def build_biome(self):
global grid, pixel_grid, GRID_SIZE
plt.figure()
DIRECTION = [[-1, 1], [0, 1]] # value to add up # axis to change
pos_x = rndm(0, GRID_SIZE - 1)
pos_y = rndm(0, GRID_SIZE - 1)
pos = [pos_x, pos_y]
desired_area = rndm(self.min_area, self.max_area)
grid[pos_x][pos_y] = self.color
pixel_ = Pixel(self.name, self.deep_ocean_range, self.color, pos)
pixel_grid[pos_x][pos_y] = pixel_
x_map = []
y_map = []
while self.curr_area < desired_area:
random_dir = [DIRECTION[0][rndm(0, 1)], DIRECTION[1][rndm(0, 1)]]
pos[random_dir[1]] += random_dir[0]
if not (0 <= pos[0] < GRID_SIZE and 0 <= pos[1] < GRID_SIZE):
pos[random_dir[1]] -= random_dir[0]
continue
if not checker[pos[0]][pos[1]]:
grid[pos[0]][pos[1]] = self.color
pixel_ = Pixel(self.name, self.deep_ocean_range, self.color,
[pos[0], pos[1]])
pixel_grid[pos[0]][
pos[1]] = pixel_ ## NOT ADDING TO THE GRID!!
checker[pos[0]][pos[1]] = True
x_map.append(pos[0])
y_map.append(pos[1])
self.curr_area += 1
plt.clf()
plt.xlim(0, GRID_SIZE)
plt.ylim(0, GRID_SIZE)
plt.plot(x_map, y_map, "bs")
plt.tight_layout()
plt.draw()
plt.pause(0.00001)
# generate
with open(fname, "w") as fout:
# loop on events
i = 0
while i < NEVENTS:
header = [99] * 10
header[0] = len(PDGs) + 1 # daughters + mother
header[4] = BeamPolarization
# array to store all the particles in the event
counter = 1
parts = []
# generate mother
P = PMin + rndm() * (PMax - PMin)
Phi = PhiMin + rndm() * (PhiMax - PhiMin)
Theta = ThetaMin + rndm() * (ThetaMax - ThetaMin)
vm = TLorentzVector(P * math.sin(Theta) * math.cos(Phi),
P * math.sin(Theta) * math.sin(Phi),
P * math.cos(Theta),
math.sqrt(P * P + MotherMass * MotherMass))
r = abs(gauss(0., VR))
f = rndm() * 2 * math.pi
vertex = (Vx + r * math.cos(f), Vy + r * math.sin(f),
VzMin + rndm() * (VzMax - VzMin))
parts.append(storeParticle(PDGmother, vm, vertex, 0))
def getobstacles(self):
n = self.xmax * self.ymax // 4
return [(rndm(0, self.xmax - 1), rndm(0, self.ymax - 1))
for i in range(n)]
BeamPolarization = -1 # not useful
with open(ofilename, "w") as fout:
# loop on events
for i in range(1, NEVENTS + 1):
vertex = (0.0, 0.0, 0.0)
counter = 0
parts = []
pelectron = TVector3()
pelectron.SetMagThetaPhi(5, math.radians(15), math.radians(180))
phi = 180 * rndm()
pgammaC = TVector3()
pgammaC.SetMagThetaPhi(Eg, math.radians(15), math.radians(0))
vnorm = pgammaC.Orthogonal()
pgamma1 = TVector3()
pgamma1.SetMagThetaPhi(Eg, math.radians(15), math.radians(0))
pgamma1.Rotate(math.radians(Phi / 2.), vnorm)
pgamma1.Rotate(math.radians(phi), pgammaC)
pgamma2 = TVector3()
pgamma2.SetMagThetaPhi(Eg, math.radians(15), math.radians(0))
pgamma2.Rotate(math.radians(Phi / 2.), vnorm)
pgamma2.Rotate(math.radians(phi - 180), pgammaC)
fname = random.choice(fnames).strip()
lname = random.choice(lnames).strip()
driver.get(
"https://docs.google.com/forms/d/e/M5YKuPkrAOiStNGgokb_0aOK173lsj-1FAIpQLScicob_MvnDQ7p-asw/viewform?vc=0&c=0&w=1"
)
elem = driver.find_element_by_xpath(
"//input[@aria-label='Your Full Name ']")
elem.clear()
elem.send_keys(fname + ' ' + lname)
elem = driver.find_element_by_xpath(
"//input[@aria-label='Your Contact Number']")
elem.clear()
elem.send_keys(random.choice(numbers).strip())
elem = driver.find_element_by_xpath("//input[@aria-label='Your Email ID']")
elem.clear()
elem.send_keys((fname + lname).lower() + str(rndm())[2:5] + '@gmail.com')
picker = '//div[@aria-posinset="' + str(int(str(rndm())[2:3]) % 3 +
1) + '"]'
driver.find_element_by_xpath(picker).click()
elem = driver.find_element_by_xpath(
"//input[@aria-label='College Name and City']")
elem.clear()
elem.send_keys(random.choice(colleges).strip())
elem = driver.find_element_by_xpath(
"//input[@aria-label='Current Location']")
elem.clear()
elem.send_keys(random.choice(locations).strip())
driver.find_element_by_xpath("//div[@aria-label='Full -Time']").click()
driver.find_element_by_xpath(
"//span[@class='appsMaterialWizButtonPaperbuttonLabel quantumWizButtonPaperbuttonLabel exportLabel']"
).click()
numbers = []
with open('C:\\Users\\Rajdeep\\Desktop\\firstnames.txt') as f:
for item in f:
fnames.append(item)
with open('C:\\Users\\Rajdeep\\Desktop\\lastnames2.txt') as f:
for item in f:
lnames.append(item)
with open('C:\\Users\\Rajdeep\\Desktop\\colleges.txt') as f:
for item in f:
colleges.append(item)
with open('C:\\Users\\Rajdeep\\Desktop\\locations.txt') as f:
for item in f:
locations.append(item)
with open('C:\\Users\\Rajdeep\\Desktop\\numbers.txt') as f:
for item in f:
numbers.append(item)
for i in range(3):
fname = random.choice(fnames).strip()[:-1]
lname = random.choice(lnames).strip()
print((fname + ' ' + lname) + ' studies at ' + random.choice(colleges).strip() + ' is from ' + random.choice(locations).strip() + ' can be called at ' + random.choice(numbers).strip() + ' and can be reached at ' + (fname + lname).lower() + str(rndm())[2:5] + '@gmail.com')
print()
for i in range(50):
print(int(str(rndm())[2:3]) % 3 + 1)
from random import normalvariate as rndm
# read in ctrl data,(size: NSTATES x 1),add noise to get pertrurbed values
# inputs: path to ctrl data,
# output: s0file.dat = control data (ctrl_file) + random noise, N(0, sigma_pert^2) (in the same folder as script is executed)
# inputs:
ctrl_file = sys.argv[1] # file that contains true data
sigma_pert = sys.argv[2] # sigma of perturbation noise
# convert to float
sigma_pert = float(sigma_pert)
# load true data
ctrl_data = np.loadtxt(ctrl_file)
# define K = no. of states
K = np.size(ctrl_data)
# define an_data vector Kx1
pert_data = np.zeros(K)
# pert_data = ctrl_data + noise (random number)
for i in range(K):
pert_data[i] = ctrl_data[i] + rndm(0, sigma_pert)
# save output to file
np.savetxt('s0file.dat', pert_data, fmt='%.10f')
# END OF FILE
##########
BeamPolarization = -1 # not useful
with open( ofilename ,"w") as fout:
# loop on events
for i in range(1,NEVENTS+1):
header = [99]*10
header[0] = len(PDGs)
header[4] = BeamPolarization
for h in header:
fout.write(str(h))
fout.write(" ")
fout.write("\n")
r = -VR + 2*VR*rndm()
#r = abs( gauss( 0., VR ) )
f = rndm()*2*math.pi
vx= Vx + r
vy= Vy
vz= VzMin + rndm()*(VzMax - VzMin)
for j,p in enumerate(PDGs):
particle = [99]*14
particle[0] = j + 1;
particle[2] = 1
particle[3] = p
P = PMin + rndm()*(PMax - PMin)
Phi = PhiMin + rndm()*(PhiMax - PhiMin)
Theta = ThetaMin + rndm()*(ThetaMax - ThetaMin)
# generate
with open(fname, "w") as fout:
# generate event
Event = TGenPhaseSpace()
Event.SetDecay(CME, len(FSMasses), array('d', FSMasses))
# loop on events
for i in range(1, NEVENTS + 1):
# generate event
counter = 1
w = Event.Generate()
# generate vertex
vertex = (VxMin + rndm() * (VxMax - VxMin),
VyMin + rndm() * (VyMax - VyMin),
VzMin + rndm() * (VzMax - VzMin))
# write header
header = [99] * 10
header[0] = len(FSPDGs) + len(PDGs) + len(
gPDGs) # daughters + mother + electron + proton
header[4] = BeamPolarization
header[6] = w
# array to store all the particles in the event
parts = []
# the reaction
for l, j in enumerate(FSPDGs):
# read in true data at time index t_index, add noise to get initial value for model
# inputs: path to true data, time index, sigma_an
# output: s0file.dat = "analysed data" = truth + noise, noise ~ N(0,sigma_an^2) (output in the same folder as script is executed)
# inputs:
truth_file = sys.argv[1] # file that contains true data
t_index = sys.argv[2] # index for time t
sigma_an = sys.argv[3] # sigma for analysis
# convert t_index to integer
t_index = int(t_index)
# convert sigma_an to float
sigma_an = float(sigma_an)
# load true data
truth_data = np.loadtxt(truth_file)
# define K = no. of states
K = np.size(truth_data[t_index, :])
# define an_data vector
an_data = np.zeros(K)
# an_data = truth_data[t_index, :] + noise (random number)
for i in range(K):
an_data[i] = truth_data[t_index, i] + rndm(0,sigma_an)
# save output to file
np.savetxt('s0file.dat', an_data, fmt='%.10f')
# END OF FILE
