def test_kde_over_time():
experiments, outcomes = utilities.load_eng_trans_data()
kde_over_time(experiments, outcomes, log=False)
kde_over_time(experiments, outcomes, log=True)
kde_over_time(experiments,
outcomes,
group_by='policy',
grouping_specifiers=['no policy', 'adaptive policy'])
plt.draw()
plt.close('all')
def test_group_results():
results = utilities.load_eng_trans_data()
experiments, outcomes = results
# test indices
groups = {
'set1': np.arange(0, 11),
'set2': np.arange(11, 25),
'set3': np.arange(25, experiments.shape[0])
}
groups = group_results(experiments,
outcomes,
group_by='index',
grouping_specifiers=groups.values(),
grouping_labels=groups.keys())
total_data = 0
for value in groups.values():
total_data += value[0].shape[0]
print(experiments.shape[0], total_data)
# test continuous parameter type
array = experiments['average planning and construction period T1']
grouping_specifiers = make_continuous_grouping_specifiers(array,
nr_of_groups=5)
groups = group_results(
experiments,
outcomes,
group_by='average planning and construction period T1',
grouping_specifiers=grouping_specifiers,
grouping_labels=[str(entry) for entry in grouping_specifiers])
total_data = 0
for value in groups.values():
total_data += value[0].shape[0]
print(experiments.shape[0], total_data)
# test integer type
array = experiments['seed PR T1']
grouping_specifiers = make_continuous_grouping_specifiers(array,
nr_of_groups=10)
groups = group_results(
experiments,
outcomes,
group_by='seed PR T1',
grouping_specifiers=grouping_specifiers,
grouping_labels=[str(entry) for entry in grouping_specifiers])
total_data = 0
for value in groups.values():
total_data += value[0].shape[0]
print(experiments.shape[0], total_data)
# test categorical type
grouping_specifiers = set(experiments["policy"])
groups = group_results(
experiments,
outcomes,
group_by='policy',
grouping_specifiers=grouping_specifiers,
grouping_labels=[str(entry) for entry in grouping_specifiers])
total_data = 0
for value in groups.values():
total_data += value[0].shape[0]
print(experiments.shape[0], total_data)
def test_multiple_densities():
experiments, outcomes = utilities.load_eng_trans_data()
ooi = 'total fraction new technologies'
multiple_densities(experiments,
outcomes,
group_by="policy",
points_in_time=[2010])
multiple_densities(experiments,
outcomes,
outcomes_to_show=ooi,
group_by="policy",
points_in_time=[2010])
multiple_densities(experiments,
outcomes,
outcomes_to_show=ooi,
group_by="policy",
points_in_time=[2010, 2100])
multiple_densities(experiments,
outcomes,
outcomes_to_show=ooi,
group_by="policy",
points_in_time=[2010, 2050, 2100])
multiple_densities(experiments,
outcomes,
outcomes_to_show=ooi,
group_by="policy",
points_in_time=[2010, 2020, 2050, 2080])
multiple_densities(experiments,
outcomes,
outcomes_to_show=ooi,
group_by="policy",
points_in_time=[2010, 2020, 2040, 2060, 2100])
multiple_densities(experiments,
outcomes,
outcomes_to_show=ooi,
group_by="policy",
points_in_time=[2010, 2020, 2040, 2060, 2080, 2100],
plot_type=ENV_LIN,
density=KDE,
experiments_to_show=[1, 2, 10])
multiple_densities(experiments,
outcomes,
outcomes_to_show=ooi,
group_by="policy",
points_in_time=[2010, 2020, 2040, 2060, 2080, 2100],
plot_type=ENV_LIN,
density=HIST,
experiments_to_show=[1, 2, 10])
multiple_densities(experiments,
outcomes,
outcomes_to_show=ooi,
group_by="policy",
points_in_time=[2010, 2020, 2040, 2060, 2080, 2100],
plot_type=ENV_LIN,
density=BOXPLOT,
experiments_to_show=[1, 2, 10])
multiple_densities(experiments,
outcomes,
outcomes_to_show=ooi,
group_by="policy",
points_in_time=[2010, 2020, 2040, 2060, 2080, 2100],
plot_type=ENV_LIN,
density=VIOLIN,
experiments_to_show=[1, 2, 10])
plt.draw()
plt.close('all')
multiple_densities(experiments,
outcomes,
outcomes_to_show=ooi,
group_by="policy",
points_in_time=[2010, 2020, 2040, 2060, 2080, 2100],
plot_type=ENV_LIN,
density=KDE,
experiments_to_show=[1, 2, 10],
log=True)
multiple_densities(experiments,
outcomes,
outcomes_to_show=ooi,
group_by="policy",
points_in_time=[2010, 2020, 2040, 2060, 2080, 2100],
plot_type=ENV_LIN,
density=HIST,
experiments_to_show=[1, 2, 10],
log=True)
multiple_densities(experiments,
outcomes,
outcomes_to_show=ooi,
group_by="policy",
points_in_time=[2010, 2020, 2040, 2060, 2080, 2100],
plot_type=ENV_LIN,
density=BOXPLOT,
experiments_to_show=[1, 2, 10],
log=True)
multiple_densities(experiments,
outcomes,
outcomes_to_show=ooi,
group_by="policy",
points_in_time=[2010, 2020, 2040, 2060, 2080, 2100],
plot_type=ENV_LIN,
density=VIOLIN,
experiments_to_show=[1, 2, 10],
log=True)
plt.draw()
plt.close('all')
def test_envelopes():
experiments, outcomes = utilities.load_eng_trans_data()
#testing titles
envelopes(experiments, outcomes, density=None, titles=None)
envelopes(experiments, outcomes, density=None, titles={})
envelopes(experiments,
outcomes,
density=None,
titles={'total fraction new technologies': 'a'})
plt.draw()
plt.close('all')
#testing ylabels
envelopes(experiments, outcomes, density=None, ylabels=None)
envelopes(experiments, outcomes, density=None, ylabels={})
envelopes(experiments,
outcomes,
density=None,
ylabels={'total fraction new technologies': 'a'})
plt.draw()
plt.close('all')
#no grouping no density
envelopes(experiments, outcomes, titles=None)
set_fig_to_bw(envelopes(experiments, outcomes, density=None)[0])
plt.draw()
plt.close('all')
#no grouping, with density
envelopes(experiments, outcomes, density=KDE)
envelopes(experiments, outcomes, density=HIST)
envelopes(experiments, outcomes, density=BOXPLOT)
envelopes(experiments, outcomes, density=VIOLIN)
set_fig_to_bw(envelopes(experiments, outcomes, density=VIOLIN)[0])
plt.draw()
plt.close('all')
# grouping and density kde
envelopes(experiments, outcomes, group_by='policy', density=VIOLIN)
envelopes(experiments, outcomes, group_by='policy', density=BOXPLOT)
envelopes(experiments,
outcomes,
group_by='policy',
density=KDE,
grouping_specifiers=['no policy', 'adaptive policy'])
envelopes(experiments,
outcomes,
group_by='policy',
density=BOXPLOT,
grouping_specifiers=['no policy', 'adaptive policy'])
envelopes(experiments, outcomes, group_by='policy', density=KDE)
plt.draw()
plt.close('all')
envelopes(experiments, outcomes, group_by='policy', density=VIOLIN)
envelopes(experiments, outcomes, group_by='policy', density=BOXPLOT)
envelopes(experiments, outcomes, group_by='policy', density=KDE)
envelopes(experiments, outcomes, group_by='policy', density=HIST)
plt.draw()
plt.close('all')
envelopes(experiments,
outcomes,
group_by='policy',
density=VIOLIN,
log=True)
envelopes(experiments,
outcomes,
group_by='policy',
density=BOXPLOT,
log=True)
envelopes(experiments, outcomes, group_by='policy', density=KDE, log=True)
envelopes(experiments, outcomes, group_by='policy', density=HIST, log=True)
plt.draw()
plt.close('all')
# grouping and density hist
envelopes(experiments, outcomes, group_by='policy', density=HIST)
envelopes(experiments, outcomes, group_by='policy', density=HIST)
set_fig_to_bw(
envelopes(experiments, outcomes, group_by='policy', density=KDE)[0])
# grouping and density
envelopes(experiments, outcomes, group_by='policy', density=KDE, fill=True)
set_fig_to_bw(
envelopes(experiments,
outcomes,
group_by='policy',
density=KDE,
fill=True)[0])
plt.draw()
plt.close('all')
def test_lines():
experiments, outcomes = utilities.load_eng_trans_data()
lines(experiments,
outcomes,
outcomes_to_show="total fraction new technologies",
experiments_to_show=np.arange(0, 600, 20),
group_by='policy',
grouping_specifiers='basic policy')
lines(experiments,
outcomes,
experiments_to_show=np.arange(0, 600, 2),
group_by='policy',
density=HIST)
lines(experiments,
outcomes,
experiments_to_show=np.arange(0, 600, 2),
group_by='policy',
density=KDE)
lines(experiments,
outcomes,
experiments_to_show=np.arange(0, 600, 2),
group_by='policy',
density=BOXPLOT)
lines(experiments,
outcomes,
experiments_to_show=np.arange(0, 600, 2),
group_by='policy',
density=VIOLIN)
lines(
experiments,
outcomes,
group_by='index',
grouping_specifiers={"blaat": np.arange(1, 100, 2)},
density=KDE,
)
lines(experiments,
outcomes,
experiments_to_show=np.arange(0, 600, 30),
group_by='policy',
density=KDE,
show_envelope=True,
grouping_specifiers=['no policy', 'adaptive policy'])
lines(experiments,
outcomes,
experiments_to_show=np.arange(0, 600, 30),
group_by='policy',
density=HIST,
show_envelope=True,
grouping_specifiers=['no policy', 'adaptive policy'])
lines(experiments,
outcomes,
experiments_to_show=np.arange(0, 600, 30),
group_by='policy',
density=BOXPLOT,
show_envelope=True,
grouping_specifiers=['no policy', 'adaptive policy'])
lines(experiments,
outcomes,
experiments_to_show=np.arange(0, 600, 30),
group_by='policy',
density=VIOLIN,
show_envelope=True,
grouping_specifiers=['no policy', 'adaptive policy'])
plt.draw()
plt.close('all')
lines(experiments,
outcomes,
experiments_to_show=np.arange(0, 600, 30),
group_by='policy',
density=KDE,
show_envelope=True,
grouping_specifiers=['no policy', 'adaptive policy'],
log=True)
lines(experiments,
outcomes,
experiments_to_show=np.arange(0, 600, 30),
group_by='policy',
density=HIST,
show_envelope=True,
grouping_specifiers=['no policy', 'adaptive policy'],
log=True)
lines(experiments,
outcomes,
experiments_to_show=np.arange(0, 600, 30),
group_by='policy',
density=BOXPLOT,
show_envelope=True,
grouping_specifiers=['no policy', 'adaptive policy'],
log=True)
lines(experiments,
outcomes,
experiments_to_show=np.arange(0, 600, 30),
group_by='policy',
density=VIOLIN,
show_envelope=True,
grouping_specifiers=['no policy', 'adaptive policy'],
log=True)
plt.draw()
plt.close('all')
set_fig_to_bw(
lines(experiments,
outcomes,
experiments_to_show=np.arange(0, 600, 20),
group_by='policy',
density=KDE)[0])
new_outcomes = {}
for key, value in outcomes.items():
new_outcomes[key] = value[0:20, :]
experiments = experiments[0:20]
#no grouping, with density
set_fig_to_bw(lines(experiments, new_outcomes, density=KDE)[0])
set_fig_to_bw(lines(experiments, new_outcomes, density=HIST)[0])
set_fig_to_bw(lines(experiments, new_outcomes, density=BOXPLOT)[0])
set_fig_to_bw(lines(experiments, new_outcomes, density=VIOLIN)[0])
# grouping and density
set_fig_to_bw(
lines(experiments, new_outcomes, group_by='policy', density='kde')[0])
# grouping, density as histograms
# grouping and density
set_fig_to_bw(
lines(experiments,
new_outcomes,
group_by='policy',
density='hist',
legend=False)[0])
plt.draw()
plt.close('all')