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 get_country_indicators(country, questions, agencies_data):
indicator_data = calc_country_indicators(country)
indicators = {}
for indicator in indicator_data:
ind = indicators[indicator] = {}
data = indicator_data[indicator][0]
ind["baseline_value"] = none_num(data[0])
ind["baseline_year"] = data[1]
ind["latest_value"] = none_num(data[2])
ind["latest_year"] = data[3]
if indicators["3G"]["latest_value"] != NA_STR:
indicators["3G"]["hs_budget_gap"] = 15 - indicators["3G"]["latest_value"]
else:
indicators["3G"]["hs_budget_gap"] = None
indicators["other"] = {}
other_indicators = indicators["other"]
baseline_denom = questions["18"]["baseline_value"] / 10000.0
latest_denom = questions["18"]["latest_value"] / 10000.0
# Outpatient Visits
other_indicators["outpatient_visits_baseline"] = questions["19"]["baseline_value"] / baseline_denom
other_indicators["outpatient_visits_latest"] = questions["19"]["latest_value"] / latest_denom
other_indicators["outpatient_visits_change"], other_indicators["outpatient_visits_change_dir"] = calc_change(other_indicators["outpatient_visits_latest"], other_indicators["outpatient_visits_baseline"])
# Skilled Personnel
other_indicators["skilled_personnel_baseline"] = questions["17"]["baseline_value"] / baseline_denom
other_indicators["skilled_personnel_latest"] = questions["17"]["latest_value"] / latest_denom
other_indicators["skilled_personnel_change"], other_indicators["skilled_personnel_change_dir"] = calc_change(other_indicators["skilled_personnel_latest"], other_indicators["skilled_personnel_baseline"])
# Health Workforce
other_indicators["health_workforce_perc_of_budget_baseline"] = questions["20"]["baseline_value"] / questions["7"]["baseline_value"]
other_indicators["health_workforce_perc_of_budget_latest"] = questions["20"]["latest_value"] / questions["7"]["latest_value"]
other_indicators["health_workforce_spent_change"], other_indicators["health_workforce_spent_change_dir"] = calc_change(questions["20"]["latest_value"], questions["20"]["baseline_value"])
other_indicators["pfm_diff"] = questions["9"]["latest_value"] - questions["9"]["baseline_value"]
def sum_agency_values(question_number, field):
sum = 0
for agency in agencies_data:
if question_number in agencies_data[agency]:
try:
sum += float(agencies_data[agency][question_number][field])
except ValueError:
pass
return sum
coordinated_programmes = sum_agency_values("5", "latest_value") - sum_agency_values("4", "latest_value")
if coordinated_programmes > 0.51:
other_indicators["coordinated_programmes"] = models.Rating.TICK
elif coordinated_programmes >= 0.11:
other_indicators["coordinated_programmes"] = models.Rating.ARROW
else:
other_indicators["coordinated_programmes"] = models.Rating.CROSS
return indicators
def calc_country_ratings(country, language=None):
"""
Returns information for all indicators for the given country in a dict with the
following form
{
"1G" : {
"base_val" : ...,
"cur_val" : ...,
"comments" : ...,
"target" : ...,
},
"2Ga" : {
"base_val" : ...,
"cur_val" : ...,
"comments" : ...,
"target" : ...,
},
.
.
.
}
"""
language = language or models.Language.objects.get(language="English")
translation = translations.get_translation(language)
gov_commentary_text = translation.gov_commentary_text
rating_question_text = translation.rating_question_text
rating_none_text = translation.rating_none_text % country.country
targets = get_country_targets(country, g_indicators)
indicators = calc_country_indicators(country)
results = {}
ratings, _ = models.GovScorecardRatings.objects.get_or_create(country=country)
comment_override, _ = models.GovScorecardComments.objects.get_or_create(country=country, language=language)
def ratings_val(obj, tmpl):
def _func(indicator):
h = indicator.replace("G", "").replace("Q", "")
d = obj.__dict__
return d.get(tmpl % h, None)
return _func
ratings_comments = ratings_val(comment_override, "er%s")
ratings_target = ratings_val(ratings, "r%s")
for indicator in indicators:
(base_val, base_year, cur_val, cur_year), comments = indicators[indicator]
target = targets[indicator]
result = {
"base_val" : base_val,
"base_year" : base_year,
"cur_val" : cur_val,
"cur_year" : cur_year,
"comments" : comments,
"commentary" : "",
"country_name" : country,
}
result["one_minus_base_val"] = base_val
if isinstance(base_val, numbers.Real):
result["one_minus_base_val"] = 100 - base_val
result["one_minus_cur_val"] = cur_val
if isinstance(cur_val, numbers.Real):
result["one_minus_cur_val"] = 100 - cur_val
result["target"] = ratings_target(indicator) or evaluate_indicator(target, base_val, cur_val)
if ratings_comments(indicator):
result["commentary"] = ratings_comments(indicator)
else:
if indicator in gov_commentary_text:
target_value = result["target"]
if target_value == Rating.QUESTION:
commentary = rating_question_text
elif target_value == Rating.NONE:
commentary = rating_none_text
elif target_value == None:
raise Exception("This shouldn't really be happening")
commentary = "Missing Data"
elif "all" in gov_commentary_text[indicator]:
commentary = gov_commentary_text[indicator]["all"]
else:
commentary = gov_commentary_text[indicator][target_value]
try:
result["commentary"] = commentary % result
except TypeError, e:
result["commentary"] = ["This text couldn't be generated, possibly because the rating was overriden. Please override the text appropriately as well"]
results[indicator] = result
def government_graphs(request, language, template_name="submission/country_graphs_by_indicator.html", extra_context=None):
extra_context = extra_context or {}
translation = request.translation
countries = sorted(Country.objects.all(), key=lambda x: x.country)
data_3G = dict([(c, calc_country_indicators(c)["3G"]) for c in countries])
data_4G = dict([(c, calc_country_indicators(c)["4G"]) for c in countries])
country_data = dict([(country, country_scorecard.get_country_export_data(country)) for country in Country.objects.all()])
# TODO
# Request from James to zero negative values
neg_to_zero = lambda x : 0 if x < 0 else x
# TODO
# Request from James to remove overly large values
remove_large = lambda x : 0 if x > 100 else x
# Nepal needs to be shown at the end of the list and with an asterix
nepal = Country.objects.get(country="Nepal")
nepal.country = nepal.country + "*"
countries_3g = list(countries) + [nepal]
countries_3g.remove(nepal)
extra_context["graph_3G"] = TargetCountryBarGraph(
countries_3g,
"graph_3G",
[data_3G[country][0][0] for country in countries_3g],
[data_3G[country][0][2] for country in countries_3g],
translation.target_language["target"], 15,
title=translation.government_graphs["3G"]["title"],
)
extra_context["graph_3G"].subtitle = {
"text": translation.government_graphs["3G"]["subtitle"],
"align": 'left',
"x": 50,
"y": 388,
"floating" : "true",
}
extra_context["graph_4G"] = CountryBarGraph(
countries,
"graph_4G",
[neg_to_zero(data_4G[country][0][0]) for country in countries],
[neg_to_zero(data_4G[country][0][2]) for country in countries],
title=translation.government_graphs["4G"]["title"],
)
extra_context["graph_hw"] = CountryBarGraph(
countries,
"graph_hw",
[remove_large(country_data[country]["indicators"]["other"]["health_workforce_perc_of_budget_baseline"] * 100) for country in countries],
[remove_large(country_data[country]["indicators"]["other"]["health_workforce_perc_of_budget_latest"] * 100) for country in countries],
title=translation.government_graphs["health_workforce"]["title"],
)
extra_context["graph_outpatient_visits"] = CountryBarGraph(
countries,
"graph_outpatient_visits",
[country_data[country]["indicators"]["other"]["outpatient_visits_baseline"] for country in countries],
[country_data[country]["indicators"]["other"]["outpatient_visits_latest"] for country in countries],
title=translation.government_graphs["outpatient_visits"]["title"],
)
extra_context["graph_outpatient_visits"].yAxis = {"title" : {"text" : ""}}
extra_context["graph_skilled_medical"] = TargetCountryBarGraph(
countries,
"graph_skilled_medical",
[country_data[country]["indicators"]["other"]["skilled_personnel_baseline"] for country in countries],
[country_data[country]["indicators"]["other"]["skilled_personnel_latest"] for country in countries],
translation.target_language["who"], 23,
title=translation.government_graphs["skilled_medical"]["title"],
)
extra_context["graph_skilled_medical"].yAxis = {"title" : {"text" : ""}}
extra_context["graph_health_budget"] = TargetCountryBarGraph(
countries,
"graph_health_budget",
[country_data[country]["indicators"]["3G"]["baseline_value"] for country in countries],
[country_data[country]["indicators"]["3G"]["latest_value"] for country in countries],
translation.target_language["target"], 15,
title=translation.government_graphs["health_budget"]["title"],
)
return direct_to_template(request, template=template_name, extra_context=extra_context)
