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Silviu Marian Udrescu 2020-04-25 17:58:57 -04:00 • committed by GitHub
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@ -10,22 +10,22 @@ ai_feynman_example.py contains an example of running a code on some examples (fo
The main function of the code, called by the user, has the following parameters: The main function of the code, called by the user, has the following parameters:
pathdir - path to the directory containing the data file * pathdir - path to the directory containing the data file
filename - the name of the file containing the data * filename - the name of the file containing the data
BF_try_time - time limit for each brute force call (set by default to 60 seconds) * BF_try_time - time limit for each brute force call (set by default to 60 seconds)
BF_ops_file_type - file containing the symbols to be used in the brute force code (set by default to "14ops.txt") * BF_ops_file_type - file containing the symbols to be used in the brute force code (set by default to "14ops.txt")
polyfit_deg - maximum degree of the polynomial tried by the polynomial fit routine (set be default to 4) * polyfit_deg - maximum degree of the polynomial tried by the polynomial fit routine (set be default to 4)
NN_epochs - number of epochs for the training (set by default to 4000) * NN_epochs - number of epochs for the training (set by default to 4000)
vars_name - name of the variables appearing in the equation (inluding the name ofthe output variable). This should be passed as a list of strings, with the name of the variables appearing in the same order as they are in the file containing the data * vars_name - name of the variables appearing in the equation (inluding the name ofthe output variable). This should be passed as a list of strings, with the name of the variables appearing in the same order as they are in the file containing the data
test_percentage - percentage of the input data to be kept aside and used as the test set * test_percentage - percentage of the input data to be kept aside and used as the test set
The data file to be analyzed should be a text file with each column containing the numerical values of each (dependent and independent) variable. The solution file will be saved in the directory called "results" under the name solution_{filename}. The solution file will contain several rows (corresponding to each point on the Pareto frontier), each row showing: The data file to be analyzed should be a text file with each column containing the numerical values of each (dependent and independent) variable. The solution file will be saved in the directory called "results" under the name solution_{filename}. The solution file will contain several rows (corresponding to each point on the Pareto frontier), each row showing:
- the mean logarithm in based 2 of the error of the discovered equation applied to the input data (this can be though of as the average error in bits) * the mean logarithm in based 2 of the error of the discovered equation applied to the input data (this can be though of as the average error in bits)
- the cummulative logarithm in based 2 of the error of the discovered equation applied to the input data (this can be though of as the cummulative error in bits) * the cummulative logarithm in based 2 of the error of the discovered equation applied to the input data (this can be though of as the cummulative error in bits)
- the complexity of the discovered equation (in bits) * the complexity of the discovered equation (in bits)
- the error of the discovered equation applied to the input data * the error of the discovered equation applied to the input data
- the symbolic expression of the discovered equation * the symbolic expression of the discovered equation
If test_percentage is different than zero, one more number is added in the beginning of each row, showing the error of the discovered equation on the test set. If test_percentage is different than zero, one more number is added in the beginning of each row, showing the error of the discovered equation on the test set.