def test_lowess():
"""
Tests lowess normalization.
"""
counts_fname = utils.load_testdata("pasilla")
# Consider only a subset of the samples
samples = OrderedDict()
samples["Untreated 1"] = "untreated1"
samples["Untreated 2"] = "untreated2"
exp_obj = experiment.Experiment(counts_fname, samples)
pairs = [["untreated1", "untreated2"]]
norm_df, unnorm_df = normalizers.norm_ma_lowess(exp_obj, pairs)
print "\nLowess Testing:"
print "--------------"
print "Pre-normalized values: "
print unnorm_df.head()
print "Normalized counts: "
print norm_df.head()
# Compare LOWESS normalized to total counts
pair = ["untreated1", "untreated2"]
plot_utils.plot_fcs(norm_df, unnorm_df, pair, "lowess_test")
def test_lowess():
"""
Tests lowess normalization.
"""
counts_fname = utils.load_testdata("pasilla")
# Consider only a subset of the samples
samples = OrderedDict()
samples["Untreated 1"] = "untreated1"
samples["Untreated 2"] = "untreated2"
exp_obj = experiment.Experiment(counts_fname, samples)
pairs = [["untreated1", "untreated2"]]
norm_df, unnorm_df = normalizers.norm_ma_lowess(exp_obj, pairs)
print("\nLowess Testing:")
print("--------------")
print("Pre-normalized values: ")
print(unnorm_df.head())
print("Normalized counts: ")
print(norm_df.head())
# Compare LOWESS normalized to total counts
pair = ["untreated1", "untreated2"]
plot_utils.plot_fcs(norm_df, unnorm_df, pair, "lowess_test")