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ParameterReader unit and ParameterWriter operation added
Juan C. Espinoza -
r1232:0f436481ae30
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@@ -1234,11 +1234,11 class PlotterData(object):
1234 1234 if plot == 'snr':
1235 1235 buffer = 10*numpy.log10(dataOut.data_SNR)
1236 1236 if plot == 'dop':
1237 buffer = 10*numpy.log10(dataOut.data_DOP)
1238 if plot == 'mean':
1239 buffer = dataOut.data_MEAN
1240 if plot == 'std':
1241 buffer = dataOut.data_STD
1237 buffer = dataOut.data_DOP
1238 if plot == 'pow':
1239 buffer = 10*numpy.log10(dataOut.data_POW)
1240 if plot == 'width':
1241 buffer = dataOut.data_WIDTH
1242 1242 if plot == 'coh':
1243 1243 buffer = dataOut.getCoherence()
1244 1244 if plot == 'phase':
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@@ -1205,7 +1205,7 class JRODataReader(JRODataIO):
1205 1205
1206 1206 thisDate = getDateFromRadarFile(thisFile)
1207 1207
1208 if thisDate in dateList:
1208 if thisDate in dateList or single_path in pathList:
1209 1209 continue
1210 1210
1211 1211 dateList.append(thisDate)
@@ -1599,10 +1599,10 class JRODataWriter(JRODataIO):
1599 1599 self.basicHeaderObj.size = self.basicHeaderSize # bytes
1600 1600 self.basicHeaderObj.version = self.versionFile
1601 1601 self.basicHeaderObj.dataBlock = self.nTotalBlocks
1602
1602 log.warning(datetime.datetime.fromtimestamp(self.dataOut.utctime))
1603 1603 utc = numpy.floor(self.dataOut.utctime)
1604 1604 milisecond = (self.dataOut.utctime - utc) * 1000.0
1605
1605 log.warning(milisecond)
1606 1606 self.basicHeaderObj.utc = utc
1607 1607 self.basicHeaderObj.miliSecond = milisecond
1608 1608 self.basicHeaderObj.timeZone = self.dataOut.timeZone
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@@ -7,74 +7,44 import datetime
7 7
8 8 from schainpy.model.data.jrodata import *
9 9 from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation, MPDecorator
10 # from .jroIO_base import *
11 10 from schainpy.model.io.jroIO_base import *
12 import schainpy
13 11 from schainpy.utils import log
14 12
15 13 @MPDecorator
16 14 class ParamReader(JRODataReader,ProcessingUnit):
17 15 '''
18 16 Reads HDF5 format files
19
20 17 path
21
22 18 startDate
23
24 19 endDate
25
26 20 startTime
27
28 21 endTime
29 22 '''
30 23
31 24 ext = ".hdf5"
32
33 25 optchar = "D"
34
35 26 timezone = None
36
37 27 startTime = None
38
39 28 endTime = None
40
41 29 fileIndex = None
42
43 30 utcList = None #To select data in the utctime list
44
45 31 blockList = None #List to blocks to be read from the file
46
47 32 blocksPerFile = None #Number of blocks to be read
48
49 33 blockIndex = None
50
51 34 path = None
52
53 35 #List of Files
54
55 36 filenameList = None
56
57 37 datetimeList = None
58
59 38 #Hdf5 File
60
61 39 listMetaname = None
62
63 40 listMeta = None
64
65 41 listDataname = None
66
67 42 listData = None
68
69 43 listShapes = None
70
71 44 fp = None
72
73 45 #dataOut reconstruction
74
75 46 dataOut = None
76 47
77
78 48 def __init__(self):#, **kwargs):
79 49 ProcessingUnit.__init__(self) #, **kwargs)
80 50 self.dataOut = Parameters()
@@ -152,7 +122,6 class ParamReader(JRODataReader,ProcessingUnit):
152 122 #----------------------------------------------------------------------------------
153 123
154 124 for thisPath in pathList:
155 # thisPath = pathList[pathDict[file]]
156 125
157 126 fileList = glob.glob1(thisPath, "*%s" %ext)
158 127 fileList.sort()
@@ -191,13 +160,9 class ParamReader(JRODataReader,ProcessingUnit):
191 160
192 161 Inputs:
193 162 filename : nombre completo del archivo de datos en formato Jicamarca (.r)
194
195 163 startDate : fecha inicial del rango seleccionado en formato datetime.date
196
197 164 endDate : fecha final del rango seleccionado en formato datetime.date
198
199 165 startTime : tiempo inicial del rango seleccionado en formato datetime.time
200
201 166 endTime : tiempo final del rango seleccionado en formato datetime.time
202 167
203 168 Return:
@@ -217,7 +182,7 class ParamReader(JRODataReader,ProcessingUnit):
217 182 except IOError:
218 183 traceback.print_exc()
219 184 raise IOError("The file %s can't be opened" %(filename))
220 #chino rata
185
221 186 #In case has utctime attribute
222 187 grp2 = grp1['utctime']
223 188 # thisUtcTime = grp2.value[0] - 5*3600 #To convert to local time
@@ -229,7 +194,6 class ParamReader(JRODataReader,ProcessingUnit):
229 194 thisUtcTime -= 5*3600
230 195
231 196 thisDatetime = datetime.datetime.fromtimestamp(thisUtcTime[0] + 5*3600)
232 # thisDatetime = datetime.datetime.fromtimestamp(thisUtcTime[0])
233 197 thisDate = thisDatetime.date()
234 198 thisTime = thisDatetime.time()
235 199
@@ -269,24 +233,18 class ParamReader(JRODataReader,ProcessingUnit):
269 233 idFile = self.fileIndex
270 234
271 235 if not(idFile < len(self.filenameList)):
272 print("No more Files")
236 self.dataOut.error = "No more Files"
273 237 return 0
274 238
275 239 filename = self.filenameList[idFile]
276
277 240 filePointer = h5py.File(filename,'r')
278
279 241 self.filename = filename
280
281 242 self.fp = filePointer
282 243
283 244 print("Setting the file: %s"%self.filename)
284 245
285 # self.__readMetadata()
286 246 self.__setBlockList()
287 247 self.__readData()
288 # self.nRecords = self.fp['Data'].attrs['blocksPerFile']
289 # self.nRecords = self.fp['Data'].attrs['nRecords']
290 248 self.blockIndex = 0
291 249 return 1
292 250
@@ -333,28 +291,14 class ParamReader(JRODataReader,ProcessingUnit):
333 291 Reads Metadata
334 292
335 293 self.pathMeta
336
337 294 self.listShapes
338 295 self.listMetaname
339 296 self.listMeta
340 297
341 298 '''
342 299
343 # grp = self.fp['Data']
344 # pathMeta = os.path.join(self.path, grp.attrs['metadata'])
345 #
346 # if pathMeta == self.pathMeta:
347 # return
348 # else:
349 # self.pathMeta = pathMeta
350 #
351 # filePointer = h5py.File(self.pathMeta,'r')
352 # groupPointer = filePointer['Metadata']
353
354 300 filename = self.filenameList[0]
355
356 301 fp = h5py.File(filename,'r')
357
358 302 gp = fp['Metadata']
359 303
360 304 listMetaname = []
@@ -372,9 +316,6 class ParamReader(JRODataReader,ProcessingUnit):
372 316 listMetaname.append(name)
373 317 listMetadata.append(data)
374 318
375 # if name=='type':
376 # self.__initDataOut(data)
377
378 319 self.listShapes = listShapes
379 320 self.listMetaname = listMetaname
380 321 self.listMeta = listMetadata
@@ -401,17 +342,11 class ParamReader(JRODataReader,ProcessingUnit):
401 342 def __setDataArray(self, dataset, shapes):
402 343
403 344 nDims = shapes[0]
404
405 345 nDim2 = shapes[1] #Dimension 0
406
407 346 nDim1 = shapes[2] #Dimension 1, number of Points or Parameters
408
409 347 nDim0 = shapes[3] #Dimension 2, number of samples or ranges
410
411 348 mode = shapes[4] #Mode of storing
412
413 349 blockList = self.blockList
414
415 350 blocksPerFile = self.blocksPerFile
416 351
417 352 #Depending on what mode the data was stored
@@ -517,7 +452,6 class ParamReader(JRODataReader,ProcessingUnit):
517 452
518 453 if not(self.isConfig):
519 454 self.setup(**kwargs)
520 # self.setObjProperties()
521 455 self.isConfig = True
522 456
523 457 self.getData()
@@ -530,18 +464,12 class ParamWriter(Operation):
530 464 HDF5 Writer, stores parameters data in HDF5 format files
531 465
532 466 path: path where the files will be stored
533
534 467 blocksPerFile: number of blocks that will be saved in per HDF5 format file
535
536 468 mode: selects the data stacking mode: '0' channels, '1' parameters, '3' table (for meteors)
537
538 469 metadataList: list of attributes that will be stored as metadata
539
540 470 dataList: list of attributes that will be stores as data
541
542 471 '''
543 472
544
545 473 ext = ".hdf5"
546 474 optchar = "D"
547 475 metaoptchar = "M"
@@ -1035,3 +963,582 class ParamWriter(Operation):
1035 963 self.putData()
1036 964 return
1037 965
966
967 @MPDecorator
968 class ParameterReader(JRODataReader,ProcessingUnit):
969 '''
970 Reads HDF5 format files
971 '''
972
973 ext = ".hdf5"
974 optchar = "D"
975 timezone = None
976 startTime = None
977 endTime = None
978 fileIndex = None
979 blockList = None #List to blocks to be read from the file
980 blocksPerFile = None #Number of blocks to be read
981 blockIndex = None
982 path = None
983 #List of Files
984 filenameList = None
985 datetimeList = None
986 #Hdf5 File
987 listMetaname = None
988 listMeta = None
989 listDataname = None
990 listData = None
991 listShapes = None
992 fp = None
993 #dataOut reconstruction
994 dataOut = None
995
996 def __init__(self):
997 ProcessingUnit.__init__(self)
998 self.dataOut = Parameters()
999 return
1000
1001 def setup(self, **kwargs):
1002
1003 path = kwargs['path']
1004 startDate = kwargs['startDate']
1005 endDate = kwargs['endDate']
1006 startTime = kwargs['startTime']
1007 endTime = kwargs['endTime']
1008 walk = kwargs['walk']
1009 if 'ext' in kwargs:
1010 ext = kwargs['ext']
1011 else:
1012 ext = '.hdf5'
1013 if 'timezone' in kwargs:
1014 self.timezone = kwargs['timezone']
1015 else:
1016 self.timezone = 'lt'
1017
1018 print("[Reading] Searching files in offline mode ...")
1019 pathList, filenameList = self.searchFilesOffLine(path, startDate=startDate, endDate=endDate,
1020 startTime=startTime, endTime=endTime,
1021 ext=ext, walk=walk)
1022
1023 if not(filenameList):
1024 print("There is no files into the folder: %s"%(path))
1025 sys.exit(-1)
1026
1027 self.fileIndex = -1
1028 self.startTime = startTime
1029 self.endTime = endTime
1030 self.__readMetadata()
1031 self.__setNextFileOffline()
1032
1033 return
1034
1035 def searchFilesOffLine(self, path, startDate=None, endDate=None, startTime=datetime.time(0,0,0), endTime=datetime.time(23,59,59), ext='.hdf5', walk=True):
1036
1037 expLabel = ''
1038 self.filenameList = []
1039 self.datetimeList = []
1040 pathList = []
1041 dateList, pathList = self.findDatafiles(path, startDate, endDate, expLabel, ext, walk, include_path=True)
1042
1043 if dateList == []:
1044 print("[Reading] No *%s files in %s from %s to %s)"%(ext, path,
1045 datetime.datetime.combine(startDate,startTime).ctime(),
1046 datetime.datetime.combine(endDate,endTime).ctime()))
1047
1048 return None, None
1049
1050 if len(dateList) > 1:
1051 print("[Reading] %d days were found in date range: %s - %s" %(len(dateList), startDate, endDate))
1052 else:
1053 print("[Reading] data was found for the date %s" %(dateList[0]))
1054
1055 filenameList = []
1056 datetimeList = []
1057
1058 for thisPath in pathList:
1059
1060 fileList = glob.glob1(thisPath, "*%s" %ext)
1061 fileList.sort()
1062
1063 for file in fileList:
1064
1065 filename = os.path.join(thisPath,file)
1066
1067 if not isFileInDateRange(filename, startDate, endDate):
1068 continue
1069
1070 thisDatetime = self.__isFileInTimeRange(filename, startDate, endDate, startTime, endTime)
1071
1072 if not(thisDatetime):
1073 continue
1074
1075 filenameList.append(filename)
1076 datetimeList.append(thisDatetime)
1077
1078 if not(filenameList):
1079 print("[Reading] Any file was found int time range %s - %s" %(datetime.datetime.combine(startDate,startTime).ctime(), datetime.datetime.combine(endDate,endTime).ctime()))
1080 return None, None
1081
1082 print("[Reading] %d file(s) was(were) found in time range: %s - %s" %(len(filenameList), startTime, endTime))
1083 print()
1084
1085 self.filenameList = filenameList
1086 self.datetimeList = datetimeList
1087
1088 return pathList, filenameList
1089
1090 def __isFileInTimeRange(self,filename, startDate, endDate, startTime, endTime):
1091
1092 """
1093 Retorna 1 si el archivo de datos se encuentra dentro del rango de horas especificado.
1094
1095 Inputs:
1096 filename : nombre completo del archivo de datos en formato Jicamarca (.r)
1097 startDate : fecha inicial del rango seleccionado en formato datetime.date
1098 endDate : fecha final del rango seleccionado en formato datetime.date
1099 startTime : tiempo inicial del rango seleccionado en formato datetime.time
1100 endTime : tiempo final del rango seleccionado en formato datetime.time
1101
1102 Return:
1103 Boolean : Retorna True si el archivo de datos contiene datos en el rango de
1104 fecha especificado, de lo contrario retorna False.
1105
1106 Excepciones:
1107 Si el archivo no existe o no puede ser abierto
1108 Si la cabecera no puede ser leida.
1109
1110 """
1111
1112 try:
1113 fp = h5py.File(filename, 'r')
1114 grp1 = fp['Data']
1115
1116 except IOError:
1117 traceback.print_exc()
1118 raise IOError("The file %s can't be opened" %(filename))
1119 #In case has utctime attribute
1120 grp2 = grp1['utctime']
1121 thisUtcTime = grp2.value[0]
1122
1123 fp.close()
1124
1125 if self.timezone == 'lt':
1126 thisUtcTime -= 5*3600
1127
1128 thisDatetime = datetime.datetime.fromtimestamp(thisUtcTime + 5*3600)
1129 thisDate = thisDatetime.date()
1130 thisTime = thisDatetime.time()
1131
1132 startUtcTime = (datetime.datetime.combine(thisDate,startTime)- datetime.datetime(1970, 1, 1)).total_seconds()
1133 endUtcTime = (datetime.datetime.combine(thisDate,endTime)- datetime.datetime(1970, 1, 1)).total_seconds()
1134
1135 #General case
1136 # o>>>>>>>>>>>>>><<<<<<<<<<<<<<o
1137 #-----------o----------------------------o-----------
1138 # startTime endTime
1139
1140 if endTime >= startTime:
1141 thisUtcLog = numpy.logical_and(thisUtcTime > startUtcTime, thisUtcTime < endUtcTime)
1142 if numpy.any(thisUtcLog): #If there is one block between the hours mentioned
1143 return thisDatetime
1144 return None
1145
1146 #If endTime < startTime then endTime belongs to the next day
1147 #<<<<<<<<<<<o o>>>>>>>>>>>
1148 #-----------o----------------------------o-----------
1149 # endTime startTime
1150
1151 if (thisDate == startDate) and numpy.all(thisUtcTime < startUtcTime):
1152 return None
1153
1154 if (thisDate == endDate) and numpy.all(thisUtcTime > endUtcTime):
1155 return None
1156
1157 if numpy.all(thisUtcTime < startUtcTime) and numpy.all(thisUtcTime > endUtcTime):
1158 return None
1159
1160 return thisDatetime
1161
1162 def __setNextFileOffline(self):
1163
1164 self.fileIndex += 1
1165 idFile = self.fileIndex
1166
1167 if not(idFile < len(self.filenameList)):
1168 self.dataOut.error = 'No more files'
1169 return 0
1170
1171 filename = self.filenameList[idFile]
1172 self.fp = h5py.File(filename, 'r')
1173 self.filename = filename
1174
1175 print("Setting the file: %s"%self.filename)
1176
1177 self.__setBlockList()
1178 self.__readData()
1179 self.blockIndex = 0
1180 return 1
1181
1182 def __setBlockList(self):
1183 '''
1184 Selects the data within the times defined
1185
1186 self.fp
1187 self.startTime
1188 self.endTime
1189 self.blockList
1190 self.blocksPerFile
1191
1192 '''
1193 fp = self.fp
1194 startTime = self.startTime
1195 endTime = self.endTime
1196
1197 grp = fp['Data']
1198 thisUtcTime = grp['utctime'].value.astype(numpy.float)[0]
1199
1200 if self.timezone == 'lt':
1201 thisUtcTime -= 5*3600
1202
1203 thisDatetime = datetime.datetime.fromtimestamp(thisUtcTime + 5*3600)
1204
1205 thisDate = thisDatetime.date()
1206 thisTime = thisDatetime.time()
1207
1208 startUtcTime = (datetime.datetime.combine(thisDate,startTime) - datetime.datetime(1970, 1, 1)).total_seconds()
1209 endUtcTime = (datetime.datetime.combine(thisDate,endTime) - datetime.datetime(1970, 1, 1)).total_seconds()
1210
1211 ind = numpy.where(numpy.logical_and(thisUtcTime >= startUtcTime, thisUtcTime < endUtcTime))[0]
1212
1213 self.blockList = ind
1214 self.blocksPerFile = len(ind)
1215
1216 return
1217
1218 def __readMetadata(self):
1219 '''
1220 Reads Metadata
1221 '''
1222
1223 filename = self.filenameList[0]
1224 fp = h5py.File(filename, 'r')
1225 gp = fp['Metadata']
1226 listMetaname = []
1227 listMetadata = []
1228
1229 for item in list(gp.items()):
1230 name = item[0]
1231
1232 if name=='variables':
1233 table = gp[name][:]
1234 listShapes = {}
1235 for shapes in table:
1236 listShapes[shapes[0].decode()] = numpy.array([shapes[1]])
1237 else:
1238 data = gp[name].value
1239 listMetaname.append(name)
1240 listMetadata.append(data)
1241
1242 self.listShapes = listShapes
1243 self.listMetaname = listMetaname
1244 self.listMeta = listMetadata
1245
1246 fp.close()
1247 return
1248
1249 def __readData(self):
1250
1251 grp = self.fp['Data']
1252 listdataname = []
1253 listdata = []
1254
1255 for item in list(grp.items()):
1256 name = item[0]
1257 listdataname.append(name)
1258 dim = self.listShapes[name][0]
1259 if dim == 0:
1260 array = grp[name].value
1261 else:
1262 array = []
1263 for i in range(dim):
1264 array.append(grp[name]['table{:02d}'.format(i)].value)
1265 array = numpy.array(array)
1266
1267 listdata.append(array)
1268
1269 self.listDataname = listdataname
1270 self.listData = listdata
1271 return
1272
1273 def getData(self):
1274
1275 for i in range(len(self.listMeta)):
1276 setattr(self.dataOut, self.listMetaname[i], self.listMeta[i])
1277
1278 for j in range(len(self.listData)):
1279 dim = self.listShapes[self.listDataname[j]][0]
1280 if dim == 0:
1281 setattr(self.dataOut, self.listDataname[j], self.listData[j][self.blockIndex])
1282 else:
1283 setattr(self.dataOut, self.listDataname[j], self.listData[j][:,self.blockIndex])
1284
1285 self.dataOut.flagNoData = False
1286 self.blockIndex += 1
1287
1288 return
1289
1290 def run(self, **kwargs):
1291
1292 if not(self.isConfig):
1293 self.setup(**kwargs)
1294 self.isConfig = True
1295
1296 if self.blockIndex == self.blocksPerFile:
1297 if not(self.__setNextFileOffline()):
1298 self.dataOut.flagNoData = True
1299 return 0
1300
1301 self.getData()
1302
1303 return
1304
1305 @MPDecorator
1306 class ParameterWriter(Operation):
1307 '''
1308 HDF5 Writer, stores parameters data in HDF5 format files
1309
1310 path: path where the files will be stored
1311 blocksPerFile: number of blocks that will be saved in per HDF5 format file
1312 mode: selects the data stacking mode: '0' channels, '1' parameters, '3' table (for meteors)
1313 metadataList: list of attributes that will be stored as metadata
1314 dataList: list of attributes that will be stores as data
1315 '''
1316
1317
1318 ext = ".hdf5"
1319 optchar = "D"
1320 metaoptchar = "M"
1321 metaFile = None
1322 filename = None
1323 path = None
1324 setFile = None
1325 fp = None
1326 grp = None
1327 ds = None
1328 firsttime = True
1329 #Configurations
1330 blocksPerFile = None
1331 blockIndex = None
1332 dataOut = None
1333 #Data Arrays
1334 dataList = None
1335 metadataList = None
1336 dsList = None #List of dictionaries with dataset properties
1337 tableDim = None
1338 dtype = [('name', 'S20'),('nDim', 'i')]
1339 currentDay = None
1340 lastTime = None
1341
1342 def __init__(self):
1343
1344 Operation.__init__(self)
1345 return
1346
1347 def setup(self, path=None, blocksPerFile=10, metadataList=None, dataList=None, setType=None):
1348 self.path = path
1349 self.blocksPerFile = blocksPerFile
1350 self.metadataList = metadataList
1351 self.dataList = dataList
1352 self.setType = setType
1353
1354 tableList = []
1355 dsList = []
1356
1357 for i in range(len(self.dataList)):
1358 dsDict = {}
1359 dataAux = getattr(self.dataOut, self.dataList[i])
1360 dsDict['variable'] = self.dataList[i]
1361
1362 if dataAux is None:
1363 continue
1364 elif isinstance(dataAux, (int, float, numpy.integer, numpy.float)):
1365 dsDict['nDim'] = 0
1366 else:
1367 dsDict['nDim'] = len(dataAux.shape)
1368 dsDict['shape'] = dataAux.shape
1369 dsDict['dsNumber'] = dataAux.shape[0]
1370
1371 dsList.append(dsDict)
1372 tableList.append((self.dataList[i], dsDict['nDim']))
1373
1374 self.dsList = dsList
1375 self.tableDim = numpy.array(tableList, dtype=self.dtype)
1376 self.currentDay = self.dataOut.datatime.date()
1377
1378 def timeFlag(self):
1379 currentTime = self.dataOut.utctime
1380 timeTuple = time.localtime(currentTime)
1381 dataDay = timeTuple.tm_yday
1382
1383 if self.lastTime is None:
1384 self.lastTime = currentTime
1385 self.currentDay = dataDay
1386 return False
1387
1388 timeDiff = currentTime - self.lastTime
1389
1390 #Si el dia es diferente o si la diferencia entre un dato y otro supera la hora
1391 if dataDay != self.currentDay:
1392 self.currentDay = dataDay
1393 return True
1394 elif timeDiff > 3*60*60:
1395 self.lastTime = currentTime
1396 return True
1397 else:
1398 self.lastTime = currentTime
1399 return False
1400
1401 def run(self, dataOut, path, blocksPerFile=10, metadataList=None, dataList=None, setType=None):
1402
1403 self.dataOut = dataOut
1404 if not(self.isConfig):
1405 self.setup(path=path, blocksPerFile=blocksPerFile,
1406 metadataList=metadataList, dataList=dataList,
1407 setType=setType)
1408
1409 self.isConfig = True
1410 self.setNextFile()
1411
1412 self.putData()
1413 return
1414
1415 def setNextFile(self):
1416
1417 ext = self.ext
1418 path = self.path
1419 setFile = self.setFile
1420
1421 timeTuple = time.localtime(self.dataOut.utctime)
1422 subfolder = 'd%4.4d%3.3d' % (timeTuple.tm_year,timeTuple.tm_yday)
1423 fullpath = os.path.join(path, subfolder)
1424
1425 if os.path.exists(fullpath):
1426 filesList = os.listdir(fullpath)
1427 filesList = [k for k in filesList if k.startswith(self.optchar)]
1428 if len( filesList ) > 0:
1429 filesList = sorted(filesList, key=str.lower)
1430 filen = filesList[-1]
1431 # el filename debera tener el siguiente formato
1432 # 0 1234 567 89A BCDE (hex)
1433 # x YYYY DDD SSS .ext
1434 if isNumber(filen[8:11]):
1435 setFile = int(filen[8:11]) #inicializo mi contador de seteo al seteo del ultimo file
1436 else:
1437 setFile = -1
1438 else:
1439 setFile = -1 #inicializo mi contador de seteo
1440 else:
1441 os.makedirs(fullpath)
1442 setFile = -1 #inicializo mi contador de seteo
1443
1444 if self.setType is None:
1445 setFile += 1
1446 file = '%s%4.4d%3.3d%03d%s' % (self.optchar,
1447 timeTuple.tm_year,
1448 timeTuple.tm_yday,
1449 setFile,
1450 ext )
1451 else:
1452 setFile = timeTuple.tm_hour*60+timeTuple.tm_min
1453 file = '%s%4.4d%3.3d%04d%s' % (self.optchar,
1454 timeTuple.tm_year,
1455 timeTuple.tm_yday,
1456 setFile,
1457 ext )
1458
1459 self.filename = os.path.join( path, subfolder, file )
1460
1461 #Setting HDF5 File
1462 self.fp = h5py.File(self.filename, 'w')
1463 #write metadata
1464 self.writeMetadata(self.fp)
1465 #Write data
1466 self.writeData(self.fp)
1467
1468 def writeMetadata(self, fp):
1469
1470 grp = fp.create_group("Metadata")
1471 grp.create_dataset('variables', data=self.tableDim, dtype=self.dtype)
1472
1473 for i in range(len(self.metadataList)):
1474 if not hasattr(self.dataOut, self.metadataList[i]):
1475 log.warning('Metadata: `{}` not found'.format(self.metadataList[i]), self.name)
1476 continue
1477 value = getattr(self.dataOut, self.metadataList[i])
1478 grp.create_dataset(self.metadataList[i], data=value)
1479 return
1480
1481 def writeData(self, fp):
1482
1483 grp = fp.create_group("Data")
1484 dtsets = []
1485 data = []
1486
1487 for dsInfo in self.dsList:
1488 if dsInfo['nDim'] == 0:
1489 ds = grp.create_dataset(
1490 dsInfo['variable'],
1491 (self.blocksPerFile, ),
1492 chunks=True,
1493 dtype=numpy.float64)
1494 dtsets.append(ds)
1495 data.append((dsInfo['variable'], -1))
1496 else:
1497 sgrp = grp.create_group(dsInfo['variable'])
1498 for i in range(dsInfo['dsNumber']):
1499 ds = sgrp.create_dataset(
1500 'table{:02d}'.format(i),
1501 (self.blocksPerFile, ) + dsInfo['shape'][1:],
1502 chunks=True)
1503 dtsets.append(ds)
1504 data.append((dsInfo['variable'], i))
1505 fp.flush()
1506
1507 log.log('creating file: {}'.format(fp.filename), 'Writing')
1508
1509 self.ds = dtsets
1510 self.data = data
1511 self.firsttime = True
1512 self.blockIndex = 0
1513 return
1514
1515 def putData(self):
1516
1517 if (self.blockIndex == self.blocksPerFile) or self.timeFlag():
1518 self.closeFile()
1519 self.setNextFile()
1520
1521 for i, ds in enumerate(self.ds):
1522 attr, ch = self.data[i]
1523 if ch == -1:
1524 ds[self.blockIndex] = getattr(self.dataOut, attr)
1525 else:
1526 ds[self.blockIndex] = getattr(self.dataOut, attr)[ch]
1527
1528 self.fp.flush()
1529 self.blockIndex += 1
1530
1531 return
1532
1533 def closeFile(self):
1534
1535 if self.blockIndex != self.blocksPerFile:
1536 for ds in self.ds:
1537 ds.resize(self.blockIndex, axis=0)
1538
1539 self.fp.flush()
1540 self.fp.close()
1541
1542 def close(self):
1543
1544 self.closeFile()
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