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Help me with this code: import numpy as np import matplotlib.pyplot as plt from scipy.stats import norm # Example of a symmetric Gaussian proposal distribution
Help me with this code: import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import norm
# Example of a symmetric Gaussian proposal distribution
def gaussianproposalcurrentvalue, sigma:
return nprandom.normalcurrentvalue, sigma
def metropolisexposurelimitinitialvalue, numsamples, proposaldistribution, data:
samples initialvalue
currentvalue initialvalue
for in rangenumsamples:
candidate proposaldistributioncurrentvalue
acceptanceratio exposuretargetcandidate data exposuretargetcurrentvalue, data
acceptanceratio minacceptanceratio, # Ensure acceptance ratio is
if nprandom.uniform acceptanceratio:
currentvalue candidate
samples.appendcurrentvalue
return samples
def exposuretargetx data:
# Convert data to a NumPy array to enable broadcasting
data nparraydata
# Calculate the target distribution using the kernel density estimation formula
return npexpx datasum lendata npsqrt nppi
# Prompt the user to input the data
printEnter exposure data commaseparated values:
datainput inputsplit
data floatx for x in datainput # Convert input string to a list of floats
# Example usage
initialvalue npmeandata # Initial exposure level mean of input data
numsamples # Number of samples to generate
samples metropolisexposurelimitinitialvalue, numsamples, gaussianproposal, data
# Calculate the th percentile exposure limit
exposurelimit nppercentilesamples
# Calculate the mean and standard deviation for the Bayesian analysis
meanestimate npmeansamples
stdestimate npstdsamples
# Calculate the probability of overexposure risk using a normal distribution
riskprobability norm.cdfexposurelimit locmeanestimate, scalestdestimate
# Calculate probabilities for each risk band
percentile norm.cdf exposurelimit locmeanestimate, scalestdestimate
percentile norm.cdf exposurelimit locmeanestimate, scalestdestimate
percentile norm.cdf exposurelimit locmeanestimate, scalestdestimate
percentile norm.cdfexposurelimit locmeanestimate, scalestdestimate
overexposurerisk norm.cdfexposurelimit locmeanestimate, scalestdestimate
# Print risk analysis results
printRisk analysis based on th percentile:"
printth Percentile:", exposurelimit
printEstimated Mean:", meanestimate
printEstimated Standard Deviation:", stdestimate
printRisk Probability Risk of overexposure: :fformatriskprobability
printProbability that true th percentile of ELV:", percentile
printProbability that true th percentile is between and of ELV:", percentile
printProbability that true th percentile is between and of ELV:", percentile
printProbability that true th percentile is between and of ELV:", percentile
# Decision based on risk probability
if riskprobability :
decision "Well controlled"
else:
decision "Poorly controlled"
printAccordingly the situation is declared:", decision
# Plot probability distribution by risk band
riskbands of ELV', of ELV', of ELV', of ELV', VLE'
probabilities percentile percentile percentile percentile overexposurerisk
pltbarriskbands, probabilities, colorb
pltxlabelRisk Band'
pltylabelProbability
plttitleProbability Distribution by Risk Band'
pltaxhlineyoverexposurerisk, colorr linestyle label'Overexposure Risk'
pltlegend
pltgridTrue
pltshow
# Plot histogram of exposure samples
plthistsamples bins densityTrue, alpha colorg label'Exposure Samples'
pltaxvlinexexposurelimit colorr linestyle label'Exposure Limit
pltxlabelExposure Level'
pltylabelDensity
plttitleHistogram of Exposure Levels"
pltlegend
pltgridTrue
pltshow
I need this to stop giving errors if I change the numbers to
or
or a different assortment of numbers from
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