def test_table_apply():
data = np.ones([3, 100])
data[1] = 2
data[2] = 3
tab = ds.Table(columns=data, labels=['a', 'b', 'c'])
newtab = util.table_apply(tab, np.mean)
assert newtab.num_rows == 1
assert all(newtab['a'] == np.mean(tab['a']))
newtab = util.table_apply(tab, lambda a: a + 1)
assert all(newtab['a'] == tab['a'] + 1)
newtab = util.table_apply(tab, lambda a: a + 1, subset=['b', 'c'])
assert all(newtab['a'] == tab['a'])
assert all(newtab['b'] == tab['b'] + 1)
def test_table_apply():
data = np.ones([3, 100])
data[1] = 2
data[2] = 3
# tab = ds.Table(data, ['a', 'b', 'c'])
tab = ds.Table().with_columns('a', data[0], 'b', data[1], 'c', data[2])
newtab = util.table_apply(tab, np.mean)
assert newtab.num_rows == 1
assert all(newtab['a'] == np.mean(tab['a']))
newtab = util.table_apply(tab, lambda a: a + 1)
assert all(newtab['a'] == tab['a'] + 1)
newtab = util.table_apply(tab, lambda a: a + 1, subset=['b', 'c'])
assert all(newtab['a'] == tab['a'])
assert all(newtab['b'] == tab['b'] + 1)
def mne_to_table(data):
"""Convert an MNE Raw object into a datascience table.
Parameters
----------
data : instance of MNE raw object.
The data to be converted to a table.
Returns
-------
table : instance of datascience Table.
The data in table format.
"""
df = pd.DataFrame(data._data.T, columns=data.ch_names)
table = ds.Table().from_df(df)
table['time'] = np.arange(df.shape[0]) / data.info['sfreq']
return table
def test_currency_format():
vs = ['$60', '$162.5']
t = ds.Table([vs, vs, vs], ['num1', 'num2', 'str'])
t.set_format(['num1', 'num2'], ds.CurrencyFormatter('$'))
assert_equal(t, """
num1 | num2 | str
$60.00 | $60.00 | $60
$162.50 | $162.50 | $162.5
""")
assert_equal(t.sort('num1'), """
num1 | num2 | str
$60.00 | $60.00 | $60
$162.50 | $162.50 | $162.5
""")
assert_equal(t.sort('str'), """
num1 | num2 | str
$162.50 | $162.50 | $162.5
$60.00 | $60.00 | $60
""")
def test_table_apply():
data = np.ones([3, 100])
data[1] = 2
data[2] = 3
# tab = ds.Table(data, ['a', 'b', 'c'])
tab = ds.Table().with_columns('a', data[0], 'b', data[1], 'c', data[2])
newtab = util.table_apply(tab, np.mean)
assert newtab.num_rows == 1
assert all(newtab['a'] == np.mean(tab['a']))
newtab = util.table_apply(tab, lambda a: a + 1)
assert all(newtab['a'] == tab['a'] + 1)
newtab = util.table_apply(tab, lambda a: a + 1, subset=['b', 'c'])
assert all(newtab['a'] == tab['a'])
assert all(newtab['b'] == tab['b'] + 1)
with pytest.raises(ValueError) as err:
util.table_apply(tab, lambda a: a + 1, subset=['b', 'd'])
assert "Colum mismatch: ['d']" in str(err.value)
def test_date_format():
vs = ['2015-07-01 22:39:44.900351']
t = ds.Table([vs], ['time'])
t.set_format('time', ds.DateFormatter("%Y-%m-%d %H:%M:%S.%f"))
assert isinstance(t['time'][0], float)
