How to use the pyranges.multithreaded.pyrange_apply function in pyranges

43     0.43    197   9956  0.019787
        44     0.44    224   9956  0.022499
        45     0.45    184   9956  0.018481
        46     0.46    198   9956  0.019888
        47     0.47    187   9956  0.018783
        48     0.48    200   9956  0.020088
        49     0.49    194   9956  0.019486
        """

        self = self.pr

        kwargs = {}
        kwargs["sparse"] = {"self": True, "other": True}
        kwargs = pr.pyranges.fill_kwargs(kwargs)

        result = pyrange_apply(_relative_distance, self, other, **kwargs)  # pylint: disable=E1132

        result = pd.Series(np.concatenate(list(result.values())))

        not_nan = ~np.isnan(result)
        result.loc[not_nan] = np.floor(result[not_nan] * 100) / 100
        vc = result.value_counts(dropna=False).to_frame().reset_index()
        vc.columns = "reldist count".split()
        vc.insert(vc.shape[1], "total", len(result))
        vc.insert(vc.shape[1], "fraction", vc["count"] / len(result))
        vc = vc.sort_values("reldist", ascending=True)
        vc = vc.reset_index(drop=True)

        return vc

def nearest(self, other, **kwargs):

        from pyranges.methods.nearest import _nearest

        kwargs = fill_kwargs(kwargs)
        if kwargs.get("how") in "upstream downstream".split():
            assert other.stranded, "If doing upstream or downstream nearest, other pyranges must be stranded"

        dfs = pyrange_apply(_nearest, self, other, **kwargs)

        return PyRanges(dfs)

def count_overlaps(self, other, **kwargs):

        kwargs = fill_kwargs(kwargs)

        from pyranges.methods.coverage import _number_overlapping
        counts = pyrange_apply(_number_overlapping, self, other, **kwargs)

        return pr.PyRanges(counts)

def set_intersect(self, other, **kwargs):

        kwargs = fill_kwargs(kwargs)
        strandedness = kwargs["strandedness"]
        strand = True if strandedness else False
        self_clusters = self.merge(strand=strand, **kwargs)
        other_clusters = other.merge(strand=strand, **kwargs)
        dfs = pyrange_apply(_intersection, self_clusters, other_clusters,
                            **kwargs)

        return PyRanges(dfs)

def coverage(self, other, **kwargs):

        kwargs = fill_kwargs(kwargs)

        counts = self.count_overlaps(other, keep_nonoverlapping=True, **kwargs)

        strand = True if kwargs["strandedness"] else False
        other = other.merge(count=True, strand=strand)

        from pyranges.methods.coverage import _coverage

        # print(counts)
        counts = pr.PyRanges(pyrange_apply(_coverage, counts, other, **kwargs))
        # print("counts" * 100)
        # print(counts)

        return counts

assert suffixes[0], "Must have nonempty first suffix when using new_pos with intersection or union."
                assert suffixes[1], "Must have nonempty second suffix when using new_pos with intersection or union."

        # def get_items_dtypes(s):

        #     columns = s.columns
        #     dtypes = (s.dfs.values())
        how = kwargs.get("how")

        if how in ["left", "outer"]:
            kwargs["example_header_other"] = other.head(1).df
        if how in ["right", "outer"]:
            kwargs["example_header_self"] = self.head(1).df


        dfs = pyrange_apply(_write_both, self, other, **kwargs)

        gr = PyRanges(dfs)

        if slack:
            gr.Start = gr.Start__slack
            gr.End = gr.End__slack
            gr = gr.drop(like="(Start|End).*__slack")

        new_position = kwargs.get("new_pos")
        if new_position:
            gr = gr.new_position(new_pos=new_position, suffixes=kwargs["suffixes"])

        return gr

def overlap(self, other, **kwargs):

        kwargs["sparse"] = {"self": False, "other": True}
        kwargs["how"] = "first"
        kwargs = fill_kwargs(kwargs)

        dfs = pyrange_apply(_overlap, self, other, **kwargs)

        # if kwargs.get("return_indexes"):
        #     return dfs
        # else:
        return pr.PyRanges(dfs)

def intersect(self, other, **kwargs):

        kwargs = fill_kwargs(kwargs)
        kwargs["sparse"] = {"self": False, "other": True}

        dfs = pyrange_apply(_intersection, self, other, **kwargs)

        return PyRanges(dfs)