elf_python/memory_receiver.py [157:202]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
class SeqStats:
    def __init__(self, name="seq", seq_limits=None):
        # Stats.
        self.stats_seq = Counter()
        self.clear_stats()
        self.name = name

        if seq_limits is None:
            self.limits = [1, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1200, 1400, 1600, 1800, 2000, 2500, 3000, 4000, 5000, float("inf")]
        else:
            self.limits = seq_limits
            if not np.isinf(self.limits[-1]):
                self.limits.append(float("inf"))

    def feed(self, seqs):
        for seq_num in seqs:
            bin_idx = None
            for i, limit in enumerate(self.limits[1:]):
                if int(seq_num) < limit:
                    bin_idx = i
                    break
            if seq_num > self.max_seq:
                self.max_seq = seq_num
            if seq_num < self.min_seq:
                self.min_seq = seq_num

            name = "[" + str(self.limits[bin_idx]) + ", " + str(self.limits[bin_idx + 1]) + ")"
            self.stats_seq[name] += 1

    def print_stats(self, reset=False):
        total_counts = sum(self.stats_seq.values())
        if total_counts > 0:
            print("Distribution of %s [min = %d / max = %d / #count = %d]:" % (self.name, self.min_seq, self.max_seq, total_counts))
            s = ""
            for r in sorted(self.stats_seq.keys(), key=lambda x : float(x.split(",")[0][1:])):
                s += "%s: %d [%.2lf%%]\n" % (r, self.stats_seq[r], 100.0 * self.stats_seq[r] / total_counts)
            print(s)
        else:
            print("Distribution of %s [#count = %d]:" % (self.name, total_counts))

        if reset: self.clear_stats()

    def clear_stats(self):
        self.stats_seq.clear()
        self.max_seq = 0
        self.min_seq = float('inf')
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



rlpytorch/utils/utils.py [302:347]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
class SeqStats:
    def __init__(self, name="seq", seq_limits=None):
        # Stats.
        self.stats_seq = Counter()
        self.clear_stats()
        self.name = name

        if seq_limits is None:
            self.limits = [1, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1200, 1400, 1600, 1800, 2000, 2500, 3000, 4000, 5000, float("inf")]
        else:
            self.limits = seq_limits
            if not np.isinf(self.limits[-1]):
                self.limits.append(float("inf"))

    def feed(self, seqs):
        for seq_num in seqs:
            bin_idx = None
            for i, limit in enumerate(self.limits[1:]):
                if int(seq_num) < limit:
                    bin_idx = i
                    break
            if seq_num > self.max_seq:
                self.max_seq = seq_num
            if seq_num < self.min_seq:
                self.min_seq = seq_num

            name = "[" + str(self.limits[bin_idx]) + ", " + str(self.limits[bin_idx + 1]) + ")"
            self.stats_seq[name] += 1

    def print_stats(self, reset=False):
        total_counts = sum(self.stats_seq.values())
        if total_counts > 0:
            print("Distribution of %s [min = %d / max = %d / #count = %d]:" % (self.name, self.min_seq, self.max_seq, total_counts))
            s = ""
            for r in sorted(self.stats_seq.keys(), key=lambda x : float(x.split(",")[0][1:])):
                s += "%s: %d [%.2lf%%]\n" % (r, self.stats_seq[r], 100.0 * self.stats_seq[r] / total_counts)
            print(s)
        else:
            print("Distribution of %s [#count = %d]:" % (self.name, total_counts))

        if reset: self.clear_stats()

    def clear_stats(self):
        self.stats_seq.clear()
        self.max_seq = 0
        self.min_seq = float('inf')
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -