def _(data: Bag, fr: float, to: float, bins: int) -> Tuple[ndarray, ndarray]:
# @jit(nopython=True, nogil=True) # todo: jit this function
def inc(values: Iterable[float]) -> ndarray:
binned = digitize(values, linspace(fr, to, bins + 1))
init = zeros(bins + 2, dtype=uint64)
for i in binned:
init[i] += 1
return init
hist = data.reduction(inc, sum)
return hist, linspace(fr, to, bins + 1)
def _(data: Bag, xfr: float, xto: float, xbins: int, yfr: float, yto: float,
ybins: int) -> Tuple[ndarray, ndarray, ndarray]:
# @jit(nopython=True, nogil=True) # todo: jit this function
def inc(values: Iterable[Tuple[float, float]]) -> ndarray:
xvalues, yvalues = column_stack(values)
xbinned = digitize(xvalues, linspace(xfr, xto, xbins + 1))
ybinned = digitize(yvalues, linspace(yfr, yto, ybins + 1))
init = zeros((xbins + 2, ybins + 2), dtype=uint64)
for x, y in zip(xbinned, ybinned):
init[x, y] += 1
return init
hist = data.reduction(inc, sum)
return hist, linspace(xfr, xto, xbins + 1), linspace(yfr, yto, ybins + 1)