def GetGLineUrl(plot_list, width=600, height=500):
"""Get Google line chart url string.
Args:
plot_list: Numeric number list.
A list also can contain negative value elements.
width: Image width when it is rendered in web browser.
height: Image height when it is rendered in web browseor.
Returns:
An url string that will create chart image in google chart.
"""
max_y = max(plot_list)
min_y = min(plot_list)
gchart = GChart()
gchart.type('line')
gchart.dataset(plot_list)
gchart.size(width, height)
gchart.axes.type('y')
gchart.axes.range(0, min_y, max_y)
gchart.scale(min_y, max_y)
return str(gchart)
def gchart(context, nodelist, type, dataset, **kwargs):
G = GChart(type, dataset, encoding=kwargs.pop('encoding', 'text'))
for node in nodelist:
if isinstance(node, TextNode):
for part in node.render(context).splitlines():
cmd, value = parse_cmd(part)
if cmd is None: continue
if cmd.startswith('axes'):
cmd = getattr(G.axes, cmd[5:])
else:
cmd = getattr(G, cmd)
cmd(*value.split())
if 'instance' in kwargs:
return G
return G.img(**kwargs)
def gchart(context, nodelist, type, dataset, **kwargs):
G = GChart(type, dataset, encoding=kwargs.pop('encoding','text'))
for node in nodelist:
if isinstance(node, TextNode):
for part in node.render(context).splitlines():
cmd,value = parse_cmd(part)
if cmd is None: continue
if cmd.startswith('axes'):
cmd = getattr(G.axes, cmd[5:])
else:
cmd = getattr(G, cmd)
cmd(*value.split())
if 'instance' in kwargs:
return G
return G.img(**kwargs)
def simple(self):
# Instantiate the GChart instance, this is all you will need for making charts
# GChart(type=None, dataset=None), see the doc for more
G = GChart()
# Set the chart type, either Google API type or regular name
G.type('pie')
# Update the chart's dataset, can be two dimensional and contain string data
G.dataset('helloworld')
# Set the size of the chart, default is 300x150
G.size(250, 100)
return G
def simple():
G = GChart()
# Set the chart type, either Google API type or regular name
G.type('pie')
# Update the chart's dataset, can be two dimensional or contain string data
G.dataset('helloworld')
# Set the size of the chart, default is 300x150
G.size(250, 100)
print G
def practice_list(request, club = None):
club = get_object_or_404(Club, Slug = club)
practices = club.practice_set.all().annotate(NumPeople = Count('person')).order_by('-Date')
if practices.count() > 10:
chart = GChart(ctype = 'line')
data = sliding_window(practices)
chart.dataset(data[:500]).axes.type('xy')
if request.method == 'POST':
form = PracticeModelForm(request.POST)
new_practice = form.save(commit = False)
new_practice.Club = club
new_practice.save()
return HttpResponseRedirect(new_practice.get_absolute_url())
else:
form = PracticeModelForm()
return render_to_response('Dojo/Practice_object_list.html', locals(),
context_instance = RequestContext(request))
def render_macro(self, req, name, content):
# XXX: This is a big security hole. Need to replace this with something that
# only accepts simple key/value pairs.
options = eval("dict(%s)" % content)
query = options.get('query', None)
ctype = options.get('type', None)
columns = options.get('columns', None)
if query is None or ctype is None:
raise ValueError("Chart 'type' and 'query' parameters are required")
for key in NON_API_KEYS:
if key in options:
del options[key]
datasets = {}
scales = {}
labels = {}
if columns is not None:
for idx, val in enumerate(columns):
if len(val) >= 2:
if val[1] == 'labels':
labels[idx] = []
elif val[1] in ('percentage', 'scaled'):
datasets[idx] = []
scales[idx] = (0,0)
db = self.env.get_db_cnx()
cursor = db.cursor()
cursor.execute(query)
col_count = 0
if columns is not None:
col_count = len(columns)
# Collect label, scale and dataset data
for row in cursor:
if not col_count:
col_count = len(row)
if columns is None:
columns = []
for idx in range(col_count):
columns.append((None, 'percentage'))
datasets[idx] = []
scales[idx] = (0,0)
elif len(columns) != col_count:
raise KeyError("Table has %d columns, but 'columns' parameter has %d items" % \
(col_count, len(columns),))
for idx, col in enumerate(row):
if idx in labels:
labels[idx].append(col)
elif idx in datasets:
try:
col_value = float(col)
except (TypeError, ValueError):
continue
datasets[idx].append(col_value)
scales[idx] = (min(scales[idx][0], col_value),
max(scales[idx][1], col_value),)
dense_dataset = []
dataset_to_idx = {}
idx_to_axis = {}
axis_to_idx = {}
axis_types = [] # x, x, y - in order
scaled_axes = {} # idx -> min/max for that scale
current_dataset = 0
current_axis = 0
for idx, col in enumerate(columns):
if len(col) >= 1 and col[0]:
idx_to_axis[idx] = current_axis
axis_to_idx[current_axis] = idx
axis_types.append(col[0])
current_axis += 1
if len(col) >= 2 and col[1] == 'scaled':
scale_min = len(col) >= 3 and col[2] or scales[idx][0]
scale_max = len(col) >= 4 and col[3] or scales[idx][1]
scaled_axes[idx] = (scale_min, scale_max,)
if idx in datasets:
dataset_to_idx[current_dataset] = idx
dense_dataset.append(datasets[idx])
current_dataset += 1
# Add axes
if 'chxt' not in options:
if axis_types:
options['chxt'] = ','.join(axis_types)
# Add axis labels
if 'chxl' not in options:
label_data = []
for idx, values in sorted(labels.items()):
if idx not in idx_to_axis:
continue
label_data.append('%d:|%s' % (idx_to_axis[idx], '|'.join(values),))
if label_data:
options['chxl'] = '|'.join(label_data)
# Add scale range axes
if 'chxr' not in options:
range_triples = []
for idx, (scale_min, scale_max) in sorted(scaled_axes.items()):
if idx not in idx_to_axis:
continue
range_triples.append('%d,%.1f,%.1f' % (idx_to_axis[idx], scale_min, scale_max,))
if range_triples:
options['chxr'] = '|'.join(range_triples)
# Add data scaling
if 'chds' not in options and scaled_axes:
scale_data = []
for cnt in range(len(dense_dataset)):
idx = dataset_to_idx[cnt]
scale_item = ','
if idx in scaled_axes:
scale_min, scale_max = scaled_axes[idx]
scale_item = '%.1f,%.1f' % (scale_min, scale_max)
scale_data.append(scale_item)
if scale_data:
options['chds'] = ','.join(scale_data)
chart = GoogleChart(ctype=ctype, dataset=dense_dataset, **options)
return Markup(chart.img())
def tarp_subsidies(request):
estimated_subsidies = []
subsidy_rates = []
amounts_received = []
names = []
colors = []
for r in SubsidyRecord.objects.all():
estimated_subsidies.append(r.estimated_subsidy)
subsidy_rates.append(r.subsidy_rate)
amounts_received.append(r.amount_received)
names.append(r.name)
colors.append(r.color)
# reverse names (API wrapper bug?)
names.reverse()
# estimated subsidies chart
estimates_subsidies_normalized = _normalize_chart_range(
estimated_subsidies)
estimated_subsidies_chart = GChart('bhs',
estimates_subsidies_normalized.values())
estimated_subsidies_chart.size((500, 250))
estimated_subsidies_chart.color('|'.join(colors))
estimated_subsidies_chart.bar(18, 2, 0)
estimated_subsidies_chart.axes.type('xy')
estimated_subsidies_chart_xlabels = range(
0, (_get_scale_bound(estimated_subsidies) + 1), 5)
estimated_subsidies_chart_xlabels = map((lambda x: str(x)),
estimated_subsidies_chart_xlabels)
estimated_subsidies_chart.axes.label(
str('|'.join(estimated_subsidies_chart_xlabels)))
estimated_subsidies_chart.axes.label('|'.join(names))
estimated_subsidies_chart.axes.style('000000')
estimated_subsidies_chart.axes.style('000000')
i = 0
for x in estimated_subsidies:
marker_text = 't $%.1f' % x
estimated_subsidies_chart.marker(marker_text, '000000', 0, i, 10, -1)
i = i + 1
# subsidy rates chart
subsidy_rates_normalized = _normalize_chart_range(subsidy_rates)
subsidy_rate_chart = GChart('bhs', subsidy_rates_normalized.values())
subsidy_rate_chart.size((500, 250))
subsidy_rate_chart.color('|'.join(colors))
subsidy_rate_chart.bar(18, 2, 0)
subsidy_rate_chart.axes.type('xy')
subsidy_rate_chart_xlabels = range(0,
(_get_scale_bound(subsidy_rates) + 1),
10)
subsidy_rate_chart_xlabels = map((lambda x: str(x)),
subsidy_rate_chart_xlabels)
subsidy_rate_chart.axes.label(str('|'.join(subsidy_rate_chart_xlabels)))
subsidy_rate_chart.axes.label('|'.join(names))
subsidy_rate_chart.axes.style('000000')
subsidy_rate_chart.axes.style('000000')
i = 0
for x in subsidy_rates:
marker_text = 't %d%%' % x
subsidy_rate_chart.marker(marker_text, '000000', 0, i, 10, -1)
i = i + 1
# amounts received chart
amounts_received_normalized = _normalize_chart_range(amounts_received)
amounts_received_chart = GChart('bhs',
amounts_received_normalized.values())
amounts_received_chart.size((500, 250))
amounts_received_chart.color('|'.join(colors))
amounts_received_chart.bar(18, 2, 0)
amounts_received_chart.axes.type('xy')
amounts_received_chart_xlabels = range(
0, (_get_scale_bound(amounts_received) + 1), 10)
amounts_received_chart_xlabels = map((lambda x: str(x)),
amounts_received_chart_xlabels)
amounts_received_chart.axes.label(
str('|'.join(amounts_received_chart_xlabels)))
amounts_received_chart.axes.label('|'.join(names))
amounts_received_chart.axes.style('000000')
amounts_received_chart.axes.style('000000')
i = 0
for x in amounts_received:
marker_text = 't $%.1f' % x
amounts_received_chart.marker(marker_text, '000000', 0, i, 10, -1)
i = i + 1
return render_to_response(
'bailout/tarp_subsidy_table.html', {
'estimated_subsidies_chart': estimated_subsidies_chart.img(),
'subsidy_rate_chart': subsidy_rate_chart.img(),
'amounts_received_chart': amounts_received_chart.img(),
'estimated_subsidies': estimated_subsidies,
'subsidy_rates': subsidy_rates,
'amounts_received': amounts_received,
'names': ' '.join(names),
'colors': '|'.join(colors)
},
context_instance=RequestContext(request))
def get_context_data(self, **kwargs):
context = super(RedDetailView, self).get_context_data(**kwargs)
app_label = 'rtg'
model = models.get_model(app_label, 'ReservaIp')
self.admin_object = admin_rtg._registry[model] #IGNORE:protected-access
self.admin_object.red_ips = Red_Ips(self.object)
if self.object.externa:
ips_activas = "No disponible (red externa)"
else:
ips_activas = self.admin_object.red_ips.ips_activas
if self.object.asignacion_ip: #gestionamos las IPs
ips_asignadas = len(self.admin_object.red_ips.asignadas)
ips_libres = self.admin_object.red_ips.ips_libres
self.admin_object.change_list_template = 'rtg/red_detail.django.html'
else: #no gestionamos las IPs
ips_asignadas = 'No se gestionan las IPs de la red'
ips_libres = ''
self.admin_object.change_list_template = 'rtg/red_detail_sin_ips.django.html'
hist_asignadas = []
hist_activas = []
for i in range(1,13):
d=HistoricoIpsEnRed.objects.filter(red=self.object).filter(fecha__month=i).aggregate(Max('ips_asignadas'),Max('ips_activas')) #IGNORE:no-member
hist_asignadas.append(d['ips_asignadas__max'])
hist_activas.append(d['ips_activas__max'])
hist_libres = deque(map(lambda x:'_' if x==None else str(self.admin_object.red_ips.num_ips-x), hist_asignadas)) #IGNORE:bad-builtin)
hist_asignadas = deque(map(lambda x:'_' if x==None else str(x), hist_asignadas)) #IGNORE:bad-builtin
hist_activas = deque(map(lambda x:'_' if x==None else str(x), hist_activas)) #IGNORE:bad-builtin
meses = deque(['Ene','Feb','Mar','Abr','May','Jun','Jul','Ago','Sep','Oct','Nov','Dic'])
mes_actual = datetime.date.today().month
# rotamos los datos para que apareza en la grafica el mes actual como último mes
meses.rotate(-mes_actual)
hist_libres.rotate(-mes_actual)
hist_asignadas.rotate(-mes_actual)
hist_activas.rotate(-mes_actual)
#Creamos el GChart pasando el dataset porque no se soporta el parametro t2
G = GChart(ctype="bvs", chd="t2:" + ','.join(hist_asignadas)+'|'+','.join(hist_libres)+'|'+','.join(hist_activas))
G.bar('a',1)
G.size(350,200)
G.color('4D89F9','C6D9FD','0000FF')
G.marker('D','0000FF','2','0','2')
G.marker('s','0000FF','2','-1','8')
G.title('Historico Utilizacion') #Fallan los acentos
G.legend('Asignadas','Libres','Activas')
G['chdlp'] = 'b|l'
G.scale(0,self.admin_object.red_ips.num_ips)
G.margin(0,0,5,0)
G.axes.type('yx')
G.axes.label(1,*meses) #IGNORE:W0142
G.axes.range(0,0,self.admin_object.red_ips.num_ips)
context.update( { 'model_name': 'red',
'num_ips': self.admin_object.red_ips.num_ips,
'ips_asignadas': ips_asignadas,
'ips_libres': ips_libres,
'ips_activas': ips_activas,
'admin_url': get_admin_url(self.request.get_full_path()),
'chart_ips_libres': G,
}
)
return context