def do_yearlyWPAvg(sstdir, sstrootname, variable, outdir, yearStart, yearEnd, threshold=28.5 + 273.15, latWindow=None):
nodata = 1.0e20
varUnits = None
thisFilter = numpy.ones((3, 3))
# thisFilter[1][1]=1
EarthSurface = 510072000
factor = 1 # (2*85*360) /( 360.0*180.0)
areaWP = []
latWindowMatrix = None
for iyear in range(yearStart, yearEnd + 1):
tempAvg = None
wdata = None
weights = None
dimVar = None
counter = None
print "Processing year {0}".format(iyear)
for imonth in range(1, 12 + 1):
idate = "{0}{1:02}".format(iyear, imonth)
fname = "{0}/{1}_{2}.nc".format(sstdir, sstrootname, idate)
thisFile = cdms2.open(fname)
thisVar = numpy.ravel(thisFile[variable][:])
if latWindow is not None:
if latWindowMatrix is None:
latWindowMatrix = numpy.zeros(thisFile[variable].shape)
for ii in xrange(latWindow[0], latWindow[1] + 1):
latWindowMatrix[:, ii] = 1
thisVarTmp = thisVar
thisVar = numpy.multiply(thisVarTmp, numpy.ravel(latWindowMatrix))
if tempAvg is None: # settings
thisGrid = thisFile[variable].getGrid()
if thisGrid is None:
thisGrid = makeGrid()
(latws, lonws) = thisGrid.getWeights()
weights = MV.outerproduct(latws, lonws)
wdata = thisVar < nodata
tempAvg = numpy.zeros(thisVar.shape)
tempAvg[wdata] = thisVar[wdata]
dimVar = numpy.squeeze(thisFile[variable][:]).shape
counter = numpy.zeros(tempAvg.shape, dtype="float")
counter[wdata] = 1
else:
wdata = thisVar < nodata
counter[wdata] = counter[wdata] + 1
tempAvg[wdata] = tempAvg[wdata] + thisVar[wdata]
# compute average
wdivide = counter > 0
avg = numpy.zeros(tempAvg.shape)
if wdivide.any:
avg[wdivide] = tempAvg[wdivide] / counter[wdivide]
# set to areas < threshold
wtzero = avg < threshold
avg[wtzero] = 0
# compute current area
warea = (avg >= threshold) * (avg < nodata)
area = factor * EarthSurface * numpy.ravel(weights)[warea].sum()
areaWP.append([iyear, area])
# create variables
outAreaTmp = numpy.reshape(avg, dimVar)
# filter before saving: grid stiching area: less data for ensemble mean here
outAreaBis = do_interp(outAreaTmp, threshold, nodata, 156, 156 + 3, 0, 4 * 80) # rebuild
outArea = do_convolve(outAreaBis, thisFilter, threshold, nodata, 156 + 2, 156 + 5, 0, 4 * 80) # smoothen
wpOut = cdms2.createVariable(
outArea,
typecode="f",
id="warmpool",
grid=thisGrid,
copyaxes=1,
attributes=dict(long_name="warmpool, average temperature method, year {0}".format(iyear), units=varUnits),
)
# write to file
outfilename = "{0}/warmpool_{1}.nc".format(outdir, iyear)
if os.path.exists(outfilename):
os.remove(outfilename)
outfile = cdms2.open(outfilename, "w")
outfile.write(wpOut)
outfile.close()
# close files
thisFile.close()
return areaWP
def do_yearlyWPall(sstdir, sstrootname, variable, outdir, yearStart, yearEnd, latWindow=None):
threshold = 28 + 273.15
nodata = 1.0e20
varUnits = None
referenceGrid = None
referenceGrid = makeGrid()
latws, lonwts = referenceGrid.getWeights()
weights = MV.outerproduct(latws, lonwts)
EarthSurface = 510072000
areaWP = []
latWindowMatrix = None
for iyear in range(yearStart, yearEnd + 1):
warmpool = None
wnodata = None
maxwarm = None
minWarm = None
print "Processing year {0}".format(iyear)
for imonth in range(1, 12 + 1):
idate = "{0}{1:02}".format(iyear, imonth)
fname = "{0}/{1}_{2}.nc".format(sstdir, sstrootname, idate)
thisFile = cdms2.open(fname)
thisVar = numpy.ravel(thisFile[variable][:])
if latWindow is not None:
if latWindowMatrix is None:
latWindowMatrix = numpy.zeros(thisFile[variable].shape)
for ii in xrange(latWindow[0], latWindow[1] + 1):
latWindowMatrix[:, ii] = 1
thisVarTmp = thisVar
thisVar = numpy.multiply(thisVarTmp, numpy.ravel(latWindowMatrix))
if warmpool is None:
dimVar = numpy.squeeze(thisFile[variable][:]).shape
varUnits = thisFile[variable].units
warmpool = numpy.ravel(numpy.zeros(dimVar))
wnodata = thisVar >= nodata
maxWarm = numpy.ravel(numpy.zeros(dimVar))
minWarm = numpy.ravel(numpy.zeros(dimVar))
monthMin = numpy.ravel(numpy.zeros(dimVar))
monthMax = numpy.ravel(numpy.zeros(dimVar))
# on first iteration, no comparison to the previous state (warmpool>=threshold)
wwp = (thisVar >= threshold) * (thisVar < nodata)
wmax = (thisVar < nodata) * (thisVar > nodata) # set to false, everywhere
wmin = (thisVar < nodata) * (thisVar > nodata) # set to False, everywhere
maxWarm[wwp] = thisVar[wwp]
minWarm[wwp] = thisVar[wwp]
monthMax[wwp] = imonth
monthMin[wwp] = imonth
else:
# warmpool: for all months, temperature > threshold
# means that current value AND memo value are > threshold
wwp = (thisVar >= threshold) * (warmpool >= threshold) * (thisVar < nodata)
wmax = (thisVar >= threshold) * (warmpool >= threshold) * (thisVar < nodata) * (thisVar >= warmpool)
wmin = (thisVar >= threshold) * (warmpool >= threshold) * (thisVar < nodata) * (thisVar < warmpool)
# reset warmpool to 0, to keep only the minimal extension
# we will encode the max and min observed
if wwp.any():
maxWarm[:] = 0
minWarm[:] = 0
maxWarm[wwp] = warmpool[wwp]
if wmax.any():
maxWarm[wmax] = thisVar[wmax]
monthMax[wmax] = imonth
minWarm[wwp] = warmpool[wwp]
if wmin.any():
minWarm[wmin] = thisVar[wmin]
monthMin[wmin] = imonth
warmpool[:] = 0 # reset warmpool to keep intersection between iterations
warmpool[wwp] = thisVar[wwp]
else:
warmpool[:] = 0
thisFile.close()
# ensure mask is set
if wnodata.any():
warmpool[wnodata] = nodata
maxWarm[wnodata] = nodata
minWarm[wnodata] = nodata
monthMin[wnodata] = nodata
monthMax[wnodata] = nodata
wtonull = warmpool == 0
if wtonull.any():
monthMin[wtonull] = 0
monthMax[wtonull] = 0
warea = (warmpool >= threshold) * (warmpool < nodata)
surface = EarthSurface * numpy.ravel(weights)[warea].sum()
areaWP.append([iyear, surface])
wpOut = cdms2.createVariable(
warmpool.reshape(dimVar),
typecode="f",
id="warmpool",
fill_value=nodata,
grid=referenceGrid,
copyaxes=0,
attributes=dict(long_name="warmpool, all temperatures method, year {0}".format(iyear), units=varUnits),
)
wpMax = cdms2.createVariable(
maxWarm.reshape(dimVar),
typecode="f",
id="warmpool_max",
fill_value=nodata,
grid=referenceGrid,
copyaxes=0,
attributes=dict(long_name="warmpool max temperature, year {0}".format(iyear), units=varUnits),
)
wpMin = cdms2.createVariable(
minWarm.reshape(dimVar),
typecode="f",
id="warmpool_min",
fill_value=nodata,
grid=referenceGrid,
copyaxes=0,
attributes=dict(long_name="warmpool min temperature, year {0}".format(iyear), units=varUnits),
)
monthMin = cdms2.createVariable(
monthMin.reshape(dimVar),
typecode="i",
id="min_date",
fill_value=0,
grid=referenceGrid,
copyaxes=0,
attributes=dict(long_name="warmpool month of min(1-12), year {0}".format(iyear), units=varUnits),
)
monthMax = cdms2.createVariable(
monthMax.reshape(dimVar),
typecode="i",
id="max_date",
fill_value=0,
grid=referenceGrid,
copyaxes=0,
attributes=dict(long_name="warmpool month of max(1-12), year {0}".format(iyear), units=varUnits),
)
outfilename = "{0}/warmpool_{1}.nc".format(outdir, iyear)
if os.path.exists(outfilename):
os.remove(outfilename)
outfile = cdms2.open(outfilename, "w")
outfile.write(wpOut)
outfile.write(wpMax)
outfile.write(wpMin)
outfile.write(monthMin)
outfile.write(monthMax)
outfile.close()
return areaWP
