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Q&A Slicing a dictionary using a string variable

I am working on adding uncertainty to some of my dynamics within a larger Monte Carlo simulation. As a way to perform multiple operations on each value, I decided to make and use a new function to ...

1 answer · posted 10mo ago by megalomaniac‭ · edited 10mo ago by megalomaniac‭

Question python

#2: Post edited by

megalomaniac‭ · 2023-07-26T15:38:32Z (10 months ago)

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I am working on adding uncertainty to some of my dynamics within a larger Monte Carlo simulation. As a way to perform multiple operations on each value, I decided to make and use a new function to pull from multiple libraries.
Before, I was using something like the following to get the data from the dictionary:
aircraft = 'C172'
dynamicmodel = getattr(ModelLibrary, re.sub(r'[0-9]','',aircraft))
CL0 = dynamicmodel["SCD"]["CL0"]
Now, I am wanting to add a function to this call so that `["SCD"]["CL0"]` is the input to the function for example. However, I can't find a way to use this string to slice the dictionary for the correct value.
I have tried using something like the following for the function without success:
aircraft = 'C172'
uncertainty = 'Study1'
dynamicmodel = getattr(ModelLibrary, re.sub(r'[0-9]','',aircraft))
uncertainlibrary = getattr(modeluncertaintylibrary, uncertainty)
~~value = "["SCD"]["CL0"]"~~
def generate_val(dynamicmodel, uncertaintylibrary, value):
CL0 = dynamicmodel + value
uncertainty_CL0 = uncertaintylibrary + value
new_CL0 = np.random.uniform((1-uncertainty_CL0)*CL0, (1+uncertainty_CL0)*CL0)
return new_CL0
However, the data types do not agree and changing the data type does not help, so I am thinking there is probably some work around that I don't know about.

I am working on adding uncertainty to some of my dynamics within a larger Monte Carlo simulation. As a way to perform multiple operations on each value, I decided to make and use a new function to pull from multiple libraries.
Before, I was using something like the following to get the data from the dictionary:
aircraft = 'C172'
dynamicmodel = getattr(ModelLibrary, re.sub(r'[0-9]','',aircraft))
CL0 = dynamicmodel["SCD"]["CL0"]
Now, I am wanting to add a function to this call so that `["SCD"]["CL0"]` is the input to the function for example. However, I can't find a way to use this string to slice the dictionary for the correct value.
I have tried using something like the following for the function without success:
aircraft = 'C172'
uncertainty = 'Study1'
dynamicmodel = getattr(ModelLibrary, re.sub(r'[0-9]','',aircraft))
uncertainlibrary = getattr(modeluncertaintylibrary, uncertainty)
value = '["SCD"]["CL0"]'
def generate_val(dynamicmodel, uncertaintylibrary, value):
CL0 = dynamicmodel + value
uncertainty_CL0 = uncertaintylibrary + value
new_CL0 = np.random.uniform((1-uncertainty_CL0)*CL0, (1+uncertainty_CL0)*CL0)
return new_CL0
However, the data types do not agree and changing the data type does not help, so I am thinking there is probably some work around that I don't know about.

#1: Initial revision by

megalomaniac‭ · 2023-07-25T22:17:33Z (10 months ago)

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Slicing a dictionary using a string variable

I am working on adding uncertainty to some of my dynamics within a larger Monte Carlo simulation. As a way to perform multiple operations on each value, I decided to make and use a new function to pull from multiple libraries.

Before, I was using something like the following to get the data from the dictionary:

    aircraft = 'C172'
    dynamicmodel = getattr(ModelLibrary, re.sub(r'[0-9]','',aircraft))
    CL0 = dynamicmodel["SCD"]["CL0"]


Now, I am wanting to add a function to this call so that `["SCD"]["CL0"]` is the input to the function for example. However, I can't find a way to use this string to slice the dictionary for the correct value.

I have tried using something like the following for the function without success:

    aircraft = 'C172'
    uncertainty = 'Study1'

    dynamicmodel = getattr(ModelLibrary, re.sub(r'[0-9]','',aircraft))
    uncertainlibrary = getattr(modeluncertaintylibrary, uncertainty)

    value = "["SCD"]["CL0"]"

    def generate_val(dynamicmodel, uncertaintylibrary, value):
        CL0 = dynamicmodel + value
        uncertainty_CL0 = uncertaintylibrary + value
        new_CL0 = np.random.uniform((1-uncertainty_CL0)*CL0, (1+uncertainty_CL0)*CL0)
        return new_CL0

However, the data types do not agree and changing the data type does not help, so I am thinking there is probably some work around that I don't know about.

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