def _(data: RDD, fr: float, to: float, bins: int) -> Tuple[ndarray, ndarray]:
@jit(['uint64[:](uint64[:], int64)', 'uint64[:](uint64[:], float64)'],
nopython=True,
nogil=True)
def inc(init: ndarray, value: float) -> ndarray:
binned = digitize([value], linspace(fr, to, bins + 1))
for i in binned:
init[i] += 1
return init
hist = data.aggregate(zeros(bins + 2, dtype=uint64), inc, com)
return hist, linspace(fr, to, bins + 1)
def _(data: RDD, xfr: float, xto: float, xbins: int, yfr: float, yto: float,
ybins: int) -> Tuple[ndarray, ndarray, ndarray]:
@jit([
'uint64[:, :](uint64[:, :], int64[:])',
'uint64[:, :](uint64[:, :], float64[:])'
],
nopython=True,
nogil=True)
def inc(init: ndarray, value: Tuple[float, float]) -> ndarray:
xbinned = digitize([value[0]], linspace(xfr, xto, xbins + 1))
ybinned = digitize([value[1]], linspace(yfr, yto, ybins + 1))
for x, y in zip(xbinned, ybinned):
init[x, y] += 1
return init
hist = data.aggregate(zeros((xbins + 2, ybins + 2), dtype=uint64), inc,
com)
return hist, linspace(xfr, xto, xbins + 1), linspace(yfr, yto, ybins + 1)
