def mep_raw(request, mep_id):
mep_ = MEP.get(mep_id)
jsonstr = simplejson.dumps(dict(mep_), indent=4, use_decimal=True)
context = {
'mep_id': mep_id,
'mep': mep_,
'jsonstr': jsonstr,
}
return direct_to_template(request, 'meps/mep_raw.html', context)
def test_trophies_retrieval_from_mep(self):
"""
Test that meps' CouchDB model can retrieve associated Django trophies.
"""
# Initialization
a_mep = MEP.get('AlainLipietz')
manual_trophy = ManualTrophy.objects.create(label="A manual trophy")
auto_trophy = AutoTrophy.objects.create(label="An auto trophy")
self.failUnlessEqual(a_mep.trophies, [])
# Let's create a reward and attribute it to verify CouchDB's update
reward = Reward.objects.create(mep_wikiname=a_mep._id, trophy=manual_trophy, reason="test")
a_mep = MEP.get('AlainLipietz')
self.failUnlessEqual(repr(a_mep.trophies), "[<ManualTrophy: A manual trophy>]")
# OK, now we verify that deletion is triggered to CouchDB
reward.delete()
a_mep = MEP.get('AlainLipietz')
self.failUnlessEqual(a_mep.trophies, [])
def test_trophies_attribution(self):
"""
Test that trophies' models can interact with CouchDB.
"""
# Initialization
a_mep = MEP.get('AlainLipietz')
manual_trophy = ManualTrophy.objects.create(label="A manual trophy")
auto_trophy = AutoTrophy.objects.create(label="An auto trophy")
self.failUnlessEqual(a_mep.trophies_ids, [])
# Let's create a reward and attribute it to verify CouchDB's update
reward = Reward.objects.create(mep_wikiname=a_mep._id, trophy=manual_trophy, reason="test")
a_mep = MEP.get('AlainLipietz')
self.failUnlessEqual(a_mep.trophies_ids, [1])
# OK, now we verify that deletion is triggered to CouchDB
reward.delete()
a_mep = MEP.get('AlainLipietz')
self.failUnlessEqual(a_mep.trophies_ids, [])
def mep(request, mep_id):
mep_ = MEP.get(mep_id)
mep_["achievements"] = autoTrophies(mep_)
positions = Position.objects.filter(mep_id=mep_id)
score_list = mep_.scores
for score in score_list:
score["color"] = score_to_color(int(score["value"]))
score_list.sort(key=lambda k: datetime.strptime(k["date"], "%d/%m/%Y"))
scores = [s["value"] for s in mep_.scores]
if score_list:
try:
import numpy
import matplotlib
matplotlib.use("Agg")
from matplotlib import pyplot
pyplot.plot(scores, "bo")
a, b = numpy.polyfit(range(len(scores)), [int(x) for x in scores], 1)
pyplot.plot([a * int(x) + b for x in range(len(scores))])
pyplot.legend(("Scores", "Mediane"), "best", shadow=True)
pyplot.plot(scores)
pyplot.axis([0, len(scores) - 1, 0, 102])
pyplot.title("%s - Votes notes evolution over time" % (mep_.infos["name"]["full"]))
pyplot.xticks(range(len(scores)), [k["date"] for k in score_list])
pyplot.xlabel("Votes dates")
pyplot.ylabel("Scores on votes")
pyplot.savefig(
realpath("./memopol2/%simg/trends/meps/%s-scores.png" % (settings.MEDIA_URL, mep_id)), format="png"
)
pyplot.clf()
except ImportError:
pass
context = {
"mep_id": mep_id,
"mep": mep_,
"positions": positions,
"visible_count": len([x for x in positions if x.visible]),
"average": sum(scores) / len(scores) if len(scores) > 0 else "",
"score_list": score_list,
}
return direct_to_template(request, "meps/mep.html", context)
def mep(request, mep_id):
mep_ = MEP.get(mep_id)
positions = Position.objects.filter(mep_id=mep_id)
score_list = mep_.scores
for score in score_list:
score['color'] = score_to_color(int(score['value']))
score_list.sort(key = lambda k : datetime.strptime(k['date'], "%d/%m/%Y"))
scores = [s['value'] for s in mep_.scores]
if score_list:
try:
import numpy
import matplotlib
matplotlib.use("Agg")
from matplotlib import pyplot
pyplot.plot(scores, 'bo')
a, b = numpy.polyfit(range(len(scores)), [int(x) for x in scores], 1)
pyplot.plot([a*int(x) + b for x in range(len(scores))])
pyplot.legend(('Scores', 'Mediane'), 'best', shadow=True)
pyplot.plot(scores)
pyplot.axis([0, len(scores) - 1, 0, 102])
pyplot.title("%s - Votes notes evolution over time" % (mep_.infos['name']['full']))
pyplot.xticks(range(len(scores)), [k['date'] for k in score_list])
pyplot.xlabel("Votes dates")
pyplot.ylabel("Scores on votes")
pyplot.savefig(realpath(".%simg/trends/meps/%s-scores.png" % (settings.MEDIA_URL, mep_id)), format="png")
pyplot.clf()
except ImportError:
pass
context = {
'mep_id': mep_id,
'mep': mep_,
'positions': positions,
'visible_count': len([x for x in positions if x.visible]),
'average': sum(scores)/len(scores) if len(scores) > 0 else "",
'score_list' : score_list,
}
return direct_to_template(request, 'meps/mep.html', context)
def mep(self):
return MEP.get(self.mep_wikiname)
def setUp(self):
# Delete all trophies for the test user
a_mep = MEP.get('AlainLipietz')
a_mep.trophies_ids = []
a_mep.save()
def mep_structure(request, mep_id):
mep_ = MEP.get(mep_id)
jsonstr = simplejson.dumps(dict(mep_), indent=4, use_decimal=True)
context = {"mep_id": mep_id, "mep": mep_, "jsonstr": jsonstr}
return direct_to_template(request, "meps/mep_structure.html", context)
def mep_json(request, mep_id):
mep_ = MEP.get(mep_id)
jsonstr = simplejson.dumps(dict(mep_), indent=4, use_decimal=True)
return HttpResponse(jsonstr, content_type="application/json")
def mep_json(request, mep_id):
mep_ = MEP.get(mep_id)
jsonstr = simplejson.dumps(dict(mep_), indent=4, use_decimal=True)
return HttpResponse(jsonstr)
