basic_tutorial_qcgpj.py

import os
import easyvvuq as uq
import chaospy as cp
import matplotlib.pyplot as plt

from easyvvuq.actions import QCGPJPool
from easyvvuq.actions import CreateRunDirectory, Encode, Decode, ExecuteLocal, Actions

params = {
    "F": {"type": "float", "default": 1.0},
    "L": {"type": "float", "default": 1.5},
    "a": {"type": "float", "min": 0.7, "max": 1.2, "default": 1.0},
    "D": {"type": "float", "min": 0.75, "max": 0.85, "default": 0.8},
    "d": {"type": "float", "default": 0.1},
    "E": {"type": "float", "default": 200000},
    "outfile": {"type": "string", "default": "output.json"}
}

encoder = uq.encoders.GenericEncoder(template_fname='beam.template', delimiter='$', target_filename='input.json')
decoder = uq.decoders.JSONDecoder(target_filename='output.json', output_columns=['g1'])
execute = ExecuteLocal('{}/beam input.json'.format(os.getcwd()))

actions = Actions(CreateRunDirectory('/tmp'),
                  Encode(encoder), execute, Decode(decoder))


campaign = uq.Campaign(name='beam', params=params, actions=actions)

vary = {
    "F": cp.Normal(1, 0.1),
    "L": cp.Normal(1.5, 0.01),
    "a": cp.Uniform(0.7, 1.2),
    "D": cp.Triangle(0.75, 0.8, 0.85)
}

campaign.set_sampler(uq.sampling.PCESampler(vary=vary, polynomial_order=1))

with QCGPJPool(template_params={'venv': '/home/bartek/.virtualenv/qcgpj7'}) as qcgpj:
#with QCGPJPool() as qcgpj:
    campaign.execute(pool=qcgpj).collate()

campaign.get_collation_result()

campaign.campaign_db.dump()

results = campaign.analyse(qoi_cols=['g1'])
results.plot_sobols_treemap('g1', figsize=(10, 10))
plt.axis('off')
results.sobols_first('g1')
results.supported_stats()
results._get_sobols_first('g1', 'F')
results.sobols_total('g1', 'F')

print("success")