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