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# imports
# standard
import random
from networkx import binomial_tree, MultiDiGraph
# local
from src.topupopt.problems.esipp.network import Arcs, Network
from src.topupopt.problems.esipp.network import ArcsWithoutLosses
from src.topupopt.problems.esipp.network import ArcsWithoutProportionalLosses
from src.topupopt.problems.esipp.network import ArcsWithoutStaticLosses
from src.topupopt.problems.esipp.resource import ResourcePrice
from src.topupopt.data.misc.utils import generate_pseudo_unique_key
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# *****************************************************************************
# *****************************************************************************
class TestNetwork:
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# *************************************************************************
# *************************************************************************
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def test_arc_technologies_static_losses(self):
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number_time_intervals = 3
number_scenarios = 2
number_options = 4
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efficiency_dict = {
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for q in range(number_scenarios)
for k in range(number_time_intervals)
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static_loss_dict = {
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for h in range(number_options)
for q in range(number_scenarios)
for k in range(number_time_intervals)
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for capacity_is_instantaneous in (True, False):
arc_tech = Arcs(
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efficiency_reverse=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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capacity_is_instantaneous=capacity_is_instantaneous,
static_loss=static_loss_dict,
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assert arc_tech.has_proportional_losses()
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assert arc_tech.has_static_losses()
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assert not arc_tech.is_infinite_capacity()
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assert not arc_tech.has_been_selected()
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assert arc_tech.is_isotropic(reverse_none_means_isotropic=True)
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assert not arc_tech.is_isotropic(reverse_none_means_isotropic=False)
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# isotropic
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arc_tech = Arcs(
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efficiency_reverse=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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capacity_is_instantaneous=capacity_is_instantaneous,
static_loss=static_loss_dict,
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assert not arc_tech.has_proportional_losses()
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assert arc_tech.has_static_losses()
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assert not arc_tech.is_infinite_capacity()
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assert not arc_tech.has_been_selected()
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assert arc_tech.is_isotropic(reverse_none_means_isotropic=True)
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assert arc_tech.is_isotropic(reverse_none_means_isotropic=False)
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# create arc technology with only one option
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arc_tech = Arcs(
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efficiency_reverse=None,
capacity=(1,),
minimum_cost=(1,),
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capacity_is_instantaneous=capacity_is_instantaneous,
static_loss={
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for q in range(number_scenarios)
for k in range(number_time_intervals)
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assert arc_tech.has_proportional_losses()
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assert arc_tech.has_static_losses()
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assert not arc_tech.is_infinite_capacity()
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assert not arc_tech.has_been_selected()
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assert arc_tech.is_isotropic(reverse_none_means_isotropic=True)
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assert not arc_tech.is_isotropic(reverse_none_means_isotropic=False)
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# create arc technology for one time interval
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arc_tech = Arcs(
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efficiency={
(q, 0): 0.5
for q in range(number_scenarios)
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efficiency_reverse=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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capacity_is_instantaneous=capacity_is_instantaneous,
static_loss={
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for h in range(number_options)
for q in range(number_scenarios)
# for k in range(number_time_intervals)
},
validate=True,
)
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assert arc_tech.has_proportional_losses()
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assert arc_tech.has_static_losses()
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assert not arc_tech.is_infinite_capacity()
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assert not arc_tech.has_been_selected()
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assert arc_tech.is_isotropic(reverse_none_means_isotropic=True)
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assert not arc_tech.is_isotropic(reverse_none_means_isotropic=False)
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# *********************************************************************
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# TypeError: The static losses should be given as a dict or None.
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error_triggered = False
try:
_ = Arcs(
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efficiency_reverse=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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capacity_is_instantaneous=capacity_is_instantaneous,
static_loss=tuple(
[k for k in range(number_time_intervals)]
for o in range(number_options)
),
validate=True,
)
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except TypeError:
error_triggered = True
assert error_triggered
# ValueError('The static losses should be specified for each arc
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# option.')
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error_triggered = False
try:
_ = Arcs(
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efficiency_reverse=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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capacity_is_instantaneous=capacity_is_instantaneous,
static_loss={
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for h in range(number_options)
for q in range(number_scenarios)
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except ValueError:
error_triggered = True
assert error_triggered
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# TypeError('The static losses must be specified via a list of lists.')
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error_triggered = False
try:
_ = Arcs(
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efficiency_reverse=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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capacity_is_instantaneous=capacity_is_instantaneous,
static_loss=[
tuple(k for k in range(number_time_intervals))
for o in range(number_options)
],
validate=True,
)
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except TypeError:
error_triggered = True
assert error_triggered
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# ValueError('The static loss values are inconsistent with the number '
# 'of options, scenarios and intervals.')
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error_triggered = False
try:
arc_tech = Arcs(
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efficiency_reverse=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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capacity_is_instantaneous=capacity_is_instantaneous,
static_loss={
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for h in range(number_options)
for q in range(number_scenarios)
for k in range(number_time_intervals - 1)
},
validate=True,
)
arc_tech.validate_sizes(
number_options=number_options,
number_scenarios=number_scenarios,
number_intervals=[
number_time_intervals for _ in range(number_scenarios)
],
)
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except ValueError:
error_triggered = True
assert error_triggered
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# TypeError('The static losses were not provided as numbers.')
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error_triggered = False
try:
_ = Arcs(
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efficiency_reverse=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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capacity_is_instantaneous=capacity_is_instantaneous,
static_loss={
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for h in range(number_options)
for q in range(number_scenarios)
for k in range(number_time_intervals)
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except TypeError:
error_triggered = True
assert error_triggered
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# ValueError('The static losses must be positive or zero.')
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error_triggered = False
try:
_ = Arcs(
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efficiency_reverse=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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capacity_is_instantaneous=capacity_is_instantaneous,
static_loss={
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for h in range(number_options)
for q in range(number_scenarios)
for k in range(number_time_intervals)
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except ValueError:
error_triggered = True
assert error_triggered
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# TypeError: The static loss dict keys must be tuples
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try:
_ = Arcs(
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efficiency=None,
efficiency_reverse=None,
static_loss={k: 1 for k in range(number_time_intervals)},
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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capacity_is_instantaneous=capacity_is_instantaneous,
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except TypeError:
error_triggered = True
assert error_triggered
# ValueError( 'The static loss dict keys must be tuples of size 3.')
error_triggered = False
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try:
_ = Arcs(
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efficiency=None,
efficiency_reverse=None,
static_loss={(k, 3): 1 for k in range(number_time_intervals)},
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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capacity_is_instantaneous=capacity_is_instantaneous,
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except ValueError:
error_triggered = True
assert error_triggered
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# TypeError(The staticl osses should be given as a dict or None.')
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try:
_ = Arcs(
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efficiency_reverse=None,
static_loss=[1 for k in range(number_time_intervals)],
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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capacity_is_instantaneous=capacity_is_instantaneous,
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except TypeError:
error_triggered = True
assert error_triggered
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# ValueError(
# 'No static loss values were provided. There should be one'+
# ' value per option, scenario and time interval.')
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try:
_ = Arcs(
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efficiency=None,
efficiency_reverse=None,
static_loss={},
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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capacity_is_instantaneous=capacity_is_instantaneous,
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except ValueError:
error_triggered = True
assert error_triggered
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# *************************************************************************
# *************************************************************************
def test_arc_technologies(self):
# *********************************************************************
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# create arc technology using instantaneous capacities
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number_scenarios = 2
number_options = 4
number_time_intervals = 3
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efficiency_dict = {
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for q in range(number_scenarios)
for k in range(number_time_intervals)
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for capacity_is_instantaneous in (True, False):
arc_tech = Arcs(
name="any",
efficiency=efficiency_dict,
efficiency_reverse=None,
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static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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capacity_is_instantaneous=capacity_is_instantaneous,
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assert arc_tech.has_proportional_losses()
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assert not arc_tech.has_static_losses()
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assert not arc_tech.is_infinite_capacity()
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assert not arc_tech.has_been_selected()
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assert arc_tech.is_isotropic(reverse_none_means_isotropic=True)
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assert not arc_tech.is_isotropic(reverse_none_means_isotropic=False)
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assert arc_tech.has_constant_efficiency()
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# create arc technology with only one option
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arc_tech = Arcs(
name="any",
efficiency=efficiency_dict,
efficiency_reverse=None,
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static_loss=None,
capacity=(1,),
minimum_cost=(1,),
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capacity_is_instantaneous=capacity_is_instantaneous,
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assert arc_tech.has_proportional_losses()
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assert not arc_tech.has_static_losses()
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assert not arc_tech.is_infinite_capacity()
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assert not arc_tech.has_been_selected()
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assert arc_tech.is_isotropic(reverse_none_means_isotropic=True)
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assert not arc_tech.is_isotropic(reverse_none_means_isotropic=False)
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assert arc_tech.has_constant_efficiency()
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# create arc technology for one time interval
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arc_tech = Arcs(
name="any",
efficiency={(0, 0): 0.95},
efficiency_reverse=None,
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static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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capacity_is_instantaneous=capacity_is_instantaneous,
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assert arc_tech.has_proportional_losses()
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assert not arc_tech.has_static_losses()
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assert not arc_tech.is_infinite_capacity()
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assert not arc_tech.has_been_selected()
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assert arc_tech.is_isotropic(reverse_none_means_isotropic=True)
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assert not arc_tech.is_isotropic(reverse_none_means_isotropic=False)
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assert arc_tech.has_constant_efficiency()
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# create arc technology for one time interval and isotropic
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arc_tech = Arcs(
name="any",
efficiency={(0, 0): 0.95},
efficiency_reverse={(0, 0): 0.95},
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static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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capacity_is_instantaneous=capacity_is_instantaneous,
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assert arc_tech.has_proportional_losses()
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assert not arc_tech.has_static_losses()
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assert not arc_tech.is_infinite_capacity()
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assert not arc_tech.has_been_selected()
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assert arc_tech.is_isotropic(reverse_none_means_isotropic=True)
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assert arc_tech.is_isotropic(reverse_none_means_isotropic=False)
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assert arc_tech.has_constant_efficiency()
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# create arc technology for one time interval and anisotropic
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arc_tech = Arcs(
name="any",
efficiency={(0, 0): 0.95},
efficiency_reverse={(0, 0): 1},
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static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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capacity_is_instantaneous=capacity_is_instantaneous,
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assert arc_tech.has_proportional_losses()
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assert not arc_tech.has_static_losses()
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assert not arc_tech.is_infinite_capacity()
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assert not arc_tech.has_been_selected()
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assert not arc_tech.is_isotropic(reverse_none_means_isotropic=True)
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assert not arc_tech.is_isotropic(reverse_none_means_isotropic=False)
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assert not arc_tech.has_constant_efficiency()
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# create arc technology for one time interval and anisotropic
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arc_tech = Arcs(
name="any",
efficiency={(0, 0): 1},
efficiency_reverse={(0, 0): 0.95},
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static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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capacity_is_instantaneous=capacity_is_instantaneous,
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assert arc_tech.has_proportional_losses()
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assert not arc_tech.has_static_losses()
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assert not arc_tech.is_infinite_capacity()
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assert not arc_tech.has_been_selected()
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assert not arc_tech.is_isotropic(reverse_none_means_isotropic=True)
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assert not arc_tech.is_isotropic(reverse_none_means_isotropic=False)
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assert not arc_tech.has_constant_efficiency()
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# create arc technology for one time interval and anisotropic
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arc_tech = Arcs(
name="any",
efficiency={(0, 0): 0.95},
efficiency_reverse={(0, 0): 0.95},
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static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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capacity_is_instantaneous=capacity_is_instantaneous,
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assert arc_tech.has_proportional_losses()
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assert not arc_tech.has_static_losses()
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assert not arc_tech.is_infinite_capacity()
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assert not arc_tech.has_been_selected()
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assert arc_tech.is_isotropic(reverse_none_means_isotropic=True)
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assert arc_tech.is_isotropic(reverse_none_means_isotropic=False)
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assert arc_tech.has_constant_efficiency()
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# *****************************************************************
# *****************************************************************
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# trigger errors
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# TypeError('The name attribute is not hashable.')
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try:
_ = Arcs(
name=[1, 2, 3],
efficiency=efficiency_dict,
efficiency_reverse=None,
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static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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capacity_is_instantaneous=capacity_is_instantaneous,
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except TypeError:
error_triggered = True
assert error_triggered
# TypeError:The efficiency dict keys must be (scenario, interval) tuples
error_triggered = False
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try:
_ = Arcs(
name="hey",
efficiency={k: 1 for k in range(number_time_intervals)},
efficiency_reverse=None,
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static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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capacity_is_instantaneous=capacity_is_instantaneous,
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except TypeError:
error_triggered = True
assert error_triggered
# ValueError( 'The efficiency dict keys must be tuples of size 2.')
error_triggered = False
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try:
_ = Arcs(
name="hey",
efficiency={(k, 3, 4): 1 for k in range(number_time_intervals)},
efficiency_reverse=None,
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static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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capacity_is_instantaneous=capacity_is_instantaneous,
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except ValueError:
error_triggered = True
assert error_triggered
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# TypeError(The efficiency should be given as a dict or None.')
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committed
try:
_ = Arcs(
name="hey",
efficiency=[1 for k in range(number_time_intervals)],
efficiency_reverse=None,
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committed
static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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committed
capacity_is_instantaneous=capacity_is_instantaneous,
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except TypeError:
error_triggered = True
assert error_triggered
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committed
# TypeError('The reverse efficiency has to match the nominal'+
# ' one when there are no proportional losses.')
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committed
try:
_ = Arcs(
name="hey",
efficiency=None,
efficiency_reverse={},
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committed
static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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committed
capacity_is_instantaneous=capacity_is_instantaneous,
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except TypeError:
error_triggered = True
assert error_triggered
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# TypeError:'The reverse efficiency should be given as a dict or None.'
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committed
try:
_ = Arcs(
name="hey",
efficiency=efficiency_dict,
efficiency_reverse=[1 for k in range(number_time_intervals)],
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committed
static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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committed
capacity_is_instantaneous=capacity_is_instantaneous,
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committed
except TypeError:
error_triggered = True
assert error_triggered
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# ValueError(
# 'No efficiency values were provided. There should be '+
# 'one value per scenario and time interval.')
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committed
try:
_ = Arcs(
name="hey",
efficiency=efficiency_dict,
efficiency_reverse={},
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committed
static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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committed
capacity_is_instantaneous=capacity_is_instantaneous,
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committed
except ValueError:
error_triggered = True
assert error_triggered
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committed
# ValueError: The keys for the efficiency dicts do not match.
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committed
try:
_ = Arcs(
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efficiency_reverse={
(key[1], key[0]): value
for key, value in efficiency_dict.items()
},
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committed
static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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committed
capacity_is_instantaneous=capacity_is_instantaneous,
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committed
except ValueError:
error_triggered = True
assert error_triggered
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committed
# TypeError: Efficiency values must be provided as numeric types.
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committed
try:
_ = Arcs(
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committed
efficiency_reverse={
(key[0], key[1]): str(value)
for key, value in efficiency_dict.items()
},
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committed
static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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committed
capacity_is_instantaneous=capacity_is_instantaneous,
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committed
except TypeError:
error_triggered = True
assert error_triggered
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committed
# ValueError('Efficiency values must be positive.')
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committed
try:
_ = Arcs(
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committed
efficiency_reverse={
(key[0], key[1]): -1 for key, value in efficiency_dict.items()
},
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committed
static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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committed
capacity_is_instantaneous=capacity_is_instantaneous,
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committed
except ValueError:
error_triggered = True
assert error_triggered
# TypeError('The capacity should be given as a list or tuple.')
error_triggered = False
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committed
try:
_ = Arcs(
name="hey",
efficiency=efficiency_dict,
efficiency_reverse=None,
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committed
static_loss=None,
capacity={o: 1 + o for o in range(number_options)},
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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committed
capacity_is_instantaneous=capacity_is_instantaneous,
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committed
except TypeError:
error_triggered = True
assert error_triggered
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committed
# TypeError: The minimum cost values should be given as a list or tuple
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committed
try:
_ = Arcs(
name="hey",
efficiency=efficiency_dict,
efficiency_reverse=None,
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committed
static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost={o: 1 + o for o in range(number_options)},
specific_capacity_cost=1,
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committed
capacity_is_instantaneous=capacity_is_instantaneous,
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committed
except TypeError:
error_triggered = True
assert error_triggered
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committed
# TypeError: The specific capacity cost was not given as a numeric type
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committed
try:
_ = Arcs(
name="hey",
efficiency=efficiency_dict,
efficiency_reverse=None,
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committed
static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=[1],
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committed
capacity_is_instantaneous=capacity_is_instantaneous,
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committed
except TypeError:
error_triggered = True
assert error_triggered
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committed
# ValueError:The number of capacity and minimum cost entries must match
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committed
try:
_ = Arcs(
name="hey",
efficiency=efficiency_dict,
efficiency_reverse=None,
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committed
static_loss=None,
capacity=tuple(1 + o for o in range(number_options + 1)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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committed
capacity_is_instantaneous=capacity_is_instantaneous,
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committed
except ValueError:
error_triggered = True
assert error_triggered
# ValueError: No entries for capacity and minimum cost were provided.
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committed
# At least one option should be provided.
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committed
try:
_ = Arcs(
name="hey",
efficiency=efficiency_dict,
efficiency_reverse=None,
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committed
static_loss=None,
capacity=tuple(),
minimum_cost=tuple(),
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committed
capacity_is_instantaneous=capacity_is_instantaneous,
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committed
except ValueError:
error_triggered = True
assert error_triggered
# ValueError: No entries for efficiency were provided. There should be
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committed
# one entry per time interval.
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committed
try:
_ = Arcs(
name="hey",
efficiency={},
efficiency_reverse=None,
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committed
static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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committed
capacity_is_instantaneous=capacity_is_instantaneous,
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committed
except ValueError:
error_triggered = True
assert error_triggered
# ValueError('The number of efficiency values must match the number of
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committed
# time intervals.')
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committed
arc_tech = Arcs(
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committed
efficiency={
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committed
for q in range(number_scenarios)
for k in range(number_time_intervals + 1)
},
efficiency_reverse=None,
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committed
static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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committed
capacity_is_instantaneous=capacity_is_instantaneous,
validate=True,
)
error_triggered = False
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committed
try:
arc_tech.validate_sizes(
number_options=number_options,
number_scenarios=number_scenarios,
number_intervals=[
number_time_intervals for _ in range(number_scenarios)
],
)
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committed
except ValueError:
error_triggered = True
assert error_triggered
# ValueError('The number of efficiency values must match the number of
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committed
# time intervals.')
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committed
try:
arc_tech = Arcs(
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committed
efficiency={
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committed
for q in range(number_scenarios)
for k in range(number_time_intervals)
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committed
efficiency_reverse={
Pedro L. Magalhães
committed
for q in range(number_scenarios)
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committed
static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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committed
capacity_is_instantaneous=capacity_is_instantaneous,
validate=True,
)
arc_tech.validate_sizes(
number_options=number_options,
number_scenarios=number_scenarios,
number_intervals=[
number_time_intervals for _ in range(number_scenarios)
],
)
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committed
except ValueError:
error_triggered = True
assert error_triggered
# ValueError('The number of capacity values must match the number of
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committed
# options.')
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committed
arc_tech = Arcs(
name="hey",
efficiency=efficiency_dict,
efficiency_reverse=None,
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committed
static_loss=None,
capacity=tuple(1 + o for o in range(number_options + 1)),
minimum_cost=tuple(1 + o for o in range(number_options + 1)),
specific_capacity_cost=1,
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committed
capacity_is_instantaneous=capacity_is_instantaneous,
validate=True,
)
error_triggered = False
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committed
try:
arc_tech.validate_sizes(
number_options=number_options,
number_scenarios=number_scenarios,
number_intervals=[
number_time_intervals for _ in range(number_scenarios)
],
)
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committed
except ValueError:
error_triggered = True
assert error_triggered
# ValueError: The minimum cost values are inconsistent with the number
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committed
# of options.
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committed
arc_tech = Arcs(
name="hey",
efficiency=efficiency_dict,
efficiency_reverse=None,
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committed
static_loss=None,
capacity=tuple(1 + o for o in range(number_options + 1)),
minimum_cost=tuple(1 + o for o in range(number_options + 1)),
specific_capacity_cost=1,
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committed
capacity_is_instantaneous=capacity_is_instantaneous,
validate=True,
)
error_triggered = False
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committed
try:
arc_tech.validate_sizes(
number_options=number_options,
number_scenarios=number_scenarios,
number_intervals=[
number_time_intervals for _ in range(number_scenarios)
],
)
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committed
except ValueError:
error_triggered = True
assert error_triggered
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committed
# TypeError('Efficiency values must be provided as numeric types.')
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committed
try:
_ = Arcs(
name="hey",
efficiency={
key: str(value) for key, value in efficiency_dict.items()
},
efficiency_reverse=None,
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committed
static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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committed
capacity_is_instantaneous=capacity_is_instantaneous,
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committed
except TypeError:
error_triggered = True
assert error_triggered
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committed
# ValueError('Efficiency values must be positive.')
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committed
try:
_ = Arcs(
name="hey",
efficiency={
key: -value * random.randint(0, 1)
for key, value in efficiency_dict.items()
},
efficiency_reverse=None,
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committed
static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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committed
capacity_is_instantaneous=capacity_is_instantaneous,
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committed
except ValueError:
error_triggered = True
assert error_triggered
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committed
# TypeError('Capacity values must be provided as numeric types.')
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committed
try:
_ = Arcs(
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committed
efficiency=efficiency_dict,
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committed
static_loss=None,
capacity=tuple(str(1 + o) for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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committed
capacity_is_instantaneous=capacity_is_instantaneous,
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committed
except TypeError:
error_triggered = True
assert error_triggered
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committed
# ValueError('Capacity values must be positive.')
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committed
try:
_ = Arcs(
name="hey",
efficiency=efficiency_dict,
efficiency_reverse=None,
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committed
static_loss=None,
capacity=tuple(
-random.randint(0, 1) for o in range(number_options)
),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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committed
capacity_is_instantaneous=capacity_is_instantaneous,
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committed
except ValueError:
error_triggered = True
assert error_triggered
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committed
# TypeError('Minimum cost values must be provided as numeric types.')
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committed
try:
_ = Arcs(
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committed
efficiency=efficiency_dict,
efficiency_reverse=None,
static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(str(1 + o) for o in range(number_options)),
specific_capacity_cost=1,
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committed
capacity_is_instantaneous=capacity_is_instantaneous,
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committed
except TypeError:
error_triggered = True
assert error_triggered
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committed
# ValueError('Minimum cost values must be positive or zero.')
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committed
try:
_ = Arcs(
name="hey",
efficiency=efficiency_dict,
efficiency_reverse=None,
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committed
static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(-1 for o in range(number_options)),
specific_capacity_cost=1,
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committed
capacity_is_instantaneous=capacity_is_instantaneous,
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committed
except ValueError:
error_triggered = True
assert error_triggered
# TypeError('The information about capacities being instantaneous or not
Pedro L. Magalhães
committed
# should be given as a boolean variable.')
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committed
try:
_ = Arcs(
name="hey",
efficiency=efficiency_dict,
efficiency_reverse=None,
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committed
static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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committed
capacity_is_instantaneous=1,
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committed
except TypeError:
error_triggered = True
assert error_triggered
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committed
# *********************************************************************
# *********************************************************************
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committed
# Network
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committed
arc_tech_AB = Arcs(
name="AB",
efficiency=efficiency_dict,
efficiency_reverse=None,
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committed
static_loss=None,
capacity=tuple(1 + o for o in range(number_options)),
minimum_cost=tuple(1 + o for o in range(number_options)),
specific_capacity_cost=1,
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committed
capacity_is_instantaneous=False,
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committed
arc_tech_AB.options_selected[0] = True
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committed
assert arc_tech_AB.number_options() == number_options
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committed
net = Network()
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committed
# add undirected arc
net.add_undirected_arc(node_key_a="A", node_key_b="B", arcs=arc_tech_AB)
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committed
# add directed arc
net.add_directed_arc(node_key_a="A", node_key_b="B", arcs=arc_tech_AB)
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committed
# add infinite capacity arc
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committed
net.add_infinite_capacity_arc(
node_key_a="C",
node_key_b="D",
efficiency={(i, j): 1 for i in range(3) for j in range(4)},
static_loss=None,
)
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committed
# add pre-existing directed arc
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committed
net.add_preexisting_directed_arc(
node_key_a="E",
node_key_b="F",
efficiency=efficiency_dict,
static_loss=None,
capacity=3,
capacity_is_instantaneous=True,
)
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committed
# add pre-existing undirected arc
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committed
net.add_preexisting_undirected_arc(
node_key_a="A",
node_key_b="C",
efficiency=efficiency_dict,
efficiency_reverse=efficiency_dict,
static_loss=None,
capacity=3,
capacity_is_instantaneous=True,
)
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committed
net.modify_network_arc(
node_key_a="A",
node_key_b="C",
arc_key_ab="AC",
data_dict={net.KEY_ARC_TECH: arc_tech_AB, net.KEY_ARC_UND: False},
)
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committed
# *********************************************************************
# *********************************************************************
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committed
# add import node
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committed
imp_resource_price = ResourcePrice(
prices=[random.random() for k in range(number_time_intervals)],
volumes=[
*[random.random() for k in range(number_time_intervals - 1)],
None,
],
)
net.add_import_node(node_key="G", prices={(0, 0, 0): imp_resource_price})
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committed
# add export node
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committed
exp_resource_price = ResourcePrice(
prices=[random.random() for k in range(number_time_intervals)],
volumes=[
*[random.random() for k in range(number_time_intervals - 1)],
None,
],
)
net.add_export_node(node_key="H", prices={(0, 0, 0): exp_resource_price})
net.add_waypoint_node(node_key="Z")
base_flow = {(i, j): random.random() for i in range(3) for j in range(4)}
net.add_source_sink_node(node_key="Y", base_flow=base_flow)
base_flow[(2, 3)] = random.random()
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committed
net.modify_network_node(
node_key="Y", node_data={net.KEY_NODE_BASE_FLOW: base_flow}
)
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committed
net.identify_node_types()
assert "Z" in net.waypoint_nodes
assert "G" in net.import_nodes
assert "H" in net.export_nodes
assert "Y" in net.source_sink_nodes
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committed
# *************************************************************************
# *************************************************************************
def test_arcs_without_losses(self):
# test arc without (static and proportional) losses
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committed
arc_tech = ArcsWithoutLosses(
name="AB",
capacity=(1, 2, 3),
minimum_cost=(4, 5, 6),
specific_capacity_cost=6,
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committed
capacity_is_instantaneous=False,
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committed
assert not arc_tech.has_proportional_losses()
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committed
assert not arc_tech.has_static_losses()
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committed
assert not arc_tech.is_infinite_capacity()
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committed
assert arc_tech.has_constant_efficiency()
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committed
# test arc without static losses
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committed
arc_tech = ArcsWithoutStaticLosses(
name="AB",
efficiency={(0, 0): 1, (0, 1): 0.9, (0, 2): 0.8},
efficiency_reverse=None,
capacity=(1, 2, 3),
minimum_cost=(4, 5, 6),
specific_capacity_cost=6,
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committed
capacity_is_instantaneous=False,
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committed
assert arc_tech.has_proportional_losses()
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committed
assert not arc_tech.has_static_losses()
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committed
assert not arc_tech.is_infinite_capacity()
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committed
assert not arc_tech.has_constant_efficiency()
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committed
# test arc without proportional losses
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committed
arc_tech = ArcsWithoutProportionalLosses(
name="AB",
static_loss={
(0, 0, 0): 0.1,
(0, 0, 1): 0.2,
(0, 0, 2): 0.3,
(1, 0, 0): 0.15,
(1, 0, 1): 0.25,
(1, 0, 2): 0.35,
(2, 0, 0): 0.16,
(2, 0, 1): 0.26,
(2, 0, 2): 0.36,
},
capacity=(1, 2, 3),
minimum_cost=(4, 5, 6),
specific_capacity_cost=6,
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committed
capacity_is_instantaneous=False,
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committed
assert not arc_tech.has_proportional_losses()
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committed
assert arc_tech.has_static_losses()
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assert not arc_tech.is_infinite_capacity()
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assert arc_tech.has_constant_efficiency()
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# *************************************************************************
# *************************************************************************
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def test_modifying_nodes(self):
# *********************************************************************
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net = Network()
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number_intervals = 3
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resource_price = ResourcePrice(
prices=[random.random() for k in range(number_intervals)],
volumes=[*[random.random() for k in range(number_intervals - 1)], None],
)
base_flow = {(0, k): random.random() for k in range(number_intervals)}
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arc_tech = ArcsWithoutLosses(
name="hello",
capacity=[5],
minimum_cost=[3],
specific_capacity_cost=3,
capacity_is_instantaneous=False,
)
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# add isolated import node
net.add_import_node(node_key="I_iso", prices={(0, 0, 0): resource_price})
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# add import node with outgoing arcs
net.add_import_node(node_key="I", prices={(0, 0, 0): resource_price})
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# add isolated export node
net.add_import_node(node_key="E_iso", prices={(0, 0, 0): resource_price})
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# add export node with incoming arcs
net.add_export_node(node_key="E", prices={(0, 0, 0): resource_price})
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# add isolated normal node
net.add_source_sink_node(node_key="A_iso", base_flow=base_flow)
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# add normal node with incoming arcs
net.add_source_sink_node(node_key="A_in", base_flow=base_flow)
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# add normal node with outgoing arcs
net.add_source_sink_node(node_key="A_out", base_flow=base_flow)
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# add normal node with incoming and outgoing arcs
net.add_source_sink_node(node_key="A", base_flow=base_flow)
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# *********************************************************************
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# arcs
net.add_directed_arc(node_key_a="I", node_key_b="A_in", arcs=arc_tech)
net.add_directed_arc(node_key_a="I", node_key_b="A", arcs=arc_tech)
net.add_directed_arc(node_key_a="A_out", node_key_b="E", arcs=arc_tech)
net.add_directed_arc(node_key_a="A", node_key_b="E", arcs=arc_tech)
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# *********************************************************************
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# change I_iso to regular: okay
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net.modify_network_node(
node_key="I_iso",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_SOURCE_SINK,
net.KEY_NODE_BASE_FLOW: base_flow,
},
)
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# reverse: okay
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net.modify_network_node(
node_key="I_iso",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_IMP,
net.KEY_NODE_PRICES: resource_price,
},
)
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# change I_iso to export: okay
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net.modify_network_node(
node_key="I_iso",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_EXP,
net.KEY_NODE_PRICES: resource_price,
},
)
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# reverse: okay
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net.modify_network_node(
node_key="I_iso",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_IMP,
net.KEY_NODE_PRICES: resource_price,
},
)
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# change I_iso to waypoint: okay
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net.modify_network_node(
node_key="I_iso", node_data={net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_WAY}
)
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# reverse: okay
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net.modify_network_node(
node_key="I_iso",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_IMP,
net.KEY_NODE_PRICES: resource_price,
},
)
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# *********************************************************************
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# change E_iso to regular: okay
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net.modify_network_node(
node_key="E_iso",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_SOURCE_SINK,
net.KEY_NODE_BASE_FLOW: base_flow,
},
)
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# reverse: okay
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net.modify_network_node(
node_key="E_iso",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_EXP,
net.KEY_NODE_PRICES: resource_price,
},
)
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# change E_iso to import: okay
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net.modify_network_node(
node_key="E_iso",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_IMP,
net.KEY_NODE_PRICES: resource_price,
},
)
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# reverse: okay
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net.modify_network_node(
node_key="E_iso",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_EXP,
net.KEY_NODE_PRICES: resource_price,
},
)
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# change E_iso to waypoint: okay
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net.modify_network_node(
node_key="E_iso", node_data={net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_WAY}
)
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# reverse: okay
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net.modify_network_node(
node_key="E_iso",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_EXP,
net.KEY_NODE_PRICES: resource_price,
},
)
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# *********************************************************************
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# change A_iso to export: okay
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net.modify_network_node(
node_key="A_iso",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_EXP,
net.KEY_NODE_PRICES: resource_price,
},
)
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# reverse: okay
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net.modify_network_node(
node_key="A_iso",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_SOURCE_SINK,
net.KEY_NODE_BASE_FLOW: base_flow,
},
)
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# change A_iso to import: okay
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net.modify_network_node(
node_key="A_iso",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_IMP,
net.KEY_NODE_PRICES: resource_price,
},
)
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# reverse: okay
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net.modify_network_node(
node_key="A_iso",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_SOURCE_SINK,
net.KEY_NODE_BASE_FLOW: base_flow,
},
)
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# change A_iso to waypoint: okay
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net.modify_network_node(
node_key="A_iso", node_data={net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_WAY}
)
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# reverse: okay
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net.modify_network_node(
node_key="A_iso",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_SOURCE_SINK,
net.KEY_NODE_BASE_FLOW: base_flow,
},
)
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# *********************************************************************
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# change I to regular: okay
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net.modify_network_node(
node_key="I",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_SOURCE_SINK,
net.KEY_NODE_BASE_FLOW: base_flow,
},
)
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# reverse: okay
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net.modify_network_node(
node_key="I",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_IMP,
net.KEY_NODE_PRICES: resource_price,
},
)
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# change I to waypoint: okay
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net.modify_network_node(
node_key="I", node_data={net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_WAY}
)
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# reverse: okay
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net.modify_network_node(
node_key="I",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_IMP,
net.KEY_NODE_PRICES: resource_price,
},
)
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# *********************************************************************
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# change E to regular: okay
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net.modify_network_node(
node_key="E",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_SOURCE_SINK,
net.KEY_NODE_BASE_FLOW: base_flow,
},
)
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# reverse: okay
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net.modify_network_node(
node_key="E",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_EXP,
net.KEY_NODE_PRICES: resource_price,
},
)
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# change E to waypoint: okay
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net.modify_network_node(
node_key="E", node_data={net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_WAY}
)
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# reverse: okay
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net.modify_network_node(
node_key="E",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_EXP,
net.KEY_NODE_PRICES: resource_price,
},
)
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# *********************************************************************
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# change A_in to export: okay
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net.modify_network_node(
node_key="A_in",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_EXP,
net.KEY_NODE_PRICES: resource_price,
},
)
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# reverse: okay
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net.modify_network_node(
node_key="A_in",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_SOURCE_SINK,
net.KEY_NODE_BASE_FLOW: base_flow,
},
)
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# change A_in to waypoint: okay
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net.modify_network_node(
node_key="A_in", node_data={net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_WAY}
)
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# reverse: okay
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net.modify_network_node(
node_key="A_in",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_SOURCE_SINK,
net.KEY_NODE_BASE_FLOW: base_flow,
},
)
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# *********************************************************************
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# change A_out to import: okay
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net.modify_network_node(
node_key="A_out",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_IMP,
net.KEY_NODE_PRICES: resource_price,
},
)
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# reverse: okay
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net.modify_network_node(
node_key="A_out",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_SOURCE_SINK,
net.KEY_NODE_BASE_FLOW: base_flow,
},
)
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# change A_out to waypoint: okay
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net.modify_network_node(
node_key="A_out", node_data={net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_WAY}
)
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# reverse: okay
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net.modify_network_node(
node_key="A_out",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_SOURCE_SINK,
net.KEY_NODE_BASE_FLOW: base_flow,
},
)
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# *********************************************************************
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# change I to export: fail
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error_triggered = False
try:
net.modify_network_node(
node_key="I",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_EXP,
net.KEY_NODE_PRICES: resource_price,
},
)
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except ValueError:
error_triggered = True
assert error_triggered
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# change E to import: fail
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error_triggered = False
try:
net.modify_network_node(
node_key="E",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_IMP,
net.KEY_NODE_PRICES: resource_price,
},
)
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except ValueError:
error_triggered = True
assert error_triggered
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# change A_out to export: fail
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error_triggered = False
try:
net.modify_network_node(
node_key="A_out",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_EXP,
net.KEY_NODE_PRICES: resource_price,
},
)
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except ValueError:
error_triggered = True
assert error_triggered
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# change A_in to import: fail
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error_triggered = False
try:
net.modify_network_node(
node_key="A_in",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_IMP,
net.KEY_NODE_PRICES: resource_price,
},
)
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except ValueError:
error_triggered = True
assert error_triggered
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# change A to export: fail
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error_triggered = False
try:
net.modify_network_node(
node_key="A",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_EXP,
net.KEY_NODE_PRICES: resource_price,
},
)
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except ValueError:
error_triggered = True
assert error_triggered
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# change A to import: fail
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error_triggered = False
try:
net.modify_network_node(
node_key="A",
node_data={
net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_IMP,
net.KEY_NODE_PRICES: resource_price,
},
)
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except ValueError:
error_triggered = True
assert error_triggered
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# *********************************************************************
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# try to modify a non-existent node
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error_triggered = False
try:
net.modify_network_node(
node_key="ABCD", node_data={net.KEY_NODE_TYPE: net.KEY_NODE_TYPE_WAY}
)
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except ValueError:
error_triggered = True
assert error_triggered
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# *********************************************************************
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# *************************************************************************
# *************************************************************************
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def test_network_disallowed_cases(self):
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net = Network()
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number_intervals = 3
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resource_price = ResourcePrice(
prices=[random.random() for k in range(number_intervals)],
volumes=[*[random.random() for k in range(number_intervals - 1)], None],
)
base_flow = {(0, k): random.random() for k in range(number_intervals)}
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lossless_arcs = ArcsWithoutLosses(
name="hello",
capacity=[5],
minimum_cost=[3],
specific_capacity_cost=3,
capacity_is_instantaneous=False,
)
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lossy_arcs = ArcsWithoutProportionalLosses(
name="hello back",
static_loss={(0, 0, k): random.random() for k in range(number_intervals)},
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capacity=(1,),
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specific_capacity_cost=0,
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# add import node I
net.add_import_node(node_key="I", prices={(0, 0, 0): resource_price})
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# add export node E
net.add_export_node(node_key="E", prices={(0, 0, 0): resource_price})
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# add regular node A
net.add_source_sink_node(node_key="A", base_flow=base_flow)
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# add regular node B
net.add_source_sink_node(node_key="B", base_flow=base_flow)
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# add a valid import-export arc
net.add_directed_arc(node_key_a="I", node_key_b="E", arcs=lossless_arcs)
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# identify the nodes and validate
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net.identify_node_types()
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# *********************************************************************
# *********************************************************************
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# trigger errors using pre-identified nodes
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# directed arcs cannot start in an export node: E -> B
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error_triggered = False
try:
net.add_directed_arc(node_key_a="E", node_key_b="B", arcs=lossless_arcs)
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except ValueError:
error_triggered = True
assert error_triggered
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# directed arcs cannot end on an import node: A -> I
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error_triggered = False
try:
net.add_directed_arc(node_key_a="A", node_key_b="I", arcs=lossless_arcs)
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except ValueError:
error_triggered = True
assert error_triggered
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# import-export nodes cannot have static losses
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error_triggered = False
try:
net.add_directed_arc(node_key_a="I", node_key_b="E", arcs=lossy_arcs)
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except ValueError:
error_triggered = True
assert error_triggered
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# undirected arcs cannot involve import nor export nodes
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error_triggered = False
try:
net.add_undirected_arc(node_key_a="I", node_key_b="A", arcs=lossless_arcs)
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except ValueError:
error_triggered = True
assert error_triggered
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# undirected arcs cannot involve import nor export nodes
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error_triggered = False
try:
net.add_undirected_arc(node_key_a="B", node_key_b="E", arcs=lossless_arcs)
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except ValueError:
error_triggered = True
assert error_triggered
# undirected arcs cannot involve import nor export nodes
error_triggered = False
try:
net.add_undirected_arc(node_key_a="I", node_key_b="E", arcs=lossy_arcs)
except ValueError:
error_triggered = True
assert error_triggered
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# *********************************************************************
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# trigger errors using non-identified nodes
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# *********************************************************************
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# create a new export node
net.add_export_node(node_key="E1", prices={(0, 0, 0): resource_price})
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# create an arc starting in that export node
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error_triggered = False
try:
net.add_directed_arc(node_key_a="E1", node_key_b="B", arcs=lossless_arcs)
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net.identify_node_types()
except ValueError:
error_triggered = True
assert error_triggered
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# remove the troublesome arc
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# *********************************************************************
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# create a new import node
net.add_import_node(node_key="I1", prices={(0, 0, 0): resource_price})
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# create an arc ending in that import node
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error_triggered = False
try:
net.add_directed_arc(node_key_a="A", node_key_b="I1", arcs=lossless_arcs)
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net.identify_node_types()
except ValueError:
error_triggered = True
assert error_triggered
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# remove the troublesome arc
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# *********************************************************************
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# check non-existent arc
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# *************************************************************************
# *************************************************************************
def test_undirected_arc_import_error(self):
# network
mynet = Network()
# import node
imp_node_key = generate_pseudo_unique_key(mynet.nodes())
mynet.add_import_node(
node_key=imp_node_key,
prices={
(0, 0, 0): ResourcePrice(prices=1+0.05, volumes=None)
},
)
# other nodes
node_A = generate_pseudo_unique_key(mynet.nodes())
mynet.add_source_sink_node(
node_key=node_A,
# base_flow=[1, -1, 0.5, -0.5]
base_flow={(0, 0): 1, (0, 1): -1, (0, 2): 0.5, (0, 3): -0.5},
)
node_B = generate_pseudo_unique_key(mynet.nodes())
mynet.add_source_sink_node(
node_key=node_B,
# base_flow=[-1, 1, -0.5, 0.5]
base_flow={(0, 0): -1, (0, 1): 1, (0, 2): -0.5, (0, 3): 0.5},
)
# add arcs
# import arc
arc_tech_IA = Arcs(
name="any",
# efficiency=[1, 1, 1, 1],
efficiency={(0, 0): 1, (0, 1): 1, (0, 2): 1, (0, 3): 1},
capacity=[0.5, 0.75, 1.0, 1.25, 1.5, 2.0],
minimum_cost=[10, 10.1, 10.2, 10.3, 10.4, 10.5],
specific_capacity_cost=1,
capacity_is_instantaneous=False,
efficiency_reverse=None,
static_loss=None,
validate=False,
)
mynet.add_undirected_arc(
node_key_a=imp_node_key, node_key_b=node_A, arcs=arc_tech_IA
)
error_raised = False
try:
# identify node types
mynet.identify_node_types()
except ValueError:
error_raised = True
assert error_raised
# *********************************************************************
# *********************************************************************
# *************************************************************************
# *************************************************************************
def test_undirected_arc_export_error(self):
# 4 nodes: one import, one export, two supply/demand nodes
mynet = Network()
# export node
exp_node_key = generate_pseudo_unique_key(mynet.nodes())
mynet.add_export_node(
node_key=exp_node_key,
prices={
(0, 0, 0): ResourcePrice(prices=0.1+0.05, volumes=None)
},
)
# other nodes
node_B = generate_pseudo_unique_key(mynet.nodes())
mynet.add_source_sink_node(
node_key=node_B,
# base_flow=[-1, 1, -0.5, 0.5]
base_flow={(0, 0): -1, (0, 1): 1, (0, 2): -0.5, (0, 3): 0.5},
)
# export arc
arc_tech_BE = Arcs(
name="any",
# efficiency=[1, 1, 1, 1],
efficiency={(0, 0): 1, (0, 1): 1, (0, 2): 1, (0, 3): 1},
capacity=[0.5, 0.75, 1.0, 1.25, 1.5, 2.0],
minimum_cost=[10, 10.1, 10.2, 10.3, 10.4, 10.5],
specific_capacity_cost=1,
capacity_is_instantaneous=False,
efficiency_reverse=None,
static_loss=None,
validate=False,
)
mynet.add_undirected_arc(
node_key_a=node_B, node_key_b=exp_node_key, arcs=arc_tech_BE
)
error_raised = False
try:
# identify node types
mynet.identify_node_types()
except ValueError:
error_raised = True
assert error_raised
# *************************************************************************
# *************************************************************************
def test_tree_topology(self):
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# create a network object with a tree topology
tree_network = binomial_tree(3, create_using=MultiDiGraph)
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network = Network(incoming_graph_data=tree_network)
for edge_key in network.edges(keys=True):
arc = ArcsWithoutLosses(
name=str(edge_key),
capacity=[5, 10],
minimum_cost=[3, 6],
specific_capacity_cost=0,
capacity_is_instantaneous=False,
)
network.add_edge(*edge_key, **{Network.KEY_ARC_TECH: arc})
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# assert that it does not have a tree topology
assert not network.has_tree_topology()
# select all the nodes
for edge_key in network.edges(keys=True):
network.edges[edge_key][Network.KEY_ARC_TECH].options_selected[0] = True
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# assert that it has a tree topology
assert network.has_tree_topology()
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# *************************************************************************
# *************************************************************************
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def test_pseudo_unique_key_generation(self):
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# create network
network = Network()
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# add node A
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# add node B
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# identify nodes
network.identify_node_types()
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# add arcs
key_list = [
"3e225573-4e78-48c8-bb08-efbeeb795c22",
"f6d30428-15d1-41e9-a952-0742eaaa5a31",
"8c29b906-2518-41c5-ada8-07b83508b5b8",
"f9a72a39-1422-4a02-af97-906ce79c32a3",
"b6941a48-10cc-465d-bf53-178bd2939bd1",
]
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for key in key_list:
network.add_edge(
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key=key,
**{network.KEY_ARC_UND: False, network.KEY_ARC_TECH: None}
)
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# use a seed number to trigger more iterations
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import uuid
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rand = random.Random()
rand.seed(360)
uuid.uuid4 = lambda: uuid.UUID(int=rand.getrandbits(128), version=4)
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error_triggered = False
try:
_ = network.get_pseudo_unique_arc_key(
node_key_start="A", node_key_end="B", max_iterations=len(key_list) - 1
)
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except Exception:
error_triggered = True
assert error_triggered
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# *************************************************************************
# *************************************************************************
def test_imp_exp_static_losses(self):
# assessment
q = 0
# 4 nodes: one import, one export, two supply/demand nodes
mynet = Network()
# import node
imp_node_key = generate_pseudo_unique_key(mynet.nodes())
imp_prices = {
qpk: ResourcePrice(
prices=0.5,
volumes=None,
)
for qpk in [(0,0,0),(0,0,1),(0,1,0),(0,1,1)]
}
mynet.add_import_node(
node_key=imp_node_key,
prices=imp_prices
)
# export node
exp_node_key = generate_pseudo_unique_key(mynet.nodes())
exp_prices = {
qpk: ResourcePrice(
prices=1.5,
volumes=None,
)
for qpk in [(0,0,0),(0,0,1),(0,1,0),(0,1,1)]
}
mynet.add_export_node(
node_key=exp_node_key,
prices=exp_prices,
)
# add arc with fixed losses from import node to export
arc_tech_IE_fix = Arcs(
name="IE_fix",
# efficiency=[1, 1, 1, 1],
efficiency={(q, 0): 1, (q, 1): 1},
efficiency_reverse=None,
validate=False,
capacity=[0.5, 1.0, 2.0],
minimum_cost=[5, 5.1, 5.2],
specific_capacity_cost=1,
capacity_is_instantaneous=False,
# static_losses=[
# [0.10, 0.15, 0.20, 0.25],
# [0.15, 0.20, 0.25, 0.30],
# [0.20, 0.25, 0.30, 0.35]]
static_loss={
(0, q, 0): 0.10,
(0, q, 1): 0.15,
(1, q, 0): 0.15,
(1, q, 1): 0.20,
(2, q, 0): 0.20,
(2, q, 1): 0.25,
},
)
mynet.add_directed_arc(
node_key_a=imp_node_key, node_key_b=exp_node_key, arcs=arc_tech_IE_fix
)
error_raised = False
try:
# identify node types
mynet.identify_node_types()
except ValueError:
error_raised = True
assert error_raised
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# *************************************************************************
# *************************************************************************
def test_antiparallel_arcs(self):
# create network
net = Network()
# add nodes
node_a = 'A'
net.add_waypoint_node(node_a)
node_b = 'B'
net.add_waypoint_node(node_b)
node_c = 'C'
net.add_waypoint_node(node_c)
# add arcs
node_pairs = ((node_a, node_b), (node_b, node_a),)
# test network
for node_pair in node_pairs:
net.add_preexisting_directed_arc(
*node_pair,
efficiency=None,
static_loss=None,
capacity=1,
capacity_is_instantaneous=False
)
# identify the node types
net.identify_node_types()
# assert that it can detected the selected antiparallel arcs
assert net.has_selected_antiparallel_arcs()
# check that it finds the right node pairs
identified_node_pairs = net.find_selected_antiparallel_arcs()
assert (node_a, node_b) in identified_node_pairs
assert (node_b, node_a) in identified_node_pairs
# *************************************************************************
# *************************************************************************
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# *****************************************************************************
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# *****************************************************************************