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MilesCranmer
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README.md
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## Running:
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You can either call the program
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or execute the program from the command line with, for example:
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```bash
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python eureqa.py --threads 8 --binary-operators plus mult pow --npop 200
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You can add more operators in `operators.jl`, or use default
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Julia ones. Make sure all operators are defined for scalar `Float32`.
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Then just
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const X = convert(Array{Float32, 2}, randn(100, 5)*2)
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# Here is the function we want to learn (x2^2 + cos(x3) - 5)
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const y = convert(Array{Float32, 1}, ((cx,)->cx^2).(X[:, 2]) + cos.(X[:, 3]) .- 5)
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```
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by either loading in a dataset, or modifying the definition of `y`.
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(The `.` are are used for vectorization of a scalar function)
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One can also adjust the relative probabilities of each operation here:
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```julia
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weights = [8, 1, 1, 1, 0.1, 0.5, 2]
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```
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## Running:
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You can either call the program by calling the `eureqa` function from `eureqa.py`,
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or execute the program from the command line with, for example:
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```bash
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python eureqa.py --threads 8 --binary-operators plus mult pow --npop 200
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You can add more operators in `operators.jl`, or use default
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Julia ones. Make sure all operators are defined for scalar `Float32`.
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Then just specify the operator names in your call, as above.
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You can also change the dataset learned on by passing in `X` and `y` as
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numpy arrays to `eureqa(...)`.
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One can also adjust the relative probabilities of each operation here,
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inside `eureqa.jl`:
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```julia
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weights = [8, 1, 1, 1, 0.1, 0.5, 2]
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```
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eureqa.py
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if test == 'simple1':
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eval_str = "X[:, 2]**2 + np.cos(X[:, 3]) - 5"
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elif test == 'simple2':
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eval_str = "X[:, 2]**3.5 + 1/abs(X[:, 0])"
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X = np.random.randn(100, 5)*3
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y = eval(eval_str)
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"--binary-operators", type=str, nargs="+", default=["plus", "mul"],
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help="Binary operators. Make sure they are defined in operators.jl")
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parser.add_argument(
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"--unary-operators", type=str, default=["exp", "sin", "cos"],
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help="Unary operators. Make sure they are defined in operators.jl")
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args = vars(parser.parse_args()) #dict
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if test == 'simple1':
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eval_str = "X[:, 2]**2 + np.cos(X[:, 3]) - 5"
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elif test == 'simple2':
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eval_str = "np.sign(X[:, 2])*np.abs(X[:, 2])**3.5 + 1/np.abs(X[:, 0])"
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X = np.random.randn(100, 5)*3
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y = eval(eval_str)
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"--binary-operators", type=str, nargs="+", default=["plus", "mul"],
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help="Binary operators. Make sure they are defined in operators.jl")
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parser.add_argument(
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"--unary-operators", type=str, nargs="+", default=["exp", "sin", "cos"],
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help="Unary operators. Make sure they are defined in operators.jl")
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args = vars(parser.parse_args()) #dict
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