def test_zscore(self):
#TODO split plate control and vehicle control into two functions
r = norm.normalize(l)
zv = zscore.calculate_zscore(r, plate_control=False)
zp = zscore.calculate_zscore(r, plate_control=True)
assert round(zv.data_df['test_CS0_X1:A'][0], 4) == -10.0
assert round(zv.data_df['test_CS0_X1:B'][2], 4) == -5.5729
assert round(zv.data_df['test_CS0_X1:D'][1], 4) == 0.6745
assert round(zp.data_df['test_CS0_X1:A'][0], 4) == -0.903
assert round(zp.data_df['test_CS0_X1:B'][2], 4) == -0.7558
assert round(zp.data_df['test_CS0_X1:D'][1], 4) == 0.8159
def normalize_data():
global data_matrix
global progressbar_total
sample_length = len(data_matrix[0])
sample_count = len(data_matrix)
for attribute_index in range(sample_length - 1):
attribute_list = list()
normalized_attribute_list = list()
for sample_index in range(sample_count):
attribute_list.append(data_matrix[sample_index][attribute_index])
for attribute in attribute_list:
z_score = zscore.calculate_zscore(attribute, attribute_list)
rounded_zscore = math.ceil(z_score * 100000) / 100000
normalized_attribute_list.append(rounded_zscore)
for sample_index in range(sample_count):
data_matrix[sample_index][
attribute_index] = normalized_attribute_list[sample_index]
progressbar.show(7,
progressbar_total,
prefix='Progress:',
suffix='Complete',
length=50)
def test_modz(self):
l2 = pe(
'functional_tests/test_merino/assemble/test_CS0_X2/test_CS0_X2_MEDIAN.gct'
)
l3 = pe(
'functional_tests/test_merino/assemble/test_CS0_X3/test_CS0_X3_MEDIAN.gct'
)
r = norm.normalize(l)
r2 = norm.normalize(l2)
r3 = norm.normalize(l3)
z = zscore.calculate_zscore(r, plate_control=True)
z2 = zscore.calculate_zscore(r2, plate_control=True)
z3 = zscore.calculate_zscore(r3, plate_control=True)
modz_gct, ccq74, weights = distil.calculate_modz([z, z2, z3])
assert round(modz_gct.data_df['test_CS0X1:A'][0], 4) == -0.5816
assert round(modz_gct.data_df['test_CS0X1:B'][2], 4) == -0.4991
assert round(modz_gct.data_df['test_CS0X1:D'][1], 4) == 1.001
