# -*- coding: utf-8 -*-
"""
Test the InputSpace class in bayesvalidrox.
Tests are available for the following functions
Class InputSpace:
check_valid_inputs - x
init_param_space - x
build_polytypes - x
transform - x
"""
import sys
import pytest
import numpy as np
sys.path.append("src/")
sys.path.append("../src/")
from bayesvalidrox.surrogate_models.inputs import Input
from bayesvalidrox.surrogate_models.input_space import InputSpace
#%% Test ExpDesign.check_valid_input
def test_check_valid_input_hasmarg() -> None:
"""
Distribution not built if no marginals set
"""
inp = Input()
with pytest.raises(AssertionError) as excinfo:
InputSpace(inp)
assert str(excinfo.value) == 'Cannot build distributions if no marginals are given'
def test_check_valid_input_haspriors() -> None:
"""
Distribution not built if no distribution set for the marginals
"""
inp = Input()
inp.add_marginals()
with pytest.raises(AssertionError) as excinfo:
InputSpace(inp)
assert str(excinfo.value) == 'Not all marginals were provided priors'
def test_check_valid_input_priorsmatch() -> None:
"""
Distribution not built if dist types do not align
"""
x = np.random.uniform(0, 1, 1000)
inp = Input()
inp.add_marginals()
inp.Marginals[0].input_data = x
inp.add_marginals()
inp.Marginals[1].dist_type = 'normal'
inp.Marginals[1].parameters = [0, 1]
with pytest.raises(AssertionError) as excinfo:
InputSpace(inp)
assert str(excinfo.value) == 'Distributions cannot be built as the priors have different types'
def test_check_valid_input_samples() -> None:
"""
Design built correctly - samples
"""
x = np.random.uniform(0, 1, 1000)
inp = Input()
inp.add_marginals()
inp.Marginals[0].input_data = x
inp.add_marginals()
inp.Marginals[1].input_data = x + 2
InputSpace(inp)
def test_check_valid_input_both() -> None:
"""
Design no built - samples and dist type given
"""
x = np.random.uniform(0, 1, 1000)
inp = Input()
inp.add_marginals()
inp.Marginals[0].input_data = x
inp.Marginals[0].dist_type = 'normal'
with pytest.raises(AssertionError) as excinfo:
InputSpace(inp)
assert str(excinfo.value) == 'Both samples and distribution type are given. Please choose only one.'
# def test_check_valid_input_distnotok() -> None:
# """
# Design built incorrectly - dist types without parameters
# """
# inp = Input()
# inp.add_marginals()
# inp.Marginals[0].dist_type = 'normal'
# inp.add_marginals()
# inp.Marginals[1].dist_type = 'normal'
# with pytest.raises(AssertionError) as excinfo:
# exp = ExpDesigns(inp)
# assert str(excinfo.value) == 'Some distributions do not have characteristic values'
def test_check_valid_input_distok() -> None:
"""
Design built correctly - dist types
"""
inp = Input()
inp.add_marginals()
inp.Marginals[0].dist_type = 'normal'
inp.Marginals[0].parameters = [0, 1]
inp.add_marginals()
inp.Marginals[1].dist_type = 'normal'
inp.Marginals[1].parameters = [0, 1]
InputSpace(inp)
def test_check_valid_input_noapc() -> None:
"""
Design built correctly - no apc
"""
inp = Input()
inp.add_marginals()
inp.Marginals[0].dist_type = 'normal'
inp.Marginals[0].parameters = [0, 1]
inp.add_marginals()
inp.Marginals[1].dist_type = 'normal'
inp.Marginals[1].parameters = [0, 1]
InputSpace(inp, meta_Model_type='gpe')
#%% Test ExpDesign.build_polytypes
def test_build_polytypes_normalerr() -> None:
"""
Build dist 'normal' - too few params
"""
inp = Input()
inp.add_marginals()
inp.Marginals[0].dist_type = 'normal'
inp.Marginals[0].parameters = []
exp = InputSpace(inp)
with pytest.raises(AssertionError) as excinfo:
exp.build_polytypes(False)
assert str(excinfo.value) == 'Distribution has too few parameters!'
def test_build_polytypes_normal() -> None:
"""
Build dist 'normal'
"""
inp = Input()
inp.add_marginals()
inp.Marginals[0].dist_type = 'normal'
inp.Marginals[0].parameters = [0, 1]
exp = InputSpace(inp)
exp.build_polytypes(False)
def test_build_polytypes_uniferr() -> None:
"""
Build dist 'unif' - too few params
"""
inp = Input()
inp.add_marginals()
inp.Marginals[0].dist_type = 'unif'
inp.Marginals[0].parameters = []
exp = InputSpace(inp)
with pytest.raises(AssertionError) as excinfo:
exp.build_polytypes(False)
assert str(excinfo.value) == 'Distribution has too few parameters!'
def test_build_polytypes_unif() -> None:
"""
Build dist 'unif'
"""
inp = Input()
inp.add_marginals()
inp.Marginals[0].dist_type = 'unif'
inp.Marginals[0].parameters = [0, 1]
exp = InputSpace(inp)
exp.build_polytypes(False)
def test_build_polytypes_gammaerr() -> None:
"""
Build dist 'gamma' - too few params
"""
inp = Input()
inp.add_marginals()
inp.Marginals[0].dist_type = 'gamma'
inp.Marginals[0].parameters = []
exp = InputSpace(inp)
with pytest.raises(AssertionError) as excinfo:
exp.build_polytypes(False)
assert str(excinfo.value) == 'Distribution has too few parameters!'
# noinspection SpellCheckingInspection
def test_build_polytypes_gamma() -> None:
"""
Build dist 'gamma'
"""
inp = Input()
inp.add_marginals()
inp.Marginals[0].dist_type = 'gamma'
inp.Marginals[0].parameters = [0, 1, 0]
exp = InputSpace(inp)
with pytest.raises(ValueError) as excinfo:
exp.build_polytypes(False)
assert str(excinfo.value) == 'Parameter values are not valid, please set differently'
# noinspection SpellCheckingInspection
def test_build_polytypes_betaerr() -> None:
"""
Build dist 'beta' - too few params
"""
inp = Input()
inp.add_marginals()
inp.Marginals[0].dist_type = 'beta'
inp.Marginals[0].parameters = []
exp = InputSpace(inp)
with pytest.raises(AssertionError) as excinfo:
exp.build_polytypes(False)
assert str(excinfo.value) == 'Distribution has too few parameters!'
def test_build_polytypes_beta() -> None:
"""
Build dist 'beta'
"""
inp = Input()
inp.add_marginals()
inp.Marginals[0].dist_type = 'beta'
inp.Marginals[0].parameters = [0.5, 1, 2, 3]
exp = InputSpace(inp)
exp.build_polytypes(False)
# noinspection SpellCheckingInspection
def test_build_polytypes_lognormerr() -> None:
"""
Build dist 'lognorm' - too few params
"""
inp = Input()
inp.add_marginals()
inp.Marginals[0].dist_type = 'lognorm'
inp.Marginals[0].parameters = []
exp = InputSpace(inp)
with pytest.raises(AssertionError) as excinfo:
exp.build_polytypes(False)
assert str(excinfo.value) == 'Distribution has too few parameters!'
def test_build_polytypes_lognorm() -> None:
"""
Build dist 'lognorm'
"""
inp = Input()
inp.add_marginals()
inp.Marginals[0].dist_type = 'lognorm'
inp.Marginals[0].parameters = [0.5, 1, 2, 3]
exp = InputSpace(inp)
exp.build_polytypes(False)
def test_build_polytypes_exponerr() -> None:
"""
Build dist 'expon' - too few params
"""
inp = Input()
inp.add_marginals()
inp.Marginals[0].dist_type = 'beta'
inp.Marginals[0].parameters = []
exp = InputSpace(inp)
with pytest.raises(AssertionError) as excinfo:
exp.build_polytypes(False)
assert str(excinfo.value) == 'Distribution has too few parameters!'
def test_build_polytypes_expon() -> None:
"""
Build dist 'expon'
"""
inp = Input()
inp.add_marginals()
inp.Marginals[0].dist_type = 'expon'
inp.Marginals[0].parameters = [0.5, 1, 2, 3]
exp = InputSpace(inp)
exp.build_polytypes(False)
def test_build_polytypes_weibullerr() -> None:
"""
Build dist 'weibull' - too few params
"""
inp = Input()
inp.add_marginals()
inp.Marginals[0].dist_type = 'weibull'
inp.Marginals[0].parameters = []
exp = InputSpace(inp)
with pytest.raises(AssertionError) as excinfo:
exp.build_polytypes(False)
assert str(excinfo.value) == 'Distribution has too few parameters!'
def test_build_polytypes_weibull() -> None:
"""
Build dist 'weibull'
"""
inp = Input()
inp.add_marginals()
inp.Marginals[0].dist_type = 'weibull'
inp.Marginals[0].parameters = [0.5, 1, 2, 3]
exp = InputSpace(inp)
exp.build_polytypes(False)
def test_build_polytypes_arbitrary() -> None:
"""
Build poly 'arbitrary'
"""
x = np.random.uniform(0, 1, 1000)
inp = Input()
inp.add_marginals()
inp.Marginals[0].input_data = x
exp = InputSpace(inp)
exp.build_polytypes(False)
def test_build_polytypes_rosenblatt() -> None:
"""
Build dist with rosenblatt
"""
x = np.random.uniform(0, 1, 1000)
inp = Input()
inp.add_marginals()
inp.Marginals[0].input_data = x
exp = InputSpace(inp)
exp.build_polytypes(True)
def test_build_polytypes_samples() -> None:
"""
Build dist from samples
"""
x = np.random.uniform(0, 1, 1000)
inp = Input()
inp.add_marginals()
inp.Marginals[0].input_data = x
exp = InputSpace(inp)
exp.build_polytypes(False)
def test_build_polytypes_samples2d() -> None:
"""
Build dist from samples - samples too high dim
"""
x = np.random.uniform(0, 1, (2, 1000))
inp = Input()
inp.add_marginals()
inp.Marginals[0].input_data = x
exp = InputSpace(inp)
with pytest.raises(ValueError) as excinfo:
exp.build_polytypes(False)
assert str(excinfo.value) == 'The samples provided to the Marginals should be 1D only'
#%% Test ExpDesign.init_param_space
def test_init_param_space_nomaxdegsample() -> None:
"""
Init param space without max_deg for given samples
"""
x = np.random.uniform(0, 1, 1000)
inp = Input()
inp.add_marginals()
inp.Marginals[0].input_data = x
exp = InputSpace(inp)
exp.init_param_space()
def test_init_param_space_maxdeg() -> None:
"""
Init param space with max_deg for given samples
"""
x = np.random.uniform(0, 1, 1000)
inp = Input()
inp.add_marginals()
inp.Marginals[0].input_data = x
exp = InputSpace(inp)
exp.init_param_space(max_deg=2)
def test_init_param_space_maxdegdist() -> None:
"""
Init param space with max_deg for given dist (not uniform)
"""
inp = Input()
inp.add_marginals()
inp.Marginals[0].dist_type = 'expon'
inp.Marginals[0].parameters = [0.5, 1, 2, 3]
exp = InputSpace(inp)
exp.init_param_space(max_deg=2)
def test_init_param_space_maxdegdistunif() -> None:
"""
Init param space with max_deg for given dist (uniform)
"""
inp = Input()
inp.add_marginals()
inp.Marginals[0].dist_type = 'unif'
inp.Marginals[0].parameters = [0.5, 1, 2, 3]
exp = InputSpace(inp)
exp.init_param_space(max_deg=2)
#%% Test ExpDesign.transform
def test_transform_noparamspace() -> None:
"""
Call transform without a built JDist
"""
x = np.random.uniform(0, 1, 1000)
y = np.random.uniform(0, 1, (2, 1000))
inp = Input()
inp.add_marginals()
inp.Marginals[0].input_data = x
exp = InputSpace(inp)
with pytest.raises(AttributeError) as excinfo:
exp.transform(y)
assert str(excinfo.value) == 'Call function init_param_space first to create JDist'
def test_transform_dimerrlow() -> None:
"""
Call transform with too few dimensions
"""
x = np.random.uniform(0, 1, 1000)
inp = Input()
inp.add_marginals()
inp.Marginals[0].input_data = x
exp = InputSpace(inp)
exp.init_param_space(max_deg=2)
with pytest.raises(AttributeError) as excinfo:
exp.transform(x)
assert str(excinfo.value) == 'X should have two dimensions'
def test_transform_dimerrhigh() -> None:
"""
Call transform with too many dimensions
"""
x = np.random.uniform(0, 1, 1000)
y = np.random.uniform(0, 1, (1, 1, 1000))
inp = Input()
inp.add_marginals()
inp.Marginals[0].input_data = x
exp = InputSpace(inp)
exp.init_param_space(max_deg=2)
with pytest.raises(AttributeError) as excinfo:
exp.transform(y)
assert str(excinfo.value) == 'X should have two dimensions'
def test_transform_dimerr0() -> None:
"""
Call transform with wrong X.shape[0]
"""
x = np.random.uniform(0, 1, 1000)
y = np.random.uniform(0, 1, (2, 1000))
inp = Input()
inp.add_marginals()
inp.Marginals[0].input_data = x
exp = InputSpace(inp)
exp.init_param_space(max_deg=2)
with pytest.raises(AttributeError) as excinfo:
exp.transform(y)
assert str(
excinfo.value) == 'The second dimension of X should be the same size as the number of marginals in the InputObj'
def test_transform_paramspace() -> None:
"""
Transform successfully
"""
x = np.random.uniform(0, 1, 1000)
y = np.random.uniform(0, 1, (1000, 1))
inp = Input()
inp.add_marginals()
inp.Marginals[0].input_data = x
exp = InputSpace(inp)
exp.init_param_space(max_deg=2)
exp.transform(y)
if 0: # See Issue #41, use these again when the issue is removed
def test_transform_rosenblatt() -> None:
"""
Transform with rosenblatt
"""
x = np.random.uniform(0, 1, 1000)
y = np.random.uniform(0, 1, (1000, 1))
inp = Input()
inp.Rosenblatt = True
inp.add_marginals()
inp.Marginals[0].input_data = x
exp = InputSpace(inp)
exp.init_param_space(max_deg=2)
exp.transform(y)
def test_transform_rosenblattuser() -> None:
"""
Transform with rosenblatt and method 'user'
"""
x = np.random.uniform(0, 1, 1000)
y = np.random.uniform(0, 1, (1000, 1))
inp = Input()
inp.Rosenblatt = True
inp.add_marginals()
inp.Marginals[0].input_data = x
exp = InputSpace(inp)
exp.init_param_space(max_deg=2)
exp.transform(y, method='user')
def test_transform_user() -> None:
"""
Transform with method 'user'
"""
x = np.random.uniform(0, 1, 1000)
y = np.random.uniform(0, 1, (1000, 1))
inp = Input()
inp.add_marginals()
inp.Marginals[0].input_data = x
exp = InputSpace(inp)
exp.init_param_space(max_deg=2)
exp.transform(y, method='user')
def test_transform_uniform() -> None:
"""
Transform uniform dist
"""
y = np.random.uniform(0, 1, (1000, 1))
inp = Input()
inp.add_marginals()
inp.Marginals[0].dist_type = 'unif'
inp.Marginals[0].parameters = [0, 1]
exp = InputSpace(inp)
exp.init_param_space(max_deg=2)
exp.transform(y)
def test_transform_norm() -> None:
"""
Transform normal dist
"""
y = np.random.uniform(0, 1, (1000, 1))
inp = Input()
inp.add_marginals()
inp.Marginals[0].dist_type = 'norm'
inp.Marginals[0].parameters = [0, 1]
exp = InputSpace(inp)
exp.init_param_space(max_deg=2)
exp.transform(y)
# TODO: what are these other params here???
def test_transform_gammanoparam() -> None:
"""
Transform gamma dist - no parameters
"""
y = np.random.uniform(0, 1, (1000, 1))
inp = Input()
inp.add_marginals()
inp.Marginals[0].dist_type = 'gamma'
inp.Marginals[0].parameters = [1, 1, 0]
exp = InputSpace(inp)
exp.init_param_space(max_deg=2)
with pytest.raises(AttributeError) as excinfo:
exp.transform(y)
assert str(excinfo.value) == 'Additional parameters have to be set for the gamma distribution!'
def test_transform_gammaparam() -> None:
"""
Transform gamma dist - with parameters
"""
y = np.random.uniform(0, 1, (1000, 1))
inp = Input()
inp.add_marginals()
inp.Marginals[0].dist_type = 'gamma'
inp.Marginals[0].parameters = [1, 1, 0]
exp = InputSpace(inp)
exp.init_param_space(max_deg=2)
exp.transform(y, params=[1, 1])