How to use the presto.psr_utils.p_to_f function in presto

def parse_eph(filenm):
    global period, time
    suffix = filenm.split(".")[-1]
    if suffix=="bestprof":
        x = bestprof.bestprof(filenm)
        fs = pu.p_to_f(x.p0_bary, x.p1_bary, x.p2_bary)
        epoch = x.epochi_bary + x.epochf_bary
        T = x.T
    elif suffix=="par":
        x = parfile.psr_par(filenm)
        # Try to see how many freq derivs we have
        fs = [x.F0]
        for ii in range(1, 20):  # hopefully 20 is an upper limit!
            attrib = "F%d"%ii
            if hasattr(x, attrib):
                fs.append(getattr(x, attrib))
            else:
                break
        epoch = x.PEPOCH
        T = (x.FINISH - x.START) * 86400.0
    else:
        print("I don't recognize the file type for", filenm)

bestpd = self.fold_p2
                bestpdd = self.fold_p3
            else:
                bestp = self.topo_p1
                bestpd = self.topo_p2
                bestpdd = self.topo_p3
        if p is not None:
            bestp = p
        if pd is not None:
            bestpd = pd
        if pdd is not None:
            bestpdd = pdd

        # self.fold_p[123] are actually frequencies, convert to periods
        foldf, foldfd, foldfdd = self.fold_p1, self.fold_p2, self.fold_p3
        foldp, foldpd, foldpdd = psr_utils.p_to_f(self.fold_p1, \
                                        self.fold_p2, self.fold_p3)

        # Get best f, fd, fdd
        # Use folding values to be consistent with prepfold_plot.c
        bestfdd = psr_utils.p_to_f(foldp, foldpd, bestpdd)[2]
        bestfd = psr_utils.p_to_f(foldp, bestpd)[1]
        bestf = 1.0/bestp

        # Get frequency and frequency derivative offsets
        f_diff = bestf - foldf
        fd_diff = bestfd - foldfd

        # bestpdd=0.0 only if there was no searching over pdd
        if bestpdd != 0.0:
            fdd_diff = bestfdd - foldfdd
        else:

if p is not None:
            bestp = p
        if pd is not None:
            bestpd = pd
        if pdd is not None:
            bestpdd = pdd

        # self.fold_p[123] are actually frequencies, convert to periods
        foldf, foldfd, foldfdd = self.fold_p1, self.fold_p2, self.fold_p3
        foldp, foldpd, foldpdd = psr_utils.p_to_f(self.fold_p1, \
                                        self.fold_p2, self.fold_p3)

        # Get best f, fd, fdd
        # Use folding values to be consistent with prepfold_plot.c
        bestfdd = psr_utils.p_to_f(foldp, foldpd, bestpdd)[2]
        bestfd = psr_utils.p_to_f(foldp, bestpd)[1]
        bestf = 1.0/bestp

        # Get frequency and frequency derivative offsets
        f_diff = bestf - foldf
        fd_diff = bestfd - foldfd

        # bestpdd=0.0 only if there was no searching over pdd
        if bestpdd != 0.0:
            fdd_diff = bestfdd - foldfdd
        else:
            fdd_diff = 0.0

        return (f_diff, fd_diff, fdd_diff)

bestpdd = self.topo_p3
        if p is not None:
            bestp = p
        if pd is not None:
            bestpd = pd
        if pdd is not None:
            bestpdd = pdd

        # self.fold_p[123] are actually frequencies, convert to periods
        foldf, foldfd, foldfdd = self.fold_p1, self.fold_p2, self.fold_p3
        foldp, foldpd, foldpdd = psr_utils.p_to_f(self.fold_p1, \
                                        self.fold_p2, self.fold_p3)

        # Get best f, fd, fdd
        # Use folding values to be consistent with prepfold_plot.c
        bestfdd = psr_utils.p_to_f(foldp, foldpd, bestpdd)[2]
        bestfd = psr_utils.p_to_f(foldp, bestpd)[1]
        bestf = 1.0/bestp

        # Get frequency and frequency derivative offsets
        f_diff = bestf - foldf
        fd_diff = bestfd - foldfd

        # bestpdd=0.0 only if there was no searching over pdd
        if bestpdd != 0.0:
            fdd_diff = bestfdd - foldfdd
        else:
            fdd_diff = 0.0

        return (f_diff, fd_diff, fdd_diff)