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| 1 | # Copyright (c) 2012-2020 Jicamarca Radio Observatory |
|
1 | # Copyright (c) 2012-2020 Jicamarca Radio Observatory | |
| 2 | # All rights reserved. |
|
2 | # All rights reserved. | |
| 3 | # |
|
3 | # | |
| 4 | # Distributed under the terms of the BSD 3-clause license. |
|
4 | # Distributed under the terms of the BSD 3-clause license. | |
| 5 | """Classes to plot Spectra data |
|
5 | """Classes to plot Spectra data | |
| 6 |
|
6 | |||
| 7 | """ |
|
7 | """ | |
| 8 |
|
8 | |||
| 9 | import os |
|
9 | import os | |
| 10 | import numpy |
|
10 | import numpy | |
| 11 |
|
11 | |||
| 12 | from schainpy.model.graphics.jroplot_base import Plot, plt, log |
|
12 | from schainpy.model.graphics.jroplot_base import Plot, plt, log | |
| 13 | from itertools import combinations |
|
13 | from itertools import combinations | |
| 14 | from matplotlib.ticker import LinearLocator |
|
14 | from matplotlib.ticker import LinearLocator | |
| 15 |
|
15 | |||
| 16 | from matplotlib import __version__ as plt_version |
|
16 | from matplotlib import __version__ as plt_version | |
| 17 |
|
17 | |||
| 18 | if plt_version >='3.3.4': |
|
18 | if plt_version >='3.3.4': | |
| 19 | EXTRA_POINTS = 0 |
|
19 | EXTRA_POINTS = 0 | |
| 20 | else: |
|
20 | else: | |
| 21 | EXTRA_POINTS = 1 |
|
21 | EXTRA_POINTS = 1 | |
| 22 |
|
22 | |||
| 23 | class SpectraPlot(Plot): |
|
23 | class SpectraPlot(Plot): | |
| 24 | ''' |
|
24 | ''' | |
| 25 | Plot for Spectra data |
|
25 | Plot for Spectra data | |
| 26 | ''' |
|
26 | ''' | |
| 27 |
|
27 | |||
| 28 | CODE = 'spc' |
|
28 | CODE = 'spc' | |
| 29 | colormap = 'jet' |
|
29 | colormap = 'jet' | |
| 30 | plot_type = 'pcolor' |
|
30 | plot_type = 'pcolor' | |
| 31 | buffering = False |
|
31 | buffering = False | |
| 32 | channelList = [] |
|
32 | channelList = [] | |
| 33 | elevationList = [] |
|
33 | elevationList = [] | |
| 34 | azimuthList = [] |
|
34 | azimuthList = [] | |
| 35 |
|
35 | |||
| 36 | def setup(self): |
|
36 | def setup(self): | |
| 37 |
|
37 | |||
| 38 | self.nplots = len(self.data.channels) |
|
38 | self.nplots = len(self.data.channels) | |
| 39 | self.ncols = int(numpy.sqrt(self.nplots) + 0.9) |
|
39 | self.ncols = int(numpy.sqrt(self.nplots) + 0.9) | |
| 40 | self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9) |
|
40 | self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9) | |
| 41 | self.height = 3.4 * self.nrows |
|
41 | self.height = 3.4 * self.nrows | |
| 42 |
|
42 | |||
| 43 | self.cb_label = 'dB' |
|
43 | self.cb_label = 'dB' | |
| 44 | if self.showprofile: |
|
44 | if self.showprofile: | |
| 45 | self.width = 5.2 * self.ncols |
|
45 | self.width = 5.2 * self.ncols | |
| 46 | else: |
|
46 | else: | |
| 47 | self.width = 4.2* self.ncols |
|
47 | self.width = 4.2* self.ncols | |
| 48 | self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.12}) |
|
48 | self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.12}) | |
| 49 | self.ylabel = 'Range [km]' |
|
49 | self.ylabel = 'Range [km]' | |
| 50 |
|
50 | |||
| 51 |
|
51 | |||
| 52 | def update_list(self,dataOut): |
|
52 | def update_list(self,dataOut): | |
| 53 | if len(self.channelList) == 0: |
|
53 | if len(self.channelList) == 0: | |
| 54 | self.channelList = dataOut.channelList |
|
54 | self.channelList = dataOut.channelList | |
| 55 | if len(self.elevationList) == 0: |
|
55 | if len(self.elevationList) == 0: | |
| 56 | self.elevationList = dataOut.elevationList |
|
56 | self.elevationList = dataOut.elevationList | |
| 57 | if len(self.azimuthList) == 0: |
|
57 | if len(self.azimuthList) == 0: | |
| 58 | self.azimuthList = dataOut.azimuthList |
|
58 | self.azimuthList = dataOut.azimuthList | |
| 59 |
|
59 | |||
| 60 | def update(self, dataOut): |
|
60 | def update(self, dataOut): | |
| 61 |
|
61 | |||
| 62 | self.update_list(dataOut) |
|
62 | self.update_list(dataOut) | |
| 63 | data = {} |
|
63 | data = {} | |
| 64 | meta = {} |
|
64 | meta = {} | |
| 65 |
|
65 | |||
| 66 | #data['rti'] = dataOut.getPower() |
|
66 | #data['rti'] = dataOut.getPower() | |
| 67 | norm = dataOut.nProfiles * dataOut.max_nIncohInt * dataOut.nCohInt * dataOut.windowOfFilter |
|
67 | norm = dataOut.nProfiles * dataOut.max_nIncohInt * dataOut.nCohInt * dataOut.windowOfFilter | |
| 68 | noise = 10*numpy.log10(dataOut.getNoise()/norm) |
|
68 | noise = 10*numpy.log10(dataOut.getNoise()/norm) | |
| 69 |
|
69 | |||
| 70 |
|
70 | |||
| 71 | z = numpy.zeros((dataOut.nChannels, dataOut.nFFTPoints, dataOut.nHeights)) |
|
71 | z = numpy.zeros((dataOut.nChannels, dataOut.nFFTPoints, dataOut.nHeights)) | |
| 72 | for ch in range(dataOut.nChannels): |
|
72 | for ch in range(dataOut.nChannels): | |
| 73 | if hasattr(dataOut.normFactor,'ndim'): |
|
73 | if hasattr(dataOut.normFactor,'ndim'): | |
| 74 | if dataOut.normFactor.ndim > 1: |
|
74 | if dataOut.normFactor.ndim > 1: | |
| 75 | z[ch] = (numpy.divide(dataOut.data_spc[ch],dataOut.normFactor[ch])) |
|
75 | z[ch] = (numpy.divide(dataOut.data_spc[ch],dataOut.normFactor[ch])) | |
| 76 |
|
76 | |||
| 77 | else: |
|
77 | else: | |
| 78 | z[ch] = (numpy.divide(dataOut.data_spc[ch],dataOut.normFactor)) |
|
78 | z[ch] = (numpy.divide(dataOut.data_spc[ch],dataOut.normFactor)) | |
| 79 | else: |
|
79 | else: | |
| 80 | z[ch] = (numpy.divide(dataOut.data_spc[ch],dataOut.normFactor)) |
|
80 | z[ch] = (numpy.divide(dataOut.data_spc[ch],dataOut.normFactor)) | |
| 81 |
|
81 | |||
| 82 |
|
82 | |||
| 83 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
83 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | |
| 84 | spc = 10*numpy.log10(z) |
|
84 | spc = 10*numpy.log10(z) | |
| 85 |
|
85 | |||
| 86 | data['spc'] = spc |
|
86 | data['spc'] = spc | |
| 87 | #print(spc[0].shape) |
|
87 | #print(spc[0].shape) | |
| 88 | data['rti'] = spc.mean(axis=1) |
|
88 | data['rti'] = spc.mean(axis=1) | |
| 89 | data['noise'] = noise |
|
89 | data['noise'] = noise | |
| 90 | meta['xrange'] = (dataOut.getFreqRange(EXTRA_POINTS)/1000., dataOut.getAcfRange(EXTRA_POINTS), dataOut.getVelRange(EXTRA_POINTS)) |
|
90 | meta['xrange'] = (dataOut.getFreqRange(EXTRA_POINTS)/1000., dataOut.getAcfRange(EXTRA_POINTS), dataOut.getVelRange(EXTRA_POINTS)) | |
| 91 | if self.CODE == 'spc_moments': |
|
91 | if self.CODE == 'spc_moments': | |
| 92 | data['moments'] = dataOut.moments |
|
92 | data['moments'] = dataOut.moments | |
| 93 |
|
93 | |||
| 94 | return data, meta |
|
94 | return data, meta | |
| 95 |
|
95 | |||
| 96 | def plot(self): |
|
96 | def plot(self): | |
| 97 | if self.xaxis == "frequency": |
|
97 | if self.xaxis == "frequency": | |
| 98 | x = self.data.xrange[0] |
|
98 | x = self.data.xrange[0] | |
| 99 | self.xlabel = "Frequency (kHz)" |
|
99 | self.xlabel = "Frequency (kHz)" | |
| 100 | elif self.xaxis == "time": |
|
100 | elif self.xaxis == "time": | |
| 101 | x = self.data.xrange[1] |
|
101 | x = self.data.xrange[1] | |
| 102 | self.xlabel = "Time (ms)" |
|
102 | self.xlabel = "Time (ms)" | |
| 103 | else: |
|
103 | else: | |
| 104 | x = self.data.xrange[2] |
|
104 | x = self.data.xrange[2] | |
| 105 | self.xlabel = "Velocity (m/s)" |
|
105 | self.xlabel = "Velocity (m/s)" | |
| 106 |
|
106 | |||
| 107 | if self.CODE == 'spc_moments': |
|
107 | if self.CODE == 'spc_moments': | |
| 108 | x = self.data.xrange[2] |
|
108 | x = self.data.xrange[2] | |
| 109 | self.xlabel = "Velocity (m/s)" |
|
109 | self.xlabel = "Velocity (m/s)" | |
| 110 |
|
110 | |||
| 111 | self.titles = [] |
|
111 | self.titles = [] | |
| 112 | y = self.data.yrange |
|
112 | y = self.data.yrange | |
| 113 | self.y = y |
|
113 | self.y = y | |
| 114 |
|
114 | |||
| 115 | data = self.data[-1] |
|
115 | data = self.data[-1] | |
| 116 | z = data['spc'] |
|
116 | z = data['spc'] | |
| 117 | #print(z.shape, x.shape, y.shape) |
|
117 | #print(z.shape, x.shape, y.shape) | |
| 118 | for n, ax in enumerate(self.axes): |
|
118 | for n, ax in enumerate(self.axes): | |
| 119 | noise = self.data['noise'][n][0] |
|
119 | noise = self.data['noise'][n][0] | |
| 120 | #print(noise) |
|
120 | #print(noise) | |
| 121 | if self.CODE == 'spc_moments': |
|
121 | if self.CODE == 'spc_moments': | |
| 122 | mean = data['moments'][n, 1] |
|
122 | mean = data['moments'][n, 1] | |
| 123 | if ax.firsttime: |
|
123 | if ax.firsttime: | |
| 124 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) |
|
124 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) | |
| 125 | self.xmin = self.xmin if self.xmin else -self.xmax |
|
125 | self.xmin = self.xmin if self.xmin else -self.xmax | |
| 126 | self.zmin = self.zmin if self.zmin else numpy.nanmin(z) |
|
126 | self.zmin = self.zmin if self.zmin else numpy.nanmin(z) | |
| 127 | self.zmax = self.zmax if self.zmax else numpy.nanmax(z) |
|
127 | self.zmax = self.zmax if self.zmax else numpy.nanmax(z) | |
| 128 | ax.plt = ax.pcolormesh(x, y, z[n].T, |
|
128 | ax.plt = ax.pcolormesh(x, y, z[n].T, | |
| 129 | vmin=self.zmin, |
|
129 | vmin=self.zmin, | |
| 130 | vmax=self.zmax, |
|
130 | vmax=self.zmax, | |
| 131 | cmap=plt.get_cmap(self.colormap) |
|
131 | cmap=plt.get_cmap(self.colormap) | |
| 132 | ) |
|
132 | ) | |
| 133 |
|
133 | |||
| 134 | if self.showprofile: |
|
134 | if self.showprofile: | |
| 135 | ax.plt_profile = self.pf_axes[n].plot( |
|
135 | ax.plt_profile = self.pf_axes[n].plot( | |
| 136 | data['rti'][n], y)[0] |
|
136 | data['rti'][n], y)[0] | |
| 137 | # ax.plt_noise = self.pf_axes[n].plot(numpy.repeat(noise, len(y)), y, |
|
137 | # ax.plt_noise = self.pf_axes[n].plot(numpy.repeat(noise, len(y)), y, | |
| 138 | # color="k", linestyle="dashed", lw=1)[0] |
|
138 | # color="k", linestyle="dashed", lw=1)[0] | |
| 139 | if self.CODE == 'spc_moments': |
|
139 | if self.CODE == 'spc_moments': | |
| 140 | ax.plt_mean = ax.plot(mean, y, color='k')[0] |
|
140 | ax.plt_mean = ax.plot(mean, y, color='k')[0] | |
| 141 | else: |
|
141 | else: | |
| 142 | ax.plt.set_array(z[n].T.ravel()) |
|
142 | ax.plt.set_array(z[n].T.ravel()) | |
| 143 | if self.showprofile: |
|
143 | if self.showprofile: | |
| 144 | ax.plt_profile.set_data(data['rti'][n], y) |
|
144 | ax.plt_profile.set_data(data['rti'][n], y) | |
| 145 | #ax.plt_noise.set_data(numpy.repeat(noise, len(y)), y) |
|
145 | #ax.plt_noise.set_data(numpy.repeat(noise, len(y)), y) | |
| 146 | if self.CODE == 'spc_moments': |
|
146 | if self.CODE == 'spc_moments': | |
| 147 | ax.plt_mean.set_data(mean, y) |
|
147 | ax.plt_mean.set_data(mean, y) | |
| 148 | if len(self.azimuthList) > 0 and len(self.elevationList) > 0: |
|
148 | if len(self.azimuthList) > 0 and len(self.elevationList) > 0: | |
| 149 | self.titles.append('CH {}: {:2.1f}elv {:2.1f}az {:3.2f}dB'.format(self.channelList[n], noise, self.elevationList[n], self.azimuthList[n])) |
|
149 | self.titles.append('CH {}: {:2.1f}elv {:2.1f}az {:3.2f}dB'.format(self.channelList[n], noise, self.elevationList[n], self.azimuthList[n])) | |
| 150 | else: |
|
150 | else: | |
| 151 | self.titles.append('CH {}: {:3.2f}dB'.format(self.channelList[n], noise)) |
|
151 | self.titles.append('CH {}: {:3.2f}dB'.format(self.channelList[n], noise)) | |
| 152 |
|
152 | |||
| 153 |
|
153 | |||
| 154 | class CrossSpectraPlot(Plot): |
|
154 | class CrossSpectraPlot(Plot): | |
| 155 |
|
155 | |||
| 156 | CODE = 'cspc' |
|
156 | CODE = 'cspc' | |
| 157 | colormap = 'jet' |
|
157 | colormap = 'jet' | |
| 158 | plot_type = 'pcolor' |
|
158 | plot_type = 'pcolor' | |
| 159 | zmin_coh = None |
|
159 | zmin_coh = None | |
| 160 | zmax_coh = None |
|
160 | zmax_coh = None | |
| 161 | zmin_phase = None |
|
161 | zmin_phase = None | |
| 162 | zmax_phase = None |
|
162 | zmax_phase = None | |
| 163 | realChannels = None |
|
163 | realChannels = None | |
| 164 | crossPairs = None |
|
164 | crossPairs = None | |
| 165 |
|
165 | |||
| 166 | def setup(self): |
|
166 | def setup(self): | |
| 167 |
|
167 | |||
| 168 | self.ncols = 4 |
|
168 | self.ncols = 4 | |
| 169 | self.nplots = len(self.data.pairs) * 2 |
|
169 | self.nplots = len(self.data.pairs) * 2 | |
| 170 | self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9) |
|
170 | self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9) | |
| 171 | self.width = 3.1 * self.ncols |
|
171 | self.width = 3.1 * self.ncols | |
| 172 | self.height = 2.6 * self.nrows |
|
172 | self.height = 2.6 * self.nrows | |
| 173 | self.ylabel = 'Range [km]' |
|
173 | self.ylabel = 'Range [km]' | |
| 174 | self.showprofile = False |
|
174 | self.showprofile = False | |
| 175 | self.plots_adjust.update({'left': 0.08, 'right': 0.92, 'wspace': 0.5, 'hspace':0.4, 'top':0.95, 'bottom': 0.08}) |
|
175 | self.plots_adjust.update({'left': 0.08, 'right': 0.92, 'wspace': 0.5, 'hspace':0.4, 'top':0.95, 'bottom': 0.08}) | |
| 176 |
|
176 | |||
| 177 | def update(self, dataOut): |
|
177 | def update(self, dataOut): | |
| 178 |
|
178 | |||
| 179 | data = {} |
|
179 | data = {} | |
| 180 | meta = {} |
|
180 | meta = {} | |
| 181 |
|
181 | |||
| 182 | spc = dataOut.data_spc |
|
182 | spc = dataOut.data_spc | |
| 183 | cspc = dataOut.data_cspc |
|
183 | cspc = dataOut.data_cspc | |
| 184 | meta['xrange'] = (dataOut.getFreqRange(EXTRA_POINTS)/1000., dataOut.getAcfRange(EXTRA_POINTS), dataOut.getVelRange(EXTRA_POINTS)) |
|
184 | meta['xrange'] = (dataOut.getFreqRange(EXTRA_POINTS)/1000., dataOut.getAcfRange(EXTRA_POINTS), dataOut.getVelRange(EXTRA_POINTS)) | |
| 185 | rawPairs = list(combinations(list(range(dataOut.nChannels)), 2)) |
|
185 | rawPairs = list(combinations(list(range(dataOut.nChannels)), 2)) | |
| 186 | meta['pairs'] = rawPairs |
|
186 | meta['pairs'] = rawPairs | |
| 187 |
|
187 | |||
| 188 | if self.crossPairs == None: |
|
188 | if self.crossPairs == None: | |
| 189 | self.crossPairs = dataOut.pairsList |
|
189 | self.crossPairs = dataOut.pairsList | |
| 190 |
|
190 | |||
| 191 | tmp = [] |
|
191 | tmp = [] | |
| 192 |
|
192 | |||
| 193 | for n, pair in enumerate(meta['pairs']): |
|
193 | for n, pair in enumerate(meta['pairs']): | |
| 194 |
|
194 | |||
| 195 | out = cspc[n] / numpy.sqrt(spc[pair[0]] * spc[pair[1]]) |
|
195 | out = cspc[n] / numpy.sqrt(spc[pair[0]] * spc[pair[1]]) | |
| 196 | coh = numpy.abs(out) |
|
196 | coh = numpy.abs(out) | |
| 197 | phase = numpy.arctan2(out.imag, out.real) * 180 / numpy.pi |
|
197 | phase = numpy.arctan2(out.imag, out.real) * 180 / numpy.pi | |
| 198 | tmp.append(coh) |
|
198 | tmp.append(coh) | |
| 199 | tmp.append(phase) |
|
199 | tmp.append(phase) | |
| 200 |
|
200 | |||
| 201 | data['cspc'] = numpy.array(tmp) |
|
201 | data['cspc'] = numpy.array(tmp) | |
| 202 |
|
202 | |||
| 203 | return data, meta |
|
203 | return data, meta | |
| 204 |
|
204 | |||
| 205 | def plot(self): |
|
205 | def plot(self): | |
| 206 |
|
206 | |||
| 207 | if self.xaxis == "frequency": |
|
207 | if self.xaxis == "frequency": | |
| 208 | x = self.data.xrange[0] |
|
208 | x = self.data.xrange[0] | |
| 209 | self.xlabel = "Frequency (kHz)" |
|
209 | self.xlabel = "Frequency (kHz)" | |
| 210 | elif self.xaxis == "time": |
|
210 | elif self.xaxis == "time": | |
| 211 | x = self.data.xrange[1] |
|
211 | x = self.data.xrange[1] | |
| 212 | self.xlabel = "Time (ms)" |
|
212 | self.xlabel = "Time (ms)" | |
| 213 | else: |
|
213 | else: | |
| 214 | x = self.data.xrange[2] |
|
214 | x = self.data.xrange[2] | |
| 215 | self.xlabel = "Velocity (m/s)" |
|
215 | self.xlabel = "Velocity (m/s)" | |
| 216 |
|
216 | |||
| 217 | self.titles = [] |
|
217 | self.titles = [] | |
| 218 |
|
218 | |||
| 219 | y = self.data.yrange |
|
219 | y = self.data.yrange | |
| 220 | self.y = y |
|
220 | self.y = y | |
| 221 |
|
221 | |||
| 222 | data = self.data[-1] |
|
222 | data = self.data[-1] | |
| 223 | cspc = data['cspc'] |
|
223 | cspc = data['cspc'] | |
| 224 |
|
224 | |||
| 225 | for n in range(len(self.data.pairs)): |
|
225 | for n in range(len(self.data.pairs)): | |
| 226 |
|
226 | |||
| 227 | pair = self.crossPairs[n] |
|
227 | pair = self.crossPairs[n] | |
| 228 |
|
228 | |||
| 229 | coh = cspc[n*2] |
|
229 | coh = cspc[n*2] | |
| 230 | phase = cspc[n*2+1] |
|
230 | phase = cspc[n*2+1] | |
| 231 | ax = self.axes[2 * n] |
|
231 | ax = self.axes[2 * n] | |
| 232 |
|
232 | |||
| 233 | if ax.firsttime: |
|
233 | if ax.firsttime: | |
| 234 | ax.plt = ax.pcolormesh(x, y, coh.T, |
|
234 | ax.plt = ax.pcolormesh(x, y, coh.T, | |
| 235 | vmin=self.zmin_coh, |
|
235 | vmin=self.zmin_coh, | |
| 236 | vmax=self.zmax_coh, |
|
236 | vmax=self.zmax_coh, | |
| 237 | cmap=plt.get_cmap(self.colormap_coh) |
|
237 | cmap=plt.get_cmap(self.colormap_coh) | |
| 238 | ) |
|
238 | ) | |
| 239 | else: |
|
239 | else: | |
| 240 | ax.plt.set_array(coh.T.ravel()) |
|
240 | ax.plt.set_array(coh.T.ravel()) | |
| 241 | self.titles.append( |
|
241 | self.titles.append( | |
| 242 | 'Coherence Ch{} * Ch{}'.format(pair[0], pair[1])) |
|
242 | 'Coherence Ch{} * Ch{}'.format(pair[0], pair[1])) | |
| 243 |
|
243 | |||
| 244 | ax = self.axes[2 * n + 1] |
|
244 | ax = self.axes[2 * n + 1] | |
| 245 | if ax.firsttime: |
|
245 | if ax.firsttime: | |
| 246 | ax.plt = ax.pcolormesh(x, y, phase.T, |
|
246 | ax.plt = ax.pcolormesh(x, y, phase.T, | |
| 247 | vmin=-180, |
|
247 | vmin=-180, | |
| 248 | vmax=180, |
|
248 | vmax=180, | |
| 249 | cmap=plt.get_cmap(self.colormap_phase) |
|
249 | cmap=plt.get_cmap(self.colormap_phase) | |
| 250 | ) |
|
250 | ) | |
| 251 | else: |
|
251 | else: | |
| 252 | ax.plt.set_array(phase.T.ravel()) |
|
252 | ax.plt.set_array(phase.T.ravel()) | |
| 253 |
|
253 | |||
| 254 | self.titles.append('Phase CH{} * CH{}'.format(pair[0], pair[1])) |
|
254 | self.titles.append('Phase CH{} * CH{}'.format(pair[0], pair[1])) | |
| 255 |
|
255 | |||
| 256 |
|
256 | |||
| 257 | class RTIPlot(Plot): |
|
257 | class RTIPlot(Plot): | |
| 258 | ''' |
|
258 | ''' | |
| 259 | Plot for RTI data |
|
259 | Plot for RTI data | |
| 260 | ''' |
|
260 | ''' | |
| 261 |
|
261 | |||
| 262 | CODE = 'rti' |
|
262 | CODE = 'rti' | |
| 263 | colormap = 'jet' |
|
263 | colormap = 'jet' | |
| 264 | plot_type = 'pcolorbuffer' |
|
264 | plot_type = 'pcolorbuffer' | |
| 265 | titles = None |
|
265 | titles = None | |
| 266 | channelList = [] |
|
266 | channelList = [] | |
| 267 | elevationList = [] |
|
267 | elevationList = [] | |
| 268 | azimuthList = [] |
|
268 | azimuthList = [] | |
| 269 |
|
269 | |||
| 270 | def setup(self): |
|
270 | def setup(self): | |
| 271 | self.xaxis = 'time' |
|
271 | self.xaxis = 'time' | |
| 272 | self.ncols = 1 |
|
272 | self.ncols = 1 | |
| 273 | #print("dataChannels ",self.data.channels) |
|
273 | #print("dataChannels ",self.data.channels) | |
| 274 | self.nrows = len(self.data.channels) |
|
274 | self.nrows = len(self.data.channels) | |
| 275 | self.nplots = len(self.data.channels) |
|
275 | self.nplots = len(self.data.channels) | |
| 276 | self.ylabel = 'Range [km]' |
|
276 | self.ylabel = 'Range [km]' | |
| 277 | self.xlabel = 'Time' |
|
277 | #self.xlabel = 'Time' | |
| 278 | self.cb_label = 'dB' |
|
278 | self.cb_label = 'dB' | |
| 279 | self.plots_adjust.update({'hspace':0.8, 'left': 0.08, 'bottom': 0.2, 'right':0.94}) |
|
279 | self.plots_adjust.update({'hspace':0.8, 'left': 0.08, 'bottom': 0.2, 'right':0.94}) | |
| 280 | self.titles = ['{} Channel {}'.format( |
|
280 | self.titles = ['{} Channel {}'.format( | |
| 281 | self.CODE.upper(), x) for x in range(self.nplots)] |
|
281 | self.CODE.upper(), x) for x in range(self.nplots)] | |
| 282 |
|
282 | |||
| 283 | def update_list(self,dataOut): |
|
283 | def update_list(self,dataOut): | |
| 284 |
|
284 | |||
| 285 | if len(self.channelList) == 0: |
|
285 | if len(self.channelList) == 0: | |
| 286 | self.channelList = dataOut.channelList |
|
286 | self.channelList = dataOut.channelList | |
| 287 | if len(self.elevationList) == 0: |
|
287 | if len(self.elevationList) == 0: | |
| 288 | self.elevationList = dataOut.elevationList |
|
288 | self.elevationList = dataOut.elevationList | |
| 289 | if len(self.azimuthList) == 0: |
|
289 | if len(self.azimuthList) == 0: | |
| 290 | self.azimuthList = dataOut.azimuthList |
|
290 | self.azimuthList = dataOut.azimuthList | |
| 291 |
|
291 | |||
| 292 |
|
292 | |||
| 293 | def update(self, dataOut): |
|
293 | def update(self, dataOut): | |
| 294 | if len(self.channelList) == 0: |
|
294 | if len(self.channelList) == 0: | |
| 295 | self.update_list(dataOut) |
|
295 | self.update_list(dataOut) | |
| 296 | data = {} |
|
296 | data = {} | |
| 297 | meta = {} |
|
297 | meta = {} | |
| 298 |
|
298 | |||
| 299 | data['rti'] = dataOut.getPower() |
|
299 | data['rti'] = dataOut.getPower() | |
| 300 |
|
300 | |||
| 301 | norm = dataOut.nProfiles * dataOut.max_nIncohInt * dataOut.nCohInt * dataOut.windowOfFilter |
|
301 | norm = dataOut.nProfiles * dataOut.max_nIncohInt * dataOut.nCohInt * dataOut.windowOfFilter | |
| 302 | noise = 10*numpy.log10(dataOut.getNoise()/norm) |
|
302 | noise = 10*numpy.log10(dataOut.getNoise()/norm) | |
| 303 | data['noise'] = noise |
|
303 | data['noise'] = noise | |
| 304 |
|
304 | |||
| 305 | return data, meta |
|
305 | return data, meta | |
| 306 |
|
306 | |||
| 307 | def plot(self): |
|
307 | def plot(self): | |
| 308 |
|
308 | |||
| 309 | self.x = self.data.times |
|
309 | self.x = self.data.times | |
| 310 | self.y = self.data.yrange |
|
310 | self.y = self.data.yrange | |
| 311 | #print(" x, y: ",self.x, self.y) |
|
311 | #print(" x, y: ",self.x, self.y) | |
| 312 | self.z = self.data[self.CODE] |
|
312 | self.z = self.data[self.CODE] | |
| 313 | self.z = numpy.array(self.z, dtype=float) |
|
313 | self.z = numpy.array(self.z, dtype=float) | |
| 314 | self.z = numpy.ma.masked_invalid(self.z) |
|
314 | self.z = numpy.ma.masked_invalid(self.z) | |
| 315 |
|
315 | |||
| 316 | try: |
|
316 | try: | |
| 317 | if self.channelList != None: |
|
317 | if self.channelList != None: | |
| 318 | if len(self.elevationList) > 0 and len(self.azimuthList) > 0: |
|
318 | if len(self.elevationList) > 0 and len(self.azimuthList) > 0: | |
| 319 | self.titles = ['{} Channel {} ({:2.1f} Elev, {:2.1f} Azth)'.format( |
|
319 | self.titles = ['{} Channel {} ({:2.1f} Elev, {:2.1f} Azth)'.format( | |
| 320 | self.CODE.upper(), x, self.elevationList[x], self.azimuthList[x]) for x in self.channelList] |
|
320 | self.CODE.upper(), x, self.elevationList[x], self.azimuthList[x]) for x in self.channelList] | |
| 321 | else: |
|
321 | else: | |
| 322 | self.titles = ['{} Channel {}'.format( |
|
322 | self.titles = ['{} Channel {}'.format( | |
| 323 | self.CODE.upper(), x) for x in self.channelList] |
|
323 | self.CODE.upper(), x) for x in self.channelList] | |
| 324 | except: |
|
324 | except: | |
| 325 | if self.channelList.any() != None: |
|
325 | if self.channelList.any() != None: | |
| 326 | if len(self.elevationList) > 0 and len(self.azimuthList) > 0: |
|
326 | if len(self.elevationList) > 0 and len(self.azimuthList) > 0: | |
| 327 | self.titles = ['{} Channel {} ({:2.1f} Elev, {:2.1f} Azth)'.format( |
|
327 | self.titles = ['{} Channel {} ({:2.1f} Elev, {:2.1f} Azth)'.format( | |
| 328 | self.CODE.upper(), x, self.elevationList[x], self.azimuthList[x]) for x in self.channelList] |
|
328 | self.CODE.upper(), x, self.elevationList[x], self.azimuthList[x]) for x in self.channelList] | |
| 329 | else: |
|
329 | else: | |
| 330 | self.titles = ['{} Channel {}'.format( |
|
330 | self.titles = ['{} Channel {}'.format( | |
| 331 | self.CODE.upper(), x) for x in self.channelList] |
|
331 | self.CODE.upper(), x) for x in self.channelList] | |
| 332 |
|
332 | |||
| 333 | if self.decimation is None: |
|
333 | if self.decimation is None: | |
| 334 | x, y, z = self.fill_gaps(self.x, self.y, self.z) |
|
334 | x, y, z = self.fill_gaps(self.x, self.y, self.z) | |
| 335 | else: |
|
335 | else: | |
| 336 | x, y, z = self.fill_gaps(*self.decimate()) |
|
336 | x, y, z = self.fill_gaps(*self.decimate()) | |
| 337 |
|
337 | |||
| 338 | #dummy_var = self.axes #ExtraΓ±amente esto actualiza el valor axes |
|
338 | #dummy_var = self.axes #ExtraΓ±amente esto actualiza el valor axes | |
| 339 | for n, ax in enumerate(self.axes): |
|
339 | for n, ax in enumerate(self.axes): | |
| 340 | self.zmin = self.zmin if self.zmin else numpy.min(self.z) |
|
340 | self.zmin = self.zmin if self.zmin else numpy.min(self.z) | |
| 341 | self.zmax = self.zmax if self.zmax else numpy.max(self.z) |
|
341 | self.zmax = self.zmax if self.zmax else numpy.max(self.z) | |
| 342 | data = self.data[-1] |
|
342 | data = self.data[-1] | |
| 343 |
|
343 | |||
| 344 | if ax.firsttime: |
|
344 | if ax.firsttime: | |
|
|
345 | if (n+1) == len(self.channelList): | |||
|
|
346 | ax.set_xlabel('Time') | |||
| 345 | ax.plt = ax.pcolormesh(x, y, z[n].T, |
|
347 | ax.plt = ax.pcolormesh(x, y, z[n].T, | |
| 346 | vmin=self.zmin, |
|
348 | vmin=self.zmin, | |
| 347 | vmax=self.zmax, |
|
349 | vmax=self.zmax, | |
| 348 | cmap=plt.get_cmap(self.colormap) |
|
350 | cmap=plt.get_cmap(self.colormap) | |
| 349 | ) |
|
351 | ) | |
| 350 | if self.showprofile: |
|
352 | if self.showprofile: | |
| 351 | ax.plot_profile = self.pf_axes[n].plot(data[self.CODE][n], self.y)[0] |
|
353 | ax.plot_profile = self.pf_axes[n].plot(data[self.CODE][n], self.y)[0] | |
| 352 | if "noise" in self.data: |
|
354 | if "noise" in self.data: | |
| 353 |
|
355 | |||
| 354 | ax.plot_noise = self.pf_axes[n].plot(numpy.repeat(data['noise'][n], len(self.y)), self.y, |
|
356 | ax.plot_noise = self.pf_axes[n].plot(numpy.repeat(data['noise'][n], len(self.y)), self.y, | |
| 355 | color="k", linestyle="dashed", lw=1)[0] |
|
357 | color="k", linestyle="dashed", lw=1)[0] | |
| 356 | else: |
|
358 | else: | |
| 357 | ax.collections.remove(ax.collections[0]) |
|
359 | ax.collections.remove(ax.collections[0]) | |
| 358 | ax.plt = ax.pcolormesh(x, y, z[n].T, |
|
360 | ax.plt = ax.pcolormesh(x, y, z[n].T, | |
| 359 | vmin=self.zmin, |
|
361 | vmin=self.zmin, | |
| 360 | vmax=self.zmax, |
|
362 | vmax=self.zmax, | |
| 361 | cmap=plt.get_cmap(self.colormap) |
|
363 | cmap=plt.get_cmap(self.colormap) | |
| 362 | ) |
|
364 | ) | |
| 363 | if self.showprofile: |
|
365 | if self.showprofile: | |
| 364 | ax.plot_profile.set_data(data[self.CODE][n], self.y) |
|
366 | ax.plot_profile.set_data(data[self.CODE][n], self.y) | |
| 365 | if "noise" in self.data: |
|
367 | if "noise" in self.data: | |
| 366 | ax.plot_noise.set_data(numpy.repeat(data['noise'][n], len(self.y)), self.y) |
|
368 | ax.plot_noise.set_data(numpy.repeat(data['noise'][n], len(self.y)), self.y) | |
| 367 |
|
369 | |||
| 368 |
|
370 | |||
| 369 | class CoherencePlot(RTIPlot): |
|
371 | class CoherencePlot(RTIPlot): | |
| 370 | ''' |
|
372 | ''' | |
| 371 | Plot for Coherence data |
|
373 | Plot for Coherence data | |
| 372 | ''' |
|
374 | ''' | |
| 373 |
|
375 | |||
| 374 | CODE = 'coh' |
|
376 | CODE = 'coh' | |
| 375 | titles = None |
|
377 | titles = None | |
| 376 |
|
378 | |||
| 377 | def setup(self): |
|
379 | def setup(self): | |
| 378 | self.xaxis = 'time' |
|
380 | self.xaxis = 'time' | |
| 379 | self.ncols = 1 |
|
381 | self.ncols = 1 | |
| 380 | self.nrows = len(self.data.pairs) |
|
382 | self.nrows = len(self.data.pairs) | |
| 381 | self.nplots = len(self.data.pairs) |
|
383 | self.nplots = len(self.data.pairs) | |
| 382 | self.ylabel = 'Range [km]' |
|
384 | self.ylabel = 'Range [km]' | |
| 383 | self.xlabel = 'Time' |
|
385 | #self.xlabel = 'Time' | |
| 384 | self.plots_adjust.update({'hspace':0.6, 'left': 0.1, 'bottom': 0.1,'right':0.95}) |
|
386 | self.plots_adjust.update({'hspace':0.6, 'left': 0.1, 'bottom': 0.1,'right':0.95}) | |
| 385 | if self.CODE == 'coh': |
|
387 | if self.CODE == 'coh': | |
| 386 | self.cb_label = '' |
|
388 | self.cb_label = '' | |
| 387 | self.titles = [ |
|
389 | self.titles = [ | |
| 388 | 'Coherence Map Ch{} * Ch{}'.format(x[0], x[1]) for x in self.data.pairs] |
|
390 | 'Coherence Map Ch{} * Ch{}'.format(x[0], x[1]) for x in self.data.pairs] | |
| 389 | else: |
|
391 | else: | |
| 390 | self.cb_label = 'Degrees' |
|
392 | self.cb_label = 'Degrees' | |
| 391 | self.titles = [ |
|
393 | self.titles = [ | |
| 392 | 'Phase Map Ch{} * Ch{}'.format(x[0], x[1]) for x in self.data.pairs] |
|
394 | 'Phase Map Ch{} * Ch{}'.format(x[0], x[1]) for x in self.data.pairs] | |
| 393 |
|
395 | |||
| 394 |
|
396 | |||
| 395 | def update(self, dataOut): |
|
397 | def update(self, dataOut): | |
| 396 |
|
398 | |||
| 397 | data = {} |
|
399 | data = {} | |
| 398 | meta = {} |
|
400 | meta = {} | |
| 399 | data['coh'] = dataOut.getCoherence() |
|
401 | data['coh'] = dataOut.getCoherence() | |
| 400 | meta['pairs'] = dataOut.pairsList |
|
402 | meta['pairs'] = dataOut.pairsList | |
| 401 |
|
403 | |||
| 402 |
|
404 | |||
| 403 | return data, meta |
|
405 | return data, meta | |
| 404 |
|
406 | |||
| 405 | def plot(self): |
|
407 | def plot(self): | |
| 406 |
|
408 | |||
| 407 | self.x = self.data.times |
|
409 | self.x = self.data.times | |
| 408 | self.y = self.data.yrange |
|
410 | self.y = self.data.yrange | |
| 409 | self.z = self.data[self.CODE] |
|
411 | self.z = self.data[self.CODE] | |
| 410 |
|
412 | |||
| 411 | self.z = numpy.ma.masked_invalid(self.z) |
|
413 | self.z = numpy.ma.masked_invalid(self.z) | |
| 412 |
|
414 | |||
| 413 | if self.decimation is None: |
|
415 | if self.decimation is None: | |
| 414 | x, y, z = self.fill_gaps(self.x, self.y, self.z) |
|
416 | x, y, z = self.fill_gaps(self.x, self.y, self.z) | |
| 415 | else: |
|
417 | else: | |
| 416 | x, y, z = self.fill_gaps(*self.decimate()) |
|
418 | x, y, z = self.fill_gaps(*self.decimate()) | |
| 417 |
|
419 | |||
| 418 | for n, ax in enumerate(self.axes): |
|
420 | for n, ax in enumerate(self.axes): | |
| 419 | self.zmin = self.zmin if self.zmin else numpy.min(self.z) |
|
421 | self.zmin = self.zmin if self.zmin else numpy.min(self.z) | |
| 420 | self.zmax = self.zmax if self.zmax else numpy.max(self.z) |
|
422 | self.zmax = self.zmax if self.zmax else numpy.max(self.z) | |
| 421 | if ax.firsttime: |
|
423 | if ax.firsttime: | |
|
|
424 | if (n+1) == len(self.channelList): | |||
|
|
425 | ax.set_xlabel('Time') | |||
| 422 | ax.plt = ax.pcolormesh(x, y, z[n].T, |
|
426 | ax.plt = ax.pcolormesh(x, y, z[n].T, | |
| 423 | vmin=self.zmin, |
|
427 | vmin=self.zmin, | |
| 424 | vmax=self.zmax, |
|
428 | vmax=self.zmax, | |
| 425 | cmap=plt.get_cmap(self.colormap) |
|
429 | cmap=plt.get_cmap(self.colormap) | |
| 426 | ) |
|
430 | ) | |
| 427 | if self.showprofile: |
|
431 | if self.showprofile: | |
| 428 | ax.plot_profile = self.pf_axes[n].plot( |
|
432 | ax.plot_profile = self.pf_axes[n].plot( | |
| 429 | self.data[self.CODE][n][-1], self.y)[0] |
|
433 | self.data[self.CODE][n][-1], self.y)[0] | |
| 430 | # ax.plot_noise = self.pf_axes[n].plot(numpy.repeat(self.data['noise'][n][-1], len(self.y)), self.y, |
|
434 | # ax.plot_noise = self.pf_axes[n].plot(numpy.repeat(self.data['noise'][n][-1], len(self.y)), self.y, | |
| 431 | # color="k", linestyle="dashed", lw=1)[0] |
|
435 | # color="k", linestyle="dashed", lw=1)[0] | |
| 432 | else: |
|
436 | else: | |
| 433 | ax.collections.remove(ax.collections[0]) |
|
437 | ax.collections.remove(ax.collections[0]) | |
| 434 | ax.plt = ax.pcolormesh(x, y, z[n].T, |
|
438 | ax.plt = ax.pcolormesh(x, y, z[n].T, | |
| 435 | vmin=self.zmin, |
|
439 | vmin=self.zmin, | |
| 436 | vmax=self.zmax, |
|
440 | vmax=self.zmax, | |
| 437 | cmap=plt.get_cmap(self.colormap) |
|
441 | cmap=plt.get_cmap(self.colormap) | |
| 438 | ) |
|
442 | ) | |
| 439 | if self.showprofile: |
|
443 | if self.showprofile: | |
| 440 | ax.plot_profile.set_data(self.data[self.CODE][n][-1], self.y) |
|
444 | ax.plot_profile.set_data(self.data[self.CODE][n][-1], self.y) | |
| 441 | # ax.plot_noise.set_data(numpy.repeat( |
|
445 | # ax.plot_noise.set_data(numpy.repeat( | |
| 442 | # self.data['noise'][n][-1], len(self.y)), self.y) |
|
446 | # self.data['noise'][n][-1], len(self.y)), self.y) | |
| 443 |
|
447 | |||
| 444 |
|
448 | |||
| 445 |
|
449 | |||
| 446 | class PhasePlot(CoherencePlot): |
|
450 | class PhasePlot(CoherencePlot): | |
| 447 | ''' |
|
451 | ''' | |
| 448 | Plot for Phase map data |
|
452 | Plot for Phase map data | |
| 449 | ''' |
|
453 | ''' | |
| 450 |
|
454 | |||
| 451 | CODE = 'phase' |
|
455 | CODE = 'phase' | |
| 452 | colormap = 'seismic' |
|
456 | colormap = 'seismic' | |
| 453 |
|
457 | |||
| 454 | def update(self, dataOut): |
|
458 | def update(self, dataOut): | |
| 455 |
|
459 | |||
| 456 | data = {} |
|
460 | data = {} | |
| 457 | meta = {} |
|
461 | meta = {} | |
| 458 | data['phase'] = dataOut.getCoherence(phase=True) |
|
462 | data['phase'] = dataOut.getCoherence(phase=True) | |
| 459 | meta['pairs'] = dataOut.pairsList |
|
463 | meta['pairs'] = dataOut.pairsList | |
| 460 |
|
464 | |||
| 461 | return data, meta |
|
465 | return data, meta | |
| 462 |
|
466 | |||
| 463 | class NoisePlot(Plot): |
|
467 | class NoisePlot(Plot): | |
| 464 | ''' |
|
468 | ''' | |
| 465 | Plot for noise |
|
469 | Plot for noise | |
| 466 | ''' |
|
470 | ''' | |
| 467 |
|
471 | |||
| 468 | CODE = 'noise' |
|
472 | CODE = 'noise' | |
| 469 | plot_type = 'scatterbuffer' |
|
473 | plot_type = 'scatterbuffer' | |
| 470 |
|
474 | |||
| 471 | def setup(self): |
|
475 | def setup(self): | |
| 472 | self.xaxis = 'time' |
|
476 | self.xaxis = 'time' | |
| 473 | self.ncols = 1 |
|
477 | self.ncols = 1 | |
| 474 | self.nrows = 1 |
|
478 | self.nrows = 1 | |
| 475 | self.nplots = 1 |
|
479 | self.nplots = 1 | |
| 476 | self.ylabel = 'Intensity [dB]' |
|
480 | self.ylabel = 'Intensity [dB]' | |
| 477 | self.xlabel = 'Time' |
|
481 | self.xlabel = 'Time' | |
| 478 | self.titles = ['Noise'] |
|
482 | self.titles = ['Noise'] | |
| 479 | self.colorbar = False |
|
483 | self.colorbar = False | |
| 480 | self.plots_adjust.update({'right': 0.85 }) |
|
484 | self.plots_adjust.update({'right': 0.85 }) | |
| 481 | #if not self.titles: |
|
485 | #if not self.titles: | |
| 482 | self.titles = ['Noise Plot'] |
|
486 | self.titles = ['Noise Plot'] | |
| 483 |
|
487 | |||
| 484 | def update(self, dataOut): |
|
488 | def update(self, dataOut): | |
| 485 |
|
489 | |||
| 486 | data = {} |
|
490 | data = {} | |
| 487 | meta = {} |
|
491 | meta = {} | |
| 488 | norm = dataOut.nProfiles * dataOut.max_nIncohInt * dataOut.nCohInt * dataOut.windowOfFilter |
|
492 | norm = dataOut.nProfiles * dataOut.max_nIncohInt * dataOut.nCohInt * dataOut.windowOfFilter | |
| 489 | noise = 10*numpy.log10(dataOut.getNoise()) |
|
493 | noise = 10*numpy.log10(dataOut.getNoise()) | |
| 490 | noise = noise.reshape(dataOut.nChannels, 1) |
|
494 | noise = noise.reshape(dataOut.nChannels, 1) | |
| 491 | data['noise'] = noise |
|
495 | data['noise'] = noise | |
| 492 | meta['yrange'] = numpy.array([]) |
|
496 | meta['yrange'] = numpy.array([]) | |
| 493 |
|
497 | |||
| 494 | return data, meta |
|
498 | return data, meta | |
| 495 |
|
499 | |||
| 496 | def plot(self): |
|
500 | def plot(self): | |
| 497 |
|
501 | |||
| 498 | x = self.data.times |
|
502 | x = self.data.times | |
| 499 | xmin = self.data.min_time |
|
503 | xmin = self.data.min_time | |
| 500 | xmax = xmin + self.xrange * 60 * 60 |
|
504 | xmax = xmin + self.xrange * 60 * 60 | |
| 501 | Y = self.data['noise'] |
|
505 | Y = self.data['noise'] | |
| 502 |
|
506 | |||
| 503 | if self.axes[0].firsttime: |
|
507 | if self.axes[0].firsttime: | |
| 504 | if self.ymin is None: self.ymin = numpy.nanmin(Y) - 5 |
|
508 | if self.ymin is None: self.ymin = numpy.nanmin(Y) - 5 | |
| 505 | if self.ymax is None: self.ymax = numpy.nanmax(Y) + 5 |
|
509 | if self.ymax is None: self.ymax = numpy.nanmax(Y) + 5 | |
| 506 | for ch in self.data.channels: |
|
510 | for ch in self.data.channels: | |
| 507 | y = Y[ch] |
|
511 | y = Y[ch] | |
| 508 | self.axes[0].plot(x, y, lw=1, label='Ch{}'.format(ch)) |
|
512 | self.axes[0].plot(x, y, lw=1, label='Ch{}'.format(ch)) | |
| 509 | plt.legend(bbox_to_anchor=(1.18, 1.0)) |
|
513 | plt.legend(bbox_to_anchor=(1.18, 1.0)) | |
| 510 | else: |
|
514 | else: | |
| 511 | for ch in self.data.channels: |
|
515 | for ch in self.data.channels: | |
| 512 | y = Y[ch] |
|
516 | y = Y[ch] | |
| 513 | self.axes[0].lines[ch].set_data(x, y) |
|
517 | self.axes[0].lines[ch].set_data(x, y) | |
| 514 |
|
518 | |||
| 515 |
|
519 | |||
| 516 | class PowerProfilePlot(Plot): |
|
520 | class PowerProfilePlot(Plot): | |
| 517 |
|
521 | |||
| 518 | CODE = 'pow_profile' |
|
522 | CODE = 'pow_profile' | |
| 519 | plot_type = 'scatter' |
|
523 | plot_type = 'scatter' | |
| 520 |
|
524 | |||
| 521 | def setup(self): |
|
525 | def setup(self): | |
| 522 |
|
526 | |||
| 523 | self.ncols = 1 |
|
527 | self.ncols = 1 | |
| 524 | self.nrows = 1 |
|
528 | self.nrows = 1 | |
| 525 | self.nplots = 1 |
|
529 | self.nplots = 1 | |
| 526 | self.height = 4 |
|
530 | self.height = 4 | |
| 527 | self.width = 3 |
|
531 | self.width = 3 | |
| 528 | self.ylabel = 'Range [km]' |
|
532 | self.ylabel = 'Range [km]' | |
| 529 | self.xlabel = 'Intensity [dB]' |
|
533 | self.xlabel = 'Intensity [dB]' | |
| 530 | self.titles = ['Power Profile'] |
|
534 | self.titles = ['Power Profile'] | |
| 531 | self.colorbar = False |
|
535 | self.colorbar = False | |
| 532 |
|
536 | |||
| 533 | def update(self, dataOut): |
|
537 | def update(self, dataOut): | |
| 534 |
|
538 | |||
| 535 | data = {} |
|
539 | data = {} | |
| 536 | meta = {} |
|
540 | meta = {} | |
| 537 | data[self.CODE] = dataOut.getPower() |
|
541 | data[self.CODE] = dataOut.getPower() | |
| 538 |
|
542 | |||
| 539 | return data, meta |
|
543 | return data, meta | |
| 540 |
|
544 | |||
| 541 | def plot(self): |
|
545 | def plot(self): | |
| 542 |
|
546 | |||
| 543 | y = self.data.yrange |
|
547 | y = self.data.yrange | |
| 544 | self.y = y |
|
548 | self.y = y | |
| 545 |
|
549 | |||
| 546 | x = self.data[-1][self.CODE] |
|
550 | x = self.data[-1][self.CODE] | |
| 547 |
|
551 | |||
| 548 | if self.xmin is None: self.xmin = numpy.nanmin(x)*0.9 |
|
552 | if self.xmin is None: self.xmin = numpy.nanmin(x)*0.9 | |
| 549 | if self.xmax is None: self.xmax = numpy.nanmax(x)*1.1 |
|
553 | if self.xmax is None: self.xmax = numpy.nanmax(x)*1.1 | |
| 550 |
|
554 | |||
| 551 | if self.axes[0].firsttime: |
|
555 | if self.axes[0].firsttime: | |
| 552 | for ch in self.data.channels: |
|
556 | for ch in self.data.channels: | |
| 553 | self.axes[0].plot(x[ch], y, lw=1, label='Ch{}'.format(ch)) |
|
557 | self.axes[0].plot(x[ch], y, lw=1, label='Ch{}'.format(ch)) | |
| 554 | plt.legend() |
|
558 | plt.legend() | |
| 555 | else: |
|
559 | else: | |
| 556 | for ch in self.data.channels: |
|
560 | for ch in self.data.channels: | |
| 557 | self.axes[0].lines[ch].set_data(x[ch], y) |
|
561 | self.axes[0].lines[ch].set_data(x[ch], y) | |
| 558 |
|
562 | |||
| 559 |
|
563 | |||
| 560 | class SpectraCutPlot(Plot): |
|
564 | class SpectraCutPlot(Plot): | |
| 561 |
|
565 | |||
| 562 | CODE = 'spc_cut' |
|
566 | CODE = 'spc_cut' | |
| 563 | plot_type = 'scatter' |
|
567 | plot_type = 'scatter' | |
| 564 | buffering = False |
|
568 | buffering = False | |
| 565 | heights = [] |
|
569 | heights = [] | |
| 566 | channelList = [] |
|
570 | channelList = [] | |
| 567 | maintitle = "Spectra Cuts" |
|
571 | maintitle = "Spectra Cuts" | |
| 568 | flag_setIndex = False |
|
572 | flag_setIndex = False | |
| 569 |
|
573 | |||
| 570 | def setup(self): |
|
574 | def setup(self): | |
| 571 |
|
575 | |||
| 572 | self.nplots = len(self.data.channels) |
|
576 | self.nplots = len(self.data.channels) | |
| 573 | self.ncols = int(numpy.sqrt(self.nplots) + 0.9) |
|
577 | self.ncols = int(numpy.sqrt(self.nplots) + 0.9) | |
| 574 | self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9) |
|
578 | self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9) | |
| 575 | self.width = 4.5 * self.ncols + 2.5 |
|
579 | self.width = 4.5 * self.ncols + 2.5 | |
| 576 | self.height = 4.8 * self.nrows |
|
580 | self.height = 4.8 * self.nrows | |
| 577 | self.ylabel = 'Power [dB]' |
|
581 | self.ylabel = 'Power [dB]' | |
| 578 | self.colorbar = False |
|
582 | self.colorbar = False | |
| 579 | self.plots_adjust.update({'left':0.1, 'hspace':0.3, 'right': 0.9, 'bottom':0.08}) |
|
583 | self.plots_adjust.update({'left':0.1, 'hspace':0.3, 'right': 0.9, 'bottom':0.08}) | |
| 580 |
|
584 | |||
| 581 | if len(self.selectedHeightsList) > 0: |
|
585 | if len(self.selectedHeightsList) > 0: | |
| 582 | self.maintitle = "Spectra Cut"# for %d km " %(int(self.selectedHeight)) |
|
586 | self.maintitle = "Spectra Cut"# for %d km " %(int(self.selectedHeight)) | |
| 583 |
|
587 | |||
| 584 |
|
588 | |||
| 585 |
|
589 | |||
| 586 | def update(self, dataOut): |
|
590 | def update(self, dataOut): | |
| 587 | if len(self.channelList) == 0: |
|
591 | if len(self.channelList) == 0: | |
| 588 | self.channelList = dataOut.channelList |
|
592 | self.channelList = dataOut.channelList | |
| 589 |
|
593 | |||
| 590 | self.heights = dataOut.heightList |
|
594 | self.heights = dataOut.heightList | |
| 591 | #print("sels: ",self.selectedHeightsList) |
|
595 | #print("sels: ",self.selectedHeightsList) | |
| 592 | if len(self.selectedHeightsList)>0 and not self.flag_setIndex: |
|
596 | if len(self.selectedHeightsList)>0 and not self.flag_setIndex: | |
| 593 |
|
597 | |||
| 594 | for sel_height in self.selectedHeightsList: |
|
598 | for sel_height in self.selectedHeightsList: | |
| 595 | index_list = numpy.where(self.heights >= sel_height) |
|
599 | index_list = numpy.where(self.heights >= sel_height) | |
| 596 | index_list = index_list[0] |
|
600 | index_list = index_list[0] | |
| 597 | self.height_index.append(index_list[0]) |
|
601 | self.height_index.append(index_list[0]) | |
| 598 | #print("sels i:"", self.height_index) |
|
602 | #print("sels i:"", self.height_index) | |
| 599 | self.flag_setIndex = True |
|
603 | self.flag_setIndex = True | |
| 600 | #print(self.height_index) |
|
604 | #print(self.height_index) | |
| 601 | data = {} |
|
605 | data = {} | |
| 602 | meta = {} |
|
606 | meta = {} | |
| 603 |
|
607 | |||
| 604 | norm = dataOut.nProfiles * dataOut.max_nIncohInt * dataOut.nCohInt * dataOut.windowOfFilter#*dataOut.nFFTPoints |
|
608 | norm = dataOut.nProfiles * dataOut.max_nIncohInt * dataOut.nCohInt * dataOut.windowOfFilter#*dataOut.nFFTPoints | |
| 605 | n0 = 10*numpy.log10(dataOut.getNoise()/norm) |
|
609 | n0 = 10*numpy.log10(dataOut.getNoise()/norm) | |
| 606 | noise = numpy.repeat(n0,(dataOut.nFFTPoints*dataOut.nHeights)).reshape(dataOut.nChannels,dataOut.nFFTPoints,dataOut.nHeights) |
|
610 | noise = numpy.repeat(n0,(dataOut.nFFTPoints*dataOut.nHeights)).reshape(dataOut.nChannels,dataOut.nFFTPoints,dataOut.nHeights) | |
| 607 |
|
611 | |||
| 608 |
|
612 | |||
| 609 | z = [] |
|
613 | z = [] | |
| 610 | for ch in range(dataOut.nChannels): |
|
614 | for ch in range(dataOut.nChannels): | |
| 611 | if hasattr(dataOut.normFactor,'shape'): |
|
615 | if hasattr(dataOut.normFactor,'shape'): | |
| 612 | z.append(numpy.divide(dataOut.data_spc[ch],dataOut.normFactor[ch])) |
|
616 | z.append(numpy.divide(dataOut.data_spc[ch],dataOut.normFactor[ch])) | |
| 613 | else: |
|
617 | else: | |
| 614 | z.append(numpy.divide(dataOut.data_spc[ch],dataOut.normFactor)) |
|
618 | z.append(numpy.divide(dataOut.data_spc[ch],dataOut.normFactor)) | |
| 615 |
|
619 | |||
| 616 | z = numpy.asarray(z) |
|
620 | z = numpy.asarray(z) | |
| 617 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
621 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | |
| 618 | spc = 10*numpy.log10(z) |
|
622 | spc = 10*numpy.log10(z) | |
| 619 |
|
623 | |||
| 620 |
|
624 | |||
| 621 | data['spc'] = spc - noise |
|
625 | data['spc'] = spc - noise | |
| 622 | meta['xrange'] = (dataOut.getFreqRange(EXTRA_POINTS)/1000., dataOut.getAcfRange(EXTRA_POINTS), dataOut.getVelRange(EXTRA_POINTS)) |
|
626 | meta['xrange'] = (dataOut.getFreqRange(EXTRA_POINTS)/1000., dataOut.getAcfRange(EXTRA_POINTS), dataOut.getVelRange(EXTRA_POINTS)) | |
| 623 |
|
627 | |||
| 624 | return data, meta |
|
628 | return data, meta | |
| 625 |
|
629 | |||
| 626 | def plot(self): |
|
630 | def plot(self): | |
| 627 | if self.xaxis == "frequency": |
|
631 | if self.xaxis == "frequency": | |
| 628 | x = self.data.xrange[0][1:] |
|
632 | x = self.data.xrange[0][1:] | |
| 629 | self.xlabel = "Frequency (kHz)" |
|
633 | self.xlabel = "Frequency (kHz)" | |
| 630 | elif self.xaxis == "time": |
|
634 | elif self.xaxis == "time": | |
| 631 | x = self.data.xrange[1] |
|
635 | x = self.data.xrange[1] | |
| 632 | self.xlabel = "Time (ms)" |
|
636 | self.xlabel = "Time (ms)" | |
| 633 | else: |
|
637 | else: | |
| 634 | x = self.data.xrange[2] |
|
638 | x = self.data.xrange[2] | |
| 635 | self.xlabel = "Velocity (m/s)" |
|
639 | self.xlabel = "Velocity (m/s)" | |
| 636 |
|
640 | |||
| 637 | self.titles = [] |
|
641 | self.titles = [] | |
| 638 |
|
642 | |||
| 639 | y = self.data.yrange |
|
643 | y = self.data.yrange | |
| 640 | z = self.data[-1]['spc'] |
|
644 | z = self.data[-1]['spc'] | |
| 641 | #print(z.shape) |
|
645 | #print(z.shape) | |
| 642 | if len(self.height_index) > 0: |
|
646 | if len(self.height_index) > 0: | |
| 643 | index = self.height_index |
|
647 | index = self.height_index | |
| 644 | else: |
|
648 | else: | |
| 645 | index = numpy.arange(0, len(y), int((len(y))/9)) |
|
649 | index = numpy.arange(0, len(y), int((len(y))/9)) | |
| 646 | #print("inde x ", index, self.axes) |
|
650 | #print("inde x ", index, self.axes) | |
| 647 |
|
651 | |||
| 648 | for n, ax in enumerate(self.axes): |
|
652 | for n, ax in enumerate(self.axes): | |
| 649 |
|
653 | |||
| 650 | if ax.firsttime: |
|
654 | if ax.firsttime: | |
| 651 |
|
655 | |||
| 652 |
|
656 | |||
| 653 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) |
|
657 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) | |
| 654 | self.xmin = self.xmin if self.xmin else -self.xmax |
|
658 | self.xmin = self.xmin if self.xmin else -self.xmax | |
| 655 | self.ymin = self.ymin if self.ymin else numpy.nanmin(z) |
|
659 | self.ymin = self.ymin if self.ymin else numpy.nanmin(z) | |
| 656 | self.ymax = self.ymax if self.ymax else numpy.nanmax(z) |
|
660 | self.ymax = self.ymax if self.ymax else numpy.nanmax(z) | |
| 657 |
|
661 | |||
| 658 |
|
662 | |||
| 659 | ax.plt = ax.plot(x, z[n, :, index].T) |
|
663 | ax.plt = ax.plot(x, z[n, :, index].T) | |
| 660 | labels = ['Range = {:2.1f}km'.format(y[i]) for i in index] |
|
664 | labels = ['Range = {:2.1f}km'.format(y[i]) for i in index] | |
| 661 | self.figures[0].legend(ax.plt, labels, loc='center right', prop={'size': 8}) |
|
665 | self.figures[0].legend(ax.plt, labels, loc='center right', prop={'size': 8}) | |
| 662 | ax.minorticks_on() |
|
666 | ax.minorticks_on() | |
| 663 | ax.grid(which='major', axis='both') |
|
667 | ax.grid(which='major', axis='both') | |
| 664 | ax.grid(which='minor', axis='x') |
|
668 | ax.grid(which='minor', axis='x') | |
| 665 | else: |
|
669 | else: | |
| 666 | for i, line in enumerate(ax.plt): |
|
670 | for i, line in enumerate(ax.plt): | |
| 667 | line.set_data(x, z[n, :, index[i]]) |
|
671 | line.set_data(x, z[n, :, index[i]]) | |
| 668 |
|
672 | |||
| 669 |
|
673 | |||
| 670 | self.titles.append('CH {}'.format(self.channelList[n])) |
|
674 | self.titles.append('CH {}'.format(self.channelList[n])) | |
| 671 | plt.suptitle(self.maintitle, fontsize=10) |
|
675 | plt.suptitle(self.maintitle, fontsize=10) | |
| 672 |
|
676 | |||
| 673 |
|
677 | |||
| 674 | class BeaconPhase(Plot): |
|
678 | class BeaconPhase(Plot): | |
| 675 |
|
679 | |||
| 676 | __isConfig = None |
|
680 | __isConfig = None | |
| 677 | __nsubplots = None |
|
681 | __nsubplots = None | |
| 678 |
|
682 | |||
| 679 | PREFIX = 'beacon_phase' |
|
683 | PREFIX = 'beacon_phase' | |
| 680 |
|
684 | |||
| 681 | def __init__(self): |
|
685 | def __init__(self): | |
| 682 | Plot.__init__(self) |
|
686 | Plot.__init__(self) | |
| 683 | self.timerange = 24*60*60 |
|
687 | self.timerange = 24*60*60 | |
| 684 | self.isConfig = False |
|
688 | self.isConfig = False | |
| 685 | self.__nsubplots = 1 |
|
689 | self.__nsubplots = 1 | |
| 686 | self.counter_imagwr = 0 |
|
690 | self.counter_imagwr = 0 | |
| 687 | self.WIDTH = 800 |
|
691 | self.WIDTH = 800 | |
| 688 | self.HEIGHT = 400 |
|
692 | self.HEIGHT = 400 | |
| 689 | self.WIDTHPROF = 120 |
|
693 | self.WIDTHPROF = 120 | |
| 690 | self.HEIGHTPROF = 0 |
|
694 | self.HEIGHTPROF = 0 | |
| 691 | self.xdata = None |
|
695 | self.xdata = None | |
| 692 | self.ydata = None |
|
696 | self.ydata = None | |
| 693 |
|
697 | |||
| 694 | self.PLOT_CODE = BEACON_CODE |
|
698 | self.PLOT_CODE = BEACON_CODE | |
| 695 |
|
699 | |||
| 696 | self.FTP_WEI = None |
|
700 | self.FTP_WEI = None | |
| 697 | self.EXP_CODE = None |
|
701 | self.EXP_CODE = None | |
| 698 | self.SUB_EXP_CODE = None |
|
702 | self.SUB_EXP_CODE = None | |
| 699 | self.PLOT_POS = None |
|
703 | self.PLOT_POS = None | |
| 700 |
|
704 | |||
| 701 | self.filename_phase = None |
|
705 | self.filename_phase = None | |
| 702 |
|
706 | |||
| 703 | self.figfile = None |
|
707 | self.figfile = None | |
| 704 |
|
708 | |||
| 705 | self.xmin = None |
|
709 | self.xmin = None | |
| 706 | self.xmax = None |
|
710 | self.xmax = None | |
| 707 |
|
711 | |||
| 708 | def getSubplots(self): |
|
712 | def getSubplots(self): | |
| 709 |
|
713 | |||
| 710 | ncol = 1 |
|
714 | ncol = 1 | |
| 711 | nrow = 1 |
|
715 | nrow = 1 | |
| 712 |
|
716 | |||
| 713 | return nrow, ncol |
|
717 | return nrow, ncol | |
| 714 |
|
718 | |||
| 715 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
719 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): | |
| 716 |
|
720 | |||
| 717 | self.__showprofile = showprofile |
|
721 | self.__showprofile = showprofile | |
| 718 | self.nplots = nplots |
|
722 | self.nplots = nplots | |
| 719 |
|
723 | |||
| 720 | ncolspan = 7 |
|
724 | ncolspan = 7 | |
| 721 | colspan = 6 |
|
725 | colspan = 6 | |
| 722 | self.__nsubplots = 2 |
|
726 | self.__nsubplots = 2 | |
| 723 |
|
727 | |||
| 724 | self.createFigure(id = id, |
|
728 | self.createFigure(id = id, | |
| 725 | wintitle = wintitle, |
|
729 | wintitle = wintitle, | |
| 726 | widthplot = self.WIDTH+self.WIDTHPROF, |
|
730 | widthplot = self.WIDTH+self.WIDTHPROF, | |
| 727 | heightplot = self.HEIGHT+self.HEIGHTPROF, |
|
731 | heightplot = self.HEIGHT+self.HEIGHTPROF, | |
| 728 | show=show) |
|
732 | show=show) | |
| 729 |
|
733 | |||
| 730 | nrow, ncol = self.getSubplots() |
|
734 | nrow, ncol = self.getSubplots() | |
| 731 |
|
735 | |||
| 732 | self.addAxes(nrow, ncol*ncolspan, 0, 0, colspan, 1) |
|
736 | self.addAxes(nrow, ncol*ncolspan, 0, 0, colspan, 1) | |
| 733 |
|
737 | |||
| 734 | def save_phase(self, filename_phase): |
|
738 | def save_phase(self, filename_phase): | |
| 735 | f = open(filename_phase,'w+') |
|
739 | f = open(filename_phase,'w+') | |
| 736 | f.write('\n\n') |
|
740 | f.write('\n\n') | |
| 737 | f.write('JICAMARCA RADIO OBSERVATORY - Beacon Phase \n') |
|
741 | f.write('JICAMARCA RADIO OBSERVATORY - Beacon Phase \n') | |
| 738 | f.write('DD MM YYYY HH MM SS pair(2,0) pair(2,1) pair(2,3) pair(2,4)\n\n' ) |
|
742 | f.write('DD MM YYYY HH MM SS pair(2,0) pair(2,1) pair(2,3) pair(2,4)\n\n' ) | |
| 739 | f.close() |
|
743 | f.close() | |
| 740 |
|
744 | |||
| 741 | def save_data(self, filename_phase, data, data_datetime): |
|
745 | def save_data(self, filename_phase, data, data_datetime): | |
| 742 | f=open(filename_phase,'a') |
|
746 | f=open(filename_phase,'a') | |
| 743 | timetuple_data = data_datetime.timetuple() |
|
747 | timetuple_data = data_datetime.timetuple() | |
| 744 | day = str(timetuple_data.tm_mday) |
|
748 | day = str(timetuple_data.tm_mday) | |
| 745 | month = str(timetuple_data.tm_mon) |
|
749 | month = str(timetuple_data.tm_mon) | |
| 746 | year = str(timetuple_data.tm_year) |
|
750 | year = str(timetuple_data.tm_year) | |
| 747 | hour = str(timetuple_data.tm_hour) |
|
751 | hour = str(timetuple_data.tm_hour) | |
| 748 | minute = str(timetuple_data.tm_min) |
|
752 | minute = str(timetuple_data.tm_min) | |
| 749 | second = str(timetuple_data.tm_sec) |
|
753 | second = str(timetuple_data.tm_sec) | |
| 750 | f.write(day+' '+month+' '+year+' '+hour+' '+minute+' '+second+' '+str(data[0])+' '+str(data[1])+' '+str(data[2])+' '+str(data[3])+'\n') |
|
754 | f.write(day+' '+month+' '+year+' '+hour+' '+minute+' '+second+' '+str(data[0])+' '+str(data[1])+' '+str(data[2])+' '+str(data[3])+'\n') | |
| 751 | f.close() |
|
755 | f.close() | |
| 752 |
|
756 | |||
| 753 | def plot(self): |
|
757 | def plot(self): | |
| 754 | log.warning('TODO: Not yet implemented...') |
|
758 | log.warning('TODO: Not yet implemented...') | |
| 755 |
|
759 | |||
| 756 | def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True', |
|
760 | def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True', | |
| 757 | xmin=None, xmax=None, ymin=None, ymax=None, hmin=None, hmax=None, |
|
761 | xmin=None, xmax=None, ymin=None, ymax=None, hmin=None, hmax=None, | |
| 758 | timerange=None, |
|
762 | timerange=None, | |
| 759 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, |
|
763 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, | |
| 760 | server=None, folder=None, username=None, password=None, |
|
764 | server=None, folder=None, username=None, password=None, | |
| 761 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): |
|
765 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): | |
| 762 |
|
766 | |||
| 763 | if dataOut.flagNoData: |
|
767 | if dataOut.flagNoData: | |
| 764 | return dataOut |
|
768 | return dataOut | |
| 765 |
|
769 | |||
| 766 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): |
|
770 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): | |
| 767 | return |
|
771 | return | |
| 768 |
|
772 | |||
| 769 | if pairsList == None: |
|
773 | if pairsList == None: | |
| 770 | pairsIndexList = dataOut.pairsIndexList[:10] |
|
774 | pairsIndexList = dataOut.pairsIndexList[:10] | |
| 771 | else: |
|
775 | else: | |
| 772 | pairsIndexList = [] |
|
776 | pairsIndexList = [] | |
| 773 | for pair in pairsList: |
|
777 | for pair in pairsList: | |
| 774 | if pair not in dataOut.pairsList: |
|
778 | if pair not in dataOut.pairsList: | |
| 775 | raise ValueError("Pair %s is not in dataOut.pairsList" %(pair)) |
|
779 | raise ValueError("Pair %s is not in dataOut.pairsList" %(pair)) | |
| 776 | pairsIndexList.append(dataOut.pairsList.index(pair)) |
|
780 | pairsIndexList.append(dataOut.pairsList.index(pair)) | |
| 777 |
|
781 | |||
| 778 | if pairsIndexList == []: |
|
782 | if pairsIndexList == []: | |
| 779 | return |
|
783 | return | |
| 780 |
|
784 | |||
| 781 | # if len(pairsIndexList) > 4: |
|
785 | # if len(pairsIndexList) > 4: | |
| 782 | # pairsIndexList = pairsIndexList[0:4] |
|
786 | # pairsIndexList = pairsIndexList[0:4] | |
| 783 |
|
787 | |||
| 784 | hmin_index = None |
|
788 | hmin_index = None | |
| 785 | hmax_index = None |
|
789 | hmax_index = None | |
| 786 |
|
790 | |||
| 787 | if hmin != None and hmax != None: |
|
791 | if hmin != None and hmax != None: | |
| 788 | indexes = numpy.arange(dataOut.nHeights) |
|
792 | indexes = numpy.arange(dataOut.nHeights) | |
| 789 | hmin_list = indexes[dataOut.heightList >= hmin] |
|
793 | hmin_list = indexes[dataOut.heightList >= hmin] | |
| 790 | hmax_list = indexes[dataOut.heightList <= hmax] |
|
794 | hmax_list = indexes[dataOut.heightList <= hmax] | |
| 791 |
|
795 | |||
| 792 | if hmin_list.any(): |
|
796 | if hmin_list.any(): | |
| 793 | hmin_index = hmin_list[0] |
|
797 | hmin_index = hmin_list[0] | |
| 794 |
|
798 | |||
| 795 | if hmax_list.any(): |
|
799 | if hmax_list.any(): | |
| 796 | hmax_index = hmax_list[-1]+1 |
|
800 | hmax_index = hmax_list[-1]+1 | |
| 797 |
|
801 | |||
| 798 | x = dataOut.getTimeRange() |
|
802 | x = dataOut.getTimeRange() | |
| 799 |
|
803 | |||
| 800 | thisDatetime = dataOut.datatime |
|
804 | thisDatetime = dataOut.datatime | |
| 801 |
|
805 | |||
| 802 | title = wintitle + " Signal Phase" # : %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
806 | title = wintitle + " Signal Phase" # : %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
| 803 | xlabel = "Local Time" |
|
807 | xlabel = "Local Time" | |
| 804 | ylabel = "Phase (degrees)" |
|
808 | ylabel = "Phase (degrees)" | |
| 805 |
|
809 | |||
| 806 | update_figfile = False |
|
810 | update_figfile = False | |
| 807 |
|
811 | |||
| 808 | nplots = len(pairsIndexList) |
|
812 | nplots = len(pairsIndexList) | |
| 809 | #phase = numpy.zeros((len(pairsIndexList),len(dataOut.beacon_heiIndexList))) |
|
813 | #phase = numpy.zeros((len(pairsIndexList),len(dataOut.beacon_heiIndexList))) | |
| 810 | phase_beacon = numpy.zeros(len(pairsIndexList)) |
|
814 | phase_beacon = numpy.zeros(len(pairsIndexList)) | |
| 811 | for i in range(nplots): |
|
815 | for i in range(nplots): | |
| 812 | pair = dataOut.pairsList[pairsIndexList[i]] |
|
816 | pair = dataOut.pairsList[pairsIndexList[i]] | |
| 813 | ccf = numpy.average(dataOut.data_cspc[pairsIndexList[i], :, hmin_index:hmax_index], axis=0) |
|
817 | ccf = numpy.average(dataOut.data_cspc[pairsIndexList[i], :, hmin_index:hmax_index], axis=0) | |
| 814 | powa = numpy.average(dataOut.data_spc[pair[0], :, hmin_index:hmax_index], axis=0) |
|
818 | powa = numpy.average(dataOut.data_spc[pair[0], :, hmin_index:hmax_index], axis=0) | |
| 815 | powb = numpy.average(dataOut.data_spc[pair[1], :, hmin_index:hmax_index], axis=0) |
|
819 | powb = numpy.average(dataOut.data_spc[pair[1], :, hmin_index:hmax_index], axis=0) | |
| 816 | avgcoherenceComplex = ccf/numpy.sqrt(powa*powb) |
|
820 | avgcoherenceComplex = ccf/numpy.sqrt(powa*powb) | |
| 817 | phase = numpy.arctan2(avgcoherenceComplex.imag, avgcoherenceComplex.real)*180/numpy.pi |
|
821 | phase = numpy.arctan2(avgcoherenceComplex.imag, avgcoherenceComplex.real)*180/numpy.pi | |
| 818 |
|
822 | |||
| 819 | if dataOut.beacon_heiIndexList: |
|
823 | if dataOut.beacon_heiIndexList: | |
| 820 | phase_beacon[i] = numpy.average(phase[dataOut.beacon_heiIndexList]) |
|
824 | phase_beacon[i] = numpy.average(phase[dataOut.beacon_heiIndexList]) | |
| 821 | else: |
|
825 | else: | |
| 822 | phase_beacon[i] = numpy.average(phase) |
|
826 | phase_beacon[i] = numpy.average(phase) | |
| 823 |
|
827 | |||
| 824 | if not self.isConfig: |
|
828 | if not self.isConfig: | |
| 825 |
|
829 | |||
| 826 | nplots = len(pairsIndexList) |
|
830 | nplots = len(pairsIndexList) | |
| 827 |
|
831 | |||
| 828 | self.setup(id=id, |
|
832 | self.setup(id=id, | |
| 829 | nplots=nplots, |
|
833 | nplots=nplots, | |
| 830 | wintitle=wintitle, |
|
834 | wintitle=wintitle, | |
| 831 | showprofile=showprofile, |
|
835 | showprofile=showprofile, | |
| 832 | show=show) |
|
836 | show=show) | |
| 833 |
|
837 | |||
| 834 | if timerange != None: |
|
838 | if timerange != None: | |
| 835 | self.timerange = timerange |
|
839 | self.timerange = timerange | |
| 836 |
|
840 | |||
| 837 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) |
|
841 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) | |
| 838 |
|
842 | |||
| 839 | if ymin == None: ymin = 0 |
|
843 | if ymin == None: ymin = 0 | |
| 840 | if ymax == None: ymax = 360 |
|
844 | if ymax == None: ymax = 360 | |
| 841 |
|
845 | |||
| 842 | self.FTP_WEI = ftp_wei |
|
846 | self.FTP_WEI = ftp_wei | |
| 843 | self.EXP_CODE = exp_code |
|
847 | self.EXP_CODE = exp_code | |
| 844 | self.SUB_EXP_CODE = sub_exp_code |
|
848 | self.SUB_EXP_CODE = sub_exp_code | |
| 845 | self.PLOT_POS = plot_pos |
|
849 | self.PLOT_POS = plot_pos | |
| 846 |
|
850 | |||
| 847 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
851 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 848 | self.isConfig = True |
|
852 | self.isConfig = True | |
| 849 | self.figfile = figfile |
|
853 | self.figfile = figfile | |
| 850 | self.xdata = numpy.array([]) |
|
854 | self.xdata = numpy.array([]) | |
| 851 | self.ydata = numpy.array([]) |
|
855 | self.ydata = numpy.array([]) | |
| 852 |
|
856 | |||
| 853 | update_figfile = True |
|
857 | update_figfile = True | |
| 854 |
|
858 | |||
| 855 | #open file beacon phase |
|
859 | #open file beacon phase | |
| 856 | path = '%s%03d' %(self.PREFIX, self.id) |
|
860 | path = '%s%03d' %(self.PREFIX, self.id) | |
| 857 | beacon_file = os.path.join(path,'%s.txt'%self.name) |
|
861 | beacon_file = os.path.join(path,'%s.txt'%self.name) | |
| 858 | self.filename_phase = os.path.join(figpath,beacon_file) |
|
862 | self.filename_phase = os.path.join(figpath,beacon_file) | |
| 859 | #self.save_phase(self.filename_phase) |
|
863 | #self.save_phase(self.filename_phase) | |
| 860 |
|
864 | |||
| 861 |
|
865 | |||
| 862 | #store data beacon phase |
|
866 | #store data beacon phase | |
| 863 | #self.save_data(self.filename_phase, phase_beacon, thisDatetime) |
|
867 | #self.save_data(self.filename_phase, phase_beacon, thisDatetime) | |
| 864 |
|
868 | |||
| 865 | self.setWinTitle(title) |
|
869 | self.setWinTitle(title) | |
| 866 |
|
870 | |||
| 867 |
|
871 | |||
| 868 | title = "Phase Plot %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) |
|
872 | title = "Phase Plot %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) | |
| 869 |
|
873 | |||
| 870 | legendlabels = ["Pair (%d,%d)"%(pair[0], pair[1]) for pair in dataOut.pairsList] |
|
874 | legendlabels = ["Pair (%d,%d)"%(pair[0], pair[1]) for pair in dataOut.pairsList] | |
| 871 |
|
875 | |||
| 872 | axes = self.axesList[0] |
|
876 | axes = self.axesList[0] | |
| 873 |
|
877 | |||
| 874 | self.xdata = numpy.hstack((self.xdata, x[0:1])) |
|
878 | self.xdata = numpy.hstack((self.xdata, x[0:1])) | |
| 875 |
|
879 | |||
| 876 | if len(self.ydata)==0: |
|
880 | if len(self.ydata)==0: | |
| 877 | self.ydata = phase_beacon.reshape(-1,1) |
|
881 | self.ydata = phase_beacon.reshape(-1,1) | |
| 878 | else: |
|
882 | else: | |
| 879 | self.ydata = numpy.hstack((self.ydata, phase_beacon.reshape(-1,1))) |
|
883 | self.ydata = numpy.hstack((self.ydata, phase_beacon.reshape(-1,1))) | |
| 880 |
|
884 | |||
| 881 |
|
885 | |||
| 882 | axes.pmultilineyaxis(x=self.xdata, y=self.ydata, |
|
886 | axes.pmultilineyaxis(x=self.xdata, y=self.ydata, | |
| 883 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, |
|
887 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, | |
| 884 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid", |
|
888 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid", | |
| 885 | XAxisAsTime=True, grid='both' |
|
889 | XAxisAsTime=True, grid='both' | |
| 886 | ) |
|
890 | ) | |
| 887 |
|
891 | |||
| 888 | self.draw() |
|
892 | self.draw() | |
| 889 |
|
893 | |||
| 890 | if dataOut.ltctime >= self.xmax: |
|
894 | if dataOut.ltctime >= self.xmax: | |
| 891 | self.counter_imagwr = wr_period |
|
895 | self.counter_imagwr = wr_period | |
| 892 | self.isConfig = False |
|
896 | self.isConfig = False | |
| 893 | update_figfile = True |
|
897 | update_figfile = True | |
| 894 |
|
898 | |||
| 895 | self.save(figpath=figpath, |
|
899 | self.save(figpath=figpath, | |
| 896 | figfile=figfile, |
|
900 | figfile=figfile, | |
| 897 | save=save, |
|
901 | save=save, | |
| 898 | ftp=ftp, |
|
902 | ftp=ftp, | |
| 899 | wr_period=wr_period, |
|
903 | wr_period=wr_period, | |
| 900 | thisDatetime=thisDatetime, |
|
904 | thisDatetime=thisDatetime, | |
| 901 | update_figfile=update_figfile) |
|
905 | update_figfile=update_figfile) | |
| 902 |
|
906 | |||
| 903 | return dataOut |
|
907 | return dataOut | |
| 904 |
|
908 | |||
| 905 | class NoiselessSpectraPlot(Plot): |
|
909 | class NoiselessSpectraPlot(Plot): | |
| 906 | ''' |
|
910 | ''' | |
| 907 | Plot for Spectra data, subtracting |
|
911 | Plot for Spectra data, subtracting | |
| 908 | the noise in all channels, using for |
|
912 | the noise in all channels, using for | |
| 909 | amisr-14 data |
|
913 | amisr-14 data | |
| 910 | ''' |
|
914 | ''' | |
| 911 |
|
915 | |||
| 912 | CODE = 'noiseless_spc' |
|
916 | CODE = 'noiseless_spc' | |
| 913 | colormap = 'jet' |
|
917 | colormap = 'jet' | |
| 914 | plot_type = 'pcolor' |
|
918 | plot_type = 'pcolor' | |
| 915 | buffering = False |
|
919 | buffering = False | |
| 916 | channelList = [] |
|
920 | channelList = [] | |
| 917 | last_noise = None |
|
921 | last_noise = None | |
| 918 |
|
922 | |||
| 919 | def setup(self): |
|
923 | def setup(self): | |
| 920 |
|
924 | |||
| 921 | self.nplots = len(self.data.channels) |
|
925 | self.nplots = len(self.data.channels) | |
| 922 | self.ncols = int(numpy.sqrt(self.nplots) + 0.9) |
|
926 | self.ncols = int(numpy.sqrt(self.nplots) + 0.9) | |
| 923 | self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9) |
|
927 | self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9) | |
| 924 | self.height = 3.5 * self.nrows |
|
928 | self.height = 3.5 * self.nrows | |
| 925 |
|
929 | |||
| 926 | self.cb_label = 'dB' |
|
930 | self.cb_label = 'dB' | |
| 927 | if self.showprofile: |
|
931 | if self.showprofile: | |
| 928 | self.width = 5.8 * self.ncols |
|
932 | self.width = 5.8 * self.ncols | |
| 929 | else: |
|
933 | else: | |
| 930 | self.width = 4.8* self.ncols |
|
934 | self.width = 4.8* self.ncols | |
| 931 | self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.92, 'bottom': 0.12}) |
|
935 | self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.92, 'bottom': 0.12}) | |
| 932 |
|
936 | |||
| 933 | self.ylabel = 'Range [km]' |
|
937 | self.ylabel = 'Range [km]' | |
| 934 |
|
938 | |||
| 935 |
|
939 | |||
| 936 | def update_list(self,dataOut): |
|
940 | def update_list(self,dataOut): | |
| 937 | if len(self.channelList) == 0: |
|
941 | if len(self.channelList) == 0: | |
| 938 | self.channelList = dataOut.channelList |
|
942 | self.channelList = dataOut.channelList | |
| 939 |
|
943 | |||
| 940 | def update(self, dataOut): |
|
944 | def update(self, dataOut): | |
| 941 |
|
945 | |||
| 942 | self.update_list(dataOut) |
|
946 | self.update_list(dataOut) | |
| 943 | data = {} |
|
947 | data = {} | |
| 944 | meta = {} |
|
948 | meta = {} | |
| 945 |
|
949 | |||
| 946 | norm = dataOut.nProfiles * dataOut.max_nIncohInt * dataOut.nCohInt * dataOut.windowOfFilter |
|
950 | norm = dataOut.nProfiles * dataOut.max_nIncohInt * dataOut.nCohInt * dataOut.windowOfFilter | |
| 947 | n0 = (dataOut.getNoise()/norm) |
|
951 | n0 = (dataOut.getNoise()/norm) | |
| 948 | noise = numpy.repeat(n0,(dataOut.nFFTPoints*dataOut.nHeights)).reshape(dataOut.nChannels,dataOut.nFFTPoints,dataOut.nHeights) |
|
952 | noise = numpy.repeat(n0,(dataOut.nFFTPoints*dataOut.nHeights)).reshape(dataOut.nChannels,dataOut.nFFTPoints,dataOut.nHeights) | |
| 949 | noise = 10*numpy.log10(noise) |
|
953 | noise = 10*numpy.log10(noise) | |
| 950 |
|
954 | |||
| 951 | z = numpy.zeros((dataOut.nChannels, dataOut.nFFTPoints, dataOut.nHeights)) |
|
955 | z = numpy.zeros((dataOut.nChannels, dataOut.nFFTPoints, dataOut.nHeights)) | |
| 952 | for ch in range(dataOut.nChannels): |
|
956 | for ch in range(dataOut.nChannels): | |
| 953 | if hasattr(dataOut.normFactor,'ndim'): |
|
957 | if hasattr(dataOut.normFactor,'ndim'): | |
| 954 | if dataOut.normFactor.ndim > 1: |
|
958 | if dataOut.normFactor.ndim > 1: | |
| 955 | z[ch] = (numpy.divide(dataOut.data_spc[ch],dataOut.normFactor[ch])) |
|
959 | z[ch] = (numpy.divide(dataOut.data_spc[ch],dataOut.normFactor[ch])) | |
| 956 | else: |
|
960 | else: | |
| 957 | z[ch] = (numpy.divide(dataOut.data_spc[ch],dataOut.normFactor)) |
|
961 | z[ch] = (numpy.divide(dataOut.data_spc[ch],dataOut.normFactor)) | |
| 958 | else: |
|
962 | else: | |
| 959 | z[ch] = (numpy.divide(dataOut.data_spc[ch],dataOut.normFactor)) |
|
963 | z[ch] = (numpy.divide(dataOut.data_spc[ch],dataOut.normFactor)) | |
| 960 |
|
964 | |||
| 961 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
965 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | |
| 962 | spc = 10*numpy.log10(z) |
|
966 | spc = 10*numpy.log10(z) | |
| 963 |
|
967 | |||
| 964 |
|
968 | |||
| 965 | data['spc'] = spc - noise |
|
969 | data['spc'] = spc - noise | |
| 966 | #print(spc.shape) |
|
970 | #print(spc.shape) | |
| 967 | data['rti'] = spc.mean(axis=1) |
|
971 | data['rti'] = spc.mean(axis=1) | |
| 968 | data['noise'] = noise |
|
972 | data['noise'] = noise | |
| 969 |
|
973 | |||
| 970 |
|
974 | |||
| 971 |
|
975 | |||
| 972 | # data['noise'] = noise |
|
976 | # data['noise'] = noise | |
| 973 | meta['xrange'] = (dataOut.getFreqRange(EXTRA_POINTS)/1000., dataOut.getAcfRange(EXTRA_POINTS), dataOut.getVelRange(EXTRA_POINTS)) |
|
977 | meta['xrange'] = (dataOut.getFreqRange(EXTRA_POINTS)/1000., dataOut.getAcfRange(EXTRA_POINTS), dataOut.getVelRange(EXTRA_POINTS)) | |
| 974 |
|
978 | |||
| 975 | return data, meta |
|
979 | return data, meta | |
| 976 |
|
980 | |||
| 977 | def plot(self): |
|
981 | def plot(self): | |
| 978 | if self.xaxis == "frequency": |
|
982 | if self.xaxis == "frequency": | |
| 979 | x = self.data.xrange[0] |
|
983 | x = self.data.xrange[0] | |
| 980 | self.xlabel = "Frequency (kHz)" |
|
984 | self.xlabel = "Frequency (kHz)" | |
| 981 | elif self.xaxis == "time": |
|
985 | elif self.xaxis == "time": | |
| 982 | x = self.data.xrange[1] |
|
986 | x = self.data.xrange[1] | |
| 983 | self.xlabel = "Time (ms)" |
|
987 | self.xlabel = "Time (ms)" | |
| 984 | else: |
|
988 | else: | |
| 985 | x = self.data.xrange[2] |
|
989 | x = self.data.xrange[2] | |
| 986 | self.xlabel = "Velocity (m/s)" |
|
990 | self.xlabel = "Velocity (m/s)" | |
| 987 |
|
991 | |||
| 988 | self.titles = [] |
|
992 | self.titles = [] | |
| 989 | y = self.data.yrange |
|
993 | y = self.data.yrange | |
| 990 | self.y = y |
|
994 | self.y = y | |
| 991 |
|
995 | |||
| 992 | data = self.data[-1] |
|
996 | data = self.data[-1] | |
| 993 | z = data['spc'] |
|
997 | z = data['spc'] | |
| 994 |
|
998 | |||
| 995 | for n, ax in enumerate(self.axes): |
|
999 | for n, ax in enumerate(self.axes): | |
| 996 | #noise = data['noise'][n] |
|
1000 | #noise = data['noise'][n] | |
| 997 |
|
1001 | |||
| 998 | if ax.firsttime: |
|
1002 | if ax.firsttime: | |
| 999 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) |
|
1003 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) | |
| 1000 | self.xmin = self.xmin if self.xmin else -self.xmax |
|
1004 | self.xmin = self.xmin if self.xmin else -self.xmax | |
| 1001 | self.zmin = self.zmin if self.zmin else numpy.nanmin(z) |
|
1005 | self.zmin = self.zmin if self.zmin else numpy.nanmin(z) | |
| 1002 | self.zmax = self.zmax if self.zmax else numpy.nanmax(z) |
|
1006 | self.zmax = self.zmax if self.zmax else numpy.nanmax(z) | |
| 1003 | ax.plt = ax.pcolormesh(x, y, z[n].T, |
|
1007 | ax.plt = ax.pcolormesh(x, y, z[n].T, | |
| 1004 | vmin=self.zmin, |
|
1008 | vmin=self.zmin, | |
| 1005 | vmax=self.zmax, |
|
1009 | vmax=self.zmax, | |
| 1006 | cmap=plt.get_cmap(self.colormap) |
|
1010 | cmap=plt.get_cmap(self.colormap) | |
| 1007 | ) |
|
1011 | ) | |
| 1008 |
|
1012 | |||
| 1009 | if self.showprofile: |
|
1013 | if self.showprofile: | |
| 1010 | ax.plt_profile = self.pf_axes[n].plot( |
|
1014 | ax.plt_profile = self.pf_axes[n].plot( | |
| 1011 | data['rti'][n], y)[0] |
|
1015 | data['rti'][n], y)[0] | |
| 1012 |
|
1016 | |||
| 1013 |
|
1017 | |||
| 1014 | else: |
|
1018 | else: | |
| 1015 | ax.plt.set_array(z[n].T.ravel()) |
|
1019 | ax.plt.set_array(z[n].T.ravel()) | |
| 1016 | if self.showprofile: |
|
1020 | if self.showprofile: | |
| 1017 | ax.plt_profile.set_data(data['rti'][n], y) |
|
1021 | ax.plt_profile.set_data(data['rti'][n], y) | |
| 1018 |
|
1022 | |||
| 1019 |
|
1023 | |||
| 1020 | self.titles.append('CH {}'.format(self.channelList[n])) |
|
1024 | self.titles.append('CH {}'.format(self.channelList[n])) | |
| 1021 |
|
1025 | |||
| 1022 |
|
1026 | |||
| 1023 | class NoiselessRTIPlot(RTIPlot): |
|
1027 | class NoiselessRTIPlot(RTIPlot): | |
| 1024 | ''' |
|
1028 | ''' | |
| 1025 | Plot for RTI data |
|
1029 | Plot for RTI data | |
| 1026 | ''' |
|
1030 | ''' | |
| 1027 |
|
1031 | |||
| 1028 | CODE = 'noiseless_rti' |
|
1032 | CODE = 'noiseless_rti' | |
| 1029 | colormap = 'jet' |
|
1033 | colormap = 'jet' | |
| 1030 | plot_type = 'pcolorbuffer' |
|
1034 | plot_type = 'pcolorbuffer' | |
| 1031 | titles = None |
|
1035 | titles = None | |
| 1032 | channelList = [] |
|
1036 | channelList = [] | |
| 1033 | elevationList = [] |
|
1037 | elevationList = [] | |
| 1034 | azimuthList = [] |
|
1038 | azimuthList = [] | |
| 1035 | last_noise = None |
|
1039 | last_noise = None | |
| 1036 |
|
1040 | |||
| 1037 | def setup(self): |
|
1041 | def setup(self): | |
| 1038 | self.xaxis = 'time' |
|
1042 | self.xaxis = 'time' | |
| 1039 | self.ncols = 1 |
|
1043 | self.ncols = 1 | |
| 1040 | #print("dataChannels ",self.data.channels) |
|
1044 | #print("dataChannels ",self.data.channels) | |
| 1041 | self.nrows = len(self.data.channels) |
|
1045 | self.nrows = len(self.data.channels) | |
| 1042 | self.nplots = len(self.data.channels) |
|
1046 | self.nplots = len(self.data.channels) | |
| 1043 | self.ylabel = 'Range [km]' |
|
1047 | self.ylabel = 'Range [km]' | |
| 1044 | self.xlabel = 'Time' |
|
1048 | #self.xlabel = 'Time' | |
| 1045 | self.cb_label = 'dB' |
|
1049 | self.cb_label = 'dB' | |
| 1046 | self.plots_adjust.update({'hspace':0.8, 'left': 0.08, 'bottom': 0.2, 'right':0.94}) |
|
1050 | self.plots_adjust.update({'hspace':0.8, 'left': 0.08, 'bottom': 0.2, 'right':0.94}) | |
| 1047 | self.titles = ['{} Channel {}'.format( |
|
1051 | self.titles = ['{} Channel {}'.format( | |
| 1048 | self.CODE.upper(), x) for x in range(self.nplots)] |
|
1052 | self.CODE.upper(), x) for x in range(self.nplots)] | |
| 1049 |
|
1053 | |||
| 1050 | def update_list(self,dataOut): |
|
1054 | def update_list(self,dataOut): | |
| 1051 | if len(self.channelList) == 0: |
|
1055 | if len(self.channelList) == 0: | |
| 1052 | self.channelList = dataOut.channelList |
|
1056 | self.channelList = dataOut.channelList | |
| 1053 | if len(self.elevationList) == 0: |
|
1057 | if len(self.elevationList) == 0: | |
| 1054 | self.elevationList = dataOut.elevationList |
|
1058 | self.elevationList = dataOut.elevationList | |
| 1055 | if len(self.azimuthList) == 0: |
|
1059 | if len(self.azimuthList) == 0: | |
| 1056 | self.azimuthList = dataOut.azimuthList |
|
1060 | self.azimuthList = dataOut.azimuthList | |
| 1057 |
|
1061 | |||
| 1058 | def update(self, dataOut): |
|
1062 | def update(self, dataOut): | |
| 1059 | if len(self.channelList) == 0: |
|
1063 | if len(self.channelList) == 0: | |
| 1060 | self.update_list(dataOut) |
|
1064 | self.update_list(dataOut) | |
| 1061 |
|
1065 | |||
| 1062 | data = {} |
|
1066 | data = {} | |
| 1063 | meta = {} |
|
1067 | meta = {} | |
| 1064 | #print(dataOut.max_nIncohInt, dataOut.nIncohInt) |
|
1068 | #print(dataOut.max_nIncohInt, dataOut.nIncohInt) | |
| 1065 | #print(dataOut.windowOfFilter,dataOut.nCohInt,dataOut.nProfiles,dataOut.max_nIncohInt,dataOut.nIncohInt |
|
1069 | #print(dataOut.windowOfFilter,dataOut.nCohInt,dataOut.nProfiles,dataOut.max_nIncohInt,dataOut.nIncohInt | |
| 1066 | norm = dataOut.nProfiles * dataOut.max_nIncohInt * dataOut.nCohInt * dataOut.windowOfFilter |
|
1070 | norm = dataOut.nProfiles * dataOut.max_nIncohInt * dataOut.nCohInt * dataOut.windowOfFilter | |
| 1067 | n0 = 10*numpy.log10(dataOut.getNoise()/norm) |
|
1071 | n0 = 10*numpy.log10(dataOut.getNoise()/norm) | |
| 1068 | data['noise'] = n0 |
|
1072 | data['noise'] = n0 | |
| 1069 | noise = numpy.repeat(n0,dataOut.nHeights).reshape(dataOut.nChannels,dataOut.nHeights) |
|
1073 | noise = numpy.repeat(n0,dataOut.nHeights).reshape(dataOut.nChannels,dataOut.nHeights) | |
| 1070 | noiseless_data = dataOut.getPower() - noise |
|
1074 | noiseless_data = dataOut.getPower() - noise | |
| 1071 |
|
1075 | |||
| 1072 | #print("power, noise:", dataOut.getPower(), n0) |
|
1076 | #print("power, noise:", dataOut.getPower(), n0) | |
| 1073 | #print(noise) |
|
1077 | #print(noise) | |
| 1074 | #print(noiseless_data) |
|
1078 | #print(noiseless_data) | |
| 1075 |
|
1079 | |||
| 1076 | data['noiseless_rti'] = noiseless_data |
|
1080 | data['noiseless_rti'] = noiseless_data | |
| 1077 |
|
1081 | |||
| 1078 | return data, meta |
|
1082 | return data, meta | |
| 1079 |
|
1083 | |||
| 1080 | def plot(self): |
|
1084 | def plot(self): | |
| 1081 | from matplotlib import pyplot as plt |
|
1085 | from matplotlib import pyplot as plt | |
| 1082 | self.x = self.data.times |
|
1086 | self.x = self.data.times | |
| 1083 | self.y = self.data.yrange |
|
1087 | self.y = self.data.yrange | |
| 1084 | self.z = self.data['noiseless_rti'] |
|
1088 | self.z = self.data['noiseless_rti'] | |
| 1085 | self.z = numpy.array(self.z, dtype=float) |
|
1089 | self.z = numpy.array(self.z, dtype=float) | |
| 1086 | self.z = numpy.ma.masked_invalid(self.z) |
|
1090 | self.z = numpy.ma.masked_invalid(self.z) | |
| 1087 |
|
1091 | |||
| 1088 |
|
1092 | |||
| 1089 | try: |
|
1093 | try: | |
| 1090 | if self.channelList != None: |
|
1094 | if self.channelList != None: | |
| 1091 | if len(self.elevationList) > 0 and len(self.azimuthList) > 0: |
|
1095 | if len(self.elevationList) > 0 and len(self.azimuthList) > 0: | |
| 1092 | self.titles = ['{} Channel {} ({:2.1f} Elev, {:2.1f} Azth)'.format( |
|
1096 | self.titles = ['{} Channel {} ({:2.1f} Elev, {:2.1f} Azth)'.format( | |
| 1093 | self.CODE.upper(), x, self.elevationList[x], self.azimuthList[x]) for x in self.channelList] |
|
1097 | self.CODE.upper(), x, self.elevationList[x], self.azimuthList[x]) for x in self.channelList] | |
| 1094 | else: |
|
1098 | else: | |
| 1095 | self.titles = ['{} Channel {}'.format( |
|
1099 | self.titles = ['{} Channel {}'.format( | |
| 1096 | self.CODE.upper(), x) for x in self.channelList] |
|
1100 | self.CODE.upper(), x) for x in self.channelList] | |
| 1097 | except: |
|
1101 | except: | |
| 1098 | if self.channelList.any() != None: |
|
1102 | if self.channelList.any() != None: | |
| 1099 | if len(self.elevationList) > 0 and len(self.azimuthList) > 0: |
|
1103 | if len(self.elevationList) > 0 and len(self.azimuthList) > 0: | |
| 1100 | self.titles = ['{} Channel {} ({:2.1f} Elev, {:2.1f} Azth)'.format( |
|
1104 | self.titles = ['{} Channel {} ({:2.1f} Elev, {:2.1f} Azth)'.format( | |
| 1101 | self.CODE.upper(), x, self.elevationList[x], self.azimuthList[x]) for x in self.channelList] |
|
1105 | self.CODE.upper(), x, self.elevationList[x], self.azimuthList[x]) for x in self.channelList] | |
| 1102 | else: |
|
1106 | else: | |
| 1103 | self.titles = ['{} Channel {}'.format( |
|
1107 | self.titles = ['{} Channel {}'.format( | |
| 1104 | self.CODE.upper(), x) for x in self.channelList] |
|
1108 | self.CODE.upper(), x) for x in self.channelList] | |
| 1105 |
|
1109 | |||
| 1106 |
|
1110 | |||
| 1107 | if self.decimation is None: |
|
1111 | if self.decimation is None: | |
| 1108 | x, y, z = self.fill_gaps(self.x, self.y, self.z) |
|
1112 | x, y, z = self.fill_gaps(self.x, self.y, self.z) | |
| 1109 | else: |
|
1113 | else: | |
| 1110 | x, y, z = self.fill_gaps(*self.decimate()) |
|
1114 | x, y, z = self.fill_gaps(*self.decimate()) | |
| 1111 |
|
1115 | |||
| 1112 | dummy_var = self.axes #ExtraΓ±amente esto actualiza el valor axes |
|
1116 | dummy_var = self.axes #ExtraΓ±amente esto actualiza el valor axes | |
| 1113 | #print("plot shapes ", z.shape, x.shape, y.shape) |
|
1117 | #print("plot shapes ", z.shape, x.shape, y.shape) | |
| 1114 | #print(self.axes) |
|
1118 | #print(self.axes) | |
| 1115 | for n, ax in enumerate(self.axes): |
|
1119 | for n, ax in enumerate(self.axes): | |
| 1116 |
|
1120 | |||
| 1117 |
|
1121 | |||
| 1118 | self.zmin = self.zmin if self.zmin else numpy.min(self.z) |
|
1122 | self.zmin = self.zmin if self.zmin else numpy.min(self.z) | |
| 1119 | self.zmax = self.zmax if self.zmax else numpy.max(self.z) |
|
1123 | self.zmax = self.zmax if self.zmax else numpy.max(self.z) | |
| 1120 | data = self.data[-1] |
|
1124 | data = self.data[-1] | |
| 1121 | if ax.firsttime: |
|
1125 | if ax.firsttime: | |
|
|
1126 | if (n+1) == len(self.channelList): | |||
|
|
1127 | ax.set_xlabel('Time') | |||
| 1122 | ax.plt = ax.pcolormesh(x, y, z[n].T, |
|
1128 | ax.plt = ax.pcolormesh(x, y, z[n].T, | |
| 1123 | vmin=self.zmin, |
|
1129 | vmin=self.zmin, | |
| 1124 | vmax=self.zmax, |
|
1130 | vmax=self.zmax, | |
| 1125 | cmap=plt.get_cmap(self.colormap) |
|
1131 | cmap=plt.get_cmap(self.colormap) | |
| 1126 | ) |
|
1132 | ) | |
| 1127 | if self.showprofile: |
|
1133 | if self.showprofile: | |
| 1128 | ax.plot_profile = self.pf_axes[n].plot(data['noiseless_rti'][n], self.y)[0] |
|
1134 | ax.plot_profile = self.pf_axes[n].plot(data['noiseless_rti'][n], self.y)[0] | |
| 1129 |
|
1135 | |||
| 1130 | else: |
|
1136 | else: | |
| 1131 | ax.collections.remove(ax.collections[0]) |
|
1137 | ax.collections.remove(ax.collections[0]) | |
| 1132 | ax.plt = ax.pcolormesh(x, y, z[n].T, |
|
1138 | ax.plt = ax.pcolormesh(x, y, z[n].T, | |
| 1133 | vmin=self.zmin, |
|
1139 | vmin=self.zmin, | |
| 1134 | vmax=self.zmax, |
|
1140 | vmax=self.zmax, | |
| 1135 | cmap=plt.get_cmap(self.colormap) |
|
1141 | cmap=plt.get_cmap(self.colormap) | |
| 1136 | ) |
|
1142 | ) | |
| 1137 | if self.showprofile: |
|
1143 | if self.showprofile: | |
| 1138 | ax.plot_profile.set_data(data['noiseless_rti'][n], self.y) |
|
1144 | ax.plot_profile.set_data(data['noiseless_rti'][n], self.y) | |
| 1139 | # if "noise" in self.data: |
|
1145 | # if "noise" in self.data: | |
| 1140 | # #ax.plot_noise.set_data(numpy.repeat(data['noise'][n], len(self.y)), self.y) |
|
1146 | # #ax.plot_noise.set_data(numpy.repeat(data['noise'][n], len(self.y)), self.y) | |
| 1141 | # ax.plot_noise.set_data(data['noise'][n], self.y) |
|
1147 | # ax.plot_noise.set_data(data['noise'][n], self.y) | |
| 1142 |
|
1148 | |||
| 1143 |
|
1149 | |||
| 1144 | class OutliersRTIPlot(Plot): |
|
1150 | class OutliersRTIPlot(Plot): | |
| 1145 | ''' |
|
1151 | ''' | |
| 1146 | Plot for data_xxxx object |
|
1152 | Plot for data_xxxx object | |
| 1147 | ''' |
|
1153 | ''' | |
| 1148 |
|
1154 | |||
| 1149 | CODE = 'outlier_rtc' # Range Time Counts |
|
1155 | CODE = 'outlier_rtc' # Range Time Counts | |
| 1150 | colormap = 'cool' |
|
1156 | colormap = 'cool' | |
| 1151 | plot_type = 'pcolorbuffer' |
|
1157 | plot_type = 'pcolorbuffer' | |
| 1152 |
|
1158 | |||
| 1153 | def setup(self): |
|
1159 | def setup(self): | |
| 1154 | self.xaxis = 'time' |
|
1160 | self.xaxis = 'time' | |
| 1155 | self.ncols = 1 |
|
1161 | self.ncols = 1 | |
| 1156 | self.nrows = self.data.shape('outlier_rtc')[0] |
|
1162 | self.nrows = self.data.shape('outlier_rtc')[0] | |
| 1157 | self.nplots = self.nrows |
|
1163 | self.nplots = self.nrows | |
| 1158 | self.plots_adjust.update({'hspace':0.8, 'left': 0.08, 'bottom': 0.2, 'right':0.94}) |
|
1164 | self.plots_adjust.update({'hspace':0.8, 'left': 0.08, 'bottom': 0.2, 'right':0.94}) | |
| 1159 |
|
1165 | |||
| 1160 |
|
1166 | |||
| 1161 | if not self.xlabel: |
|
1167 | if not self.xlabel: | |
| 1162 | self.xlabel = 'Time' |
|
1168 | self.xlabel = 'Time' | |
| 1163 |
|
1169 | |||
| 1164 | self.ylabel = 'Height [km]' |
|
1170 | self.ylabel = 'Height [km]' | |
| 1165 | if not self.titles: |
|
1171 | if not self.titles: | |
| 1166 | self.titles = ['Outliers Ch:{}'.format(x) for x in range(self.nrows)] |
|
1172 | self.titles = ['Outliers Ch:{}'.format(x) for x in range(self.nrows)] | |
| 1167 |
|
1173 | |||
| 1168 | def update(self, dataOut): |
|
1174 | def update(self, dataOut): | |
| 1169 |
|
1175 | |||
| 1170 | data = {} |
|
1176 | data = {} | |
| 1171 | data['outlier_rtc'] = dataOut.data_outlier |
|
1177 | data['outlier_rtc'] = dataOut.data_outlier | |
| 1172 |
|
1178 | |||
| 1173 | meta = {} |
|
1179 | meta = {} | |
| 1174 |
|
1180 | |||
| 1175 | return data, meta |
|
1181 | return data, meta | |
| 1176 |
|
1182 | |||
| 1177 | def plot(self): |
|
1183 | def plot(self): | |
| 1178 | # self.data.normalize_heights() |
|
1184 | # self.data.normalize_heights() | |
| 1179 | self.x = self.data.times |
|
1185 | self.x = self.data.times | |
| 1180 | self.y = self.data.yrange |
|
1186 | self.y = self.data.yrange | |
| 1181 | self.z = self.data['outlier_rtc'] |
|
1187 | self.z = self.data['outlier_rtc'] | |
| 1182 |
|
1188 | |||
| 1183 | #self.z = numpy.ma.masked_invalid(self.z) |
|
1189 | #self.z = numpy.ma.masked_invalid(self.z) | |
| 1184 |
|
1190 | |||
| 1185 | if self.decimation is None: |
|
1191 | if self.decimation is None: | |
| 1186 | x, y, z = self.fill_gaps(self.x, self.y, self.z) |
|
1192 | x, y, z = self.fill_gaps(self.x, self.y, self.z) | |
| 1187 | else: |
|
1193 | else: | |
| 1188 | x, y, z = self.fill_gaps(*self.decimate()) |
|
1194 | x, y, z = self.fill_gaps(*self.decimate()) | |
| 1189 |
|
1195 | |||
| 1190 | for n, ax in enumerate(self.axes): |
|
1196 | for n, ax in enumerate(self.axes): | |
| 1191 |
|
1197 | |||
| 1192 | self.zmax = self.zmax if self.zmax is not None else numpy.max( |
|
1198 | self.zmax = self.zmax if self.zmax is not None else numpy.max( | |
| 1193 | self.z[n]) |
|
1199 | self.z[n]) | |
| 1194 | self.zmin = self.zmin if self.zmin is not None else numpy.min( |
|
1200 | self.zmin = self.zmin if self.zmin is not None else numpy.min( | |
| 1195 | self.z[n]) |
|
1201 | self.z[n]) | |
| 1196 | data = self.data[-1] |
|
1202 | data = self.data[-1] | |
| 1197 | if ax.firsttime: |
|
1203 | if ax.firsttime: | |
| 1198 | if self.zlimits is not None: |
|
1204 | if self.zlimits is not None: | |
| 1199 | self.zmin, self.zmax = self.zlimits[n] |
|
1205 | self.zmin, self.zmax = self.zlimits[n] | |
| 1200 |
|
1206 | |||
| 1201 | ax.plt = ax.pcolormesh(x, y, z[n].T, |
|
1207 | ax.plt = ax.pcolormesh(x, y, z[n].T, | |
| 1202 | vmin=self.zmin, |
|
1208 | vmin=self.zmin, | |
| 1203 | vmax=self.zmax, |
|
1209 | vmax=self.zmax, | |
| 1204 | cmap=self.cmaps[n] |
|
1210 | cmap=self.cmaps[n] | |
| 1205 | ) |
|
1211 | ) | |
| 1206 | if self.showprofile: |
|
1212 | if self.showprofile: | |
| 1207 | ax.plot_profile = self.pf_axes[n].plot(data['outlier_rtc'][n], self.y)[0] |
|
1213 | ax.plot_profile = self.pf_axes[n].plot(data['outlier_rtc'][n], self.y)[0] | |
| 1208 | self.pf_axes[n].set_xlabel('') |
|
1214 | self.pf_axes[n].set_xlabel('') | |
| 1209 | else: |
|
1215 | else: | |
| 1210 | if self.zlimits is not None: |
|
1216 | if self.zlimits is not None: | |
| 1211 | self.zmin, self.zmax = self.zlimits[n] |
|
1217 | self.zmin, self.zmax = self.zlimits[n] | |
| 1212 | ax.collections.remove(ax.collections[0]) |
|
1218 | ax.collections.remove(ax.collections[0]) | |
| 1213 | ax.plt = ax.pcolormesh(x, y, z[n].T , |
|
1219 | ax.plt = ax.pcolormesh(x, y, z[n].T , | |
| 1214 | vmin=self.zmin, |
|
1220 | vmin=self.zmin, | |
| 1215 | vmax=self.zmax, |
|
1221 | vmax=self.zmax, | |
| 1216 | cmap=self.cmaps[n] |
|
1222 | cmap=self.cmaps[n] | |
| 1217 | ) |
|
1223 | ) | |
| 1218 | if self.showprofile: |
|
1224 | if self.showprofile: | |
| 1219 | ax.plot_profile.set_data(data['outlier_rtc'][n], self.y) |
|
1225 | ax.plot_profile.set_data(data['outlier_rtc'][n], self.y) | |
| 1220 | self.pf_axes[n].set_xlabel('') |
|
1226 | self.pf_axes[n].set_xlabel('') | |
| 1221 |
|
1227 | |||
| 1222 | class NIncohIntRTIPlot(Plot): |
|
1228 | class NIncohIntRTIPlot(Plot): | |
| 1223 | ''' |
|
1229 | ''' | |
| 1224 | Plot for data_xxxx object |
|
1230 | Plot for data_xxxx object | |
| 1225 | ''' |
|
1231 | ''' | |
| 1226 |
|
1232 | |||
| 1227 | CODE = 'integrations_rtc' # Range Time Counts |
|
1233 | CODE = 'integrations_rtc' # Range Time Counts | |
| 1228 | colormap = 'BuGn' |
|
1234 | colormap = 'BuGn' | |
| 1229 | plot_type = 'pcolorbuffer' |
|
1235 | plot_type = 'pcolorbuffer' | |
| 1230 |
|
1236 | |||
| 1231 | def setup(self): |
|
1237 | def setup(self): | |
| 1232 | self.xaxis = 'time' |
|
1238 | self.xaxis = 'time' | |
| 1233 | self.ncols = 1 |
|
1239 | self.ncols = 1 | |
| 1234 | self.nrows = self.data.shape('integrations_rtc')[0] |
|
1240 | self.nrows = self.data.shape('integrations_rtc')[0] | |
| 1235 | self.nplots = self.nrows |
|
1241 | self.nplots = self.nrows | |
| 1236 | self.plots_adjust.update({'hspace':0.8, 'left': 0.08, 'bottom': 0.2, 'right':0.94}) |
|
1242 | self.plots_adjust.update({'hspace':0.8, 'left': 0.08, 'bottom': 0.2, 'right':0.94}) | |
| 1237 |
|
1243 | |||
| 1238 |
|
1244 | |||
| 1239 | if not self.xlabel: |
|
1245 | if not self.xlabel: | |
| 1240 | self.xlabel = 'Time' |
|
1246 | self.xlabel = 'Time' | |
| 1241 |
|
1247 | |||
| 1242 | self.ylabel = 'Height [km]' |
|
1248 | self.ylabel = 'Height [km]' | |
| 1243 | if not self.titles: |
|
1249 | if not self.titles: | |
| 1244 | self.titles = ['Integration Ch:{}'.format(x) for x in range(self.nrows)] |
|
1250 | self.titles = ['Integration Ch:{}'.format(x) for x in range(self.nrows)] | |
| 1245 |
|
1251 | |||
| 1246 | def update(self, dataOut): |
|
1252 | def update(self, dataOut): | |
| 1247 |
|
1253 | |||
| 1248 | data = {} |
|
1254 | data = {} | |
| 1249 | data['integrations_rtc'] = dataOut.nIncohInt |
|
1255 | data['integrations_rtc'] = dataOut.nIncohInt | |
| 1250 |
|
1256 | |||
| 1251 | meta = {} |
|
1257 | meta = {} | |
| 1252 |
|
1258 | |||
| 1253 | return data, meta |
|
1259 | return data, meta | |
| 1254 |
|
1260 | |||
| 1255 | def plot(self): |
|
1261 | def plot(self): | |
| 1256 | # self.data.normalize_heights() |
|
1262 | # self.data.normalize_heights() | |
| 1257 | self.x = self.data.times |
|
1263 | self.x = self.data.times | |
| 1258 | self.y = self.data.yrange |
|
1264 | self.y = self.data.yrange | |
| 1259 | self.z = self.data['integrations_rtc'] |
|
1265 | self.z = self.data['integrations_rtc'] | |
| 1260 |
|
1266 | |||
| 1261 | #self.z = numpy.ma.masked_invalid(self.z) |
|
1267 | #self.z = numpy.ma.masked_invalid(self.z) | |
| 1262 |
|
1268 | |||
| 1263 | if self.decimation is None: |
|
1269 | if self.decimation is None: | |
| 1264 | x, y, z = self.fill_gaps(self.x, self.y, self.z) |
|
1270 | x, y, z = self.fill_gaps(self.x, self.y, self.z) | |
| 1265 | else: |
|
1271 | else: | |
| 1266 | x, y, z = self.fill_gaps(*self.decimate()) |
|
1272 | x, y, z = self.fill_gaps(*self.decimate()) | |
| 1267 |
|
1273 | |||
| 1268 | for n, ax in enumerate(self.axes): |
|
1274 | for n, ax in enumerate(self.axes): | |
| 1269 |
|
1275 | |||
| 1270 | self.zmax = self.zmax if self.zmax is not None else numpy.max( |
|
1276 | self.zmax = self.zmax if self.zmax is not None else numpy.max( | |
| 1271 | self.z[n]) |
|
1277 | self.z[n]) | |
| 1272 | self.zmin = self.zmin if self.zmin is not None else numpy.min( |
|
1278 | self.zmin = self.zmin if self.zmin is not None else numpy.min( | |
| 1273 | self.z[n]) |
|
1279 | self.z[n]) | |
| 1274 | data = self.data[-1] |
|
1280 | data = self.data[-1] | |
| 1275 | if ax.firsttime: |
|
1281 | if ax.firsttime: | |
| 1276 | if self.zlimits is not None: |
|
1282 | if self.zlimits is not None: | |
| 1277 | self.zmin, self.zmax = self.zlimits[n] |
|
1283 | self.zmin, self.zmax = self.zlimits[n] | |
| 1278 |
|
1284 | |||
| 1279 | ax.plt = ax.pcolormesh(x, y, z[n].T, |
|
1285 | ax.plt = ax.pcolormesh(x, y, z[n].T, | |
| 1280 | vmin=self.zmin, |
|
1286 | vmin=self.zmin, | |
| 1281 | vmax=self.zmax, |
|
1287 | vmax=self.zmax, | |
| 1282 | cmap=self.cmaps[n] |
|
1288 | cmap=self.cmaps[n] | |
| 1283 | ) |
|
1289 | ) | |
| 1284 | if self.showprofile: |
|
1290 | if self.showprofile: | |
| 1285 | ax.plot_profile = self.pf_axes[n].plot(data['integrations_rtc'][n], self.y)[0] |
|
1291 | ax.plot_profile = self.pf_axes[n].plot(data['integrations_rtc'][n], self.y)[0] | |
| 1286 | self.pf_axes[n].set_xlabel('') |
|
1292 | self.pf_axes[n].set_xlabel('') | |
| 1287 | else: |
|
1293 | else: | |
| 1288 | if self.zlimits is not None: |
|
1294 | if self.zlimits is not None: | |
| 1289 | self.zmin, self.zmax = self.zlimits[n] |
|
1295 | self.zmin, self.zmax = self.zlimits[n] | |
| 1290 | ax.collections.remove(ax.collections[0]) |
|
1296 | ax.collections.remove(ax.collections[0]) | |
| 1291 | ax.plt = ax.pcolormesh(x, y, z[n].T , |
|
1297 | ax.plt = ax.pcolormesh(x, y, z[n].T , | |
| 1292 | vmin=self.zmin, |
|
1298 | vmin=self.zmin, | |
| 1293 | vmax=self.zmax, |
|
1299 | vmax=self.zmax, | |
| 1294 | cmap=self.cmaps[n] |
|
1300 | cmap=self.cmaps[n] | |
| 1295 | ) |
|
1301 | ) | |
| 1296 | if self.showprofile: |
|
1302 | if self.showprofile: | |
| 1297 | ax.plot_profile.set_data(data['integrations_rtc'][n], self.y) |
|
1303 | ax.plot_profile.set_data(data['integrations_rtc'][n], self.y) | |
| 1298 | self.pf_axes[n].set_xlabel('') |
|
1304 | self.pf_axes[n].set_xlabel('') | |
| 1299 |
|
1305 | |||
| 1300 |
|
1306 | |||
| 1301 | import datetime |
|
1307 | import datetime | |
| 1302 | class NoiselessRTILinePlot(Plot): |
|
1308 | class NoiselessRTILinePlot(Plot): | |
| 1303 | ''' |
|
1309 | ''' | |
| 1304 | Plot for RTI data |
|
1310 | Plot for RTI data | |
| 1305 | ''' |
|
1311 | ''' | |
| 1306 |
|
1312 | |||
| 1307 | CODE = 'noiseless_rtiLine' |
|
1313 | CODE = 'noiseless_rtiLine' | |
| 1308 |
|
1314 | |||
| 1309 | plot_type = 'scatter' |
|
1315 | plot_type = 'scatter' | |
| 1310 | titles = None |
|
1316 | titles = None | |
| 1311 | channelList = [] |
|
1317 | channelList = [] | |
| 1312 | elevationList = [] |
|
1318 | elevationList = [] | |
| 1313 | azimuthList = [] |
|
1319 | azimuthList = [] | |
| 1314 | last_noise = None |
|
1320 | last_noise = None | |
| 1315 |
|
1321 | |||
| 1316 | def setup(self): |
|
1322 | def setup(self): | |
| 1317 | self.xaxis = 'Range (Km)' |
|
1323 | self.xaxis = 'Range (Km)' | |
| 1318 | self.nplots = len(self.data.channels) |
|
1324 | self.nplots = len(self.data.channels) | |
| 1319 | self.nrows = int(numpy.ceil(self.nplots/2)) |
|
1325 | self.nrows = int(numpy.ceil(self.nplots/2)) | |
| 1320 | self.ncols = int(numpy.ceil(self.nplots/self.nrows)) |
|
1326 | self.ncols = int(numpy.ceil(self.nplots/self.nrows)) | |
| 1321 | self.ylabel = 'Intensity [dB]' |
|
1327 | self.ylabel = 'Intensity [dB]' | |
| 1322 | self.titles = ['Channel '+str(self.data.channels[i])+" " for i in self.data.channels] |
|
1328 | self.titles = ['Channel '+str(self.data.channels[i])+" " for i in self.data.channels] | |
| 1323 | self.colorbar = False |
|
1329 | self.colorbar = False | |
| 1324 | self.width = 6 |
|
1330 | self.width = 6 | |
| 1325 | self.height = 4 |
|
1331 | self.height = 4 | |
| 1326 |
|
1332 | |||
| 1327 | def update_list(self,dataOut): |
|
1333 | def update_list(self,dataOut): | |
| 1328 | if len(self.channelList) == 0: |
|
1334 | if len(self.channelList) == 0: | |
| 1329 | self.channelList = dataOut.channelList |
|
1335 | self.channelList = dataOut.channelList | |
| 1330 | if len(self.elevationList) == 0: |
|
1336 | if len(self.elevationList) == 0: | |
| 1331 | self.elevationList = dataOut.elevationList |
|
1337 | self.elevationList = dataOut.elevationList | |
| 1332 | if len(self.azimuthList) == 0: |
|
1338 | if len(self.azimuthList) == 0: | |
| 1333 | self.azimuthList = dataOut.azimuthList |
|
1339 | self.azimuthList = dataOut.azimuthList | |
| 1334 |
|
1340 | |||
| 1335 | def update(self, dataOut): |
|
1341 | def update(self, dataOut): | |
| 1336 | if len(self.channelList) == 0: |
|
1342 | if len(self.channelList) == 0: | |
| 1337 | self.update_list(dataOut) |
|
1343 | self.update_list(dataOut) | |
| 1338 |
|
1344 | |||
| 1339 | data = {} |
|
1345 | data = {} | |
| 1340 | meta = {} |
|
1346 | meta = {} | |
| 1341 | #print(dataOut.max_nIncohInt, dataOut.nIncohInt) |
|
1347 | #print(dataOut.max_nIncohInt, dataOut.nIncohInt) | |
| 1342 | #print(dataOut.windowOfFilter,dataOut.nCohInt,dataOut.nProfiles,dataOut.max_nIncohInt,dataOut.nIncohInt) |
|
1348 | #print(dataOut.windowOfFilter,dataOut.nCohInt,dataOut.nProfiles,dataOut.max_nIncohInt,dataOut.nIncohInt) | |
| 1343 | norm = dataOut.nProfiles * dataOut.max_nIncohInt * dataOut.nCohInt * dataOut.windowOfFilter |
|
1349 | norm = dataOut.nProfiles * dataOut.max_nIncohInt * dataOut.nCohInt * dataOut.windowOfFilter | |
| 1344 |
|
1350 | |||
| 1345 | n0 = 10*numpy.log10(dataOut.getNoise()/norm) |
|
1351 | n0 = 10*numpy.log10(dataOut.getNoise()/norm) | |
| 1346 | data['noise'] = n0 |
|
1352 | data['noise'] = n0 | |
| 1347 |
|
1353 | |||
| 1348 | noise = numpy.repeat(n0,dataOut.nHeights).reshape(dataOut.nChannels,dataOut.nHeights) |
|
1354 | noise = numpy.repeat(n0,dataOut.nHeights).reshape(dataOut.nChannels,dataOut.nHeights) | |
| 1349 | noiseless_data = dataOut.getPower() - noise |
|
1355 | noiseless_data = dataOut.getPower() - noise | |
| 1350 |
|
1356 | |||
| 1351 | #print("power, noise:", dataOut.getPower(), n0) |
|
1357 | #print("power, noise:", dataOut.getPower(), n0) | |
| 1352 | #print(noise) |
|
1358 | #print(noise) | |
| 1353 | #print(noiseless_data) |
|
1359 | #print(noiseless_data) | |
| 1354 |
|
1360 | |||
| 1355 | data['noiseless_rtiLine'] = noiseless_data |
|
1361 | data['noiseless_rtiLine'] = noiseless_data | |
| 1356 |
|
1362 | |||
| 1357 | #print(noiseless_data.shape, self.name) |
|
1363 | #print(noiseless_data.shape, self.name) | |
| 1358 | data['time'] = dataOut.utctime |
|
1364 | data['time'] = dataOut.utctime | |
| 1359 |
|
1365 | |||
| 1360 | return data, meta |
|
1366 | return data, meta | |
| 1361 |
|
1367 | |||
| 1362 | def plot(self): |
|
1368 | def plot(self): | |
| 1363 |
|
1369 | |||
| 1364 | self.x = self.data.times |
|
1370 | self.x = self.data.times | |
| 1365 | self.y = self.data.yrange |
|
1371 | self.y = self.data.yrange | |
| 1366 | #print(self.data['noiseless_rtiLine'].shape, self.y.shape, self.name) |
|
1372 | #print(self.data['noiseless_rtiLine'].shape, self.y.shape, self.name) | |
| 1367 | #ts = self.data['time'][0].squeeze() |
|
1373 | #ts = self.data['time'][0].squeeze() | |
| 1368 | if len(self.data['noiseless_rtiLine'])>2 : |
|
1374 | if len(self.data['noiseless_rtiLine'])>2 : | |
| 1369 | self.z = self.data['noiseless_rtiLine'][:, -1,:] |
|
1375 | self.z = self.data['noiseless_rtiLine'][:, -1,:] | |
| 1370 | else: |
|
1376 | else: | |
| 1371 | self.z = self.data['noiseless_rtiLine'] |
|
1377 | self.z = self.data['noiseless_rtiLine'] | |
| 1372 | #print(self.z.shape, self.y.shape, ts) |
|
1378 | #print(self.z.shape, self.y.shape, ts) | |
| 1373 | #thisDatetime = datetime.datetime.utcfromtimestamp(ts) |
|
1379 | #thisDatetime = datetime.datetime.utcfromtimestamp(ts) | |
| 1374 |
|
1380 | |||
| 1375 | for i,ax in enumerate(self.axes): |
|
1381 | for i,ax in enumerate(self.axes): | |
| 1376 | #self.titles[i] = "Channel {} {}".format(i, thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
1382 | #self.titles[i] = "Channel {} {}".format(i, thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
| 1377 |
|
1383 | |||
| 1378 |
|
1384 | |||
| 1379 | if ax.firsttime: |
|
1385 | if ax.firsttime: | |
| 1380 | #self.xmin = min(self.z) |
|
1386 | #self.xmin = min(self.z) | |
| 1381 | #self.xmax = max(self.z) |
|
1387 | #self.xmax = max(self.z) | |
| 1382 | ax.plt_r = ax.plot(self.z[i], self.y)[0] |
|
1388 | ax.plt_r = ax.plot(self.z[i], self.y)[0] | |
| 1383 | else: |
|
1389 | else: | |
| 1384 | ax.plt_r.set_data(self.z[i], self.y) |
|
1390 | ax.plt_r.set_data(self.z[i], self.y) | |
| 1385 |
|
1391 | |||
| 1386 |
|
1392 | |||
| 1387 |
|
1393 | |||
| 1388 | class GeneralProfilePlot(Plot): |
|
1394 | class GeneralProfilePlot(Plot): | |
| 1389 | ''' |
|
1395 | ''' | |
| 1390 | Plot for RTI data |
|
1396 | Plot for RTI data | |
| 1391 | ''' |
|
1397 | ''' | |
| 1392 |
|
1398 | |||
| 1393 | CODE = 'general_profilePlot' |
|
1399 | CODE = 'general_profilePlot' | |
| 1394 |
|
1400 | |||
| 1395 | plot_type = 'scatter' |
|
1401 | plot_type = 'scatter' | |
| 1396 | titles = None |
|
1402 | titles = None | |
| 1397 | channelList = [] |
|
1403 | channelList = [] | |
| 1398 | elevationList = [] |
|
1404 | elevationList = [] | |
| 1399 | azimuthList = [] |
|
1405 | azimuthList = [] | |
| 1400 | last_noise = None |
|
1406 | last_noise = None | |
| 1401 |
|
1407 | |||
| 1402 | def setup(self): |
|
1408 | def setup(self): | |
| 1403 | self.xaxis = 'Range (Km)' |
|
1409 | self.xaxis = 'Range (Km)' | |
| 1404 | self.nplots = len(self.data.channels) |
|
1410 | self.nplots = len(self.data.channels) | |
| 1405 | self.nrows = int(numpy.ceil(self.nplots/2)) |
|
1411 | self.nrows = int(numpy.ceil(self.nplots/2)) | |
| 1406 | self.ncols = int(numpy.ceil(self.nplots/self.nrows)) |
|
1412 | self.ncols = int(numpy.ceil(self.nplots/self.nrows)) | |
| 1407 | self.ylabel = 'Intensity [dB]' |
|
1413 | self.ylabel = 'Intensity [dB]' | |
| 1408 | self.titles = ['Channel '+str(self.data.channels[i])+" " for i in self.data.channels] |
|
1414 | self.titles = ['Channel '+str(self.data.channels[i])+" " for i in self.data.channels] | |
| 1409 | self.colorbar = False |
|
1415 | self.colorbar = False | |
| 1410 | self.width = 6 |
|
1416 | self.width = 6 | |
| 1411 | self.height = 4 |
|
1417 | self.height = 4 | |
| 1412 |
|
1418 | |||
| 1413 | def update_list(self,dataOut): |
|
1419 | def update_list(self,dataOut): | |
| 1414 | if len(self.channelList) == 0: |
|
1420 | if len(self.channelList) == 0: | |
| 1415 | self.channelList = dataOut.channelList |
|
1421 | self.channelList = dataOut.channelList | |
| 1416 | if len(self.elevationList) == 0: |
|
1422 | if len(self.elevationList) == 0: | |
| 1417 | self.elevationList = dataOut.elevationList |
|
1423 | self.elevationList = dataOut.elevationList | |
| 1418 | if len(self.azimuthList) == 0: |
|
1424 | if len(self.azimuthList) == 0: | |
| 1419 | self.azimuthList = dataOut.azimuthList |
|
1425 | self.azimuthList = dataOut.azimuthList | |
| 1420 |
|
1426 | |||
| 1421 | def update(self, dataOut): |
|
1427 | def update(self, dataOut): | |
| 1422 | if len(self.channelList) == 0: |
|
1428 | if len(self.channelList) == 0: | |
| 1423 | self.update_list(dataOut) |
|
1429 | self.update_list(dataOut) | |
| 1424 |
|
1430 | |||
| 1425 | data = {} |
|
1431 | data = {} | |
| 1426 | meta = {} |
|
1432 | meta = {} | |
| 1427 |
|
1433 | |||
| 1428 | norm = dataOut.nProfiles * dataOut.max_nIncohInt * dataOut.nCohInt * dataOut.windowOfFilter |
|
1434 | norm = dataOut.nProfiles * dataOut.max_nIncohInt * dataOut.nCohInt * dataOut.windowOfFilter | |
| 1429 | n0 = 10*numpy.log10(dataOut.getNoise()/norm) |
|
1435 | n0 = 10*numpy.log10(dataOut.getNoise()/norm) | |
| 1430 | data['noise'] = n0 |
|
1436 | data['noise'] = n0 | |
| 1431 |
|
1437 | |||
| 1432 | noise = numpy.repeat(n0,dataOut.nHeights).reshape(dataOut.nChannels,dataOut.nHeights) |
|
1438 | noise = numpy.repeat(n0,dataOut.nHeights).reshape(dataOut.nChannels,dataOut.nHeights) | |
| 1433 | noiseless_data = dataOut.getPower() - noise |
|
1439 | noiseless_data = dataOut.getPower() - noise | |
| 1434 |
|
1440 | |||
| 1435 | data['noiseless_rtiLine'] = noiseless_data |
|
1441 | data['noiseless_rtiLine'] = noiseless_data | |
| 1436 |
|
1442 | |||
| 1437 | #print(noiseless_data.shape, self.name) |
|
1443 | #print(noiseless_data.shape, self.name) | |
| 1438 | data['time'] = dataOut.utctime |
|
1444 | data['time'] = dataOut.utctime | |
| 1439 |
|
1445 | |||
| 1440 | return data, meta |
|
1446 | return data, meta | |
| 1441 |
|
1447 | |||
| 1442 | def plot(self): |
|
1448 | def plot(self): | |
| 1443 |
|
1449 | |||
| 1444 | self.x = self.data.times |
|
1450 | self.x = self.data.times | |
| 1445 | self.y = self.data.yrange |
|
1451 | self.y = self.data.yrange | |
| 1446 | #print(self.data['noiseless_rtiLine'].shape, self.y.shape, self.name) |
|
1452 | #print(self.data['noiseless_rtiLine'].shape, self.y.shape, self.name) | |
| 1447 | #ts = self.data['time'][0].squeeze() |
|
1453 | #ts = self.data['time'][0].squeeze() | |
| 1448 | if len(self.data['noiseless_rtiLine'])>2 : |
|
1454 | if len(self.data['noiseless_rtiLine'])>2 : | |
| 1449 | self.z = self.data['noiseless_rtiLine'][:, -1,:] |
|
1455 | self.z = self.data['noiseless_rtiLine'][:, -1,:] | |
| 1450 | else: |
|
1456 | else: | |
| 1451 | self.z = self.data['noiseless_rtiLine'] |
|
1457 | self.z = self.data['noiseless_rtiLine'] | |
| 1452 | #print(self.z.shape, self.y.shape, ts) |
|
1458 | #print(self.z.shape, self.y.shape, ts) | |
| 1453 | #thisDatetime = datetime.datetime.utcfromtimestamp(ts) |
|
1459 | #thisDatetime = datetime.datetime.utcfromtimestamp(ts) | |
| 1454 |
|
1460 | |||
| 1455 | for i,ax in enumerate(self.axes): |
|
1461 | for i,ax in enumerate(self.axes): | |
| 1456 | #self.titles[i] = "Channel {} {}".format(i, thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
1462 | #self.titles[i] = "Channel {} {}".format(i, thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
| 1457 |
|
1463 | |||
| 1458 |
|
1464 | |||
| 1459 | if ax.firsttime: |
|
1465 | if ax.firsttime: | |
| 1460 | #self.xmin = min(self.z) |
|
1466 | #self.xmin = min(self.z) | |
| 1461 | #self.xmax = max(self.z) |
|
1467 | #self.xmax = max(self.z) | |
| 1462 | ax.plt_r = ax.plot(self.z[i], self.y)[0] |
|
1468 | ax.plt_r = ax.plot(self.z[i], self.y)[0] | |
| 1463 | else: |
|
1469 | else: | |
| 1464 | ax.plt_r.set_data(self.z[i], self.y) No newline at end of file |
|
1470 | ax.plt_r.set_data(self.z[i], self.y) | |
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