Ejemplo n.º 1
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def single_object_alpha(biom_object, metrics, tree_object):
	"""given a metric calculates alpha diversity of a biom object

	Inputs:
	biom_object: biom formatted OTU table
	metrics: list of alpha diversity metrics
	tree_object: tree object for the phylogenetic metrics

	Output:
	calculations: tab delimitted string with the calculations for the object
	"""

	calcs = []
	for metric in metrics:
		try:
			metric_f = get_nonphylogenetic_metric(metric)
			is_phylogenetic = False
		except AttributeError:
			try:
				metric_f = get_phylogenetic_metric(metric)
				is_phylogenetic = True
			except AttributeError:
				print 'something is wrong with conf file'
		c = AlphaDiversityCalc(metric_f, is_phylogenetic)
		calcs.append(c)

	all_calcs = AlphaDiversityCalcs(calcs)

	result = all_calcs(data_path=biom_object, tree_path=tree_object,
		log_path=None)
	return all_calcs.formatResult(result)
Ejemplo n.º 2
0
def single_object_alpha(biom_object, metrics, tree_object):
    """given a metric calculates alpha diversity of a biom object

	Inputs:
	biom_object: biom formatted OTU table
	metrics: list of alpha diversity metrics
	tree_object: tree object for the phylogenetic metrics

	Output:
	calculations: tab delimitted string with the calculations for the object
	"""

    calcs = []
    for metric in metrics:
        try:
            metric_f = get_nonphylogenetic_metric(metric)
            is_phylogenetic = False
        except AttributeError:
            try:
                metric_f = get_phylogenetic_metric(metric)
                is_phylogenetic = True
            except AttributeError:
                print 'something is wrong with conf file'
        c = AlphaDiversityCalc(metric_f, is_phylogenetic)
        calcs.append(c)

    all_calcs = AlphaDiversityCalcs(calcs)

    result = all_calcs(data_path=biom_object,
                       tree_path=tree_object,
                       log_path=None)
    return all_calcs.formatResult(result)
Ejemplo n.º 3
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def single_file_cup(otu_filepath, metrics, outfilepath, r, alpha, f, ci_type):
    """Compute variations of the conditional uncovered probability.

    otufilepath: path to otu_table file
    metrics: comma separated list of required metrics
    outfilepath: path to output file

    r: Number of new colors that are required for the next prediction
    alpha: desired confidence level
    f: ratio between upper and lower bound
    ci_type: type of confidence interval. One of:
             ULCL: upper and lower bounds with conservative lower bound
             ULCU: upper and lower woth conservative upper bound
             U: Upper bound only, lower bound fixed to 0
             L: Lower bound only, upper bound fixed to 1

    The opposite of uncovered probability is sometimes called coverage.
    """
    metrics_list = metrics.split(',')
    calcs = []

    params = {'r': r,
              'alpha': alpha,
              'f':f,
              'ci_type':ci_type}
                  
    for metric in metrics_list:
        try:
            metric_f = get_cup_metric(metric)
        except AttributeError:
            stderr.write(
                "Could not find metric %s.\n Known metrics are: %s\n" \
                    % (metric, ', '.join(list_known_metrics())))
            exit(1)
            
        c = AlphaDiversityCalc(metric_f, params=params)
        calcs.append(c)
    
    all_calcs = AlphaDiversityCalcs(calcs)

    try:
        result = all_calcs(data_path=otu_filepath,
            result_path=outfilepath, log_path=None)
        if result:  #can send to stdout instead of file
            print all_calcs.formatResult(result)
    except IOError, e:
        stderr.write("Failed because of missing files.\n")
        stderr.write(str(e)+'\n')
        exit(1)
Ejemplo n.º 4
0
 def test1(self):
     """ checks that output from AlphaDiversityCalcs is the right shape
     when run on phylo, multiple return value nonphylo, and another nonphylo
     """
     calc1 = AlphaDiversityCalc(metric=observed_otus)
     calc2 = AlphaDiversityCalc(metric=PD_whole_tree, is_phylogenetic=True)
     calc3 = AlphaDiversityCalc(metric=osd)
     calcs = AlphaDiversityCalcs([calc1, calc2, calc3])
     results = calcs(data_path=self.otu_table1_fp,
                     tree_path=self.tree1,
                     result_path=None,
                     log_path=None)
     self.assertEqual(results[0].shape, (3, 5))
     self.assertEqual(len(results[1]), 3)
     self.assertEqual(len(results[2]), 5)