1509 | class BeaconPhase(Figure): | |
| 1502 |
|
1510 | |||
| 1503 | __isConfig = None |
|
1511 | __isConfig = None | |
| 1504 | __nsubplots = None |
|
1512 | __nsubplots = None | |
| 1505 |
|
1513 | |||
| 1506 | PREFIX = 'beacon_phase' |
|
1514 | PREFIX = 'beacon_phase' | |
| 1507 |
|
1515 | |||
| 1508 | def __init__(self, **kwargs): |
|
1516 | def __init__(self, **kwargs): | |
| 1509 | Figure.__init__(self, **kwargs) |
|
1517 | Figure.__init__(self, **kwargs) | |
| 1510 | self.timerange = 24*60*60 |
|
1518 | self.timerange = 24*60*60 | |
| 1511 | self.isConfig = False |
|
1519 | self.isConfig = False | |
| 1512 | self.__nsubplots = 1 |
|
1520 | self.__nsubplots = 1 | |
| 1513 | self.counter_imagwr = 0 |
|
1521 | self.counter_imagwr = 0 | |
| 1514 | self.WIDTH = 800 |
|
1522 | self.WIDTH = 800 | |
| 1515 | self.HEIGHT = 400 |
|
1523 | self.HEIGHT = 400 | |
| 1516 | self.WIDTHPROF = 120 |
|
1524 | self.WIDTHPROF = 120 | |
| 1517 | self.HEIGHTPROF = 0 |
|
1525 | self.HEIGHTPROF = 0 | |
| 1518 | self.xdata = None |
|
1526 | self.xdata = None | |
| 1519 | self.ydata = None |
|
1527 | self.ydata = None | |
| 1520 |
|
1528 | |||
| 1521 | self.PLOT_CODE = BEACON_CODE |
|
1529 | self.PLOT_CODE = BEACON_CODE | |
| 1522 |
|
1530 | |||
| 1523 | self.FTP_WEI = None |
|
1531 | self.FTP_WEI = None | |
| 1524 | self.EXP_CODE = None |
|
1532 | self.EXP_CODE = None | |
| 1525 | self.SUB_EXP_CODE = None |
|
1533 | self.SUB_EXP_CODE = None | |
| 1526 | self.PLOT_POS = None |
|
1534 | self.PLOT_POS = None | |
| 1527 |
|
1535 | |||
| 1528 | self.filename_phase = None |
|
1536 | self.filename_phase = None | |
| 1529 |
|
1537 | |||
| 1530 | self.figfile = None |
|
1538 | self.figfile = None | |
| 1531 |
|
1539 | |||
| 1532 | self.xmin = None |
|
1540 | self.xmin = None | |
| 1533 | self.xmax = None |
|
1541 | self.xmax = None | |
| 1534 |
|
1542 | |||
| 1535 | def getSubplots(self): |
|
1543 | def getSubplots(self): | |
| 1536 |
|
1544 | |||
| 1537 | ncol = 1 |
|
1545 | ncol = 1 | |
| 1538 | nrow = 1 |
|
1546 | nrow = 1 | |
| 1539 |
|
1547 | |||
| 1540 | return nrow, ncol |
|
1548 | return nrow, ncol | |
| 1541 |
|
1549 | |||
| 1542 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
1550 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): | |
| 1543 |
|
1551 | |||
| 1544 | self.__showprofile = showprofile |
|
1552 | self.__showprofile = showprofile | |
| 1545 | self.nplots = nplots |
|
1553 | self.nplots = nplots | |
| 1546 |
|
1554 | |||
| 1547 | ncolspan = 7 |
|
1555 | ncolspan = 7 | |
| 1548 | colspan = 6 |
|
1556 | colspan = 6 | |
| 1549 | self.__nsubplots = 2 |
|
1557 | self.__nsubplots = 2 | |
| 1550 |
|
1558 | |||
| 1551 | self.createFigure(id = id, |
|
1559 | self.createFigure(id = id, | |
| 1552 | wintitle = wintitle, |
|
1560 | wintitle = wintitle, | |
| 1553 | widthplot = self.WIDTH+self.WIDTHPROF, |
|
1561 | widthplot = self.WIDTH+self.WIDTHPROF, | |
| 1554 | heightplot = self.HEIGHT+self.HEIGHTPROF, |
|
1562 | heightplot = self.HEIGHT+self.HEIGHTPROF, | |
| 1555 | show=show) |
|
1563 | show=show) | |
| 1556 |
|
1564 | |||
| 1557 | nrow, ncol = self.getSubplots() |
|
1565 | nrow, ncol = self.getSubplots() | |
| 1558 |
|
1566 | |||
| 1559 | self.addAxes(nrow, ncol*ncolspan, 0, 0, colspan, 1) |
|
1567 | self.addAxes(nrow, ncol*ncolspan, 0, 0, colspan, 1) | |
| 1560 |
|
1568 | |||
| 1561 | def save_phase(self, filename_phase): |
|
1569 | def save_phase(self, filename_phase): | |
| 1562 | f = open(filename_phase,'w+') |
|
1570 | f = open(filename_phase,'w+') | |
| 1563 | f.write('\n\n') |
|
1571 | f.write('\n\n') | |
| 1564 | f.write('JICAMARCA RADIO OBSERVATORY - Beacon Phase \n') |
|
1572 | f.write('JICAMARCA RADIO OBSERVATORY - Beacon Phase \n') | |
| 1565 | f.write('DD MM YYYY HH MM SS pair(2,0) pair(2,1) pair(2,3) pair(2,4)\n\n' ) |
|
1573 | f.write('DD MM YYYY HH MM SS pair(2,0) pair(2,1) pair(2,3) pair(2,4)\n\n' ) | |
| 1566 | f.close() |
|
1574 | f.close() | |
| 1567 |
|
1575 | |||
| 1568 | def save_data(self, filename_phase, data, data_datetime): |
|
1576 | def save_data(self, filename_phase, data, data_datetime): | |
| 1569 | f=open(filename_phase,'a') |
|
1577 | f=open(filename_phase,'a') | |
| 1570 | timetuple_data = data_datetime.timetuple() |
|
1578 | timetuple_data = data_datetime.timetuple() | |
| 1571 | day = str(timetuple_data.tm_mday) |
|
1579 | day = str(timetuple_data.tm_mday) | |
| 1572 | month = str(timetuple_data.tm_mon) |
|
1580 | month = str(timetuple_data.tm_mon) | |
| 1573 | year = str(timetuple_data.tm_year) |
|
1581 | year = str(timetuple_data.tm_year) | |
| 1574 | hour = str(timetuple_data.tm_hour) |
|
1582 | hour = str(timetuple_data.tm_hour) | |
| 1575 | minute = str(timetuple_data.tm_min) |
|
1583 | minute = str(timetuple_data.tm_min) | |
| 1576 | second = str(timetuple_data.tm_sec) |
|
1584 | second = str(timetuple_data.tm_sec) | |
| 1577 | f.write(day+' '+month+' '+year+' '+hour+' '+minute+' '+second+' '+str(data[0])+' '+str(data[1])+' '+str(data[2])+' '+str(data[3])+'\n') |
|
1585 | f.write(day+' '+month+' '+year+' '+hour+' '+minute+' '+second+' '+str(data[0])+' '+str(data[1])+' '+str(data[2])+' '+str(data[3])+'\n') | |
| 1578 | f.close() |
|
1586 | f.close() | |
| 1579 |
|
1587 | |||
| 1580 |
|
1588 | |||
| 1581 | def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True', |
|
1589 | def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True', | |
| 1582 | xmin=None, xmax=None, ymin=None, ymax=None, hmin=None, hmax=None, |
|
1590 | xmin=None, xmax=None, ymin=None, ymax=None, hmin=None, hmax=None, | |
| 1583 | timerange=None, |
|
1591 | timerange=None, | |
| 1584 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, |
|
1592 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, | |
| 1585 | server=None, folder=None, username=None, password=None, |
|
1593 | server=None, folder=None, username=None, password=None, | |
| 1586 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): |
|
1594 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): | |
| 1587 |
|
1595 | |||
| 1588 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): |
|
1596 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): | |
| 1589 | return |
|
1597 | return | |
| 1590 |
|
1598 | |||
| 1591 | if pairsList == None: |
|
1599 | if pairsList == None: | |
| 1592 | pairsIndexList = dataOut.pairsIndexList[:10] |
|
1600 | pairsIndexList = dataOut.pairsIndexList[:10] | |
| 1593 | else: |
|
1601 | else: | |
| 1594 | pairsIndexList = [] |
|
1602 | pairsIndexList = [] | |
| 1595 | for pair in pairsList: |
|
1603 | for pair in pairsList: | |
| 1596 | if pair not in dataOut.pairsList: |
|
1604 | if pair not in dataOut.pairsList: | |
| 1597 | raise ValueError, "Pair %s is not in dataOut.pairsList" %(pair) |
|
1605 | raise ValueError, "Pair %s is not in dataOut.pairsList" %(pair) | |
| 1598 | pairsIndexList.append(dataOut.pairsList.index(pair)) |
|
1606 | pairsIndexList.append(dataOut.pairsList.index(pair)) | |
| 1599 |
|
1607 | |||
| 1600 | if pairsIndexList == []: |
|
1608 | if pairsIndexList == []: | |
| 1601 | return |
|
1609 | return | |
| 1602 |
|
1610 | |||
| 1603 | # if len(pairsIndexList) > 4: |
|
1611 | # if len(pairsIndexList) > 4: | |
| 1604 | # pairsIndexList = pairsIndexList[0:4] |
|
1612 | # pairsIndexList = pairsIndexList[0:4] | |
| 1605 |
|
1613 | |||
| 1606 | hmin_index = None |
|
1614 | hmin_index = None | |
| 1607 | hmax_index = None |
|
1615 | hmax_index = None | |
| 1608 |
|
1616 | |||
| 1609 | if hmin != None and hmax != None: |
|
1617 | if hmin != None and hmax != None: | |
| 1610 | indexes = numpy.arange(dataOut.nHeights) |
|
1618 | indexes = numpy.arange(dataOut.nHeights) | |
| 1611 | hmin_list = indexes[dataOut.heightList >= hmin] |
|
1619 | hmin_list = indexes[dataOut.heightList >= hmin] | |
| 1612 | hmax_list = indexes[dataOut.heightList <= hmax] |
|
1620 | hmax_list = indexes[dataOut.heightList <= hmax] | |
| 1613 |
|
1621 | |||
| 1614 | if hmin_list.any(): |
|
1622 | if hmin_list.any(): | |
| 1615 | hmin_index = hmin_list[0] |
|
1623 | hmin_index = hmin_list[0] | |
| 1616 |
|
1624 | |||
| 1617 | if hmax_list.any(): |
|
1625 | if hmax_list.any(): | |
| 1618 | hmax_index = hmax_list[-1]+1 |
|
1626 | hmax_index = hmax_list[-1]+1 | |
| 1619 |
|
1627 | |||
| 1620 | x = dataOut.getTimeRange() |
|
1628 | x = dataOut.getTimeRange() | |
| 1621 | #y = dataOut.getHeiRange() |
|
1629 | #y = dataOut.getHeiRange() | |
| 1622 |
|
1630 | |||
| 1623 |
|
1631 | |||
| 1624 | thisDatetime = dataOut.datatime |
|
1632 | thisDatetime = dataOut.datatime | |
| 1625 |
|
1633 | |||
| 1626 | title = wintitle + " Signal Phase" # : %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
1634 | title = wintitle + " Signal Phase" # : %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
| 1627 | xlabel = "Local Time" |
|
1635 | xlabel = "Local Time" | |
| 1628 | ylabel = "Phase (degrees)" |
|
1636 | ylabel = "Phase (degrees)" | |
| 1629 |
|
1637 | |||
| 1630 | update_figfile = False |
|
1638 | update_figfile = False | |
| 1631 |
|
1639 | |||
| 1632 | nplots = len(pairsIndexList) |
|
1640 | nplots = len(pairsIndexList) | |
| 1633 | #phase = numpy.zeros((len(pairsIndexList),len(dataOut.beacon_heiIndexList))) |
|
1641 | #phase = numpy.zeros((len(pairsIndexList),len(dataOut.beacon_heiIndexList))) | |
| 1634 | phase_beacon = numpy.zeros(len(pairsIndexList)) |
|
1642 | phase_beacon = numpy.zeros(len(pairsIndexList)) | |
| 1635 | for i in range(nplots): |
|
1643 | for i in range(nplots): | |
| 1636 | pair = dataOut.pairsList[pairsIndexList[i]] |
|
1644 | pair = dataOut.pairsList[pairsIndexList[i]] | |
| 1637 | ccf = numpy.average(dataOut.data_cspc[pairsIndexList[i], :, hmin_index:hmax_index], axis=0) |
|
1645 | ccf = numpy.average(dataOut.data_cspc[pairsIndexList[i], :, hmin_index:hmax_index], axis=0) | |
| 1638 | powa = numpy.average(dataOut.data_spc[pair[0], :, hmin_index:hmax_index], axis=0) |
|
1646 | powa = numpy.average(dataOut.data_spc[pair[0], :, hmin_index:hmax_index], axis=0) | |
| 1639 | powb = numpy.average(dataOut.data_spc[pair[1], :, hmin_index:hmax_index], axis=0) |
|
1647 | powb = numpy.average(dataOut.data_spc[pair[1], :, hmin_index:hmax_index], axis=0) | |
| 1640 | avgcoherenceComplex = ccf/numpy.sqrt(powa*powb) |
|
1648 | avgcoherenceComplex = ccf/numpy.sqrt(powa*powb) | |
| 1641 | phase = numpy.arctan2(avgcoherenceComplex.imag, avgcoherenceComplex.real)*180/numpy.pi |
|
1649 | phase = numpy.arctan2(avgcoherenceComplex.imag, avgcoherenceComplex.real)*180/numpy.pi | |
| 1642 |
|
1650 | |||
| 1643 | #print "Phase %d%d" %(pair[0], pair[1]) |
|
1651 | #print "Phase %d%d" %(pair[0], pair[1]) | |
| 1644 | #print phase[dataOut.beacon_heiIndexList] |
|
1652 | #print phase[dataOut.beacon_heiIndexList] | |
| 1645 |
|
1653 | |||
| 1646 | if dataOut.beacon_heiIndexList: |
|
1654 | if dataOut.beacon_heiIndexList: | |
| 1647 | phase_beacon[i] = numpy.average(phase[dataOut.beacon_heiIndexList]) |
|
1655 | phase_beacon[i] = numpy.average(phase[dataOut.beacon_heiIndexList]) | |
| 1648 | else: |
|
1656 | else: | |
| 1649 | phase_beacon[i] = numpy.average(phase) |
|
1657 | phase_beacon[i] = numpy.average(phase) | |
| 1650 |
|
1658 | |||
| 1651 | if not self.isConfig: |
|
1659 | if not self.isConfig: | |
| 1652 |
|
1660 | |||
| 1653 | nplots = len(pairsIndexList) |
|
1661 | nplots = len(pairsIndexList) | |
| 1654 |
|
1662 | |||
| 1655 | self.setup(id=id, |
|
1663 | self.setup(id=id, | |
| 1656 | nplots=nplots, |
|
1664 | nplots=nplots, | |
| 1657 | wintitle=wintitle, |
|
1665 | wintitle=wintitle, | |
| 1658 | showprofile=showprofile, |
|
1666 | showprofile=showprofile, | |
| 1659 | show=show) |
|
1667 | show=show) | |
| 1660 |
|
1668 | |||
| 1661 | if timerange != None: |
|
1669 | if timerange != None: | |
| 1662 | self.timerange = timerange |
|
1670 | self.timerange = timerange | |
| 1663 |
|
1671 | |||
| 1664 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) |
|
1672 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) | |
| 1665 |
|
1673 | |||
| 1666 | if ymin == None: ymin = 0 |
|
1674 | if ymin == None: ymin = 0 | |
| 1667 | if ymax == None: ymax = 360 |
|
1675 | if ymax == None: ymax = 360 | |
| 1668 |
|
1676 | |||
| 1669 | self.FTP_WEI = ftp_wei |
|
1677 | self.FTP_WEI = ftp_wei | |
| 1670 | self.EXP_CODE = exp_code |
|
1678 | self.EXP_CODE = exp_code | |
| 1671 | self.SUB_EXP_CODE = sub_exp_code |
|
1679 | self.SUB_EXP_CODE = sub_exp_code | |
| 1672 | self.PLOT_POS = plot_pos |
|
1680 | self.PLOT_POS = plot_pos | |
| 1673 |
|
1681 | |||
| 1674 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
1682 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 1675 | self.isConfig = True |
|
1683 | self.isConfig = True | |
| 1676 | self.figfile = figfile |
|
1684 | self.figfile = figfile | |
| 1677 | self.xdata = numpy.array([]) |
|
1685 | self.xdata = numpy.array([]) | |
| 1678 | self.ydata = numpy.array([]) |
|
1686 | self.ydata = numpy.array([]) | |
| 1679 |
|
1687 | |||
| 1680 | update_figfile = True |
|
1688 | update_figfile = True | |
| 1681 |
|
1689 | |||
| 1682 | #open file beacon phase |
|
1690 | #open file beacon phase | |
| 1683 | path = '%s%03d' %(self.PREFIX, self.id) |
|
1691 | path = '%s%03d' %(self.PREFIX, self.id) | |
| 1684 | beacon_file = os.path.join(path,'%s.txt'%self.name) |
|
1692 | beacon_file = os.path.join(path,'%s.txt'%self.name) | |
| 1685 | self.filename_phase = os.path.join(figpath,beacon_file) |
|
1693 | self.filename_phase = os.path.join(figpath,beacon_file) | |
| 1686 | #self.save_phase(self.filename_phase) |
|
1694 | #self.save_phase(self.filename_phase) | |
| 1687 |
|
1695 | |||
| 1688 |
|
1696 | |||
| 1689 | #store data beacon phase |
|
1697 | #store data beacon phase | |
| 1690 | #self.save_data(self.filename_phase, phase_beacon, thisDatetime) |
|
1698 | #self.save_data(self.filename_phase, phase_beacon, thisDatetime) | |
| 1691 |
|
1699 | |||
| 1692 | self.setWinTitle(title) |
|
1700 | self.setWinTitle(title) | |
| 1693 |
|
1701 | |||
| 1694 |
|
1702 | |||
| 1695 | title = "Phase Plot %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) |
|
1703 | title = "Phase Plot %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) | |
| 1696 |
|
1704 | |||
| 1697 | legendlabels = ["Pair (%d,%d)"%(pair[0], pair[1]) for pair in dataOut.pairsList] |
|
1705 | legendlabels = ["Pair (%d,%d)"%(pair[0], pair[1]) for pair in dataOut.pairsList] | |
| 1698 |
|
1706 | |||
| 1699 | axes = self.axesList[0] |
|
1707 | axes = self.axesList[0] | |
| 1700 |
|
1708 | |||
| 1701 | self.xdata = numpy.hstack((self.xdata, x[0:1])) |
|
1709 | self.xdata = numpy.hstack((self.xdata, x[0:1])) | |
| 1702 |
|
1710 | |||
| 1703 | if len(self.ydata)==0: |
|
1711 | if len(self.ydata)==0: | |
| 1704 | self.ydata = phase_beacon.reshape(-1,1) |
|
1712 | self.ydata = phase_beacon.reshape(-1,1) | |
| 1705 | else: |
|
1713 | else: | |
| 1706 | self.ydata = numpy.hstack((self.ydata, phase_beacon.reshape(-1,1))) |
|
1714 | self.ydata = numpy.hstack((self.ydata, phase_beacon.reshape(-1,1))) | |
| 1707 |
|
1715 | |||
| 1708 |
|
1716 | |||
| 1709 | axes.pmultilineyaxis(x=self.xdata, y=self.ydata, |
|
1717 | axes.pmultilineyaxis(x=self.xdata, y=self.ydata, | |
| 1710 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, |
|
1718 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, | |
| 1711 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid", |
|
1719 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid", | |
| 1712 | XAxisAsTime=True, grid='both' |
|
1720 | XAxisAsTime=True, grid='both' | |
| 1713 | ) |
|
1721 | ) | |
| 1714 |
|
1722 | |||
| 1715 | self.draw() |
|
1723 | self.draw() | |
| 1716 |
|
1724 | |||
| 1717 | if dataOut.ltctime >= self.xmax: |
|
1725 | if dataOut.ltctime >= self.xmax: | |
| 1718 | self.counter_imagwr = wr_period |
|
1726 | self.counter_imagwr = wr_period | |
| 1719 | self.isConfig = False |
|
1727 | self.isConfig = False | |
| 1720 | update_figfile = True |
|
1728 | update_figfile = True | |
| 1721 |
|
1729 | |||
| 1722 | self.save(figpath=figpath, |
|
1730 | self.save(figpath=figpath, | |
| 1723 | figfile=figfile, |
|
1731 | figfile=figfile, | |
| 1724 | save=save, |
|
1732 | save=save, | |
| 1725 | ftp=ftp, |
|
1733 | ftp=ftp, | |
| 1726 | wr_period=wr_period, |
|
1734 | wr_period=wr_period, | |
| 1727 | thisDatetime=thisDatetime, |
|
1735 | thisDatetime=thisDatetime, | |
| 1728 | update_figfile=update_figfile) |
|
1736 | update_figfile=update_figfile) | |
| @@ -1,754 +1,793 | |||||
| 1 | import numpy |
|
1 | import numpy | |
| 2 |
|
2 | |||
| 3 | from jroproc_base import ProcessingUnit, Operation |
|
3 | from jroproc_base import ProcessingUnit, Operation | |
| 4 | from schainpy.model.data.jrodata import Spectra |
|
4 | from schainpy.model.data.jrodata import Spectra | |
| 5 | from schainpy.model.data.jrodata import hildebrand_sekhon |
|
5 | from schainpy.model.data.jrodata import hildebrand_sekhon | |
| 6 |
|
6 | |||
| 7 | class SpectraAFCProc(ProcessingUnit): |
|
7 | class SpectraAFCProc(ProcessingUnit): | |
| 8 |
|
8 | |||
| 9 | def __init__(self, **kwargs): |
|
9 | def __init__(self, **kwargs): | |
| 10 |
|
10 | |||
| 11 | ProcessingUnit.__init__(self, **kwargs) |
|
11 | ProcessingUnit.__init__(self, **kwargs) | |
| 12 |
|
12 | |||
| 13 | self.buffer = None |
|
13 | self.buffer = None | |
| 14 | self.firstdatatime = None |
|
14 | self.firstdatatime = None | |
| 15 | self.profIndex = 0 |
|
15 | self.profIndex = 0 | |
| 16 | self.dataOut = Spectra() |
|
16 | self.dataOut = Spectra() | |
| 17 | self.id_min = None |
|
17 | self.id_min = None | |
| 18 | self.id_max = None |
|
18 | self.id_max = None | |
| 19 |
|
19 | |||
| 20 | def __updateSpecFromVoltage(self): |
|
20 | def __updateSpecFromVoltage(self): | |
| 21 |
|
21 | |||
| 22 | self.dataOut.plotting = "spectra_acf" |
|
22 | self.dataOut.plotting = "spectra_acf" | |
| 23 |
|
23 | |||
| 24 | self.dataOut.timeZone = self.dataIn.timeZone |
|
24 | self.dataOut.timeZone = self.dataIn.timeZone | |
| 25 | self.dataOut.dstFlag = self.dataIn.dstFlag |
|
25 | self.dataOut.dstFlag = self.dataIn.dstFlag | |
| 26 | self.dataOut.errorCount = self.dataIn.errorCount |
|
26 | self.dataOut.errorCount = self.dataIn.errorCount | |
| 27 | self.dataOut.useLocalTime = self.dataIn.useLocalTime |
|
27 | self.dataOut.useLocalTime = self.dataIn.useLocalTime | |
| 28 |
|
28 | |||
| 29 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() |
|
29 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() | |
| 30 | self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy() |
|
30 | self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy() | |
| 31 | self.dataOut.ippSeconds = self.dataIn.getDeltaH()*(10**-6)/0.15 |
|
31 | self.dataOut.ippSeconds = self.dataIn.getDeltaH()*(10**-6)/0.15 | |
| 32 |
|
32 | |||
| 33 | self.dataOut.channelList = self.dataIn.channelList |
|
33 | self.dataOut.channelList = self.dataIn.channelList | |
| 34 | self.dataOut.heightList = self.dataIn.heightList |
|
34 | self.dataOut.heightList = self.dataIn.heightList | |
| 35 | self.dataOut.dtype = numpy.dtype([('real','<f4'),('imag','<f4')]) |
|
35 | self.dataOut.dtype = numpy.dtype([('real','<f4'),('imag','<f4')]) | |
| 36 |
|
36 | |||
| 37 | self.dataOut.nBaud = self.dataIn.nBaud |
|
37 | self.dataOut.nBaud = self.dataIn.nBaud | |
| 38 | self.dataOut.nCode = self.dataIn.nCode |
|
38 | self.dataOut.nCode = self.dataIn.nCode | |
| 39 | self.dataOut.code = self.dataIn.code |
|
39 | self.dataOut.code = self.dataIn.code | |
| 40 | # self.dataOut.nProfiles = self.dataOut.nFFTPoints |
|
40 | # self.dataOut.nProfiles = self.dataOut.nFFTPoints | |
| 41 |
|
41 | |||
| 42 | self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock |
|
42 | self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock | |
| 43 | self.dataOut.utctime = self.firstdatatime |
|
43 | self.dataOut.utctime = self.firstdatatime | |
| 44 | self.dataOut.flagDecodeData = self.dataIn.flagDecodeData #asumo q la data esta decodificada |
|
44 | self.dataOut.flagDecodeData = self.dataIn.flagDecodeData #asumo q la data esta decodificada | |
| 45 | self.dataOut.flagDeflipData = self.dataIn.flagDeflipData #asumo q la data esta sin flip |
|
45 | self.dataOut.flagDeflipData = self.dataIn.flagDeflipData #asumo q la data esta sin flip | |
| 46 | self.dataOut.flagShiftFFT = False |
|
46 | self.dataOut.flagShiftFFT = False | |
| 47 |
|
47 | |||
| 48 | self.dataOut.nCohInt = self.dataIn.nCohInt |
|
48 | self.dataOut.nCohInt = self.dataIn.nCohInt | |
| 49 | self.dataOut.nIncohInt = 1 |
|
49 | self.dataOut.nIncohInt = 1 | |
| 50 |
|
50 | |||
| 51 | self.dataOut.windowOfFilter = self.dataIn.windowOfFilter |
|
51 | self.dataOut.windowOfFilter = self.dataIn.windowOfFilter | |
| 52 |
|
52 | |||
| 53 | self.dataOut.frequency = self.dataIn.frequency |
|
53 | self.dataOut.frequency = self.dataIn.frequency | |
| 54 | self.dataOut.realtime = self.dataIn.realtime |
|
54 | self.dataOut.realtime = self.dataIn.realtime | |
| 55 |
|
55 | |||
| 56 | self.dataOut.azimuth = self.dataIn.azimuth |
|
56 | self.dataOut.azimuth = self.dataIn.azimuth | |
| 57 | self.dataOut.zenith = self.dataIn.zenith |
|
57 | self.dataOut.zenith = self.dataIn.zenith | |
| 58 |
|
58 | |||
| 59 | self.dataOut.beam.codeList = self.dataIn.beam.codeList |
|
59 | self.dataOut.beam.codeList = self.dataIn.beam.codeList | |
| 60 | self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList |
|
60 | self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList | |
| 61 | self.dataOut.beam.zenithList = self.dataIn.beam.zenithList |
|
61 | self.dataOut.beam.zenithList = self.dataIn.beam.zenithList | |
| 62 |
|
62 | |||
| 63 | def __decodeData(self, nProfiles, code): |
|
63 | def __decodeData(self, nProfiles, code): | |
| 64 |
|
64 | |||
| 65 | if code is None: |
|
65 | if code is None: | |
| 66 | return |
|
66 | return | |
| 67 |
|
67 | |||
| 68 | for i in range(nProfiles): |
|
68 | for i in range(nProfiles): | |
| 69 | self.buffer[:,i,:] = self.buffer[:,i,:]*code[0][i] |
|
69 | self.buffer[:,i,:] = self.buffer[:,i,:]*code[0][i] | |
| 70 |
|
70 | |||
| 71 | def __getFft(self): |
|
71 | def __getFft(self): | |
| 72 | """ |
|
72 | """ | |
| 73 | Convierte valores de Voltaje a Spectra |
|
73 | Convierte valores de Voltaje a Spectra | |
| 74 |
|
74 | |||
| 75 | Affected: |
|
75 | Affected: | |
| 76 | self.dataOut.data_spc |
|
76 | self.dataOut.data_spc | |
| 77 | self.dataOut.data_cspc |
|
77 | self.dataOut.data_cspc | |
| 78 | self.dataOut.data_dc |
|
78 | self.dataOut.data_dc | |
| 79 | self.dataOut.heightList |
|
79 | self.dataOut.heightList | |
| 80 | self.profIndex |
|
80 | self.profIndex | |
| 81 | self.buffer |
|
81 | self.buffer | |
| 82 | self.dataOut.flagNoData |
|
82 | self.dataOut.flagNoData | |
| 83 | """ |
|
83 | """ | |
| 84 | nsegments = self.dataOut.nHeights |
|
84 | nsegments = self.dataOut.nHeights | |
| 85 |
|
85 | |||
| 86 | _fft_buffer = numpy.zeros((self.dataOut.nChannels, self.dataOut.nProfiles, nsegments), dtype='complex') |
|
86 | _fft_buffer = numpy.zeros((self.dataOut.nChannels, self.dataOut.nProfiles, nsegments), dtype='complex') | |
| 87 |
|
87 | |||
| 88 | for i in range(nsegments): |
|
88 | for i in range(nsegments): | |
| 89 | try: |
|
89 | try: | |
| 90 | _fft_buffer[:,:,i] = self.buffer[:,i:i+self.dataOut.nProfiles] |
|
90 | _fft_buffer[:,:,i] = self.buffer[:,i:i+self.dataOut.nProfiles] | |
| 91 |
|
91 | |||
| 92 | if self.code is not None: |
|
92 | if self.code is not None: | |
| 93 | _fft_buffer[:,:,i] = _fft_buffer[:,:,i]*self.code[0] |
|
93 | _fft_buffer[:,:,i] = _fft_buffer[:,:,i]*self.code[0] | |
| 94 | except: |
|
94 | except: | |
| 95 | pass |
|
95 | pass | |
| 96 |
|
96 | |||
| 97 | fft_volt = numpy.fft.fft(_fft_buffer, n=self.dataOut.nFFTPoints, axis=1) |
|
97 | fft_volt = numpy.fft.fft(_fft_buffer, n=self.dataOut.nFFTPoints, axis=1) | |
| 98 | fft_volt = fft_volt.astype(numpy.dtype('complex')) |
|
98 | fft_volt = fft_volt.astype(numpy.dtype('complex')) | |
| 99 | dc = fft_volt[:,0,:] |
|
99 | dc = fft_volt[:,0,:] | |
| 100 |
|
100 | |||
| 101 | #calculo de self-spectra |
|
101 | #calculo de self-spectra | |
| 102 | spc = fft_volt * numpy.conjugate(fft_volt) |
|
102 | spc = fft_volt * numpy.conjugate(fft_volt) | |
| 103 | data = numpy.fft.ifft(spc, axis=1) |
|
103 | data = numpy.fft.ifft(spc, axis=1) | |
| 104 | data = numpy.fft.fftshift(data, axes=(1,)) |
|
104 | data = numpy.fft.fftshift(data, axes=(1,)) | |
| 105 |
|
105 | |||
| 106 | spc = data |
|
106 | spc = data | |
| 107 |
|
107 | |||
| 108 | blocksize = 0 |
|
108 | blocksize = 0 | |
| 109 | blocksize += dc.size |
|
109 | blocksize += dc.size | |
| 110 | blocksize += spc.size |
|
110 | blocksize += spc.size | |
| 111 |
|
111 | |||
| 112 | cspc = None |
|
112 | cspc = None | |
| 113 | pairIndex = 0 |
|
113 | pairIndex = 0 | |
| 114 |
|
114 | |||
| 115 | if self.dataOut.pairsList != None: |
|
115 | if self.dataOut.pairsList != None: | |
| 116 | #calculo de cross-spectra |
|
116 | #calculo de cross-spectra | |
| 117 | cspc = numpy.zeros((self.dataOut.nPairs, self.dataOut.nFFTPoints, self.dataOut.nHeights), dtype='complex') |
|
117 | cspc = numpy.zeros((self.dataOut.nPairs, self.dataOut.nFFTPoints, self.dataOut.nHeights), dtype='complex') | |
| 118 | for pair in self.dataOut.pairsList: |
|
118 | for pair in self.dataOut.pairsList: | |
| 119 | if pair[0] not in self.dataOut.channelList: |
|
119 | if pair[0] not in self.dataOut.channelList: | |
| 120 | raise ValueError, "Error getting CrossSpectra: pair 0 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList)) |
|
120 | raise ValueError, "Error getting CrossSpectra: pair 0 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList)) | |
| 121 | if pair[1] not in self.dataOut.channelList: |
|
121 | if pair[1] not in self.dataOut.channelList: | |
| 122 | raise ValueError, "Error getting CrossSpectra: pair 1 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList)) |
|
122 | raise ValueError, "Error getting CrossSpectra: pair 1 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList)) | |
| 123 |
|
123 | |||
| 124 | chan_index0 = self.dataOut.channelList.index(pair[0]) |
|
124 | chan_index0 = self.dataOut.channelList.index(pair[0]) | |
| 125 | chan_index1 = self.dataOut.channelList.index(pair[1]) |
|
125 | chan_index1 = self.dataOut.channelList.index(pair[1]) | |
| 126 |
|
126 | |||
| 127 | cspc[pairIndex,:,:] = fft_volt[chan_index0,:,:] * numpy.conjugate(fft_volt[chan_index1,:,:]) |
|
127 | cspc[pairIndex,:,:] = fft_volt[chan_index0,:,:] * numpy.conjugate(fft_volt[chan_index1,:,:]) | |
| 128 | pairIndex += 1 |
|
128 | pairIndex += 1 | |
| 129 | blocksize += cspc.size |
|
129 | blocksize += cspc.size | |
| 130 |
|
130 | |||
| 131 | self.dataOut.data_spc = spc |
|
131 | self.dataOut.data_spc = spc | |
| 132 | self.dataOut.data_cspc = cspc |
|
132 | self.dataOut.data_cspc = cspc | |
| 133 | self.dataOut.data_dc = dc |
|
133 | self.dataOut.data_dc = dc | |
| 134 | self.dataOut.blockSize = blocksize |
|
134 | self.dataOut.blockSize = blocksize | |
| 135 | self.dataOut.flagShiftFFT = True |
|
135 | self.dataOut.flagShiftFFT = True | |
| 136 |
|
136 | |||
| 137 | def run(self, nProfiles=None, nFFTPoints=None, pairsList=[], code=None, nCode=1, nBaud=1,real= None, imag=None): |
|
137 | def run(self, nProfiles=None, nFFTPoints=None, pairsList=[], code=None, nCode=1, nBaud=1,real= None, imag=None): | |
| 138 |
|
138 | |||
| 139 | self.dataOut.flagNoData = True |
|
139 | self.dataOut.flagNoData = True | |
| 140 |
|
140 | |||
| 141 | if self.dataIn.type == "Spectra": |
|
141 | if self.dataIn.type == "Spectra": | |
| 142 | self.dataOut.copy(self.dataIn) |
|
142 | self.dataOut.copy(self.dataIn) | |
| 143 | spc = self.dataOut.data_spc |
|
143 | spc = self.dataOut.data_spc | |
| 144 | data = numpy.fft.ifft(spc, axis=1) |
|
144 | data = numpy.fft.ifft(spc, axis=1) | |
| 145 | data = numpy.fft.fftshift(data, axes=(1,)) |
|
145 | data = numpy.fft.fftshift(data, axes=(1,)) | |
| 146 | acf = numpy.abs(data) # Autocorrelacion LLAMAR A ESTE VALOR ACF |
|
146 | acf = numpy.abs(data) # Autocorrelacion LLAMAR A ESTE VALOR ACF | |
| 147 | if real: |
|
147 | if real: | |
| 148 | acf = data.real |
|
148 | acf = data.real | |
| 149 | if imag: |
|
149 | if imag: | |
| 150 | acf = data.imag |
|
150 | acf = data.imag | |
| 151 | shape = acf.shape # nchannels, nprofiles, nsamples |
|
151 | shape = acf.shape # nchannels, nprofiles, nsamples | |
| 152 |
|
152 | |||
|
|
153 | #import matplotlib.pyplot as plt | |||
|
|
154 | #acf_tmp=acf[0,:,85] | |||
|
|
155 | #plt.plot(acf_tmp) | |||
|
|
156 | #plt.show() | |||
|
|
157 | ||||
|
|
158 | for i in range(shape[1]): | |||
|
|
159 | tmp = numpy.argmax(acf[0,:,i]) | |||
|
|
160 | if i>30: | |||
|
|
161 | value = (acf[0,:,i][tmp+3]+acf[0,:,i][tmp+4])/2.0 | |||
|
|
162 | acf[0,:,i][tmp] = value | |||
|
|
163 | acf[0,:,i][tmp-1] = value | |||
|
|
164 | acf[0,:,i][tmp+1] = value | |||
|
|
165 | acf[0,:,i][tmp-2] = value | |||
|
|
166 | acf[0,:,i][tmp+2] = value | |||
|
|
167 | ||||
|
|
168 | import scipy as sp | |||
|
|
169 | from scipy import signal | |||
|
|
170 | acf[0,:,i] = sp.signal.medfilt(acf[0,:,i],21) | |||
|
|
171 | ||||
|
|
172 | ||||
|
|
173 | ||||
|
|
174 | #print numpy.argmax(acf[0,:,85]) | |||
|
|
175 | #import matplotlib.pyplot as plt | |||
|
|
176 | #plt.plot(acf[0,:,85]) | |||
|
|
177 | #a= acf[0,:,85] | |||
|
|
178 | #b= acf[0,:,0] | |||
|
|
179 | #print a[200],a[198],a[199], a[201],a[202],a[203] | |||
|
|
180 | #plt.show() | |||
|
|
181 | #import time | |||
|
|
182 | #time.sleep(10) | |||
|
|
183 | ||||
|
|
184 | ||||
| 153 | # Normalizando |
|
185 | # Normalizando | |
| 154 | for i in range(shape[0]): |
|
186 | for i in range(shape[0]): | |
| 155 | for j in range(shape[2]): |
|
187 | for j in range(shape[2]): | |
| 156 | acf[i,:,j]= acf[i,:,j] / numpy.max(numpy.abs(acf[i,:,j])) |
|
188 | acf[i,:,j]= acf[i,:,j] / numpy.max(numpy.abs(acf[i,:,j])) | |
| 157 |
|
189 | |||
|
|
190 | #import matplotlib.pyplot as plt | |||
|
|
191 | #plt.plot(acf[0,:,85]) | |||
|
|
192 | #plt.show() | |||
|
|
193 | #import time | |||
|
|
194 | #time.sleep(20) | |||
|
|
195 | ||||
|
|
196 | ||||
| 158 | self.dataOut.data_acf = acf |
|
197 | self.dataOut.data_acf = acf | |
| 159 | return True |
|
198 | return True | |
| 160 |
|
199 | |||
| 161 | if code is not None: |
|
200 | if code is not None: | |
| 162 | self.code = numpy.array(code).reshape(nCode,nBaud) |
|
201 | self.code = numpy.array(code).reshape(nCode,nBaud) | |
| 163 | else: |
|
202 | else: | |
| 164 | self.code = None |
|
203 | self.code = None | |
| 165 |
|
204 | |||
| 166 | if self.dataIn.type == "Voltage": |
|
205 | if self.dataIn.type == "Voltage": | |
| 167 |
|
206 | |||
| 168 | if nFFTPoints == None: |
|
207 | if nFFTPoints == None: | |
| 169 | raise ValueError, "This SpectraProc.run() need nFFTPoints input variable" |
|
208 | raise ValueError, "This SpectraProc.run() need nFFTPoints input variable" | |
| 170 |
|
209 | |||
| 171 | if nProfiles == None: |
|
210 | if nProfiles == None: | |
| 172 | nProfiles = nFFTPoints |
|
211 | nProfiles = nFFTPoints | |
| 173 |
|
212 | |||
| 174 | self.dataOut.ippFactor = 1 |
|
213 | self.dataOut.ippFactor = 1 | |
| 175 |
|
214 | |||
| 176 | self.dataOut.nFFTPoints = nFFTPoints |
|
215 | self.dataOut.nFFTPoints = nFFTPoints | |
| 177 | self.dataOut.nProfiles = nProfiles |
|
216 | self.dataOut.nProfiles = nProfiles | |
| 178 | self.dataOut.pairsList = pairsList |
|
217 | self.dataOut.pairsList = pairsList | |
| 179 |
|
218 | |||
| 180 | # if self.buffer is None: |
|
219 | # if self.buffer is None: | |
| 181 | # self.buffer = numpy.zeros( (self.dataIn.nChannels, nProfiles, self.dataIn.nHeights), |
|
220 | # self.buffer = numpy.zeros( (self.dataIn.nChannels, nProfiles, self.dataIn.nHeights), | |
| 182 | # dtype='complex') |
|
221 | # dtype='complex') | |
| 183 |
|
222 | |||
| 184 | if not self.dataIn.flagDataAsBlock: |
|
223 | if not self.dataIn.flagDataAsBlock: | |
| 185 | self.buffer = self.dataIn.data.copy() |
|
224 | self.buffer = self.dataIn.data.copy() | |
| 186 |
|
225 | |||
| 187 | # for i in range(self.dataIn.nHeights): |
|
226 | # for i in range(self.dataIn.nHeights): | |
| 188 | # self.buffer[:, self.profIndex, self.profIndex:] = voltage_data[:,:self.dataIn.nHeights - self.profIndex] |
|
227 | # self.buffer[:, self.profIndex, self.profIndex:] = voltage_data[:,:self.dataIn.nHeights - self.profIndex] | |
| 189 | # |
|
228 | # | |
| 190 | # self.profIndex += 1 |
|
229 | # self.profIndex += 1 | |
| 191 |
|
230 | |||
| 192 | else: |
|
231 | else: | |
| 193 | raise ValueError, "" |
|
232 | raise ValueError, "" | |
| 194 |
|
233 | |||
| 195 | self.firstdatatime = self.dataIn.utctime |
|
234 | self.firstdatatime = self.dataIn.utctime | |
| 196 |
|
235 | |||
| 197 | self.profIndex == nProfiles |
|
236 | self.profIndex == nProfiles | |
| 198 |
|
237 | |||
| 199 | self.__updateSpecFromVoltage() |
|
238 | self.__updateSpecFromVoltage() | |
| 200 |
|
239 | |||
| 201 | self.__getFft() |
|
240 | self.__getFft() | |
| 202 |
|
241 | |||
| 203 | self.dataOut.flagNoData = False |
|
242 | self.dataOut.flagNoData = False | |
| 204 |
|
243 | |||
| 205 | return True |
|
244 | return True | |
| 206 |
|
245 | |||
| 207 | raise ValueError, "The type of input object '%s' is not valid"%(self.dataIn.type) |
|
246 | raise ValueError, "The type of input object '%s' is not valid"%(self.dataIn.type) | |
| 208 |
|
247 | |||
| 209 | def __selectPairs(self, pairsList): |
|
248 | def __selectPairs(self, pairsList): | |
| 210 |
|
249 | |||
| 211 | if channelList == None: |
|
250 | if channelList == None: | |
| 212 | return |
|
251 | return | |
| 213 |
|
252 | |||
| 214 | pairsIndexListSelected = [] |
|
253 | pairsIndexListSelected = [] | |
| 215 |
|
254 | |||
| 216 | for thisPair in pairsList: |
|
255 | for thisPair in pairsList: | |
| 217 |
|
256 | |||
| 218 | if thisPair not in self.dataOut.pairsList: |
|
257 | if thisPair not in self.dataOut.pairsList: | |
| 219 | continue |
|
258 | continue | |
| 220 |
|
259 | |||
| 221 | pairIndex = self.dataOut.pairsList.index(thisPair) |
|
260 | pairIndex = self.dataOut.pairsList.index(thisPair) | |
| 222 |
|
261 | |||
| 223 | pairsIndexListSelected.append(pairIndex) |
|
262 | pairsIndexListSelected.append(pairIndex) | |
| 224 |
|
263 | |||
| 225 | if not pairsIndexListSelected: |
|
264 | if not pairsIndexListSelected: | |
| 226 | self.dataOut.data_cspc = None |
|
265 | self.dataOut.data_cspc = None | |
| 227 | self.dataOut.pairsList = [] |
|
266 | self.dataOut.pairsList = [] | |
| 228 | return |
|
267 | return | |
| 229 |
|
268 | |||
| 230 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected] |
|
269 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected] | |
| 231 | self.dataOut.pairsList = [self.dataOut.pairsList[i] for i in pairsIndexListSelected] |
|
270 | self.dataOut.pairsList = [self.dataOut.pairsList[i] for i in pairsIndexListSelected] | |
| 232 |
|
271 | |||
| 233 | return |
|
272 | return | |
| 234 |
|
273 | |||
| 235 | def __selectPairsByChannel(self, channelList=None): |
|
274 | def __selectPairsByChannel(self, channelList=None): | |
| 236 |
|
275 | |||
| 237 | if channelList == None: |
|
276 | if channelList == None: | |
| 238 | return |
|
277 | return | |
| 239 |
|
278 | |||
| 240 | pairsIndexListSelected = [] |
|
279 | pairsIndexListSelected = [] | |
| 241 | for pairIndex in self.dataOut.pairsIndexList: |
|
280 | for pairIndex in self.dataOut.pairsIndexList: | |
| 242 | #First pair |
|
281 | #First pair | |
| 243 | if self.dataOut.pairsList[pairIndex][0] not in channelList: |
|
282 | if self.dataOut.pairsList[pairIndex][0] not in channelList: | |
| 244 | continue |
|
283 | continue | |
| 245 | #Second pair |
|
284 | #Second pair | |
| 246 | if self.dataOut.pairsList[pairIndex][1] not in channelList: |
|
285 | if self.dataOut.pairsList[pairIndex][1] not in channelList: | |
| 247 | continue |
|
286 | continue | |
| 248 |
|
287 | |||
| 249 | pairsIndexListSelected.append(pairIndex) |
|
288 | pairsIndexListSelected.append(pairIndex) | |
| 250 |
|
289 | |||
| 251 | if not pairsIndexListSelected: |
|
290 | if not pairsIndexListSelected: | |
| 252 | self.dataOut.data_cspc = None |
|
291 | self.dataOut.data_cspc = None | |
| 253 | self.dataOut.pairsList = [] |
|
292 | self.dataOut.pairsList = [] | |
| 254 | return |
|
293 | return | |
| 255 |
|
294 | |||
| 256 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected] |
|
295 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected] | |
| 257 | self.dataOut.pairsList = [self.dataOut.pairsList[i] for i in pairsIndexListSelected] |
|
296 | self.dataOut.pairsList = [self.dataOut.pairsList[i] for i in pairsIndexListSelected] | |
| 258 |
|
297 | |||
| 259 | return |
|
298 | return | |
| 260 |
|
299 | |||
| 261 | def selectChannels(self, channelList): |
|
300 | def selectChannels(self, channelList): | |
| 262 |
|
301 | |||
| 263 | channelIndexList = [] |
|
302 | channelIndexList = [] | |
| 264 |
|
303 | |||
| 265 | for channel in channelList: |
|
304 | for channel in channelList: | |
| 266 | if channel not in self.dataOut.channelList: |
|
305 | if channel not in self.dataOut.channelList: | |
| 267 | raise ValueError, "Error selecting channels, Channel %d is not valid.\nAvailable channels = %s" %(channel, str(self.dataOut.channelList)) |
|
306 | raise ValueError, "Error selecting channels, Channel %d is not valid.\nAvailable channels = %s" %(channel, str(self.dataOut.channelList)) | |
| 268 |
|
307 | |||
| 269 | index = self.dataOut.channelList.index(channel) |
|
308 | index = self.dataOut.channelList.index(channel) | |
| 270 | channelIndexList.append(index) |
|
309 | channelIndexList.append(index) | |
| 271 |
|
310 | |||
| 272 | self.selectChannelsByIndex(channelIndexList) |
|
311 | self.selectChannelsByIndex(channelIndexList) | |
| 273 |
|
312 | |||
| 274 | def selectChannelsByIndex(self, channelIndexList): |
|
313 | def selectChannelsByIndex(self, channelIndexList): | |
| 275 | """ |
|
314 | """ | |
| 276 | Selecciona un bloque de datos en base a canales segun el channelIndexList |
|
315 | Selecciona un bloque de datos en base a canales segun el channelIndexList | |
| 277 |
|
316 | |||
| 278 | Input: |
|
317 | Input: | |
| 279 | channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] |
|
318 | channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] | |
| 280 |
|
319 | |||
| 281 | Affected: |
|
320 | Affected: | |
| 282 | self.dataOut.data_spc |
|
321 | self.dataOut.data_spc | |
| 283 | self.dataOut.channelIndexList |
|
322 | self.dataOut.channelIndexList | |
| 284 | self.dataOut.nChannels |
|
323 | self.dataOut.nChannels | |
| 285 |
|
324 | |||
| 286 | Return: |
|
325 | Return: | |
| 287 | None |
|
326 | None | |
| 288 | """ |
|
327 | """ | |
| 289 |
|
328 | |||
| 290 | for channelIndex in channelIndexList: |
|
329 | for channelIndex in channelIndexList: | |
| 291 | if channelIndex not in self.dataOut.channelIndexList: |
|
330 | if channelIndex not in self.dataOut.channelIndexList: | |
| 292 | raise ValueError, "Error selecting channels: The value %d in channelIndexList is not valid.\nAvailable channel indexes = " %(channelIndex, self.dataOut.channelIndexList) |
|
331 | raise ValueError, "Error selecting channels: The value %d in channelIndexList is not valid.\nAvailable channel indexes = " %(channelIndex, self.dataOut.channelIndexList) | |
| 293 |
|
332 | |||
| 294 | # nChannels = len(channelIndexList) |
|
333 | # nChannels = len(channelIndexList) | |
| 295 |
|
334 | |||
| 296 | data_spc = self.dataOut.data_spc[channelIndexList,:] |
|
335 | data_spc = self.dataOut.data_spc[channelIndexList,:] | |
| 297 | data_dc = self.dataOut.data_dc[channelIndexList,:] |
|
336 | data_dc = self.dataOut.data_dc[channelIndexList,:] | |
| 298 |
|
337 | |||
| 299 | self.dataOut.data_spc = data_spc |
|
338 | self.dataOut.data_spc = data_spc | |
| 300 | self.dataOut.data_dc = data_dc |
|
339 | self.dataOut.data_dc = data_dc | |
| 301 |
|
340 | |||
| 302 | self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] |
|
341 | self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] | |
| 303 | # self.dataOut.nChannels = nChannels |
|
342 | # self.dataOut.nChannels = nChannels | |
| 304 |
|
343 | |||
| 305 | self.__selectPairsByChannel(self.dataOut.channelList) |
|
344 | self.__selectPairsByChannel(self.dataOut.channelList) | |
| 306 |
|
345 | |||
| 307 | return 1 |
|
346 | return 1 | |
| 308 |
|
347 | |||
| 309 | def selectHeights(self, minHei, maxHei): |
|
348 | def selectHeights(self, minHei, maxHei): | |
| 310 | """ |
|
349 | """ | |
| 311 | Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango |
|
350 | Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango | |
| 312 | minHei <= height <= maxHei |
|
351 | minHei <= height <= maxHei | |
| 313 |
|
352 | |||
| 314 | Input: |
|
353 | Input: | |
| 315 | minHei : valor minimo de altura a considerar |
|
354 | minHei : valor minimo de altura a considerar | |
| 316 | maxHei : valor maximo de altura a considerar |
|
355 | maxHei : valor maximo de altura a considerar | |
| 317 |
|
356 | |||
| 318 | Affected: |
|
357 | Affected: | |
| 319 | Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex |
|
358 | Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex | |
| 320 |
|
359 | |||
| 321 | Return: |
|
360 | Return: | |
| 322 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
361 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 | |
| 323 | """ |
|
362 | """ | |
| 324 |
|
363 | |||
| 325 | if (minHei > maxHei): |
|
364 | if (minHei > maxHei): | |
| 326 | raise ValueError, "Error selecting heights: Height range (%d,%d) is not valid" % (minHei, maxHei) |
|
365 | raise ValueError, "Error selecting heights: Height range (%d,%d) is not valid" % (minHei, maxHei) | |
| 327 |
|
366 | |||
| 328 | if (minHei < self.dataOut.heightList[0]): |
|
367 | if (minHei < self.dataOut.heightList[0]): | |
| 329 | minHei = self.dataOut.heightList[0] |
|
368 | minHei = self.dataOut.heightList[0] | |
| 330 |
|
369 | |||
| 331 | if (maxHei > self.dataOut.heightList[-1]): |
|
370 | if (maxHei > self.dataOut.heightList[-1]): | |
| 332 | maxHei = self.dataOut.heightList[-1] |
|
371 | maxHei = self.dataOut.heightList[-1] | |
| 333 |
|
372 | |||
| 334 | minIndex = 0 |
|
373 | minIndex = 0 | |
| 335 | maxIndex = 0 |
|
374 | maxIndex = 0 | |
| 336 | heights = self.dataOut.heightList |
|
375 | heights = self.dataOut.heightList | |
| 337 |
|
376 | |||
| 338 | inda = numpy.where(heights >= minHei) |
|
377 | inda = numpy.where(heights >= minHei) | |
| 339 | indb = numpy.where(heights <= maxHei) |
|
378 | indb = numpy.where(heights <= maxHei) | |
| 340 |
|
379 | |||
| 341 | try: |
|
380 | try: | |
| 342 | minIndex = inda[0][0] |
|
381 | minIndex = inda[0][0] | |
| 343 | except: |
|
382 | except: | |
| 344 | minIndex = 0 |
|
383 | minIndex = 0 | |
| 345 |
|
384 | |||
| 346 | try: |
|
385 | try: | |
| 347 | maxIndex = indb[0][-1] |
|
386 | maxIndex = indb[0][-1] | |
| 348 | except: |
|
387 | except: | |
| 349 | maxIndex = len(heights) |
|
388 | maxIndex = len(heights) | |
| 350 |
|
389 | |||
| 351 | self.selectHeightsByIndex(minIndex, maxIndex) |
|
390 | self.selectHeightsByIndex(minIndex, maxIndex) | |
| 352 |
|
391 | |||
| 353 | return 1 |
|
392 | return 1 | |
| 354 |
|
393 | |||
| 355 | def getBeaconSignal(self, tauindex = 0, channelindex = 0, hei_ref=None): |
|
394 | def getBeaconSignal(self, tauindex = 0, channelindex = 0, hei_ref=None): | |
| 356 | newheis = numpy.where(self.dataOut.heightList>self.dataOut.radarControllerHeaderObj.Taus[tauindex]) |
|
395 | newheis = numpy.where(self.dataOut.heightList>self.dataOut.radarControllerHeaderObj.Taus[tauindex]) | |
| 357 |
|
396 | |||
| 358 | if hei_ref != None: |
|
397 | if hei_ref != None: | |
| 359 | newheis = numpy.where(self.dataOut.heightList>hei_ref) |
|
398 | newheis = numpy.where(self.dataOut.heightList>hei_ref) | |
| 360 |
|
399 | |||
| 361 | minIndex = min(newheis[0]) |
|
400 | minIndex = min(newheis[0]) | |
| 362 | maxIndex = max(newheis[0]) |
|
401 | maxIndex = max(newheis[0]) | |
| 363 | data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1] |
|
402 | data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1] | |
| 364 | heightList = self.dataOut.heightList[minIndex:maxIndex+1] |
|
403 | heightList = self.dataOut.heightList[minIndex:maxIndex+1] | |
| 365 |
|
404 | |||
| 366 | # determina indices |
|
405 | # determina indices | |
| 367 | nheis = int(self.dataOut.radarControllerHeaderObj.txB/(self.dataOut.heightList[1]-self.dataOut.heightList[0])) |
|
406 | nheis = int(self.dataOut.radarControllerHeaderObj.txB/(self.dataOut.heightList[1]-self.dataOut.heightList[0])) | |
| 368 | avg_dB = 10*numpy.log10(numpy.sum(data_spc[channelindex,:,:],axis=0)) |
|
407 | avg_dB = 10*numpy.log10(numpy.sum(data_spc[channelindex,:,:],axis=0)) | |
| 369 | beacon_dB = numpy.sort(avg_dB)[-nheis:] |
|
408 | beacon_dB = numpy.sort(avg_dB)[-nheis:] | |
| 370 | beacon_heiIndexList = [] |
|
409 | beacon_heiIndexList = [] | |
| 371 | for val in avg_dB.tolist(): |
|
410 | for val in avg_dB.tolist(): | |
| 372 | if val >= beacon_dB[0]: |
|
411 | if val >= beacon_dB[0]: | |
| 373 | beacon_heiIndexList.append(avg_dB.tolist().index(val)) |
|
412 | beacon_heiIndexList.append(avg_dB.tolist().index(val)) | |
| 374 |
|
413 | |||
| 375 | #data_spc = data_spc[:,:,beacon_heiIndexList] |
|
414 | #data_spc = data_spc[:,:,beacon_heiIndexList] | |
| 376 | data_cspc = None |
|
415 | data_cspc = None | |
| 377 | if self.dataOut.data_cspc is not None: |
|
416 | if self.dataOut.data_cspc is not None: | |
| 378 | data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1] |
|
417 | data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1] | |
| 379 | #data_cspc = data_cspc[:,:,beacon_heiIndexList] |
|
418 | #data_cspc = data_cspc[:,:,beacon_heiIndexList] | |
| 380 |
|
419 | |||
| 381 | data_dc = None |
|
420 | data_dc = None | |
| 382 | if self.dataOut.data_dc is not None: |
|
421 | if self.dataOut.data_dc is not None: | |
| 383 | data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1] |
|
422 | data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1] | |
| 384 | #data_dc = data_dc[:,beacon_heiIndexList] |
|
423 | #data_dc = data_dc[:,beacon_heiIndexList] | |
| 385 |
|
424 | |||
| 386 | self.dataOut.data_spc = data_spc |
|
425 | self.dataOut.data_spc = data_spc | |
| 387 | self.dataOut.data_cspc = data_cspc |
|
426 | self.dataOut.data_cspc = data_cspc | |
| 388 | self.dataOut.data_dc = data_dc |
|
427 | self.dataOut.data_dc = data_dc | |
| 389 | self.dataOut.heightList = heightList |
|
428 | self.dataOut.heightList = heightList | |
| 390 | self.dataOut.beacon_heiIndexList = beacon_heiIndexList |
|
429 | self.dataOut.beacon_heiIndexList = beacon_heiIndexList | |
| 391 |
|
430 | |||
| 392 | return 1 |
|
431 | return 1 | |
| 393 |
|
432 | |||
| 394 |
|
433 | |||
| 395 | def selectHeightsByIndex(self, minIndex, maxIndex): |
|
434 | def selectHeightsByIndex(self, minIndex, maxIndex): | |
| 396 | """ |
|
435 | """ | |
| 397 | Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango |
|
436 | Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango | |
| 398 | minIndex <= index <= maxIndex |
|
437 | minIndex <= index <= maxIndex | |
| 399 |
|
438 | |||
| 400 | Input: |
|
439 | Input: | |
| 401 | minIndex : valor de indice minimo de altura a considerar |
|
440 | minIndex : valor de indice minimo de altura a considerar | |
| 402 | maxIndex : valor de indice maximo de altura a considerar |
|
441 | maxIndex : valor de indice maximo de altura a considerar | |
| 403 |
|
442 | |||
| 404 | Affected: |
|
443 | Affected: | |
| 405 | self.dataOut.data_spc |
|
444 | self.dataOut.data_spc | |
| 406 | self.dataOut.data_cspc |
|
445 | self.dataOut.data_cspc | |
| 407 | self.dataOut.data_dc |
|
446 | self.dataOut.data_dc | |
| 408 | self.dataOut.heightList |
|
447 | self.dataOut.heightList | |
| 409 |
|
448 | |||
| 410 | Return: |
|
449 | Return: | |
| 411 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
450 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 | |
| 412 | """ |
|
451 | """ | |
| 413 |
|
452 | |||
| 414 | if (minIndex < 0) or (minIndex > maxIndex): |
|
453 | if (minIndex < 0) or (minIndex > maxIndex): | |
| 415 | raise ValueError, "Error selecting heights: Index range (%d,%d) is not valid" % (minIndex, maxIndex) |
|
454 | raise ValueError, "Error selecting heights: Index range (%d,%d) is not valid" % (minIndex, maxIndex) | |
| 416 |
|
455 | |||
| 417 | if (maxIndex >= self.dataOut.nHeights): |
|
456 | if (maxIndex >= self.dataOut.nHeights): | |
| 418 | maxIndex = self.dataOut.nHeights-1 |
|
457 | maxIndex = self.dataOut.nHeights-1 | |
| 419 |
|
458 | |||
| 420 | #Spectra |
|
459 | #Spectra | |
| 421 | data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1] |
|
460 | data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1] | |
| 422 |
|
461 | |||
| 423 | data_cspc = None |
|
462 | data_cspc = None | |
| 424 | if self.dataOut.data_cspc is not None: |
|
463 | if self.dataOut.data_cspc is not None: | |
| 425 | data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1] |
|
464 | data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1] | |
| 426 |
|
465 | |||
| 427 | data_dc = None |
|
466 | data_dc = None | |
| 428 | if self.dataOut.data_dc is not None: |
|
467 | if self.dataOut.data_dc is not None: | |
| 429 | data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1] |
|
468 | data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1] | |
| 430 |
|
469 | |||
| 431 | self.dataOut.data_spc = data_spc |
|
470 | self.dataOut.data_spc = data_spc | |
| 432 | self.dataOut.data_cspc = data_cspc |
|
471 | self.dataOut.data_cspc = data_cspc | |
| 433 | self.dataOut.data_dc = data_dc |
|
472 | self.dataOut.data_dc = data_dc | |
| 434 |
|
473 | |||
| 435 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1] |
|
474 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1] | |
| 436 |
|
475 | |||
| 437 | return 1 |
|
476 | return 1 | |
| 438 |
|
477 | |||
| 439 | def removeDC(self, mode = 2): |
|
478 | def removeDC(self, mode = 2): | |
| 440 | jspectra = self.dataOut.data_spc |
|
479 | jspectra = self.dataOut.data_spc | |
| 441 | jcspectra = self.dataOut.data_cspc |
|
480 | jcspectra = self.dataOut.data_cspc | |
| 442 |
|
481 | |||
| 443 |
|
482 | |||
| 444 | num_chan = jspectra.shape[0] |
|
483 | num_chan = jspectra.shape[0] | |
| 445 | num_hei = jspectra.shape[2] |
|
484 | num_hei = jspectra.shape[2] | |
| 446 |
|
485 | |||
| 447 | if jcspectra is not None: |
|
486 | if jcspectra is not None: | |
| 448 | jcspectraExist = True |
|
487 | jcspectraExist = True | |
| 449 | num_pairs = jcspectra.shape[0] |
|
488 | num_pairs = jcspectra.shape[0] | |
| 450 | else: jcspectraExist = False |
|
489 | else: jcspectraExist = False | |
| 451 |
|
490 | |||
| 452 | freq_dc = jspectra.shape[1]/2 |
|
491 | freq_dc = jspectra.shape[1]/2 | |
| 453 | ind_vel = numpy.array([-2,-1,1,2]) + freq_dc |
|
492 | ind_vel = numpy.array([-2,-1,1,2]) + freq_dc | |
| 454 |
|
493 | |||
| 455 | if ind_vel[0]<0: |
|
494 | if ind_vel[0]<0: | |
| 456 | ind_vel[range(0,1)] = ind_vel[range(0,1)] + self.num_prof |
|
495 | ind_vel[range(0,1)] = ind_vel[range(0,1)] + self.num_prof | |
| 457 |
|
496 | |||
| 458 | if mode == 1: |
|
497 | if mode == 1: | |
| 459 | jspectra[:,freq_dc,:] = (jspectra[:,ind_vel[1],:] + jspectra[:,ind_vel[2],:])/2 #CORRECCION |
|
498 | jspectra[:,freq_dc,:] = (jspectra[:,ind_vel[1],:] + jspectra[:,ind_vel[2],:])/2 #CORRECCION | |
| 460 |
|
499 | |||
| 461 | if jcspectraExist: |
|
500 | if jcspectraExist: | |
| 462 | jcspectra[:,freq_dc,:] = (jcspectra[:,ind_vel[1],:] + jcspectra[:,ind_vel[2],:])/2 |
|
501 | jcspectra[:,freq_dc,:] = (jcspectra[:,ind_vel[1],:] + jcspectra[:,ind_vel[2],:])/2 | |
| 463 |
|
502 | |||
| 464 | if mode == 2: |
|
503 | if mode == 2: | |
| 465 |
|
504 | |||
| 466 | vel = numpy.array([-2,-1,1,2]) |
|
505 | vel = numpy.array([-2,-1,1,2]) | |
| 467 | xx = numpy.zeros([4,4]) |
|
506 | xx = numpy.zeros([4,4]) | |
| 468 |
|
507 | |||
| 469 | for fil in range(4): |
|
508 | for fil in range(4): | |
| 470 | xx[fil,:] = vel[fil]**numpy.asarray(range(4)) |
|
509 | xx[fil,:] = vel[fil]**numpy.asarray(range(4)) | |
| 471 |
|
510 | |||
| 472 | xx_inv = numpy.linalg.inv(xx) |
|
511 | xx_inv = numpy.linalg.inv(xx) | |
| 473 | xx_aux = xx_inv[0,:] |
|
512 | xx_aux = xx_inv[0,:] | |
| 474 |
|
513 | |||
| 475 | for ich in range(num_chan): |
|
514 | for ich in range(num_chan): | |
| 476 | yy = jspectra[ich,ind_vel,:] |
|
515 | yy = jspectra[ich,ind_vel,:] | |
| 477 | jspectra[ich,freq_dc,:] = numpy.dot(xx_aux,yy) |
|
516 | jspectra[ich,freq_dc,:] = numpy.dot(xx_aux,yy) | |
| 478 |
|
517 | |||
| 479 | junkid = jspectra[ich,freq_dc,:]<=0 |
|
518 | junkid = jspectra[ich,freq_dc,:]<=0 | |
| 480 | cjunkid = sum(junkid) |
|
519 | cjunkid = sum(junkid) | |
| 481 |
|
520 | |||
| 482 | if cjunkid.any(): |
|
521 | if cjunkid.any(): | |
| 483 | jspectra[ich,freq_dc,junkid.nonzero()] = (jspectra[ich,ind_vel[1],junkid] + jspectra[ich,ind_vel[2],junkid])/2 |
|
522 | jspectra[ich,freq_dc,junkid.nonzero()] = (jspectra[ich,ind_vel[1],junkid] + jspectra[ich,ind_vel[2],junkid])/2 | |
| 484 |
|
523 | |||
| 485 | if jcspectraExist: |
|
524 | if jcspectraExist: | |
| 486 | for ip in range(num_pairs): |
|
525 | for ip in range(num_pairs): | |
| 487 | yy = jcspectra[ip,ind_vel,:] |
|
526 | yy = jcspectra[ip,ind_vel,:] | |
| 488 | jcspectra[ip,freq_dc,:] = numpy.dot(xx_aux,yy) |
|
527 | jcspectra[ip,freq_dc,:] = numpy.dot(xx_aux,yy) | |
| 489 |
|
528 | |||
| 490 |
|
529 | |||
| 491 | self.dataOut.data_spc = jspectra |
|
530 | self.dataOut.data_spc = jspectra | |
| 492 | self.dataOut.data_cspc = jcspectra |
|
531 | self.dataOut.data_cspc = jcspectra | |
| 493 |
|
532 | |||
| 494 | return 1 |
|
533 | return 1 | |
| 495 |
|
534 | |||
| 496 | def removeInterference(self, interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None): |
|
535 | def removeInterference(self, interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None): | |
| 497 |
|
536 | |||
| 498 | jspectra = self.dataOut.data_spc |
|
537 | jspectra = self.dataOut.data_spc | |
| 499 | jcspectra = self.dataOut.data_cspc |
|
538 | jcspectra = self.dataOut.data_cspc | |
| 500 | jnoise = self.dataOut.getNoise() |
|
539 | jnoise = self.dataOut.getNoise() | |
| 501 | num_incoh = self.dataOut.nIncohInt |
|
540 | num_incoh = self.dataOut.nIncohInt | |
| 502 |
|
541 | |||
| 503 | num_channel = jspectra.shape[0] |
|
542 | num_channel = jspectra.shape[0] | |
| 504 | num_prof = jspectra.shape[1] |
|
543 | num_prof = jspectra.shape[1] | |
| 505 | num_hei = jspectra.shape[2] |
|
544 | num_hei = jspectra.shape[2] | |
| 506 |
|
545 | |||
| 507 | #hei_interf |
|
546 | #hei_interf | |
| 508 | if hei_interf is None: |
|
547 | if hei_interf is None: | |
| 509 | count_hei = num_hei/2 #Como es entero no importa |
|
548 | count_hei = num_hei/2 #Como es entero no importa | |
| 510 | hei_interf = numpy.asmatrix(range(count_hei)) + num_hei - count_hei |
|
549 | hei_interf = numpy.asmatrix(range(count_hei)) + num_hei - count_hei | |
| 511 | hei_interf = numpy.asarray(hei_interf)[0] |
|
550 | hei_interf = numpy.asarray(hei_interf)[0] | |
| 512 | #nhei_interf |
|
551 | #nhei_interf | |
| 513 | if (nhei_interf == None): |
|
552 | if (nhei_interf == None): | |
| 514 | nhei_interf = 5 |
|
553 | nhei_interf = 5 | |
| 515 | if (nhei_interf < 1): |
|
554 | if (nhei_interf < 1): | |
| 516 | nhei_interf = 1 |
|
555 | nhei_interf = 1 | |
| 517 | if (nhei_interf > count_hei): |
|
556 | if (nhei_interf > count_hei): | |
| 518 | nhei_interf = count_hei |
|
557 | nhei_interf = count_hei | |
| 519 | if (offhei_interf == None): |
|
558 | if (offhei_interf == None): | |
| 520 | offhei_interf = 0 |
|
559 | offhei_interf = 0 | |
| 521 |
|
560 | |||
| 522 | ind_hei = range(num_hei) |
|
561 | ind_hei = range(num_hei) | |
| 523 | # mask_prof = numpy.asarray(range(num_prof - 2)) + 1 |
|
562 | # mask_prof = numpy.asarray(range(num_prof - 2)) + 1 | |
| 524 | # mask_prof[range(num_prof/2 - 1,len(mask_prof))] += 1 |
|
563 | # mask_prof[range(num_prof/2 - 1,len(mask_prof))] += 1 | |
| 525 | mask_prof = numpy.asarray(range(num_prof)) |
|
564 | mask_prof = numpy.asarray(range(num_prof)) | |
| 526 | num_mask_prof = mask_prof.size |
|
565 | num_mask_prof = mask_prof.size | |
| 527 | comp_mask_prof = [0, num_prof/2] |
|
566 | comp_mask_prof = [0, num_prof/2] | |
| 528 |
|
567 | |||
| 529 |
|
568 | |||
| 530 | #noise_exist: Determina si la variable jnoise ha sido definida y contiene la informacion del ruido de cada canal |
|
569 | #noise_exist: Determina si la variable jnoise ha sido definida y contiene la informacion del ruido de cada canal | |
| 531 | if (jnoise.size < num_channel or numpy.isnan(jnoise).any()): |
|
570 | if (jnoise.size < num_channel or numpy.isnan(jnoise).any()): | |
| 532 | jnoise = numpy.nan |
|
571 | jnoise = numpy.nan | |
| 533 | noise_exist = jnoise[0] < numpy.Inf |
|
572 | noise_exist = jnoise[0] < numpy.Inf | |
| 534 |
|
573 | |||
| 535 | #Subrutina de Remocion de la Interferencia |
|
574 | #Subrutina de Remocion de la Interferencia | |
| 536 | for ich in range(num_channel): |
|
575 | for ich in range(num_channel): | |
| 537 | #Se ordena los espectros segun su potencia (menor a mayor) |
|
576 | #Se ordena los espectros segun su potencia (menor a mayor) | |
| 538 | power = jspectra[ich,mask_prof,:] |
|
577 | power = jspectra[ich,mask_prof,:] | |
| 539 | power = power[:,hei_interf] |
|
578 | power = power[:,hei_interf] | |
| 540 | power = power.sum(axis = 0) |
|
579 | power = power.sum(axis = 0) | |
| 541 | psort = power.ravel().argsort() |
|
580 | psort = power.ravel().argsort() | |
| 542 |
|
581 | |||
| 543 | #Se estima la interferencia promedio en los Espectros de Potencia empleando |
|
582 | #Se estima la interferencia promedio en los Espectros de Potencia empleando | |
| 544 | junkspc_interf = jspectra[ich,:,hei_interf[psort[range(offhei_interf, nhei_interf + offhei_interf)]]] |
|
583 | junkspc_interf = jspectra[ich,:,hei_interf[psort[range(offhei_interf, nhei_interf + offhei_interf)]]] | |
| 545 |
|
584 | |||
| 546 | if noise_exist: |
|
585 | if noise_exist: | |
| 547 | # tmp_noise = jnoise[ich] / num_prof |
|
586 | # tmp_noise = jnoise[ich] / num_prof | |
| 548 | tmp_noise = jnoise[ich] |
|
587 | tmp_noise = jnoise[ich] | |
| 549 | junkspc_interf = junkspc_interf - tmp_noise |
|
588 | junkspc_interf = junkspc_interf - tmp_noise | |
| 550 | #junkspc_interf[:,comp_mask_prof] = 0 |
|
589 | #junkspc_interf[:,comp_mask_prof] = 0 | |
| 551 |
|
590 | |||
| 552 | jspc_interf = junkspc_interf.sum(axis = 0) / nhei_interf |
|
591 | jspc_interf = junkspc_interf.sum(axis = 0) / nhei_interf | |
| 553 | jspc_interf = jspc_interf.transpose() |
|
592 | jspc_interf = jspc_interf.transpose() | |
| 554 | #Calculando el espectro de interferencia promedio |
|
593 | #Calculando el espectro de interferencia promedio | |
| 555 | noiseid = numpy.where(jspc_interf <= tmp_noise/ numpy.sqrt(num_incoh)) |
|
594 | noiseid = numpy.where(jspc_interf <= tmp_noise/ numpy.sqrt(num_incoh)) | |
| 556 | noiseid = noiseid[0] |
|
595 | noiseid = noiseid[0] | |
| 557 | cnoiseid = noiseid.size |
|
596 | cnoiseid = noiseid.size | |
| 558 | interfid = numpy.where(jspc_interf > tmp_noise/ numpy.sqrt(num_incoh)) |
|
597 | interfid = numpy.where(jspc_interf > tmp_noise/ numpy.sqrt(num_incoh)) | |
| 559 | interfid = interfid[0] |
|
598 | interfid = interfid[0] | |
| 560 | cinterfid = interfid.size |
|
599 | cinterfid = interfid.size | |
| 561 |
|
600 | |||
| 562 | if (cnoiseid > 0): jspc_interf[noiseid] = 0 |
|
601 | if (cnoiseid > 0): jspc_interf[noiseid] = 0 | |
| 563 |
|
602 | |||
| 564 | #Expandiendo los perfiles a limpiar |
|
603 | #Expandiendo los perfiles a limpiar | |
| 565 | if (cinterfid > 0): |
|
604 | if (cinterfid > 0): | |
| 566 | new_interfid = (numpy.r_[interfid - 1, interfid, interfid + 1] + num_prof)%num_prof |
|
605 | new_interfid = (numpy.r_[interfid - 1, interfid, interfid + 1] + num_prof)%num_prof | |
| 567 | new_interfid = numpy.asarray(new_interfid) |
|
606 | new_interfid = numpy.asarray(new_interfid) | |
| 568 | new_interfid = {x for x in new_interfid} |
|
607 | new_interfid = {x for x in new_interfid} | |
| 569 | new_interfid = numpy.array(list(new_interfid)) |
|
608 | new_interfid = numpy.array(list(new_interfid)) | |
| 570 | new_cinterfid = new_interfid.size |
|
609 | new_cinterfid = new_interfid.size | |
| 571 | else: new_cinterfid = 0 |
|
610 | else: new_cinterfid = 0 | |
| 572 |
|
611 | |||
| 573 | for ip in range(new_cinterfid): |
|
612 | for ip in range(new_cinterfid): | |
| 574 | ind = junkspc_interf[:,new_interfid[ip]].ravel().argsort() |
|
613 | ind = junkspc_interf[:,new_interfid[ip]].ravel().argsort() | |
| 575 | jspc_interf[new_interfid[ip]] = junkspc_interf[ind[nhei_interf/2],new_interfid[ip]] |
|
614 | jspc_interf[new_interfid[ip]] = junkspc_interf[ind[nhei_interf/2],new_interfid[ip]] | |
| 576 |
|
615 | |||
| 577 |
|
616 | |||
| 578 | jspectra[ich,:,ind_hei] = jspectra[ich,:,ind_hei] - jspc_interf #Corregir indices |
|
617 | jspectra[ich,:,ind_hei] = jspectra[ich,:,ind_hei] - jspc_interf #Corregir indices | |
| 579 |
|
618 | |||
| 580 | #Removiendo la interferencia del punto de mayor interferencia |
|
619 | #Removiendo la interferencia del punto de mayor interferencia | |
| 581 | ListAux = jspc_interf[mask_prof].tolist() |
|
620 | ListAux = jspc_interf[mask_prof].tolist() | |
| 582 | maxid = ListAux.index(max(ListAux)) |
|
621 | maxid = ListAux.index(max(ListAux)) | |
| 583 |
|
622 | |||
| 584 |
|
623 | |||
| 585 | if cinterfid > 0: |
|
624 | if cinterfid > 0: | |
| 586 | for ip in range(cinterfid*(interf == 2) - 1): |
|
625 | for ip in range(cinterfid*(interf == 2) - 1): | |
| 587 | ind = (jspectra[ich,interfid[ip],:] < tmp_noise*(1 + 1/numpy.sqrt(num_incoh))).nonzero() |
|
626 | ind = (jspectra[ich,interfid[ip],:] < tmp_noise*(1 + 1/numpy.sqrt(num_incoh))).nonzero() | |
| 588 | cind = len(ind) |
|
627 | cind = len(ind) | |
| 589 |
|
628 | |||
| 590 | if (cind > 0): |
|
629 | if (cind > 0): | |
| 591 | jspectra[ich,interfid[ip],ind] = tmp_noise*(1 + (numpy.random.uniform(cind) - 0.5)/numpy.sqrt(num_incoh)) |
|
630 | jspectra[ich,interfid[ip],ind] = tmp_noise*(1 + (numpy.random.uniform(cind) - 0.5)/numpy.sqrt(num_incoh)) | |
| 592 |
|
631 | |||
| 593 | ind = numpy.array([-2,-1,1,2]) |
|
632 | ind = numpy.array([-2,-1,1,2]) | |
| 594 | xx = numpy.zeros([4,4]) |
|
633 | xx = numpy.zeros([4,4]) | |
| 595 |
|
634 | |||
| 596 | for id1 in range(4): |
|
635 | for id1 in range(4): | |
| 597 | xx[:,id1] = ind[id1]**numpy.asarray(range(4)) |
|
636 | xx[:,id1] = ind[id1]**numpy.asarray(range(4)) | |
| 598 |
|
637 | |||
| 599 | xx_inv = numpy.linalg.inv(xx) |
|
638 | xx_inv = numpy.linalg.inv(xx) | |
| 600 | xx = xx_inv[:,0] |
|
639 | xx = xx_inv[:,0] | |
| 601 | ind = (ind + maxid + num_mask_prof)%num_mask_prof |
|
640 | ind = (ind + maxid + num_mask_prof)%num_mask_prof | |
| 602 | yy = jspectra[ich,mask_prof[ind],:] |
|
641 | yy = jspectra[ich,mask_prof[ind],:] | |
| 603 | jspectra[ich,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx) |
|
642 | jspectra[ich,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx) | |
| 604 |
|
643 | |||
| 605 |
|
644 | |||
| 606 | indAux = (jspectra[ich,:,:] < tmp_noise*(1-1/numpy.sqrt(num_incoh))).nonzero() |
|
645 | indAux = (jspectra[ich,:,:] < tmp_noise*(1-1/numpy.sqrt(num_incoh))).nonzero() | |
| 607 | jspectra[ich,indAux[0],indAux[1]] = tmp_noise * (1 - 1/numpy.sqrt(num_incoh)) |
|
646 | jspectra[ich,indAux[0],indAux[1]] = tmp_noise * (1 - 1/numpy.sqrt(num_incoh)) | |
| 608 |
|
647 | |||
| 609 | #Remocion de Interferencia en el Cross Spectra |
|
648 | #Remocion de Interferencia en el Cross Spectra | |
| 610 | if jcspectra is None: return jspectra, jcspectra |
|
649 | if jcspectra is None: return jspectra, jcspectra | |
| 611 | num_pairs = jcspectra.size/(num_prof*num_hei) |
|
650 | num_pairs = jcspectra.size/(num_prof*num_hei) | |
| 612 | jcspectra = jcspectra.reshape(num_pairs, num_prof, num_hei) |
|
651 | jcspectra = jcspectra.reshape(num_pairs, num_prof, num_hei) | |
| 613 |
|
652 | |||
| 614 | for ip in range(num_pairs): |
|
653 | for ip in range(num_pairs): | |
| 615 |
|
654 | |||
| 616 | #------------------------------------------- |
|
655 | #------------------------------------------- | |
| 617 |
|
656 | |||
| 618 | cspower = numpy.abs(jcspectra[ip,mask_prof,:]) |
|
657 | cspower = numpy.abs(jcspectra[ip,mask_prof,:]) | |
| 619 | cspower = cspower[:,hei_interf] |
|
658 | cspower = cspower[:,hei_interf] | |
| 620 | cspower = cspower.sum(axis = 0) |
|
659 | cspower = cspower.sum(axis = 0) | |
| 621 |
|
660 | |||
| 622 | cspsort = cspower.ravel().argsort() |
|
661 | cspsort = cspower.ravel().argsort() | |
| 623 | junkcspc_interf = jcspectra[ip,:,hei_interf[cspsort[range(offhei_interf, nhei_interf + offhei_interf)]]] |
|
662 | junkcspc_interf = jcspectra[ip,:,hei_interf[cspsort[range(offhei_interf, nhei_interf + offhei_interf)]]] | |
| 624 | junkcspc_interf = junkcspc_interf.transpose() |
|
663 | junkcspc_interf = junkcspc_interf.transpose() | |
| 625 | jcspc_interf = junkcspc_interf.sum(axis = 1)/nhei_interf |
|
664 | jcspc_interf = junkcspc_interf.sum(axis = 1)/nhei_interf | |
| 626 |
|
665 | |||
| 627 | ind = numpy.abs(jcspc_interf[mask_prof]).ravel().argsort() |
|
666 | ind = numpy.abs(jcspc_interf[mask_prof]).ravel().argsort() | |
| 628 |
|
667 | |||
| 629 | median_real = numpy.median(numpy.real(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:])) |
|
668 | median_real = numpy.median(numpy.real(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:])) | |
| 630 | median_imag = numpy.median(numpy.imag(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:])) |
|
669 | median_imag = numpy.median(numpy.imag(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:])) | |
| 631 | junkcspc_interf[comp_mask_prof,:] = numpy.complex(median_real, median_imag) |
|
670 | junkcspc_interf[comp_mask_prof,:] = numpy.complex(median_real, median_imag) | |
| 632 |
|
671 | |||
| 633 | for iprof in range(num_prof): |
|
672 | for iprof in range(num_prof): | |
| 634 | ind = numpy.abs(junkcspc_interf[iprof,:]).ravel().argsort() |
|
673 | ind = numpy.abs(junkcspc_interf[iprof,:]).ravel().argsort() | |
| 635 | jcspc_interf[iprof] = junkcspc_interf[iprof, ind[nhei_interf/2]] |
|
674 | jcspc_interf[iprof] = junkcspc_interf[iprof, ind[nhei_interf/2]] | |
| 636 |
|
675 | |||
| 637 | #Removiendo la Interferencia |
|
676 | #Removiendo la Interferencia | |
| 638 | jcspectra[ip,:,ind_hei] = jcspectra[ip,:,ind_hei] - jcspc_interf |
|
677 | jcspectra[ip,:,ind_hei] = jcspectra[ip,:,ind_hei] - jcspc_interf | |
| 639 |
|
678 | |||
| 640 | ListAux = numpy.abs(jcspc_interf[mask_prof]).tolist() |
|
679 | ListAux = numpy.abs(jcspc_interf[mask_prof]).tolist() | |
| 641 | maxid = ListAux.index(max(ListAux)) |
|
680 | maxid = ListAux.index(max(ListAux)) | |
| 642 |
|
681 | |||
| 643 | ind = numpy.array([-2,-1,1,2]) |
|
682 | ind = numpy.array([-2,-1,1,2]) | |
| 644 | xx = numpy.zeros([4,4]) |
|
683 | xx = numpy.zeros([4,4]) | |
| 645 |
|
684 | |||
| 646 | for id1 in range(4): |
|
685 | for id1 in range(4): | |
| 647 | xx[:,id1] = ind[id1]**numpy.asarray(range(4)) |
|
686 | xx[:,id1] = ind[id1]**numpy.asarray(range(4)) | |
| 648 |
|
687 | |||
| 649 | xx_inv = numpy.linalg.inv(xx) |
|
688 | xx_inv = numpy.linalg.inv(xx) | |
| 650 | xx = xx_inv[:,0] |
|
689 | xx = xx_inv[:,0] | |
| 651 |
|
690 | |||
| 652 | ind = (ind + maxid + num_mask_prof)%num_mask_prof |
|
691 | ind = (ind + maxid + num_mask_prof)%num_mask_prof | |
| 653 | yy = jcspectra[ip,mask_prof[ind],:] |
|
692 | yy = jcspectra[ip,mask_prof[ind],:] | |
| 654 | jcspectra[ip,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx) |
|
693 | jcspectra[ip,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx) | |
| 655 |
|
694 | |||
| 656 | #Guardar Resultados |
|
695 | #Guardar Resultados | |
| 657 | self.dataOut.data_spc = jspectra |
|
696 | self.dataOut.data_spc = jspectra | |
| 658 | self.dataOut.data_cspc = jcspectra |
|
697 | self.dataOut.data_cspc = jcspectra | |
| 659 |
|
698 | |||
| 660 | return 1 |
|
699 | return 1 | |
| 661 |
|
700 | |||
| 662 | def setRadarFrequency(self, frequency=None): |
|
701 | def setRadarFrequency(self, frequency=None): | |
| 663 |
|
702 | |||
| 664 | if frequency != None: |
|
703 | if frequency != None: | |
| 665 | self.dataOut.frequency = frequency |
|
704 | self.dataOut.frequency = frequency | |
| 666 |
|
705 | |||
| 667 | return 1 |
|
706 | return 1 | |
| 668 |
|
707 | |||
| 669 | def getNoise(self, minHei=None, maxHei=None, minVel=None, maxVel=None): |
|
708 | def getNoise(self, minHei=None, maxHei=None, minVel=None, maxVel=None): | |
| 670 | #validacion de rango |
|
709 | #validacion de rango | |
| 671 | if minHei == None: |
|
710 | if minHei == None: | |
| 672 | minHei = self.dataOut.heightList[0] |
|
711 | minHei = self.dataOut.heightList[0] | |
| 673 |
|
712 | |||
| 674 | if maxHei == None: |
|
713 | if maxHei == None: | |
| 675 | maxHei = self.dataOut.heightList[-1] |
|
714 | maxHei = self.dataOut.heightList[-1] | |
| 676 |
|
715 | |||
| 677 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): |
|
716 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): | |
| 678 | print 'minHei: %.2f is out of the heights range'%(minHei) |
|
717 | print 'minHei: %.2f is out of the heights range'%(minHei) | |
| 679 | print 'minHei is setting to %.2f'%(self.dataOut.heightList[0]) |
|
718 | print 'minHei is setting to %.2f'%(self.dataOut.heightList[0]) | |
| 680 | minHei = self.dataOut.heightList[0] |
|
719 | minHei = self.dataOut.heightList[0] | |
| 681 |
|
720 | |||
| 682 | if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei): |
|
721 | if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei): | |
| 683 | print 'maxHei: %.2f is out of the heights range'%(maxHei) |
|
722 | print 'maxHei: %.2f is out of the heights range'%(maxHei) | |
| 684 | print 'maxHei is setting to %.2f'%(self.dataOut.heightList[-1]) |
|
723 | print 'maxHei is setting to %.2f'%(self.dataOut.heightList[-1]) | |
| 685 | maxHei = self.dataOut.heightList[-1] |
|
724 | maxHei = self.dataOut.heightList[-1] | |
| 686 |
|
725 | |||
| 687 | # validacion de velocidades |
|
726 | # validacion de velocidades | |
| 688 | velrange = self.dataOut.getVelRange(1) |
|
727 | velrange = self.dataOut.getVelRange(1) | |
| 689 |
|
728 | |||
| 690 | if minVel == None: |
|
729 | if minVel == None: | |
| 691 | minVel = velrange[0] |
|
730 | minVel = velrange[0] | |
| 692 |
|
731 | |||
| 693 | if maxVel == None: |
|
732 | if maxVel == None: | |
| 694 | maxVel = velrange[-1] |
|
733 | maxVel = velrange[-1] | |
| 695 |
|
734 | |||
| 696 | if (minVel < velrange[0]) or (minVel > maxVel): |
|
735 | if (minVel < velrange[0]) or (minVel > maxVel): | |
| 697 | print 'minVel: %.2f is out of the velocity range'%(minVel) |
|
736 | print 'minVel: %.2f is out of the velocity range'%(minVel) | |
| 698 | print 'minVel is setting to %.2f'%(velrange[0]) |
|
737 | print 'minVel is setting to %.2f'%(velrange[0]) | |
| 699 | minVel = velrange[0] |
|
738 | minVel = velrange[0] | |
| 700 |
|
739 | |||
| 701 | if (maxVel > velrange[-1]) or (maxVel < minVel): |
|
740 | if (maxVel > velrange[-1]) or (maxVel < minVel): | |
| 702 | print 'maxVel: %.2f is out of the velocity range'%(maxVel) |
|
741 | print 'maxVel: %.2f is out of the velocity range'%(maxVel) | |
| 703 | print 'maxVel is setting to %.2f'%(velrange[-1]) |
|
742 | print 'maxVel is setting to %.2f'%(velrange[-1]) | |
| 704 | maxVel = velrange[-1] |
|
743 | maxVel = velrange[-1] | |
| 705 |
|
744 | |||
| 706 | # seleccion de indices para rango |
|
745 | # seleccion de indices para rango | |
| 707 | minIndex = 0 |
|
746 | minIndex = 0 | |
| 708 | maxIndex = 0 |
|
747 | maxIndex = 0 | |
| 709 | heights = self.dataOut.heightList |
|
748 | heights = self.dataOut.heightList | |
| 710 |
|
749 | |||
| 711 | inda = numpy.where(heights >= minHei) |
|
750 | inda = numpy.where(heights >= minHei) | |
| 712 | indb = numpy.where(heights <= maxHei) |
|
751 | indb = numpy.where(heights <= maxHei) | |
| 713 |
|
752 | |||
| 714 | try: |
|
753 | try: | |
| 715 | minIndex = inda[0][0] |
|
754 | minIndex = inda[0][0] | |
| 716 | except: |
|
755 | except: | |
| 717 | minIndex = 0 |
|
756 | minIndex = 0 | |
| 718 |
|
757 | |||
| 719 | try: |
|
758 | try: | |
| 720 | maxIndex = indb[0][-1] |
|
759 | maxIndex = indb[0][-1] | |
| 721 | except: |
|
760 | except: | |
| 722 | maxIndex = len(heights) |
|
761 | maxIndex = len(heights) | |
| 723 |
|
762 | |||
| 724 | if (minIndex < 0) or (minIndex > maxIndex): |
|
763 | if (minIndex < 0) or (minIndex > maxIndex): | |
| 725 | raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex) |
|
764 | raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex) | |
| 726 |
|
765 | |||
| 727 | if (maxIndex >= self.dataOut.nHeights): |
|
766 | if (maxIndex >= self.dataOut.nHeights): | |
| 728 | maxIndex = self.dataOut.nHeights-1 |
|
767 | maxIndex = self.dataOut.nHeights-1 | |
| 729 |
|
768 | |||
| 730 | # seleccion de indices para velocidades |
|
769 | # seleccion de indices para velocidades | |
| 731 | indminvel = numpy.where(velrange >= minVel) |
|
770 | indminvel = numpy.where(velrange >= minVel) | |
| 732 | indmaxvel = numpy.where(velrange <= maxVel) |
|
771 | indmaxvel = numpy.where(velrange <= maxVel) | |
| 733 | try: |
|
772 | try: | |
| 734 | minIndexVel = indminvel[0][0] |
|
773 | minIndexVel = indminvel[0][0] | |
| 735 | except: |
|
774 | except: | |
| 736 | minIndexVel = 0 |
|
775 | minIndexVel = 0 | |
| 737 |
|
776 | |||
| 738 | try: |
|
777 | try: | |
| 739 | maxIndexVel = indmaxvel[0][-1] |
|
778 | maxIndexVel = indmaxvel[0][-1] | |
| 740 | except: |
|
779 | except: | |
| 741 | maxIndexVel = len(velrange) |
|
780 | maxIndexVel = len(velrange) | |
| 742 |
|
781 | |||
| 743 | #seleccion del espectro |
|
782 | #seleccion del espectro | |
| 744 | data_spc = self.dataOut.data_spc[:,minIndexVel:maxIndexVel+1,minIndex:maxIndex+1] |
|
783 | data_spc = self.dataOut.data_spc[:,minIndexVel:maxIndexVel+1,minIndex:maxIndex+1] | |
| 745 | #estimacion de ruido |
|
784 | #estimacion de ruido | |
| 746 | noise = numpy.zeros(self.dataOut.nChannels) |
|
785 | noise = numpy.zeros(self.dataOut.nChannels) | |
| 747 |
|
786 | |||
| 748 | for channel in range(self.dataOut.nChannels): |
|
787 | for channel in range(self.dataOut.nChannels): | |
| 749 | daux = data_spc[channel,:,:] |
|
788 | daux = data_spc[channel,:,:] | |
| 750 | noise[channel] = hildebrand_sekhon(daux, self.dataOut.nIncohInt) |
|
789 | noise[channel] = hildebrand_sekhon(daux, self.dataOut.nIncohInt) | |
| 751 |
|
790 | |||
| 752 | self.dataOut.noise_estimation = noise.copy() |
|
791 | self.dataOut.noise_estimation = noise.copy() | |
| 753 |
|
792 | |||
| 754 | return 1 |
|
793 | return 1 | |
| @@ -1,1395 +1,1520 | |||||
| 1 | import sys |
|
1 | import sys | |
| 2 | import numpy |
|
2 | import numpy | |
| 3 | from scipy import interpolate |
|
3 | from scipy import interpolate | |
| 4 | from schainpy import cSchain |
|
4 | from schainpy import cSchain | |
| 5 | from jroproc_base import ProcessingUnit, Operation |
|
5 | from jroproc_base import ProcessingUnit, Operation | |
| 6 | from schainpy.model.data.jrodata import Voltage |
|
6 | from schainpy.model.data.jrodata import Voltage | |
| 7 | from time import time |
|
7 | from time import time | |
| 8 |
|
8 | |||
|
|
9 | import math | |||
|
|
10 | ||||
|
|
11 | def rep_seq(x, rep=10): | |||
|
|
12 | L = len(x) * rep | |||
|
|
13 | res = numpy.zeros(L, dtype=x.dtype) | |||
|
|
14 | idx = numpy.arange(len(x)) * rep | |||
|
|
15 | for i in numpy.arange(rep): | |||
|
|
16 | res[idx + i] = x | |||
|
|
17 | return(res) | |||
|
|
18 | ||||
|
|
19 | ||||
|
|
20 | def create_pseudo_random_code(clen=10000, seed=0): | |||
|
|
21 | """ | |||
|
|
22 | seed is a way of reproducing the random code without | |||
|
|
23 | having to store all actual codes. the seed can then | |||
|
|
24 | act as a sort of station_id. | |||
|
|
25 | ||||
|
|
26 | """ | |||
|
|
27 | numpy.random.seed(seed) | |||
|
|
28 | phases = numpy.array( | |||
|
|
29 | numpy.exp(1.0j * 2.0 * math.pi * numpy.random.random(clen)), | |||
|
|
30 | dtype=numpy.complex64, | |||
|
|
31 | ) | |||
|
|
32 | return(phases) | |||
|
|
33 | ||||
|
|
34 | ||||
|
|
35 | def periodic_convolution_matrix(envelope, rmin=0, rmax=100): | |||
|
|
36 | """ | |||
|
|
37 | we imply that the number of measurements is equal to the number of elements | |||
|
|
38 | in code | |||
|
|
39 | ||||
|
|
40 | """ | |||
|
|
41 | L = len(envelope) | |||
|
|
42 | ridx = numpy.arange(rmin, rmax) | |||
|
|
43 | A = numpy.zeros([L, rmax-rmin], dtype=numpy.complex64) | |||
|
|
44 | for i in numpy.arange(L): | |||
|
|
45 | A[i, :] = envelope[(i-ridx) % L] | |||
|
|
46 | result = {} | |||
|
|
47 | result['A'] = A | |||
|
|
48 | result['ridx'] = ridx | |||
|
|
49 | return(result) | |||
|
|
50 | ||||
|
|
51 | ||||
|
|
52 | B_cache = 0 | |||
|
|
53 | r_cache = 0 | |||
|
|
54 | B_cached = False | |||
|
|
55 | def create_estimation_matrix(code, rmin=0, rmax=1000, cache=True): | |||
|
|
56 | global B_cache | |||
|
|
57 | global r_cache | |||
|
|
58 | global B_cached | |||
|
|
59 | ||||
|
|
60 | if not cache or not B_cached: | |||
|
|
61 | r_cache = periodic_convolution_matrix( | |||
|
|
62 | envelope=code, rmin=rmin, rmax=rmax, | |||
|
|
63 | ) | |||
|
|
64 | A = r_cache['A'] | |||
|
|
65 | Ah = numpy.transpose(numpy.conjugate(A)) | |||
|
|
66 | B_cache = numpy.dot(numpy.linalg.inv(numpy.dot(Ah, A)), Ah) | |||
|
|
67 | r_cache['B'] = B_cache | |||
|
|
68 | B_cached = True | |||
|
|
69 | return(r_cache) | |||
|
|
70 | else: | |||
|
|
71 | return(r_cache) | |||
|
|
72 | ||||
| 9 | class VoltageProc(ProcessingUnit): |
|
73 | class VoltageProc(ProcessingUnit): | |
| 10 |
|
74 | |||
| 11 |
|
75 | |||
| 12 | def __init__(self, **kwargs): |
|
76 | def __init__(self, **kwargs): | |
| 13 |
|
77 | |||
| 14 | ProcessingUnit.__init__(self, **kwargs) |
|
78 | ProcessingUnit.__init__(self, **kwargs) | |
| 15 |
|
79 | |||
| 16 | # self.objectDict = {} |
|
80 | # self.objectDict = {} | |
| 17 | self.dataOut = Voltage() |
|
81 | self.dataOut = Voltage() | |
| 18 | self.flip = 1 |
|
82 | self.flip = 1 | |
| 19 |
|
83 | |||
| 20 | def run(self): |
|
84 | def run(self): | |
| 21 | if self.dataIn.type == 'AMISR': |
|
85 | if self.dataIn.type == 'AMISR': | |
| 22 | self.__updateObjFromAmisrInput() |
|
86 | self.__updateObjFromAmisrInput() | |
| 23 |
|
87 | |||
| 24 | if self.dataIn.type == 'Voltage': |
|
88 | if self.dataIn.type == 'Voltage': | |
| 25 | self.dataOut.copy(self.dataIn) |
|
89 | self.dataOut.copy(self.dataIn) | |
| 26 |
|
90 | |||
| 27 | # self.dataOut.copy(self.dataIn) |
|
91 | # self.dataOut.copy(self.dataIn) | |
| 28 |
|
92 | |||
| 29 | def __updateObjFromAmisrInput(self): |
|
93 | def __updateObjFromAmisrInput(self): | |
| 30 |
|
94 | |||
| 31 | self.dataOut.timeZone = self.dataIn.timeZone |
|
95 | self.dataOut.timeZone = self.dataIn.timeZone | |
| 32 | self.dataOut.dstFlag = self.dataIn.dstFlag |
|
96 | self.dataOut.dstFlag = self.dataIn.dstFlag | |
| 33 | self.dataOut.errorCount = self.dataIn.errorCount |
|
97 | self.dataOut.errorCount = self.dataIn.errorCount | |
| 34 | self.dataOut.useLocalTime = self.dataIn.useLocalTime |
|
98 | self.dataOut.useLocalTime = self.dataIn.useLocalTime | |
| 35 |
|
99 | |||
| 36 | self.dataOut.flagNoData = self.dataIn.flagNoData |
|
100 | self.dataOut.flagNoData = self.dataIn.flagNoData | |
| 37 | self.dataOut.data = self.dataIn.data |
|
101 | self.dataOut.data = self.dataIn.data | |
| 38 | self.dataOut.utctime = self.dataIn.utctime |
|
102 | self.dataOut.utctime = self.dataIn.utctime | |
| 39 | self.dataOut.channelList = self.dataIn.channelList |
|
103 | self.dataOut.channelList = self.dataIn.channelList | |
| 40 | # self.dataOut.timeInterval = self.dataIn.timeInterval |
|
104 | # self.dataOut.timeInterval = self.dataIn.timeInterval | |
| 41 | self.dataOut.heightList = self.dataIn.heightList |
|
105 | self.dataOut.heightList = self.dataIn.heightList | |
| 42 | self.dataOut.nProfiles = self.dataIn.nProfiles |
|
106 | self.dataOut.nProfiles = self.dataIn.nProfiles | |
| 43 |
|
107 | |||
| 44 | self.dataOut.nCohInt = self.dataIn.nCohInt |
|
108 | self.dataOut.nCohInt = self.dataIn.nCohInt | |
| 45 | self.dataOut.ippSeconds = self.dataIn.ippSeconds |
|
109 | self.dataOut.ippSeconds = self.dataIn.ippSeconds | |
| 46 | self.dataOut.frequency = self.dataIn.frequency |
|
110 | self.dataOut.frequency = self.dataIn.frequency | |
| 47 |
|
111 | |||
| 48 | self.dataOut.azimuth = self.dataIn.azimuth |
|
112 | self.dataOut.azimuth = self.dataIn.azimuth | |
| 49 | self.dataOut.zenith = self.dataIn.zenith |
|
113 | self.dataOut.zenith = self.dataIn.zenith | |
| 50 |
|
114 | |||
| 51 | self.dataOut.beam.codeList = self.dataIn.beam.codeList |
|
115 | self.dataOut.beam.codeList = self.dataIn.beam.codeList | |
| 52 | self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList |
|
116 | self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList | |
| 53 | self.dataOut.beam.zenithList = self.dataIn.beam.zenithList |
|
117 | self.dataOut.beam.zenithList = self.dataIn.beam.zenithList | |
| 54 | # |
|
118 | # | |
| 55 | # pass# |
|
119 | # pass# | |
| 56 | # |
|
120 | # | |
| 57 | # def init(self): |
|
121 | # def init(self): | |
| 58 | # |
|
122 | # | |
| 59 | # |
|
123 | # | |
| 60 | # if self.dataIn.type == 'AMISR': |
|
124 | # if self.dataIn.type == 'AMISR': | |
| 61 | # self.__updateObjFromAmisrInput() |
|
125 | # self.__updateObjFromAmisrInput() | |
| 62 | # |
|
126 | # | |
| 63 | # if self.dataIn.type == 'Voltage': |
|
127 | # if self.dataIn.type == 'Voltage': | |
| 64 | # self.dataOut.copy(self.dataIn) |
|
128 | # self.dataOut.copy(self.dataIn) | |
| 65 | # # No necesita copiar en cada init() los atributos de dataIn |
|
129 | # # No necesita copiar en cada init() los atributos de dataIn | |
| 66 | # # la copia deberia hacerse por cada nuevo bloque de datos |
|
130 | # # la copia deberia hacerse por cada nuevo bloque de datos | |
| 67 |
|
131 | |||
| 68 | def selectChannels(self, channelList): |
|
132 | def selectChannels(self, channelList): | |
| 69 |
|
133 | |||
| 70 | channelIndexList = [] |
|
134 | channelIndexList = [] | |
| 71 |
|
135 | |||
| 72 | for channel in channelList: |
|
136 | for channel in channelList: | |
| 73 | if channel not in self.dataOut.channelList: |
|
137 | if channel not in self.dataOut.channelList: | |
| 74 | raise ValueError, "Channel %d is not in %s" %(channel, str(self.dataOut.channelList)) |
|
138 | raise ValueError, "Channel %d is not in %s" %(channel, str(self.dataOut.channelList)) | |
| 75 |
|
139 | |||
| 76 | index = self.dataOut.channelList.index(channel) |
|
140 | index = self.dataOut.channelList.index(channel) | |
| 77 | channelIndexList.append(index) |
|
141 | channelIndexList.append(index) | |
| 78 |
|
142 | |||
| 79 | self.selectChannelsByIndex(channelIndexList) |
|
143 | self.selectChannelsByIndex(channelIndexList) | |
| 80 |
|
144 | |||
| 81 | def selectChannelsByIndex(self, channelIndexList): |
|
145 | def selectChannelsByIndex(self, channelIndexList): | |
| 82 | """ |
|
146 | """ | |
| 83 | Selecciona un bloque de datos en base a canales segun el channelIndexList |
|
147 | Selecciona un bloque de datos en base a canales segun el channelIndexList | |
| 84 |
|
148 | |||
| 85 | Input: |
|
149 | Input: | |
| 86 | channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] |
|
150 | channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] | |
| 87 |
|
151 | |||
| 88 | Affected: |
|
152 | Affected: | |
| 89 | self.dataOut.data |
|
153 | self.dataOut.data | |
| 90 | self.dataOut.channelIndexList |
|
154 | self.dataOut.channelIndexList | |
| 91 | self.dataOut.nChannels |
|
155 | self.dataOut.nChannels | |
| 92 | self.dataOut.m_ProcessingHeader.totalSpectra |
|
156 | self.dataOut.m_ProcessingHeader.totalSpectra | |
| 93 | self.dataOut.systemHeaderObj.numChannels |
|
157 | self.dataOut.systemHeaderObj.numChannels | |
| 94 | self.dataOut.m_ProcessingHeader.blockSize |
|
158 | self.dataOut.m_ProcessingHeader.blockSize | |
| 95 |
|
159 | |||
| 96 | Return: |
|
160 | Return: | |
| 97 | None |
|
161 | None | |
| 98 | """ |
|
162 | """ | |
| 99 |
|
163 | |||
| 100 | for channelIndex in channelIndexList: |
|
164 | for channelIndex in channelIndexList: | |
| 101 | if channelIndex not in self.dataOut.channelIndexList: |
|
165 | if channelIndex not in self.dataOut.channelIndexList: | |
| 102 | print channelIndexList |
|
166 | print channelIndexList | |
| 103 | raise ValueError, "The value %d in channelIndexList is not valid" %channelIndex |
|
167 | raise ValueError, "The value %d in channelIndexList is not valid" %channelIndex | |
| 104 |
|
168 | |||
| 105 | if self.dataOut.flagDataAsBlock: |
|
169 | if self.dataOut.flagDataAsBlock: | |
| 106 | """ |
|
170 | """ | |
| 107 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
171 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] | |
| 108 | """ |
|
172 | """ | |
| 109 | data = self.dataOut.data[channelIndexList,:,:] |
|
173 | data = self.dataOut.data[channelIndexList,:,:] | |
| 110 | else: |
|
174 | else: | |
| 111 | data = self.dataOut.data[channelIndexList,:] |
|
175 | data = self.dataOut.data[channelIndexList,:] | |
| 112 |
|
176 | |||
| 113 | self.dataOut.data = data |
|
177 | self.dataOut.data = data | |
| 114 | self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] |
|
178 | self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] | |
| 115 | # self.dataOut.nChannels = nChannels |
|
179 | # self.dataOut.nChannels = nChannels | |
| 116 |
|
180 | |||
| 117 | return 1 |
|
181 | return 1 | |
| 118 |
|
182 | |||
| 119 | def selectHeights(self, minHei=None, maxHei=None): |
|
183 | def selectHeights(self, minHei=None, maxHei=None): | |
| 120 | """ |
|
184 | """ | |
| 121 | Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango |
|
185 | Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango | |
| 122 | minHei <= height <= maxHei |
|
186 | minHei <= height <= maxHei | |
| 123 |
|
187 | |||
| 124 | Input: |
|
188 | Input: | |
| 125 | minHei : valor minimo de altura a considerar |
|
189 | minHei : valor minimo de altura a considerar | |
| 126 | maxHei : valor maximo de altura a considerar |
|
190 | maxHei : valor maximo de altura a considerar | |
| 127 |
|
191 | |||
| 128 | Affected: |
|
192 | Affected: | |
| 129 | Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex |
|
193 | Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex | |
| 130 |
|
194 | |||
| 131 | Return: |
|
195 | Return: | |
| 132 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
196 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 | |
| 133 | """ |
|
197 | """ | |
| 134 |
|
198 | |||
| 135 | if minHei == None: |
|
199 | if minHei == None: | |
| 136 | minHei = self.dataOut.heightList[0] |
|
200 | minHei = self.dataOut.heightList[0] | |
| 137 |
|
201 | |||
| 138 | if maxHei == None: |
|
202 | if maxHei == None: | |
| 139 | maxHei = self.dataOut.heightList[-1] |
|
203 | maxHei = self.dataOut.heightList[-1] | |
| 140 |
|
204 | |||
| 141 | if (minHei < self.dataOut.heightList[0]): |
|
205 | if (minHei < self.dataOut.heightList[0]): | |
| 142 | minHei = self.dataOut.heightList[0] |
|
206 | minHei = self.dataOut.heightList[0] | |
| 143 |
|
207 | |||
| 144 | if (maxHei > self.dataOut.heightList[-1]): |
|
208 | if (maxHei > self.dataOut.heightList[-1]): | |
| 145 | maxHei = self.dataOut.heightList[-1] |
|
209 | maxHei = self.dataOut.heightList[-1] | |
| 146 |
|
210 | |||
| 147 | minIndex = 0 |
|
211 | minIndex = 0 | |
| 148 | maxIndex = 0 |
|
212 | maxIndex = 0 | |
| 149 | heights = self.dataOut.heightList |
|
213 | heights = self.dataOut.heightList | |
| 150 |
|
214 | |||
| 151 | inda = numpy.where(heights >= minHei) |
|
215 | inda = numpy.where(heights >= minHei) | |
| 152 | indb = numpy.where(heights <= maxHei) |
|
216 | indb = numpy.where(heights <= maxHei) | |
| 153 |
|
217 | |||
| 154 | try: |
|
218 | try: | |
| 155 | minIndex = inda[0][0] |
|
219 | minIndex = inda[0][0] | |
| 156 | except: |
|
220 | except: | |
| 157 | minIndex = 0 |
|
221 | minIndex = 0 | |
| 158 |
|
222 | |||
| 159 | try: |
|
223 | try: | |
| 160 | maxIndex = indb[0][-1] |
|
224 | maxIndex = indb[0][-1] | |
| 161 | except: |
|
225 | except: | |
| 162 | maxIndex = len(heights) |
|
226 | maxIndex = len(heights) | |
| 163 |
|
227 | |||
| 164 | self.selectHeightsByIndex(minIndex, maxIndex) |
|
228 | self.selectHeightsByIndex(minIndex, maxIndex) | |
| 165 |
|
229 | |||
| 166 | return 1 |
|
230 | return 1 | |
| 167 |
|
231 | |||
| 168 |
|
232 | |||
| 169 | def selectHeightsByIndex(self, minIndex, maxIndex): |
|
233 | def selectHeightsByIndex(self, minIndex, maxIndex): | |
| 170 | """ |
|
234 | """ | |
| 171 | Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango |
|
235 | Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango | |
| 172 | minIndex <= index <= maxIndex |
|
236 | minIndex <= index <= maxIndex | |
| 173 |
|
237 | |||
| 174 | Input: |
|
238 | Input: | |
| 175 | minIndex : valor de indice minimo de altura a considerar |
|
239 | minIndex : valor de indice minimo de altura a considerar | |
| 176 | maxIndex : valor de indice maximo de altura a considerar |
|
240 | maxIndex : valor de indice maximo de altura a considerar | |
| 177 |
|
241 | |||
| 178 | Affected: |
|
242 | Affected: | |
| 179 | self.dataOut.data |
|
243 | self.dataOut.data | |
| 180 | self.dataOut.heightList |
|
244 | self.dataOut.heightList | |
| 181 |
|
245 | |||
| 182 | Return: |
|
246 | Return: | |
| 183 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
247 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 | |
| 184 | """ |
|
248 | """ | |
| 185 |
|
249 | |||
| 186 | if (minIndex < 0) or (minIndex > maxIndex): |
|
250 | if (minIndex < 0) or (minIndex > maxIndex): | |
| 187 | raise ValueError, "Height index range (%d,%d) is not valid" % (minIndex, maxIndex) |
|
251 | raise ValueError, "Height index range (%d,%d) is not valid" % (minIndex, maxIndex) | |
| 188 |
|
252 | |||
| 189 | if (maxIndex >= self.dataOut.nHeights): |
|
253 | if (maxIndex >= self.dataOut.nHeights): | |
| 190 | maxIndex = self.dataOut.nHeights |
|
254 | maxIndex = self.dataOut.nHeights | |
| 191 |
|
255 | |||
| 192 | #voltage |
|
256 | #voltage | |
| 193 | if self.dataOut.flagDataAsBlock: |
|
257 | if self.dataOut.flagDataAsBlock: | |
| 194 | """ |
|
258 | """ | |
| 195 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
259 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] | |
| 196 | """ |
|
260 | """ | |
| 197 | data = self.dataOut.data[:,:, minIndex:maxIndex] |
|
261 | data = self.dataOut.data[:,:, minIndex:maxIndex] | |
| 198 | else: |
|
262 | else: | |
| 199 | data = self.dataOut.data[:, minIndex:maxIndex] |
|
263 | data = self.dataOut.data[:, minIndex:maxIndex] | |
| 200 |
|
264 | |||
| 201 | # firstHeight = self.dataOut.heightList[minIndex] |
|
265 | # firstHeight = self.dataOut.heightList[minIndex] | |
| 202 |
|
266 | |||
| 203 | self.dataOut.data = data |
|
267 | self.dataOut.data = data | |
| 204 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex] |
|
268 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex] | |
| 205 |
|
269 | |||
| 206 | if self.dataOut.nHeights <= 1: |
|
270 | if self.dataOut.nHeights <= 1: | |
| 207 | raise ValueError, "selectHeights: Too few heights. Current number of heights is %d" %(self.dataOut.nHeights) |
|
271 | raise ValueError, "selectHeights: Too few heights. Current number of heights is %d" %(self.dataOut.nHeights) | |
| 208 |
|
272 | |||
| 209 | return 1 |
|
273 | return 1 | |
| 210 |
|
274 | |||
| 211 |
|
275 | |||
| 212 | def filterByHeights(self, window): |
|
276 | def filterByHeights(self, window): | |
| 213 |
|
277 | |||
| 214 | deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0] |
|
278 | deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0] | |
| 215 |
|
279 | |||
| 216 | if window == None: |
|
280 | if window == None: | |
| 217 | window = (self.dataOut.radarControllerHeaderObj.txA/self.dataOut.radarControllerHeaderObj.nBaud) / deltaHeight |
|
281 | window = (self.dataOut.radarControllerHeaderObj.txA/self.dataOut.radarControllerHeaderObj.nBaud) / deltaHeight | |
| 218 |
|
282 | |||
| 219 | newdelta = deltaHeight * window |
|
283 | newdelta = deltaHeight * window | |
| 220 | r = self.dataOut.nHeights % window |
|
284 | r = self.dataOut.nHeights % window | |
| 221 | newheights = (self.dataOut.nHeights-r)/window |
|
285 | newheights = (self.dataOut.nHeights-r)/window | |
| 222 |
|
286 | |||
| 223 | if newheights <= 1: |
|
287 | if newheights <= 1: | |
| 224 | raise ValueError, "filterByHeights: Too few heights. Current number of heights is %d and window is %d" %(self.dataOut.nHeights, window) |
|
288 | raise ValueError, "filterByHeights: Too few heights. Current number of heights is %d and window is %d" %(self.dataOut.nHeights, window) | |
| 225 |
|
289 | |||
| 226 | if self.dataOut.flagDataAsBlock: |
|
290 | if self.dataOut.flagDataAsBlock: | |
| 227 | """ |
|
291 | """ | |
| 228 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
292 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] | |
| 229 | """ |
|
293 | """ | |
| 230 | buffer = self.dataOut.data[:, :, 0:self.dataOut.nHeights-r] |
|
294 | buffer = self.dataOut.data[:, :, 0:self.dataOut.nHeights-r] | |
| 231 | buffer = buffer.reshape(self.dataOut.nChannels,self.dataOut.nProfiles,self.dataOut.nHeights/window,window) |
|
295 | buffer = buffer.reshape(self.dataOut.nChannels,self.dataOut.nProfiles,self.dataOut.nHeights/window,window) | |
| 232 | buffer = numpy.sum(buffer,3) |
|
296 | buffer = numpy.sum(buffer,3) | |
| 233 |
|
297 | |||
| 234 | else: |
|
298 | else: | |
| 235 | buffer = self.dataOut.data[:,0:self.dataOut.nHeights-r] |
|
299 | buffer = self.dataOut.data[:,0:self.dataOut.nHeights-r] | |
| 236 | buffer = buffer.reshape(self.dataOut.nChannels,self.dataOut.nHeights/window,window) |
|
300 | buffer = buffer.reshape(self.dataOut.nChannels,self.dataOut.nHeights/window,window) | |
| 237 | buffer = numpy.sum(buffer,2) |
|
301 | buffer = numpy.sum(buffer,2) | |
| 238 |
|
302 | |||
| 239 | self.dataOut.data = buffer |
|
303 | self.dataOut.data = buffer | |
| 240 | self.dataOut.heightList = self.dataOut.heightList[0] + numpy.arange( newheights )*newdelta |
|
304 | self.dataOut.heightList = self.dataOut.heightList[0] + numpy.arange( newheights )*newdelta | |
| 241 | self.dataOut.windowOfFilter = window |
|
305 | self.dataOut.windowOfFilter = window | |
| 242 |
|
306 | |||
| 243 | def setH0(self, h0, deltaHeight = None): |
|
307 | def setH0(self, h0, deltaHeight = None): | |
| 244 |
|
308 | |||
| 245 | if not deltaHeight: |
|
309 | if not deltaHeight: | |
| 246 | deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0] |
|
310 | deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0] | |
| 247 |
|
311 | |||
| 248 | nHeights = self.dataOut.nHeights |
|
312 | nHeights = self.dataOut.nHeights | |
| 249 |
|
313 | |||
| 250 | newHeiRange = h0 + numpy.arange(nHeights)*deltaHeight |
|
314 | newHeiRange = h0 + numpy.arange(nHeights)*deltaHeight | |
| 251 |
|
315 | |||
| 252 | self.dataOut.heightList = newHeiRange |
|
316 | self.dataOut.heightList = newHeiRange | |
| 253 |
|
317 | |||
| 254 | def deFlip(self, channelList = []): |
|
318 | def deFlip(self, channelList = []): | |
| 255 |
|
319 | |||
| 256 | data = self.dataOut.data.copy() |
|
320 | data = self.dataOut.data.copy() | |
| 257 |
|
321 | |||
| 258 | if self.dataOut.flagDataAsBlock: |
|
322 | if self.dataOut.flagDataAsBlock: | |
| 259 | flip = self.flip |
|
323 | flip = self.flip | |
| 260 | profileList = range(self.dataOut.nProfiles) |
|
324 | profileList = range(self.dataOut.nProfiles) | |
| 261 |
|
325 | |||
| 262 | if not channelList: |
|
326 | if not channelList: | |
| 263 | for thisProfile in profileList: |
|
327 | for thisProfile in profileList: | |
| 264 | data[:,thisProfile,:] = data[:,thisProfile,:]*flip |
|
328 | data[:,thisProfile,:] = data[:,thisProfile,:]*flip | |
| 265 | flip *= -1.0 |
|
329 | flip *= -1.0 | |
| 266 | else: |
|
330 | else: | |
| 267 | for thisChannel in channelList: |
|
331 | for thisChannel in channelList: | |
| 268 | if thisChannel not in self.dataOut.channelList: |
|
332 | if thisChannel not in self.dataOut.channelList: | |
| 269 | continue |
|
333 | continue | |
| 270 |
|
334 | |||
| 271 | for thisProfile in profileList: |
|
335 | for thisProfile in profileList: | |
| 272 | data[thisChannel,thisProfile,:] = data[thisChannel,thisProfile,:]*flip |
|
336 | data[thisChannel,thisProfile,:] = data[thisChannel,thisProfile,:]*flip | |
| 273 | flip *= -1.0 |
|
337 | flip *= -1.0 | |
| 274 |
|
338 | |||
| 275 | self.flip = flip |
|
339 | self.flip = flip | |
| 276 |
|
340 | |||
| 277 | else: |
|
341 | else: | |
| 278 | if not channelList: |
|
342 | if not channelList: | |
| 279 | data[:,:] = data[:,:]*self.flip |
|
343 | data[:,:] = data[:,:]*self.flip | |
| 280 | else: |
|
344 | else: | |
| 281 | for thisChannel in channelList: |
|
345 | for thisChannel in channelList: | |
| 282 | if thisChannel not in self.dataOut.channelList: |
|
346 | if thisChannel not in self.dataOut.channelList: | |
| 283 | continue |
|
347 | continue | |
| 284 |
|
348 | |||
| 285 | data[thisChannel,:] = data[thisChannel,:]*self.flip |
|
349 | data[thisChannel,:] = data[thisChannel,:]*self.flip | |
| 286 |
|
350 | |||
| 287 | self.flip *= -1. |
|
351 | self.flip *= -1. | |
| 288 |
|
352 | |||
| 289 | self.dataOut.data = data |
|
353 | self.dataOut.data = data | |
| 290 |
|
354 | |||
| 291 | def setRadarFrequency(self, frequency=None): |
|
355 | def setRadarFrequency(self, frequency=None): | |
| 292 |
|
356 | |||
| 293 | if frequency != None: |
|
357 | if frequency != None: | |
| 294 | self.dataOut.frequency = frequency |
|
358 | self.dataOut.frequency = frequency | |
| 295 |
|
359 | |||
| 296 | return 1 |
|
360 | return 1 | |
| 297 |
|
361 | |||
| 298 | def interpolateHeights(self, topLim, botLim): |
|
362 | def interpolateHeights(self, topLim, botLim): | |
| 299 | #69 al 72 para julia |
|
363 | #69 al 72 para julia | |
| 300 | #82-84 para meteoros |
|
364 | #82-84 para meteoros | |
| 301 | if len(numpy.shape(self.dataOut.data))==2: |
|
365 | if len(numpy.shape(self.dataOut.data))==2: | |
| 302 | sampInterp = (self.dataOut.data[:,botLim-1] + self.dataOut.data[:,topLim+1])/2 |
|
366 | sampInterp = (self.dataOut.data[:,botLim-1] + self.dataOut.data[:,topLim+1])/2 | |
| 303 | sampInterp = numpy.transpose(numpy.tile(sampInterp,(topLim-botLim + 1,1))) |
|
367 | sampInterp = numpy.transpose(numpy.tile(sampInterp,(topLim-botLim + 1,1))) | |
| 304 | #self.dataOut.data[:,botLim:limSup+1] = sampInterp |
|
368 | #self.dataOut.data[:,botLim:limSup+1] = sampInterp | |
| 305 | self.dataOut.data[:,botLim:topLim+1] = sampInterp |
|
369 | self.dataOut.data[:,botLim:topLim+1] = sampInterp | |
| 306 | else: |
|
370 | else: | |
| 307 | nHeights = self.dataOut.data.shape[2] |
|
371 | nHeights = self.dataOut.data.shape[2] | |
| 308 | x = numpy.hstack((numpy.arange(botLim),numpy.arange(topLim+1,nHeights))) |
|
372 | x = numpy.hstack((numpy.arange(botLim),numpy.arange(topLim+1,nHeights))) | |
| 309 | y = self.dataOut.data[:,:,range(botLim)+range(topLim+1,nHeights)] |
|
373 | y = self.dataOut.data[:,:,range(botLim)+range(topLim+1,nHeights)] | |
| 310 | f = interpolate.interp1d(x, y, axis = 2) |
|
374 | f = interpolate.interp1d(x, y, axis = 2) | |
| 311 | xnew = numpy.arange(botLim,topLim+1) |
|
375 | xnew = numpy.arange(botLim,topLim+1) | |
| 312 | ynew = f(xnew) |
|
376 | ynew = f(xnew) | |
| 313 |
|
377 | |||
| 314 | self.dataOut.data[:,:,botLim:topLim+1] = ynew |
|
378 | self.dataOut.data[:,:,botLim:topLim+1] = ynew | |
| 315 |
|
379 | |||
| 316 | # import collections |
|
380 | # import collections | |
| 317 |
|
381 | |||
| 318 | class CohInt(Operation): |
|
382 | class CohInt(Operation): | |
| 319 |
|
383 | |||
| 320 | isConfig = False |
|
384 | isConfig = False | |
| 321 | __profIndex = 0 |
|
385 | __profIndex = 0 | |
| 322 | __byTime = False |
|
386 | __byTime = False | |
| 323 | __initime = None |
|
387 | __initime = None | |
| 324 | __lastdatatime = None |
|
388 | __lastdatatime = None | |
| 325 | __integrationtime = None |
|
389 | __integrationtime = None | |
| 326 | __buffer = None |
|
390 | __buffer = None | |
| 327 | __bufferStride = [] |
|
391 | __bufferStride = [] | |
| 328 | __dataReady = False |
|
392 | __dataReady = False | |
| 329 | __profIndexStride = 0 |
|
393 | __profIndexStride = 0 | |
| 330 | __dataToPutStride = False |
|
394 | __dataToPutStride = False | |
| 331 | n = None |
|
395 | n = None | |
| 332 |
|
396 | |||
| 333 | def __init__(self, **kwargs): |
|
397 | def __init__(self, **kwargs): | |
| 334 |
|
398 | |||
| 335 | Operation.__init__(self, **kwargs) |
|
399 | Operation.__init__(self, **kwargs) | |
| 336 |
|
400 | |||
| 337 | # self.isConfig = False |
|
401 | # self.isConfig = False | |
| 338 |
|
402 | |||
| 339 | def setup(self, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False): |
|
403 | def setup(self, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False): | |
| 340 | """ |
|
404 | """ | |
| 341 | Set the parameters of the integration class. |
|
405 | Set the parameters of the integration class. | |
| 342 |
|
406 | |||
| 343 | Inputs: |
|
407 | Inputs: | |
| 344 |
|
408 | |||
| 345 | n : Number of coherent integrations |
|
409 | n : Number of coherent integrations | |
| 346 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work |
|
410 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work | |
| 347 | overlapping : |
|
411 | overlapping : | |
| 348 | """ |
|
412 | """ | |
| 349 |
|
413 | |||
| 350 | self.__initime = None |
|
414 | self.__initime = None | |
| 351 | self.__lastdatatime = 0 |
|
415 | self.__lastdatatime = 0 | |
| 352 | self.__buffer = None |
|
416 | self.__buffer = None | |
| 353 | self.__dataReady = False |
|
417 | self.__dataReady = False | |
| 354 | self.byblock = byblock |
|
418 | self.byblock = byblock | |
| 355 | self.stride = stride |
|
419 | self.stride = stride | |
| 356 |
|
420 | |||
| 357 | if n == None and timeInterval == None: |
|
421 | if n == None and timeInterval == None: | |
| 358 | raise ValueError, "n or timeInterval should be specified ..." |
|
422 | raise ValueError, "n or timeInterval should be specified ..." | |
| 359 |
|
423 | |||
| 360 | if n != None: |
|
424 | if n != None: | |
| 361 | self.n = n |
|
425 | self.n = n | |
| 362 | self.__byTime = False |
|
426 | self.__byTime = False | |
| 363 | else: |
|
427 | else: | |
| 364 | self.__integrationtime = timeInterval #* 60. #if (type(timeInterval)!=integer) -> change this line |
|
428 | self.__integrationtime = timeInterval #* 60. #if (type(timeInterval)!=integer) -> change this line | |
| 365 | self.n = 9999 |
|
429 | self.n = 9999 | |
| 366 | self.__byTime = True |
|
430 | self.__byTime = True | |
| 367 |
|
431 | |||
| 368 | if overlapping: |
|
432 | if overlapping: | |
| 369 | self.__withOverlapping = True |
|
433 | self.__withOverlapping = True | |
| 370 | self.__buffer = None |
|
434 | self.__buffer = None | |
| 371 | else: |
|
435 | else: | |
| 372 | self.__withOverlapping = False |
|
436 | self.__withOverlapping = False | |
| 373 | self.__buffer = 0 |
|
437 | self.__buffer = 0 | |
| 374 |
|
438 | |||
| 375 | self.__profIndex = 0 |
|
439 | self.__profIndex = 0 | |
| 376 |
|
440 | |||
| 377 | def putData(self, data): |
|
441 | def putData(self, data): | |
| 378 |
|
442 | |||
| 379 | """ |
|
443 | """ | |
| 380 | Add a profile to the __buffer and increase in one the __profileIndex |
|
444 | Add a profile to the __buffer and increase in one the __profileIndex | |
| 381 |
|
445 | |||
| 382 | """ |
|
446 | """ | |
| 383 |
|
447 | |||
| 384 | if not self.__withOverlapping: |
|
448 | if not self.__withOverlapping: | |
| 385 | self.__buffer += data.copy() |
|
449 | self.__buffer += data.copy() | |
| 386 | self.__profIndex += 1 |
|
450 | self.__profIndex += 1 | |
| 387 | return |
|
451 | return | |
| 388 |
|
452 | |||
| 389 | #Overlapping data |
|
453 | #Overlapping data | |
| 390 | nChannels, nHeis = data.shape |
|
454 | nChannels, nHeis = data.shape | |
| 391 | data = numpy.reshape(data, (1, nChannels, nHeis)) |
|
455 | data = numpy.reshape(data, (1, nChannels, nHeis)) | |
| 392 |
|
456 | |||
| 393 | #If the buffer is empty then it takes the data value |
|
457 | #If the buffer is empty then it takes the data value | |
| 394 | if self.__buffer is None: |
|
458 | if self.__buffer is None: | |
| 395 | self.__buffer = data |
|
459 | self.__buffer = data | |
| 396 | self.__profIndex += 1 |
|
460 | self.__profIndex += 1 | |
| 397 | return |
|
461 | return | |
| 398 |
|
462 | |||
| 399 | #If the buffer length is lower than n then stakcing the data value |
|
463 | #If the buffer length is lower than n then stakcing the data value | |
| 400 | if self.__profIndex < self.n: |
|
464 | if self.__profIndex < self.n: | |
| 401 | self.__buffer = numpy.vstack((self.__buffer, data)) |
|
465 | self.__buffer = numpy.vstack((self.__buffer, data)) | |
| 402 | self.__profIndex += 1 |
|
466 | self.__profIndex += 1 | |
| 403 | return |
|
467 | return | |
| 404 |
|
468 | |||
| 405 | #If the buffer length is equal to n then replacing the last buffer value with the data value |
|
469 | #If the buffer length is equal to n then replacing the last buffer value with the data value | |
| 406 | self.__buffer = numpy.roll(self.__buffer, -1, axis=0) |
|
470 | self.__buffer = numpy.roll(self.__buffer, -1, axis=0) | |
| 407 | self.__buffer[self.n-1] = data |
|
471 | self.__buffer[self.n-1] = data | |
| 408 | self.__profIndex = self.n |
|
472 | self.__profIndex = self.n | |
| 409 | return |
|
473 | return | |
| 410 |
|
474 | |||
| 411 |
|
475 | |||
| 412 | def pushData(self): |
|
476 | def pushData(self): | |
| 413 | """ |
|
477 | """ | |
| 414 | Return the sum of the last profiles and the profiles used in the sum. |
|
478 | Return the sum of the last profiles and the profiles used in the sum. | |
| 415 |
|
479 | |||
| 416 | Affected: |
|
480 | Affected: | |
| 417 |
|
481 | |||
| 418 | self.__profileIndex |
|
482 | self.__profileIndex | |
| 419 |
|
483 | |||
| 420 | """ |
|
484 | """ | |
| 421 |
|
485 | |||
| 422 | if not self.__withOverlapping: |
|
486 | if not self.__withOverlapping: | |
| 423 | data = self.__buffer |
|
487 | data = self.__buffer | |
| 424 | n = self.__profIndex |
|
488 | n = self.__profIndex | |
| 425 |
|
489 | |||
| 426 | self.__buffer = 0 |
|
490 | self.__buffer = 0 | |
| 427 | self.__profIndex = 0 |
|
491 | self.__profIndex = 0 | |
| 428 |
|
492 | |||
| 429 | return data, n |
|
493 | return data, n | |
| 430 |
|
494 | |||
| 431 | #Integration with Overlapping |
|
495 | #Integration with Overlapping | |
| 432 | data = numpy.sum(self.__buffer, axis=0) |
|
496 | data = numpy.sum(self.__buffer, axis=0) | |
| 433 | # print data |
|
497 | # print data | |
| 434 | # raise |
|
498 | # raise | |
| 435 | n = self.__profIndex |
|
499 | n = self.__profIndex | |
| 436 |
|
500 | |||
| 437 | return data, n |
|
501 | return data, n | |
| 438 |
|
502 | |||
| 439 | def byProfiles(self, data): |
|
503 | def byProfiles(self, data): | |
| 440 |
|
504 | |||
| 441 | self.__dataReady = False |
|
505 | self.__dataReady = False | |
| 442 | avgdata = None |
|
506 | avgdata = None | |
| 443 | # n = None |
|
507 | # n = None | |
| 444 | # print data |
|
508 | # print data | |
| 445 | # raise |
|
509 | # raise | |
| 446 | self.putData(data) |
|
510 | self.putData(data) | |
| 447 |
|
511 | |||
| 448 | if self.__profIndex == self.n: |
|
512 | if self.__profIndex == self.n: | |
| 449 | avgdata, n = self.pushData() |
|
513 | avgdata, n = self.pushData() | |
| 450 | self.__dataReady = True |
|
514 | self.__dataReady = True | |
| 451 |
|
515 | |||
| 452 | return avgdata |
|
516 | return avgdata | |
| 453 |
|
517 | |||
| 454 | def byTime(self, data, datatime): |
|
518 | def byTime(self, data, datatime): | |
| 455 |
|
519 | |||
| 456 | self.__dataReady = False |
|
520 | self.__dataReady = False | |
| 457 | avgdata = None |
|
521 | avgdata = None | |
| 458 | n = None |
|
522 | n = None | |
| 459 |
|
523 | |||
| 460 | self.putData(data) |
|
524 | self.putData(data) | |
| 461 |
|
525 | |||
| 462 | if (datatime - self.__initime) >= self.__integrationtime: |
|
526 | if (datatime - self.__initime) >= self.__integrationtime: | |
| 463 | avgdata, n = self.pushData() |
|
527 | avgdata, n = self.pushData() | |
| 464 | self.n = n |
|
528 | self.n = n | |
| 465 | self.__dataReady = True |
|
529 | self.__dataReady = True | |
| 466 |
|
530 | |||
| 467 | return avgdata |
|
531 | return avgdata | |
| 468 |
|
532 | |||
| 469 | def integrateByStride(self, data, datatime): |
|
533 | def integrateByStride(self, data, datatime): | |
| 470 | # print data |
|
534 | # print data | |
| 471 | if self.__profIndex == 0: |
|
535 | if self.__profIndex == 0: | |
| 472 | self.__buffer = [[data.copy(), datatime]] |
|
536 | self.__buffer = [[data.copy(), datatime]] | |
| 473 | else: |
|
537 | else: | |
| 474 | self.__buffer.append([data.copy(),datatime]) |
|
538 | self.__buffer.append([data.copy(),datatime]) | |
| 475 | self.__profIndex += 1 |
|
539 | self.__profIndex += 1 | |
| 476 | self.__dataReady = False |
|
540 | self.__dataReady = False | |
| 477 |
|
541 | |||
| 478 | if self.__profIndex == self.n * self.stride : |
|
542 | if self.__profIndex == self.n * self.stride : | |
| 479 | self.__dataToPutStride = True |
|
543 | self.__dataToPutStride = True | |
| 480 | self.__profIndexStride = 0 |
|
544 | self.__profIndexStride = 0 | |
| 481 | self.__profIndex = 0 |
|
545 | self.__profIndex = 0 | |
| 482 | self.__bufferStride = [] |
|
546 | self.__bufferStride = [] | |
| 483 | for i in range(self.stride): |
|
547 | for i in range(self.stride): | |
| 484 | current = self.__buffer[i::self.stride] |
|
548 | current = self.__buffer[i::self.stride] | |
| 485 | data = numpy.sum([t[0] for t in current], axis=0) |
|
549 | data = numpy.sum([t[0] for t in current], axis=0) | |
| 486 | avgdatatime = numpy.average([t[1] for t in current]) |
|
550 | avgdatatime = numpy.average([t[1] for t in current]) | |
| 487 | # print data |
|
551 | # print data | |
| 488 | self.__bufferStride.append((data, avgdatatime)) |
|
552 | self.__bufferStride.append((data, avgdatatime)) | |
| 489 |
|
553 | |||
| 490 | if self.__dataToPutStride: |
|
554 | if self.__dataToPutStride: | |
| 491 | self.__dataReady = True |
|
555 | self.__dataReady = True | |
| 492 | self.__profIndexStride += 1 |
|
556 | self.__profIndexStride += 1 | |
| 493 | if self.__profIndexStride == self.stride: |
|
557 | if self.__profIndexStride == self.stride: | |
| 494 | self.__dataToPutStride = False |
|
558 | self.__dataToPutStride = False | |
| 495 | # print self.__bufferStride[self.__profIndexStride - 1] |
|
559 | # print self.__bufferStride[self.__profIndexStride - 1] | |
| 496 | # raise |
|
560 | # raise | |
| 497 | return self.__bufferStride[self.__profIndexStride - 1] |
|
561 | return self.__bufferStride[self.__profIndexStride - 1] | |
| 498 |
|
562 | |||
| 499 |
|
563 | |||
| 500 | return None, None |
|
564 | return None, None | |
| 501 |
|
565 | |||
| 502 | def integrate(self, data, datatime=None): |
|
566 | def integrate(self, data, datatime=None): | |
| 503 |
|
567 | |||
| 504 | if self.__initime == None: |
|
568 | if self.__initime == None: | |
| 505 | self.__initime = datatime |
|
569 | self.__initime = datatime | |
| 506 |
|
570 | |||
| 507 | if self.__byTime: |
|
571 | if self.__byTime: | |
| 508 | avgdata = self.byTime(data, datatime) |
|
572 | avgdata = self.byTime(data, datatime) | |
| 509 | else: |
|
573 | else: | |
| 510 | avgdata = self.byProfiles(data) |
|
574 | avgdata = self.byProfiles(data) | |
| 511 |
|
575 | |||
| 512 |
|
576 | |||
| 513 | self.__lastdatatime = datatime |
|
577 | self.__lastdatatime = datatime | |
| 514 |
|
578 | |||
| 515 | if avgdata is None: |
|
579 | if avgdata is None: | |
| 516 | return None, None |
|
580 | return None, None | |
| 517 |
|
581 | |||
| 518 | avgdatatime = self.__initime |
|
582 | avgdatatime = self.__initime | |
| 519 |
|
583 | |||
| 520 | deltatime = datatime - self.__lastdatatime |
|
584 | deltatime = datatime - self.__lastdatatime | |
| 521 |
|
585 | |||
| 522 | if not self.__withOverlapping: |
|
586 | if not self.__withOverlapping: | |
| 523 | self.__initime = datatime |
|
587 | self.__initime = datatime | |
| 524 | else: |
|
588 | else: | |
| 525 | self.__initime += deltatime |
|
589 | self.__initime += deltatime | |
| 526 |
|
590 | |||
| 527 | return avgdata, avgdatatime |
|
591 | return avgdata, avgdatatime | |
| 528 |
|
592 | |||
| 529 | def integrateByBlock(self, dataOut): |
|
593 | def integrateByBlock(self, dataOut): | |
| 530 |
|
594 | |||
| 531 | times = int(dataOut.data.shape[1]/self.n) |
|
595 | times = int(dataOut.data.shape[1]/self.n) | |
| 532 | avgdata = numpy.zeros((dataOut.nChannels, times, dataOut.nHeights), dtype=numpy.complex) |
|
596 | avgdata = numpy.zeros((dataOut.nChannels, times, dataOut.nHeights), dtype=numpy.complex) | |
| 533 |
|
597 | |||
| 534 | id_min = 0 |
|
598 | id_min = 0 | |
| 535 | id_max = self.n |
|
599 | id_max = self.n | |
| 536 |
|
600 | |||
| 537 | for i in range(times): |
|
601 | for i in range(times): | |
| 538 | junk = dataOut.data[:,id_min:id_max,:] |
|
602 | junk = dataOut.data[:,id_min:id_max,:] | |
| 539 | avgdata[:,i,:] = junk.sum(axis=1) |
|
603 | avgdata[:,i,:] = junk.sum(axis=1) | |
| 540 | id_min += self.n |
|
604 | id_min += self.n | |
| 541 | id_max += self.n |
|
605 | id_max += self.n | |
| 542 |
|
606 | |||
| 543 | timeInterval = dataOut.ippSeconds*self.n |
|
607 | timeInterval = dataOut.ippSeconds*self.n | |
| 544 | avgdatatime = (times - 1) * timeInterval + dataOut.utctime |
|
608 | avgdatatime = (times - 1) * timeInterval + dataOut.utctime | |
| 545 | self.__dataReady = True |
|
609 | self.__dataReady = True | |
| 546 | return avgdata, avgdatatime |
|
610 | return avgdata, avgdatatime | |
| 547 |
|
611 | |||
| 548 | def run(self, dataOut, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False, **kwargs): |
|
612 | def run(self, dataOut, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False, **kwargs): | |
| 549 | if not self.isConfig: |
|
613 | if not self.isConfig: | |
| 550 | self.setup(n=n, stride=stride, timeInterval=timeInterval, overlapping=overlapping, byblock=byblock, **kwargs) |
|
614 | self.setup(n=n, stride=stride, timeInterval=timeInterval, overlapping=overlapping, byblock=byblock, **kwargs) | |
| 551 | self.isConfig = True |
|
615 | self.isConfig = True | |
| 552 |
|
616 | |||
| 553 | if dataOut.flagDataAsBlock: |
|
617 | if dataOut.flagDataAsBlock: | |
| 554 | """ |
|
618 | """ | |
| 555 | Si la data es leida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
619 | Si la data es leida por bloques, dimension = [nChannels, nProfiles, nHeis] | |
| 556 | """ |
|
620 | """ | |
| 557 | avgdata, avgdatatime = self.integrateByBlock(dataOut) |
|
621 | avgdata, avgdatatime = self.integrateByBlock(dataOut) | |
| 558 | dataOut.nProfiles /= self.n |
|
622 | dataOut.nProfiles /= self.n | |
| 559 | else: |
|
623 | else: | |
| 560 | if stride is None: |
|
624 | if stride is None: | |
| 561 | avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime) |
|
625 | avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime) | |
| 562 | else: |
|
626 | else: | |
| 563 | avgdata, avgdatatime = self.integrateByStride(dataOut.data, dataOut.utctime) |
|
627 | avgdata, avgdatatime = self.integrateByStride(dataOut.data, dataOut.utctime) | |
| 564 |
|
628 | |||
| 565 |
|
629 | |||
| 566 | # dataOut.timeInterval *= n |
|
630 | # dataOut.timeInterval *= n | |
| 567 | dataOut.flagNoData = True |
|
631 | dataOut.flagNoData = True | |
| 568 |
|
632 | |||
| 569 | if self.__dataReady: |
|
633 | if self.__dataReady: | |
| 570 | dataOut.data = avgdata |
|
634 | dataOut.data = avgdata | |
| 571 | dataOut.nCohInt *= self.n |
|
635 | dataOut.nCohInt *= self.n | |
| 572 | dataOut.utctime = avgdatatime |
|
636 | dataOut.utctime = avgdatatime | |
| 573 | # print avgdata, avgdatatime |
|
637 | # print avgdata, avgdatatime | |
| 574 | # raise |
|
638 | # raise | |
| 575 | # dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt |
|
639 | # dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt | |
| 576 | dataOut.flagNoData = False |
|
640 | dataOut.flagNoData = False | |
| 577 |
|
641 | |||
| 578 | class Decoder(Operation): |
|
642 | class Decoder(Operation): | |
| 579 |
|
643 | |||
| 580 | isConfig = False |
|
644 | isConfig = False | |
| 581 | __profIndex = 0 |
|
645 | __profIndex = 0 | |
| 582 |
|
646 | |||
| 583 | code = None |
|
647 | code = None | |
| 584 |
|
648 | |||
| 585 | nCode = None |
|
649 | nCode = None | |
| 586 | nBaud = None |
|
650 | nBaud = None | |
| 587 |
|
651 | |||
| 588 | def __init__(self, **kwargs): |
|
652 | def __init__(self, **kwargs): | |
| 589 |
|
653 | |||
| 590 | Operation.__init__(self, **kwargs) |
|
654 | Operation.__init__(self, **kwargs) | |
| 591 |
|
655 | |||
| 592 | self.times = None |
|
656 | self.times = None | |
| 593 | self.osamp = None |
|
657 | self.osamp = None | |
| 594 | # self.__setValues = False |
|
658 | # self.__setValues = False | |
| 595 | self.isConfig = False |
|
659 | self.isConfig = False | |
| 596 |
|
660 | |||
| 597 | def setup(self, code, osamp, dataOut): |
|
661 | def setup(self, code, osamp, dataOut): | |
| 598 |
|
662 | |||
| 599 | self.__profIndex = 0 |
|
663 | self.__profIndex = 0 | |
| 600 |
|
664 | |||
| 601 | self.code = code |
|
665 | self.code = code | |
| 602 |
|
666 | |||
| 603 | self.nCode = len(code) |
|
667 | self.nCode = len(code) | |
| 604 | self.nBaud = len(code[0]) |
|
668 | self.nBaud = len(code[0]) | |
| 605 |
|
669 | |||
| 606 | if (osamp != None) and (osamp >1): |
|
670 | if (osamp != None) and (osamp >1): | |
| 607 | self.osamp = osamp |
|
671 | self.osamp = osamp | |
| 608 | self.code = numpy.repeat(code, repeats=self.osamp, axis=1) |
|
672 | self.code = numpy.repeat(code, repeats=self.osamp, axis=1) | |
| 609 | self.nBaud = self.nBaud*self.osamp |
|
673 | self.nBaud = self.nBaud*self.osamp | |
| 610 |
|
674 | |||
| 611 | self.__nChannels = dataOut.nChannels |
|
675 | self.__nChannels = dataOut.nChannels | |
| 612 | self.__nProfiles = dataOut.nProfiles |
|
676 | self.__nProfiles = dataOut.nProfiles | |
| 613 | self.__nHeis = dataOut.nHeights |
|
677 | self.__nHeis = dataOut.nHeights | |
| 614 |
|
678 | |||
| 615 | if self.__nHeis < self.nBaud: |
|
679 | if self.__nHeis < self.nBaud: | |
| 616 | raise ValueError, 'Number of heights (%d) should be greater than number of bauds (%d)' %(self.__nHeis, self.nBaud) |
|
680 | raise ValueError, 'Number of heights (%d) should be greater than number of bauds (%d)' %(self.__nHeis, self.nBaud) | |
| 617 |
|
681 | |||
| 618 | #Frequency |
|
682 | #Frequency | |
| 619 | __codeBuffer = numpy.zeros((self.nCode, self.__nHeis), dtype=numpy.complex) |
|
683 | __codeBuffer = numpy.zeros((self.nCode, self.__nHeis), dtype=numpy.complex) | |
| 620 |
|
684 | |||
| 621 | __codeBuffer[:,0:self.nBaud] = self.code |
|
685 | __codeBuffer[:,0:self.nBaud] = self.code | |
| 622 |
|
686 | |||
| 623 | self.fft_code = numpy.conj(numpy.fft.fft(__codeBuffer, axis=1)) |
|
687 | self.fft_code = numpy.conj(numpy.fft.fft(__codeBuffer, axis=1)) | |
| 624 |
|
688 | |||
| 625 | if dataOut.flagDataAsBlock: |
|
689 | if dataOut.flagDataAsBlock: | |
| 626 |
|
690 | |||
| 627 | self.ndatadec = self.__nHeis #- self.nBaud + 1 |
|
691 | self.ndatadec = self.__nHeis #- self.nBaud + 1 | |
| 628 |
|
692 | |||
| 629 | self.datadecTime = numpy.zeros((self.__nChannels, self.__nProfiles, self.ndatadec), dtype=numpy.complex) |
|
693 | self.datadecTime = numpy.zeros((self.__nChannels, self.__nProfiles, self.ndatadec), dtype=numpy.complex) | |
| 630 |
|
694 | |||
| 631 | else: |
|
695 | else: | |
| 632 |
|
696 | |||
| 633 | #Time |
|
697 | #Time | |
| 634 | self.ndatadec = self.__nHeis #- self.nBaud + 1 |
|
698 | self.ndatadec = self.__nHeis #- self.nBaud + 1 | |
| 635 |
|
699 | |||
| 636 | self.datadecTime = numpy.zeros((self.__nChannels, self.ndatadec), dtype=numpy.complex) |
|
700 | self.datadecTime = numpy.zeros((self.__nChannels, self.ndatadec), dtype=numpy.complex) | |
| 637 |
|
701 | |||
| 638 | def __convolutionInFreq(self, data): |
|
702 | def __convolutionInFreq(self, data): | |
| 639 |
|
703 | |||
| 640 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) |
|
704 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) | |
| 641 |
|
705 | |||
| 642 | fft_data = numpy.fft.fft(data, axis=1) |
|
706 | fft_data = numpy.fft.fft(data, axis=1) | |
| 643 |
|
707 | |||
| 644 | conv = fft_data*fft_code |
|
708 | conv = fft_data*fft_code | |
| 645 |
|
709 | |||
| 646 | data = numpy.fft.ifft(conv,axis=1) |
|
710 | data = numpy.fft.ifft(conv,axis=1) | |
| 647 |
|
711 | |||
| 648 | return data |
|
712 | return data | |
| 649 |
|
713 | |||
| 650 | def __convolutionInFreqOpt(self, data): |
|
714 | def __convolutionInFreqOpt(self, data): | |
| 651 |
|
715 | |||
| 652 | raise NotImplementedError |
|
716 | raise NotImplementedError | |
| 653 |
|
717 | |||
| 654 | def __convolutionInTime(self, data): |
|
718 | def __convolutionInTime(self, data): | |
| 655 |
|
719 | |||
| 656 | code = self.code[self.__profIndex] |
|
720 | code = self.code[self.__profIndex] | |
| 657 | for i in range(self.__nChannels): |
|
721 | for i in range(self.__nChannels): | |
| 658 | self.datadecTime[i,:] = numpy.correlate(data[i,:], code, mode='full')[self.nBaud-1:] |
|
722 | self.datadecTime[i,:] = numpy.correlate(data[i,:], code, mode='full')[self.nBaud-1:] | |
| 659 |
|
723 | |||
| 660 | return self.datadecTime |
|
724 | return self.datadecTime | |
| 661 |
|
725 | |||
| 662 | def __convolutionByBlockInTime(self, data): |
|
726 | def __convolutionByBlockInTime(self, data): | |
| 663 |
|
727 | |||
| 664 | repetitions = self.__nProfiles / self.nCode |
|
728 | repetitions = self.__nProfiles / self.nCode | |
| 665 |
|
729 | |||
| 666 | junk = numpy.lib.stride_tricks.as_strided(self.code, (repetitions, self.code.size), (0, self.code.itemsize)) |
|
730 | junk = numpy.lib.stride_tricks.as_strided(self.code, (repetitions, self.code.size), (0, self.code.itemsize)) | |
| 667 | junk = junk.flatten() |
|
731 | junk = junk.flatten() | |
| 668 | code_block = numpy.reshape(junk, (self.nCode*repetitions, self.nBaud)) |
|
732 | code_block = numpy.reshape(junk, (self.nCode*repetitions, self.nBaud)) | |
| 669 | profilesList = xrange(self.__nProfiles) |
|
733 | profilesList = xrange(self.__nProfiles) | |
| 670 |
|
734 | |||
| 671 | for i in range(self.__nChannels): |
|
735 | for i in range(self.__nChannels): | |
| 672 | for j in profilesList: |
|
736 | for j in profilesList: | |
| 673 | self.datadecTime[i,j,:] = numpy.correlate(data[i,j,:], code_block[j,:], mode='full')[self.nBaud-1:] |
|
737 | self.datadecTime[i,j,:] = numpy.correlate(data[i,j,:], code_block[j,:], mode='full')[self.nBaud-1:] | |
| 674 | return self.datadecTime |
|
738 | return self.datadecTime | |
| 675 |
|
739 | |||
| 676 | def __convolutionByBlockInFreq(self, data): |
|
740 | def __convolutionByBlockInFreq(self, data): | |
| 677 |
|
741 | |||
| 678 | raise NotImplementedError, "Decoder by frequency fro Blocks not implemented" |
|
742 | raise NotImplementedError, "Decoder by frequency fro Blocks not implemented" | |
| 679 |
|
743 | |||
| 680 |
|
744 | |||
| 681 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) |
|
745 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) | |
| 682 |
|
746 | |||
| 683 | fft_data = numpy.fft.fft(data, axis=2) |
|
747 | fft_data = numpy.fft.fft(data, axis=2) | |
| 684 |
|
748 | |||
| 685 | conv = fft_data*fft_code |
|
749 | conv = fft_data*fft_code | |
| 686 |
|
750 | |||
| 687 | data = numpy.fft.ifft(conv,axis=2) |
|
751 | data = numpy.fft.ifft(conv,axis=2) | |
| 688 |
|
752 | |||
| 689 | return data |
|
753 | return data | |
| 690 |
|
754 | |||
| 691 |
|
755 | |||
| 692 | def run(self, dataOut, code=None, nCode=None, nBaud=None, mode = 0, osamp=None, times=None): |
|
756 | def run(self, dataOut, code=None, nCode=None, nBaud=None, mode = 0, osamp=None, times=None): | |
| 693 |
|
757 | |||
| 694 | if dataOut.flagDecodeData: |
|
758 | if dataOut.flagDecodeData: | |
| 695 | print "This data is already decoded, recoding again ..." |
|
759 | print "This data is already decoded, recoding again ..." | |
| 696 |
|
760 | |||
| 697 | if not self.isConfig: |
|
761 | if not self.isConfig: | |
| 698 |
|
762 | |||
| 699 | if code is None: |
|
763 | if code is None: | |
| 700 | if dataOut.code is None: |
|
764 | if dataOut.code is None: | |
| 701 | raise ValueError, "Code could not be read from %s instance. Enter a value in Code parameter" %dataOut.type |
|
765 | raise ValueError, "Code could not be read from %s instance. Enter a value in Code parameter" %dataOut.type | |
| 702 |
|
766 | |||
| 703 | code = dataOut.code |
|
767 | code = dataOut.code | |
| 704 | else: |
|
768 | else: | |
| 705 | code = numpy.array(code).reshape(nCode,nBaud) |
|
769 | code = numpy.array(code).reshape(nCode,nBaud) | |
| 706 | self.setup(code, osamp, dataOut) |
|
770 | self.setup(code, osamp, dataOut) | |
| 707 |
|
771 | |||
| 708 | self.isConfig = True |
|
772 | self.isConfig = True | |
| 709 |
|
773 | |||
| 710 | if mode == 3: |
|
774 | if mode == 3: | |
| 711 | sys.stderr.write("Decoder Warning: mode=%d is not valid, using mode=0\n" %mode) |
|
775 | sys.stderr.write("Decoder Warning: mode=%d is not valid, using mode=0\n" %mode) | |
| 712 |
|
776 | |||
| 713 | if times != None: |
|
777 | if times != None: | |
| 714 | sys.stderr.write("Decoder Warning: Argument 'times' in not used anymore\n") |
|
778 | sys.stderr.write("Decoder Warning: Argument 'times' in not used anymore\n") | |
| 715 |
|
779 | |||
| 716 | if self.code is None: |
|
780 | if self.code is None: | |
| 717 | print "Fail decoding: Code is not defined." |
|
781 | print "Fail decoding: Code is not defined." | |
| 718 | return |
|
782 | return | |
| 719 |
|
783 | |||
| 720 | self.__nProfiles = dataOut.nProfiles |
|
784 | self.__nProfiles = dataOut.nProfiles | |
| 721 | datadec = None |
|
785 | datadec = None | |
| 722 |
|
786 | |||
| 723 | if mode == 3: |
|
787 | if mode == 3: | |
| 724 | mode = 0 |
|
788 | mode = 0 | |
| 725 |
|
789 | |||
| 726 | if dataOut.flagDataAsBlock: |
|
790 | if dataOut.flagDataAsBlock: | |
| 727 | """ |
|
791 | """ | |
| 728 | Decoding when data have been read as block, |
|
792 | Decoding when data have been read as block, | |
| 729 | """ |
|
793 | """ | |
| 730 |
|
794 | |||
| 731 | if mode == 0: |
|
795 | if mode == 0: | |
| 732 | datadec = self.__convolutionByBlockInTime(dataOut.data) |
|
796 | datadec = self.__convolutionByBlockInTime(dataOut.data) | |
| 733 | if mode == 1: |
|
797 | if mode == 1: | |
| 734 | datadec = self.__convolutionByBlockInFreq(dataOut.data) |
|
798 | datadec = self.__convolutionByBlockInFreq(dataOut.data) | |
| 735 | else: |
|
799 | else: | |
| 736 | """ |
|
800 | """ | |
| 737 | Decoding when data have been read profile by profile |
|
801 | Decoding when data have been read profile by profile | |
| 738 | """ |
|
802 | """ | |
| 739 | if mode == 0: |
|
803 | if mode == 0: | |
| 740 | datadec = self.__convolutionInTime(dataOut.data) |
|
804 | datadec = self.__convolutionInTime(dataOut.data) | |
| 741 |
|
805 | |||
| 742 | if mode == 1: |
|
806 | if mode == 1: | |
| 743 | datadec = self.__convolutionInFreq(dataOut.data) |
|
807 | datadec = self.__convolutionInFreq(dataOut.data) | |
| 744 |
|
808 | |||
| 745 | if mode == 2: |
|
809 | if mode == 2: | |
| 746 | datadec = self.__convolutionInFreqOpt(dataOut.data) |
|
810 | datadec = self.__convolutionInFreqOpt(dataOut.data) | |
| 747 |
|
811 | |||
| 748 | if datadec is None: |
|
812 | if datadec is None: | |
| 749 | raise ValueError, "Codification mode selected is not valid: mode=%d. Try selecting 0 or 1" %mode |
|
813 | raise ValueError, "Codification mode selected is not valid: mode=%d. Try selecting 0 or 1" %mode | |
| 750 |
|
814 | |||
| 751 | dataOut.code = self.code |
|
815 | dataOut.code = self.code | |
| 752 | dataOut.nCode = self.nCode |
|
816 | dataOut.nCode = self.nCode | |
| 753 | dataOut.nBaud = self.nBaud |
|
817 | dataOut.nBaud = self.nBaud | |
| 754 |
|
818 | |||
| 755 | dataOut.data = datadec |
|
819 | dataOut.data = datadec | |
| 756 |
|
820 | |||
| 757 | dataOut.heightList = dataOut.heightList[0:datadec.shape[-1]] |
|
821 | dataOut.heightList = dataOut.heightList[0:datadec.shape[-1]] | |
| 758 |
|
822 | |||
| 759 | dataOut.flagDecodeData = True #asumo q la data esta decodificada |
|
823 | dataOut.flagDecodeData = True #asumo q la data esta decodificada | |
| 760 |
|
824 | |||
| 761 | if self.__profIndex == self.nCode-1: |
|
825 | if self.__profIndex == self.nCode-1: | |
| 762 | self.__profIndex = 0 |
|
826 | self.__profIndex = 0 | |
| 763 | return 1 |
|
827 | return 1 | |
| 764 |
|
828 | |||
| 765 | self.__profIndex += 1 |
|
829 | self.__profIndex += 1 | |
| 766 |
|
830 | |||
| 767 | return 1 |
|
831 | return 1 | |
| 768 | # dataOut.flagDeflipData = True #asumo q la data no esta sin flip |
|
832 | # dataOut.flagDeflipData = True #asumo q la data no esta sin flip | |
| 769 |
|
833 | |||
| 770 |
|
834 | |||
| 771 | class ProfileConcat(Operation): |
|
835 | class ProfileConcat(Operation): | |
| 772 |
|
836 | |||
| 773 | isConfig = False |
|
837 | isConfig = False | |
| 774 | buffer = None |
|
838 | buffer = None | |
| 775 |
|
839 | |||
| 776 | def __init__(self, **kwargs): |
|
840 | def __init__(self, **kwargs): | |
| 777 |
|
841 | |||
| 778 | Operation.__init__(self, **kwargs) |
|
842 | Operation.__init__(self, **kwargs) | |
| 779 | self.profileIndex = 0 |
|
843 | self.profileIndex = 0 | |
| 780 |
|
844 | |||
| 781 | def reset(self): |
|
845 | def reset(self): | |
| 782 | self.buffer = numpy.zeros_like(self.buffer) |
|
846 | self.buffer = numpy.zeros_like(self.buffer) | |
| 783 | self.start_index = 0 |
|
847 | self.start_index = 0 | |
| 784 | self.times = 1 |
|
848 | self.times = 1 | |
| 785 |
|
849 | |||
| 786 | def setup(self, data, m, n=1): |
|
850 | def setup(self, data, m, n=1): | |
| 787 | self.buffer = numpy.zeros((data.shape[0],data.shape[1]*m),dtype=type(data[0,0])) |
|
851 | self.buffer = numpy.zeros((data.shape[0],data.shape[1]*m),dtype=type(data[0,0])) | |
| 788 | self.nHeights = data.shape[1]#.nHeights |
|
852 | self.nHeights = data.shape[1]#.nHeights | |
| 789 | self.start_index = 0 |
|
853 | self.start_index = 0 | |
| 790 | self.times = 1 |
|
854 | self.times = 1 | |
| 791 |
|
855 | |||
| 792 | def concat(self, data): |
|
856 | def concat(self, data): | |
| 793 |
|
857 | |||
| 794 | self.buffer[:,self.start_index:self.nHeights*self.times] = data.copy() |
|
858 | self.buffer[:,self.start_index:self.nHeights*self.times] = data.copy() | |
| 795 | self.start_index = self.start_index + self.nHeights |
|
859 | self.start_index = self.start_index + self.nHeights | |
| 796 |
|
860 | |||
| 797 | def run(self, dataOut, m): |
|
861 | def run(self, dataOut, m): | |
| 798 |
|
862 | |||
| 799 | dataOut.flagNoData = True |
|
863 | dataOut.flagNoData = True | |
| 800 |
|
864 | |||
| 801 | if not self.isConfig: |
|
865 | if not self.isConfig: | |
| 802 | self.setup(dataOut.data, m, 1) |
|
866 | self.setup(dataOut.data, m, 1) | |
| 803 | self.isConfig = True |
|
867 | self.isConfig = True | |
| 804 |
|
868 | |||
| 805 | if dataOut.flagDataAsBlock: |
|
869 | if dataOut.flagDataAsBlock: | |
| 806 | raise ValueError, "ProfileConcat can only be used when voltage have been read profile by profile, getBlock = False" |
|
870 | raise ValueError, "ProfileConcat can only be used when voltage have been read profile by profile, getBlock = False" | |
| 807 |
|
871 | |||
| 808 | else: |
|
872 | else: | |
| 809 | self.concat(dataOut.data) |
|
873 | self.concat(dataOut.data) | |
| 810 | self.times += 1 |
|
874 | self.times += 1 | |
| 811 | if self.times > m: |
|
875 | if self.times > m: | |
| 812 | dataOut.data = self.buffer |
|
876 | dataOut.data = self.buffer | |
| 813 | self.reset() |
|
877 | self.reset() | |
| 814 | dataOut.flagNoData = False |
|
878 | dataOut.flagNoData = False | |
| 815 | # se deben actualizar mas propiedades del header y del objeto dataOut, por ejemplo, las alturas |
|
879 | # se deben actualizar mas propiedades del header y del objeto dataOut, por ejemplo, las alturas | |
| 816 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
880 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 817 | xf = dataOut.heightList[0] + dataOut.nHeights * deltaHeight * m |
|
881 | xf = dataOut.heightList[0] + dataOut.nHeights * deltaHeight * m | |
| 818 | dataOut.heightList = numpy.arange(dataOut.heightList[0], xf, deltaHeight) |
|
882 | dataOut.heightList = numpy.arange(dataOut.heightList[0], xf, deltaHeight) | |
| 819 | dataOut.ippSeconds *= m |
|
883 | dataOut.ippSeconds *= m | |
| 820 |
|
884 | |||
| 821 | class ProfileSelector(Operation): |
|
885 | class ProfileSelector(Operation): | |
| 822 |
|
886 | |||
| 823 | profileIndex = None |
|
887 | profileIndex = None | |
| 824 | # Tamanho total de los perfiles |
|
888 | # Tamanho total de los perfiles | |
| 825 | nProfiles = None |
|
889 | nProfiles = None | |
| 826 |
|
890 | |||
| 827 | def __init__(self, **kwargs): |
|
891 | def __init__(self, **kwargs): | |
| 828 |
|
892 | |||
| 829 | Operation.__init__(self, **kwargs) |
|
893 | Operation.__init__(self, **kwargs) | |
| 830 | self.profileIndex = 0 |
|
894 | self.profileIndex = 0 | |
| 831 |
|
895 | |||
| 832 | def incProfileIndex(self): |
|
896 | def incProfileIndex(self): | |
| 833 |
|
897 | |||
| 834 | self.profileIndex += 1 |
|
898 | self.profileIndex += 1 | |
| 835 |
|
899 | |||
| 836 | if self.profileIndex >= self.nProfiles: |
|
900 | if self.profileIndex >= self.nProfiles: | |
| 837 | self.profileIndex = 0 |
|
901 | self.profileIndex = 0 | |
| 838 |
|
902 | |||
| 839 | def isThisProfileInRange(self, profileIndex, minIndex, maxIndex): |
|
903 | def isThisProfileInRange(self, profileIndex, minIndex, maxIndex): | |
| 840 |
|
904 | |||
| 841 | if profileIndex < minIndex: |
|
905 | if profileIndex < minIndex: | |
| 842 | return False |
|
906 | return False | |
| 843 |
|
907 | |||
| 844 | if profileIndex > maxIndex: |
|
908 | if profileIndex > maxIndex: | |
| 845 | return False |
|
909 | return False | |
| 846 |
|
910 | |||
| 847 | return True |
|
911 | return True | |
| 848 |
|
912 | |||
| 849 | def isThisProfileInList(self, profileIndex, profileList): |
|
913 | def isThisProfileInList(self, profileIndex, profileList): | |
| 850 |
|
914 | |||
| 851 | if profileIndex not in profileList: |
|
915 | if profileIndex not in profileList: | |
| 852 | return False |
|
916 | return False | |
| 853 |
|
917 | |||
| 854 | return True |
|
918 | return True | |
| 855 |
|
919 | |||
| 856 | def run(self, dataOut, profileList=None, profileRangeList=None, beam=None, byblock=False, rangeList = None, nProfiles=None): |
|
920 | def run(self, dataOut, profileList=None, profileRangeList=None, beam=None, byblock=False, rangeList = None, nProfiles=None): | |
| 857 |
|
921 | |||
| 858 | """ |
|
922 | """ | |
| 859 | ProfileSelector: |
|
923 | ProfileSelector: | |
| 860 |
|
924 | |||
| 861 | Inputs: |
|
925 | Inputs: | |
| 862 | profileList : Index of profiles selected. Example: profileList = (0,1,2,7,8) |
|
926 | profileList : Index of profiles selected. Example: profileList = (0,1,2,7,8) | |
| 863 |
|
927 | |||
| 864 | profileRangeList : Minimum and maximum profile indexes. Example: profileRangeList = (4, 30) |
|
928 | profileRangeList : Minimum and maximum profile indexes. Example: profileRangeList = (4, 30) | |
| 865 |
|
929 | |||
| 866 | rangeList : List of profile ranges. Example: rangeList = ((4, 30), (32, 64), (128, 256)) |
|
930 | rangeList : List of profile ranges. Example: rangeList = ((4, 30), (32, 64), (128, 256)) | |
| 867 |
|
931 | |||
| 868 | """ |
|
932 | """ | |
| 869 |
|
933 | |||
| 870 | if rangeList is not None: |
|
934 | if rangeList is not None: | |
| 871 | if type(rangeList[0]) not in (tuple, list): |
|
935 | if type(rangeList[0]) not in (tuple, list): | |
| 872 | rangeList = [rangeList] |
|
936 | rangeList = [rangeList] | |
| 873 |
|
937 | |||
| 874 | dataOut.flagNoData = True |
|
938 | dataOut.flagNoData = True | |
| 875 |
|
939 | |||
| 876 | if dataOut.flagDataAsBlock: |
|
940 | if dataOut.flagDataAsBlock: | |
| 877 | """ |
|
941 | """ | |
| 878 | data dimension = [nChannels, nProfiles, nHeis] |
|
942 | data dimension = [nChannels, nProfiles, nHeis] | |
| 879 | """ |
|
943 | """ | |
| 880 | if profileList != None: |
|
944 | if profileList != None: | |
| 881 | dataOut.data = dataOut.data[:,profileList,:] |
|
945 | dataOut.data = dataOut.data[:,profileList,:] | |
| 882 |
|
946 | |||
| 883 | if profileRangeList != None: |
|
947 | if profileRangeList != None: | |
| 884 | minIndex = profileRangeList[0] |
|
948 | minIndex = profileRangeList[0] | |
| 885 | maxIndex = profileRangeList[1] |
|
949 | maxIndex = profileRangeList[1] | |
| 886 | profileList = range(minIndex, maxIndex+1) |
|
950 | profileList = range(minIndex, maxIndex+1) | |
| 887 |
|
951 | |||
| 888 | dataOut.data = dataOut.data[:,minIndex:maxIndex+1,:] |
|
952 | dataOut.data = dataOut.data[:,minIndex:maxIndex+1,:] | |
| 889 |
|
953 | |||
| 890 | if rangeList != None: |
|
954 | if rangeList != None: | |
| 891 |
|
955 | |||
| 892 | profileList = [] |
|
956 | profileList = [] | |
| 893 |
|
957 | |||
| 894 | for thisRange in rangeList: |
|
958 | for thisRange in rangeList: | |
| 895 | minIndex = thisRange[0] |
|
959 | minIndex = thisRange[0] | |
| 896 | maxIndex = thisRange[1] |
|
960 | maxIndex = thisRange[1] | |
| 897 |
|
961 | |||
| 898 | profileList.extend(range(minIndex, maxIndex+1)) |
|
962 | profileList.extend(range(minIndex, maxIndex+1)) | |
| 899 |
|
963 | |||
| 900 | dataOut.data = dataOut.data[:,profileList,:] |
|
964 | dataOut.data = dataOut.data[:,profileList,:] | |
| 901 |
|
965 | |||
| 902 | dataOut.nProfiles = len(profileList) |
|
966 | dataOut.nProfiles = len(profileList) | |
| 903 | dataOut.profileIndex = dataOut.nProfiles - 1 |
|
967 | dataOut.profileIndex = dataOut.nProfiles - 1 | |
| 904 | dataOut.flagNoData = False |
|
968 | dataOut.flagNoData = False | |
| 905 |
|
969 | |||
| 906 | return True |
|
970 | return True | |
| 907 |
|
971 | |||
| 908 | """ |
|
972 | """ | |
| 909 | data dimension = [nChannels, nHeis] |
|
973 | data dimension = [nChannels, nHeis] | |
| 910 | """ |
|
974 | """ | |
| 911 |
|
975 | |||
| 912 | if profileList != None: |
|
976 | if profileList != None: | |
| 913 |
|
977 | |||
| 914 | if self.isThisProfileInList(dataOut.profileIndex, profileList): |
|
978 | if self.isThisProfileInList(dataOut.profileIndex, profileList): | |
| 915 |
|
979 | |||
| 916 | self.nProfiles = len(profileList) |
|
980 | self.nProfiles = len(profileList) | |
| 917 | dataOut.nProfiles = self.nProfiles |
|
981 | dataOut.nProfiles = self.nProfiles | |
| 918 | dataOut.profileIndex = self.profileIndex |
|
982 | dataOut.profileIndex = self.profileIndex | |
| 919 | dataOut.flagNoData = False |
|
983 | dataOut.flagNoData = False | |
| 920 |
|
984 | |||
| 921 | self.incProfileIndex() |
|
985 | self.incProfileIndex() | |
| 922 | return True |
|
986 | return True | |
| 923 |
|
987 | |||
| 924 | if profileRangeList != None: |
|
988 | if profileRangeList != None: | |
| 925 |
|
989 | |||
| 926 | minIndex = profileRangeList[0] |
|
990 | minIndex = profileRangeList[0] | |
| 927 | maxIndex = profileRangeList[1] |
|
991 | maxIndex = profileRangeList[1] | |
| 928 |
|
992 | |||
| 929 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): |
|
993 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): | |
| 930 |
|
994 | |||
| 931 | self.nProfiles = maxIndex - minIndex + 1 |
|
995 | self.nProfiles = maxIndex - minIndex + 1 | |
| 932 | dataOut.nProfiles = self.nProfiles |
|
996 | dataOut.nProfiles = self.nProfiles | |
| 933 | dataOut.profileIndex = self.profileIndex |
|
997 | dataOut.profileIndex = self.profileIndex | |
| 934 | dataOut.flagNoData = False |
|
998 | dataOut.flagNoData = False | |
| 935 |
|
999 | |||
| 936 | self.incProfileIndex() |
|
1000 | self.incProfileIndex() | |
| 937 | return True |
|
1001 | return True | |
| 938 |
|
1002 | |||
| 939 | if rangeList != None: |
|
1003 | if rangeList != None: | |
| 940 |
|
1004 | |||
| 941 | nProfiles = 0 |
|
1005 | nProfiles = 0 | |
| 942 |
|
1006 | |||
| 943 | for thisRange in rangeList: |
|
1007 | for thisRange in rangeList: | |
| 944 | minIndex = thisRange[0] |
|
1008 | minIndex = thisRange[0] | |
| 945 | maxIndex = thisRange[1] |
|
1009 | maxIndex = thisRange[1] | |
| 946 |
|
1010 | |||
| 947 | nProfiles += maxIndex - minIndex + 1 |
|
1011 | nProfiles += maxIndex - minIndex + 1 | |
| 948 |
|
1012 | |||
| 949 | for thisRange in rangeList: |
|
1013 | for thisRange in rangeList: | |
| 950 |
|
1014 | |||
| 951 | minIndex = thisRange[0] |
|
1015 | minIndex = thisRange[0] | |
| 952 | maxIndex = thisRange[1] |
|
1016 | maxIndex = thisRange[1] | |
| 953 |
|
1017 | |||
| 954 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): |
|
1018 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): | |
| 955 |
|
1019 | |||
| 956 | self.nProfiles = nProfiles |
|
1020 | self.nProfiles = nProfiles | |
| 957 | dataOut.nProfiles = self.nProfiles |
|
1021 | dataOut.nProfiles = self.nProfiles | |
| 958 | dataOut.profileIndex = self.profileIndex |
|
1022 | dataOut.profileIndex = self.profileIndex | |
| 959 | dataOut.flagNoData = False |
|
1023 | dataOut.flagNoData = False | |
| 960 |
|
1024 | |||
| 961 | self.incProfileIndex() |
|
1025 | self.incProfileIndex() | |
| 962 |
|
1026 | |||
| 963 | break |
|
1027 | break | |
| 964 |
|
1028 | |||
| 965 | return True |
|
1029 | return True | |
| 966 |
|
1030 | |||
| 967 |
|
1031 | |||
| 968 | if beam != None: #beam is only for AMISR data |
|
1032 | if beam != None: #beam is only for AMISR data | |
| 969 | if self.isThisProfileInList(dataOut.profileIndex, dataOut.beamRangeDict[beam]): |
|
1033 | if self.isThisProfileInList(dataOut.profileIndex, dataOut.beamRangeDict[beam]): | |
| 970 | dataOut.flagNoData = False |
|
1034 | dataOut.flagNoData = False | |
| 971 | dataOut.profileIndex = self.profileIndex |
|
1035 | dataOut.profileIndex = self.profileIndex | |
| 972 |
|
1036 | |||
| 973 | self.incProfileIndex() |
|
1037 | self.incProfileIndex() | |
| 974 |
|
1038 | |||
| 975 | return True |
|
1039 | return True | |
| 976 |
|
1040 | |||
| 977 | raise ValueError, "ProfileSelector needs profileList, profileRangeList or rangeList parameter" |
|
1041 | raise ValueError, "ProfileSelector needs profileList, profileRangeList or rangeList parameter" | |
| 978 |
|
1042 | |||
| 979 | return False |
|
1043 | return False | |
| 980 |
|
1044 | |||
| 981 | class Reshaper(Operation): |
|
1045 | class Reshaper(Operation): | |
| 982 |
|
1046 | |||
| 983 | def __init__(self, **kwargs): |
|
1047 | def __init__(self, **kwargs): | |
| 984 |
|
1048 | |||
| 985 | Operation.__init__(self, **kwargs) |
|
1049 | Operation.__init__(self, **kwargs) | |
| 986 |
|
1050 | |||
| 987 | self.__buffer = None |
|
1051 | self.__buffer = None | |
| 988 | self.__nitems = 0 |
|
1052 | self.__nitems = 0 | |
| 989 |
|
1053 | |||
| 990 | def __appendProfile(self, dataOut, nTxs): |
|
1054 | def __appendProfile(self, dataOut, nTxs): | |
| 991 |
|
1055 | |||
| 992 | if self.__buffer is None: |
|
1056 | if self.__buffer is None: | |
| 993 | shape = (dataOut.nChannels, int(dataOut.nHeights/nTxs) ) |
|
1057 | shape = (dataOut.nChannels, int(dataOut.nHeights/nTxs) ) | |
| 994 | self.__buffer = numpy.empty(shape, dtype = dataOut.data.dtype) |
|
1058 | self.__buffer = numpy.empty(shape, dtype = dataOut.data.dtype) | |
| 995 |
|
1059 | |||
| 996 | ini = dataOut.nHeights * self.__nitems |
|
1060 | ini = dataOut.nHeights * self.__nitems | |
| 997 | end = ini + dataOut.nHeights |
|
1061 | end = ini + dataOut.nHeights | |
| 998 |
|
1062 | |||
| 999 | self.__buffer[:, ini:end] = dataOut.data |
|
1063 | self.__buffer[:, ini:end] = dataOut.data | |
| 1000 |
|
1064 | |||
| 1001 | self.__nitems += 1 |
|
1065 | self.__nitems += 1 | |
| 1002 |
|
1066 | |||
| 1003 | return int(self.__nitems*nTxs) |
|
1067 | return int(self.__nitems*nTxs) | |
| 1004 |
|
1068 | |||
| 1005 | def __getBuffer(self): |
|
1069 | def __getBuffer(self): | |
| 1006 |
|
1070 | |||
| 1007 | if self.__nitems == int(1./self.__nTxs): |
|
1071 | if self.__nitems == int(1./self.__nTxs): | |
| 1008 |
|
1072 | |||
| 1009 | self.__nitems = 0 |
|
1073 | self.__nitems = 0 | |
| 1010 |
|
1074 | |||
| 1011 | return self.__buffer.copy() |
|
1075 | return self.__buffer.copy() | |
| 1012 |
|
1076 | |||
| 1013 | return None |
|
1077 | return None | |
| 1014 |
|
1078 | |||
| 1015 | def __checkInputs(self, dataOut, shape, nTxs): |
|
1079 | def __checkInputs(self, dataOut, shape, nTxs): | |
| 1016 |
|
1080 | |||
| 1017 | if shape is None and nTxs is None: |
|
1081 | if shape is None and nTxs is None: | |
| 1018 | raise ValueError, "Reshaper: shape of factor should be defined" |
|
1082 | raise ValueError, "Reshaper: shape of factor should be defined" | |
| 1019 |
|
1083 | |||
| 1020 | if nTxs: |
|
1084 | if nTxs: | |
| 1021 | if nTxs < 0: |
|
1085 | if nTxs < 0: | |
| 1022 | raise ValueError, "nTxs should be greater than 0" |
|
1086 | raise ValueError, "nTxs should be greater than 0" | |
| 1023 |
|
1087 | |||
| 1024 | if nTxs < 1 and dataOut.nProfiles % (1./nTxs) != 0: |
|
1088 | if nTxs < 1 and dataOut.nProfiles % (1./nTxs) != 0: | |
| 1025 | raise ValueError, "nProfiles= %d is not divisibled by (1./nTxs) = %f" %(dataOut.nProfiles, (1./nTxs)) |
|
1089 | raise ValueError, "nProfiles= %d is not divisibled by (1./nTxs) = %f" %(dataOut.nProfiles, (1./nTxs)) | |
| 1026 |
|
1090 | |||
| 1027 | shape = [dataOut.nChannels, dataOut.nProfiles*nTxs, dataOut.nHeights/nTxs] |
|
1091 | shape = [dataOut.nChannels, dataOut.nProfiles*nTxs, dataOut.nHeights/nTxs] | |
| 1028 |
|
1092 | |||
| 1029 | return shape, nTxs |
|
1093 | return shape, nTxs | |
| 1030 |
|
1094 | |||
| 1031 | if len(shape) != 2 and len(shape) != 3: |
|
1095 | if len(shape) != 2 and len(shape) != 3: | |
| 1032 | raise ValueError, "shape dimension should be equal to 2 or 3. shape = (nProfiles, nHeis) or (nChannels, nProfiles, nHeis). Actually shape = (%d, %d, %d)" %(dataOut.nChannels, dataOut.nProfiles, dataOut.nHeights) |
|
1096 | raise ValueError, "shape dimension should be equal to 2 or 3. shape = (nProfiles, nHeis) or (nChannels, nProfiles, nHeis). Actually shape = (%d, %d, %d)" %(dataOut.nChannels, dataOut.nProfiles, dataOut.nHeights) | |
| 1033 |
|
1097 | |||
| 1034 | if len(shape) == 2: |
|
1098 | if len(shape) == 2: | |
| 1035 | shape_tuple = [dataOut.nChannels] |
|
1099 | shape_tuple = [dataOut.nChannels] | |
| 1036 | shape_tuple.extend(shape) |
|
1100 | shape_tuple.extend(shape) | |
| 1037 | else: |
|
1101 | else: | |
| 1038 | shape_tuple = list(shape) |
|
1102 | shape_tuple = list(shape) | |
| 1039 |
|
1103 | |||
| 1040 | nTxs = 1.0*shape_tuple[1]/dataOut.nProfiles |
|
1104 | nTxs = 1.0*shape_tuple[1]/dataOut.nProfiles | |
| 1041 |
|
1105 | |||
| 1042 | return shape_tuple, nTxs |
|
1106 | return shape_tuple, nTxs | |
| 1043 |
|
1107 | |||
| 1044 | def run(self, dataOut, shape=None, nTxs=None): |
|
1108 | def run(self, dataOut, shape=None, nTxs=None): | |
| 1045 |
|
1109 | |||
| 1046 | shape_tuple, self.__nTxs = self.__checkInputs(dataOut, shape, nTxs) |
|
1110 | shape_tuple, self.__nTxs = self.__checkInputs(dataOut, shape, nTxs) | |
| 1047 |
|
1111 | |||
| 1048 | dataOut.flagNoData = True |
|
1112 | dataOut.flagNoData = True | |
| 1049 | profileIndex = None |
|
1113 | profileIndex = None | |
| 1050 |
|
1114 | |||
| 1051 | if dataOut.flagDataAsBlock: |
|
1115 | if dataOut.flagDataAsBlock: | |
| 1052 |
|
1116 | |||
| 1053 | dataOut.data = numpy.reshape(dataOut.data, shape_tuple) |
|
1117 | dataOut.data = numpy.reshape(dataOut.data, shape_tuple) | |
| 1054 | dataOut.flagNoData = False |
|
1118 | dataOut.flagNoData = False | |
| 1055 |
|
1119 | |||
| 1056 | profileIndex = int(dataOut.nProfiles*self.__nTxs) - 1 |
|
1120 | profileIndex = int(dataOut.nProfiles*self.__nTxs) - 1 | |
| 1057 |
|
1121 | |||
| 1058 | else: |
|
1122 | else: | |
| 1059 |
|
1123 | |||
| 1060 | if self.__nTxs < 1: |
|
1124 | if self.__nTxs < 1: | |
| 1061 |
|
1125 | |||
| 1062 | self.__appendProfile(dataOut, self.__nTxs) |
|
1126 | self.__appendProfile(dataOut, self.__nTxs) | |
| 1063 | new_data = self.__getBuffer() |
|
1127 | new_data = self.__getBuffer() | |
| 1064 |
|
1128 | |||
| 1065 | if new_data is not None: |
|
1129 | if new_data is not None: | |
| 1066 | dataOut.data = new_data |
|
1130 | dataOut.data = new_data | |
| 1067 | dataOut.flagNoData = False |
|
1131 | dataOut.flagNoData = False | |
| 1068 |
|
1132 | |||
| 1069 | profileIndex = dataOut.profileIndex*nTxs |
|
1133 | profileIndex = dataOut.profileIndex*nTxs | |
| 1070 |
|
1134 | |||
| 1071 | else: |
|
1135 | else: | |
| 1072 | raise ValueError, "nTxs should be greater than 0 and lower than 1, or use VoltageReader(..., getblock=True)" |
|
1136 | raise ValueError, "nTxs should be greater than 0 and lower than 1, or use VoltageReader(..., getblock=True)" | |
| 1073 |
|
1137 | |||
| 1074 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1138 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1075 |
|
1139 | |||
| 1076 | dataOut.heightList = numpy.arange(dataOut.nHeights/self.__nTxs) * deltaHeight + dataOut.heightList[0] |
|
1140 | dataOut.heightList = numpy.arange(dataOut.nHeights/self.__nTxs) * deltaHeight + dataOut.heightList[0] | |
| 1077 |
|
1141 | |||
| 1078 | dataOut.nProfiles = int(dataOut.nProfiles*self.__nTxs) |
|
1142 | dataOut.nProfiles = int(dataOut.nProfiles*self.__nTxs) | |
| 1079 |
|
1143 | |||
| 1080 | dataOut.profileIndex = profileIndex |
|
1144 | dataOut.profileIndex = profileIndex | |
| 1081 |
|
1145 | |||
| 1082 | dataOut.ippSeconds /= self.__nTxs |
|
1146 | dataOut.ippSeconds /= self.__nTxs | |
| 1083 |
|
1147 | |||
| 1084 | class SplitProfiles(Operation): |
|
1148 | class SplitProfiles(Operation): | |
| 1085 |
|
1149 | |||
| 1086 | def __init__(self, **kwargs): |
|
1150 | def __init__(self, **kwargs): | |
| 1087 |
|
1151 | |||
| 1088 | Operation.__init__(self, **kwargs) |
|
1152 | Operation.__init__(self, **kwargs) | |
| 1089 |
|
1153 | |||
| 1090 | def run(self, dataOut, n): |
|
1154 | def run(self, dataOut, n): | |
| 1091 |
|
1155 | |||
| 1092 | dataOut.flagNoData = True |
|
1156 | dataOut.flagNoData = True | |
| 1093 | profileIndex = None |
|
1157 | profileIndex = None | |
| 1094 |
|
1158 | |||
| 1095 | if dataOut.flagDataAsBlock: |
|
1159 | if dataOut.flagDataAsBlock: | |
| 1096 |
|
1160 | |||
| 1097 | #nchannels, nprofiles, nsamples |
|
1161 | #nchannels, nprofiles, nsamples | |
| 1098 | shape = dataOut.data.shape |
|
1162 | shape = dataOut.data.shape | |
| 1099 |
|
1163 | |||
| 1100 | if shape[2] % n != 0: |
|
1164 | if shape[2] % n != 0: | |
| 1101 | raise ValueError, "Could not split the data, n=%d has to be multiple of %d" %(n, shape[2]) |
|
1165 | raise ValueError, "Could not split the data, n=%d has to be multiple of %d" %(n, shape[2]) | |
| 1102 |
|
1166 | |||
| 1103 | new_shape = shape[0], shape[1]*n, shape[2]/n |
|
1167 | new_shape = shape[0], shape[1]*n, shape[2]/n | |
| 1104 |
|
1168 | |||
| 1105 | dataOut.data = numpy.reshape(dataOut.data, new_shape) |
|
1169 | dataOut.data = numpy.reshape(dataOut.data, new_shape) | |
| 1106 | dataOut.flagNoData = False |
|
1170 | dataOut.flagNoData = False | |
| 1107 |
|
1171 | |||
| 1108 | profileIndex = int(dataOut.nProfiles/n) - 1 |
|
1172 | profileIndex = int(dataOut.nProfiles/n) - 1 | |
| 1109 |
|
1173 | |||
| 1110 | else: |
|
1174 | else: | |
| 1111 |
|
1175 | |||
| 1112 | raise ValueError, "Could not split the data when is read Profile by Profile. Use VoltageReader(..., getblock=True)" |
|
1176 | raise ValueError, "Could not split the data when is read Profile by Profile. Use VoltageReader(..., getblock=True)" | |
| 1113 |
|
1177 | |||
| 1114 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1178 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1115 |
|
1179 | |||
| 1116 | dataOut.heightList = numpy.arange(dataOut.nHeights/n) * deltaHeight + dataOut.heightList[0] |
|
1180 | dataOut.heightList = numpy.arange(dataOut.nHeights/n) * deltaHeight + dataOut.heightList[0] | |
| 1117 |
|
1181 | |||
| 1118 | dataOut.nProfiles = int(dataOut.nProfiles*n) |
|
1182 | dataOut.nProfiles = int(dataOut.nProfiles*n) | |
| 1119 |
|
1183 | |||
| 1120 | dataOut.profileIndex = profileIndex |
|
1184 | dataOut.profileIndex = profileIndex | |
| 1121 |
|
1185 | |||
| 1122 | dataOut.ippSeconds /= n |
|
1186 | dataOut.ippSeconds /= n | |
| 1123 |
|
1187 | |||
| 1124 | class CombineProfiles(Operation): |
|
1188 | class CombineProfiles(Operation): | |
| 1125 |
|
1189 | |||
| 1126 | def __init__(self, **kwargs): |
|
1190 | def __init__(self, **kwargs): | |
| 1127 |
|
1191 | |||
| 1128 | Operation.__init__(self, **kwargs) |
|
1192 | Operation.__init__(self, **kwargs) | |
| 1129 |
|
1193 | |||
| 1130 | self.__remData = None |
|
1194 | self.__remData = None | |
| 1131 | self.__profileIndex = 0 |
|
1195 | self.__profileIndex = 0 | |
| 1132 |
|
1196 | |||
| 1133 | def run(self, dataOut, n): |
|
1197 | def run(self, dataOut, n): | |
| 1134 |
|
1198 | |||
| 1135 | dataOut.flagNoData = True |
|
1199 | dataOut.flagNoData = True | |
| 1136 | profileIndex = None |
|
1200 | profileIndex = None | |
| 1137 |
|
1201 | |||
| 1138 | if dataOut.flagDataAsBlock: |
|
1202 | if dataOut.flagDataAsBlock: | |
| 1139 |
|
1203 | |||
| 1140 | #nchannels, nprofiles, nsamples |
|
1204 | #nchannels, nprofiles, nsamples | |
| 1141 | shape = dataOut.data.shape |
|
1205 | shape = dataOut.data.shape | |
| 1142 | new_shape = shape[0], shape[1]/n, shape[2]*n |
|
1206 | new_shape = shape[0], shape[1]/n, shape[2]*n | |
| 1143 |
|
1207 | |||
| 1144 | if shape[1] % n != 0: |
|
1208 | if shape[1] % n != 0: | |
| 1145 | raise ValueError, "Could not split the data, n=%d has to be multiple of %d" %(n, shape[1]) |
|
1209 | raise ValueError, "Could not split the data, n=%d has to be multiple of %d" %(n, shape[1]) | |
| 1146 |
|
1210 | |||
| 1147 | dataOut.data = numpy.reshape(dataOut.data, new_shape) |
|
1211 | dataOut.data = numpy.reshape(dataOut.data, new_shape) | |
| 1148 | dataOut.flagNoData = False |
|
1212 | dataOut.flagNoData = False | |
| 1149 |
|
1213 | |||
| 1150 | profileIndex = int(dataOut.nProfiles*n) - 1 |
|
1214 | profileIndex = int(dataOut.nProfiles*n) - 1 | |
| 1151 |
|
1215 | |||
| 1152 | else: |
|
1216 | else: | |
| 1153 |
|
1217 | |||
| 1154 | #nchannels, nsamples |
|
1218 | #nchannels, nsamples | |
| 1155 | if self.__remData is None: |
|
1219 | if self.__remData is None: | |
| 1156 | newData = dataOut.data |
|
1220 | newData = dataOut.data | |
| 1157 | else: |
|
1221 | else: | |
| 1158 | newData = numpy.concatenate((self.__remData, dataOut.data), axis=1) |
|
1222 | newData = numpy.concatenate((self.__remData, dataOut.data), axis=1) | |
| 1159 |
|
1223 | |||
| 1160 | self.__profileIndex += 1 |
|
1224 | self.__profileIndex += 1 | |
| 1161 |
|
1225 | |||
| 1162 | if self.__profileIndex < n: |
|
1226 | if self.__profileIndex < n: | |
| 1163 | self.__remData = newData |
|
1227 | self.__remData = newData | |
| 1164 | #continue |
|
1228 | #continue | |
| 1165 | return |
|
1229 | return | |
| 1166 |
|
1230 | |||
| 1167 | self.__profileIndex = 0 |
|
1231 | self.__profileIndex = 0 | |
| 1168 | self.__remData = None |
|
1232 | self.__remData = None | |
| 1169 |
|
1233 | |||
| 1170 | dataOut.data = newData |
|
1234 | dataOut.data = newData | |
| 1171 | dataOut.flagNoData = False |
|
1235 | dataOut.flagNoData = False | |
| 1172 |
|
1236 | |||
| 1173 | profileIndex = dataOut.profileIndex/n |
|
1237 | profileIndex = dataOut.profileIndex/n | |
| 1174 |
|
1238 | |||
| 1175 |
|
1239 | |||
| 1176 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1240 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1177 |
|
1241 | |||
| 1178 | dataOut.heightList = numpy.arange(dataOut.nHeights*n) * deltaHeight + dataOut.heightList[0] |
|
1242 | dataOut.heightList = numpy.arange(dataOut.nHeights*n) * deltaHeight + dataOut.heightList[0] | |
| 1179 |
|
1243 | |||
| 1180 | dataOut.nProfiles = int(dataOut.nProfiles/n) |
|
1244 | dataOut.nProfiles = int(dataOut.nProfiles/n) | |
| 1181 |
|
1245 | |||
| 1182 | dataOut.profileIndex = profileIndex |
|
1246 | dataOut.profileIndex = profileIndex | |
| 1183 |
|
1247 | |||
| 1184 | dataOut.ippSeconds *= n |
|
1248 | dataOut.ippSeconds *= n | |
| 1185 |
|
1249 | |||
| 1186 |
|
1250 | |||
| 1187 | class SSheightProfiles(Operation): |
|
1251 | class SSheightProfiles(Operation): | |
| 1188 |
|
1252 | |||
| 1189 | step = None |
|
1253 | step = None | |
| 1190 | nsamples = None |
|
1254 | nsamples = None | |
| 1191 | bufferShape = None |
|
1255 | bufferShape = None | |
| 1192 | profileShape = None |
|
1256 | profileShape = None | |
| 1193 | sshProfiles = None |
|
1257 | sshProfiles = None | |
| 1194 | profileIndex = None |
|
1258 | profileIndex = None | |
| 1195 |
|
1259 | |||
| 1196 | def __init__(self, **kwargs): |
|
1260 | def __init__(self, **kwargs): | |
| 1197 |
|
1261 | |||
| 1198 | Operation.__init__(self, **kwargs) |
|
1262 | Operation.__init__(self, **kwargs) | |
| 1199 | self.isConfig = False |
|
1263 | self.isConfig = False | |
| 1200 |
|
1264 | |||
| 1201 | def setup(self,dataOut ,step = None , nsamples = None): |
|
1265 | def setup(self,dataOut ,step = None , nsamples = None): | |
| 1202 |
|
1266 | |||
| 1203 | if step == None and nsamples == None: |
|
1267 | if step == None and nsamples == None: | |
| 1204 | raise ValueError, "step or nheights should be specified ..." |
|
1268 | raise ValueError, "step or nheights should be specified ..." | |
| 1205 |
|
1269 | |||
| 1206 | self.step = step |
|
1270 | self.step = step | |
| 1207 | self.nsamples = nsamples |
|
1271 | self.nsamples = nsamples | |
| 1208 | self.__nChannels = dataOut.nChannels |
|
1272 | self.__nChannels = dataOut.nChannels | |
| 1209 | self.__nProfiles = dataOut.nProfiles |
|
1273 | self.__nProfiles = dataOut.nProfiles | |
| 1210 | self.__nHeis = dataOut.nHeights |
|
1274 | self.__nHeis = dataOut.nHeights | |
| 1211 | shape = dataOut.data.shape #nchannels, nprofiles, nsamples |
|
1275 | shape = dataOut.data.shape #nchannels, nprofiles, nsamples | |
| 1212 |
|
1276 | |||
| 1213 |
|
1277 | |||
| 1214 | residue = (shape[1] - self.nsamples) % self.step |
|
1278 | residue = (shape[1] - self.nsamples) % self.step | |
| 1215 | if residue != 0: |
|
1279 | if residue != 0: | |
| 1216 | print "The residue is %d, step=%d should be multiple of %d to avoid loss of %d samples"%(residue,step,shape[1] - self.nsamples,residue) |
|
1280 | print "The residue is %d, step=%d should be multiple of %d to avoid loss of %d samples"%(residue,step,shape[1] - self.nsamples,residue) | |
| 1217 |
|
1281 | |||
| 1218 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1282 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1219 | numberProfile = self.nsamples |
|
1283 | numberProfile = self.nsamples | |
| 1220 | numberSamples = (shape[1] - self.nsamples)/self.step |
|
1284 | numberSamples = (shape[1] - self.nsamples)/self.step | |
| 1221 |
|
1285 | |||
| 1222 | print "New number of profile: %d, number of height: %d, Resolution %d Km"%(numberProfile,numberSamples,deltaHeight*self.step) |
|
1286 | print "New number of profile: %d, number of height: %d, Resolution %d Km"%(numberProfile,numberSamples,deltaHeight*self.step) | |
| 1223 |
|
1287 | |||
| 1224 | self.bufferShape = shape[0], numberSamples, numberProfile # nchannels, nsamples , nprofiles |
|
1288 | self.bufferShape = shape[0], numberSamples, numberProfile # nchannels, nsamples , nprofiles | |
| 1225 | self.profileShape = shape[0], numberProfile, numberSamples # nchannels, nprofiles, nsamples |
|
1289 | self.profileShape = shape[0], numberProfile, numberSamples # nchannels, nprofiles, nsamples | |
| 1226 |
|
1290 | |||
| 1227 | self.buffer = numpy.zeros(self.bufferShape , dtype=numpy.complex) |
|
1291 | self.buffer = numpy.zeros(self.bufferShape , dtype=numpy.complex) | |
| 1228 | self.sshProfiles = numpy.zeros(self.profileShape, dtype=numpy.complex) |
|
1292 | self.sshProfiles = numpy.zeros(self.profileShape, dtype=numpy.complex) | |
| 1229 |
|
1293 | |||
| 1230 | def run(self, dataOut, step, nsamples): |
|
1294 | def run(self, dataOut, step, nsamples): | |
| 1231 |
|
1295 | |||
| 1232 | dataOut.flagNoData = True |
|
1296 | dataOut.flagNoData = True | |
| 1233 | dataOut.flagDataAsBlock = False |
|
1297 | dataOut.flagDataAsBlock = False | |
| 1234 | profileIndex = None |
|
1298 | profileIndex = None | |
| 1235 |
|
1299 | |||
| 1236 | if not self.isConfig: |
|
1300 | if not self.isConfig: | |
| 1237 | self.setup(dataOut, step=step , nsamples=nsamples) |
|
1301 | self.setup(dataOut, step=step , nsamples=nsamples) | |
| 1238 | self.isConfig = True |
|
1302 | self.isConfig = True | |
| 1239 |
|
1303 | |||
| 1240 | for i in range(self.buffer.shape[1]): |
|
1304 | for i in range(self.buffer.shape[1]): | |
| 1241 | self.buffer[:,i] = numpy.flip(dataOut.data[:,i*self.step:i*self.step + self.nsamples]) |
|
1305 | self.buffer[:,i] = numpy.flip(dataOut.data[:,i*self.step:i*self.step + self.nsamples]) | |
| 1242 | #self.buffer[:,j,self.__nHeis-j*self.step - self.nheights:self.__nHeis-j*self.step] = numpy.flip(dataOut.data[:,j*self.step:j*self.step + self.nheights]) |
|
1306 | #self.buffer[:,j,self.__nHeis-j*self.step - self.nheights:self.__nHeis-j*self.step] = numpy.flip(dataOut.data[:,j*self.step:j*self.step + self.nheights]) | |
| 1243 |
|
1307 | |||
| 1244 | for j in range(self.buffer.shape[0]): |
|
1308 | for j in range(self.buffer.shape[0]): | |
| 1245 | self.sshProfiles[j] = numpy.transpose(self.buffer[j]) |
|
1309 | self.sshProfiles[j] = numpy.transpose(self.buffer[j]) | |
| 1246 |
|
1310 | |||
| 1247 | profileIndex = self.nsamples |
|
1311 | profileIndex = self.nsamples | |
| 1248 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1312 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1249 | ippSeconds = (deltaHeight*1.0e-6)/(0.15) |
|
1313 | ippSeconds = (deltaHeight*1.0e-6)/(0.15) | |
| 1250 |
|
1314 | |||
| 1251 | dataOut.data = self.sshProfiles |
|
1315 | dataOut.data = self.sshProfiles | |
| 1252 | dataOut.flagNoData = False |
|
1316 | dataOut.flagNoData = False | |
| 1253 | dataOut.heightList = numpy.arange(self.buffer.shape[1]) *self.step*deltaHeight + dataOut.heightList[0] |
|
1317 | dataOut.heightList = numpy.arange(self.buffer.shape[1]) *self.step*deltaHeight + dataOut.heightList[0] | |
| 1254 | dataOut.nProfiles = int(dataOut.nProfiles*self.nsamples) |
|
1318 | dataOut.nProfiles = int(dataOut.nProfiles*self.nsamples) | |
| 1255 | dataOut.profileIndex = profileIndex |
|
1319 | dataOut.profileIndex = profileIndex | |
| 1256 | dataOut.flagDataAsBlock = True |
|
1320 | dataOut.flagDataAsBlock = True | |
| 1257 | dataOut.ippSeconds = ippSeconds |
|
1321 | dataOut.ippSeconds = ippSeconds | |
| 1258 | dataOut.step = self.step |
|
1322 | dataOut.step = self.step | |
| 1259 |
|
1323 | |||
| 1260 |
|
1324 | |||
|
|
1325 | import time | |||
|
|
1326 | ################################################# | |||
|
|
1327 | ||||
|
|
1328 | class decoPseudorandom(Operation): | |||
|
|
1329 | ||||
|
|
1330 | nProfiles= 0 | |||
|
|
1331 | buffer= None | |||
|
|
1332 | isConfig = False | |||
|
|
1333 | ||||
|
|
1334 | def setup(self, clen= 10000,seed= 0,Nranges= 1000,oversample=1): | |||
|
|
1335 | #code = create_pseudo_random_code(clen=clen, seed=seed) | |||
|
|
1336 | code= rep_seq(create_pseudo_random_code(clen=clen, seed=seed),rep=oversample) | |||
|
|
1337 | #print ("code_rx", code.shape) | |||
|
|
1338 | #N = int(an_len/clen) # 100 | |||
|
|
1339 | B_cache = 0 | |||
|
|
1340 | r_cache = 0 | |||
|
|
1341 | B_cached = False | |||
|
|
1342 | r = create_estimation_matrix(code=code, cache=True, rmax=Nranges) | |||
|
|
1343 | #print ("code shape", code.shape) | |||
|
|
1344 | #print ("seed",seed) | |||
|
|
1345 | #print ("Code", code[0:10]) | |||
|
|
1346 | self.B = r['B'] | |||
|
|
1347 | ||||
|
|
1348 | ||||
|
|
1349 | def run (self,dataOut,length_code= 10000,seed= 0,Nranges= 1000,oversample=1): | |||
|
|
1350 | #print((dataOut.data.shape)) | |||
|
|
1351 | if not self.isConfig: | |||
|
|
1352 | self.setup(clen= length_code,seed= seed,Nranges= Nranges,oversample=oversample) | |||
|
|
1353 | self.isConfig = True | |||
|
|
1354 | ||||
|
|
1355 | dataOut.flagNoData = True | |||
|
|
1356 | data =dataOut.data | |||
|
|
1357 | #print "length_CODE",length_code | |||
|
|
1358 | data_shape = (data.shape[1]) | |||
|
|
1359 | #print "data_shape",data_shape | |||
|
|
1360 | n = (length_code /data_shape) | |||
|
|
1361 | #print "we need this number of sample",n | |||
|
|
1362 | ||||
|
|
1363 | if n>0 and self.buffer is None: | |||
|
|
1364 | self.buffer = numpy.zeros([1, length_code], dtype=numpy.complex64) | |||
|
|
1365 | self.buffer[0][0:data_shape] = data[0] | |||
|
|
1366 | #print "FIRST CREATION",self.buffer.shape | |||
|
|
1367 | ||||
|
|
1368 | else: | |||
|
|
1369 | self.buffer[0][self.nProfiles*data_shape:(self.nProfiles+1)*data_shape]=data[0] | |||
|
|
1370 | ||||
|
|
1371 | #print "buffer_shape",(self.buffer.shape) | |||
|
|
1372 | self.nProfiles += 1 | |||
|
|
1373 | #print "count",self.nProfiles | |||
|
|
1374 | ||||
|
|
1375 | if self.nProfiles== n: | |||
|
|
1376 | temporal = numpy.dot(self.B, numpy.transpose(self.buffer)) | |||
|
|
1377 | #print temporal.shape | |||
|
|
1378 | #import time | |||
|
|
1379 | #time.sleep(40) | |||
|
|
1380 | dataOut.data=numpy.transpose(temporal) | |||
|
|
1381 | ||||
|
|
1382 | dataOut.flagNoData = False | |||
|
|
1383 | self.buffer= None | |||
|
|
1384 | self.nProfiles = 0 | |||
|
|
1385 | ||||
| 1261 | # import collections |
|
1386 | # import collections | |
| 1262 | # from scipy.stats import mode |
|
1387 | # from scipy.stats import mode | |
| 1263 | # |
|
1388 | # | |
| 1264 | # class Synchronize(Operation): |
|
1389 | # class Synchronize(Operation): | |
| 1265 | # |
|
1390 | # | |
| 1266 | # isConfig = False |
|
1391 | # isConfig = False | |
| 1267 | # __profIndex = 0 |
|
1392 | # __profIndex = 0 | |
| 1268 | # |
|
1393 | # | |
| 1269 | # def __init__(self, **kwargs): |
|
1394 | # def __init__(self, **kwargs): | |
| 1270 | # |
|
1395 | # | |
| 1271 | # Operation.__init__(self, **kwargs) |
|
1396 | # Operation.__init__(self, **kwargs) | |
| 1272 | # # self.isConfig = False |
|
1397 | # # self.isConfig = False | |
| 1273 | # self.__powBuffer = None |
|
1398 | # self.__powBuffer = None | |
| 1274 | # self.__startIndex = 0 |
|
1399 | # self.__startIndex = 0 | |
| 1275 | # self.__pulseFound = False |
|
1400 | # self.__pulseFound = False | |
| 1276 | # |
|
1401 | # | |
| 1277 | # def __findTxPulse(self, dataOut, channel=0, pulse_with = None): |
|
1402 | # def __findTxPulse(self, dataOut, channel=0, pulse_with = None): | |
| 1278 | # |
|
1403 | # | |
| 1279 | # #Read data |
|
1404 | # #Read data | |
| 1280 | # |
|
1405 | # | |
| 1281 | # powerdB = dataOut.getPower(channel = channel) |
|
1406 | # powerdB = dataOut.getPower(channel = channel) | |
| 1282 | # noisedB = dataOut.getNoise(channel = channel)[0] |
|
1407 | # noisedB = dataOut.getNoise(channel = channel)[0] | |
| 1283 | # |
|
1408 | # | |
| 1284 | # self.__powBuffer.extend(powerdB.flatten()) |
|
1409 | # self.__powBuffer.extend(powerdB.flatten()) | |
| 1285 | # |
|
1410 | # | |
| 1286 | # dataArray = numpy.array(self.__powBuffer) |
|
1411 | # dataArray = numpy.array(self.__powBuffer) | |
| 1287 | # |
|
1412 | # | |
| 1288 | # filteredPower = numpy.correlate(dataArray, dataArray[0:self.__nSamples], "same") |
|
1413 | # filteredPower = numpy.correlate(dataArray, dataArray[0:self.__nSamples], "same") | |
| 1289 | # |
|
1414 | # | |
| 1290 | # maxValue = numpy.nanmax(filteredPower) |
|
1415 | # maxValue = numpy.nanmax(filteredPower) | |
| 1291 | # |
|
1416 | # | |
| 1292 | # if maxValue < noisedB + 10: |
|
1417 | # if maxValue < noisedB + 10: | |
| 1293 | # #No se encuentra ningun pulso de transmision |
|
1418 | # #No se encuentra ningun pulso de transmision | |
| 1294 | # return None |
|
1419 | # return None | |
| 1295 | # |
|
1420 | # | |
| 1296 | # maxValuesIndex = numpy.where(filteredPower > maxValue - 0.1*abs(maxValue))[0] |
|
1421 | # maxValuesIndex = numpy.where(filteredPower > maxValue - 0.1*abs(maxValue))[0] | |
| 1297 | # |
|
1422 | # | |
| 1298 | # if len(maxValuesIndex) < 2: |
|
1423 | # if len(maxValuesIndex) < 2: | |
| 1299 | # #Solo se encontro un solo pulso de transmision de un baudio, esperando por el siguiente TX |
|
1424 | # #Solo se encontro un solo pulso de transmision de un baudio, esperando por el siguiente TX | |
| 1300 | # return None |
|
1425 | # return None | |
| 1301 | # |
|
1426 | # | |
| 1302 | # phasedMaxValuesIndex = maxValuesIndex - self.__nSamples |
|
1427 | # phasedMaxValuesIndex = maxValuesIndex - self.__nSamples | |
| 1303 | # |
|
1428 | # | |
| 1304 | # #Seleccionar solo valores con un espaciamiento de nSamples |
|
1429 | # #Seleccionar solo valores con un espaciamiento de nSamples | |
| 1305 | # pulseIndex = numpy.intersect1d(maxValuesIndex, phasedMaxValuesIndex) |
|
1430 | # pulseIndex = numpy.intersect1d(maxValuesIndex, phasedMaxValuesIndex) | |
| 1306 | # |
|
1431 | # | |
| 1307 | # if len(pulseIndex) < 2: |
|
1432 | # if len(pulseIndex) < 2: | |
| 1308 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 |
|
1433 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 | |
| 1309 | # return None |
|
1434 | # return None | |
| 1310 | # |
|
1435 | # | |
| 1311 | # spacing = pulseIndex[1:] - pulseIndex[:-1] |
|
1436 | # spacing = pulseIndex[1:] - pulseIndex[:-1] | |
| 1312 | # |
|
1437 | # | |
| 1313 | # #remover senales que se distancien menos de 10 unidades o muestras |
|
1438 | # #remover senales que se distancien menos de 10 unidades o muestras | |
| 1314 | # #(No deberian existir IPP menor a 10 unidades) |
|
1439 | # #(No deberian existir IPP menor a 10 unidades) | |
| 1315 | # |
|
1440 | # | |
| 1316 | # realIndex = numpy.where(spacing > 10 )[0] |
|
1441 | # realIndex = numpy.where(spacing > 10 )[0] | |
| 1317 | # |
|
1442 | # | |
| 1318 | # if len(realIndex) < 2: |
|
1443 | # if len(realIndex) < 2: | |
| 1319 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 |
|
1444 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 | |
| 1320 | # return None |
|
1445 | # return None | |
| 1321 | # |
|
1446 | # | |
| 1322 | # #Eliminar pulsos anchos (deja solo la diferencia entre IPPs) |
|
1447 | # #Eliminar pulsos anchos (deja solo la diferencia entre IPPs) | |
| 1323 | # realPulseIndex = pulseIndex[realIndex] |
|
1448 | # realPulseIndex = pulseIndex[realIndex] | |
| 1324 | # |
|
1449 | # | |
| 1325 | # period = mode(realPulseIndex[1:] - realPulseIndex[:-1])[0][0] |
|
1450 | # period = mode(realPulseIndex[1:] - realPulseIndex[:-1])[0][0] | |
| 1326 | # |
|
1451 | # | |
| 1327 | # print "IPP = %d samples" %period |
|
1452 | # print "IPP = %d samples" %period | |
| 1328 | # |
|
1453 | # | |
| 1329 | # self.__newNSamples = dataOut.nHeights #int(period) |
|
1454 | # self.__newNSamples = dataOut.nHeights #int(period) | |
| 1330 | # self.__startIndex = int(realPulseIndex[0]) |
|
1455 | # self.__startIndex = int(realPulseIndex[0]) | |
| 1331 | # |
|
1456 | # | |
| 1332 | # return 1 |
|
1457 | # return 1 | |
| 1333 | # |
|
1458 | # | |
| 1334 | # |
|
1459 | # | |
| 1335 | # def setup(self, nSamples, nChannels, buffer_size = 4): |
|
1460 | # def setup(self, nSamples, nChannels, buffer_size = 4): | |
| 1336 | # |
|
1461 | # | |
| 1337 | # self.__powBuffer = collections.deque(numpy.zeros( buffer_size*nSamples,dtype=numpy.float), |
|
1462 | # self.__powBuffer = collections.deque(numpy.zeros( buffer_size*nSamples,dtype=numpy.float), | |
| 1338 | # maxlen = buffer_size*nSamples) |
|
1463 | # maxlen = buffer_size*nSamples) | |
| 1339 | # |
|
1464 | # | |
| 1340 | # bufferList = [] |
|
1465 | # bufferList = [] | |
| 1341 | # |
|
1466 | # | |
| 1342 | # for i in range(nChannels): |
|
1467 | # for i in range(nChannels): | |
| 1343 | # bufferByChannel = collections.deque(numpy.zeros( buffer_size*nSamples, dtype=numpy.complex) + numpy.NAN, |
|
1468 | # bufferByChannel = collections.deque(numpy.zeros( buffer_size*nSamples, dtype=numpy.complex) + numpy.NAN, | |
| 1344 | # maxlen = buffer_size*nSamples) |
|
1469 | # maxlen = buffer_size*nSamples) | |
| 1345 | # |
|
1470 | # | |
| 1346 | # bufferList.append(bufferByChannel) |
|
1471 | # bufferList.append(bufferByChannel) | |
| 1347 | # |
|
1472 | # | |
| 1348 | # self.__nSamples = nSamples |
|
1473 | # self.__nSamples = nSamples | |
| 1349 | # self.__nChannels = nChannels |
|
1474 | # self.__nChannels = nChannels | |
| 1350 | # self.__bufferList = bufferList |
|
1475 | # self.__bufferList = bufferList | |
| 1351 | # |
|
1476 | # | |
| 1352 | # def run(self, dataOut, channel = 0): |
|
1477 | # def run(self, dataOut, channel = 0): | |
| 1353 | # |
|
1478 | # | |
| 1354 | # if not self.isConfig: |
|
1479 | # if not self.isConfig: | |
| 1355 | # nSamples = dataOut.nHeights |
|
1480 | # nSamples = dataOut.nHeights | |
| 1356 | # nChannels = dataOut.nChannels |
|
1481 | # nChannels = dataOut.nChannels | |
| 1357 | # self.setup(nSamples, nChannels) |
|
1482 | # self.setup(nSamples, nChannels) | |
| 1358 | # self.isConfig = True |
|
1483 | # self.isConfig = True | |
| 1359 | # |
|
1484 | # | |
| 1360 | # #Append new data to internal buffer |
|
1485 | # #Append new data to internal buffer | |
| 1361 | # for thisChannel in range(self.__nChannels): |
|
1486 | # for thisChannel in range(self.__nChannels): | |
| 1362 | # bufferByChannel = self.__bufferList[thisChannel] |
|
1487 | # bufferByChannel = self.__bufferList[thisChannel] | |
| 1363 | # bufferByChannel.extend(dataOut.data[thisChannel]) |
|
1488 | # bufferByChannel.extend(dataOut.data[thisChannel]) | |
| 1364 | # |
|
1489 | # | |
| 1365 | # if self.__pulseFound: |
|
1490 | # if self.__pulseFound: | |
| 1366 | # self.__startIndex -= self.__nSamples |
|
1491 | # self.__startIndex -= self.__nSamples | |
| 1367 | # |
|
1492 | # | |
| 1368 | # #Finding Tx Pulse |
|
1493 | # #Finding Tx Pulse | |
| 1369 | # if not self.__pulseFound: |
|
1494 | # if not self.__pulseFound: | |
| 1370 | # indexFound = self.__findTxPulse(dataOut, channel) |
|
1495 | # indexFound = self.__findTxPulse(dataOut, channel) | |
| 1371 | # |
|
1496 | # | |
| 1372 | # if indexFound == None: |
|
1497 | # if indexFound == None: | |
| 1373 | # dataOut.flagNoData = True |
|
1498 | # dataOut.flagNoData = True | |
| 1374 | # return |
|
1499 | # return | |
| 1375 | # |
|
1500 | # | |
| 1376 | # self.__arrayBuffer = numpy.zeros((self.__nChannels, self.__newNSamples), dtype = numpy.complex) |
|
1501 | # self.__arrayBuffer = numpy.zeros((self.__nChannels, self.__newNSamples), dtype = numpy.complex) | |
| 1377 | # self.__pulseFound = True |
|
1502 | # self.__pulseFound = True | |
| 1378 | # self.__startIndex = indexFound |
|
1503 | # self.__startIndex = indexFound | |
| 1379 | # |
|
1504 | # | |
| 1380 | # #If pulse was found ... |
|
1505 | # #If pulse was found ... | |
| 1381 | # for thisChannel in range(self.__nChannels): |
|
1506 | # for thisChannel in range(self.__nChannels): | |
| 1382 | # bufferByChannel = self.__bufferList[thisChannel] |
|
1507 | # bufferByChannel = self.__bufferList[thisChannel] | |
| 1383 | # #print self.__startIndex |
|
1508 | # #print self.__startIndex | |
| 1384 | # x = numpy.array(bufferByChannel) |
|
1509 | # x = numpy.array(bufferByChannel) | |
| 1385 | # self.__arrayBuffer[thisChannel] = x[self.__startIndex:self.__startIndex+self.__newNSamples] |
|
1510 | # self.__arrayBuffer[thisChannel] = x[self.__startIndex:self.__startIndex+self.__newNSamples] | |
| 1386 | # |
|
1511 | # | |
| 1387 | # deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1512 | # deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1388 | # dataOut.heightList = numpy.arange(self.__newNSamples)*deltaHeight |
|
1513 | # dataOut.heightList = numpy.arange(self.__newNSamples)*deltaHeight | |
| 1389 | # # dataOut.ippSeconds = (self.__newNSamples / deltaHeight)/1e6 |
|
1514 | # # dataOut.ippSeconds = (self.__newNSamples / deltaHeight)/1e6 | |
| 1390 | # |
|
1515 | # | |
| 1391 | # dataOut.data = self.__arrayBuffer |
|
1516 | # dataOut.data = self.__arrayBuffer | |
| 1392 | # |
|
1517 | # | |
| 1393 | # self.__startIndex += self.__newNSamples |
|
1518 | # self.__startIndex += self.__newNSamples | |
| 1394 | # |
|
1519 | # | |
| 1395 | # return |
|
1520 | # return | |
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