autora.theorist.bms.utils
present_results(model, model_len, desc_len)
Prints out the best equation, its description length, along with a plot of how this has progressed over the course of the search tasks
Parameters:
Name | Type | Description | Default |
---|---|---|---|
model
|
Tree
|
The equation which best describes the data |
required |
model_len
|
float
|
The equation loss (defined as description length) |
required |
desc_len
|
List[float]
|
Record of equation loss over time |
required |
Returns: Nothing
Source code in temp_dir/bms/src/autora/theorist/bms/utils.py
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|
run(pms, num_steps, thinning=100)
Parameters:
Name | Type | Description | Default |
---|---|---|---|
pms
|
Parallel
|
Parallel Machine Scientist (BMS is essentially a wrapper for pms) |
required |
num_steps
|
int
|
number of epochs / mcmc step & tree swap iterations |
required |
thinning
|
int
|
number of epochs between recording model loss to the trace |
100
|
Returns:
Name | Type | Description |
---|---|---|
model |
Tree
|
The equation which best describes the data |
model_len |
float
|
(defined as description length) loss function score |
desc_len |
List[float]
|
Record of loss function score over time |
Source code in temp_dir/bms/src/autora/theorist/bms/utils.py
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