Commit ce3f2d71 authored by Liubov Chuprikova's avatar Liubov Chuprikova
Browse files

New upstream version 2019.7.0

parent 52a2b782

ci/recipe/meta.yaml

+5 −1
Original line number Diff line number Diff line
@@ -19,7 +19,8 @@ requirements: 


  run:

    - python {{ python }}

    - scikit-learn 0.20.2

    - scikit-learn 0.21.2

    - joblib

    - scikit-bio

    - biom-format >=2.1.5,<2.2.0

    - blast >=2.6.0
@@ -27,6 +28,9 @@ requirements: 
    - vsearch <=2.7.0

    - qiime2 {{ release }}.*

    - q2-types {{ release }}.*

    - q2-quality-control {{ release }}.*

    - q2-taxa {{ release }}.*

    - q2-feature-table {{ release }}.*



test:

  imports:

q2_feature_classifier/_consensus_assignment.py

+8 −1
Original line number Diff line number Diff line
@@ -11,6 +11,7 @@ import subprocess 
import pandas as pd

from os.path import isfile

from collections import Counter, defaultdict

import qiime2





def _get_default_unassignable_label():
@@ -40,7 +41,7 @@ def _consensus_assignments( 
            consensus = {'': ('', '')}

        result = pd.DataFrame.from_dict(consensus, 'index')

        result.index.name = 'Feature ID'

        result.columns = ['Taxon', 'Confidence']

        result.columns = ['Taxon', 'Consensus']

        return result
@@ -242,3 +243,9 @@ def _compute_consensus_annotation(annotations, min_consensus, 
        consensus_fraction_result = 1.0



    return annotation, consensus_fraction_result





def _annotate_method(taxa, method):

    taxa = taxa.view(pd.DataFrame)

    taxa['Method'] = method

    return qiime2.Artifact.import_data('FeatureData[Taxonomy]', taxa)

q2_feature_classifier/_skl.py

+3 −3
Original line number Diff line number Diff line
@@ -9,7 +9,7 @@ 
from itertools import islice, repeat

from copy import deepcopy



from sklearn.externals.joblib import Parallel, delayed

from joblib import Parallel, delayed



_specific_fitters = [

        ['naive_bayes',
@@ -38,7 +38,7 @@ def _extract_reads(reads): 




def predict(reads, pipeline, separator=';', chunk_size=262144, n_jobs=1,

            pre_dispatch='2*n_jobs', confidence=-1.):

            pre_dispatch='2*n_jobs', confidence='disable'):

    return (m for c in Parallel(n_jobs=n_jobs, batch_size=1,

                                pre_dispatch=pre_dispatch)

            (delayed(_predict_chunk)(pipeline, separator, confidence, chunk)
@@ -46,7 +46,7 @@ def predict(reads, pipeline, separator=';', chunk_size=262144, n_jobs=1, 




def _predict_chunk(pipeline, separator, confidence, chunk):

    if confidence < 0.:

    if confidence == 'disable':

        return _predict_chunk_without_conf(pipeline, chunk)

    else:

        return _predict_chunk_with_conf(pipeline, separator, confidence, chunk)

q2_feature_classifier/_taxonomic_classifier.py

+1 −1
Original line number Diff line number Diff line
@@ -11,7 +11,7 @@ import tarfile 
import os



import sklearn

from sklearn.externals import joblib

import joblib

from sklearn.pipeline import Pipeline

import qiime2.plugin

import qiime2.plugin.model as model

q2_feature_classifier/_version.py

+3 −3
Original line number Diff line number Diff line
@@ -23,9 +23,9 @@ def get_keywords(): 
    # setup.py/versioneer.py will grep for the variable names, so they must

    # each be defined on a line of their own. _version.py will just call

    # get_keywords().

    git_refnames = " (tag: 2019.4.0)"

    git_full = "e2ba97ea232a02f4c489b51ff0481583d394a339"

    git_date = "2019-05-03 04:14:49 +0000"

    git_refnames = " (tag: 2019.7.0)"

    git_full = "bc7ed3a741779ccb32114a229af65cc8c1510743"

    git_date = "2019-07-30 18:15:57 +0000"

    keywords = {"refnames": git_refnames, "full": git_full, "date": git_date}

    return keywords