def calculate_msd():
parameterFile = "parameters.json"
parser = argparse.ArgumentParser()
parser.add_argument("-d",
"--directory",
type=str,
default="./",
help="input directory")
#parser.add_argument("-o", "--output", type=str, help="output directory")
#parser.add_argument("-p", "--prefix", type=str, default="cornea",help="prefix for output file")
parser.add_argument("-s",
"--skip",
type=int,
default=1100,
help="skip this many samples")
parser.add_argument("-m",
"--howmany",
type=int,
default=30,
help="read this many samples")
parser.add_argument("-t",
"--step",
type=int,
default=4,
help="step snapshots with this spacing in flow field")
parser.add_argument("-a",
"--average",
type=int,
default=5,
help="average over these many samples in flow field")
args = parser.parse_args()
param = read_param_CAPMD.Param(
p.paramsFromFile(capmd.Parameters(), parameterFile))
sheet = Dynamics(initype="fromCSV",
param=param,
datapath='output/',
multiopt="many")
skip = 0
step = 1
howmany = 500
sheet.readDataMany("CAPMD", skip, step, howmany, False, readtypes=[1])
sheet.validate_initialise()
sheet.getMSD(False)
plt.show()
return 0
parser.add_argument("-c", "--conffile", type=str, default="plane_periodic.conf", help="configuration file")
parser.add_argument("-d", "--directory", type=str, default="/home/sh18581/Documents/Dome/samos_check/periodic_test/data_phi_1/data_v0_0.01/data_nu_0.01/",help="input directory")
parser.add_argument("-s", "--skip", type=int, default=300, help="skip this many samples")
parser.add_argument("-m", "--howmany", type=int, default=500, help="read this many samples")
parser.add_argument("-t", "--step", type=int, default=20, help="step snapshots with this spacing")
parser.add_argument("-o", "--outfile", type=str, default="correlations.p", help="pickle file name")
args = parser.parse_args()
# Choose to show as plots as well:
plotall = True
# Use the Configuration constructor in its readCSV format to generate the topology
# fromCSV(kwargs["parampath"],kwargs["datapath"],kwargs["multiopt"])
parampath0 = args.directory + args.conffile
param = Param(parampath0)
Cells = Dynamics(initype="fromCSV",param=param,datapath=args.directory,multiopt="many")
# Now read in as desired
# def readDataMany(self,skip=0,step=1,howmany='all',Nvariable=False,readtypes = 'all'):
Cells.readDataMany("SAMoS",args.skip,1,args.howmany,False,readtypes = 'all')
Cells.validate_initialise()
# Start collecting all of this in data dictionary
data={'configuration':args.directory,'skip':args.skip,'howmany':args.howmany,'step':args.step}
# 1st basic set of analyses
# Will save as pickle file regardless
# A - Velocity distributions and mean velocity
# vav, vdist,vdist2 = getVelDist(self,bins,bins2,usetype='all',verbose=True):
# Bins are in normalised units (by mean velocity)
def main(): ctrl = Controller() dyn = Dynamics()
class VideoStreamHandler(socketserver.StreamRequestHandler):
command = Dynamics()
identify_features = features()
print("Video Server Active")
def handle(self):
global command
global distance
global previous_distance
stream_bytes = b''
AEB = 0
try:
while True:
stream_bytes += self.rfile.read(1024)
first = stream_bytes.find(b'\xff\xd8')
last = stream_bytes.find(b'\xff\xd9')
if first != -1 and last != -1:
jpg = stream_bytes[first:last + 2]
stream_bytes = stream_bytes[last + 2:]
#read images in stream
img = cv2.imdecode(np.frombuffer(jpg, dtype=np.uint8),
cv2.IMREAD_COLOR)
#Perspective Transform
src = np.float32([[00, 100], [320, 100], [-10, 150],
[330, 150]])
dst = np.float32([[0, 0], [320, 0], [0, 240], [320, 240]])
M = cv2.getPerspectiveTransform(src, dst)
image = cv2.warpPerspective(img, M, (320, 240))
#Image Processing -Identify Features
img, image, stop, average_heading, sigFlag, carFlag = self.identify_features.haar(
img, image)
#Display Processed Images and views
cv2.imshow('Feild Of View', img)
cv2.imshow('Birds Eye', image) #img
#HC-SR04 distance data
a = (previous_distance + distance) / 2
b = previous_distance - distance
if distance < 25: #Object under threshold distance
AEB = 1
#Emergency Brakes Flag
else:
AEB = 0
if cv2.waitKey(3) & 0xFF == ord('q'):
break
if sigFlag == 0: # Signal is Green
#Set Lane Departure limits
if ((average_heading < 150) and
(stop == 0)) and AEB == 0:
print("Turn left")
self.command.fleft()
elif ((average_heading > 170) and
(stop == 0)) and AEB == 0:
print("Turn right")
self.command.fright()
elif ((170 >= average_heading >= 150) and
(stop == 0)) and AEB == 0:
print("In lane")
self.command.forward()
elif stop == 1:
print("BRAKES ACTIVE due to Stop sign")
self.command.brake()
elif AEB == 1:
self.command.brake()
if carFlag == 1: #If car spotted
print("Car Ahead at " + str(distance) + " cm")
else:
print(
"Obstacle Ahead!, Emergency Brakes Active")
else:
pass
elif sigFlag == 1: # Signal is Red
pass
print("Signal Red, waiting to turn Green...")
self.command.brake()
finally:
cv2.destroyAllWindows()
self.command.halt()
self.command.closeconn()
sys.exit()
