def proposal_countries_map(request, proposal_id):
filename = join(settings.MEDIA_DIRECTORY, 'img', 'trends', 'proposal', "%s-countries-map.svg" % proposal_id)
cache = get_content_cache(request, filename)
if cache:
return HttpResponse(cache, mimetype="image/svg+xml")
proposal = get_object_or_404(Proposal, id=proposal_id)
countries = {}
for country in Country.objects.order_by('code'):
countries[country.code] = Score.objects.filter(proposal=proposal, representative__mep__countrymep__country=country).aggregate(average_score=Avg('value'))['average_score']
current_country = None
out = ""
for line in open(join(settings.MEDIA_DIRECTORY, "grey_europe_map.svg"), "r").readlines():
if ' {}' in line:
get = re.match('.*([a-z][a-z]).*', line)
if get and get.group(1).upper() in countries.keys():
current_country = get.group(1).upper()
# HAHAHAHA blam those who can't write a human uzable xml lib for python
if current_country:
if countries[current_country]:
line = re.sub("{}", "{fill:rgb(%s, %s, %s);}" % color(countries[current_country]), line)
current_country = None
out += line
check_dir(filename)
open(filename, "w").write(out)
return HttpResponse(out, mimetype="image/svg+xml")
def score_color(self):
return "rgb(%s, %s, %s)" % color(self.total_score)
def group_proposal_score_heatmap(request, proposal_id):
filename = join(settings.MEDIA_DIRECTORY, 'img', 'trends', 'group', "groups-%s-repartition-heatmap.png" % proposal_id)
cache = get_content_cache(request, filename)
if cache:
return cache
proposal = get_object_or_404(Proposal, id=proposal_id)
countries= proposal.countries
groups = proposal.groups
fig = pyplot.figure(figsize=(len(countries) / 2.8, len(groups) / 2.8))
ax = fig.add_subplot(111)
ax.set_xlim(0, len(proposal.countries))
ax.set_ylim(0, len(groups))
biggest_group_of_a_country = 0
for country in countries:
for group in groups:
meps = MEP.objects.filter(score__proposal=proposal,
groupmep__end__gte=proposal.date,
groupmep__begin__lte=proposal.date,
countrymep__begin__lte=proposal.date,
countrymep__end__gte=proposal.date,
countrymep__country=country,
groupmep__group=group).distinct().count()
if meps > biggest_group_of_a_country:
biggest_group_of_a_country = meps
biggest_group_of_a_country = float(biggest_group_of_a_country)
a = 0
for country in countries:
b = 0
for group in groups:
meps = MEP.objects.filter(score__proposal=proposal,
groupmep__end__gte=proposal.date,
groupmep__begin__lte=proposal.date,
countrymep__begin__lte=proposal.date,
countrymep__end__gte=proposal.date,
countrymep__country=country,
groupmep__group=group).distinct().count()
score = Score.objects.filter(proposal=proposal,
representative__mep__groupmep__group=group,
representative__mep__groupmep__begin__lte=proposal.date,
representative__mep__groupmep__end__gte=proposal.date,
representative__mep__countrymep__country=country,
representative__mep__countrymep__begin__lte=proposal.date,
representative__mep__countrymep__end__gte=proposal.date).aggregate(Avg('value'))['value__avg']
if score:
ax.scatter(a + 0.5,b + 0.5, s=250*(meps/biggest_group_of_a_country),
c=map(lambda x: x/255., color(score)),
alpha=0.5)
b += 1
a += 1
#group_bar = {}
#scores = []
#maxeu = 0
#for score_range in range(0, 100, 10):
#meps = MEP.objects.filter(groupmep__end__gte=proposal.date, groupmep__begin__lte=proposal.date, score__proposal=proposal, score__value__lt=score_range + 10 if score_range != 90 else 101, score__value__gte=score_range).distinct().count()
#if meps > maxeu:
#maxeu = meps
#scores.append(meps)
#for mep in MEP.objects.filter(score__proposal=proposal, groupmep__group=group):
#for group in proposal.groups:
#for score_range in range(0, 100, 10):
#meps = group.mep_set.filter(groupmep__end__gte=proposal.date, groupmep__begin__lte=proposal.date, score__proposal=proposal, score__value__lt=score_range + 10 if score_range != 90 else 101, score__value__gte=score_range).distinct().count()
#scores[score_range/10] -= meps
#group_bar[group.abbreviation] = pyplot.bar(score_range/10 + 0.1, meps + scores[score_range/10], width=0.8, color=group_color.get(group.abbreviation, '#FFFFFF'))
#a, b = zip(*group_bar.items())
#pyplot.legend(list(b), list(a), 'best', shadow=False)
pyplot.title("Heatmap of group/country on %s" % proposal.short_name if proposal.short_name else proposal.title)
#pyplot.xticks(range(11), range(0, 110, 10))
pyplot.xticks(map(lambda x: x + 0.5, range(len(countries))), map(lambda x: x.code, countries))
pyplot.yticks(map(lambda x: x + 0.5, range(len(groups))), map(lambda x: x.abbreviation, groups))
#pyplot.xlabel("Score range 10 by 10")
#pyplot.ylabel("MEPs per group")
#pyplot.axis([0, 10.1, 0, maxeu + 3])
check_dir(filename)
pyplot.savefig(filename, format="png", bbox_inches='tight')
pyplot.figure(figsize=(8, 6))
pyplot.clf()
return send_file(request, filename, content_type="image/png")
def color_tuple(self):
return color(self.value)
def color(self):
red, green, _ = color(self.value)
return "rgb(%d, %d, 0)" % (red, green)
def group_proposal_score_heatmap(request, proposal_id):
filename = join(settings.MEDIA_DIRECTORY, 'img', 'trends', 'group', get_language() + "-groups-%s-repartition-heatmap.png" % proposal_id)
cache = get_content_cache(request, filename)
if cache:
return cache
proposal = get_object_or_404(Proposal, id=proposal_id)
countries= proposal.countries
groups = proposal.groups
if proposal.institution != "EU":
return HttpResponse("")
fig = pyplot.figure(figsize=(len(countries) / 2.8, len(groups) / 2.8))
ax = fig.add_subplot(111)
ax.set_xlim(0, len(proposal.countries))
ax.set_ylim(0, len(groups))
biggest_group_of_a_country = 0
for country in countries:
for group in groups:
meps = MEP.objects.filter(score__proposal=proposal,
groupmep__end__gte=proposal.date,
groupmep__begin__lte=proposal.date,
countrymep__begin__lte=proposal.date,
countrymep__end__gte=proposal.date,
countrymep__country=country,
groupmep__group=group).distinct().count()
if not meps:
meps = MEP.objects.filter(score__proposal=proposal,
countrymep__country=country,
groupmep__group=group).distinct().count()
if meps > biggest_group_of_a_country:
biggest_group_of_a_country = meps
biggest_group_of_a_country = float(biggest_group_of_a_country)
a = 0.5
for country in countries:
b = 0.5
for group in groups:
meps = MEP.objects.filter(score__proposal=proposal,
groupmep__end__gte=proposal.date,
groupmep__begin__lte=proposal.date,
countrymep__begin__lte=proposal.date,
countrymep__end__gte=proposal.date,
countrymep__country=country,
groupmep__group=group).distinct().count()
if not meps:
meps = MEP.objects.filter(score__proposal=proposal,
countrymep__country=country,
groupmep__group=group).distinct().count()
score = Score.objects.filter(proposal=proposal,
representative__mep__groupmep__group=group,
representative__mep__groupmep__begin__lte=proposal.date,
representative__mep__groupmep__end__gte=proposal.date,
representative__mep__countrymep__country=country,
representative__mep__countrymep__begin__lte=proposal.date,
representative__mep__countrymep__end__gte=proposal.date).aggregate(Avg('value'))['value__avg']
if not score:
score = Score.objects.filter(proposal=proposal,
representative__mep__groupmep__group=group,
representative__mep__countrymep__country=country).aggregate(Avg('value'))['value__avg']
if score:
ax.scatter(a, b, s=280*(meps/biggest_group_of_a_country),
c=map(lambda x: x/255., color(score)),
alpha=0.6)
b += 1
a += 1
pyplot.title(ugettext("Heatmap of group/country on %(proposal)s") % {"proposal": proposal.short_name if proposal.short_name else proposal.title})
pyplot.xticks(map(lambda x: x + 0.5, range(len(countries))), map(lambda x: x.code, countries))
pyplot.yticks(map(lambda x: x + 0.5, range(len(groups))), map(lambda x: x.abbreviation, groups))
check_dir(filename)
pyplot.savefig(filename, format="png", bbox_inches='tight')
pyplot.figure(figsize=(8, 6))
pyplot.clf()
return send_file(request, filename, content_type="image/png")
