I'm trying to implement a dual task. Both task ask to judge a number. The stimuli appear shortly after one another with a variable interval (a_soa).
I need to collect the reaction times to the stimuli which are given on the keyboard (first task: y or x key; second task: , or . key). I'm currently struggeling to implement this because for the first task the program needs to start waiting for a response before the second task is even drawn. Then the second stimulus appears and marks the beginning of a possible response to the second task.
The code for both functions that I'm using and the main function are included below.
def StimPresent(a_soa, b_s1, c_s2):
"""
Function StimPresent(a, b, c) presents stimulus_1 (b) for SOA ((a) number of frames),
then it adds stimulus_2 (d) and shows both for max 60 frames
and returns time of stimulus onset (tim)
"""
if event.getKeys(keyList='escape'):
myWin.close()
core.quit()
for frameN in range(a_soa):
b_s1.draw()
fixation.draw()
if frameN == 0: # RT S1 starting immediately after flip
onsetS1 = RT1.getTime()
myWin.flip()
for frameN in range(a_soa, (a_soa+60)):
b_s1.draw()
fixation.draw()
c_s2.draw()
if frameN == (a_soa+1):
onsetS2 = RT2.getTime() #RT S2 starting immediately after soa flip
myWin.flip()
for frameN in range((a_soa+60), 300):
fixation.draw()
myWin.flip()
return [b_s1, onsetS1, c_s2, onsetS2, a_soa]
def GetRTs(onS1, onS2):
allkeys = []
event.clearEvents()
while len(allkeys)!=2:
if event.getKeys(['y']):
buttonR1 = 55
allkeys.append(buttonR1)
buttonR1Time = RT1.getTime()
theRT1 = buttonR1Time - onS1
elif event.getKeys(['x']):
buttonR1 = 44
allkeys.append(buttonR1)
buttonR1Time = RT1.getTime()
theRT1 = buttonR1Time - onS1
else:
buttonR1 = 666
allkeys.append(buttonR1)
buttonR1Time = 'NaN'
theRT1 = 'NaN'
if event.getKeys(','):
buttonR2 = 44
allkeys.append(buttonR1)
buttonR2Time = RT2.getTime()
theRT2 = buttonR2Time - onS2
elif event.getKeys('.'):
buttonR2 = 55
allkeys.append(buttonR1)
buttonR2Time = RT2.getTime()
theRT2 = buttonR2Time - onS2
else:
buttonR2 = 666
allkeys.append(buttonR1)
buttonR2Time = 'NaN'
theRT2 = 'NaN'
if RT2.getTime() - onS2 > 210:
break
elif event.getKeys(['escape']):
myWin.close()
core.quit()
return [buttonR1, buttonR1Time, buttonR2, buttonR2Time, theRT1, theRT2]
main program
for b in range(block < 2):
for thisTrial in trials:
"""
---------------------
Start des Durchgangs
---------------------
"""
RSIFix()
showChar = StimPresent(thisTrial.SOA, thisTrial.Stimulus_1, thisTrial.Stimulus_2)
s1 = showChar[0]
s1onset = showChar[1]
s2 = showChar[2]
s2onset = showChar[3]
soa = showChar[4]
responses = GetRTs(s1onset, s2onset)
Thanks for any help :)
If using the Psychopy's event module to collect responses, you need to integrate the checking for keypresses into your drawing loop. i.e. check for a keypress once for every win.flip() call, so that you are effectively checking for responses once per screen refresh (and effectively getting a very granular time resolution, typically at 16.67 ms for a 60 Hz display).
The way the event.getKeys() function works is that the timestamp is the time at which the function is called, not the time at which the key was pressed. i.e. in your current code, the key could have been pressed during the stimuli and be just sitting in a buffer waiting for you to process it. So all of your reaction times will appear to be after the stimuli have finished being shown.
Having said that, best practice now (from PsychoPy 3.1 onwards) is not to use the event module if reaction times are important. Instead, use the new Keyboard class:
https://www.psychopy.org/api/hardware/keyboard.html
This was ported from the Psychtoolbox project and has far better timing performance. And importantly, the timestamp reflects the actual time the key was pressed, regardless of when you check for responses, and doesn't have its resolution tied to the display refresh rate.
Thanks a lot, your comment helped me! I rewrote the code with the keyboard class but now I'm running into another problem: The function is only returning 666 as buttonR1Code and buttonR2Code. These should only be given if now response was collected.
How can I fix this? Any suggestions?
def StimPresent(a_soa, b_s1, c_s2):
"""
Function StimPresent(a, b, c) presents stimulus_1 (b) for SOA ((a) number of frames),
then it adds stimulus_2 (d) and shows both for max 60 frames
and returns time of stimulus onset (tim)
"""
kbR1 = keyboard.Keyboard()
kbR2 = keyboard.Keyboard()
allkeys = 0
while allkeys < 2:
if event.getKeys(keyList='escape'):
myWin.close()
core.quit()
for frameN in range(a_soa):
b_s1.draw()
fixation.draw()
if frameN == 0: # RT S1 starting immediately after flip
onsetS1 = RT1.getTime()
kbR1.clock.reset()
keyR1 = kbR1.getKeys(['y', 'x'], waitRelease=True)
if keyR1 == 'y':
buttonR1 = 55
allkeys += 1
buttonR1Iden = keyR1.name
buttonR1Dur = keyR1.duration
theRT1 = keyR1.rt
elif keyR1 == 'x':
buttonR1 = 44
allkeys += 1
buttonR1Iden = keyR1.name
buttonR1Dur = keyR1.duration
theRT1 = keyR1.rt
myWin.flip()
for frameN in range(a_soa, (a_soa+60)):
b_s1.draw()
fixation.draw()
c_s2.draw()
if frameN == (a_soa+1):
onsetS2 = RT2.getTime() #RT S2 starting immediately after soa flip
kbR2.clock.reset()
keyR1 = kbR1.getKeys(['y', 'x'], waitRelease=True)
keyR2 = kbR2.getKeys(['.', ','], waitRelease=True)
if allkeys == 0:
if keyR1 == 'y':
buttonR1 = 55
allkeys += 1
buttonR1Iden = keyR1.name
buttonR1Dur = keyR1.duration
theRT1 = keyR1.rt
elif keyR1 == 'x':
buttonR1 = 44
allkeys += 1
buttonR1Iden = keyR1.name
buttonR1Dur = keyR1.duration
theRT1 = keyR1.rt
if allkeys == 1:
if kbR2.getKeys(keyList=['.'], waitRelease=True):
buttonR2 = 55
allkeys += 1
buttonR2Iden = kbR2.name
buttonR2Dur = kbR2.duration
theRT2 = kbR2.rt
elif kbR2.getKeys(keyList=[','], waitRelease=True):
buttonR2 = 44
allkeys += 1
buttonR2Iden = kbR2.name
buttonR2Dur = kbR2.duration
theRT2 = kbR2.rt
myWin.flip()
for frameN in range((a_soa+60), 300):
fixation.draw()
deadlineS1 = 210
deadlineS2 = 210
keyR1 = kbR1.getKeys(['y', 'x'], waitRelease=True)
keyR2 = kbR2.getKeys(['.', ','], waitRelease=True)
if allkeys == 0:
if keyR1 == 'y':
buttonR1 = 55
allkeys += 1
buttonR1Iden = keyR1.name
buttonR1Dur = keyR1.duration
theRT1 = keyR1.rt
elif keyR1 == 'x':
buttonR1 = 44
allkeys += 1
buttonR1Iden = keyR1.name
buttonR1Dur = keyR1.duration
theRT1 = keyR1.rt
elif frameN > deadlineS1:
buttonR1 = 666
allkeys += 1
buttonR1Iden = 'NaN'
buttonR1Dur = 'NaN'
theRT1 = 'NaN'
if allkeys == 1:
if kbR2.getKeys(keyList=['.'], waitRelease=True):
buttonR2 = 55
allkeys += 1
buttonR2Iden = kbR2.name
buttonR2Dur = kbR2.duration
theRT2 = kbR2.rt
elif kbR2.getKeys(keyList=[','], waitRelease=True):
buttonR2 = 44
allkeys += 1
buttonR2Iden = kbR2.name
buttonR2Dur = kbR2.duration
theRT2 = kbR2.rt
elif frameN > deadlineS2:
buttonR2 = 666
allkeys += 1
buttonR2Iden = 'NaN'
buttonR2Dur = 'NaN'
theRT2 = 'NaN'
myWin.flip()
return [b_s1, onsetS1, buttonR1, buttonR1Iden, buttonR1Dur, theRT1, c_s2, onsetS2, buttonR1, buttonR1Iden, buttonR1Dur, theRT2, a_soa]
Thanks :)
Related
I begin to code the python and I am not have more experience in syntax of python
I want to send a value from the RFID reader. If it saves successfully, the PIR Motion Sensor will be disabled in a moment. and reworking within the specified time.
If the temperature is measured And send the value to the function RFID Reader to record the temperature and the PIR Motion Sensor stops working as well.
class Security:
global dbHost
global dbUser
global dbPass
global dbNameEmp
global dbNameSecure
dbHost = 'localhost'
dbUser = 'root'
dbPass = 'iTdev#2020'
dbNameEmp = 'empinfo'
dbNameSecure = 'secureinfo'
def __init__(self):
self.msg=""
def Temperature(self):
while True:
GPIO.output(TRIG, False)
time.sleep(0.5)
GPIO.output(TRIG, True)
time.sleep(0.01)
GPIO.output(TRIG, False)
while GPIO.input(ECHO) == 0 :
pulse_start = time.time()
while GPIO.input(ECHO) == 1 :
pulse_end = time.time()
pulse_duration = pulse_end - pulse_start
distance = pulse_duration * 11150
distance = round(distance,2)
if distance > 0 and distance < 3 :
buzzer.on()
time.sleep(0.1)
buzzer.off()
print ("Distance: %scm" % (distance))
#print "Ambient Temperature :", sensor.get_ambient()
print ("Temperature: %.1fc" % (sensor.get_object_1()))
msgTemp = ("%.1f" % (sensor.get_object_1()))
w, h = textsize(msgTemp, font=proportional(CP437_FONT))
if w <= device.width:
x = round((device.width - w) / 2)
with canvas(device) as draw:
text(draw, (x, 0), msgTemp, fill="white", font=proportional(CP437_FONT))
else:
show_message(device, msgTemp, fill="white", font=proportional(CP437_FONT),scroll_delay=0.04)
time.sleep(1)
device.clear()
def rfid_callback(self, state, dev):
rfid_presented = ""
keys = "X^1234567890XXXXqwertzuiopXXXXasdfghjklXXXXXyxcvbnmXXXXXXXXXXXXXXXXXXXXXXX"
while True:
r,w,x = select([dev], [], [])
for event in dev.read():
if event.type==1 and event.value==1:
if event.code==28:
rfid_presented = rfid_presented.replace("X", "")
travel = state.replace("Thread-", "")
dbConnEmp = mysql.connect(host=dbHost, user=dbUser, passwd=dbPass, db=dbNameEmp)
curEmp = dbConnEmp.cursor()
curEmp.execute("Select RFidEmp FROM RFidMaster WHERE (RFidStatus = 1) AND RFidNumber = '%s'" % (rfid_presented))
resultRFid = curEmp.fetchone()
if curEmp.rowcount != 1:
# print("Access Denied." + travel)
with canvas(device) as draw:
text(draw, (0, 0), "None", fill="white", font=proportional(CP437_FONT))
time.sleep(0.5)
device.clear()
else:
# print("Unlocking Door." + travel)
dbConnSecure = mysql.connect(host=dbHost, user=dbUser, passwd=dbPass, db=dbNameSecure)
curSecure = dbConnSecure.cursor()
curSecure.execute("SELECT EntraId,DATE_FORMAT(CreateDate, '%Y%m%d') AS CreateDate FROM entranlog ORDER BY EntraId DESC, CreateDate DESC LIMIT 1")
resultKey = curSecure.fetchone()
KeyDate = time.strftime("%Y%m%d")
if curSecure.rowcount != 1:
KeyId = KeyDate+"0001"
else:
if resultKey[1] == KeyDate:
iSum = int(resultKey[0])
def sum(x, y):
return x + y
KeyId = ('%d' % sum(iSum, 1))
else:
KeyId = KeyDate+"0001"
create_date = time.strftime('%Y-%m-%d %H:%M:%S')
insertSecure = "INSERT INTO entranlog (EntraId,EntraAction,EntraStatus,CreateBy,CreateDate) VALUES (%s,%s,%s,%s,%s)"
valSecure = (KeyId,travel,1,resultRFid[0],create_date)
curSecure.execute(insertSecure, valSecure)
dbConnSecure.commit()
# print("Welcome: " + resultRFid[0])
with canvas(device) as draw:
text(draw, (0, 0), "Hello", fill="white", font=proportional(CP437_FONT))
print(curSecure.rowcount, "record inserted.")
time.sleep(0.8)
device.clear()
rfid_presented = ""
else:
rfid_presented += keys[ event.code ]
def PirSensor(self):
while True:
led_blue.on()
time.sleep(0.1)
current_state = GPIO.input(pir_sensor)
if current_state == 1:
print("GPIO pin %s is %s" % (pir_sensor, current_state))
GPIO.output(relay_alarm,True)
led_blue.off()
led_red.blink(0.1, 0.2)
# buzzer.beep(0.5, 0.5, 3)
time.sleep(5)
GPIO.output(relay_alarm,False)
led_red.off()
led_yellow.blink(0.5, 0.5)
time.sleep(5)
led_yellow.off()
def main(self):
devIn = threading.Thread(target=self.rfid_callback, args=['1', InputDevice('/dev/input/event0')])
devIn.start()
devOut = threading.Thread(target=self.rfid_callback, args=['2', InputDevice('/dev/input/event1')])
devOut.start()
Pir = threading.Thread(target=self.PirSensor)
Pir.start()
Temp = threading.Thread(target=self.Temperature)
Temp.start()
if __name__ == "__main__":
g=Security()
g.main()
I am coding a program with Tkinter to calculate wind values. It takes Rwy Heading, Wind Direction and Wind Speed to calculate the wind whether headwind, tailwind or crosswind with the calculated relevant wind speed.
I get this error:
Traceback (most recent call last):
File "C:\Users\altug\Desktop\PROJECTS\ÇALIŞMA.py", line 40, in <module>
rwy_var= int(rwy)
ValueError: invalid literal for int() with base 10: ''
I both tried IntVar() and int(str) method to convert string into integer but it didn't sort out the problem.
Below you can find my code:
ent1 = Entry(root)
ent1.grid(row = 0, column = 1)
ent2 = Entry(root)
ent2.grid(row = 1, column = 1)
ent3 = Entry(root)
ent3.grid(row = 2, column = 1)
rwy = ent1.get()
wind_direction = ent2.get()
wind_speed = ent3.get()
rwy_var= IntVar()
wind_direction_var= IntVar()
wind_speed_var = IntVar()
rwy_var= int(rwy)
wind_direction_var= int(wind_direction)
wind_speed_var = int(wind_speed)
x = rwy_var - wind_direction_var
radx = math.radians(x)
sinx = math.sin(radx)
cosx = math.cos(radx)
def htwind():
txt.delete(0.0, "end")
b = rwy_var + 90
a = rwy_var - 90
if b > 360:
b -= 360
elif a <0:
a+= 360
if x == abs(90):
result = 0
txt.insert(0.0, result +'\n')
elif a <= wind_direction_var or wind_direction_var<= b :
sh = wind_speed_var * cosx
result = "Headwind"+ " " + round(abs(sh))+ " " + "kt"
txt.insert(0.0, result +'\n')
elif a >= wind_direction_var or wind_direction_var >= b :
st = wind_speed_var * cosx
result = "Tailwind"+ " " + round(abs(st))+ " " + "kt"
txt.insert(0.0, result +'\n')
return ""
def xwind():
txt.delete(0.0, "end")
c=rwy_var-180
d= rwy_var + 180
if d > 360:
d -= 360
elif c<0:
c+= 360
if x == 0 or x == abs(180) or y == 0 or y == abs(180):
print("0")
elif c< wind_direction_var:
sxwl = wind_speed_var * sinx
rslt = "L"+""+round(abs(sxwl))+""+"kt"
txt.insert(0.0, rslt +'\n')
elif wind_direction_var<d:
sxwr = wind_speed_var * sinx
rslt = "R"+""+round(abs(sxwr))+""+"kt"
txt.insert(0.0, rslt +'\n')
return ""
txt = Text(root, width=6, height=2, wrap =WORD)
txt.grid(row =1, column = 1)
button_1 =Button(root, text = "search", command=lambda:[htwind(),xwind()])
button_1.grid(row =0, column = 5)
What is my mistake ?
Thanks in advance.
The IntVar is special in that it can't be directly converted to an int. To get its int value, do
rwy_var = rwy.get()
i have been given a matrix space of 400,400 with few obstacles inside . I have eight set of actions namely up, down, left right with edge cost of 1 and 4 diagonals with edge cost of 1.42. i took initial node as (5,5) and final node as (195,295). I'm able to reach the goal using Dijkstra's algorithm quite quickly but am not able to backtrack and have been stuck for a long time. Can someone please help me. Here's my code
import numpy as np
import matplotlib.pyplot as plt
import time
import math
blank_list = []
for entries in range(160000):
entries = math.inf
blank_list.append(entries)
initial_matrix = np.array(blank_list, dtype = object).reshape(400, 400)
rows = initial_matrix.shape[0]
cols = initial_matrix.shape[1]
flag = False
# Obstacles
for h in range(0, rows):
for k in range(0, cols):
if (k-225)**2 + (h-50)**2 <= 625:
initial_matrix[h][k] = flag
for h in range(0, rows):
for k in range(0, cols):
if h<= 13*k -140 and h<= 185 and h<= -(7/5)*k +290 and h<= (6/5)*k +30 and h<= -(6/5)*k +210 and h<= k + 100:
initial_matrix[h][k] = flag
for h in range(0, rows):
for k in range(0, cols):
if ((k-150)**2)/1600 + ((h-100)**2)/400 <= 1:
initial_matrix[h][k] = flag
# move subfunctions
def move_right(i,j, map_):
if not map_[i,j+1]:
return None
if j == 300:
return None
else:
cost = initial_matrix[i][j] + 1
j = j + 1
return (i,j) , cost
def move_left(i,j,map_):
if not map_[i,j-1]:
return None
if j == 0:
return None
else:
cost = initial_matrix[i][j] + 1
j = j - 1
return (i,j) , cost
def move_up(i,j,map_):
if not map_[i-1,j]:
return None
if i == 0:
return None
else:
cost = initial_matrix[i][j] + 1
i = i - 1
return (i,j) , cost
def move_down(i,j,map_):
if not map_[i+1,j]:
return None
if i == 200:
return None
else:
cost = initial_matrix[i][j] + 1
i = i + 1
return (i,j) , cost
def move_upright(i,j,map_):
if not map_[i-1,j+1]:
return None
if j == 300 or i == 0:
return None
else:
cost = 1.42 + initial_matrix[i][j]
j = j + 1
i = i - 1
return (i,j) , cost
def move_downright(i,j,map_):
if not map_[i+1,j+1]:
return None
if j == 300 or i == 200:
return None
else:
cost = 1.42 + initial_matrix[i][j]
j = j + 1
i = i + 1
return (i,j) , cost
def move_upleft(i,j,map_):
if map_[i-1,j-1]:
return None
if j == 0 or i == 0:
return None
else:
cost = 1.42 + initial_matrix[i][j]
j = j - 1
i = i - 1
return (i,j) , cost
def move_downleft(i,j,map_):
if not map_[i+1,j-1]:
return None
if j == 0 or i == 200:
return None
else:
cost = 1.42 + initial_matrix[i][j]
j = j - 1
i = i + 1
return (i,j) , cost
def get_neighbours(i,j):
neighbours_cost = []
index = []
action_up = move_up(i,j,initial_matrix)
if action_up is not None:
neighbours_cost.append(action_up[1])
index.append(action_up[0])
action_down = move_down(i,j,initial_matrix)
if action_down is not None:
neighbours_cost.append(action_down[1])
index.append(action_down[0])
action_left = move_left(i,j,initial_matrix)
if action_left is not None:
neighbours_cost.append(action_left[1])
index.append(action_left[0])
action_right = move_right(i,j,initial_matrix)
if action_right is not None:
neighbours_cost.append(action_right[1])
index.append(action_right[0])
action_upright = move_upright(i,j,initial_matrix)
if action_upright is not None:
neighbours_cost.append(action_upright[1])
index.append(action_upright[0])
action_downright = move_downright(i,j,initial_matrix)
if action_downright is not None:
neighbours_cost.append(action_downright[1])
index.append(action_downright[0])
action_upleft = move_upleft(i,j,initial_matrix)
if action_upleft is not None:
neighbours_cost.append(action_upleft[1])
index.append(action_upleft[0])
action_downleft = move_downleft(i,j,initial_matrix)
if action_downleft is not None:
neighbours_cost.append(action_downleft[1])
index.append(action_downleft[0])
return neighbours_cost, index
'''def get_current_value(i,j):
current_value = initial_matrix[i][j]
return current_value'''
'''def locate_value_index(mat):
i,j = np.where(mat == node)
i = int(i)
j = int(j)
return (i,j)'''
def sort_list1(list_a,list_b):
list_b = [i[1] for i in sorted(zip(list_a, list_b))]
def sort_list2(list_a):
list_a.sort()
goal = (195,295)
ind = (5,5)
initial_matrix[ind[0]][ind[1]] = 0
node_cost = 0
explore_queue = []
index_queue = []
index_queue.append(ind)
explore_queue.append(node_cost)
visited = set()
breakwhile = False
start_time = time.clock()
while len(index_queue) != 0 and not breakwhile:
node = index_queue[0]
visited.add(node)
#for i in range(len(index_queue)):
index_queue.pop(0)
explore_queue.pop(0)
#print(visited)
#val = get_current_value(ind[0],ind[1])
pair = get_neighbours(node[0],node[1])
neighbours_cost = pair[0]
index = pair[1]
#print(index)
#print(neighbours_cost)
#######
if node == goal:
print('goal reached')
breakwhile = True
#######
for i in range(len(index)):
if index[i] not in visited:
old_cost = initial_matrix[index[i][0]][index[i][1]]
if neighbours_cost[i] < old_cost:
initial_matrix[index[i][0]][index[i][1]] = neighbours_cost[i]
if old_cost != math.inf:
ind_node = index_queue.index((index[i][0], index[i][1]))
index_queue.pop(ind_node)
explore_queue.pop(ind_node)
index_queue.append(index[i])
explore_queue.append(initial_matrix[index[i][0]][index[i][1]])
sort_list1(explore_queue,index_queue)
sort_list2(explore_queue)
end_time = time.clock()
print(end_time - start_time)
I figured out the solution. it is to create dictionary with all the index values and iterating them over a while loop
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy import linalg, optimize
%matplotlib inline
Data load
data = pd.read_csv("D:/Stat/TimeSeries/KRW_month_0617_1.csv",index_col="Date") / 100
para = open("D:/Stat/TimeSeries/KRW_month_0617_1.txt").readlines()[0:2]
data.index = pd.to_datetime(data.index)
Parameters
cond = []
params = []
time = []
for i in para:
j = i.split()
for k in j:
cond.append(k)
cond = cond[1:]
for i in range(len(cond)):
cond[i] = round(float(cond[i]),4)
params = cond[0:23]
time = cond[23:]
maturity = np.array(time[1:])
timegap = 1/cond[23]
Functions We need
def Paramcheck(Params, checkStationary = 1):
result = 0
Kappa = np.array([[params[20],0,0], [0,params[21],0], [0,0,params[22]]])
Sigma = np.array([[params[1],0,0], [params[2],params[3],0], [params[4],params[5],params[6]]])
State = np.array([params[7], params[8], params[9]])
Lambda = params[0]
SigmaEps = np.identity(10)
for i in range(10):
SigmaEps[i][i] = params[i+10]
for i in range(len(Sigma)):
if Sigma[i][i] < 0:
result = 1
for j in SigmaEps:
if np.any(SigmaEps) < 0:
result = 1
if Lambda < 0.05 or Lambda > 2:
result = 1
elif State[0] < 0:
result = 1
elif Kappa[0][0] < 0:
result = 1
if result == 0 and checkStationary > 0:
if max(np.linalg.eigvals(-Kappa).real) > 0:
result = 2
return result
def CheckDet(x):
if x == np.inf or x == np.nan:
result = 1
elif x < 0:
result = 2
elif abs(x) < 10**-250:
result = 3
else:
result = 0
return result
def NS_factor(lambda_val, maturity):
col1 = np.ones(len(maturity))
col2 = (1 - np.exp(-lambda_val*maturity))/(lambda_val*maturity)
col3 = col2 - np.exp(-lambda_val*maturity)
factor = np.array([col1,col2,col3]).transpose()
return factor
def DNS_Kalman_filter(Params, *args):
N = Paramcheck(Params)
if N == 0:
Kappa = np.array([[params[20],0,0], [0,params[21],0], [0,0,params[22]]])
Sigma = np.array([[params[1],0,0], [params[2],params[3],0],
[params[4],params[5],params[6]]])
State = np.array([params[7], params[8], params[9]])
Lambda = params[0]
SigmaEps = np.identity(10)
for i in range(10):
SigmaEps[i][i] = params[i+10]
Obs_Yield = args[0]
Obs_Date = args[1]
Timegap = args[2]
Obs_Mty = args[3]
Finalstate = args[4]
Mty_length = len(Obs_Mty)
B = NS_factor(lambda_val = Lambda,maturity = Obs_Mty)
H_large = SigmaEps **2
N_obs = len(Obs_Date)
LLH_vec = np.zeros(N_obs)
phi1 = linalg.expm(-Kappa*Timegap)
phi0 = (np.identity(3)-phi1) # State
Eigenvalues = np.linalg.eig(Kappa)[0]
Eigen_vec = np.linalg.eig(Kappa)[1]
Eigen_vec_inv = np.linalg.inv(Eigen_vec)
S = Eigen_vec_inv # Sigma # Sigma.transpose() # Eigen_vec_inv.transpose()
Atilde = np.dot(Sigma[0], Sigma[0])
Btilde = np.dot(Sigma[1], Sigma[1])
Ctilde = np.dot(Sigma[2], Sigma[2])
Dtilde = np.dot(Sigma[0], Sigma[1])
Etilde = np.dot(Sigma[0], Sigma[2])
Ftilde = np.dot(Sigma[1], Sigma[2])
res1= Atilde* Obs_Mty* Obs_Mty/6
res2= Btilde*(1/(2*Lambda**2) - (1-np.exp(-Lambda*Obs_Mty))/(Lambda**3*Obs_Mty) + (1-
np.exp(-2*Lambda*Obs_Mty))/(4*Lambda**3*Obs_Mty))
res3= Ctilde*(1/(2*Lambda**2) + np.exp(-Lambda*Obs_Mty)/(Lambda**2)-
Obs_Mty*np.exp(-2*Lambda*Obs_Mty)/(4*Lambda) -
3*np.exp(-2*Lambda*Obs_Mty)/(4*Lambda**2) - 2*(1-np.exp(-
Lambda*Obs_Mty))/(Lambda**3*Obs_Mty) + 5*(1-
np.exp(-2*Lambda*Obs_Mty))/(8*Lambda**3*Obs_Mty))
res4= Dtilde*(Obs_Mty/(2*Lambda) + np.exp(-Lambda*Obs_Mty)/(Lambda**2) - (1-np.exp(-
Lambda*Obs_Mty))/(Lambda**3*Obs_Mty))
res5= Etilde*(3*np.exp(-Lambda*Obs_Mty)/(Lambda**2) + Obs_Mty/(2*Lambda)+Obs_Mty*np.exp(-
Lambda*Obs_Mty)/(Lambda) - 3*(1-np.exp(-Lambda*Obs_Mty))/(Lambda**3*Obs_Mty))
res6= Ftilde*(1/(Lambda**2) + np.exp(-Lambda*Obs_Mty)/(Lambda**2) -
np.exp(-2*Lambda*Obs_Mty)/(2*Lambda**2) - 3*(1-np.exp(-
Lambda*Obs_Mty))/(Lambda**3*Obs_Mty) + 3*(1-
np.exp(-2*Lambda*Obs_Mty))/(4*Lambda**3*Obs_Mty))
val = res1 + res2 + res3 + res4 + res5 + res6
V_mat = np.zeros([3,3])
V_lim = np.zeros([3,3])
for i in range(3):
for j in range(3):
V_mat[i][j] = S[i][j]*(1-np.exp(-(Eigenvalues[i] +
Eigenvalues[j])*Timegap))/(Eigenvalues[i] + Eigenvalues[j])
V_lim[i][j] = S[i][j]/(Eigenvalues[i] + Eigenvalues[j])
Q = (Eigen_vec # V_mat # Eigen_vec.transpose()).real
Sigma_lim = (Eigen_vec # V_lim # Eigen_vec.transpose()).real
for i in range(N_obs):
y = Obs_Yield[i]
xhat = phi0 + phi1 # State
y_implied = B # xhat
v = y - y_implied + val
Sigmahat = phi1 # Sigma_lim # phi1.transpose() + Q
F = B # Sigmahat # B.transpose() + H_large
detF = np.linalg.det(F)
if CheckDet(detF) > 0:
N = 3
break
Finv = np.linalg.inv(F)
State = xhat + Sigmahat # B.transpose() # Finv # v
Sigma_lim = Sigmahat - Sigmahat # B.transpose() # Finv # B # Sigmahat
LLH_vec[i] = np.log(detF) + v.transpose() # Finv # v
if N == 0:
if Finalstate:
yDate = Obs_Date[-1]
result = np.array([yDate,State])
else:
result = 0.5 * (sum(LLH_vec) + Mty_length*N_obs*np.log(2*np.pi))
else:
result = 7000000
return result
I made a code that does Arbitrage Free Nelson-Siegel model. Data is return rates of bond (1Y,1.5Y, ... ,20Y). I wanna optimize that function with scipy optimize.minimize function with fixed *args.
Suppose that Initial parmas are verified that it's close to optimized params from empirical experiments using Dynamic Nelson-Siegel Model.
LLC_new = 0
while True:
LLC_old = LLC_new
OPT = optimize.minimize(x0=params,fun=DNS_Kalman_filter, args=
(data.values,data.index,timegap,maturity,0))
params = OPT.x
LLC_new = round(OPT.fun,5)
print("Current LLC: %0.5f" %LLC_new)
if LLC_old == LLC_new:
OPT_para = params
FinalState = DNS_Kalman_filter(params,data.values,data.index,timegap,maturity,True)
break
Result is
Current LLC: -7613.70146
Current LLC: -7613.70146
LLC(log-likelihood value) isn't maximized. It's not a result I desire using Optimizer.
Is there any solution for that?
In R, there is optim() function works as similar as scipy.optimize.minimize() which works really well. I also have a R code for that very similar to this Python code.
I am struggling with a very simple loop that perfectly works if run "standalone", but doesn't work anymore if I use it as an outer loop for many other instructions (which also perfectly work if run standalone for only 1 iteration).
The simple outer loop is a
for i in range(0,somevalue):
do some inner instructions
Here is the full code, which perfectly works if I put a range of dimension 1, whilst it never ends if I put even a simple range of dimension 2:
import numpy as np
import numpy.ma as ma
import random
import matplotlib.pyplot as plt
i = int
x = np.zeros(1440)
class_x = np.zeros(1440)
w1 = np.array([0,6*60])
w2 = np.array([20*60,23*60])
x[w1[0]:(w1[1])] = np.full(np.diff(w1),0.001)
x[w2[0]:(w2[1])] = np.full(np.diff(w2),0.001)
x_masked = np.zeros_like(ma.masked_not_equal(x,0.001))
c = 10
func_time = 300
max_free_spot = int
i = 0
for i in range(0,1):
tot_time = 0
switch_count = 0
switch_ons = []
while
tot_time <= func_time:
switch_on = random.choice([random.randint(w1[0],(w1[1]-c)),random.randint(w2[0],(w2[1]-c))])
if x[switch_on] == 0.001:
if switch_on in range(w1[0],w1[1]):
if np.any(x[switch_on:w1[1]]!=0.001):
next_switch = [switch_on + k[0] for k in np.where(x[switch_on:]!=0.001)]
if (next_switch[0] - switch_on) >= c and max_free_spot >= c:
upper_limit = min((next_switch[0]-switch_on),min(func_time,w1[1]-switch_on))
elif (next_switch[0] - switch_on) < c and max_free_spot >= c:
continue
else: upper_limit = next_switch[0]-switch_on
else:
upper_limit = min(func_time,w1[1]-switch_on) #max random length of cycle
if upper_limit >= c:
indexes = np.arange(switch_on,switch_on+(random.randint(c,upper_limit)))
else:
indexes = np.arange(switch_on,switch_on+upper_limit)
else:
if np.any(x[switch_on:w2[1]]!=0.001):
next_switch = [switch_on + k[0] for k in np.where(x[switch_on:]!=0.001)]
if (next_switch[0] - switch_on) >= c:
upper_limit = min((next_switch[0]-switch_on),min(func_time,w2[1]-switch_on))
elif (next_switch[0] - switch_on) < c and max_free_spot >= c:
continue
else: upper_limit = next_switch[0]-switch_on
else:
upper_limit = min(func_time,w2[1]-switch_on)
if upper_limit >= c:
indexes = np.arange(switch_on,switch_on+(random.randint(c,upper_limit)))
else:
indexes = np.arange(switch_on,switch_on+upper_limit)
tot_time = tot_time + indexes.size
switch_ons.append(switch_on)
if tot_time > func_time:
indexes_adj = indexes[:-(tot_time-func_time)]
coincidence = random.randint(1,5)
np.put(x_masked,indexes_adj,(2*coincidence),mode='clip')
np.put(x,indexes_adj,(2*coincidence))
x_masked = np.zeros_like(ma.masked_greater_equal(x_masked,0.001))
tot_time = (tot_time - indexes.size) + indexes_adj.size
switch_count = switch_count + 1
break
else:
coincidence = random.randint(1,5)
np.put(x_masked,indexes,(2*coincidence),mode='clip')
np.put(x,indexes,(2*coincidence))
x_masked = np.zeros_like(ma.masked_greater_equal(x_masked,0.001))
tot_time = tot_time
switch_count = switch_count + 1
free_spots = []
for j in ma.notmasked_contiguous(x_masked):
free_spots.append(j.stop-j.start)
max_free_spot = max(free_spots)
class_x = class_x + x
plt.plot(class_x)
Any help is really really appreciated