| @@ -1,426 +1,400 | |||||
| 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 |
|
10 | from figure import Figure | |
| 11 | from plotting_codes import * |
|
11 | from plotting_codes import * | |
| 12 |
|
12 | |||
| 13 | class Scope(Figure): |
|
13 | class Scope(Figure): | |
| 14 |
|
14 | |||
| 15 | isConfig = None |
|
15 | isConfig = None | |
| 16 |
|
16 | |||
| 17 | def __init__(self, **kwargs): |
|
17 | def __init__(self, **kwargs): | |
| 18 | Figure.__init__(self, **kwargs) |
|
18 | Figure.__init__(self, **kwargs) | |
| 19 | self.isConfig = False |
|
19 | self.isConfig = False | |
| 20 | self.WIDTH = 300 |
|
20 | self.WIDTH = 300 | |
| 21 | self.HEIGHT = 200 |
|
21 | self.HEIGHT = 200 | |
| 22 | self.counter_imagwr = 0 |
|
22 | self.counter_imagwr = 0 | |
| 23 |
|
23 | |||
| 24 | def getSubplots(self): |
|
24 | def getSubplots(self): | |
| 25 |
|
25 | |||
| 26 | nrow = self.nplots |
|
26 | nrow = self.nplots | |
| 27 | ncol = 3 |
|
27 | ncol = 3 | |
| 28 | return nrow, ncol |
|
28 | return nrow, ncol | |
| 29 |
|
29 | |||
| 30 | def setup(self, id, nplots, wintitle, show): |
|
30 | def setup(self, id, nplots, wintitle, show): | |
| 31 |
|
31 | |||
| 32 | self.nplots = nplots |
|
32 | self.nplots = nplots | |
| 33 |
|
33 | |||
| 34 |
self.createFigure(id=id, |
|
34 | self.createFigure(id=id, | |
| 35 |
wintitle=wintitle, |
|
35 | wintitle=wintitle, | |
| 36 | show=show) |
|
36 | show=show) | |
| 37 |
|
37 | |||
| 38 | nrow,ncol = self.getSubplots() |
|
38 | nrow,ncol = self.getSubplots() | |
| 39 | colspan = 3 |
|
39 | colspan = 3 | |
| 40 | rowspan = 1 |
|
40 | rowspan = 1 | |
| 41 |
|
41 | |||
| 42 | for i in range(nplots): |
|
42 | for i in range(nplots): | |
| 43 | self.addAxes(nrow, ncol, i, 0, colspan, rowspan) |
|
43 | self.addAxes(nrow, ncol, i, 0, colspan, rowspan) | |
| 44 |
|
44 | |||
| 45 | def plot_iq(self, x, y, id, channelIndexList, thisDatetime, wintitle, show, xmin, xmax, ymin, ymax): |
|
45 | def plot_iq(self, x, y, id, channelIndexList, thisDatetime, wintitle, show, xmin, xmax, ymin, ymax): | |
| 46 | yreal = y[channelIndexList,:].real |
|
46 | yreal = y[channelIndexList,:].real | |
| 47 | yimag = y[channelIndexList,:].imag |
|
47 | yimag = y[channelIndexList,:].imag | |
| 48 |
|
48 | |||
| 49 | title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
49 | title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
| 50 | xlabel = "Range (Km)" |
|
50 | xlabel = "Range (Km)" | |
| 51 | ylabel = "Intensity - IQ" |
|
51 | ylabel = "Intensity - IQ" | |
| 52 |
|
52 | |||
| 53 | if not self.isConfig: |
|
53 | if not self.isConfig: | |
| 54 | nplots = len(channelIndexList) |
|
54 | nplots = len(channelIndexList) | |
| 55 |
|
55 | |||
| 56 | self.setup(id=id, |
|
56 | self.setup(id=id, | |
| 57 | nplots=nplots, |
|
57 | nplots=nplots, | |
| 58 | wintitle='', |
|
58 | wintitle='', | |
| 59 | show=show) |
|
59 | show=show) | |
| 60 |
|
60 | |||
| 61 | if xmin == None: xmin = numpy.nanmin(x) |
|
61 | if xmin == None: xmin = numpy.nanmin(x) | |
| 62 | if xmax == None: xmax = numpy.nanmax(x) |
|
62 | if xmax == None: xmax = numpy.nanmax(x) | |
| 63 | if ymin == None: ymin = min(numpy.nanmin(yreal),numpy.nanmin(yimag)) |
|
63 | if ymin == None: ymin = min(numpy.nanmin(yreal),numpy.nanmin(yimag)) | |
| 64 | if ymax == None: ymax = max(numpy.nanmax(yreal),numpy.nanmax(yimag)) |
|
64 | if ymax == None: ymax = max(numpy.nanmax(yreal),numpy.nanmax(yimag)) | |
| 65 |
|
65 | |||
| 66 | self.isConfig = True |
|
66 | self.isConfig = True | |
| 67 |
|
67 | |||
| 68 | self.setWinTitle(title) |
|
68 | self.setWinTitle(title) | |
| 69 |
|
69 | |||
| 70 | for i in range(len(self.axesList)): |
|
70 | for i in range(len(self.axesList)): | |
| 71 | title = "Channel %d" %(i) |
|
71 | title = "Channel %d" %(i) | |
| 72 | axes = self.axesList[i] |
|
72 | axes = self.axesList[i] | |
| 73 |
|
73 | |||
| 74 | axes.pline(x, yreal[i,:], |
|
74 | axes.pline(x, yreal[i,:], | |
| 75 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, |
|
75 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, | |
| 76 | xlabel=xlabel, ylabel=ylabel, title=title) |
|
76 | xlabel=xlabel, ylabel=ylabel, title=title) | |
| 77 |
|
77 | |||
| 78 | axes.addpline(x, yimag[i,:], idline=1, color="red", linestyle="solid", lw=2) |
|
78 | axes.addpline(x, yimag[i,:], idline=1, color="red", linestyle="solid", lw=2) | |
| 79 |
|
79 | |||
| 80 | def plot_power(self, x, y, id, channelIndexList, thisDatetime, wintitle, show, xmin, xmax, ymin, ymax): |
|
80 | def plot_power(self, x, y, id, channelIndexList, thisDatetime, wintitle, show, xmin, xmax, ymin, ymax): | |
| 81 | y = y[channelIndexList,:] * numpy.conjugate(y[channelIndexList,:]) |
|
81 | y = y[channelIndexList,:] * numpy.conjugate(y[channelIndexList,:]) | |
| 82 | yreal = y.real |
|
82 | yreal = y.real | |
| 83 |
|
83 | |||
| 84 | title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
84 | title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
| 85 | xlabel = "Range (Km)" |
|
85 | xlabel = "Range (Km)" | |
| 86 | ylabel = "Intensity" |
|
86 | ylabel = "Intensity" | |
| 87 |
|
87 | |||
| 88 | if not self.isConfig: |
|
88 | if not self.isConfig: | |
| 89 | nplots = len(channelIndexList) |
|
89 | nplots = len(channelIndexList) | |
| 90 |
|
90 | |||
| 91 | self.setup(id=id, |
|
91 | self.setup(id=id, | |
| 92 | nplots=nplots, |
|
92 | nplots=nplots, | |
| 93 | wintitle='', |
|
93 | wintitle='', | |
| 94 | show=show) |
|
94 | show=show) | |
| 95 |
|
95 | |||
| 96 | if xmin == None: xmin = numpy.nanmin(x) |
|
96 | if xmin == None: xmin = numpy.nanmin(x) | |
| 97 | if xmax == None: xmax = numpy.nanmax(x) |
|
97 | if xmax == None: xmax = numpy.nanmax(x) | |
| 98 | if ymin == None: ymin = numpy.nanmin(yreal) |
|
98 | if ymin == None: ymin = numpy.nanmin(yreal) | |
| 99 | if ymax == None: ymax = numpy.nanmax(yreal) |
|
99 | if ymax == None: ymax = numpy.nanmax(yreal) | |
| 100 |
|
100 | |||
| 101 | self.isConfig = True |
|
101 | self.isConfig = True | |
| 102 |
|
102 | |||
| 103 | self.setWinTitle(title) |
|
103 | self.setWinTitle(title) | |
| 104 |
|
104 | |||
| 105 | for i in range(len(self.axesList)): |
|
105 | for i in range(len(self.axesList)): | |
| 106 | title = "Channel %d" %(i) |
|
106 | title = "Channel %d" %(i) | |
| 107 | axes = self.axesList[i] |
|
107 | axes = self.axesList[i] | |
| 108 | ychannel = yreal[i,:] |
|
108 | ychannel = yreal[i,:] | |
| 109 | axes.pline(x, ychannel, |
|
109 | axes.pline(x, ychannel, | |
| 110 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, |
|
110 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, | |
| 111 | xlabel=xlabel, ylabel=ylabel, title=title) |
|
111 | xlabel=xlabel, ylabel=ylabel, title=title) | |
| 112 |
|
112 | |||
| 113 |
|
113 | |||
| 114 | def run(self, dataOut, id, wintitle="", channelList=None, |
|
114 | def run(self, dataOut, id, wintitle="", channelList=None, | |
| 115 | xmin=None, xmax=None, ymin=None, ymax=None, save=False, |
|
115 | xmin=None, xmax=None, ymin=None, ymax=None, save=False, | |
| 116 | figpath='./', figfile=None, show=True, wr_period=1, |
|
116 | figpath='./', figfile=None, show=True, wr_period=1, | |
| 117 | ftp=False, server=None, folder=None, username=None, password=None, type='power', **kwargs): |
|
117 | ftp=False, server=None, folder=None, username=None, password=None, type='power', **kwargs): | |
| 118 |
|
118 | |||
| 119 | """ |
|
119 | """ | |
| 120 |
|
120 | |||
| 121 | Input: |
|
121 | Input: | |
| 122 | dataOut : |
|
122 | dataOut : | |
| 123 | id : |
|
123 | id : | |
| 124 | wintitle : |
|
124 | wintitle : | |
| 125 | channelList : |
|
125 | channelList : | |
| 126 | xmin : None, |
|
126 | xmin : None, | |
| 127 | xmax : None, |
|
127 | xmax : None, | |
| 128 | ymin : None, |
|
128 | ymin : None, | |
| 129 | ymax : None, |
|
129 | ymax : None, | |
| 130 | """ |
|
130 | """ | |
| 131 |
|
131 | |||
| 132 | if channelList == None: |
|
132 | if channelList == None: | |
| 133 | channelIndexList = dataOut.channelIndexList |
|
133 | channelIndexList = dataOut.channelIndexList | |
| 134 | else: |
|
134 | else: | |
| 135 | channelIndexList = [] |
|
135 | channelIndexList = [] | |
| 136 | for channel in channelList: |
|
136 | for channel in channelList: | |
| 137 | if channel not in dataOut.channelList: |
|
137 | if channel not in dataOut.channelList: | |
| 138 | raise ValueError, "Channel %d is not in dataOut.channelList" |
|
138 | raise ValueError, "Channel %d is not in dataOut.channelList" | |
| 139 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
139 | channelIndexList.append(dataOut.channelList.index(channel)) | |
| 140 |
|
140 | |||
| 141 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) |
|
141 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) | |
| 142 |
|
142 | |||
| 143 | if dataOut.flagDataAsBlock: |
|
143 | if dataOut.flagDataAsBlock: | |
| 144 |
|
144 | |||
| 145 | for i in range(dataOut.nProfiles): |
|
145 | for i in range(dataOut.nProfiles): | |
| 146 |
|
146 | |||
| 147 | wintitle1 = wintitle + " [Profile = %d] " %i |
|
147 | wintitle1 = wintitle + " [Profile = %d] " %i | |
| 148 |
|
148 | |||
| 149 | if type == "power": |
|
149 | if type == "power": | |
| 150 |
self.plot_power(dataOut.heightList, |
|
150 | self.plot_power(dataOut.heightList, | |
| 151 | dataOut.data[:,i,:], |
|
151 | dataOut.data[:,i,:], | |
| 152 |
id, |
|
152 | id, | |
| 153 |
channelIndexList, |
|
153 | channelIndexList, | |
| 154 | thisDatetime, |
|
154 | thisDatetime, | |
| 155 | wintitle1, |
|
155 | wintitle1, | |
| 156 | show, |
|
156 | show, | |
| 157 | xmin, |
|
157 | xmin, | |
| 158 | xmax, |
|
158 | xmax, | |
| 159 | ymin, |
|
159 | ymin, | |
| 160 | ymax) |
|
160 | ymax) | |
| 161 |
|
161 | |||
| 162 | if type == "iq": |
|
162 | if type == "iq": | |
| 163 |
self.plot_iq(dataOut.heightList, |
|
163 | self.plot_iq(dataOut.heightList, | |
| 164 | dataOut.data[:,i,:], |
|
164 | dataOut.data[:,i,:], | |
| 165 |
id, |
|
165 | id, | |
| 166 |
channelIndexList, |
|
166 | channelIndexList, | |
| 167 | thisDatetime, |
|
167 | thisDatetime, | |
| 168 | wintitle1, |
|
168 | wintitle1, | |
| 169 | show, |
|
169 | show, | |
| 170 | xmin, |
|
170 | xmin, | |
| 171 | xmax, |
|
171 | xmax, | |
| 172 | ymin, |
|
172 | ymin, | |
| 173 | ymax) |
|
173 | ymax) | |
| 174 |
|
174 | |||
| 175 | self.draw() |
|
175 | self.draw() | |
| 176 |
|
176 | |||
| 177 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
177 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 178 | figfile = self.getFilename(name = str_datetime) + "_" + str(i) |
|
178 | figfile = self.getFilename(name = str_datetime) + "_" + str(i) | |
| 179 |
|
179 | |||
| 180 | self.save(figpath=figpath, |
|
180 | self.save(figpath=figpath, | |
| 181 | figfile=figfile, |
|
181 | figfile=figfile, | |
| 182 | save=save, |
|
182 | save=save, | |
| 183 | ftp=ftp, |
|
183 | ftp=ftp, | |
| 184 | wr_period=wr_period, |
|
184 | wr_period=wr_period, | |
| 185 | thisDatetime=thisDatetime) |
|
185 | thisDatetime=thisDatetime) | |
| 186 |
|
186 | |||
| 187 | else: |
|
187 | else: | |
| 188 | wintitle += " [Profile = %d] " %dataOut.profileIndex |
|
188 | wintitle += " [Profile = %d] " %dataOut.profileIndex | |
| 189 |
|
189 | |||
| 190 | if type == "power": |
|
190 | if type == "power": | |
| 191 |
self.plot_power(dataOut.heightList, |
|
191 | self.plot_power(dataOut.heightList, | |
| 192 | dataOut.data, |
|
192 | dataOut.data, | |
| 193 |
id, |
|
193 | id, | |
| 194 |
channelIndexList, |
|
194 | channelIndexList, | |
| 195 | thisDatetime, |
|
195 | thisDatetime, | |
| 196 | wintitle, |
|
196 | wintitle, | |
| 197 | show, |
|
197 | show, | |
| 198 | xmin, |
|
198 | xmin, | |
| 199 | xmax, |
|
199 | xmax, | |
| 200 | ymin, |
|
200 | ymin, | |
| 201 | ymax) |
|
201 | ymax) | |
| 202 |
|
202 | |||
| 203 | if type == "iq": |
|
203 | if type == "iq": | |
| 204 |
self.plot_iq(dataOut.heightList, |
|
204 | self.plot_iq(dataOut.heightList, | |
| 205 | dataOut.data, |
|
205 | dataOut.data, | |
| 206 |
id, |
|
206 | id, | |
| 207 |
channelIndexList, |
|
207 | channelIndexList, | |
| 208 | thisDatetime, |
|
208 | thisDatetime, | |
| 209 | wintitle, |
|
209 | wintitle, | |
| 210 | show, |
|
210 | show, | |
| 211 | xmin, |
|
211 | xmin, | |
| 212 | xmax, |
|
212 | xmax, | |
| 213 | ymin, |
|
213 | ymin, | |
| 214 | ymax) |
|
214 | ymax) | |
| 215 |
|
215 | |||
| 216 | self.draw() |
|
216 | self.draw() | |
| 217 |
|
217 | |||
| 218 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") + "_" + str(dataOut.profileIndex) |
|
218 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") + "_" + str(dataOut.profileIndex) | |
| 219 |
figfile = self.getFilename(name = str_datetime) |
|
219 | figfile = self.getFilename(name = str_datetime) | |
| 220 |
|
220 | |||
| 221 | self.save(figpath=figpath, |
|
221 | self.save(figpath=figpath, | |
| 222 | figfile=figfile, |
|
222 | figfile=figfile, | |
| 223 | save=save, |
|
223 | save=save, | |
| 224 | ftp=ftp, |
|
224 | ftp=ftp, | |
| 225 | wr_period=wr_period, |
|
225 | wr_period=wr_period, | |
| 226 | thisDatetime=thisDatetime) |
|
226 | thisDatetime=thisDatetime) | |
| 227 |
|
227 | |||
| 228 |
|
228 | |||
| 229 | class VoltACFPLot(Figure): |
|
229 | class VoltACFPLot(Figure): | |
| 230 |
|
230 | |||
| 231 | isConfig = None |
|
231 | isConfig = None | |
| 232 | __nsubplots = None |
|
232 | __nsubplots = None | |
| 233 | PREFIX = 'voltacf' |
|
233 | PREFIX = 'voltacf' | |
| 234 |
|
234 | |||
| 235 | def __init__(self, **kwargs): |
|
235 | def __init__(self, **kwargs): | |
| 236 |
|
|
236 | Figure.__init__(self,**kwargs) | |
| 237 | self.isConfig = False |
|
237 | self.isConfig = False | |
| 238 | self.__nsubplots = 1 |
|
238 | self.__nsubplots = 1 | |
| 239 | self.PLOT_CODE = VOLT_ACF_CODE |
|
239 | self.PLOT_CODE = VOLT_ACF_CODE | |
| 240 | self.WIDTH = 900 |
|
240 | self.WIDTH = 900 | |
| 241 | self.HEIGHT = 700 |
|
241 | self.HEIGHT = 700 | |
| 242 | self.counter_imagwr= 0 |
|
242 | self.counter_imagwr= 0 | |
| 243 | self.FTP_WEI = None |
|
243 | self.FTP_WEI = None | |
| 244 | self.EXP_CODE = None |
|
244 | self.EXP_CODE = None | |
| 245 | self.SUB_EXP_CODE = None |
|
245 | self.SUB_EXP_CODE = None | |
| 246 | self.PLOT_POS = None |
|
246 | self.PLOT_POS = None | |
| 247 |
|
247 | |||
| 248 | def getSubplots(self) : |
|
248 | def getSubplots(self) : | |
| 249 | ncol = 1 |
|
249 | ncol = 1 | |
| 250 | nrow = 1 |
|
250 | nrow = 1 | |
| 251 | return nrow, ncol |
|
251 | return nrow, ncol | |
| 252 |
|
252 | |||
| 253 | def setup(self,id, nplots,wintitle,show): |
|
253 | def setup(self,id, nplots,wintitle,show): | |
| 254 | self.nplots = nplots |
|
254 | self.nplots = nplots | |
| 255 | ncolspan = 1 |
|
255 | ncolspan = 1 | |
| 256 | colspan = 1 |
|
256 | colspan = 1 | |
| 257 | self.createFigure(id=id, |
|
257 | self.createFigure(id=id, | |
| 258 | wintitle = wintitle, |
|
258 | wintitle = wintitle, | |
| 259 | widthplot = self.WIDTH, |
|
259 | widthplot = self.WIDTH, | |
| 260 | heightplot = self.HEIGHT, |
|
260 | heightplot = self.HEIGHT, | |
| 261 | show = show) |
|
261 | show = show) | |
|
|
262 | ||||
| 262 | nrow, ncol = self.getSubplots() |
|
263 | nrow, ncol = self.getSubplots() | |
| 263 | counter = 0 |
|
264 | counter = 0 | |
|
|
265 | ||||
| 264 | for y in range(nrow): |
|
266 | for y in range(nrow): | |
| 265 |
|
|
267 | for x in range(ncol): | |
| 266 |
|
|
268 | self.addAxes(nrow, ncol*ncolspan,y, x*ncolspan, colspan, 1) | |
| 267 |
|
269 | |||
| 268 | def run(self,dataOut, id, wintitle="",channelList = None , channel =None, nSamples = None, |
|
270 | def run(self,dataOut, id, wintitle="",channelList = None , channel =None, nSamples = None, | |
| 269 | nSampleList= None, resolutionFactor=None, xmin= None, xmax = None, ymin=None, ymax=None, |
|
271 | nSampleList= None, resolutionFactor=None, xmin= None, xmax = None, ymin=None, ymax=None, | |
| 270 | save= False, figpath='./', figfile= None,show= True, ftp= False, wr_period=1, server= None, |
|
272 | save= False, figpath='./', figfile= None,show= True, ftp= False, wr_period=1, server= None, | |
| 271 | folder= None, username =None, password= None, ftp_wei=0 , exp_code=0,sub_exp_code=0,plot_pos=0, |
|
273 | folder= None, username =None, password= None, ftp_wei=0 , exp_code=0,sub_exp_code=0,plot_pos=0, | |
| 272 | xaxis="time"): |
|
274 | xaxis="time"): | |
| 273 |
|
275 | |||
| 274 | channel0 = channel |
|
276 | channel0 = channel | |
| 275 | nSamples = nSamples |
|
277 | nSamples = nSamples | |
| 276 | resFactor = resolutionFactor |
|
278 | resFactor = resolutionFactor | |
| 277 |
|
279 | |||
| 278 | if nSamples == None: |
|
280 | if nSamples == None: | |
| 279 | nSamples = 20 |
|
281 | nSamples = 20 | |
| 280 |
|
282 | |||
| 281 | if resFactor == None: |
|
283 | if resFactor == None: | |
| 282 | resFactor = 5 |
|
284 | resFactor = 5 | |
| 283 |
|
285 | |||
| 284 | if channel0 == None: |
|
286 | if channel0 == None: | |
| 285 | channel0 = 0 |
|
287 | channel0 = 0 | |
| 286 | else: |
|
288 | else: | |
| 287 | if channel0 not in dataOut.channelList: |
|
289 | if channel0 not in dataOut.channelList: | |
| 288 | raise ValueError, "Channel %d is not in %s dataOut.channelList"%(channel0, dataOut.channelList) |
|
290 | raise ValueError, "Channel %d is not in %s dataOut.channelList"%(channel0, dataOut.channelList) | |
| 289 |
|
291 | |||
| 290 |
if channelList == None: |
|
292 | if channelList == None: | |
| 291 | channelIndexList = dataOut.channelIndexList |
|
293 | channelIndexList = dataOut.channelIndexList | |
| 292 | channelList = dataOut.channelList |
|
294 | channelList = dataOut.channelList | |
| 293 |
|
295 | |||
| 294 | else: |
|
296 | else: | |
| 295 | channelIndexList = [] |
|
297 | channelIndexList = [] | |
| 296 | for channel in channelList: |
|
298 | for channel in channelList: | |
| 297 | if channel not in dataOut.channelList: |
|
299 | if channel not in dataOut.channelList: | |
| 298 | raise ValueError, "Channel %d is not in dataOut.channelList" |
|
300 | raise ValueError, "Channel %d is not in dataOut.channelList" | |
| 299 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
301 | channelIndexList.append(dataOut.channelList.index(channel)) | |
| 300 |
|
302 | |||
| 301 |
|
||||
| 302 | #factor = dataOut.normFactor |
|
303 | #factor = dataOut.normFactor | |
| 303 | y = dataOut.getHeiRange() |
|
304 | y = dataOut.getHeiRange() | |
| 304 | #print y, dataOut.heightList[0] |
|
305 | #print y, dataOut.heightList[0] | |
| 305 | #print "pause" |
|
306 | #print "pause" | |
| 306 | #import time |
|
307 | #import time | |
| 307 | #time.sleep(10) |
|
308 | #time.sleep(10) | |
| 308 | deltaHeight = dataOut.heightList[1]-dataOut.heightList[0] |
|
309 | deltaHeight = dataOut.heightList[1]-dataOut.heightList[0] | |
| 309 | z = dataOut.data |
|
310 | z = dataOut.data_acfLag | |
|
|
311 | ||||
|
|
312 | shape = dataOut.data_acfLag.shape | |||
| 310 |
|
313 | |||
| 311 | shape = dataOut.data.shape |
|
|||
| 312 |
hei_index = numpy.arange(shape[2]) |
|
314 | hei_index = numpy.arange(shape[2]) | |
| 313 | hei_plot = numpy.arange(nSamples)*resFactor |
|
315 | hei_plot = numpy.arange(nSamples)*resFactor | |
| 314 |
|
316 | |||
| 315 | if nSampleList is not None: |
|
317 | if nSampleList is not None: | |
| 316 | for nsample in nSampleList: |
|
318 | for nsample in nSampleList: | |
| 317 | if nsample not in dataOut.heightList/deltaHeight: |
|
319 | if nsample not in dataOut.heightList/deltaHeight: | |
| 318 |
|
|
320 | print "Lista available : %s "%(dataOut.heightList/deltaHeight) | |
| 319 | raise ValueError, "nsample %d is not in %s dataOut.heightList"%(nsample,dataOut.heightList) |
|
321 | raise ValueError, "nsample %d is not in %s dataOut.heightList"%(nsample,dataOut.heightList) | |
| 320 |
|
322 | |||
| 321 | if nSampleList is not None: |
|
323 | if nSampleList is not None: | |
| 322 | hei_plot = numpy.array(nSampleList)*resFactor |
|
324 | hei_plot = numpy.array(nSampleList)*resFactor | |
| 323 |
|
325 | |||
| 324 | if hei_plot[-1] >= hei_index[-1]: |
|
326 | if hei_plot[-1] >= hei_index[-1]: | |
| 325 | print ("La cantidad de puntos en altura es %d y la resolucion es %f Km"%(hei_plot.shape[0],deltaHeight*resFactor )) |
|
327 | print ("La cantidad de puntos en altura es %d y la resolucion es %f 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]) |
|
328 | 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 |
|
329 | |||
| 328 | #escalamiento -1 a 1 a resolucion (factor de resolucion en altura)* deltaHeight |
|
330 | #escalamiento -1 a 1 a resolucion (factor de resolucion en altura)* deltaHeight | |
| 329 | #min = numpy.min(z[0,:,0]) |
|
331 | #min = numpy.min(z[0,:,0]) | |
| 330 | #max =numpy.max(z[0,:,0]) |
|
332 | #max =numpy.max(z[0,:,0]) | |
|
|
333 | #print shape[0] | |||
| 331 | for i in range(shape[0]): |
|
334 | for i in range(shape[0]): | |
|
|
335 | #print "amigo i",i | |||
| 332 | for j in range(shape[2]): |
|
336 | for j in range(shape[2]): | |
| 333 |
|
|
337 | min = numpy.min(z[i,:,j]) | |
| 334 |
|
|
338 | max = numpy.max(z[i,:,j]) | |
| 335 | z[i,:,j]= (((z[i,:,j]-min)/(max-min))*deltaHeight*resFactor + j*deltaHeight+dataOut.heightList[0]) |
|
339 | z[i,:,j]= (((z[i,:,j]-min)/(max-min))*deltaHeight*resFactor + j*deltaHeight+dataOut.heightList[0]) | |
| 336 |
|
340 | |||
| 337 |
|
||||
| 338 | if xaxis == "time": |
|
341 | if xaxis == "time": | |
| 339 | x = dataOut.getAcfRange()*1000 |
|
342 | x = dataOut.getAcfRange()*1000 | |
| 340 | zdB = z[channel0,:,hei_plot] |
|
343 | zdB = z[channel0,:,hei_plot] | |
| 341 | xlabel = "Time (ms)" |
|
344 | xlabel = "Time (ms)" | |
| 342 | ylabel = "VOLT_ACF" |
|
345 | ylabel = "VOLT_ACF" | |
| 343 |
|
||||
| 344 |
|
||||
| 345 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) |
|
346 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) | |
| 346 | title = wintitle + "VOLT ACF Plot Ch %s %s" %(channel0,thisDatetime.strftime("%d-%b-%Y")) |
|
347 | title = wintitle + "VOLT ACF Plot Ch %s %s" %(channel0,thisDatetime.strftime("%d-%b-%Y")) | |
| 347 |
|
348 | |||
| 348 | if not self.isConfig: |
|
349 | if not self.isConfig: | |
| 349 |
|
350 | |||
| 350 | nplots = 1 |
|
351 | nplots = 1 | |
| 351 |
|
352 | |||
| 352 | self.setup(id=id, |
|
353 | self.setup(id=id, | |
| 353 | nplots=nplots, |
|
354 | nplots=nplots, | |
| 354 | wintitle=wintitle, |
|
355 | wintitle=wintitle, | |
| 355 | show=show) |
|
356 | show=show) | |
| 356 |
|
357 | |||
| 357 | if xmin == None: xmin = numpy.nanmin(x)#*0.9 |
|
358 | if xmin == None: xmin = numpy.nanmin(x)#*0.9 | |
| 358 | if xmax == None: xmax = numpy.nanmax(x)#*1.1 |
|
359 | if xmax == None: xmax = numpy.nanmax(x)#*1.1 | |
| 359 | if ymin == None: ymin = numpy.nanmin(zdB) |
|
360 | if ymin == None: ymin = numpy.nanmin(zdB) | |
| 360 | if ymax == None: ymax = numpy.nanmax(zdB) |
|
361 | if ymax == None: ymax = numpy.nanmax(zdB) | |
| 361 |
|
362 | |||
| 362 | print ("El parametro resFactor es %d y la resolucion en altura es %f"%(resFactor,deltaHeight )) |
|
363 | print ("El parametro resFactor es %d y la resolucion en altura es %f"%(resFactor,deltaHeight )) | |
| 363 | print ("La cantidad de puntos en altura es %d y la nueva resolucion es %f Km"%(hei_plot.shape[0],deltaHeight*resFactor )) |
|
364 | print ("La cantidad de puntos en altura es %d y la nueva resolucion es %f Km"%(hei_plot.shape[0],deltaHeight*resFactor )) | |
| 364 | print ("La altura maxima es %d Km"%(hei_plot[-1]*deltaHeight )) |
|
365 | print ("La altura maxima es %d Km"%(hei_plot[-1]*deltaHeight )) | |
| 365 |
|
366 | |||
| 366 | self.FTP_WEI = ftp_wei |
|
367 | self.FTP_WEI = ftp_wei | |
| 367 | self.EXP_CODE = exp_code |
|
368 | self.EXP_CODE = exp_code | |
| 368 | self.SUB_EXP_CODE = sub_exp_code |
|
369 | self.SUB_EXP_CODE = sub_exp_code | |
| 369 | self.PLOT_POS = plot_pos |
|
370 | self.PLOT_POS = plot_pos | |
| 370 |
|
371 | |||
| 371 | self.isConfig = True |
|
372 | self.isConfig = True | |
| 372 |
|
373 | |||
| 373 | self.setWinTitle(title) |
|
374 | self.setWinTitle(title) | |
| 374 |
|
||||
| 375 |
|
|
375 | title = "VOLT ACF Plot: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
| 376 | axes = self.axesList[0] |
|
376 | axes = self.axesList[0] | |
| 377 |
|
377 | |||
| 378 | legendlabels = ["Range = %dKm" %y[i] for i in hei_plot] |
|
378 | legendlabels = ["Range = %dKm" %y[i] for i in hei_plot] | |
| 379 |
|
379 | |||
| 380 | axes.pmultilineyaxis( x, zdB, |
|
380 | axes.pmultilineyaxis( x, zdB, | |
| 381 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, |
|
381 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, | |
| 382 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, |
|
382 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, | |
| 383 | ytick_visible=True, nxticks=5, |
|
383 | ytick_visible=True, nxticks=5, | |
| 384 | grid='x') |
|
384 | grid='x') | |
| 385 |
|
385 | |||
| 386 | self.draw() |
|
386 | self.draw() | |
| 387 |
|
387 | |||
| 388 | if figfile == None: |
|
388 | if figfile == None: | |
| 389 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
389 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 390 | name = str_datetime |
|
390 | name = str_datetime | |
| 391 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): |
|
391 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): | |
| 392 | name = name + '_az' + '_%2.2f'%(dataOut.azimuth) + '_zn' + '_%2.2f'%(dataOut.zenith) |
|
392 | name = name + '_az' + '_%2.2f'%(dataOut.azimuth) + '_zn' + '_%2.2f'%(dataOut.zenith) | |
| 393 | figfile = self.getFilename(name) |
|
393 | figfile = self.getFilename(name) | |
| 394 |
|
394 | |||
| 395 | self.save(figpath=figpath, |
|
395 | self.save(figpath=figpath, | |
| 396 | figfile=figfile, |
|
396 | figfile=figfile, | |
| 397 | save=save, |
|
397 | save=save, | |
| 398 | ftp=ftp, |
|
398 | ftp=ftp, | |
| 399 | wr_period=wr_period, |
|
399 | wr_period=wr_period, | |
| 400 | thisDatetime=thisDatetime) |
|
400 | thisDatetime=thisDatetime) | |
| 401 |
|
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| 402 |
|
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| 403 |
|
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| 404 |
|
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| 405 |
|
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| 406 |
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| 407 |
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| 408 |
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| 409 |
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| 410 |
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| 411 |
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| 412 |
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| 413 |
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| 414 |
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| 415 |
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| 416 |
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| 417 |
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| 418 |
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| 419 |
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| 420 |
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| 422 |
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| 424 |
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| 425 |
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| 426 |
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| @@ -1,1682 +1,1686 | |||||
| 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 |
|
9 | import math | |
| 10 |
|
10 | |||
| 11 | def rep_seq(x, rep=10): |
|
11 | def rep_seq(x, rep=10): | |
| 12 | L = len(x) * rep |
|
12 | L = len(x) * rep | |
| 13 | res = numpy.zeros(L, dtype=x.dtype) |
|
13 | res = numpy.zeros(L, dtype=x.dtype) | |
| 14 | idx = numpy.arange(len(x)) * rep |
|
14 | idx = numpy.arange(len(x)) * rep | |
| 15 | for i in numpy.arange(rep): |
|
15 | for i in numpy.arange(rep): | |
| 16 | res[idx + i] = x |
|
16 | res[idx + i] = x | |
| 17 | return(res) |
|
17 | return(res) | |
| 18 |
|
18 | |||
| 19 |
|
19 | |||
| 20 | def create_pseudo_random_code(clen=10000, seed=0): |
|
20 | def create_pseudo_random_code(clen=10000, seed=0): | |
| 21 | """ |
|
21 | """ | |
| 22 | seed is a way of reproducing the random code without |
|
22 | seed is a way of reproducing the random code without | |
| 23 | having to store all actual codes. the seed can then |
|
23 | having to store all actual codes. the seed can then | |
| 24 | act as a sort of station_id. |
|
24 | act as a sort of station_id. | |
| 25 |
|
25 | |||
| 26 | """ |
|
26 | """ | |
| 27 | numpy.random.seed(seed) |
|
27 | numpy.random.seed(seed) | |
| 28 | phases = numpy.array( |
|
28 | phases = numpy.array( | |
| 29 | numpy.exp(1.0j * 2.0 * math.pi * numpy.random.random(clen)), |
|
29 | numpy.exp(1.0j * 2.0 * math.pi * numpy.random.random(clen)), | |
| 30 | dtype=numpy.complex64, |
|
30 | dtype=numpy.complex64, | |
| 31 | ) |
|
31 | ) | |
| 32 | return(phases) |
|
32 | return(phases) | |
| 33 |
|
33 | |||
| 34 |
|
34 | |||
| 35 | def periodic_convolution_matrix(envelope, rmin=0, rmax=100): |
|
35 | def periodic_convolution_matrix(envelope, rmin=0, rmax=100): | |
| 36 | """ |
|
36 | """ | |
| 37 | we imply that the number of measurements is equal to the number of elements |
|
37 | we imply that the number of measurements is equal to the number of elements | |
| 38 | in code |
|
38 | in code | |
| 39 |
|
39 | |||
| 40 | """ |
|
40 | """ | |
| 41 | L = len(envelope) |
|
41 | L = len(envelope) | |
| 42 | ridx = numpy.arange(rmin, rmax) |
|
42 | ridx = numpy.arange(rmin, rmax) | |
| 43 | A = numpy.zeros([L, rmax-rmin], dtype=numpy.complex64) |
|
43 | A = numpy.zeros([L, rmax-rmin], dtype=numpy.complex64) | |
| 44 | for i in numpy.arange(L): |
|
44 | for i in numpy.arange(L): | |
| 45 | A[i, :] = envelope[(i-ridx) % L] |
|
45 | A[i, :] = envelope[(i-ridx) % L] | |
| 46 | result = {} |
|
46 | result = {} | |
| 47 | result['A'] = A |
|
47 | result['A'] = A | |
| 48 | result['ridx'] = ridx |
|
48 | result['ridx'] = ridx | |
| 49 | return(result) |
|
49 | return(result) | |
| 50 |
|
50 | |||
| 51 |
|
51 | |||
| 52 | B_cache = 0 |
|
52 | B_cache = 0 | |
| 53 | r_cache = 0 |
|
53 | r_cache = 0 | |
| 54 | B_cached = False |
|
54 | B_cached = False | |
| 55 | def create_estimation_matrix(code, rmin=0, rmax=1000, cache=True): |
|
55 | def create_estimation_matrix(code, rmin=0, rmax=1000, cache=True): | |
| 56 | global B_cache |
|
56 | global B_cache | |
| 57 | global r_cache |
|
57 | global r_cache | |
| 58 | global B_cached |
|
58 | global B_cached | |
| 59 |
|
59 | |||
| 60 | if not cache or not B_cached: |
|
60 | if not cache or not B_cached: | |
| 61 | r_cache = periodic_convolution_matrix( |
|
61 | r_cache = periodic_convolution_matrix( | |
| 62 | envelope=code, rmin=rmin, rmax=rmax, |
|
62 | envelope=code, rmin=rmin, rmax=rmax, | |
| 63 | ) |
|
63 | ) | |
| 64 | A = r_cache['A'] |
|
64 | A = r_cache['A'] | |
| 65 | Ah = numpy.transpose(numpy.conjugate(A)) |
|
65 | Ah = numpy.transpose(numpy.conjugate(A)) | |
| 66 | B_cache = numpy.dot(numpy.linalg.inv(numpy.dot(Ah, A)), Ah) |
|
66 | B_cache = numpy.dot(numpy.linalg.inv(numpy.dot(Ah, A)), Ah) | |
| 67 | r_cache['B'] = B_cache |
|
67 | r_cache['B'] = B_cache | |
| 68 | B_cached = True |
|
68 | B_cached = True | |
| 69 | return(r_cache) |
|
69 | return(r_cache) | |
| 70 | else: |
|
70 | else: | |
| 71 | return(r_cache) |
|
71 | return(r_cache) | |
| 72 |
|
72 | |||
| 73 | class VoltageProc(ProcessingUnit): |
|
73 | class VoltageProc(ProcessingUnit): | |
| 74 |
|
74 | |||
| 75 |
|
75 | |||
| 76 | def __init__(self, **kwargs): |
|
76 | def __init__(self, **kwargs): | |
| 77 |
|
77 | |||
| 78 | ProcessingUnit.__init__(self, **kwargs) |
|
78 | ProcessingUnit.__init__(self, **kwargs) | |
| 79 |
|
79 | |||
| 80 | # self.objectDict = {} |
|
80 | # self.objectDict = {} | |
| 81 | self.dataOut = Voltage() |
|
81 | self.dataOut = Voltage() | |
| 82 | self.flip = 1 |
|
82 | self.flip = 1 | |
| 83 |
|
83 | |||
| 84 | def run(self): |
|
84 | def run(self): | |
| 85 | if self.dataIn.type == 'AMISR': |
|
85 | if self.dataIn.type == 'AMISR': | |
| 86 | self.__updateObjFromAmisrInput() |
|
86 | self.__updateObjFromAmisrInput() | |
| 87 |
|
87 | |||
| 88 | if self.dataIn.type == 'Voltage': |
|
88 | if self.dataIn.type == 'Voltage': | |
| 89 | self.dataOut.copy(self.dataIn) |
|
89 | self.dataOut.copy(self.dataIn) | |
| 90 |
|
90 | |||
| 91 | # self.dataOut.copy(self.dataIn) |
|
91 | # self.dataOut.copy(self.dataIn) | |
| 92 |
|
92 | |||
| 93 | def __updateObjFromAmisrInput(self): |
|
93 | def __updateObjFromAmisrInput(self): | |
| 94 |
|
94 | |||
| 95 | self.dataOut.timeZone = self.dataIn.timeZone |
|
95 | self.dataOut.timeZone = self.dataIn.timeZone | |
| 96 | self.dataOut.dstFlag = self.dataIn.dstFlag |
|
96 | self.dataOut.dstFlag = self.dataIn.dstFlag | |
| 97 | self.dataOut.errorCount = self.dataIn.errorCount |
|
97 | self.dataOut.errorCount = self.dataIn.errorCount | |
| 98 | self.dataOut.useLocalTime = self.dataIn.useLocalTime |
|
98 | self.dataOut.useLocalTime = self.dataIn.useLocalTime | |
| 99 |
|
99 | |||
| 100 | self.dataOut.flagNoData = self.dataIn.flagNoData |
|
100 | self.dataOut.flagNoData = self.dataIn.flagNoData | |
| 101 | self.dataOut.data = self.dataIn.data |
|
101 | self.dataOut.data = self.dataIn.data | |
| 102 | self.dataOut.utctime = self.dataIn.utctime |
|
102 | self.dataOut.utctime = self.dataIn.utctime | |
| 103 | self.dataOut.channelList = self.dataIn.channelList |
|
103 | self.dataOut.channelList = self.dataIn.channelList | |
| 104 | # self.dataOut.timeInterval = self.dataIn.timeInterval |
|
104 | # self.dataOut.timeInterval = self.dataIn.timeInterval | |
| 105 | self.dataOut.heightList = self.dataIn.heightList |
|
105 | self.dataOut.heightList = self.dataIn.heightList | |
| 106 | self.dataOut.nProfiles = self.dataIn.nProfiles |
|
106 | self.dataOut.nProfiles = self.dataIn.nProfiles | |
| 107 |
|
107 | |||
| 108 | self.dataOut.nCohInt = self.dataIn.nCohInt |
|
108 | self.dataOut.nCohInt = self.dataIn.nCohInt | |
| 109 | self.dataOut.ippSeconds = self.dataIn.ippSeconds |
|
109 | self.dataOut.ippSeconds = self.dataIn.ippSeconds | |
| 110 | self.dataOut.frequency = self.dataIn.frequency |
|
110 | self.dataOut.frequency = self.dataIn.frequency | |
| 111 |
|
111 | |||
| 112 | self.dataOut.azimuth = self.dataIn.azimuth |
|
112 | self.dataOut.azimuth = self.dataIn.azimuth | |
| 113 | self.dataOut.zenith = self.dataIn.zenith |
|
113 | self.dataOut.zenith = self.dataIn.zenith | |
| 114 |
|
114 | |||
| 115 | self.dataOut.beam.codeList = self.dataIn.beam.codeList |
|
115 | self.dataOut.beam.codeList = self.dataIn.beam.codeList | |
| 116 | self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList |
|
116 | self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList | |
| 117 | self.dataOut.beam.zenithList = self.dataIn.beam.zenithList |
|
117 | self.dataOut.beam.zenithList = self.dataIn.beam.zenithList | |
| 118 | # |
|
118 | # | |
| 119 | # pass# |
|
119 | # pass# | |
| 120 | # |
|
120 | # | |
| 121 | # def init(self): |
|
121 | # def init(self): | |
| 122 | # |
|
122 | # | |
| 123 | # |
|
123 | # | |
| 124 | # if self.dataIn.type == 'AMISR': |
|
124 | # if self.dataIn.type == 'AMISR': | |
| 125 | # self.__updateObjFromAmisrInput() |
|
125 | # self.__updateObjFromAmisrInput() | |
| 126 | # |
|
126 | # | |
| 127 | # if self.dataIn.type == 'Voltage': |
|
127 | # if self.dataIn.type == 'Voltage': | |
| 128 | # self.dataOut.copy(self.dataIn) |
|
128 | # self.dataOut.copy(self.dataIn) | |
| 129 | # # No necesita copiar en cada init() los atributos de dataIn |
|
129 | # # No necesita copiar en cada init() los atributos de dataIn | |
| 130 | # # la copia deberia hacerse por cada nuevo bloque de datos |
|
130 | # # la copia deberia hacerse por cada nuevo bloque de datos | |
| 131 |
|
131 | |||
| 132 | def selectChannels(self, channelList): |
|
132 | def selectChannels(self, channelList): | |
| 133 |
|
133 | |||
| 134 | channelIndexList = [] |
|
134 | channelIndexList = [] | |
| 135 |
|
135 | |||
| 136 | for channel in channelList: |
|
136 | for channel in channelList: | |
| 137 | if channel not in self.dataOut.channelList: |
|
137 | if channel not in self.dataOut.channelList: | |
| 138 | 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)) | |
| 139 |
|
139 | |||
| 140 | index = self.dataOut.channelList.index(channel) |
|
140 | index = self.dataOut.channelList.index(channel) | |
| 141 | channelIndexList.append(index) |
|
141 | channelIndexList.append(index) | |
| 142 |
|
142 | |||
| 143 | self.selectChannelsByIndex(channelIndexList) |
|
143 | self.selectChannelsByIndex(channelIndexList) | |
| 144 |
|
144 | |||
| 145 | def selectChannelsByIndex(self, channelIndexList): |
|
145 | def selectChannelsByIndex(self, channelIndexList): | |
| 146 | """ |
|
146 | """ | |
| 147 | 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 | |
| 148 |
|
148 | |||
| 149 | Input: |
|
149 | Input: | |
| 150 | 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] | |
| 151 |
|
151 | |||
| 152 | Affected: |
|
152 | Affected: | |
| 153 | self.dataOut.data |
|
153 | self.dataOut.data | |
| 154 | self.dataOut.channelIndexList |
|
154 | self.dataOut.channelIndexList | |
| 155 | self.dataOut.nChannels |
|
155 | self.dataOut.nChannels | |
| 156 | self.dataOut.m_ProcessingHeader.totalSpectra |
|
156 | self.dataOut.m_ProcessingHeader.totalSpectra | |
| 157 | self.dataOut.systemHeaderObj.numChannels |
|
157 | self.dataOut.systemHeaderObj.numChannels | |
| 158 | self.dataOut.m_ProcessingHeader.blockSize |
|
158 | self.dataOut.m_ProcessingHeader.blockSize | |
| 159 |
|
159 | |||
| 160 | Return: |
|
160 | Return: | |
| 161 | None |
|
161 | None | |
| 162 | """ |
|
162 | """ | |
| 163 |
|
163 | |||
| 164 | for channelIndex in channelIndexList: |
|
164 | for channelIndex in channelIndexList: | |
| 165 | if channelIndex not in self.dataOut.channelIndexList: |
|
165 | if channelIndex not in self.dataOut.channelIndexList: | |
| 166 | print channelIndexList |
|
166 | print channelIndexList | |
| 167 | raise ValueError, "The value %d in channelIndexList is not valid" %channelIndex |
|
167 | raise ValueError, "The value %d in channelIndexList is not valid" %channelIndex | |
| 168 |
|
168 | |||
| 169 | if self.dataOut.flagDataAsBlock: |
|
169 | if self.dataOut.flagDataAsBlock: | |
| 170 | """ |
|
170 | """ | |
| 171 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
171 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] | |
| 172 | """ |
|
172 | """ | |
| 173 | data = self.dataOut.data[channelIndexList,:,:] |
|
173 | data = self.dataOut.data[channelIndexList,:,:] | |
| 174 | else: |
|
174 | else: | |
| 175 | data = self.dataOut.data[channelIndexList,:] |
|
175 | data = self.dataOut.data[channelIndexList,:] | |
| 176 |
|
176 | |||
| 177 | self.dataOut.data = data |
|
177 | self.dataOut.data = data | |
| 178 | self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] |
|
178 | self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] | |
| 179 | # self.dataOut.nChannels = nChannels |
|
179 | # self.dataOut.nChannels = nChannels | |
| 180 |
|
180 | |||
| 181 | return 1 |
|
181 | return 1 | |
| 182 |
|
182 | |||
| 183 | def selectHeights(self, minHei=None, maxHei=None): |
|
183 | def selectHeights(self, minHei=None, maxHei=None): | |
| 184 | """ |
|
184 | """ | |
| 185 | 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 | |
| 186 | minHei <= height <= maxHei |
|
186 | minHei <= height <= maxHei | |
| 187 |
|
187 | |||
| 188 | Input: |
|
188 | Input: | |
| 189 | minHei : valor minimo de altura a considerar |
|
189 | minHei : valor minimo de altura a considerar | |
| 190 | maxHei : valor maximo de altura a considerar |
|
190 | maxHei : valor maximo de altura a considerar | |
| 191 |
|
191 | |||
| 192 | Affected: |
|
192 | Affected: | |
| 193 | Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex |
|
193 | Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex | |
| 194 |
|
194 | |||
| 195 | Return: |
|
195 | Return: | |
| 196 | 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 | |
| 197 | """ |
|
197 | """ | |
| 198 |
|
198 | |||
| 199 | if minHei == None: |
|
199 | if minHei == None: | |
| 200 | minHei = self.dataOut.heightList[0] |
|
200 | minHei = self.dataOut.heightList[0] | |
| 201 |
|
201 | |||
| 202 | if maxHei == None: |
|
202 | if maxHei == None: | |
| 203 | maxHei = self.dataOut.heightList[-1] |
|
203 | maxHei = self.dataOut.heightList[-1] | |
| 204 |
|
204 | |||
| 205 | if (minHei < self.dataOut.heightList[0]): |
|
205 | if (minHei < self.dataOut.heightList[0]): | |
| 206 | minHei = self.dataOut.heightList[0] |
|
206 | minHei = self.dataOut.heightList[0] | |
| 207 |
|
207 | |||
| 208 | if (maxHei > self.dataOut.heightList[-1]): |
|
208 | if (maxHei > self.dataOut.heightList[-1]): | |
| 209 | maxHei = self.dataOut.heightList[-1] |
|
209 | maxHei = self.dataOut.heightList[-1] | |
| 210 |
|
210 | |||
| 211 | minIndex = 0 |
|
211 | minIndex = 0 | |
| 212 | maxIndex = 0 |
|
212 | maxIndex = 0 | |
| 213 | heights = self.dataOut.heightList |
|
213 | heights = self.dataOut.heightList | |
| 214 |
|
214 | |||
| 215 | inda = numpy.where(heights >= minHei) |
|
215 | inda = numpy.where(heights >= minHei) | |
| 216 | indb = numpy.where(heights <= maxHei) |
|
216 | indb = numpy.where(heights <= maxHei) | |
| 217 |
|
217 | |||
| 218 | try: |
|
218 | try: | |
| 219 | minIndex = inda[0][0] |
|
219 | minIndex = inda[0][0] | |
| 220 | except: |
|
220 | except: | |
| 221 | minIndex = 0 |
|
221 | minIndex = 0 | |
| 222 |
|
222 | |||
| 223 | try: |
|
223 | try: | |
| 224 | maxIndex = indb[0][-1] |
|
224 | maxIndex = indb[0][-1] | |
| 225 | except: |
|
225 | except: | |
| 226 | maxIndex = len(heights) |
|
226 | maxIndex = len(heights) | |
| 227 |
|
227 | |||
| 228 | self.selectHeightsByIndex(minIndex, maxIndex) |
|
228 | self.selectHeightsByIndex(minIndex, maxIndex) | |
| 229 |
|
229 | |||
| 230 | return 1 |
|
230 | return 1 | |
| 231 |
|
231 | |||
| 232 |
|
232 | |||
| 233 | def selectHeightsByIndex(self, minIndex, maxIndex): |
|
233 | def selectHeightsByIndex(self, minIndex, maxIndex): | |
| 234 | """ |
|
234 | """ | |
| 235 | 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 | |
| 236 | minIndex <= index <= maxIndex |
|
236 | minIndex <= index <= maxIndex | |
| 237 |
|
237 | |||
| 238 | Input: |
|
238 | Input: | |
| 239 | minIndex : valor de indice minimo de altura a considerar |
|
239 | minIndex : valor de indice minimo de altura a considerar | |
| 240 | maxIndex : valor de indice maximo de altura a considerar |
|
240 | maxIndex : valor de indice maximo de altura a considerar | |
| 241 |
|
241 | |||
| 242 | Affected: |
|
242 | Affected: | |
| 243 | self.dataOut.data |
|
243 | self.dataOut.data | |
| 244 | self.dataOut.heightList |
|
244 | self.dataOut.heightList | |
| 245 |
|
245 | |||
| 246 | Return: |
|
246 | Return: | |
| 247 | 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 | |
| 248 | """ |
|
248 | """ | |
| 249 |
|
249 | |||
| 250 | if (minIndex < 0) or (minIndex > maxIndex): |
|
250 | if (minIndex < 0) or (minIndex > maxIndex): | |
| 251 | 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) | |
| 252 |
|
252 | |||
| 253 | if (maxIndex >= self.dataOut.nHeights): |
|
253 | if (maxIndex >= self.dataOut.nHeights): | |
| 254 | maxIndex = self.dataOut.nHeights |
|
254 | maxIndex = self.dataOut.nHeights | |
| 255 |
|
255 | |||
| 256 | #voltage |
|
256 | #voltage | |
| 257 | if self.dataOut.flagDataAsBlock: |
|
257 | if self.dataOut.flagDataAsBlock: | |
| 258 | """ |
|
258 | """ | |
| 259 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
259 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] | |
| 260 | """ |
|
260 | """ | |
| 261 | data = self.dataOut.data[:,:, minIndex:maxIndex] |
|
261 | data = self.dataOut.data[:,:, minIndex:maxIndex] | |
| 262 | else: |
|
262 | else: | |
| 263 | data = self.dataOut.data[:, minIndex:maxIndex] |
|
263 | data = self.dataOut.data[:, minIndex:maxIndex] | |
| 264 |
|
264 | |||
| 265 | # firstHeight = self.dataOut.heightList[minIndex] |
|
265 | # firstHeight = self.dataOut.heightList[minIndex] | |
| 266 |
|
266 | |||
| 267 | self.dataOut.data = data |
|
267 | self.dataOut.data = data | |
| 268 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex] |
|
268 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex] | |
| 269 |
|
269 | |||
| 270 | if self.dataOut.nHeights <= 1: |
|
270 | if self.dataOut.nHeights <= 1: | |
| 271 | 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) | |
| 272 |
|
272 | |||
| 273 | return 1 |
|
273 | return 1 | |
| 274 |
|
274 | |||
| 275 |
|
275 | |||
| 276 | def filterByHeights(self, window): |
|
276 | def filterByHeights(self, window): | |
| 277 |
|
277 | |||
| 278 | deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0] |
|
278 | deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0] | |
| 279 |
|
279 | |||
| 280 | if window == None: |
|
280 | if window == None: | |
| 281 | window = (self.dataOut.radarControllerHeaderObj.txA/self.dataOut.radarControllerHeaderObj.nBaud) / deltaHeight |
|
281 | window = (self.dataOut.radarControllerHeaderObj.txA/self.dataOut.radarControllerHeaderObj.nBaud) / deltaHeight | |
| 282 |
|
282 | |||
| 283 | newdelta = deltaHeight * window |
|
283 | newdelta = deltaHeight * window | |
| 284 | r = self.dataOut.nHeights % window |
|
284 | r = self.dataOut.nHeights % window | |
| 285 | newheights = (self.dataOut.nHeights-r)/window |
|
285 | newheights = (self.dataOut.nHeights-r)/window | |
| 286 |
|
286 | |||
| 287 | if newheights <= 1: |
|
287 | if newheights <= 1: | |
| 288 | 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) | |
| 289 |
|
289 | |||
| 290 | if self.dataOut.flagDataAsBlock: |
|
290 | if self.dataOut.flagDataAsBlock: | |
| 291 | """ |
|
291 | """ | |
| 292 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
292 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] | |
| 293 | """ |
|
293 | """ | |
| 294 | buffer = self.dataOut.data[:, :, 0:self.dataOut.nHeights-r] |
|
294 | buffer = self.dataOut.data[:, :, 0:self.dataOut.nHeights-r] | |
| 295 | 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) | |
| 296 | buffer = numpy.sum(buffer,3) |
|
296 | buffer = numpy.sum(buffer,3) | |
| 297 |
|
297 | |||
| 298 | else: |
|
298 | else: | |
| 299 | buffer = self.dataOut.data[:,0:self.dataOut.nHeights-r] |
|
299 | buffer = self.dataOut.data[:,0:self.dataOut.nHeights-r] | |
| 300 | buffer = buffer.reshape(self.dataOut.nChannels,self.dataOut.nHeights/window,window) |
|
300 | buffer = buffer.reshape(self.dataOut.nChannels,self.dataOut.nHeights/window,window) | |
| 301 | buffer = numpy.sum(buffer,2) |
|
301 | buffer = numpy.sum(buffer,2) | |
| 302 |
|
302 | |||
| 303 | self.dataOut.data = buffer |
|
303 | self.dataOut.data = buffer | |
| 304 | self.dataOut.heightList = self.dataOut.heightList[0] + numpy.arange( newheights )*newdelta |
|
304 | self.dataOut.heightList = self.dataOut.heightList[0] + numpy.arange( newheights )*newdelta | |
| 305 | self.dataOut.windowOfFilter = window |
|
305 | self.dataOut.windowOfFilter = window | |
| 306 |
|
306 | |||
| 307 | def setH0(self, h0, deltaHeight = None): |
|
307 | def setH0(self, h0, deltaHeight = None): | |
| 308 |
|
308 | |||
| 309 | if not deltaHeight: |
|
309 | if not deltaHeight: | |
| 310 | deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0] |
|
310 | deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0] | |
| 311 |
|
311 | |||
| 312 | nHeights = self.dataOut.nHeights |
|
312 | nHeights = self.dataOut.nHeights | |
| 313 |
|
313 | |||
| 314 | newHeiRange = h0 + numpy.arange(nHeights)*deltaHeight |
|
314 | newHeiRange = h0 + numpy.arange(nHeights)*deltaHeight | |
| 315 |
|
315 | |||
| 316 | self.dataOut.heightList = newHeiRange |
|
316 | self.dataOut.heightList = newHeiRange | |
| 317 |
|
317 | |||
| 318 | def deFlip(self, channelList = []): |
|
318 | def deFlip(self, channelList = []): | |
| 319 |
|
319 | |||
| 320 | data = self.dataOut.data.copy() |
|
320 | data = self.dataOut.data.copy() | |
| 321 |
|
321 | |||
| 322 | if self.dataOut.flagDataAsBlock: |
|
322 | if self.dataOut.flagDataAsBlock: | |
| 323 | flip = self.flip |
|
323 | flip = self.flip | |
| 324 | profileList = range(self.dataOut.nProfiles) |
|
324 | profileList = range(self.dataOut.nProfiles) | |
| 325 |
|
325 | |||
| 326 | if not channelList: |
|
326 | if not channelList: | |
| 327 | for thisProfile in profileList: |
|
327 | for thisProfile in profileList: | |
| 328 | data[:,thisProfile,:] = data[:,thisProfile,:]*flip |
|
328 | data[:,thisProfile,:] = data[:,thisProfile,:]*flip | |
| 329 | flip *= -1.0 |
|
329 | flip *= -1.0 | |
| 330 | else: |
|
330 | else: | |
| 331 | for thisChannel in channelList: |
|
331 | for thisChannel in channelList: | |
| 332 | if thisChannel not in self.dataOut.channelList: |
|
332 | if thisChannel not in self.dataOut.channelList: | |
| 333 | continue |
|
333 | continue | |
| 334 |
|
334 | |||
| 335 | for thisProfile in profileList: |
|
335 | for thisProfile in profileList: | |
| 336 | data[thisChannel,thisProfile,:] = data[thisChannel,thisProfile,:]*flip |
|
336 | data[thisChannel,thisProfile,:] = data[thisChannel,thisProfile,:]*flip | |
| 337 | flip *= -1.0 |
|
337 | flip *= -1.0 | |
| 338 |
|
338 | |||
| 339 | self.flip = flip |
|
339 | self.flip = flip | |
| 340 |
|
340 | |||
| 341 | else: |
|
341 | else: | |
| 342 | if not channelList: |
|
342 | if not channelList: | |
| 343 | data[:,:] = data[:,:]*self.flip |
|
343 | data[:,:] = data[:,:]*self.flip | |
| 344 | else: |
|
344 | else: | |
| 345 | for thisChannel in channelList: |
|
345 | for thisChannel in channelList: | |
| 346 | if thisChannel not in self.dataOut.channelList: |
|
346 | if thisChannel not in self.dataOut.channelList: | |
| 347 | continue |
|
347 | continue | |
| 348 |
|
348 | |||
| 349 | data[thisChannel,:] = data[thisChannel,:]*self.flip |
|
349 | data[thisChannel,:] = data[thisChannel,:]*self.flip | |
| 350 |
|
350 | |||
| 351 | self.flip *= -1. |
|
351 | self.flip *= -1. | |
| 352 |
|
352 | |||
| 353 | self.dataOut.data = data |
|
353 | self.dataOut.data = data | |
| 354 |
|
354 | |||
| 355 | def setRadarFrequency(self, frequency=None): |
|
355 | def setRadarFrequency(self, frequency=None): | |
| 356 |
|
356 | |||
| 357 | if frequency != None: |
|
357 | if frequency != None: | |
| 358 | self.dataOut.frequency = frequency |
|
358 | self.dataOut.frequency = frequency | |
| 359 |
|
359 | |||
| 360 | return 1 |
|
360 | return 1 | |
| 361 |
|
361 | |||
| 362 | def interpolateHeights(self, topLim, botLim): |
|
362 | def interpolateHeights(self, topLim, botLim): | |
| 363 | #69 al 72 para julia |
|
363 | #69 al 72 para julia | |
| 364 | #82-84 para meteoros |
|
364 | #82-84 para meteoros | |
| 365 | if len(numpy.shape(self.dataOut.data))==2: |
|
365 | if len(numpy.shape(self.dataOut.data))==2: | |
| 366 | 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 | |
| 367 | sampInterp = numpy.transpose(numpy.tile(sampInterp,(topLim-botLim + 1,1))) |
|
367 | sampInterp = numpy.transpose(numpy.tile(sampInterp,(topLim-botLim + 1,1))) | |
| 368 | #self.dataOut.data[:,botLim:limSup+1] = sampInterp |
|
368 | #self.dataOut.data[:,botLim:limSup+1] = sampInterp | |
| 369 | self.dataOut.data[:,botLim:topLim+1] = sampInterp |
|
369 | self.dataOut.data[:,botLim:topLim+1] = sampInterp | |
| 370 | else: |
|
370 | else: | |
| 371 | nHeights = self.dataOut.data.shape[2] |
|
371 | nHeights = self.dataOut.data.shape[2] | |
| 372 | x = numpy.hstack((numpy.arange(botLim),numpy.arange(topLim+1,nHeights))) |
|
372 | x = numpy.hstack((numpy.arange(botLim),numpy.arange(topLim+1,nHeights))) | |
| 373 | y = self.dataOut.data[:,:,range(botLim)+range(topLim+1,nHeights)] |
|
373 | y = self.dataOut.data[:,:,range(botLim)+range(topLim+1,nHeights)] | |
| 374 | f = interpolate.interp1d(x, y, axis = 2) |
|
374 | f = interpolate.interp1d(x, y, axis = 2) | |
| 375 | xnew = numpy.arange(botLim,topLim+1) |
|
375 | xnew = numpy.arange(botLim,topLim+1) | |
| 376 | ynew = f(xnew) |
|
376 | ynew = f(xnew) | |
| 377 |
|
377 | |||
| 378 | self.dataOut.data[:,:,botLim:topLim+1] = ynew |
|
378 | self.dataOut.data[:,:,botLim:topLim+1] = ynew | |
| 379 |
|
379 | |||
| 380 | # import collections |
|
380 | # import collections | |
| 381 |
|
381 | |||
| 382 | class CohInt(Operation): |
|
382 | class CohInt(Operation): | |
| 383 |
|
383 | |||
| 384 | isConfig = False |
|
384 | isConfig = False | |
| 385 | __profIndex = 0 |
|
385 | __profIndex = 0 | |
| 386 | __byTime = False |
|
386 | __byTime = False | |
| 387 | __initime = None |
|
387 | __initime = None | |
| 388 | __lastdatatime = None |
|
388 | __lastdatatime = None | |
| 389 | __integrationtime = None |
|
389 | __integrationtime = None | |
| 390 | __buffer = None |
|
390 | __buffer = None | |
| 391 | __bufferStride = [] |
|
391 | __bufferStride = [] | |
| 392 | __dataReady = False |
|
392 | __dataReady = False | |
| 393 | __profIndexStride = 0 |
|
393 | __profIndexStride = 0 | |
| 394 | __dataToPutStride = False |
|
394 | __dataToPutStride = False | |
| 395 | n = None |
|
395 | n = None | |
| 396 |
|
396 | |||
| 397 | def __init__(self, **kwargs): |
|
397 | def __init__(self, **kwargs): | |
| 398 |
|
398 | |||
| 399 | Operation.__init__(self, **kwargs) |
|
399 | Operation.__init__(self, **kwargs) | |
| 400 |
|
400 | |||
| 401 | # self.isConfig = False |
|
401 | # self.isConfig = False | |
| 402 |
|
402 | |||
| 403 | 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): | |
| 404 | """ |
|
404 | """ | |
| 405 | Set the parameters of the integration class. |
|
405 | Set the parameters of the integration class. | |
| 406 |
|
406 | |||
| 407 | Inputs: |
|
407 | Inputs: | |
| 408 |
|
408 | |||
| 409 | n : Number of coherent integrations |
|
409 | n : Number of coherent integrations | |
| 410 | 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 | |
| 411 | overlapping : |
|
411 | overlapping : | |
| 412 | """ |
|
412 | """ | |
| 413 |
|
413 | |||
| 414 | self.__initime = None |
|
414 | self.__initime = None | |
| 415 | self.__lastdatatime = 0 |
|
415 | self.__lastdatatime = 0 | |
| 416 | self.__buffer = None |
|
416 | self.__buffer = None | |
| 417 | self.__dataReady = False |
|
417 | self.__dataReady = False | |
| 418 | self.byblock = byblock |
|
418 | self.byblock = byblock | |
| 419 | self.stride = stride |
|
419 | self.stride = stride | |
| 420 |
|
420 | |||
| 421 | if n == None and timeInterval == None: |
|
421 | if n == None and timeInterval == None: | |
| 422 | raise ValueError, "n or timeInterval should be specified ..." |
|
422 | raise ValueError, "n or timeInterval should be specified ..." | |
| 423 |
|
423 | |||
| 424 | if n != None: |
|
424 | if n != None: | |
| 425 | self.n = n |
|
425 | self.n = n | |
| 426 | self.__byTime = False |
|
426 | self.__byTime = False | |
| 427 | else: |
|
427 | else: | |
| 428 | self.__integrationtime = timeInterval #* 60. #if (type(timeInterval)!=integer) -> change this line |
|
428 | self.__integrationtime = timeInterval #* 60. #if (type(timeInterval)!=integer) -> change this line | |
| 429 | self.n = 9999 |
|
429 | self.n = 9999 | |
| 430 | self.__byTime = True |
|
430 | self.__byTime = True | |
| 431 |
|
431 | |||
| 432 | if overlapping: |
|
432 | if overlapping: | |
| 433 | self.__withOverlapping = True |
|
433 | self.__withOverlapping = True | |
| 434 | self.__buffer = None |
|
434 | self.__buffer = None | |
| 435 | else: |
|
435 | else: | |
| 436 | self.__withOverlapping = False |
|
436 | self.__withOverlapping = False | |
| 437 | self.__buffer = 0 |
|
437 | self.__buffer = 0 | |
| 438 |
|
438 | |||
| 439 | self.__profIndex = 0 |
|
439 | self.__profIndex = 0 | |
| 440 |
|
440 | |||
| 441 | def putData(self, data): |
|
441 | def putData(self, data): | |
| 442 |
|
442 | |||
| 443 | """ |
|
443 | """ | |
| 444 | 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 | |
| 445 |
|
445 | |||
| 446 | """ |
|
446 | """ | |
| 447 |
|
447 | |||
| 448 | if not self.__withOverlapping: |
|
448 | if not self.__withOverlapping: | |
| 449 | self.__buffer += data.copy() |
|
449 | self.__buffer += data.copy() | |
| 450 | self.__profIndex += 1 |
|
450 | self.__profIndex += 1 | |
| 451 | return |
|
451 | return | |
| 452 |
|
452 | |||
| 453 | #Overlapping data |
|
453 | #Overlapping data | |
| 454 | nChannels, nHeis = data.shape |
|
454 | nChannels, nHeis = data.shape | |
| 455 | data = numpy.reshape(data, (1, nChannels, nHeis)) |
|
455 | data = numpy.reshape(data, (1, nChannels, nHeis)) | |
| 456 |
|
456 | |||
| 457 | #If the buffer is empty then it takes the data value |
|
457 | #If the buffer is empty then it takes the data value | |
| 458 | if self.__buffer is None: |
|
458 | if self.__buffer is None: | |
| 459 | self.__buffer = data |
|
459 | self.__buffer = data | |
| 460 | self.__profIndex += 1 |
|
460 | self.__profIndex += 1 | |
| 461 | return |
|
461 | return | |
| 462 |
|
462 | |||
| 463 | #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 | |
| 464 | if self.__profIndex < self.n: |
|
464 | if self.__profIndex < self.n: | |
| 465 | self.__buffer = numpy.vstack((self.__buffer, data)) |
|
465 | self.__buffer = numpy.vstack((self.__buffer, data)) | |
| 466 | self.__profIndex += 1 |
|
466 | self.__profIndex += 1 | |
| 467 | return |
|
467 | return | |
| 468 |
|
468 | |||
| 469 | #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 | |
| 470 | self.__buffer = numpy.roll(self.__buffer, -1, axis=0) |
|
470 | self.__buffer = numpy.roll(self.__buffer, -1, axis=0) | |
| 471 | self.__buffer[self.n-1] = data |
|
471 | self.__buffer[self.n-1] = data | |
| 472 | self.__profIndex = self.n |
|
472 | self.__profIndex = self.n | |
| 473 | return |
|
473 | return | |
| 474 |
|
474 | |||
| 475 |
|
475 | |||
| 476 | def pushData(self): |
|
476 | def pushData(self): | |
| 477 | """ |
|
477 | """ | |
| 478 | 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. | |
| 479 |
|
479 | |||
| 480 | Affected: |
|
480 | Affected: | |
| 481 |
|
481 | |||
| 482 | self.__profileIndex |
|
482 | self.__profileIndex | |
| 483 |
|
483 | |||
| 484 | """ |
|
484 | """ | |
| 485 |
|
485 | |||
| 486 | if not self.__withOverlapping: |
|
486 | if not self.__withOverlapping: | |
| 487 | data = self.__buffer |
|
487 | data = self.__buffer | |
| 488 | n = self.__profIndex |
|
488 | n = self.__profIndex | |
| 489 |
|
489 | |||
| 490 | self.__buffer = 0 |
|
490 | self.__buffer = 0 | |
| 491 | self.__profIndex = 0 |
|
491 | self.__profIndex = 0 | |
| 492 |
|
492 | |||
| 493 | return data, n |
|
493 | return data, n | |
| 494 |
|
494 | |||
| 495 | #Integration with Overlapping |
|
495 | #Integration with Overlapping | |
| 496 | data = numpy.sum(self.__buffer, axis=0) |
|
496 | data = numpy.sum(self.__buffer, axis=0) | |
| 497 | # print data |
|
497 | # print data | |
| 498 | # raise |
|
498 | # raise | |
| 499 | n = self.__profIndex |
|
499 | n = self.__profIndex | |
| 500 |
|
500 | |||
| 501 | return data, n |
|
501 | return data, n | |
| 502 |
|
502 | |||
| 503 | def byProfiles(self, data): |
|
503 | def byProfiles(self, data): | |
| 504 |
|
504 | |||
| 505 | self.__dataReady = False |
|
505 | self.__dataReady = False | |
| 506 | avgdata = None |
|
506 | avgdata = None | |
| 507 | # n = None |
|
507 | # n = None | |
| 508 | # print data |
|
508 | # print data | |
| 509 | # raise |
|
509 | # raise | |
| 510 | self.putData(data) |
|
510 | self.putData(data) | |
| 511 |
|
511 | |||
| 512 | if self.__profIndex == self.n: |
|
512 | if self.__profIndex == self.n: | |
| 513 | avgdata, n = self.pushData() |
|
513 | avgdata, n = self.pushData() | |
| 514 | self.__dataReady = True |
|
514 | self.__dataReady = True | |
| 515 |
|
515 | |||
| 516 | return avgdata |
|
516 | return avgdata | |
| 517 |
|
517 | |||
| 518 | def byTime(self, data, datatime): |
|
518 | def byTime(self, data, datatime): | |
| 519 |
|
519 | |||
| 520 | self.__dataReady = False |
|
520 | self.__dataReady = False | |
| 521 | avgdata = None |
|
521 | avgdata = None | |
| 522 | n = None |
|
522 | n = None | |
| 523 |
|
523 | |||
| 524 | self.putData(data) |
|
524 | self.putData(data) | |
| 525 |
|
525 | |||
| 526 | if (datatime - self.__initime) >= self.__integrationtime: |
|
526 | if (datatime - self.__initime) >= self.__integrationtime: | |
| 527 | avgdata, n = self.pushData() |
|
527 | avgdata, n = self.pushData() | |
| 528 | self.n = n |
|
528 | self.n = n | |
| 529 | self.__dataReady = True |
|
529 | self.__dataReady = True | |
| 530 |
|
530 | |||
| 531 | return avgdata |
|
531 | return avgdata | |
| 532 |
|
532 | |||
| 533 | def integrateByStride(self, data, datatime): |
|
533 | def integrateByStride(self, data, datatime): | |
| 534 | # print data |
|
534 | # print data | |
| 535 | if self.__profIndex == 0: |
|
535 | if self.__profIndex == 0: | |
| 536 | self.__buffer = [[data.copy(), datatime]] |
|
536 | self.__buffer = [[data.copy(), datatime]] | |
| 537 | else: |
|
537 | else: | |
| 538 | self.__buffer.append([data.copy(),datatime]) |
|
538 | self.__buffer.append([data.copy(),datatime]) | |
| 539 | self.__profIndex += 1 |
|
539 | self.__profIndex += 1 | |
| 540 | self.__dataReady = False |
|
540 | self.__dataReady = False | |
| 541 |
|
541 | |||
| 542 | if self.__profIndex == self.n * self.stride : |
|
542 | if self.__profIndex == self.n * self.stride : | |
| 543 | self.__dataToPutStride = True |
|
543 | self.__dataToPutStride = True | |
| 544 | self.__profIndexStride = 0 |
|
544 | self.__profIndexStride = 0 | |
| 545 | self.__profIndex = 0 |
|
545 | self.__profIndex = 0 | |
| 546 | self.__bufferStride = [] |
|
546 | self.__bufferStride = [] | |
| 547 | for i in range(self.stride): |
|
547 | for i in range(self.stride): | |
| 548 | current = self.__buffer[i::self.stride] |
|
548 | current = self.__buffer[i::self.stride] | |
| 549 | data = numpy.sum([t[0] for t in current], axis=0) |
|
549 | data = numpy.sum([t[0] for t in current], axis=0) | |
| 550 | avgdatatime = numpy.average([t[1] for t in current]) |
|
550 | avgdatatime = numpy.average([t[1] for t in current]) | |
| 551 | # print data |
|
551 | # print data | |
| 552 | self.__bufferStride.append((data, avgdatatime)) |
|
552 | self.__bufferStride.append((data, avgdatatime)) | |
| 553 |
|
553 | |||
| 554 | if self.__dataToPutStride: |
|
554 | if self.__dataToPutStride: | |
| 555 | self.__dataReady = True |
|
555 | self.__dataReady = True | |
| 556 | self.__profIndexStride += 1 |
|
556 | self.__profIndexStride += 1 | |
| 557 | if self.__profIndexStride == self.stride: |
|
557 | if self.__profIndexStride == self.stride: | |
| 558 | self.__dataToPutStride = False |
|
558 | self.__dataToPutStride = False | |
| 559 | # print self.__bufferStride[self.__profIndexStride - 1] |
|
559 | # print self.__bufferStride[self.__profIndexStride - 1] | |
| 560 | # raise |
|
560 | # raise | |
| 561 | return self.__bufferStride[self.__profIndexStride - 1] |
|
561 | return self.__bufferStride[self.__profIndexStride - 1] | |
| 562 |
|
562 | |||
| 563 |
|
563 | |||
| 564 | return None, None |
|
564 | return None, None | |
| 565 |
|
565 | |||
| 566 | def integrate(self, data, datatime=None): |
|
566 | def integrate(self, data, datatime=None): | |
| 567 |
|
567 | |||
| 568 | if self.__initime == None: |
|
568 | if self.__initime == None: | |
| 569 | self.__initime = datatime |
|
569 | self.__initime = datatime | |
| 570 |
|
570 | |||
| 571 | if self.__byTime: |
|
571 | if self.__byTime: | |
| 572 | avgdata = self.byTime(data, datatime) |
|
572 | avgdata = self.byTime(data, datatime) | |
| 573 | else: |
|
573 | else: | |
| 574 | avgdata = self.byProfiles(data) |
|
574 | avgdata = self.byProfiles(data) | |
| 575 |
|
575 | |||
| 576 |
|
576 | |||
| 577 | self.__lastdatatime = datatime |
|
577 | self.__lastdatatime = datatime | |
| 578 |
|
578 | |||
| 579 | if avgdata is None: |
|
579 | if avgdata is None: | |
| 580 | return None, None |
|
580 | return None, None | |
| 581 |
|
581 | |||
| 582 | avgdatatime = self.__initime |
|
582 | avgdatatime = self.__initime | |
| 583 |
|
583 | |||
| 584 | deltatime = datatime - self.__lastdatatime |
|
584 | deltatime = datatime - self.__lastdatatime | |
| 585 |
|
585 | |||
| 586 | if not self.__withOverlapping: |
|
586 | if not self.__withOverlapping: | |
| 587 | self.__initime = datatime |
|
587 | self.__initime = datatime | |
| 588 | else: |
|
588 | else: | |
| 589 | self.__initime += deltatime |
|
589 | self.__initime += deltatime | |
| 590 |
|
590 | |||
| 591 | return avgdata, avgdatatime |
|
591 | return avgdata, avgdatatime | |
| 592 |
|
592 | |||
| 593 | def integrateByBlock(self, dataOut): |
|
593 | def integrateByBlock(self, dataOut): | |
| 594 |
|
594 | |||
| 595 | times = int(dataOut.data.shape[1]/self.n) |
|
595 | times = int(dataOut.data.shape[1]/self.n) | |
| 596 | avgdata = numpy.zeros((dataOut.nChannels, times, dataOut.nHeights), dtype=numpy.complex) |
|
596 | avgdata = numpy.zeros((dataOut.nChannels, times, dataOut.nHeights), dtype=numpy.complex) | |
| 597 |
|
597 | |||
| 598 | id_min = 0 |
|
598 | id_min = 0 | |
| 599 | id_max = self.n |
|
599 | id_max = self.n | |
| 600 |
|
600 | |||
| 601 | for i in range(times): |
|
601 | for i in range(times): | |
| 602 | junk = dataOut.data[:,id_min:id_max,:] |
|
602 | junk = dataOut.data[:,id_min:id_max,:] | |
| 603 | avgdata[:,i,:] = junk.sum(axis=1) |
|
603 | avgdata[:,i,:] = junk.sum(axis=1) | |
| 604 | id_min += self.n |
|
604 | id_min += self.n | |
| 605 | id_max += self.n |
|
605 | id_max += self.n | |
| 606 |
|
606 | |||
| 607 | timeInterval = dataOut.ippSeconds*self.n |
|
607 | timeInterval = dataOut.ippSeconds*self.n | |
| 608 | avgdatatime = (times - 1) * timeInterval + dataOut.utctime |
|
608 | avgdatatime = (times - 1) * timeInterval + dataOut.utctime | |
| 609 | self.__dataReady = True |
|
609 | self.__dataReady = True | |
| 610 | return avgdata, avgdatatime |
|
610 | return avgdata, avgdatatime | |
| 611 |
|
611 | |||
| 612 | 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): | |
| 613 | if not self.isConfig: |
|
613 | if not self.isConfig: | |
| 614 | 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) | |
| 615 | self.isConfig = True |
|
615 | self.isConfig = True | |
| 616 |
|
616 | |||
| 617 | if dataOut.flagDataAsBlock: |
|
617 | if dataOut.flagDataAsBlock: | |
| 618 | """ |
|
618 | """ | |
| 619 | Si la data es leida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
619 | Si la data es leida por bloques, dimension = [nChannels, nProfiles, nHeis] | |
| 620 | """ |
|
620 | """ | |
| 621 | avgdata, avgdatatime = self.integrateByBlock(dataOut) |
|
621 | avgdata, avgdatatime = self.integrateByBlock(dataOut) | |
| 622 | dataOut.nProfiles /= self.n |
|
622 | dataOut.nProfiles /= self.n | |
| 623 | else: |
|
623 | else: | |
| 624 | if stride is None: |
|
624 | if stride is None: | |
| 625 | avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime) |
|
625 | avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime) | |
| 626 | else: |
|
626 | else: | |
| 627 | avgdata, avgdatatime = self.integrateByStride(dataOut.data, dataOut.utctime) |
|
627 | avgdata, avgdatatime = self.integrateByStride(dataOut.data, dataOut.utctime) | |
| 628 |
|
628 | |||
| 629 |
|
629 | |||
| 630 | # dataOut.timeInterval *= n |
|
630 | # dataOut.timeInterval *= n | |
| 631 | dataOut.flagNoData = True |
|
631 | dataOut.flagNoData = True | |
| 632 |
|
632 | |||
| 633 | if self.__dataReady: |
|
633 | if self.__dataReady: | |
| 634 | dataOut.data = avgdata |
|
634 | dataOut.data = avgdata | |
| 635 | dataOut.nCohInt *= self.n |
|
635 | dataOut.nCohInt *= self.n | |
| 636 | dataOut.utctime = avgdatatime |
|
636 | dataOut.utctime = avgdatatime | |
| 637 | # print avgdata, avgdatatime |
|
637 | # print avgdata, avgdatatime | |
| 638 | # raise |
|
638 | # raise | |
| 639 | # dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt |
|
639 | # dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt | |
| 640 | dataOut.flagNoData = False |
|
640 | dataOut.flagNoData = False | |
| 641 |
|
641 | |||
| 642 | class Decoder(Operation): |
|
642 | class Decoder(Operation): | |
| 643 |
|
643 | |||
| 644 | isConfig = False |
|
644 | isConfig = False | |
| 645 | __profIndex = 0 |
|
645 | __profIndex = 0 | |
| 646 |
|
646 | |||
| 647 | code = None |
|
647 | code = None | |
| 648 |
|
648 | |||
| 649 | nCode = None |
|
649 | nCode = None | |
| 650 | nBaud = None |
|
650 | nBaud = None | |
| 651 |
|
651 | |||
| 652 | def __init__(self, **kwargs): |
|
652 | def __init__(self, **kwargs): | |
| 653 |
|
653 | |||
| 654 | Operation.__init__(self, **kwargs) |
|
654 | Operation.__init__(self, **kwargs) | |
| 655 |
|
655 | |||
| 656 | self.times = None |
|
656 | self.times = None | |
| 657 | self.osamp = None |
|
657 | self.osamp = None | |
| 658 | # self.__setValues = False |
|
658 | # self.__setValues = False | |
| 659 | self.isConfig = False |
|
659 | self.isConfig = False | |
| 660 |
|
660 | |||
| 661 | def setup(self, code, osamp, dataOut): |
|
661 | def setup(self, code, osamp, dataOut): | |
| 662 |
|
662 | |||
| 663 | self.__profIndex = 0 |
|
663 | self.__profIndex = 0 | |
| 664 |
|
664 | |||
| 665 | self.code = code |
|
665 | self.code = code | |
| 666 |
|
666 | |||
| 667 | self.nCode = len(code) |
|
667 | self.nCode = len(code) | |
| 668 | self.nBaud = len(code[0]) |
|
668 | self.nBaud = len(code[0]) | |
| 669 |
|
669 | |||
| 670 | if (osamp != None) and (osamp >1): |
|
670 | if (osamp != None) and (osamp >1): | |
| 671 | self.osamp = osamp |
|
671 | self.osamp = osamp | |
| 672 | self.code = numpy.repeat(code, repeats=self.osamp, axis=1) |
|
672 | self.code = numpy.repeat(code, repeats=self.osamp, axis=1) | |
| 673 | self.nBaud = self.nBaud*self.osamp |
|
673 | self.nBaud = self.nBaud*self.osamp | |
| 674 |
|
674 | |||
| 675 | self.__nChannels = dataOut.nChannels |
|
675 | self.__nChannels = dataOut.nChannels | |
| 676 | self.__nProfiles = dataOut.nProfiles |
|
676 | self.__nProfiles = dataOut.nProfiles | |
| 677 | self.__nHeis = dataOut.nHeights |
|
677 | self.__nHeis = dataOut.nHeights | |
| 678 |
|
678 | |||
| 679 | if self.__nHeis < self.nBaud: |
|
679 | if self.__nHeis < self.nBaud: | |
| 680 | 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) | |
| 681 |
|
681 | |||
| 682 | #Frequency |
|
682 | #Frequency | |
| 683 | __codeBuffer = numpy.zeros((self.nCode, self.__nHeis), dtype=numpy.complex) |
|
683 | __codeBuffer = numpy.zeros((self.nCode, self.__nHeis), dtype=numpy.complex) | |
| 684 |
|
684 | |||
| 685 | __codeBuffer[:,0:self.nBaud] = self.code |
|
685 | __codeBuffer[:,0:self.nBaud] = self.code | |
| 686 |
|
686 | |||
| 687 | self.fft_code = numpy.conj(numpy.fft.fft(__codeBuffer, axis=1)) |
|
687 | self.fft_code = numpy.conj(numpy.fft.fft(__codeBuffer, axis=1)) | |
| 688 |
|
688 | |||
| 689 | if dataOut.flagDataAsBlock: |
|
689 | if dataOut.flagDataAsBlock: | |
| 690 |
|
690 | |||
| 691 | self.ndatadec = self.__nHeis #- self.nBaud + 1 |
|
691 | self.ndatadec = self.__nHeis #- self.nBaud + 1 | |
| 692 |
|
692 | |||
| 693 | 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) | |
| 694 |
|
694 | |||
| 695 | else: |
|
695 | else: | |
| 696 |
|
696 | |||
| 697 | #Time |
|
697 | #Time | |
| 698 | self.ndatadec = self.__nHeis #- self.nBaud + 1 |
|
698 | self.ndatadec = self.__nHeis #- self.nBaud + 1 | |
| 699 |
|
699 | |||
| 700 | self.datadecTime = numpy.zeros((self.__nChannels, self.ndatadec), dtype=numpy.complex) |
|
700 | self.datadecTime = numpy.zeros((self.__nChannels, self.ndatadec), dtype=numpy.complex) | |
| 701 |
|
701 | |||
| 702 | def __convolutionInFreq(self, data): |
|
702 | def __convolutionInFreq(self, data): | |
| 703 |
|
703 | |||
| 704 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) |
|
704 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) | |
| 705 |
|
705 | |||
| 706 | fft_data = numpy.fft.fft(data, axis=1) |
|
706 | fft_data = numpy.fft.fft(data, axis=1) | |
| 707 |
|
707 | |||
| 708 | conv = fft_data*fft_code |
|
708 | conv = fft_data*fft_code | |
| 709 |
|
709 | |||
| 710 | data = numpy.fft.ifft(conv,axis=1) |
|
710 | data = numpy.fft.ifft(conv,axis=1) | |
| 711 |
|
711 | |||
| 712 | return data |
|
712 | return data | |
| 713 |
|
713 | |||
| 714 | def __convolutionInFreqOpt(self, data): |
|
714 | def __convolutionInFreqOpt(self, data): | |
| 715 |
|
715 | |||
| 716 | raise NotImplementedError |
|
716 | raise NotImplementedError | |
| 717 |
|
717 | |||
| 718 | def __convolutionInTime(self, data): |
|
718 | def __convolutionInTime(self, data): | |
| 719 |
|
719 | |||
| 720 | code = self.code[self.__profIndex] |
|
720 | code = self.code[self.__profIndex] | |
| 721 | for i in range(self.__nChannels): |
|
721 | for i in range(self.__nChannels): | |
| 722 | 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:] | |
| 723 |
|
723 | |||
| 724 | return self.datadecTime |
|
724 | return self.datadecTime | |
| 725 |
|
725 | |||
| 726 | def __convolutionByBlockInTime(self, data): |
|
726 | def __convolutionByBlockInTime(self, data): | |
| 727 |
|
727 | |||
| 728 | repetitions = self.__nProfiles / self.nCode |
|
728 | repetitions = self.__nProfiles / self.nCode | |
| 729 |
|
729 | |||
| 730 | 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)) | |
| 731 | junk = junk.flatten() |
|
731 | junk = junk.flatten() | |
| 732 | code_block = numpy.reshape(junk, (self.nCode*repetitions, self.nBaud)) |
|
732 | code_block = numpy.reshape(junk, (self.nCode*repetitions, self.nBaud)) | |
| 733 | profilesList = xrange(self.__nProfiles) |
|
733 | profilesList = xrange(self.__nProfiles) | |
| 734 |
|
734 | |||
| 735 | for i in range(self.__nChannels): |
|
735 | for i in range(self.__nChannels): | |
| 736 | for j in profilesList: |
|
736 | for j in profilesList: | |
| 737 | 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:] | |
| 738 | return self.datadecTime |
|
738 | return self.datadecTime | |
| 739 |
|
739 | |||
| 740 | def __convolutionByBlockInFreq(self, data): |
|
740 | def __convolutionByBlockInFreq(self, data): | |
| 741 |
|
741 | |||
| 742 | raise NotImplementedError, "Decoder by frequency fro Blocks not implemented" |
|
742 | raise NotImplementedError, "Decoder by frequency fro Blocks not implemented" | |
| 743 |
|
743 | |||
| 744 |
|
744 | |||
| 745 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) |
|
745 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) | |
| 746 |
|
746 | |||
| 747 | fft_data = numpy.fft.fft(data, axis=2) |
|
747 | fft_data = numpy.fft.fft(data, axis=2) | |
| 748 |
|
748 | |||
| 749 | conv = fft_data*fft_code |
|
749 | conv = fft_data*fft_code | |
| 750 |
|
750 | |||
| 751 | data = numpy.fft.ifft(conv,axis=2) |
|
751 | data = numpy.fft.ifft(conv,axis=2) | |
| 752 |
|
752 | |||
| 753 | return data |
|
753 | return data | |
| 754 |
|
754 | |||
| 755 |
|
755 | |||
| 756 | 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): | |
| 757 |
|
757 | |||
| 758 | if dataOut.flagDecodeData: |
|
758 | if dataOut.flagDecodeData: | |
| 759 | print "This data is already decoded, recoding again ..." |
|
759 | print "This data is already decoded, recoding again ..." | |
| 760 |
|
760 | |||
| 761 | if not self.isConfig: |
|
761 | if not self.isConfig: | |
| 762 |
|
762 | |||
| 763 | if code is None: |
|
763 | if code is None: | |
| 764 | if dataOut.code is None: |
|
764 | if dataOut.code is None: | |
| 765 | 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 | |
| 766 |
|
766 | |||
| 767 | code = dataOut.code |
|
767 | code = dataOut.code | |
| 768 | else: |
|
768 | else: | |
| 769 | code = numpy.array(code).reshape(nCode,nBaud) |
|
769 | code = numpy.array(code).reshape(nCode,nBaud) | |
| 770 | self.setup(code, osamp, dataOut) |
|
770 | self.setup(code, osamp, dataOut) | |
| 771 |
|
771 | |||
| 772 | self.isConfig = True |
|
772 | self.isConfig = True | |
| 773 |
|
773 | |||
| 774 | if mode == 3: |
|
774 | if mode == 3: | |
| 775 | 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) | |
| 776 |
|
776 | |||
| 777 | if times != None: |
|
777 | if times != None: | |
| 778 | 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") | |
| 779 |
|
779 | |||
| 780 | if self.code is None: |
|
780 | if self.code is None: | |
| 781 | print "Fail decoding: Code is not defined." |
|
781 | print "Fail decoding: Code is not defined." | |
| 782 | return |
|
782 | return | |
| 783 |
|
783 | |||
| 784 | self.__nProfiles = dataOut.nProfiles |
|
784 | self.__nProfiles = dataOut.nProfiles | |
| 785 | datadec = None |
|
785 | datadec = None | |
| 786 |
|
786 | |||
| 787 | if mode == 3: |
|
787 | if mode == 3: | |
| 788 | mode = 0 |
|
788 | mode = 0 | |
| 789 |
|
789 | |||
| 790 | if dataOut.flagDataAsBlock: |
|
790 | if dataOut.flagDataAsBlock: | |
| 791 | """ |
|
791 | """ | |
| 792 | Decoding when data have been read as block, |
|
792 | Decoding when data have been read as block, | |
| 793 | """ |
|
793 | """ | |
| 794 |
|
794 | |||
| 795 | if mode == 0: |
|
795 | if mode == 0: | |
| 796 | datadec = self.__convolutionByBlockInTime(dataOut.data) |
|
796 | datadec = self.__convolutionByBlockInTime(dataOut.data) | |
| 797 | if mode == 1: |
|
797 | if mode == 1: | |
| 798 | datadec = self.__convolutionByBlockInFreq(dataOut.data) |
|
798 | datadec = self.__convolutionByBlockInFreq(dataOut.data) | |
| 799 | else: |
|
799 | else: | |
| 800 | """ |
|
800 | """ | |
| 801 | Decoding when data have been read profile by profile |
|
801 | Decoding when data have been read profile by profile | |
| 802 | """ |
|
802 | """ | |
| 803 | if mode == 0: |
|
803 | if mode == 0: | |
| 804 | datadec = self.__convolutionInTime(dataOut.data) |
|
804 | datadec = self.__convolutionInTime(dataOut.data) | |
| 805 |
|
805 | |||
| 806 | if mode == 1: |
|
806 | if mode == 1: | |
| 807 | datadec = self.__convolutionInFreq(dataOut.data) |
|
807 | datadec = self.__convolutionInFreq(dataOut.data) | |
| 808 |
|
808 | |||
| 809 | if mode == 2: |
|
809 | if mode == 2: | |
| 810 | datadec = self.__convolutionInFreqOpt(dataOut.data) |
|
810 | datadec = self.__convolutionInFreqOpt(dataOut.data) | |
| 811 |
|
811 | |||
| 812 | if datadec is None: |
|
812 | if datadec is None: | |
| 813 | 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 | |
| 814 |
|
814 | |||
| 815 | dataOut.code = self.code |
|
815 | dataOut.code = self.code | |
| 816 | dataOut.nCode = self.nCode |
|
816 | dataOut.nCode = self.nCode | |
| 817 | dataOut.nBaud = self.nBaud |
|
817 | dataOut.nBaud = self.nBaud | |
| 818 |
|
818 | |||
| 819 | dataOut.data = datadec |
|
819 | dataOut.data = datadec | |
| 820 |
|
820 | |||
| 821 | dataOut.heightList = dataOut.heightList[0:datadec.shape[-1]] |
|
821 | dataOut.heightList = dataOut.heightList[0:datadec.shape[-1]] | |
| 822 |
|
822 | |||
| 823 | dataOut.flagDecodeData = True #asumo q la data esta decodificada |
|
823 | dataOut.flagDecodeData = True #asumo q la data esta decodificada | |
| 824 |
|
824 | |||
| 825 | if self.__profIndex == self.nCode-1: |
|
825 | if self.__profIndex == self.nCode-1: | |
| 826 | self.__profIndex = 0 |
|
826 | self.__profIndex = 0 | |
| 827 | return 1 |
|
827 | return 1 | |
| 828 |
|
828 | |||
| 829 | self.__profIndex += 1 |
|
829 | self.__profIndex += 1 | |
| 830 |
|
830 | |||
| 831 | return 1 |
|
831 | return 1 | |
| 832 | # dataOut.flagDeflipData = True #asumo q la data no esta sin flip |
|
832 | # dataOut.flagDeflipData = True #asumo q la data no esta sin flip | |
| 833 |
|
833 | |||
| 834 |
|
834 | |||
| 835 | class ProfileConcat(Operation): |
|
835 | class ProfileConcat(Operation): | |
| 836 |
|
836 | |||
| 837 | isConfig = False |
|
837 | isConfig = False | |
| 838 | buffer = None |
|
838 | buffer = None | |
| 839 | concat_m =None |
|
839 | concat_m =None | |
| 840 |
|
840 | |||
| 841 | def __init__(self, **kwargs): |
|
841 | def __init__(self, **kwargs): | |
| 842 |
|
842 | |||
| 843 | Operation.__init__(self, **kwargs) |
|
843 | Operation.__init__(self, **kwargs) | |
| 844 | self.profileIndex = 0 |
|
844 | self.profileIndex = 0 | |
| 845 |
|
845 | |||
| 846 | def reset(self): |
|
846 | def reset(self): | |
| 847 | self.buffer = numpy.zeros_like(self.buffer) |
|
847 | self.buffer = numpy.zeros_like(self.buffer) | |
| 848 | self.start_index = 0 |
|
848 | self.start_index = 0 | |
| 849 | self.times = 1 |
|
849 | self.times = 1 | |
| 850 |
|
850 | |||
| 851 | def setup(self, data, m, n=1): |
|
851 | def setup(self, data, m, n=1): | |
| 852 | self.buffer = numpy.zeros((data.shape[0],data.shape[1]*m),dtype=type(data[0,0])) |
|
852 | self.buffer = numpy.zeros((data.shape[0],data.shape[1]*m),dtype=type(data[0,0])) | |
| 853 | self.nHeights = data.shape[1]#.nHeights |
|
853 | self.nHeights = data.shape[1]#.nHeights | |
| 854 | self.start_index = 0 |
|
854 | self.start_index = 0 | |
| 855 | self.times = 1 |
|
855 | self.times = 1 | |
| 856 |
|
856 | |||
| 857 | def concat(self, data): |
|
857 | def concat(self, data): | |
| 858 |
|
858 | |||
| 859 | self.buffer[:,self.start_index:self.nHeights*self.times] = data.copy() |
|
859 | self.buffer[:,self.start_index:self.nHeights*self.times] = data.copy() | |
| 860 | self.start_index = self.start_index + self.nHeights |
|
860 | self.start_index = self.start_index + self.nHeights | |
| 861 |
|
861 | |||
| 862 | def run(self, dataOut, m): |
|
862 | def run(self, dataOut, m): | |
| 863 |
|
863 | |||
| 864 | self.concat_m= m |
|
864 | self.concat_m= m | |
| 865 | dataOut.flagNoData = True |
|
865 | dataOut.flagNoData = True | |
| 866 |
|
866 | |||
| 867 | if not self.isConfig: |
|
867 | if not self.isConfig: | |
| 868 | self.setup(dataOut.data, m, 1) |
|
868 | self.setup(dataOut.data, m, 1) | |
| 869 | self.isConfig = True |
|
869 | self.isConfig = True | |
| 870 |
|
870 | |||
| 871 | if dataOut.flagDataAsBlock: |
|
871 | if dataOut.flagDataAsBlock: | |
| 872 | raise ValueError, "ProfileConcat can only be used when voltage have been read profile by profile, getBlock = False" |
|
872 | raise ValueError, "ProfileConcat can only be used when voltage have been read profile by profile, getBlock = False" | |
| 873 |
|
873 | |||
| 874 | else: |
|
874 | else: | |
| 875 | self.concat(dataOut.data) |
|
875 | self.concat(dataOut.data) | |
| 876 | self.times += 1 |
|
876 | self.times += 1 | |
| 877 | if self.times > m: |
|
877 | if self.times > m: | |
| 878 | dataOut.data = self.buffer |
|
878 | dataOut.data = self.buffer | |
| 879 | self.reset() |
|
879 | self.reset() | |
| 880 | dataOut.flagNoData = False |
|
880 | dataOut.flagNoData = False | |
| 881 | # se deben actualizar mas propiedades del header y del objeto dataOut, por ejemplo, las alturas |
|
881 | # se deben actualizar mas propiedades del header y del objeto dataOut, por ejemplo, las alturas | |
| 882 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
882 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 883 | xf = dataOut.heightList[0] + dataOut.nHeights * deltaHeight * m |
|
883 | xf = dataOut.heightList[0] + dataOut.nHeights * deltaHeight * m | |
| 884 | dataOut.heightList = numpy.arange(dataOut.heightList[0], xf, deltaHeight) |
|
884 | dataOut.heightList = numpy.arange(dataOut.heightList[0], xf, deltaHeight) | |
| 885 | dataOut.ippSeconds *= m |
|
885 | dataOut.ippSeconds *= m | |
| 886 | dataOut.concat_m = int(m) |
|
886 | dataOut.concat_m = int(m) | |
| 887 |
|
887 | |||
| 888 | class ProfileSelector(Operation): |
|
888 | class ProfileSelector(Operation): | |
| 889 |
|
889 | |||
| 890 | profileIndex = None |
|
890 | profileIndex = None | |
| 891 | # Tamanho total de los perfiles |
|
891 | # Tamanho total de los perfiles | |
| 892 | nProfiles = None |
|
892 | nProfiles = None | |
| 893 |
|
893 | |||
| 894 | def __init__(self, **kwargs): |
|
894 | def __init__(self, **kwargs): | |
| 895 |
|
895 | |||
| 896 | Operation.__init__(self, **kwargs) |
|
896 | Operation.__init__(self, **kwargs) | |
| 897 | self.profileIndex = 0 |
|
897 | self.profileIndex = 0 | |
| 898 |
|
898 | |||
| 899 | def incProfileIndex(self): |
|
899 | def incProfileIndex(self): | |
| 900 |
|
900 | |||
| 901 | self.profileIndex += 1 |
|
901 | self.profileIndex += 1 | |
| 902 |
|
902 | |||
| 903 | if self.profileIndex >= self.nProfiles: |
|
903 | if self.profileIndex >= self.nProfiles: | |
| 904 | self.profileIndex = 0 |
|
904 | self.profileIndex = 0 | |
| 905 |
|
905 | |||
| 906 | def isThisProfileInRange(self, profileIndex, minIndex, maxIndex): |
|
906 | def isThisProfileInRange(self, profileIndex, minIndex, maxIndex): | |
| 907 |
|
907 | |||
| 908 | if profileIndex < minIndex: |
|
908 | if profileIndex < minIndex: | |
| 909 | return False |
|
909 | return False | |
| 910 |
|
910 | |||
| 911 | if profileIndex > maxIndex: |
|
911 | if profileIndex > maxIndex: | |
| 912 | return False |
|
912 | return False | |
| 913 |
|
913 | |||
| 914 | return True |
|
914 | return True | |
| 915 |
|
915 | |||
| 916 | def isThisProfileInList(self, profileIndex, profileList): |
|
916 | def isThisProfileInList(self, profileIndex, profileList): | |
| 917 |
|
917 | |||
| 918 | if profileIndex not in profileList: |
|
918 | if profileIndex not in profileList: | |
| 919 | return False |
|
919 | return False | |
| 920 |
|
920 | |||
| 921 | return True |
|
921 | return True | |
| 922 |
|
922 | |||
| 923 | def run(self, dataOut, profileList=None, profileRangeList=None, beam=None, byblock=False, rangeList = None, nProfiles=None): |
|
923 | def run(self, dataOut, profileList=None, profileRangeList=None, beam=None, byblock=False, rangeList = None, nProfiles=None): | |
| 924 |
|
924 | |||
| 925 | """ |
|
925 | """ | |
| 926 | ProfileSelector: |
|
926 | ProfileSelector: | |
| 927 |
|
927 | |||
| 928 | Inputs: |
|
928 | Inputs: | |
| 929 | profileList : Index of profiles selected. Example: profileList = (0,1,2,7,8) |
|
929 | profileList : Index of profiles selected. Example: profileList = (0,1,2,7,8) | |
| 930 |
|
930 | |||
| 931 | profileRangeList : Minimum and maximum profile indexes. Example: profileRangeList = (4, 30) |
|
931 | profileRangeList : Minimum and maximum profile indexes. Example: profileRangeList = (4, 30) | |
| 932 |
|
932 | |||
| 933 | rangeList : List of profile ranges. Example: rangeList = ((4, 30), (32, 64), (128, 256)) |
|
933 | rangeList : List of profile ranges. Example: rangeList = ((4, 30), (32, 64), (128, 256)) | |
| 934 |
|
934 | |||
| 935 | """ |
|
935 | """ | |
| 936 | print "HOLA MUNDO CRUEL" |
|
936 | #print "HOLA MUNDO CRUEL" | |
| 937 | if rangeList is not None: |
|
937 | if rangeList is not None: | |
| 938 | if type(rangeList[0]) not in (tuple, list): |
|
938 | if type(rangeList[0]) not in (tuple, list): | |
| 939 | rangeList = [rangeList] |
|
939 | rangeList = [rangeList] | |
| 940 |
|
940 | |||
| 941 | dataOut.flagNoData = True |
|
941 | dataOut.flagNoData = True | |
| 942 |
|
942 | |||
| 943 | if dataOut.flagDataAsBlock: |
|
943 | if dataOut.flagDataAsBlock: | |
| 944 | """ |
|
944 | """ | |
| 945 | data dimension = [nChannels, nProfiles, nHeis] |
|
945 | data dimension = [nChannels, nProfiles, nHeis] | |
| 946 | """ |
|
946 | """ | |
| 947 | if profileList != None: |
|
947 | if profileList != None: | |
| 948 | dataOut.data = dataOut.data[:,profileList,:] |
|
948 | dataOut.data = dataOut.data[:,profileList,:] | |
| 949 |
|
949 | |||
| 950 | if profileRangeList != None: |
|
950 | if profileRangeList != None: | |
| 951 | minIndex = profileRangeList[0] |
|
951 | minIndex = profileRangeList[0] | |
| 952 | maxIndex = profileRangeList[1] |
|
952 | maxIndex = profileRangeList[1] | |
| 953 | profileList = range(minIndex, maxIndex+1) |
|
953 | profileList = range(minIndex, maxIndex+1) | |
| 954 |
|
954 | |||
| 955 | dataOut.data = dataOut.data[:,minIndex:maxIndex+1,:] |
|
955 | dataOut.data = dataOut.data[:,minIndex:maxIndex+1,:] | |
| 956 |
|
956 | |||
| 957 | if rangeList != None: |
|
957 | if rangeList != None: | |
| 958 |
|
958 | |||
| 959 | profileList = [] |
|
959 | profileList = [] | |
| 960 |
|
960 | |||
| 961 | for thisRange in rangeList: |
|
961 | for thisRange in rangeList: | |
| 962 | minIndex = thisRange[0] |
|
962 | minIndex = thisRange[0] | |
| 963 | maxIndex = thisRange[1] |
|
963 | maxIndex = thisRange[1] | |
| 964 |
|
964 | |||
| 965 | profileList.extend(range(minIndex, maxIndex+1)) |
|
965 | profileList.extend(range(minIndex, maxIndex+1)) | |
| 966 |
|
966 | |||
| 967 | dataOut.data = dataOut.data[:,profileList,:] |
|
967 | dataOut.data = dataOut.data[:,profileList,:] | |
| 968 |
|
968 | |||
| 969 | dataOut.nProfiles = len(profileList) |
|
969 | dataOut.nProfiles = len(profileList) | |
| 970 | dataOut.profileIndex = dataOut.nProfiles - 1 |
|
970 | dataOut.profileIndex = dataOut.nProfiles - 1 | |
| 971 | dataOut.flagNoData = False |
|
971 | dataOut.flagNoData = False | |
| 972 |
|
972 | |||
| 973 | return True |
|
973 | return True | |
| 974 |
|
974 | |||
| 975 | """ |
|
975 | """ | |
| 976 | data dimension = [nChannels, nHeis] |
|
976 | data dimension = [nChannels, nHeis] | |
| 977 | """ |
|
977 | """ | |
| 978 |
|
978 | |||
| 979 | if profileList != None: |
|
979 | if profileList != None: | |
| 980 |
|
980 | |||
| 981 | if self.isThisProfileInList(dataOut.profileIndex, profileList): |
|
981 | if self.isThisProfileInList(dataOut.profileIndex, profileList): | |
| 982 |
|
982 | |||
| 983 | self.nProfiles = len(profileList) |
|
983 | self.nProfiles = len(profileList) | |
| 984 | dataOut.nProfiles = self.nProfiles |
|
984 | dataOut.nProfiles = self.nProfiles | |
| 985 | dataOut.profileIndex = self.profileIndex |
|
985 | dataOut.profileIndex = self.profileIndex | |
| 986 | dataOut.flagNoData = False |
|
986 | dataOut.flagNoData = False | |
| 987 |
|
987 | |||
| 988 | self.incProfileIndex() |
|
988 | self.incProfileIndex() | |
| 989 | return True |
|
989 | return True | |
| 990 |
|
990 | |||
| 991 | if profileRangeList != None: |
|
991 | if profileRangeList != None: | |
| 992 |
|
992 | |||
| 993 | minIndex = profileRangeList[0] |
|
993 | minIndex = profileRangeList[0] | |
| 994 | maxIndex = profileRangeList[1] |
|
994 | maxIndex = profileRangeList[1] | |
| 995 |
|
995 | |||
| 996 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): |
|
996 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): | |
| 997 |
|
997 | |||
| 998 | self.nProfiles = maxIndex - minIndex + 1 |
|
998 | self.nProfiles = maxIndex - minIndex + 1 | |
| 999 | dataOut.nProfiles = self.nProfiles |
|
999 | dataOut.nProfiles = self.nProfiles | |
| 1000 | dataOut.profileIndex = self.profileIndex |
|
1000 | dataOut.profileIndex = self.profileIndex | |
| 1001 | dataOut.flagNoData = False |
|
1001 | dataOut.flagNoData = False | |
| 1002 |
|
1002 | |||
| 1003 | self.incProfileIndex() |
|
1003 | self.incProfileIndex() | |
| 1004 | return True |
|
1004 | return True | |
| 1005 |
|
1005 | |||
| 1006 | if rangeList != None: |
|
1006 | if rangeList != None: | |
| 1007 |
|
1007 | |||
| 1008 | nProfiles = 0 |
|
1008 | nProfiles = 0 | |
| 1009 |
|
1009 | |||
| 1010 | for thisRange in rangeList: |
|
1010 | for thisRange in rangeList: | |
| 1011 | minIndex = thisRange[0] |
|
1011 | minIndex = thisRange[0] | |
| 1012 | maxIndex = thisRange[1] |
|
1012 | maxIndex = thisRange[1] | |
| 1013 |
|
1013 | |||
| 1014 | nProfiles += maxIndex - minIndex + 1 |
|
1014 | nProfiles += maxIndex - minIndex + 1 | |
| 1015 |
|
1015 | |||
| 1016 | for thisRange in rangeList: |
|
1016 | for thisRange in rangeList: | |
| 1017 |
|
1017 | |||
| 1018 | minIndex = thisRange[0] |
|
1018 | minIndex = thisRange[0] | |
| 1019 | maxIndex = thisRange[1] |
|
1019 | maxIndex = thisRange[1] | |
| 1020 |
|
1020 | |||
| 1021 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): |
|
1021 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): | |
| 1022 |
|
1022 | |||
| 1023 | self.nProfiles = nProfiles |
|
1023 | self.nProfiles = nProfiles | |
| 1024 | dataOut.nProfiles = self.nProfiles |
|
1024 | dataOut.nProfiles = self.nProfiles | |
| 1025 | dataOut.profileIndex = self.profileIndex |
|
1025 | dataOut.profileIndex = self.profileIndex | |
| 1026 | dataOut.flagNoData = False |
|
1026 | dataOut.flagNoData = False | |
| 1027 |
|
1027 | |||
| 1028 | self.incProfileIndex() |
|
1028 | self.incProfileIndex() | |
| 1029 |
|
1029 | |||
| 1030 | break |
|
1030 | break | |
| 1031 |
|
1031 | |||
| 1032 | return True |
|
1032 | return True | |
| 1033 |
|
1033 | |||
| 1034 |
|
1034 | |||
| 1035 | if beam != None: #beam is only for AMISR data |
|
1035 | if beam != None: #beam is only for AMISR data | |
| 1036 | if self.isThisProfileInList(dataOut.profileIndex, dataOut.beamRangeDict[beam]): |
|
1036 | if self.isThisProfileInList(dataOut.profileIndex, dataOut.beamRangeDict[beam]): | |
| 1037 | dataOut.flagNoData = False |
|
1037 | dataOut.flagNoData = False | |
| 1038 | dataOut.profileIndex = self.profileIndex |
|
1038 | dataOut.profileIndex = self.profileIndex | |
| 1039 |
|
1039 | |||
| 1040 | self.incProfileIndex() |
|
1040 | self.incProfileIndex() | |
| 1041 |
|
1041 | |||
| 1042 | return True |
|
1042 | return True | |
| 1043 |
|
1043 | |||
| 1044 | raise ValueError, "ProfileSelector needs profileList, profileRangeList or rangeList parameter" |
|
1044 | raise ValueError, "ProfileSelector needs profileList, profileRangeList or rangeList parameter" | |
| 1045 |
|
1045 | |||
| 1046 | return False |
|
1046 | return False | |
| 1047 |
|
1047 | |||
| 1048 | class Reshaper(Operation): |
|
1048 | class Reshaper(Operation): | |
| 1049 |
|
1049 | |||
| 1050 | def __init__(self, **kwargs): |
|
1050 | def __init__(self, **kwargs): | |
| 1051 |
|
1051 | |||
| 1052 | Operation.__init__(self, **kwargs) |
|
1052 | Operation.__init__(self, **kwargs) | |
| 1053 |
|
1053 | |||
| 1054 | self.__buffer = None |
|
1054 | self.__buffer = None | |
| 1055 | self.__nitems = 0 |
|
1055 | self.__nitems = 0 | |
| 1056 |
|
1056 | |||
| 1057 | def __appendProfile(self, dataOut, nTxs): |
|
1057 | def __appendProfile(self, dataOut, nTxs): | |
| 1058 |
|
1058 | |||
| 1059 | if self.__buffer is None: |
|
1059 | if self.__buffer is None: | |
| 1060 | shape = (dataOut.nChannels, int(dataOut.nHeights/nTxs) ) |
|
1060 | shape = (dataOut.nChannels, int(dataOut.nHeights/nTxs) ) | |
| 1061 | self.__buffer = numpy.empty(shape, dtype = dataOut.data.dtype) |
|
1061 | self.__buffer = numpy.empty(shape, dtype = dataOut.data.dtype) | |
| 1062 |
|
1062 | |||
| 1063 | ini = dataOut.nHeights * self.__nitems |
|
1063 | ini = dataOut.nHeights * self.__nitems | |
| 1064 | end = ini + dataOut.nHeights |
|
1064 | end = ini + dataOut.nHeights | |
| 1065 |
|
1065 | |||
| 1066 | self.__buffer[:, ini:end] = dataOut.data |
|
1066 | self.__buffer[:, ini:end] = dataOut.data | |
| 1067 |
|
1067 | |||
| 1068 | self.__nitems += 1 |
|
1068 | self.__nitems += 1 | |
| 1069 |
|
1069 | |||
| 1070 | return int(self.__nitems*nTxs) |
|
1070 | return int(self.__nitems*nTxs) | |
| 1071 |
|
1071 | |||
| 1072 | def __getBuffer(self): |
|
1072 | def __getBuffer(self): | |
| 1073 |
|
1073 | |||
| 1074 | if self.__nitems == int(1./self.__nTxs): |
|
1074 | if self.__nitems == int(1./self.__nTxs): | |
| 1075 |
|
1075 | |||
| 1076 | self.__nitems = 0 |
|
1076 | self.__nitems = 0 | |
| 1077 |
|
1077 | |||
| 1078 | return self.__buffer.copy() |
|
1078 | return self.__buffer.copy() | |
| 1079 |
|
1079 | |||
| 1080 | return None |
|
1080 | return None | |
| 1081 |
|
1081 | |||
| 1082 | def __checkInputs(self, dataOut, shape, nTxs): |
|
1082 | def __checkInputs(self, dataOut, shape, nTxs): | |
| 1083 |
|
1083 | |||
| 1084 | if shape is None and nTxs is None: |
|
1084 | if shape is None and nTxs is None: | |
| 1085 | raise ValueError, "Reshaper: shape of factor should be defined" |
|
1085 | raise ValueError, "Reshaper: shape of factor should be defined" | |
| 1086 |
|
1086 | |||
| 1087 | if nTxs: |
|
1087 | if nTxs: | |
| 1088 | if nTxs < 0: |
|
1088 | if nTxs < 0: | |
| 1089 | raise ValueError, "nTxs should be greater than 0" |
|
1089 | raise ValueError, "nTxs should be greater than 0" | |
| 1090 |
|
1090 | |||
| 1091 | if nTxs < 1 and dataOut.nProfiles % (1./nTxs) != 0: |
|
1091 | if nTxs < 1 and dataOut.nProfiles % (1./nTxs) != 0: | |
| 1092 | raise ValueError, "nProfiles= %d is not divisibled by (1./nTxs) = %f" %(dataOut.nProfiles, (1./nTxs)) |
|
1092 | raise ValueError, "nProfiles= %d is not divisibled by (1./nTxs) = %f" %(dataOut.nProfiles, (1./nTxs)) | |
| 1093 |
|
1093 | |||
| 1094 | shape = [dataOut.nChannels, dataOut.nProfiles*nTxs, dataOut.nHeights/nTxs] |
|
1094 | shape = [dataOut.nChannels, dataOut.nProfiles*nTxs, dataOut.nHeights/nTxs] | |
| 1095 |
|
1095 | |||
| 1096 | return shape, nTxs |
|
1096 | return shape, nTxs | |
| 1097 |
|
1097 | |||
| 1098 | if len(shape) != 2 and len(shape) != 3: |
|
1098 | if len(shape) != 2 and len(shape) != 3: | |
| 1099 | 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) |
|
1099 | 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) | |
| 1100 |
|
1100 | |||
| 1101 | if len(shape) == 2: |
|
1101 | if len(shape) == 2: | |
| 1102 | shape_tuple = [dataOut.nChannels] |
|
1102 | shape_tuple = [dataOut.nChannels] | |
| 1103 | shape_tuple.extend(shape) |
|
1103 | shape_tuple.extend(shape) | |
| 1104 | else: |
|
1104 | else: | |
| 1105 | shape_tuple = list(shape) |
|
1105 | shape_tuple = list(shape) | |
| 1106 |
|
1106 | |||
| 1107 | nTxs = 1.0*shape_tuple[1]/dataOut.nProfiles |
|
1107 | nTxs = 1.0*shape_tuple[1]/dataOut.nProfiles | |
| 1108 |
|
1108 | |||
| 1109 | return shape_tuple, nTxs |
|
1109 | return shape_tuple, nTxs | |
| 1110 |
|
1110 | |||
| 1111 | def run(self, dataOut, shape=None, nTxs=None): |
|
1111 | def run(self, dataOut, shape=None, nTxs=None): | |
| 1112 |
|
1112 | |||
| 1113 | shape_tuple, self.__nTxs = self.__checkInputs(dataOut, shape, nTxs) |
|
1113 | shape_tuple, self.__nTxs = self.__checkInputs(dataOut, shape, nTxs) | |
| 1114 |
|
1114 | |||
| 1115 | dataOut.flagNoData = True |
|
1115 | dataOut.flagNoData = True | |
| 1116 | profileIndex = None |
|
1116 | profileIndex = None | |
| 1117 |
|
1117 | |||
| 1118 | if dataOut.flagDataAsBlock: |
|
1118 | if dataOut.flagDataAsBlock: | |
| 1119 |
|
1119 | |||
| 1120 | dataOut.data = numpy.reshape(dataOut.data, shape_tuple) |
|
1120 | dataOut.data = numpy.reshape(dataOut.data, shape_tuple) | |
| 1121 | dataOut.flagNoData = False |
|
1121 | dataOut.flagNoData = False | |
| 1122 |
|
1122 | |||
| 1123 | profileIndex = int(dataOut.nProfiles*self.__nTxs) - 1 |
|
1123 | profileIndex = int(dataOut.nProfiles*self.__nTxs) - 1 | |
| 1124 |
|
1124 | |||
| 1125 | else: |
|
1125 | else: | |
| 1126 |
|
1126 | |||
| 1127 | if self.__nTxs < 1: |
|
1127 | if self.__nTxs < 1: | |
| 1128 |
|
1128 | |||
| 1129 | self.__appendProfile(dataOut, self.__nTxs) |
|
1129 | self.__appendProfile(dataOut, self.__nTxs) | |
| 1130 | new_data = self.__getBuffer() |
|
1130 | new_data = self.__getBuffer() | |
| 1131 |
|
1131 | |||
| 1132 | if new_data is not None: |
|
1132 | if new_data is not None: | |
| 1133 | dataOut.data = new_data |
|
1133 | dataOut.data = new_data | |
| 1134 | dataOut.flagNoData = False |
|
1134 | dataOut.flagNoData = False | |
| 1135 |
|
1135 | |||
| 1136 | profileIndex = dataOut.profileIndex*nTxs |
|
1136 | profileIndex = dataOut.profileIndex*nTxs | |
| 1137 |
|
1137 | |||
| 1138 | else: |
|
1138 | else: | |
| 1139 | raise ValueError, "nTxs should be greater than 0 and lower than 1, or use VoltageReader(..., getblock=True)" |
|
1139 | raise ValueError, "nTxs should be greater than 0 and lower than 1, or use VoltageReader(..., getblock=True)" | |
| 1140 |
|
1140 | |||
| 1141 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1141 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1142 |
|
1142 | |||
| 1143 | dataOut.heightList = numpy.arange(dataOut.nHeights/self.__nTxs) * deltaHeight + dataOut.heightList[0] |
|
1143 | dataOut.heightList = numpy.arange(dataOut.nHeights/self.__nTxs) * deltaHeight + dataOut.heightList[0] | |
| 1144 |
|
1144 | |||
| 1145 | dataOut.nProfiles = int(dataOut.nProfiles*self.__nTxs) |
|
1145 | dataOut.nProfiles = int(dataOut.nProfiles*self.__nTxs) | |
| 1146 |
|
1146 | |||
| 1147 | dataOut.profileIndex = profileIndex |
|
1147 | dataOut.profileIndex = profileIndex | |
| 1148 |
|
1148 | |||
| 1149 | dataOut.ippSeconds /= self.__nTxs |
|
1149 | dataOut.ippSeconds /= self.__nTxs | |
| 1150 |
|
1150 | |||
| 1151 | class SplitProfiles(Operation): |
|
1151 | class SplitProfiles(Operation): | |
| 1152 |
|
1152 | |||
| 1153 | def __init__(self, **kwargs): |
|
1153 | def __init__(self, **kwargs): | |
| 1154 |
|
1154 | |||
| 1155 | Operation.__init__(self, **kwargs) |
|
1155 | Operation.__init__(self, **kwargs) | |
| 1156 |
|
1156 | |||
| 1157 | def run(self, dataOut, n): |
|
1157 | def run(self, dataOut, n): | |
| 1158 |
|
1158 | |||
| 1159 | dataOut.flagNoData = True |
|
1159 | dataOut.flagNoData = True | |
| 1160 | profileIndex = None |
|
1160 | profileIndex = None | |
| 1161 |
|
1161 | |||
| 1162 | if dataOut.flagDataAsBlock: |
|
1162 | if dataOut.flagDataAsBlock: | |
| 1163 |
|
1163 | |||
| 1164 | #nchannels, nprofiles, nsamples |
|
1164 | #nchannels, nprofiles, nsamples | |
| 1165 | shape = dataOut.data.shape |
|
1165 | shape = dataOut.data.shape | |
| 1166 |
|
1166 | |||
| 1167 | if shape[2] % n != 0: |
|
1167 | if shape[2] % n != 0: | |
| 1168 | raise ValueError, "Could not split the data, n=%d has to be multiple of %d" %(n, shape[2]) |
|
1168 | raise ValueError, "Could not split the data, n=%d has to be multiple of %d" %(n, shape[2]) | |
| 1169 |
|
1169 | |||
| 1170 | new_shape = shape[0], shape[1]*n, shape[2]/n |
|
1170 | new_shape = shape[0], shape[1]*n, shape[2]/n | |
| 1171 |
|
1171 | |||
| 1172 | dataOut.data = numpy.reshape(dataOut.data, new_shape) |
|
1172 | dataOut.data = numpy.reshape(dataOut.data, new_shape) | |
| 1173 | dataOut.flagNoData = False |
|
1173 | dataOut.flagNoData = False | |
| 1174 |
|
1174 | |||
| 1175 | profileIndex = int(dataOut.nProfiles/n) - 1 |
|
1175 | profileIndex = int(dataOut.nProfiles/n) - 1 | |
| 1176 |
|
1176 | |||
| 1177 | else: |
|
1177 | else: | |
| 1178 |
|
1178 | |||
| 1179 | raise ValueError, "Could not split the data when is read Profile by Profile. Use VoltageReader(..., getblock=True)" |
|
1179 | raise ValueError, "Could not split the data when is read Profile by Profile. Use VoltageReader(..., getblock=True)" | |
| 1180 |
|
1180 | |||
| 1181 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1181 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1182 |
|
1182 | |||
| 1183 | dataOut.heightList = numpy.arange(dataOut.nHeights/n) * deltaHeight + dataOut.heightList[0] |
|
1183 | dataOut.heightList = numpy.arange(dataOut.nHeights/n) * deltaHeight + dataOut.heightList[0] | |
| 1184 |
|
1184 | |||
| 1185 | dataOut.nProfiles = int(dataOut.nProfiles*n) |
|
1185 | dataOut.nProfiles = int(dataOut.nProfiles*n) | |
| 1186 |
|
1186 | |||
| 1187 | dataOut.profileIndex = profileIndex |
|
1187 | dataOut.profileIndex = profileIndex | |
| 1188 |
|
1188 | |||
| 1189 | dataOut.ippSeconds /= n |
|
1189 | dataOut.ippSeconds /= n | |
| 1190 |
|
1190 | |||
| 1191 | class CombineProfiles(Operation): |
|
1191 | class CombineProfiles(Operation): | |
| 1192 |
|
1192 | |||
| 1193 | def __init__(self, **kwargs): |
|
1193 | def __init__(self, **kwargs): | |
| 1194 |
|
1194 | |||
| 1195 | Operation.__init__(self, **kwargs) |
|
1195 | Operation.__init__(self, **kwargs) | |
| 1196 |
|
1196 | |||
| 1197 | self.__remData = None |
|
1197 | self.__remData = None | |
| 1198 | self.__profileIndex = 0 |
|
1198 | self.__profileIndex = 0 | |
| 1199 |
|
1199 | |||
| 1200 | def run(self, dataOut, n): |
|
1200 | def run(self, dataOut, n): | |
| 1201 |
|
1201 | |||
| 1202 | dataOut.flagNoData = True |
|
1202 | dataOut.flagNoData = True | |
| 1203 | profileIndex = None |
|
1203 | profileIndex = None | |
| 1204 |
|
1204 | |||
| 1205 | if dataOut.flagDataAsBlock: |
|
1205 | if dataOut.flagDataAsBlock: | |
| 1206 |
|
1206 | |||
| 1207 | #nchannels, nprofiles, nsamples |
|
1207 | #nchannels, nprofiles, nsamples | |
| 1208 | shape = dataOut.data.shape |
|
1208 | shape = dataOut.data.shape | |
| 1209 | new_shape = shape[0], shape[1]/n, shape[2]*n |
|
1209 | new_shape = shape[0], shape[1]/n, shape[2]*n | |
| 1210 |
|
1210 | |||
| 1211 | if shape[1] % n != 0: |
|
1211 | if shape[1] % n != 0: | |
| 1212 | raise ValueError, "Could not split the data, n=%d has to be multiple of %d" %(n, shape[1]) |
|
1212 | raise ValueError, "Could not split the data, n=%d has to be multiple of %d" %(n, shape[1]) | |
| 1213 |
|
1213 | |||
| 1214 | dataOut.data = numpy.reshape(dataOut.data, new_shape) |
|
1214 | dataOut.data = numpy.reshape(dataOut.data, new_shape) | |
| 1215 | dataOut.flagNoData = False |
|
1215 | dataOut.flagNoData = False | |
| 1216 |
|
1216 | |||
| 1217 | profileIndex = int(dataOut.nProfiles*n) - 1 |
|
1217 | profileIndex = int(dataOut.nProfiles*n) - 1 | |
| 1218 |
|
1218 | |||
| 1219 | else: |
|
1219 | else: | |
| 1220 |
|
1220 | |||
| 1221 | #nchannels, nsamples |
|
1221 | #nchannels, nsamples | |
| 1222 | if self.__remData is None: |
|
1222 | if self.__remData is None: | |
| 1223 | newData = dataOut.data |
|
1223 | newData = dataOut.data | |
| 1224 | else: |
|
1224 | else: | |
| 1225 | newData = numpy.concatenate((self.__remData, dataOut.data), axis=1) |
|
1225 | newData = numpy.concatenate((self.__remData, dataOut.data), axis=1) | |
| 1226 |
|
1226 | |||
| 1227 | self.__profileIndex += 1 |
|
1227 | self.__profileIndex += 1 | |
| 1228 |
|
1228 | |||
| 1229 | if self.__profileIndex < n: |
|
1229 | if self.__profileIndex < n: | |
| 1230 | self.__remData = newData |
|
1230 | self.__remData = newData | |
| 1231 | #continue |
|
1231 | #continue | |
| 1232 | return |
|
1232 | return | |
| 1233 |
|
1233 | |||
| 1234 | self.__profileIndex = 0 |
|
1234 | self.__profileIndex = 0 | |
| 1235 | self.__remData = None |
|
1235 | self.__remData = None | |
| 1236 |
|
1236 | |||
| 1237 | dataOut.data = newData |
|
1237 | dataOut.data = newData | |
| 1238 | dataOut.flagNoData = False |
|
1238 | dataOut.flagNoData = False | |
| 1239 |
|
1239 | |||
| 1240 | profileIndex = dataOut.profileIndex/n |
|
1240 | profileIndex = dataOut.profileIndex/n | |
| 1241 |
|
1241 | |||
| 1242 |
|
1242 | |||
| 1243 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1243 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1244 |
|
1244 | |||
| 1245 | dataOut.heightList = numpy.arange(dataOut.nHeights*n) * deltaHeight + dataOut.heightList[0] |
|
1245 | dataOut.heightList = numpy.arange(dataOut.nHeights*n) * deltaHeight + dataOut.heightList[0] | |
| 1246 |
|
1246 | |||
| 1247 | dataOut.nProfiles = int(dataOut.nProfiles/n) |
|
1247 | dataOut.nProfiles = int(dataOut.nProfiles/n) | |
| 1248 |
|
1248 | |||
| 1249 | dataOut.profileIndex = profileIndex |
|
1249 | dataOut.profileIndex = profileIndex | |
| 1250 |
|
1250 | |||
| 1251 | dataOut.ippSeconds *= n |
|
1251 | dataOut.ippSeconds *= n | |
| 1252 |
|
1252 | |||
| 1253 |
|
1253 | |||
| 1254 | class SSheightProfiles(Operation): |
|
1254 | class SSheightProfiles(Operation): | |
| 1255 |
|
1255 | |||
| 1256 | step = None |
|
1256 | step = None | |
| 1257 | nsamples = None |
|
1257 | nsamples = None | |
| 1258 | bufferShape = None |
|
1258 | bufferShape = None | |
| 1259 | profileShape = None |
|
1259 | profileShape = None | |
| 1260 | sshProfiles = None |
|
1260 | sshProfiles = None | |
| 1261 | profileIndex = None |
|
1261 | profileIndex = None | |
| 1262 |
|
1262 | |||
| 1263 | def __init__(self, **kwargs): |
|
1263 | def __init__(self, **kwargs): | |
| 1264 |
|
1264 | |||
| 1265 | Operation.__init__(self, **kwargs) |
|
1265 | Operation.__init__(self, **kwargs) | |
| 1266 | self.isConfig = False |
|
1266 | self.isConfig = False | |
| 1267 |
|
1267 | |||
| 1268 | def setup(self,dataOut ,step = None , nsamples = None): |
|
1268 | def setup(self,dataOut ,step = None , nsamples = None): | |
| 1269 |
|
1269 | |||
| 1270 | if step == None and nsamples == None: |
|
1270 | if step == None and nsamples == None: | |
| 1271 | raise ValueError, "step or nheights should be specified ..." |
|
1271 | raise ValueError, "step or nheights should be specified ..." | |
| 1272 |
|
1272 | |||
| 1273 | self.step = step |
|
1273 | self.step = step | |
| 1274 | self.nsamples = nsamples |
|
1274 | self.nsamples = nsamples | |
| 1275 | self.__nChannels = dataOut.nChannels |
|
1275 | self.__nChannels = dataOut.nChannels | |
| 1276 | self.__nProfiles = dataOut.nProfiles |
|
1276 | self.__nProfiles = dataOut.nProfiles | |
| 1277 | self.__nHeis = dataOut.nHeights |
|
1277 | self.__nHeis = dataOut.nHeights | |
| 1278 | shape = dataOut.data.shape #nchannels, nprofiles, nsamples |
|
1278 | shape = dataOut.data.shape #nchannels, nprofiles, nsamples | |
| 1279 | print "input nChannels",self.__nChannels |
|
1279 | print "input nChannels",self.__nChannels | |
| 1280 | print "input nProfiles",self.__nProfiles |
|
1280 | print "input nProfiles",self.__nProfiles | |
| 1281 | print "input nHeis",self.__nHeis |
|
1281 | print "input nHeis",self.__nHeis | |
| 1282 | print "input Shape",shape |
|
1282 | print "input Shape",shape | |
| 1283 |
|
1283 | |||
| 1284 |
|
1284 | |||
| 1285 |
|
1285 | |||
| 1286 | residue = (shape[1] - self.nsamples) % self.step |
|
1286 | residue = (shape[1] - self.nsamples) % self.step | |
| 1287 | if residue != 0: |
|
1287 | if residue != 0: | |
| 1288 | 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) |
|
1288 | 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) | |
| 1289 |
|
1289 | |||
| 1290 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1290 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1291 | numberProfile = self.nsamples |
|
1291 | numberProfile = self.nsamples | |
| 1292 | numberSamples = (shape[1] - self.nsamples)/self.step |
|
1292 | numberSamples = (shape[1] - self.nsamples)/self.step | |
| 1293 |
|
1293 | |||
| 1294 | print "new numberProfile",numberProfile |
|
1294 | print "new numberProfile",numberProfile | |
| 1295 | print "new numberSamples",numberSamples |
|
1295 | print "new numberSamples",numberSamples | |
| 1296 |
|
1296 | |||
| 1297 | print "New number of profile: %d, number of height: %d, Resolution %f Km"%(numberProfile,numberSamples,deltaHeight*self.step) |
|
1297 | print "New number of profile: %d, number of height: %d, Resolution %f Km"%(numberProfile,numberSamples,deltaHeight*self.step) | |
| 1298 |
|
1298 | |||
| 1299 | self.bufferShape = shape[0], numberSamples, numberProfile # nchannels, nsamples , nprofiles |
|
1299 | self.bufferShape = shape[0], numberSamples, numberProfile # nchannels, nsamples , nprofiles | |
| 1300 | self.profileShape = shape[0], numberProfile, numberSamples # nchannels, nprofiles, nsamples |
|
1300 | self.profileShape = shape[0], numberProfile, numberSamples # nchannels, nprofiles, nsamples | |
| 1301 |
|
1301 | |||
| 1302 | self.buffer = numpy.zeros(self.bufferShape , dtype=numpy.complex) |
|
1302 | self.buffer = numpy.zeros(self.bufferShape , dtype=numpy.complex) | |
| 1303 | self.sshProfiles = numpy.zeros(self.profileShape, dtype=numpy.complex) |
|
1303 | self.sshProfiles = numpy.zeros(self.profileShape, dtype=numpy.complex) | |
| 1304 |
|
1304 | |||
| 1305 | def run(self, dataOut, step, nsamples): |
|
1305 | def run(self, dataOut, step, nsamples): | |
| 1306 |
|
1306 | |||
| 1307 | dataOut.flagNoData = True |
|
1307 | dataOut.flagNoData = True | |
| 1308 | dataOut.flagDataAsBlock = False |
|
1308 | dataOut.flagDataAsBlock = False | |
| 1309 | profileIndex = None |
|
1309 | profileIndex = None | |
| 1310 |
|
1310 | |||
| 1311 |
|
1311 | |||
| 1312 | if not self.isConfig: |
|
1312 | if not self.isConfig: | |
| 1313 | self.setup(dataOut, step=step , nsamples=nsamples) |
|
1313 | self.setup(dataOut, step=step , nsamples=nsamples) | |
| 1314 | self.isConfig = True |
|
1314 | self.isConfig = True | |
| 1315 |
|
1315 | |||
| 1316 | for i in range(self.buffer.shape[1]): |
|
1316 | for i in range(self.buffer.shape[1]): | |
| 1317 | #self.buffer[:,i] = numpy.flip(dataOut.data[:,i*self.step:i*self.step + self.nsamples]) |
|
1317 | #self.buffer[:,i] = numpy.flip(dataOut.data[:,i*self.step:i*self.step + self.nsamples]) | |
| 1318 | self.buffer[:,i] = dataOut.data[:,i*self.step:i*self.step + self.nsamples] |
|
1318 | self.buffer[:,i] = dataOut.data[:,i*self.step:i*self.step + self.nsamples] | |
| 1319 | #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]) |
|
1319 | #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]) | |
| 1320 |
|
1320 | |||
| 1321 | for j in range(self.buffer.shape[0]): |
|
1321 | for j in range(self.buffer.shape[0]): | |
| 1322 | self.sshProfiles[j] = numpy.transpose(self.buffer[j]) |
|
1322 | self.sshProfiles[j] = numpy.transpose(self.buffer[j]) | |
| 1323 |
|
1323 | |||
| 1324 | profileIndex = self.nsamples |
|
1324 | profileIndex = self.nsamples | |
| 1325 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1325 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1326 | ippSeconds = (deltaHeight*1.0e-6)/(0.15) |
|
1326 | ippSeconds = (deltaHeight*1.0e-6)/(0.15) | |
| 1327 | #print "ippSeconds",ippSeconds |
|
1327 | #print "ippSeconds",ippSeconds | |
| 1328 | try: |
|
1328 | try: | |
| 1329 | if dataOut.concat_m is not None: |
|
1329 | if dataOut.concat_m is not None: | |
| 1330 | ippSeconds= ippSeconds/float(dataOut.concat_m) |
|
1330 | ippSeconds= ippSeconds/float(dataOut.concat_m) | |
| 1331 | #print "Profile concat %d"%dataOut.concat_m |
|
1331 | #print "Profile concat %d"%dataOut.concat_m | |
| 1332 | except: |
|
1332 | except: | |
| 1333 | pass |
|
1333 | pass | |
| 1334 |
|
1334 | |||
| 1335 | dataOut.data = self.sshProfiles |
|
1335 | dataOut.data = self.sshProfiles | |
| 1336 | dataOut.flagNoData = False |
|
1336 | dataOut.flagNoData = False | |
| 1337 | dataOut.heightList = numpy.arange(self.buffer.shape[1]) *self.step*deltaHeight + dataOut.heightList[0] |
|
1337 | dataOut.heightList = numpy.arange(self.buffer.shape[1]) *self.step*deltaHeight + dataOut.heightList[0] | |
| 1338 | dataOut.nProfiles = int(dataOut.nProfiles*self.nsamples) |
|
1338 | dataOut.nProfiles = int(dataOut.nProfiles*self.nsamples) | |
| 1339 | dataOut.profileIndex = profileIndex |
|
1339 | dataOut.profileIndex = profileIndex | |
| 1340 | dataOut.flagDataAsBlock = True |
|
1340 | dataOut.flagDataAsBlock = True | |
| 1341 | dataOut.ippSeconds = ippSeconds |
|
1341 | dataOut.ippSeconds = ippSeconds | |
| 1342 | dataOut.step = self.step |
|
1342 | dataOut.step = self.step | |
| 1343 |
|
1343 | |||
| 1344 | class voltACFLags(Operation): |
|
1344 | class voltACFLags(Operation): | |
| 1345 |
|
1345 | |||
| 1346 | data_acf = None |
|
1346 | data_acf = None | |
| 1347 | lags = None |
|
1347 | lags = None | |
| 1348 | mode = None |
|
1348 | mode = None | |
| 1349 | fullBuffer = None |
|
1349 | fullBuffer = None | |
| 1350 | pairsList = None |
|
1350 | pairsList = None | |
| 1351 | tmp = None |
|
1351 | tmp = None | |
| 1352 |
|
1352 | |||
| 1353 | def __init__(self, **kwargs): |
|
1353 | def __init__(self, **kwargs): | |
| 1354 | Operation.__init__(self, **kwargs) |
|
1354 | Operation.__init__(self, **kwargs) | |
| 1355 | self.isConfig = False |
|
1355 | self.isConfig = False | |
| 1356 | self.profIndex = 0 |
|
1356 | self.profIndex = 0 | |
| 1357 | self.buffer = None |
|
1357 | self.buffer = None | |
|
|
1358 | self.channelList = [] | |||
| 1358 |
|
1359 | |||
| 1359 |
|
1360 | |||
| 1360 | def setup(self,dataOut ,lags = None,mode =None, fullBuffer= None ,pairsList = None,nAvg = 1): |
|
1361 | def setup(self,dataOut ,lags = None,mode =None, fullBuffer= None ,pairsList = None,nAvg = 1): | |
| 1361 |
|
1362 | |||
| 1362 | self.lags = lags |
|
1363 | self.lags = lags | |
| 1363 | print self.lags |
|
1364 | print self.lags | |
| 1364 | self.mode = mode |
|
1365 | self.mode = mode | |
| 1365 | self.fullBuffer= fullBuffer |
|
1366 | self.fullBuffer= fullBuffer | |
| 1366 | self.nAvg = nAvg |
|
1367 | self.nAvg = nAvg | |
| 1367 | self.pairsList = pairsList |
|
1368 | self.pairsList = [pairsList] | |
| 1368 | nChannels = dataOut.nChannels |
|
1369 | nChannels = dataOut.nChannels | |
| 1369 | nProfiles = dataOut.nProfiles |
|
1370 | nProfiles = dataOut.nProfiles | |
| 1370 | nHeights = dataOut.nHeights |
|
1371 | nHeights = dataOut.nHeights | |
| 1371 | self.__nProfiles = dataOut.nProfiles |
|
1372 | self.__nProfiles = dataOut.nProfiles | |
| 1372 | self.__nHeis = dataOut.nHeights |
|
1373 | self.__nHeis = dataOut.nHeights | |
| 1373 |
|
1374 | |||
| 1374 | if mode == 'time': |
|
1375 | if mode == 'time': | |
| 1375 | print "Mode lags equal time for default." |
|
1376 | print "Mode lags equal time for default." | |
| 1376 | else: |
|
1377 | else: | |
| 1377 | print "Mode lags equal height." |
|
1378 | print "Mode lags equal height." | |
| 1378 |
|
1379 | |||
| 1379 | if pairsList == None: |
|
1380 | if pairsList == None: | |
| 1380 | print "Pairs list selected by default (1,0)" |
|
1381 | print "Pairs list selected by default (1,0)" | |
| 1381 | pairsList = [(0,1)] |
|
1382 | pairsList = [(0,1)] | |
| 1382 | self.pairsList= pairsList |
|
1383 | self.pairsList= pairsList | |
| 1383 |
|
1384 | |||
| 1384 | self.selectChannels(self.pairsList) |
|
1385 | ||
|
|
1386 | for i in range(len(self.pairsList)): | |||
|
|
1387 | self.channelList.append(self.pairsList[i][0]) | |||
|
|
1388 | self.channelList.append(self.pairsList[i][1]) | |||
| 1385 |
|
1389 | |||
| 1386 | if lags == None: |
|
1390 | if lags == None: | |
| 1387 | if mode=='time': |
|
1391 | if mode=='time': | |
| 1388 | self.lags = numpy.arange(0,nProfiles)# -nProfiles+1, nProfiles |
|
1392 | self.lags = numpy.arange(0,nProfiles)# -nProfiles+1, nProfiles | |
| 1389 | print "self.lags", len(self.lags) |
|
1393 | print "self.lags", len(self.lags) | |
| 1390 | if mode=='height': |
|
1394 | if mode=='height': | |
| 1391 | self.lags = numpy.arange(0,nHeights)# -nHeights+1, nHeights |
|
1395 | self.lags = numpy.arange(0,nHeights)# -nHeights+1, nHeights | |
| 1392 |
|
1396 | |||
| 1393 | # buffer de canalaes, perfiles, alturas |
|
1397 | # buffer de canalaes, perfiles, alturas | |
| 1394 | if self.buffer is None: |
|
1398 | if self.buffer is None: | |
| 1395 |
self.buffer = numpy.zeros(( |
|
1399 | self.buffer = numpy.zeros((nChannels,nProfiles,nHeights),dtype='complex') | |
| 1396 |
|
1400 | |||
| 1397 | if fullBuffer: |
|
1401 | if fullBuffer: | |
| 1398 | self.tmp = numpy.zeros((len(pairsList), len(self.lags), nProfiles, nHeights), dtype = 'complex')*numpy.nan |
|
1402 | self.tmp = numpy.zeros((len(self.pairsList), len(self.lags), nProfiles, nHeights), dtype = 'complex')*numpy.nan | |
| 1399 | elif mode =='time': |
|
1403 | elif mode =='time': | |
| 1400 | self.tmp = numpy.zeros((len(pairsList), len(self.lags), nHeights),dtype='complex') |
|
1404 | self.tmp = numpy.zeros((len(self.pairsList), len(self.lags), nHeights),dtype='complex') | |
| 1401 | elif mode =='height': |
|
1405 | elif mode =='height': | |
| 1402 |
self.tmp = numpy.zeros(len(pairsList), |
|
1406 | self.tmp = numpy.zeros((len(self.pairsList), len(self.lags), nProfiles),dtype='complex') | |
| 1403 |
|
1407 | |||
| 1404 | print "lags", len(self.lags),self.lags |
|
1408 | print "lags", len(self.lags),self.lags | |
| 1405 | print "mode",self.mode |
|
1409 | print "mode",self.mode | |
| 1406 | print "nChannels", nChannels |
|
1410 | print "nChannels", nChannels | |
| 1407 | print "nProfiles", nProfiles |
|
1411 | print "nProfiles", nProfiles | |
| 1408 | print "nHeights" , nHeights |
|
1412 | print "nHeights" , nHeights | |
|
|
1413 | print "acf_channels",len(self.pairsList) | |||
|
|
1414 | print "channelList",self.channelList | |||
| 1409 | print "pairsList", pairsList,len(self.pairsList) |
|
1415 | print "pairsList", pairsList,len(self.pairsList) | |
| 1410 | print "fullBuffer", fullBuffer |
|
1416 | print "fullBuffer", fullBuffer | |
| 1411 | #print "type(pairsList)",type(pairsList) |
|
1417 | #print "type(pairsList)",type(pairsList) | |
| 1412 | print "tmp.shape",self.tmp.shape |
|
1418 | print "tmp.shape",self.tmp.shape | |
| 1413 |
|
1419 | |||
| 1414 |
|
1420 | |||
| 1415 | def run(self, dataOut, lags =None,mode ='time',fullBuffer= False ,pairsList = None,nAvg = 1): |
|
1421 | def run(self, dataOut, lags =None,mode ='time',fullBuffer= False ,pairsList = None,nAvg = 1): | |
| 1416 |
|
1422 | |||
| 1417 | dataOut.flagNoData = True |
|
1423 | dataOut.flagNoData = True | |
| 1418 |
|
1424 | |||
| 1419 | if not self.isConfig: |
|
1425 | if not self.isConfig: | |
| 1420 | self.setup(dataOut, lags = lags,mode = mode, fullBuffer= fullBuffer ,pairsList = pairsList,nAvg=nAvg) |
|
1426 | self.setup(dataOut, lags = lags,mode = mode, fullBuffer= fullBuffer ,pairsList = pairsList,nAvg=nAvg) | |
| 1421 | self.isConfig = True |
|
1427 | self.isConfig = True | |
| 1422 | print "pairsList Ale", self.pairsList |
|
1428 | ||
| 1423 | print dataOut.data[pairsList,:].shape |
|
|||
| 1424 | if dataOut.type == "Voltage": |
|
1429 | if dataOut.type == "Voltage": | |
| 1425 | if dataOut.flagDataAsBlock: |
|
1430 | if dataOut.flagDataAsBlock: | |
| 1426 | print "Not implemented yet" |
|
1431 | print "Not implemented yet" | |
| 1427 | return 0 |
|
1432 | return 0 | |
| 1428 | else: |
|
1433 | else: | |
| 1429 | print "shapebuffer",self.buffer[:,0,:].shape |
|
1434 | self.buffer[:, self.profIndex, :] = dataOut.data | |
| 1430 | self.buffer[:, self.profIndex, :] = dataOut.data#error |
|
|||
| 1431 | self.profIndex += 1 |
|
1435 | self.profIndex += 1 | |
| 1432 |
|
1436 | |||
| 1433 | if self.profIndex == self.__nProfiles : |
|
1437 | if self.profIndex == self.__nProfiles : | |
|
|
1438 | ||||
| 1434 | data_pre = self.buffer #data |
|
1439 | data_pre = self.buffer #data | |
| 1435 | print "size",data_pre.shape |
|
|||
| 1436 | # Here is the loop :D |
|
|||
| 1437 | for l in range(len(self.pairsList)): |
|
1440 | for l in range(len(self.pairsList)): | |
| 1438 | ch0 = self.pairsList[l][0] |
|
1441 | ch0 = self.pairsList[l][0] | |
| 1439 | ch1 = self.pairsList[l][1] |
|
1442 | ch1 = self.pairsList[l][1] | |
| 1440 | for i in range(len(self.lags)): |
|
1443 | for i in range(len(self.lags)): | |
| 1441 | idx = self.lags[i] |
|
1444 | idx = self.lags[i] | |
| 1442 | if self.mode == 'time': |
|
1445 | if self.mode == 'time': | |
| 1443 | acf0 = data_pre[ch0,:self.__nProfiles-idx,:]*numpy.conj(data_pre[ch1,idx:,:]) # pair,lag,height |
|
1446 | acf0 = data_pre[ch0,:self.__nProfiles-idx,:]*numpy.conj(data_pre[ch1,idx:,:]) # pair,lag,height | |
| 1444 | else: |
|
1447 | else: | |
| 1445 | acf0 = data_pre[ch0,:,:self.__nHeights-idx]*numpy.conj(data_pre[ch1,:,idx:]) # pair,lag,profile |
|
1448 | acf0 = data_pre[ch0,:,:self.__nHeights-idx]*numpy.conj(data_pre[ch1,:,idx:]) # pair,lag,profile | |
| 1446 |
|
1449 | |||
| 1447 | if self.fullBuffer: |
|
1450 | if self.fullBuffer: | |
| 1448 | self.tmp[l,i,:acf0.shape[0],:]= acf0 |
|
1451 | self.tmp[l,i,:acf0.shape[0],:]= acf0 | |
| 1449 | else: |
|
1452 | else: | |
| 1450 | self.tmp[l,i,:]= numpy.sum(acf0,axis=0) |
|
1453 | self.tmp[l,i,:]= numpy.sum(acf0,axis=0) | |
| 1451 | if self.fullBuffer: |
|
1454 | if self.fullBuffer: | |
| 1452 | self.tmp = numpy.sum(numpy.reshape(self.tmp,(self.tmp.shape[0],self.tmp.shape[1],self.tmp.shape[2]/self.nAvg,self.nAvg,self.tmp.shape[3])),axis=3) |
|
1455 | self.tmp = numpy.sum(numpy.reshape(self.tmp,(self.tmp.shape[0],self.tmp.shape[1],self.tmp.shape[2]/self.nAvg,self.nAvg,self.tmp.shape[3])),axis=3) | |
| 1453 | dataOut.nAvg = self.nAvg |
|
1456 | dataOut.nAvg = self.nAvg | |
| 1454 |
|
||||
| 1455 |
|
|
1457 | if self.mode == 'time': | |
|
|
1458 | #print "entre" | |||
| 1456 |
|
|
1459 | delta = dataOut.ippSeconds*dataOut.nCohInt | |
| 1457 |
|
|
1460 | else: | |
| 1458 | delta = dataOut.heightList[1] - dataOut.heightList[0] |
|
1461 | delta = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1459 |
|
1462 | |||
| 1460 |
shape= self.tmp.shape |
|
1463 | shape= self.tmp.shape | |
| 1461 | # Normalizando |
|
1464 | for i in range(len(self.pairsList)): | |
| 1462 | for i in range(len(pairsList)): |
|
|||
| 1463 | for j in range(shape[2]): |
|
1465 | for j in range(shape[2]): | |
| 1464 |
self.tmp[i,:,j]= self.tmp[i,:,j].real |
|
1466 | self.tmp[i,:,j]= self.tmp[i,:,j].real/numpy.max(numpy.abs(self.tmp[i,:,j])) | |
| 1465 |
|
1467 | |||
| 1466 | #import matplotlib.pyplot as plt |
|
1468 | #import matplotlib.pyplot as plt | |
| 1467 | #print "test",self.tmp.shape |
|
1469 | #print "test",self.tmp.shape | |
| 1468 | #print self.tmp[0,0,0] |
|
1470 | #print self.tmp[0,0,0] | |
| 1469 | #print numpy.max(numpy.abs(self.tmp[0,:,0])) |
|
1471 | #print numpy.max(numpy.abs(self.tmp[0,:,0])) | |
| 1470 | #acf_tmp=self.tmp[0,:,100].real/numpy.max(numpy.abs(self.tmp[0,:,100])) |
|
1472 | #acf_tmp=self.tmp[0,:,100].real/numpy.max(numpy.abs(self.tmp[0,:,100])) | |
| 1471 | #print acf_tmp |
|
1473 | #print acf_tmp | |
| 1472 | #plt.plot(acf_tmp) |
|
1474 | #plt.plot(acf_tmp) | |
| 1473 | #plt.show() |
|
1475 | #plt.show() | |
| 1474 | #import time |
|
1476 | #import time | |
| 1475 | #time.sleep(20) |
|
1477 | #time.sleep(20) | |
| 1476 |
dataOut.data |
|
1478 | dataOut.data = self.buffer | |
|
|
1479 | dataOut.data_acfLag = self.tmp | |||
| 1477 | dataOut.mode = self.mode |
|
1480 | dataOut.mode = self.mode | |
| 1478 | dataOut.nLags = len(self.lags) |
|
1481 | dataOut.nLags = len(self.lags) | |
| 1479 | dataOut.nProfiles = len(self.lags) |
|
1482 | dataOut.nProfiles = len(self.lags) | |
| 1480 | dataOut.pairsList = pairsList |
|
1483 | dataOut.pairsList = pairsList | |
| 1481 | dataOut.nPairs = len(pairsList) |
|
1484 | dataOut.nPairs = len(pairsList) | |
| 1482 | dataOut.lagRange = numpy.array(self.lags)*delta |
|
1485 | dataOut.lagRange = numpy.array(self.lags)*delta | |
| 1483 | dataOut.flagDataAsBlock = True |
|
1486 | dataOut.flagDataAsBlock = True | |
| 1484 | dataOut.flagNoData = False |
|
1487 | dataOut.flagNoData = False | |
|
|
1488 | self.profIndex = 0 | |||
| 1485 |
|
1489 | |||
| 1486 |
|
1490 | |||
| 1487 | import time |
|
1491 | import time | |
| 1488 | ################################################# |
|
1492 | ################################################# | |
| 1489 |
|
1493 | |||
| 1490 | class decoPseudorandom(Operation): |
|
1494 | class decoPseudorandom(Operation): | |
| 1491 |
|
1495 | |||
| 1492 | nProfiles= 0 |
|
1496 | nProfiles= 0 | |
| 1493 | buffer= None |
|
1497 | buffer= None | |
| 1494 | isConfig = False |
|
1498 | isConfig = False | |
| 1495 |
|
1499 | |||
| 1496 | def setup(self, clen= 10000,seed= 0,Nranges= 1000,oversample=1): |
|
1500 | def setup(self, clen= 10000,seed= 0,Nranges= 1000,oversample=1): | |
| 1497 | #code = create_pseudo_random_code(clen=clen, seed=seed) |
|
1501 | #code = create_pseudo_random_code(clen=clen, seed=seed) | |
| 1498 | code= rep_seq(create_pseudo_random_code(clen=clen, seed=seed),rep=oversample) |
|
1502 | code= rep_seq(create_pseudo_random_code(clen=clen, seed=seed),rep=oversample) | |
| 1499 | #print ("code_rx", code.shape) |
|
1503 | #print ("code_rx", code.shape) | |
| 1500 | #N = int(an_len/clen) # 100 |
|
1504 | #N = int(an_len/clen) # 100 | |
| 1501 | B_cache = 0 |
|
1505 | B_cache = 0 | |
| 1502 | r_cache = 0 |
|
1506 | r_cache = 0 | |
| 1503 | B_cached = False |
|
1507 | B_cached = False | |
| 1504 | r = create_estimation_matrix(code=code, cache=True, rmax=Nranges) |
|
1508 | r = create_estimation_matrix(code=code, cache=True, rmax=Nranges) | |
| 1505 | #print ("code shape", code.shape) |
|
1509 | #print ("code shape", code.shape) | |
| 1506 | #print ("seed",seed) |
|
1510 | #print ("seed",seed) | |
| 1507 | #print ("Code", code[0:10]) |
|
1511 | #print ("Code", code[0:10]) | |
| 1508 | self.B = r['B'] |
|
1512 | self.B = r['B'] | |
| 1509 |
|
1513 | |||
| 1510 |
|
1514 | |||
| 1511 | def run (self,dataOut,length_code= 10000,seed= 0,Nranges= 1000,oversample=1): |
|
1515 | def run (self,dataOut,length_code= 10000,seed= 0,Nranges= 1000,oversample=1): | |
| 1512 | #print((dataOut.data.shape)) |
|
1516 | #print((dataOut.data.shape)) | |
| 1513 | if not self.isConfig: |
|
1517 | if not self.isConfig: | |
| 1514 | self.setup(clen= length_code,seed= seed,Nranges= Nranges,oversample=oversample) |
|
1518 | self.setup(clen= length_code,seed= seed,Nranges= Nranges,oversample=oversample) | |
| 1515 | self.isConfig = True |
|
1519 | self.isConfig = True | |
| 1516 |
|
1520 | |||
| 1517 | dataOut.flagNoData = True |
|
1521 | dataOut.flagNoData = True | |
| 1518 | data =dataOut.data |
|
1522 | data =dataOut.data | |
| 1519 | #print "length_CODE",length_code |
|
1523 | #print "length_CODE",length_code | |
| 1520 | data_shape = (data.shape[1]) |
|
1524 | data_shape = (data.shape[1]) | |
| 1521 | #print "data_shape",data_shape |
|
1525 | #print "data_shape",data_shape | |
| 1522 | n = (length_code /data_shape) |
|
1526 | n = (length_code /data_shape) | |
| 1523 | #print "we need this number of sample",n |
|
1527 | #print "we need this number of sample",n | |
| 1524 |
|
1528 | |||
| 1525 | if n>0 and self.buffer is None: |
|
1529 | if n>0 and self.buffer is None: | |
| 1526 | self.buffer = numpy.zeros([1, length_code], dtype=numpy.complex64) |
|
1530 | self.buffer = numpy.zeros([1, length_code], dtype=numpy.complex64) | |
| 1527 | self.buffer[0][0:data_shape] = data[0] |
|
1531 | self.buffer[0][0:data_shape] = data[0] | |
| 1528 | #print "FIRST CREATION",self.buffer.shape |
|
1532 | #print "FIRST CREATION",self.buffer.shape | |
| 1529 |
|
1533 | |||
| 1530 | else: |
|
1534 | else: | |
| 1531 | self.buffer[0][self.nProfiles*data_shape:(self.nProfiles+1)*data_shape]=data[0] |
|
1535 | self.buffer[0][self.nProfiles*data_shape:(self.nProfiles+1)*data_shape]=data[0] | |
| 1532 |
|
1536 | |||
| 1533 | #print "buffer_shape",(self.buffer.shape) |
|
1537 | #print "buffer_shape",(self.buffer.shape) | |
| 1534 | self.nProfiles += 1 |
|
1538 | self.nProfiles += 1 | |
| 1535 | #print "count",self.nProfiles |
|
1539 | #print "count",self.nProfiles | |
| 1536 |
|
1540 | |||
| 1537 | if self.nProfiles== n: |
|
1541 | if self.nProfiles== n: | |
| 1538 | temporal = numpy.dot(self.B, numpy.transpose(self.buffer)) |
|
1542 | temporal = numpy.dot(self.B, numpy.transpose(self.buffer)) | |
| 1539 | #print temporal.shape |
|
1543 | #print temporal.shape | |
| 1540 | #import time |
|
1544 | #import time | |
| 1541 | #time.sleep(40) |
|
1545 | #time.sleep(40) | |
| 1542 | dataOut.data=numpy.transpose(temporal) |
|
1546 | dataOut.data=numpy.transpose(temporal) | |
| 1543 |
|
1547 | |||
| 1544 | dataOut.flagNoData = False |
|
1548 | dataOut.flagNoData = False | |
| 1545 | self.buffer= None |
|
1549 | self.buffer= None | |
| 1546 | self.nProfiles = 0 |
|
1550 | self.nProfiles = 0 | |
| 1547 |
|
1551 | |||
| 1548 | # import collections |
|
1552 | # import collections | |
| 1549 | # from scipy.stats import mode |
|
1553 | # from scipy.stats import mode | |
| 1550 | # |
|
1554 | # | |
| 1551 | # class Synchronize(Operation): |
|
1555 | # class Synchronize(Operation): | |
| 1552 | # |
|
1556 | # | |
| 1553 | # isConfig = False |
|
1557 | # isConfig = False | |
| 1554 | # __profIndex = 0 |
|
1558 | # __profIndex = 0 | |
| 1555 | # |
|
1559 | # | |
| 1556 | # def __init__(self, **kwargs): |
|
1560 | # def __init__(self, **kwargs): | |
| 1557 | # |
|
1561 | # | |
| 1558 | # Operation.__init__(self, **kwargs) |
|
1562 | # Operation.__init__(self, **kwargs) | |
| 1559 | # # self.isConfig = False |
|
1563 | # # self.isConfig = False | |
| 1560 | # self.__powBuffer = None |
|
1564 | # self.__powBuffer = None | |
| 1561 | # self.__startIndex = 0 |
|
1565 | # self.__startIndex = 0 | |
| 1562 | # self.__pulseFound = False |
|
1566 | # self.__pulseFound = False | |
| 1563 | # |
|
1567 | # | |
| 1564 | # def __findTxPulse(self, dataOut, channel=0, pulse_with = None): |
|
1568 | # def __findTxPulse(self, dataOut, channel=0, pulse_with = None): | |
| 1565 | # |
|
1569 | # | |
| 1566 | # #Read data |
|
1570 | # #Read data | |
| 1567 | # |
|
1571 | # | |
| 1568 | # powerdB = dataOut.getPower(channel = channel) |
|
1572 | # powerdB = dataOut.getPower(channel = channel) | |
| 1569 | # noisedB = dataOut.getNoise(channel = channel)[0] |
|
1573 | # noisedB = dataOut.getNoise(channel = channel)[0] | |
| 1570 | # |
|
1574 | # | |
| 1571 | # self.__powBuffer.extend(powerdB.flatten()) |
|
1575 | # self.__powBuffer.extend(powerdB.flatten()) | |
| 1572 | # |
|
1576 | # | |
| 1573 | # dataArray = numpy.array(self.__powBuffer) |
|
1577 | # dataArray = numpy.array(self.__powBuffer) | |
| 1574 | # |
|
1578 | # | |
| 1575 | # filteredPower = numpy.correlate(dataArray, dataArray[0:self.__nSamples], "same") |
|
1579 | # filteredPower = numpy.correlate(dataArray, dataArray[0:self.__nSamples], "same") | |
| 1576 | # |
|
1580 | # | |
| 1577 | # maxValue = numpy.nanmax(filteredPower) |
|
1581 | # maxValue = numpy.nanmax(filteredPower) | |
| 1578 | # |
|
1582 | # | |
| 1579 | # if maxValue < noisedB + 10: |
|
1583 | # if maxValue < noisedB + 10: | |
| 1580 | # #No se encuentra ningun pulso de transmision |
|
1584 | # #No se encuentra ningun pulso de transmision | |
| 1581 | # return None |
|
1585 | # return None | |
| 1582 | # |
|
1586 | # | |
| 1583 | # maxValuesIndex = numpy.where(filteredPower > maxValue - 0.1*abs(maxValue))[0] |
|
1587 | # maxValuesIndex = numpy.where(filteredPower > maxValue - 0.1*abs(maxValue))[0] | |
| 1584 | # |
|
1588 | # | |
| 1585 | # if len(maxValuesIndex) < 2: |
|
1589 | # if len(maxValuesIndex) < 2: | |
| 1586 | # #Solo se encontro un solo pulso de transmision de un baudio, esperando por el siguiente TX |
|
1590 | # #Solo se encontro un solo pulso de transmision de un baudio, esperando por el siguiente TX | |
| 1587 | # return None |
|
1591 | # return None | |
| 1588 | # |
|
1592 | # | |
| 1589 | # phasedMaxValuesIndex = maxValuesIndex - self.__nSamples |
|
1593 | # phasedMaxValuesIndex = maxValuesIndex - self.__nSamples | |
| 1590 | # |
|
1594 | # | |
| 1591 | # #Seleccionar solo valores con un espaciamiento de nSamples |
|
1595 | # #Seleccionar solo valores con un espaciamiento de nSamples | |
| 1592 | # pulseIndex = numpy.intersect1d(maxValuesIndex, phasedMaxValuesIndex) |
|
1596 | # pulseIndex = numpy.intersect1d(maxValuesIndex, phasedMaxValuesIndex) | |
| 1593 | # |
|
1597 | # | |
| 1594 | # if len(pulseIndex) < 2: |
|
1598 | # if len(pulseIndex) < 2: | |
| 1595 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 |
|
1599 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 | |
| 1596 | # return None |
|
1600 | # return None | |
| 1597 | # |
|
1601 | # | |
| 1598 | # spacing = pulseIndex[1:] - pulseIndex[:-1] |
|
1602 | # spacing = pulseIndex[1:] - pulseIndex[:-1] | |
| 1599 | # |
|
1603 | # | |
| 1600 | # #remover senales que se distancien menos de 10 unidades o muestras |
|
1604 | # #remover senales que se distancien menos de 10 unidades o muestras | |
| 1601 | # #(No deberian existir IPP menor a 10 unidades) |
|
1605 | # #(No deberian existir IPP menor a 10 unidades) | |
| 1602 | # |
|
1606 | # | |
| 1603 | # realIndex = numpy.where(spacing > 10 )[0] |
|
1607 | # realIndex = numpy.where(spacing > 10 )[0] | |
| 1604 | # |
|
1608 | # | |
| 1605 | # if len(realIndex) < 2: |
|
1609 | # if len(realIndex) < 2: | |
| 1606 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 |
|
1610 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 | |
| 1607 | # return None |
|
1611 | # return None | |
| 1608 | # |
|
1612 | # | |
| 1609 | # #Eliminar pulsos anchos (deja solo la diferencia entre IPPs) |
|
1613 | # #Eliminar pulsos anchos (deja solo la diferencia entre IPPs) | |
| 1610 | # realPulseIndex = pulseIndex[realIndex] |
|
1614 | # realPulseIndex = pulseIndex[realIndex] | |
| 1611 | # |
|
1615 | # | |
| 1612 | # period = mode(realPulseIndex[1:] - realPulseIndex[:-1])[0][0] |
|
1616 | # period = mode(realPulseIndex[1:] - realPulseIndex[:-1])[0][0] | |
| 1613 | # |
|
1617 | # | |
| 1614 | # print "IPP = %d samples" %period |
|
1618 | # print "IPP = %d samples" %period | |
| 1615 | # |
|
1619 | # | |
| 1616 | # self.__newNSamples = dataOut.nHeights #int(period) |
|
1620 | # self.__newNSamples = dataOut.nHeights #int(period) | |
| 1617 | # self.__startIndex = int(realPulseIndex[0]) |
|
1621 | # self.__startIndex = int(realPulseIndex[0]) | |
| 1618 | # |
|
1622 | # | |
| 1619 | # return 1 |
|
1623 | # return 1 | |
| 1620 | # |
|
1624 | # | |
| 1621 | # |
|
1625 | # | |
| 1622 | # def setup(self, nSamples, nChannels, buffer_size = 4): |
|
1626 | # def setup(self, nSamples, nChannels, buffer_size = 4): | |
| 1623 | # |
|
1627 | # | |
| 1624 | # self.__powBuffer = collections.deque(numpy.zeros( buffer_size*nSamples,dtype=numpy.float), |
|
1628 | # self.__powBuffer = collections.deque(numpy.zeros( buffer_size*nSamples,dtype=numpy.float), | |
| 1625 | # maxlen = buffer_size*nSamples) |
|
1629 | # maxlen = buffer_size*nSamples) | |
| 1626 | # |
|
1630 | # | |
| 1627 | # bufferList = [] |
|
1631 | # bufferList = [] | |
| 1628 | # |
|
1632 | # | |
| 1629 | # for i in range(nChannels): |
|
1633 | # for i in range(nChannels): | |
| 1630 | # bufferByChannel = collections.deque(numpy.zeros( buffer_size*nSamples, dtype=numpy.complex) + numpy.NAN, |
|
1634 | # bufferByChannel = collections.deque(numpy.zeros( buffer_size*nSamples, dtype=numpy.complex) + numpy.NAN, | |
| 1631 | # maxlen = buffer_size*nSamples) |
|
1635 | # maxlen = buffer_size*nSamples) | |
| 1632 | # |
|
1636 | # | |
| 1633 | # bufferList.append(bufferByChannel) |
|
1637 | # bufferList.append(bufferByChannel) | |
| 1634 | # |
|
1638 | # | |
| 1635 | # self.__nSamples = nSamples |
|
1639 | # self.__nSamples = nSamples | |
| 1636 | # self.__nChannels = nChannels |
|
1640 | # self.__nChannels = nChannels | |
| 1637 | # self.__bufferList = bufferList |
|
1641 | # self.__bufferList = bufferList | |
| 1638 | # |
|
1642 | # | |
| 1639 | # def run(self, dataOut, channel = 0): |
|
1643 | # def run(self, dataOut, channel = 0): | |
| 1640 | # |
|
1644 | # | |
| 1641 | # if not self.isConfig: |
|
1645 | # if not self.isConfig: | |
| 1642 | # nSamples = dataOut.nHeights |
|
1646 | # nSamples = dataOut.nHeights | |
| 1643 | # nChannels = dataOut.nChannels |
|
1647 | # nChannels = dataOut.nChannels | |
| 1644 | # self.setup(nSamples, nChannels) |
|
1648 | # self.setup(nSamples, nChannels) | |
| 1645 | # self.isConfig = True |
|
1649 | # self.isConfig = True | |
| 1646 | # |
|
1650 | # | |
| 1647 | # #Append new data to internal buffer |
|
1651 | # #Append new data to internal buffer | |
| 1648 | # for thisChannel in range(self.__nChannels): |
|
1652 | # for thisChannel in range(self.__nChannels): | |
| 1649 | # bufferByChannel = self.__bufferList[thisChannel] |
|
1653 | # bufferByChannel = self.__bufferList[thisChannel] | |
| 1650 | # bufferByChannel.extend(dataOut.data[thisChannel]) |
|
1654 | # bufferByChannel.extend(dataOut.data[thisChannel]) | |
| 1651 | # |
|
1655 | # | |
| 1652 | # if self.__pulseFound: |
|
1656 | # if self.__pulseFound: | |
| 1653 | # self.__startIndex -= self.__nSamples |
|
1657 | # self.__startIndex -= self.__nSamples | |
| 1654 | # |
|
1658 | # | |
| 1655 | # #Finding Tx Pulse |
|
1659 | # #Finding Tx Pulse | |
| 1656 | # if not self.__pulseFound: |
|
1660 | # if not self.__pulseFound: | |
| 1657 | # indexFound = self.__findTxPulse(dataOut, channel) |
|
1661 | # indexFound = self.__findTxPulse(dataOut, channel) | |
| 1658 | # |
|
1662 | # | |
| 1659 | # if indexFound == None: |
|
1663 | # if indexFound == None: | |
| 1660 | # dataOut.flagNoData = True |
|
1664 | # dataOut.flagNoData = True | |
| 1661 | # return |
|
1665 | # return | |
| 1662 | # |
|
1666 | # | |
| 1663 | # self.__arrayBuffer = numpy.zeros((self.__nChannels, self.__newNSamples), dtype = numpy.complex) |
|
1667 | # self.__arrayBuffer = numpy.zeros((self.__nChannels, self.__newNSamples), dtype = numpy.complex) | |
| 1664 | # self.__pulseFound = True |
|
1668 | # self.__pulseFound = True | |
| 1665 | # self.__startIndex = indexFound |
|
1669 | # self.__startIndex = indexFound | |
| 1666 | # |
|
1670 | # | |
| 1667 | # #If pulse was found ... |
|
1671 | # #If pulse was found ... | |
| 1668 | # for thisChannel in range(self.__nChannels): |
|
1672 | # for thisChannel in range(self.__nChannels): | |
| 1669 | # bufferByChannel = self.__bufferList[thisChannel] |
|
1673 | # bufferByChannel = self.__bufferList[thisChannel] | |
| 1670 | # #print self.__startIndex |
|
1674 | # #print self.__startIndex | |
| 1671 | # x = numpy.array(bufferByChannel) |
|
1675 | # x = numpy.array(bufferByChannel) | |
| 1672 | # self.__arrayBuffer[thisChannel] = x[self.__startIndex:self.__startIndex+self.__newNSamples] |
|
1676 | # self.__arrayBuffer[thisChannel] = x[self.__startIndex:self.__startIndex+self.__newNSamples] | |
| 1673 | # |
|
1677 | # | |
| 1674 | # deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1678 | # deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1675 | # dataOut.heightList = numpy.arange(self.__newNSamples)*deltaHeight |
|
1679 | # dataOut.heightList = numpy.arange(self.__newNSamples)*deltaHeight | |
| 1676 | # # dataOut.ippSeconds = (self.__newNSamples / deltaHeight)/1e6 |
|
1680 | # # dataOut.ippSeconds = (self.__newNSamples / deltaHeight)/1e6 | |
| 1677 | # |
|
1681 | # | |
| 1678 | # dataOut.data = self.__arrayBuffer |
|
1682 | # dataOut.data = self.__arrayBuffer | |
| 1679 | # |
|
1683 | # | |
| 1680 | # self.__startIndex += self.__newNSamples |
|
1684 | # self.__startIndex += self.__newNSamples | |
| 1681 | # |
|
1685 | # | |
| 1682 | # return |
|
1686 | # return | |
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