aquakin.MonteCarloResult#
- class aquakin.MonteCarloResult(input_names, output_names, samples, outputs, n_drawn, n_valid, sampler, seed)[source]#
Bases:
objectResult of
monte_carlo(): the sampled input/output ensemble.- Variables:
output_names (input_names,) – Names of the inputs (columns of
samples) and outputs (columns ofoutputs).samples (np.ndarray) –
(n_valid, d)sampled input vectors (in physical space) with a finite output.outputs (np.ndarray) –
(n_valid, m)model outputs.n_valid (n_drawn,) – Points drawn / kept (a non-finite output – a failed/clipped solve – is dropped).
seed (sampler,) – Sampler used and its seed (fixing it makes the result reproducible).
- Parameters:
input_names (list[str])
output_names (list[str])
samples (ndarray)
outputs (ndarray)
n_drawn (int)
n_valid (int)
sampler (str)
seed (int)
- __init__(input_names, output_names, samples, outputs, n_drawn, n_valid, sampler, seed)#
- Parameters:
input_names (list[str])
output_names (list[str])
samples (ndarray)
outputs (ndarray)
n_drawn (int)
n_valid (int)
sampler (str)
seed (int)
- Return type:
None
Methods
__init__(input_names, output_names, samples, ...)mean()Per-output mean, shape
(m,).output_named(name)The
(n_valid,)ensemble of one output by name.percentiles([q])Per-output percentiles, shape
(len(q), m).std()Per-output standard deviation, shape
(m,).summary([q])A human-readable table of mean / std / percentiles per output.
Attributes
input_namesoutput_namessamplesoutputsn_drawnn_validsamplerseed- output_named(name)[source]#
The
(n_valid,)ensemble of one output by name.- Parameters:
name (str)
- Return type:
ndarray