コード例 #1
0
def test_group():

	dm = DataMatrix(length=4)
	dm.a = 'b', 'b', 'a', 'a'
	dm.b = 'x', 'x', 'x', 'y'
	dm.c = IntColumn
	dm.c = 0, 1, 2, 3
	dm = ops.group(dm, [dm.a, dm.b])
	check_series(dm.c, [[2, np.nan], [3, np.nan], [0, 1]])
コード例 #2
0
def test_group():

    dm = DataMatrix(length=4)
    dm.a = 'b', 'b', 'a', 'a'
    dm.b = 'x', 'x', 'x', 'y'
    dm.c = IntColumn
    dm.c = 0, 1, 2, 3
    dm = ops.group(dm, [dm.a, dm.b])
    check_series(dm.c, [[3, np.nan], [2, np.nan], [0, 1]])  # Order guaranteed?
コード例 #3
0
def test_group():

    dm = DataMatrix(length=4)
    dm.a = 'b', 'b', 'a', 'a'
    dm.b = 'x', 'x', 'x', 'y'
    dm.c = IntColumn
    dm.c = 0, 1, 2, 3
    dm = ops.group(dm, [dm.a, dm.b])
    # Assert that at least one of the permutations passes
    for ref in itertools.permutations([[3, np.nan], [2, np.nan], [0, 1]]):
        try:
            check_series(dm.c, ref)
            break
        except AssertionError:
            pass
    else:
        assert (False)
コード例 #4
0
ファイル: helpers.py プロジェクト: smathot/semantic_pupil 
def descriptives(dm):

	"""
	desc:
		Provides basic descriptives of response times. These are printed
		directly to the stdout.

	arguments:
		dm:
			type: DataMatrix
	"""

	ops.keep_only(dm, cols=['type', 'rt'])
	gm = ops.group(dm, by=[dm.type])
	gm.mean_rt = series.reduce_(gm.rt)
	gm.se_rt = series.reduce_(gm.rt, lambda x: np.nanstd(x)/np.sqrt(len(x)))
	gm.n = series.reduce_(gm.rt, lambda x: np.sum(~np.isnan(x)))
	del gm.rt
	print(gm)