def _getIndex(self, cellId): """ returns the cell index of a sample location """ nrCells = PCRaster.clone().nrRows() * PCRaster.clone().nrCols() found = False cell = 1 index = 0 while found == False and cell <= nrCells: if PCRaster.cellvalue(self._spatialId, cell)[1] == True and PCRaster.cellvalue( self._spatialId, cell)[0] == cellId: index = cell found = True cell += 1 return index
monthlyArchiveFile= 'cru_alpha_sc_results.zip' specificQArchiveFile= 'cru_specificrunoff_results.zip' rootQSpecFileNames= ['waterrunoff%s.map','landrunoff%s.map'] rootQFileName= 'qc' MV= -999. startYear= 1958; endYear= 2001 yearList= range(startYear,endYear+1) rootR3AVGFileName= 'r3_avg%s.map' LDD= pcr.readmap('glwd_lddlake.map') LDDBasins= pcr.readmap('glwd130m_ldd.map') cellArea= pcr.readmap('cellarea30.map') fracWat= pcr.readmap('glwd130m_fracw.map') lakeMask= pcr.readmap('lake.map') != 0 catchments= pcr.catchment(LDDBasins,pcr.pit(LDDBasins)) pcr.report(catchments,'catchments.map') maximumCatchmentID= pcr.cellvalue(pcr.mapmaximum(pcr.scalar(catchments)),1)[0] catchmentSizeLimit= 0. #-main #-opening zip file print 'extracting information from zip file' currentPath= os.getcwd() zipArchive= zipfile.ZipFile(monthlyArchiveFile) print 'processing maps: discharge over %d-%d' % (startYear,endYear) iCnt= 0 yearStartPos= len(rootQFileName) yearEndPos= yearStartPos+4 #-loop through zip file and retrieve relevant maps for fileName in zipArchive.namelist(): if rootQFileName in fileName and not 'ini' in fileName:
def __init__(self, tssFilename, model, idMap=None, noHeader=False): """ """ if not isinstance(tssFilename, str): raise Exception( "timeseries output filename must be of type string") self._outputFilename = tssFilename self._maxId = 1 self._spatialId = None self._spatialDatatype = None self._spatialIdGiven = False self._userModel = model self._writeHeader = not noHeader # array to store the timestep values self._sampleValues = None _idMap = False #if isinstance(idMap, str) or isinstance(idMap, PCRaster._PCRaster.Field): if isinstance(idMap, str) or isinstance(idMap, PCRaster._pcraster.Field): _idMap = True nrRows = self._userModel.nrTimeSteps() - self._userModel.firstTimeStep( ) + 1 if _idMap: self._spatialId = idMap if isinstance(idMap, str): self._spatialId = PCRaster.readmap(idMap) _allowdDataTypes = [ PCRaster.Nominal, PCRaster.Ordinal, PCRaster.Boolean ] if self._spatialId.dataType() not in _allowdDataTypes: raise Exception( "idMap must be of type Nominal, Ordinal or Boolean") if self._spatialId.isSpatial(): self._maxId, valid = PCRaster.cellvalue( PCRaster.mapmaximum(PCRaster.ordinal(self._spatialId)), 1) else: self._maxId = 1 # cell indices of the sample locations self._sampleAddresses = [] for cellId in range(1, self._maxId + 1): thecellId = self._getIndex(cellId) if thecellId != 0: self._sampleAddresses.append(thecellId) else: print "CellId " + str(cellId) + " not found." self._spatialIdGiven = True nrCols = self._maxId self._sampleValues = [[Decimal("NaN")] * nrCols for _ in [0] * nrRows] else: self._sampleValues = [[Decimal("NaN")] * 1 for _ in [0] * nrRows]
class wf_TimeoutputTimeseries(object): """ Class to create pcrcalc timeoutput style timeseries """ def __init__(self, tssFilename, model, idMap=None, noHeader=False): """ """ if not isinstance(tssFilename, str): raise Exception( "timeseries output filename must be of type string") self._outputFilename = tssFilename self._maxId = 1 self._spatialId = None self._spatialDatatype = None self._spatialIdGiven = False self._userModel = model self._writeHeader = not noHeader # array to store the timestep values self._sampleValues = None _idMap = False #if isinstance(idMap, str) or isinstance(idMap, PCRaster._PCRaster.Field): if isinstance(idMap, str) or isinstance(idMap, PCRaster._pcraster.Field): _idMap = True nrRows = self._userModel.nrTimeSteps() - self._userModel.firstTimeStep( ) + 1 if _idMap: self._spatialId = idMap if isinstance(idMap, str): self._spatialId = PCRaster.readmap(idMap) _allowdDataTypes = [ PCRaster.Nominal, PCRaster.Ordinal, PCRaster.Boolean ] if self._spatialId.dataType() not in _allowdDataTypes: raise Exception( "idMap must be of type Nominal, Ordinal or Boolean") if self._spatialId.isSpatial(): self._maxId, valid = PCRaster.cellvalue( PCRaster.mapmaximum(PCRaster.ordinal(self._spatialId)), 1) else: self._maxId = 1 # cell indices of the sample locations self._sampleAddresses = [] for cellId in range(1, self._maxId + 1): thecellId = self._getIndex(cellId) if thecellId != 0: self._sampleAddresses.append(thecellId) else: print "CellId " + str(cellId) + " not found." self._spatialIdGiven = True nrCols = self._maxId self._sampleValues = [[Decimal("NaN")] * nrCols for _ in [0] * nrRows] else: self._sampleValues = [[Decimal("NaN")] * 1 for _ in [0] * nrRows] def _getIndex(self, cellId): """ returns the cell index of a sample location """ nrCells = PCRaster.clone().nrRows() * PCRaster.clone().nrCols() found = False cell = 1 index = 0 while found == False and cell <= nrCells: if PCRaster.cellvalue(self._spatialId, cell)[1] == True and PCRaster.cellvalue( self._spatialId, cell)[0] == cellId: index = cell found = True cell += 1 return index def sample(self, expression): """ Sampling the current values of 'expression' at the given locations for the current timestep """ arrayRowPos = self._userModel.currentTimeStep( ) - self._userModel.firstTimeStep() #if isinstance(expression, float): # expression = PCRaster.scalar(expression) try: # store the data type for tss file header if self._spatialDatatype == None: self._spatialDatatype = str(expression.dataType()) except AttributeError, e: datatype, sep, tail = str(e).partition(" ") msg = "Argument must be a PCRaster map, type %s given. If necessary use data conversion functions like scalar()" % ( datatype) raise AttributeError(msg) if self._spatialIdGiven: if expression.dataType() == PCRaster.Scalar or expression.dataType( ) == PCRaster.Directional: tmp = PCRaster.areaaverage(PCRaster.spatial(expression), PCRaster.spatial(self._spatialId)) else: tmp = PCRaster.areamajority(PCRaster.spatial(expression), PCRaster.spatial(self._spatialId)) col = 0 for cellIndex in self._sampleAddresses: value, valid = PCRaster.cellvalue(tmp, cellIndex) if not valid: value = Decimal("NaN") self._sampleValues[arrayRowPos][col] = value col += 1 else: if expression.dataType() == PCRaster.Scalar or expression.dataType( ) == PCRaster.Directional: tmp = PCRaster.maptotal(PCRaster.spatial(expression))\ / PCRaster.maptotal(PCRaster.scalar(PCRaster.defined(PCRaster.spatial(expression)))) else: tmp = PCRaster.mapmaximum(PCRaster.maptotal(PCRaster.areamajority(PCRaster.spatial(expression),\ PCRaster.spatial(PCRaster.nominal(1))))) value, valid = PCRaster.cellvalue(tmp, 1) if not valid: value = Decimal("NaN") self._sampleValues[arrayRowPos] = value if self._userModel.currentTimeStep() == self._userModel.nrTimeSteps(): self._writeTssFile()