def filtering_test():
arr = np.array([
[0.2, 0.3, 0.4],
[0.1, 0.3, 0.6],
[0.6, 0.3, 0.6]])
cols = ['a','b','c']
index = ['one','two','three']
name = 'test_table'
t = Table(arr, cols, index, name)
# filter by equality
t2 = t.filter_on_column('c',0.6)
arr2 = np.array([
[0.1, 0.3, 0.6],
[0.6, 0.3, 0.6]])
cols2 = ['a','b','c']
index2 = ['two','three']
name2 = 'test_table'
assert(t2.shape == arr2.shape and np.all(t2.arr == arr2) and t2.cols == cols2 and t2.index == index2 and t2.name == name2)
# filter by < 0.6
t2 = t.filter_on_column('c',0.6,operator.lt)
arr2 = np.array([
[0.2, 0.3, 0.4]])
cols2 = ['a','b','c']
index2 = ['one']
name2 = 'test_table'
assert(t2.shape == arr2.shape and np.all(t2.arr == arr2) and t2.cols == cols2 and t2.index == index2 and t2.name == name2)
# filter by < 0.6 and omit column
t2 = t.filter_on_column('c',0.6,operator.lt,omit=True)
arr2 = np.array([
[0.2, 0.3]])
cols2 = ['a','b']
index2 = ['one']
name2 = 'test_table'
assert(t2.shape == arr2.shape and np.all(t2.arr == arr2) and t2.cols == cols2 and t2.index == index2 and t2.name == name2)
