def test_load_from_data_encodes_data():
encoder = OneHotEncoder(['animal', 'color'], ['weight'], max_levels_default=100)
data = [{'animal': 'cat', 'color': 'blue', 'weight': 1.0},
{'animal': 'cat', 'color': 'red', 'weight': 3.0},
{'animal': 'dog', 'color': 'yellow', 'weight': 5.5},
{'animal': 'fish', 'color': 'blue', 'weight': 7.0},
{'animal': 'cat', 'color': 'blue', 'weight': 2.0},
{'animal': 'cat', 'color': 'blue', 'weight': 0.0},
{'animal': 'cat', 'color': 'blue', 'weight': 99.9}]
encoder.load_from_data_stream(data)
encoded_data = [encoder.encode_row(row) for row in data]
assert len(encoded_data) == len(data)
assert len(encoded_data[0]) != len(data[0])
def test_load_from_data_encodes_data_correctly():
encoder = OneHotEncoder(['animal', 'color'], ['weight'], max_levels_default=100)
data = [{'animal': 'cat', 'color': 'blue', 'weight': 6.0},
{'animal': 'cat', 'color': 'red', 'weight': 3.0},
{'animal': 'dog', 'color': 'yellow', 'weight': 5.5},
{'animal': 'fish', 'color': 'blue', 'weight': 7.0},
{'animal': 'cat', 'color': 'magenta', 'weight': 2.0},
{'animal': 'mouse', 'color': 'purple', 'weight': 0.0},
{'animal': 'mouse', 'color': 'black', 'weight': 99.9}]
encoder.load_from_data_stream(data)
encoded_data = [encoder.encode_row(row) for row in data]
assert len(encoded_data) == len(data)
assert len(encoded_data[0]) != len(data[0])
first_row = encoded_data[0]
expected = [6.0, # weight is numeric and comes first
1.0, # animal is first categorical and cat is the most common, first row is cat
0.0, # animal, mouse is next most common, not a mouse
0.0, # animal, dog and fish tied for frequency but dog first alphabetically
0.0, # animal, fish, cat is not a fish
1.0, # color is next categorical alphabetically and blue is most common, first row blue
0.0, # black
0.0, # magenta
0.0, # purple
0.0, # red
0.0] # yellow
assert first_row == expected
second_row = encoded_data[1]
expected = [3.0, # weight is numeric and comes first
1.0, # animal is first categorical and cat is the most common, first row is cat
0.0, # animal, mouse is next most common, not a mouse
0.0, # animal, dog and fish tied for frequency but dog first alphabetically
0.0, # animal, fish, cat is not a fish
0.0, # color is next categorical alphabetically and blue is most common, first row blue
0.0, # black next alphabetically for ones with frequency 1
0.0, # magenta next
0.0, # purple
1.0, # red, this is red
0.0] # yellow
assert second_row == expected
last_row = encoded_data[-1]
expected = [99.9, # weight is numeric and comes first
0.0, # animal is first categorical and cat is the most common, first row is cat
1.0, # animal, mouse is next most common, not a mouse
0.0, # animal, dog and fish tied for frequency but dog first alphabetically
0.0, # animal, fish, cat is not a fish
0.0, # color is next categorical alphabetically and blue is most common, first row blue
1.0, # black next alphabetically for ones with frequency 1, this one black
0.0, # magenta next
0.0, # purple
0.0, # red
0.0] # yellow
expected_total = [[6.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[3.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0],
[5.5, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0],
[7.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[2.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0],
[99.9, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0]]
assert encoded_data == expected_total