def test_where_all_are_true(self):
M = [[1, 2, 3], [2, 3, 4], [3, 4, 5]]
col_names = ['heigh', 'weight', 'age']
lables = [0, 0, 1]
M = eights.utils.cast_list_of_list_to_sa(M, col_names=col_names)
arguments = [{
'func': val_eq,
'col_name': 'heigh',
'vals': 1
}, {
'func': val_lt,
'col_name': 'weight',
'vals': 3
}, {
'func': val_between,
'col_name': 'age',
'vals': (3, 4)
}]
res = where_all_are_true(M, arguments, 'eq_to_stuff')
ctrl = np.array([(1, 2, 3, True), (2, 3, 4, False), (3, 4, 5, False)],
dtype=[('heigh', '<i8'), ('weight', '<i8'),
('age', '<i8'), ('eq_to_stuff', '?')])
self.assertTrue(np.array_equal(res, ctrl))
def test_where_all_are_true(self):
M = [[1,2,3], [2,3,4], [3,4,5]]
col_names = ['heigh','weight', 'age']
lables= [0,0,1]
M = eights.utils.cast_list_of_list_to_sa(
M,
col_names=col_names)
arguments = [{'func': val_eq, 'col_name': 'heigh', 'vals': 1},
{'func': val_lt, 'col_name': 'weight', 'vals': 3},
{'func': val_between, 'col_name': 'age', 'vals':
(3, 4)}]
res = where_all_are_true(
M,
arguments,
'eq_to_stuff')
ctrl = np.array(
[(1, 2, 3, True), (2, 3, 4, False), (3, 4, 5, False)],
dtype=[('heigh', '<i8'), ('weight', '<i8'), ('age', '<i8'),
('eq_to_stuff', '?')])
self.assertTrue(np.array_equal(res, ctrl))
if False:
plot_correlation_scatter_plot(M)
plot_correlation_matrix(M)
plot_kernel_density(M["f0"]) # no designation of col name
plot_box_plot(M["f0"]) # no designation of col name
if False:
from eights.generate import val_between, where_all_are_true, append_cols # val_btwn, where
# generate a composite rule
M = where_all_are_true(
M,
[
{"func": val_between, "col_name": "f0", "vals": (3.5, 5.0)},
{"func": val_between, "col_name": "f1", "vals": (2.7, 3.1)},
],
"a new col_name",
)
# new eval function
def rounds_to_val(M, col_name, boundary):
return np.round(M[col_name]) == boundary
M = where_all_are_true(M, [{"func": rounds_to_val, "col_name": "f0", "vals": 5}], "new_col")
from eights.truncate import fewer_then_n_nonzero_in_col, remove_rows_where, remove_cols, val_eq
# remove Useless row
M = fewer_then_n_nonzero_in_col(M, 1)
M = append_cols(M, labels, "labels")
print x
if False:
plot_correlation_scatter_plot(M)
plot_correlation_matrix(M)
plot_kernel_density(M['f0']) #no designation of col name
plot_box_plot(M['f0']) #no designation of col name
if False:
from eights.generate import val_between, where_all_are_true, append_cols #val_btwn, where
#generate a composite rule
M = where_all_are_true(M, [{
'func': val_between,
'col_name': 'f0',
'vals': (3.5, 5.0)
}, {
'func': val_between,
'col_name': 'f1',
'vals': (2.7, 3.1)
}], 'a new col_name')
#new eval function
def rounds_to_val(M, col_name, boundary):
return (np.round(M[col_name]) == boundary)
M = where_all_are_true(M, [{
'func': rounds_to_val,
'col_name': 'f0',
'vals': 5
}], 'new_col')
