##// END OF EJS Templates
schain
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Add MP150KmRTIPlot and several AverageDriftsPlot classes for testing the 150kM plotting.
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r1768:008ae31786c1
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1 import os
1 import os
2 import datetime
2 import datetime
3 import numpy
3 import numpy
4
4
5 from schainpy.model.graphics.jroplot_base import Plot, plt
5 from schainpy.model.graphics.jroplot_base import Plot, plt
6 from schainpy.model.graphics.jroplot_spectra import SpectraPlot, RTIPlot, CoherencePlot, SpectraCutPlot
6 from schainpy.model.graphics.jroplot_spectra import SpectraPlot, RTIPlot, CoherencePlot, SpectraCutPlot
7 from schainpy.utils import log
7 from schainpy.utils import log
8
8
9 EARTH_RADIUS = 6.3710e3
9 EARTH_RADIUS = 6.3710e3
10
10
11
11
12 def ll2xy(lat1, lon1, lat2, lon2):
12 def ll2xy(lat1, lon1, lat2, lon2):
13
13
14 p = 0.017453292519943295
14 p = 0.017453292519943295
15 a = 0.5 - numpy.cos((lat2 - lat1) * p) / 2 + numpy.cos(lat1 * p) * \
15 a = 0.5 - numpy.cos((lat2 - lat1) * p) / 2 + numpy.cos(lat1 * p) * \
16 numpy.cos(lat2 * p) * (1 - numpy.cos((lon2 - lon1) * p)) / 2
16 numpy.cos(lat2 * p) * (1 - numpy.cos((lon2 - lon1) * p)) / 2
17 r = 12742 * numpy.arcsin(numpy.sqrt(a))
17 r = 12742 * numpy.arcsin(numpy.sqrt(a))
18 theta = numpy.arctan2(numpy.sin((lon2 - lon1) * p) * numpy.cos(lat2 * p), numpy.cos(lat1 * p)
18 theta = numpy.arctan2(numpy.sin((lon2 - lon1) * p) * numpy.cos(lat2 * p), numpy.cos(lat1 * p)
19 * numpy.sin(lat2 * p) - numpy.sin(lat1 * p) * numpy.cos(lat2 * p) * numpy.cos((lon2 - lon1) * p))
19 * numpy.sin(lat2 * p) - numpy.sin(lat1 * p) * numpy.cos(lat2 * p) * numpy.cos((lon2 - lon1) * p))
20 theta = -theta + numpy.pi / 2
20 theta = -theta + numpy.pi / 2
21 return r * numpy.cos(theta), r * numpy.sin(theta)
21 return r * numpy.cos(theta), r * numpy.sin(theta)
22
22
23
23
24 def km2deg(km):
24 def km2deg(km):
25 '''
25 '''
26 Convert distance in km to degrees
26 Convert distance in km to degrees
27 '''
27 '''
28
28
29 return numpy.rad2deg(km / EARTH_RADIUS)
29 return numpy.rad2deg(km / EARTH_RADIUS)
30
30
31
31
32
32
33 class SpectralMomentsPlot(SpectraPlot):
33 class SpectralMomentsPlot(SpectraPlot):
34 '''
34 '''
35 Plot for Spectral Moments
35 Plot for Spectral Moments
36 '''
36 '''
37 CODE = 'spc_moments'
37 CODE = 'spc_moments'
38 # colormap = 'jet'
38 # colormap = 'jet'
39 # plot_type = 'pcolor'
39 # plot_type = 'pcolor'
40
40
41 class DobleGaussianPlot(SpectraPlot):
41 class DobleGaussianPlot(SpectraPlot):
42 '''
42 '''
43 Plot for Double Gaussian Plot
43 Plot for Double Gaussian Plot
44 '''
44 '''
45 CODE = 'gaussian_fit'
45 CODE = 'gaussian_fit'
46 # colormap = 'jet'
46 # colormap = 'jet'
47 # plot_type = 'pcolor'
47 # plot_type = 'pcolor'
48
48
49
49
50 class DoubleGaussianSpectraCutPlot(SpectraCutPlot):
50 class DoubleGaussianSpectraCutPlot(SpectraCutPlot):
51 '''
51 '''
52 Plot SpectraCut with Double Gaussian Fit
52 Plot SpectraCut with Double Gaussian Fit
53 '''
53 '''
54 CODE = 'cut_gaussian_fit'
54 CODE = 'cut_gaussian_fit'
55
55
56
56
57 class SpectralFitObliquePlot(SpectraPlot):
57 class SpectralFitObliquePlot(SpectraPlot):
58 '''
58 '''
59 Plot for Spectral Oblique
59 Plot for Spectral Oblique
60 '''
60 '''
61 CODE = 'spc_moments'
61 CODE = 'spc_moments'
62 colormap = 'jet'
62 colormap = 'jet'
63 plot_type = 'pcolor'
63 plot_type = 'pcolor'
64
64
65
65
66
66
67 class SnrPlot(RTIPlot):
67 class SnrPlot(RTIPlot):
68 '''
68 '''
69 Plot for SNR Data
69 Plot for SNR Data
70 '''
70 '''
71
71
72 CODE = 'snr'
72 CODE = 'snr'
73 colormap = 'jet'
73 colormap = 'jet'
74
74
75 def update(self, dataOut):
75 def update(self, dataOut):
76
76
77 data = {
77 data = {
78 'snr': 10 * numpy.log10(dataOut.data_snr)
78 'snr': 10 * numpy.log10(dataOut.data_snr)
79 }
79 }
80
80
81 return data, {}
81 return data, {}
82
82
83 class DopplerPlot(RTIPlot):
83 class DopplerPlot(RTIPlot):
84 '''
84 '''
85 Plot for DOPPLER Data (1st moment)
85 Plot for DOPPLER Data (1st moment)
86 '''
86 '''
87
87
88 CODE = 'dop'
88 CODE = 'dop'
89 colormap = 'RdBu_r'
89 colormap = 'RdBu_r'
90
90
91 def update(self, dataOut):
91 def update(self, dataOut):
92
92
93 data = {
93 data = {
94 'dop': dataOut.data_dop
94 'dop': dataOut.data_dop
95 }
95 }
96
96
97 return data, {}
97 return data, {}
98
98
99 class PowerPlot(RTIPlot):
99 class PowerPlot(RTIPlot):
100 '''
100 '''
101 Plot for Power Data (0 moment)
101 Plot for Power Data (0 moment)
102 '''
102 '''
103
103
104 CODE = 'pow'
104 CODE = 'pow'
105 colormap = 'jet'
105 colormap = 'jet'
106
106
107 def update(self, dataOut):
107 def update(self, dataOut):
108
108
109 data = {
109 data = {
110 'pow': 10 * numpy.log10(dataOut.data_pow / dataOut.normFactor)
110 'pow': 10 * numpy.log10(dataOut.data_pow / dataOut.normFactor)
111 }
111 }
112
112
113 return data, {}
113 return data, {}
114
114
115 class SpectralWidthPlot(RTIPlot):
115 class SpectralWidthPlot(RTIPlot):
116 '''
116 '''
117 Plot for Spectral Width Data (2nd moment)
117 Plot for Spectral Width Data (2nd moment)
118 '''
118 '''
119
119
120 CODE = 'width'
120 CODE = 'width'
121 colormap = 'jet'
121 colormap = 'jet'
122
122
123 def update(self, dataOut):
123 def update(self, dataOut):
124
124
125 data = {
125 data = {
126 'width': dataOut.data_width
126 'width': dataOut.data_width
127 }
127 }
128
128
129 return data, {}
129 return data, {}
130
130
131 class SkyMapPlot(Plot):
131 class SkyMapPlot(Plot):
132 '''
132 '''
133 Plot for meteors detection data
133 Plot for meteors detection data
134 '''
134 '''
135
135
136 CODE = 'param'
136 CODE = 'param'
137
137
138 def setup(self):
138 def setup(self):
139
139
140 self.ncols = 1
140 self.ncols = 1
141 self.nrows = 1
141 self.nrows = 1
142 self.width = 7.2
142 self.width = 7.2
143 self.height = 7.2
143 self.height = 7.2
144 self.nplots = 1
144 self.nplots = 1
145 self.xlabel = 'Zonal Zenith Angle (deg)'
145 self.xlabel = 'Zonal Zenith Angle (deg)'
146 self.ylabel = 'Meridional Zenith Angle (deg)'
146 self.ylabel = 'Meridional Zenith Angle (deg)'
147 self.polar = True
147 self.polar = True
148 self.ymin = -180
148 self.ymin = -180
149 self.ymax = 180
149 self.ymax = 180
150 self.colorbar = False
150 self.colorbar = False
151
151
152 def plot(self):
152 def plot(self):
153
153
154 arrayParameters = numpy.concatenate(self.data['param'])
154 arrayParameters = numpy.concatenate(self.data['param'])
155 error = arrayParameters[:, -1]
155 error = arrayParameters[:, -1]
156 indValid = numpy.where(error == 0)[0]
156 indValid = numpy.where(error == 0)[0]
157 finalMeteor = arrayParameters[indValid, :]
157 finalMeteor = arrayParameters[indValid, :]
158 finalAzimuth = finalMeteor[:, 3]
158 finalAzimuth = finalMeteor[:, 3]
159 finalZenith = finalMeteor[:, 4]
159 finalZenith = finalMeteor[:, 4]
160
160
161 x = finalAzimuth * numpy.pi / 180
161 x = finalAzimuth * numpy.pi / 180
162 y = finalZenith
162 y = finalZenith
163
163
164 ax = self.axes[0]
164 ax = self.axes[0]
165
165
166 if ax.firsttime:
166 if ax.firsttime:
167 ax.plot = ax.plot(x, y, 'bo', markersize=5)[0]
167 ax.plot = ax.plot(x, y, 'bo', markersize=5)[0]
168 else:
168 else:
169 ax.plot.set_data(x, y)
169 ax.plot.set_data(x, y)
170
170
171 dt1 = self.getDateTime(self.data.min_time).strftime('%y/%m/%d %H:%M:%S')
171 dt1 = self.getDateTime(self.data.min_time).strftime('%y/%m/%d %H:%M:%S')
172 dt2 = self.getDateTime(self.data.max_time).strftime('%y/%m/%d %H:%M:%S')
172 dt2 = self.getDateTime(self.data.max_time).strftime('%y/%m/%d %H:%M:%S')
173 title = 'Meteor Detection Sky Map\n %s - %s \n Number of events: %5.0f\n' % (dt1,
173 title = 'Meteor Detection Sky Map\n %s - %s \n Number of events: %5.0f\n' % (dt1,
174 dt2,
174 dt2,
175 len(x))
175 len(x))
176 self.titles[0] = title
176 self.titles[0] = title
177
177
178
178
179 class GenericRTIPlot(Plot):
179 class GenericRTIPlot(Plot):
180 '''
180 '''
181 Plot for data_xxxx object
181 Plot for data_xxxx object
182 '''
182 '''
183
183
184 CODE = 'param'
184 CODE = 'param'
185 colormap = 'viridis'
185 colormap = 'viridis'
186 plot_type = 'pcolorbuffer'
186 plot_type = 'pcolorbuffer'
187
187
188 def setup(self):
188 def setup(self):
189 self.xaxis = 'time'
189 self.xaxis = 'time'
190 self.ncols = 1
190 self.ncols = 1
191 self.nrows = self.data.shape('param')[0]
191 self.nrows = self.data.shape('param')[0]
192 self.nplots = self.nrows
192 self.nplots = self.nrows
193 self.plots_adjust.update({'hspace':0.8, 'left': 0.1, 'bottom': 0.08, 'right':0.95, 'top': 0.95})
193 self.plots_adjust.update({'hspace':0.8, 'left': 0.1, 'bottom': 0.08, 'right':0.95, 'top': 0.95})
194
194
195 if not self.xlabel:
195 if not self.xlabel:
196 self.xlabel = 'Time'
196 self.xlabel = 'Time'
197
197
198 self.ylabel = 'Range [km]'
198 self.ylabel = 'Range [km]'
199 if not self.titles:
199 if not self.titles:
200 self.titles = ['Param {}'.format(x) for x in range(self.nrows)]
200 self.titles = ['Param {}'.format(x) for x in range(self.nrows)]
201
201
202 def update(self, dataOut):
202 def update(self, dataOut):
203
203
204 data = {
204 data = {
205 'param' : numpy.concatenate([getattr(dataOut, attr) for attr in self.attr_data], axis=0)
205 'param' : numpy.concatenate([getattr(dataOut, attr) for attr in self.attr_data], axis=0)
206 }
206 }
207
207
208 meta = {}
208 meta = {}
209
209
210 return data, meta
210 return data, meta
211
211
212 def plot(self):
212 def plot(self):
213 # self.data.normalize_heights()
213 # self.data.normalize_heights()
214 self.x = self.data.times
214 self.x = self.data.times
215 self.y = self.data.yrange
215 self.y = self.data.yrange
216 self.z = self.data['param']
216 self.z = self.data['param']
217
217
218 self.z = numpy.ma.masked_invalid(self.z)
218 self.z = numpy.ma.masked_invalid(self.z)
219
219
220 if self.decimation is None:
220 if self.decimation is None:
221 x, y, z = self.fill_gaps(self.x, self.y, self.z)
221 x, y, z = self.fill_gaps(self.x, self.y, self.z)
222 else:
222 else:
223 x, y, z = self.fill_gaps(*self.decimate())
223 x, y, z = self.fill_gaps(*self.decimate())
224
224
225 for n, ax in enumerate(self.axes):
225 for n, ax in enumerate(self.axes):
226
226
227 self.zmax = self.zmax if self.zmax is not None else numpy.max(
227 self.zmax = self.zmax if self.zmax is not None else numpy.max(
228 self.z[n])
228 self.z[n])
229 self.zmin = self.zmin if self.zmin is not None else numpy.min(
229 self.zmin = self.zmin if self.zmin is not None else numpy.min(
230 self.z[n])
230 self.z[n])
231
231
232 if ax.firsttime:
232 if ax.firsttime:
233 if self.zlimits is not None:
233 if self.zlimits is not None:
234 self.zmin, self.zmax = self.zlimits[n]
234 self.zmin, self.zmax = self.zlimits[n]
235
235
236 ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n],
236 ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n],
237 vmin=self.zmin,
237 vmin=self.zmin,
238 vmax=self.zmax,
238 vmax=self.zmax,
239 cmap=self.cmaps[n]
239 cmap=self.cmaps[n]
240 )
240 )
241 else:
241 else:
242 if self.zlimits is not None:
242 if self.zlimits is not None:
243 self.zmin, self.zmax = self.zlimits[n]
243 self.zmin, self.zmax = self.zlimits[n]
244 ax.plt.remove()
244 ax.plt.remove()
245 ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n],
245 ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n],
246 vmin=self.zmin,
246 vmin=self.zmin,
247 vmax=self.zmax,
247 vmax=self.zmax,
248 cmap=self.cmaps[n]
248 cmap=self.cmaps[n]
249 )
249 )
250
250
251
251
252 class PolarMapPlot(Plot):
252 class PolarMapPlot(Plot):
253 '''
253 '''
254 Plot for weather radar
254 Plot for weather radar
255 '''
255 '''
256
256
257 CODE = 'param'
257 CODE = 'param'
258 colormap = 'seismic'
258 colormap = 'seismic'
259
259
260 def setup(self):
260 def setup(self):
261 self.ncols = 1
261 self.ncols = 1
262 self.nrows = 1
262 self.nrows = 1
263 self.width = 9
263 self.width = 9
264 self.height = 8
264 self.height = 8
265 self.mode = self.data.meta['mode']
265 self.mode = self.data.meta['mode']
266 if self.channels is not None:
266 if self.channels is not None:
267 self.nplots = len(self.channels)
267 self.nplots = len(self.channels)
268 self.nrows = len(self.channels)
268 self.nrows = len(self.channels)
269 else:
269 else:
270 self.nplots = self.data.shape(self.CODE)[0]
270 self.nplots = self.data.shape(self.CODE)[0]
271 self.nrows = self.nplots
271 self.nrows = self.nplots
272 self.channels = list(range(self.nplots))
272 self.channels = list(range(self.nplots))
273 if self.mode == 'E':
273 if self.mode == 'E':
274 self.xlabel = 'Longitude'
274 self.xlabel = 'Longitude'
275 self.ylabel = 'Latitude'
275 self.ylabel = 'Latitude'
276 else:
276 else:
277 self.xlabel = 'Range (km)'
277 self.xlabel = 'Range (km)'
278 self.ylabel = 'Height (km)'
278 self.ylabel = 'Height (km)'
279 self.bgcolor = 'white'
279 self.bgcolor = 'white'
280 self.cb_labels = self.data.meta['units']
280 self.cb_labels = self.data.meta['units']
281 self.lat = self.data.meta['latitude']
281 self.lat = self.data.meta['latitude']
282 self.lon = self.data.meta['longitude']
282 self.lon = self.data.meta['longitude']
283 self.xmin, self.xmax = float(
283 self.xmin, self.xmax = float(
284 km2deg(self.xmin) + self.lon), float(km2deg(self.xmax) + self.lon)
284 km2deg(self.xmin) + self.lon), float(km2deg(self.xmax) + self.lon)
285 self.ymin, self.ymax = float(
285 self.ymin, self.ymax = float(
286 km2deg(self.ymin) + self.lat), float(km2deg(self.ymax) + self.lat)
286 km2deg(self.ymin) + self.lat), float(km2deg(self.ymax) + self.lat)
287 # self.polar = True
287 # self.polar = True
288
288
289 def plot(self):
289 def plot(self):
290
290
291 for n, ax in enumerate(self.axes):
291 for n, ax in enumerate(self.axes):
292 data = self.data['param'][self.channels[n]]
292 data = self.data['param'][self.channels[n]]
293
293
294 zeniths = numpy.linspace(
294 zeniths = numpy.linspace(
295 0, self.data.meta['max_range'], data.shape[1])
295 0, self.data.meta['max_range'], data.shape[1])
296 if self.mode == 'E':
296 if self.mode == 'E':
297 azimuths = -numpy.radians(self.data.yrange) + numpy.pi / 2
297 azimuths = -numpy.radians(self.data.yrange) + numpy.pi / 2
298 r, theta = numpy.meshgrid(zeniths, azimuths)
298 r, theta = numpy.meshgrid(zeniths, azimuths)
299 x, y = r * numpy.cos(theta) * numpy.cos(numpy.radians(self.data.meta['elevation'])), r * numpy.sin(
299 x, y = r * numpy.cos(theta) * numpy.cos(numpy.radians(self.data.meta['elevation'])), r * numpy.sin(
300 theta) * numpy.cos(numpy.radians(self.data.meta['elevation']))
300 theta) * numpy.cos(numpy.radians(self.data.meta['elevation']))
301 x = km2deg(x) + self.lon
301 x = km2deg(x) + self.lon
302 y = km2deg(y) + self.lat
302 y = km2deg(y) + self.lat
303 else:
303 else:
304 azimuths = numpy.radians(self.data.yrange)
304 azimuths = numpy.radians(self.data.yrange)
305 r, theta = numpy.meshgrid(zeniths, azimuths)
305 r, theta = numpy.meshgrid(zeniths, azimuths)
306 x, y = r * numpy.cos(theta), r * numpy.sin(theta)
306 x, y = r * numpy.cos(theta), r * numpy.sin(theta)
307 self.y = zeniths
307 self.y = zeniths
308
308
309 if ax.firsttime:
309 if ax.firsttime:
310 if self.zlimits is not None:
310 if self.zlimits is not None:
311 self.zmin, self.zmax = self.zlimits[n]
311 self.zmin, self.zmax = self.zlimits[n]
312 ax.plt = ax.pcolormesh(# r, theta, numpy.ma.array(data, mask=numpy.isnan(data)),
312 ax.plt = ax.pcolormesh(# r, theta, numpy.ma.array(data, mask=numpy.isnan(data)),
313 x, y, numpy.ma.array(data, mask=numpy.isnan(data)),
313 x, y, numpy.ma.array(data, mask=numpy.isnan(data)),
314 vmin=self.zmin,
314 vmin=self.zmin,
315 vmax=self.zmax,
315 vmax=self.zmax,
316 cmap=self.cmaps[n])
316 cmap=self.cmaps[n])
317 else:
317 else:
318 if self.zlimits is not None:
318 if self.zlimits is not None:
319 self.zmin, self.zmax = self.zlimits[n]
319 self.zmin, self.zmax = self.zlimits[n]
320 ax.plt.remove()
320 ax.plt.remove()
321 ax.plt = ax.pcolormesh(# r, theta, numpy.ma.array(data, mask=numpy.isnan(data)),
321 ax.plt = ax.pcolormesh(# r, theta, numpy.ma.array(data, mask=numpy.isnan(data)),
322 x, y, numpy.ma.array(data, mask=numpy.isnan(data)),
322 x, y, numpy.ma.array(data, mask=numpy.isnan(data)),
323 vmin=self.zmin,
323 vmin=self.zmin,
324 vmax=self.zmax,
324 vmax=self.zmax,
325 cmap=self.cmaps[n])
325 cmap=self.cmaps[n])
326
326
327 if self.mode == 'A':
327 if self.mode == 'A':
328 continue
328 continue
329
329
330 # plot district names
330 # plot district names
331 f = open('/data/workspace/schain_scripts/distrito.csv')
331 f = open('/data/workspace/schain_scripts/distrito.csv')
332 for line in f:
332 for line in f:
333 label, lon, lat = [s.strip() for s in line.split(',') if s]
333 label, lon, lat = [s.strip() for s in line.split(',') if s]
334 lat = float(lat)
334 lat = float(lat)
335 lon = float(lon)
335 lon = float(lon)
336 # ax.plot(lon, lat, '.b', ms=2)
336 # ax.plot(lon, lat, '.b', ms=2)
337 ax.text(lon, lat, label.decode('utf8'), ha='center',
337 ax.text(lon, lat, label.decode('utf8'), ha='center',
338 va='bottom', size='8', color='black')
338 va='bottom', size='8', color='black')
339
339
340 # plot limites
340 # plot limites
341 limites = []
341 limites = []
342 tmp = []
342 tmp = []
343 for line in open('/data/workspace/schain_scripts/lima.csv'):
343 for line in open('/data/workspace/schain_scripts/lima.csv'):
344 if '#' in line:
344 if '#' in line:
345 if tmp:
345 if tmp:
346 limites.append(tmp)
346 limites.append(tmp)
347 tmp = []
347 tmp = []
348 continue
348 continue
349 values = line.strip().split(',')
349 values = line.strip().split(',')
350 tmp.append((float(values[0]), float(values[1])))
350 tmp.append((float(values[0]), float(values[1])))
351 for points in limites:
351 for points in limites:
352 ax.add_patch(
352 ax.add_patch(
353 Polygon(points, ec='k', fc='none', ls='--', lw=0.5))
353 Polygon(points, ec='k', fc='none', ls='--', lw=0.5))
354
354
355 # plot Cuencas
355 # plot Cuencas
356 for cuenca in ('rimac', 'lurin', 'mala', 'chillon', 'chilca', 'chancay-huaral'):
356 for cuenca in ('rimac', 'lurin', 'mala', 'chillon', 'chilca', 'chancay-huaral'):
357 f = open('/data/workspace/schain_scripts/{}.csv'.format(cuenca))
357 f = open('/data/workspace/schain_scripts/{}.csv'.format(cuenca))
358 values = [line.strip().split(',') for line in f]
358 values = [line.strip().split(',') for line in f]
359 points = [(float(s[0]), float(s[1])) for s in values]
359 points = [(float(s[0]), float(s[1])) for s in values]
360 ax.add_patch(Polygon(points, ec='b', fc='none'))
360 ax.add_patch(Polygon(points, ec='b', fc='none'))
361
361
362 # plot grid
362 # plot grid
363 for r in (15, 30, 45, 60):
363 for r in (15, 30, 45, 60):
364 ax.add_artist(plt.Circle((self.lon, self.lat),
364 ax.add_artist(plt.Circle((self.lon, self.lat),
365 km2deg(r), color='0.6', fill=False, lw=0.2))
365 km2deg(r), color='0.6', fill=False, lw=0.2))
366 ax.text(
366 ax.text(
367 self.lon + (km2deg(r)) * numpy.cos(60 * numpy.pi / 180),
367 self.lon + (km2deg(r)) * numpy.cos(60 * numpy.pi / 180),
368 self.lat + (km2deg(r)) * numpy.sin(60 * numpy.pi / 180),
368 self.lat + (km2deg(r)) * numpy.sin(60 * numpy.pi / 180),
369 '{}km'.format(r),
369 '{}km'.format(r),
370 ha='center', va='bottom', size='8', color='0.6', weight='heavy')
370 ha='center', va='bottom', size='8', color='0.6', weight='heavy')
371
371
372 if self.mode == 'E':
372 if self.mode == 'E':
373 title = 'El={}$^\circ$'.format(self.data.meta['elevation'])
373 title = 'El={}$^\circ$'.format(self.data.meta['elevation'])
374 label = 'E{:02d}'.format(int(self.data.meta['elevation']))
374 label = 'E{:02d}'.format(int(self.data.meta['elevation']))
375 else:
375 else:
376 title = 'Az={}$^\circ$'.format(self.data.meta['azimuth'])
376 title = 'Az={}$^\circ$'.format(self.data.meta['azimuth'])
377 label = 'A{:02d}'.format(int(self.data.meta['azimuth']))
377 label = 'A{:02d}'.format(int(self.data.meta['azimuth']))
378
378
379 self.save_labels = ['{}-{}'.format(lbl, label) for lbl in self.labels]
379 self.save_labels = ['{}-{}'.format(lbl, label) for lbl in self.labels]
380 self.titles = ['{} {}'.format(
380 self.titles = ['{} {}'.format(
381 self.data.parameters[x], title) for x in self.channels]
381 self.data.parameters[x], title) for x in self.channels]
382
383 class MP150KmRTIPlot(Plot):
384 '''
385 Plot for data_xxxx object
386 '''
387
388 CODE = 'param'
389 colormap = 'viridis'
390 plot_type = 'pcolorbuffer'
391
392 def setup(self):
393 self.xaxis = 'time'
394 self.ncols = 1
395 self.nrows = self.data.shape('param')[0]
396 self.nplots = self.nrows
397 self.plots_adjust.update({'hspace':0.8, 'left': 0.1, 'bottom': 0.08, 'right':0.95, 'top': 0.95})
398
399 if not self.xlabel:
400 self.xlabel = 'Time'
401
402 self.ylabel = 'Range [km]'
403 if not self.titles:
404 self.titles = ['Param {}'.format(x) for x in range(self.nrows)]
405
406 def update(self, dataOut):
407 data = {
408 #'param' : numpy.concatenate([getattr(dataOut, attr) for attr in self.attr_data], axis=0)[0:3,:] # SNL, VERTICAL, ZONAL
409 'param' : dataOut.data_output[0:3,:] # SNL, VERTICAL, ZONAL
410 }
411
412 meta = {}
413
414 return data, meta
415
416 def plot(self):
417 # self.data.normalize_heights()
418 self.x = self.data.times
419 self.y = self.data.yrange
420 self.z = self.data['param']
421
422
423 self.z = numpy.ma.masked_invalid(self.z)
424
425 if self.decimation is None:
426 x, y, z = self.fill_gaps(self.x, self.y, self.z)
427 else:
428 x, y, z = self.fill_gaps(*self.decimate())
429
430 for n, ax in enumerate(self.axes):
431 self.zmax = self.zmax if self.zmax is not None else numpy.max(
432 self.z[n])
433 self.zmin = self.zmin if self.zmin is not None else numpy.min(
434 self.z[n])
435
436 if ax.firsttime:
437 if self.zlimits is not None:
438 self.zmin, self.zmax = self.zlimits[n]
439
440 ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n],
441 vmin=self.zmin,
442 vmax=self.zmax,
443 cmap=self.cmaps[n]
444 )
445 else:
446 if self.zlimits is not None:
447 self.zmin, self.zmax = self.zlimits[n]
448 ax.plt.remove()
449 ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n],
450 vmin=self.zmin,
451 vmax=self.zmax,
452 cmap=self.cmaps[n]
453 )
454
455 class AverageDriftsPlot_v2(Plot):
456 '''
457 Plot for average 150 Km echoes
458 '''
459
460 CODE = 'average'
461 plot_type = 'scatterbuffer'
462
463 def setup(self):
464 self.xaxis = 'time'
465 self.ncols = 1
466
467 self.nplots = 2
468 self.nrows = 2
469
470 self.ylabel = 'Velocity\nm/s'
471 self.xlabel = 'Local time'
472 #self.titles = ['VERTICAL VELOCITY: AVERAGE AND ERRORS', 'ZONAL VELOCITY: AVERAGE AND ERRORS']
473 self.titles = ['VERTICAL VELOCITY: AVERAGE', 'ZONAL VELOCITY: AVERAGE']
474
475 self.colorbar = False
476 self.plots_adjust.update({'hspace':0.5, 'left': 0.1, 'bottom': 0.1, 'right':0.95, 'top': 0.95 })
477
478
479 def update(self, dataOut):
480
481 data = {}
482 meta = {}
483
484 #data['average']= numpy.nanmean(dataOut.data_output[1:3,:], axis=1) # VERTICAL, ZONAL
485 data['average']= numpy.nanmean(dataOut.data_output[1:3,:], axis=1) # VERTICAL, ZONAL
486 data['error']= numpy.nanmean(dataOut.data_output[3:,:], axis=1) # ERROR VERTICAL, ERROR ZONAL
487 meta['yrange'] = numpy.array([])
488
489 return data, meta
490
491 def plot(self):
492
493 self.x = self.data.times
494 #self.xmin = self.data.min_time
495 #self.xmax = self.xmin + self.xrange * 60 * 60
496 self.y = self.data['average']
497 print('self.y:', self.y.shape)
498 self.y_error = self.data['error']
499 print('self.y_error:', self.y_error.shape)
500
501 for n, ax in enumerate(self.axes):
502 if ax.firsttime:
503 self.ymin = self.ymin if self.ymin is not None else -50
504 self.ymax = self.ymax if self.ymax is not None else 50
505 self.axes[n].plot(self.x, self.y[n], c='r', ls=':', lw=1)
506 else:
507 self.axes[n].lines[0].set_data(self.x, self.y[n])
508 '''
509 for n, ax in enumerate(self.axes):
510
511 if ax.firsttime:
512 self.ymin = self.ymin if self.ymin is not None else -50
513 self.ymax = self.ymax if self.ymax is not None else 50
514 ax.scatter(self.x, self.y[n], c='g', s=0.8)
515 #ax.errorbar(self.x, self.y[n], yerr = self.y_error[n,:], ecolor='r', elinewidth=0.2, fmt='|')
516 else:
517 ax.scatter(self.x, self.y[n], c='g', s=0.8)
518 #ax.errorbar(self.x, self.y[n], yerr = self.y_error[n,:], ecolor='r', elinewidth=0.2, fmt='|')
519 '''
520 class AverageDriftsPlot_bck(Plot):
521 '''
522 Plot for average 150 Km echoes
523 '''
524 CODE = 'average'
525 plot_type = 'scatterbuffer'
526
527 def setup(self):
528 self.xaxis = 'time'
529 self.ncols = 1
530 self.nplots = 2
531 self.nrows = 2
532 self.ylabel = 'Velocity\nm/s'
533 self.xlabel = 'Time'
534 self.titles = ['VERTICAL VELOCITY: AVERAGE', 'ZONAL VELOCITY: AVERAGE']
535 self.colorbar = False
536 self.plots_adjust.update({'hspace':0.5, 'left': 0.1, 'bottom': 0.1, 'right':0.95, 'top': 0.95 })
537
538
539
540 def update(self, dataOut):
541
542 data = {}
543 meta = {}
544 data['average']= numpy.nanmean(dataOut.data_output[1:3,:], axis=1) # VERTICAL, ZONAL
545 meta['yrange'] = numpy.array([])
546
547 return data, meta
548
549 def plot(self):
550
551 self.x = self.data.times
552 self.y = self.data['average']
553
554 for n, ax in enumerate(self.axes):
555 if ax.firsttime:
556
557 if self.zlimits is not None:
558 self.axes[n].set_ylim(self.zlimits[n])
559 self.axes[n].plot(self.x, self.y[n], c='r', ls='-', lw=1)
560 else:
561
562 if self.zlimits is not None:
563 ax.set_ylim((self.zlimits[n]))
564 self.axes[n].lines[0].set_data(self.x, self.y[n])
565
566 class AverageDriftsPlot(Plot):
567 '''
568 Plot for average 150 Km echoes
569 '''
570 CODE = 'average'
571 plot_type = 'scatterbuffer'
572
573 def setup(self):
574 self.xaxis = 'time'
575 self.ncols = 1
576 self.nplots = 2
577 self.nrows = 2
578 self.ylabel = 'Velocity\nm/s'
579 self.xlabel = 'Time'
580 self.titles = ['VERTICAL VELOCITY: AVERAGE', 'ZONAL VELOCITY: AVERAGE']
581 self.colorbar = False
582 self.plots_adjust.update({'hspace':0.5, 'left': 0.1, 'bottom': 0.1, 'right':0.95, 'top': 0.95 })
583
584
585
586 def update(self, dataOut):
587
588 data = {}
589 meta = {}
590 data['average']= dataOut.avg_output[0:2] # VERTICAL, ZONAL velocities
591 meta['yrange'] = numpy.array([])
592
593 return data, meta
594
595 def plot(self):
596
597 self.x = self.data.times
598 self.y = self.data['average']
599
600 for n, ax in enumerate(self.axes):
601
602 if ax.firsttime:
603
604 if self.zlimits is not None:
605 ax.set_ylim((self.zlimits[n]))
606 self.axes[n].plot(self.x, self.y[n], c='r', ls='-', lw=1)
607 else:
608
609 if self.zlimits is not None:
610 ax.set_ylim((self.zlimits[n]))
611 self.axes[n].lines[0].set_data(self.x, self.y[n])
612
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