comparison cwpair2_util.py @ 2:279cdc63bcff draft

Uploaded

1:4d86371aafa8

COLORS = 'krg'
Y_LABEL = 'Peak-pair counts'
X_LABEL = 'Peak-pair distance (bp)'
TICK_WIDTH = 3
ADJUST = [0.140, 0.9, 0.9, 0.1]
pyplot.rc('xtick.major', size=10.00)
pyplot.rc('ytick.major', size=10.00)
pyplot.rc('lines', linewidth=4.00)
pyplot.rc('axes', linewidth=3.00)
pyplot.rc('font', family='Bitstream Vera Sans', size=32.0)

        os.mkdir('%s_%s' % (match_method, PREVIEW_PLOTS))
        os.mkdir('%s_%s' % (match_method, SIMPLES))
        os.mkdir('%s_%s' % (match_method, STATS_GRAPH))


def process_file(dataset_path, galaxy_hid, method, threshold, up_distance, down_distance,
                 binsize, output_files, plot_format, sort_chromosome, sort_score):
    if method == 'all':
        match_methods = METHODS.keys()
    else:
        match_methods = [method]
    statistics = []

                                threshold,
                                up_distance,
                                down_distance,
                                binsize,
                                output_files,
                                plot_format,
                                sort_chromosome,
                                sort_score)
        statistics.append(stats)
    if output_files == 'all' and method == 'all':
        frequency_plot([s['dist'] for s in statistics],

                       labels=METHODS.keys())
    return statistics


def perform_process(dataset_path, galaxy_hid, method, threshold, up_distance,
                    down_distance, binsize, output_files, plot_format, sort_chromosome, sort_score):
    output_details = output_files in ["all", "simple_orphan_detail"]
    output_plots = output_files in ["all"]
    output_orphans = output_files in ["all", "simple_orphan", "simple_orphan_detail"]
    # Keep track of statistics for the output file
    statistics = {}

        # Details
        detailed_output = td_writer('%s_%s' % (method, DETAILS), extension=TABULAR_EXT)
        detailed_output.writerow(('chrom', 'start', 'end', 'value', 'strand') * 2 + ('midpoint', 'c-w reads sum', 'c-w distance (bp)'))
    if output_plots:
        # Final Plot
        final_plot_path = make_path('%s_%s' % (method, FINAL_PLOTS), plot_format)
    if output_orphans:
        # Orphans
        orphan_output = td_writer('%s_%s' % (method, ORPHANS), extension=TABULAR_EXT)
        orphan_output.writerow(('chrom', 'strand', 'start', 'end', 'value'))
    if output_plots:
        # Preview Plot
        preview_plot_path = make_path('%s_%s' % (method, PREVIEW_PLOTS), plot_format)
    # Simple
    simple_output = td_writer('%s_%s' % (method, SIMPLES), extension=GFF_EXT)
    statistics['stats_path'] = 'statistics.%s' % TABULAR_EXT
    if output_plots:
        statistics['graph_path'] = make_path('%s_%s' % (method, STATS_GRAPH), plot_format)
    statistics['perc95'] = perc95(chromosomes)
    if threshold > 0:
        # Apply filter
        filter(chromosomes, threshold)
    if method == 'mode':

2:279cdc63bcff

COLORS = 'krg'
Y_LABEL = 'Peak-pair counts'
X_LABEL = 'Peak-pair distance (bp)'
TICK_WIDTH = 3
ADJUST = [0.140, 0.9, 0.9, 0.1]
PLOT_FORMAT = 'pdf'
pyplot.rc('xtick.major', size=10.00)
pyplot.rc('ytick.major', size=10.00)
pyplot.rc('lines', linewidth=4.00)
pyplot.rc('axes', linewidth=3.00)
pyplot.rc('font', family='Bitstream Vera Sans', size=32.0)

        os.mkdir('%s_%s' % (match_method, PREVIEW_PLOTS))
        os.mkdir('%s_%s' % (match_method, SIMPLES))
        os.mkdir('%s_%s' % (match_method, STATS_GRAPH))


def process_file(dataset_path, galaxy_hid, method, threshold, up_distance,
                 down_distance, binsize, output_files, sort_chromosome, sort_score):
    if method == 'all':
        match_methods = METHODS.keys()
    else:
        match_methods = [method]
    statistics = []

                                threshold,
                                up_distance,
                                down_distance,
                                binsize,
                                output_files,
                                sort_chromosome,
                                sort_score)
        statistics.append(stats)
    if output_files == 'all' and method == 'all':
        frequency_plot([s['dist'] for s in statistics],

                       labels=METHODS.keys())
    return statistics


def perform_process(dataset_path, galaxy_hid, method, threshold, up_distance,
                    down_distance, binsize, output_files, sort_chromosome, sort_score):
    output_details = output_files in ["all", "simple_orphan_detail"]
    output_plots = output_files in ["all"]
    output_orphans = output_files in ["all", "simple_orphan", "simple_orphan_detail"]
    # Keep track of statistics for the output file
    statistics = {}

        # Details
        detailed_output = td_writer('%s_%s' % (method, DETAILS), extension=TABULAR_EXT)
        detailed_output.writerow(('chrom', 'start', 'end', 'value', 'strand') * 2 + ('midpoint', 'c-w reads sum', 'c-w distance (bp)'))
    if output_plots:
        # Final Plot
        final_plot_path = make_path('%s_%s' % (method, FINAL_PLOTS), PLOT_FORMAT)
    if output_orphans:
        # Orphans
        orphan_output = td_writer('%s_%s' % (method, ORPHANS), extension=TABULAR_EXT)
        orphan_output.writerow(('chrom', 'strand', 'start', 'end', 'value'))
    if output_plots:
        # Preview Plot
        preview_plot_path = make_path('%s_%s' % (method, PREVIEW_PLOTS), PLOT_FORMAT)
    # Simple
    simple_output = td_writer('%s_%s' % (method, SIMPLES), extension=GFF_EXT)
    statistics['stats_path'] = 'statistics.%s' % TABULAR_EXT
    if output_plots:
        statistics['graph_path'] = make_path('%s_%s' % (method, STATS_GRAPH), PLOT_FORMAT)
    statistics['perc95'] = perc95(chromosomes)
    if threshold > 0:
        # Apply filter
        filter(chromosomes, threshold)
    if method == 'mode':