def testFillGap_onCartesianParameters(self):
data = numpy.zeros((6, 6), numpy.uint8)
data[1][2] = 1
data[2][1] = 1
data[3][2] = 1
data[2][3] = 1
obj = _cartesian.new()
param = _cartesianparam.new()
param.setData(data)
param.nodata = 255.0
param.quantity = "DBZH"
obj.addParameter(param)
param = _cartesianparam.new()
data[1][2] = 2
data[2][1] = 2
data[3][2] = 2
data[2][3] = 2
param.setData(data)
param.nodata = 255.0
param.quantity = "TH"
obj.addParameter(param)
t = _transform.new()
result = t.fillGap(obj)
data = result.getParameter("DBZH").getData()
self.assertEqual(1, data[2][2])
data = result.getParameter("TH").getData()
self.assertEqual(2, data[2][2])
def test_sum_different_quantity(self):
p1 = _cartesianparam.new()
p1.quantity = "DBZH"
p1.setData(reshape(array((NO_DATA, 111, 0, 111), uint8), (2, 2)))
p1.nodata, p1.undetect, p1.gain, p1.offset = NO_DATA, UNDETECT, 0.5, -32.5
d1 = _ravefield.new()
d1.addAttribute("what/gain", DEFAULT_DISTANCE_GAIN)
d1.setData(reshape(array((0, 100, 75, 50), uint8), (2, 2)))
d1.addAttribute("how/task", "se.smhi.composite.distance.radar")
p1.addQualityField(d1)
p2 = _cartesianparam.new()
p2.quantity = "TH"
p2.setData(reshape(array((NO_DATA, 111, 0, 111), uint8), (2, 2)))
p2.nodata, p2.undetect, p2.gain, p2.offset = NO_DATA, UNDETECT, 0.5, -32.5
d2 = _ravefield.new()
d2.addAttribute("what/gain", DEFAULT_DISTANCE_GAIN)
d2.setData(reshape(array((0, 100, 75, 50), uint8), (2, 2)))
d2.addAttribute("how/task", "se.smhi.composite.distance.radar")
p2.addQualityField(d2)
obj = _acrr.new()
obj.sum(p1, 200.0, 1.6)
try:
obj.sum(p2, 200.0, 1.6)
self.fail("Expected IOError")
except IOError:
pass
self.assertEqual(True, obj.isInitialized())
self.assertEqual("DBZH", obj.getQuantity())
def test_accumulate_distfield_nodata(self):
distance_field1 = (10, 20, 30, ACRR_NO_DATA)
distance_field2 = (10, 20, 30, ACRR_NO_DATA)
p1 = _cartesianparam.new()
p1.quantity = "DBZH"
p1.setData(reshape(array((111, 111, UNDETECT, NO_DATA), uint8),
(2, 2)))
p1.nodata, p1.undetect, p1.gain, p1.offset = NO_DATA, UNDETECT, 0.5, -32.5
d1 = _ravefield.new()
d1.addAttribute("what/gain", DEFAULT_DISTANCE_GAIN)
d1.setData(reshape(array(distance_field1, uint8), (2, 2)))
d1.addAttribute("how/task", "se.smhi.composite.distance.radar")
p1.addQualityField(d1)
p2 = _cartesianparam.new()
p2.quantity = "DBZH"
p2.setData(reshape(array((111, 111, 111, NO_DATA), uint8), (2, 2)))
p2.nodata, p2.undetect, p2.gain, p2.offset = NO_DATA, UNDETECT, 0.5, -32.5
d2 = _ravefield.new()
d2.addAttribute("what/gain", DEFAULT_DISTANCE_GAIN)
d2.setData(reshape(array(distance_field2, uint8), (2, 2)))
d2.addAttribute("how/task", "se.smhi.composite.distance.radar")
p2.addQualityField(d2)
obj = _acrr.new()
obj.nodata = ACRR_NO_DATA
obj.undetect = UNDETECT
obj.sum(p1, 200.0, 1.6)
obj.sum(p2, 200.0, 1.6)
result = obj.accumulate(0.0, 2, 1.0)
self.assertAlmostEqual(1.0, result.getAttribute("what/prodpar"), 4)
self.assertEqual("ACRR", result.quantity)
self.assertAlmostEqual(ACRR_NO_DATA, result.nodata, 4)
self.assertAlmostEqual(UNDETECT, result.undetect, 4)
refAcrr = [1.0, 1.0, 0.5, ACRR_NO_DATA]
refDist = self.calculateAvgDistanceField(
[distance_field1, distance_field2], DEFAULT_DISTANCE_GAIN)
Acrr = result.getData().flatten()
qfield = result.getQualityFieldByHowTask(
"se.smhi.composite.distance.radar")
self.assertAlmostEqual(0.0, qfield.getAttribute("what/offset"), 4)
self.assertAlmostEqual(1000.0, qfield.getAttribute("what/gain"), 4)
Dist = qfield.getData().flatten()
for i in range(len(refAcrr)):
self.assertAlmostEqual(Acrr[i], refAcrr[i], 2)
self.assertAlmostEqual(Dist[i], refDist[i], 2)
def test_addParameter(self):
obj = _cartesian.new()
param = _cartesianparam.new()
param.quantity = "DBZH"
param.setData(numpy.zeros((240, 240), numpy.uint8))
param2 = _cartesianparam.new()
param2.quantity = "MMH"
param2.setData(numpy.zeros((240, 240), numpy.uint8))
self.assertFalse(obj.hasParameter("DBZH"))
obj.addParameter(param)
self.assertTrue(obj.hasParameter("DBZH"))
obj.addParameter(param2)
self.assertTrue(obj.hasParameter("DBZH"))
self.assertTrue(obj.hasParameter("MMH"))
def readCT(filename):
ct, cp = _cartesian.new(), _cartesianparam.new()
nodelist = _pyhl.read_nodelist(filename)
for n in NODENAMES:
nodelist.selectNode(n)
nodelist.fetch()
ct.defaultParameter = "CT"
ct.projection = _projection.new("MSG", "no description",
nodelist.getNode("/PROJECTION").data())
cp.setData(nodelist.getNode("/CT").data())
ysize = nodelist.getNode("/CT/N_LINES").data()
xsize = nodelist.getNode("/CT/N_COLS").data()
ULx = nodelist.getNode("/XGEO_UP_LEFT").data()
ULy = nodelist.getNode("/YGEO_UP_LEFT").data()
LRx = nodelist.getNode("/XGEO_LOW_RIGHT").data()
LRy = nodelist.getNode("/YGEO_LOW_RIGHT").data()
yscale = (ULy - LRy) / ysize
xscale = (LRx - ULx) / xsize
xoffset, yoffset = xscale / 2, yscale / 2 # Offsets to adjust LL and UR corners
LLx = LRx - (xsize * xscale) - xoffset
LLy = ULy - (ysize * yscale) - yoffset
URx = LRx + xoffset
URy = ULy + yoffset
ct.areaextent = (LLx, LLy, URx, URy) # Differs ~5 cm from PPS and PyTROLL
ct.xscale, ct.yscale = xscale, yscale
cp.quantity = "CT"
cp.gain, cp.offset = 1.0, 0.0
cp.nodata, cp.undetect = -1.0, 0.0
ct.addParameter(cp)
return ct
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_setGetValue(self):
obj = _cartesianparam.new()
obj.nodata = 255.0
obj.undetect = 0.0
a = numpy.arange(120)
a = numpy.array(a.astype(numpy.float64), numpy.float64)
a = numpy.reshape(a, (12, 10)).astype(numpy.float64)
obj.setData(a)
data = [
((0, 1), 10.0, _rave.RaveValueType_DATA),
((1, 1), 20.0, _rave.RaveValueType_DATA),
((2, 2), 30.0, _rave.RaveValueType_DATA),
((9, 4), 49.0, _rave.RaveValueType_DATA),
((8, 4), obj.nodata, _rave.RaveValueType_NODATA),
((4, 8), obj.undetect, _rave.RaveValueType_UNDETECT),
]
for v in data:
obj.setValue(v[0], v[1])
# Verify
for v in data:
r = obj.getValue(v[0])
self.assertAlmostEqual(v[1], r[1], 4)
self.assertEqual(v[2], r[0])
def test_getValue(self):
obj = _cartesian.new()
param = _cartesianparam.new()
param.quantity = "DBZH"
param.nodata = 255.0
param.undetect = 0.0
a = numpy.arange(120)
a = numpy.array(a.astype(numpy.float64), numpy.float64)
a = numpy.reshape(a, (12, 10)).astype(numpy.float64)
a[0][1] = param.nodata
a[1][0] = param.undetect
param.setData(a)
obj.addParameter(param)
obj.defaultParameter = "DBZH"
pairs = [(0, 0, 0.0, _rave.RaveValueType_UNDETECT),
(1, 0, param.nodata, _rave.RaveValueType_NODATA),
(0, 1, param.undetect, _rave.RaveValueType_UNDETECT),
(2, 0, 2.0, _rave.RaveValueType_DATA),
(0, 3, 30.0, _rave.RaveValueType_DATA)]
for cval in pairs:
result = obj.getValue((cval[0], cval[1]))
self.assertAlmostEqual(cval[2], result[1], 4)
self.assertEqual(cval[3], result[0])
def test_isTransformable_noscale(self):
proj = _rave.projection(
"x", "y",
"+proj=stere +ellps=bessel +lat_0=90 +lon_0=14 +lat_ts=60 +datum=WGS84"
)
data = numpy.zeros((10, 10), numpy.float64)
param = _cartesianparam.new()
param.quantity = "DBZH"
param.setData(data)
obj = _cartesian.new()
obj.xscale = 1000.0
obj.yscale = 1000.0
obj.projection = proj
obj.addParameter(param)
self.assertEqual(True, obj.isTransformable())
obj.xscale = 1000.0
obj.yscale = 0.0
self.assertEqual(False, obj.isTransformable())
obj.xscale = 0.0
obj.yscale = 1000.0
self.assertEqual(False, obj.isTransformable())
def test_setGetConvertedValue(self):
obj = _cartesianparam.new()
obj.nodata = 255.0
obj.undetect = 0.0
obj.gain = 2.0
obj.offset = 1.0
a = numpy.arange(120)
a = numpy.array(a.astype(numpy.float64), numpy.float64)
a = numpy.reshape(a, (12, 10)).astype(numpy.float64)
obj.setData(a)
obj.setValue((0, 1), 10.0)
obj.setValue((1, 1), 20.0)
obj.setConvertedValue((2, 2), 14.5)
obj.setConvertedValue((3, 3), 15.0)
r = obj.getConvertedValue((0, 1))
self.assertEqual(_rave.RaveValueType_DATA, r[0])
self.assertAlmostEqual(21.0, r[1], 4)
r = obj.getConvertedValue((1, 1))
self.assertEqual(_rave.RaveValueType_DATA, r[0])
self.assertAlmostEqual(41.0, r[1], 4)
r = obj.getConvertedValue((2, 2))
self.assertEqual(_rave.RaveValueType_DATA, r[0])
self.assertAlmostEqual(14.5, r[1], 4)
r = obj.getConvertedValue((3, 3))
self.assertEqual(_rave.RaveValueType_DATA, r[0])
self.assertAlmostEqual(15.0, r[1], 4)
def test_getConvertedValueAtLonLat(self):
obj = _cartesian.new()
obj.projection = _rave.projection(
"gnom", "gnom",
"+proj=gnom +R=6371000.0 +lat_0=56.3675 +lon_0=12.8544")
obj.xscale = 100.0
obj.yscale = 100.0
xy = obj.projection.fwd(deg2rad((12.8544, 56.3675)))
obj.areaextent = (xy[0] - 4 * 100.0, xy[1] - 5 * 100.0,
xy[0] + 6 * 100.0, xy[1] + 5 * 100.0)
param = _cartesianparam.new()
param.quantity = "DBZH"
param.nodata = 255.0
param.undetect = 0.0
a = numpy.arange(99)
a = numpy.array(a.astype(numpy.float64), numpy.float64)
a = numpy.reshape(a, (11, 9)).astype(numpy.float64)
param.setData(a)
obj.addParameter(param)
obj.defaultParameter = "DBZH"
expected = obj.getConvertedValue((4, 5))
actual = obj.getConvertedValueAtLonLat(deg2rad((12.8544, 56.3675)))
self.assertEqual(expected[0], actual[0])
self.assertAlmostEqual(expected[1], actual[1], 4)
def test_getParameter(self):
obj = _cartesian.new()
param = _cartesianparam.new()
param.quantity = "DBZH"
param.setData(numpy.zeros((240, 240), numpy.uint8))
param2 = _cartesianparam.new()
param2.quantity = "MMH"
param2.setData(numpy.zeros((240, 240), numpy.uint8))
obj.addParameter(param)
obj.addParameter(param2)
result = obj.getParameter("DBZH")
result2 = obj.getParameter("MMH")
self.assertTrue(param == result)
self.assertTrue(param2 == result2)
self.assertTrue(None == obj.getParameter("MMHH"))
def test_quantity_typeError(self):
obj = _cartesianparam.new()
try:
obj.quantity = 10
self.fail("Expected TypeError")
except TypeError:
pass
self.assertEqual(None, obj.quantity)
def test_addParameter_differentSizes(self):
obj = _cartesian.new()
param = _cartesianparam.new()
param.quantity = "DBZH"
param.setData(numpy.zeros((240, 240), numpy.uint8))
param2 = _cartesianparam.new()
param2.quantity = "MMH"
param2.setData(numpy.zeros((241, 241), numpy.uint8))
obj.addParameter(param)
try:
obj.addParameter(param2)
self.fail("Expected AttributeError")
except AttributeError:
pass
self.assertTrue(obj.hasParameter("DBZH"))
self.assertFalse(obj.hasParameter("MMH"))
def test_undetect_typeError(self):
obj = _cartesianparam.new()
self.assertAlmostEqual(0.0, obj.undetect, 4)
try:
obj.undetect = 10
self.fail("Expected TypeError")
except TypeError:
pass
self.assertAlmostEqual(0.0, obj.undetect, 4)
def test_datatype(self):
obj = _cartesianparam.new()
self.assertEqual(_rave.RaveDataType_UNDEFINED, obj.datatype)
try:
obj.datatype = _rave.RaveDataType_INT
self.fail("Expected AttributeError")
except AttributeError:
pass
self.assertEqual(_rave.RaveDataType_UNDEFINED, obj.datatype)
def test_attribute_visibility(self):
attrs = [
'xsize', 'ysize', 'quantity', 'gain', 'offset', 'nodata',
'undetect', 'datatype'
]
obj = _cartesianparam.new()
alist = dir(obj)
for a in attrs:
self.assertEqual(True, a in alist)
def test_ysize(self):
obj = _cartesianparam.new()
self.assertEqual(0, obj.ysize)
try:
obj.ysize = 10
self.fail("Expected AttributeError")
except AttributeError:
pass
self.assertEqual(0, obj.ysize)
def test_nodata_typeError(self):
obj = _cartesianparam.new()
self.assertAlmostEqual(0.0, obj.nodata, 4)
try:
obj.nodata = 10
self.fail("Expected TypeError")
except TypeError:
pass
self.assertAlmostEqual(0.0, obj.nodata, 4)
def test_gain_typeError(self):
obj = _cartesianparam.new()
self.assertAlmostEqual(1.0, obj.gain, 4)
try:
obj.gain = 10
self.fail("Expected TypeError")
except TypeError:
pass
self.assertAlmostEqual(1.0, obj.gain, 4)
def test_getParameterCount(self):
obj = _cartesian.new()
param = _cartesianparam.new()
param.quantity = "DBZH"
param.setData(numpy.zeros((240, 240), numpy.uint8))
param2 = _cartesianparam.new()
param2.quantity = "MMH"
param2.setData(numpy.zeros((240, 240), numpy.uint8))
param3 = _cartesianparam.new()
param3.quantity = "MMH"
param3.setData(numpy.zeros((240, 240), numpy.uint8))
self.assertEqual(0, obj.getParameterCount())
obj.addParameter(param)
self.assertEqual(1, obj.getParameterCount())
obj.addParameter(param2)
self.assertEqual(2, obj.getParameterCount())
obj.addParameter(param3)
self.assertEqual(2, obj.getParameterCount())
def test_setData_uint64(self):
obj = _cartesianparam.new()
a = numpy.arange(120)
a = numpy.array(a.astype(numpy.uint64), numpy.uint64)
a = numpy.reshape(a, (12, 10)).astype(numpy.uint64)
obj.setData(a)
self.assertEqual(_rave.RaveDataType_ULONG, obj.datatype)
self.assertEqual(10, obj.xsize)
self.assertEqual(12, obj.ysize)
def test_setConvertedValue_roundOff(self):
obj = _cartesianparam.new()
obj.nodata = 255.0
obj.undetect = 0.0
obj.gain = 0.4
obj.offset = -30.0
# test uint8
a = numpy.arange(120)
a = numpy.array(a.astype(numpy.uint8), numpy.uint8)
a = numpy.reshape(a, (12, 10)).astype(numpy.uint8)
obj.setData(a)
obj.setConvertedValue((0, 1), -0.5)
r = obj.getValue((0, 1))
self.assertEqual(_rave.RaveValueType_DATA, r[0])
self.assertAlmostEqual(74.0, r[1], 4)
#test int8
a = numpy.arange(120)
a = numpy.array(a.astype(numpy.int8), numpy.int8)
a = numpy.reshape(a, (12, 10)).astype(numpy.int8)
obj.setData(a)
obj.setConvertedValue((0, 1), 1.5)
r = obj.getValue((0, 1))
self.assertEqual(_rave.RaveValueType_DATA, r[0])
self.assertAlmostEqual(79.0, r[1], 4)
#test uint
a = numpy.arange(120)
a = numpy.array(a.astype(numpy.uint), numpy.uint)
a = numpy.reshape(a, (12, 10)).astype(numpy.uint)
obj.setData(a)
obj.setConvertedValue((0, 1), 2.25)
r = obj.getValue((0, 1))
self.assertEqual(_rave.RaveValueType_DATA, r[0])
self.assertAlmostEqual(81.0, r[1], 4)
#test int
a = numpy.arange(120)
a = numpy.array(a.astype(numpy.int), numpy.int)
a = numpy.reshape(a, (12, 10)).astype(numpy.int)
obj.setData(a)
obj.setConvertedValue((0, 1), -1.75)
r = obj.getValue((0, 1))
self.assertEqual(_rave.RaveValueType_DATA, r[0])
self.assertAlmostEqual(71.0, r[1], 4)
def test_getConvertedQualityValueAtLonLat(self):
obj = _cartesian.new()
obj.projection = _rave.projection(
"gnom", "gnom",
"+proj=gnom +R=6371000.0 +lat_0=56.3675 +lon_0=12.8544")
obj.xscale = 100.0
obj.yscale = 100.0
xy = obj.projection.fwd(deg2rad((12.8544, 56.3675)))
obj.areaextent = (xy[0] - 4 * 100.0, xy[1] - 5 * 100.0,
xy[0] + 6 * 100.0, xy[1] + 5 * 100.0)
param = _cartesianparam.new()
param.quantity = "DBZH"
param.nodata = 255.0
param.undetect = 0.0
a = numpy.zeros((11, 9))
a = numpy.array(a.astype(numpy.float64), numpy.float64)
a = numpy.reshape(a, (11, 9)).astype(numpy.float64)
param.setData(a)
qf = numpy.arange(99)
qf = numpy.array(qf.astype(numpy.float64), numpy.float64)
qf = numpy.reshape(qf, (11, 9)).astype(numpy.float64)
qf2 = numpy.arange(99)
qf2 = numpy.array(qf.astype(numpy.float64), numpy.float64)
qf2 = numpy.reshape(qf, (11, 9)).astype(numpy.float64)
qf2[5][4] = 199.0
field1 = _ravefield.new()
field1.addAttribute("how/task", "se.task.1")
field1.addAttribute("what/offset", 10.0)
field1.addAttribute("what/gain", 2.0)
field1.setData(qf)
param.addQualityField(field1)
field2 = _ravefield.new()
field2.addAttribute("how/task", "se.task.2")
field2.addAttribute("what/gain", 3.0)
field2.setData(qf2)
param.addQualityField(field2)
obj.addParameter(param)
obj.defaultParameter = "DBZH"
#expected = obj.getConvertedValue((4,5))
result = obj.getConvertedQualityValueAtLonLat(
deg2rad((12.8544, 56.3675)), "se.task.1")
self.assertAlmostEqual(10.0 + 2.0 * 49.0, result, 4)
result = obj.getConvertedQualityValueAtLonLat(
deg2rad((12.8544, 56.3675)), "se.task.2")
self.assertAlmostEqual(3.0 * 199.0, result, 4)
def test_addParameter_no_quantity(self):
obj = _cartesian.new()
param = _cartesianparam.new()
param.setData(numpy.zeros((10, 10), numpy.uint8))
try:
obj.addParameter(param)
self.fail("Expected AttributeError")
except AttributeError:
pass
def test_accumulate_tofewfiles(self):
p1 = _cartesianparam.new()
p1.quantity = "DBZH"
p1.setData(reshape(array((NO_DATA, 0, 0, 0), uint8), (2, 2)))
p1.nodata, p1.undetect, p1.gain, p1.offset = NO_DATA, UNDETECT, 0.5, -32.5
d1 = _ravefield.new()
d1.addAttribute("what/gain", DEFAULT_DISTANCE_GAIN)
d1.setData(reshape(array((0, 100, 75, 50), uint8), (2, 2)))
d1.addAttribute("how/task", "se.smhi.composite.distance.radar")
p1.addQualityField(d1)
p2 = _cartesianparam.new()
p2.quantity = "DBZH"
p2.setData(reshape(array((0, NO_DATA, 0, 0), uint8), (2, 2)))
p2.nodata, p2.undetect, p2.gain, p2.offset = NO_DATA, UNDETECT, 0.5, -32.5
d2 = _ravefield.new()
d2.addAttribute("what/gain", DEFAULT_DISTANCE_GAIN)
d2.setData(reshape(array((10, 20, 25, 50), uint8), (2, 2)))
d2.addAttribute("how/task", "se.smhi.composite.distance.radar")
p2.addQualityField(d2)
obj = _acrr.new()
obj.nodata = ACRR_NO_DATA
obj.undetect = UNDETECT
obj.sum(p1, 200.0, 1.6)
obj.sum(p2, 200.0, 1.6)
result = obj.accumulate(0.0, 3, 1.0)
self.assertAlmostEqual(1.0, result.getAttribute("what/prodpar"), 4)
self.assertEqual("ACRR", result.quantity)
self.assertAlmostEqual(ACRR_NO_DATA, result.nodata, 4)
self.assertAlmostEqual(UNDETECT, result.undetect, 4)
refAcrr = [ACRR_NO_DATA, ACRR_NO_DATA, ACRR_NO_DATA, ACRR_NO_DATA]
Acrr = result.getData().flatten()
for i in range(len(refAcrr)):
self.assertAlmostEqual(Acrr[i], refAcrr[i], 2)
def test_getParameterNames(self):
obj = _cartesian.new()
param = _cartesianparam.new()
param.quantity = "DBZH"
param.setData(numpy.zeros((240, 240), numpy.uint8))
param2 = _cartesianparam.new()
param2.quantity = "MMH"
param2.setData(numpy.zeros((240, 240), numpy.uint8))
result = obj.getParameterNames()
self.assertEqual(0, len(result))
obj.addParameter(param)
result = obj.getParameterNames()
self.assertEqual(1, len(result))
self.assertTrue("DBZH" in result)
obj.addParameter(param2)
result = obj.getParameterNames()
self.assertEqual(2, len(result))
self.assertTrue("DBZH" in result)
self.assertTrue("MMH" in result)
def test_datatypes_fromData(self):
types = [(numpy.int8, _rave.RaveDataType_CHAR),
(numpy.uint8, _rave.RaveDataType_UCHAR),
(numpy.int16, _rave.RaveDataType_SHORT),
(numpy.int32, _rave.RaveDataType_INT),
(numpy.int64, _rave.RaveDataType_LONG),
(numpy.float32, _rave.RaveDataType_FLOAT),
(numpy.float64, _rave.RaveDataType_DOUBLE)]
obj = _cartesianparam.new()
for type in types:
d = numpy.zeros((10, 10), type[0])
obj.setData(d)
self.assertEqual(type[1], obj.datatype)
def test_getData_int8(self):
obj = _cartesianparam.new()
a = numpy.arange(120)
a = numpy.array(a.astype(numpy.int8), numpy.int8)
a = numpy.reshape(a, (12, 10)).astype(numpy.int8)
obj.setData(a)
obj.setValue((3, 2), 5)
obj.setValue((4, 4), 7)
result = obj.getData()
self.assertEqual(5, result[2][3])
self.assertEqual(7, result[4][4])
self.assertEqual("int8", result.dtype.name)
def test_isTransformable_noproj(self):
data = numpy.zeros((10, 10), numpy.float64)
param = _cartesianparam.new()
param.quantity = "DBZH"
param.setData(data)
obj = _cartesian.new()
obj.xscale = 1000.0
obj.yscale = 1000.0
obj.addParameter(param)
self.assertEqual(False, obj.isTransformable())
