def get_li(self, kernel_type, li_recip):
# relative azimuth angle
# ensure it is in a [0,2] pi range
phi = da.fabs(
(self.angle_info.raa_rad % (2.0 * self.global_args.m_pi)))
cos_phi = da.cos(phi)
sin_phi = da.sin(phi)
tanti = da.tan(self.angle_info.sza_rad)
tantv = da.tan(self.angle_info.vza_rad)
cos1, sin1, tan1 = self.get_pangles(tantv, self.global_args.br,
self.global_args.nearly_zero)
cos2, sin2, tan2 = self.get_pangles(tanti, self.global_args.br,
self.global_args.nearly_zero)
# sets cos & sin phase angle terms
cos_phaang, phaang, sin_phaang = self.get_phaang(
cos1, cos2, sin1, sin2, cos_phi)
distance = self.get_distance(tan1, tan2, cos_phi)
overlap_info = self.get_overlap(cos1, cos2, tan1, tan2, sin_phi,
distance, self.global_args.hb,
self.global_args.m_pi)
if kernel_type.lower() == 'sparse':
if li_recip:
li = overlap_info.overlap - overlap_info.temp + 0.5 * (
1.0 + cos_phaang) / cos1 / cos2
else:
li = overlap_info.overlap - overlap_info.temp + 0.5 * (
1.0 + cos_phaang) / cos1
else:
if kernel_type.lower() == 'dense':
if li_recip:
li = (1.0 + cos_phaang) / (
cos1 * cos2 *
(overlap_info.temp - overlap_info.overlap)) - 2.0
else:
li = (1.0 + cos_phaang) / (
cos1 *
(overlap_info.temp - overlap_info.overlap)) - 2.0
return li
def test_arithmetic():
x = np.arange(5).astype('f4') + 2
y = np.arange(5).astype('i8') + 2
z = np.arange(5).astype('i4') + 2
a = da.from_array(x, chunks=(2,))
b = da.from_array(y, chunks=(2,))
c = da.from_array(z, chunks=(2,))
assert eq(a + b, x + y)
assert eq(a * b, x * y)
assert eq(a - b, x - y)
assert eq(a / b, x / y)
assert eq(b & b, y & y)
assert eq(b | b, y | y)
assert eq(b ^ b, y ^ y)
assert eq(a // b, x // y)
assert eq(a ** b, x ** y)
assert eq(a % b, x % y)
assert eq(a > b, x > y)
assert eq(a < b, x < y)
assert eq(a >= b, x >= y)
assert eq(a <= b, x <= y)
assert eq(a == b, x == y)
assert eq(a != b, x != y)
assert eq(a + 2, x + 2)
assert eq(a * 2, x * 2)
assert eq(a - 2, x - 2)
assert eq(a / 2, x / 2)
assert eq(b & True, y & True)
assert eq(b | True, y | True)
assert eq(b ^ True, y ^ True)
assert eq(a // 2, x // 2)
assert eq(a ** 2, x ** 2)
assert eq(a % 2, x % 2)
assert eq(a > 2, x > 2)
assert eq(a < 2, x < 2)
assert eq(a >= 2, x >= 2)
assert eq(a <= 2, x <= 2)
assert eq(a == 2, x == 2)
assert eq(a != 2, x != 2)
assert eq(2 + b, 2 + y)
assert eq(2 * b, 2 * y)
assert eq(2 - b, 2 - y)
assert eq(2 / b, 2 / y)
assert eq(True & b, True & y)
assert eq(True | b, True | y)
assert eq(True ^ b, True ^ y)
assert eq(2 // b, 2 // y)
assert eq(2 ** b, 2 ** y)
assert eq(2 % b, 2 % y)
assert eq(2 > b, 2 > y)
assert eq(2 < b, 2 < y)
assert eq(2 >= b, 2 >= y)
assert eq(2 <= b, 2 <= y)
assert eq(2 == b, 2 == y)
assert eq(2 != b, 2 != y)
assert eq(-a, -x)
assert eq(abs(a), abs(x))
assert eq(~(a == b), ~(x == y))
assert eq(~(a == b), ~(x == y))
assert eq(da.logaddexp(a, b), np.logaddexp(x, y))
assert eq(da.logaddexp2(a, b), np.logaddexp2(x, y))
assert eq(da.exp(b), np.exp(y))
assert eq(da.log(a), np.log(x))
assert eq(da.log10(a), np.log10(x))
assert eq(da.log1p(a), np.log1p(x))
assert eq(da.expm1(b), np.expm1(y))
assert eq(da.sqrt(a), np.sqrt(x))
assert eq(da.square(a), np.square(x))
assert eq(da.sin(a), np.sin(x))
assert eq(da.cos(b), np.cos(y))
assert eq(da.tan(a), np.tan(x))
assert eq(da.arcsin(b/10), np.arcsin(y/10))
assert eq(da.arccos(b/10), np.arccos(y/10))
assert eq(da.arctan(b/10), np.arctan(y/10))
assert eq(da.arctan2(b*10, a), np.arctan2(y*10, x))
assert eq(da.hypot(b, a), np.hypot(y, x))
assert eq(da.sinh(a), np.sinh(x))
assert eq(da.cosh(b), np.cosh(y))
assert eq(da.tanh(a), np.tanh(x))
assert eq(da.arcsinh(b*10), np.arcsinh(y*10))
assert eq(da.arccosh(b*10), np.arccosh(y*10))
assert eq(da.arctanh(b/10), np.arctanh(y/10))
assert eq(da.deg2rad(a), np.deg2rad(x))
assert eq(da.rad2deg(a), np.rad2deg(x))
assert eq(da.logical_and(a < 1, b < 4), np.logical_and(x < 1, y < 4))
assert eq(da.logical_or(a < 1, b < 4), np.logical_or(x < 1, y < 4))
assert eq(da.logical_xor(a < 1, b < 4), np.logical_xor(x < 1, y < 4))
assert eq(da.logical_not(a < 1), np.logical_not(x < 1))
assert eq(da.maximum(a, 5 - a), np.maximum(a, 5 - a))
assert eq(da.minimum(a, 5 - a), np.minimum(a, 5 - a))
assert eq(da.fmax(a, 5 - a), np.fmax(a, 5 - a))
assert eq(da.fmin(a, 5 - a), np.fmin(a, 5 - a))
assert eq(da.isreal(a + 1j * b), np.isreal(x + 1j * y))
assert eq(da.iscomplex(a + 1j * b), np.iscomplex(x + 1j * y))
assert eq(da.isfinite(a), np.isfinite(x))
assert eq(da.isinf(a), np.isinf(x))
assert eq(da.isnan(a), np.isnan(x))
assert eq(da.signbit(a - 3), np.signbit(x - 3))
assert eq(da.copysign(a - 3, b), np.copysign(x - 3, y))
assert eq(da.nextafter(a - 3, b), np.nextafter(x - 3, y))
assert eq(da.ldexp(c, c), np.ldexp(z, z))
assert eq(da.fmod(a * 12, b), np.fmod(x * 12, y))
assert eq(da.floor(a * 0.5), np.floor(x * 0.5))
assert eq(da.ceil(a), np.ceil(x))
assert eq(da.trunc(a / 2), np.trunc(x / 2))
assert eq(da.degrees(b), np.degrees(y))
assert eq(da.radians(a), np.radians(x))
assert eq(da.rint(a + 0.3), np.rint(x + 0.3))
assert eq(da.fix(a - 2.5), np.fix(x - 2.5))
assert eq(da.angle(a + 1j), np.angle(x + 1j))
assert eq(da.real(a + 1j), np.real(x + 1j))
assert eq((a + 1j).real, np.real(x + 1j))
assert eq(da.imag(a + 1j), np.imag(x + 1j))
assert eq((a + 1j).imag, np.imag(x + 1j))
assert eq(da.conj(a + 1j * b), np.conj(x + 1j * y))
assert eq((a + 1j * b).conj(), (x + 1j * y).conj())
assert eq(da.clip(b, 1, 4), np.clip(y, 1, 4))
assert eq(da.fabs(b), np.fabs(y))
assert eq(da.sign(b - 2), np.sign(y - 2))
l1, l2 = da.frexp(a)
r1, r2 = np.frexp(x)
assert eq(l1, r1)
assert eq(l2, r2)
l1, l2 = da.modf(a)
r1, r2 = np.modf(x)
assert eq(l1, r1)
assert eq(l2, r2)
assert eq(da.around(a, -1), np.around(x, -1))
class RexCallPlugin(BaseRexPlugin):
"""
RexCall is used for expressions, which calculate something.
An example is
SELECT a + b FROM ...
but also
a > 3
Typically, a RexCall has inputs (which can be RexNodes again)
and calls a function on these inputs.
The inputs can either be a column or a scalar value.
"""
class_name = "org.apache.calcite.rex.RexCall"
OPERATION_MAPPING = {
# "binary" functions
"and":
ReduceOperation(operation=operator.and_),
"or":
ReduceOperation(operation=operator.or_),
">":
ReduceOperation(operation=operator.gt),
">=":
ReduceOperation(operation=operator.ge),
"<":
ReduceOperation(operation=operator.lt),
"<=":
ReduceOperation(operation=operator.le),
"=":
ReduceOperation(operation=operator.eq),
"<>":
ReduceOperation(operation=operator.ne),
"+":
ReduceOperation(operation=operator.add),
"-":
ReduceOperation(operation=operator.sub),
"/":
ReduceOperation(operation=SQLDivisionOperator()),
"*":
ReduceOperation(operation=operator.mul),
# special operations
"case":
CaseOperation(),
"like":
LikeOperation(),
"similar to":
SimilarOperation(),
"not":
NotOperation(),
"is null":
IsNullOperation(),
"is not null":
NotOperation().of(IsNullOperation()),
"is true":
IsTrueOperation(),
"is not true":
NotOperation().of(IsTrueOperation()),
"is false":
IsFalseOperation(),
"is not false":
NotOperation().of(IsFalseOperation()),
"is unknown":
IsNullOperation(),
"is not unknown":
NotOperation().of(IsNullOperation()),
"rand":
RandOperation(),
"rand_integer":
RandIntegerOperation(),
# Unary math functions
"abs":
TensorScalarOperation(lambda x: x.abs(), np.abs),
"acos":
Operation(da.arccos),
"asin":
Operation(da.arcsin),
"atan":
Operation(da.arctan),
"atan2":
Operation(da.arctan2),
"cbrt":
Operation(da.cbrt),
"ceil":
CeilFloorOperation("ceil"),
"cos":
Operation(da.cos),
"cot":
Operation(lambda x: 1 / da.tan(x)),
"degrees":
Operation(da.degrees),
"exp":
Operation(da.exp),
"floor":
CeilFloorOperation("floor"),
"log10":
Operation(da.log10),
"ln":
Operation(da.log),
# "mod": Operation(da.mod), # needs cast
"power":
Operation(da.power),
"radians":
Operation(da.radians),
"round":
TensorScalarOperation(lambda x, *ops: x.round(*ops), np.round),
"sign":
Operation(da.sign),
"sin":
Operation(da.sin),
"tan":
Operation(da.tan),
"truncate":
Operation(da.trunc),
# string operations
"||":
ReduceOperation(operation=operator.add),
"char_length":
TensorScalarOperation(lambda x: x.str.len(), lambda x: len(x)),
"upper":
TensorScalarOperation(lambda x: x.str.upper(), lambda x: x.upper()),
"lower":
TensorScalarOperation(lambda x: x.str.lower(), lambda x: x.lower()),
"position":
PositionOperation(),
"trim":
TrimOperation(),
"overlay":
OverlayOperation(),
"substring":
SubStringOperation(),
"initcap":
TensorScalarOperation(lambda x: x.str.title(), lambda x: x.title()),
# date/time operations
"extract":
ExtractOperation(),
"localtime":
Operation(lambda *args: pd.Timestamp.now()),
"localtimestamp":
Operation(lambda *args: pd.Timestamp.now()),
"current_time":
Operation(lambda *args: pd.Timestamp.now()),
"current_date":
Operation(lambda *args: pd.Timestamp.now()),
"current_timestamp":
Operation(lambda *args: pd.Timestamp.now()),
"last_day":
TensorScalarOperation(
lambda x: x + pd.tseries.offsets.MonthEnd(1),
lambda x: convert_to_datetime(x) + pd.tseries.offsets.MonthEnd(1),
),
}
def convert(
self,
rex: "org.apache.calcite.rex.RexNode",
dc: DataContainer,
context: "dask_sql.Context",
) -> SeriesOrScalar:
# Prepare the operands by turning the RexNodes into python expressions
operands = [
RexConverter.convert(o, dc, context=context)
for o in rex.getOperands()
]
# Now use the operator name in the mapping
operator_name = str(rex.getOperator().getName())
operator_name = operator_name.lower()
try:
operation = self.OPERATION_MAPPING[operator_name]
except KeyError:
try:
operation = context.functions[operator_name]
except KeyError:
raise NotImplementedError(
f"{operator_name} not (yet) implemented")
logger.debug(
f"Executing {operator_name} on {[str(LoggableDataFrame(df)) for df in operands]}"
)
if hasattr(operation, "needs_dc") and operation.needs_dc:
return operation(*operands, dc=dc)
else:
return operation(*operands)
def test_arithmetic():
x = np.arange(5).astype('f4') + 2
y = np.arange(5).astype('i8') + 2
z = np.arange(5).astype('i4') + 2
a = da.from_array(x, chunks=(2, ))
b = da.from_array(y, chunks=(2, ))
c = da.from_array(z, chunks=(2, ))
assert eq(a + b, x + y)
assert eq(a * b, x * y)
assert eq(a - b, x - y)
assert eq(a / b, x / y)
assert eq(b & b, y & y)
assert eq(b | b, y | y)
assert eq(b ^ b, y ^ y)
assert eq(a // b, x // y)
assert eq(a**b, x**y)
assert eq(a % b, x % y)
assert eq(a > b, x > y)
assert eq(a < b, x < y)
assert eq(a >= b, x >= y)
assert eq(a <= b, x <= y)
assert eq(a == b, x == y)
assert eq(a != b, x != y)
assert eq(a + 2, x + 2)
assert eq(a * 2, x * 2)
assert eq(a - 2, x - 2)
assert eq(a / 2, x / 2)
assert eq(b & True, y & True)
assert eq(b | True, y | True)
assert eq(b ^ True, y ^ True)
assert eq(a // 2, x // 2)
assert eq(a**2, x**2)
assert eq(a % 2, x % 2)
assert eq(a > 2, x > 2)
assert eq(a < 2, x < 2)
assert eq(a >= 2, x >= 2)
assert eq(a <= 2, x <= 2)
assert eq(a == 2, x == 2)
assert eq(a != 2, x != 2)
assert eq(2 + b, 2 + y)
assert eq(2 * b, 2 * y)
assert eq(2 - b, 2 - y)
assert eq(2 / b, 2 / y)
assert eq(True & b, True & y)
assert eq(True | b, True | y)
assert eq(True ^ b, True ^ y)
assert eq(2 // b, 2 // y)
assert eq(2**b, 2**y)
assert eq(2 % b, 2 % y)
assert eq(2 > b, 2 > y)
assert eq(2 < b, 2 < y)
assert eq(2 >= b, 2 >= y)
assert eq(2 <= b, 2 <= y)
assert eq(2 == b, 2 == y)
assert eq(2 != b, 2 != y)
assert eq(-a, -x)
assert eq(abs(a), abs(x))
assert eq(~(a == b), ~(x == y))
assert eq(~(a == b), ~(x == y))
assert eq(da.logaddexp(a, b), np.logaddexp(x, y))
assert eq(da.logaddexp2(a, b), np.logaddexp2(x, y))
assert eq(da.exp(b), np.exp(y))
assert eq(da.log(a), np.log(x))
assert eq(da.log10(a), np.log10(x))
assert eq(da.log1p(a), np.log1p(x))
assert eq(da.expm1(b), np.expm1(y))
assert eq(da.sqrt(a), np.sqrt(x))
assert eq(da.square(a), np.square(x))
assert eq(da.sin(a), np.sin(x))
assert eq(da.cos(b), np.cos(y))
assert eq(da.tan(a), np.tan(x))
assert eq(da.arcsin(b / 10), np.arcsin(y / 10))
assert eq(da.arccos(b / 10), np.arccos(y / 10))
assert eq(da.arctan(b / 10), np.arctan(y / 10))
assert eq(da.arctan2(b * 10, a), np.arctan2(y * 10, x))
assert eq(da.hypot(b, a), np.hypot(y, x))
assert eq(da.sinh(a), np.sinh(x))
assert eq(da.cosh(b), np.cosh(y))
assert eq(da.tanh(a), np.tanh(x))
assert eq(da.arcsinh(b * 10), np.arcsinh(y * 10))
assert eq(da.arccosh(b * 10), np.arccosh(y * 10))
assert eq(da.arctanh(b / 10), np.arctanh(y / 10))
assert eq(da.deg2rad(a), np.deg2rad(x))
assert eq(da.rad2deg(a), np.rad2deg(x))
assert eq(da.logical_and(a < 1, b < 4), np.logical_and(x < 1, y < 4))
assert eq(da.logical_or(a < 1, b < 4), np.logical_or(x < 1, y < 4))
assert eq(da.logical_xor(a < 1, b < 4), np.logical_xor(x < 1, y < 4))
assert eq(da.logical_not(a < 1), np.logical_not(x < 1))
assert eq(da.maximum(a, 5 - a), np.maximum(a, 5 - a))
assert eq(da.minimum(a, 5 - a), np.minimum(a, 5 - a))
assert eq(da.fmax(a, 5 - a), np.fmax(a, 5 - a))
assert eq(da.fmin(a, 5 - a), np.fmin(a, 5 - a))
assert eq(da.isreal(a + 1j * b), np.isreal(x + 1j * y))
assert eq(da.iscomplex(a + 1j * b), np.iscomplex(x + 1j * y))
assert eq(da.isfinite(a), np.isfinite(x))
assert eq(da.isinf(a), np.isinf(x))
assert eq(da.isnan(a), np.isnan(x))
assert eq(da.signbit(a - 3), np.signbit(x - 3))
assert eq(da.copysign(a - 3, b), np.copysign(x - 3, y))
assert eq(da.nextafter(a - 3, b), np.nextafter(x - 3, y))
assert eq(da.ldexp(c, c), np.ldexp(z, z))
assert eq(da.fmod(a * 12, b), np.fmod(x * 12, y))
assert eq(da.floor(a * 0.5), np.floor(x * 0.5))
assert eq(da.ceil(a), np.ceil(x))
assert eq(da.trunc(a / 2), np.trunc(x / 2))
assert eq(da.degrees(b), np.degrees(y))
assert eq(da.radians(a), np.radians(x))
assert eq(da.rint(a + 0.3), np.rint(x + 0.3))
assert eq(da.fix(a - 2.5), np.fix(x - 2.5))
assert eq(da.angle(a + 1j), np.angle(x + 1j))
assert eq(da.real(a + 1j), np.real(x + 1j))
assert eq((a + 1j).real, np.real(x + 1j))
assert eq(da.imag(a + 1j), np.imag(x + 1j))
assert eq((a + 1j).imag, np.imag(x + 1j))
assert eq(da.conj(a + 1j * b), np.conj(x + 1j * y))
assert eq((a + 1j * b).conj(), (x + 1j * y).conj())
assert eq(da.clip(b, 1, 4), np.clip(y, 1, 4))
assert eq(da.fabs(b), np.fabs(y))
assert eq(da.sign(b - 2), np.sign(y - 2))
l1, l2 = da.frexp(a)
r1, r2 = np.frexp(x)
assert eq(l1, r1)
assert eq(l2, r2)
l1, l2 = da.modf(a)
r1, r2 = np.modf(x)
assert eq(l1, r1)
assert eq(l2, r2)
assert eq(da.around(a, -1), np.around(x, -1))
H[0, :] * da.cos(p) + (H[1, :] * da.sin(r) + H[2, :] * da.cos(r)) * da.sin(p))
fG = lambda Axyz, Ag, Cg: da.dot(Ag.T, (Axyz - Cg[0, :]).T)
fGi = lambda Ax, Ay, Az, Ag, Cg, i: da.dot(Ag.T, (da.column_stack((Ax, Ay, Az))[slice(*i)] - Cg[0, :]).T)
fbinningClip = lambda x, bin2_iStEn, bin1_nAverage: da.mean(da.reshape(x[slice(*bin2_iStEn)], (-1, bin1_nAverage)), 1)
fbinning = lambda x, bin1_nAverage: da.mean(da.reshape(x, (-1, bin1_nAverage)), 1)
repeat3shift1 = lambda A2: [A2[t:(len(A2) - 2 + t)] for t in range(3)]
median3cols = lambda a, b, c: da.where(a < b, da.where(c < a, a, da.where(b < c, b, c)),
da.where(a < c, a, da.where(c < b, b, c)))
median3 = lambda x: da.hstack((np.NaN, median3cols(*repeat3shift1(x)), np.NaN))
# not convertable to dask easily:
fVabs_old = lambda Gxyz, kVabs: np.polyval(kVabs.flat, np.sqrt(np.tan(fInclination(Gxyz))))
rep2mean = lambda x, bOk: np.interp(np.arange(len(x)), np.flatnonzero(bOk), x[bOk], np.NaN, np.NaN)
fForce2Vabs_fitted = lambda x: da.where(x > 2, 2, da.where(x < 1, 0.25 * x, 0.25 * x + 0.3 * (x - 1) ** 4))
fIncl2Force = lambda incl: da.sqrt(da.tan(incl))
fVabs = lambda Gxyz, kVabs: fForce2Vabs_fitted(fIncl2Force(fInclination(Gxyz)))
f = lambda fun, *args: fun(*args)
positiveInd = lambda i, L: np.int32(da.where(i < 0, L - i, i))
minInterval = lambda iLims1, iLims2, L: f(
lambda iL1, iL2: da.transpose([max(iL1[:, 0], iL2[:, 0]), min(iL1[:, -1], iL2[:, -1])]), positiveInd(iLims1, L),
positiveInd(iLims2, L))
fStEn2bool = lambda iStEn, length: da.hstack(
[(da.ones(iEn2iSt, dtype=np.bool8) if b else da.zeros(iEn2iSt, dtype=np.bool8)) for iEn2iSt, b in da.vstack((
da.diff(
da.hstack(
(
0,
iStEn.flat,
length))),
da.hstack(
