def _ensure_itree_codes_fetched():
global _itree_codes_by_region, _all_itree_codes
if _itree_codes_by_region is None:
result, err = ecobackend.json_benefits_call("itree_codes.json", {})
if err:
raise Exception("Failed to retrieve i-Tree codes from ecoservice")
_itree_codes_by_region = result["Codes"]
_all_itree_codes = set(itertools.chain(*_itree_codes_by_region.values()))
def _run_model(instance, growth_model, scenario, region_code):
n_years = scenario['years']
yearly_counts, planted_trees = growth_model.run(scenario)
eco_trees = _model_trees_to_eco_trees(planted_trees, region_code)
eco_input = {
'region': region_code,
'instance_id': str(instance.id),
'years': n_years,
'scenario_trees': eco_trees
}
eco, err = ecobackend.json_benefits_call('eco_scenario.json',
eco_input,
post=True,
convert_params=False)
if err:
raise Exception(err)
total_eco = compute_currency_and_transform_units(instance, eco['Total'])
total_eco = format_benefits(instance, total_eco, None, digits=0)
currency_symbol = total_eco['currency_symbol']
total_eco = _list_for_display(total_eco['benefits'])
yearly_eco = [
compute_currency_and_transform_units(instance, benefits)
for benefits in eco['Years']
]
yearly_eco = [_list_for_display(benefits) for benefits in yearly_eco]
yearly_eco_condensed = yearly_eco[0]
for i in range(0, len(yearly_eco_condensed)):
yearly_eco_condensed[i] = {
'label': yearly_eco_condensed[i]['label'],
'unit': yearly_eco_condensed[i]['unit'],
'values': [benefits[i]['value'] for benefits in yearly_eco],
'currencies': [benefits[i]['currency'] for benefits in yearly_eco]
}
year_headers = [_('Year %(n)s' % {'n': i}) for i in range(1, n_years + 1)]
growth_csv_data = _growth_csv_data(instance, year_headers, planted_trees)
return {
'years': n_years,
'yearly_counts': yearly_counts,
'total_eco': total_eco,
'yearly_eco': yearly_eco_condensed,
'currency_symbol': currency_symbol,
'currency_axis_label': "%s %s" % (currency_symbol, _('saved')),
'eco_csv_header': _eco_csv_header(year_headers),
'growth_csv_data': growth_csv_data,
}
def invalidate_ecoservice_cache_if_stale():
from treemap import ecobackend
global my_itree_code_override_rev
cached_rev = _init_if_needed()
if my_itree_code_override_rev != cached_rev:
__, err = ecobackend.json_benefits_call('invalidate_cache', {})
if err:
raise Exception('Failed to invalidate ecoservice cache')
my_itree_code_override_rev = cached_rev
def _ensure_itree_codes_fetched():
global _itree_codes_by_region, _all_itree_codes
if _itree_codes_by_region is None:
result, err = ecobackend.json_benefits_call('itree_codes.json', {})
if err:
raise Exception('Failed to retrieve i-Tree codes from ecoservice')
_itree_codes_by_region = result['Codes']
_all_itree_codes = set(
itertools.chain(*_itree_codes_by_region.values()))
def _run_model(instance, growth_model, scenario, region_code):
n_years = scenario['years']
yearly_counts, planted_trees = growth_model.run(scenario)
eco_trees = _model_trees_to_eco_trees(planted_trees, region_code)
eco_input = {
'region': region_code,
'instance_id': str(instance.id),
'years': n_years,
'scenario_trees': eco_trees
}
eco, err = ecobackend.json_benefits_call('eco_scenario.json',
eco_input,
post=True,
convert_params=False)
if err:
raise Exception(err)
total_eco = compute_currency_and_transform_units(instance, eco['Total'])
total_eco = format_benefits(instance, total_eco, None, digits=0)
currency_symbol = total_eco['currency_symbol']
total_eco = _list_for_display(total_eco['benefits'])
yearly_eco = [compute_currency_and_transform_units(instance, benefits)
for benefits in eco['Years']]
yearly_eco = [_list_for_display(benefits) for benefits in yearly_eco]
yearly_eco_condensed = yearly_eco[0]
for i in range(0, len(yearly_eco_condensed)):
yearly_eco_condensed[i] = {
'label': yearly_eco_condensed[i]['label'],
'unit': yearly_eco_condensed[i]['unit'],
'values': [benefits[i]['value'] for benefits in yearly_eco],
'currencies': [benefits[i]['currency'] for benefits in yearly_eco]
}
year_headers = [_('Year %(n)s' % {'n': i}) for i in range(1, n_years + 1)]
growth_csv_data = _growth_csv_data(instance, year_headers, planted_trees)
return {
'years': n_years,
'yearly_counts': yearly_counts,
'total_eco': total_eco,
'yearly_eco': yearly_eco_condensed,
'currency_symbol': currency_symbol,
'currency_axis_label': "%s %s" % (currency_symbol, _('saved')),
'eco_csv_header': _eco_csv_header(year_headers),
'growth_csv_data': growth_csv_data,
}
def benefits_for_object(self, instance, plot):
tree = plot.current_tree()
error = None
if tree is None:
rslt = None
error = 'NO_TREE'
elif not tree.diameter:
rslt = None
error = 'MISSING_DBH'
elif not tree.species:
rslt = None
error = 'MISSING_SPECIES'
else:
region_code = plot.itree_region.code
if region_code:
params = {
'otmcode': tree.species.otm_code,
'diameter': tree.diameter,
'region': region_code,
'instanceid': instance.pk,
'speciesid': tree.species.pk
}
rawb, err = ecobackend.json_benefits_call(
'eco.json', params.iteritems())
if err:
rslt = {'error': err}
error = err
else:
benefits = compute_currency_and_transform_units(
instance, rawb['Benefits'])
rslt = benefits
else:
rslt = None
error = 'MISSING_REGION'
basis = {
'plot': {
'n_objects_used': 1 if rslt else 0,
'n_objects_discarded': 0 if rslt else 1
}
}
return (rslt, basis, error)
def tree_benefits(instance, tree_or_tree_id):
"""Given a tree id, determine eco benefits via eco.py"""
if isinstance(tree_or_tree_id, int):
InstanceTree = instance.scope_model(Tree)
tree = get_object_or_404(InstanceTree, pk=tree_or_tree_id)
else:
tree = tree_or_tree_id
if not tree.diameter:
rslt = {'tree_benefits': {}, 'error': 'MISSING_DBH'}
elif not tree.species:
rslt = {'tree_benefits': {}, 'error': 'MISSING_SPECIES'}
else:
if instance.itree_region_default:
region = instance.itree_region_default
else:
regions = ITreeRegion.objects\
.filter(geometry__contains=tree.plot.geom)
if len(regions) > 0:
region = regions[0].code
else:
region = None
if region:
params = {'otmcode': tree.species.otm_code,
'diameter': tree.diameter,
'region': region,
'instanceid': instance.pk,
'speciesid': tree.species.pk}
rawb, err = ecobackend.json_benefits_call(
'eco.json', params.iteritems())
if err:
rslt = {'error': err}
else:
benefits, _ = _compute_currency_and_transform_units(
instance, rawb['Benefits'])
rslt = {'tree_benefits': benefits}
else:
rslt = {'tree_benefits': {}, 'error': 'MISSING_REGION'}
return rslt
def benefits_for_object(self, instance, plot):
tree = plot.current_tree()
error = None
if tree is None:
rslt = None
error = 'NO_TREE'
elif not tree.diameter:
rslt = None
error = 'MISSING_DBH'
elif not tree.species:
rslt = None
error = 'MISSING_SPECIES'
else:
region_code = plot.itree_region.code
if region_code:
params = {'otmcode': tree.species.otm_code,
'diameter': tree.diameter,
'region': region_code,
'instanceid': instance.pk,
'speciesid': tree.species.pk}
rawb, err = ecobackend.json_benefits_call(
'eco.json', params.iteritems())
if err:
rslt = {'error': err}
error = err
else:
benefits = compute_currency_and_transform_units(
instance, rawb['Benefits'])
rslt = benefits
else:
rslt = None
error = 'MISSING_REGION'
basis = {'plot':
{'n_objects_used': 1 if rslt else 0,
'n_objects_discarded': 0 if rslt else 1}}
return (rslt, basis, error)
def benefits_for_object(self, instance, plot):
tree = plot.current_tree()
error = None
if tree is None:
rslt = None
error = "NO_TREE"
elif not tree.diameter:
rslt = None
error = "MISSING_DBH"
elif not tree.species:
rslt = None
error = "MISSING_SPECIES"
else:
region_code = plot.itree_region.code
if region_code:
params = {
"otmcode": tree.species.otm_code,
"diameter": tree.diameter,
"region": region_code,
"instanceid": instance.pk,
"speciesid": tree.species.pk,
}
rawb, err = ecobackend.json_benefits_call("eco.json", params.iteritems())
if err:
rslt = {"error": err}
error = err
else:
benefits = compute_currency_and_transform_units(instance, rawb["Benefits"])
rslt = benefits
else:
rslt = None
error = "MISSING_REGION"
basis = {"plot": {"n_objects_used": 1 if rslt else 0, "n_objects_discarded": 0 if rslt else 1}}
return (rslt, basis, error)
def benefits_for_filter(self, instance, item_filter):
from treemap.models import Plot, Tree
instance = item_filter.instance
plots = item_filter.get_objects(Plot)
trees = Tree.objects.filter(plot__in=plots)
n_total_trees = trees.count()
if not instance.has_itree_region():
basis = {'plot':
{'n_objects_used': 0,
'n_objects_discarded': n_total_trees}}
return ({}, basis)
if n_total_trees == 0:
basis = {'plot':
{'n_objects_used': 0,
'n_objects_discarded': n_total_trees}}
empty_rslt = compute_currency_and_transform_units(
instance, {})
return (empty_rslt, basis)
# When calculating benefits we can skip region information
# if there is only one intersecting region or if the
# instance forces a region on us
regions = instance.itree_regions()
if len(regions) == 1:
region_code = regions[0].code
else:
region_code = None
# We want to do a values query that returns the info that
# we need for an eco calculation:
# diameter, species id and species code
#
# The species id is used to find potential overrides
values = ('diameter',
'species__pk',
'species__otm_code',)
# If there isn't a single region we need to
# include geometry information
if not region_code:
values += ('plot__geom',)
# We use two extra instance filter to help out
# the database a bit when doing the joins
treeValues = trees.filter(species__isnull=False)\
.filter(diameter__isnull=False)\
.filter(plot__instance=instance)\
.filter(species__instance=instance)\
.values_list(*values)
query = self._make_sql_from_query(treeValues.query)
# We want to extract x and y coordinates but django
# doesn't make this easy since we need to force a join
# on plot/mapfeature. To make sure the djago machinery
# does that we use "plot__geom" above and then
# do this rather dubious string manipulation below
if not region_code:
targetGeomField = '"treemap_mapfeature"."the_geom_webmercator"'
xyGeomFields = 'ST_X(%s), ST_Y(%s)' % \
(targetGeomField, targetGeomField)
query = query.replace(targetGeomField, xyGeomFields, 1)
params = {'query': query,
'instance_id': instance.pk,
'region': region_code or ""}
rawb, err = ecobackend.json_benefits_call(
'eco_summary.json', params.iteritems(), post=True)
if err:
raise Exception(err)
benefits = rawb['Benefits']
if 'n_trees' in benefits:
n_computed_trees = int(benefits['n_trees'])
else:
n_computed_trees = 1
# Extrapolate an average over the rest of the urban forest
if n_computed_trees > 0 and n_total_trees > 0:
percent = float(n_computed_trees) / n_total_trees
for key in benefits:
benefits[key] /= percent
rslt = compute_currency_and_transform_units(instance, benefits)
basis = {'plot':
{'n_objects_used': n_computed_trees,
'n_objects_discarded': n_total_trees - n_computed_trees}}
return (rslt, basis)
def benefits_for_trees(trees, instance):
# When calculating benefits we can skip region information
# if there is only one intersecting region or if the
# instance forces a region on us
region = None
if instance.itree_region_default:
region = instance.itree_region_default
else:
regions = ITreeRegion.objects.filter(
geometry__intersects=instance.bounds)
if regions.length() == 1:
region = regions[0].code
# We want to do a values query that returns the info that
# we need for an eco calculation:
# diameter, species id and species code
#
# The species id is used to find potential overrides
values = ('diameter',
'species__pk',
'species__otm_code',)
# If there isn't a single region we need to
# include geometry information
if not region:
values += ('plot__geom',)
# We use two extra instance filter to help out
# the database a bit when doing the joins
treeValues = trees.filter(species__isnull=False)\
.filter(diameter__isnull=False)\
.filter(plot__instance=instance)\
.filter(species__instance=instance)\
.values_list(*values)
query = _make_sql_from_query(treeValues.query)
# We want to extract x and y coordinates but django
# doesn't make this easy since we need to force a join
# on plot/mapfeature. To make sure the djago machinery
# does that we use "plot__geom" above and then
# do this rather dubious string manipulation below
if not region:
targetGeomField = '"treemap_mapfeature"."the_geom_webmercator"'
xyGeomFields = 'ST_X(%s), ST_Y(%s)' % \
(targetGeomField, targetGeomField)
query = query.replace(targetGeomField, xyGeomFields, 1)
params = {'query': query,
'instance_id': instance.pk,
'region': region or ""}
rawb, err = ecobackend.json_benefits_call(
'eco_summary.json', params.iteritems(), post=True)
if err:
raise Exception(err)
benefits = rawb['Benefits']
return _compute_currency_and_transform_units(instance, benefits)
def benefits_for_filter(self, instance, item_filter):
from treemap.models import Plot, Tree
instance = item_filter.instance
plots = item_filter.get_objects(Plot)
trees = Tree.objects.filter(plot__in=plots)
n_total_trees = trees.count()
if not instance.has_itree_region():
basis = {'plot':
{'n_objects_used': 0,
'n_objects_discarded': n_total_trees}}
return ({}, basis)
if n_total_trees == 0:
basis = {'plot':
{'n_objects_used': 0,
'n_objects_discarded': n_total_trees}}
empty_rslt = compute_currency_and_transform_units(
instance, {})
return (empty_rslt, basis)
# When calculating benefits we can skip region information
# if there is only one intersecting region or if the
# instance forces a region on us
regions = instance.itree_regions()
if len(regions) == 1:
region_code = regions[0].code
else:
region_code = None
# We want to do a values query that returns the info that
# we need for an eco calculation:
# diameter, species id and species code
#
# The species id is used to find potential overrides
values = ('diameter',
'species__pk',
'species__otm_code',)
# If there isn't a single region we need to
# include geometry information
if not region_code:
values += ('plot__geom',)
# We use two extra instance filter to help out
# the database a bit when doing the joins
treeValues = trees.filter(species__isnull=False)\
.filter(diameter__isnull=False)\
.filter(plot__instance=instance)\
.filter(species__instance=instance)\
.values_list(*values)
query = self._make_sql_from_query(treeValues.query)
# We want to extract x and y coordinates but django
# doesn't make this easy since we need to force a join
# on plot/mapfeature. To make sure the djago machinery
# does that we use "plot__geom" above and then
# do this rather dubious string manipulation below
if not region_code:
targetGeomField = '"treemap_mapfeature"."the_geom_webmercator"'
xyGeomFields = 'ST_X(%s), ST_Y(%s)' % \
(targetGeomField, targetGeomField)
query = query.replace(targetGeomField, xyGeomFields, 1)
params = {'query': query,
'instance_id': instance.pk,
'region': region_code or ""}
rawb, err = ecobackend.json_benefits_call(
'eco_summary.json', params.iteritems(), post=True)
if err:
raise Exception(err)
benefits = rawb['Benefits']
if 'n_trees' in benefits:
n_computed_trees = int(benefits['n_trees'])
else:
n_computed_trees = 1
# Extrapolate an average over the rest of the urban forest
if n_computed_trees > 0 and n_total_trees > 0:
percent = float(n_computed_trees) / n_total_trees
for key in benefits:
benefits[key] /= percent
rslt = compute_currency_and_transform_units(instance, benefits)
basis = {'plot':
{'n_objects_used': n_computed_trees,
'n_objects_discarded': n_total_trees - n_computed_trees}}
return (rslt, basis)
