def test_drop_function5(self):
"""Soccer data example."""
mis_id = self.mis_id
test_data = np.array([
[1.,.2,mis_id,mis_id,5.,6.,7.,8.],
[1.,.2,mis_id,mis_id,5.,6.,7.,8.],
[1.,.2,mis_id,mis_id,5.,6.,7.,8.],
[1.,.2,mis_id,mis_id,5.,6.,7.,8.],
[1.,.2,mis_id,mis_id,5.,6.,7.,8.],
[1.,.2,3.,4.,5.,6.,7.,8.],
[1.,.2,3.,4.,5.,6.,mis_id,mis_id],
[1.,.2,3.,4.,5.,6.,mis_id,mis_id],
[1.,.2,3.,4.,5.,6.,mis_id,mis_id]])
expect = np.array([
[1.,.2,mis_id,mis_id,5.,6.,7.,8.],
[1.,.2,mis_id,mis_id,5.,6.,7.,8.],
[1.,.2,mis_id,mis_id,5.,6.,7.,8.],
[1.,.2,mis_id,mis_id,5.,6.,7.,8.],
[1.,.2,mis_id,mis_id,5.,6.,7.,8.],
[1.,.2,mis_id,mis_id,5.,6.,7.,8.],
[1.,.2,3.,4.,5.,6.,mis_id,mis_id],
[1.,.2,3.,4.,5.,6.,mis_id,mis_id],
[1.,.2,3.,4.,5.,6.,mis_id,mis_id]])
obtained = ra.drop_expanded_ragged_entries(test_data, 6)
self.assertTrue(np.all(obtained == expect))
def stitch_position_data(pos,ball,NO_PLAYERS=11):
"""Puts position data into a single array.
stitch_position_data does not change the ordering of the data and
stitches the position data together as given. Therefore, if the playing
position must be controlled sort_position_data must be called first.
Args:
pos: position data list (indexed ragged array)
ball: list with two matrices (1st and 2nd half)
NO_PLAYERS: default = 11
Returns:
output_fields:
"""
# magic numbers
_MISSING_ = -2.0**13
_NO_DIM_ = 2 # x- and y-coordinates
_POST_LOOK_ = 20
# end magic numbers
frames = ball[:,0]
min_frame = min(frames)
max_frame = max(frames)
no_frames = ball.shape[0]
if no_frames != (max_frame - min_frame + 1):
raise IndexError("No of ball frames doesn't match")
no_players_input = len(pos)
input_fields = ra.expand_indexed_ragged_array(pos, frames,
lambda x: x[1], _MISSING_)
input_fields_clean = ra.drop_expanded_ragged_entries(input_fields,NO_PLAYERS*_NO_DIM_,_MISSING_)
output_fields = ra.condense_expanded_ragged_array(input_fields, missing_id = _MISSING_)
return output_fields
def test_drop_function1(self):
"""Tests simple case."""
mis_id = self.mis_id
test_data = np.array([[1.,.2,mis_id],
[1.,2.,mis_id],
[1.,2.,3.],
[mis_id,2.,3.]])
expect = test_data.copy()
expect[2,2] = mis_id
obtained = ra.drop_expanded_ragged_entries(test_data, 2)
self.assertTrue(np.all(obtained == expect))
def test_drop_function3(self):
"""Tests continuous and offsets entries."""
mis_id = self.mis_id
test_data = np.array([[1.,.2,mis_id,mis_id],
[1.,2.,mis_id,mis_id],
[1.,mis_id,3.,4.],
[mis_id,2.,3.,4.],
[mis_id,2.,3.,4.]])
expect = np.array([[1.,.2,mis_id,mis_id],
[1.,2.,mis_id,mis_id],
[1.,mis_id,3.,mis_id],
[mis_id,2.,3.,mis_id],
[mis_id,2.,3.,mis_id]])
obtained = ra.drop_expanded_ragged_entries(test_data, 2)
self.assertTrue(np.all(obtained == expect))
def test_drop_function4(self):
"""Tests case with fewer entries."""
mis_id = self.mis_id
test_data = np.array([[1.,.2,mis_id,mis_id],
[1.,2.,mis_id,mis_id],
[mis_id,2.,3.,4.],
[mis_id,mis_id,mis_id,4.],
[mis_id,mis_id,mis_id,4.]])
expect = np.array([[1.,.2,mis_id,mis_id],
[1.,2.,mis_id,mis_id],
[mis_id,2.,3.,mis_id],
[mis_id,mis_id,mis_id,4.],
[mis_id,mis_id,mis_id,4.]])
obtained = ra.drop_expanded_ragged_entries(test_data, 2)
self.assertTrue(np.all(obtained == expect))
def test_drop_function3(self):
"""Tests complete change of entry positions."""
mis_id = self.mis_id
test_data = np.array([[1.,.2,mis_id,mis_id],
[1.,2.,mis_id,mis_id],
[mis_id,mis_id,3.,4.],
[mis_id,mis_id,3.,4.],
[mis_id,mis_id,3.,4.]])
expect = np.array([[1.,.2,mis_id,mis_id],
[1.,2.,mis_id,mis_id],
[mis_id,mis_id,3.,4.],
[mis_id,mis_id,3.,4.],
[mis_id,mis_id,3.,4.]])
obtained = ra.drop_expanded_ragged_entries(test_data, 2)
self.assertTrue(np.all(obtained == expect))