The requested changes are too big and content was truncated. Show full diff
| @@ -1,662 +1,662 | |||
|
|
1 | 1 | # Copyright (c) 2012-2020 Jicamarca Radio Observatory |
|
|
2 | 2 | # All rights reserved. |
|
|
3 | 3 | # |
|
|
4 | 4 | # Distributed under the terms of the BSD 3-clause license. |
|
|
5 | 5 | """API to create signal chain projects |
|
|
6 | 6 | |
|
|
7 | 7 | The API is provide through class: Project |
|
|
8 | 8 | """ |
|
|
9 | 9 | |
|
|
10 | 10 | import re |
|
|
11 | 11 | import sys |
|
|
12 | 12 | import ast |
|
|
13 | 13 | import datetime |
|
|
14 | 14 | import traceback |
|
|
15 | 15 | import time |
|
|
16 | 16 | import multiprocessing |
|
|
17 | 17 | from multiprocessing import Process, Queue |
|
|
18 | 18 | from threading import Thread |
|
|
19 | 19 | from xml.etree.ElementTree import ElementTree, Element, SubElement |
|
|
20 | 20 | |
|
|
21 | 21 | from schainpy.admin import Alarm, SchainWarning |
|
|
22 | 22 | from schainpy.model import * |
|
|
23 | 23 | from schainpy.utils import log |
|
|
24 | 24 | |
|
|
25 | 25 | if 'darwin' in sys.platform and sys.version_info[0] == 3 and sys.version_info[1] > 7: |
|
|
26 | 26 | multiprocessing.set_start_method('fork') |
|
|
27 | 27 | |
|
|
28 | 28 | class ConfBase(): |
|
|
29 | 29 | |
|
|
30 | 30 | def __init__(self): |
|
|
31 | 31 | |
|
|
32 | 32 | self.id = '0' |
|
|
33 | 33 | self.name = None |
|
|
34 | 34 | self.priority = None |
|
|
35 | 35 | self.parameters = {} |
|
|
36 | 36 | self.object = None |
|
|
37 | 37 | self.operations = [] |
|
|
38 | 38 | |
|
|
39 | 39 | def getId(self): |
|
|
40 | 40 | |
|
|
41 | 41 | return self.id |
|
|
42 | 42 | |
|
|
43 | 43 | def getNewId(self): |
|
|
44 | 44 | |
|
|
45 | 45 | return int(self.id) * 10 + len(self.operations) + 1 |
|
|
46 | 46 | |
|
|
47 | 47 | def updateId(self, new_id): |
|
|
48 | 48 | |
|
|
49 | 49 | self.id = str(new_id) |
|
|
50 | 50 | |
|
|
51 | 51 | n = 1 |
|
|
52 | 52 | for conf in self.operations: |
|
|
53 | 53 | conf_id = str(int(new_id) * 10 + n) |
|
|
54 | 54 | conf.updateId(conf_id) |
|
|
55 | 55 | n += 1 |
|
|
56 | 56 | |
|
|
57 | 57 | def getKwargs(self): |
|
|
58 | 58 | |
|
|
59 | 59 | params = {} |
|
|
60 | 60 | |
|
|
61 | 61 | for key, value in self.parameters.items(): |
|
|
62 | 62 | if value not in (None, '', ' '): |
|
|
63 | 63 | params[key] = value |
|
|
64 | 64 | |
|
|
65 | 65 | return params |
|
|
66 | 66 | |
|
|
67 | 67 | def update(self, **kwargs): |
|
|
68 | 68 | |
|
|
69 | 69 | if 'format' not in kwargs: |
|
|
70 | 70 | kwargs['format'] = None |
|
|
71 | 71 | for key, value, fmt in kwargs.items(): |
|
|
72 | 72 | self.addParameter(name=key, value=value, format=fmt) |
|
|
73 | 73 | |
|
|
74 | 74 | def addParameter(self, name, value, format=None): |
|
|
75 | 75 | ''' |
|
|
76 | 76 | ''' |
|
|
77 | if os.path.isdir(value): | |
|
|
78 | self.parameters[name] = value | |
|
|
77 | if format is not None: | |
|
|
78 | self.parameters[name] = eval(format)(value) | |
|
|
79 | 79 | elif isinstance(value, str) and re.search(r'(\d+/\d+/\d+)', value): |
|
|
80 | 80 | self.parameters[name] = datetime.date(*[int(x) for x in value.split('/')]) |
|
|
81 | 81 | elif isinstance(value, str) and re.search(r'(\d+:\d+:\d+)', value): |
|
|
82 | 82 | self.parameters[name] = datetime.time(*[int(x) for x in value.split(':')]) |
|
|
83 | 83 | else: |
|
|
84 | 84 | try: |
|
|
85 | 85 | self.parameters[name] = ast.literal_eval(value) |
|
|
86 | 86 | except: |
|
|
87 | 87 | if isinstance(value, str) and ',' in value: |
|
|
88 | 88 | self.parameters[name] = value.split(',') |
|
|
89 | 89 | else: |
|
|
90 | 90 | self.parameters[name] = value |
|
|
91 | 91 | |
|
|
92 | 92 | def getParameters(self): |
|
|
93 | 93 | |
|
|
94 | 94 | params = {} |
|
|
95 | 95 | for key, value in self.parameters.items(): |
|
|
96 | 96 | s = type(value).__name__ |
|
|
97 | 97 | if s == 'date': |
|
|
98 | 98 | params[key] = value.strftime('%Y/%m/%d') |
|
|
99 | 99 | elif s == 'time': |
|
|
100 | 100 | params[key] = value.strftime('%H:%M:%S') |
|
|
101 | 101 | else: |
|
|
102 | 102 | params[key] = str(value) |
|
|
103 | 103 | |
|
|
104 | 104 | return params |
|
|
105 | 105 | |
|
|
106 | 106 | def makeXml(self, element): |
|
|
107 | 107 | |
|
|
108 | 108 | xml = SubElement(element, self.ELEMENTNAME) |
|
|
109 | 109 | for label in self.xml_labels: |
|
|
110 | 110 | xml.set(label, str(getattr(self, label))) |
|
|
111 | 111 | |
|
|
112 | 112 | for key, value in self.getParameters().items(): |
|
|
113 | 113 | xml_param = SubElement(xml, 'Parameter') |
|
|
114 | 114 | xml_param.set('name', key) |
|
|
115 | 115 | xml_param.set('value', value) |
|
|
116 | 116 | |
|
|
117 | 117 | for conf in self.operations: |
|
|
118 | 118 | conf.makeXml(xml) |
|
|
119 | 119 | |
|
|
120 | 120 | def __str__(self): |
|
|
121 | 121 | |
|
|
122 | 122 | if self.ELEMENTNAME == 'Operation': |
|
|
123 | 123 | s = ' {}[id={}]\n'.format(self.name, self.id) |
|
|
124 | 124 | else: |
|
|
125 | 125 | s = '{}[id={}, inputId={}]\n'.format(self.name, self.id, self.inputId) |
|
|
126 | 126 | |
|
|
127 | 127 | for key, value in self.parameters.items(): |
|
|
128 | 128 | if self.ELEMENTNAME == 'Operation': |
|
|
129 | 129 | s += ' {}: {}\n'.format(key, value) |
|
|
130 | 130 | else: |
|
|
131 | 131 | s += ' {}: {}\n'.format(key, value) |
|
|
132 | 132 | |
|
|
133 | 133 | for conf in self.operations: |
|
|
134 | 134 | s += str(conf) |
|
|
135 | 135 | |
|
|
136 | 136 | return s |
|
|
137 | 137 | |
|
|
138 | 138 | class OperationConf(ConfBase): |
|
|
139 | 139 | |
|
|
140 | 140 | ELEMENTNAME = 'Operation' |
|
|
141 | 141 | xml_labels = ['id', 'name'] |
|
|
142 | 142 | |
|
|
143 | 143 | def setup(self, id, name, priority, project_id, err_queue): |
|
|
144 | 144 | |
|
|
145 | 145 | self.id = str(id) |
|
|
146 | 146 | self.project_id = project_id |
|
|
147 | 147 | self.name = name |
|
|
148 | 148 | self.type = 'other' |
|
|
149 | 149 | self.err_queue = err_queue |
|
|
150 | 150 | |
|
|
151 | 151 | def readXml(self, element, project_id, err_queue): |
|
|
152 | 152 | |
|
|
153 | 153 | self.id = element.get('id') |
|
|
154 | 154 | self.name = element.get('name') |
|
|
155 | 155 | self.type = 'other' |
|
|
156 | 156 | self.project_id = str(project_id) |
|
|
157 | 157 | self.err_queue = err_queue |
|
|
158 | 158 | |
|
|
159 | 159 | for elm in element.iter('Parameter'): |
|
|
160 | 160 | self.addParameter(elm.get('name'), elm.get('value')) |
|
|
161 | 161 | |
|
|
162 | 162 | def createObject(self): |
|
|
163 | 163 | |
|
|
164 | 164 | className = eval(self.name) |
|
|
165 | 165 | |
|
|
166 | 166 | if 'Plot' in self.name or 'Writer' in self.name or 'Send' in self.name or 'print' in self.name: |
|
|
167 | 167 | kwargs = self.getKwargs() |
|
|
168 | 168 | opObj = className(self.id, self.id, self.project_id, self.err_queue, **kwargs) |
|
|
169 | 169 | opObj.start() |
|
|
170 | 170 | self.type = 'external' |
|
|
171 | 171 | else: |
|
|
172 | 172 | opObj = className() |
|
|
173 | 173 | |
|
|
174 | 174 | self.object = opObj |
|
|
175 | 175 | return opObj |
|
|
176 | 176 | |
|
|
177 | 177 | class ProcUnitConf(ConfBase): |
|
|
178 | 178 | |
|
|
179 | 179 | ELEMENTNAME = 'ProcUnit' |
|
|
180 | 180 | xml_labels = ['id', 'inputId', 'name'] |
|
|
181 | 181 | |
|
|
182 | 182 | def setup(self, project_id, id, name, datatype, inputId, err_queue): |
|
|
183 | 183 | ''' |
|
|
184 | 184 | ''' |
|
|
185 | 185 | |
|
|
186 | 186 | if datatype == None and name == None: |
|
|
187 | 187 | raise ValueError('datatype or name should be defined') |
|
|
188 | 188 | |
|
|
189 | 189 | if name == None: |
|
|
190 | 190 | if 'Proc' in datatype: |
|
|
191 | 191 | name = datatype |
|
|
192 | 192 | else: |
|
|
193 | 193 | name = '%sProc' % (datatype) |
|
|
194 | 194 | |
|
|
195 | 195 | if datatype == None: |
|
|
196 | 196 | datatype = name.replace('Proc', '') |
|
|
197 | 197 | |
|
|
198 | 198 | self.id = str(id) |
|
|
199 | 199 | self.project_id = project_id |
|
|
200 | 200 | self.name = name |
|
|
201 | 201 | self.datatype = datatype |
|
|
202 | 202 | self.inputId = inputId |
|
|
203 | 203 | self.err_queue = err_queue |
|
|
204 | 204 | self.operations = [] |
|
|
205 | 205 | self.parameters = {} |
|
|
206 | 206 | |
|
|
207 | 207 | def removeOperation(self, id): |
|
|
208 | 208 | |
|
|
209 | 209 | i = [1 if x.id==id else 0 for x in self.operations] |
|
|
210 | 210 | self.operations.pop(i.index(1)) |
|
|
211 | 211 | |
|
|
212 | 212 | def getOperation(self, id): |
|
|
213 | 213 | |
|
|
214 | 214 | for conf in self.operations: |
|
|
215 | 215 | if conf.id == id: |
|
|
216 | 216 | return conf |
|
|
217 | 217 | |
|
|
218 | 218 | def addOperation(self, name, optype='self'): |
|
|
219 | 219 | ''' |
|
|
220 | 220 | ''' |
|
|
221 | 221 | |
|
|
222 | 222 | id = self.getNewId() |
|
|
223 | 223 | conf = OperationConf() |
|
|
224 | 224 | conf.setup(id, name=name, priority='0', project_id=self.project_id, err_queue=self.err_queue) |
|
|
225 | 225 | self.operations.append(conf) |
|
|
226 | 226 | |
|
|
227 | 227 | return conf |
|
|
228 | 228 | |
|
|
229 | 229 | def readXml(self, element, project_id, err_queue): |
|
|
230 | 230 | |
|
|
231 | 231 | self.id = element.get('id') |
|
|
232 | 232 | self.name = element.get('name') |
|
|
233 | 233 | self.inputId = None if element.get('inputId') == 'None' else element.get('inputId') |
|
|
234 | 234 | self.datatype = element.get('datatype', self.name.replace(self.ELEMENTNAME.replace('Unit', ''), '')) |
|
|
235 | 235 | self.project_id = str(project_id) |
|
|
236 | 236 | self.err_queue = err_queue |
|
|
237 | 237 | self.operations = [] |
|
|
238 | 238 | self.parameters = {} |
|
|
239 | 239 | |
|
|
240 | 240 | for elm in element: |
|
|
241 | 241 | if elm.tag == 'Parameter': |
|
|
242 | 242 | self.addParameter(elm.get('name'), elm.get('value')) |
|
|
243 | 243 | elif elm.tag == 'Operation': |
|
|
244 | 244 | conf = OperationConf() |
|
|
245 | 245 | conf.readXml(elm, project_id, err_queue) |
|
|
246 | 246 | self.operations.append(conf) |
|
|
247 | 247 | |
|
|
248 | 248 | def createObjects(self): |
|
|
249 | 249 | ''' |
|
|
250 | 250 | Instancia de unidades de procesamiento. |
|
|
251 | 251 | ''' |
|
|
252 | 252 | |
|
|
253 | 253 | className = eval(self.name) |
|
|
254 | 254 | kwargs = self.getKwargs() |
|
|
255 | 255 | procUnitObj = className() |
|
|
256 | 256 | procUnitObj.name = self.name |
|
|
257 | 257 | log.success('creating process...', self.name) |
|
|
258 | 258 | |
|
|
259 | 259 | for conf in self.operations: |
|
|
260 | 260 | |
|
|
261 | 261 | opObj = conf.createObject() |
|
|
262 | 262 | |
|
|
263 | 263 | log.success('adding operation: {}, type:{}'.format( |
|
|
264 | 264 | conf.name, |
|
|
265 | 265 | conf.type), self.name) |
|
|
266 | 266 | |
|
|
267 | 267 | procUnitObj.addOperation(conf, opObj) |
|
|
268 | 268 | |
|
|
269 | 269 | self.object = procUnitObj |
|
|
270 | 270 | |
|
|
271 | 271 | def run(self): |
|
|
272 | 272 | ''' |
|
|
273 | 273 | ''' |
|
|
274 | 274 | |
|
|
275 | 275 | return self.object.call(**self.getKwargs()) |
|
|
276 | 276 | |
|
|
277 | 277 | |
|
|
278 | 278 | class ReadUnitConf(ProcUnitConf): |
|
|
279 | 279 | |
|
|
280 | 280 | ELEMENTNAME = 'ReadUnit' |
|
|
281 | 281 | |
|
|
282 | 282 | def __init__(self): |
|
|
283 | 283 | |
|
|
284 | 284 | self.id = None |
|
|
285 | 285 | self.datatype = None |
|
|
286 | 286 | self.name = None |
|
|
287 | 287 | self.inputId = None |
|
|
288 | 288 | self.operations = [] |
|
|
289 | 289 | self.parameters = {} |
|
|
290 | 290 | |
|
|
291 | 291 | def setup(self, project_id, id, name, datatype, err_queue, path='', startDate='', endDate='', |
|
|
292 | 292 | startTime='', endTime='', server=None, **kwargs): |
|
|
293 | 293 | |
|
|
294 | 294 | if datatype == None and name == None: |
|
|
295 | 295 | raise ValueError('datatype or name should be defined') |
|
|
296 | 296 | if name == None: |
|
|
297 | 297 | if 'Reader' in datatype: |
|
|
298 | 298 | name = datatype |
|
|
299 | 299 | datatype = name.replace('Reader','') |
|
|
300 | 300 | else: |
|
|
301 | 301 | name = '{}Reader'.format(datatype) |
|
|
302 | 302 | if datatype == None: |
|
|
303 | 303 | if 'Reader' in name: |
|
|
304 | 304 | datatype = name.replace('Reader','') |
|
|
305 | 305 | else: |
|
|
306 | 306 | datatype = name |
|
|
307 | 307 | name = '{}Reader'.format(name) |
|
|
308 | 308 | |
|
|
309 | 309 | self.id = id |
|
|
310 | 310 | self.project_id = project_id |
|
|
311 | 311 | self.name = name |
|
|
312 | 312 | self.datatype = datatype |
|
|
313 | 313 | self.err_queue = err_queue |
|
|
314 | 314 | |
|
|
315 | self.addParameter(name='path', value=path) | |
|
|
315 | self.addParameter(name='path', value=path, format='str') | |
|
|
316 | 316 | self.addParameter(name='startDate', value=startDate) |
|
|
317 | 317 | self.addParameter(name='endDate', value=endDate) |
|
|
318 | 318 | self.addParameter(name='startTime', value=startTime) |
|
|
319 | 319 | self.addParameter(name='endTime', value=endTime) |
|
|
320 | 320 | |
|
|
321 | 321 | for key, value in kwargs.items(): |
|
|
322 | 322 | self.addParameter(name=key, value=value) |
|
|
323 | 323 | |
|
|
324 | 324 | |
|
|
325 | 325 | class Project(Process): |
|
|
326 | 326 | """API to create signal chain projects""" |
|
|
327 | 327 | |
|
|
328 | 328 | ELEMENTNAME = 'Project' |
|
|
329 | 329 | |
|
|
330 | 330 | def __init__(self, name=''): |
|
|
331 | 331 | |
|
|
332 | 332 | Process.__init__(self) |
|
|
333 | 333 | self.id = '1' |
|
|
334 | 334 | if name: |
|
|
335 | 335 | self.name = '{} ({})'.format(Process.__name__, name) |
|
|
336 | 336 | self.filename = None |
|
|
337 | 337 | self.description = None |
|
|
338 | 338 | self.email = None |
|
|
339 | 339 | self.alarm = [] |
|
|
340 | 340 | self.configurations = {} |
|
|
341 | 341 | # self.err_queue = Queue() |
|
|
342 | 342 | self.err_queue = None |
|
|
343 | 343 | self.started = False |
|
|
344 | 344 | |
|
|
345 | 345 | def getNewId(self): |
|
|
346 | 346 | |
|
|
347 | 347 | idList = list(self.configurations.keys()) |
|
|
348 | 348 | id = int(self.id) * 10 |
|
|
349 | 349 | |
|
|
350 | 350 | while True: |
|
|
351 | 351 | id += 1 |
|
|
352 | 352 | |
|
|
353 | 353 | if str(id) in idList: |
|
|
354 | 354 | continue |
|
|
355 | 355 | |
|
|
356 | 356 | break |
|
|
357 | 357 | |
|
|
358 | 358 | return str(id) |
|
|
359 | 359 | |
|
|
360 | 360 | def updateId(self, new_id): |
|
|
361 | 361 | |
|
|
362 | 362 | self.id = str(new_id) |
|
|
363 | 363 | |
|
|
364 | 364 | keyList = list(self.configurations.keys()) |
|
|
365 | 365 | keyList.sort() |
|
|
366 | 366 | |
|
|
367 | 367 | n = 1 |
|
|
368 | 368 | new_confs = {} |
|
|
369 | 369 | |
|
|
370 | 370 | for procKey in keyList: |
|
|
371 | 371 | |
|
|
372 | 372 | conf = self.configurations[procKey] |
|
|
373 | 373 | idProcUnit = str(int(self.id) * 10 + n) |
|
|
374 | 374 | conf.updateId(idProcUnit) |
|
|
375 | 375 | new_confs[idProcUnit] = conf |
|
|
376 | 376 | n += 1 |
|
|
377 | 377 | |
|
|
378 | 378 | self.configurations = new_confs |
|
|
379 | 379 | |
|
|
380 | 380 | def setup(self, id=1, name='', description='', email=None, alarm=[]): |
|
|
381 | 381 | |
|
|
382 | 382 | self.id = str(id) |
|
|
383 | 383 | self.description = description |
|
|
384 | 384 | self.email = email |
|
|
385 | 385 | self.alarm = alarm |
|
|
386 | 386 | if name: |
|
|
387 | 387 | self.name = '{} ({})'.format(Process.__name__, name) |
|
|
388 | 388 | |
|
|
389 | 389 | def update(self, **kwargs): |
|
|
390 | 390 | |
|
|
391 | 391 | for key, value in kwargs.items(): |
|
|
392 | 392 | setattr(self, key, value) |
|
|
393 | 393 | |
|
|
394 | 394 | def clone(self): |
|
|
395 | 395 | |
|
|
396 | 396 | p = Project() |
|
|
397 | 397 | p.id = self.id |
|
|
398 | 398 | p.name = self.name |
|
|
399 | 399 | p.description = self.description |
|
|
400 | 400 | p.configurations = self.configurations.copy() |
|
|
401 | 401 | |
|
|
402 | 402 | return p |
|
|
403 | 403 | |
|
|
404 | 404 | def addReadUnit(self, id=None, datatype=None, name=None, **kwargs): |
|
|
405 | 405 | |
|
|
406 | 406 | ''' |
|
|
407 | 407 | ''' |
|
|
408 | 408 | |
|
|
409 | 409 | if id is None: |
|
|
410 | 410 | idReadUnit = self.getNewId() |
|
|
411 | 411 | else: |
|
|
412 | 412 | idReadUnit = str(id) |
|
|
413 | 413 | |
|
|
414 | 414 | conf = ReadUnitConf() |
|
|
415 | 415 | conf.setup(self.id, idReadUnit, name, datatype, self.err_queue, **kwargs) |
|
|
416 | 416 | self.configurations[conf.id] = conf |
|
|
417 | 417 | |
|
|
418 | 418 | return conf |
|
|
419 | 419 | |
|
|
420 | 420 | def addProcUnit(self, id=None, inputId='0', datatype=None, name=None): |
|
|
421 | 421 | |
|
|
422 | 422 | ''' |
|
|
423 | 423 | ''' |
|
|
424 | 424 | |
|
|
425 | 425 | if id is None: |
|
|
426 | 426 | idProcUnit = self.getNewId() |
|
|
427 | 427 | else: |
|
|
428 | 428 | idProcUnit = id |
|
|
429 | 429 | |
|
|
430 | 430 | conf = ProcUnitConf() |
|
|
431 | 431 | conf.setup(self.id, idProcUnit, name, datatype, inputId, self.err_queue) |
|
|
432 | 432 | self.configurations[conf.id] = conf |
|
|
433 | 433 | |
|
|
434 | 434 | return conf |
|
|
435 | 435 | |
|
|
436 | 436 | def removeProcUnit(self, id): |
|
|
437 | 437 | |
|
|
438 | 438 | if id in self.configurations: |
|
|
439 | 439 | self.configurations.pop(id) |
|
|
440 | 440 | |
|
|
441 | 441 | def getReadUnit(self): |
|
|
442 | 442 | |
|
|
443 | 443 | for obj in list(self.configurations.values()): |
|
|
444 | 444 | if obj.ELEMENTNAME == 'ReadUnit': |
|
|
445 | 445 | return obj |
|
|
446 | 446 | |
|
|
447 | 447 | return None |
|
|
448 | 448 | |
|
|
449 | 449 | def getProcUnit(self, id): |
|
|
450 | 450 | |
|
|
451 | 451 | return self.configurations[id] |
|
|
452 | 452 | |
|
|
453 | 453 | def getUnits(self): |
|
|
454 | 454 | |
|
|
455 | 455 | keys = list(self.configurations) |
|
|
456 | 456 | keys.sort() |
|
|
457 | 457 | |
|
|
458 | 458 | for key in keys: |
|
|
459 | 459 | yield self.configurations[key] |
|
|
460 | 460 | |
|
|
461 | 461 | def updateUnit(self, id, **kwargs): |
|
|
462 | 462 | |
|
|
463 | 463 | conf = self.configurations[id].update(**kwargs) |
|
|
464 | 464 | |
|
|
465 | 465 | def makeXml(self): |
|
|
466 | 466 | |
|
|
467 | 467 | xml = Element('Project') |
|
|
468 | 468 | xml.set('id', str(self.id)) |
|
|
469 | 469 | xml.set('name', self.name) |
|
|
470 | 470 | xml.set('description', self.description) |
|
|
471 | 471 | |
|
|
472 | 472 | for conf in self.configurations.values(): |
|
|
473 | 473 | conf.makeXml(xml) |
|
|
474 | 474 | |
|
|
475 | 475 | self.xml = xml |
|
|
476 | 476 | |
|
|
477 | 477 | def writeXml(self, filename=None): |
|
|
478 | 478 | |
|
|
479 | 479 | if filename == None: |
|
|
480 | 480 | if self.filename: |
|
|
481 | 481 | filename = self.filename |
|
|
482 | 482 | else: |
|
|
483 | 483 | filename = 'schain.xml' |
|
|
484 | 484 | |
|
|
485 | 485 | if not filename: |
|
|
486 | 486 | print('filename has not been defined. Use setFilename(filename) for do it.') |
|
|
487 | 487 | return 0 |
|
|
488 | 488 | |
|
|
489 | 489 | abs_file = os.path.abspath(filename) |
|
|
490 | 490 | |
|
|
491 | 491 | if not os.access(os.path.dirname(abs_file), os.W_OK): |
|
|
492 | 492 | print('No write permission on %s' % os.path.dirname(abs_file)) |
|
|
493 | 493 | return 0 |
|
|
494 | 494 | |
|
|
495 | 495 | if os.path.isfile(abs_file) and not(os.access(abs_file, os.W_OK)): |
|
|
496 | 496 | print('File %s already exists and it could not be overwriten' % abs_file) |
|
|
497 | 497 | return 0 |
|
|
498 | 498 | |
|
|
499 | 499 | self.makeXml() |
|
|
500 | 500 | |
|
|
501 | 501 | ElementTree(self.xml).write(abs_file, method='xml') |
|
|
502 | 502 | |
|
|
503 | 503 | self.filename = abs_file |
|
|
504 | 504 | |
|
|
505 | 505 | return 1 |
|
|
506 | 506 | |
|
|
507 | 507 | def readXml(self, filename): |
|
|
508 | 508 | |
|
|
509 | 509 | abs_file = os.path.abspath(filename) |
|
|
510 | 510 | |
|
|
511 | 511 | self.configurations = {} |
|
|
512 | 512 | |
|
|
513 | 513 | try: |
|
|
514 | 514 | self.xml = ElementTree().parse(abs_file) |
|
|
515 | 515 | except: |
|
|
516 | 516 | log.error('Error reading %s, verify file format' % filename) |
|
|
517 | 517 | return 0 |
|
|
518 | 518 | |
|
|
519 | 519 | self.id = self.xml.get('id') |
|
|
520 | 520 | self.name = self.xml.get('name') |
|
|
521 | 521 | self.description = self.xml.get('description') |
|
|
522 | 522 | |
|
|
523 | 523 | for element in self.xml: |
|
|
524 | 524 | if element.tag == 'ReadUnit': |
|
|
525 | 525 | conf = ReadUnitConf() |
|
|
526 | 526 | conf.readXml(element, self.id, self.err_queue) |
|
|
527 | 527 | self.configurations[conf.id] = conf |
|
|
528 | 528 | elif element.tag == 'ProcUnit': |
|
|
529 | 529 | conf = ProcUnitConf() |
|
|
530 | 530 | input_proc = self.configurations[element.get('inputId')] |
|
|
531 | 531 | conf.readXml(element, self.id, self.err_queue) |
|
|
532 | 532 | self.configurations[conf.id] = conf |
|
|
533 | 533 | |
|
|
534 | 534 | self.filename = abs_file |
|
|
535 | 535 | |
|
|
536 | 536 | return 1 |
|
|
537 | 537 | |
|
|
538 | 538 | def __str__(self): |
|
|
539 | 539 | |
|
|
540 | 540 | text = '\nProject[id=%s, name=%s, description=%s]\n\n' % ( |
|
|
541 | 541 | self.id, |
|
|
542 | 542 | self.name, |
|
|
543 | 543 | self.description, |
|
|
544 | 544 | ) |
|
|
545 | 545 | |
|
|
546 | 546 | for conf in self.configurations.values(): |
|
|
547 | 547 | text += '{}'.format(conf) |
|
|
548 | 548 | |
|
|
549 | 549 | return text |
|
|
550 | 550 | |
|
|
551 | 551 | def createObjects(self): |
|
|
552 | 552 | |
|
|
553 | 553 | keys = list(self.configurations.keys()) |
|
|
554 | 554 | keys.sort() |
|
|
555 | 555 | for key in keys: |
|
|
556 | 556 | conf = self.configurations[key] |
|
|
557 | 557 | conf.createObjects() |
|
|
558 | 558 | if conf.inputId is not None: |
|
|
559 | 559 | conf.object.setInput(self.configurations[conf.inputId].object) |
|
|
560 | 560 | |
|
|
561 | 561 | def monitor(self): |
|
|
562 | 562 | |
|
|
563 | 563 | t = Thread(target=self._monitor, args=(self.err_queue, self.ctx)) |
|
|
564 | 564 | t.start() |
|
|
565 | 565 | |
|
|
566 | 566 | def _monitor(self, queue, ctx): |
|
|
567 | 567 | |
|
|
568 | 568 | import socket |
|
|
569 | 569 | |
|
|
570 | 570 | procs = 0 |
|
|
571 | 571 | err_msg = '' |
|
|
572 | 572 | |
|
|
573 | 573 | while True: |
|
|
574 | 574 | msg = queue.get() |
|
|
575 | 575 | if '#_start_#' in msg: |
|
|
576 | 576 | procs += 1 |
|
|
577 | 577 | elif '#_end_#' in msg: |
|
|
578 | 578 | procs -=1 |
|
|
579 | 579 | else: |
|
|
580 | 580 | err_msg = msg |
|
|
581 | 581 | |
|
|
582 | 582 | if procs == 0 or 'Traceback' in err_msg: |
|
|
583 | 583 | break |
|
|
584 | 584 | time.sleep(0.1) |
|
|
585 | 585 | |
|
|
586 | 586 | if '|' in err_msg: |
|
|
587 | 587 | name, err = err_msg.split('|') |
|
|
588 | 588 | if 'SchainWarning' in err: |
|
|
589 | 589 | log.warning(err.split('SchainWarning:')[-1].split('\n')[0].strip(), name) |
|
|
590 | 590 | elif 'SchainError' in err: |
|
|
591 | 591 | log.error(err.split('SchainError:')[-1].split('\n')[0].strip(), name) |
|
|
592 | 592 | else: |
|
|
593 | 593 | log.error(err, name) |
|
|
594 | 594 | else: |
|
|
595 | 595 | name, err = self.name, err_msg |
|
|
596 | 596 | |
|
|
597 | 597 | time.sleep(1) |
|
|
598 | 598 | |
|
|
599 | 599 | ctx.term() |
|
|
600 | 600 | |
|
|
601 | 601 | message = ''.join(err) |
|
|
602 | 602 | |
|
|
603 | 603 | if err_msg: |
|
|
604 | 604 | subject = 'SChain v%s: Error running %s\n' % ( |
|
|
605 | 605 | schainpy.__version__, self.name) |
|
|
606 | 606 | |
|
|
607 | 607 | subtitle = 'Hostname: %s\n' % socket.gethostbyname( |
|
|
608 | 608 | socket.gethostname()) |
|
|
609 | 609 | subtitle += 'Working directory: %s\n' % os.path.abspath('./') |
|
|
610 | 610 | subtitle += 'Configuration file: %s\n' % self.filename |
|
|
611 | 611 | subtitle += 'Time: %s\n' % str(datetime.datetime.now()) |
|
|
612 | 612 | |
|
|
613 | 613 | readUnitConfObj = self.getReadUnit() |
|
|
614 | 614 | if readUnitConfObj: |
|
|
615 | 615 | subtitle += '\nInput parameters:\n' |
|
|
616 | 616 | subtitle += '[Data path = %s]\n' % readUnitConfObj.parameters['path'] |
|
|
617 | 617 | subtitle += '[Start date = %s]\n' % readUnitConfObj.parameters['startDate'] |
|
|
618 | 618 | subtitle += '[End date = %s]\n' % readUnitConfObj.parameters['endDate'] |
|
|
619 | 619 | subtitle += '[Start time = %s]\n' % readUnitConfObj.parameters['startTime'] |
|
|
620 | 620 | subtitle += '[End time = %s]\n' % readUnitConfObj.parameters['endTime'] |
|
|
621 | 621 | |
|
|
622 | 622 | a = Alarm( |
|
|
623 | 623 | modes=self.alarm, |
|
|
624 | 624 | email=self.email, |
|
|
625 | 625 | message=message, |
|
|
626 | 626 | subject=subject, |
|
|
627 | 627 | subtitle=subtitle, |
|
|
628 | 628 | filename=self.filename |
|
|
629 | 629 | ) |
|
|
630 | 630 | |
|
|
631 | 631 | a.start() |
|
|
632 | 632 | |
|
|
633 | 633 | def setFilename(self, filename): |
|
|
634 | 634 | |
|
|
635 | 635 | self.filename = filename |
|
|
636 | 636 | |
|
|
637 | 637 | def runProcs(self): |
|
|
638 | 638 | |
|
|
639 | 639 | err = False |
|
|
640 | 640 | n = len(self.configurations) |
|
|
641 | 641 | |
|
|
642 | 642 | while not err: |
|
|
643 | 643 | for conf in self.getUnits(): |
|
|
644 | 644 | ok = conf.run() |
|
|
645 | 645 | if ok == 'Error': |
|
|
646 | 646 | n -= 1 |
|
|
647 | 647 | continue |
|
|
648 | 648 | elif not ok: |
|
|
649 | 649 | break |
|
|
650 | 650 | if n == 0: |
|
|
651 | 651 | err = True |
|
|
652 | 652 | |
|
|
653 | 653 | def run(self): |
|
|
654 | 654 | |
|
|
655 | 655 | log.success('\nStarting Project {} [id={}]'.format(self.name, self.id), tag='') |
|
|
656 | 656 | self.started = True |
|
|
657 | 657 | self.start_time = time.time() |
|
|
658 | 658 | self.createObjects() |
|
|
659 | 659 | self.runProcs() |
|
|
660 | 660 | log.success('{} Done (Time: {:4.2f}s)'.format( |
|
|
661 | 661 | self.name, |
|
|
662 | 662 | time.time()-self.start_time), '') |
| @@ -1,2378 +1,2383 | |||
|
|
1 | 1 | import os |
|
|
2 | 2 | import datetime |
|
|
3 | 3 | import numpy |
|
|
4 | 4 | from mpl_toolkits.axisartist.grid_finder import FixedLocator, DictFormatter |
|
|
5 | 5 | |
|
|
6 | 6 | from schainpy.model.graphics.jroplot_base import Plot, plt |
|
|
7 | 7 | from schainpy.model.graphics.jroplot_spectra import SpectraPlot, RTIPlot, CoherencePlot, SpectraCutPlot |
|
|
8 | 8 | from schainpy.utils import log |
|
|
9 | 9 | # libreria wradlib |
|
|
10 | 10 | import wradlib as wrl |
|
|
11 | 11 | |
|
|
12 | 12 | EARTH_RADIUS = 6.3710e3 |
|
|
13 | 13 | |
|
|
14 | 14 | |
|
|
15 | 15 | def ll2xy(lat1, lon1, lat2, lon2): |
|
|
16 | 16 | |
|
|
17 | 17 | p = 0.017453292519943295 |
|
|
18 | 18 | a = 0.5 - numpy.cos((lat2 - lat1) * p)/2 + numpy.cos(lat1 * p) * \ |
|
|
19 | 19 | numpy.cos(lat2 * p) * (1 - numpy.cos((lon2 - lon1) * p)) / 2 |
|
|
20 | 20 | r = 12742 * numpy.arcsin(numpy.sqrt(a)) |
|
|
21 | 21 | theta = numpy.arctan2(numpy.sin((lon2-lon1)*p)*numpy.cos(lat2*p), numpy.cos(lat1*p) |
|
|
22 | 22 | * numpy.sin(lat2*p)-numpy.sin(lat1*p)*numpy.cos(lat2*p)*numpy.cos((lon2-lon1)*p)) |
|
|
23 | 23 | theta = -theta + numpy.pi/2 |
|
|
24 | 24 | return r*numpy.cos(theta), r*numpy.sin(theta) |
|
|
25 | 25 | |
|
|
26 | 26 | |
|
|
27 | 27 | def km2deg(km): |
|
|
28 | 28 | ''' |
|
|
29 | 29 | Convert distance in km to degrees |
|
|
30 | 30 | ''' |
|
|
31 | 31 | |
|
|
32 | 32 | return numpy.rad2deg(km/EARTH_RADIUS) |
|
|
33 | 33 | |
|
|
34 | 34 | |
|
|
35 | 35 | |
|
|
36 | 36 | class SpectralMomentsPlot(SpectraPlot): |
|
|
37 | 37 | ''' |
|
|
38 | 38 | Plot for Spectral Moments |
|
|
39 | 39 | ''' |
|
|
40 | 40 | CODE = 'spc_moments' |
|
|
41 | 41 | # colormap = 'jet' |
|
|
42 | 42 | # plot_type = 'pcolor' |
|
|
43 | 43 | |
|
|
44 | 44 | class DobleGaussianPlot(SpectraPlot): |
|
|
45 | 45 | ''' |
|
|
46 | 46 | Plot for Double Gaussian Plot |
|
|
47 | 47 | ''' |
|
|
48 | 48 | CODE = 'gaussian_fit' |
|
|
49 | 49 | # colormap = 'jet' |
|
|
50 | 50 | # plot_type = 'pcolor' |
|
|
51 | 51 | |
|
|
52 | 52 | class DoubleGaussianSpectraCutPlot(SpectraCutPlot): |
|
|
53 | 53 | ''' |
|
|
54 | 54 | Plot SpectraCut with Double Gaussian Fit |
|
|
55 | 55 | ''' |
|
|
56 | 56 | CODE = 'cut_gaussian_fit' |
|
|
57 | 57 | |
|
|
58 | 58 | class SnrPlot(RTIPlot): |
|
|
59 | 59 | ''' |
|
|
60 | 60 | Plot for SNR Data |
|
|
61 | 61 | ''' |
|
|
62 | 62 | |
|
|
63 | 63 | CODE = 'snr' |
|
|
64 | 64 | colormap = 'jet' |
|
|
65 | 65 | |
|
|
66 | 66 | def update(self, dataOut): |
|
|
67 | 67 | |
|
|
68 | 68 | data = { |
|
|
69 | 69 | 'snr': 10*numpy.log10(dataOut.data_snr) |
|
|
70 | 70 | } |
|
|
71 | 71 | |
|
|
72 | 72 | return data, {} |
|
|
73 | 73 | |
|
|
74 | 74 | class DopplerPlot(RTIPlot): |
|
|
75 | 75 | ''' |
|
|
76 | 76 | Plot for DOPPLER Data (1st moment) |
|
|
77 | 77 | ''' |
|
|
78 | 78 | |
|
|
79 | 79 | CODE = 'dop' |
|
|
80 | 80 | colormap = 'jet' |
|
|
81 | 81 | |
|
|
82 | 82 | def update(self, dataOut): |
|
|
83 | 83 | |
|
|
84 | 84 | data = { |
|
|
85 | 85 | 'dop': 10*numpy.log10(dataOut.data_dop) |
|
|
86 | 86 | } |
|
|
87 | 87 | |
|
|
88 | 88 | return data, {} |
|
|
89 | 89 | |
|
|
90 | 90 | class PowerPlot(RTIPlot): |
|
|
91 | 91 | ''' |
|
|
92 | 92 | Plot for Power Data (0 moment) |
|
|
93 | 93 | ''' |
|
|
94 | 94 | |
|
|
95 | 95 | CODE = 'pow' |
|
|
96 | 96 | colormap = 'jet' |
|
|
97 | 97 | |
|
|
98 | 98 | def update(self, dataOut): |
|
|
99 | 99 | data = { |
|
|
100 | 100 | 'pow': 10*numpy.log10(dataOut.data_pow/dataOut.normFactor) |
|
|
101 | 101 | } |
|
|
102 | 102 | return data, {} |
|
|
103 | 103 | |
|
|
104 | 104 | class SpectralWidthPlot(RTIPlot): |
|
|
105 | 105 | ''' |
|
|
106 | 106 | Plot for Spectral Width Data (2nd moment) |
|
|
107 | 107 | ''' |
|
|
108 | 108 | |
|
|
109 | 109 | CODE = 'width' |
|
|
110 | 110 | colormap = 'jet' |
|
|
111 | 111 | |
|
|
112 | 112 | def update(self, dataOut): |
|
|
113 | 113 | |
|
|
114 | 114 | data = { |
|
|
115 | 115 | 'width': dataOut.data_width |
|
|
116 | 116 | } |
|
|
117 | 117 | |
|
|
118 | 118 | return data, {} |
|
|
119 | 119 | |
|
|
120 | 120 | class SkyMapPlot(Plot): |
|
|
121 | 121 | ''' |
|
|
122 | 122 | Plot for meteors detection data |
|
|
123 | 123 | ''' |
|
|
124 | 124 | |
|
|
125 | 125 | CODE = 'param' |
|
|
126 | 126 | |
|
|
127 | 127 | def setup(self): |
|
|
128 | 128 | |
|
|
129 | 129 | self.ncols = 1 |
|
|
130 | 130 | self.nrows = 1 |
|
|
131 | 131 | self.width = 7.2 |
|
|
132 | 132 | self.height = 7.2 |
|
|
133 | 133 | self.nplots = 1 |
|
|
134 | 134 | self.xlabel = 'Zonal Zenith Angle (deg)' |
|
|
135 | 135 | self.ylabel = 'Meridional Zenith Angle (deg)' |
|
|
136 | 136 | self.polar = True |
|
|
137 | 137 | self.ymin = -180 |
|
|
138 | 138 | self.ymax = 180 |
|
|
139 | 139 | self.colorbar = False |
|
|
140 | 140 | |
|
|
141 | 141 | def plot(self): |
|
|
142 | 142 | |
|
|
143 | 143 | arrayParameters = numpy.concatenate(self.data['param']) |
|
|
144 | 144 | error = arrayParameters[:, -1] |
|
|
145 | 145 | indValid = numpy.where(error == 0)[0] |
|
|
146 | 146 | finalMeteor = arrayParameters[indValid, :] |
|
|
147 | 147 | finalAzimuth = finalMeteor[:, 3] |
|
|
148 | 148 | finalZenith = finalMeteor[:, 4] |
|
|
149 | 149 | |
|
|
150 | 150 | x = finalAzimuth * numpy.pi / 180 |
|
|
151 | 151 | y = finalZenith |
|
|
152 | 152 | |
|
|
153 | 153 | ax = self.axes[0] |
|
|
154 | 154 | |
|
|
155 | 155 | if ax.firsttime: |
|
|
156 | 156 | ax.plot = ax.plot(x, y, 'bo', markersize=5)[0] |
|
|
157 | 157 | else: |
|
|
158 | 158 | ax.plot.set_data(x, y) |
|
|
159 | 159 | |
|
|
160 | 160 | dt1 = self.getDateTime(self.data.min_time).strftime('%y/%m/%d %H:%M:%S') |
|
|
161 | 161 | dt2 = self.getDateTime(self.data.max_time).strftime('%y/%m/%d %H:%M:%S') |
|
|
162 | 162 | title = 'Meteor Detection Sky Map\n %s - %s \n Number of events: %5.0f\n' % (dt1, |
|
|
163 | 163 | dt2, |
|
|
164 | 164 | len(x)) |
|
|
165 | 165 | self.titles[0] = title |
|
|
166 | 166 | |
|
|
167 | 167 | |
|
|
168 | 168 | class GenericRTIPlot(Plot): |
|
|
169 | 169 | ''' |
|
|
170 | 170 | Plot for data_xxxx object |
|
|
171 | 171 | ''' |
|
|
172 | 172 | |
|
|
173 | 173 | CODE = 'param' |
|
|
174 | 174 | colormap = 'viridis' |
|
|
175 | 175 | plot_type = 'pcolorbuffer' |
|
|
176 | 176 | |
|
|
177 | 177 | def setup(self): |
|
|
178 | 178 | self.xaxis = 'time' |
|
|
179 | 179 | self.ncols = 1 |
|
|
180 | 180 | self.nrows = self.data.shape('param')[0] |
|
|
181 | 181 | self.nplots = self.nrows |
|
|
182 | 182 | self.plots_adjust.update({'hspace':0.8, 'left': 0.1, 'bottom': 0.08, 'right':0.95, 'top': 0.95}) |
|
|
183 | 183 | |
|
|
184 | 184 | if not self.xlabel: |
|
|
185 | 185 | self.xlabel = 'Time' |
|
|
186 | 186 | |
|
|
187 | 187 | self.ylabel = 'Range [km]' |
|
|
188 | 188 | if not self.titles: |
|
|
189 | 189 | self.titles = ['Param {}'.format(x) for x in range(self.nrows)] |
|
|
190 | 190 | |
|
|
191 | 191 | def update(self, dataOut): |
|
|
192 | 192 | |
|
|
193 | 193 | data = { |
|
|
194 | 194 | 'param' : numpy.concatenate([getattr(dataOut, attr) for attr in self.attr_data], axis=0) |
|
|
195 | 195 | } |
|
|
196 | 196 | |
|
|
197 | 197 | meta = {} |
|
|
198 | 198 | |
|
|
199 | 199 | return data, meta |
|
|
200 | 200 | |
|
|
201 | 201 | def plot(self): |
|
|
202 | 202 | # self.data.normalize_heights() |
|
|
203 | 203 | self.x = self.data.times |
|
|
204 | 204 | self.y = self.data.yrange |
|
|
205 | 205 | self.z = self.data['param'] |
|
|
206 | 206 | self.z = 10*numpy.log10(self.z) |
|
|
207 | 207 | self.z = numpy.ma.masked_invalid(self.z) |
|
|
208 | 208 | |
|
|
209 | 209 | if self.decimation is None: |
|
|
210 | 210 | x, y, z = self.fill_gaps(self.x, self.y, self.z) |
|
|
211 | 211 | else: |
|
|
212 | 212 | x, y, z = self.fill_gaps(*self.decimate()) |
|
|
213 | 213 | |
|
|
214 | 214 | for n, ax in enumerate(self.axes): |
|
|
215 | 215 | |
|
|
216 | 216 | self.zmax = self.zmax if self.zmax is not None else numpy.max( |
|
|
217 | 217 | self.z[n]) |
|
|
218 | 218 | self.zmin = self.zmin if self.zmin is not None else numpy.min( |
|
|
219 | 219 | self.z[n]) |
|
|
220 | 220 | |
|
|
221 | 221 | if ax.firsttime: |
|
|
222 | 222 | if self.zlimits is not None: |
|
|
223 | 223 | self.zmin, self.zmax = self.zlimits[n] |
|
|
224 | 224 | |
|
|
225 | 225 | ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n], |
|
|
226 | 226 | vmin=self.zmin, |
|
|
227 | 227 | vmax=self.zmax, |
|
|
228 | 228 | cmap=self.cmaps[n] |
|
|
229 | 229 | ) |
|
|
230 | 230 | else: |
|
|
231 | 231 | if self.zlimits is not None: |
|
|
232 | 232 | self.zmin, self.zmax = self.zlimits[n] |
|
|
233 | 233 | ax.collections.remove(ax.collections[0]) |
|
|
234 | 234 | ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n], |
|
|
235 | 235 | vmin=self.zmin, |
|
|
236 | 236 | vmax=self.zmax, |
|
|
237 | 237 | cmap=self.cmaps[n] |
|
|
238 | 238 | ) |
|
|
239 | 239 | |
|
|
240 | 240 | |
|
|
241 | 241 | class PolarMapPlot(Plot): |
|
|
242 | 242 | ''' |
|
|
243 | 243 | Plot for weather radar |
|
|
244 | 244 | ''' |
|
|
245 | 245 | |
|
|
246 | 246 | CODE = 'param' |
|
|
247 | 247 | colormap = 'seismic' |
|
|
248 | 248 | |
|
|
249 | 249 | def setup(self): |
|
|
250 | 250 | self.ncols = 1 |
|
|
251 | 251 | self.nrows = 1 |
|
|
252 | 252 | self.width = 9 |
|
|
253 | 253 | self.height = 8 |
|
|
254 | 254 | self.mode = self.data.meta['mode'] |
|
|
255 | 255 | if self.channels is not None: |
|
|
256 | 256 | self.nplots = len(self.channels) |
|
|
257 | 257 | self.nrows = len(self.channels) |
|
|
258 | 258 | else: |
|
|
259 | 259 | self.nplots = self.data.shape(self.CODE)[0] |
|
|
260 | 260 | self.nrows = self.nplots |
|
|
261 | 261 | self.channels = list(range(self.nplots)) |
|
|
262 | 262 | if self.mode == 'E': |
|
|
263 | 263 | self.xlabel = 'Longitude' |
|
|
264 | 264 | self.ylabel = 'Latitude' |
|
|
265 | 265 | else: |
|
|
266 | 266 | self.xlabel = 'Range (km)' |
|
|
267 | 267 | self.ylabel = 'Height (km)' |
|
|
268 | 268 | self.bgcolor = 'white' |
|
|
269 | 269 | self.cb_labels = self.data.meta['units'] |
|
|
270 | 270 | self.lat = self.data.meta['latitude'] |
|
|
271 | 271 | self.lon = self.data.meta['longitude'] |
|
|
272 | 272 | self.xmin, self.xmax = float( |
|
|
273 | 273 | km2deg(self.xmin) + self.lon), float(km2deg(self.xmax) + self.lon) |
|
|
274 | 274 | self.ymin, self.ymax = float( |
|
|
275 | 275 | km2deg(self.ymin) + self.lat), float(km2deg(self.ymax) + self.lat) |
|
|
276 | 276 | # self.polar = True |
|
|
277 | 277 | |
|
|
278 | 278 | def plot(self): |
|
|
279 | 279 | |
|
|
280 | 280 | for n, ax in enumerate(self.axes): |
|
|
281 | 281 | data = self.data['param'][self.channels[n]] |
|
|
282 | 282 | |
|
|
283 | 283 | zeniths = numpy.linspace( |
|
|
284 | 284 | 0, self.data.meta['max_range'], data.shape[1]) |
|
|
285 | 285 | if self.mode == 'E': |
|
|
286 | 286 | azimuths = -numpy.radians(self.data.yrange)+numpy.pi/2 |
|
|
287 | 287 | r, theta = numpy.meshgrid(zeniths, azimuths) |
|
|
288 | 288 | x, y = r*numpy.cos(theta)*numpy.cos(numpy.radians(self.data.meta['elevation'])), r*numpy.sin( |
|
|
289 | 289 | theta)*numpy.cos(numpy.radians(self.data.meta['elevation'])) |
|
|
290 | 290 | x = km2deg(x) + self.lon |
|
|
291 | 291 | y = km2deg(y) + self.lat |
|
|
292 | 292 | else: |
|
|
293 | 293 | azimuths = numpy.radians(self.data.yrange) |
|
|
294 | 294 | r, theta = numpy.meshgrid(zeniths, azimuths) |
|
|
295 | 295 | x, y = r*numpy.cos(theta), r*numpy.sin(theta) |
|
|
296 | 296 | self.y = zeniths |
|
|
297 | 297 | |
|
|
298 | 298 | if ax.firsttime: |
|
|
299 | 299 | if self.zlimits is not None: |
|
|
300 | 300 | self.zmin, self.zmax = self.zlimits[n] |
|
|
301 | 301 | ax.plt = ax.pcolormesh( # r, theta, numpy.ma.array(data, mask=numpy.isnan(data)), |
|
|
302 | 302 | x, y, numpy.ma.array(data, mask=numpy.isnan(data)), |
|
|
303 | 303 | vmin=self.zmin, |
|
|
304 | 304 | vmax=self.zmax, |
|
|
305 | 305 | cmap=self.cmaps[n]) |
|
|
306 | 306 | else: |
|
|
307 | 307 | if self.zlimits is not None: |
|
|
308 | 308 | self.zmin, self.zmax = self.zlimits[n] |
|
|
309 | 309 | ax.collections.remove(ax.collections[0]) |
|
|
310 | 310 | ax.plt = ax.pcolormesh( # r, theta, numpy.ma.array(data, mask=numpy.isnan(data)), |
|
|
311 | 311 | x, y, numpy.ma.array(data, mask=numpy.isnan(data)), |
|
|
312 | 312 | vmin=self.zmin, |
|
|
313 | 313 | vmax=self.zmax, |
|
|
314 | 314 | cmap=self.cmaps[n]) |
|
|
315 | 315 | |
|
|
316 | 316 | if self.mode == 'A': |
|
|
317 | 317 | continue |
|
|
318 | 318 | |
|
|
319 | 319 | # plot district names |
|
|
320 | 320 | f = open('/data/workspace/schain_scripts/distrito.csv') |
|
|
321 | 321 | for line in f: |
|
|
322 | 322 | label, lon, lat = [s.strip() for s in line.split(',') if s] |
|
|
323 | 323 | lat = float(lat) |
|
|
324 | 324 | lon = float(lon) |
|
|
325 | 325 | # ax.plot(lon, lat, '.b', ms=2) |
|
|
326 | 326 | ax.text(lon, lat, label.decode('utf8'), ha='center', |
|
|
327 | 327 | va='bottom', size='8', color='black') |
|
|
328 | 328 | |
|
|
329 | 329 | # plot limites |
|
|
330 | 330 | limites = [] |
|
|
331 | 331 | tmp = [] |
|
|
332 | 332 | for line in open('/data/workspace/schain_scripts/lima.csv'): |
|
|
333 | 333 | if '#' in line: |
|
|
334 | 334 | if tmp: |
|
|
335 | 335 | limites.append(tmp) |
|
|
336 | 336 | tmp = [] |
|
|
337 | 337 | continue |
|
|
338 | 338 | values = line.strip().split(',') |
|
|
339 | 339 | tmp.append((float(values[0]), float(values[1]))) |
|
|
340 | 340 | for points in limites: |
|
|
341 | 341 | ax.add_patch( |
|
|
342 | 342 | Polygon(points, ec='k', fc='none', ls='--', lw=0.5)) |
|
|
343 | 343 | |
|
|
344 | 344 | # plot Cuencas |
|
|
345 | 345 | for cuenca in ('rimac', 'lurin', 'mala', 'chillon', 'chilca', 'chancay-huaral'): |
|
|
346 | 346 | f = open('/data/workspace/schain_scripts/{}.csv'.format(cuenca)) |
|
|
347 | 347 | values = [line.strip().split(',') for line in f] |
|
|
348 | 348 | points = [(float(s[0]), float(s[1])) for s in values] |
|
|
349 | 349 | ax.add_patch(Polygon(points, ec='b', fc='none')) |
|
|
350 | 350 | |
|
|
351 | 351 | # plot grid |
|
|
352 | 352 | for r in (15, 30, 45, 60): |
|
|
353 | 353 | ax.add_artist(plt.Circle((self.lon, self.lat), |
|
|
354 | 354 | km2deg(r), color='0.6', fill=False, lw=0.2)) |
|
|
355 | 355 | ax.text( |
|
|
356 | 356 | self.lon + (km2deg(r))*numpy.cos(60*numpy.pi/180), |
|
|
357 | 357 | self.lat + (km2deg(r))*numpy.sin(60*numpy.pi/180), |
|
|
358 | 358 | '{}km'.format(r), |
|
|
359 | 359 | ha='center', va='bottom', size='8', color='0.6', weight='heavy') |
|
|
360 | 360 | |
|
|
361 | 361 | if self.mode == 'E': |
|
|
362 | 362 | title = 'El={}$^\circ$'.format(self.data.meta['elevation']) |
|
|
363 | 363 | label = 'E{:02d}'.format(int(self.data.meta['elevation'])) |
|
|
364 | 364 | else: |
|
|
365 | 365 | title = 'Az={}$^\circ$'.format(self.data.meta['azimuth']) |
|
|
366 | 366 | label = 'A{:02d}'.format(int(self.data.meta['azimuth'])) |
|
|
367 | 367 | |
|
|
368 | 368 | self.save_labels = ['{}-{}'.format(lbl, label) for lbl in self.labels] |
|
|
369 | 369 | self.titles = ['{} {}'.format( |
|
|
370 | 370 | self.data.parameters[x], title) for x in self.channels] |
|
|
371 | 371 | |
|
|
372 | 372 | class WeatherPlot(Plot): |
|
|
373 | 373 | CODE = 'weather' |
|
|
374 | 374 | plot_name = 'weather' |
|
|
375 | 375 | plot_type = 'ppistyle' |
|
|
376 | 376 | buffering = False |
|
|
377 | 377 | |
|
|
378 | 378 | def setup(self): |
|
|
379 | 379 | self.ncols = 1 |
|
|
380 | 380 | self.nrows = 1 |
|
|
381 | 381 | self.width =8 |
|
|
382 | 382 | self.height =8 |
|
|
383 | 383 | self.nplots= 1 |
|
|
384 | 384 | self.ylabel= 'Range [Km]' |
|
|
385 | 385 | self.titles= ['Weather'] |
|
|
386 | 386 | self.colorbar=False |
|
|
387 | 387 | self.ini =0 |
|
|
388 | 388 | self.len_azi =0 |
|
|
389 | 389 | self.buffer_ini = None |
|
|
390 | 390 | self.buffer_azi = None |
|
|
391 | 391 | self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08}) |
|
|
392 | 392 | self.flag =0 |
|
|
393 | 393 | self.indicador= 0 |
|
|
394 | 394 | self.last_data_azi = None |
|
|
395 | 395 | self.val_mean = None |
|
|
396 | 396 | |
|
|
397 | 397 | def update(self, dataOut): |
|
|
398 | 398 | |
|
|
399 | 399 | data = {} |
|
|
400 | 400 | meta = {} |
|
|
401 | 401 | if hasattr(dataOut, 'dataPP_POWER'): |
|
|
402 | 402 | factor = 1 |
|
|
403 | 403 | if hasattr(dataOut, 'nFFTPoints'): |
|
|
404 | 404 | factor = dataOut.normFactor |
|
|
405 | 405 | #print("DIME EL SHAPE PORFAVOR",dataOut.data_360.shape) |
|
|
406 | 406 | data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor)) |
|
|
407 | 407 | data['azi'] = dataOut.data_azi |
|
|
408 | 408 | data['ele'] = dataOut.data_ele |
|
|
409 | 409 | return data, meta |
|
|
410 | 410 | |
|
|
411 | 411 | def get2List(self,angulos): |
|
|
412 | 412 | list1=[] |
|
|
413 | 413 | list2=[] |
|
|
414 | 414 | for i in reversed(range(len(angulos))): |
|
|
415 | 415 | diff_ = angulos[i]-angulos[i-1] |
|
|
416 | 416 | if diff_ >1.5: |
|
|
417 | 417 | list1.append(i-1) |
|
|
418 | 418 | list2.append(diff_) |
|
|
419 | 419 | return list(reversed(list1)),list(reversed(list2)) |
|
|
420 | 420 | |
|
|
421 | 421 | def fixData360(self,list_,ang_): |
|
|
422 | 422 | if list_[0]==-1: |
|
|
423 | 423 | vec = numpy.where(ang_<ang_[0]) |
|
|
424 | 424 | ang_[vec] = ang_[vec]+360 |
|
|
425 | 425 | return ang_ |
|
|
426 | 426 | return ang_ |
|
|
427 | 427 | |
|
|
428 | 428 | def fixData360HL(self,angulos): |
|
|
429 | 429 | vec = numpy.where(angulos>=360) |
|
|
430 | 430 | angulos[vec]=angulos[vec]-360 |
|
|
431 | 431 | return angulos |
|
|
432 | 432 | |
|
|
433 | 433 | def search_pos(self,pos,list_): |
|
|
434 | 434 | for i in range(len(list_)): |
|
|
435 | 435 | if pos == list_[i]: |
|
|
436 | 436 | return True,i |
|
|
437 | 437 | i=None |
|
|
438 | 438 | return False,i |
|
|
439 | 439 | |
|
|
440 | 440 | def fixDataComp(self,ang_,list1_,list2_): |
|
|
441 | 441 | size = len(ang_) |
|
|
442 | 442 | size2 = 0 |
|
|
443 | 443 | for i in range(len(list2_)): |
|
|
444 | 444 | size2=size2+round(list2_[i])-1 |
|
|
445 | 445 | new_size= size+size2 |
|
|
446 | 446 | ang_new = numpy.zeros(new_size) |
|
|
447 | 447 | ang_new2 = numpy.zeros(new_size) |
|
|
448 | 448 | |
|
|
449 | 449 | tmp = 0 |
|
|
450 | 450 | c = 0 |
|
|
451 | 451 | for i in range(len(ang_)): |
|
|
452 | 452 | ang_new[tmp +c] = ang_[i] |
|
|
453 | 453 | ang_new2[tmp+c] = ang_[i] |
|
|
454 | 454 | condition , value = self.search_pos(i,list1_) |
|
|
455 | 455 | if condition: |
|
|
456 | 456 | pos = tmp + c + 1 |
|
|
457 | 457 | for k in range(round(list2_[value])-1): |
|
|
458 | 458 | ang_new[pos+k] = ang_new[pos+k-1]+1 |
|
|
459 | 459 | ang_new2[pos+k] = numpy.nan |
|
|
460 | 460 | tmp = pos +k |
|
|
461 | 461 | c = 0 |
|
|
462 | 462 | c=c+1 |
|
|
463 | 463 | return ang_new,ang_new2 |
|
|
464 | 464 | |
|
|
465 | 465 | def globalCheckPED(self,angulos): |
|
|
466 | 466 | l1,l2 = self.get2List(angulos) |
|
|
467 | 467 | if len(l1)>0: |
|
|
468 | 468 | angulos2 = self.fixData360(list_=l1,ang_=angulos) |
|
|
469 | 469 | l1,l2 = self.get2List(angulos2) |
|
|
470 | 470 | |
|
|
471 | 471 | ang1_,ang2_ = self.fixDataComp(ang_=angulos2,list1_=l1,list2_=l2) |
|
|
472 | 472 | ang1_ = self.fixData360HL(ang1_) |
|
|
473 | 473 | ang2_ = self.fixData360HL(ang2_) |
|
|
474 | 474 | else: |
|
|
475 | 475 | ang1_= angulos |
|
|
476 | 476 | ang2_= angulos |
|
|
477 | 477 | return ang1_,ang2_ |
|
|
478 | 478 | |
|
|
479 | 479 | def analizeDATA(self,data_azi): |
|
|
480 | 480 | list1 = [] |
|
|
481 | 481 | list2 = [] |
|
|
482 | 482 | dat = data_azi |
|
|
483 | 483 | for i in reversed(range(1,len(dat))): |
|
|
484 | 484 | if dat[i]>dat[i-1]: |
|
|
485 | 485 | diff = int(dat[i])-int(dat[i-1]) |
|
|
486 | 486 | else: |
|
|
487 | 487 | diff = 360+int(dat[i])-int(dat[i-1]) |
|
|
488 | 488 | if diff > 1: |
|
|
489 | 489 | list1.append(i-1) |
|
|
490 | 490 | list2.append(diff-1) |
|
|
491 | 491 | return list1,list2 |
|
|
492 | 492 | |
|
|
493 | 493 | def fixDATANEW(self,data_azi,data_weather): |
|
|
494 | 494 | list1,list2 = self.analizeDATA(data_azi) |
|
|
495 | 495 | if len(list1)== 0: |
|
|
496 | 496 | return data_azi,data_weather |
|
|
497 | 497 | else: |
|
|
498 | 498 | resize = 0 |
|
|
499 | 499 | for i in range(len(list2)): |
|
|
500 | 500 | resize= resize + list2[i] |
|
|
501 | 501 | new_data_azi = numpy.resize(data_azi,resize) |
|
|
502 | 502 | new_data_weather= numpy.resize(date_weather,resize) |
|
|
503 | 503 | |
|
|
504 | 504 | for i in range(len(list2)): |
|
|
505 | 505 | j=0 |
|
|
506 | 506 | position=list1[i]+1 |
|
|
507 | 507 | for j in range(list2[i]): |
|
|
508 | 508 | new_data_azi[position+j]=new_data_azi[position+j-1]+1 |
|
|
509 | 509 | return new_data_azi |
|
|
510 | 510 | |
|
|
511 | 511 | def fixDATA(self,data_azi): |
|
|
512 | 512 | data=data_azi |
|
|
513 | 513 | for i in range(len(data)): |
|
|
514 | 514 | if numpy.isnan(data[i]): |
|
|
515 | 515 | data[i]=data[i-1]+1 |
|
|
516 | 516 | return data |
|
|
517 | 517 | |
|
|
518 | 518 | def replaceNAN(self,data_weather,data_azi,val): |
|
|
519 | 519 | data= data_azi |
|
|
520 | 520 | data_T= data_weather |
|
|
521 | 521 | if data.shape[0]> data_T.shape[0]: |
|
|
522 | 522 | data_N = numpy.ones( [data.shape[0],data_T.shape[1]]) |
|
|
523 | 523 | c = 0 |
|
|
524 | 524 | for i in range(len(data)): |
|
|
525 | 525 | if numpy.isnan(data[i]): |
|
|
526 | 526 | data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan |
|
|
527 | 527 | else: |
|
|
528 | 528 | data_N[i,:]=data_T[c,:] |
|
|
529 | 529 | c=c+1 |
|
|
530 | 530 | return data_N |
|
|
531 | 531 | else: |
|
|
532 | 532 | for i in range(len(data)): |
|
|
533 | 533 | if numpy.isnan(data[i]): |
|
|
534 | 534 | data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan |
|
|
535 | 535 | return data_T |
|
|
536 | 536 | |
|
|
537 | 537 | def const_ploteo(self,data_weather,data_azi,step,res): |
|
|
538 | 538 | if self.ini==0: |
|
|
539 | 539 | #------- |
|
|
540 | 540 | n = (360/res)-len(data_azi) |
|
|
541 | 541 | #--------------------- new ------------------------- |
|
|
542 | 542 | data_azi_new ,data_azi_old= self.globalCheckPED(data_azi) |
|
|
543 | 543 | #------------------------ |
|
|
544 | 544 | start = data_azi_new[-1] + res |
|
|
545 | 545 | end = data_azi_new[0] - res |
|
|
546 | 546 | #------ new |
|
|
547 | 547 | self.last_data_azi = end |
|
|
548 | 548 | if start>end: |
|
|
549 | 549 | end = end + 360 |
|
|
550 | 550 | azi_vacia = numpy.linspace(start,end,int(n)) |
|
|
551 | 551 | azi_vacia = numpy.where(azi_vacia>360,azi_vacia-360,azi_vacia) |
|
|
552 | 552 | data_azi = numpy.hstack((data_azi_new,azi_vacia)) |
|
|
553 | 553 | # RADAR |
|
|
554 | 554 | val_mean = numpy.mean(data_weather[:,-1]) |
|
|
555 | 555 | self.val_mean = val_mean |
|
|
556 | 556 | data_weather_cmp = numpy.ones([(360-data_weather.shape[0]),data_weather.shape[1]])*val_mean |
|
|
557 | 557 | data_weather = self.replaceNAN(data_weather=data_weather,data_azi=data_azi_old,val=self.val_mean) |
|
|
558 | 558 | data_weather = numpy.vstack((data_weather,data_weather_cmp)) |
|
|
559 | 559 | else: |
|
|
560 | 560 | # azimuth |
|
|
561 | 561 | flag=0 |
|
|
562 | 562 | start_azi = self.res_azi[0] |
|
|
563 | 563 | #-----------new------------ |
|
|
564 | 564 | data_azi ,data_azi_old= self.globalCheckPED(data_azi) |
|
|
565 | 565 | data_weather = self.replaceNAN(data_weather=data_weather,data_azi=data_azi_old,val=self.val_mean) |
|
|
566 | 566 | #-------------------------- |
|
|
567 | 567 | start = data_azi[0] |
|
|
568 | 568 | end = data_azi[-1] |
|
|
569 | 569 | self.last_data_azi= end |
|
|
570 | 570 | if start< start_azi: |
|
|
571 | 571 | start = start +360 |
|
|
572 | 572 | if end <start_azi: |
|
|
573 | 573 | end = end +360 |
|
|
574 | 574 | |
|
|
575 | 575 | pos_ini = int((start-start_azi)/res) |
|
|
576 | 576 | len_azi = len(data_azi) |
|
|
577 | 577 | if (360-pos_ini)<len_azi: |
|
|
578 | 578 | if pos_ini+1==360: |
|
|
579 | 579 | pos_ini=0 |
|
|
580 | 580 | else: |
|
|
581 | 581 | flag=1 |
|
|
582 | 582 | dif= 360-pos_ini |
|
|
583 | 583 | comp= len_azi-dif |
|
|
584 | 584 | #----------------- |
|
|
585 | 585 | if flag==0: |
|
|
586 | 586 | # AZIMUTH |
|
|
587 | 587 | self.res_azi[pos_ini:pos_ini+len_azi] = data_azi |
|
|
588 | 588 | # RADAR |
|
|
589 | 589 | self.res_weather[pos_ini:pos_ini+len_azi,:] = data_weather |
|
|
590 | 590 | else: |
|
|
591 | 591 | # AZIMUTH |
|
|
592 | 592 | self.res_azi[pos_ini:pos_ini+dif] = data_azi[0:dif] |
|
|
593 | 593 | self.res_azi[0:comp] = data_azi[dif:] |
|
|
594 | 594 | # RADAR |
|
|
595 | 595 | self.res_weather[pos_ini:pos_ini+dif,:] = data_weather[0:dif,:] |
|
|
596 | 596 | self.res_weather[0:comp,:] = data_weather[dif:,:] |
|
|
597 | 597 | flag=0 |
|
|
598 | 598 | data_azi = self.res_azi |
|
|
599 | 599 | data_weather = self.res_weather |
|
|
600 | 600 | |
|
|
601 | 601 | return data_weather,data_azi |
|
|
602 | 602 | |
|
|
603 | 603 | def plot(self): |
|
|
604 | 604 | thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S') |
|
|
605 | 605 | data = self.data[-1] |
|
|
606 | 606 | r = self.data.yrange |
|
|
607 | 607 | delta_height = r[1]-r[0] |
|
|
608 | 608 | r_mask = numpy.where(r>=0)[0] |
|
|
609 | 609 | r = numpy.arange(len(r_mask))*delta_height |
|
|
610 | 610 | self.y = 2*r |
|
|
611 | 611 | # RADAR |
|
|
612 | 612 | #data_weather = data['weather'] |
|
|
613 | 613 | # PEDESTAL |
|
|
614 | 614 | #data_azi = data['azi'] |
|
|
615 | 615 | res = 1 |
|
|
616 | 616 | # STEP |
|
|
617 | 617 | step = (360/(res*data['weather'].shape[0])) |
|
|
618 | 618 | |
|
|
619 | 619 | self.res_weather, self.res_azi = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_azi=data['azi'],step=step,res=res) |
|
|
620 | 620 | self.res_ele = numpy.mean(data['ele']) |
|
|
621 | 621 | ################# PLOTEO ################### |
|
|
622 | 622 | for i,ax in enumerate(self.axes): |
|
|
623 | self.zmin = self.zmin if self.zmin else 20 | |
|
|
624 | self.zmax = self.zmax if self.zmax else 80 | |
|
|
623 | 625 | if ax.firsttime: |
|
|
624 | 626 | plt.clf() |
|
|
625 |
cgax, pm = wrl.vis.plot_ppi(self.res_weather,r=r,az=self.res_azi,fig=self.figures[0], proj='cg', vmin= |
|
|
|
627 | cgax, pm = wrl.vis.plot_ppi(self.res_weather,r=r,az=self.res_azi,fig=self.figures[0], proj='cg', vmin=self.zmin, vmax=self.zmax) | |
|
|
626 | 628 | else: |
|
|
627 | 629 | plt.clf() |
|
|
628 |
cgax, pm = wrl.vis.plot_ppi(self.res_weather,r=r,az=self.res_azi,fig=self.figures[0], proj='cg', vmin= |
|
|
|
630 | cgax, pm = wrl.vis.plot_ppi(self.res_weather,r=r,az=self.res_azi,fig=self.figures[0], proj='cg', vmin=self.zmin, vmax=self.zmax) | |
|
|
629 | 631 | caax = cgax.parasites[0] |
|
|
630 | 632 | paax = cgax.parasites[1] |
|
|
631 | 633 | cbar = plt.gcf().colorbar(pm, pad=0.075) |
|
|
632 | 634 | caax.set_xlabel('x_range [km]') |
|
|
633 | 635 | caax.set_ylabel('y_range [km]') |
|
|
634 |
plt.text(1.0, 1.05, 'Azimuth '+str(thisDatetime)+" Step "+str(self.ini)+ " E |
|
|
|
636 | plt.text(1.0, 1.05, 'Azimuth '+str(thisDatetime)+" Step "+str(self.ini)+ " EL: "+str(round(self.res_ele, 1)), transform=caax.transAxes, va='bottom',ha='right') | |
|
|
635 | 637 | |
|
|
636 | 638 | self.ini= self.ini+1 |
|
|
637 | 639 | |
|
|
638 | 640 | |
|
|
639 | 641 | class WeatherRHIPlot(Plot): |
|
|
640 | 642 | CODE = 'weather' |
|
|
641 | 643 | plot_name = 'weather' |
|
|
642 | 644 | plot_type = 'rhistyle' |
|
|
643 | 645 | buffering = False |
|
|
644 | 646 | data_ele_tmp = None |
|
|
645 | 647 | |
|
|
646 | 648 | def setup(self): |
|
|
647 | 649 | print("********************") |
|
|
648 | 650 | print("********************") |
|
|
649 | 651 | print("********************") |
|
|
650 | 652 | print("SETUP WEATHER PLOT") |
|
|
651 | 653 | self.ncols = 1 |
|
|
652 | 654 | self.nrows = 1 |
|
|
653 | 655 | self.nplots= 1 |
|
|
654 | 656 | self.ylabel= 'Range [Km]' |
|
|
655 | 657 | self.titles= ['Weather'] |
|
|
656 | 658 | if self.channels is not None: |
|
|
657 | 659 | self.nplots = len(self.channels) |
|
|
658 | 660 | self.nrows = len(self.channels) |
|
|
659 | 661 | else: |
|
|
660 | 662 | self.nplots = self.data.shape(self.CODE)[0] |
|
|
661 | 663 | self.nrows = self.nplots |
|
|
662 | 664 | self.channels = list(range(self.nplots)) |
|
|
663 | 665 | print("channels",self.channels) |
|
|
664 | 666 | print("que saldra", self.data.shape(self.CODE)[0]) |
|
|
665 | 667 | self.titles = ['{} Channel {}'.format(self.CODE.upper(), x) for x in range(self.nrows)] |
|
|
666 | 668 | print("self.titles",self.titles) |
|
|
667 | 669 | self.colorbar=False |
|
|
668 |
self.width = |
|
|
|
670 | self.width =12 | |
|
|
669 | 671 | self.height =8 |
|
|
670 | 672 | self.ini =0 |
|
|
671 | 673 | self.len_azi =0 |
|
|
672 | 674 | self.buffer_ini = None |
|
|
673 | 675 | self.buffer_ele = None |
|
|
674 | 676 | self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08}) |
|
|
675 | 677 | self.flag =0 |
|
|
676 | 678 | self.indicador= 0 |
|
|
677 | 679 | self.last_data_ele = None |
|
|
678 | 680 | self.val_mean = None |
|
|
679 | 681 | |
|
|
680 | 682 | def update(self, dataOut): |
|
|
681 | 683 | |
|
|
682 | 684 | data = {} |
|
|
683 | 685 | meta = {} |
|
|
684 | 686 | if hasattr(dataOut, 'dataPP_POWER'): |
|
|
685 | 687 | factor = 1 |
|
|
686 | 688 | if hasattr(dataOut, 'nFFTPoints'): |
|
|
687 | 689 | factor = dataOut.normFactor |
|
|
688 | 690 | print("dataOut",dataOut.data_360.shape) |
|
|
689 | 691 | # |
|
|
690 | 692 | data['weather'] = 10*numpy.log10(dataOut.data_360/(factor)) |
|
|
691 | 693 | # |
|
|
692 | 694 | #data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor)) |
|
|
693 | 695 | data['azi'] = dataOut.data_azi |
|
|
694 | 696 | data['ele'] = dataOut.data_ele |
|
|
695 | 697 | #print("UPDATE") |
|
|
696 | 698 | #print("data[weather]",data['weather'].shape) |
|
|
697 | 699 | #print("data[azi]",data['azi']) |
|
|
698 | 700 | return data, meta |
|
|
699 | 701 | |
|
|
700 | 702 | def get2List(self,angulos): |
|
|
701 | 703 | list1=[] |
|
|
702 | 704 | list2=[] |
|
|
703 | 705 | for i in reversed(range(len(angulos))): |
|
|
704 | 706 | if not i==0:#el caso de i=0 evalula el primero de la lista con el ultimo y no es relevante |
|
|
705 | 707 | diff_ = angulos[i]-angulos[i-1] |
|
|
706 | 708 | if abs(diff_) >1.5: |
|
|
707 | 709 | list1.append(i-1) |
|
|
708 | 710 | list2.append(diff_) |
|
|
709 | 711 | return list(reversed(list1)),list(reversed(list2)) |
|
|
710 | 712 | |
|
|
711 | 713 | def fixData90(self,list_,ang_): |
|
|
712 | 714 | if list_[0]==-1: |
|
|
713 | 715 | vec = numpy.where(ang_<ang_[0]) |
|
|
714 | 716 | ang_[vec] = ang_[vec]+90 |
|
|
715 | 717 | return ang_ |
|
|
716 | 718 | return ang_ |
|
|
717 | 719 | |
|
|
718 | 720 | def fixData90HL(self,angulos): |
|
|
719 | 721 | vec = numpy.where(angulos>=90) |
|
|
720 | 722 | angulos[vec]=angulos[vec]-90 |
|
|
721 | 723 | return angulos |
|
|
722 | 724 | |
|
|
723 | 725 | |
|
|
724 | 726 | def search_pos(self,pos,list_): |
|
|
725 | 727 | for i in range(len(list_)): |
|
|
726 | 728 | if pos == list_[i]: |
|
|
727 | 729 | return True,i |
|
|
728 | 730 | i=None |
|
|
729 | 731 | return False,i |
|
|
730 | 732 | |
|
|
731 | 733 | def fixDataComp(self,ang_,list1_,list2_,tipo_case): |
|
|
732 | 734 | size = len(ang_) |
|
|
733 | 735 | size2 = 0 |
|
|
734 | 736 | for i in range(len(list2_)): |
|
|
735 | 737 | size2=size2+round(abs(list2_[i]))-1 |
|
|
736 | 738 | new_size= size+size2 |
|
|
737 | 739 | ang_new = numpy.zeros(new_size) |
|
|
738 | 740 | ang_new2 = numpy.zeros(new_size) |
|
|
739 | 741 | |
|
|
740 | 742 | tmp = 0 |
|
|
741 | 743 | c = 0 |
|
|
742 | 744 | for i in range(len(ang_)): |
|
|
743 | 745 | ang_new[tmp +c] = ang_[i] |
|
|
744 | 746 | ang_new2[tmp+c] = ang_[i] |
|
|
745 | 747 | condition , value = self.search_pos(i,list1_) |
|
|
746 | 748 | if condition: |
|
|
747 | 749 | pos = tmp + c + 1 |
|
|
748 | 750 | for k in range(round(abs(list2_[value]))-1): |
|
|
749 | 751 | if tipo_case==0 or tipo_case==3:#subida |
|
|
750 | 752 | ang_new[pos+k] = ang_new[pos+k-1]+1 |
|
|
751 | 753 | ang_new2[pos+k] = numpy.nan |
|
|
752 | 754 | elif tipo_case==1 or tipo_case==2:#bajada |
|
|
753 | 755 | ang_new[pos+k] = ang_new[pos+k-1]-1 |
|
|
754 | 756 | ang_new2[pos+k] = numpy.nan |
|
|
755 | 757 | |
|
|
756 | 758 | tmp = pos +k |
|
|
757 | 759 | c = 0 |
|
|
758 | 760 | c=c+1 |
|
|
759 | 761 | return ang_new,ang_new2 |
|
|
760 | 762 | |
|
|
761 | 763 | def globalCheckPED(self,angulos,tipo_case): |
|
|
762 | 764 | l1,l2 = self.get2List(angulos) |
|
|
763 | 765 | ##print("l1",l1) |
|
|
764 | 766 | ##print("l2",l2) |
|
|
765 | 767 | if len(l1)>0: |
|
|
766 | 768 | #angulos2 = self.fixData90(list_=l1,ang_=angulos) |
|
|
767 | 769 | #l1,l2 = self.get2List(angulos2) |
|
|
768 | 770 | ang1_,ang2_ = self.fixDataComp(ang_=angulos,list1_=l1,list2_=l2,tipo_case=tipo_case) |
|
|
769 | 771 | #ang1_ = self.fixData90HL(ang1_) |
|
|
770 | 772 | #ang2_ = self.fixData90HL(ang2_) |
|
|
771 | 773 | else: |
|
|
772 | 774 | ang1_= angulos |
|
|
773 | 775 | ang2_= angulos |
|
|
774 | 776 | return ang1_,ang2_ |
|
|
775 | 777 | |
|
|
776 | 778 | |
|
|
777 | 779 | def replaceNAN(self,data_weather,data_ele,val): |
|
|
778 | 780 | data= data_ele |
|
|
779 | 781 | data_T= data_weather |
|
|
780 | 782 | if data.shape[0]> data_T.shape[0]: |
|
|
781 | 783 | data_N = numpy.ones( [data.shape[0],data_T.shape[1]]) |
|
|
782 | 784 | c = 0 |
|
|
783 | 785 | for i in range(len(data)): |
|
|
784 | 786 | if numpy.isnan(data[i]): |
|
|
785 | 787 | data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan |
|
|
786 | 788 | else: |
|
|
787 | 789 | data_N[i,:]=data_T[c,:] |
|
|
788 | 790 | c=c+1 |
|
|
789 | 791 | return data_N |
|
|
790 | 792 | else: |
|
|
791 | 793 | for i in range(len(data)): |
|
|
792 | 794 | if numpy.isnan(data[i]): |
|
|
793 | 795 | data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan |
|
|
794 | 796 | return data_T |
|
|
795 | 797 | |
|
|
796 | 798 | def check_case(self,data_ele,ang_max,ang_min): |
|
|
797 | 799 | start = data_ele[0] |
|
|
798 | 800 | end = data_ele[-1] |
|
|
799 | 801 | number = (end-start) |
|
|
800 | 802 | len_ang=len(data_ele) |
|
|
801 | 803 | print("start",start) |
|
|
802 | 804 | print("end",end) |
|
|
803 | 805 | print("number",number) |
|
|
804 | 806 | |
|
|
805 | 807 | print("len_ang",len_ang) |
|
|
806 | 808 | |
|
|
807 | 809 | #exit(1) |
|
|
808 | 810 | |
|
|
809 | 811 | if start<end and (round(abs(number)+1)>=len_ang or (numpy.argmin(data_ele)==0)):#caso subida |
|
|
810 | 812 | return 0 |
|
|
811 | 813 | #elif start>end and (round(abs(number)+1)>=len_ang or(numpy.argmax(data_ele)==0)):#caso bajada |
|
|
812 | 814 | # return 1 |
|
|
813 | 815 | elif round(abs(number)+1)>=len_ang and (start>end or(numpy.argmax(data_ele)==0)):#caso bajada |
|
|
814 | 816 | return 1 |
|
|
815 | 817 | elif round(abs(number)+1)<len_ang and data_ele[-2]>data_ele[-1]:# caso BAJADA CAMBIO ANG MAX |
|
|
816 | 818 | return 2 |
|
|
817 | 819 | elif round(abs(number)+1)<len_ang and data_ele[-2]<data_ele[-1] :# caso SUBIDA CAMBIO ANG MIN |
|
|
818 | 820 | return 3 |
|
|
819 | 821 | |
|
|
820 | 822 | |
|
|
821 | 823 | def const_ploteo(self,val_ch,data_weather,data_ele,step,res,ang_max,ang_min): |
|
|
822 | 824 | ang_max= ang_max |
|
|
823 | 825 | ang_min= ang_min |
|
|
824 | 826 | data_weather=data_weather |
|
|
825 | 827 | val_ch=val_ch |
|
|
826 | 828 | ##print("*********************DATA WEATHER**************************************") |
|
|
827 | 829 | ##print(data_weather) |
|
|
828 | 830 | if self.ini==0: |
|
|
829 | 831 | ''' |
|
|
830 | 832 | print("**********************************************") |
|
|
831 | 833 | print("**********************************************") |
|
|
832 | 834 | print("***************ini**************") |
|
|
833 | 835 | print("**********************************************") |
|
|
834 | 836 | print("**********************************************") |
|
|
835 | 837 | ''' |
|
|
836 | 838 | #print("data_ele",data_ele) |
|
|
837 | 839 | #---------------------------------------------------------- |
|
|
838 | 840 | tipo_case = self.check_case(data_ele,ang_max,ang_min) |
|
|
839 | 841 | print("check_case",tipo_case) |
|
|
840 | 842 | #exit(1) |
|
|
841 | 843 | #--------------------- new ------------------------- |
|
|
842 | 844 | data_ele_new ,data_ele_old= self.globalCheckPED(data_ele,tipo_case) |
|
|
843 | 845 | |
|
|
844 | 846 | #-------------------------CAMBIOS RHI--------------------------------- |
|
|
845 | 847 | start= ang_min |
|
|
846 | 848 | end = ang_max |
|
|
847 | 849 | n= (ang_max-ang_min)/res |
|
|
848 | 850 | #------ new |
|
|
849 | 851 | self.start_data_ele = data_ele_new[0] |
|
|
850 | 852 | self.end_data_ele = data_ele_new[-1] |
|
|
851 | 853 | if tipo_case==0 or tipo_case==3: # SUBIDA |
|
|
852 | 854 | n1= round(self.start_data_ele)- start |
|
|
853 | 855 | n2= end - round(self.end_data_ele) |
|
|
854 | 856 | print(self.start_data_ele) |
|
|
855 | 857 | print(self.end_data_ele) |
|
|
856 | 858 | if n1>0: |
|
|
857 | 859 | ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1) |
|
|
858 | 860 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
859 | 861 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
860 | 862 | print("ele1_nan",ele1_nan.shape) |
|
|
861 | 863 | print("data_ele_old",data_ele_old.shape) |
|
|
862 | 864 | data_ele_old = numpy.hstack((ele1_nan,data_ele_old)) |
|
|
863 | 865 | if n2>0: |
|
|
864 | 866 | ele2= numpy.linspace(self.end_data_ele+1,end,n2) |
|
|
865 | 867 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
866 | 868 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
867 | 869 | print("ele2_nan",ele2_nan.shape) |
|
|
868 | 870 | print("data_ele_old",data_ele_old.shape) |
|
|
869 | 871 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
870 | 872 | |
|
|
871 | 873 | if tipo_case==1 or tipo_case==2: # BAJADA |
|
|
872 | 874 | data_ele_new = data_ele_new[::-1] # reversa |
|
|
873 | 875 | data_ele_old = data_ele_old[::-1]# reversa |
|
|
874 | 876 | data_weather = data_weather[::-1,:]# reversa |
|
|
875 | 877 | vec= numpy.where(data_ele_new<ang_max) |
|
|
876 | 878 | data_ele_new = data_ele_new[vec] |
|
|
877 | 879 | data_ele_old = data_ele_old[vec] |
|
|
878 | 880 | data_weather = data_weather[vec[0]] |
|
|
879 | 881 | vec2= numpy.where(0<data_ele_new) |
|
|
880 | 882 | data_ele_new = data_ele_new[vec2] |
|
|
881 | 883 | data_ele_old = data_ele_old[vec2] |
|
|
882 | 884 | data_weather = data_weather[vec2[0]] |
|
|
883 | 885 | self.start_data_ele = data_ele_new[0] |
|
|
884 | 886 | self.end_data_ele = data_ele_new[-1] |
|
|
885 | 887 | |
|
|
886 | 888 | n1= round(self.start_data_ele)- start |
|
|
887 | 889 | n2= end - round(self.end_data_ele)-1 |
|
|
888 | 890 | print(self.start_data_ele) |
|
|
889 | 891 | print(self.end_data_ele) |
|
|
890 | 892 | if n1>0: |
|
|
891 | 893 | ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1) |
|
|
892 | 894 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
893 | 895 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
894 | 896 | data_ele_old = numpy.hstack((ele1_nan,data_ele_old)) |
|
|
895 | 897 | if n2>0: |
|
|
896 | 898 | ele2= numpy.linspace(self.end_data_ele+1,end,n2) |
|
|
897 | 899 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
898 | 900 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
899 | 901 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
900 | 902 | # RADAR |
|
|
901 | 903 | # NOTA data_ele y data_weather es la variable que retorna |
|
|
902 | 904 | val_mean = numpy.mean(data_weather[:,-1]) |
|
|
903 | 905 | self.val_mean = val_mean |
|
|
904 | 906 | data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
905 | 907 | self.data_ele_tmp[val_ch]= data_ele_old |
|
|
906 | 908 | else: |
|
|
907 | 909 | #print("**********************************************") |
|
|
908 | 910 | #print("****************VARIABLE**********************") |
|
|
909 | 911 | #-------------------------CAMBIOS RHI--------------------------------- |
|
|
910 | 912 | #--------------------------------------------------------------------- |
|
|
911 | 913 | ##print("INPUT data_ele",data_ele) |
|
|
912 | 914 | flag=0 |
|
|
913 | 915 | start_ele = self.res_ele[0] |
|
|
914 | 916 | tipo_case = self.check_case(data_ele,ang_max,ang_min) |
|
|
915 | 917 | #print("TIPO DE DATA",tipo_case) |
|
|
916 | 918 | #-----------new------------ |
|
|
917 | 919 | data_ele ,data_ele_old = self.globalCheckPED(data_ele,tipo_case) |
|
|
918 | 920 | data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
919 | 921 | |
|
|
920 | 922 | #-------------------------------NEW RHI ITERATIVO------------------------- |
|
|
921 | 923 | |
|
|
922 | 924 | if tipo_case==0 : # SUBIDA |
|
|
923 | 925 | vec = numpy.where(data_ele<ang_max) |
|
|
924 | 926 | data_ele = data_ele[vec] |
|
|
925 | 927 | data_ele_old = data_ele_old[vec] |
|
|
926 | 928 | data_weather = data_weather[vec[0]] |
|
|
927 | 929 | |
|
|
928 | 930 | vec2 = numpy.where(0<data_ele) |
|
|
929 | 931 | data_ele= data_ele[vec2] |
|
|
930 | 932 | data_ele_old= data_ele_old[vec2] |
|
|
931 | 933 | ##print(data_ele_new) |
|
|
932 | 934 | data_weather= data_weather[vec2[0]] |
|
|
933 | 935 | |
|
|
934 | 936 | new_i_ele = int(round(data_ele[0])) |
|
|
935 | 937 | new_f_ele = int(round(data_ele[-1])) |
|
|
936 | 938 | #print(new_i_ele) |
|
|
937 | 939 | #print(new_f_ele) |
|
|
938 | 940 | #print(data_ele,len(data_ele)) |
|
|
939 | 941 | #print(data_ele_old,len(data_ele_old)) |
|
|
940 | 942 | if new_i_ele< 2: |
|
|
941 | 943 | self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan |
|
|
942 | 944 | self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean) |
|
|
943 | 945 | self.data_ele_tmp[val_ch][new_i_ele:new_i_ele+len(data_ele)]=data_ele_old |
|
|
944 | 946 | self.res_ele[new_i_ele:new_i_ele+len(data_ele)]= data_ele |
|
|
945 | 947 | self.res_weather[val_ch][new_i_ele:new_i_ele+len(data_ele),:]= data_weather |
|
|
946 | 948 | data_ele = self.res_ele |
|
|
947 | 949 | data_weather = self.res_weather[val_ch] |
|
|
948 | 950 | |
|
|
949 | 951 | elif tipo_case==1 : #BAJADA |
|
|
950 | 952 | data_ele = data_ele[::-1] # reversa |
|
|
951 | 953 | data_ele_old = data_ele_old[::-1]# reversa |
|
|
952 | 954 | data_weather = data_weather[::-1,:]# reversa |
|
|
953 | 955 | vec= numpy.where(data_ele<ang_max) |
|
|
954 | 956 | data_ele = data_ele[vec] |
|
|
955 | 957 | data_ele_old = data_ele_old[vec] |
|
|
956 | 958 | data_weather = data_weather[vec[0]] |
|
|
957 | 959 | vec2= numpy.where(0<data_ele) |
|
|
958 | 960 | data_ele = data_ele[vec2] |
|
|
959 | 961 | data_ele_old = data_ele_old[vec2] |
|
|
960 | 962 | data_weather = data_weather[vec2[0]] |
|
|
961 | 963 | |
|
|
962 | 964 | |
|
|
963 | 965 | new_i_ele = int(round(data_ele[0])) |
|
|
964 | 966 | new_f_ele = int(round(data_ele[-1])) |
|
|
965 | 967 | #print(data_ele) |
|
|
966 | 968 | #print(ang_max) |
|
|
967 | 969 | #print(data_ele_old) |
|
|
968 | 970 | if new_i_ele <= 1: |
|
|
969 | 971 | new_i_ele = 1 |
|
|
970 | 972 | if round(data_ele[-1])>=ang_max-1: |
|
|
971 | 973 | self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan |
|
|
972 | 974 | self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean) |
|
|
973 | 975 | self.data_ele_tmp[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1]=data_ele_old |
|
|
974 | 976 | self.res_ele[new_i_ele-1:new_i_ele+len(data_ele)-1]= data_ele |
|
|
975 | 977 | self.res_weather[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1,:]= data_weather |
|
|
976 | 978 | data_ele = self.res_ele |
|
|
977 | 979 | data_weather = self.res_weather[val_ch] |
|
|
978 | 980 | |
|
|
979 | 981 | elif tipo_case==2: #bajada |
|
|
980 | 982 | vec = numpy.where(data_ele<ang_max) |
|
|
981 | 983 | data_ele = data_ele[vec] |
|
|
982 | 984 | data_weather= data_weather[vec[0]] |
|
|
983 | 985 | |
|
|
984 | 986 | len_vec = len(vec) |
|
|
985 | 987 | data_ele_new = data_ele[::-1] # reversa |
|
|
986 | 988 | data_weather = data_weather[::-1,:] |
|
|
987 | 989 | new_i_ele = int(data_ele_new[0]) |
|
|
988 | 990 | new_f_ele = int(data_ele_new[-1]) |
|
|
989 | 991 | |
|
|
990 | 992 | n1= new_i_ele- ang_min |
|
|
991 | 993 | n2= ang_max - new_f_ele-1 |
|
|
992 | 994 | if n1>0: |
|
|
993 | 995 | ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1) |
|
|
994 | 996 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
995 | 997 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
996 | 998 | data_ele_old = numpy.hstack((ele1_nan,data_ele_new)) |
|
|
997 | 999 | if n2>0: |
|
|
998 | 1000 | ele2= numpy.linspace(new_f_ele+1,ang_max,n2) |
|
|
999 | 1001 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
1000 | 1002 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
1001 | 1003 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
1002 | 1004 | |
|
|
1003 | 1005 | self.data_ele_tmp[val_ch] = data_ele_old |
|
|
1004 | 1006 | self.res_ele = data_ele |
|
|
1005 | 1007 | self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
1006 | 1008 | data_ele = self.res_ele |
|
|
1007 | 1009 | data_weather = self.res_weather[val_ch] |
|
|
1008 | 1010 | |
|
|
1009 | 1011 | elif tipo_case==3:#subida |
|
|
1010 | 1012 | vec = numpy.where(0<data_ele) |
|
|
1011 | 1013 | data_ele= data_ele[vec] |
|
|
1012 | 1014 | data_ele_new = data_ele |
|
|
1013 | 1015 | data_ele_old= data_ele_old[vec] |
|
|
1014 | 1016 | data_weather= data_weather[vec[0]] |
|
|
1015 | 1017 | pos_ini = numpy.argmin(data_ele) |
|
|
1016 | 1018 | if pos_ini>0: |
|
|
1017 | 1019 | len_vec= len(data_ele) |
|
|
1018 | 1020 | vec3 = numpy.linspace(pos_ini,len_vec-1,len_vec-pos_ini).astype(int) |
|
|
1019 | 1021 | #print(vec3) |
|
|
1020 | 1022 | data_ele= data_ele[vec3] |
|
|
1021 | 1023 | data_ele_new = data_ele |
|
|
1022 | 1024 | data_ele_old= data_ele_old[vec3] |
|
|
1023 | 1025 | data_weather= data_weather[vec3] |
|
|
1024 | 1026 | |
|
|
1025 | 1027 | new_i_ele = int(data_ele_new[0]) |
|
|
1026 | 1028 | new_f_ele = int(data_ele_new[-1]) |
|
|
1027 | 1029 | n1= new_i_ele- ang_min |
|
|
1028 | 1030 | n2= ang_max - new_f_ele-1 |
|
|
1029 | 1031 | if n1>0: |
|
|
1030 | 1032 | ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1) |
|
|
1031 | 1033 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
1032 | 1034 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
1033 | 1035 | data_ele_old = numpy.hstack((ele1_nan,data_ele_new)) |
|
|
1034 | 1036 | if n2>0: |
|
|
1035 | 1037 | ele2= numpy.linspace(new_f_ele+1,ang_max,n2) |
|
|
1036 | 1038 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
1037 | 1039 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
1038 | 1040 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
1039 | 1041 | |
|
|
1040 | 1042 | self.data_ele_tmp[val_ch] = data_ele_old |
|
|
1041 | 1043 | self.res_ele = data_ele |
|
|
1042 | 1044 | self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
1043 | 1045 | data_ele = self.res_ele |
|
|
1044 | 1046 | data_weather = self.res_weather[val_ch] |
|
|
1045 | 1047 | #print("self.data_ele_tmp",self.data_ele_tmp) |
|
|
1046 | 1048 | return data_weather,data_ele |
|
|
1047 | 1049 | |
|
|
1048 | 1050 | |
|
|
1049 | 1051 | def plot(self): |
|
|
1050 | 1052 | thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S') |
|
|
1051 | 1053 | data = self.data[-1] |
|
|
1052 | 1054 | r = self.data.yrange |
|
|
1053 | 1055 | delta_height = r[1]-r[0] |
|
|
1054 | 1056 | r_mask = numpy.where(r>=0)[0] |
|
|
1055 | 1057 | ##print("delta_height",delta_height) |
|
|
1056 | 1058 | #print("r_mask",r_mask,len(r_mask)) |
|
|
1057 | 1059 | r = numpy.arange(len(r_mask))*delta_height |
|
|
1058 | 1060 | self.y = 2*r |
|
|
1059 | 1061 | res = 1 |
|
|
1060 | 1062 | ###print("data['weather'].shape[0]",data['weather'].shape[0]) |
|
|
1061 | 1063 | ang_max = self.ang_max |
|
|
1062 | 1064 | ang_min = self.ang_min |
|
|
1063 | 1065 | var_ang =ang_max - ang_min |
|
|
1064 | 1066 | step = (int(var_ang)/(res*data['weather'].shape[0])) |
|
|
1065 | 1067 | ###print("step",step) |
|
|
1066 | 1068 | #-------------------------------------------------------- |
|
|
1067 | 1069 | ##print('weather',data['weather'].shape) |
|
|
1068 | 1070 | ##print('ele',data['ele'].shape) |
|
|
1069 | 1071 | |
|
|
1070 | 1072 | ###self.res_weather, self.res_ele = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min) |
|
|
1071 | 1073 | ###self.res_azi = numpy.mean(data['azi']) |
|
|
1072 | 1074 | ###print("self.res_ele",self.res_ele) |
|
|
1073 | 1075 | plt.clf() |
|
|
1074 | 1076 | subplots = [121, 122] |
|
|
1077 | cg={'angular_spacing': 20.} | |
|
|
1075 | 1078 | if self.ini==0: |
|
|
1076 | 1079 | self.data_ele_tmp = numpy.ones([self.nplots,int(var_ang)])*numpy.nan |
|
|
1077 | 1080 | self.res_weather= numpy.ones([self.nplots,int(var_ang),len(r_mask)])*numpy.nan |
|
|
1078 | 1081 | print("SHAPE",self.data_ele_tmp.shape) |
|
|
1079 | 1082 | |
|
|
1080 | 1083 | for i,ax in enumerate(self.axes): |
|
|
1081 | 1084 | self.res_weather[i], self.res_ele = self.const_ploteo(val_ch=i, data_weather=data['weather'][i][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min) |
|
|
1082 | 1085 | self.res_azi = numpy.mean(data['azi']) |
|
|
1083 | 1086 | if i==0: |
|
|
1084 | 1087 | print("*****************************************************************************to plot**************************",self.res_weather[i].shape) |
|
|
1088 | self.zmin = self.zmin if self.zmin else 20 | |
|
|
1089 | self.zmax = self.zmax if self.zmax else 80 | |
|
|
1085 | 1090 | if ax.firsttime: |
|
|
1086 | 1091 | #plt.clf() |
|
|
1087 |
cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj= |
|
|
|
1092 | cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj=cg,vmin=self.zmin, vmax=self.zmax) | |
|
|
1088 | 1093 | #fig=self.figures[0] |
|
|
1089 | 1094 | else: |
|
|
1090 | 1095 | #plt.clf() |
|
|
1091 | 1096 | if i==0: |
|
|
1092 | 1097 | print(self.res_weather[i]) |
|
|
1093 | 1098 | print(self.res_ele) |
|
|
1094 |
cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj= |
|
|
|
1099 | cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj=cg,vmin=self.zmin, vmax=self.zmax) | |
|
|
1095 | 1100 | caax = cgax.parasites[0] |
|
|
1096 | 1101 | paax = cgax.parasites[1] |
|
|
1097 | 1102 | cbar = plt.gcf().colorbar(pm, pad=0.075) |
|
|
1098 | 1103 | caax.set_xlabel('x_range [km]') |
|
|
1099 | 1104 | caax.set_ylabel('y_range [km]') |
|
|
1100 | 1105 | plt.text(1.0, 1.05, 'Elevacion '+str(thisDatetime)+" Step "+str(self.ini)+ " Azi: "+str(round(self.res_azi,2)), transform=caax.transAxes, va='bottom',ha='right') |
|
|
1101 | 1106 | print("***************************self.ini****************************",self.ini) |
|
|
1102 | 1107 | self.ini= self.ini+1 |
|
|
1103 | 1108 | |
|
|
1104 | 1109 | class WeatherRHI_vRF2_Plot(Plot): |
|
|
1105 | 1110 | CODE = 'weather' |
|
|
1106 | 1111 | plot_name = 'weather' |
|
|
1107 | 1112 | plot_type = 'rhistyle' |
|
|
1108 | 1113 | buffering = False |
|
|
1109 | 1114 | data_ele_tmp = None |
|
|
1110 | 1115 | |
|
|
1111 | 1116 | def setup(self): |
|
|
1112 | 1117 | print("********************") |
|
|
1113 | 1118 | print("********************") |
|
|
1114 | 1119 | print("********************") |
|
|
1115 | 1120 | print("SETUP WEATHER PLOT") |
|
|
1116 | 1121 | self.ncols = 1 |
|
|
1117 | 1122 | self.nrows = 1 |
|
|
1118 | 1123 | self.nplots= 1 |
|
|
1119 | 1124 | self.ylabel= 'Range [Km]' |
|
|
1120 | 1125 | self.titles= ['Weather'] |
|
|
1121 | 1126 | if self.channels is not None: |
|
|
1122 | 1127 | self.nplots = len(self.channels) |
|
|
1123 | 1128 | self.nrows = len(self.channels) |
|
|
1124 | 1129 | else: |
|
|
1125 | 1130 | self.nplots = self.data.shape(self.CODE)[0] |
|
|
1126 | 1131 | self.nrows = self.nplots |
|
|
1127 | 1132 | self.channels = list(range(self.nplots)) |
|
|
1128 | 1133 | print("channels",self.channels) |
|
|
1129 | 1134 | print("que saldra", self.data.shape(self.CODE)[0]) |
|
|
1130 | 1135 | self.titles = ['{} Channel {}'.format(self.CODE.upper(), x) for x in range(self.nrows)] |
|
|
1131 | 1136 | print("self.titles",self.titles) |
|
|
1132 | 1137 | self.colorbar=False |
|
|
1133 | 1138 | self.width =8 |
|
|
1134 | 1139 | self.height =8 |
|
|
1135 | 1140 | self.ini =0 |
|
|
1136 | 1141 | self.len_azi =0 |
|
|
1137 | 1142 | self.buffer_ini = None |
|
|
1138 | 1143 | self.buffer_ele = None |
|
|
1139 | 1144 | self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08}) |
|
|
1140 | 1145 | self.flag =0 |
|
|
1141 | 1146 | self.indicador= 0 |
|
|
1142 | 1147 | self.last_data_ele = None |
|
|
1143 | 1148 | self.val_mean = None |
|
|
1144 | 1149 | |
|
|
1145 | 1150 | def update(self, dataOut): |
|
|
1146 | 1151 | |
|
|
1147 | 1152 | data = {} |
|
|
1148 | 1153 | meta = {} |
|
|
1149 | 1154 | if hasattr(dataOut, 'dataPP_POWER'): |
|
|
1150 | 1155 | factor = 1 |
|
|
1151 | 1156 | if hasattr(dataOut, 'nFFTPoints'): |
|
|
1152 | 1157 | factor = dataOut.normFactor |
|
|
1153 | 1158 | print("dataOut",dataOut.data_360.shape) |
|
|
1154 | 1159 | # |
|
|
1155 | 1160 | data['weather'] = 10*numpy.log10(dataOut.data_360/(factor)) |
|
|
1156 | 1161 | # |
|
|
1157 | 1162 | #data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor)) |
|
|
1158 | 1163 | data['azi'] = dataOut.data_azi |
|
|
1159 | 1164 | data['ele'] = dataOut.data_ele |
|
|
1160 | 1165 | data['case_flag'] = dataOut.case_flag |
|
|
1161 | 1166 | #print("UPDATE") |
|
|
1162 | 1167 | #print("data[weather]",data['weather'].shape) |
|
|
1163 | 1168 | #print("data[azi]",data['azi']) |
|
|
1164 | 1169 | return data, meta |
|
|
1165 | 1170 | |
|
|
1166 | 1171 | def get2List(self,angulos): |
|
|
1167 | 1172 | list1=[] |
|
|
1168 | 1173 | list2=[] |
|
|
1169 | 1174 | for i in reversed(range(len(angulos))): |
|
|
1170 | 1175 | if not i==0:#el caso de i=0 evalula el primero de la lista con el ultimo y no es relevante |
|
|
1171 | 1176 | diff_ = angulos[i]-angulos[i-1] |
|
|
1172 | 1177 | if abs(diff_) >1.5: |
|
|
1173 | 1178 | list1.append(i-1) |
|
|
1174 | 1179 | list2.append(diff_) |
|
|
1175 | 1180 | return list(reversed(list1)),list(reversed(list2)) |
|
|
1176 | 1181 | |
|
|
1177 | 1182 | def fixData90(self,list_,ang_): |
|
|
1178 | 1183 | if list_[0]==-1: |
|
|
1179 | 1184 | vec = numpy.where(ang_<ang_[0]) |
|
|
1180 | 1185 | ang_[vec] = ang_[vec]+90 |
|
|
1181 | 1186 | return ang_ |
|
|
1182 | 1187 | return ang_ |
|
|
1183 | 1188 | |
|
|
1184 | 1189 | def fixData90HL(self,angulos): |
|
|
1185 | 1190 | vec = numpy.where(angulos>=90) |
|
|
1186 | 1191 | angulos[vec]=angulos[vec]-90 |
|
|
1187 | 1192 | return angulos |
|
|
1188 | 1193 | |
|
|
1189 | 1194 | |
|
|
1190 | 1195 | def search_pos(self,pos,list_): |
|
|
1191 | 1196 | for i in range(len(list_)): |
|
|
1192 | 1197 | if pos == list_[i]: |
|
|
1193 | 1198 | return True,i |
|
|
1194 | 1199 | i=None |
|
|
1195 | 1200 | return False,i |
|
|
1196 | 1201 | |
|
|
1197 | 1202 | def fixDataComp(self,ang_,list1_,list2_,tipo_case): |
|
|
1198 | 1203 | size = len(ang_) |
|
|
1199 | 1204 | size2 = 0 |
|
|
1200 | 1205 | for i in range(len(list2_)): |
|
|
1201 | 1206 | size2=size2+round(abs(list2_[i]))-1 |
|
|
1202 | 1207 | new_size= size+size2 |
|
|
1203 | 1208 | ang_new = numpy.zeros(new_size) |
|
|
1204 | 1209 | ang_new2 = numpy.zeros(new_size) |
|
|
1205 | 1210 | |
|
|
1206 | 1211 | tmp = 0 |
|
|
1207 | 1212 | c = 0 |
|
|
1208 | 1213 | for i in range(len(ang_)): |
|
|
1209 | 1214 | ang_new[tmp +c] = ang_[i] |
|
|
1210 | 1215 | ang_new2[tmp+c] = ang_[i] |
|
|
1211 | 1216 | condition , value = self.search_pos(i,list1_) |
|
|
1212 | 1217 | if condition: |
|
|
1213 | 1218 | pos = tmp + c + 1 |
|
|
1214 | 1219 | for k in range(round(abs(list2_[value]))-1): |
|
|
1215 | 1220 | if tipo_case==0 or tipo_case==3:#subida |
|
|
1216 | 1221 | ang_new[pos+k] = ang_new[pos+k-1]+1 |
|
|
1217 | 1222 | ang_new2[pos+k] = numpy.nan |
|
|
1218 | 1223 | elif tipo_case==1 or tipo_case==2:#bajada |
|
|
1219 | 1224 | ang_new[pos+k] = ang_new[pos+k-1]-1 |
|
|
1220 | 1225 | ang_new2[pos+k] = numpy.nan |
|
|
1221 | 1226 | |
|
|
1222 | 1227 | tmp = pos +k |
|
|
1223 | 1228 | c = 0 |
|
|
1224 | 1229 | c=c+1 |
|
|
1225 | 1230 | return ang_new,ang_new2 |
|
|
1226 | 1231 | |
|
|
1227 | 1232 | def globalCheckPED(self,angulos,tipo_case): |
|
|
1228 | 1233 | l1,l2 = self.get2List(angulos) |
|
|
1229 | 1234 | ##print("l1",l1) |
|
|
1230 | 1235 | ##print("l2",l2) |
|
|
1231 | 1236 | if len(l1)>0: |
|
|
1232 | 1237 | #angulos2 = self.fixData90(list_=l1,ang_=angulos) |
|
|
1233 | 1238 | #l1,l2 = self.get2List(angulos2) |
|
|
1234 | 1239 | ang1_,ang2_ = self.fixDataComp(ang_=angulos,list1_=l1,list2_=l2,tipo_case=tipo_case) |
|
|
1235 | 1240 | #ang1_ = self.fixData90HL(ang1_) |
|
|
1236 | 1241 | #ang2_ = self.fixData90HL(ang2_) |
|
|
1237 | 1242 | else: |
|
|
1238 | 1243 | ang1_= angulos |
|
|
1239 | 1244 | ang2_= angulos |
|
|
1240 | 1245 | return ang1_,ang2_ |
|
|
1241 | 1246 | |
|
|
1242 | 1247 | |
|
|
1243 | 1248 | def replaceNAN(self,data_weather,data_ele,val): |
|
|
1244 | 1249 | data= data_ele |
|
|
1245 | 1250 | data_T= data_weather |
|
|
1246 | 1251 | if data.shape[0]> data_T.shape[0]: |
|
|
1247 | 1252 | data_N = numpy.ones( [data.shape[0],data_T.shape[1]]) |
|
|
1248 | 1253 | c = 0 |
|
|
1249 | 1254 | for i in range(len(data)): |
|
|
1250 | 1255 | if numpy.isnan(data[i]): |
|
|
1251 | 1256 | data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan |
|
|
1252 | 1257 | else: |
|
|
1253 | 1258 | data_N[i,:]=data_T[c,:] |
|
|
1254 | 1259 | c=c+1 |
|
|
1255 | 1260 | return data_N |
|
|
1256 | 1261 | else: |
|
|
1257 | 1262 | for i in range(len(data)): |
|
|
1258 | 1263 | if numpy.isnan(data[i]): |
|
|
1259 | 1264 | data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan |
|
|
1260 | 1265 | return data_T |
|
|
1261 | 1266 | |
|
|
1262 | 1267 | def check_case(self,data_ele,ang_max,ang_min): |
|
|
1263 | 1268 | start = data_ele[0] |
|
|
1264 | 1269 | end = data_ele[-1] |
|
|
1265 | 1270 | number = (end-start) |
|
|
1266 | 1271 | len_ang=len(data_ele) |
|
|
1267 | 1272 | print("start",start) |
|
|
1268 | 1273 | print("end",end) |
|
|
1269 | 1274 | print("number",number) |
|
|
1270 | 1275 | |
|
|
1271 | 1276 | print("len_ang",len_ang) |
|
|
1272 | 1277 | |
|
|
1273 | 1278 | #exit(1) |
|
|
1274 | 1279 | |
|
|
1275 | 1280 | if start<end and (round(abs(number)+1)>=len_ang or (numpy.argmin(data_ele)==0)):#caso subida |
|
|
1276 | 1281 | return 0 |
|
|
1277 | 1282 | #elif start>end and (round(abs(number)+1)>=len_ang or(numpy.argmax(data_ele)==0)):#caso bajada |
|
|
1278 | 1283 | # return 1 |
|
|
1279 | 1284 | elif round(abs(number)+1)>=len_ang and (start>end or(numpy.argmax(data_ele)==0)):#caso bajada |
|
|
1280 | 1285 | return 1 |
|
|
1281 | 1286 | elif round(abs(number)+1)<len_ang and data_ele[-2]>data_ele[-1]:# caso BAJADA CAMBIO ANG MAX |
|
|
1282 | 1287 | return 2 |
|
|
1283 | 1288 | elif round(abs(number)+1)<len_ang and data_ele[-2]<data_ele[-1] :# caso SUBIDA CAMBIO ANG MIN |
|
|
1284 | 1289 | return 3 |
|
|
1285 | 1290 | |
|
|
1286 | 1291 | |
|
|
1287 | 1292 | def const_ploteo(self,val_ch,data_weather,data_ele,step,res,ang_max,ang_min,case_flag): |
|
|
1288 | 1293 | ang_max= ang_max |
|
|
1289 | 1294 | ang_min= ang_min |
|
|
1290 | 1295 | data_weather=data_weather |
|
|
1291 | 1296 | val_ch=val_ch |
|
|
1292 | 1297 | ##print("*********************DATA WEATHER**************************************") |
|
|
1293 | 1298 | ##print(data_weather) |
|
|
1294 | 1299 | if self.ini==0: |
|
|
1295 | 1300 | ''' |
|
|
1296 | 1301 | print("**********************************************") |
|
|
1297 | 1302 | print("**********************************************") |
|
|
1298 | 1303 | print("***************ini**************") |
|
|
1299 | 1304 | print("**********************************************") |
|
|
1300 | 1305 | print("**********************************************") |
|
|
1301 | 1306 | ''' |
|
|
1302 | 1307 | #print("data_ele",data_ele) |
|
|
1303 | 1308 | #---------------------------------------------------------- |
|
|
1304 | 1309 | tipo_case = case_flag[-1] |
|
|
1305 | 1310 | #tipo_case = self.check_case(data_ele,ang_max,ang_min) |
|
|
1306 | 1311 | print("check_case",tipo_case) |
|
|
1307 | 1312 | #exit(1) |
|
|
1308 | 1313 | #--------------------- new ------------------------- |
|
|
1309 | 1314 | data_ele_new ,data_ele_old= self.globalCheckPED(data_ele,tipo_case) |
|
|
1310 | 1315 | |
|
|
1311 | 1316 | #-------------------------CAMBIOS RHI--------------------------------- |
|
|
1312 | 1317 | start= ang_min |
|
|
1313 | 1318 | end = ang_max |
|
|
1314 | 1319 | n= (ang_max-ang_min)/res |
|
|
1315 | 1320 | #------ new |
|
|
1316 | 1321 | self.start_data_ele = data_ele_new[0] |
|
|
1317 | 1322 | self.end_data_ele = data_ele_new[-1] |
|
|
1318 | 1323 | if tipo_case==0 or tipo_case==3: # SUBIDA |
|
|
1319 | 1324 | n1= round(self.start_data_ele)- start |
|
|
1320 | 1325 | n2= end - round(self.end_data_ele) |
|
|
1321 | 1326 | print(self.start_data_ele) |
|
|
1322 | 1327 | print(self.end_data_ele) |
|
|
1323 | 1328 | if n1>0: |
|
|
1324 | 1329 | ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1) |
|
|
1325 | 1330 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
1326 | 1331 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
1327 | 1332 | print("ele1_nan",ele1_nan.shape) |
|
|
1328 | 1333 | print("data_ele_old",data_ele_old.shape) |
|
|
1329 | 1334 | data_ele_old = numpy.hstack((ele1_nan,data_ele_old)) |
|
|
1330 | 1335 | if n2>0: |
|
|
1331 | 1336 | ele2= numpy.linspace(self.end_data_ele+1,end,n2) |
|
|
1332 | 1337 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
1333 | 1338 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
1334 | 1339 | print("ele2_nan",ele2_nan.shape) |
|
|
1335 | 1340 | print("data_ele_old",data_ele_old.shape) |
|
|
1336 | 1341 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
1337 | 1342 | |
|
|
1338 | 1343 | if tipo_case==1 or tipo_case==2: # BAJADA |
|
|
1339 | 1344 | data_ele_new = data_ele_new[::-1] # reversa |
|
|
1340 | 1345 | data_ele_old = data_ele_old[::-1]# reversa |
|
|
1341 | 1346 | data_weather = data_weather[::-1,:]# reversa |
|
|
1342 | 1347 | vec= numpy.where(data_ele_new<ang_max) |
|
|
1343 | 1348 | data_ele_new = data_ele_new[vec] |
|
|
1344 | 1349 | data_ele_old = data_ele_old[vec] |
|
|
1345 | 1350 | data_weather = data_weather[vec[0]] |
|
|
1346 | 1351 | vec2= numpy.where(0<data_ele_new) |
|
|
1347 | 1352 | data_ele_new = data_ele_new[vec2] |
|
|
1348 | 1353 | data_ele_old = data_ele_old[vec2] |
|
|
1349 | 1354 | data_weather = data_weather[vec2[0]] |
|
|
1350 | 1355 | self.start_data_ele = data_ele_new[0] |
|
|
1351 | 1356 | self.end_data_ele = data_ele_new[-1] |
|
|
1352 | 1357 | |
|
|
1353 | 1358 | n1= round(self.start_data_ele)- start |
|
|
1354 | 1359 | n2= end - round(self.end_data_ele)-1 |
|
|
1355 | 1360 | print(self.start_data_ele) |
|
|
1356 | 1361 | print(self.end_data_ele) |
|
|
1357 | 1362 | if n1>0: |
|
|
1358 | 1363 | ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1) |
|
|
1359 | 1364 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
1360 | 1365 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
1361 | 1366 | data_ele_old = numpy.hstack((ele1_nan,data_ele_old)) |
|
|
1362 | 1367 | if n2>0: |
|
|
1363 | 1368 | ele2= numpy.linspace(self.end_data_ele+1,end,n2) |
|
|
1364 | 1369 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
1365 | 1370 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
1366 | 1371 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
1367 | 1372 | # RADAR |
|
|
1368 | 1373 | # NOTA data_ele y data_weather es la variable que retorna |
|
|
1369 | 1374 | val_mean = numpy.mean(data_weather[:,-1]) |
|
|
1370 | 1375 | self.val_mean = val_mean |
|
|
1371 | 1376 | data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
1372 | 1377 | print("eleold",data_ele_old) |
|
|
1373 | 1378 | print(self.data_ele_tmp[val_ch]) |
|
|
1374 | 1379 | print(data_ele_old.shape[0]) |
|
|
1375 | 1380 | print(self.data_ele_tmp[val_ch].shape[0]) |
|
|
1376 | 1381 | if (data_ele_old.shape[0]==91 or self.data_ele_tmp[val_ch].shape[0]==91): |
|
|
1377 | 1382 | import sys |
|
|
1378 | 1383 | print("EXIT",self.ini) |
|
|
1379 | 1384 | |
|
|
1380 | 1385 | sys.exit(1) |
|
|
1381 | 1386 | self.data_ele_tmp[val_ch]= data_ele_old |
|
|
1382 | 1387 | else: |
|
|
1383 | 1388 | #print("**********************************************") |
|
|
1384 | 1389 | #print("****************VARIABLE**********************") |
|
|
1385 | 1390 | #-------------------------CAMBIOS RHI--------------------------------- |
|
|
1386 | 1391 | #--------------------------------------------------------------------- |
|
|
1387 | 1392 | ##print("INPUT data_ele",data_ele) |
|
|
1388 | 1393 | flag=0 |
|
|
1389 | 1394 | start_ele = self.res_ele[0] |
|
|
1390 | 1395 | #tipo_case = self.check_case(data_ele,ang_max,ang_min) |
|
|
1391 | 1396 | tipo_case = case_flag[-1] |
|
|
1392 | 1397 | #print("TIPO DE DATA",tipo_case) |
|
|
1393 | 1398 | #-----------new------------ |
|
|
1394 | 1399 | data_ele ,data_ele_old = self.globalCheckPED(data_ele,tipo_case) |
|
|
1395 | 1400 | data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
1396 | 1401 | |
|
|
1397 | 1402 | #-------------------------------NEW RHI ITERATIVO------------------------- |
|
|
1398 | 1403 | |
|
|
1399 | 1404 | if tipo_case==0 : # SUBIDA |
|
|
1400 | 1405 | vec = numpy.where(data_ele<ang_max) |
|
|
1401 | 1406 | data_ele = data_ele[vec] |
|
|
1402 | 1407 | data_ele_old = data_ele_old[vec] |
|
|
1403 | 1408 | data_weather = data_weather[vec[0]] |
|
|
1404 | 1409 | |
|
|
1405 | 1410 | vec2 = numpy.where(0<data_ele) |
|
|
1406 | 1411 | data_ele= data_ele[vec2] |
|
|
1407 | 1412 | data_ele_old= data_ele_old[vec2] |
|
|
1408 | 1413 | ##print(data_ele_new) |
|
|
1409 | 1414 | data_weather= data_weather[vec2[0]] |
|
|
1410 | 1415 | |
|
|
1411 | 1416 | new_i_ele = int(round(data_ele[0])) |
|
|
1412 | 1417 | new_f_ele = int(round(data_ele[-1])) |
|
|
1413 | 1418 | #print(new_i_ele) |
|
|
1414 | 1419 | #print(new_f_ele) |
|
|
1415 | 1420 | #print(data_ele,len(data_ele)) |
|
|
1416 | 1421 | #print(data_ele_old,len(data_ele_old)) |
|
|
1417 | 1422 | if new_i_ele< 2: |
|
|
1418 | 1423 | self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan |
|
|
1419 | 1424 | self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean) |
|
|
1420 | 1425 | self.data_ele_tmp[val_ch][new_i_ele:new_i_ele+len(data_ele)]=data_ele_old |
|
|
1421 | 1426 | self.res_ele[new_i_ele:new_i_ele+len(data_ele)]= data_ele |
|
|
1422 | 1427 | self.res_weather[val_ch][new_i_ele:new_i_ele+len(data_ele),:]= data_weather |
|
|
1423 | 1428 | data_ele = self.res_ele |
|
|
1424 | 1429 | data_weather = self.res_weather[val_ch] |
|
|
1425 | 1430 | |
|
|
1426 | 1431 | elif tipo_case==1 : #BAJADA |
|
|
1427 | 1432 | data_ele = data_ele[::-1] # reversa |
|
|
1428 | 1433 | data_ele_old = data_ele_old[::-1]# reversa |
|
|
1429 | 1434 | data_weather = data_weather[::-1,:]# reversa |
|
|
1430 | 1435 | vec= numpy.where(data_ele<ang_max) |
|
|
1431 | 1436 | data_ele = data_ele[vec] |
|
|
1432 | 1437 | data_ele_old = data_ele_old[vec] |
|
|
1433 | 1438 | data_weather = data_weather[vec[0]] |
|
|
1434 | 1439 | vec2= numpy.where(0<data_ele) |
|
|
1435 | 1440 | data_ele = data_ele[vec2] |
|
|
1436 | 1441 | data_ele_old = data_ele_old[vec2] |
|
|
1437 | 1442 | data_weather = data_weather[vec2[0]] |
|
|
1438 | 1443 | |
|
|
1439 | 1444 | |
|
|
1440 | 1445 | new_i_ele = int(round(data_ele[0])) |
|
|
1441 | 1446 | new_f_ele = int(round(data_ele[-1])) |
|
|
1442 | 1447 | #print(data_ele) |
|
|
1443 | 1448 | #print(ang_max) |
|
|
1444 | 1449 | #print(data_ele_old) |
|
|
1445 | 1450 | if new_i_ele <= 1: |
|
|
1446 | 1451 | new_i_ele = 1 |
|
|
1447 | 1452 | if round(data_ele[-1])>=ang_max-1: |
|
|
1448 | 1453 | self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan |
|
|
1449 | 1454 | self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean) |
|
|
1450 | 1455 | self.data_ele_tmp[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1]=data_ele_old |
|
|
1451 | 1456 | self.res_ele[new_i_ele-1:new_i_ele+len(data_ele)-1]= data_ele |
|
|
1452 | 1457 | self.res_weather[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1,:]= data_weather |
|
|
1453 | 1458 | data_ele = self.res_ele |
|
|
1454 | 1459 | data_weather = self.res_weather[val_ch] |
|
|
1455 | 1460 | |
|
|
1456 | 1461 | elif tipo_case==2: #bajada |
|
|
1457 | 1462 | vec = numpy.where(data_ele<ang_max) |
|
|
1458 | 1463 | data_ele = data_ele[vec] |
|
|
1459 | 1464 | data_weather= data_weather[vec[0]] |
|
|
1460 | 1465 | |
|
|
1461 | 1466 | len_vec = len(vec) |
|
|
1462 | 1467 | data_ele_new = data_ele[::-1] # reversa |
|
|
1463 | 1468 | data_weather = data_weather[::-1,:] |
|
|
1464 | 1469 | new_i_ele = int(data_ele_new[0]) |
|
|
1465 | 1470 | new_f_ele = int(data_ele_new[-1]) |
|
|
1466 | 1471 | |
|
|
1467 | 1472 | n1= new_i_ele- ang_min |
|
|
1468 | 1473 | n2= ang_max - new_f_ele-1 |
|
|
1469 | 1474 | if n1>0: |
|
|
1470 | 1475 | ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1) |
|
|
1471 | 1476 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
1472 | 1477 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
1473 | 1478 | data_ele_old = numpy.hstack((ele1_nan,data_ele_new)) |
|
|
1474 | 1479 | if n2>0: |
|
|
1475 | 1480 | ele2= numpy.linspace(new_f_ele+1,ang_max,n2) |
|
|
1476 | 1481 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
1477 | 1482 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
1478 | 1483 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
1479 | 1484 | |
|
|
1480 | 1485 | self.data_ele_tmp[val_ch] = data_ele_old |
|
|
1481 | 1486 | self.res_ele = data_ele |
|
|
1482 | 1487 | self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
1483 | 1488 | data_ele = self.res_ele |
|
|
1484 | 1489 | data_weather = self.res_weather[val_ch] |
|
|
1485 | 1490 | |
|
|
1486 | 1491 | elif tipo_case==3:#subida |
|
|
1487 | 1492 | vec = numpy.where(0<data_ele) |
|
|
1488 | 1493 | data_ele= data_ele[vec] |
|
|
1489 | 1494 | data_ele_new = data_ele |
|
|
1490 | 1495 | data_ele_old= data_ele_old[vec] |
|
|
1491 | 1496 | data_weather= data_weather[vec[0]] |
|
|
1492 | 1497 | pos_ini = numpy.argmin(data_ele) |
|
|
1493 | 1498 | if pos_ini>0: |
|
|
1494 | 1499 | len_vec= len(data_ele) |
|
|
1495 | 1500 | vec3 = numpy.linspace(pos_ini,len_vec-1,len_vec-pos_ini).astype(int) |
|
|
1496 | 1501 | #print(vec3) |
|
|
1497 | 1502 | data_ele= data_ele[vec3] |
|
|
1498 | 1503 | data_ele_new = data_ele |
|
|
1499 | 1504 | data_ele_old= data_ele_old[vec3] |
|
|
1500 | 1505 | data_weather= data_weather[vec3] |
|
|
1501 | 1506 | |
|
|
1502 | 1507 | new_i_ele = int(data_ele_new[0]) |
|
|
1503 | 1508 | new_f_ele = int(data_ele_new[-1]) |
|
|
1504 | 1509 | n1= new_i_ele- ang_min |
|
|
1505 | 1510 | n2= ang_max - new_f_ele-1 |
|
|
1506 | 1511 | if n1>0: |
|
|
1507 | 1512 | ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1) |
|
|
1508 | 1513 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
1509 | 1514 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
1510 | 1515 | data_ele_old = numpy.hstack((ele1_nan,data_ele_new)) |
|
|
1511 | 1516 | if n2>0: |
|
|
1512 | 1517 | ele2= numpy.linspace(new_f_ele+1,ang_max,n2) |
|
|
1513 | 1518 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
1514 | 1519 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
1515 | 1520 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
1516 | 1521 | |
|
|
1517 | 1522 | self.data_ele_tmp[val_ch] = data_ele_old |
|
|
1518 | 1523 | self.res_ele = data_ele |
|
|
1519 | 1524 | self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
1520 | 1525 | data_ele = self.res_ele |
|
|
1521 | 1526 | data_weather = self.res_weather[val_ch] |
|
|
1522 | 1527 | #print("self.data_ele_tmp",self.data_ele_tmp) |
|
|
1523 | 1528 | return data_weather,data_ele |
|
|
1524 | 1529 | |
|
|
1525 | 1530 | |
|
|
1526 | 1531 | def plot(self): |
|
|
1527 | 1532 | thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S') |
|
|
1528 | 1533 | data = self.data[-1] |
|
|
1529 | 1534 | r = self.data.yrange |
|
|
1530 | 1535 | delta_height = r[1]-r[0] |
|
|
1531 | 1536 | r_mask = numpy.where(r>=0)[0] |
|
|
1532 | 1537 | ##print("delta_height",delta_height) |
|
|
1533 | 1538 | #print("r_mask",r_mask,len(r_mask)) |
|
|
1534 | 1539 | r = numpy.arange(len(r_mask))*delta_height |
|
|
1535 | 1540 | self.y = 2*r |
|
|
1536 | 1541 | res = 1 |
|
|
1537 | 1542 | ###print("data['weather'].shape[0]",data['weather'].shape[0]) |
|
|
1538 | 1543 | ang_max = self.ang_max |
|
|
1539 | 1544 | ang_min = self.ang_min |
|
|
1540 | 1545 | var_ang =ang_max - ang_min |
|
|
1541 | 1546 | step = (int(var_ang)/(res*data['weather'].shape[0])) |
|
|
1542 | 1547 | ###print("step",step) |
|
|
1543 | 1548 | #-------------------------------------------------------- |
|
|
1544 | 1549 | ##print('weather',data['weather'].shape) |
|
|
1545 | 1550 | ##print('ele',data['ele'].shape) |
|
|
1546 | 1551 | |
|
|
1547 | 1552 | ###self.res_weather, self.res_ele = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min) |
|
|
1548 | 1553 | ###self.res_azi = numpy.mean(data['azi']) |
|
|
1549 | 1554 | ###print("self.res_ele",self.res_ele) |
|
|
1550 | 1555 | plt.clf() |
|
|
1551 | 1556 | subplots = [121, 122] |
|
|
1552 | 1557 | try: |
|
|
1553 | 1558 | if self.data[-2]['ele'].max()<data['ele'].max(): |
|
|
1554 | 1559 | self.ini=0 |
|
|
1555 | 1560 | except: |
|
|
1556 | 1561 | pass |
|
|
1557 | 1562 | if self.ini==0: |
|
|
1558 | 1563 | self.data_ele_tmp = numpy.ones([self.nplots,int(var_ang)])*numpy.nan |
|
|
1559 | 1564 | self.res_weather= numpy.ones([self.nplots,int(var_ang),len(r_mask)])*numpy.nan |
|
|
1560 | 1565 | print("SHAPE",self.data_ele_tmp.shape) |
|
|
1561 | 1566 | |
|
|
1562 | 1567 | for i,ax in enumerate(self.axes): |
|
|
1563 | 1568 | self.res_weather[i], self.res_ele = self.const_ploteo(val_ch=i, data_weather=data['weather'][i][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min,case_flag=self.data['case_flag']) |
|
|
1564 | 1569 | self.res_azi = numpy.mean(data['azi']) |
|
|
1565 | 1570 | |
|
|
1566 | 1571 | if ax.firsttime: |
|
|
1567 | 1572 | #plt.clf() |
|
|
1568 | 1573 | print("Frist Plot") |
|
|
1569 | 1574 | cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80) |
|
|
1570 | 1575 | #fig=self.figures[0] |
|
|
1571 | 1576 | else: |
|
|
1572 | 1577 | #plt.clf() |
|
|
1573 | 1578 | print("ELSE PLOT") |
|
|
1574 | 1579 | cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80) |
|
|
1575 | 1580 | caax = cgax.parasites[0] |
|
|
1576 | 1581 | paax = cgax.parasites[1] |
|
|
1577 | 1582 | cbar = plt.gcf().colorbar(pm, pad=0.075) |
|
|
1578 | 1583 | caax.set_xlabel('x_range [km]') |
|
|
1579 | 1584 | caax.set_ylabel('y_range [km]') |
|
|
1580 | 1585 | plt.text(1.0, 1.05, 'Elevacion '+str(thisDatetime)+" Step "+str(self.ini)+ " Azi: "+str(round(self.res_azi,2)), transform=caax.transAxes, va='bottom',ha='right') |
|
|
1581 | 1586 | print("***************************self.ini****************************",self.ini) |
|
|
1582 | 1587 | self.ini= self.ini+1 |
|
|
1583 | 1588 | |
|
|
1584 | 1589 | class WeatherRHI_vRF_Plot(Plot): |
|
|
1585 | 1590 | CODE = 'weather' |
|
|
1586 | 1591 | plot_name = 'weather' |
|
|
1587 | 1592 | plot_type = 'rhistyle' |
|
|
1588 | 1593 | buffering = False |
|
|
1589 | 1594 | data_ele_tmp = None |
|
|
1590 | 1595 | |
|
|
1591 | 1596 | def setup(self): |
|
|
1592 | 1597 | print("********************") |
|
|
1593 | 1598 | print("********************") |
|
|
1594 | 1599 | print("********************") |
|
|
1595 | 1600 | print("SETUP WEATHER PLOT") |
|
|
1596 | 1601 | self.ncols = 1 |
|
|
1597 | 1602 | self.nrows = 1 |
|
|
1598 | 1603 | self.nplots= 1 |
|
|
1599 | 1604 | self.ylabel= 'Range [Km]' |
|
|
1600 | 1605 | self.titles= ['Weather'] |
|
|
1601 | 1606 | if self.channels is not None: |
|
|
1602 | 1607 | self.nplots = len(self.channels) |
|
|
1603 | 1608 | self.nrows = len(self.channels) |
|
|
1604 | 1609 | else: |
|
|
1605 | 1610 | self.nplots = self.data.shape(self.CODE)[0] |
|
|
1606 | 1611 | self.nrows = self.nplots |
|
|
1607 | 1612 | self.channels = list(range(self.nplots)) |
|
|
1608 | 1613 | print("channels",self.channels) |
|
|
1609 | 1614 | print("que saldra", self.data.shape(self.CODE)[0]) |
|
|
1610 | 1615 | self.titles = ['{} Channel {}'.format(self.CODE.upper(), x) for x in range(self.nrows)] |
|
|
1611 | 1616 | print("self.titles",self.titles) |
|
|
1612 | 1617 | self.colorbar=False |
|
|
1613 | 1618 | self.width =8 |
|
|
1614 | 1619 | self.height =8 |
|
|
1615 | 1620 | self.ini =0 |
|
|
1616 | 1621 | self.len_azi =0 |
|
|
1617 | 1622 | self.buffer_ini = None |
|
|
1618 | 1623 | self.buffer_ele = None |
|
|
1619 | 1624 | self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08}) |
|
|
1620 | 1625 | self.flag =0 |
|
|
1621 | 1626 | self.indicador= 0 |
|
|
1622 | 1627 | self.last_data_ele = None |
|
|
1623 | 1628 | self.val_mean = None |
|
|
1624 | 1629 | |
|
|
1625 | 1630 | def update(self, dataOut): |
|
|
1626 | 1631 | |
|
|
1627 | 1632 | data = {} |
|
|
1628 | 1633 | meta = {} |
|
|
1629 | 1634 | if hasattr(dataOut, 'dataPP_POWER'): |
|
|
1630 | 1635 | factor = 1 |
|
|
1631 | 1636 | if hasattr(dataOut, 'nFFTPoints'): |
|
|
1632 | 1637 | factor = dataOut.normFactor |
|
|
1633 | 1638 | print("dataOut",dataOut.data_360.shape) |
|
|
1634 | 1639 | # |
|
|
1635 | 1640 | data['weather'] = 10*numpy.log10(dataOut.data_360/(factor)) |
|
|
1636 | 1641 | # |
|
|
1637 | 1642 | #data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor)) |
|
|
1638 | 1643 | data['azi'] = dataOut.data_azi |
|
|
1639 | 1644 | data['ele'] = dataOut.data_ele |
|
|
1640 | 1645 | data['case_flag'] = dataOut.case_flag |
|
|
1641 | 1646 | #print("UPDATE") |
|
|
1642 | 1647 | #print("data[weather]",data['weather'].shape) |
|
|
1643 | 1648 | #print("data[azi]",data['azi']) |
|
|
1644 | 1649 | return data, meta |
|
|
1645 | 1650 | |
|
|
1646 | 1651 | def get2List(self,angulos): |
|
|
1647 | 1652 | list1=[] |
|
|
1648 | 1653 | list2=[] |
|
|
1649 | 1654 | #print(angulos) |
|
|
1650 | 1655 | #exit(1) |
|
|
1651 | 1656 | for i in reversed(range(len(angulos))): |
|
|
1652 | 1657 | if not i==0:#el caso de i=0 evalula el primero de la lista con el ultimo y no es relevante |
|
|
1653 | 1658 | diff_ = angulos[i]-angulos[i-1] |
|
|
1654 | 1659 | if abs(diff_) >1.5: |
|
|
1655 | 1660 | list1.append(i-1) |
|
|
1656 | 1661 | list2.append(diff_) |
|
|
1657 | 1662 | return list(reversed(list1)),list(reversed(list2)) |
|
|
1658 | 1663 | |
|
|
1659 | 1664 | def fixData90(self,list_,ang_): |
|
|
1660 | 1665 | if list_[0]==-1: |
|
|
1661 | 1666 | vec = numpy.where(ang_<ang_[0]) |
|
|
1662 | 1667 | ang_[vec] = ang_[vec]+90 |
|
|
1663 | 1668 | return ang_ |
|
|
1664 | 1669 | return ang_ |
|
|
1665 | 1670 | |
|
|
1666 | 1671 | def fixData90HL(self,angulos): |
|
|
1667 | 1672 | vec = numpy.where(angulos>=90) |
|
|
1668 | 1673 | angulos[vec]=angulos[vec]-90 |
|
|
1669 | 1674 | return angulos |
|
|
1670 | 1675 | |
|
|
1671 | 1676 | |
|
|
1672 | 1677 | def search_pos(self,pos,list_): |
|
|
1673 | 1678 | for i in range(len(list_)): |
|
|
1674 | 1679 | if pos == list_[i]: |
|
|
1675 | 1680 | return True,i |
|
|
1676 | 1681 | i=None |
|
|
1677 | 1682 | return False,i |
|
|
1678 | 1683 | |
|
|
1679 | 1684 | def fixDataComp(self,ang_,list1_,list2_,tipo_case): |
|
|
1680 | 1685 | size = len(ang_) |
|
|
1681 | 1686 | size2 = 0 |
|
|
1682 | 1687 | for i in range(len(list2_)): |
|
|
1683 | 1688 | size2=size2+round(abs(list2_[i]))-1 |
|
|
1684 | 1689 | new_size= size+size2 |
|
|
1685 | 1690 | ang_new = numpy.zeros(new_size) |
|
|
1686 | 1691 | ang_new2 = numpy.zeros(new_size) |
|
|
1687 | 1692 | |
|
|
1688 | 1693 | tmp = 0 |
|
|
1689 | 1694 | c = 0 |
|
|
1690 | 1695 | for i in range(len(ang_)): |
|
|
1691 | 1696 | ang_new[tmp +c] = ang_[i] |
|
|
1692 | 1697 | ang_new2[tmp+c] = ang_[i] |
|
|
1693 | 1698 | condition , value = self.search_pos(i,list1_) |
|
|
1694 | 1699 | if condition: |
|
|
1695 | 1700 | pos = tmp + c + 1 |
|
|
1696 | 1701 | for k in range(round(abs(list2_[value]))-1): |
|
|
1697 | 1702 | if tipo_case==0 or tipo_case==3:#subida |
|
|
1698 | 1703 | ang_new[pos+k] = ang_new[pos+k-1]+1 |
|
|
1699 | 1704 | ang_new2[pos+k] = numpy.nan |
|
|
1700 | 1705 | elif tipo_case==1 or tipo_case==2:#bajada |
|
|
1701 | 1706 | ang_new[pos+k] = ang_new[pos+k-1]-1 |
|
|
1702 | 1707 | ang_new2[pos+k] = numpy.nan |
|
|
1703 | 1708 | |
|
|
1704 | 1709 | tmp = pos +k |
|
|
1705 | 1710 | c = 0 |
|
|
1706 | 1711 | c=c+1 |
|
|
1707 | 1712 | return ang_new,ang_new2 |
|
|
1708 | 1713 | |
|
|
1709 | 1714 | def globalCheckPED(self,angulos,tipo_case): |
|
|
1710 | 1715 | l1,l2 = self.get2List(angulos) |
|
|
1711 | 1716 | print("l1",l1) |
|
|
1712 | 1717 | print("l2",l2) |
|
|
1713 | 1718 | if len(l1)>0: |
|
|
1714 | 1719 | #angulos2 = self.fixData90(list_=l1,ang_=angulos) |
|
|
1715 | 1720 | #l1,l2 = self.get2List(angulos2) |
|
|
1716 | 1721 | ang1_,ang2_ = self.fixDataComp(ang_=angulos,list1_=l1,list2_=l2,tipo_case=tipo_case) |
|
|
1717 | 1722 | #ang1_ = self.fixData90HL(ang1_) |
|
|
1718 | 1723 | #ang2_ = self.fixData90HL(ang2_) |
|
|
1719 | 1724 | else: |
|
|
1720 | 1725 | ang1_= angulos |
|
|
1721 | 1726 | ang2_= angulos |
|
|
1722 | 1727 | return ang1_,ang2_ |
|
|
1723 | 1728 | |
|
|
1724 | 1729 | |
|
|
1725 | 1730 | def replaceNAN(self,data_weather,data_ele,val): |
|
|
1726 | 1731 | data= data_ele |
|
|
1727 | 1732 | data_T= data_weather |
|
|
1728 | 1733 | #print(data.shape[0]) |
|
|
1729 | 1734 | #print(data_T.shape[0]) |
|
|
1730 | 1735 | #exit(1) |
|
|
1731 | 1736 | if data.shape[0]> data_T.shape[0]: |
|
|
1732 | 1737 | data_N = numpy.ones( [data.shape[0],data_T.shape[1]]) |
|
|
1733 | 1738 | c = 0 |
|
|
1734 | 1739 | for i in range(len(data)): |
|
|
1735 | 1740 | if numpy.isnan(data[i]): |
|
|
1736 | 1741 | data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan |
|
|
1737 | 1742 | else: |
|
|
1738 | 1743 | data_N[i,:]=data_T[c,:] |
|
|
1739 | 1744 | c=c+1 |
|
|
1740 | 1745 | return data_N |
|
|
1741 | 1746 | else: |
|
|
1742 | 1747 | for i in range(len(data)): |
|
|
1743 | 1748 | if numpy.isnan(data[i]): |
|
|
1744 | 1749 | data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan |
|
|
1745 | 1750 | return data_T |
|
|
1746 | 1751 | |
|
|
1747 | 1752 | |
|
|
1748 | 1753 | def const_ploteo(self,val_ch,data_weather,data_ele,step,res,ang_max,ang_min,case_flag): |
|
|
1749 | 1754 | ang_max= ang_max |
|
|
1750 | 1755 | ang_min= ang_min |
|
|
1751 | 1756 | data_weather=data_weather |
|
|
1752 | 1757 | val_ch=val_ch |
|
|
1753 | 1758 | ##print("*********************DATA WEATHER**************************************") |
|
|
1754 | 1759 | ##print(data_weather) |
|
|
1755 | 1760 | |
|
|
1756 | 1761 | ''' |
|
|
1757 | 1762 | print("**********************************************") |
|
|
1758 | 1763 | print("**********************************************") |
|
|
1759 | 1764 | print("***************ini**************") |
|
|
1760 | 1765 | print("**********************************************") |
|
|
1761 | 1766 | print("**********************************************") |
|
|
1762 | 1767 | ''' |
|
|
1763 | 1768 | #print("data_ele",data_ele) |
|
|
1764 | 1769 | #---------------------------------------------------------- |
|
|
1765 | 1770 | |
|
|
1766 | 1771 | #exit(1) |
|
|
1767 | 1772 | tipo_case = case_flag[-1] |
|
|
1768 | 1773 | print("tipo_case",tipo_case) |
|
|
1769 | 1774 | #--------------------- new ------------------------- |
|
|
1770 | 1775 | data_ele_new ,data_ele_old= self.globalCheckPED(data_ele,tipo_case) |
|
|
1771 | 1776 | |
|
|
1772 | 1777 | #-------------------------CAMBIOS RHI--------------------------------- |
|
|
1773 | 1778 | |
|
|
1774 | 1779 | vec = numpy.where(data_ele<ang_max) |
|
|
1775 | 1780 | data_ele = data_ele[vec] |
|
|
1776 | 1781 | data_weather= data_weather[vec[0]] |
|
|
1777 | 1782 | |
|
|
1778 | 1783 | len_vec = len(vec) |
|
|
1779 | 1784 | data_ele_new = data_ele[::-1] # reversa |
|
|
1780 | 1785 | data_weather = data_weather[::-1,:] |
|
|
1781 | 1786 | new_i_ele = int(data_ele_new[0]) |
|
|
1782 | 1787 | new_f_ele = int(data_ele_new[-1]) |
|
|
1783 | 1788 | |
|
|
1784 | 1789 | n1= new_i_ele- ang_min |
|
|
1785 | 1790 | n2= ang_max - new_f_ele-1 |
|
|
1786 | 1791 | if n1>0: |
|
|
1787 | 1792 | ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1) |
|
|
1788 | 1793 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
1789 | 1794 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
1790 | 1795 | data_ele_old = numpy.hstack((ele1_nan,data_ele_new)) |
|
|
1791 | 1796 | if n2>0: |
|
|
1792 | 1797 | ele2= numpy.linspace(new_f_ele+1,ang_max,n2) |
|
|
1793 | 1798 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
1794 | 1799 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
1795 | 1800 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
1796 | 1801 | |
|
|
1797 | 1802 | |
|
|
1798 | 1803 | print("ele shape",data_ele.shape) |
|
|
1799 | 1804 | print(data_ele) |
|
|
1800 | 1805 | |
|
|
1801 | 1806 | #print("self.data_ele_tmp",self.data_ele_tmp) |
|
|
1802 | 1807 | val_mean = numpy.mean(data_weather[:,-1]) |
|
|
1803 | 1808 | self.val_mean = val_mean |
|
|
1804 | 1809 | data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
1805 | 1810 | self.data_ele_tmp[val_ch]= data_ele_old |
|
|
1806 | 1811 | |
|
|
1807 | 1812 | |
|
|
1808 | 1813 | print("data_weather shape",data_weather.shape) |
|
|
1809 | 1814 | print(data_weather) |
|
|
1810 | 1815 | #exit(1) |
|
|
1811 | 1816 | return data_weather,data_ele |
|
|
1812 | 1817 | |
|
|
1813 | 1818 | |
|
|
1814 | 1819 | def plot(self): |
|
|
1815 | 1820 | thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S') |
|
|
1816 | 1821 | data = self.data[-1] |
|
|
1817 | 1822 | r = self.data.yrange |
|
|
1818 | 1823 | delta_height = r[1]-r[0] |
|
|
1819 | 1824 | r_mask = numpy.where(r>=0)[0] |
|
|
1820 | 1825 | ##print("delta_height",delta_height) |
|
|
1821 | 1826 | #print("r_mask",r_mask,len(r_mask)) |
|
|
1822 | 1827 | r = numpy.arange(len(r_mask))*delta_height |
|
|
1823 | 1828 | self.y = 2*r |
|
|
1824 | 1829 | res = 1 |
|
|
1825 | 1830 | ###print("data['weather'].shape[0]",data['weather'].shape[0]) |
|
|
1826 | 1831 | ang_max = self.ang_max |
|
|
1827 | 1832 | ang_min = self.ang_min |
|
|
1828 | 1833 | var_ang =ang_max - ang_min |
|
|
1829 | 1834 | step = (int(var_ang)/(res*data['weather'].shape[0])) |
|
|
1830 | 1835 | ###print("step",step) |
|
|
1831 | 1836 | #-------------------------------------------------------- |
|
|
1832 | 1837 | ##print('weather',data['weather'].shape) |
|
|
1833 | 1838 | ##print('ele',data['ele'].shape) |
|
|
1834 | 1839 | |
|
|
1835 | 1840 | ###self.res_weather, self.res_ele = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min) |
|
|
1836 | 1841 | ###self.res_azi = numpy.mean(data['azi']) |
|
|
1837 | 1842 | ###print("self.res_ele",self.res_ele) |
|
|
1838 | 1843 | plt.clf() |
|
|
1839 | 1844 | subplots = [121, 122] |
|
|
1840 | 1845 | if self.ini==0: |
|
|
1841 | 1846 | self.data_ele_tmp = numpy.ones([self.nplots,int(var_ang)])*numpy.nan |
|
|
1842 | 1847 | self.res_weather= numpy.ones([self.nplots,int(var_ang),len(r_mask)])*numpy.nan |
|
|
1843 | 1848 | print("SHAPE",self.data_ele_tmp.shape) |
|
|
1844 | 1849 | |
|
|
1845 | 1850 | for i,ax in enumerate(self.axes): |
|
|
1846 | 1851 | self.res_weather[i], self.res_ele = self.const_ploteo(val_ch=i, data_weather=data['weather'][i][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min,case_flag=self.data['case_flag']) |
|
|
1847 | 1852 | self.res_azi = numpy.mean(data['azi']) |
|
|
1848 | 1853 | |
|
|
1849 | 1854 | print(self.res_ele) |
|
|
1850 | 1855 | #exit(1) |
|
|
1851 | 1856 | if ax.firsttime: |
|
|
1852 | 1857 | #plt.clf() |
|
|
1853 | 1858 | cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80) |
|
|
1854 | 1859 | #fig=self.figures[0] |
|
|
1855 | 1860 | else: |
|
|
1856 | 1861 | |
|
|
1857 | 1862 | #plt.clf() |
|
|
1858 | 1863 | cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80) |
|
|
1859 | 1864 | caax = cgax.parasites[0] |
|
|
1860 | 1865 | paax = cgax.parasites[1] |
|
|
1861 | 1866 | cbar = plt.gcf().colorbar(pm, pad=0.075) |
|
|
1862 | 1867 | caax.set_xlabel('x_range [km]') |
|
|
1863 | 1868 | caax.set_ylabel('y_range [km]') |
|
|
1864 | 1869 | plt.text(1.0, 1.05, 'Elevacion '+str(thisDatetime)+" Step "+str(self.ini)+ " Azi: "+str(round(self.res_azi,2)), transform=caax.transAxes, va='bottom',ha='right') |
|
|
1865 | 1870 | print("***************************self.ini****************************",self.ini) |
|
|
1866 | 1871 | self.ini= self.ini+1 |
|
|
1867 | 1872 | |
|
|
1868 | 1873 | class WeatherRHI_vRF3_Plot(Plot): |
|
|
1869 | 1874 | CODE = 'weather' |
|
|
1870 | 1875 | plot_name = 'weather' |
|
|
1871 | 1876 | plot_type = 'rhistyle' |
|
|
1872 | 1877 | buffering = False |
|
|
1873 | 1878 | data_ele_tmp = None |
|
|
1874 | 1879 | |
|
|
1875 | 1880 | def setup(self): |
|
|
1876 | 1881 | print("********************") |
|
|
1877 | 1882 | print("********************") |
|
|
1878 | 1883 | print("********************") |
|
|
1879 | 1884 | print("SETUP WEATHER PLOT") |
|
|
1880 | 1885 | self.ncols = 1 |
|
|
1881 | 1886 | self.nrows = 1 |
|
|
1882 | 1887 | self.nplots= 1 |
|
|
1883 | 1888 | self.ylabel= 'Range [Km]' |
|
|
1884 | 1889 | self.titles= ['Weather'] |
|
|
1885 | 1890 | if self.channels is not None: |
|
|
1886 | 1891 | self.nplots = len(self.channels) |
|
|
1887 | 1892 | self.nrows = len(self.channels) |
|
|
1888 | 1893 | else: |
|
|
1889 | 1894 | self.nplots = self.data.shape(self.CODE)[0] |
|
|
1890 | 1895 | self.nrows = self.nplots |
|
|
1891 | 1896 | self.channels = list(range(self.nplots)) |
|
|
1892 | 1897 | print("channels",self.channels) |
|
|
1893 | 1898 | print("que saldra", self.data.shape(self.CODE)[0]) |
|
|
1894 | 1899 | self.titles = ['{} Channel {}'.format(self.CODE.upper(), x) for x in range(self.nrows)] |
|
|
1895 | 1900 | print("self.titles",self.titles) |
|
|
1896 | 1901 | self.colorbar=False |
|
|
1897 | 1902 | self.width =8 |
|
|
1898 | 1903 | self.height =8 |
|
|
1899 | 1904 | self.ini =0 |
|
|
1900 | 1905 | self.len_azi =0 |
|
|
1901 | 1906 | self.buffer_ini = None |
|
|
1902 | 1907 | self.buffer_ele = None |
|
|
1903 | 1908 | self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08}) |
|
|
1904 | 1909 | self.flag =0 |
|
|
1905 | 1910 | self.indicador= 0 |
|
|
1906 | 1911 | self.last_data_ele = None |
|
|
1907 | 1912 | self.val_mean = None |
|
|
1908 | 1913 | |
|
|
1909 | 1914 | def update(self, dataOut): |
|
|
1910 | 1915 | |
|
|
1911 | 1916 | data = {} |
|
|
1912 | 1917 | meta = {} |
|
|
1913 | 1918 | if hasattr(dataOut, 'dataPP_POWER'): |
|
|
1914 | 1919 | factor = 1 |
|
|
1915 | 1920 | if hasattr(dataOut, 'nFFTPoints'): |
|
|
1916 | 1921 | factor = dataOut.normFactor |
|
|
1917 | 1922 | print("dataOut",dataOut.data_360.shape) |
|
|
1918 | 1923 | # |
|
|
1919 | 1924 | data['weather'] = 10*numpy.log10(dataOut.data_360/(factor)) |
|
|
1920 | 1925 | # |
|
|
1921 | 1926 | #data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor)) |
|
|
1922 | 1927 | data['azi'] = dataOut.data_azi |
|
|
1923 | 1928 | data['ele'] = dataOut.data_ele |
|
|
1924 | 1929 | #data['case_flag'] = dataOut.case_flag |
|
|
1925 | 1930 | #print("UPDATE") |
|
|
1926 | 1931 | #print("data[weather]",data['weather'].shape) |
|
|
1927 | 1932 | #print("data[azi]",data['azi']) |
|
|
1928 | 1933 | return data, meta |
|
|
1929 | 1934 | |
|
|
1930 | 1935 | def get2List(self,angulos): |
|
|
1931 | 1936 | list1=[] |
|
|
1932 | 1937 | list2=[] |
|
|
1933 | 1938 | for i in reversed(range(len(angulos))): |
|
|
1934 | 1939 | if not i==0:#el caso de i=0 evalula el primero de la lista con el ultimo y no es relevante |
|
|
1935 | 1940 | diff_ = angulos[i]-angulos[i-1] |
|
|
1936 | 1941 | if abs(diff_) >1.5: |
|
|
1937 | 1942 | list1.append(i-1) |
|
|
1938 | 1943 | list2.append(diff_) |
|
|
1939 | 1944 | return list(reversed(list1)),list(reversed(list2)) |
|
|
1940 | 1945 | |
|
|
1941 | 1946 | def fixData90(self,list_,ang_): |
|
|
1942 | 1947 | if list_[0]==-1: |
|
|
1943 | 1948 | vec = numpy.where(ang_<ang_[0]) |
|
|
1944 | 1949 | ang_[vec] = ang_[vec]+90 |
|
|
1945 | 1950 | return ang_ |
|
|
1946 | 1951 | return ang_ |
|
|
1947 | 1952 | |
|
|
1948 | 1953 | def fixData90HL(self,angulos): |
|
|
1949 | 1954 | vec = numpy.where(angulos>=90) |
|
|
1950 | 1955 | angulos[vec]=angulos[vec]-90 |
|
|
1951 | 1956 | return angulos |
|
|
1952 | 1957 | |
|
|
1953 | 1958 | |
|
|
1954 | 1959 | def search_pos(self,pos,list_): |
|
|
1955 | 1960 | for i in range(len(list_)): |
|
|
1956 | 1961 | if pos == list_[i]: |
|
|
1957 | 1962 | return True,i |
|
|
1958 | 1963 | i=None |
|
|
1959 | 1964 | return False,i |
|
|
1960 | 1965 | |
|
|
1961 | 1966 | def fixDataComp(self,ang_,list1_,list2_,tipo_case): |
|
|
1962 | 1967 | size = len(ang_) |
|
|
1963 | 1968 | size2 = 0 |
|
|
1964 | 1969 | for i in range(len(list2_)): |
|
|
1965 | 1970 | size2=size2+round(abs(list2_[i]))-1 |
|
|
1966 | 1971 | new_size= size+size2 |
|
|
1967 | 1972 | ang_new = numpy.zeros(new_size) |
|
|
1968 | 1973 | ang_new2 = numpy.zeros(new_size) |
|
|
1969 | 1974 | |
|
|
1970 | 1975 | tmp = 0 |
|
|
1971 | 1976 | c = 0 |
|
|
1972 | 1977 | for i in range(len(ang_)): |
|
|
1973 | 1978 | ang_new[tmp +c] = ang_[i] |
|
|
1974 | 1979 | ang_new2[tmp+c] = ang_[i] |
|
|
1975 | 1980 | condition , value = self.search_pos(i,list1_) |
|
|
1976 | 1981 | if condition: |
|
|
1977 | 1982 | pos = tmp + c + 1 |
|
|
1978 | 1983 | for k in range(round(abs(list2_[value]))-1): |
|
|
1979 | 1984 | if tipo_case==0 or tipo_case==3:#subida |
|
|
1980 | 1985 | ang_new[pos+k] = ang_new[pos+k-1]+1 |
|
|
1981 | 1986 | ang_new2[pos+k] = numpy.nan |
|
|
1982 | 1987 | elif tipo_case==1 or tipo_case==2:#bajada |
|
|
1983 | 1988 | ang_new[pos+k] = ang_new[pos+k-1]-1 |
|
|
1984 | 1989 | ang_new2[pos+k] = numpy.nan |
|
|
1985 | 1990 | |
|
|
1986 | 1991 | tmp = pos +k |
|
|
1987 | 1992 | c = 0 |
|
|
1988 | 1993 | c=c+1 |
|
|
1989 | 1994 | return ang_new,ang_new2 |
|
|
1990 | 1995 | |
|
|
1991 | 1996 | def globalCheckPED(self,angulos,tipo_case): |
|
|
1992 | 1997 | l1,l2 = self.get2List(angulos) |
|
|
1993 | 1998 | ##print("l1",l1) |
|
|
1994 | 1999 | ##print("l2",l2) |
|
|
1995 | 2000 | if len(l1)>0: |
|
|
1996 | 2001 | #angulos2 = self.fixData90(list_=l1,ang_=angulos) |
|
|
1997 | 2002 | #l1,l2 = self.get2List(angulos2) |
|
|
1998 | 2003 | ang1_,ang2_ = self.fixDataComp(ang_=angulos,list1_=l1,list2_=l2,tipo_case=tipo_case) |
|
|
1999 | 2004 | #ang1_ = self.fixData90HL(ang1_) |
|
|
2000 | 2005 | #ang2_ = self.fixData90HL(ang2_) |
|
|
2001 | 2006 | else: |
|
|
2002 | 2007 | ang1_= angulos |
|
|
2003 | 2008 | ang2_= angulos |
|
|
2004 | 2009 | return ang1_,ang2_ |
|
|
2005 | 2010 | |
|
|
2006 | 2011 | |
|
|
2007 | 2012 | def replaceNAN(self,data_weather,data_ele,val): |
|
|
2008 | 2013 | data= data_ele |
|
|
2009 | 2014 | data_T= data_weather |
|
|
2010 | 2015 | |
|
|
2011 | 2016 | if data.shape[0]> data_T.shape[0]: |
|
|
2012 | 2017 | print("IF") |
|
|
2013 | 2018 | data_N = numpy.ones( [data.shape[0],data_T.shape[1]]) |
|
|
2014 | 2019 | c = 0 |
|
|
2015 | 2020 | for i in range(len(data)): |
|
|
2016 | 2021 | if numpy.isnan(data[i]): |
|
|
2017 | 2022 | data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan |
|
|
2018 | 2023 | else: |
|
|
2019 | 2024 | data_N[i,:]=data_T[c,:] |
|
|
2020 | 2025 | c=c+1 |
|
|
2021 | 2026 | return data_N |
|
|
2022 | 2027 | else: |
|
|
2023 | 2028 | print("else") |
|
|
2024 | 2029 | for i in range(len(data)): |
|
|
2025 | 2030 | if numpy.isnan(data[i]): |
|
|
2026 | 2031 | data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan |
|
|
2027 | 2032 | return data_T |
|
|
2028 | 2033 | |
|
|
2029 | 2034 | def check_case(self,data_ele,ang_max,ang_min): |
|
|
2030 | 2035 | start = data_ele[0] |
|
|
2031 | 2036 | end = data_ele[-1] |
|
|
2032 | 2037 | number = (end-start) |
|
|
2033 | 2038 | len_ang=len(data_ele) |
|
|
2034 | 2039 | print("start",start) |
|
|
2035 | 2040 | print("end",end) |
|
|
2036 | 2041 | print("number",number) |
|
|
2037 | 2042 | |
|
|
2038 | 2043 | print("len_ang",len_ang) |
|
|
2039 | 2044 | |
|
|
2040 | 2045 | #exit(1) |
|
|
2041 | 2046 | |
|
|
2042 | 2047 | if start<end and (round(abs(number)+1)>=len_ang or (numpy.argmin(data_ele)==0)):#caso subida |
|
|
2043 | 2048 | return 0 |
|
|
2044 | 2049 | #elif start>end and (round(abs(number)+1)>=len_ang or(numpy.argmax(data_ele)==0)):#caso bajada |
|
|
2045 | 2050 | # return 1 |
|
|
2046 | 2051 | elif round(abs(number)+1)>=len_ang and (start>end or(numpy.argmax(data_ele)==0)):#caso bajada |
|
|
2047 | 2052 | return 1 |
|
|
2048 | 2053 | elif round(abs(number)+1)<len_ang and data_ele[-2]>data_ele[-1]:# caso BAJADA CAMBIO ANG MAX |
|
|
2049 | 2054 | return 2 |
|
|
2050 | 2055 | elif round(abs(number)+1)<len_ang and data_ele[-2]<data_ele[-1] :# caso SUBIDA CAMBIO ANG MIN |
|
|
2051 | 2056 | return 3 |
|
|
2052 | 2057 | |
|
|
2053 | 2058 | |
|
|
2054 | 2059 | def const_ploteo(self,val_ch,data_weather,data_ele,step,res,ang_max,ang_min,case_flag): |
|
|
2055 | 2060 | ang_max= ang_max |
|
|
2056 | 2061 | ang_min= ang_min |
|
|
2057 | 2062 | data_weather=data_weather |
|
|
2058 | 2063 | val_ch=val_ch |
|
|
2059 | 2064 | ##print("*********************DATA WEATHER**************************************") |
|
|
2060 | 2065 | ##print(data_weather) |
|
|
2061 | 2066 | if self.ini==0: |
|
|
2062 | 2067 | |
|
|
2063 | 2068 | #--------------------- new ------------------------- |
|
|
2064 | 2069 | data_ele_new ,data_ele_old= self.globalCheckPED(data_ele,tipo_case) |
|
|
2065 | 2070 | |
|
|
2066 | 2071 | #-------------------------CAMBIOS RHI--------------------------------- |
|
|
2067 | 2072 | start= ang_min |
|
|
2068 | 2073 | end = ang_max |
|
|
2069 | 2074 | n= (ang_max-ang_min)/res |
|
|
2070 | 2075 | #------ new |
|
|
2071 | 2076 | self.start_data_ele = data_ele_new[0] |
|
|
2072 | 2077 | self.end_data_ele = data_ele_new[-1] |
|
|
2073 | 2078 | if tipo_case==0 or tipo_case==3: # SUBIDA |
|
|
2074 | 2079 | n1= round(self.start_data_ele)- start |
|
|
2075 | 2080 | n2= end - round(self.end_data_ele) |
|
|
2076 | 2081 | print(self.start_data_ele) |
|
|
2077 | 2082 | print(self.end_data_ele) |
|
|
2078 | 2083 | if n1>0: |
|
|
2079 | 2084 | ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1) |
|
|
2080 | 2085 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
2081 | 2086 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
2082 | 2087 | print("ele1_nan",ele1_nan.shape) |
|
|
2083 | 2088 | print("data_ele_old",data_ele_old.shape) |
|
|
2084 | 2089 | data_ele_old = numpy.hstack((ele1_nan,data_ele_old)) |
|
|
2085 | 2090 | if n2>0: |
|
|
2086 | 2091 | ele2= numpy.linspace(self.end_data_ele+1,end,n2) |
|
|
2087 | 2092 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
2088 | 2093 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
2089 | 2094 | print("ele2_nan",ele2_nan.shape) |
|
|
2090 | 2095 | print("data_ele_old",data_ele_old.shape) |
|
|
2091 | 2096 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
2092 | 2097 | |
|
|
2093 | 2098 | if tipo_case==1 or tipo_case==2: # BAJADA |
|
|
2094 | 2099 | data_ele_new = data_ele_new[::-1] # reversa |
|
|
2095 | 2100 | data_ele_old = data_ele_old[::-1]# reversa |
|
|
2096 | 2101 | data_weather = data_weather[::-1,:]# reversa |
|
|
2097 | 2102 | vec= numpy.where(data_ele_new<ang_max) |
|
|
2098 | 2103 | data_ele_new = data_ele_new[vec] |
|
|
2099 | 2104 | data_ele_old = data_ele_old[vec] |
|
|
2100 | 2105 | data_weather = data_weather[vec[0]] |
|
|
2101 | 2106 | vec2= numpy.where(0<data_ele_new) |
|
|
2102 | 2107 | data_ele_new = data_ele_new[vec2] |
|
|
2103 | 2108 | data_ele_old = data_ele_old[vec2] |
|
|
2104 | 2109 | data_weather = data_weather[vec2[0]] |
|
|
2105 | 2110 | self.start_data_ele = data_ele_new[0] |
|
|
2106 | 2111 | self.end_data_ele = data_ele_new[-1] |
|
|
2107 | 2112 | |
|
|
2108 | 2113 | n1= round(self.start_data_ele)- start |
|
|
2109 | 2114 | n2= end - round(self.end_data_ele)-1 |
|
|
2110 | 2115 | print(self.start_data_ele) |
|
|
2111 | 2116 | print(self.end_data_ele) |
|
|
2112 | 2117 | if n1>0: |
|
|
2113 | 2118 | ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1) |
|
|
2114 | 2119 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
2115 | 2120 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
2116 | 2121 | data_ele_old = numpy.hstack((ele1_nan,data_ele_old)) |
|
|
2117 | 2122 | if n2>0: |
|
|
2118 | 2123 | ele2= numpy.linspace(self.end_data_ele+1,end,n2) |
|
|
2119 | 2124 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
2120 | 2125 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
2121 | 2126 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
2122 | 2127 | # RADAR |
|
|
2123 | 2128 | # NOTA data_ele y data_weather es la variable que retorna |
|
|
2124 | 2129 | val_mean = numpy.mean(data_weather[:,-1]) |
|
|
2125 | 2130 | self.val_mean = val_mean |
|
|
2126 | 2131 | data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
2127 | 2132 | print("eleold",data_ele_old) |
|
|
2128 | 2133 | print(self.data_ele_tmp[val_ch]) |
|
|
2129 | 2134 | print(data_ele_old.shape[0]) |
|
|
2130 | 2135 | print(self.data_ele_tmp[val_ch].shape[0]) |
|
|
2131 | 2136 | if (data_ele_old.shape[0]==91 or self.data_ele_tmp[val_ch].shape[0]==91): |
|
|
2132 | 2137 | import sys |
|
|
2133 | 2138 | print("EXIT",self.ini) |
|
|
2134 | 2139 | |
|
|
2135 | 2140 | sys.exit(1) |
|
|
2136 | 2141 | self.data_ele_tmp[val_ch]= data_ele_old |
|
|
2137 | 2142 | else: |
|
|
2138 | 2143 | #print("**********************************************") |
|
|
2139 | 2144 | #print("****************VARIABLE**********************") |
|
|
2140 | 2145 | #-------------------------CAMBIOS RHI--------------------------------- |
|
|
2141 | 2146 | #--------------------------------------------------------------------- |
|
|
2142 | 2147 | ##print("INPUT data_ele",data_ele) |
|
|
2143 | 2148 | flag=0 |
|
|
2144 | 2149 | start_ele = self.res_ele[0] |
|
|
2145 | 2150 | #tipo_case = self.check_case(data_ele,ang_max,ang_min) |
|
|
2146 | 2151 | tipo_case = case_flag[-1] |
|
|
2147 | 2152 | #print("TIPO DE DATA",tipo_case) |
|
|
2148 | 2153 | #-----------new------------ |
|
|
2149 | 2154 | data_ele ,data_ele_old = self.globalCheckPED(data_ele,tipo_case) |
|
|
2150 | 2155 | data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
2151 | 2156 | |
|
|
2152 | 2157 | #-------------------------------NEW RHI ITERATIVO------------------------- |
|
|
2153 | 2158 | |
|
|
2154 | 2159 | if tipo_case==0 : # SUBIDA |
|
|
2155 | 2160 | vec = numpy.where(data_ele<ang_max) |
|
|
2156 | 2161 | data_ele = data_ele[vec] |
|
|
2157 | 2162 | data_ele_old = data_ele_old[vec] |
|
|
2158 | 2163 | data_weather = data_weather[vec[0]] |
|
|
2159 | 2164 | |
|
|
2160 | 2165 | vec2 = numpy.where(0<data_ele) |
|
|
2161 | 2166 | data_ele= data_ele[vec2] |
|
|
2162 | 2167 | data_ele_old= data_ele_old[vec2] |
|
|
2163 | 2168 | ##print(data_ele_new) |
|
|
2164 | 2169 | data_weather= data_weather[vec2[0]] |
|
|
2165 | 2170 | |
|
|
2166 | 2171 | new_i_ele = int(round(data_ele[0])) |
|
|
2167 | 2172 | new_f_ele = int(round(data_ele[-1])) |
|
|
2168 | 2173 | #print(new_i_ele) |
|
|
2169 | 2174 | #print(new_f_ele) |
|
|
2170 | 2175 | #print(data_ele,len(data_ele)) |
|
|
2171 | 2176 | #print(data_ele_old,len(data_ele_old)) |
|
|
2172 | 2177 | if new_i_ele< 2: |
|
|
2173 | 2178 | self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan |
|
|
2174 | 2179 | self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean) |
|
|
2175 | 2180 | self.data_ele_tmp[val_ch][new_i_ele:new_i_ele+len(data_ele)]=data_ele_old |
|
|
2176 | 2181 | self.res_ele[new_i_ele:new_i_ele+len(data_ele)]= data_ele |
|
|
2177 | 2182 | self.res_weather[val_ch][new_i_ele:new_i_ele+len(data_ele),:]= data_weather |
|
|
2178 | 2183 | data_ele = self.res_ele |
|
|
2179 | 2184 | data_weather = self.res_weather[val_ch] |
|
|
2180 | 2185 | |
|
|
2181 | 2186 | elif tipo_case==1 : #BAJADA |
|
|
2182 | 2187 | data_ele = data_ele[::-1] # reversa |
|
|
2183 | 2188 | data_ele_old = data_ele_old[::-1]# reversa |
|
|
2184 | 2189 | data_weather = data_weather[::-1,:]# reversa |
|
|
2185 | 2190 | vec= numpy.where(data_ele<ang_max) |
|
|
2186 | 2191 | data_ele = data_ele[vec] |
|
|
2187 | 2192 | data_ele_old = data_ele_old[vec] |
|
|
2188 | 2193 | data_weather = data_weather[vec[0]] |
|
|
2189 | 2194 | vec2= numpy.where(0<data_ele) |
|
|
2190 | 2195 | data_ele = data_ele[vec2] |
|
|
2191 | 2196 | data_ele_old = data_ele_old[vec2] |
|
|
2192 | 2197 | data_weather = data_weather[vec2[0]] |
|
|
2193 | 2198 | |
|
|
2194 | 2199 | |
|
|
2195 | 2200 | new_i_ele = int(round(data_ele[0])) |
|
|
2196 | 2201 | new_f_ele = int(round(data_ele[-1])) |
|
|
2197 | 2202 | #print(data_ele) |
|
|
2198 | 2203 | #print(ang_max) |
|
|
2199 | 2204 | #print(data_ele_old) |
|
|
2200 | 2205 | if new_i_ele <= 1: |
|
|
2201 | 2206 | new_i_ele = 1 |
|
|
2202 | 2207 | if round(data_ele[-1])>=ang_max-1: |
|
|
2203 | 2208 | self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan |
|
|
2204 | 2209 | self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean) |
|
|
2205 | 2210 | self.data_ele_tmp[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1]=data_ele_old |
|
|
2206 | 2211 | self.res_ele[new_i_ele-1:new_i_ele+len(data_ele)-1]= data_ele |
|
|
2207 | 2212 | self.res_weather[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1,:]= data_weather |
|
|
2208 | 2213 | data_ele = self.res_ele |
|
|
2209 | 2214 | data_weather = self.res_weather[val_ch] |
|
|
2210 | 2215 | |
|
|
2211 | 2216 | elif tipo_case==2: #bajada |
|
|
2212 | 2217 | vec = numpy.where(data_ele<ang_max) |
|
|
2213 | 2218 | data_ele = data_ele[vec] |
|
|
2214 | 2219 | data_weather= data_weather[vec[0]] |
|
|
2215 | 2220 | |
|
|
2216 | 2221 | len_vec = len(vec) |
|
|
2217 | 2222 | data_ele_new = data_ele[::-1] # reversa |
|
|
2218 | 2223 | data_weather = data_weather[::-1,:] |
|
|
2219 | 2224 | new_i_ele = int(data_ele_new[0]) |
|
|
2220 | 2225 | new_f_ele = int(data_ele_new[-1]) |
|
|
2221 | 2226 | |
|
|
2222 | 2227 | n1= new_i_ele- ang_min |
|
|
2223 | 2228 | n2= ang_max - new_f_ele-1 |
|
|
2224 | 2229 | if n1>0: |
|
|
2225 | 2230 | ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1) |
|
|
2226 | 2231 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
2227 | 2232 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
2228 | 2233 | data_ele_old = numpy.hstack((ele1_nan,data_ele_new)) |
|
|
2229 | 2234 | if n2>0: |
|
|
2230 | 2235 | ele2= numpy.linspace(new_f_ele+1,ang_max,n2) |
|
|
2231 | 2236 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
2232 | 2237 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
2233 | 2238 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
2234 | 2239 | |
|
|
2235 | 2240 | self.data_ele_tmp[val_ch] = data_ele_old |
|
|
2236 | 2241 | self.res_ele = data_ele |
|
|
2237 | 2242 | self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
2238 | 2243 | data_ele = self.res_ele |
|
|
2239 | 2244 | data_weather = self.res_weather[val_ch] |
|
|
2240 | 2245 | |
|
|
2241 | 2246 | elif tipo_case==3:#subida |
|
|
2242 | 2247 | vec = numpy.where(0<data_ele) |
|
|
2243 | 2248 | data_ele= data_ele[vec] |
|
|
2244 | 2249 | data_ele_new = data_ele |
|
|
2245 | 2250 | data_ele_old= data_ele_old[vec] |
|
|
2246 | 2251 | data_weather= data_weather[vec[0]] |
|
|
2247 | 2252 | pos_ini = numpy.argmin(data_ele) |
|
|
2248 | 2253 | if pos_ini>0: |
|
|
2249 | 2254 | len_vec= len(data_ele) |
|
|
2250 | 2255 | vec3 = numpy.linspace(pos_ini,len_vec-1,len_vec-pos_ini).astype(int) |
|
|
2251 | 2256 | #print(vec3) |
|
|
2252 | 2257 | data_ele= data_ele[vec3] |
|
|
2253 | 2258 | data_ele_new = data_ele |
|
|
2254 | 2259 | data_ele_old= data_ele_old[vec3] |
|
|
2255 | 2260 | data_weather= data_weather[vec3] |
|
|
2256 | 2261 | |
|
|
2257 | 2262 | new_i_ele = int(data_ele_new[0]) |
|
|
2258 | 2263 | new_f_ele = int(data_ele_new[-1]) |
|
|
2259 | 2264 | n1= new_i_ele- ang_min |
|
|
2260 | 2265 | n2= ang_max - new_f_ele-1 |
|
|
2261 | 2266 | if n1>0: |
|
|
2262 | 2267 | ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1) |
|
|
2263 | 2268 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
2264 | 2269 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
2265 | 2270 | data_ele_old = numpy.hstack((ele1_nan,data_ele_new)) |
|
|
2266 | 2271 | if n2>0: |
|
|
2267 | 2272 | ele2= numpy.linspace(new_f_ele+1,ang_max,n2) |
|
|
2268 | 2273 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
2269 | 2274 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
2270 | 2275 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
2271 | 2276 | |
|
|
2272 | 2277 | self.data_ele_tmp[val_ch] = data_ele_old |
|
|
2273 | 2278 | self.res_ele = data_ele |
|
|
2274 | 2279 | self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
2275 | 2280 | data_ele = self.res_ele |
|
|
2276 | 2281 | data_weather = self.res_weather[val_ch] |
|
|
2277 | 2282 | #print("self.data_ele_tmp",self.data_ele_tmp) |
|
|
2278 | 2283 | return data_weather,data_ele |
|
|
2279 | 2284 | |
|
|
2280 | 2285 | def const_ploteo_vRF(self,val_ch,data_weather,data_ele,res,ang_max,ang_min): |
|
|
2281 | 2286 | |
|
|
2282 | 2287 | data_ele_new ,data_ele_old= self.globalCheckPED(data_ele,1) |
|
|
2283 | 2288 | |
|
|
2284 | 2289 | data_ele = data_ele_old.copy() |
|
|
2285 | 2290 | |
|
|
2286 | 2291 | diff_1 = ang_max - data_ele[0] |
|
|
2287 | 2292 | angles_1_nan = numpy.linspace(ang_max,data_ele[0]+1,int(diff_1)-1)#*numpy.nan |
|
|
2288 | 2293 | |
|
|
2289 | 2294 | diff_2 = data_ele[-1]-ang_min |
|
|
2290 | 2295 | angles_2_nan = numpy.linspace(data_ele[-1]-1,ang_min,int(diff_2)-1)#*numpy.nan |
|
|
2291 | 2296 | |
|
|
2292 | 2297 | angles_filled = numpy.concatenate((angles_1_nan,data_ele,angles_2_nan)) |
|
|
2293 | 2298 | |
|
|
2294 | 2299 | print(angles_filled) |
|
|
2295 | 2300 | |
|
|
2296 | 2301 | data_1_nan = numpy.ones([angles_1_nan.shape[0],len(self.r_mask)])*numpy.nan |
|
|
2297 | 2302 | data_2_nan = numpy.ones([angles_2_nan.shape[0],len(self.r_mask)])*numpy.nan |
|
|
2298 | 2303 | |
|
|
2299 | 2304 | data_filled = numpy.concatenate((data_1_nan,data_weather,data_2_nan),axis=0) |
|
|
2300 | 2305 | #val_mean = numpy.mean(data_weather[:,-1]) |
|
|
2301 | 2306 | #self.val_mean = val_mean |
|
|
2302 | 2307 | print(data_filled) |
|
|
2303 | 2308 | data_filled = self.replaceNAN(data_weather=data_filled,data_ele=angles_filled,val=numpy.nan) |
|
|
2304 | 2309 | |
|
|
2305 | 2310 | print(data_filled) |
|
|
2306 | 2311 | print(data_filled.shape) |
|
|
2307 | 2312 | print(angles_filled.shape) |
|
|
2308 | 2313 | |
|
|
2309 | 2314 | return data_filled,angles_filled |
|
|
2310 | 2315 | |
|
|
2311 | 2316 | def plot(self): |
|
|
2312 | 2317 | thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S') |
|
|
2313 | 2318 | data = self.data[-1] |
|
|
2314 | 2319 | r = self.data.yrange |
|
|
2315 | 2320 | delta_height = r[1]-r[0] |
|
|
2316 | 2321 | r_mask = numpy.where(r>=0)[0] |
|
|
2317 | 2322 | self.r_mask =r_mask |
|
|
2318 | 2323 | ##print("delta_height",delta_height) |
|
|
2319 | 2324 | #print("r_mask",r_mask,len(r_mask)) |
|
|
2320 | 2325 | r = numpy.arange(len(r_mask))*delta_height |
|
|
2321 | 2326 | self.y = 2*r |
|
|
2322 | 2327 | res = 1 |
|
|
2323 | 2328 | ###print("data['weather'].shape[0]",data['weather'].shape[0]) |
|
|
2324 | 2329 | ang_max = self.ang_max |
|
|
2325 | 2330 | ang_min = self.ang_min |
|
|
2326 | 2331 | var_ang =ang_max - ang_min |
|
|
2327 | 2332 | step = (int(var_ang)/(res*data['weather'].shape[0])) |
|
|
2328 | 2333 | ###print("step",step) |
|
|
2329 | 2334 | #-------------------------------------------------------- |
|
|
2330 | 2335 | ##print('weather',data['weather'].shape) |
|
|
2331 | 2336 | ##print('ele',data['ele'].shape) |
|
|
2332 | 2337 | |
|
|
2333 | 2338 | ###self.res_weather, self.res_ele = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min) |
|
|
2334 | 2339 | ###self.res_azi = numpy.mean(data['azi']) |
|
|
2335 | 2340 | ###print("self.res_ele",self.res_ele) |
|
|
2336 | 2341 | |
|
|
2337 | 2342 | plt.clf() |
|
|
2338 | 2343 | subplots = [121, 122] |
|
|
2339 | 2344 | #if self.ini==0: |
|
|
2340 | 2345 | #self.res_weather= numpy.ones([self.nplots,int(var_ang),len(r_mask)])*numpy.nan |
|
|
2341 | 2346 | #print("SHAPE",self.data_ele_tmp.shape) |
|
|
2342 | 2347 | |
|
|
2343 | 2348 | for i,ax in enumerate(self.axes): |
|
|
2344 | 2349 | res_weather, self.res_ele = self.const_ploteo_vRF(val_ch=i, data_weather=data['weather'][i][:,r_mask],data_ele=data['ele'],res=res,ang_max=ang_max,ang_min=ang_min) |
|
|
2345 | 2350 | self.res_azi = numpy.mean(data['azi']) |
|
|
2346 | 2351 | |
|
|
2347 | 2352 | if ax.firsttime: |
|
|
2348 | 2353 | #plt.clf() |
|
|
2349 | 2354 | print("Frist Plot") |
|
|
2350 | 2355 | print(data['weather'][i][:,r_mask].shape) |
|
|
2351 | 2356 | print(data['ele'].shape) |
|
|
2352 | 2357 | cgax, pm = wrl.vis.plot_rhi(res_weather,r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80) |
|
|
2353 | 2358 | #cgax, pm = wrl.vis.plot_rhi(data['weather'][i][:,r_mask],r=r,th=data['ele'],ax=subplots[i], proj='cg',vmin=20, vmax=80) |
|
|
2354 | 2359 | gh = cgax.get_grid_helper() |
|
|
2355 | 2360 | locs = numpy.linspace(ang_min,ang_max,var_ang+1) |
|
|
2356 | 2361 | gh.grid_finder.grid_locator1 = FixedLocator(locs) |
|
|
2357 | 2362 | gh.grid_finder.tick_formatter1 = DictFormatter(dict([(i, r"${0:.0f}^\circ$".format(i)) for i in locs])) |
|
|
2358 | 2363 | |
|
|
2359 | 2364 | |
|
|
2360 | 2365 | #fig=self.figures[0] |
|
|
2361 | 2366 | else: |
|
|
2362 | 2367 | #plt.clf() |
|
|
2363 | 2368 | print("ELSE PLOT") |
|
|
2364 | 2369 | cgax, pm = wrl.vis.plot_rhi(res_weather,r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80) |
|
|
2365 | 2370 | #cgax, pm = wrl.vis.plot_rhi(data['weather'][i][:,r_mask],r=r,th=data['ele'],ax=subplots[i], proj='cg',vmin=20, vmax=80) |
|
|
2366 | 2371 | gh = cgax.get_grid_helper() |
|
|
2367 | 2372 | locs = numpy.linspace(ang_min,ang_max,var_ang+1) |
|
|
2368 | 2373 | gh.grid_finder.grid_locator1 = FixedLocator(locs) |
|
|
2369 | 2374 | gh.grid_finder.tick_formatter1 = DictFormatter(dict([(i, r"${0:.0f}^\circ$".format(i)) for i in locs])) |
|
|
2370 | 2375 | |
|
|
2371 | 2376 | caax = cgax.parasites[0] |
|
|
2372 | 2377 | paax = cgax.parasites[1] |
|
|
2373 | 2378 | cbar = plt.gcf().colorbar(pm, pad=0.075) |
|
|
2374 | 2379 | caax.set_xlabel('x_range [km]') |
|
|
2375 | 2380 | caax.set_ylabel('y_range [km]') |
|
|
2376 | 2381 | plt.text(1.0, 1.05, 'Elevacion '+str(thisDatetime)+" Step "+str(self.ini)+ " Azi: "+str(round(self.res_azi,2)), transform=caax.transAxes, va='bottom',ha='right') |
|
|
2377 | 2382 | print("***************************self.ini****************************",self.ini) |
|
|
2378 | 2383 | self.ini= self.ini+1 |
|
|
1 | NO CONTENT: modified file | |
| The requested commit or file is too big and content was truncated. Show full diff | |||
General Comments 0
You need to be logged in to leave comments.
Login now