],
"Services": ["50", "51", "52", "64", "71t74", "H", "J", "M", "N", "O"],
}
for year in config.STUDY_YEARS:
path = fileutils.getcache("emissions_estimates_%d.csv" % year, "usa")
emissions_fh = open(path, "w")
emissions_csv = csv.writer(emissions_fh)
path = fileutils.getcache("fossil_fuel_estimates_%d.csv" % year, "usa")
energy_fh = open(path, "w")
energy_csv = csv.writer(energy_fh)
# yes hybrid, yes imports, no inflation
iogen = common.iogen_for_year(year, True, True)
# not hybrid, yes imports, yes inflation
iogen_normal = common.iogen_for_year(year, False, True, True)
pce = iogen_normal.get_Y(True).get_pce()
xn = iogen_normal.get_x(True)
A = iogen.get_A() # direct requirements
Z = iogen.get_Z()
hpce = iogen.get_Y().get_pce()
header = ["sector", "total"]
for source in eia.modified_sources:
if source in eia.conversion_factors:
# space labels out by at least 0.04 so they don't overlap
if prev_pos is not None and prev_pos - position < 0.03:
position = prev_pos - 0.03
plot.add_custom_setup(
"set label %d '%s' at graph 0.81, %.2f font 'Arial,8'"
% (i + 1, group_name, position))
prev_pos = position
plot.generate_plot()
for year in config.STUDY_YEARS:
# args: year, is_hybrid, allow_imports, adjust for inflation
iogen = common.iogen_for_year(year, True, True, True)
iogen_standard = common.iogen_for_year(year, False, True, True)
energy_codes = []
for i in range(len(eia.modified_sources)):
source = eia.modified_sources[i]
naics = eia.source_naics_map[source][year]
energy_codes.append(naics)
L = iogen.get_L()
Y = iogen.get_Y() # mixed units
###### hybrid vectors
import_colname = bea.fd_sectors[year]["imports"]
import_column = Y.get_named_column(import_colname)
"Services": [
"50", "51", "52", "64", "71t74", "H", "J", "M", "N", "O"],
}
for year in config.STUDY_YEARS:
path = fileutils.getcache("emissions_estimates_%d.csv" % year, "usa")
emissions_fh = open(path, "w")
emissions_csv = csv.writer(emissions_fh)
path = fileutils.getcache("fossil_fuel_estimates_%d.csv" % year, "usa")
energy_fh = open(path, "w")
energy_csv = csv.writer(energy_fh)
# yes hybrid, yes imports, no inflation
iogen = common.iogen_for_year(year, True, True)
# not hybrid, yes imports, yes inflation
iogen_normal = common.iogen_for_year(year, False, True, True)
pce = iogen_normal.get_Y(True).get_pce()
xn = iogen_normal.get_x(True)
A = iogen.get_A() # direct requirements
Z = iogen.get_Z()
hpce = iogen.get_Y().get_pce()
header = ["sector", "total"]
for source in eia.modified_sources:
if source in eia.conversion_factors:
