def test_zrA(self):
gra = _gra.new()
self.assertAlmostEqual(200.0, gra.zrA, 4)
gra.zrA = 10
self.assertAlmostEqual(10.0, gra.zrA, 4)
gra.zrA = 11.1
self.assertAlmostEqual(11.1, gra.zrA, 4)
def test_upperThreshold(self):
gra = _gra.new()
self.assertAlmostEqual(2.0, gra.upperThreshold, 4)
gra.upperThreshold = 10
self.assertAlmostEqual(10.0, gra.upperThreshold, 4)
gra.upperThreshold = 11.1
self.assertAlmostEqual(11.1, gra.upperThreshold, 4)
def test_lowerThreshold(self):
gra = _gra.new()
self.assertAlmostEqual(-0.25, gra.lowerThreshold, 4)
gra.lowerThreshold = 10
self.assertAlmostEqual(10.0, gra.lowerThreshold, 4)
gra.lowerThreshold = 11.1
self.assertAlmostEqual(11.1, gra.lowerThreshold, 4)
def test_apply(self):
distance = _ravefield.new()
distance.setData(numpy.zeros((2, 2), numpy.float64))
distance.setValue(0, 0, 0.1)
distance.setValue(0, 1, 0.2)
distance.setValue(1, 0, 0.3)
distance.setValue(1, 1, 0.4)
distance.addAttribute("what/gain", 10000.0)
distance.addAttribute("what/offset", 0.0)
param = _cartesianparam.new()
param.setData(numpy.zeros((2, 2), numpy.float64))
param.setValue((0, 0), 1)
param.setValue((0, 1), 2)
param.setValue((1, 0), 3)
param.setValue((1, 1), 4)
param.quantity = "ACRR"
param.gain = 10.0
param.offset = 2.0
gra = _gra.new()
gra.A = 1.0
gra.B = 2.0
gra.C = 3.0
result = gra.apply(distance, param)
self.assertAlmostEqual(47.77, result.getConvertedValue((0, 0))[1], 2)
self.assertAlmostEqual(1102.61, result.getConvertedValue((0, 1))[1], 2)
self.assertAlmostEqual(3200.0, result.getConvertedValue((1, 0))[1], 4)
self.assertAlmostEqual(4200.0, result.getConvertedValue((1, 1))[1], 4)
def test_C(self):
gra = _gra.new()
self.assertAlmostEqual(0.0, gra.C, 4)
gra.C = 10
self.assertAlmostEqual(10.0, gra.C, 4)
gra.C = 11.1
self.assertAlmostEqual(11.1, gra.C, 4)
def test_zrb(self):
gra = _gra.new()
self.assertAlmostEqual(1.6, gra.zrb, 4)
gra.zrb = 10
self.assertAlmostEqual(10.0, gra.zrb, 4)
gra.zrb = 11.1
self.assertAlmostEqual(11.1, gra.zrb, 4)
def test_attribute_visibility(self):
attrs = [
'A', 'B', 'C', 'upperThreshold', 'lowerThreshold', 'zrA', 'zrb'
]
gra = _gra.new()
alist = dir(gra)
for a in attrs:
self.assertEqual(True, a in alist)
def _apply_gra(self, result, d, t):
if nodomdb:
self.logger.info(
"Could not load rave_dom_db, probably due to missing dependencies like jprops or sqlalchemy, ignoring gra correction"
)
return
try:
zrA = self.zr_A
zrb = self.zr_b
db = rave_dom_db.create_db_from_conf()
dt = datetime.datetime(int(d[:4]), int(d[4:6]), int(d[6:]),
int(t[:2]), int(t[2:4]), 0)
dt = dt - datetime.timedelta(
seconds=3600 * 12) # 12 hours back in time for now..
gra = _gra.new()
gra.A = DEFAULTA
gra.B = DEFAULTB
gra.C = DEFAULTC
gra.zrA = zrA
gra.zrb = zrb
grac = db.get_gra_coefficient(dt)
if grac != None and not math.isnan(grac.a) and not math.isnan(
grac.b) and not math.isnan(grac.c):
if self.verbose:
self.logger.debug(
"Applying gra coefficients from database")
gra.A = grac.a
gra.B = grac.b
gra.C = grac.c
else:
self.logger.info(
"Could not find coefficients for given time, trying to get aged or climatologic coefficients"
)
nowdt = datetime.datetime(int(d[:4]), int(d[4:6]), int(d[6:]),
int(t[:2]), int(t[2:4]), 0)
agedt = nowdt - datetime.timedelta(
seconds=3600 * 48) # 2 days back
sig, pts, loss, r, rsig, corr, gra.A, gra.B, gra.C, mean, dev = self.get_backup_gra_coefficient(
db, agedt, nowdt)
dfield = result.findQualityFieldByHowTask(
"se.smhi.composite.distance.radar")
param = result.getParameter(self.quantity)
gra_field = gra.apply(dfield, param)
gra_field.quantity = self.quantity + "_CORR"
return gra_field
except Exception:
import traceback
traceback.print_exc()
self.logger.error("Failed to apply gra coefficients", exc_info=1)
return None
def test_apply_DBZH_gain2000(self):
distance = _ravefield.new()
distance.setData(numpy.zeros((1, 1), numpy.float64))
distance.setValue(0, 0, 13)
distance.addAttribute("what/gain", 2000.0)
distance.addAttribute("what/offset", 0.0)
param = _cartesianparam.new()
param.setData(numpy.zeros((1, 1), numpy.float64))
param.setValue((0, 0), 78)
param.quantity = "DBZH"
param.gain = 0.4
param.offset = -30.0
gra = _gra.new()
gra.A = 0.323868
gra.B = -0.001078
gra.C = 0.000018
gra.zrA = 200.0
gra.zrb = 1.6
result = gra.apply(distance, param)
self.assertAlmostEqual(79.23, result.getValue((0, 0))[1], 2)
def test_apply_DBZH(self):
distance = _ravefield.new()
distance.setData(numpy.zeros((2, 2), numpy.float64))
distance.setValue(0, 0, 0.1)
distance.setValue(0, 1, 0.2)
distance.setValue(1, 0, 0.3)
distance.setValue(1, 1, 0.4)
distance.addAttribute("what/gain", 10000.0)
distance.addAttribute("what/offset", 0.0)
param = _cartesianparam.new()
param.setData(numpy.zeros((2, 2), numpy.float64))
param.setValue((0, 0), 1)
param.setValue((0, 1), 2)
param.setValue((1, 0), 3)
param.setValue((1, 1), 4)
param.quantity = "DBZH"
param.gain = 10.0
param.offset = 2.0
gra = _gra.new()
gra.A = 1.0
gra.B = 2.0
gra.C = 3.0
gra.zrA = 100.0
gra.zrb = 1.1
result = gra.apply(distance, param)
self.assertAlmostEqual(18.60, result.getConvertedValue((0, 0))[1], 2)
self.assertAlmostEqual(40.7, result.getConvertedValue((0, 1))[1], 2)
self.assertAlmostEqual(54.0, result.getConvertedValue((1, 0))[1], 4)
self.assertAlmostEqual(64.0, result.getConvertedValue((1, 1))[1], 4)
self.assertEqual(
"GRA: A=1.000000, B=2.000000, C=3.000000, low_db=-0.250000, high_db=2.000000",
result.getAttribute("how/task_args"))
def test_new(self):
obj = _gra.new()
self.assertNotEqual(-1, str(type(obj)).find("GraCore"))
def generate(files, arguments):
args = arglist2dict(arguments)
zr_a = 200.0
zr_b = 1.6
quantity = "DBZH"
accept = 0.0
distancefield = "se.smhi.composite.distance.radar"
hours = 1
N = 5
applygra = False
#Accept is the required limit for how many nodata-pixels that are allowed in order for the
#data to be accumulated
#If we expect to have 10 observations and an accept limit of 20, then it can be 0, 1 or 2 observations
#with nodata for that position.
etime = args["time"]
edate = args["date"]
img = None
if "zra" in args.keys():
zr_a = float(args["zra"])
if "zrb" in args.keys():
zr_b = float(args["zrb"])
if "quantity" in args.keys():
quantity = args["quantity"]
if "accept" in args.keys():
accept = float(args["accept"]) / 100.0
if "distancefield" in args.keys():
distancefield = args["distancefield"]
if "hours" in args.keys():
hours = int(args["hours"])
if "N" in args.keys():
N = int(args["N"])
if "applygra" in args:
applygra = True
if distancefield == "eu.baltrad.composite.quality.distance.radar":
distancefield = "se.smhi.composite.distance.radar"
pdatetime = datetime.datetime.strptime(
edate + etime, "%Y%m%d%H%M%S") - datetime.timedelta(minutes=60 * hours)
sdate = pdatetime.strftime("%Y%m%d")
stime = pdatetime.strftime("%H%M00")
acrr = _acrr.new()
acrr.nodata = -1.0
acrr.undetect = 0.0
acrr.quality_field_name = distancefield
nodes = None
for fname in files:
obj = None
if ravebdb != None:
obj = ravebdb.get_rave_object(fname)
else:
rio = _raveio.open(fname)
obj = rio.object
if _cartesianvolume.isCartesianVolume(obj):
obj = obj.getImage(0)
if not _cartesian.isCartesian(obj):
raise AttributeError("Must call plugin with cartesian products")
if img == None:
img = _cartesian.new()
img.xscale = obj.xscale
img.yscale = obj.yscale
img.areaextent = obj.areaextent
img.projection = obj.projection
img.product = _rave.Rave_ProductType_RR
img.source = obj.source
img.time = etime
img.date = edate
img.startdate = sdate
img.starttime = stime
img.enddate = edate
img.endtime = etime
if obj.hasAttribute("how/nodes") and nodes == None:
nodes = obj.getAttribute("how/nodes")
if obj.xscale != img.xscale or obj.yscale != img.yscale or \
obj.projection.definition != img.projection.definition:
raise AttributeError(
"Scale or projdef inconsistancy for used area")
par = obj.getParameter(quantity)
if par == None:
logger.warn("Could not find parameter (%s) for %s %s" %
(quantity, obj.date, obj.time))
else:
if par.getQualityFieldByHowTask(distancefield) != None:
acrr.sum(par, zr_a, zr_b)
# accept, N, hours
result = acrr.accumulate(accept, N, hours)
fileno, outfile = rave_tempfile.mktemp(suffix='.h5', close="True")
if nodes != None:
img.addAttribute("how/nodes", nodes)
img.addParameter(result)
#logger.info("Apply gra: %s"%`applygra`)
if applygra:
db = rave_dom_db.create_db_from_conf()
dt = datetime.datetime(int(edate[:4]), int(edate[4:6]), int(edate[6:]),
int(etime[:2]), int(etime[2:4]), 0)
dt = dt - datetime.timedelta(
seconds=3600 * 12) # 12 hours back in time for now..
gra = _gra.new()
gra.A = DEFAULTA
gra.B = DEFAULTB
gra.C = DEFAULTC
gra.zrA = zr_a
gra.zrb = zr_b
grac = db.get_gra_coefficient(dt)
if grac != None and not math.isnan(grac.a) and not math.isnan(
grac.b) and not math.isnan(grac.c):
logger.debug("Using gra coefficients from database, quantity: %s" %
quantity)
gra.A = grac.a
gra.B = grac.b
gra.C = grac.c
else:
logger.info(
"Could not find coefficients for given time, trying to get aged or climatologic coefficients"
)
nowdt = datetime.datetime(int(edate[:4]), int(edate[4:6]),
int(edate[6:]), int(etime[:2]),
int(etime[2:4]), 0)
agedt = nowdt - datetime.timedelta(
seconds=3600 * 48) # 2 days back
sig, pts, loss, r, rsig, corr, gra.A, gra.B, gra.C, mean, dev = get_backup_gra_coefficient(
db, agedt, nowdt)
dfield = result.getQualityFieldByHowTask(distancefield)
gra_field = gra.apply(dfield, result)
gra_field.quantity = result.quantity + "_CORR"
img.addParameter(gra_field)
ios = _raveio.new()
ios.object = img
ios.filename = outfile
ios.version = RAVE_IO_DEFAULT_VERSION
ios.save()
return outfile
