def _create_pie(self, cr, uid, ids, report, fields, results, context):
pdf_string = cStringIO.StringIO()
can = canvas.init(fname=pdf_string, format='pdf')
ar = area.T(size=(350, 350),
legend=legend.T(),
x_grid_style=None,
y_grid_style=None)
colors = map(lambda x: fill_style.Plain(bgcolor=x),
misc.choice_colors(len(results)))
if reduce(lambda x, y: x + y, map(lambda x: x[1], results)) == 0.0:
raise except_osv(
_('Error'),
_("The sum of the data (2nd field) is null.\nWe can't draw a pie chart !"
))
plot = pie_plot.T(data=results,
arc_offsets=[0, 10, 0, 10],
shadow=(2, -2, fill_style.gray50),
label_offset=25,
arrow_style=arrow.a3,
fill_styles=colors)
ar.add_plot(plot)
ar.draw(can)
can.close()
self.obj = external_pdf(pdf_string.getvalue())
self.obj.render()
pdf_string.close()
return True
def _create_pie(self, cr, uid, ids, report, fields, results, context):
pdf_string = cStringIO.StringIO()
can = canvas.init(fname=pdf_string, format='pdf')
ar = area.T(size=(350,350), legend=legend.T(),
x_grid_style = None, y_grid_style = None)
colors = map(lambda x:fill_style.Plain(bgcolor=x), misc.choice_colors(len(results)))
if reduce(lambda x,y : x+y, map(lambda x : x[1],results)) == 0.0:
raise except_osv(_('Error'), _("The sum of the data (2nd field) is null.\nWe can't draw a pie chart !"))
plot = pie_plot.T(data=results, arc_offsets=[0,10,0,10],
shadow = (2, -2, fill_style.gray50),
label_offset = 25,
arrow_style = arrow.a3,
fill_styles=colors)
ar.add_plot(plot)
ar.draw(can)
can.close()
self.obj = external_pdf(pdf_string.getvalue())
self.obj.render()
pdf_string.close()
return True
def _create_bars(self, cr, uid, ids, report, fields, results, context):
service = netsvc.LocalService("object_proxy")
pdf_string = cStringIO.StringIO()
can = canvas.init(fname=pdf_string, format='pdf')
can.show(80, 380, '/16/H' + report['title'])
process_date = {}
process_date['D'] = lambda x: reduce(lambda xx, yy: xx + '-' + yy,
x.split('-')[1:3])
process_date['M'] = lambda x: x.split('-')[1]
process_date['Y'] = lambda x: x.split('-')[0]
order_date = {}
order_date['D'] = lambda x: time.mktime((2005, int(x.split('-')[
0]), int(x.split('-')[1]), 0, 0, 0, 0, 0, 0))
order_date['M'] = lambda x: x
order_date['Y'] = lambda x: x
ar = area.T(size=(350, 350),
x_axis=axis.X(label=fields[0]['name'], format="/a-30{}%s"),
y_axis=axis.Y(
label=', '.join(map(lambda x: x['name'], fields[1:]))))
idx = 0
date_idx = None
fct = {}
for f in fields:
field_id = (f['field_child3'] and f['field_child3'][0]) or (
f['field_child2'] and f['field_child2'][0]) or (
f['field_child1']
and f['field_child1'][0]) or (f['field_child0']
and f['field_child0'][0])
if field_id:
type = service.execute(cr.dbname, uid, 'ir.model.fields',
'read', [field_id], ['ttype'])
if type[0]['ttype'] == 'date':
date_idx = idx
fct[idx] = process_date[report['frequency']]
else:
fct[idx] = lambda x: x
else:
fct[idx] = lambda x: x
idx += 1
# plot are usually displayed year by year
# so we do so if the first field is a date
data_by_year = {}
if date_idx != None:
for r in results:
key = process_date['Y'](r[date_idx])
if not data_by_year.has_key(key):
data_by_year[key] = []
for i in range(len(r)):
r[i] = fct[i](r[i])
data_by_year[key].append(r)
else:
data_by_year[''] = results
nb_bar = len(data_by_year) * (len(fields) - 1)
colors = map(lambda x: fill_style.Plain(bgcolor=x),
misc.choice_colors(nb_bar))
abscissa = {}
for line in data_by_year.keys():
fields_bar = []
# sum data and save it in a list. An item for a fields
for d in data_by_year[line]:
for idx in range(len(fields) - 1):
fields_bar.append({})
if fields_bar[idx].has_key(d[0]):
fields_bar[idx][d[0]] += d[idx + 1]
else:
fields_bar[idx][d[0]] = d[idx + 1]
for idx in range(len(fields) - 1):
data = {}
for k in fields_bar[idx].keys():
if data.has_key(k):
data[k] += fields_bar[idx][k]
else:
data[k] = fields_bar[idx][k]
data_cum = []
prev = 0.0
keys = data.keys()
keys.sort()
# cumulate if necessary
for k in keys:
data_cum.append([k, float(data[k]) + float(prev)])
if fields[idx + 1]['cumulate']:
prev += data[k]
idx0 = 0
plot = bar_plot.T(
label=fields[idx + 1]['name'] + ' ' + str(line),
data=data_cum,
cluster=(idx0 * (len(fields) - 1) + idx, nb_bar),
fill_style=colors[idx0 * (len(fields) - 1) + idx])
ar.add_plot(plot)
abscissa.update(fields_bar[idx])
idx0 += 1
abscissa = map(lambda x: [x, None], abscissa)
abscissa.sort()
ar.x_coord = category_coord.T(abscissa, 0)
ar.draw(can)
can.close()
self.obj = external_pdf(pdf_string.getvalue())
self.obj.render()
pdf_string.close()
return True
def _create_bars(self, cr, uid, ids, report, fields, results, context):
pool = openerp.registry(cr.dbname)
pdf_string = cStringIO.StringIO()
can = canvas.init(fname=pdf_string, format='pdf')
can.show(80,380,'/16/H'+report['title'])
process_date = {
'D': lambda x: reduce(lambda xx, yy: xx + '-' + yy, x.split('-')[1:3]),
'M': lambda x: x.split('-')[1],
'Y': lambda x: x.split('-')[0]
}
order_date = {
'D': lambda x: time.mktime((2005, int(x.split('-')[0]), int(x.split('-')[1]), 0, 0, 0, 0, 0, 0)),
'M': lambda x: x,
'Y': lambda x: x
}
ar = area.T(size=(350,350),
x_axis = axis.X(label = fields[0]['name'], format="/a-30{}%s"),
y_axis = axis.Y(label = ', '.join(map(lambda x : x['name'], fields[1:]))))
idx = 0
date_idx = None
fct = {}
for f in fields:
field_id = (f['field_child3'] and f['field_child3'][0]) or (f['field_child2'] and f['field_child2'][0]) or (f['field_child1'] and f['field_child1'][0]) or (f['field_child0'] and f['field_child0'][0])
if field_id:
type = pool['ir.model.fields'].read(cr, uid, [field_id],['ttype'])
if type[0]['ttype'] == 'date':
date_idx = idx
fct[idx] = process_date[report['frequency']]
else:
fct[idx] = lambda x : x
else:
fct[idx] = lambda x : x
idx+=1
# plot are usually displayed year by year
# so we do so if the first field is a date
data_by_year = {}
if date_idx is not None:
for r in results:
key = process_date['Y'](r[date_idx])
if key not in data_by_year:
data_by_year[key] = []
for i in range(len(r)):
r[i] = fct[i](r[i])
data_by_year[key].append(r)
else:
data_by_year[''] = results
nb_bar = len(data_by_year)*(len(fields)-1)
colors = map(lambda x:fill_style.Plain(bgcolor=x), misc.choice_colors(nb_bar))
abscissa = {}
for line in data_by_year.keys():
fields_bar = []
# sum data and save it in a list. An item for a fields
for d in data_by_year[line]:
for idx in range(len(fields)-1):
fields_bar.append({})
if d[0] in fields_bar[idx]:
fields_bar[idx][d[0]] += d[idx+1]
else:
fields_bar[idx][d[0]] = d[idx+1]
for idx in range(len(fields)-1):
data = {}
for k in fields_bar[idx].keys():
if k in data:
data[k] += fields_bar[idx][k]
else:
data[k] = fields_bar[idx][k]
data_cum = []
prev = 0.0
keys = data.keys()
keys.sort()
# cumulate if necessary
for k in keys:
data_cum.append([k, float(data[k])+float(prev)])
if fields[idx+1]['cumulate']:
prev += data[k]
idx0 = 0
plot = bar_plot.T(label=fields[idx+1]['name']+' '+str(line), data = data_cum, cluster=(idx0*(len(fields)-1)+idx,nb_bar), fill_style=colors[idx0*(len(fields)-1)+idx])
ar.add_plot(plot)
abscissa.update(fields_bar[idx])
idx0 += 1
abscissa = map(lambda x : [x, None], abscissa)
abscissa.sort()
ar.x_coord = category_coord.T(abscissa,0)
ar.draw(can)
can.close()
self.obj = external_pdf(pdf_string.getvalue())
self.obj.render()
pdf_string.close()
return True
def _create_lines(self, cr, uid, ids, report, fields, results, context):
pool = openerp.registry(cr.dbname)
pdf_string = cStringIO.StringIO()
can = canvas.init(fname=pdf_string, format="pdf")
can.show(80, 380, "/16/H" + report["title"])
ar = area.T(
size=(350, 350),
# x_coord = category_coord.T(['2005-09-01','2005-10-22'],0),
x_axis=axis.X(label=fields[0]["name"], format="/a-30{}%s"),
y_axis=axis.Y(label=", ".join(map(lambda x: x["name"], fields[1:]))),
)
process_date = {
"D": lambda x: reduce(lambda xx, yy: xx + "-" + yy, x.split("-")[1:3]),
"M": lambda x: x.split("-")[1],
"Y": lambda x: x.split("-")[0],
}
order_date = {
"D": lambda x: time.mktime((2005, int(x.split("-")[0]), int(x.split("-")[1]), 0, 0, 0, 0, 0, 0)),
"M": lambda x: x,
"Y": lambda x: x,
}
abscissa = []
idx = 0
date_idx = None
fct = {}
for f in fields:
field_id = (
(f["field_child3"] and f["field_child3"][0])
or (f["field_child2"] and f["field_child2"][0])
or (f["field_child1"] and f["field_child1"][0])
or (f["field_child0"] and f["field_child0"][0])
)
if field_id:
type = pool["ir.model.fields"].read(cr, uid, [field_id], ["ttype"])
if type[0]["ttype"] == "date":
date_idx = idx
fct[idx] = process_date[report["frequency"]]
else:
fct[idx] = lambda x: x
else:
fct[idx] = lambda x: x
idx += 1
# plots are usually displayed year by year
# so we do so if the first field is a date
data_by_year = {}
if date_idx is not None:
for r in results:
key = process_date["Y"](r[date_idx])
if key not in data_by_year:
data_by_year[key] = []
for i in range(len(r)):
r[i] = fct[i](r[i])
data_by_year[key].append(r)
else:
data_by_year[""] = results
idx0 = 0
nb_bar = len(data_by_year) * (len(fields) - 1)
colors = map(lambda x: line_style.T(color=x), misc.choice_colors(nb_bar))
abscissa = {}
for line in data_by_year.keys():
fields_bar = []
# sum data and save it in a list. An item for a fields
for d in data_by_year[line]:
for idx in range(len(fields) - 1):
fields_bar.append({})
if d[0] in fields_bar[idx]:
fields_bar[idx][d[0]] += d[idx + 1]
else:
fields_bar[idx][d[0]] = d[idx + 1]
for idx in range(len(fields) - 1):
data = {}
for k in fields_bar[idx].keys():
if k in data:
data[k] += fields_bar[idx][k]
else:
data[k] = fields_bar[idx][k]
data_cum = []
prev = 0.0
keys = data.keys()
keys.sort()
# cumulate if necessary
for k in keys:
data_cum.append([k, float(data[k]) + float(prev)])
if fields[idx + 1]["cumulate"]:
prev += data[k]
idx0 = 0
plot = line_plot.T(
label=fields[idx + 1]["name"] + " " + str(line),
data=data_cum,
line_style=colors[idx0 * (len(fields) - 1) + idx],
)
ar.add_plot(plot)
abscissa.update(fields_bar[idx])
idx0 += 1
abscissa = map(lambda x: [x, None], abscissa)
ar.x_coord = category_coord.T(abscissa, 0)
ar.draw(can)
can.close()
self.obj = external_pdf(pdf_string.getvalue())
self.obj.render()
pdf_string.close()
return True
def _create_lines(self, cr, uid, ids, report, fields, results, context):
pool = yuancloud.registry(cr.dbname)
pdf_string = cStringIO.StringIO()
can = canvas.init(fname=pdf_string, format='pdf')
can.show(80,380,'/16/H'+report['title'])
ar = area.T(size=(350,350),
#x_coord = category_coord.T(['2005-09-01','2005-10-22'],0),
x_axis = axis.X(label = fields[0]['name'], format="/a-30{}%s"),
y_axis = axis.Y(label = ', '.join(map(lambda x : x['name'], fields[1:]))))
process_date = {
'D': lambda x: reduce(lambda xx, yy: xx + '-' + yy, x.split('-')[1:3]),
'M': lambda x: x.split('-')[1],
'Y': lambda x: x.split('-')[0]
}
order_date = {
'D': lambda x: time.mktime((2005, int(x.split('-')[0]), int(x.split('-')[1]), 0, 0, 0, 0, 0, 0)),
'M': lambda x: x,
'Y': lambda x: x
}
abscissa = []
idx = 0
date_idx = None
fct = {}
for f in fields:
field_id = (f['field_child3'] and f['field_child3'][0]) or (f['field_child2'] and f['field_child2'][0]) or (f['field_child1'] and f['field_child1'][0]) or (f['field_child0'] and f['field_child0'][0])
if field_id:
type = pool['ir.model.fields'].read(cr, uid, [field_id],['ttype'])
if type[0]['ttype'] == 'date':
date_idx = idx
fct[idx] = process_date[report['frequency']]
else:
fct[idx] = lambda x : x
else:
fct[idx] = lambda x : x
idx+=1
# plots are usually displayed year by year
# so we do so if the first field is a date
data_by_year = {}
if date_idx is not None:
for r in results:
key = process_date['Y'](r[date_idx])
if key not in data_by_year:
data_by_year[key] = []
for i in range(len(r)):
r[i] = fct[i](r[i])
data_by_year[key].append(r)
else:
data_by_year[''] = results
idx0 = 0
nb_bar = len(data_by_year)*(len(fields)-1)
colors = map(lambda x:line_style.T(color=x), misc.choice_colors(nb_bar))
abscissa = {}
for line in data_by_year.keys():
fields_bar = []
# sum data and save it in a list. An item for a fields
for d in data_by_year[line]:
for idx in range(len(fields)-1):
fields_bar.append({})
if d[0] in fields_bar[idx]:
fields_bar[idx][d[0]] += d[idx+1]
else:
fields_bar[idx][d[0]] = d[idx+1]
for idx in range(len(fields)-1):
data = {}
for k in fields_bar[idx].keys():
if k in data:
data[k] += fields_bar[idx][k]
else:
data[k] = fields_bar[idx][k]
data_cum = []
prev = 0.0
keys = data.keys()
keys.sort()
# cumulate if necessary
for k in keys:
data_cum.append([k, float(data[k])+float(prev)])
if fields[idx+1]['cumulate']:
prev += data[k]
idx0 = 0
plot = line_plot.T(label=fields[idx+1]['name']+' '+str(line), data = data_cum, line_style=colors[idx0*(len(fields)-1)+idx])
ar.add_plot(plot)
abscissa.update(fields_bar[idx])
idx0 += 1
abscissa = map(lambda x : [x, None], abscissa)
ar.x_coord = category_coord.T(abscissa,0)
ar.draw(can)
can.close()
self.obj = external_pdf(pdf_string.getvalue())
self.obj.render()
pdf_string.close()
return True
def _create_lines(self, cr, uid, ids, report, fields, results, context):
service = netsvc.LocalService("object_proxy")
pdf_string = cStringIO.StringIO()
can = canvas.init(fname=pdf_string, format='pdf')
can.show(80,380,'/16/H'+report['title'])
ar = area.T(size=(350,350),
#x_coord = category_coord.T(['2005-09-01','2005-10-22'],0),
x_axis = axis.X(label = fields[0]['name'], format="/a-30{}%s"),
y_axis = axis.Y(label = ', '.join(map(lambda x : x['name'], fields[1:]))))
process_date = {}
process_date['D'] = lambda x : reduce(lambda xx,yy : xx+'-'+yy,x.split('-')[1:3])
process_date['M'] = lambda x : x.split('-')[1]
process_date['Y'] = lambda x : x.split('-')[0]
order_date = {}
order_date['D'] = lambda x : time.mktime((2005,int(x.split('-')[0]), int(x.split('-')[1]),0,0,0,0,0,0))
order_date['M'] = lambda x : x
order_date['Y'] = lambda x : x
abscissa = []
tmp = {}
idx = 0
date_idx = None
fct = {}
for f in fields:
field_id = (f['field_child3'] and f['field_child3'][0]) or (f['field_child2'] and f['field_child2'][0]) or (f['field_child1'] and f['field_child1'][0]) or (f['field_child0'] and f['field_child0'][0])
if field_id:
type = service.execute(cr.dbname, uid, 'ir.model.fields', 'read', [field_id],['ttype'])
if type[0]['ttype'] == 'date':
date_idx = idx
fct[idx] = process_date[report['frequency']]
else:
fct[idx] = lambda x : x
else:
fct[idx] = lambda x : x
idx+=1
# plots are usually displayed year by year
# so we do so if the first field is a date
data_by_year = {}
if date_idx != None:
for r in results:
key = process_date['Y'](r[date_idx])
if not data_by_year.has_key(key):
data_by_year[key] = []
for i in range(len(r)):
r[i] = fct[i](r[i])
data_by_year[key].append(r)
else:
data_by_year[''] = results
idx0 = 0
nb_bar = len(data_by_year)*(len(fields)-1)
colors = map(lambda x:line_style.T(color=x), misc.choice_colors(nb_bar))
abscissa = {}
for line in data_by_year.keys():
fields_bar = []
# sum data and save it in a list. An item for a fields
for d in data_by_year[line]:
for idx in range(len(fields)-1):
fields_bar.append({})
if fields_bar[idx].has_key(d[0]):
fields_bar[idx][d[0]] += d[idx+1]
else:
fields_bar[idx][d[0]] = d[idx+1]
for idx in range(len(fields)-1):
data = {}
for k in fields_bar[idx].keys():
if data.has_key(k):
data[k] += fields_bar[idx][k]
else:
data[k] = fields_bar[idx][k]
data_cum = []
prev = 0.0
keys = data.keys()
keys.sort()
# cumulate if necessary
for k in keys:
data_cum.append([k, float(data[k])+float(prev)])
if fields[idx+1]['cumulate']:
prev += data[k]
idx0 = 0
plot = line_plot.T(label=fields[idx+1]['name']+' '+str(line), data = data_cum, line_style=colors[idx0*(len(fields)-1)+idx])
ar.add_plot(plot)
abscissa.update(fields_bar[idx])
idx0 += 1
abscissa = map(lambda x : [x, None], abscissa)
ar.x_coord = category_coord.T(abscissa,0)
ar.draw(can)
can.close()
self.obj = external_pdf(pdf_string.getvalue())
self.obj.render()
pdf_string.close()
return True