Anaphory

import typing
from collections import Counter

import numpy


def match_pixels(
    prediction: numpy.ndarray, ground_truth: numpy.ndarray
) -> (typing.Mapping, int):
    """Compare two rasters and calculate the deviation under good matching.

Anaphory

<?xml version='1.0' encoding='UTF-8'?>
<beast namespace="beast.math.distributions:beast.core:beast.evolution.operators:beast.evolution.alignment:beast.evolution.substitutionmodel" version="2.6">
  <data id="vocabulary" dataType="integer" spec="Alignment">
    <sequence id="language_data_vocabulary:Burmish_Achang" taxon="Burmish_Achang" value="0??????????????????????????????????????????0000000000000000001000000000000000010000000001000001000000000000001000000000000000000000000001000000000000000000001000000000001000000000000000001000000000000000001000000000000000010000000000000000000100000000000000000000000000000100000000000000000000010000000000000000000000010000000000000000000000000000000001000000001000000000000010000000000000000010000000000000000000000100000000000000000000000000000001000000000000000010000000000000000000000000100000000000000100000000001000000000000000000000000000000000000000000000000000000100000000000000000001000000000000000000000000000000000010000000000100000000000000000?????000000000000000000

Anaphory

Keybase proof

I hereby claim:

• I am anaphory on github.
• I am anaphory (https://keybase.io/anaphory) on keybase.
• I have a public key ASCVWgVP2NiRqAl2iERc5hBOnrdfNTWdmc9PwR5FrwGnwQo

To claim this, I am signing this object:

Anaphory

import random
import bisect
from collections import Counter


class DiscreteProbabilities:
    def __init__(self, ps):
        keys, values = zip(*sorted(ps.items(), key=lambda kv: kv[1], reverse=True))
        self.values = numpy.cumsum(values)
        self.values /= self.values[-1]

Anaphory

$ ipython -i learn_self_prediction.py
Python 3.7.0 (default, Jul 15 2018, 10:44:58)
Type 'copyright', 'credits' or 'license' for more information
IPython 6.5.0 -- An enhanced Interactive Python. Type '?' for help.
2018-08-24 13:25:17.004949: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA

 0
6334.686 6314.654 6454.043 5467.191 4630.695 5274.8535 4090.4727 5082.1665 4502.7056 4170.152 3758.1313 3549.1992 5426.775 4515.8086 4039.757 4290.015 4046.6309 3355.1636 3481.4727 4011.1167 4178.433 3500.3604 4051.9387 3624.7375 3237.043 3290.1333 2853.6572 3310.5354 4224.2935 3168.8103 1848.3478 3250.229 3800.9048 2348.2676 3272.28 2983.5427 3413.0337 3097.3425 2112.8743 3239.0488 3507.999 2810.7412 3342.6511 3041.751 3207.8457 3690.589 3361.581 3579.3613 4382.718 3158.9675 2267.3567 3017.4578 3500.6853 3729.4807 3245.2744 2825.9363 2228.9045 3072.2527 2228.2583 2793.7139 2314.4797 3250.0674 3723.1445 217

Anaphory

#!/usr/bin/env python

"""Script to plot trees with ASR using ete3."""

import argparse
import sys

import pandas
import ete3

Anaphory

#!/usr/bin/env python3

import collections

class DiscreteProbabilityDistribution:
    def __init__(self, pdict):
        try:
            self.pdict = collections.Counter(pdict)
        except:
            self.pdict = collections.Counter({pdict: 1})