def setWeights(self, weights):
"""
Plot the linear regression line for given weights; assuming h_w(x) = weights[0]*x + weights[1].
This will draw on the existing pacman window with the existing points
weights: array or list of 2 values (or if just one value, the bias weight is assumed to be zero). If None,
no line is drawn. Default: None
"""
weights = np.array(weights)
if weights.size >= 2:
w = weights[0]
b = weights[1]
else:
w = float(weights)
b = 0
# xmin = min(x)
# xmax = max(x)
#
# ymin = w*xmin + b
# ymax = w*xmax + b
#
# point1 = (xmin+self.xShift, ymin+self.yShift)
# point2 = (xmax+self.xShift, ymax+self.yShift)
(point1, point2) = plotUtil.lineBoxIntersection(
w, -1, b, 1 - self.xShift, 1 - self.yShift,
self.width - 2 - self.xShift, self.height - 2 - self.yShift)
if point1 is not None and point2 is not None:
point1 = (point1[0] + self.xShift, point1[1] + self.yShift)
point2 = (point2[0] + self.xShift, point2[1] + self.yShift)
dx = point2[0] - point1[0]
dy = point2[1] - point1[1]
if dx == 0:
angle = 90 + 180 * dy * 1.0 / abs(dy)
else:
angle = math.atan(dy * 1.0 / dx) * 180.0 / math.pi
if self.line is not None:
graphicsUtils.remove_from_screen(self.line)
self.line = graphicsUtils.polygon(
[self.to_screen(point1),
self.to_screen(point2)],
LINE_COLOR,
filled=0,
behind=0)
if self.addPacmanToLineStart is True and len(self.agentImages) > 0:
# Bring pacman to front of display
graphicsUtils._canvas.tag_raise(self.agentImages[0][1][0])
# Put pacman at beginning of line
self.movePacman(point1, angle, self.agentImages[0][1])
graphicsUtils.refresh()
def setWeights(self, weights):
"""
Plot the logistic regression line for given weights
This will draw on the existing pacman window with the existing points
weights: array or list of 2 values (or if just one value, the bias weight is assumed to be zero). If None,
no line is drawn. Default: None
"""
weights = np.array(weights)
if weights.size >= 2:
w = weights[0]
b = weights[1]
else:
w = float(weights)
b = 0
xmin = 1 - self.xShift
xmax = self.width - 2 - self.xShift
x = np.linspace(xmin, xmax, 30)
y = 1.0 / (1 + np.exp(-(w * x + b)))
x += self.xShift
y += self.yShift
if self.line is not None:
for obj in self.line:
graphicsUtils.remove_from_screen(obj)
self.line = []
prevPoint = self.to_screen((x[0], y[0]))
for i in xrange(1, len(x)):
point = self.to_screen((x[i], y[i]))
self.line.append(graphicsUtils.line(prevPoint, point, LINE_COLOR))
prevPoint = point
# prevPoint = self.to_screen((x[0],y[0]))
# for i in xrange(1,len(x)):
# point = self.to_screen((x[i],y[i]))
# line.append(graphicsUtils.line(prevPoint, point, LINE_COLOR, filled=0, behind=0)
#
# prevPoint = point
if self.addPacmanToLineStart is True and len(self.agentImages) > 0:
# Bring pacman to front of display
graphicsUtils._canvas.tag_raise(self.agentImages[0][1][0])
# Put pacman at beginning of line
if w >= 0:
self.movePacman((x[0] - 0.5, y[0]), Directions.EAST,
self.agentImages[0][1])
else:
self.movePacman((x[-1] + 0.5, y[-1]), Directions.WEST,
self.agentImages[0][1])
graphicsUtils.refresh()
graphicsUtils.sleep(1)
def setWeights(self, weights):
"""
Plot the logistic regression line for given weights
This will draw on the existing pacman window with the existing points
weights: array or list of 2 values (or if just one value, the bias weight is assumed to be zero). If None,
no line is drawn. Default: None
"""
weights = np.array(weights)
if weights.size >= 2:
w = weights[0]
b = weights[1]
else:
w = float(weights)
b = 0
xmin = 1 - self.xShift
xmax = self.width-2 - self.xShift
x = np.linspace(xmin, xmax,30)
y = 1.0/(1+np.exp(-(w*x+b)))
x += self.xShift
y += self.yShift
if self.line is not None:
for obj in self.line:
graphicsUtils.remove_from_screen(obj)
self.line = []
prevPoint = self.to_screen((x[0],y[0]))
for i in xrange(1,len(x)):
point = self.to_screen((x[i],y[i]))
self.line.append(graphicsUtils.line(prevPoint, point, LINE_COLOR))
prevPoint = point
# prevPoint = self.to_screen((x[0],y[0]))
# for i in xrange(1,len(x)):
# point = self.to_screen((x[i],y[i]))
# line.append(graphicsUtils.line(prevPoint, point, LINE_COLOR, filled=0, behind=0)
#
# prevPoint = point
if self.addPacmanToLineStart is True and len(self.agentImages) > 0:
# Bring pacman to front of display
graphicsUtils._canvas.tag_raise(self.agentImages[0][1][0])
# Put pacman at beginning of line
if w >= 0:
self.movePacman((x[0]-0.5,y[0]), Directions.EAST, self.agentImages[0][1])
else:
self.movePacman((x[-1]+0.5,y[-1]), Directions.WEST, self.agentImages[0][1])
graphicsUtils.refresh()
def setWeights(self, weights):
"""
Plot the linear regression line for given weights; assuming h_w(x) = weights[0]*x + weights[1].
This will draw on the existing pacman window with the existing points
weights: array or list of 2 values (or if just one value, the bias weight is assumed to be zero). If None,
no line is drawn. Default: None
"""
weights = np.array(weights)
if weights.size >= 2:
w = weights[0]
b = weights[1]
else:
w = float(weights)
b = 0
# xmin = min(x)
# xmax = max(x)
#
# ymin = w*xmin + b
# ymax = w*xmax + b
#
# point1 = (xmin+self.xShift, ymin+self.yShift)
# point2 = (xmax+self.xShift, ymax+self.yShift)
(point1, point2) = plotUtil.lineBoxIntersection(w, -1, b,
1-self.xShift, 1-self.yShift,
self.width-2-self.xShift, self.height-2-self.yShift)
if point1 is not None and point2 is not None:
point1 = (point1[0]+self.xShift, point1[1]+self.yShift)
point2 = (point2[0]+self.xShift, point2[1]+self.yShift)
dx = point2[0]-point1[0]
dy = point2[1]-point1[1]
if dx == 0:
angle = 90 + 180*dy*1.0/abs(dy)
else:
angle = math.atan(dy*1.0/dx)*180.0/math.pi
if self.line is not None:
graphicsUtils.remove_from_screen(self.line)
self.line = graphicsUtils.polygon([self.to_screen(point1), self.to_screen(point2)], LINE_COLOR, filled=0, behind=0)
if self.addPacmanToLineStart is True and len(self.agentImages) > 0:
# Bring pacman to front of display
graphicsUtils._canvas.tag_raise(self.agentImages[0][1][0])
# Put pacman at beginning of line
self.movePacman(point1, angle, self.agentImages[0][1])
graphicsUtils.refresh()
def setWeights(self, weights):
"""
Plot the logistic regression line for given weights
This will draw on the existing pacman window with the existing points
weights: array or list of 2 values (or if just one value, the bias weight is assumed to be zero). If None,
no line is drawn. Default: None
"""
weights = np.array(weights)
if self.prev_weights is not None:
if np.allclose(self.prev_weights, weights):
return False # no line update
self.prev_weights = weights.copy()
w1 = weights[0]
w2 = weights[1]
if weights.size >= 3:
b = weights[2]
else:
b = 0
# Line functions
# Line where w1*x1 + w2*x2 + b = 0
# x2 = -(w1*x1 + b)/w2 or
# x1 = -(w2*x2 + b)/w1
# Figure out where line intersections bounding box around points
if w1 == 0 and w2 == 0:
return
(point1, point2) = plotUtil.lineBoxIntersection(
w1, w2, b, 1 - self.xShift, 1 - self.yShift,
self.width - 2 - self.xShift, self.height - 2 - self.yShift)
if point1 is not None and point2 is not None:
point1 = (point1[0] + self.xShift, point1[1] + self.yShift)
point2 = (point2[0] + self.xShift, point2[1] + self.yShift)
if self.line is not None:
graphicsUtils.remove_from_screen(self.line)
self.line = graphicsUtils.polygon(
[self.to_screen(point1),
self.to_screen(point2)],
LINE_COLOR,
filled=0,
behind=0)
graphicsUtils.refresh()
return True # updated line
def swapImages(self, agentIndex, newState):
"""
Changes an image from a ghost to a pacman or vis versa (for capture)
"""
prevState, prevImage = self.agentImages[agentIndex]
for item in prevImage:
gU.remove_from_screen(item)
if newState.isPacman:
image = self.drawPacman(newState, agentIndex)
self.agentImages[agentIndex] = (newState, image)
else:
image = self.drawGhost(newState, agentIndex)
self.agentImages[agentIndex] = (newState, image)
gU.refresh()
def setWeights(self, weights):
"""
Plot the logistic regression line for given weights
This will draw on the existing pacman window with the existing points
weights: array or list of 2 values (or if just one value, the bias weight is assumed to be zero). If None,
no line is drawn. Default: None
"""
weights = np.array(weights)
if self.prev_weights is not None:
if np.allclose(self.prev_weights, weights):
return False # no line update
self.prev_weights = weights.copy()
w1 = weights[0]
w2 = weights[1]
if weights.size >= 3:
b = weights[2]
else:
b = 0
# Line functions
# Line where w1*x1 + w2*x2 + b = 0
# x2 = -(w1*x1 + b)/w2 or
# x1 = -(w2*x2 + b)/w1
# Figure out where line intersections bounding box around points
if w1 == 0 and w2 == 0:
return
(point1, point2) = plotUtil.lineBoxIntersection(w1, w2, b,
1-self.xShift, 1-self.yShift,
self.width-2-self.xShift, self.height-2-self.yShift)
if point1 is not None and point2 is not None:
point1 = (point1[0]+self.xShift, point1[1]+self.yShift)
point2 = (point2[0]+self.xShift, point2[1]+self.yShift)
if self.line is not None:
graphicsUtils.remove_from_screen(self.line)
self.line = graphicsUtils.polygon([self.to_screen(point1), self.to_screen(point2)], LINE_COLOR, filled=0, behind=0)
graphicsUtils.refresh()
return True # updated line
def clearExpandedCells(self):
if 'expandedCells' in dir(self) and len(self.expandedCells) > 0:
for cell in self.expandedCells:
gU.remove_from_screen(cell)
def removeCapsule(self, cell, capsuleImages):
x, y = cell
gU.remove_from_screen(capsuleImages[(x, y)])
def removeFood(self, cell, foodImages):
x, y = cell
gU.remove_from_screen(foodImages[x][y])
def _remove(obj):
parts = Display.partDict[obj]
graphicsUtils.remove_from_screen(parts);
