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)
def overall_and_subset_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)
# test init
assert(t.shape == arr.shape and np.all(t.arr == arr) and t.cols == cols and t.index == index and t.name == name)
# test copy
t2 = t.copy()
assert(t2.shape == arr.shape and np.all(t2.arr == arr) and t2.cols == cols and t2.index == index and t2.name == name)
# change values in the copy and make sure original is unmodified
t2.arr[0,:] = 1
t2.index[0] = 'one_m'
t2.cols[0] = 'big A'
t2.name = 'modified_table'
assert(t.shape == arr.shape and np.all(t.arr == arr) and t.cols == cols and t.index == index and t.name == name)
## subset the first and last rows of t2
arr2 = np.array([
[1, 1, 1],
[0.6, 0.3, 0.6]])
index2 = ['one_m','three']
cols2 = ['big A','b','c']
name2 = 'modified_table'
# by list of indices
t3 = t2.row_subset([0,2])
assert(t3.shape == arr2.shape and np.all(t3.arr == arr2) and t3.cols == cols2 and t3.index == index2 and t3.name == name2)
t3_arr = t2.row_subset_arr([0,2])
assert(np.all(t3_arr==arr2))
# by list of names
t3 = t2.row_subset(['one_m','three'])
assert(t3.shape == arr2.shape and np.all(t3.arr == arr2) and t3.cols == cols2 and t3.index == index2 and t3.name == name2)
t3_arr = t2.row_subset_arr(['one_m','three'])
assert(np.all(t3_arr==arr2))
# by array of indices
t3 = t2.row_subset(np.array([0,2]))
assert(t3.shape == arr2.shape and np.all(t3.arr == arr2) and t3.cols == cols2 and t3.index == index2 and t3.name == name2)
t3_arr = t2.row_subset_arr(np.array([0,2]))
assert(np.all(t3_arr==arr2))
# by array of names
t3 = t2.row_subset(np.array(['one_m','three']))
assert(t3.shape == arr2.shape and np.all(t3.arr == arr2) and t3.cols == cols2 and t3.index == index2 and t3.name == name2)
t3_arr = t2.row_subset_arr(['one_m','three'])
assert(np.all(t3_arr==arr2))
# subset just the middle row of t2
arr2 = np.array([
[0.1, 0.3, 0.6]])
cols2 = ['big A','b','c']
index2 = ['two']
name2 = 'modified_table'
# by index
t3 = t2.row_subset(1)
assert(t3.shape == arr2.shape and np.all(t3.arr == arr2) and t3.cols == cols2 and t3.index == index2 and t3.name == name2)
t3_arr = t2.row_subset_arr(1)
assert(np.all(t3_arr==arr2))
# by name
t3 = t2.row_subset('two')
assert(t3.shape == arr2.shape and np.all(t3.arr == arr2) and t3.cols == cols2 and t3.index == index2 and t3.name == name2)
t3_arr = t2.row_subset_arr('two')
assert(np.all(t3_arr==arr2.squeeze()))
## subset the first and last columns of t2
arr2 = np.array([
[1, 1],
[0.1, 0.6],
[0.6, 0.6]])
index2 = ['one_m','two','three']
cols2 = ['big A','c']
name2 = 'modified_table'
# by list of indices
t3 = t2.subset([0,2])
assert(t3.shape == arr2.shape and np.all(t3.arr == arr2) and t3.cols == cols2 and t3.index == index2 and t3.name == name2)
t3_arr = t2.subset_arr([0,2])
assert(np.all(t3_arr==arr2))
# by list of names
t3 = t2.subset(['big A','c'])
assert(t3.shape == arr2.shape and np.all(t3.arr == arr2) and t3.cols == cols2 and t3.index == index2 and t3.name == name2)
t3_arr = t2.subset_arr(['big A','c'])
assert(np.all(t3_arr==arr2))
# by array of indices
t3 = t2.subset(np.array([0,2]))
assert(t3.shape == arr2.shape and np.all(t3.arr == arr2) and t3.cols == cols2 and t3.index == index2 and t3.name == name2)
t3_arr = t2.subset_arr(np.array([0,2]))
assert(np.all(t3_arr==arr2))
# by array of names
t3 = t2.subset(np.array(['big A','c']))
assert(t3.shape == arr2.shape and np.all(t3.arr == arr2) and t3.cols == cols2 and t3.index == index2 and t3.name == name2)
t3_arr = t2.subset_arr(np.array(['big A','c']))
assert(np.all(t3_arr==arr2))
## subset just the middle column of t2
arr2 = np.array([
[1],
[0.3],
[0.3]])
index2 = ['one_m','two','three']
cols2 = ['b']
name2 = 'modified_table'
# by index
t3 = t2.subset(1)
assert(t3.shape == arr2.shape and np.all(t3.arr == arr2) and t3.cols == cols2 and t3.index == index2 and t3.name == name2)
t3_arr = t2.subset_arr(np.array(['b']))
assert(np.all(t3_arr==arr2.squeeze()))
# by name
t3 = t2.subset('b')
assert(t3.shape == arr2.shape and np.all(t3.arr == arr2) and t3.cols == cols2 and t3.index == index2 and t3.name == name2)
t3_arr = t2.subset_arr(['b'])
assert(np.all(t3_arr==arr2.squeeze()))
## row_subset without index
t2 = Table(arr, cols, None, name)
# subset the first and last rows of t2
arr2 = np.array([
[0.2, 0.3, 0.4],
[0.6, 0.3, 0.6]])
index2 = None
cols2 = ['a','b','c']
name2 = 'test_table'
# by list of indices
t3 = t2.row_subset([0,2])
assert(t3.shape == arr2.shape and np.all(t3.arr == arr2) and t3.cols == cols2 and t3.index == index2 and t3.name == name2)
t3_arr = t2.row_subset_arr([0,2])
assert(np.all(t3_arr==arr2))
# by array of indices
t3 = t2.row_subset(np.array([0,2]))
assert(t3.shape == arr2.shape and np.all(t3.arr == arr2) and t3.cols == cols2 and t3.index == index2 and t3.name == name2)
t3_arr = t2.row_subset_arr(np.array([0,2]))
assert(np.all(t3_arr==arr2))
## subset just the middle row of t2
arr2 = np.array([
[0.1, 0.3, 0.6]])
cols2 = ['a','b','c']
name2 = 'test_table'
# by index
t3 = t2.row_subset(1)
assert(t3.shape == arr2.shape and np.all(t3.arr == arr2) and t3.cols == cols2 and t3.index == index2 and t3.name == name2)
t3_arr = t2.row_subset_arr(1)
assert(np.all(t3_arr==arr2.squeeze()))
## subset just the middle value of t2
arr2 = np.array([
[0.3]])
cols2 = ['b']
name2 = 'test_table'
# by index
t3 = t2.row_subset(1).subset(1)
assert(t3.shape == arr2.shape and np.all(t3.arr == arr2) and t3.cols == cols2 and t3.index == index2 and t3.name == name2)
t3_arr = t2.row_subset(1).subset_arr(1)
assert(np.all(t3_arr==np.array([0.3])))
