def highlevelgraphs(request, language, template_name="submissions/highlevelgraphs.html", extra_context=None, titles=None):
extra_context = extra_context or {}
translation = request.translation
indicators = calc_overall_agency_indicators(funcs=positive_funcs)
for indicator in indicators:
(baseline_value, _, latest_value, _) = indicators[indicator][0]
name = "graph_%s" % indicator.lower()
if indicator not in ["5DPc"]:
graph = highlevel_graph_by_indicator(indicator, name, translation, baseline_value, latest_value, target_values[indicator])
else:
graph = highlevel_graph_by_indicator(indicator, name, translation, baseline_value, latest_value)
extra_context["graph_%s" % indicator] = graph
agency_data = dict([(agency, agency_scorecard.get_agency_scorecard_data(agency)) for agency in Agency.objects.all()])
extra_context["graph_pfm"] = additional_graph_by_indicator("5DPb", "graph_pfm", translation, agency_data)
extra_context["graph_procurement"] = additional_graph_by_indicator("5DPa", "graph_procurement", translation, agency_data)
extra_context["graph_multi_year"] = additional_graph_by_indicator("3DP", "graph_multi_year", translation, agency_data)
extra_context["graph_pba"] = additional_graph_by_indicator("2DPc", "graph_pba", translation, agency_data)
extra_context["graph_tc"] = additional_graph_by_indicator("2DPb", "graph_tc", translation, agency_data)
extra_context["graph_aob"] = additional_graph_by_indicator("2DPa", "graph_aob", translation, agency_data)
return direct_to_template(request, template=template_name, extra_context=extra_context)
def agency_graphs_by_indicator(request, indicator, language, template_name="submissions/agency_graphs_by_indicator.html", extra_context=None):
extra_context = extra_context or {}
translation = request.translation
indicators = calc_overall_agency_indicators(funcs=positive_funcs)
extra_context["graphs"] = graphs = []
name = "graph_%s" % indicator
(baseline_value, baseline_year, latest_value, latest_year) = indicators[indicator][0]
target = target_values[indicator]
graph = highlevel_graph_by_indicator(indicator, name, translation, baseline_value, latest_value, target=target)
graphs.append({
"name" : name,
"obj" : graph
})
agency_data = dict([(agency, agency_scorecard.get_agency_scorecard_data(agency)) for agency in Agency.objects.all()])
name = "graph2_%s" % indicator
graph = additional_graph_by_indicator(indicator, name, translation, agency_data)
graphs.append({
"name" : name,
"obj" : graph
})
return direct_to_template(request, template=template_name, extra_context=extra_context)
def projectiongraphs(request, language, template_name="submissions/projectiongraphs.html", extra_context=None):
extra_context = extra_context or {}
translation = request.translation
indicators = calc_overall_agency_indicators(funcs=positive_funcs)
for indicator in ["2DPa", "5DPb"]:
(baseline_value, baseline_year, latest_value, latest_year) = indicators[indicator][0]
baseline_year, latest_year = int(baseline_year), int(latest_year)
target_value = target_values[indicator]
# Find the intersection point between the horizontal target line and the trend line
# i.e. x = (y - c)/m
m = (latest_value - baseline_value) / (latest_year - baseline_year)
c = baseline_value
intersection = (target_value - c) / m + baseline_year
y = lambda x : m * (x - baseline_year) + c
start_year = baseline_year
end_year = int(round(intersection, 0) + 1)
target_data = [target_value] * (end_year - start_year + 1)
actual_data = [y(year) for year in range(start_year, latest_year + 1)]
projected_data = [(year - start_year, y(year)) for year in range(latest_year, end_year + 1)]
graph = DPChart("graph_%s" % indicator.lower())
graph.chart = {
"marginTop" : 50,
"defaultSeriesType": "line",
}
graph.title = {"text" : translation.projection_graphs[indicator]["title"]}
graph.xAxis = {"categories" : range(start_year, end_year + 1)}
graph.yAxis = {"title" : {"text" : ""}}
graph.series = [{
"name" : "Actual",
"data" : actual_data
}, {
"name" : "Projected",
"data" : projected_data,
"dashStyle" : "shortDash",
"color" : "#89A54E",
}, {
"name": translation.target_language["target"],
"data": target_data,
"marker": {
"enabled": "false"
},
}]
extra_context["graph_%s" % indicator] = graph
return direct_to_template(request, template=template_name, extra_context=extra_context)
