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]
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:
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()
