def agency_table_by_indicator(request, indicator, language="English", template_name="submissions/agency_table_by_indicator.html", extra_context=None):
dp_gov_map = {
"1DP" : "1G",
"2DPa" : "2Ga",
"2DPb" : "2Gb",
"3DP" : "3G",
"4DP" : "4G",
"5DPa" : "5Gb",
"5DPb" : "5Ga",
"6DP" : "6G",
"7DP" : "7G",
"8DP" : "8G",
}
extra_context = extra_context or {}
extra_context["translation"] = request.translation
country_calcs = None
countries = models.Country.objects.all().order_by("country")
if indicator in dp_gov_map:
gov_indicator = dp_gov_map[indicator]
country_calcs = [(c, target.calc_country_ratings(c)[gov_indicator]) for c in countries]
agencies = []
for agency in models.Agency.objects.all():
agency_values = []
for country in countries:
if country in agency.countries:
inds = indicators.calc_agency_country_indicators(agency, country, indicators.positive_funcs)
ratings = target.country_agency_indicator_ratings(country, agency)
base_val, base_year, latest_val, cur_year = inds[indicator][0]
country_abs_values = {
"baseline_value" : tbl_float_format(base_val),
"base_year" : base_year,
"latest_value" : tbl_float_format(latest_val),
"cur_year" : cur_year,
"rating" : ratings[indicator],
"cellclass" : "",
}
else:
country_abs_values = {
"baseline_value" : "",
"base_year" : "",
"latest_value" : "",
"cur_year" : "",
"rating" : "",
"cellclass" : "notactive",
}
agency_values.append((country, country_abs_values))
agency_values = sorted(agency_values, key=lambda x: x[0].country)
agencies.append((agency, agency_values))
agencies = sorted(agencies, key=lambda x: x[0].agency)
extra_context["agencies"] = agencies
extra_context["countries"] = countries
extra_context["country_calcs"] = country_calcs
return direct_to_template(request, template=template_name, extra_context=extra_context)
def country_table(request, language="English", template_name="submissions/country_table.html", extra_context=None):
extra_context = extra_context or {}
extra_context["translation"] = translation = request.translation
abs_values = {}
for country in models.Country.objects.all().order_by("country"):
country_abs_values = {}
country_ratings = target.calc_country_ratings(country)
inds = indicators.calc_country_indicators(country, indicators.positive_funcs)
for indicator in inds:
tpl = inds[indicator][0]
base_val, base_year, latest_val, latest_year = tpl
rating = country_ratings[indicator]["target"]
if type(base_val) == str: base_val = base_val.upper()
if type(latest_val) == str: latest_val = latest_val.upper()
if indicator == "2Gb":
# The indicator turns this into 100/0
# This code turns it back - to much effort
# to figure out why it does this
base_val = "Y" if base_val == 100 else "N"
latest_val = "Y" if latest_val == 100 else "N"
if indicator == "2Ga":
base_val1 = base_val[0] if base_val else None
base_val2 = base_val[1] if base_val else None
latest_val1 = latest_val[0] if latest_val else None
latest_val2 = latest_val[1] if latest_val else None
country_abs_values["2Ga1"] = (
tbl_float_format(base_val1),
tbl_float_format(latest_val1),
None,
base_year,
rating
)
country_abs_values["2Ga2"] = (
tbl_float_format(base_val2),
tbl_float_format(latest_val2),
None,
base_year,
rating,
)
else:
decimal_places = {
"5Ga" : 1
}
places = decimal_places.get(indicator, 0)
country_abs_values[indicator] = (
tbl_float_format(base_val, places),
tbl_float_format(latest_val, places),
tbl_float_format(perc_change(base_val, latest_val), places),
base_year,
rating
)
abs_values[country.country] = country_abs_values
extra_context["abs_values"] = sorted(abs_values.items())
extra_context["spm_map"] = translation.gov_spm_map
return direct_to_template(request, template=template_name, extra_context=extra_context)
def country_response_breakdown(
request, template_name="submissions/country_response_breakdown.html", extra_context=None
):
"""
Return a histogram of responses for each country indicator
"""
extra_context = extra_context or {}
is_na = lambda r: r["target"] == Rating.NONE
is_question = lambda r: r["target"] == Rating.QUESTION
is_response = lambda r: not (is_na(r) or is_question(r))
countries = Country.objects.all()
counts = defaultdict(int, {})
for country in countries:
results = calc_country_ratings(country)
for indicator in g_indicators:
counts["%s_na" % indicator] += 1 if is_na(results[indicator]) else 0
counts["%s_question" % indicator] += 1 if is_question(results[indicator]) else 0
counts["%s_response" % indicator] += 1 if is_response(results[indicator]) else 0
counts["%s_total" % indicator] += 1
extra_context["counts"] = counts
return direct_to_template(request, template=template_name, extra_context=extra_context)
def get_country_export_data(country, language=None):
"""
Return all the data that is required for the country scorecard
"""
language = language or models.Language.objects.get(language="English")
translation = translations.get_translation(language)
data = target.calc_country_ratings(country, language)
data["questions"] = get_country_questions(country)
data["agencies"] = get_agency_values(country)
data["indicators"] = get_country_indicators(country, data["questions"], data["agencies"])
data["np"], data["p"] = target.get_agency_progress(country)
ratings, _ = models.GovScorecardRatings.objects.get_or_create(country=country)
comments_override, _ = models.CountryScorecardOverrideComments.objects.get_or_create(
country=country, language=language
)
try:
data["ER1a"] = data["1G"]["target"]
data["ER1b"] = data["1G"]["commentary"]
data["ER2a"] = data["2Ga"]["target"]
data["ER2b"] = data["2Ga"]["commentary"]
data["ER3a"] = data["2Gb"]["target"]
data["ER3b"] = data["2Gb"]["commentary"]
data["ER4a"] = data["3G"]["target"]
data["ER4b"] = data["3G"]["commentary"]
data["ER4c"] = country.country
data["ER5a"] = data["4G"]["target"]
data["ER5b"] = data["4G"]["commentary"]
data["ER6a"] = data["5Ga"]["target"]
data["ER6b"] = data["5Ga"]["commentary"]
data["ER7a"] = data["5Gb"]["target"]
data["ER7b"] = data["5Gb"]["commentary"]
data["ER8a"] = data["6G"]["target"]
data["ER8b"] = data["6G"]["commentary"]
data["ER9a"] = data["7G"]["target"]
data["ER9b"] = data["7G"]["commentary"]
data["ER10a"] = data["8G"]["target"]
data["ER10b"] = data["8G"]["commentary"]
data["file"] = country.country
data["TB2"] = translation.gov_tb2 % country.country.upper()
data["CD1"] = data["ER1a"]
data["CD2"] = comments_override.cd2 or data["questions"]["1"]["comments"]
data["HSP1"] = ratings.hsp1 or data["Q2G"]["target"]
data["HSP2"] = ratings.hsp2 or data["Q3G"]["target"]
data["HSM1"] = ratings.hsm1 or data["Q12G"]["target"]
data["HSM2"] = data["questions"]["15"]["latest_value"]
data["HSM3"] = data["ER10a"]
data["HSM4"] = ratings.hsm4
data["BC1"] = data["questions"]["5"]["baseline_year"]
data["BC2"] = data["questions"]["6"]["baseline_value"]
data["BC3"] = data["questions"]["5"]["latest_year"]
data["BC4"] = data["questions"]["6"]["latest_value"]
data["BC5"] = "?????"
data["BC6"] = "?????"
data["BC7"] = "?????"
data["BC8"] = "?????"
data["BC9"] = "?????"
data["BC10"] = "?????"
data["PC1"] = data["indicators"]["3G"]["latest_value"]
data["PC2"] = data["indicators"]["3G"]["hs_budget_gap"]
data["PC3"] = translation.gov_pc3 % data["PC1"]
data["PC4"] = translation.gov_pc4 % data["PC2"]
data["PF1"] = data["questions"]["16"]["latest_value"]
data["PF2"] = comments_override.pf2 or data["questions"]["16"]["comments"]
data["PFM1"] = data["ER6a"]
data["PFM2"] = comments_override.pfm2 or data["questions"]["9"]["comments"]
data["PR1"] = data["ER7a"]
data["PR2"] = comments_override.pr2 or data["questions"]["10"]["comments"]
data["TA1"] = data["indicators"]["other"]["coordinated_programmes"]
data["TA2"] = ""
for agency in data["agencies"]:
aqs = data["agencies"][agency]
if "4" in aqs:
data["TA2"] += "%s %s" % (agency, aqs["4"]["comments"].replace("%", "%%"))
data["TA2"] += "\n"
data["TA2"] = comments_override.ta2 or data["TA2"]
data["PHC1"] = data["indicators"]["other"]["outpatient_visits_baseline"]
data["PHC2"] = data["questions"]["19"]["baseline_year"]
data["PHC3"] = data["indicators"]["other"]["outpatient_visits_latest"]
data["PHC4"] = data["questions"]["19"]["latest_year"]
data["PHC5"] = data["indicators"]["other"]["outpatient_visits_change"]
data["PHC6"] = data["indicators"]["other"]["outpatient_visits_change_dir"]
data["PHC7"] = ""
data["HRH1"] = data["indicators"]["other"]["skilled_personnel_baseline"]
data["HRH2"] = data["questions"]["17"]["baseline_year"]
data["HRH3"] = data["indicators"]["other"]["skilled_personnel_latest"]
data["HRH4"] = data["questions"]["17"]["latest_year"]
data["HRH5"] = data["indicators"]["other"]["skilled_personnel_change"]
data["HRH6"] = data["indicators"]["other"]["skilled_personnel_change_dir"]
data["HRH7"] = ""
data["HS1"] = data["questions"]["20"]["baseline_value"]
data["HS2"] = data["questions"]["20"]["baseline_year"]
data["HS3"] = data["questions"]["20"]["latest_value"]
data["HS4"] = data["questions"]["20"]["latest_year"]
data["HS5"] = data["indicators"]["other"]["health_workforce_spent_change"]
data["HS6"] = data["indicators"]["other"]["health_workforce_spent_change_dir"]
data["HS7"] = ""
data["RF1"] = data["ER8a"]
data["RF2"] = comments_override.rf2 or data["questions"]["22"]["latest_value"]
data["RF3"] = comments_override.rf3 or data["questions"]["23"]["latest_value"]
data["HMIS1"] = ratings.hmis1 or data["Q21G"]["target"]
data["HMIS2"] = comments_override.hmis2 or data["questions"]["21"]["comments"]
data["JAR1"] = ratings.jar1 or data["Q12G"]["target"]
data["JAR2"] = "Field no longer used"
data["JAR3"] = "Field no longer used"
data["JAR4"] = comments_override.jar4 or data["questions"]["24"]["comments"]
data["JAR5"] = "Field no longer used"
data["DBR1"] = data["ER8a"]
data["DBR2"] = comments_override.dbr2 or data["questions"]["11"]["comments"]
group1 = ["MDG1", "MDG2", "MDG3", "MDG4"]
group2 = ["MDG5a", "MDG5b", "MDG6a", "MDG6b", "MDG6c", "MDG7a", "MDG7b"]
group1_index = "abcde"
group2_index = "12345"
needs_percent = ["MDG1", "MDG2", "MDG6a", "MDG6b", "MDG7a", "MDG7b"]
add_perc = lambda ind: "%" if ind in needs_percent else ""
for mdg in group1 + group2:
# import pdb; pdb.set_trace()
index = group1_index if mdg in group1 else group2_index
mdgdata = models.MDGData.objects.get(mdg_target=mdg, country=country)
if not mdgdata.latest_value:
data[mdg + index[0]] = ""
data[mdg + index[1]] = ""
data[mdg + index[2]] = "questionmdg"
data[mdg + index[3]] = ""
data[mdg + index[4]] = ""
elif not mdgdata.baseline_value:
data[mdg + index[0]] = str(fformat_front(mdgdata.latest_value)) + add_perc(mdg)
data[mdg + index[1]] = mdgdata.latest_year
data[mdg + index[2]] = "questionmdg"
data[mdg + index[3]] = ""
data[mdg + index[4]] = ""
else:
fmt = fformat_two if mdg == "MDG3" else fformat_front
data[mdg + index[0]] = str(fmt(mdgdata.latest_value)) + add_perc(mdg)
data[mdg + index[1]] = mdgdata.latest_year
data[mdg + index[2]] = mdgdata.arrow
data[mdg + index[3]] = str(fmt(mdgdata.change)) + add_perc(mdg)
data[mdg + index[4]] = mdgdata.baseline_year
data["F1"] = country.country
data["CN1"] = data["TB2"]
data["GN1"] = country.country
data["Header"] = country.country
for i in range(1, 14):
data["P%d" % i] = data["p"].get(i - 1, "pwhite")
data["NP%d" % i] = data["np"].get(i - 1, "npwhite")
working_draft, _ = models.CountryWorkingDraft.objects.get_or_create(country=country)
data["workingdraft"] = "workingdraft" if working_draft.is_draft else ""
except Exception, e:
traceback.print_exc()