<jupyter_start><jupyter_text><jupyter_code>import numpy as np
n = 1000 # Number of particles on the main circle
k = 10 # Number of layers on vertical axis
Particles = numpy.ones((k, n)) # 

for i in range(0, k):
  for j in range(0,n):
    if (j > n/2): Particles[i,j] = 0

WaitTime = numpy.zeros((n,2)) # 
t = 0 # global time

for i in range(0, n):
    WaitTime[i] = np.sort(numpy.random.exponential(1.), numpy.random.exponential(1.))
def whichParticle():
    lowestTimeIndex = np.argmin(WaitTime[:][0]) # which particle moves first
    dt = WaitTime[lowestTimeIndex]
    t += dt # Global time step
    for i in xrange(0,n):
        WaitTime[i] -= [dt, dt] # Local wait time step
    WaitTime[lowestTimeIndex][0] = numpy.random.exponential(1.) # New exponential clock for particle that jumps
    return lowestTimeIndex
def jump(jumpIndex, jumpLayer):<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1318181818181818, 'fraction_numerical': 0.02159090909090909, 'mean_word_length': 4.005681818181818, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 6, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '372925', 'license': 'MIT', 'n_tokens_mistral': 319, 'n_tokens_neox': 307, 'n_words': 92, 'path': 'TasepCylinder.ipynb', 'repo_name': 'EzAccount/TASEPsimulation', 'size': '880'}