def print_result(result, minyear, maxyear):
data = {}
sort = {}
for row in result:
year = row[0]
industry = row[1]
value = row[2]
percent = row[3]
if industry not in data:
data[industry] = {}
data[industry][year] = (value, percent)
if year == maxyear:
sort[percent] = industry
for percent in sorted(sort.keys(), reverse=True):
industry = sort[percent]
if industry in sector_titles:
ind_name = sector_titles[industry]
elif "sec" + industry in sector_titles:
ind_name = sector_titles["sec" + industry]
else:
print(industry)
data_i = data[industry][minyear]
data_f = data[industry][maxyear]
if data_f[1] >= 1: # suppress sectors with <1% of total
print(ind_name.ljust(20) + " & %s & %.1f & %s & %.1f \\NN" %
(utils.add_commas(data_i[0]), data_i[1],
utils.add_commas(data_f[0]), data_f[1]))
def print_result(result, minyear, maxyear):
data = {}
sort = {}
for row in result:
year = row[0]
industry = row[1]
value = row[2]
percent = row[3]
if industry not in data:
data[industry] = {}
data[industry][year] = (value, percent)
if year == maxyear:
sort[percent] = industry
for percent in sorted(sort.keys(), reverse=True):
industry = sort[percent]
if industry in sector_titles:
ind_name = sector_titles[industry]
elif "sec" + industry in sector_titles:
ind_name = sector_titles["sec" + industry]
else:
print(industry)
data_i = data[industry][minyear]
data_f = data[industry][maxyear]
if data_f[1] >= 1: # suppress sectors with <1% of total
print(
ind_name.ljust(20) + " & %s & %.1f & %s & %.1f \\NN" %
(utils.add_commas(data_i[0]), data_i[1],
utils.add_commas(data_f[0]), data_f[1]))
def do_import_table():
minyear = min(config.STUDY_YEARS)
maxyear = max(config.STUDY_YEARS)
sector = 'CONS_h'
fd = {}
fd_imports = {}
for year in (minyear, maxyear):
strings = {
"schema": config.WIOD_SCHEMA,
"year": year,
}
stmt = db.prepare(
"""SELECT country, sum(value)
FROM %(schema)s.niot_%(year)d
WHERE to_ind = $1
AND is_import = $2
GROUP BY country""" % strings)
fd[year] = {}
fd_imports[year] = {}
for (country, value) in stmt(sector, True):
fd_imports[year][country] = value
fd[year][country] = value
for (country, value) in stmt(sector, False):
fd[year][country] += value
shares = {}
for (country, total) in fd[maxyear].items():
share = fd_imports[maxyear][country] / total
shares[share] = country
sorted_shares = sorted(shares.keys(), reverse=True)
midpoint = int(len(sorted_shares) / 2)
for i in range(midpoint):
values = []
for index in (i, i + midpoint):
country = shares[sorted_shares[index]]
minval = imfdata.convert_to_2005(
fd_imports[minyear][country], country, minyear)
maxval = imfdata.convert_to_2005(
fd_imports[maxyear][country], country, maxyear)
minshare = fd_imports[minyear][country] / fd[minyear][country]
maxshare = fd_imports[maxyear][country] / fd[maxyear][country]
values += [
config.countries[country],
utils.add_commas(minval), utils.add_commas(maxval),
"%.1f" % (minshare * 100), "%.1f" % (maxshare * 100),
""] # want blank space between two halves
values.pop() # remove trailing empty string
print(" & ".join(values) + " \\NN")
def get_key_title(self, key):
country = config.countries[key]
size = self.data["size"][key]
style = self.data["style"][key]
if style not in (5, 7, 9, 11, 13, 15):
size = -size
return "%s: %s" % (country, utils.add_commas(size))
def print_wiod_compare():
usa97 = wiod_comparison_data[1997]
usa02 = wiod_comparison_data[2002]
envgen97 = wiod.common.envgen_for_year(1997, ["FC_HH"])
envgen97.set_condition_args("USA")
wiod97 = envgen97.get_env_vector("CO2")
envgen02 = wiod.common.envgen_for_year(2002, ["FC_HH"])
envgen02.set_condition_args("USA")
wiod02 = envgen02.get_env_vector("CO2")
sectors = sorted(envgen97.get_sectors())
if "FC_HH" not in sectors:
sectors.append("FC_HH")
for sector in sectors:
short_sector = sector.replace("sec", "")
if short_sector in usa97:
label = wiod_code_map.sector_title(short_sector)
vals = []
vals.append(usa97[short_sector]["tons"] / 1000)
vals.append(wiod97.get_element(sector))
vals.append(usa02[short_sector]["tons"] / 1000)
vals.append(wiod02.get_element(sector))
row = [label] + [utils.add_commas(val) for val in vals]
print(" & ".join(row) + " \\NN")
def describe_balance_intensity():
export_total = export_balance.sum(0)
import_total = import_balance.sum(0)
all_total = all_E.sum(0)
balance = export_total.subtract(import_total)
balance_ratio = balance.divide(all_total)
country_name = config.countries[base_country]
years = [str(minyear), str(maxyear)]
fields = []
for y in years:
balance_val = balance.get_element("sum", y)
ratio_val = balance_ratio.get_element("sum", y)
(gdp_val, env_val, intensity) = \
common.get_efficiency(base_country, int(y))
if int(y) in balance_plots:
plot = balance_plots[int(y)]
# ratio = exports to imports
plot.set_value("2 ratio", base_country, ratio_val)
plot.set_value("1 intensity", base_country, intensity)
if int(y) in worldmap:
worldmap[int(y)].set_country_value(base_country, balance_val)
fields.append(utils.add_commas(balance_val))
fields.append("%.2f" % ratio_val)
fields.append("%.2f" % intensity)
print(country_name.ljust(15) + " & " + " & ".join(fields) + " \\NN")
def print_wiod_compare():
usa97 = wiod_comparison_data[1997]
usa02 = wiod_comparison_data[2002]
envgen97 = wiod.common.envgen_for_year(1997, ["FC_HH"])
envgen97.set_condition_args("USA")
wiod97 = envgen97.get_env_vector("CO2")
envgen02 = wiod.common.envgen_for_year(2002, ["FC_HH"])
envgen02.set_condition_args("USA")
wiod02 = envgen02.get_env_vector("CO2")
sectors = sorted(envgen97.get_sectors())
if "FC_HH" not in sectors:
sectors.append("FC_HH")
for sector in sectors:
short_sector = sector.replace("sec", "")
if short_sector in usa97:
label = wiod_code_map.sector_title(short_sector)
vals = []
vals.append(usa97[short_sector]["tons"] / 1000)
vals.append(wiod97.get_element(sector))
vals.append(usa02[short_sector]["tons"] / 1000)
vals.append(wiod02.get_element(sector))
row = [label] + [utils.add_commas(val) for val in vals]
print(" & ".join(row) + " \\NN")
def describe_balance_intensity():
export_total = export_balance.sum(0)
import_total = import_balance.sum(0)
all_total = all_E.sum(0)
balance = export_total.subtract(import_total)
balance_ratio = balance.divide(all_total)
country_name = config.countries[base_country]
years = [str(minyear), str(maxyear)]
fields = []
for y in years:
balance_val = balance.get_element("sum", y)
ratio_val = balance_ratio.get_element("sum", y)
(gdp_val, env_val, intensity) = \
common.get_efficiency(base_country, int(y))
if int(y) in balance_plots:
plot = balance_plots[int(y)]
# ratio = exports to imports
plot.set_value("2 ratio", base_country, ratio_val)
plot.set_value("1 intensity", base_country, intensity)
if int(y) in worldmap:
worldmap[int(y)].set_country_value(base_country, balance_val)
fields.append(utils.add_commas(balance_val))
fields.append("%.2f" % ratio_val)
fields.append("%.2f" % intensity)
print(country_name.ljust(15) + " & " + " & ".join(fields) + " \\NN")
def describe_balance(ratios=False):
export_total = export_balance.sum(0)
import_total = import_balance.sum(0)
all_total = all_E.sum(0)
balance = export_total.subtract(import_total)
country_name = config.countries[base_country]
oddyears = [
str(y) for y in filter(lambda x: x % 2 == 1, config.STUDY_YEARS)
]
if ratios:
balance_ratio = balance.divide(all_total)
print(
country_name.ljust(15) + " & " +
" & ".join([("%.2f" %
balance_ratio.get_element("sum", y)).rjust(6)
for y in oddyears]) + " \\\\")
else:
print(
country_name.ljust(15) + " & " + " & ".join([
utils.add_commas(balance.get_element("sum", y)).rjust(9)
for y in oddyears
]) + " \\\\")
def format_vals(i):
p = percents[i]
if p < 10:
spacer = " ~ "
else:
spacer = " "
return utils.add_commas(vals[i]) + \
spacer + ("(%.1f\\%%)" % p) + \
" & " + "%.3f" % ivals[i]
def format_vals(i):
p = percents[i]
if p < 10:
spacer = " ~ "
else:
spacer = " "
return utils.add_commas(vals[i]) + \
spacer + ("(%.1f\\%%)" % p) + \
" & " + "%.3f" % ivals[i]
def do_overview_table(sortby):
minyear = min(config.STUDY_YEARS)
maxyear = max(config.STUDY_YEARS)
data = {}
reverse_data = {}
for (country, name) in config.countries.items():
(env_i, gdp_i, intensity_i) = common.get_efficiency(
country, minyear, "env", "gdp")
(env_f, gdp_f, intensity_f) = common.get_efficiency(
country, maxyear, "env", "gdp")
if sortby == "growth":
pop_i = common.get_national_value(country, minyear, "pop")
pop_f = common.get_national_value(country, maxyear, "pop")
ppp_i = common.get_national_value(country, minyear, "ppppc")
ppp_f = common.get_national_value(country, maxyear, "ppppc")
percap_i = env_i / pop_i * 1000
percap_f = env_f / pop_f * 1000
growth = intensity_f - intensity_i
pgrowth = percap_f - percap_i
reverse_data[ppp_i] = name
data[name] = [
utils.add_commas(val).rjust(10) for val in (ppp_i, ppp_f)]
data[name] += [
"%.2f" % val for val in (intensity_i, intensity_f, growth,
percap_i, percap_f, pgrowth)]
else: # end year intensity
reverse_data[intensity_f] = name
data[name] = [
utils.add_commas(val).rjust(10)
for val in (gdp_i, gdp_f, env_i, env_f)]
data[name] += ["%.2f" % val for val in (intensity_i, intensity_f)]
for key in sorted(reverse_data.keys()):
country = reverse_data[key]
vals = data[country]
print(country.ljust(18) + " & " + " & ".join(vals) + " \\NN")
def print_co2_allyears():
headrow = ["sector"] + [str(year) for year in config.STUDY_YEARS]
print(" & ".join(headrow) + " \\\\")
for sector in sorted(wiod_code_map.codes.keys()):
row = [wiod_code_map.sector_title(sector)]
for year in config.STUDY_YEARS:
agg_data = wiod_comparison_data[year]
sector_data = agg_data[sector]
row.append(utils.add_commas(sector_data["tons"] / 1000))
#row.append(utils.add_commas(sector_data["dollars"]))
#row.append("%.3f" % (sector_data["tons"] / sector_data["dollars"]))
print(" & ".join(row) + " \\NN")
def print_co2_allyears():
headrow = ["sector"] + [str(year) for year in config.STUDY_YEARS]
print(" & ".join(headrow) + " \\\\")
for sector in sorted(wiod_code_map.codes.keys()):
row = [wiod_code_map.sector_title(sector)]
for year in config.STUDY_YEARS:
agg_data = wiod_comparison_data[year]
sector_data = agg_data[sector]
row.append(utils.add_commas(sector_data["tons"] / 1000))
#row.append(utils.add_commas(sector_data["dollars"]))
#row.append("%.3f" % (sector_data["tons"] / sector_data["dollars"]))
print(" & ".join(row) + " \\NN")
def print_table(vector, is_intensities):
for group in sorted(vector.keys()):
numerator = vector[group]
if is_intensities:
denominator = pce_dollars[group]
values = ["%.2f" % (numerator[year] / denominator[year] * 1000)
for year in config.STUDY_YEARS]
else:
values = [utils.add_commas(numerator[year])
for year in config.STUDY_YEARS]
print(group + " & " + " & ".join(values) + " \\NN")
def describe_balance(ratios=False):
export_total = export_balance.sum(0)
import_total = import_balance.sum(0)
all_total = all_E.sum(0)
balance = export_total.subtract(import_total)
country_name = config.countries[base_country]
oddyears = [str(y) for y in filter(lambda x: x % 2 == 1,
config.STUDY_YEARS)]
if ratios:
balance_ratio = balance.divide(all_total)
print(country_name.ljust(15) + " & " + " & ".join(
[("%.2f" % balance_ratio.get_element("sum", y)).rjust(6)
for y in oddyears]) + " \\\\")
else:
print(country_name.ljust(15) + " & " + " & ".join(
[utils.add_commas(balance.get_element("sum", y)).rjust(9)
for y in oddyears]) + " \\\\")
def do_kyoto_table():
minyear = min(config.STUDY_YEARS)
maxyear = max(config.STUDY_YEARS)
minstrings = {
"schema": config.WIOD_SCHEMA,
"year": minyear,
"fd_sectors": sqlhelper.set_repr(config.default_fd_sectors),
}
maxstrings = minstrings.copy()
maxstrings["year"] = maxyear
envsql = """SELECT value FROM %(schema)s.env_%(year)d
WHERE country = $1 AND measurement = $2
AND industry = 'total'"""
envstmt_i = db.prepare(envsql % minstrings)
envstmt_f = db.prepare(envsql % maxstrings)
un_stmt = db.prepare(
"SELECT value FROM %s.mdg_emissions" % config.UN_SCHEMA +
" WHERE country = $1 AND year = $2")
data = {}
(eu_i, eu_f, un_eu_90, un_eu_i, un_eu_f) = (0, 0, 0, 0, 0)
for (country, name) in config.countries.items():
env_i = envstmt_i(country, "CO2")[0][0]
env_f = envstmt_f(country, "CO2")[0][0]
percent = (env_f - env_i) / env_i * 100
(un_env_90, un_env_91, un_env_i, un_env_f,
un_percent, un_percent_90) = \
(0, 0, 0, 0, None, None)
result = un_stmt(country, 1990)
if len(result):
un_env_90 = result[0][0]
else:
# use 1991 as a proxy for 1990 for some countries if applicable
# germany is the only annex b country that is applicable
# so hopefully it won't mess up eu15 calculation too much
result = un_stmt(country, 1991)
if len(result):
un_env_91 = result[0][0]
result = un_stmt(country, minyear)
if len(result):
un_env_i = result[0][0]
result = un_stmt(country, maxyear)
if len(result):
un_env_f = result[0][0]
if un_env_i and un_env_f:
un_percent = (un_env_f - un_env_i) / un_env_i * 100
if un_env_90 and un_env_f:
un_percent_90 = (un_env_f - un_env_90) / un_env_90 * 100
data[country] = (env_i, env_f, percent, un_percent, un_percent_90)
if country in config.eu15:
eu_i += env_i
eu_f += env_f
un_eu_i += un_env_i
un_eu_f += un_env_f
if un_env_90:
un_eu_90 += un_env_90
else:
un_eu_90 += un_env_91
eu_percent = (eu_f - eu_i) / eu_i * 100
un_eu_percent = (un_eu_f - un_eu_i) / un_eu_i * 100
un_eu_percent_90 = (un_eu_f - un_eu_90) / un_eu_90 * 100
print("%s & %s & %s & %d\\%% & %.1f\\%% & %.1f\\%% & %.1f \\NN" %
("EU-15".ljust(18),
utils.add_commas(eu_i).rjust(9),
utils.add_commas(eu_f).rjust(9),
-8, eu_percent, un_eu_percent, un_eu_percent_90))
for (target, countries) in config.annex_b_countries.items():
for country in countries:
vals = data[country]
if vals[4] is None:
percent_90 = ""
else:
percent_90 = "%.1f" % vals[4]
print("%s & %s & %s & %d\\%% & %.1f\\%% & %.1f & %s \\NN" %
(config.countries[country].ljust(18),
utils.add_commas(vals[0]).rjust(9),
utils.add_commas(vals[1]).rjust(9),
target, vals[2], vals[3], percent_90))
