| @@ -1,1350 +1,1351 | |||||
| 1 | # Copyright (c) 2012-2021 Jicamarca Radio Observatory |
|
1 | # Copyright (c) 2012-2021 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 | #import collections.abc |
|
11 | #import collections.abc | |
| 12 |
|
12 | |||
| 13 | from schainpy.model.graphics.jroplot_base import Plot, plt, log |
|
13 | from schainpy.model.graphics.jroplot_base import Plot, plt, log | |
| 14 |
|
14 | |||
| 15 | class SpectraPlot(Plot): |
|
15 | class SpectraPlot(Plot): | |
| 16 | ''' |
|
16 | ''' | |
| 17 | Plot for Spectra data |
|
17 | Plot for Spectra data | |
| 18 | ''' |
|
18 | ''' | |
| 19 |
|
19 | |||
| 20 | CODE = 'spc' |
|
20 | CODE = 'spc' | |
| 21 | colormap = 'jet' |
|
21 | colormap = 'jet' | |
| 22 | plot_type = 'pcolor' |
|
22 | plot_type = 'pcolor' | |
| 23 | buffering = False |
|
23 | buffering = False | |
| 24 |
|
24 | |||
| 25 | def setup(self): |
|
25 | def setup(self): | |
| 26 |
|
26 | |||
| 27 | self.nplots = len(self.data.channels) |
|
27 | self.nplots = len(self.data.channels) | |
| 28 | self.ncols = int(numpy.sqrt(self.nplots) + 0.9) |
|
28 | self.ncols = int(numpy.sqrt(self.nplots) + 0.9) | |
| 29 | self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9) |
|
29 | self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9) | |
| 30 | self.height = 2.6 * self.nrows |
|
30 | self.height = 2.6 * self.nrows | |
| 31 | self.cb_label = 'dB' |
|
31 | self.cb_label = 'dB' | |
| 32 | if self.showprofile: |
|
32 | if self.showprofile: | |
| 33 | self.width = 4 * self.ncols |
|
33 | self.width = 4 * self.ncols | |
| 34 | else: |
|
34 | else: | |
| 35 | self.width = 3.5 * self.ncols |
|
35 | self.width = 3.5 * self.ncols | |
| 36 | self.plots_adjust.update({'wspace': 0.8, 'hspace':0.2, 'left': 0.2, 'right': 0.9, 'bottom': 0.18}) |
|
36 | self.plots_adjust.update({'wspace': 0.8, 'hspace':0.2, 'left': 0.2, 'right': 0.9, 'bottom': 0.18}) | |
| 37 | self.ylabel = 'Range [km]' |
|
37 | self.ylabel = 'Range [km]' | |
| 38 |
|
38 | |||
| 39 | def update(self, dataOut): |
|
39 | def update(self, dataOut): | |
| 40 |
|
40 | |||
| 41 | data = {} |
|
41 | data = {} | |
| 42 | meta = {} |
|
42 | meta = {} | |
| 43 |
|
43 | |||
| 44 | spc = 10*numpy.log10(dataOut.data_spc/dataOut.normFactor) |
|
44 | spc = 10*numpy.log10(dataOut.data_spc/dataOut.normFactor) | |
| 45 | #print("dataOut.normFactor: ", dataOut.normFactor) |
|
45 | #print("dataOut.normFactor: ", dataOut.normFactor) | |
| 46 | #print("spc: ", dataOut.data_spc[0,0,0]) |
|
46 | #print("spc: ", dataOut.data_spc[0,0,0]) | |
| 47 | #spc = 10*numpy.log10(dataOut.data_spc) |
|
47 | #spc = 10*numpy.log10(dataOut.data_spc) | |
| 48 | #print("Spc: ",spc[0]) |
|
48 | #print("Spc: ",spc[0]) | |
| 49 | #exit(1) |
|
49 | #exit(1) | |
| 50 | data['spc'] = spc |
|
50 | data['spc'] = spc | |
| 51 | data['rti'] = dataOut.getPower() |
|
51 | data['rti'] = dataOut.getPower() | |
| 52 | #print(data['rti'][0]) |
|
52 | #print(data['rti'][0]) | |
| 53 | #exit(1) |
|
53 | #exit(1) | |
| 54 | #print("NormFactor: ",dataOut.normFactor) |
|
54 | #print("NormFactor: ",dataOut.normFactor) | |
| 55 | #data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor) |
|
55 | #data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor) | |
| 56 | if hasattr(dataOut, 'LagPlot'): #Double Pulse |
|
56 | if hasattr(dataOut, 'LagPlot'): #Double Pulse | |
| 57 | max_hei_id = dataOut.nHeights - 2*dataOut.LagPlot |
|
57 | max_hei_id = dataOut.nHeights - 2*dataOut.LagPlot | |
| 58 | #data['noise'] = 10*numpy.log10(dataOut.getNoise(ymin_index=46,ymax_index=max_hei_id)/dataOut.normFactor) |
|
58 | #data['noise'] = 10*numpy.log10(dataOut.getNoise(ymin_index=46,ymax_index=max_hei_id)/dataOut.normFactor) | |
| 59 | #data['noise'] = 10*numpy.log10(dataOut.getNoise(ymin_index=40,ymax_index=max_hei_id)/dataOut.normFactor) |
|
59 | #data['noise'] = 10*numpy.log10(dataOut.getNoise(ymin_index=40,ymax_index=max_hei_id)/dataOut.normFactor) | |
| 60 | data['noise'] = 10*numpy.log10(dataOut.getNoise(ymin_index=53,ymax_index=max_hei_id)/dataOut.normFactor) |
|
60 | data['noise'] = 10*numpy.log10(dataOut.getNoise(ymin_index=53,ymax_index=max_hei_id)/dataOut.normFactor) | |
| 61 | data['noise'][0] = 10*numpy.log10(dataOut.getNoise(ymin_index=53)[0]/dataOut.normFactor) |
|
61 | data['noise'][0] = 10*numpy.log10(dataOut.getNoise(ymin_index=53)[0]/dataOut.normFactor) | |
| 62 | #data['noise'][1] = 22.035507 |
|
62 | #data['noise'][1] = 22.035507 | |
| 63 | else: |
|
63 | else: | |
| 64 | data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor) |
|
64 | data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor) | |
| 65 | #data['noise'] = 10*numpy.log10(dataOut.getNoise(ymin_index=26,ymax_index=44)/dataOut.normFactor) |
|
65 | #data['noise'] = 10*numpy.log10(dataOut.getNoise(ymin_index=26,ymax_index=44)/dataOut.normFactor) | |
| 66 | meta['xrange'] = (dataOut.getFreqRange(1)/1000., dataOut.getAcfRange(1), dataOut.getVelRange(1)) |
|
66 | extrapoints = spc.shape[1] % dataOut.nFFTPoints | |
|
|
67 | meta['xrange'] = (dataOut.getFreqRange(extrapoints))/1000., dataOut.getAcfRange(extrapoints)), dataOut.getVelRange(extrapoints))) | |||
| 67 |
|
68 | |||
| 68 | if self.CODE == 'spc_moments': |
|
69 | if self.CODE == 'spc_moments': | |
| 69 | data['moments'] = dataOut.moments |
|
70 | data['moments'] = dataOut.moments | |
| 70 | if self.CODE == 'gaussian_fit': |
|
71 | if self.CODE == 'gaussian_fit': | |
| 71 | data['gaussfit'] = dataOut.DGauFitParams |
|
72 | data['gaussfit'] = dataOut.DGauFitParams | |
| 72 |
|
73 | |||
| 73 | return data, meta |
|
74 | return data, meta | |
| 74 |
|
75 | |||
| 75 | def plot(self): |
|
76 | def plot(self): | |
| 76 |
|
77 | |||
| 77 | if self.xaxis == "frequency": |
|
78 | if self.xaxis == "frequency": | |
| 78 | x = self.data.xrange[0] |
|
79 | x = self.data.xrange[0] | |
| 79 | self.xlabel = "Frequency (kHz)" |
|
80 | self.xlabel = "Frequency (kHz)" | |
| 80 | elif self.xaxis == "time": |
|
81 | elif self.xaxis == "time": | |
| 81 | x = self.data.xrange[1] |
|
82 | x = self.data.xrange[1] | |
| 82 | self.xlabel = "Time (ms)" |
|
83 | self.xlabel = "Time (ms)" | |
| 83 | else: |
|
84 | else: | |
| 84 | x = self.data.xrange[2] |
|
85 | x = self.data.xrange[2] | |
| 85 | self.xlabel = "Velocity (m/s)" |
|
86 | self.xlabel = "Velocity (m/s)" | |
| 86 |
|
87 | |||
| 87 | if (self.CODE == 'spc_moments') | (self.CODE == 'gaussian_fit'): |
|
88 | if (self.CODE == 'spc_moments') | (self.CODE == 'gaussian_fit'): | |
| 88 | x = self.data.xrange[2] |
|
89 | x = self.data.xrange[2] | |
| 89 | self.xlabel = "Velocity (m/s)" |
|
90 | self.xlabel = "Velocity (m/s)" | |
| 90 |
|
91 | |||
| 91 | self.titles = [] |
|
92 | self.titles = [] | |
| 92 |
|
93 | |||
| 93 | y = self.data.yrange |
|
94 | y = self.data.yrange | |
| 94 | self.y = y |
|
95 | self.y = y | |
| 95 |
|
96 | |||
| 96 | data = self.data[-1] |
|
97 | data = self.data[-1] | |
| 97 | z = data['spc'] |
|
98 | z = data['spc'] | |
| 98 |
|
99 | |||
| 99 | self.CODE2 = 'spc_oblique' |
|
100 | self.CODE2 = 'spc_oblique' | |
| 100 |
|
101 | |||
| 101 | for n, ax in enumerate(self.axes): |
|
102 | for n, ax in enumerate(self.axes): | |
| 102 | noise = data['noise'][n] |
|
103 | noise = data['noise'][n] | |
| 103 | if self.CODE == 'spc_moments': |
|
104 | if self.CODE == 'spc_moments': | |
| 104 | mean = data['moments'][n, 1] |
|
105 | mean = data['moments'][n, 1] | |
| 105 | if self.CODE == 'gaussian_fit': |
|
106 | if self.CODE == 'gaussian_fit': | |
| 106 | gau0 = data['gaussfit'][n][2,:,0] |
|
107 | gau0 = data['gaussfit'][n][2,:,0] | |
| 107 | gau1 = data['gaussfit'][n][2,:,1] |
|
108 | gau1 = data['gaussfit'][n][2,:,1] | |
| 108 | if ax.firsttime: |
|
109 | if ax.firsttime: | |
| 109 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) |
|
110 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) | |
| 110 | self.xmin = self.xmin if self.xmin else numpy.nanmin(x)#-self.xmax |
|
111 | self.xmin = self.xmin if self.xmin else numpy.nanmin(x)#-self.xmax | |
| 111 | #self.zmin = self.zmin if self.zmin else numpy.nanmin(z) |
|
112 | #self.zmin = self.zmin if self.zmin else numpy.nanmin(z) | |
| 112 | #self.zmax = self.zmax if self.zmax else numpy.nanmax(z) |
|
113 | #self.zmax = self.zmax if self.zmax else numpy.nanmax(z) | |
| 113 | if self.zlimits is not None: |
|
114 | if self.zlimits is not None: | |
| 114 | self.zmin, self.zmax = self.zlimits[n] |
|
115 | self.zmin, self.zmax = self.zlimits[n] | |
| 115 |
|
116 | |||
| 116 | ax.plt = ax.pcolormesh(x, y, z[n].T, |
|
117 | ax.plt = ax.pcolormesh(x, y, z[n].T, | |
| 117 | vmin=self.zmin, |
|
118 | vmin=self.zmin, | |
| 118 | vmax=self.zmax, |
|
119 | vmax=self.zmax, | |
| 119 | cmap=plt.get_cmap(self.colormap), |
|
120 | cmap=plt.get_cmap(self.colormap), | |
| 120 | ) |
|
121 | ) | |
| 121 |
|
122 | |||
| 122 | if self.showprofile: |
|
123 | if self.showprofile: | |
| 123 | ax.plt_profile = self.pf_axes[n].plot( |
|
124 | ax.plt_profile = self.pf_axes[n].plot( | |
| 124 | data['rti'][n], y)[0] |
|
125 | data['rti'][n], y)[0] | |
| 125 | ax.plt_noise = self.pf_axes[n].plot(numpy.repeat(noise, len(y)), y, |
|
126 | ax.plt_noise = self.pf_axes[n].plot(numpy.repeat(noise, len(y)), y, | |
| 126 | color="k", linestyle="dashed", lw=1)[0] |
|
127 | color="k", linestyle="dashed", lw=1)[0] | |
| 127 | if self.CODE == 'spc_moments': |
|
128 | if self.CODE == 'spc_moments': | |
| 128 | ax.plt_mean = ax.plot(mean, y, color='k', lw=1)[0] |
|
129 | ax.plt_mean = ax.plot(mean, y, color='k', lw=1)[0] | |
| 129 | if self.CODE == 'gaussian_fit': |
|
130 | if self.CODE == 'gaussian_fit': | |
| 130 | ax.plt_gau0 = ax.plot(gau0, y, color='r', lw=1)[0] |
|
131 | ax.plt_gau0 = ax.plot(gau0, y, color='r', lw=1)[0] | |
| 131 | ax.plt_gau1 = ax.plot(gau1, y, color='y', lw=1)[0] |
|
132 | ax.plt_gau1 = ax.plot(gau1, y, color='y', lw=1)[0] | |
| 132 | else: |
|
133 | else: | |
| 133 | if self.zlimits is not None: |
|
134 | if self.zlimits is not None: | |
| 134 | self.zmin, self.zmax = self.zlimits[n] |
|
135 | self.zmin, self.zmax = self.zlimits[n] | |
| 135 | ax.plt.set_array(z[n].T.ravel()) |
|
136 | ax.plt.set_array(z[n].T.ravel()) | |
| 136 | if self.showprofile: |
|
137 | if self.showprofile: | |
| 137 | ax.plt_profile.set_data(data['rti'][n], y) |
|
138 | ax.plt_profile.set_data(data['rti'][n], y) | |
| 138 | ax.plt_noise.set_data(numpy.repeat(noise, len(y)), y) |
|
139 | ax.plt_noise.set_data(numpy.repeat(noise, len(y)), y) | |
| 139 | if self.CODE == 'spc_moments': |
|
140 | if self.CODE == 'spc_moments': | |
| 140 | ax.plt_mean.set_data(mean, y) |
|
141 | ax.plt_mean.set_data(mean, y) | |
| 141 | if self.CODE == 'gaussian_fit': |
|
142 | if self.CODE == 'gaussian_fit': | |
| 142 | ax.plt_gau0.set_data(gau0, y) |
|
143 | ax.plt_gau0.set_data(gau0, y) | |
| 143 | ax.plt_gau1.set_data(gau1, y) |
|
144 | ax.plt_gau1.set_data(gau1, y) | |
| 144 | self.titles.append('CH {}: {:3.2f}dB'.format(n, noise)) |
|
145 | self.titles.append('CH {}: {:3.2f}dB'.format(n, noise)) | |
| 145 |
|
146 | |||
| 146 | class SpectraObliquePlot(Plot): |
|
147 | class SpectraObliquePlot(Plot): | |
| 147 | ''' |
|
148 | ''' | |
| 148 | Plot for Spectra data |
|
149 | Plot for Spectra data | |
| 149 | ''' |
|
150 | ''' | |
| 150 |
|
151 | |||
| 151 | CODE = 'spc_oblique' |
|
152 | CODE = 'spc_oblique' | |
| 152 | colormap = 'jet' |
|
153 | colormap = 'jet' | |
| 153 | plot_type = 'pcolor' |
|
154 | plot_type = 'pcolor' | |
| 154 |
|
155 | |||
| 155 | def setup(self): |
|
156 | def setup(self): | |
| 156 | self.xaxis = "oblique" |
|
157 | self.xaxis = "oblique" | |
| 157 | self.nplots = len(self.data.channels) |
|
158 | self.nplots = len(self.data.channels) | |
| 158 | self.ncols = int(numpy.sqrt(self.nplots) + 0.9) |
|
159 | self.ncols = int(numpy.sqrt(self.nplots) + 0.9) | |
| 159 | self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9) |
|
160 | self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9) | |
| 160 | self.height = 2.6 * self.nrows |
|
161 | self.height = 2.6 * self.nrows | |
| 161 | self.cb_label = 'dB' |
|
162 | self.cb_label = 'dB' | |
| 162 | if self.showprofile: |
|
163 | if self.showprofile: | |
| 163 | self.width = 4 * self.ncols |
|
164 | self.width = 4 * self.ncols | |
| 164 | else: |
|
165 | else: | |
| 165 | self.width = 3.5 * self.ncols |
|
166 | self.width = 3.5 * self.ncols | |
| 166 | self.plots_adjust.update({'wspace': 0.8, 'hspace':0.2, 'left': 0.2, 'right': 0.9, 'bottom': 0.18}) |
|
167 | self.plots_adjust.update({'wspace': 0.8, 'hspace':0.2, 'left': 0.2, 'right': 0.9, 'bottom': 0.18}) | |
| 167 | self.ylabel = 'Range [km]' |
|
168 | self.ylabel = 'Range [km]' | |
| 168 |
|
169 | |||
| 169 | def update(self, dataOut): |
|
170 | def update(self, dataOut): | |
| 170 |
|
171 | |||
| 171 | data = {} |
|
172 | data = {} | |
| 172 | meta = {} |
|
173 | meta = {} | |
| 173 |
|
174 | |||
| 174 | spc = 10*numpy.log10(dataOut.data_spc/dataOut.normFactor) |
|
175 | spc = 10*numpy.log10(dataOut.data_spc/dataOut.normFactor) | |
| 175 | data['spc'] = spc |
|
176 | data['spc'] = spc | |
| 176 | data['rti'] = dataOut.getPower() |
|
177 | data['rti'] = dataOut.getPower() | |
| 177 | data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor) |
|
178 | data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor) | |
| 178 | meta['xrange'] = (dataOut.getFreqRange(1)/1000., dataOut.getAcfRange(1), dataOut.getVelRange(1)) |
|
179 | meta['xrange'] = (dataOut.getFreqRange(1)/1000., dataOut.getAcfRange(1), dataOut.getVelRange(1)) | |
| 179 | ''' |
|
180 | ''' | |
| 180 | data['shift1'] = dataOut.Oblique_params[0,-2,:] |
|
181 | data['shift1'] = dataOut.Oblique_params[0,-2,:] | |
| 181 | data['shift2'] = dataOut.Oblique_params[0,-1,:] |
|
182 | data['shift2'] = dataOut.Oblique_params[0,-1,:] | |
| 182 | data['shift1_error'] = dataOut.Oblique_param_errors[0,-2,:] |
|
183 | data['shift1_error'] = dataOut.Oblique_param_errors[0,-2,:] | |
| 183 | data['shift2_error'] = dataOut.Oblique_param_errors[0,-1,:] |
|
184 | data['shift2_error'] = dataOut.Oblique_param_errors[0,-1,:] | |
| 184 | ''' |
|
185 | ''' | |
| 185 | ''' |
|
186 | ''' | |
| 186 | data['shift1'] = dataOut.Oblique_params[0,1,:] |
|
187 | data['shift1'] = dataOut.Oblique_params[0,1,:] | |
| 187 | data['shift2'] = dataOut.Oblique_params[0,4,:] |
|
188 | data['shift2'] = dataOut.Oblique_params[0,4,:] | |
| 188 | data['shift1_error'] = dataOut.Oblique_param_errors[0,1,:] |
|
189 | data['shift1_error'] = dataOut.Oblique_param_errors[0,1,:] | |
| 189 | data['shift2_error'] = dataOut.Oblique_param_errors[0,4,:] |
|
190 | data['shift2_error'] = dataOut.Oblique_param_errors[0,4,:] | |
| 190 | ''' |
|
191 | ''' | |
| 191 | data['shift1'] = dataOut.Dop_EEJ_T1[0] |
|
192 | data['shift1'] = dataOut.Dop_EEJ_T1[0] | |
| 192 | data['shift2'] = dataOut.Dop_EEJ_T2[0] |
|
193 | data['shift2'] = dataOut.Dop_EEJ_T2[0] | |
| 193 | data['max_val_2'] = dataOut.Oblique_params[0,-1,:] |
|
194 | data['max_val_2'] = dataOut.Oblique_params[0,-1,:] | |
| 194 | data['shift1_error'] = dataOut.Err_Dop_EEJ_T1[0] |
|
195 | data['shift1_error'] = dataOut.Err_Dop_EEJ_T1[0] | |
| 195 | data['shift2_error'] = dataOut.Err_Dop_EEJ_T2[0] |
|
196 | data['shift2_error'] = dataOut.Err_Dop_EEJ_T2[0] | |
| 196 |
|
197 | |||
| 197 | return data, meta |
|
198 | return data, meta | |
| 198 |
|
199 | |||
| 199 | def plot(self): |
|
200 | def plot(self): | |
| 200 |
|
201 | |||
| 201 | if self.xaxis == "frequency": |
|
202 | if self.xaxis == "frequency": | |
| 202 | x = self.data.xrange[0] |
|
203 | x = self.data.xrange[0] | |
| 203 | self.xlabel = "Frequency (kHz)" |
|
204 | self.xlabel = "Frequency (kHz)" | |
| 204 | elif self.xaxis == "time": |
|
205 | elif self.xaxis == "time": | |
| 205 | x = self.data.xrange[1] |
|
206 | x = self.data.xrange[1] | |
| 206 | self.xlabel = "Time (ms)" |
|
207 | self.xlabel = "Time (ms)" | |
| 207 | else: |
|
208 | else: | |
| 208 | x = self.data.xrange[2] |
|
209 | x = self.data.xrange[2] | |
| 209 | self.xlabel = "Velocity (m/s)" |
|
210 | self.xlabel = "Velocity (m/s)" | |
| 210 |
|
211 | |||
| 211 | self.titles = [] |
|
212 | self.titles = [] | |
| 212 |
|
213 | |||
| 213 | y = self.data.yrange |
|
214 | y = self.data.yrange | |
| 214 | self.y = y |
|
215 | self.y = y | |
| 215 |
|
216 | |||
| 216 | data = self.data[-1] |
|
217 | data = self.data[-1] | |
| 217 | z = data['spc'] |
|
218 | z = data['spc'] | |
| 218 |
|
219 | |||
| 219 | for n, ax in enumerate(self.axes): |
|
220 | for n, ax in enumerate(self.axes): | |
| 220 | noise = self.data['noise'][n][-1] |
|
221 | noise = self.data['noise'][n][-1] | |
| 221 | shift1 = data['shift1'] |
|
222 | shift1 = data['shift1'] | |
| 222 | #print(shift1) |
|
223 | #print(shift1) | |
| 223 | shift2 = data['shift2'] |
|
224 | shift2 = data['shift2'] | |
| 224 | max_val_2 = data['max_val_2'] |
|
225 | max_val_2 = data['max_val_2'] | |
| 225 | err1 = data['shift1_error'] |
|
226 | err1 = data['shift1_error'] | |
| 226 | err2 = data['shift2_error'] |
|
227 | err2 = data['shift2_error'] | |
| 227 | if ax.firsttime: |
|
228 | if ax.firsttime: | |
| 228 |
|
229 | |||
| 229 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) |
|
230 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) | |
| 230 | self.xmin = self.xmin if self.xmin else -self.xmax |
|
231 | self.xmin = self.xmin if self.xmin else -self.xmax | |
| 231 | self.zmin = self.zmin if self.zmin else numpy.nanmin(z) |
|
232 | self.zmin = self.zmin if self.zmin else numpy.nanmin(z) | |
| 232 | self.zmax = self.zmax if self.zmax else numpy.nanmax(z) |
|
233 | self.zmax = self.zmax if self.zmax else numpy.nanmax(z) | |
| 233 | ax.plt = ax.pcolormesh(x, y, z[n].T, |
|
234 | ax.plt = ax.pcolormesh(x, y, z[n].T, | |
| 234 | vmin=self.zmin, |
|
235 | vmin=self.zmin, | |
| 235 | vmax=self.zmax, |
|
236 | vmax=self.zmax, | |
| 236 | cmap=plt.get_cmap(self.colormap) |
|
237 | cmap=plt.get_cmap(self.colormap) | |
| 237 | ) |
|
238 | ) | |
| 238 |
|
239 | |||
| 239 | if self.showprofile: |
|
240 | if self.showprofile: | |
| 240 | ax.plt_profile = self.pf_axes[n].plot( |
|
241 | ax.plt_profile = self.pf_axes[n].plot( | |
| 241 | self.data['rti'][n][-1], y)[0] |
|
242 | self.data['rti'][n][-1], y)[0] | |
| 242 | ax.plt_noise = self.pf_axes[n].plot(numpy.repeat(noise, len(y)), y, |
|
243 | ax.plt_noise = self.pf_axes[n].plot(numpy.repeat(noise, len(y)), y, | |
| 243 | color="k", linestyle="dashed", lw=1)[0] |
|
244 | color="k", linestyle="dashed", lw=1)[0] | |
| 244 |
|
245 | |||
| 245 | self.ploterr1 = ax.errorbar(shift1, y, xerr=err1, fmt='k^', elinewidth=2.2, marker='o', linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2) |
|
246 | self.ploterr1 = ax.errorbar(shift1, y, xerr=err1, fmt='k^', elinewidth=2.2, marker='o', linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2) | |
| 246 | self.ploterr2 = ax.errorbar(shift2, y, xerr=err2, fmt='m^',elinewidth=2.2,marker='o',linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2) |
|
247 | self.ploterr2 = ax.errorbar(shift2, y, xerr=err2, fmt='m^',elinewidth=2.2,marker='o',linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2) | |
| 247 | self.ploterr3 = ax.errorbar(max_val_2, y, xerr=0, fmt='g^',elinewidth=2.2,marker='o',linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2) |
|
248 | self.ploterr3 = ax.errorbar(max_val_2, y, xerr=0, fmt='g^',elinewidth=2.2,marker='o',linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2) | |
| 248 |
|
249 | |||
| 249 | #print("plotter1: ", self.ploterr1,shift1) |
|
250 | #print("plotter1: ", self.ploterr1,shift1) | |
| 250 |
|
251 | |||
| 251 | else: |
|
252 | else: | |
| 252 | #print("else plotter1: ", self.ploterr1,shift1) |
|
253 | #print("else plotter1: ", self.ploterr1,shift1) | |
| 253 | self.ploterr1.remove() |
|
254 | self.ploterr1.remove() | |
| 254 | self.ploterr2.remove() |
|
255 | self.ploterr2.remove() | |
| 255 | self.ploterr3.remove() |
|
256 | self.ploterr3.remove() | |
| 256 | ax.plt.set_array(z[n].T.ravel()) |
|
257 | ax.plt.set_array(z[n].T.ravel()) | |
| 257 | if self.showprofile: |
|
258 | if self.showprofile: | |
| 258 | ax.plt_profile.set_data(self.data['rti'][n][-1], y) |
|
259 | ax.plt_profile.set_data(self.data['rti'][n][-1], y) | |
| 259 | ax.plt_noise.set_data(numpy.repeat(noise, len(y)), y) |
|
260 | ax.plt_noise.set_data(numpy.repeat(noise, len(y)), y) | |
| 260 | self.ploterr1 = ax.errorbar(shift1, y, xerr=err1, fmt='k^', elinewidth=2.2, marker='o', linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2) |
|
261 | self.ploterr1 = ax.errorbar(shift1, y, xerr=err1, fmt='k^', elinewidth=2.2, marker='o', linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2) | |
| 261 | self.ploterr2 = ax.errorbar(shift2, y, xerr=err2, fmt='m^',elinewidth=2.2,marker='o',linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2) |
|
262 | self.ploterr2 = ax.errorbar(shift2, y, xerr=err2, fmt='m^',elinewidth=2.2,marker='o',linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2) | |
| 262 | self.ploterr3 = ax.errorbar(max_val_2, y, xerr=0, fmt='g^',elinewidth=2.2,marker='o',linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2) |
|
263 | self.ploterr3 = ax.errorbar(max_val_2, y, xerr=0, fmt='g^',elinewidth=2.2,marker='o',linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2) | |
| 263 |
|
264 | |||
| 264 | self.titles.append('CH {}: {:3.2f}dB'.format(n, noise)) |
|
265 | self.titles.append('CH {}: {:3.2f}dB'.format(n, noise)) | |
| 265 |
|
266 | |||
| 266 |
|
267 | |||
| 267 | class CrossSpectraPlot(Plot): |
|
268 | class CrossSpectraPlot(Plot): | |
| 268 |
|
269 | |||
| 269 | CODE = 'cspc' |
|
270 | CODE = 'cspc' | |
| 270 | colormap = 'jet' |
|
271 | colormap = 'jet' | |
| 271 | plot_type = 'pcolor' |
|
272 | plot_type = 'pcolor' | |
| 272 | zmin_coh = None |
|
273 | zmin_coh = None | |
| 273 | zmax_coh = None |
|
274 | zmax_coh = None | |
| 274 | zmin_phase = None |
|
275 | zmin_phase = None | |
| 275 | zmax_phase = None |
|
276 | zmax_phase = None | |
| 276 |
|
277 | |||
| 277 | def setup(self): |
|
278 | def setup(self): | |
| 278 |
|
279 | |||
| 279 | self.ncols = 4 |
|
280 | self.ncols = 4 | |
| 280 | self.nplots = len(self.data.pairs) * 2 |
|
281 | self.nplots = len(self.data.pairs) * 2 | |
| 281 | self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9) |
|
282 | self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9) | |
| 282 | self.width = 3.1 * self.ncols |
|
283 | self.width = 3.1 * self.ncols | |
| 283 | self.height = 5 * self.nrows |
|
284 | self.height = 5 * self.nrows | |
| 284 | self.ylabel = 'Range [km]' |
|
285 | self.ylabel = 'Range [km]' | |
| 285 | self.showprofile = False |
|
286 | self.showprofile = False | |
| 286 | self.plots_adjust.update({'left': 0.08, 'right': 0.92, 'wspace': 0.5, 'hspace':0.4, 'top':0.95, 'bottom': 0.08}) |
|
287 | self.plots_adjust.update({'left': 0.08, 'right': 0.92, 'wspace': 0.5, 'hspace':0.4, 'top':0.95, 'bottom': 0.08}) | |
| 287 |
|
288 | |||
| 288 | def update(self, dataOut): |
|
289 | def update(self, dataOut): | |
| 289 |
|
290 | |||
| 290 | data = {} |
|
291 | data = {} | |
| 291 | meta = {} |
|
292 | meta = {} | |
| 292 |
|
293 | |||
| 293 | spc = dataOut.data_spc |
|
294 | spc = dataOut.data_spc | |
| 294 | cspc = dataOut.data_cspc |
|
295 | cspc = dataOut.data_cspc | |
| 295 | meta['xrange'] = (dataOut.getFreqRange(1)/1000., dataOut.getAcfRange(1), dataOut.getVelRange(1)) |
|
296 | meta['xrange'] = (dataOut.getFreqRange(1)/1000., dataOut.getAcfRange(1), dataOut.getVelRange(1)) | |
| 296 | meta['pairs'] = dataOut.pairsList |
|
297 | meta['pairs'] = dataOut.pairsList | |
| 297 |
|
298 | |||
| 298 | tmp = [] |
|
299 | tmp = [] | |
| 299 |
|
300 | |||
| 300 | for n, pair in enumerate(meta['pairs']): |
|
301 | for n, pair in enumerate(meta['pairs']): | |
| 301 | out = cspc[n] / numpy.sqrt(spc[pair[0]] * spc[pair[1]]) |
|
302 | out = cspc[n] / numpy.sqrt(spc[pair[0]] * spc[pair[1]]) | |
| 302 | coh = numpy.abs(out) |
|
303 | coh = numpy.abs(out) | |
| 303 | phase = numpy.arctan2(out.imag, out.real) * 180 / numpy.pi |
|
304 | phase = numpy.arctan2(out.imag, out.real) * 180 / numpy.pi | |
| 304 | tmp.append(coh) |
|
305 | tmp.append(coh) | |
| 305 | tmp.append(phase) |
|
306 | tmp.append(phase) | |
| 306 |
|
307 | |||
| 307 | data['cspc'] = numpy.array(tmp) |
|
308 | data['cspc'] = numpy.array(tmp) | |
| 308 |
|
309 | |||
| 309 | return data, meta |
|
310 | return data, meta | |
| 310 |
|
311 | |||
| 311 | def plot(self): |
|
312 | def plot(self): | |
| 312 |
|
313 | |||
| 313 | if self.xaxis == "frequency": |
|
314 | if self.xaxis == "frequency": | |
| 314 | x = self.data.xrange[0] |
|
315 | x = self.data.xrange[0] | |
| 315 | self.xlabel = "Frequency (kHz)" |
|
316 | self.xlabel = "Frequency (kHz)" | |
| 316 | elif self.xaxis == "time": |
|
317 | elif self.xaxis == "time": | |
| 317 | x = self.data.xrange[1] |
|
318 | x = self.data.xrange[1] | |
| 318 | self.xlabel = "Time (ms)" |
|
319 | self.xlabel = "Time (ms)" | |
| 319 | else: |
|
320 | else: | |
| 320 | x = self.data.xrange[2] |
|
321 | x = self.data.xrange[2] | |
| 321 | self.xlabel = "Velocity (m/s)" |
|
322 | self.xlabel = "Velocity (m/s)" | |
| 322 |
|
323 | |||
| 323 | self.titles = [] |
|
324 | self.titles = [] | |
| 324 |
|
325 | |||
| 325 | y = self.data.yrange |
|
326 | y = self.data.yrange | |
| 326 | self.y = y |
|
327 | self.y = y | |
| 327 |
|
328 | |||
| 328 | data = self.data[-1] |
|
329 | data = self.data[-1] | |
| 329 | cspc = data['cspc'] |
|
330 | cspc = data['cspc'] | |
| 330 |
|
331 | |||
| 331 | for n in range(len(self.data.pairs)): |
|
332 | for n in range(len(self.data.pairs)): | |
| 332 | pair = self.data.pairs[n] |
|
333 | pair = self.data.pairs[n] | |
| 333 | coh = cspc[n*2] |
|
334 | coh = cspc[n*2] | |
| 334 | phase = cspc[n*2+1] |
|
335 | phase = cspc[n*2+1] | |
| 335 | ax = self.axes[2 * n] |
|
336 | ax = self.axes[2 * n] | |
| 336 | if ax.firsttime: |
|
337 | if ax.firsttime: | |
| 337 | ax.plt = ax.pcolormesh(x, y, coh.T, |
|
338 | ax.plt = ax.pcolormesh(x, y, coh.T, | |
| 338 | vmin=0, |
|
339 | vmin=0, | |
| 339 | vmax=1, |
|
340 | vmax=1, | |
| 340 | cmap=plt.get_cmap(self.colormap_coh) |
|
341 | cmap=plt.get_cmap(self.colormap_coh) | |
| 341 | ) |
|
342 | ) | |
| 342 | else: |
|
343 | else: | |
| 343 | ax.plt.set_array(coh.T.ravel()) |
|
344 | ax.plt.set_array(coh.T.ravel()) | |
| 344 | self.titles.append( |
|
345 | self.titles.append( | |
| 345 | 'Coherence Ch{} * Ch{}'.format(pair[0], pair[1])) |
|
346 | 'Coherence Ch{} * Ch{}'.format(pair[0], pair[1])) | |
| 346 |
|
347 | |||
| 347 | ax = self.axes[2 * n + 1] |
|
348 | ax = self.axes[2 * n + 1] | |
| 348 | if ax.firsttime: |
|
349 | if ax.firsttime: | |
| 349 | ax.plt = ax.pcolormesh(x, y, phase.T, |
|
350 | ax.plt = ax.pcolormesh(x, y, phase.T, | |
| 350 | vmin=-180, |
|
351 | vmin=-180, | |
| 351 | vmax=180, |
|
352 | vmax=180, | |
| 352 | cmap=plt.get_cmap(self.colormap_phase) |
|
353 | cmap=plt.get_cmap(self.colormap_phase) | |
| 353 | ) |
|
354 | ) | |
| 354 | else: |
|
355 | else: | |
| 355 | ax.plt.set_array(phase.T.ravel()) |
|
356 | ax.plt.set_array(phase.T.ravel()) | |
| 356 | self.titles.append('Phase CH{} * CH{}'.format(pair[0], pair[1])) |
|
357 | self.titles.append('Phase CH{} * CH{}'.format(pair[0], pair[1])) | |
| 357 |
|
358 | |||
| 358 |
|
359 | |||
| 359 | class CrossSpectra4Plot(Plot): |
|
360 | class CrossSpectra4Plot(Plot): | |
| 360 |
|
361 | |||
| 361 | CODE = 'cspc' |
|
362 | CODE = 'cspc' | |
| 362 | colormap = 'jet' |
|
363 | colormap = 'jet' | |
| 363 | plot_type = 'pcolor' |
|
364 | plot_type = 'pcolor' | |
| 364 | zmin_coh = None |
|
365 | zmin_coh = None | |
| 365 | zmax_coh = None |
|
366 | zmax_coh = None | |
| 366 | zmin_phase = None |
|
367 | zmin_phase = None | |
| 367 | zmax_phase = None |
|
368 | zmax_phase = None | |
| 368 |
|
369 | |||
| 369 | def setup(self): |
|
370 | def setup(self): | |
| 370 |
|
371 | |||
| 371 | self.ncols = 4 |
|
372 | self.ncols = 4 | |
| 372 | self.nrows = len(self.data.pairs) |
|
373 | self.nrows = len(self.data.pairs) | |
| 373 | self.nplots = self.nrows * 4 |
|
374 | self.nplots = self.nrows * 4 | |
| 374 | self.width = 3.1 * self.ncols |
|
375 | self.width = 3.1 * self.ncols | |
| 375 | self.height = 5 * self.nrows |
|
376 | self.height = 5 * self.nrows | |
| 376 | self.ylabel = 'Range [km]' |
|
377 | self.ylabel = 'Range [km]' | |
| 377 | self.showprofile = False |
|
378 | self.showprofile = False | |
| 378 | self.plots_adjust.update({'left': 0.08, 'right': 0.92, 'wspace': 0.5, 'hspace':0.4, 'top':0.95, 'bottom': 0.08}) |
|
379 | self.plots_adjust.update({'left': 0.08, 'right': 0.92, 'wspace': 0.5, 'hspace':0.4, 'top':0.95, 'bottom': 0.08}) | |
| 379 |
|
380 | |||
| 380 | def plot(self): |
|
381 | def plot(self): | |
| 381 |
|
382 | |||
| 382 | if self.xaxis == "frequency": |
|
383 | if self.xaxis == "frequency": | |
| 383 | x = self.data.xrange[0] |
|
384 | x = self.data.xrange[0] | |
| 384 | self.xlabel = "Frequency (kHz)" |
|
385 | self.xlabel = "Frequency (kHz)" | |
| 385 | elif self.xaxis == "time": |
|
386 | elif self.xaxis == "time": | |
| 386 | x = self.data.xrange[1] |
|
387 | x = self.data.xrange[1] | |
| 387 | self.xlabel = "Time (ms)" |
|
388 | self.xlabel = "Time (ms)" | |
| 388 | else: |
|
389 | else: | |
| 389 | x = self.data.xrange[2] |
|
390 | x = self.data.xrange[2] | |
| 390 | self.xlabel = "Velocity (m/s)" |
|
391 | self.xlabel = "Velocity (m/s)" | |
| 391 |
|
392 | |||
| 392 | self.titles = [] |
|
393 | self.titles = [] | |
| 393 |
|
394 | |||
| 394 |
|
395 | |||
| 395 | y = self.data.heights |
|
396 | y = self.data.heights | |
| 396 | self.y = y |
|
397 | self.y = y | |
| 397 | nspc = self.data['spc'] |
|
398 | nspc = self.data['spc'] | |
| 398 | #print(numpy.shape(self.data['spc'])) |
|
399 | #print(numpy.shape(self.data['spc'])) | |
| 399 | spc = self.data['cspc'][0] |
|
400 | spc = self.data['cspc'][0] | |
| 400 | #print(numpy.shape(nspc)) |
|
401 | #print(numpy.shape(nspc)) | |
| 401 | #exit() |
|
402 | #exit() | |
| 402 | #nspc[1,:,:] = numpy.flip(nspc[1,:,:],axis=0) |
|
403 | #nspc[1,:,:] = numpy.flip(nspc[1,:,:],axis=0) | |
| 403 | #print(numpy.shape(spc)) |
|
404 | #print(numpy.shape(spc)) | |
| 404 | #exit() |
|
405 | #exit() | |
| 405 | cspc = self.data['cspc'][1] |
|
406 | cspc = self.data['cspc'][1] | |
| 406 |
|
407 | |||
| 407 | #xflip=numpy.flip(x) |
|
408 | #xflip=numpy.flip(x) | |
| 408 | #print(numpy.shape(cspc)) |
|
409 | #print(numpy.shape(cspc)) | |
| 409 | #exit() |
|
410 | #exit() | |
| 410 |
|
411 | |||
| 411 | for n in range(self.nrows): |
|
412 | for n in range(self.nrows): | |
| 412 | noise = self.data['noise'][:,-1] |
|
413 | noise = self.data['noise'][:,-1] | |
| 413 | pair = self.data.pairs[n] |
|
414 | pair = self.data.pairs[n] | |
| 414 | #print(pair) |
|
415 | #print(pair) | |
| 415 | #exit() |
|
416 | #exit() | |
| 416 | ax = self.axes[4 * n] |
|
417 | ax = self.axes[4 * n] | |
| 417 | if ax.firsttime: |
|
418 | if ax.firsttime: | |
| 418 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) |
|
419 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) | |
| 419 | self.xmin = self.xmin if self.xmin else -self.xmax |
|
420 | self.xmin = self.xmin if self.xmin else -self.xmax | |
| 420 | self.zmin = self.zmin if self.zmin else numpy.nanmin(nspc) |
|
421 | self.zmin = self.zmin if self.zmin else numpy.nanmin(nspc) | |
| 421 | self.zmax = self.zmax if self.zmax else numpy.nanmax(nspc) |
|
422 | self.zmax = self.zmax if self.zmax else numpy.nanmax(nspc) | |
| 422 | ax.plt = ax.pcolormesh(x , y , nspc[pair[0]].T, |
|
423 | ax.plt = ax.pcolormesh(x , y , nspc[pair[0]].T, | |
| 423 | vmin=self.zmin, |
|
424 | vmin=self.zmin, | |
| 424 | vmax=self.zmax, |
|
425 | vmax=self.zmax, | |
| 425 | cmap=plt.get_cmap(self.colormap) |
|
426 | cmap=plt.get_cmap(self.colormap) | |
| 426 | ) |
|
427 | ) | |
| 427 | else: |
|
428 | else: | |
| 428 | #print(numpy.shape(nspc[pair[0]].T)) |
|
429 | #print(numpy.shape(nspc[pair[0]].T)) | |
| 429 | #exit() |
|
430 | #exit() | |
| 430 | ax.plt.set_array(nspc[pair[0]].T.ravel()) |
|
431 | ax.plt.set_array(nspc[pair[0]].T.ravel()) | |
| 431 | self.titles.append('CH {}: {:3.2f}dB'.format(pair[0], noise[pair[0]])) |
|
432 | self.titles.append('CH {}: {:3.2f}dB'.format(pair[0], noise[pair[0]])) | |
| 432 |
|
433 | |||
| 433 | ax = self.axes[4 * n + 1] |
|
434 | ax = self.axes[4 * n + 1] | |
| 434 |
|
435 | |||
| 435 | if ax.firsttime: |
|
436 | if ax.firsttime: | |
| 436 | ax.plt = ax.pcolormesh(x , y, numpy.flip(nspc[pair[1]],axis=0).T, |
|
437 | ax.plt = ax.pcolormesh(x , y, numpy.flip(nspc[pair[1]],axis=0).T, | |
| 437 | vmin=self.zmin, |
|
438 | vmin=self.zmin, | |
| 438 | vmax=self.zmax, |
|
439 | vmax=self.zmax, | |
| 439 | cmap=plt.get_cmap(self.colormap) |
|
440 | cmap=plt.get_cmap(self.colormap) | |
| 440 | ) |
|
441 | ) | |
| 441 | else: |
|
442 | else: | |
| 442 |
|
443 | |||
| 443 | ax.plt.set_array(numpy.flip(nspc[pair[1]],axis=0).T.ravel()) |
|
444 | ax.plt.set_array(numpy.flip(nspc[pair[1]],axis=0).T.ravel()) | |
| 444 | self.titles.append('CH {}: {:3.2f}dB'.format(pair[1], noise[pair[1]])) |
|
445 | self.titles.append('CH {}: {:3.2f}dB'.format(pair[1], noise[pair[1]])) | |
| 445 |
|
446 | |||
| 446 | out = cspc[n] / numpy.sqrt(spc[pair[0]] * spc[pair[1]]) |
|
447 | out = cspc[n] / numpy.sqrt(spc[pair[0]] * spc[pair[1]]) | |
| 447 | coh = numpy.abs(out) |
|
448 | coh = numpy.abs(out) | |
| 448 | phase = numpy.arctan2(out.imag, out.real) * 180 / numpy.pi |
|
449 | phase = numpy.arctan2(out.imag, out.real) * 180 / numpy.pi | |
| 449 |
|
450 | |||
| 450 | ax = self.axes[4 * n + 2] |
|
451 | ax = self.axes[4 * n + 2] | |
| 451 | if ax.firsttime: |
|
452 | if ax.firsttime: | |
| 452 | ax.plt = ax.pcolormesh(x, y, numpy.flip(coh,axis=0).T, |
|
453 | ax.plt = ax.pcolormesh(x, y, numpy.flip(coh,axis=0).T, | |
| 453 | vmin=0, |
|
454 | vmin=0, | |
| 454 | vmax=1, |
|
455 | vmax=1, | |
| 455 | cmap=plt.get_cmap(self.colormap_coh) |
|
456 | cmap=plt.get_cmap(self.colormap_coh) | |
| 456 | ) |
|
457 | ) | |
| 457 | else: |
|
458 | else: | |
| 458 | ax.plt.set_array(numpy.flip(coh,axis=0).T.ravel()) |
|
459 | ax.plt.set_array(numpy.flip(coh,axis=0).T.ravel()) | |
| 459 | self.titles.append( |
|
460 | self.titles.append( | |
| 460 | 'Coherence Ch{} * Ch{}'.format(pair[0], pair[1])) |
|
461 | 'Coherence Ch{} * Ch{}'.format(pair[0], pair[1])) | |
| 461 |
|
462 | |||
| 462 | ax = self.axes[4 * n + 3] |
|
463 | ax = self.axes[4 * n + 3] | |
| 463 | if ax.firsttime: |
|
464 | if ax.firsttime: | |
| 464 | ax.plt = ax.pcolormesh(x, y, numpy.flip(phase,axis=0).T, |
|
465 | ax.plt = ax.pcolormesh(x, y, numpy.flip(phase,axis=0).T, | |
| 465 | vmin=-180, |
|
466 | vmin=-180, | |
| 466 | vmax=180, |
|
467 | vmax=180, | |
| 467 | cmap=plt.get_cmap(self.colormap_phase) |
|
468 | cmap=plt.get_cmap(self.colormap_phase) | |
| 468 | ) |
|
469 | ) | |
| 469 | else: |
|
470 | else: | |
| 470 | ax.plt.set_array(numpy.flip(phase,axis=0).T.ravel()) |
|
471 | ax.plt.set_array(numpy.flip(phase,axis=0).T.ravel()) | |
| 471 | self.titles.append('Phase CH{} * CH{}'.format(pair[0], pair[1])) |
|
472 | self.titles.append('Phase CH{} * CH{}'.format(pair[0], pair[1])) | |
| 472 |
|
473 | |||
| 473 |
|
474 | |||
| 474 | class CrossSpectra2Plot(Plot): |
|
475 | class CrossSpectra2Plot(Plot): | |
| 475 |
|
476 | |||
| 476 | CODE = 'cspc' |
|
477 | CODE = 'cspc' | |
| 477 | colormap = 'jet' |
|
478 | colormap = 'jet' | |
| 478 | plot_type = 'pcolor' |
|
479 | plot_type = 'pcolor' | |
| 479 | zmin_coh = None |
|
480 | zmin_coh = None | |
| 480 | zmax_coh = None |
|
481 | zmax_coh = None | |
| 481 | zmin_phase = None |
|
482 | zmin_phase = None | |
| 482 | zmax_phase = None |
|
483 | zmax_phase = None | |
| 483 |
|
484 | |||
| 484 | def setup(self): |
|
485 | def setup(self): | |
| 485 |
|
486 | |||
| 486 | self.ncols = 1 |
|
487 | self.ncols = 1 | |
| 487 | self.nrows = len(self.data.pairs) |
|
488 | self.nrows = len(self.data.pairs) | |
| 488 | self.nplots = self.nrows * 1 |
|
489 | self.nplots = self.nrows * 1 | |
| 489 | self.width = 3.1 * self.ncols |
|
490 | self.width = 3.1 * self.ncols | |
| 490 | self.height = 5 * self.nrows |
|
491 | self.height = 5 * self.nrows | |
| 491 | self.ylabel = 'Range [km]' |
|
492 | self.ylabel = 'Range [km]' | |
| 492 | self.showprofile = False |
|
493 | self.showprofile = False | |
| 493 | self.plots_adjust.update({'left': 0.22, 'right': .90, 'wspace': 0.5, 'hspace':0.4, 'top':0.95, 'bottom': 0.08}) |
|
494 | self.plots_adjust.update({'left': 0.22, 'right': .90, 'wspace': 0.5, 'hspace':0.4, 'top':0.95, 'bottom': 0.08}) | |
| 494 |
|
495 | |||
| 495 | def plot(self): |
|
496 | def plot(self): | |
| 496 |
|
497 | |||
| 497 | if self.xaxis == "frequency": |
|
498 | if self.xaxis == "frequency": | |
| 498 | x = self.data.xrange[0] |
|
499 | x = self.data.xrange[0] | |
| 499 | self.xlabel = "Frequency (kHz)" |
|
500 | self.xlabel = "Frequency (kHz)" | |
| 500 | elif self.xaxis == "time": |
|
501 | elif self.xaxis == "time": | |
| 501 | x = self.data.xrange[1] |
|
502 | x = self.data.xrange[1] | |
| 502 | self.xlabel = "Time (ms)" |
|
503 | self.xlabel = "Time (ms)" | |
| 503 | else: |
|
504 | else: | |
| 504 | x = self.data.xrange[2] |
|
505 | x = self.data.xrange[2] | |
| 505 | self.xlabel = "Velocity (m/s)" |
|
506 | self.xlabel = "Velocity (m/s)" | |
| 506 |
|
507 | |||
| 507 | self.titles = [] |
|
508 | self.titles = [] | |
| 508 |
|
509 | |||
| 509 |
|
510 | |||
| 510 | y = self.data.heights |
|
511 | y = self.data.heights | |
| 511 | self.y = y |
|
512 | self.y = y | |
| 512 | #nspc = self.data['spc'] |
|
513 | #nspc = self.data['spc'] | |
| 513 | #print(numpy.shape(self.data['spc'])) |
|
514 | #print(numpy.shape(self.data['spc'])) | |
| 514 | #spc = self.data['cspc'][0] |
|
515 | #spc = self.data['cspc'][0] | |
| 515 | #print(numpy.shape(spc)) |
|
516 | #print(numpy.shape(spc)) | |
| 516 | #exit() |
|
517 | #exit() | |
| 517 | cspc = self.data['cspc'][1] |
|
518 | cspc = self.data['cspc'][1] | |
| 518 | #print(numpy.shape(cspc)) |
|
519 | #print(numpy.shape(cspc)) | |
| 519 | #exit() |
|
520 | #exit() | |
| 520 |
|
521 | |||
| 521 | for n in range(self.nrows): |
|
522 | for n in range(self.nrows): | |
| 522 | noise = self.data['noise'][:,-1] |
|
523 | noise = self.data['noise'][:,-1] | |
| 523 | pair = self.data.pairs[n] |
|
524 | pair = self.data.pairs[n] | |
| 524 | #print(pair) #exit() |
|
525 | #print(pair) #exit() | |
| 525 |
|
526 | |||
| 526 |
|
527 | |||
| 527 |
|
528 | |||
| 528 | out = cspc[n]# / numpy.sqrt(spc[pair[0]] * spc[pair[1]]) |
|
529 | out = cspc[n]# / numpy.sqrt(spc[pair[0]] * spc[pair[1]]) | |
| 529 |
|
530 | |||
| 530 | #print(out[:,53]) |
|
531 | #print(out[:,53]) | |
| 531 | #exit() |
|
532 | #exit() | |
| 532 | cross = numpy.abs(out) |
|
533 | cross = numpy.abs(out) | |
| 533 | z = cross/self.data.nFactor |
|
534 | z = cross/self.data.nFactor | |
| 534 | #print("here") |
|
535 | #print("here") | |
| 535 | #print(dataOut.data_spc[0,0,0]) |
|
536 | #print(dataOut.data_spc[0,0,0]) | |
| 536 | #exit() |
|
537 | #exit() | |
| 537 |
|
538 | |||
| 538 | cross = 10*numpy.log10(z) |
|
539 | cross = 10*numpy.log10(z) | |
| 539 | #print(numpy.shape(cross)) |
|
540 | #print(numpy.shape(cross)) | |
| 540 | #print(cross[0,:]) |
|
541 | #print(cross[0,:]) | |
| 541 | #print(self.data.nFactor) |
|
542 | #print(self.data.nFactor) | |
| 542 | #exit() |
|
543 | #exit() | |
| 543 | #phase = numpy.arctan2(out.imag, out.real) * 180 / numpy.pi |
|
544 | #phase = numpy.arctan2(out.imag, out.real) * 180 / numpy.pi | |
| 544 |
|
545 | |||
| 545 | ax = self.axes[1 * n] |
|
546 | ax = self.axes[1 * n] | |
| 546 | if ax.firsttime: |
|
547 | if ax.firsttime: | |
| 547 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) |
|
548 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) | |
| 548 | self.xmin = self.xmin if self.xmin else -self.xmax |
|
549 | self.xmin = self.xmin if self.xmin else -self.xmax | |
| 549 | self.zmin = self.zmin if self.zmin else numpy.nanmin(cross) |
|
550 | self.zmin = self.zmin if self.zmin else numpy.nanmin(cross) | |
| 550 | self.zmax = self.zmax if self.zmax else numpy.nanmax(cross) |
|
551 | self.zmax = self.zmax if self.zmax else numpy.nanmax(cross) | |
| 551 | ax.plt = ax.pcolormesh(x, y, cross.T, |
|
552 | ax.plt = ax.pcolormesh(x, y, cross.T, | |
| 552 | vmin=self.zmin, |
|
553 | vmin=self.zmin, | |
| 553 | vmax=self.zmax, |
|
554 | vmax=self.zmax, | |
| 554 | cmap=plt.get_cmap(self.colormap) |
|
555 | cmap=plt.get_cmap(self.colormap) | |
| 555 | ) |
|
556 | ) | |
| 556 | else: |
|
557 | else: | |
| 557 | ax.plt.set_array(cross.T.ravel()) |
|
558 | ax.plt.set_array(cross.T.ravel()) | |
| 558 | self.titles.append( |
|
559 | self.titles.append( | |
| 559 | 'Cross Spectra Power Ch{} * Ch{}'.format(pair[0], pair[1])) |
|
560 | 'Cross Spectra Power Ch{} * Ch{}'.format(pair[0], pair[1])) | |
| 560 |
|
561 | |||
| 561 |
|
562 | |||
| 562 | class CrossSpectra3Plot(Plot): |
|
563 | class CrossSpectra3Plot(Plot): | |
| 563 |
|
564 | |||
| 564 | CODE = 'cspc' |
|
565 | CODE = 'cspc' | |
| 565 | colormap = 'jet' |
|
566 | colormap = 'jet' | |
| 566 | plot_type = 'pcolor' |
|
567 | plot_type = 'pcolor' | |
| 567 | zmin_coh = None |
|
568 | zmin_coh = None | |
| 568 | zmax_coh = None |
|
569 | zmax_coh = None | |
| 569 | zmin_phase = None |
|
570 | zmin_phase = None | |
| 570 | zmax_phase = None |
|
571 | zmax_phase = None | |
| 571 |
|
572 | |||
| 572 | def setup(self): |
|
573 | def setup(self): | |
| 573 |
|
574 | |||
| 574 | self.ncols = 3 |
|
575 | self.ncols = 3 | |
| 575 | self.nrows = len(self.data.pairs) |
|
576 | self.nrows = len(self.data.pairs) | |
| 576 | self.nplots = self.nrows * 3 |
|
577 | self.nplots = self.nrows * 3 | |
| 577 | self.width = 3.1 * self.ncols |
|
578 | self.width = 3.1 * self.ncols | |
| 578 | self.height = 5 * self.nrows |
|
579 | self.height = 5 * self.nrows | |
| 579 | self.ylabel = 'Range [km]' |
|
580 | self.ylabel = 'Range [km]' | |
| 580 | self.showprofile = False |
|
581 | self.showprofile = False | |
| 581 | self.plots_adjust.update({'left': 0.22, 'right': .90, 'wspace': 0.5, 'hspace':0.4, 'top':0.95, 'bottom': 0.08}) |
|
582 | self.plots_adjust.update({'left': 0.22, 'right': .90, 'wspace': 0.5, 'hspace':0.4, 'top':0.95, 'bottom': 0.08}) | |
| 582 |
|
583 | |||
| 583 | def plot(self): |
|
584 | def plot(self): | |
| 584 |
|
585 | |||
| 585 | if self.xaxis == "frequency": |
|
586 | if self.xaxis == "frequency": | |
| 586 | x = self.data.xrange[0] |
|
587 | x = self.data.xrange[0] | |
| 587 | self.xlabel = "Frequency (kHz)" |
|
588 | self.xlabel = "Frequency (kHz)" | |
| 588 | elif self.xaxis == "time": |
|
589 | elif self.xaxis == "time": | |
| 589 | x = self.data.xrange[1] |
|
590 | x = self.data.xrange[1] | |
| 590 | self.xlabel = "Time (ms)" |
|
591 | self.xlabel = "Time (ms)" | |
| 591 | else: |
|
592 | else: | |
| 592 | x = self.data.xrange[2] |
|
593 | x = self.data.xrange[2] | |
| 593 | self.xlabel = "Velocity (m/s)" |
|
594 | self.xlabel = "Velocity (m/s)" | |
| 594 |
|
595 | |||
| 595 | self.titles = [] |
|
596 | self.titles = [] | |
| 596 |
|
597 | |||
| 597 |
|
598 | |||
| 598 | y = self.data.heights |
|
599 | y = self.data.heights | |
| 599 | self.y = y |
|
600 | self.y = y | |
| 600 | #nspc = self.data['spc'] |
|
601 | #nspc = self.data['spc'] | |
| 601 | #print(numpy.shape(self.data['spc'])) |
|
602 | #print(numpy.shape(self.data['spc'])) | |
| 602 | #spc = self.data['cspc'][0] |
|
603 | #spc = self.data['cspc'][0] | |
| 603 | #print(numpy.shape(spc)) |
|
604 | #print(numpy.shape(spc)) | |
| 604 | #exit() |
|
605 | #exit() | |
| 605 | cspc = self.data['cspc'][1] |
|
606 | cspc = self.data['cspc'][1] | |
| 606 | #print(numpy.shape(cspc)) |
|
607 | #print(numpy.shape(cspc)) | |
| 607 | #exit() |
|
608 | #exit() | |
| 608 |
|
609 | |||
| 609 | for n in range(self.nrows): |
|
610 | for n in range(self.nrows): | |
| 610 | noise = self.data['noise'][:,-1] |
|
611 | noise = self.data['noise'][:,-1] | |
| 611 | pair = self.data.pairs[n] |
|
612 | pair = self.data.pairs[n] | |
| 612 | #print(pair) #exit() |
|
613 | #print(pair) #exit() | |
| 613 |
|
614 | |||
| 614 |
|
615 | |||
| 615 |
|
616 | |||
| 616 | out = cspc[n]# / numpy.sqrt(spc[pair[0]] * spc[pair[1]]) |
|
617 | out = cspc[n]# / numpy.sqrt(spc[pair[0]] * spc[pair[1]]) | |
| 617 |
|
618 | |||
| 618 | #print(out[:,53]) |
|
619 | #print(out[:,53]) | |
| 619 | #exit() |
|
620 | #exit() | |
| 620 | cross = numpy.abs(out) |
|
621 | cross = numpy.abs(out) | |
| 621 | z = cross/self.data.nFactor |
|
622 | z = cross/self.data.nFactor | |
| 622 | cross = 10*numpy.log10(z) |
|
623 | cross = 10*numpy.log10(z) | |
| 623 |
|
624 | |||
| 624 | out_r= out.real/self.data.nFactor |
|
625 | out_r= out.real/self.data.nFactor | |
| 625 | #out_r = 10*numpy.log10(out_r) |
|
626 | #out_r = 10*numpy.log10(out_r) | |
| 626 |
|
627 | |||
| 627 | out_i= out.imag/self.data.nFactor |
|
628 | out_i= out.imag/self.data.nFactor | |
| 628 | #out_i = 10*numpy.log10(out_i) |
|
629 | #out_i = 10*numpy.log10(out_i) | |
| 629 | #print(numpy.shape(cross)) |
|
630 | #print(numpy.shape(cross)) | |
| 630 | #print(cross[0,:]) |
|
631 | #print(cross[0,:]) | |
| 631 | #print(self.data.nFactor) |
|
632 | #print(self.data.nFactor) | |
| 632 | #exit() |
|
633 | #exit() | |
| 633 | #phase = numpy.arctan2(out.imag, out.real) * 180 / numpy.pi |
|
634 | #phase = numpy.arctan2(out.imag, out.real) * 180 / numpy.pi | |
| 634 |
|
635 | |||
| 635 | ax = self.axes[3 * n] |
|
636 | ax = self.axes[3 * n] | |
| 636 | if ax.firsttime: |
|
637 | if ax.firsttime: | |
| 637 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) |
|
638 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) | |
| 638 | self.xmin = self.xmin if self.xmin else -self.xmax |
|
639 | self.xmin = self.xmin if self.xmin else -self.xmax | |
| 639 | self.zmin = self.zmin if self.zmin else numpy.nanmin(cross) |
|
640 | self.zmin = self.zmin if self.zmin else numpy.nanmin(cross) | |
| 640 | self.zmax = self.zmax if self.zmax else numpy.nanmax(cross) |
|
641 | self.zmax = self.zmax if self.zmax else numpy.nanmax(cross) | |
| 641 | ax.plt = ax.pcolormesh(x, y, cross.T, |
|
642 | ax.plt = ax.pcolormesh(x, y, cross.T, | |
| 642 | vmin=self.zmin, |
|
643 | vmin=self.zmin, | |
| 643 | vmax=self.zmax, |
|
644 | vmax=self.zmax, | |
| 644 | cmap=plt.get_cmap(self.colormap) |
|
645 | cmap=plt.get_cmap(self.colormap) | |
| 645 | ) |
|
646 | ) | |
| 646 | else: |
|
647 | else: | |
| 647 | ax.plt.set_array(cross.T.ravel()) |
|
648 | ax.plt.set_array(cross.T.ravel()) | |
| 648 | self.titles.append( |
|
649 | self.titles.append( | |
| 649 | 'Cross Spectra Power Ch{} * Ch{}'.format(pair[0], pair[1])) |
|
650 | 'Cross Spectra Power Ch{} * Ch{}'.format(pair[0], pair[1])) | |
| 650 |
|
651 | |||
| 651 | ax = self.axes[3 * n + 1] |
|
652 | ax = self.axes[3 * n + 1] | |
| 652 | if ax.firsttime: |
|
653 | if ax.firsttime: | |
| 653 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) |
|
654 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) | |
| 654 | self.xmin = self.xmin if self.xmin else -self.xmax |
|
655 | self.xmin = self.xmin if self.xmin else -self.xmax | |
| 655 | self.zmin = self.zmin if self.zmin else numpy.nanmin(cross) |
|
656 | self.zmin = self.zmin if self.zmin else numpy.nanmin(cross) | |
| 656 | self.zmax = self.zmax if self.zmax else numpy.nanmax(cross) |
|
657 | self.zmax = self.zmax if self.zmax else numpy.nanmax(cross) | |
| 657 | ax.plt = ax.pcolormesh(x, y, out_r.T, |
|
658 | ax.plt = ax.pcolormesh(x, y, out_r.T, | |
| 658 | vmin=-1.e6, |
|
659 | vmin=-1.e6, | |
| 659 | vmax=0, |
|
660 | vmax=0, | |
| 660 | cmap=plt.get_cmap(self.colormap) |
|
661 | cmap=plt.get_cmap(self.colormap) | |
| 661 | ) |
|
662 | ) | |
| 662 | else: |
|
663 | else: | |
| 663 | ax.plt.set_array(out_r.T.ravel()) |
|
664 | ax.plt.set_array(out_r.T.ravel()) | |
| 664 | self.titles.append( |
|
665 | self.titles.append( | |
| 665 | 'Cross Spectra Real Ch{} * Ch{}'.format(pair[0], pair[1])) |
|
666 | 'Cross Spectra Real Ch{} * Ch{}'.format(pair[0], pair[1])) | |
| 666 |
|
667 | |||
| 667 | ax = self.axes[3 * n + 2] |
|
668 | ax = self.axes[3 * n + 2] | |
| 668 |
|
669 | |||
| 669 |
|
670 | |||
| 670 | if ax.firsttime: |
|
671 | if ax.firsttime: | |
| 671 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) |
|
672 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) | |
| 672 | self.xmin = self.xmin if self.xmin else -self.xmax |
|
673 | self.xmin = self.xmin if self.xmin else -self.xmax | |
| 673 | self.zmin = self.zmin if self.zmin else numpy.nanmin(cross) |
|
674 | self.zmin = self.zmin if self.zmin else numpy.nanmin(cross) | |
| 674 | self.zmax = self.zmax if self.zmax else numpy.nanmax(cross) |
|
675 | self.zmax = self.zmax if self.zmax else numpy.nanmax(cross) | |
| 675 | ax.plt = ax.pcolormesh(x, y, out_i.T, |
|
676 | ax.plt = ax.pcolormesh(x, y, out_i.T, | |
| 676 | vmin=-1.e6, |
|
677 | vmin=-1.e6, | |
| 677 | vmax=1.e6, |
|
678 | vmax=1.e6, | |
| 678 | cmap=plt.get_cmap(self.colormap) |
|
679 | cmap=plt.get_cmap(self.colormap) | |
| 679 | ) |
|
680 | ) | |
| 680 | else: |
|
681 | else: | |
| 681 | ax.plt.set_array(out_i.T.ravel()) |
|
682 | ax.plt.set_array(out_i.T.ravel()) | |
| 682 | self.titles.append( |
|
683 | self.titles.append( | |
| 683 | 'Cross Spectra Imag Ch{} * Ch{}'.format(pair[0], pair[1])) |
|
684 | 'Cross Spectra Imag Ch{} * Ch{}'.format(pair[0], pair[1])) | |
| 684 |
|
685 | |||
| 685 | class RTIPlot(Plot): |
|
686 | class RTIPlot(Plot): | |
| 686 | ''' |
|
687 | ''' | |
| 687 | Plot for RTI data |
|
688 | Plot for RTI data | |
| 688 | ''' |
|
689 | ''' | |
| 689 |
|
690 | |||
| 690 | CODE = 'rti' |
|
691 | CODE = 'rti' | |
| 691 | colormap = 'jet' |
|
692 | colormap = 'jet' | |
| 692 | plot_type = 'pcolorbuffer' |
|
693 | plot_type = 'pcolorbuffer' | |
| 693 |
|
694 | |||
| 694 | def setup(self): |
|
695 | def setup(self): | |
| 695 | self.xaxis = 'time' |
|
696 | self.xaxis = 'time' | |
| 696 | self.ncols = 1 |
|
697 | self.ncols = 1 | |
| 697 | self.nrows = len(self.data.channels) |
|
698 | self.nrows = len(self.data.channels) | |
| 698 | self.nplots = len(self.data.channels) |
|
699 | self.nplots = len(self.data.channels) | |
| 699 | self.ylabel = 'Range [km]' |
|
700 | self.ylabel = 'Range [km]' | |
| 700 | self.xlabel = 'Time' |
|
701 | self.xlabel = 'Time' | |
| 701 | self.cb_label = 'dB' |
|
702 | self.cb_label = 'dB' | |
| 702 | self.plots_adjust.update({'hspace':0.8, 'left': 0.1, 'bottom': 0.1, 'right':0.95}) |
|
703 | self.plots_adjust.update({'hspace':0.8, 'left': 0.1, 'bottom': 0.1, 'right':0.95}) | |
| 703 | self.titles = ['{} Channel {}'.format( |
|
704 | self.titles = ['{} Channel {}'.format( | |
| 704 | self.CODE.upper(), x) for x in range(self.nrows)] |
|
705 | self.CODE.upper(), x) for x in range(self.nrows)] | |
| 705 |
|
706 | |||
| 706 | def update(self, dataOut): |
|
707 | def update(self, dataOut): | |
| 707 |
|
708 | |||
| 708 | data = {} |
|
709 | data = {} | |
| 709 | meta = {} |
|
710 | meta = {} | |
| 710 | data['rti'] = dataOut.getPower() |
|
711 | data['rti'] = dataOut.getPower() | |
| 711 | #print(numpy.shape(data['rti'])) |
|
712 | #print(numpy.shape(data['rti'])) | |
| 712 |
|
713 | |||
| 713 | data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor) |
|
714 | data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor) | |
| 714 |
|
715 | |||
| 715 | return data, meta |
|
716 | return data, meta | |
| 716 |
|
717 | |||
| 717 | def plot(self): |
|
718 | def plot(self): | |
| 718 |
|
719 | |||
| 719 | self.x = self.data.times |
|
720 | self.x = self.data.times | |
| 720 | self.y = self.data.yrange |
|
721 | self.y = self.data.yrange | |
| 721 | self.z = self.data[self.CODE] |
|
722 | self.z = self.data[self.CODE] | |
| 722 | #print("Inside RTI: ", self.z) |
|
723 | #print("Inside RTI: ", self.z) | |
| 723 | self.z = numpy.ma.masked_invalid(self.z) |
|
724 | self.z = numpy.ma.masked_invalid(self.z) | |
| 724 |
|
725 | |||
| 725 | if self.decimation is None: |
|
726 | if self.decimation is None: | |
| 726 | x, y, z = self.fill_gaps(self.x, self.y, self.z) |
|
727 | x, y, z = self.fill_gaps(self.x, self.y, self.z) | |
| 727 | else: |
|
728 | else: | |
| 728 | x, y, z = self.fill_gaps(*self.decimate()) |
|
729 | x, y, z = self.fill_gaps(*self.decimate()) | |
| 729 | #print("self.z: ", self.z) |
|
730 | #print("self.z: ", self.z) | |
| 730 | #exit(1) |
|
731 | #exit(1) | |
| 731 | ''' |
|
732 | ''' | |
| 732 | if not isinstance(self.zmin, collections.abc.Sequence): |
|
733 | if not isinstance(self.zmin, collections.abc.Sequence): | |
| 733 | if not self.zmin: |
|
734 | if not self.zmin: | |
| 734 | self.zmin = [numpy.min(self.z)]*len(self.axes) |
|
735 | self.zmin = [numpy.min(self.z)]*len(self.axes) | |
| 735 | else: |
|
736 | else: | |
| 736 | self.zmin = [self.zmin]*len(self.axes) |
|
737 | self.zmin = [self.zmin]*len(self.axes) | |
| 737 |
|
738 | |||
| 738 | if not isinstance(self.zmax, collections.abc.Sequence): |
|
739 | if not isinstance(self.zmax, collections.abc.Sequence): | |
| 739 | if not self.zmax: |
|
740 | if not self.zmax: | |
| 740 | self.zmax = [numpy.max(self.z)]*len(self.axes) |
|
741 | self.zmax = [numpy.max(self.z)]*len(self.axes) | |
| 741 | else: |
|
742 | else: | |
| 742 | self.zmax = [self.zmax]*len(self.axes) |
|
743 | self.zmax = [self.zmax]*len(self.axes) | |
| 743 | ''' |
|
744 | ''' | |
| 744 | for n, ax in enumerate(self.axes): |
|
745 | for n, ax in enumerate(self.axes): | |
| 745 |
|
746 | |||
| 746 | self.zmin = self.zmin if self.zmin else numpy.min(self.z) |
|
747 | self.zmin = self.zmin if self.zmin else numpy.min(self.z) | |
| 747 | self.zmax = self.zmax if self.zmax else numpy.max(self.z) |
|
748 | self.zmax = self.zmax if self.zmax else numpy.max(self.z) | |
| 748 |
|
749 | |||
| 749 | if ax.firsttime: |
|
750 | if ax.firsttime: | |
| 750 | if self.zlimits is not None: |
|
751 | if self.zlimits is not None: | |
| 751 | self.zmin, self.zmax = self.zlimits[n] |
|
752 | self.zmin, self.zmax = self.zlimits[n] | |
| 752 | ax.plt = ax.pcolormesh(x, y, z[n].T, |
|
753 | ax.plt = ax.pcolormesh(x, y, z[n].T, | |
| 753 | vmin=self.zmin, |
|
754 | vmin=self.zmin, | |
| 754 | vmax=self.zmax, |
|
755 | vmax=self.zmax, | |
| 755 | cmap=plt.get_cmap(self.colormap) |
|
756 | cmap=plt.get_cmap(self.colormap) | |
| 756 | ) |
|
757 | ) | |
| 757 | if self.showprofile: |
|
758 | if self.showprofile: | |
| 758 | ax.plot_profile = self.pf_axes[n].plot( |
|
759 | ax.plot_profile = self.pf_axes[n].plot( | |
| 759 | self.data['rti'][n][-1], self.y)[0] |
|
760 | self.data['rti'][n][-1], self.y)[0] | |
| 760 | ax.plot_noise = self.pf_axes[n].plot(numpy.repeat(self.data['noise'][n][-1], len(self.y)), self.y, |
|
761 | ax.plot_noise = self.pf_axes[n].plot(numpy.repeat(self.data['noise'][n][-1], len(self.y)), self.y, | |
| 761 | color="k", linestyle="dashed", lw=1)[0] |
|
762 | color="k", linestyle="dashed", lw=1)[0] | |
| 762 | else: |
|
763 | else: | |
| 763 | if self.zlimits is not None: |
|
764 | if self.zlimits is not None: | |
| 764 | self.zmin, self.zmax = self.zlimits[n] |
|
765 | self.zmin, self.zmax = self.zlimits[n] | |
| 765 | ax.plt.remove() |
|
766 | ax.plt.remove() | |
| 766 | ax.plt = ax.pcolormesh(x, y, z[n].T, |
|
767 | ax.plt = ax.pcolormesh(x, y, z[n].T, | |
| 767 | vmin=self.zmin, |
|
768 | vmin=self.zmin, | |
| 768 | vmax=self.zmax, |
|
769 | vmax=self.zmax, | |
| 769 | cmap=plt.get_cmap(self.colormap) |
|
770 | cmap=plt.get_cmap(self.colormap) | |
| 770 | ) |
|
771 | ) | |
| 771 | if self.showprofile: |
|
772 | if self.showprofile: | |
| 772 | ax.plot_profile.set_data(self.data['rti'][n][-1], self.y) |
|
773 | ax.plot_profile.set_data(self.data['rti'][n][-1], self.y) | |
| 773 | ax.plot_noise.set_data(numpy.repeat( |
|
774 | ax.plot_noise.set_data(numpy.repeat( | |
| 774 | self.data['noise'][n][-1], len(self.y)), self.y) |
|
775 | self.data['noise'][n][-1], len(self.y)), self.y) | |
| 775 |
|
776 | |||
| 776 |
|
777 | |||
| 777 | class SpectrogramPlot(Plot): |
|
778 | class SpectrogramPlot(Plot): | |
| 778 | ''' |
|
779 | ''' | |
| 779 | Plot for Spectrogram data |
|
780 | Plot for Spectrogram data | |
| 780 | ''' |
|
781 | ''' | |
| 781 |
|
782 | |||
| 782 | CODE = 'Spectrogram_Profile' |
|
783 | CODE = 'Spectrogram_Profile' | |
| 783 | colormap = 'binary' |
|
784 | colormap = 'binary' | |
| 784 | plot_type = 'pcolorbuffer' |
|
785 | plot_type = 'pcolorbuffer' | |
| 785 |
|
786 | |||
| 786 | def setup(self): |
|
787 | def setup(self): | |
| 787 | self.xaxis = 'time' |
|
788 | self.xaxis = 'time' | |
| 788 | self.ncols = 1 |
|
789 | self.ncols = 1 | |
| 789 | self.nrows = len(self.data.channels) |
|
790 | self.nrows = len(self.data.channels) | |
| 790 | self.nplots = len(self.data.channels) |
|
791 | self.nplots = len(self.data.channels) | |
| 791 | self.xlabel = 'Time' |
|
792 | self.xlabel = 'Time' | |
| 792 | #self.cb_label = 'dB' |
|
793 | #self.cb_label = 'dB' | |
| 793 | self.plots_adjust.update({'hspace':1.2, 'left': 0.1, 'bottom': 0.12, 'right':0.95}) |
|
794 | self.plots_adjust.update({'hspace':1.2, 'left': 0.1, 'bottom': 0.12, 'right':0.95}) | |
| 794 | self.titles = [] |
|
795 | self.titles = [] | |
| 795 |
|
796 | |||
| 796 | #self.titles = ['{} Channel {} \n H = {} km ({} - {})'.format( |
|
797 | #self.titles = ['{} Channel {} \n H = {} km ({} - {})'.format( | |
| 797 | #self.CODE.upper(), x, self.data.heightList[self.data.hei], self.data.heightList[self.data.hei],self.data.heightList[self.data.hei]+(self.data.DH*self.data.nProfiles)) for x in range(self.nrows)] |
|
798 | #self.CODE.upper(), x, self.data.heightList[self.data.hei], self.data.heightList[self.data.hei],self.data.heightList[self.data.hei]+(self.data.DH*self.data.nProfiles)) for x in range(self.nrows)] | |
| 798 |
|
799 | |||
| 799 | self.titles = ['{} Channel {}'.format( |
|
800 | self.titles = ['{} Channel {}'.format( | |
| 800 | self.CODE.upper(), x) for x in range(self.nrows)] |
|
801 | self.CODE.upper(), x) for x in range(self.nrows)] | |
| 801 |
|
802 | |||
| 802 |
|
803 | |||
| 803 | def update(self, dataOut): |
|
804 | def update(self, dataOut): | |
| 804 | data = {} |
|
805 | data = {} | |
| 805 | meta = {} |
|
806 | meta = {} | |
| 806 |
|
807 | |||
| 807 | maxHei = 1620#+12000 |
|
808 | maxHei = 1620#+12000 | |
| 808 | maxHei = 1180 |
|
809 | maxHei = 1180 | |
| 809 | maxHei = 500 |
|
810 | maxHei = 500 | |
| 810 | indb = numpy.where(dataOut.heightList <= maxHei) |
|
811 | indb = numpy.where(dataOut.heightList <= maxHei) | |
| 811 | hei = indb[0][-1] |
|
812 | hei = indb[0][-1] | |
| 812 | #print(dataOut.heightList) |
|
813 | #print(dataOut.heightList) | |
| 813 |
|
814 | |||
| 814 | factor = dataOut.nIncohInt |
|
815 | factor = dataOut.nIncohInt | |
| 815 | z = dataOut.data_spc[:,:,hei] / factor |
|
816 | z = dataOut.data_spc[:,:,hei] / factor | |
| 816 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
817 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | |
| 817 | #buffer = 10 * numpy.log10(z) |
|
818 | #buffer = 10 * numpy.log10(z) | |
| 818 |
|
819 | |||
| 819 | meta['xrange'] = (dataOut.getFreqRange(1)/1000., dataOut.getAcfRange(1), dataOut.getVelRange(1)) |
|
820 | meta['xrange'] = (dataOut.getFreqRange(1)/1000., dataOut.getAcfRange(1), dataOut.getVelRange(1)) | |
| 820 |
|
821 | |||
| 821 |
|
822 | |||
| 822 | #self.hei = hei |
|
823 | #self.hei = hei | |
| 823 | #self.heightList = dataOut.heightList |
|
824 | #self.heightList = dataOut.heightList | |
| 824 | #self.DH = (dataOut.heightList[1] - dataOut.heightList[0])/dataOut.step |
|
825 | #self.DH = (dataOut.heightList[1] - dataOut.heightList[0])/dataOut.step | |
| 825 | #self.nProfiles = dataOut.nProfiles |
|
826 | #self.nProfiles = dataOut.nProfiles | |
| 826 |
|
827 | |||
| 827 | data['Spectrogram_Profile'] = 10 * numpy.log10(z) |
|
828 | data['Spectrogram_Profile'] = 10 * numpy.log10(z) | |
| 828 |
|
829 | |||
| 829 | data['hei'] = hei |
|
830 | data['hei'] = hei | |
| 830 | data['DH'] = (dataOut.heightList[1] - dataOut.heightList[0])/dataOut.step |
|
831 | data['DH'] = (dataOut.heightList[1] - dataOut.heightList[0])/dataOut.step | |
| 831 | data['nProfiles'] = dataOut.nProfiles |
|
832 | data['nProfiles'] = dataOut.nProfiles | |
| 832 | #meta['yrange'] = dataOut.heightList[0:dataOut.NSHTS] |
|
833 | #meta['yrange'] = dataOut.heightList[0:dataOut.NSHTS] | |
| 833 | ''' |
|
834 | ''' | |
| 834 | import matplotlib.pyplot as plt |
|
835 | import matplotlib.pyplot as plt | |
| 835 | plt.plot(10 * numpy.log10(z[0,:])) |
|
836 | plt.plot(10 * numpy.log10(z[0,:])) | |
| 836 | plt.show() |
|
837 | plt.show() | |
| 837 |
|
838 | |||
| 838 | from time import sleep |
|
839 | from time import sleep | |
| 839 | sleep(10) |
|
840 | sleep(10) | |
| 840 | ''' |
|
841 | ''' | |
| 841 | return data, meta |
|
842 | return data, meta | |
| 842 |
|
843 | |||
| 843 | def plot(self): |
|
844 | def plot(self): | |
| 844 |
|
845 | |||
| 845 | self.x = self.data.times |
|
846 | self.x = self.data.times | |
| 846 | self.z = self.data[self.CODE] |
|
847 | self.z = self.data[self.CODE] | |
| 847 | self.y = self.data.xrange[0] |
|
848 | self.y = self.data.xrange[0] | |
| 848 |
|
849 | |||
| 849 | hei = self.data['hei'][-1] |
|
850 | hei = self.data['hei'][-1] | |
| 850 | DH = self.data['DH'][-1] |
|
851 | DH = self.data['DH'][-1] | |
| 851 | nProfiles = self.data['nProfiles'][-1] |
|
852 | nProfiles = self.data['nProfiles'][-1] | |
| 852 |
|
853 | |||
| 853 | self.ylabel = "Frequency (kHz)" |
|
854 | self.ylabel = "Frequency (kHz)" | |
| 854 |
|
855 | |||
| 855 | self.z = numpy.ma.masked_invalid(self.z) |
|
856 | self.z = numpy.ma.masked_invalid(self.z) | |
| 856 |
|
857 | |||
| 857 | if self.decimation is None: |
|
858 | if self.decimation is None: | |
| 858 | x, y, z = self.fill_gaps(self.x, self.y, self.z) |
|
859 | x, y, z = self.fill_gaps(self.x, self.y, self.z) | |
| 859 | else: |
|
860 | else: | |
| 860 | x, y, z = self.fill_gaps(*self.decimate()) |
|
861 | x, y, z = self.fill_gaps(*self.decimate()) | |
| 861 |
|
862 | |||
| 862 | for n, ax in enumerate(self.axes): |
|
863 | for n, ax in enumerate(self.axes): | |
| 863 | self.zmin = self.zmin if self.zmin else numpy.min(self.z) |
|
864 | self.zmin = self.zmin if self.zmin else numpy.min(self.z) | |
| 864 | self.zmax = self.zmax if self.zmax else numpy.max(self.z) |
|
865 | self.zmax = self.zmax if self.zmax else numpy.max(self.z) | |
| 865 | data = self.data[-1] |
|
866 | data = self.data[-1] | |
| 866 | if ax.firsttime: |
|
867 | if ax.firsttime: | |
| 867 | ax.plt = ax.pcolormesh(x, y, z[n].T, |
|
868 | ax.plt = ax.pcolormesh(x, y, z[n].T, | |
| 868 | vmin=self.zmin, |
|
869 | vmin=self.zmin, | |
| 869 | vmax=self.zmax, |
|
870 | vmax=self.zmax, | |
| 870 | cmap=plt.get_cmap(self.colormap) |
|
871 | cmap=plt.get_cmap(self.colormap) | |
| 871 | ) |
|
872 | ) | |
| 872 | else: |
|
873 | else: | |
| 873 | ax.plt.remove() |
|
874 | ax.plt.remove() | |
| 874 | ax.plt = ax.pcolormesh(x, y, z[n].T, |
|
875 | ax.plt = ax.pcolormesh(x, y, z[n].T, | |
| 875 | vmin=self.zmin, |
|
876 | vmin=self.zmin, | |
| 876 | vmax=self.zmax, |
|
877 | vmax=self.zmax, | |
| 877 | cmap=plt.get_cmap(self.colormap) |
|
878 | cmap=plt.get_cmap(self.colormap) | |
| 878 | ) |
|
879 | ) | |
| 879 |
|
880 | |||
| 880 | #self.titles.append('Spectrogram') |
|
881 | #self.titles.append('Spectrogram') | |
| 881 |
|
882 | |||
| 882 | #self.titles.append('{} Channel {} \n H = {} km ({} - {})'.format( |
|
883 | #self.titles.append('{} Channel {} \n H = {} km ({} - {})'.format( | |
| 883 | #self.CODE.upper(), x, y[hei], y[hei],y[hei]+(DH*nProfiles))) |
|
884 | #self.CODE.upper(), x, y[hei], y[hei],y[hei]+(DH*nProfiles))) | |
| 884 |
|
885 | |||
| 885 |
|
886 | |||
| 886 |
|
887 | |||
| 887 |
|
888 | |||
| 888 | class CoherencePlot(RTIPlot): |
|
889 | class CoherencePlot(RTIPlot): | |
| 889 | ''' |
|
890 | ''' | |
| 890 | Plot for Coherence data |
|
891 | Plot for Coherence data | |
| 891 | ''' |
|
892 | ''' | |
| 892 |
|
893 | |||
| 893 | CODE = 'coh' |
|
894 | CODE = 'coh' | |
| 894 |
|
895 | |||
| 895 | def setup(self): |
|
896 | def setup(self): | |
| 896 | self.xaxis = 'time' |
|
897 | self.xaxis = 'time' | |
| 897 | self.ncols = 1 |
|
898 | self.ncols = 1 | |
| 898 | self.nrows = len(self.data.pairs) |
|
899 | self.nrows = len(self.data.pairs) | |
| 899 | self.nplots = len(self.data.pairs) |
|
900 | self.nplots = len(self.data.pairs) | |
| 900 | self.ylabel = 'Range [km]' |
|
901 | self.ylabel = 'Range [km]' | |
| 901 | self.xlabel = 'Time' |
|
902 | self.xlabel = 'Time' | |
| 902 | self.plots_adjust.update({'hspace':0.6, 'left': 0.1, 'bottom': 0.1,'right':0.95}) |
|
903 | self.plots_adjust.update({'hspace':0.6, 'left': 0.1, 'bottom': 0.1,'right':0.95}) | |
| 903 | if self.CODE == 'coh': |
|
904 | if self.CODE == 'coh': | |
| 904 | self.cb_label = '' |
|
905 | self.cb_label = '' | |
| 905 | self.titles = [ |
|
906 | self.titles = [ | |
| 906 | 'Coherence Map Ch{} * Ch{}'.format(x[0], x[1]) for x in self.data.pairs] |
|
907 | 'Coherence Map Ch{} * Ch{}'.format(x[0], x[1]) for x in self.data.pairs] | |
| 907 | else: |
|
908 | else: | |
| 908 | self.cb_label = 'Degrees' |
|
909 | self.cb_label = 'Degrees' | |
| 909 | self.titles = [ |
|
910 | self.titles = [ | |
| 910 | 'Phase Map Ch{} * Ch{}'.format(x[0], x[1]) for x in self.data.pairs] |
|
911 | 'Phase Map Ch{} * Ch{}'.format(x[0], x[1]) for x in self.data.pairs] | |
| 911 |
|
912 | |||
| 912 | def update(self, dataOut): |
|
913 | def update(self, dataOut): | |
| 913 |
|
914 | |||
| 914 | data = {} |
|
915 | data = {} | |
| 915 | meta = {} |
|
916 | meta = {} | |
| 916 | data['coh'] = dataOut.getCoherence() |
|
917 | data['coh'] = dataOut.getCoherence() | |
| 917 | meta['pairs'] = dataOut.pairsList |
|
918 | meta['pairs'] = dataOut.pairsList | |
| 918 |
|
919 | |||
| 919 | return data, meta |
|
920 | return data, meta | |
| 920 |
|
921 | |||
| 921 | class PhasePlot(CoherencePlot): |
|
922 | class PhasePlot(CoherencePlot): | |
| 922 | ''' |
|
923 | ''' | |
| 923 | Plot for Phase map data |
|
924 | Plot for Phase map data | |
| 924 | ''' |
|
925 | ''' | |
| 925 |
|
926 | |||
| 926 | CODE = 'phase' |
|
927 | CODE = 'phase' | |
| 927 | colormap = 'seismic' |
|
928 | colormap = 'seismic' | |
| 928 |
|
929 | |||
| 929 | def update(self, dataOut): |
|
930 | def update(self, dataOut): | |
| 930 |
|
931 | |||
| 931 | data = {} |
|
932 | data = {} | |
| 932 | meta = {} |
|
933 | meta = {} | |
| 933 | data['phase'] = dataOut.getCoherence(phase=True) |
|
934 | data['phase'] = dataOut.getCoherence(phase=True) | |
| 934 | meta['pairs'] = dataOut.pairsList |
|
935 | meta['pairs'] = dataOut.pairsList | |
| 935 |
|
936 | |||
| 936 | return data, meta |
|
937 | return data, meta | |
| 937 |
|
938 | |||
| 938 | class NoisePlot(Plot): |
|
939 | class NoisePlot(Plot): | |
| 939 | ''' |
|
940 | ''' | |
| 940 | Plot for noise |
|
941 | Plot for noise | |
| 941 | ''' |
|
942 | ''' | |
| 942 |
|
943 | |||
| 943 | CODE = 'noise' |
|
944 | CODE = 'noise' | |
| 944 | plot_type = 'scatterbuffer' |
|
945 | plot_type = 'scatterbuffer' | |
| 945 |
|
946 | |||
| 946 | def setup(self): |
|
947 | def setup(self): | |
| 947 | self.xaxis = 'time' |
|
948 | self.xaxis = 'time' | |
| 948 | self.ncols = 1 |
|
949 | self.ncols = 1 | |
| 949 | self.nrows = 1 |
|
950 | self.nrows = 1 | |
| 950 | self.nplots = 1 |
|
951 | self.nplots = 1 | |
| 951 | self.ylabel = 'Intensity [dB]' |
|
952 | self.ylabel = 'Intensity [dB]' | |
| 952 | self.xlabel = 'Time' |
|
953 | self.xlabel = 'Time' | |
| 953 | self.titles = ['Noise'] |
|
954 | self.titles = ['Noise'] | |
| 954 | self.colorbar = False |
|
955 | self.colorbar = False | |
| 955 | self.plots_adjust.update({'right': 0.85 }) |
|
956 | self.plots_adjust.update({'right': 0.85 }) | |
| 956 |
|
957 | |||
| 957 | def update(self, dataOut): |
|
958 | def update(self, dataOut): | |
| 958 |
|
959 | |||
| 959 | data = {} |
|
960 | data = {} | |
| 960 | meta = {} |
|
961 | meta = {} | |
| 961 | data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor).reshape(dataOut.nChannels, 1) |
|
962 | data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor).reshape(dataOut.nChannels, 1) | |
| 962 | meta['yrange'] = numpy.array([]) |
|
963 | meta['yrange'] = numpy.array([]) | |
| 963 |
|
964 | |||
| 964 | return data, meta |
|
965 | return data, meta | |
| 965 |
|
966 | |||
| 966 | def plot(self): |
|
967 | def plot(self): | |
| 967 |
|
968 | |||
| 968 | x = self.data.times |
|
969 | x = self.data.times | |
| 969 | xmin = self.data.min_time |
|
970 | xmin = self.data.min_time | |
| 970 | xmax = xmin + self.xrange * 60 * 60 |
|
971 | xmax = xmin + self.xrange * 60 * 60 | |
| 971 | Y = self.data['noise'] |
|
972 | Y = self.data['noise'] | |
| 972 |
|
973 | |||
| 973 | if self.axes[0].firsttime: |
|
974 | if self.axes[0].firsttime: | |
| 974 | self.ymin = numpy.nanmin(Y) - 5 |
|
975 | self.ymin = numpy.nanmin(Y) - 5 | |
| 975 | self.ymax = numpy.nanmax(Y) + 5 |
|
976 | self.ymax = numpy.nanmax(Y) + 5 | |
| 976 | for ch in self.data.channels: |
|
977 | for ch in self.data.channels: | |
| 977 | y = Y[ch] |
|
978 | y = Y[ch] | |
| 978 | self.axes[0].plot(x, y, lw=1, label='Ch{}'.format(ch)) |
|
979 | self.axes[0].plot(x, y, lw=1, label='Ch{}'.format(ch)) | |
| 979 | plt.legend(bbox_to_anchor=(1.18, 1.0)) |
|
980 | plt.legend(bbox_to_anchor=(1.18, 1.0)) | |
| 980 | else: |
|
981 | else: | |
| 981 | for ch in self.data.channels: |
|
982 | for ch in self.data.channels: | |
| 982 | y = Y[ch] |
|
983 | y = Y[ch] | |
| 983 | self.axes[0].lines[ch].set_data(x, y) |
|
984 | self.axes[0].lines[ch].set_data(x, y) | |
| 984 |
|
985 | |||
| 985 | self.ymin = numpy.nanmin(Y) - 5 |
|
986 | self.ymin = numpy.nanmin(Y) - 5 | |
| 986 | self.ymax = numpy.nanmax(Y) + 10 |
|
987 | self.ymax = numpy.nanmax(Y) + 10 | |
| 987 |
|
988 | |||
| 988 |
|
989 | |||
| 989 | class PowerProfilePlot(Plot): |
|
990 | class PowerProfilePlot(Plot): | |
| 990 |
|
991 | |||
| 991 | CODE = 'pow_profile' |
|
992 | CODE = 'pow_profile' | |
| 992 | plot_type = 'scatter' |
|
993 | plot_type = 'scatter' | |
| 993 |
|
994 | |||
| 994 | def setup(self): |
|
995 | def setup(self): | |
| 995 |
|
996 | |||
| 996 | self.ncols = 1 |
|
997 | self.ncols = 1 | |
| 997 | self.nrows = 1 |
|
998 | self.nrows = 1 | |
| 998 | self.nplots = 1 |
|
999 | self.nplots = 1 | |
| 999 | self.height = 4 |
|
1000 | self.height = 4 | |
| 1000 | self.width = 3 |
|
1001 | self.width = 3 | |
| 1001 | self.ylabel = 'Range [km]' |
|
1002 | self.ylabel = 'Range [km]' | |
| 1002 | self.xlabel = 'Intensity [dB]' |
|
1003 | self.xlabel = 'Intensity [dB]' | |
| 1003 | self.titles = ['Power Profile'] |
|
1004 | self.titles = ['Power Profile'] | |
| 1004 | self.colorbar = False |
|
1005 | self.colorbar = False | |
| 1005 |
|
1006 | |||
| 1006 | def update(self, dataOut): |
|
1007 | def update(self, dataOut): | |
| 1007 |
|
1008 | |||
| 1008 | data = {} |
|
1009 | data = {} | |
| 1009 | meta = {} |
|
1010 | meta = {} | |
| 1010 | data[self.CODE] = dataOut.getPower() |
|
1011 | data[self.CODE] = dataOut.getPower() | |
| 1011 |
|
1012 | |||
| 1012 | return data, meta |
|
1013 | return data, meta | |
| 1013 |
|
1014 | |||
| 1014 | def plot(self): |
|
1015 | def plot(self): | |
| 1015 |
|
1016 | |||
| 1016 | y = self.data.yrange |
|
1017 | y = self.data.yrange | |
| 1017 | self.y = y |
|
1018 | self.y = y | |
| 1018 |
|
1019 | |||
| 1019 | x = self.data[-1][self.CODE] |
|
1020 | x = self.data[-1][self.CODE] | |
| 1020 |
|
1021 | |||
| 1021 | if self.xmin is None: self.xmin = numpy.nanmin(x)*0.9 |
|
1022 | if self.xmin is None: self.xmin = numpy.nanmin(x)*0.9 | |
| 1022 | if self.xmax is None: self.xmax = numpy.nanmax(x)*1.1 |
|
1023 | if self.xmax is None: self.xmax = numpy.nanmax(x)*1.1 | |
| 1023 |
|
1024 | |||
| 1024 | if self.axes[0].firsttime: |
|
1025 | if self.axes[0].firsttime: | |
| 1025 | for ch in self.data.channels: |
|
1026 | for ch in self.data.channels: | |
| 1026 | self.axes[0].plot(x[ch], y, lw=1, label='Ch{}'.format(ch)) |
|
1027 | self.axes[0].plot(x[ch], y, lw=1, label='Ch{}'.format(ch)) | |
| 1027 | plt.legend() |
|
1028 | plt.legend() | |
| 1028 | else: |
|
1029 | else: | |
| 1029 | for ch in self.data.channels: |
|
1030 | for ch in self.data.channels: | |
| 1030 | self.axes[0].lines[ch].set_data(x[ch], y) |
|
1031 | self.axes[0].lines[ch].set_data(x[ch], y) | |
| 1031 |
|
1032 | |||
| 1032 |
|
1033 | |||
| 1033 | class SpectraCutPlot(Plot): |
|
1034 | class SpectraCutPlot(Plot): | |
| 1034 |
|
1035 | |||
| 1035 | CODE = 'spc_cut' |
|
1036 | CODE = 'spc_cut' | |
| 1036 | plot_type = 'scatter' |
|
1037 | plot_type = 'scatter' | |
| 1037 | buffering = False |
|
1038 | buffering = False | |
| 1038 |
|
1039 | |||
| 1039 | def setup(self): |
|
1040 | def setup(self): | |
| 1040 |
|
1041 | |||
| 1041 | self.nplots = len(self.data.channels) |
|
1042 | self.nplots = len(self.data.channels) | |
| 1042 | self.ncols = int(numpy.sqrt(self.nplots) + 0.9) |
|
1043 | self.ncols = int(numpy.sqrt(self.nplots) + 0.9) | |
| 1043 | self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9) |
|
1044 | self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9) | |
| 1044 | self.width = 3.4 * self.ncols + 1.5 |
|
1045 | self.width = 3.4 * self.ncols + 1.5 | |
| 1045 | self.height = 3 * self.nrows |
|
1046 | self.height = 3 * self.nrows | |
| 1046 | self.ylabel = 'Power [dB]' |
|
1047 | self.ylabel = 'Power [dB]' | |
| 1047 | self.colorbar = False |
|
1048 | self.colorbar = False | |
| 1048 | self.plots_adjust.update({'left':0.1, 'hspace':0.3, 'right': 0.75, 'bottom':0.08}) |
|
1049 | self.plots_adjust.update({'left':0.1, 'hspace':0.3, 'right': 0.75, 'bottom':0.08}) | |
| 1049 |
|
1050 | |||
| 1050 | def update(self, dataOut): |
|
1051 | def update(self, dataOut): | |
| 1051 |
|
1052 | |||
| 1052 | data = {} |
|
1053 | data = {} | |
| 1053 | meta = {} |
|
1054 | meta = {} | |
| 1054 | spc = 10*numpy.log10(dataOut.data_spc/dataOut.normFactor) |
|
1055 | spc = 10*numpy.log10(dataOut.data_spc/dataOut.normFactor) | |
| 1055 | data['spc'] = spc |
|
1056 | data['spc'] = spc | |
| 1056 | meta['xrange'] = (dataOut.getFreqRange(1)/1000., dataOut.getAcfRange(1), dataOut.getVelRange(1)) |
|
1057 | meta['xrange'] = (dataOut.getFreqRange(1)/1000., dataOut.getAcfRange(1), dataOut.getVelRange(1)) | |
| 1057 | if self.CODE == 'cut_gaussian_fit': |
|
1058 | if self.CODE == 'cut_gaussian_fit': | |
| 1058 | data['gauss_fit0'] = 10*numpy.log10(dataOut.GaussFit0/dataOut.normFactor) |
|
1059 | data['gauss_fit0'] = 10*numpy.log10(dataOut.GaussFit0/dataOut.normFactor) | |
| 1059 | data['gauss_fit1'] = 10*numpy.log10(dataOut.GaussFit1/dataOut.normFactor) |
|
1060 | data['gauss_fit1'] = 10*numpy.log10(dataOut.GaussFit1/dataOut.normFactor) | |
| 1060 | return data, meta |
|
1061 | return data, meta | |
| 1061 |
|
1062 | |||
| 1062 | def plot(self): |
|
1063 | def plot(self): | |
| 1063 | if self.xaxis == "frequency": |
|
1064 | if self.xaxis == "frequency": | |
| 1064 | x = self.data.xrange[0][1:] |
|
1065 | x = self.data.xrange[0][1:] | |
| 1065 | self.xlabel = "Frequency (kHz)" |
|
1066 | self.xlabel = "Frequency (kHz)" | |
| 1066 | elif self.xaxis == "time": |
|
1067 | elif self.xaxis == "time": | |
| 1067 | x = self.data.xrange[1] |
|
1068 | x = self.data.xrange[1] | |
| 1068 | self.xlabel = "Time (ms)" |
|
1069 | self.xlabel = "Time (ms)" | |
| 1069 | else: |
|
1070 | else: | |
| 1070 | x = self.data.xrange[2][:-1] |
|
1071 | x = self.data.xrange[2][:-1] | |
| 1071 | self.xlabel = "Velocity (m/s)" |
|
1072 | self.xlabel = "Velocity (m/s)" | |
| 1072 |
|
1073 | |||
| 1073 | if self.CODE == 'cut_gaussian_fit': |
|
1074 | if self.CODE == 'cut_gaussian_fit': | |
| 1074 | x = self.data.xrange[2][:-1] |
|
1075 | x = self.data.xrange[2][:-1] | |
| 1075 | self.xlabel = "Velocity (m/s)" |
|
1076 | self.xlabel = "Velocity (m/s)" | |
| 1076 |
|
1077 | |||
| 1077 | self.titles = [] |
|
1078 | self.titles = [] | |
| 1078 |
|
1079 | |||
| 1079 | y = self.data.yrange |
|
1080 | y = self.data.yrange | |
| 1080 | data = self.data[-1] |
|
1081 | data = self.data[-1] | |
| 1081 | z = data['spc'] |
|
1082 | z = data['spc'] | |
| 1082 |
|
1083 | |||
| 1083 | if self.height_index: |
|
1084 | if self.height_index: | |
| 1084 | index = numpy.array(self.height_index) |
|
1085 | index = numpy.array(self.height_index) | |
| 1085 | else: |
|
1086 | else: | |
| 1086 | index = numpy.arange(0, len(y), int((len(y))/9)) |
|
1087 | index = numpy.arange(0, len(y), int((len(y))/9)) | |
| 1087 |
|
1088 | |||
| 1088 | for n, ax in enumerate(self.axes): |
|
1089 | for n, ax in enumerate(self.axes): | |
| 1089 | if self.CODE == 'cut_gaussian_fit': |
|
1090 | if self.CODE == 'cut_gaussian_fit': | |
| 1090 | gau0 = data['gauss_fit0'] |
|
1091 | gau0 = data['gauss_fit0'] | |
| 1091 | gau1 = data['gauss_fit1'] |
|
1092 | gau1 = data['gauss_fit1'] | |
| 1092 | if ax.firsttime: |
|
1093 | if ax.firsttime: | |
| 1093 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) |
|
1094 | self.xmax = self.xmax if self.xmax else numpy.nanmax(x) | |
| 1094 | self.xmin = self.xmin if self.xmin else -self.xmax |
|
1095 | self.xmin = self.xmin if self.xmin else -self.xmax | |
| 1095 | self.ymin = self.ymin if self.ymin else numpy.nanmin(z[:,:,index]) |
|
1096 | self.ymin = self.ymin if self.ymin else numpy.nanmin(z[:,:,index]) | |
| 1096 | self.ymax = self.ymax if self.ymax else numpy.nanmax(z[:,:,index]) |
|
1097 | self.ymax = self.ymax if self.ymax else numpy.nanmax(z[:,:,index]) | |
| 1097 | #print(self.ymax) |
|
1098 | #print(self.ymax) | |
| 1098 | #print(z[n, :, index]) |
|
1099 | #print(z[n, :, index]) | |
| 1099 | ax.plt = ax.plot(x, z[n, :, index].T, lw=0.25) |
|
1100 | ax.plt = ax.plot(x, z[n, :, index].T, lw=0.25) | |
| 1100 | if self.CODE == 'cut_gaussian_fit': |
|
1101 | if self.CODE == 'cut_gaussian_fit': | |
| 1101 | ax.plt_gau0 = ax.plot(x, gau0[n, :, index].T, lw=1, linestyle='-.') |
|
1102 | ax.plt_gau0 = ax.plot(x, gau0[n, :, index].T, lw=1, linestyle='-.') | |
| 1102 | for i, line in enumerate(ax.plt_gau0): |
|
1103 | for i, line in enumerate(ax.plt_gau0): | |
| 1103 | line.set_color(ax.plt[i].get_color()) |
|
1104 | line.set_color(ax.plt[i].get_color()) | |
| 1104 | ax.plt_gau1 = ax.plot(x, gau1[n, :, index].T, lw=1, linestyle='--') |
|
1105 | ax.plt_gau1 = ax.plot(x, gau1[n, :, index].T, lw=1, linestyle='--') | |
| 1105 | for i, line in enumerate(ax.plt_gau1): |
|
1106 | for i, line in enumerate(ax.plt_gau1): | |
| 1106 | line.set_color(ax.plt[i].get_color()) |
|
1107 | line.set_color(ax.plt[i].get_color()) | |
| 1107 | labels = ['Range = {:2.1f}km'.format(y[i]) for i in index] |
|
1108 | labels = ['Range = {:2.1f}km'.format(y[i]) for i in index] | |
| 1108 | self.figures[0].legend(ax.plt, labels, loc='center right') |
|
1109 | self.figures[0].legend(ax.plt, labels, loc='center right') | |
| 1109 | else: |
|
1110 | else: | |
| 1110 | for i, line in enumerate(ax.plt): |
|
1111 | for i, line in enumerate(ax.plt): | |
| 1111 | line.set_data(x, z[n, :, index[i]].T) |
|
1112 | line.set_data(x, z[n, :, index[i]].T) | |
| 1112 | for i, line in enumerate(ax.plt_gau0): |
|
1113 | for i, line in enumerate(ax.plt_gau0): | |
| 1113 | line.set_data(x, gau0[n, :, index[i]].T) |
|
1114 | line.set_data(x, gau0[n, :, index[i]].T) | |
| 1114 | line.set_color(ax.plt[i].get_color()) |
|
1115 | line.set_color(ax.plt[i].get_color()) | |
| 1115 | for i, line in enumerate(ax.plt_gau1): |
|
1116 | for i, line in enumerate(ax.plt_gau1): | |
| 1116 | line.set_data(x, gau1[n, :, index[i]].T) |
|
1117 | line.set_data(x, gau1[n, :, index[i]].T) | |
| 1117 | line.set_color(ax.plt[i].get_color()) |
|
1118 | line.set_color(ax.plt[i].get_color()) | |
| 1118 | self.titles.append('CH {}'.format(n)) |
|
1119 | self.titles.append('CH {}'.format(n)) | |
| 1119 |
|
1120 | |||
| 1120 |
|
1121 | |||
| 1121 | class BeaconPhase(Plot): |
|
1122 | class BeaconPhase(Plot): | |
| 1122 |
|
1123 | |||
| 1123 | __isConfig = None |
|
1124 | __isConfig = None | |
| 1124 | __nsubplots = None |
|
1125 | __nsubplots = None | |
| 1125 |
|
1126 | |||
| 1126 | PREFIX = 'beacon_phase' |
|
1127 | PREFIX = 'beacon_phase' | |
| 1127 |
|
1128 | |||
| 1128 | def __init__(self): |
|
1129 | def __init__(self): | |
| 1129 | Plot.__init__(self) |
|
1130 | Plot.__init__(self) | |
| 1130 | self.timerange = 24*60*60 |
|
1131 | self.timerange = 24*60*60 | |
| 1131 | self.isConfig = False |
|
1132 | self.isConfig = False | |
| 1132 | self.__nsubplots = 1 |
|
1133 | self.__nsubplots = 1 | |
| 1133 | self.counter_imagwr = 0 |
|
1134 | self.counter_imagwr = 0 | |
| 1134 | self.WIDTH = 800 |
|
1135 | self.WIDTH = 800 | |
| 1135 | self.HEIGHT = 400 |
|
1136 | self.HEIGHT = 400 | |
| 1136 | self.WIDTHPROF = 120 |
|
1137 | self.WIDTHPROF = 120 | |
| 1137 | self.HEIGHTPROF = 0 |
|
1138 | self.HEIGHTPROF = 0 | |
| 1138 | self.xdata = None |
|
1139 | self.xdata = None | |
| 1139 | self.ydata = None |
|
1140 | self.ydata = None | |
| 1140 |
|
1141 | |||
| 1141 | self.PLOT_CODE = BEACON_CODE |
|
1142 | self.PLOT_CODE = BEACON_CODE | |
| 1142 |
|
1143 | |||
| 1143 | self.FTP_WEI = None |
|
1144 | self.FTP_WEI = None | |
| 1144 | self.EXP_CODE = None |
|
1145 | self.EXP_CODE = None | |
| 1145 | self.SUB_EXP_CODE = None |
|
1146 | self.SUB_EXP_CODE = None | |
| 1146 | self.PLOT_POS = None |
|
1147 | self.PLOT_POS = None | |
| 1147 |
|
1148 | |||
| 1148 | self.filename_phase = None |
|
1149 | self.filename_phase = None | |
| 1149 |
|
1150 | |||
| 1150 | self.figfile = None |
|
1151 | self.figfile = None | |
| 1151 |
|
1152 | |||
| 1152 | self.xmin = None |
|
1153 | self.xmin = None | |
| 1153 | self.xmax = None |
|
1154 | self.xmax = None | |
| 1154 |
|
1155 | |||
| 1155 | def getSubplots(self): |
|
1156 | def getSubplots(self): | |
| 1156 |
|
1157 | |||
| 1157 | ncol = 1 |
|
1158 | ncol = 1 | |
| 1158 | nrow = 1 |
|
1159 | nrow = 1 | |
| 1159 |
|
1160 | |||
| 1160 | return nrow, ncol |
|
1161 | return nrow, ncol | |
| 1161 |
|
1162 | |||
| 1162 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
1163 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): | |
| 1163 |
|
1164 | |||
| 1164 | self.__showprofile = showprofile |
|
1165 | self.__showprofile = showprofile | |
| 1165 | self.nplots = nplots |
|
1166 | self.nplots = nplots | |
| 1166 |
|
1167 | |||
| 1167 | ncolspan = 7 |
|
1168 | ncolspan = 7 | |
| 1168 | colspan = 6 |
|
1169 | colspan = 6 | |
| 1169 | self.__nsubplots = 2 |
|
1170 | self.__nsubplots = 2 | |
| 1170 |
|
1171 | |||
| 1171 | self.createFigure(id = id, |
|
1172 | self.createFigure(id = id, | |
| 1172 | wintitle = wintitle, |
|
1173 | wintitle = wintitle, | |
| 1173 | widthplot = self.WIDTH+self.WIDTHPROF, |
|
1174 | widthplot = self.WIDTH+self.WIDTHPROF, | |
| 1174 | heightplot = self.HEIGHT+self.HEIGHTPROF, |
|
1175 | heightplot = self.HEIGHT+self.HEIGHTPROF, | |
| 1175 | show=show) |
|
1176 | show=show) | |
| 1176 |
|
1177 | |||
| 1177 | nrow, ncol = self.getSubplots() |
|
1178 | nrow, ncol = self.getSubplots() | |
| 1178 |
|
1179 | |||
| 1179 | self.addAxes(nrow, ncol*ncolspan, 0, 0, colspan, 1) |
|
1180 | self.addAxes(nrow, ncol*ncolspan, 0, 0, colspan, 1) | |
| 1180 |
|
1181 | |||
| 1181 | def save_phase(self, filename_phase): |
|
1182 | def save_phase(self, filename_phase): | |
| 1182 | f = open(filename_phase,'w+') |
|
1183 | f = open(filename_phase,'w+') | |
| 1183 | f.write('\n\n') |
|
1184 | f.write('\n\n') | |
| 1184 | f.write('JICAMARCA RADIO OBSERVATORY - Beacon Phase \n') |
|
1185 | f.write('JICAMARCA RADIO OBSERVATORY - Beacon Phase \n') | |
| 1185 | f.write('DD MM YYYY HH MM SS pair(2,0) pair(2,1) pair(2,3) pair(2,4)\n\n' ) |
|
1186 | f.write('DD MM YYYY HH MM SS pair(2,0) pair(2,1) pair(2,3) pair(2,4)\n\n' ) | |
| 1186 | f.close() |
|
1187 | f.close() | |
| 1187 |
|
1188 | |||
| 1188 | def save_data(self, filename_phase, data, data_datetime): |
|
1189 | def save_data(self, filename_phase, data, data_datetime): | |
| 1189 | f=open(filename_phase,'a') |
|
1190 | f=open(filename_phase,'a') | |
| 1190 | timetuple_data = data_datetime.timetuple() |
|
1191 | timetuple_data = data_datetime.timetuple() | |
| 1191 | day = str(timetuple_data.tm_mday) |
|
1192 | day = str(timetuple_data.tm_mday) | |
| 1192 | month = str(timetuple_data.tm_mon) |
|
1193 | month = str(timetuple_data.tm_mon) | |
| 1193 | year = str(timetuple_data.tm_year) |
|
1194 | year = str(timetuple_data.tm_year) | |
| 1194 | hour = str(timetuple_data.tm_hour) |
|
1195 | hour = str(timetuple_data.tm_hour) | |
| 1195 | minute = str(timetuple_data.tm_min) |
|
1196 | minute = str(timetuple_data.tm_min) | |
| 1196 | second = str(timetuple_data.tm_sec) |
|
1197 | second = str(timetuple_data.tm_sec) | |
| 1197 | f.write(day+' '+month+' '+year+' '+hour+' '+minute+' '+second+' '+str(data[0])+' '+str(data[1])+' '+str(data[2])+' '+str(data[3])+'\n') |
|
1198 | f.write(day+' '+month+' '+year+' '+hour+' '+minute+' '+second+' '+str(data[0])+' '+str(data[1])+' '+str(data[2])+' '+str(data[3])+'\n') | |
| 1198 | f.close() |
|
1199 | f.close() | |
| 1199 |
|
1200 | |||
| 1200 | def plot(self): |
|
1201 | def plot(self): | |
| 1201 | log.warning('TODO: Not yet implemented...') |
|
1202 | log.warning('TODO: Not yet implemented...') | |
| 1202 |
|
1203 | |||
| 1203 | def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True', |
|
1204 | def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True', | |
| 1204 | xmin=None, xmax=None, ymin=None, ymax=None, hmin=None, hmax=None, |
|
1205 | xmin=None, xmax=None, ymin=None, ymax=None, hmin=None, hmax=None, | |
| 1205 | timerange=None, |
|
1206 | timerange=None, | |
| 1206 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, |
|
1207 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, | |
| 1207 | server=None, folder=None, username=None, password=None, |
|
1208 | server=None, folder=None, username=None, password=None, | |
| 1208 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): |
|
1209 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): | |
| 1209 |
|
1210 | |||
| 1210 | if dataOut.flagNoData: |
|
1211 | if dataOut.flagNoData: | |
| 1211 | return dataOut |
|
1212 | return dataOut | |
| 1212 |
|
1213 | |||
| 1213 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): |
|
1214 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): | |
| 1214 | return |
|
1215 | return | |
| 1215 |
|
1216 | |||
| 1216 | if pairsList == None: |
|
1217 | if pairsList == None: | |
| 1217 | pairsIndexList = dataOut.pairsIndexList[:10] |
|
1218 | pairsIndexList = dataOut.pairsIndexList[:10] | |
| 1218 | else: |
|
1219 | else: | |
| 1219 | pairsIndexList = [] |
|
1220 | pairsIndexList = [] | |
| 1220 | for pair in pairsList: |
|
1221 | for pair in pairsList: | |
| 1221 | if pair not in dataOut.pairsList: |
|
1222 | if pair not in dataOut.pairsList: | |
| 1222 | raise ValueError("Pair %s is not in dataOut.pairsList" %(pair)) |
|
1223 | raise ValueError("Pair %s is not in dataOut.pairsList" %(pair)) | |
| 1223 | pairsIndexList.append(dataOut.pairsList.index(pair)) |
|
1224 | pairsIndexList.append(dataOut.pairsList.index(pair)) | |
| 1224 |
|
1225 | |||
| 1225 | if pairsIndexList == []: |
|
1226 | if pairsIndexList == []: | |
| 1226 | return |
|
1227 | return | |
| 1227 |
|
1228 | |||
| 1228 | # if len(pairsIndexList) > 4: |
|
1229 | # if len(pairsIndexList) > 4: | |
| 1229 | # pairsIndexList = pairsIndexList[0:4] |
|
1230 | # pairsIndexList = pairsIndexList[0:4] | |
| 1230 |
|
1231 | |||
| 1231 | hmin_index = None |
|
1232 | hmin_index = None | |
| 1232 | hmax_index = None |
|
1233 | hmax_index = None | |
| 1233 |
|
1234 | |||
| 1234 | if hmin != None and hmax != None: |
|
1235 | if hmin != None and hmax != None: | |
| 1235 | indexes = numpy.arange(dataOut.nHeights) |
|
1236 | indexes = numpy.arange(dataOut.nHeights) | |
| 1236 | hmin_list = indexes[dataOut.heightList >= hmin] |
|
1237 | hmin_list = indexes[dataOut.heightList >= hmin] | |
| 1237 | hmax_list = indexes[dataOut.heightList <= hmax] |
|
1238 | hmax_list = indexes[dataOut.heightList <= hmax] | |
| 1238 |
|
1239 | |||
| 1239 | if hmin_list.any(): |
|
1240 | if hmin_list.any(): | |
| 1240 | hmin_index = hmin_list[0] |
|
1241 | hmin_index = hmin_list[0] | |
| 1241 |
|
1242 | |||
| 1242 | if hmax_list.any(): |
|
1243 | if hmax_list.any(): | |
| 1243 | hmax_index = hmax_list[-1]+1 |
|
1244 | hmax_index = hmax_list[-1]+1 | |
| 1244 |
|
1245 | |||
| 1245 | x = dataOut.getTimeRange() |
|
1246 | x = dataOut.getTimeRange() | |
| 1246 |
|
1247 | |||
| 1247 | thisDatetime = dataOut.datatime |
|
1248 | thisDatetime = dataOut.datatime | |
| 1248 |
|
1249 | |||
| 1249 | title = wintitle + " Signal Phase" # : %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
1250 | title = wintitle + " Signal Phase" # : %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
| 1250 | xlabel = "Local Time" |
|
1251 | xlabel = "Local Time" | |
| 1251 | ylabel = "Phase (degrees)" |
|
1252 | ylabel = "Phase (degrees)" | |
| 1252 |
|
1253 | |||
| 1253 | update_figfile = False |
|
1254 | update_figfile = False | |
| 1254 |
|
1255 | |||
| 1255 | nplots = len(pairsIndexList) |
|
1256 | nplots = len(pairsIndexList) | |
| 1256 | #phase = numpy.zeros((len(pairsIndexList),len(dataOut.beacon_heiIndexList))) |
|
1257 | #phase = numpy.zeros((len(pairsIndexList),len(dataOut.beacon_heiIndexList))) | |
| 1257 | phase_beacon = numpy.zeros(len(pairsIndexList)) |
|
1258 | phase_beacon = numpy.zeros(len(pairsIndexList)) | |
| 1258 | for i in range(nplots): |
|
1259 | for i in range(nplots): | |
| 1259 | pair = dataOut.pairsList[pairsIndexList[i]] |
|
1260 | pair = dataOut.pairsList[pairsIndexList[i]] | |
| 1260 | ccf = numpy.average(dataOut.data_cspc[pairsIndexList[i], :, hmin_index:hmax_index], axis=0) |
|
1261 | ccf = numpy.average(dataOut.data_cspc[pairsIndexList[i], :, hmin_index:hmax_index], axis=0) | |
| 1261 | powa = numpy.average(dataOut.data_spc[pair[0], :, hmin_index:hmax_index], axis=0) |
|
1262 | powa = numpy.average(dataOut.data_spc[pair[0], :, hmin_index:hmax_index], axis=0) | |
| 1262 | powb = numpy.average(dataOut.data_spc[pair[1], :, hmin_index:hmax_index], axis=0) |
|
1263 | powb = numpy.average(dataOut.data_spc[pair[1], :, hmin_index:hmax_index], axis=0) | |
| 1263 | avgcoherenceComplex = ccf/numpy.sqrt(powa*powb) |
|
1264 | avgcoherenceComplex = ccf/numpy.sqrt(powa*powb) | |
| 1264 | phase = numpy.arctan2(avgcoherenceComplex.imag, avgcoherenceComplex.real)*180/numpy.pi |
|
1265 | phase = numpy.arctan2(avgcoherenceComplex.imag, avgcoherenceComplex.real)*180/numpy.pi | |
| 1265 |
|
1266 | |||
| 1266 | if dataOut.beacon_heiIndexList: |
|
1267 | if dataOut.beacon_heiIndexList: | |
| 1267 | phase_beacon[i] = numpy.average(phase[dataOut.beacon_heiIndexList]) |
|
1268 | phase_beacon[i] = numpy.average(phase[dataOut.beacon_heiIndexList]) | |
| 1268 | else: |
|
1269 | else: | |
| 1269 | phase_beacon[i] = numpy.average(phase) |
|
1270 | phase_beacon[i] = numpy.average(phase) | |
| 1270 |
|
1271 | |||
| 1271 | if not self.isConfig: |
|
1272 | if not self.isConfig: | |
| 1272 |
|
1273 | |||
| 1273 | nplots = len(pairsIndexList) |
|
1274 | nplots = len(pairsIndexList) | |
| 1274 |
|
1275 | |||
| 1275 | self.setup(id=id, |
|
1276 | self.setup(id=id, | |
| 1276 | nplots=nplots, |
|
1277 | nplots=nplots, | |
| 1277 | wintitle=wintitle, |
|
1278 | wintitle=wintitle, | |
| 1278 | showprofile=showprofile, |
|
1279 | showprofile=showprofile, | |
| 1279 | show=show) |
|
1280 | show=show) | |
| 1280 |
|
1281 | |||
| 1281 | if timerange != None: |
|
1282 | if timerange != None: | |
| 1282 | self.timerange = timerange |
|
1283 | self.timerange = timerange | |
| 1283 |
|
1284 | |||
| 1284 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) |
|
1285 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) | |
| 1285 |
|
1286 | |||
| 1286 | if ymin == None: ymin = 0 |
|
1287 | if ymin == None: ymin = 0 | |
| 1287 | if ymax == None: ymax = 360 |
|
1288 | if ymax == None: ymax = 360 | |
| 1288 |
|
1289 | |||
| 1289 | self.FTP_WEI = ftp_wei |
|
1290 | self.FTP_WEI = ftp_wei | |
| 1290 | self.EXP_CODE = exp_code |
|
1291 | self.EXP_CODE = exp_code | |
| 1291 | self.SUB_EXP_CODE = sub_exp_code |
|
1292 | self.SUB_EXP_CODE = sub_exp_code | |
| 1292 | self.PLOT_POS = plot_pos |
|
1293 | self.PLOT_POS = plot_pos | |
| 1293 |
|
1294 | |||
| 1294 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
1295 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 1295 | self.isConfig = True |
|
1296 | self.isConfig = True | |
| 1296 | self.figfile = figfile |
|
1297 | self.figfile = figfile | |
| 1297 | self.xdata = numpy.array([]) |
|
1298 | self.xdata = numpy.array([]) | |
| 1298 | self.ydata = numpy.array([]) |
|
1299 | self.ydata = numpy.array([]) | |
| 1299 |
|
1300 | |||
| 1300 | update_figfile = True |
|
1301 | update_figfile = True | |
| 1301 |
|
1302 | |||
| 1302 | #open file beacon phase |
|
1303 | #open file beacon phase | |
| 1303 | path = '%s%03d' %(self.PREFIX, self.id) |
|
1304 | path = '%s%03d' %(self.PREFIX, self.id) | |
| 1304 | beacon_file = os.path.join(path,'%s.txt'%self.name) |
|
1305 | beacon_file = os.path.join(path,'%s.txt'%self.name) | |
| 1305 | self.filename_phase = os.path.join(figpath,beacon_file) |
|
1306 | self.filename_phase = os.path.join(figpath,beacon_file) | |
| 1306 | #self.save_phase(self.filename_phase) |
|
1307 | #self.save_phase(self.filename_phase) | |
| 1307 |
|
1308 | |||
| 1308 |
|
1309 | |||
| 1309 | #store data beacon phase |
|
1310 | #store data beacon phase | |
| 1310 | #self.save_data(self.filename_phase, phase_beacon, thisDatetime) |
|
1311 | #self.save_data(self.filename_phase, phase_beacon, thisDatetime) | |
| 1311 |
|
1312 | |||
| 1312 | self.setWinTitle(title) |
|
1313 | self.setWinTitle(title) | |
| 1313 |
|
1314 | |||
| 1314 |
|
1315 | |||
| 1315 | title = "Phase Plot %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) |
|
1316 | title = "Phase Plot %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) | |
| 1316 |
|
1317 | |||
| 1317 | legendlabels = ["Pair (%d,%d)"%(pair[0], pair[1]) for pair in dataOut.pairsList] |
|
1318 | legendlabels = ["Pair (%d,%d)"%(pair[0], pair[1]) for pair in dataOut.pairsList] | |
| 1318 |
|
1319 | |||
| 1319 | axes = self.axesList[0] |
|
1320 | axes = self.axesList[0] | |
| 1320 |
|
1321 | |||
| 1321 | self.xdata = numpy.hstack((self.xdata, x[0:1])) |
|
1322 | self.xdata = numpy.hstack((self.xdata, x[0:1])) | |
| 1322 |
|
1323 | |||
| 1323 | if len(self.ydata)==0: |
|
1324 | if len(self.ydata)==0: | |
| 1324 | self.ydata = phase_beacon.reshape(-1,1) |
|
1325 | self.ydata = phase_beacon.reshape(-1,1) | |
| 1325 | else: |
|
1326 | else: | |
| 1326 | self.ydata = numpy.hstack((self.ydata, phase_beacon.reshape(-1,1))) |
|
1327 | self.ydata = numpy.hstack((self.ydata, phase_beacon.reshape(-1,1))) | |
| 1327 |
|
1328 | |||
| 1328 |
|
1329 | |||
| 1329 | axes.pmultilineyaxis(x=self.xdata, y=self.ydata, |
|
1330 | axes.pmultilineyaxis(x=self.xdata, y=self.ydata, | |
| 1330 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, |
|
1331 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, | |
| 1331 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid", |
|
1332 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid", | |
| 1332 | XAxisAsTime=True, grid='both' |
|
1333 | XAxisAsTime=True, grid='both' | |
| 1333 | ) |
|
1334 | ) | |
| 1334 |
|
1335 | |||
| 1335 | self.draw() |
|
1336 | self.draw() | |
| 1336 |
|
1337 | |||
| 1337 | if dataOut.ltctime >= self.xmax: |
|
1338 | if dataOut.ltctime >= self.xmax: | |
| 1338 | self.counter_imagwr = wr_period |
|
1339 | self.counter_imagwr = wr_period | |
| 1339 | self.isConfig = False |
|
1340 | self.isConfig = False | |
| 1340 | update_figfile = True |
|
1341 | update_figfile = True | |
| 1341 |
|
1342 | |||
| 1342 | self.save(figpath=figpath, |
|
1343 | self.save(figpath=figpath, | |
| 1343 | figfile=figfile, |
|
1344 | figfile=figfile, | |
| 1344 | save=save, |
|
1345 | save=save, | |
| 1345 | ftp=ftp, |
|
1346 | ftp=ftp, | |
| 1346 | wr_period=wr_period, |
|
1347 | wr_period=wr_period, | |
| 1347 | thisDatetime=thisDatetime, |
|
1348 | thisDatetime=thisDatetime, | |
| 1348 | update_figfile=update_figfile) |
|
1349 | update_figfile=update_figfile) | |
| 1349 |
|
1350 | |||
| 1350 | return dataOut |
|
1351 | return dataOut | |
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