def shortestDistanceFromWall(self, point):
'''returns the shortest distance of the point to
a maze wall in degrees'''
from psychopy.event import xydist
point-=self.pos
X=Maze.I; Y = Maze.J
(gx,gy)=self.dispSize/2.0
arena=(((-gx,-gy),(gx,-gy)), ((gx,-gy),(gx,gy)),
((-gx,gy),(gx,gy)),((-gx,gy),(-gx,-gy)))
# check outside walls
dists=(abs(point[Y]+gy), abs(-point[X]+gx),
abs(-point[Y]+gy),abs(point[X]+gx))
shd = min(dists)
edge=arena[dists.index(shd)]
# check the lines
for line in self.lineXY:
dim=int(line[1][X]==line[0][X])
# 1 is vertical
mx=int(line[0][dim]<line[1][dim])
mn=1-mx
if point[dim]>line[mx][dim]:
d=xydist(point,line[mx])
ol=line[mx]
elif point[dim]<line[mn][dim]:
d=xydist(point,line[mn])
ol=line[mn]
else:
d=abs(point[1-dim]-line[0][1-dim])
ol=line
if d<shd:
shd=d; edge=ol
#print shd,point, edge
return shd-self.lw/2.0, edge
def circleLine(p0,lin1,lin2,r):
""" compute circle line intersetion
p0 - circle center
lin1, lin2 - line edges
r - circle radius
"""
# translate first
p2=lin2-p0; p1=lin1-p0
dpos=p2-p1
dr=dpos[X]**2+dpos[Y]**2
det=p1[X]*p2[Y]-p1[Y]*p2[X]
discriminant= dr*r**2-det**2
if discriminant<0:
raise NameError('No intersection')
temp1=(2*bool(dpos[Y]>=0)-1)*dpos[X]*discriminant**0.5
temp2=abs(dpos[Y])*discriminant**0.5
inter=(((det*dpos[Y]+temp1)/dr,
(-det*dpos[X]+temp2)/dr),
((det*dpos[Y]-temp1)/dr,
(-det*dpos[X]-temp2)/dr))
# output point which is nearer to p1
i= (xydist(p1,inter[0])+xydist(p2,inter[0]) >
xydist(p1,inter[1])+xydist(p2,inter[1]))
# check whether inter lies between line edges
cw=xydist(p1,p2)
if xydist(p1,inter[i])>=cw or xydist(p2,inter[i])>=cw:
raise NameError('Intersection out of bounds')
return np.array(inter[i])+p0
def getJudgment(self,giveFeedback=False):
'''asks subject to select chaser chasee'''
position=np.transpose(self.pos)
cond=position.shape[1]
self.mouse.clickReset();self.mouse.setVisible(1)
elem=self.elem
t0=core.getTime();selected=[]
mkey=self.mouse.getPressed()
lastPress=t0
while sum(mkey)>0:
elem.draw()
self.wind.flip()
mkey=self.mouse.getPressed()
released=True
clrs=np.ones((cond,1))*Q.agentCLR
while len(selected) <2:
elem.draw()
self.wind.flip()
mpos=self.mouse.getPos()
mkey=self.mouse.getPressed()
mtime=core.getTime()
for a in range(cond):
if (event.xydist(mpos,np.squeeze(position[:,a]))
< Q.agentRadius*self.scale):
if 0<sum(mkey) and released: # button pressed
if selected.count(a)==0: # avoid selecting twice
clrs[a]=Q.selectedCLR
elem.setColors(clrs,'rgb')
selected.append(a)
self.output.write('\t%d\t%2.4f' % (a,mtime-t0))
released=False
elif a in selected: # no button pressed but selected already
clrs[a]=Q.selectedCLR
elem.setColors(clrs,'rgb')
else: # no button pressed but mouse cursor over agent
clrs[a]=Q.mouseoverCLR
elem.setColors(clrs,'rgb')
elif a in selected: # no button pressed, no cursor over agent, but already selected
clrs[a]=Q.selectedCLR
elem.setColors(clrs,'rgb')
else: # no button press, no cursor over agent, not selected
clrs[a]=Q.agentCLR
elem.setColors(clrs,'rgb')
if 0==sum(mkey) and not released:
released=True
t0=core.getTime()
while core.getTime()-t0<1:
elem.draw()
self.wind.flip()
self.mouse.setVisible(0)
if (selected[0]==0 and selected[1]==1
or selected[0]==1 and selected[1]==0):
return 1
else: return 0
def draw(self, debug_mode=False):
mouse_x, mouse_y = self.mouse.getPos()
for text_stim in self.contrib_choices:
if xydist((mouse_x, mouse_y), text_stim.pos) < self.mouseover_threshold:
text_stim.color = 'darkorange'
if self.mouse.getPressed()[0]:
self.contrib_choice = text_stim.text
self.contrib_instructions.setText(self.instr_text_preformat.format(self.contrib_choice))
self.continue_button.clickable = True
else:
text_stim.color = 'white'
text_stim.draw()
self.continue_button.draw()
self.contrib_instructions.draw()
if self.gaze_pos_getter is not None:
self.gaze.pos = self.coords(self.gaze_pos_getter())
self.gaze.draw()
def test_xydist(self):
assert event.xydist([0,0], [1,1]) == np.sqrt(2)
def test_misc(self):
assert event.xydist([0, 0], [1, 1]) == sqrt(2)
def test_misc(self):
assert event.xydist([0,0], [1,1]) == sqrt(2)
def generateTrial(nragents,maze,rejectionDistance=0.0,STATISTICS=False):
''' generates the agent trajectories for a single trial
the generation may take considerably longer when rejectionDistance>0
nragents - number of agents to generate
maze - Maze class instance (see Maze.py)
rejectionDistance - chaser-chasee minimum distance in degrees
STATISTICS - if True will log stats for the Diagnosis class
returns ndarray of size (nrframes x nragents x 3)
first dim - number of frames is derived based on trial duration
and frame rate (both in Settings.py)
second dim - the first agents is chasee,
the second agents is chaser,
the rest are distractors
third dim - X position in degrees, Y position in degrees,
direction in radians
if STATISTICS is True returns statistics
'''
if STATISTICS: nrbacktracks=0
# init chaser chasee
chasee=RandomAgent(Q.nrframes,maze.dispSize,maze.pos,
Q.pDirChange[CHASEE],Q.aSpeed,Q.phiRange[0])
chaser=HeatSeekingChaser(Q.nrframes,maze.dispSize,maze.pos,
Q.pDirChange[CHASER],Q.aSpeed,Q.phiRange[CHASER],True)
while (xydist(chaser.getPosition(),chasee.getPosition())<Q.initDistCC[MIN]
and xydist(chaser.getPosition(),chasee.getPosition())>Q.initDistCC[MAX]):
# resample until valid distance between chaser and chasee is obtained
chasee.reset(); chaser.reset()
agents=[chasee,chaser]
# init distractors
for d in range(nragents-2):
distractor=RandomAgent(Q.nrframes,maze.dispSize,maze.pos,
Q.pDirChange[DISTRACTOR],Q.aSpeed,Q.phiRange[CHASEE])
agents.append(distractor)
# check for wall collisions
for a in range(nragents):
d,edge=maze.shortestDistanceFromWall(agents[a].getPosition())
while d<=Q.agentRadius:
agents[a].reset()
d,edge=maze.shortestDistanceFromWall(agents[a].getPosition())
# generate the movement of chasee and chaser
finished=False
while not finished:
# check the distance
(dx,dy)=chasee.getPosition() - chaser.getPosition()
if np.sqrt(dx**2+dy**2)<rejectionDistance:
if STATISTICS: nrbacktracks+=1
deadend=chaser.backtrack()
chasee.backtrack()
if deadend: # reset the algorithm
print 'dead end', chasee.f
if STATISTICS: return None, None, None, None,None
else: return None
(dx,dy)=chasee.getPosition() - chaser.getPosition()
# move chaser and avoid walls
chaser.move((dx,dy))
d,edge=maze.shortestDistanceFromWall(chaser.getPosition())
if d<=Q.agentRadius:
newD=maze.bounceOff(chaser.getPosition(),
chaser.getPosition(-1),edge,Q.agentRadius)
chaser.crashed(newD=newD,targetPos=(dx,dy))
# move chasee and avoid walls
finished=chasee.move()
d,edge=maze.shortestDistanceFromWall(chasee.getPosition())
if d<=Q.agentRadius:
newD=maze.bounceOff(chasee.getPosition(),
chasee.getPosition(-1),edge,Q.agentRadius)
chasee.crashed(newD)
#if chaser.f>401:
# raise NameError('stop')
# generate distractor movement
finished=False
while not finished and nragents>2:
for a in range(2,nragents):
finished=agents[a].move()
d,edge=maze.shortestDistanceFromWall(agents[a].getPosition())
if d<=Q.agentRadius:
newD=maze.bounceOff(agents[a].getPosition(),
agents[a].getPosition(-1),edge,Q.agentRadius)
agents[a].crashed(newD)
trajectories=np.zeros((Q.nrframes,nragents,3))
for a in range(nragents):
tt=agents[a].getTrajectory()
trajectories[:,a,X]=tt[:,X]
trajectories[:,a,Y]=tt[:,Y]
trajectories[:,a,PHI]=tt[:,PHI]
if STATISTICS:
#statistics=np.zeros((nrframes,nragents,3))
statistics=[trajectories,np.zeros((Q.nrframes,3)),
np.zeros((3)),nrbacktracks,[chasee.ndc.sum(),chaser.ndc.sum(),agents[2].ndc.sum()]]
for a in range(3):
statistics[1][:,a]=agents[a].getTrajectory()[:,PHI]
statistics[2][a]=agents[a].nrcrashes.sum()
return statistics
else: return trajectories
def inStim(pointer, target):
pos1 = pointer.getPos()
pos2 = target.pos
return (event.xydist(pos1, pos2) < 0.05)
