Source code for sourmash.minhash

# -*- coding: UTF-8 -*-
from __future__ import unicode_literals, division

import math
import copy
from import Mapping

from . import VERSION
from ._lowlevel import ffi, lib
from .utils import RustObject, rustcall, decode_str
from .exceptions import SourmashError
from deprecation import deprecated

# default MurmurHash seed

def get_minhash_default_seed():
    "Return the default seed value used for the MurmurHash hashing function."

# we use the 64-bit hash space of MurmurHash only
# this is 2 ** 64 - 1 in hexadecimal

def get_minhash_max_hash():
    "Return the maximum hash value."

def _get_max_hash_for_scaled(scaled):
    "Convert a 'scaled' value into a 'max_hash' value."
    if scaled == 0:
        return 0
    elif scaled == 1:
        return get_minhash_max_hash()

    return min(
        int(round(get_minhash_max_hash() / scaled, 0)),

def _get_scaled_for_max_hash(max_hash):
    "Convert a 'max_hash' value into a 'scaled' value."
    if max_hash == 0:
        return 0
    return min(
        int(round(get_minhash_max_hash() / max_hash, 0)),

def to_bytes(s):
    # Allow for strings, bytes or int
    # Single item of byte string = int

    if isinstance(s, bytes):
        return s

    if not isinstance(s, (str, bytes, int)):
        raise TypeError("Requires a string-like sequence")

    if isinstance(s, str):
        s = s.encode("utf-8")
    elif isinstance(s, int):
        s = bytes([s])

    return s

def hash_murmur(kmer, seed=MINHASH_DEFAULT_SEED):
    "hash_murmur(string, [,seed])\n\n"
    "Compute a hash for a string, optionally using a seed (an integer). "
    "The current default seed is returned by hash_seed()."

    return lib.hash_murmur(to_bytes(kmer), seed)

def translate_codon(codon):
    "Translate a codon into an amino acid."
        return rustcall(lib.sourmash_translate_codon,
    except SourmashError as e:
        raise ValueError(e.message)

class _HashesWrapper(Mapping):
    "A read-only view of the hashes contained by a MinHash object."
    def __init__(self, h):
        self._data = h

    def __getitem__(self, key):
        return self._data[key]

    def __repr__(self):
        return repr(self._data)

    def __len__(self):
        return len(self._data)

    def __iter__(self):
        return iter(self._data)

    def __eq__(self, other):
        return list(self.items()) == list(other.items())

    def __setitem__(self, k, v):
        raise RuntimeError("cannot modify hashes directly; use 'add' methods")

[docs]class MinHash(RustObject): """\ The core sketch object for sourmash. MinHash objects store and provide functionality for subsampled hash values from DNA, RNA, and amino acid sequences. MinHash also supports both the standard MinHash behavior (bounded size or ``num``) and a non-standard MinHash, called "modulo hash" behavior, or ``scaled``. Please see the API examples at for more information. Basic usage: >>> from sourmash import MinHash >>> mh1 = MinHash(n=20, ksize=3) >>> mh1.add_sequence('ATGAGAGACGATAGACAGATGAC') >>> mh2 = MinHash(n=20, ksize=3) >>> mh2.add_sequence('ATGAGActCGATAGaCAGATGAC') >>> round(mh1.similarity(mh2), 2) 0.85 """ __dealloc_func__ = lib.kmerminhash_free
[docs] def __init__( self, n, ksize, is_protein=False, dayhoff=False, hp=False, track_abundance=False, seed=MINHASH_DEFAULT_SEED, max_hash=0, mins=None, scaled=0, ): """\ Create a sourmash.MinHash object. To create a standard (``num``) MinHash, use: ``MinHash(<num>, <ksize>, ...)`` To create a ``scaled`` MinHash, use ``MinHash(0, <ksize>, scaled=<int>, ...)`` Optional arguments: * is_protein (default False) - aa k-mers * dayhoff (default False) - dayhoff encoding * hp (default False) - hydrophilic/hydrophobic aa * track_abundance (default False) - track hash multiplicity * mins (default None) - list of hashvals, or (hashval, abund) pairs * seed (default 42) - murmurhash seed """ # support max_hash in constructor, for now. if max_hash: if scaled: raise ValueError("cannot set both max_hash and scaled") scaled = _get_scaled_for_max_hash(max_hash) if scaled and n: raise ValueError("cannot set both n and max_hash") if not n and not scaled: raise ValueError("cannot omit both n and scaled") if dayhoff or hp: is_protein = False if dayhoff: hash_function = lib.HASH_FUNCTIONS_MURMUR64_DAYHOFF ksize = ksize*3 elif hp: hash_function = lib.HASH_FUNCTIONS_MURMUR64_HP ksize = ksize*3 elif is_protein: hash_function = lib.HASH_FUNCTIONS_MURMUR64_PROTEIN ksize = ksize*3 else: hash_function = lib.HASH_FUNCTIONS_MURMUR64_DNA self._objptr = lib.kmerminhash_new( scaled, ksize, hash_function, seed, track_abundance, n ) if mins: if track_abundance: self.set_abundances(mins) else: self.add_many(mins)
def __copy__(self): "Create a new copy of this MinHash." a = MinHash( self.num, self.ksize, is_protein=self.is_protein, dayhoff=self.dayhoff, hp=self.hp, track_abundance=self.track_abundance, seed=self.seed, max_hash=self.max_hash, ) a.merge(self) return a def __getstate__(self): "support pickling via __getstate__/__setstate__" return ( self.num, self.ksize, self.is_protein, self.dayhoff, self.hp, self.hashes, None, self.track_abundance, self.max_hash, self.seed, ) def __setstate__(self, tup): "support pickling via __getstate__/__setstate__" (n, ksize, is_protein, dayhoff, hp, mins, _, track_abundance, max_hash, seed) = tup self.__del__() hash_function = ( lib.HASH_FUNCTIONS_MURMUR64_DAYHOFF if dayhoff else lib.HASH_FUNCTIONS_MURMUR64_HP if hp else lib.HASH_FUNCTIONS_MURMUR64_PROTEIN if is_protein else lib.HASH_FUNCTIONS_MURMUR64_DNA ) scaled = _get_scaled_for_max_hash(max_hash) self._objptr = lib.kmerminhash_new( scaled, ksize, hash_function, seed, track_abundance, n ) if track_abundance: self.set_abundances(mins) else: self.add_many(mins) def __eq__(self, other): "equality testing via ==" return self.__getstate__() == other.__getstate__()
[docs] def copy_and_clear(self): "Create an empty copy of this MinHash." a = MinHash( self.num, self.ksize, self.is_protein, self.dayhoff, self.hp, self.track_abundance, self.seed, self.max_hash, ) return a
[docs] def add_sequence(self, sequence, force=False): "Add a sequence into the sketch." self._methodcall(lib.kmerminhash_add_sequence, to_bytes(sequence), force)
[docs] def add_kmer(self, kmer): "Add a kmer into the sketch." if self.is_dna: if len(kmer) != self.ksize: raise ValueError("kmer to add is not {} in length".format(self.ksize)) else: if len(kmer) != self.ksize*3: raise ValueError("kmer to add is not {} in length".format(self.ksize*3)) self.add_sequence(kmer)
[docs] def add_many(self, hashes): """Add many hashes to the sketch at once. ``hashes`` can be either an iterable (list, set, etc.), or another ``MinHash`` object. """ if isinstance(hashes, MinHash): self._methodcall(lib.kmerminhash_add_from, hashes._objptr) else: self._methodcall(lib.kmerminhash_add_many, list(hashes), len(hashes))
[docs] def remove_many(self, hashes): "Remove many hashes at once; ``hashes`` must be an iterable." self._methodcall(lib.kmerminhash_remove_many, list(hashes), len(hashes))
def __len__(self): "Number of hashes." return self._methodcall(lib.kmerminhash_get_mins_size)
[docs] @deprecated(deprecated_in="3.5", removed_in="5.0", current_version=VERSION, details='Use .hashes property instead.') def get_mins(self, with_abundance=False): """Return list of hashes or if ``with_abundance`` a list of (hash, abund). """ mins = self.hashes if not with_abundance: return mins.keys() return mins
[docs] @deprecated(deprecated_in="3.5", removed_in="5.0", current_version=VERSION, details='Use .hashes property instead.') def get_hashes(self): "Return the list of hashes." return self.hashes.keys()
@property def hashes(self): size ="uintptr_t *") mins_ptr = self._methodcall(lib.kmerminhash_get_mins, size) size = size[0] try: if self.track_abundance: size_abunds ="uintptr_t *") abunds_ptr = self._methodcall(lib.kmerminhash_get_abunds, size_abunds) size_abunds = size_abunds[0] assert size == size_abunds result = dict(zip(ffi.unpack(mins_ptr, size), ffi.unpack(abunds_ptr, size))) lib.kmerminhash_slice_free(abunds_ptr, size) return _HashesWrapper(result) else: d = ffi.unpack(mins_ptr, size) return _HashesWrapper({ k : 1 for k in d }) finally: lib.kmerminhash_slice_free(mins_ptr, size) @property def seed(self): return self._methodcall(lib.kmerminhash_seed) @property def num(self): return self._methodcall(lib.kmerminhash_num) @property def scaled(self): mx = self._methodcall(lib.kmerminhash_max_hash) if mx: return _get_scaled_for_max_hash(mx) return 0 @property def is_dna(self): return not (self.is_protein or self.dayhoff or self.hp) @property def is_protein(self): return self._methodcall(lib.kmerminhash_is_protein) @property def dayhoff(self): return self._methodcall(lib.kmerminhash_dayhoff) @property def hp(self): return self._methodcall(lib.kmerminhash_hp) @property def ksize(self): k = self._methodcall(lib.kmerminhash_ksize) if not self.is_dna: assert k % 3 == 0 k = int(k / 3) return k @property @deprecated(deprecated_in="3.5", removed_in="5.0", current_version=VERSION, details='Use scaled instead.') def max_hash(self): return self._methodcall(lib.kmerminhash_max_hash) @property def track_abundance(self): return self._methodcall(lib.kmerminhash_track_abundance) @track_abundance.setter def track_abundance(self, b): if self.track_abundance == b: return if b is False: self._methodcall(lib.kmerminhash_disable_abundance) elif len(self) > 0: raise RuntimeError("Can only set track_abundance=True if the MinHash is empty") else: self._methodcall(lib.kmerminhash_enable_abundance)
[docs] def add_hash(self, h): "Add a single hash value." return self._methodcall(lib.kmerminhash_add_hash, h)
[docs] def add_hash_with_abundance(self, h, a): "Add a single hash value with an abundance." if self.track_abundance: return self._methodcall(lib.kmerminhash_add_hash_with_abundance, h, a) else: raise RuntimeError( "Use track_abundance=True when constructing " "the MinHash to use add_hash_with_abundance." )
[docs] def clear(self): "Clears all hashes and abundances." return self._methodcall(lib.kmerminhash_clear)
[docs] def count_common(self, other, downsample=False): """\ Return the number of hashes in common between ``self`` and ``other``. Optionally downsample ``scaled`` objects to highest ``scaled`` value. """ if not isinstance(other, MinHash): raise TypeError("Must be a MinHash!") return self._methodcall(lib.kmerminhash_count_common, other._get_objptr(), downsample)
[docs] def downsample(self, num=None, scaled=None): """Copy this object and downsample new object to either `num` or `scaled`. """ if num is None and scaled is None: raise ValueError('must specify either num or scaled to downsample') elif num is not None: if self.num and self.num < num: raise ValueError("new sample num is higher than current sample num") max_hash=0 elif scaled is not None: if self.num: raise ValueError("num != 0 - cannot downsample a standard MinHash") max_hash = self.max_hash if max_hash is None: raise ValueError("no max_hash available - cannot downsample") old_scaled = _get_scaled_for_max_hash(self.max_hash) if old_scaled > scaled: raise ValueError( "new scaled {} is lower than current sample scaled {}".format( scaled, old_scaled ) ) max_hash = _get_max_hash_for_scaled(scaled) num = 0 ### # create new object: a = MinHash( num, self.ksize, self.is_protein, self.dayhoff, self.hp, self.track_abundance, self.seed, max_hash ) # copy over hashes: if self.track_abundance: a.set_abundances(self.hashes) else: a.add_many(self) return a
[docs] def flatten(self): """Return a new MinHash with track_abundance=False.""" # create new object: a = MinHash( self.num, self.ksize, self.is_protein, self.dayhoff, self.hp, False, self.seed, self.max_hash ) a.add_many(self) return a
[docs] def jaccard(self, other, downsample=False): "Calculate Jaccard similarity of two MinHash objects." if self.num != other.num: err = "must have same num: {} != {}".format(self.num, other.num) raise TypeError(err) return self._methodcall(lib.kmerminhash_similarity, other._get_objptr(), True, downsample)
[docs] def similarity(self, other, ignore_abundance=False, downsample=False): """Calculate similarity of two sketches. If the sketches are not abundance weighted, or ignore_abundance=True, compute Jaccard similarity. If the sketches are abundance weighted, calculate the angular similarity, a distance metric based on the cosine similarity. Note, because the term frequencies (tf-idf weights) cannot be negative, the angle will never be < 0deg or > 90deg. See """ return self._methodcall(lib.kmerminhash_similarity, other._get_objptr(), ignore_abundance, downsample)
[docs] def angular_similarity(self, other): "Calculate the angular similarity." return self._methodcall(lib.kmerminhash_angular_similarity, other._get_objptr())
def is_compatible(self, other): return self._methodcall(lib.kmerminhash_is_compatible, other._get_objptr())
[docs] def contained_by(self, other, downsample=False): """\ Calculate how much of self is contained by other. """ if not len(self): return 0.0 return self.count_common(other, downsample) / len(self)
def __iadd__(self, other): if not isinstance(other, MinHash): raise TypeError("Must be a MinHash!") self._methodcall(lib.kmerminhash_merge, other._get_objptr()) return self merge = __iadd__
[docs] def set_abundances(self, values, clear=True): """Set abundances for hashes from ``values``, where ``values[hash] = abund`` """ if self.track_abundance: hashes = [] abunds = [] for h, v in values.items(): hashes.append(h) abunds.append(v) self._methodcall(lib.kmerminhash_set_abundances, hashes, abunds, len(hashes), clear) else: raise RuntimeError( "Use track_abundance=True when constructing " "the MinHash to use set_abundances." )
[docs] def add_protein(self, sequence): "Add a protein sequence." self._methodcall(lib.kmerminhash_add_protein, to_bytes(sequence))
@property def moltype(self): # TODO: test in minhash tests if self.is_protein: return 'protein' elif self.dayhoff: return 'dayhoff' elif self.hp: return 'hp' else: return 'DNA'