def setUp(self) -> None:
"""
Sets up unittest
"""
self.a_line = Line(M, N, (MIN_X, MAX_X), (MIN_Y, MAX_Y))
self.m = self.a_line.m
self.n = self.a_line.n
def setUp(self) -> None:
"""
Sets up unittest
"""
a_line = Line((1, 1), (0, 0), (-1, 1), (-1, 1))
self.train_set = a_line.training_set(1000)
self.file_path = path.dirname(path.abspath(__file__))
def __init__(self, m_range: (float, float),
n_range: ((float, float), (float, float)),
x_range: (float, float),
y_range: (float, float)):
super().__init__(x_range, y_range, "DoubleLine")
self.m = uniform(m_range[0], m_range[1])
n1 = uniform(n_range[0][0], n_range[0][1])
n2 = uniform(n_range[1][0], n_range[1][1])
self.line1 = Line((self.m, self.m), (n1, n1), x_range, y_range)
self.line2 = Line((self.m, self.m), (n2, n2), x_range, y_range)
return
class TestLine(TestCase):
def setUp(self) -> None:
"""
Sets up unittest
"""
self.a_line = Line(M, N, (MIN_X, MAX_X), (MIN_Y, MAX_Y))
self.m = self.a_line.m
self.n = self.a_line.n
def test_x_to_y(self):
x = 20
expected = self.m * x + self.n
actual = self.a_line.x_to_y(x)
assert abs(actual[0] - expected) < EPSILON
def test_y_to_x(self):
y = 20
expected = (y - self.n) / self.m
actual = self.a_line.y_to_x(y)
assert abs(actual[0] - expected) < EPSILON
def test_is_above(self):
x = 0
y = 40
assert self.a_line.is_above(x, y)
x = 1
y = self.a_line.x_to_y(x)[0]
y1 = y + 0.5
y2 = y - 0.5
assert self.a_line.is_above(x, y1)
assert not self.a_line.is_above(x, y2)
def test_graph(self):
x, y = self.a_line.graph()
assert len(x) == len(y)
FIG_SIZE = (12 * 3, 12)
X_MIN = Y_MIN = -50
X_MAX = Y_MAX = 50
SLOPE = (-2.0, 2.0)
INTERCEPT = (-10.0, 10.0)
N = 100
TO_SHOW = 1500
np.random.seed(3)
seed(3)
if __name__ == '__main__':
logging.basicConfig(level=logging.INFO)
# Predict a line
line = Line(SLOPE, INTERCEPT, (X_MIN, X_MAX), (Y_MIN, Y_MAX))
# Initialize perceptron
perceptron = LearningPerceptron("learning perceptron", 2, 0.1)
# Random dataset
train_set = line.training_set(N)
test_set = line.training_set(TO_SHOW)
# First plot
fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=FIG_SIZE)
prediction = do_prediction(perceptron, test_set)
logging.info("First Plot")
plot_result(test_set, np.array(prediction), line, ax1)
ax1.set_title("Before training\n", fontsize=20)
class DoubleLine(Pattern):
"""Double Line, define points inside and outside two line on plane"""
def __init__(self, m_range: (float, float),
n_range: ((float, float), (float, float)),
x_range: (float, float),
y_range: (float, float)):
super().__init__(x_range, y_range, "DoubleLine")
self.m = uniform(m_range[0], m_range[1])
n1 = uniform(n_range[0][0], n_range[0][1])
n2 = uniform(n_range[1][0], n_range[1][1])
self.line1 = Line((self.m, self.m), (n1, n1), x_range, y_range)
self.line2 = Line((self.m, self.m), (n2, n2), x_range, y_range)
return
def x_to_y(self, x: float) -> [float]:
"""
Gives y values from x value
:param x: abscissa coordinate
:return: ordinate coordinate
"""
return [self.line1.x_to_y(x)[0], self.line2.x_to_y(x)[0]]
def y_to_x(self, y: float) -> [float]:
"""
Gives x values from y value
:param y: ordinate coordinate
:return: abscissa coordinate
"""
return [self.line1.y_to_x(y)[0], self.line2.y_to_x(y)[0]]
# outside
def is_above(self, x: float, y: float) -> bool:
"""
Return if a given point is above pattern
:param x: x coordinate
:param y: y coordinate
:return: Whether the point is above
"""
return not self.line1.is_above(x, y) or self.line2.is_above(x, y)
def graph(self) -> ([float], [float]):
"""
Gives values to be graph
:return: Two arrays to be used for graphic pattern
"""
x1, y1 = self.line1.graph()
x2, y2 = self.line2.graph()
return x1 + x2, y1 + y2
def add_results(self, ax: Axes) -> None:
"""
Add pattern to a Axes figure on matplotlib
:param ax: Axes in which results will be inserted
:return: None (update ax)
"""
x, y = self.graph()
x1 = x[0:2]
x2 = x[2:4]
y1 = y[0:2]
y2 = y[2:4]
ax.plot(x1, y1, "-", label="Line 1")
ax.plot(x2, y2, "-", label="Line 2")
X_MAX = Y_MAX = 50
FIG_SIZE = (6 * 4 + 2, 6)
TITLE_SIZE = 20
RADIUS = 30
FACE = 50
CENTER = (0.0, 0.0)
SLOPE = (-2.0, 2.0)
INTERCEPT = (-10.0, 10.0)
INTERCEPT1 = (-40.0, -20.0)
INTERCEPT2 = (20.0, 40.0)
TWO_INTERCEPT = (INTERCEPT1, INTERCEPT2)
if __name__ == '__main__':
logging.basicConfig(level=logging.INFO)
line = Line(SLOPE, INTERCEPT, (X_MIN, X_MAX), (Y_MIN, Y_MAX))
double_line = DoubleLine(SLOPE, TWO_INTERCEPT, (X_MIN, X_MAX),
(Y_MIN, Y_MAX))
circle = Circle(RADIUS, CENTER, (X_MIN, X_MAX), (Y_MIN, Y_MAX))
square = Square(FACE, CENTER, (X_MIN, X_MAX), (Y_MIN, Y_MAX))
fig = plt.figure(figsize=FIG_SIZE)
ax1 = fig.add_subplot(141)
ax2 = fig.add_subplot(142)
ax3 = fig.add_subplot(143)
ax4 = fig.add_subplot(144)
figures = {line: ax1, double_line: ax2, circle: ax3, square: ax4}
for figure in figures.keys():
logging.info("Generating {}".format(figure.name))