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remove redundant code
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@j-bryan
j-bryan committed Dec 4, 2024
1 parent 816f5d4 commit b40ed92
Showing 1 changed file with 0 additions and 172 deletions.
172 changes: 0 additions & 172 deletions templates/bilevel_templates.py
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Original file line number Diff line number Diff line change
Expand Up @@ -144,30 +144,6 @@ def __init__(self):
self._dispatch_results_name = "" # str, keeps track of the name of the Database or OutStream used pass dispatch
# data to the outer workflow

# def createWorkflow(self, case, components, sources) -> None:
# super().createWorkflow(case, components, sources)
# # FIXME Assume synthetic histories for now but could be multiple static histories

# # Collect relevant variables before we start adding names/parameters/nodes to various parts of the XML
# cap_vars = get_capacity_vars(components, self.namingTemplate["variable"]) # dict[str, valued param]
# disp_vars = get_dispatch_vars(components, self.namingTemplates["dispatch"]) # list[str]

# # Fill out variable names for final_return variable group
# results_vargroup = self._template.find("GRO_final_return")
# results_vars = self._get_statistical_results_vars(case, components)
# results_vargroup.add_variables(*results_vars)

# # For all ARMA sources, create a model node for the accompanying pickled ROM, add that ROM to the ensemble model,
# # and create steps to load the model and write its metadata.
# self._add_time_series_roms(case, sources)

# # For
# self._modify_components(case, components)
# self._modify_case_labels(case.get_labels())
# self._modify_time_vars(case.get_time_name(), case.get_year_name())
# self._modify_econ_metrics(case, components)
# self._modify_result_statistics(case, components)

def createWorkflow(self, case, components, sources) -> None:
super().createWorkflow(case, components, sources)

Expand Down Expand Up @@ -366,74 +342,6 @@ def _add_time_series_roms(self, case: Case, sources: list[Placeholder]):
vg_dispatch.add_variables(self.namingTemplates["cluster_index"])
dispatch_eval.add_index(self.namingTemplates["cluster_index"], "GRO_dispatch_in_Time")

def _modify_components(self, case: Case, components: list[Component]):
"""
Modify variable groups and the Monte Carlo sampler to include capacity and dispatch variables
"""
mc = self._template.find("Samplers/MonteCarlo[@name='mc_arma_dispatch']")
vg_capacities = self._template.find("VariableGroups/Group[@name='GRO_capacities']")
vg_init_disp = self._template.find("VariableGroups/Group[@name='GRO_init_disp']")
vg_full_disp = self._template.find("VariableGroups/Group[@name='GRO_full_dispatch']")

# change inner input due to components requested
for component in components:
name = component.name
# treat capacity
## we just need to make sure everything we need gets into the dispatch ensemble model.
## For each interaction of each component, that means making sure the Function, ARMA, or constant makes it.
## Constants from outer (namely sweep/opt capacities) are set in the MC Sampler from the outer
## The Dispatch needs info from the Outer to know which capacity to use, so we can't pass it from here.
capacity = component.get_capacity(None, raw=True)

if capacity.is_parametric():
# this capacity is being [swept or optimized in outer] (list) or is constant (float)
# -> so add a node, put either the const value or a dummy in place
cap_name = self.namingTemplates['variable'].format(unit=name, feature='capacity')
values = capacity.get_value(debug=case.debug['enabled'])
if isinstance(values, list):
cap_val = 42 # placeholder
else:
cap_val = values
mc.add_constant(cap_name, cap_val)
# add component to applicable variable groups
vg_capacities.add_variables(cap_name)
elif capacity.type in ['StaticHistory', 'SyntheticHistory', 'Function', 'Variable']:
# capacity is limited by a signal, so it has to be handled in the dispatch; don't include it here.
# OR capacity is limited by a function, and we also can't handle it here, but in the dispatch.
pass
else:
raise NotImplementedError(f'Capacity from "{capacity}" not implemented yet. Component: {cap_name}')

for tracker in component.get_tracking_vars():
resource_list = sorted(list(component.get_resources()))
for resource in resource_list:
var_name = self.namingTemplates['dispatch'].format(component=name, tracker=tracker, resource=resource)
vg_init_disp.add_variables(var_name)
vg_full_disp.add_variables(var_name)

def _modify_econ_metrics(self, case: Case, components: list[Component]) -> None:
"""
Modifies template to include economic metrics
@ In, case, HERON Case, defining Case instance
@ In, components, list[Component], case components
@ Out, None
"""
# get all economic metrics intended for use in TEAL and reported back
econ_metrics = case.get_econ_metrics(nametype='output')
tot_act_vars = self._get_activity_metrics(components)

# find variable groups to update with economic metrics
dispatch_out = self._template.find("VariableGroups/Group[@name='GRO_dispatch_out']")
arma_samp_out = self._template.find("VariableGroups/Group[@name='GRO_armasamples_out_scalar']")
# find point set output node to update with economic metrics
arma_metrics = self._template.find("DataObjects/PointSet[@name='arma_metrics']")

# update fields with econ metric names
metrics = econ_metrics + tot_act_vars
dispatch_out.add_variables(*metrics)
arma_samp_out.add_variables(*metrics)
arma_metrics.add_outputs(*metrics)

def _add_uncertain_cashflow_params(self, components) -> None:
cf_attrs = ["_driver", "_alpha", "_reference", "_scale"]

Expand Down Expand Up @@ -469,86 +377,6 @@ def _add_uncertain_cashflow_params(self, components) -> None:
sampler_var.set_distribution(dist_snippet)
mc.add_variable(sampler_var)

def _modify_inner_result_statistics(self, template, case, components):
"""
Modifies template to include result statistics
@ In, template, xml.etree.ElementTree.Element, root of XML to modify
@ In, case, HERON Case, defining Case instance
@ Out, None
"""
# final return variable group (sent to outer)
group_final_return = self._create_statistical_results_vargroup("GRO_final_return")

# fill out PostProcessor nodes
pp_node = template.find('Models').find(".//PostProcessor[@name='statistics']")
# add default statistics
result_statistics = case.get_result_statistics() # list of stats beyond default
tot_act_vars = []
for component in components:
for tracker in component.get_tracking_vars():
resource_list = np.sort(list(component.get_resources()))
for resource in resource_list:
tot_act_var = "TotalActivity"+ "__" +component.name + "__" + tracker + "__" + resource
tot_act_vars.append(tot_act_var)
for var in tot_act_vars:
for stat, pref in zip(DEFAULT_STATS_NAMES, default_stats_prefixes):
pp_node.append(xmlUtils.newNode(stat, text=var, attrib={'prefix': pref}))

for em in econ_metrics + tot_act_vars:
for stat, pref in zip(DEFAULT_STATS_NAMES, default_stats_prefixes):
pp_node.append(xmlUtils.newNode(stat, text=em, attrib={'prefix': pref}))
# add any user supplied statistics beyond defaults
if any(stat not in DEFAULT_STATS_NAMES + default_stats_tot_act for stat in result_statistics):
for raven_metric_name in result_statistics:
if raven_metric_name not in DEFAULT_STATS_NAMES:
prefix = self._get_stats_metrics_prefixes(case, [raven_metric_name], use_extra=False)[0]
# add subnode to PostProcessor
if raven_metric_name == 'percentile':
# add percent attribute
percent = result_statistics[raven_metric_name]
if isinstance(percent, list):
for p in percent:
pp_node.append(xmlUtils.newNode(raven_metric_name, text=em,
attrib={'prefix': prefix,
'percent': p}))
else:

pp_node.append(xmlUtils.newNode(raven_metric_name, text=em,
attrib={'prefix': prefix,
'percent': percent}))
elif raven_metric_name in ['valueAtRisk', 'expectedShortfall', 'sortinoRatio', 'gainLossRatio']:
threshold = result_statistics[raven_metric_name]
if isinstance(threshold, list):
for t in threshold:
if not em.startswith("TotalActivity"):
pp_node.append(xmlUtils.newNode(raven_metric_name, text=em,
attrib={'prefix': prefix,
'threshold': t}))
else:
if not em.startswith("TotalActivity"):
pp_node.append(xmlUtils.newNode(raven_metric_name, text=em,
attrib={'prefix': prefix,
'threshold': threshold}))
else:
if not em.startswith("TotalActivity"):
pp_node.append(xmlUtils.newNode(raven_metric_name, text=em,
attrib={'prefix': prefix}))
if em.startswith("TotalActivity"):
if prefix not in FINANCIAL_PREFIXES:
pp_node.append(xmlUtils.newNode(raven_metric_name, text=em,
attrib={'prefix': prefix}))

# if not specified, "sweep" mode has additional defaults
elif case.get_mode() == 'sweep':
sweep_stats_prefixes = self._get_stats_metrics_prefixes(case, SWEEP_DEFAULT_STATS_NAMES, use_extra=False)
for em in econ_metrics:
for stat, pref in zip(SWEEP_DEFAULT_STATS_NAMES, sweep_stats_prefixes):
pp_node.append(xmlUtils.newNode(stat, text=em, attrib={'prefix': pref}))
for var in tot_act_vars:
for stat, pref in zip(SWEEP_DEFAULT_STATS_NAMES, sweep_stats_prefixes):
pp_node.append(xmlUtils.newNode(stat, text=var, attrib={'prefix': pref}))
# if not specified, "opt" mode is handled in _modify_inner_optimization_settings

@staticmethod
def _add_stats_to_postprocessor(pp, names, vars, meta) -> None:
# for stat_name, var_name in itertools.product(names, vars):
Expand Down

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